The La Londe Conference in Marketing Communications and Consumer Behavior

JBR Special Issues 1999 - 2009

The La Londe Conference in Marketing Communications and Consumer Behavior              

     

Contents

• 1999 Lalonde conference Yves Evrard, Wayne D. Hoyer and Alain Strazzieri Introduction to the special issue on marketing communications and consumer behavior

• 2001 La Londe conference Christian Derbaix , Lynn R. Kahle, Dwight Merunka and Alain Strazzieri Introduction to the special issue on marketing communications and consumer behavior

• 2003 La Londe conference Gilles Laurent and Judy Zaichkowsky Preface to La Londe 2003 special issue: communications and consumer behavior

• 2005 La Londe conference Curtis P. Haugtvedt, Dwight R. Merunka and Luk Warlop Marketing communications and consumer behavior: Introduction to the special issue from the 2005 La Londe seminar

• 2007 La Londe Conference Søren Askegaard, Dwight R. Merunka and M. Joseph Sirgy Marketing communications and consumer behavior: Introduction to the special issue from the 2007 La Londe conference

• 2009 La Londe Conference Virginie De Barnier, Chris A. Janiszewski, Dwight R. Merunka, Stijn M.J. van Osselaer Marketing communications and consumer behavior: Introduction to the special issue from the 2009 La Londe conference

Journal of Business Research 58 (2005) 339 – 340

Editorial

Introduction to the special issue on marketing communications and consumer behavior$ Abstract This special issue includes a selection of papers presented at the 1999 La Londe Seminar. After a description of the conference, this introduction shortly presents the papers included in the special issue: two guest papers from Sidney Levy and Robert Peterson, and five competitive papers dealing with marketing communications and consumer behavior. D 2003 Elsevier Inc. All rights reserved.

1. A small and ‘‘interactive’’ conference The seminar is unlike many other conferences in that it is small (72 participants this year) and is characterized by a friendly and informal atmosphere of exchange between researchers from all over the world (14 countries represented this year). In order to facilitate fruitful exchanges, each presentation lasts 45 min. Participants are scholars with an interest in developing a scientific understanding of consumer behavior in order to better design and implement advertising and other marketing communication tools.

2. An outstanding scientific committee IAE and the conference organizers are very grateful to the respected colleagues who served as members of the scientific committee. These individuals reviewed and constructively commented on the 83 papers submitted. Thirtyone papers were accepted and included in the proceedings. Heartfelt thanks are given to the following scholars: Gerald Albaum (University of Oregon), Rajeev Batra (University of Michigan at Ann Arbor), Russell W. Belk (University of Utah), Christian Derbaix (FUCAM, Mons), Peter Doyle (University of Warwick), Alain Jolibert (ESA, Universite´ Pierre Mende`s-France, Grenoble), Lynn R. Kahle (University of Oregon), Michel Laroche (Universite´ Concordia, Montre´al), Siew Meng Leong (National University of Singapore), Claude R. Martin (University of Michigan at $ In 1974, Eric Langeard created the IAE ‘‘International Research Seminar in Marketing’’, primarily known as the ‘‘Se´nanque Seminar’’. Eric passed away in November 1998. At the beginning of the 1999 seminar, Pierre Eiglier, Bob Peterson, Yves Evrard and Sid Levy gave a tribute to the founding father of the seminar. Adieu Eric! All your friends are grateful.

0148-2963/03/$ – see front matter D 2003 Elsevier Inc. All rights reserved. doi:10.1016/S0148-2963(03)00099-7

Ann Arbor), Hans Mulbacher (Universita¨t Innsbruck), Robert A. Peterson (The University of Texas at Austin), Rik Pieters (Tilburg University), Christian Pinson (INSEAD), Bernard Pras (Universite´ de Paris IX-Dauphine, ESSEC), Don E. Schultz (Northwestern University, Medill), Jan-Benedict Steenkamp (Catholic University at Leuven), Alice M. Tybout (Northwestern University, Kellogg), Mark Uncles (University of New South Wales),W. Fred van Raaij (Erasmus University) and Arch G. Woodside (Tulane University). This year, for the first time, we requested other respected colleagues to be ad hoc reviewers. We appreciated strongly their fruitful cooperation. The following are the names of those who helped: Dana Alden (University of Hawaii), Mark Alpert (University of Texas at Austin), Philippe Aurier (Universite´ de Montpellier 2), Michelle Bergadaa (Universite´ de Gene`ve), Peter Bloch (University of Missouri), Susan Broniarczyk (University of Texas at Austin), Daniel Caumont (Universite´ de Nancy), Jean-Charles Chebat (HEC Montreal), Terry Childers (University of Minnesota), Bettina Cornwell (University of Memphis), Ayn Crowley (Drake University), Rene´ Darmon (ESSEC), Kalpesh Desai (SUNY-Buffalo), Pierre Desmet (ESSEC and Paris-Dauphine), Marie-Laure Gavard-Perret (Universite´ de Savoie), Pierre Gre´gory (Universite´ de Paris I), Pam Henderson (Washington State University), Jeff Inman (University of Wisconsin) Richard Ladwein (IAE Universite´ de Lille), David Mazursky (Hebrew University of Jerusalem), Dwight Merunka (IAE Universite´ d’Aix-Marseille), Ashesh Mukherjee (McGill University), Pascale Quester (University of Adelaide), Peter Reed (Monash University), Elyette Roux (ESSEC), Eric Spangenberg (Washington State University), Pierre Valette-Florence (Universite´ de Grenoble), Bjorn Waliser (Universite´ de Strasbourg), Judy Zaichkowsky (Simon Frazier University), Monique Zollinger (Universite´ de Tours).

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Editorial

3. A vivifying ‘‘heritage assessment’’ session Since this conference was the last of the millennium, three distinguished scholars were requested to participate to a heritage assessment session. We asked these individuals to provide a panoramic view of the evolution of research and to evaluate the contributions on topics relevant for the conference. Frank Bass presented brightly a history of diffusion theory in marketing (not included in this special issue). Sid Levy impassioned the attendants with his probably impartial and surely erudite narration of the battles between ‘‘quantitativists’’ and ‘‘qualitativists’’ in the Consumer Behavior research community. He advocated convincingly for more realistic research and more open-minded researchers. Bob Peterson presented published and forthcoming metaanalyses results showing convincingly that the variance accounted for in several areas of consumer behavior research was very weak. He argued that one of the causes of that unpleasant fact was that the data collected by questionnaires are no more than on the spot constructions.

4. From Nelson’s theory to internet communication through advertising affective reactions effects The five competitive papers selected for inclusion in this special issue address various issues, from testing an old advertising theory to exploring the new wold of Internet communication. Sridhar Moorthy and Scott A Hawskins present the results of a laboratory experiment aimed at verifying if advertising repetition (real or told) influences more the perceived quality of experience (vs. search) goods as argued by Nelson (1970). They find limited support to the Nelson’s theory. June Cotte, Robin Higie Coulter and Melissa Moore study the effects of credibility and of the perception of manipulative intent on the ad’s ability to induce the intended emotion (specifically guilt). Their experiment shows notably the disrupting effect of the perception of manipulative intent. Mark I. Alpert, Judy I. Alpert and Elliot N. Malz study the effects of background music on audience responses

(moods, attitudes and intentions), using structural profiles of music elements and introducing purchase occasion congruity. Their experiment supports the positive effect of congruent music. Majorie Dijkstra, Heidi E.J.J.M. Buijtels and W. Fred van Raaij study the effects on consumer cognitive, affective and conative responses of single-medium and multiplemedia campaigns (TV, print, Internet). Among other results, their laboratory experiment suggests that Internet alone is hardly effective, but can play a complementary function. David R. Fortin and Ruby Roy Dholakia study the effect of interactivity (specifically three levels for online advertising) on involvement with the ad and arousal. Their experiment with 360 self-recruited web users indicates notably a mediating role of the perception of social presence and a plateau effect of interactivity on involvement.

5. Final words Finally, as cochairs and coordinator of this conference, we strongly wish to express our gratefulness to Arch Woodside, editor in chief of the Journal of Business Research, for instigating in 1995 a special issue devoted to a selection of the papers. This action was a determinant factor of the success of this biennial meeting of worldwide scholars involved in consumer behavior and marketing communications research.

Yves Evrard HEC, Paris, France Wayne D. Hoyer University of Texas, Austin, USA Alain Strazzieri* IAE Aix, Universite´ d’Aix-Marseille, Clos Guiot, 13540 Puyricard, France E-mail address: [email protected] * Corresponding author.

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The evolution of qualitative research in consumer behavior Sidney J. Levy Department of Marketing, University of Arizona, Room 320U, McClelland Hall, Tucson, AZ 85721-0108, USA

Abstract This article is my response to an invitation to prepare a ‘‘heritage assessment’’ for presentation to the International Research Seminar at La Londe les Maures in June 1999. Such an assessment is, according to Alain Strazzieri, an authorized view of what is worth remembering from the literature about topics in consumer behavior research. This charge is an open one and I will execute it freely. My presentation of this view has been authorized by the seminar’s Scientific Committee. Otherwise, you will have to judge my authority on its merits. It does have the weight of my advanced years, giving me the advantage of having started formal study of consumers when research into their behavior was still young. My main themes are the intellectual battling and intellectual cycling that have gone on in our field, especially with reference to the role of qualitative research. D 2003 Elsevier Inc. All rights reserved. Keywords: Qualitative research; Consumer behavior; Intellectual battling; Intellectual cycling

1. Intellectual conflict: theme and variations The perspectives I derived in the late 1940s came mainly from the topics and methods of the behavioral sciences that were the fashion of the period and that I studied at the University of Chicago. Some of my teachers were outstanding names in the behavioral sciences. I studied with or was exposed to the thinking of Robert Redfield, W. Lloyd Warner, Everett Hughes, Herbert Blumer, Edward Shils, David Reisman, William E. Henry, Don Campbell, and others. The so-called ‘‘Second Chicago School’’ of Sociology was flourishing (Fine, 1995) and my home base, The Committee on Human Development, provided a multidisciplinary and eclectic education. Among my fellow students and friends were Herbert Gans, Lee Rainwater, and Erving Goffman. There was great intellectual stimulation, with argumentation over philosophies, subject matter, and methods. Some of these controversial topics show how the modern roots of our present concerns reach back to the 1920s and 1930s. For instance, criticism of the work of Piaget (1926) still goes on because he generalized grandly from observing small samples of children. In basic scientific tradition, he drew inferences and conclusions from his observations and other researchers dispute his hypotheses and try to refute them. The behavioral science disciplines

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grew vigorously in the 1940s and 1950s. Much of the study that goes on nowadays in the consumer research field adds some basic knowledge to the early learning; it also refines, elaborates, and, most strongly, applies what we have learned. However, the fundamental intellectual battle still goes on between the partisans of nomothetic approaches and the partisans of idiographic study. The scholars reading this article are surely familiar with much of the history of our discipline, but I will remind us of some highlights that stand out in my mind. Major phenomena in the research area are the growth of qualitative methods and the resistance to them by people who prefer to rely on quantitative methods. Gary Fine (1995) gives an excellent account of this struggle at Chicago, describing the conflict between the advocates of quantitative methods and those committed to the prewar (World War II) emphasis upon qualitative methods and field research methodologies. He notes that Blumer criticized ‘‘those who were attempting to achieve exactitude in social science at the price of direct and naturalistic study’’ (p. 145) and cites David Reisman’s recollection that the enmity was a problem for graduate students who worked with Hughes and with me, as well as for nontenured colleagues, particularly with Nelson Foote and Anselm Strauss. . .Unrealistically, if understandably, translating acidulous comments by faculty members into actual prescriptions of what would pass muster, some able graduate students feared to write a dissertation

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without tables in it. . .I sometimes had the dismal experience of having as a doctoral candidate someone who had been a spirited undergraduate and watching that person become more timid and less original as time went by. (Reisman, in Berger, 1990, p. 63) More than 50 years later, when I ran a workshop on qualitative research, one of the doctoral students responded with this fretful statement: I suppose what I mean is that there has to be a certain consistency in epistemology, ontological assumptions, and the use of techniques of data collection and presentation. Why do we have to constantly justify the use of certain techniques, and why do we willingly or unwillingly participate in perpetuating the dominance of a particular discourse of ‘‘doing research;’’ in other words, why are we ashamed to be purely qualitative, just as we are not ashamed to be purely quantitative? I find that I am constantly grappling with this in my own research, and would like to find a way of dealing with this issue, so that we can have other ways of collecting, analyzing, and presenting data. One wonders about the persistence of this contentiousness, and the lack of objectivity shown by so many academicians with doctorates to their names. These remarks are true for fields other than marketing: a professor of finance recently raved in my presence that he hated the behavioral people he believed were ruining his field. This struggle has a certain one-sidedness to it as the quantitative people have the dominant paradigm and the greater power. Scholars who are interested in qualitative research usually understand the role of measurement and do not deny its value and even the need for it in the large place it occupies in the activities of the research world. They believe that they are bringing new and useful insights to the marketing field. These scholars mainly would like to be free to do their kinds of research, to get it published, and to be hired as regular members of a faculty. However, generally, the dominant paradigm people resist, show great hostility, and at many schools refuse to hire any faculty who are qualitatively oriented. They behave defensively, foolishly acting as though their livelihoods are threatened by the projective techniques and ethnographies that will replace surveys, regressions, and multivariate methods. At the 1989 conference of the Association for Consumer Research, they complained fearfully that qualitative researchers might be taking over the conference. They also attack, looking down on the qualitative people, and sneer at them as if they were chiropractors or dentists who could not succeed as physicians. At a recent conference of the American Marketing Association, one participant implied that qualitative researchers are like modern artists who do unrealistic, distorted work because they are not competent at drawing: that is, unlike Picasso who we knew could really draw, they

supposedly cannot properly measure and hold their work up to the criteria that govern scientific research. The oddity here is that an ethnography or thick description surely captures a situation more realistically than a particular statistic, no matter how large the sample or whatever the level of confidence.

2. Conflict and cycling of ideas However, the ebb and flow of intellectual conflict is an ordinary thing, in the nature of science, and is a requirement for ideas to demonstrate their viability. It does not afflict qualitative consumer researchers only. The prewar sociologists at Chicago resisted the incoming proponents of quantitative methods, just as historians who pursue the ancient tradition of qualitative study of the past sputtered and fumed when the cliometricians arrived with their threatening statistical techniques for measuring history and their use of tables as well as tales. Often, of course, the emotional component of the critics’ reactions is so great as to have little to do with the science of the matter. Real scholars are calmer, having a comprehension of the variety of ways science goes on and understanding that ultimately it should address itself to rival hypotheses and whether they can be shown to be false. Like the presumption of innocence in law, any generalization—whether drawn from qualitative or quantitative study—may be taken as valid until there is evidence that it is not true; then, the exception does not prove the rule (except in the sense of testing it) but provides an occasion for fresh theory or insight. All researchers make observations of some kinds, draw inferences from those observations to arrive at their preferred ways of explaining the phenomena they have observed and how generally they occur. However, there are many ways of doing that. I am reminded of a research meeting at which a psychologist told the head of a pharmaceutical company that some consumers were stomach-oriented and others were anal-oriented when it came to taking laxatives. The executive asked ‘‘How many are there of each type?’’ and the psychologist replied, ‘‘Enough of them, sir!’’—and undoubtedly there are. The differences in approaches became apparent in the 1930s when the influx of European scholars brought to America and to the business world quantitative methods as in the survey and panel methods of Paul Lazarsfeld (Lazarsfeld, 1940) and depth techniques as in the psychoanalytic interpretations of Ernest Dichter. Hal Kassarjian (1994) describes in detail these European roots. His informative chapter appears in the valuable overview of research traditions in marketing provided by Laurent et al. (1994). The study of consumer behavior gained momentum in the late 1940s and 1950s, especially as its value was embraced by advertising agencies on behalf of their clients. A lot of that work was proprietary and did not appear in journals—and the Association for Consumer Research and

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the Journal of Consumer Research did not show up until the 1970s. However, there was the large-scale survey work by Alfred Politz and a variety of so-called motivation or qualitative research studies—many of which were reported on in the trade press. The 1950s were a kind of heyday of communications research (Klapper, 1960) and studies in persuasion (Hovland et al., 1953). The lively character of the work in that post-World War II period is especially evident in the two volumes on Consumer Behavior edited by Lincoln H. Clark (1954 – 1955). These volumes report on two conferences held at the University of Michigan that brought together scholars from several research organizations. The disciplines of sociology, psychology, and economics were well-represented, and although there were tables and statistics reported—and the University of Michigan Survey Research Center had a dominating role—the papers had a markedly thoughtful and discursive quality, suggesting some breadth of thinking and conversation that went on about the lives of consumers, their life cycles, and their decision making. Such earlier subjects and methods are like the trunk of a tree that in time grew many branches and leafed out into the variety of sessions and the flowering richness of specific topics apparent in modern journals and in the contemporary conferences of the Association for Consumer Research, the Society for Consumer Psychology, and the International Research Seminar. I will not repeat here some of the historical developments that I have noted on other occasions (Levy, 1991, 1994, 1996). The ‘‘motivation research’’ of the 1950s was subsequently perceived to have died of its excesses, and the rise of the computer assisted in pushing positivism and its methods to the fore. But all along, the protagonists of qualitative research persisted, partially aided (and partially disserved) by the business world’s huge embrace of focus groups. By the 1970s, the growth of consumer research generally, in both business and academic studies, was so great that there was room for qualitative work and need for the ideas it could engender. Since then, importantly, qualitative research scholars have made names for themselves as leaders in the application of the various methods drawn from the various behavioral sciences—ethnographies, semiotic studies that include literary analyses and examination of rhetoric, inquiries eliciting projective materials, etc. Simply put, these kinds of studies contrast with surveys and experiments by turning from the measurement of variables to intensive description, interpretation of situations, and the search for meaning.

3. The need for qualitative research Reasonable scholars—presumably meaning those who agree with me—may have read the great essay by Kurt Lewin (1935) on The Conflict Between Aristotelian and Galileian Modes of Thought in Contemporary Psychology, or the more recent perspectives provided by Morgan and

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Smircich (1980) and Hunt (1991). Lewin points out the lingering Aristotelian influence that gives a valuative color to modes of thought and searches empirically for the lawfulness of events through their regularity and frequency. The result is a preference for understanding events that possess a certain persistence and stability and the placement of less common events and individuality as outside the realm of science. This underlying idea that the lawful and the individual are antithetical shows itself when the critics want to know if qualitative findings are generalizable. As Lewin (1935, p. 15) says, ‘‘If one shows a film of a concrete incident in the behavior of a certain child, the first question of the psychologist usually is: ‘Do all children do that, or is it at least common?’’’ Lawfulness as frequency means that repetition is a major criterion, and leads to the commanding role of statistics, ‘‘the most striking expression of this Aristotelian mode of thinking’’ (p. 16). As a field theorist, a leader in the Gestalt school of psychology, Lewin was less concerned with frequent repetition than with the nature of the whole situation. Since all events must in truth be lawful, interest in the situation and the holistic attitude that underlies its study mean that we perceive the events of consumer behavior as dynamic outcomes of multiple forces. As Lewin sums up, ‘‘The tendency to comprehend the actual situation as fully and concretely as possible, even in its individual peculiarities, makes the most precise possible qualitative and quantitative determination necessary and profitable’’ (1935, p. 25). Historically, more and more scholars have come to seek that comprehension of the situation, or at least to approximate it. Thus, despite the resistance that still occurs, this aspiration has gained a large number of adherents, more visibility, and a fairly loud voice. The more fully researchers want to understand consumer behavior, the more they are motivated to use methods that allow the interaction of multiple forces to show itself. Were this to be done ideally, a consumer event would be intensively scrutinized by a team of thinkers representing every discipline, explaining every possible antecedent and current element with any possible effect on the action at issue. Short of that, we engage in the varieties of research activity called qualitative research. That means going beyond the exponents of behaviorism (unlike behavioralists) who want to limit their data and thinking to explicit and plainly observable acts and events, to stimulus and response; and who focus on the degree to which the phenomena occur and the level of confidence we may have in getting the same results were the study to be repeated. Being more broadly behavioral means the unleashing of all we can do to find out what consumers’ lives are like, especially with reference to the situations that interest us. Getting reports on their actions may seem the easier part, although some skeptical scientists want to watch the behavior rather than be told about it in an interview or a laboratory. That means going out into the field, mingling with the subjects as if being one of them, making detailed notes, creating the methods of case studies, participant

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observation, autodriving, ethnography, and thick descriptions. We are also challenged to deal with consumers’ inner lives, including their introspections, with all the hazards entailed in their self-expression, their truth and lies, their ignorance, uncertainty, face work, contradictions, and mechanisms of defense—all in all, their being complex human beings. Methods arise to gather this sort of information, such as depth interviews, focus groups sessions, and projective techniques. That also means we have to interpret the complexity and make inferences from what is observable to what is underlying and theoretically operative. Despite their necessity, introspection, and interpretation arouse the inevitable demon of subjectivity, on the part of the subjects, the researchers, and certainly their critics. We enlarge our vocabularies, having to learn words such as phenomenology, hermeneutic, semiotic, emic and etic, hegemonies, rituals, myths, symbolic consumption, and postmodernity. That irritates a lot of people who forget they also had to learn what partial derivatives are. However, what are we to do? We are people thinking about people and giving a lot of emphasis to how they perceive themselves and their relations to the outside world and the products they consume. Regardless of the long history I am describing here, it is a sign of the irregular situation of qualitative research that examples of its application still turn up in the business press as if it were some remarkable newcomer. Recently, The Wall Street Journal (1999) reported Chrysler’s ‘‘first vehicle designed entirely through an unconventional market-research process known as ‘archetype research.’ (Ah, Carl Jung!). . .overseen by a. . .French-born medical anthropologist named G. Clotaire Rapaille.’’ The research involved poring over focus group protocols in which participants were asked to drift back to their childhoods and jot down the memories invoked by the prototype of the vehicle. A project about Procter & Gamble’s Folgers Coffee was also mentioned in which ‘‘Dr. Rapaille concluded that aroma sells coffee more than taste does because aroma invokes feelings of home.’’ If this was news to Procter & Gamble, perhaps the ‘‘unconventionality’’ and ever-renewed sense of novelty about qualitative research is due to the persisting naivete´ and capacity for astonishment of corporate personnel. Nevertheless, in the face of continuing contention, acrimony, and defensiveness on all sides, qualitative scientists have persisted and amplified their numbers. Their stream of work seems to be well established now. It has taken root and a substantial number of scholars are devotedly pursuing the content and methods of qualitative study and publishing their work. Although qualitative research is a subfield of a relatively small field, it has radiated out into the world. Sage Publications sells an active list of materials about qualitative research and such work has partisans around the globe at schools and companies. Most marketing research organizations claim to do qualitative research, even if only or mainly focus groups; the Burke Institute and the A.C. Nielsen Center for Marketing Research expose their students to

the topic. Perhaps another sign of the degree of recognition and acceptance that has occurred are publications that reflect back on particular contributors and their work. Along the way, a notable example was Elizabeth Hirschman’s (1985) analysis of Scientific Style and the Conduct of Consumer Research. More recently, Hope Schau (1998) discussed the character of Russell Belk’s ideas, Stephen Brown (1999) compared Morris Holbrook’s thinking and style with Theodore Levitt’s, and Sage Publications has a forthcoming volume collecting 50 years of my writing, edited by Dennis Rook (1999). Alain Jolibert is planning to edit a French volume of the intellectual biographies of 11 contributors to marketing thought. However, looking back and summing up in this field are not far advanced and there is a need for more grand integrations and overviews. A few signs of such maturation are the volumes by McCracken (1988), Hirschman and Holbrook (1992), and by Firat and Dholakia (1998). Otherwise, the closest we come is with reviews of the literature on focal topics in single articles, in proceedings, and in edited collections of chapters written for books such as John Sherry’s (1995, 1998) Contemporary Marketing and Consumer Behavior and his ServiceScapes. Textbooks serve this summary function by harvesting the findings of many individual studies, although the applied orientation of textbooks is usually so great that considerations of theory and method are less apparent. As academic consumer research studies were gathering steam in the 1960s, the landmark text by Engel, Kollat, and Blackwell that emerged in 1968 organized its contents by using the common categories that continue today. These are general cultural and environmental forces, reference group memberships, and psychological components that affect consumer decision-making. The early books relied a lot on fashionable theoretical currents, such as personality and learning theory, cognitive dissonance and its reduction, involvement, and social stratification. In a doctoral seminar I taught in 1977, Kenneth Wisniewski wrote a paper on the diffusion of innovation and Deborah RoedderJohn wrote one on perceived risk; both papers suggested that the concepts seemed to have been largely exhausted. Two outstanding books provided overviews of the basic theoretical resources available to researchers: Behavioral Science Foundations of Consumer Behavior, edited by Joel Cohen (1972), and Consumer Behavior: Theoretical Sources, edited by Ward and Robertson (1973). Early textbooks often included the identical material and anthologies collected many of the same articles, but in time, there was a proliferation of studies, with fresh and diverse examples. The goals of communicating research findings, assessing them and applying them, were emphasized by Engel et al., but in their sixth edition in 1990, they added this fifth objective: To make the field of consumer behavior exciting, interesting, and relevant to both students and faculty. With advanced textbook technology, the modern consumer behavior books are gorgeous with their varied fonts, colors, pictures, charts, and boxes. Along this line, the

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volume by Michael R. Solomon (1992, 1st ed.) is remarkable for the lavishness and variety of its illustrations and its comprehensive coverage. Texts on advertising relate a lot to consumer behavior and show similar opulence of design. The effect is sometimes broken up and distracting, probably in keeping with the fragmentation characteristic of postmodern organization and the students’ experience with MTV, the Internet, and the provocative visualizations in the fast moving world of special effects.

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sumers as qualifying the theories of economists and psychologists by showing the role of consumer behavior under certain conditions, such as branding and variety seeking. 4.2. Too much psychology Another respondent criticizes the consumer research orientation as overly dominated by psychology and idealizes the earlier days as more comfortable with qualitative research, which was hardly the case; but lends support to my perception of the viciousness that still goes on.

4. A little study Recent and contemporary qualitative consumer research has clearly made a place for itself and contributed to a great richness of detail in exploring consumer situations. It is so varied and ramified, it would be difficult to enumerate here all that has specifically been learned. Rather than do that, I will be a dutiful qualitative researcher and report on a modest research project I carried out in preparation for this article. To share the challenge of the assignment, I asked a few outstanding individuals in the consumer research field what they regarded as important contributions. Although I asked for accomplishments and what we have learned, I got some negative views as well. I will quote the most salient comments. 4.1. The dark side Well, here’s a dark side point of view. You might not want to hear this, but one thing I’ve been thinking is that marketing, at least the part about ‘‘listening to the customer,’’ has been so enormously successful that we only have ourselves to blame for the current situation we’re in. What do I mean? I think marketing helped to bring about postmodernism, where everyone thinks his or her own point of view is equally valid (cf. ‘‘the customer is always right’’); that diversity is more important than quality, that quality is not a truth but an opinion. . .Rather than pursuing knowledge and beauty and goodness for all, we have numerous tiny special groups ranting ‘‘listen to us, we have special needs’’ as if we all do not have needs, and as if those needs don’t turn out to be rather common. This respondent is pointing out that research approaches have philosophical implications, that the emphasis on phenomenology that underlies the famous marketing concept is overdone and has adverse consequences. She points to the contemporary conflict of the traditional pursuit of absolutes, such as truth and virtue, versus the rampant individualism and relativism some people find so destructive. Her thought echoes the criticism of the broadening concept of marketing specified by Laczniak and Michie (1979) as promoting social disorder. In additional remarks, she continues in a more positive vein to see the benefit of marketing study of con-

A fascinating element of consumer research is that, since consumers are people and being involved in a consumption or exchange situation requires interacting with other people, our discipline should always have identified with all of the social sciences. My perception is that it did—in the early stages of development when scholars were well versed in a variety of disciplines. But, during the years that marketing departments responded to the pressures of business schools needing to develop an image of being ‘‘research-oriented,’’ our discipline had to pick one science to pattern itself after, and, for reasons I’m not sure about, that discipline was psychology. We seem to have been struggling ever since to return to a world that is more reflective of the complexities of consumers, consumption and exchange processes, but the struggle has really hurt the discipline as a whole. . .My perception is that the field was very comfortable with qualitative methods early in its development, but along the way, someone decided that for either speed of analysis or rigor we needed to move to surveys, with scales to complete, or experiments with lots of control. Then, people got interested in qualitative methods again, but only as defined by the rigor identified as ethnography. As each wave builds, in order to defend the value of whichever method someone prefers, everyone seems to have criticized the other methods or worse, assert that the other methods are of no value. The academic world has been most vicious about this. 4.3. Going to extremes This respondent also thinks that current study has been distracted away from the middle road of inquiry by being either too abstract and unrealistic or too concrete and descriptive. We have, as academics tended to study things that are totally abstracted from reality in order to develop control in the research process (almost all experimental research until the past few years) or we have moved to observing only real world events/contexts (rafting on a river, watching a specific movie or baseball team) which are, by definition, so specific as to provide little room for generalization.

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4.4. Interpreting patterns This next respondent sees development toward studying complexity and recognizes that the main merit of qualitative study is the field approach. There the goal is to explain the nature of situations, learning their characteristics and ‘‘deeper’’ relationships rather than, or in addition to, surveying (measuring and correlating) the frequency of subjects’ verbalizations. When Engel, Kollat, and Blackwell first came out, there was significant reliance on survey research which analyzed patterns in what people told us about themselves. But now, the focus is on mathematical models, experiments, and ethnographic observations to find patterns that consumers are not able to articulate about themselves. For example, Grant McCracken’s article on ‘‘Homeyness’’ dug into people’s home furnishings to lay out the characteristics that contribute to making an environment homey: layering, embracing, variable, engaging, mnemonic, etc.. . .there is much greater awareness of and healthy questioning of the scientific assumptions made in pursuit of that contribution to knowledge. We now acknowledge that we all start out by making particular assumptions, and then proceed to see what new contribution can be made after that. . .and give more attention to finding tensions that consumers operate within rather than point estimate of their preferences. . .some people call this postmodern, others just call it appreciating complexity. 4.5. Cycles, extending methods, and theories Another respondent associates freely to the evolution of consumer research, noting its cyclical character and its increasingly wide range of theorizing, use of various methods of research, and diversity of topics. Some study is seen as oriented to capturing consumers’ realities, while others’ look for underlying or more basic processes. A stream of consciousness response: I discovered that all of the hoo-hah about product symbolism some of us stumbled upon in the 1980s had been written about in the 1950s by yourself and a few others. . .perhaps the true hallmark of consumer behavior research is rediscovering the wheel??. . .Haire’s shopping list methodology. . . shopping/farmers’ market, etc., and ethnography (Odyssey) to capture phenomenology and real world experiences of consumers. . .methodologies ranging from the information display board to autodriving that capture the predominance of the visual channel. . .constructive memory processes (Bettman) and prospect theory. . . the symbolic renaissance of the 1980s. . .deeper descriptions: cultural meaning transfer (McCracken), aesthetics/ experiential consumption (Holbrook), extended self (Belk), rituals and structuralism (Rook and Levy)

. . .attitude models (Fishbein). . .deep study of subcultures, (Pen˜aloza) Hispanic immigrants, (Schouten) Harley riders. . .etc. 4.6. Fleshing out the details The final respondent provides a relatively detached summary that implies the big ideas have all been had, but are still guiding specific studies. The major contribution of the ’60s were the comprehensive models such as Howard and Sheth. They identified the basic influences and processes involved in CB. I don’t think much has been added in terms of scope. Since this time, we have been fleshing out the details. . .Attitude research of the 70s provided an important understanding of belief-based attitudes, a framework still useful today. . .Social influence work of the 70s. . .the human information processing paradigm. . .early research strictly cognitive. . .expanded to include emotional responses, low-involvement decision making and judgment, and even non-conscious processes. . .‘‘revolt’’ of the late 80s, most notably, the Odyssey project re-introduced the macro perspectives that had been part of the comprehensive models of the 1960s. . .focusing on the meanings of brands and consumption. . .included symbolic, ritual, emotional, social, and sensation aspects of consumption. . .qualitative methods used in sociology and anthropology. The respondents’ associations show the sense of change and developments over time. They recognize the richness and variety of the field of consumer research, and they show some sharp individual differences in awareness and evaluation of what has been achieved. Their views reflect the coming and going of qualitative research as it has contended for its place in the sun of the research world. In my view, having been part of this intellectual fray and survived it for over 50 years, I must say it has been enjoyable despite the many anxious moments in trying to cope with dubious clients, skeptical students, rigid reviewers, and supercilious colleagues. I am grateful that our heritage is sometimes funny, even ridiculous, so that we can laugh rather than cry about it. I am grateful to know and to have known so many of the participants— especially the really bright ones—who have collectively created and continue to work on our great common endeavor. References Berger B, editor. Authors of their own lives: intellectual autobiographies by twenty American sociologists. Berkeley (CA): University of California Press; 1990. Brown S. Marketing and literature: the anxiety of academic influence. J Mark 1999;63(January):1 – 15.

S.J. Levy / Journal of Business Research 58 (2005) 341–347 Clark LH, editor. Consumer behavior, vols. I – II. New York: New York Univ. Press; 1954 – 1955. Cohen JB, editor. Behavioral science foundations of consumer behavior. New York: Free Press; 1972. Fine GA. A second Chicago school? Chicago (IL): University of Chicago Press; 1995. Firat AF, Dholakia N. Consuming people: from political economy to theaters of consumption. New York: Routledge; 1998. Hirschman EC. Scientific style and the conduct of consumer research. J Consum Res 1985;12(September):225 – 39. Hirschman EC, Holbrook MB. Postmodern consumer research. Thousand Oaks (CA): Sage Publications; 1992. Hovland CI, Janis IL, Kelley HH. Communication and persuasion. New Haven (CT): Yale Univ. Press; 1953. Hunt S. Modern marketing theory: critical issues in the philosophy of marketing science. Cincinnati (OH): Southwestern; 1991. Kassarjian HH. Scholarly traditions and European roots of American consumer research. In: Laurent G, et al., editors. Research traditions in marketing. Boston (MA): Kluwer Academic Publishers; 1994. p. 265 – 79. Klapper JT. The effects of mass communication. New York: Free Press; 1960. Laczniak GR, Michie DA. The social disorder of the broadened concept of marketing. J Am Acad Mark Sci 1979;7, 3(Summer):214 – 32. Laurent G, Lilien GL, Pras B. Research traditions in marketing. Boston (MA): Kluwer Academic Publishers; 1994. Lazarsfeld P. Radio and the printed page. New York: Duell, Sloan and Pearce; 1940. Levy SJ. President’s column: a brief history. Assoc Consum Res Newsl (March) 1991;2 – 6. Levy SJ. Commentary by Sidney J. Levy. In: Laurent G, et al., editors. Research traditions in marketing. Boston (MA): Kluwer Academic Publishers; 1994. p. 283 – 7. Levy SJ. Stalking the amphisbaena. J Consum Res 1996;23, 3(December): 163 – 76. Lewin K. The conflict between Aristotelian and Galileian modes of thought

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in contemporary psychology. A dynamic theory of personality. New York: McGraw-Hill; 1935. p. 1 – 42. McCracken G. Culture and consumption. Bloomington (IN): Indiana Univ. Press; 1988. Morgan G, Smircich L. The case for qualitative research. Acad Manage Rev 1980;5(October):491 – 500. Piaget J. The language and thought of the child. New York: Harcourt Brace; 1926. Rook D, editor. Brands, consumers, symbols, and research: Sidney J. Levy on marketing. Thousand Oaks (CA): Sage Publications; 1999. Schau HJ. Discourse of possessions: the metatheory of Russell W. Belk. In: Alba JW, Hutchinson JW, editors. Adv Consum Res, vol. XXV; 1998. p. 37 – 44. Sherry Jr JF, editor. Contemporary marketing and consumer behavior: an anthropological sourcebook. Thousand Oaks, CA: Sage Publications; 1995. Sherry Jr JF, editor. ServiceScapes. Chicago (IL): NTC Business Books; 1998. Solomon M. Consumer behavior. Boston (MA): Allyn & Bacon; 1992. Wall Street Journal. But how does it make you feel? 1999;B1 [May 3]. Ward S, Robertson T, editors. Consumer behavior: theoretical sources. Englewood Cliffs (NJ): Prentice-Hall; 1973.

Further reading Merton R. Mass persuasion. New York: Harper & Brothers; 1946. Murray HA, et al. Techniques for a systematic investigation of fantasy. New York: Oxford Univ. Press; 1937. Warner WL, Henry WE. The radio day time serial: a symbolic analysis. Genet Psychol Monogr 1948;37:3 – 71. Warner WL, Meeker M, Eells K. Social class in America. Chicago (IL): Science Research Associates; 1949. p. 273. Wilder FF. Radio’s daytime serial [pamphlet]. New York: Columbia Broadcasting System; 1945.

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Response construction in consumer behavior research$ Robert A. Peterson* Department of Marketing, Mc Combs School of Business, The University of Texas, Austin, TX 78712, USA

Abstract To date, researchers have been relatively unsuccessful in accounting for a substantial proportion of the variance in the measures of consumer behavior that have been investigated. It is posited here that one of the primary reasons for this lack of success is that most studies of consumer behavior use self-reports—answers or responses to research questions—that are often very labile. It is further posited that responses to research questions are not generally revealed (retrieved directly from memory) but rather are constructed at the time a question is asked and answered. Because they are derived from processes that are inherently constructive, self-reports are susceptible to a variety of contaminating influences that collectively constrain the ability of researchers to explain or predict consumer behavior. Several suggestions are offered for addressing response construction processes and their effects. D 2003 Elsevier Inc. All rights reserved. Keywords: Consumer behavior; Response construction; Consumer behavior research

1. Introduction More than two decades ago, Jacoby (1978) authored a scathing ‘‘state-of-the-art review’’ of consumer behavior research. Jacoby began his review, which coincidentally received the prestigious Harold H. Maynard Award from the American Marketing Association for its contribution to marketing theory, by stating that ‘‘too large a proportion of the consumer (including marketing) research literature is not worth the paper it is printed on or the time it takes to read’’ (p. 87). A major theme throughout his review was that researchers had produced relatively little substantive knowledge of consumer behavior. If ‘‘substantive knowledge’’ can be equated with ‘‘variance accounted for,’’ it would appear that Jacoby (1978) was correct in his assessment of consumer behavior knowledge produced. Following an analysis of 70 different behavioral data sets (including but not limited to consumer behavior data sets), Cote and Buckley (1987) found that, of the variance accounted for in a variety of construct measures, less than 42% was due to the traits studied; the

$ An earlier version of this article was presented at the 1999 Marketing Communications and Consumer Behavior Seminar in La Londe les Maures, France. Appreciation is expressed to Gerald Albaum, Steven P. Brown, and Wayne D. Hoyer for their comments on a preliminary draft of the article. * Tel.: +1-512-471-9438. E-mail address: [email protected] (R.A. Peterson).

0148-2963/$ – see front matter D 2003 Elsevier Inc. All rights reserved. doi:10.1016/S0148-2963(03)00100-0

remainder was accounted for by the methods employed and by error. Although Peterson and Jolibert’s (1995) meta-analysis of 1520 country-of-origin effects revealed that, on average, the presence of a country-of-origin cue accounted for 26% of the variance in perceptions and purchase intentions, their results appear to be somewhat of an anomaly. In a general meta-analysis of the variance accounted for in consumer behavior experiments over the time period 1970 – 1982 (which included the publication of Jacoby’s 1978 review), Peterson et al. (1985) found that, across 118 independent experiments containing 1036 effects, on average, 5% of the variance in the dependent variables was accounted for by experimental manipulations. An identical percentage was obtained by Wilson and Sherrell (1993) in their metaanalysis of the effect of message source manipulation on persuasibility. More recently, a meta-analysis of 580 surveybased regression analyses (a majority of which were carried out in consumer behavior studies) conducted by the author covering the period 1964 – 1994 revealed that, on average, the variance accounted for in a dependent variable by an independent variable was slightly less than 1% (the average zero-order correlation coefficient was .08). Thus, in general, the amount of variance accounted for in measures of consumer behavior would seem to be relatively minor. A question then arises as to why this is so. The amount of variance accounted for is a function of many factors, including the theory employed (or the lack of

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theory), the research procedures and techniques utilized, the individuals and populations studied, and even the phenomena and constructs investigated. However, there is another plausible explanation for the minimal variance typically accounted for in consumer behavior research. This explanation is based on the data collected and analyzed in consumer behavior research. 1.1. Reliance on self-report data Much of what is known about consumer behavior, and, indeed, human behavior in general, is based on self-reports or, more generally, answers or responses to questions (e.g., Peterson and Kerin, 1981). While the theories, research procedures and techniques, individuals and populations studied, and phenomena and constructs investigated vary greatly in consumer behavior research, a common thread is the use of self-report data. To illustrate, examination of the articles contained in the Journal of Consumer Research since its inception reveals that fully 73% have relied on self-report data for their conclusions. Self-report data are usually accepted at ‘‘face value,’’ regardless of their source (oftentimes college students) and despite the fact that there is virtual consensus as to their fallibility. One need only peruse such classic articles as ‘‘Telling More Than We Can Know: Verbal Reports on Mental Processes’’ (Nisbett and Wilson, 1977) or ‘‘Verbal Reports as Data’’ (Ericsson and Simon, 1980) to appreciate the difficulties that can arise when using self-report data in consumer behavior research. A possible reason for the fallibility of self-report data relates to the notion that answers to research questions are constructed as they are elicited. This notion is the subject of this article.

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were no more than chaotic swirls of thought.’’ More recently, in the context of attitude measurement, Wilson and Hodges (1992) concluded that attitudes are ‘‘temporary constructs’’ formed at the moment a question is asked and answered. This opinion is consistent with that of Zaller and Feldman (1992, p. 582), who wrote that ‘‘people do not merely reveal preexisting attitudes on surveys; to some considerable extent, people are using the questionnaire to decide what their ‘attitudes’ are’’ (i.e., they construct their attitudes and question answers simultaneously). Even more recently, Schwarz et al. (1998, p. 150) observed that participants in a survey answering an attitude question . . .may either retrieve a previously formed attitude judgment from memory, or they may ‘‘compute’’ [emphasis added] a judgment [response] on the spot.. . .[To do so] they will also need to retrieve or construct [emphasis added] some standard against which the target is evaluated. In brief, although the ‘‘traditional view [of the attitude response process] holds that evaluative responses are cognitively represented in memory and may be directly (and automatically) activated’’ (Lavine et al., 1998, p. 359), there is an increasing belief among researchers that many attitudes are temporary constructions. Consequently, to the extent that attitudes are constructed, as seems to be the case for a variety of attitudes, answers to questions reporting attitudes must also be constructed (e.g., Lavine et al., 1998; Tourangeau and Rasinski, 1988; Zaller and Feldman, 1992). There is no logical alternative to response construction in such a case. 2.1. Response construction is pervasive

2. Responses are constructed The fundamental premise of this article is that the selfreport data employed in consumer behavior research consist of answers that have been constructed as responses to questions. Although answers to certain questions (‘‘Are you male or female?’’) may almost be reflexive, it is proposed that, in general, even the answers to factual questions, such those asking about age and income, are constructed ‘‘on-line,’’ ‘‘on-the-fly,’’ or in ‘‘real time’’ when the questions are asked. Rather than simply retrieving a response from memory—merely recalling information from memory or revealing a psychological characteristic and reporting that information or characteristic in response to a question, it is hypothesized that consumers generally construct their response when answering a question. The notion that responses are subject to inherently constructive cognitive processes is neither new nor novel. For example, more than 30 years ago, Bogart (1967, p. 335) wrote that sometimes asking a question ‘‘forces the crystallization and expression of opinions where [previously] there

This article goes beyond responses to attitude questions in that it argues that responses to most questions are constructed, not only those to attitude questions. As such, the present position is consistent with that of Schwarz et al. (1998, p. 150), who observed that if study participants are answering a question about behavior, they ‘‘need to recall or reconstruct [emphasis added] relevant instances of this behavior from memory.’’ Even questions that intuitively would be expected to be answered through direct recall, such as questions about past behaviors, generally require that responses be constructed (e.g., Blair and Burton, 1987; Menon, 1997). Note, however, that no argument is being put forth here as to the specific psychological processes underlying response construction. Such an argument is beyond the purpose and scope of this article (and any attempt at exposition would greatly exceed the current page constraint). Although it is argued that responses to questions are constructed, construction is perhaps best construed as existing as a continuous phenomenon that can take several different forms and occur at various stages of the question-and-answer process. Semantics aside, the extent to

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which response construction occurs is a matter of degree and conditional on several factors, including the phenomenon or construct being investigated and the accessibility and diagnosticity of information about it residing in memory. Succinctly stated, response construction can vary from complete response fabrication to a minor coalescing of stored information or tweaking the words contained in an answer. Moreover, response construction can be conscious or unconscious, and many memory principles can be invoked when attempting to explain or predict it. Consider a question for which no information is available in memory on which to form an answer. By definition, any response must be constructed. Thus, answers to a question asking about a fictitious issue or entity, such as the ‘‘Agricultural Trade Act of 1983’’ (Bishop et al., 1986), the ‘‘Texas state law regulating television news broadcasting’’ (Peterson, 2000, Fig. 3.1), or bogus (nonexistent) advertising slogans (Glassman and Ford, 1988) can only result from constructive processes. Consider further a question for which relevant information is not readily available in memory or, if available, needs to be aggregated or coalesced prior to an answer being formulated. An example might be a question that inquires about a consumer’s satisfaction with an automobile purchased 3 years ago, since satisfaction with the automobile is not likely to be directly or immediately accessible. Another example might be a question about intention to purchase a new refrigerator or expectations regarding the attributes of a new refrigerator. Unless the consumers questioned are experiencing problems with their current refrigerator, contemplating remodeling their kitchen, planning to purchase a refrigerator as a gift, or the like, they probably have not thought about purchasing a new refrigerator prior to being asked about doing so. Again, constructive processes must logically occur before such questions can be answered. Although the evidence supporting the notion of response construction is primarily indirect and somewhat circumstantial, it is compelling. Rejecting the notion of response construction requires the assumption that all information necessary to answer any question is capable of being (and, indeed, has been) encoded into memory, stored in memory, and recalled from memory without error. There is a substantial body of research in psychology, however, that refutes this assumption. Further, the assumption implies, in part, that the answer to any question is unaffected by, or independent of, the manner and context in which the question is asked. With few exceptions, though, the existing research evidence indicates that the manner and context in which a question is asked influences its answer.

identifiable process (cf. Fischoff, 1991). Consequently, there is a vast literature that can be brought to bear on the topic of response construction. Almost any research finding that demonstrates how a question answer or a judgment can be influenced or manipulated can be interpreted as evidence of response construction. Only if a question answer or a judgment is not subject to being influenced or manipulated can an argument logically be made for direct response retrieval. Consider just the following examples of research providing support for the notion of response construction. (Numerous other examples exist; the present ones were selected simply because they were readily available.) 3.1. Methodological research There is a plethora of methodological research on designing and administering questionnaires that suggest that the form, manner, and context in which a question is asked to a large extent determines the answer to it. Changing a single word (e.g., Gannon and Ostrom, 1996; Loftus and Zanni, 1975) or phrase (e.g., Levine, 1997) in a question has been shown to produce very different responses. Indeed, the accuracy of answers to even straightforward, factual (objective) questions, such as age (Peterson, 1984) and household income (Peterson and Kerin, 1980), has been shown to vary as a function of question format. Perhaps the most convincing evidence of response construction from the methodological literature relates to question order. It has been consistently documented that, under certain conditions, ‘‘people construct answers to survey questions on the basis of their responses to earlier items’’ (Simmons et al., 1993, p. 316). This finding has variously been termed an ‘‘assimilation – contrast effect’’ (e.g., Manis et al., 1988), a ‘‘part – whole’’ effect (e.g., Mason et al., 1994), and a ‘‘carryover – backfire’’ effect (e.g., Bickart, 1993). In general, to the extent that a response to a question is accessible and diagnostic, it may be used to construct responses to subsequent questions (e.g., Feldman and Lynch, 1988). Because the methodological literature is so diverse and voluminous, no attempt is made to summarize it. One needs to merely peruse such methodologically oriented journals as Public Opinion Quarterly or such compilations as Autobiographical Memory and the Validity of Retrospective Reports (Schwarz and Sudman, 1994) to be exposed to methodological research on source effects, question-order effects, mode-of-administration effects, and type-of-question effects, among others. All of these effects can be interpreted as inducing as well as influencing responses. Thus, they support the notion of response construction. Schwarz (1999) presents a concise yet enlightening review of recent research on these various effects.

3. Support for response construction 3.2. Context effects research Response construction is a ubiquitous cognitive phenomenon evidenced throughout the behavioral literature, although it has not traditionally been recognized as an

In a classic series of studies demonstrating group conformity, Asch (1940, 1956) asked people to judge the

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relative lengths of lines in a display. Although the lines were discernibly different in length, Asch was able to manipulate the responses of target individuals in a group by having research confederates in the group report judgments that were obviously in error. If the responses of the target individuals were not constructed but represented independent judgments, they should not have been subject to manipulation. Asch’s work is important because it represents one of the first empirical demonstrations of the influence of context on answers to research questions. In general, the psychophysics and social psychology literatures posit that the context within which a response is generated can markedly influence that response. As Stapel and Winkielman (1998, p. 634) recently pointed out: There is no such thing as a context-free judgment.. . .The context in which a target stimulus is embedded provides a frame of reference for interpretation and judgment. Hence, the same target can be associated with different responses depending on the context in which it is judged. Researchers (e.g., Birnbaum, 1982; Parducci, 1965; Volkman, 1951) have consistently documented that ratings of the size, weight, or shape of a particular stimulus object in a stimulus set are partially a function of the sizes, weights, or shapes of other stimulus objects in the set. Virtually identical effects have been observed for social judgments as well. In a widely cited study, Pepitone and DiNubile (1976) showed that a homicide was rated as a less severe crime if the rating was preceded by the evaluation of another homicide than if the rating was preceded by the evaluation of an assault. Similarly, Kendrick and Gutierres (1980) demonstrated that ratings of female attractiveness were influenced by prior exposure to extremely attractive females, and Biernat et al. (1997) found that explicit self-ratings influenced subsequent ratings of others. Analogous to Asch’s findings, the above findings lend themselves to a response construction interpretation. If responses (ratings) are not constructed, they should not be subject to influence through a context manipulation. 3.3. False memory research A general theme of current memory research is the fallibility of memory. There is a voluminous yet oftentimes contentious literature on ‘‘constructive memory,’’ ‘‘recovered memory,’’ ‘‘false memory,’’ ‘‘reconstructive memory,’’ and ‘‘confabricated memory.’’ One need only peruse tomes such as Recovered Memories and False Memories (Conway, 1997) or The Recovered Memory/False Memory Debate (Pezdek and Banks, 1996) to become aware of the issues being addressed in research on human memory. Schacter (1999) summarized much of the recent research on memory fallibility in an article titled ‘‘The Seven Sins of Memory.’’ Of interest here is his review of suggestibility

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(the fifth ‘‘sin’’), the idea that false memories can be created or memories ‘‘implanted’’ as a result of a questioning process. Research on suggestibility supports the proposition that responses are constructed in memory, not retrieved from memory. Several studies are presented to illustrate this distinction. Loftus (1993), in the first of several studies, reported the results of asking an individual to remember the time he had been lost in a shopping mall at age five. Despite the fact that the individual had never actually been lost in a shopping mall, the individual produced a detailed description of the event. Kassin and Kiechel (1996) had subjects perform a computer-based reaction time test. Subjects were told not to press the ‘‘ALT’’ key because doing so would cause the computer to crash. Although no subjects actually pressed the ALT key, a ‘‘witness’’ reported that they did, and ultimately almost 70% of the subjects falsely confessed. Hyman and Billings (1998) conducted a study similar to the one reported by Loftus in which a significant percentage of the undergraduate college students surveyed produced a false memory of a childhood event. What was especially interesting in this study was that the false memories became more vivid and detailed the second time they were elicited. Related research (e.g., Levine, 1997; Markus, 1986) has documented that memories of prior events or even emotions tend to display a consistency bias in that ‘‘recollections tend to exaggerate the consistency between [people’s] past and present attitudes, beliefs, and feelings’’ (Schacter, 1999, p. 193). At the present time, memory research suggests that certain false memories can be created in many people in particular situations. (It is important to note the emphasized adjectives. The creation of false memories appears to be conditional on a variety of factors, including gender, age, nature and intensity of the topic, and so forth.) This research contributes a theoretical foundation for guiding future research on response construction as well as convincingly documents that answers to questions can be completely fabricated, whether consciously or unconsciously. 3.4. Information processing research Research conducted on the construction of preferences, choices, judgments, beliefs, or the like (often referred to as constructive information processing research) offers useful insights into response construction. This is because, in one sense, the construction of preferences, choices, or the like is directly reflected by responses to questions about them. For example, in referencing the work of Slovic et al. (1990), Payne et al. (1992, p. 89) stated that ‘‘preferences for and beliefs about objects or events of any complexity are often constructed—not merely revealed—in the generation of a response to a judgment or choice task.’’ Therefore, if preferences, choices, judgments, or beliefs are constructed at the moment of elicitation (Slovic, 1995), then corresponding or consequent answers must also be constructed to the eliciting questions. (Note that exceptions might include answers to

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questions about established, noncomplex habitual behaviors or long-standing, elementary preferences.) If so, the organizing framework proposed by Bettman et al. (1998) for investigating constructive processes may prove useful when investigating the construction of responses.

4. Discussion and conclusion The objective of this article is really quite modest. The article simply represents an attempt to focus attention on one of the reasons researchers have been relatively unsuccessful in precisely explaining or consistently predicting various consumer behavior phenomena. In particular, the article posits that, with rare exceptions, answers to questions asked in consumer behavior research studies (and, indeed, in behavioral studies generally) tend to be constructed rather than revealed or directly retrieved from memory. If this article does nothing more than alert producers and interpreters of consumer behavior research to the existence and implications of response construction, it will be considered a successful endeavor. Response construction is analogous to other cognitive phenomena in that it is not directly observable. There is, however, substantial indirect evidence that most question responses are indeed constructed. Consequently, the notion of response construction has major implications for consumer behavior research. An obvious implication is that researchers should not generally expect to account for, say, a majority of the variance in the measures of consumer behavior investigated. (Although an argument might be made that research accounting for a large proportion of the variance in measures of consumer behavior is either trivial or the findings obvious and therefore uninteresting, such an argument ignores the reality of response construction as a determinant of a study outcome.) Thus, for example, assessments of the reliability of a multi-item scale should take into account the constructive nature of responses to individual scale items. In light of the existence of response construction, very high internal consistency scale reliability estimates (those close to 1.0) should be viewed with suspicion, not awe, and what is an ‘‘acceptable’’ reliability coefficient should probably be rethought. This is particularly so for the constructs frequently studied in consumer behavior research—attitudes, emotions, attributions, and so forth. Even as theories of consumer behavior and research methodologies become more sophisticated and ever more capable of finer distinctions, as long as self-reports or responses to questions serve as the primary source of information about consumer behavior, a lacuna in knowledge will remain. Because responses are constructed, they are susceptible to a myriad of contaminating influences (many of which are likely yet undiscovered). What is needed is systematic research, conceptual as well as empirical, that will at least establish the general boundary con-

ditions of response construction. In this regard, Hilton (1995) forcefully argues that a ‘‘constructionist perspective’’ specifically requires an explicit recognition of the role of context when obtaining verbal reports. Moreover, because question responses are susceptible to contaminating influences, increased attention should be given to these influences when eliciting responses. Systematic research along the lines of that conducted by Blair and Burton (1987) and Menon (1997) on asking behavioral frequency questions is needed across a variety of consumer behavior phenomena. Incorporating experimental treatments into a research investigation to evaluate the possible effects of questionnaire structure, mode of data collection, and question form on responses should become standard practice. For instance, employing different questionnaire versions as treatments should be routine in basic research. One benefit of such a practice is that it permits both a practical and a statistical assessment of the stability of the phenomenon or construct being investigated. Fortunately, if recent consumer behavior and marketing research publications are an indication of an incipient trend, there is a renewal of interest in topics that can be subsumed under the rubric of response construction. A second implication of response construction is that researchers need to incorporate measures other than selfreports of consumer behavior phenomena into their investigations. Recently, Winer (1999) has argued in favor of an increased use of scanner data in consumer behavior research to corroborate findings based on self-reports. Other researchers have espoused the use of nonverbal data when studying consumer behavior. Although it is not clear exactly what nonverbal data should be collected and analyzed, attempts should be made to substitute, supplement, and complement self-report data in future investigations. For example, Peterson et al. (1995) studied the effects of nonverbal voice characteristics, such as rate of speaking, average pause duration, and fundamental frequency contour, as complements to self-reports. Response construction, as both a reflection of and a consequence of cognitive information processing, is worthy of investigation in and of itself, not as merely a contributor to measurement unreliability or as a methodological artifact. The notion of response construction should minimally serve as the basis of a framework that will facilitate the organization, integration, and application of methodological as well as substantive findings from numerous and disparate disciplines. Until that happens, the explanatory and predictive power of consumer behavior research will remain low.

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Journal of Business Research 58 (2005) 354 – 360

Advertising repetition and quality perception Sridhar Moorthy*, Scott A. Hawkins Joseph L. Rotman School of Management, University of Toronto, 105 St. George Street, Toronto, Ontario, Canada M5S 3E6

Abstract Nelson [J. Polit. Econ. 78 (1970) 311; J. Polit. Econ. 81 (1974) 729; Nelson P. The economic value of advertising. In: Brozen Y, editor. Advertising and society. New York: New York Univ. Press, 1974. pp. 43 – 66] has argued that advertising spending is a signal of product quality for experience goods because consumers can rationally infer that high-quality products would advertise more than low-quality products. In this paper, we compare Nelson’s view of advertising with marketing views of advertising using ad repetition as a surrogate for ad spending. Our results show limited support for Nelson’s theory but substantial support for ad repetition influencing perceived quality through attitude toward the ad. D 2003 Elsevier Inc. All rights reserved. Keywords: Advertising; Spending; Quality

1. Introduction In a seminal paper nearly 30 years ago, Nelson (1970) proposed a distinction between two types of goods, search goods and experience goods, and offered a new theory of advertising based on that distinction. Search goods were defined as products whose quality consumers can verify before purchasing (e.g., clothing, furniture, and jewelry). Experience goods were defined as products whose quality the consumer cannot determine until after buying and experiencing the product (e.g., foods, books, and detergents). Nelson argued that advertising claims for experience goods are uninformative because consumers cannot verify such claims before purchasing the product. Advertising spending, however, is informative because consumers can rationally infer that products that advertise more are of higher quality than products that advertise less. By contrast, for search goods, advertising claims are informative, and no further information is needed from, or provided by, the spending level. Nelson’s view of advertising for experience goods is radically different from ‘‘the marketing view.’’ Whereas Nelson minimizes the importance of the ad itself—for example, it is not even necessary for the firm to advertise as long as it has other ways of ‘‘burning money’’—the

* Corresponding author. E-mail address: [email protected] (S. Moorthy). 0148-2963/$ – see front matter D 2003 Elsevier Inc. All rights reserved. doi:10.1016/S0148-2963(03)00108-5

marketing literature emphasizes it (Batra et al., 1996). In marketing, it is taken as a given that ad design and ad claims have significant effects on product perceptions— regardless of the nature of the product. In fact, the work of Hoch and Ha (1986) suggests that, if anything, advertising claims might be even more effective in shaping perceptions for experience goods because the experience itself is likely to be ambiguous. Marketing textbooks are replete with examples of how the same physical product (e.g., 7-Up) has been ‘‘positioned’’ in different ways through different ad campaigns. In this paper, we test the Nelson theory against the ‘‘marketing view.’’ We use the term ‘‘marketing view’’ to refer to three theories: learning, ad attitude, and mere exposure. Each of these theories points to a different type of advertising effect, and multiple effects may coexist in an ad campaign. So it is not a matter of picking one of these theories and ruling out the rest. Rather, because these theories as a group have much in common and contrast sharply with the Nelson view, we examine whether the data support the marketing view or the Nelson view. There are potentially many ways to test Nelson’s theory, depending on the myriad ways in which advertising moneys can be spent—repetition (frequency), reach, ‘‘large’’ versus ‘‘small’’ ads, color versus black-and-white ads, TV versus print, etc.—and whether the researcher uses observational or experimental methods. This paper uses experimental methods and advertising repetition as the spending variable.

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Much of the existing literature uses observational data. The papers by Rotfeld and Rotzell (1976), Kotowitz and Mathewson (1986), Tellis and Fornell (1988), Davis et al. (1991), and Caves and Greene (1996) examine the correlation between some measure of objective quality (e.g., Consumer Reports rankings), or managers’ perceptions of their customer’s perceptions of quality (PIMS data), and advertising spending across brands. In general, these papers find limited support for Nelson’s theory. For example, Caves and Greene’s (1996) comprehensive study of 196 product categories concludes: ‘‘These results suggest that quality-signaling is not the function of most advertising of consumer goods.’’ In contrast to these generally negative results are the generally positive results in the experimental literature. Unlike the observational literature where the focus is on the advertising spending-objective quality correlation, here the focus is on the advertising spending-perceived quality correlation. Kirmani and Wright (1989) cue advertising spending via size, vehicle (reach), production elements, and frequency in some experiments, and in others advertising spending information is simply given to subjects. Their strongest results in support of Nelson are obtained with size, vehicle, production elements, and spending levels. With frequency, their results contradict Nelson: ad campaigns described as high frequency were found to correlate negatively with perceived quality. A common feature of the Kirmani and Wright (1989) experiments is that subjects are not given the opportunity to infer advertising spending from a real advertising campaign—the common situation in the real world. Instead, campaign elements are artificially highlighted and in some cases advertising spending levels are given in dollars. The highlighting of advertising expense information in these experiments raises the possibility of demand effects driving the reported advertising spending-perceived correlation. It also raises the question of whether consumers can spontaneously pickup advertising spending information under naturalistic conditions. If they do not, then Nelson’s theory—even if it is internally valid—would have limited applicability. Kirmani (1990) partially corrects for these deficiencies by exposing subjects to fictional ads of different sizes. Kirmani (1997) goes further, exposing subjects to real ads at different frequencies. Kirmani (1997) finds an inverted U-shaped relationship between ad spending and quality perceptions. The upward sloping part of the curve is consistent with Nelson’s theory; the downward-sloping part is not. In this paper, we manipulate advertising spending via advertising repetition and measure its effect on consumers’ perceptions of quality. A key feature of our experiment is that it is explicitly designed to compare Nelson’s theory to the marketing view. The comparison is important because with ad repetition serving as a surrogate for ad spending, both views can predict the same overall relationship between perceived quality and advertising spending. Never-

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theless, the mechanisms underlying the two approaches and their implications for advertising practice are completely different. Our experiment exploits these differences to discriminate between Nelson’s theory and the marketing view. In the process, it differs from Kirmani and Wright (1989) and Kirmani (1990) in several important ways. First, we use real ads. Not only does this increase the external validity of our results, but it also increases their internal validity. To adequately test Nelson’s theory, consumers must be assured that money was actually spent on advertising—otherwise, they would not be able to rule out the possibility of a lowquality product masquerading as a high-quality product. With fictitious products and fictitious advertising, this is hard to do (for example, in Kirmani, 1990, the ads were in a black-and-white magazine, and the cover page of the magazine was a set of instructions that asked the subjects to ‘‘look through the magazine as they naturally would if they were reading it at home.’’ Real magazines are generally in color and do not have reading instructions on their cover pages). Second, we experimentally manipulate whether respondents have to spontaneously pick up advertising frequency by actual exposure to an advertising campaign or frequency information is provided to them. By contrast, Kirmani and Wright (1989) only provided the summary information, and Kirmani (1990, 1997) only varied the physical exposure. For Nelson’s theory to have any external validity, of course, consumers ought to be able to pick up advertising spending information spontaneously while an advertising campaign unfolds. But for Nelson’s theory to have internal validity, it ought not to make a difference how the spending information is given to subjects. By contrast, the theories comprising the marketing view are explicitly theories about physical exposure to advertising. Finally, we examine four product categories, two of which are classifiable as search goods and the other two as experience goods. Nelson makes different predictions depending on whether the product is a search good or an experience good; but for the marketing view, it makes no difference.

2. Background 2.1. Nelson’s theory The essence of Nelson’s (1970, 1974a,b) theory is the idea that for experience goods, consumers should rationally infer that only high-quality products would spend much in advertising. This is because only high-quality brands can count on obtaining a significant number of repeat purchases. Low-quality brands pretending to be high quality will be ‘‘discovered’’ to be poor values after the first purchase, will not generate repeat purchases, and so cannot justify matching the high-quality firm’s advertising expenditures. For

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search goods, on the other hand, advertising copy will be directly informative, and advertising spending has no signaling role to play [Nelson’s theory can be seen as giving a logical basis for why consumers should use a brand’s presence in the media as a cue to its popularity or acceptability with other consumers; Sutherland and Galloway, 1981. Note, however, that popularity and quality may not be correlated (see discussion below)]. Nelson’s theory is really a theory about the relationship between the true, objectively measured, quality of a product and advertising spending. Quality as perceived by consumers is nevertheless a key construct in the theory. Nelson postulates that consumers start out being uncertain about the quality of experience goods, but after observing the advertising spending level—and going through the logic outlined above—their perception matches the reality. Despite its compelling logic, several questions may be raised about the applicability of Nelson’s theory in the real world. First, consumers may not be able to observe or infer advertising spending levels. Advertising budgets are not printed on ads so it is difficult for the average consumer to tell whether brand X is spending more or less than brand Y. Moreover, advertising invariably involves nonpublic hidden costs—e.g., the cost of hiring advertising agencies, and the time devoted to developing and testing advertisements. Hertzendorf (1993) shows that the efficacy of advertising spending as a signal of quality goes down considerably if consumers are not able to observe advertising expenditures perfectly. Second, consumers may not be able to observe quality even after using the product. The difficulty arises not only because consumers are not ‘‘expert’’ at evaluating performance (Kempf and Smith, 1998), but also because they typically consume one brand at a time under ‘‘noisy’’ conditions—unlike, say, a professional testing laboratory, which can compare several brands simultaneously under controlled conditions. Hoch and Ha (1986) argue that when product trial is ambiguous, advertising claims shape consumers’ perceptions; Horstmann and MacDonald (1994) show theoretically that if consumption experience is not fully informative, then the signaling role of advertising spending is diluted. Third, advertising spending in the real world may be tied to market share, which is a function of value, not quality per se. For example, the brands rated high in quality by Consumer Reports are often not the products with the highest market share nor even Consumer Reports’ own ‘‘best buys.’’ Fourth, why should firms use advertising spending to signal product quality when other easier-to-read signaling instruments such as price (e.g., Bagwell and Riordan, 1991) and money-back guarantees (e.g., Moorthy and Srinivasan, 1995) are available? Finally, Nelson’s theory assumes that advertising claims on experiential attributes are uninformative. Yet most advertising for experience goods has experiential claims—e.g.,

most cereal advertising claims that the cereal tastes ‘‘great’’—and marketing specialists believe that such claims have a positive effect on their brands on repetition (Hawkins and Hoch, 1992). 2.2. The marketing view In the marketing view of advertising, there are at least three ways by which advertising can shape consumers’ perceptions of product quality: (1) by providing information about product attributes (learning theory: Hovland et al., 1953; Lavidge and Steiner, 1961; McGuire, 1978), (2) by increasing the consumer’s familiarity with the brand (mere exposure theory: Wilson, 1979; Zajonc, 1980; Sawyer, 1981), and (3) by shaping the consumer’s attitude toward the ad (attitude-toward-the-ad-theory: Mitchell and Olson, 1981; MacKenzie et al., 1986; Brown and Stayman, 1992). These alternative ways are not meant to be mutually exclusive. It is quite possible, for instance, that both mere exposure effects and learning go on simultaneously. As alternatives to Nelson’s theory, learning theory, mere exposure effects theory, and attitude-toward-the-ad-theory have much in common. First, like Nelson’s theory, they are consistent with a positive relationship between advertising repetition and perceived quality. Second, unlike Nelson’s theory, they are based on actual physical exposure of consumers to advertising repetition. In contrast, in Nelson’s theory, it does not matter how consumers get the advertising spending information; what is relevant is the spending signal, not how it is acquired. Third, because they are based on physical exposure to advertising, these alternative theories are amenable to ‘‘wear-out’’ phenomena. If the same ad is repeated too often, consumers may get irritated and bored, and this may inspire a degradation of perceived quality (Pechmann and Stewart, 1989). In contrast, wear-out would be hard to accommodate in Nelson’s theory: every additional exposure augments the spending signal and is therefore useful information for a motivated consumer. Finally, none of these alternative theories makes a distinction between search and experience goods. Table 1 summarizes these contrasting predictions.

Table 1 Nelson’s theory versus the marketing view

1. Relationship between ad repetition and perceived quality 2. Does it matter whether the respondent is actually exposed to ads repeatedly or is merely told the repetition frequency?

Nelson

Marketing view

Increasing for experience goods, no relationship for search goods No

Increasing for both search and experience goods. Inverted U-shaped relationship possible. Yes; the relationship between repetition and perceived quality applies only with actual repetition.

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3. Experiment The basic idea behind our experiment is that we present ad spending information in two different ways, actual repetition of ads and ‘‘told’’ repetition—where the consumers are merely told about repetition frequency in a credible manner—and see whether it makes a difference to how consumers perceive product quality. Further, by including both search goods and experience goods in our study, we examine whether it matters if the product is a search good or an experience good. To make our advertising manipulations the sole source of information and familiarity for the products, we use Italian products advertised in an Italian magazine on non-Italian-speaking Canadian subjects. The cover story was that a number of Italian companies were considering entry into Canada and the subjects’ task was to examine each ad carefully in order to determine the likelihood of the product’s success in Canada. The study involved a 2 (product category type: search vs. experience)  2 (product categories)  3 (number of ad repetitions: one, three, or five)  2 (type of repetition: ‘‘told’’ vs. actual) factorial mixed-model design. One hundred and seventy-nine undergraduate students formed the subject pool. Product category type and (nested within it) the two product categories of each type were within-subjects factors, while the type and level of repetition were betweensubjects factors. We chose overcoats (brand allegro) and cookware (brand Æturnum) as the two search goods, and yogurt (brand Yomo) and nasal spray (brand deltinarolo) as the two experience goods. These classifications are easy to defend. Clothing and food products are often cited as the quintessential search and experience goods, respectively (Nelson, 1970; Davis et al., 1991). Cookware is a search good because its design, materials, and construction are observable in the store. Nasal spray is an experience good because the active ingredients are in an opaque bottle, and the consumer cannot evaluate things like efficacy and ease of use without actually using the product. A manipulation check supported the classification. When asked the question, ‘‘How easy is it to verify advertising claims about quality before purchasing the following products?’’ our subjects responded with mean ratings of 3.4 for nasal spray, 2.9 for yogurt, 2.6 for cookware, and 2.0 for overcoats on a four-point scale ranging from 1 = very easy to 4 = very difficult. These ratings show significant difference between category types when analyzed in a 3 (number of repetitions)  2 (type of repetition)  2 (type of category)  2 (categories) mixed-model MANOVA: F(1,173) = 165.46, P < .01. Subjects in the actual repetition condition saw five consecutive issues of the magazine Gente. Subjects in the told repetition condition saw only the last magazine issue, but on top of each ad was a label noting the frequency of appearance of the ad. Thus, for example, subjects in the three actual repetitions condition saw the test ads three times in five magazine issues, whereas subjects in the three told

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repetitions condition saw the test ads once but the label told them that the ads appeared in ‘‘three out of five issues.’’ Each magazine issue had eight full-page ads from Gente and the actual cover page of the issue. Some issues had four test ads (for yogurt, cookware, overcoats, and nasal spray) and four filler ads; others had eight filler ads. There was no editorial material in these magazine mock-ups. This was consistent with the stated purpose of our study and our desire not to ‘‘take up too much of their time.’’ By choosing ads from a real magazine and including its cover pages in our magazine mock-ups, we intended to (1) corroborate our cover story, and (2) establish that the advertising was real. As discussed earlier, for Nelson’s signaling theory to work, consumers must be reasonably certain that actual advertising moneys were spent by the manufacturer of the product. Our use of Italian print ads on English-speaking subjects also was designed to improve the chances of Nelson’s theory applying because the subjects could not—even if they wanted to—get any information from the ad copy. But the ads were not totally uninformative. There was visual information in the ads— the pictures of the products and (in the case of the overcoat) the pictures of the models wearing the overcoat as well. These pictures give some information about the search attributes of the products but not about the experience attributes of the products. From a learning theory perspective, therefore, there was not much to learn for these ads.

4. Results 4.1. Manipulation checks In order to assess the effectiveness of the repetition manipulation in the two instruction conditions, the perceived number of repetitions provided by each subject was submitted to a 3 (number of repetitions)  2 (type of repetition) mixed-model MANOVA. There was a significant increase in the number of perceived repetitions as the number of ad repetitions increased [ F(2,173) = 143.8, P < .001]. Type of repetition did not interact with repetition [ F(2,173) = 2.69, P>.05]. Simple effects tests indicated that the perceived number of repetitions increased with the number of ad repetitions in both the actual [ F(2,174) = 52.3, P < .001] and told [ F(2,174) = 95.8, P < .001] repetition conditions. 4.2. Perceived quality Perceived quality was measured by asking questions of the form, ‘‘How would you rate the overall quality of the Æturnum brand of cookware?’’ and taking responses on nine-point scales anchored by ‘‘very poor quality’’ and ‘‘very good quality.’’ The cell means and standard deviations are shown in Table 2.

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Table 2 Perceived quality: cell means and standard deviations

Cookware

Type of repetition

No. of repetitions

Mean

S.D.

N

Actual

1 3 5 1 3 5 1 3 5 1 3 5 1 3 5 1 3 5 1 3 5 1 3 5

4.79 5.86 6.31 6.26 6.58 6.00 6.34 5.86 7.52 6.61 6.74 6.57 4.52 5.48 5.55 5.23 5.94 4.97 5.59 6.52 6.69 6.23 6.42 6.03

3.19 1.27 1.77 1.57 1.52 1.62 2.14 2.12 1.68 1.75 2.07 1.78 1.92 1.94 1.40 1.91 1.71 1.33 1.50 1.09 1.04 1.48 1.57 1.10

29 29 29 31 31 30 29 29 29 31 31 30 29 29 29 31 31 30 29 29 29 31 31 30

Told

Overcoat

Actual

Told

Nasal spray

Actual

Told

Yogurt

Actual

Told

The effect of number of repetitions on product quality ratings was examined using a 2 (category type)  2 (category)  3 (number of repetitions)  2 (type of repetition) mixed-model MANOVA with categories nested within category type. The first two variables were within-subject factors, and the last two variables were between-subject factors. Product quality ratings show a significant increase with the number of repetitions [ F(2,173) = 4.83, P < .01]. However, Fig. 1 indicates that this effect is qualified by a significant interaction of number of repetitions and type of repetition [ F(2,173) = 8.0, P < .01]. Polynomial contrasts show a linear trend over number of repetitions for actual repetition (t = 4.56, P < .001) and a quadratic trend over number of repetitions for told repetition (t = 1.96, P < .053). Thus, while perceived quality consistently increased as the

number of actual ad repetitions increased, the quality ratings increased and decreased in an inverted U relationship as the number of told repetitions increased. Nelson’s theory would predict no difference in perceived quality’s response to actual and told repetition. There was no significant category_type by repetition interaction on quality ratings [ F(2,173) = 2.12, P>.12]. That is, the effect of repetition on quality ratings did not depend on the nature of the product category, contradicting Nelson’s theory. Polynomial contrasts suggest that the culprit may be a significant linear trend over number of repetitions for search goods (t = 2.2, P < .03)—not predicted by Nelson’s theory—that is insufficiently different from a significant linear (t = 2.0, P < .05) and quadratic trend (t = 2.75, P < .01)—increasing and then decreasing—for experience goods. At the category level (Table 3), actual repetition has a significant effect in all categories; told repetition is not significant in any of the four categories. 4.3. Attitude toward the ad (Aad) Ad attitude was measured by asking questions of the form, ‘‘What was your overall opinion of the advertisement for the Æturnum brand of cookware?’’ and taking responses on ninepoint scales anchored by ‘‘very good’’ and ‘‘very bad.’’ A MANOVA analysis of ad attitudes shows a significant main effect for repetition [ F(2,173) = 4.1, P < .02] and an insignificant interaction effect with repetition type [ F(2,173) = 2.1, P>.12]. The simple effects show that Aad responds linearly to actual repetition [ F(2,173) = 4.7, P < .02], but there is no response to told repetition [ F(2,173) = 1.5, P>.22], which is to be expected since subjects saw the ads only once in all the told repetition conditions. To see whether Aad might be mediating the relationship between repetition and perceived quality, we subjected each category’s perceived quality ratings to ANOVAs, with actual or told repetition as the only between-subject factor, with and without the corresponding Aad as a covariate (a MANOVA covariance analysis does not make sense in this context since, for example, attitude toward the yogurt ad cannot be a covariate for the perceived quality of nasal spray). These analyses with corresponding effect sizes (g2) are shown in Tables 3 and 4. Aad is highly significant in all categories with large effect sizes, and it does not mediate the relationship between told repetition and perceived quality. Table 3 Perceived quality of each category by actual and told repetition Cookware

Overcoats 2

F ratio g ( P) Actual repetition Told repetition Fig. 1. Perceived quality and repetition: actual versus told repetition.

3.54 * (.033) 1.05 (.355)

Nasal spray 2

F ratio g ( P)

.078 5.30 * (.007) .023 0.07 (.930)

* Significant at .05 level.

F ratio ( P)

.112 3.09 * (.051) .002 2.77 (.068)

2

Yogurt

g

F ratio g2 ( P)

.069

6.79 * (.002) 0.58 (.561)

.059

.139 .013

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Table 4 Perceived quality of each category by repetition and repetition type with Aad as covariate Cookware Repetition

Actual repetition Told repetition

Overcoats Aad

Repetition

Nasal spray Aad

Repetition

Yogurt Aad

Repetition

Aad

F ratio ( P)

g2

F ratio ( P)

g2

F ratio ( P)

g2

F ratio ( P)

g2

F ratio ( P)

g2

F ratio ( P)

g2

F ratio ( P)

g2

F ratio ( P)

g2

0.74 (.482) 1.25 (.292)

.017

262.19 * (.000) 48.13 * (.000)

.760

7.34 * (.001) 0.018 (.982)

.150

172.41 * (.000) 102.67 * (.000)

.675

0.60 (.550) 2.10 (.128)

.014

57.59 * (.000) 87.83 * (.000)

.410

5.00 * (.009) 3.67 * (.029)

.108

76.77 * (.000) 139.96 * (.000)

.480

.028

.354

.000

.538

.046

.500

.077

.614

* Significant at .05 level.

There is some evidence, however, that it mediates between actual repetition and perceived quality: in two out of four categories, repetition loses significance when Aad is introduced, and in three out of four categories its effect size goes down.

5. Discussion Our results generally do not support Nelson’s theory. Referring to Prediction 2 in Table 1, we find that it makes a difference how advertising spending information is conveyed to subjects. When advertising spending information is embedded in the physical repetition of ads, perceived quality increases linearly with repetition; but when advertising spending information is embedded in statements of ad repetition, perceived quality has an inverted U relationship to repetition, with no linear trend. These differences are even starker at the individual category level (Table 3). Whereas actual repetition has a positive linear effect in all categories, told repetition has no effect in any of the categories. The results with respect to Prediction 1 are also not favorable to Nelson. Nelson would predict an effect for repetition only for experience goods. We find, however, that category type does not matter. Our results are, however, quite congenial to the marketing view. We noted earlier that the marketing view of advertising comprises at least three effects—learning, familiarity, and attitude toward the ad—each of whom can explain a positive relationship between perceived quality and actual repetition. Out of these, our experiment was not particularly well-suited to test for learning because we deliberately minimized the information in the ads in order to give Nelson’s theory its best shot. The other two effects cannot be ruled out, and in particular there is evidence of attitude toward the ad mediating the relationship between actual repetition and perceived quality in three out of the four categories. In fact, even in the category (overcoats) where attitude toward the ad does not seem to mediate, it is almost five times as effective as repetition in explaining the variance in quality. The two different ways of communicating the spending signal were obviously not equivalent. Advertising frequency information—and by extension advertising spending infor-

mation—was more salient and easier to acquire in the told repetition condition than in the actual repetition condition. Nelson’s theory, then, should have its best shot at succeeding in the told repetition condition. Yet even in this condition, what we get is an inverted U relationship between repetition and perceived quality when pooling across categories, and no relationship at all at the individual category level. The upward-sloping part of the inverted U curve is consistent with Nelson’s theory; the downward-sloping part contradicts it. Kirmani and Wright (1989) and Kirmani (1990) obtained similar results—under similar conditions (we discussed earlier that the manipulations of advertising in Kirmani and Wright, 1989 and Kirmani, 1990, made the advertising spending signal more salient than they would be in the real world. In this sense, they were closer to our told repetition condition than to our actual repetition condition). Kirmani (1990) interpreted the downward-sloping part as a ‘‘desperation undermine.’’ Instead of reasoning that ‘‘higher advertising spending signals higher quality because the firm is confident of repeat purchase’’—which is what Nelson would like them to do—subjects seem to think that ‘‘higher advertising spending signals lower quality because the firm must be desperate to spend so much on advertising.’’ Desperation reasoning seems more likely when excessive spending is more salient.

6. Conclusion In the conventional view of advertising, as described in marketing textbooks, the effectiveness of advertising is a function of its content (the message), execution (how the ad conveys the message), and frequency (how often a consumer sees the ad) (Kotler, 1997, chap. 20; Batra et al., 1996, chap. 5). The advertising spending level enters the picture only in service of these three factors. If a company does not spend enough on advertising, then its content might be off-base, or the ads might be poorly executed, or the frequency might be inadequate. Nelson’s (1970, 1974a,b) theory offers a radically different view. It argues that how advertising works depend on whether the product is a search good or an experience good and that the marketing view applies only to search goods. For experience goods, the only thing that matters is the advertising

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spending level—or, for that matter, any "wasteful" spending—not content, execution, or frequency. This paper offers evidence in support of the marketing view. Our experiments show that it matters how advertising spending information is communicated to subjects. Subjects respond more to advertising repetition—in the sense of changing their perceived quality judgments—when they are actually exposed to advertising than when the advertising frequency data are provided to them as an abstract number. On the other hand, it does not seem to make much difference whether the product being advertised is a search good or an experience good. Our results suggest that the ad itself is a critical variable mediating the response to repetition. Subjects in our study seemed to like an ad more after repeated exposure to it and seemed to transfer this liking to the product being advertised, raising its quality rating. Our results are also consistent with ‘‘mere exposure’’ effects: increased ad exposure increasing familiarity with the brand and hence perceived quality. Learning effects were largely precluded by our experimental design, but other research suggests that it is an important way by which real-world advertising works (Batra et al., 1996, p. 151). Marketing professionals ought to be reassured by our findings. As it is practiced in the real world, advertising does not seem to differentiate between search goods and experience goods. Ad claims cover both search and experience attributes, and often even credence attributes. Advertising agencies have existed for a long time, and every year firms channel billions of advertising dollars through them. These practices would be hard to explain if advertising did nothing more than ‘‘burn money.’’

Acknowledgements This research was supported by grants from the Social Sciences and Humanities Research Council of Canada. The authors thank Amna Kirmani, John Lynch, and Akshay Rao for valuable discussions at various stages of the project.

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Davis E, Kay J, Star J. Is advertising rational? Bus Strateg Rev 1991; (Autumn):1 – 23. Hawkins SA, Hoch SJ. Low-involvement learning: memory without evaluation. J Consum Res 1992;19(September):212 – 25. Hertzendorf MH. I’m not a high-quality firm—but I play one on TV. R J Econ 1993;24(Summer):236 – 47. Hoch SJ, Ha Y-W. Consumer learning: advertising and the ambiguity of product experience. J Consum Res 1986;13(September):221 – 33. Horstmann IJ, MacDonald GM. When is advertising a signal of product quality? J Econ Manage Strategy 1994;3(Fall):561 – 84. Hovland CI, Janis IL, Kelly HH. Communication and persuasion. New Haven (CT): Yale Univ. Press, 1953. Kempf DS, Smith RE. Consumer processing of product trial and the influence of prior advertising: a structural modeling approach. J Mark Res 1998;35(August):325 – 38. Kirmani A. The effect of perceived advertising costs on brand perceptions. J Consum Res 1990;17(September):160 – 71. Kirmani A. Advertising repetition as a signal of quality: if it’s advertised so much, something must be wrong. J Advert 1997;(Fall):160 – 71. Kirmani A, Wright P. Money talks: perceived advertising expense and expected product quality. J Consum Res 1989;16(December):344 – 53. Kotler P. Marketing management: analysis, planning, implementation, and control. Englewood Cliffs (NJ): Prentice-Hall; 1997. Kotowitz Y, Mathewson F. Advertising and consumer learning. In: Ippolito PM, Scheffman DT, editors. Empirical approaches to consumer protection economics: proceedings of a conference sponsored by the Bureau of Economics Federal Trade Commission, April 26 – 27, 1984. Washington (DC): Federal Trade Commission; 1986. p. 109 – 34. Lavidge RJ, Steiner GA. A model for predictive measurements of advertising effectiveness. J Mark 1961;25(October):59 – 62. MacKenzie SB, Lutz RJ, Belch GE. The role of attitude toward the ad as mediator of advertising effectiveness: a test of competing explanations. J Mark Res 1986;23:130 – 43. McGuire WJ. An information processing model of advertising effectiveness. In: Davis HL, Silk AJ, editors. Behavioral and management science in marketing. New York: Ronald Press; 1978. p. 156 – 80. Mitchell A, Olson J. Are product attribute beliefs the only mediator of advertising effects on brand attitudes? J Mark Res 1981;18:318 – 32. Moorthy S, Srinivasan K. Signaling quality with a money-bank guarantee: the role of transaction costs. Mark Sci 1995;442 – 66. Nelson P. Information and consumer behavior. J Polit Econ 1970;78: 311 – 29. Nelson P. Advertising as information. J Polit Econ 1974a;81:729 – 54. Nelson P. The economic value of advertising. In: Brozen Y, editor. Advertising and society. New York: New York Univ. Press; 1974b. p. 43 – 66. Pechmann C, Stewart DW. Advertising repetition: a critical review of wearin and wearout. In: Leigh JH, Martin Jr CR, editors. Current issues and research in advertising 1988. Ann Arbor (MI): University of Michigan Press; 1989. p. 285 – 330. Rotfeld HJ, Rotzell KB. Advertising and product quality: are heavily advertised products better? J Consum Aff 1976;10(Summer):33 – 47. Sawyer AG. Repetition, cognitive responses, and persuasion. In: Petty RE, Ostrom TM, Brock TC, editors. Cognitive responses in persuasion. Hillsdale (NJ): Erlbaum; 1981. p. 237 – 62. Sutherland M, Galloway J. Role of advertising: persuasion or agenda setting? J Advert Res 1981;21(October):25 – 9. Tellis GJ, Fornell C. The relationship between advertising and product quality over the product life cycle: a contingency theory. J Mark Res 1988;15(February):64 – 71. Wilson WR. Feeling more than we can know: exposure effects without learning. J Pers Soc Psychol 1979;37(June):811 – 21. Zajonc RB. Feeling and thinking: preferences need no inferences. Am Psychol 1980;35:151 – 75.

Journal of Business Research 58 (2005) 361 – 368

Enhancing or disrupting guilt: the role of ad credibility and perceived manipulative intent June Cottea,*, Robin A. Coulterb, Melissa Moorec a

University of Western Ontario, London, ON, Canada b University of Connecticut, Storrs, CT, USA c Mississippi State University, Mississippi State, MS, USA

Abstract Viewing the consumer as an active, skeptical reader of the persuasion attempt is an emerging perspective in advertising research. This perspective suggests that a consumer’s recognition of an emotional ‘‘tactic’’ in an ad can have a significant impact on an ad’s intended effect. Adopting this approach, we examine whether consumers’ evaluations of an ad’s credibility can enhance, and perceptions of manipulative intent can disrupt, the emotional response intended by the advertiser. We also investigate the effects of these two variables on attitude toward the ad and corporate attributions, including attitude toward the sponsor of the ad. We examine a commonly employed emotional tactic—the guilt appeal—and report the results of an experimental study. Our results suggest that credible guilt advertisements that are not overtly manipulative induce guilt feelings and positive attitudes. However, when consumers infer manipulative intent by the marketer, consumers do not feel guilty, but do have negative attitudes toward the sponsor of the advertisement and the advertisement. D 2003 Elsevier Inc. All rights reserved. Keywords: Advertising; Credibility; Manipulation; Guilt

1. Introduction Marketing communications specialists use a variety of appeals to accomplish their objectives. For example, informational appeals are often used to introduce a new product or to provide an update on brand enhancements, and emotional appeals are developed to make the viewer laugh or feel guilty. Sometimes advertisers are successful in achieving their intended objectives with a particular advertisement and sometimes they are not. Indeed, research has documented that there are no guarantees that the viewing audience actually feels the intended emotion associated with the appeal (Englis, 1990; Stout et al., 1990). For example, advertisers using a guilt appeal expect the audience to feel guilty and have some feeling of failing at their own ideals or ethical principles (Ruth and Faber, 1988; Wolman, 1973), but viewers do not always feel guilty (Coulter and Pinto, 1995). This article discusses two factors—consumers’ evaluations of the advertisement’s credibility and the advertiser’s

* Corresponding author. Ivey School of Business, University of Western Ontario, London, ON, Canada N6A 3K7. E-mail address: [email protected] (J. Cotte). 0148-2963/03/$ – see front matter D 2003 Elsevier Inc. All rights reserved. doi:10.1016/S0148-2963(03)00102-4

manipulative intent—that we believe can affect whether or not the advertiser accomplishes his or her objectives. We consider these two variables by examining the congruency between visual representation (the advertisement) and consumers’ responses (Scott, 1994) in the context of guilt appeals. We posit that one explanation for a lack of congruency between advertisers’ intentions and the consumers’ reactions is that consumers are active recipients of the advertising attempt. Specifically, consumers evaluate ad credibility and advertisers’ motivations. Further, we believe that when consumers perceive the advertiser as ill-intentioned, the intended emotion associated with the appeal, in our case guilt, may be attenuated such that the consumer does not feel guilty. In contrast, when an ad is perceived as credible and not manipulative, our expectation is that the consumers will experience the guilt intended by the advertiser. We begin by briefly discussing the use of guilt appeals in advertising. Then, we introduce two consumer evaluations— ad credibility and inferences of manipulative intent (IMI)— which we believe can enhance and interfere with marketers’ intentions, respectively. We then describe the experimental research designed to test our hypotheses and discuss our results. We conclude with a discussion of the theoretical and managerial implications of our investigation.

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2. Guilt advertising appeals Guilt appeals—appeals where an advertiser attempts to make consumers feel guilty to influence their behavior—are commonplace in advertising. In fact, the use of this type of appeal is growing (Huhmann and Brotherton, 1997; Samalin and Hogarty, 1994). The psychology literature describes several forms of guilt, including anticipatory, existential, and reactive guilt (Izard, 1977; Rawlings, 1970). Further, Huhmann and Brotherton (1997) have documented the types of advertisers that attempt to generate these forms of guilt. Below, we define each type of guilt and provide a fictitious ad scenario to demonstrate the use of each form of guilt appeal (all ad scenarios taken from Coulter et al., 1997). Guilt that results from an individual contemplating a potential violation of one’s own standards is referred to as anticipatory guilt (Rawlings, 1970). Huhmann and Brotherton (1997) document that companies that manufacture and promote consumer nondurable goods and health care products, health care services, and charities often use this type of guilt appeal. The ad scenario below describes an appeal that attempts to create anticipatory guilt; the ad offers consumers the ability to avoid disappointing their children by purchasing a cell phone. Ad Scenario 1: It’s Saturday morning. The long-awaited (and many times postponed) trip to the beach is finally here. You and the kids are excited about the day’s activities. Then the phone rings. . .It’s your boss. He wants you to contact a potential multimillion dollar client today. Your youngest daughter, mortified by what might be another ‘‘Well, we can go to the beach next week’’ bleats ‘‘Daddy, when can I become one of your clients?’’. . .If only you had a cellular phone. You could avoid disappointing your kids and talk to the potential client en route to the beach. The second type of guilt is reactive guilt, i.e., a guilt response to having violated one’s standards of acceptable behavior (Rawlings, 1970). Huhmann and Brotherton (1997) found that manufacturers and advertisers of consumer goods (both durable and nondurable) and health care products and services focus on reactive guilt. The second scenario illustrates an ad attempting to remind readers of their own past transgressions in an attempt to sell a phone reminder service. Ad Scenario 2: It is 6:00 p.m., and you’re swamped with work, but you promise your wife. . .‘‘I’ll be packing up soon. I just have to read one or two more reports.’’ Predictably, you become engulfed in your work and the next thing you know it’s 9:00 p.m.! Well, she’ll understand. . .As you walk through the dining room, you stumble upon what once was a magnificent dinner for two. But the food is cold and the candles have burned down. Staring you in the face is a card saying, ‘‘Happy Anniversary, Darling.’’ You can’t believe it. How could you let such an important date slip by? If only you had

signed up for that ‘‘Special Event’’ phone calling service that would have reminded you of important dates. Finally, existential guilt is experienced as a consequence of a discrepancy between one’s well-being and of others (Izard, 1977), and Huhmann and Brotherton (1997) find that charity ads very often use this type of appeal. The final ad scenario depicts an ad attempting to evoke existential guilt by contrasting the condition of a starving child with the (presumably healthier) condition of the ad’s reader to solicit charitable donations. Ad Scenario 3: An emaciated child is perched on a log in the barren waste of the desert. He can barely move, as he has no muscle, to support his frail body. His eyes tell a tale of a boy who, if only someone had helped to provide him nutrition, could have blossomed into a bright young man. In the background, a vulture looks on. With just a small contribution, you can help stop such famine and the tragedy faced by these innocent youths. You can make a lifesaving difference. Common to these three forms of guilt appeals is the expectation that seeing ads that employ these tactics will cause viewers to feel guilt and take some action (for example, become volunteers or purchase a product or service). 2.1. Cognitive evaluations of advertisements We argue that understanding more about the effects of ad credibility and perceptions of the advertiser’s motivations will help to explain why some guilt ads work, i.e., have the intended effect of making the viewer feel guilty, whereas other guilt ads do not work. In the advertising and consumer behavior literature, ad credibility has been defined as the ‘‘extent to which the consumer perceives claims made about the brand in the ad to be truthful and believable’’ (MacKenzie and Lutz, 1989, p. 51). Thus, ad credibility focuses on the advertisement and the consumer’s evaluation of the truth and believability of the content of the advertisement (i.e., the visual and verbal content in the ad). We believe readers will interpret the ad itself (rather than only the source) to determine if the claims it makes are true. For example, concerning the ad depicted in Ad Scenario 3, one reader may believe the claim, ‘‘with just a small contribution, you can help stop such famine,’’ whereas another reader may not believe the claim in the ad. IMI have been defined as ‘‘consumer inferences that the advertiser is attempting to persuade by inappropriate, unfair, or manipulative means’’ (Campbell, 1995, p. 228). Hence, consumers’ IMI concern their assessments of the advertiser’s motivations as well as the extent to which the ad is perceived as fair. Thus, the reader who believes the ad (it is credible) and the reader who does not believe the ad (it is not credible) may have an independent assessment of whether the ad is manipulative or not. For example, a reader considering the ad in Scenario 3 might find the ad credible,

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but feel the ad was manipulative because of its use of a very poignant picture, rather than simply words. To summarize, we believe that ad credibility and perceptions of manipulative intent (by the advertiser) are distinct constructs that will negatively covary. That is, we would expect that the greater the perceived credibility of the ad, the less likely the consumer would perceive the advertiser being ill intended. A consumer can read an ad and think that the claims in the ad are true and credible (for example, one may agree that many children around the world are starving), yet concurrently perceive the advertiser is attempting to manipulate them (i.e., they are trying to make me feel guilty so that I will donate to the charity). Hence, we hypothesize: H1: A negative relationship exists between perceived ad credibility and perceptions of manipulative intent. 2.2. The effects of ad credibility and perceived manipulative intent on feeling guilty Research on persuasive communications has indicated that consumers have a variety of emotional responses to advertisements (Englis, 1990; Stout et al., 1990), and that those responses are not always the intended responses. Research investigating emotional reactions elicited by the use of guilt appeals has identified the felt emotions of guilt, annoyance, and unhappiness as yielding the greatest impact on subsequent attitudes and purchase intention (Coulter and Pinto, 1995; Englis, 1990; Pinto and Priest, 1991). Positive emotions (e.g., feeling happy) yield a positive influence on attitudes toward the ad (Aad) (Holbrook and Batra, 1987). Alternatively, negative emotions (e.g., feeling annoyed) can result in a negative Aad (Burke and Edell, 1989; Edell and Burke, 1987), yet evoke a positive influence on behavior (Bagozzi and Moore, 1994; Ray and Wilkie, 1970; Sternthal and Craig, 1974). Other negative emotions, such as fear (Shelton and Rogers, 1981) and sadness (Cialdini and Kenrick, 1976), can also have a strong influence on creating a positive attitude toward helping. As we have noted previously, we believe that whether or not a guilt appeal will have its intended effect is, in part, dependent upon the viewers’ assessment of the advertiser’s motivations and ad credibility. We discuss each, in turn. 2.2.1. The effects of perceived manipulative intent Research by Eagly et al. (1978) and Wood and Eagly (1981) suggests that when a viewer perceives manipulative intent by the advertiser, they are likely to ‘‘resist’’ the message. We believe that this resistance has an impact on the viewers’ emotional responses (Batra and Ray, 1986). Research on guilt appeals provides some support for our contention (Coulter and Pinto, 1995). Specifically, Coulter and Pinto (1995) examined working mothers’ responses to low-, medium-, and high-intensity guilt ads and found that for high-intensity guilt appeals, the mothers did not feel guilty, but were rather angry. Englis (1990) also found high

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correlations between guilt appeals and the unintended emotions of anger, disdain, and disgust. We believe that this reaction is a function of the subjects evaluating the ad and perceiving it as inappropriate and unfair. Specifically, with regard to guilt appeals, we posit that: H2a: As consumers perceive more unfairness, inappropriateness, or manipulative intent, they are less likely to feel guilty. H2b: As consumers perceive more unfairness, inappropriateness, or manipulative intent, they are more likely to feel angry. 2.2.2. The effects of ad credibility Cognitive response theory and empirical research suggest that when persuasive communications are perceived as more credible or include strong arguments for the product or topic, the cognitive responses and Aad are more favorable (Petty and Cacioppo, 1986). We believe that ad credibility will also affect emotional responses. We suggest that if consumers believe an ad (find it credible) and perceive no manipulative intent, then consumers’ emotional responses will be more congruent with the intent of the advertiser. In our context, this means that the viewer seeing a credible guilt appeal will likely feel guilty. Thus, we posit that: H3: The greater the perceived ad credibility, the more likely the consumers feel guilty. 2.3. The effects of ad credibility and perceived manipulative intent on Aad Research has theorized about and empirically examined the effects of ad credibility and perceived manipulative intent on measures of ad effectiveness, including Aad. This research suggests that ad credibility is likely to have a positive effect on consumer reactions to the ad (Kavanoor et al., 1997; MacKenzie and Lutz, 1989) and overall ad effectiveness (Goldberg and Hartwick, 1990). Furthermore, IMI have a negative effect on attitude toward the ad (Campbell, 1995). We believe that actually feeling guilty may influence Aad positively or negatively, depending on perceived credibility and level of manipulation. Consistent with this perspective, we posit: H4: A positive relationship exists between perceived ad credibility and Aad. H5: A negative relationship exists between perceptions of manipulative intent and Aad. 2.4. The effects of ad credibility and perceived manipulative intent on the attitude toward the sponsor of the ad (Asponsor) Researchers have also theoretically and empirically examined the effects of ad credibility and perceived manipulative intent on Asponsor and attributions about the sponsor

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(Campbell, 1995; Friestad and Wright, 1994). In the extreme, perceptions of manipulative intent may create cognitions of mistrust of the company, which can lead to a consumer backlash against the advertiser (Basil et al., 1998; Osterhus, 1997). Thus, we expect: H6: A positive relationship exists between perceived ad credibility and corporate attributions and Asponsor. H7: A negative relationship exists between perceptions of manipulative intent and corporate attributions and Asponsor.

what they thought advertisers were attempting to accomplish with a series of ads and that each student would get one ad to assess. After examining the ad, students completed a short questionnaire. Embedded among other questions regarding intended emotions (e.g., make me happy, feel afraid) was a five-point Likert-type question, ‘‘[The sponsor] intended for me to feel guilty when viewing this advertisement’’ (1 = strongly disagree; 5 = strongly agree). The two ads did not differ significantly from one another in their perceived level of intended guilt [x¯EDF = 3.67, x¯STC = 4.00, t(35) = 0.85, P > .40].

2.5. Ad selection and pretesting Consistent with recent advertising research, we chose to use real ads in our study (see e.g., Kover, 1995). We made a concerted effort to identify ads for which our subject pool (undergraduate students) perceived that the advertiser’s intent was to create guilt in the audience. As a first step in identifying print advertisements to use in our study, we asked 80 undergraduate students to collect print ads for which they perceived that the advertiser’s intent was to instill guilt in them. From this collection, the authors identified four ads that appeared with the greatest frequency and then talked with the students to understand more about their reactions to the advertisements. The ads were for (1) MCI, (2) Environmental Defense Fund (EDF), (3) Save the Children (STC), and (4) Wrigley’s Gum (WG). Our next decision concerned which ads to use as stimuli. We wanted to examine only one type of guilt—so that our results would not be a function of type of guilt—and so the three authors individually evaluated the types of guilt evoked in the four ads. Social marketing causes often use guilt appeals, and the type of guilt appeal they most frequently use is existential guilt (Huhmann and Brotherton, 1997). We concurred that both the EDF and STC ads intended to evoke existential guilt, whereas the MCI ad intended to evoke anticipatory guilt and the WG ad intended to evoke reactive guilt. Thus, based on the debriefings and our assessments of the types of guilt intended in the ads, we selected the EDF and STC ads for our experiment. Due to the prevalence of existential appeals by charitable organizations, readers of these ads should be familiar with guilt appeals in social marketing ads. Although as we discuss below, prior familiarity with the specific ad shown did not affect our results. Past research has indicated that the intensity of the guilt appeal has an effect on emotional reactions and attitude to the ad, as well as behavior (Coulter and Pinto, 1995). To ensure that the EDF and STC ad had similar levels of perceived intended guilt, we conducted a pilot study with 37 undergraduate students (none of whom participated in the previous data collection). The EDF ad was originally in color, and research has shown that color gets more attention and creates longer viewing (e.g., Chute, 1980; Lamberski and Dwyer, 1981). We wanted to minimize this potential confound and so we used black and white versions of both ads. We told the students we were interested in understanding more about

3. Methodology Sixty-three undergraduate students, none of whom participated in our previous data collections, participated in our study. We randomly gave black and white copies of the EDF (n = 32) and STC ads (n = 31) to the students and instructed them that we were interested in their initial reactions to the ad. Having seen the ad, the students completed a questionnaire. The first question assessed subjects’ prior exposure to the ad. On the following pages, the subjects completed a questionnaire including 17 five-point Likert-scaled felt emotional responses to the ad (Edell and Burke, 1987; Izard, 1977; Plutchik, 1980). Several guilt items were embedded among many other emotion items to ensure that subjects did not focus on guilt. Additionally, the subjects completed five-point Likert ad evaluation items measuring Aad and the sponsor, or organization (Asponsor) in the ad (MacKenzie and Lutz, 1989). Next, the subjects indicated the level (on a five-point Likert scale) of five emotions (including guilt) they believed the advertiser was intending to create, as well as three items measuring attributions about the ad’s sponsor (Coulter and Pinto, 1995). Last, they evaluated the advertiser’s manipulative intentions (Campbell, 1995). All measures of felt emotions were taken before any items asking about inferences of advertisers’ intentions. 3.1. Measurement The five-point scale items used to measure each variable and the corresponding reliability coefficients are included in Table 1. The scales were either entirely or partially adopted from previous research. Specifically, the items measuring ad credibility are a combination of items used by Eaton (1988) and MacKenzie and Lutz (1989). The IMI scale is adopted from Campbell (1995). A factor analysis (including a scree plot) of the IMI indicates that the scale is unidimensional, with one factor accounting for 68% of the variance extracted (eigenvalue of 4.1), and other factors having eigenvalues of 0.5 or less. Feeling guilty is comprised of four items found in the research conducted by Bozinoff and Ghingold (1983) and Pinto and Priest (1991). The measures for attitude toward the ad (Aad) and sponsor (Asponsor) come from MacKenzie

J. Cotte et al. / Journal of Business Research 58 (2005) 361–368 Table 1 Scales and reliabilities Scale items Ad credibilitya Believable Truthful Realistic Inferences of manipulative intenta The way this ad tries to persuade people seems acceptable to me. The advertiser tried to manipulate the audience in ways I do not like. I was annoyed by this ad because the advertiser seemed to be trying to inappropriately manage or control the consumer audience. I didn’t mind this ad; the advertiser tried to be persuasive without being excessively manipulative. The ad was fair in what was said and shown. I think that this advertisement is unfair/fair. Feeling guiltya Guilty Irresponsible Accountable Ashamed Attitude towards the ad Good/Bad Favorable/Unfavorable Positive/Negative Attitude towards the sponsor Good/bad Favorable/unfavorable Positive/negative

Reliability measure (a) .87

.89

.80

.96

.97

a Items measuring this construct were on a five-point Likert scale, 1 being strongly disagree and 5 being strongly agree.

and Lutz (1989). Items used to assess corporate attributions were taken from Coulter and Pinto (1995) and appear in Table 2. 3.2. Manipulation check To determine whether subjects perceived the advertiser was intending to make them feel guilty, we embedded the same five-point Likert-type question, ‘‘[The company] intended for me to feel [emotion] when viewing this advertisement’’ (1 = strongly disagree; 5 = strongly agree), that was used in the pilot study. Subjects perceived no significant difference in level of intended guilt across the two ads [x¯EDF = 3.78, x¯STC = 4.13, t(61) = 1.28, P >.21]. 3.3. Results Our analyses indicate that all our hypothesized relationships were significant in the predicted direction. Across the two ads, we found that ad credibility and IMI are negatively correlated (r = .51, P < .001, supporting H1). Additionally,

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there is a significant negative correlation between IMI and feeling guilty (r = .42, P < .01). This finding supports H2a; as readers infer more of a manipulative intent on the part of the marketer, they are less likely to feel guilty. In addition, as readers perceive more manipulation, they are more likely to become angry (r =.34, P < .01), supporting H2b. Furthermore, ad credibility is positively related to feeling guilty (r =.48, P < .001, supporting H3). Thus, if readers view an ad as credible, they are more likely to feel guilty. As expected, ad credibility is positively related to Aad (r =.52, P < .001, supporting H4), whereas perceived manipulative intent is negatively related to Aad (r = .62, P < .001, supporting H5). Supporting H6, ad credibility is positively related to corporate attributions and attitude toward the sponsor (see Table 2). Additionally, we found that the greater the perceived manipulative intent, the more negative the attributions made about the sponsor of the ad, and the more negative the overall attitude to the Asponsor (supporting H7, see Table 2). The two ads were perceived by readers as equally credible [x¯EDF = 4.14, x¯STC = 4.06, t(61) = 0.30, P >.76]. However, the ads did differ on perceived manipulative intent, with readers perceiving significantly higher IMI in the children’s relief charity ad [x¯EDF = 1.78, x¯STC = 2.72, t(61) = 3.45, P < .001]. Therefore, we also analyzed each ad individually. Reactions to the same ad varied across subjects, although the variation was not very large. Because these variances are not large, using correlations to explain the variance accounted for in our tests is relatively conservative; a significant correlation depends in part in how much variance there is to explain in the variable. Our analyses of the individual ads again illustrate the significant negative relationship between ad credibility and IMI ( .62 for the EDF ad and .48 for the STC ad; see Table 3). Analyses of ad credibility, IMI, and feeling guilty demonstrate that when the ad is not perceived as manipulative (the EDF ad), ad credibility is positively and significantly related to feeling guilty, A ad , and corporate attributions. In addition, the relationship between IMI and the other variables is nonsignificant (see Table 3). However, when the advertiser is perceived as manipulative (the STC ad), credibility is not significantly related to feeling guilty.

Table 2 Credibility, inferences of manipulative intent, and corporate attributions Ad credibility Asponsor Corporate attributions [The sponsor] is primarily concerned with making money. I have a good feeling about [the sponsor]. [The sponsor] has consumers’ best interests at heart. n = 63. * P < .01. *** P < .001.

IMI

.45***

.49***

.41 *

.55***

.39 * .49***

.56*** .38 *

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Table 3 Credibility, inferences of manipulative intent, feeling guilty

IMI Feeling guilty Aad Asponsor Corporate attributions [The sponsor] is primarily concerned with making money. I have a good feeling about [the sponsor]. [The sponsor] has consumers’ best interests at heart.

EDF ad

STC ad

Ad IMI credibility

Ad IMI credibility

.62*** .64*** .67*** .34

.30 .31 .21

.48*** .29 .44** .60***

.44** .72*** .66***

.47*

.29

.49*

.52*

.52*

.27

.47*

.41**

.43**

.22

.39**

.71***

EDF, n = 32; STC, n = 31. * P < .01. ** P < .05. *** P < .001.

Thus, if consumers believe that an ad is credible, yet manipulative, they are less likely to react as the advertiser intended, i.e., feel guilty. Moreover, consumers will have negative ad and sponsor evaluations, and make negative attributions about the corporation. At the same time, credibility remains positively and significantly related to Aad, Asponsor, and corporate attributions. Feeling guilty is positively related to Aad for both ads (EDF: r =.46, P < .001; STC: r =.54, P < .01). Since a potential confound might have been prior familiarity with the ad used in the study, it is important to point out that there was no difference in familiarity (reported number of times the ad was seen) between the two ads used and familiarity with the ad was not significantly related to either feeling guilty or IMI for either ad.

4. Discussion This article discusses two factors—consumers’ evaluations of the advertisement’s credibility and consumers’ perceptions of the advertiser’s manipulative intent—that can, respectively, enhance or disrupt the advertiser’s intended objectives. Because consumers are active readers of advertising, they may or may not respond as the advertiser expected, that is, they may or may not feel guilty as a consequence of seeing a guilt appeal. Specifically, when consumers perceive that a guilt appeal ad is credible, they are more likely to feel guilty. However, this is only the case when consumers infer the advertiser’s intent is not manipulative. If the consumer does perceive manipulative intent, he or she is less likely to feel guilty. Thus, a consumer’s evaluation of an ad’s credibility and the advertisers’ motivations can either enhance or disrupt message response. Our findings also suggest that consumers’ evaluations of ad credibility and advertiser motivations extend beyond

message response and impact subsequent attitudes toward the ad, attitudes toward the sponsor, and corporate attributions. Specifically, if consumers perceive an ad as credible, they are more likely to hold a positive attitude toward the advertisement and sponsor. Conversely, if consumers perceive manipulative intent on the part of the marketer, they are more likely to hold a negative attitude toward the advertisement and sponsor as well as negative corporate attributions. As such, advertisers need to walk a fine line between getting a message across and being perceived as overtly manipulative. Advertisers need to use caution when selecting guilt-inducing tactics due to the negative effects of perceived manipulation and unfairness on attitudes towards the company. Our research sheds some explanatory light on a controversy in the research dealing with negative emotional appeals (like fear or guilt). In their recent meta-analysis, Brown et al. (1998) point out that there are ‘‘strong and robust’’ results stating that negative appeals lead to negative ad, brand, and sponsor attitudes. However, they point out conflicting research that demonstrates positive effects of negative appeals. The present research demonstrates that if a negative appeal ad (in our case guilt) is credible and is not perceived as manipulative, the ad will lead to positive corporate attributions and attitudes. However, if the ad is seen as manipulative, despite the fact that it may be credible, then negative appeals can lead to negative corporate attributions and attitudes. One possible explanation for why one ad may be seen as manipulative and one may not (given equal credibility and levels of intended guilt) may be the type of guilt intended. As we reviewed earlier, there are three main types of guilt: reactive, anticipatory, and existential (Huhmann and Brotherton, 1997). Our study focused exclusively on two ads intended to elicit existential guilt. Future research might examine whether there is a link between the type of guilt intended and IMI: If there is indeed a link, advertisers would have some guidance on how to avoid these types of inferences by portraying different types of guilt in their ads. Although we did not assess individual differences in this research, it is possible that some people are more prone to feeling guilty, or feeling emotions in general (Basil et al., 1998; Moore and Harris, 1996). Future research should examine the role dispositional (trait) guilt plays in evaluating the advertiser’s intentions, and the ad itself (see, for example, Basil et al., 1998). Finally, although we did assess levels of prior familiarity with the ad (and found no difference), the persuasion knowledge literature suggests that consumers do not necessarily need to be familiar with the ad itself, but can call on their prior knowledge (Friestad and Wright, 1994) to make their evaluations. This knowledge may be of the tactics of this particular marketer in previous ads (for example, that STC ‘‘always’’ includes pictures of starving children) or knowledge of the typical marketing tactics in a product category (for example, charities ‘‘always’’ try to make you

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feel guilty in their ads). Future research could determine how this type of agent and topic knowledge might interact with ad credibility and IMI (see Coulter et al., 1999). Some product categories (like social marketing campaigns) have used guilt appeals for decades. Persuasion knowledge of these guilt tactics in these categories may be higher than in some other areas, like nondurable consumer products. If the use of a guilt appeal is novel for a product category, then perhaps a lack of persuasion knowledge might lead to less perceptions of marketer manipulation. 4.1. Implications for marketers Looking across our results, we suggest that the advertiser striving for an effective use of a guilt appeal should focus on presenting viewers with messages that resonate with consumers’ experiences. More speculatively, marketers may also want to consider offering strategies for reducing guilt, such that consumers believe the claims, feel guilty, and act (by purchasing or following through with some other behavior) to alleviate the guilt, all without feeling overtly manipulated. However, an important caveat is that the more guilt tactics have been used in an industry, the higher will be the persuasion knowledge of most readers of the ad and the less likely it is that the tactic will go unrecognized. This research offers some empirical insights on guilt appeals, a growing strategic choice of advertisers (Murphy, 1994; Samalin and Hogarty, 1994). Guilt appeals that are perceived as containing well known manipulative tactics do not ‘‘work’’; there will not be a congruency between the representation in the ad and the consumer’s response (Scott, 1994). In this era of increasingly market-savvy consumers, advertisers need to avoid well-known guilt ‘‘tricks’’ and rather develop appeals that provide credible information in a nonmanipulative way.

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Purchase occasion influence on the role of music in advertising Mark I. Alperta,*, Judy I. Alpertb, Elliot N. Maltzc a

Department of Marketing, The University of Texas at Austin, Austin, TX 78712, USA b Moonglow Jazz Group, USA c Willamette University, Salem, OR, USA

Abstract The role of background music in audience responses to commercials (and other marketing elements) has received increasing attention in recent years. This article extends the discussion of music’s influence in two ways: (1) by using music theory to analyze and investigate the effects of music’s structural profiles on consumers’ moods and emotions and (2) by examining the relationship between music’s evoked moods that are congruent versus incongruent with the purchase occasion and the resulting effect on purchase intentions. The study reported provides empirical support for the notion that when music is used to evoke emotions congruent with the symbolic meaning of product purchase, the likelihood of purchasing is enhanced. D 2003 Elsevier Inc. All rights reserved. Keywords: Music; Mood; Emotions; Situational influence; Advertising; Consumer behavior

1. Introduction How does the perceived purchase situation affect the impact of music in advertising on consumers’ moods, attitudes, and behaviors? This issue is motivated by the increased interest in emotional advertising and the complex roles that music assumes within it. For many marketing communication settings, the amount of objective information-processing activity is minimal, and there is substantial evidence that affective information processing may be instrumental in forming (or reinforcing) preferences and choices. Music has been used in stores, offices, and as a background in advertisements and has been reported to influence listeners’ emotions and behaviors. Music is a very useful tool for persuasion and exploring just how and why this is so is an important area for research. This article discusses, integrates, and builds upon the work of Gorn (1982) and others (e.g., Bruner, 1990) who provide theoretical and empirical insight into the ways in which music may influence consumer responses. To that end, we present an investigation into the effect of congruity and incongruity between affect or ‘‘mood’’ evoked by music imbedded in an advertisement and affect consistent with the

* Corresponding author. E-mail address: [email protected] (M.I. Alpert). 0148-2963/03/$ – see front matter D 2003 Elsevier Inc. All rights reserved. doi:10.1016/S0148-2963(03)00101-2

symbolic meaning of the purchase itself. Implications for marketing theory and strategy will be discussed. 1.1. Theoretical base and literature review The role of music in marketing and consumer behavior research has been addressed in education, psychology, communication, and other fields to determine its effects on behavior, mood, and preferences. As a result of this body of work, we know that in some instances, music appears to increase communication effectiveness in the context of advertisements. In other circumstances, music may decrease effectiveness for reasons that are not selfevident (e.g., ‘‘When is ‘popular’ music an inappropriate background?’’) Discussing how, when, and why music works seems to be appropriate to understanding the role of music in communications. In an effort to provide possible explanations, this article discusses the structural elements of music in the surrounding context of an advertisement and its interaction with the consumer. Although knowledge of formal musical analysis can assist in drawing inferences regarding how listeners may be affected by particular musical passages, it is also necessary to consider the context in which the musical and advertising ‘‘communication’’ takes place. Accordingly, we shall focus on musical structure and its interactions with important moderators such as ‘‘fit’’ between musical and

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nonmusical meanings in the advertisement and purchase situation. Musical structure consists of elements such as sound, harmony, melody, and rhythm. Key factors in how these musical elements impact on the ad and the product are (1) the consumer, through different levels of involvement and cognitive or affective processing, (2) the consumer’s subjective perception of the appropriateness of the music as it relates to the central idea of the ad (‘‘fit’’ as defined by MacInnis and Park, 1991), and (3) the organization of musical elements. There has been interest in examining how musical elements influence affect and processing (Alpert and Alpert, 1990; Bruner, 1990). In addition, knowledge of cultural and social conditioning in forming musical taste as well as products can help in this prediction (Farnsworth, 1969; Holbrook and Schindler, 1989). Given a target market’s demographics, we can predict, with some accuracy, its musical and product preferences and tastes. Thus, we may know with some degree of certainty how they might perceive the appropriateness of certain musical selections with the overall message of an ad, although level of involvement and processing may vary across individuals and situations (Petty et al., 1983). Here, we investigate two key factors: music’s role in determining the emotional message of an advertisement and the impact of congruence between this message and the intended emotional meaning that may be conveyed through the purchase of the advertised product.

salient cues are processed to yield attitudes in a manner affected by mood. The likelihood that a host of behaviors may be performed appears to be enhanced by positive moods (Gardner, 1985). For negative moods, there have been mixed results, and several studies have shown that negative affect serves as a motivator to mood improvement through the performance of positive, prosaic acts. This finding agrees with the notion that where possible, people feeling badly will try to feel better. Negative moods’ effects on behavior may be more complex than the effects of positive moods (Cialdini and Kenrick, 1976). For example, helping may be enhanced by some negative mood states such as sadness (Baumann et al., 1981) and not by others such as frustration. This may be due to some evidence that negative mood states are not as homogeneous as positive ones (Isen, 1984) and that behaviors seen to reverse unpleasant mood states (e.g., helping) may overcome tendencies to enact mood-congruent behavior (e.g., withdrawal). In view of the fact that music is a common element in commercials and one that has a long history of mood inducement in a variety of contexts, the next section will focus on how music has been used as an independent variable to affect moods, as well as other dependent variables of interest to marketers. For brevity, this section will highlight key studies. Details on these and other studies are in Alpert and Alpert (1990), Bruner (1990), and Kellaris and Cox (1993).

1.2. Music also affects important mood states

1.3. Music effects

Music not only enhances recall for a product or an ad through an evoked image, but it may evoke moods, feelings, emotions, and behaviors. Consumer behavior theorists have conceptualized how consumers’ attitudes, affective states, and behaviors have been impacted by moods under central and peripheral processing, as well as affect and behavior conditioning. The association between mood states and affective responses, judgments, and behavior can be seen as both direct and indirect. A direct affective reaction may be viewed as a conditioned response when there are direct linkages in associations in memory between mood states and affective reactions (Griffitt and Guay, 1969) and between mood states and behavior (see Gardner, 1985, for additional references). Indirect associations between feeling states and affective responses and/or behavior include the influence of information processing or cognitive activity. Mood may affect evaluations by evoking moodcongruent thoughts and affect the performance of the behavior by increasing the accessibility of positive associations to the behavior (Clark and Isen, 1982; Goldberg and Gorn, 1987). To the extent that associations are direct and involve little conscious information processing, mood’s effects may be seen as via the peripheral route. Indirect associations may operate via the central route when other

Gorn (1982) suggested that peripheral influences such as background music used in commercials may become associated with the advertised product (in memory, even if not consciously) and influence product choice through classical conditioning. Mere exposure did not lead to liking, which apparently depended on whether the target product, a pen, was presented with liked versus disliked music. The second experiment by Gorn (1982) provided support for his hypothesis that when subjects were not in a decision-making mode, the commercial’s impact appeared to be more influential in its appeal when presented with musical background as opposed to product information. He concluded that through classical conditioning, the product becomes associated with the positive feelings of liked music. A replication of the Gorn study (1982) by Kellaris and Cox (1989) failed to reproduce the positive effect of liked versus disliked music after controlling for musical structural elements and possible demand effects. Their results question the effect of single exposures that merely vary background music’s appeal. They called for research on the influence of music’s structural elements on cognitive and affective responses (such as mood) toward the ad and the product. The key basic research relating musical elements to emotional responses was reported by Hevner (1935), who presented subjects with identical pieces, controlling for all

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elements but major and minor modes. She concluded that all of the historically affirmed characteristics of the two modes, perceived as happy and sad, respectively, were confirmed in her study. In later research, she also reported associations between musical elements, such as fast tempo, loud dynamics, lively and varied rhythm, and high register with perceptions of the music as happy, merry, graceful, and playful. Musical elements such as slower tempo, quiet dynamics, unvaried rhythm, and low register were reported to be sad, dreamy, and sentimental (Hevner, 1935, 1936). She noted that although mode is never the sole factor that determines the way music is perceived, it is the most stable, generally understood, and influential of any of the elements in expressing the affective mood of music. Additional studies of musical structural elements’ effects on emotional responses are summarized in Bruner (1990) and North et al. (1999). Additional musical effects on mood and consumer behavior are found in studies such as Dube et al. (1995), who varied the musical background of a videosimulated bank and produced effects on pleasure and arousal and corresponding effects on desires to affiliate with bank employees. Higher affiliation was associated with musically induced pleasure and arousal. Alpert and Alpert (1990) replicated and extended Hevner’s findings, concluding that equally liked but unfamiliar music produced emotional responses predictable from analysis of its structural profile of musical elements. These mood states were associated with influence on purchase intention towards greeting cards viewed with the varying background music. Rather than generalize main effects from their study (sad music was ‘‘better’’), they suggested that future research may be productively directed at the interactions among music type, card type, and situation. They speculated that happy music may ‘‘help’’ happy cards when purchased for joyous occasions; sad music may help sad cards more than happy ones for sad situations such as funerals. The present study replicates and extends this work and tests their hypotheses about the role of musical structure on moods and consumer behavior under situational variation. For comparison, we also use unfamiliar music and simulated greeting card advertisements, but we vary the purpose of the greeting card by varying the occasion for which it is to be bought.

or purchase behavior of products presented along with the music.

2. Hypotheses

H2: When evoked mood is congruent with the mood of the purchase occasion, buying intention is higher than when the buyer and occasion moods are inconsistent.

It appears from the music literature that major and minor modes are important influences on listeners’ feelings and moods, and along with other musical elements, create a gestalt for happy and sad as perceived by listeners. Moreover, equally well-liked but unfamiliar music (to remove some effects specific to remembered music) with different musical structures may induce different moods. These in turn may predispose listeners toward different attitudes and/

H1: All else equal, music whose structural profile is ‘‘happy’’ influences listener moods to become more positive than music analyzed a priori as ‘‘sad.’’ From the extensive literature on the effects of mood states on information processing and interpersonal activities, a number of related inferences may also be derived. Most relevant for this particular study are those that pertain to the congruity between mood and thoughts and actions that may be affected by mood. As noted in a review by Bower (1991), ‘‘people who are temporarily (or characteristically) happy or unhappy tend to select interpersonal activities as well as social situations which will maintain their mood’’ (p. 31). He also noted that moods influence the processing of affectively congruent information as well impact-biased recall. In the context of the present study, this implies that persons feeling good (bad) will prefer choosing a greeting card for a happy (sad) occasion. This behavior would also be consistent with findings reported by Park and Young (1986) regarding the need for consistency between an advertisement’s musical ‘‘meaning’’ and the intended advertising message. Later work by MacInnis and Park (1991) provided additional support for the positive effect of musical and nonmusical consistency of message and resulting impact on advertising effectiveness. In the present study, the consistency would be reinforced through purchasing a greeting card one believes to represent feelings the sender wishes to convey to the card’s recipient. To the extent that a card is sent to symbolize a happy or sad occasion and one’s (music-induced) mood while viewing the card may be affectively conditioned and associated with the advertised product, purchase probability may be enhanced by congruity between communication effects and consumers’ feelings about greeting card ‘‘messages.’’ A number of studies have defined congruency in differing ways. Their findings are mixed and show congruency effects may be moderated by a number of factors. However, when congruent or moderately congruent information is presented in an ad, information processing generally is enhanced. Taken together, these studies suggest that:

3. Methodology The experimental subjects were 75 student volunteers from principles of marketing and promotional policies classes in a major southwestern university. Although the

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test products were ones purchased by students, use of convenience samples of students limits the ability to generalize to some extent. Their use in this study was deemed appropriate for theory application and testing to investigate the basic process of musical and purchase occasion influence on emotions, attitudes, and purchase intentions (Calder et al., 1981). Extensions using other samples would be justified if initial results were promising. Volunteers received credit toward their course grade and were randomly assigned to treatment groups and times. The design was a 2 (music) by 2 (occasion) between-subjects factorial contained within a parallel study of source credibility and expertise effects. Subjects were told that the study concerned consumer responses to advertisements, and that they would be exposed to a series of slides depicting partial advertisement materials to be tested for possible inclusion in finished advertisements. Some would contain music and others would not. Because of time constraints, they would be asked questions about their responses to only a few of the ads. Confidentiality was assured. Attention was directed to the booklets on the tables in front of them, and they were told to complete the first page: names and classes (for credit) and wait for instructions. Then they were exposed to a series of 10 black-and-white slides, each of which was viewed for 45 seconds and preceded by an identifying announcement (e.g., ‘‘This is an ad for a financial institution, . . . greeting card . . . etc.’’). Black and white was used to avoid extraneous color effects on moods (and other responses) that might confound the measurements (Bellizzi et al., 1983). 3.1. Musical influence manipulation This treatment involved varying the background music for the target ad, 30-second excerpts from Bach preludes in Volume I of the Well-Tempered Clavier. All groups heard the same (pretested as) neutral music with the first simulated greeting card ad. Two of the four groups heard sad music with the second simulated card (the target ad) and the other two heard happy music. The sad music was from a prelude (XXII in B-flat minor) whose musical elements had been structurally analyzed as likely to produce feelings of sadness. The happy music was from a prelude (III in C#-major) that had a contrasting structure believed to produce feelings of happiness. Pretests had indicated the pieces were perceived as unfamiliar, equally liked but happy and sad, respectively. These excerpts were used as background music to the same, (pretested as) neutral slide of a mountain range and verbal message, ‘‘Friendship is a gift,’’ operationalizing the background music construct. 3.2. Occasion manipulation Also randomized within groups, half of those hearing happy or sad music with the second card were asked about their purchase likelihoods for happy occasions (‘‘for a friend

who was having a birthday’’) and half for sad occasions (‘‘for a friend who was sick in the hospital’’). Pretests had shown these scenarios evoked different perceptions of happiness/mood. 3.3. Measures Immediately after exposure to the fourth and sixth ads, subjects were asked to complete measures of feelings and then thoughts evoked by the ads, including their likelihood of purchasing the product in the ad. After the seventh and tenth ads, which simulated pictures for greeting cards, matched with the neutral and happy (or sad) musical excerpts, respectively, they were asked to provide the same measures. Hence, evoked feelings and attitudes were asked about ads with celebrities, experts, music, and no music. Using similar measures after ads with and without music was intended to minimize demand effects (and apparently did so, as indicated below). All measures were obtained using seven-point bipolar scales such as good/bad, happy/sad, excited/calm, and the like. Subjects were first asked to circle the number between the pair of words to indicate the feelings and emotions they had while viewing the advertisement. Next, they were asked to indicate their thoughts and opinions about the advertisements using similar (but randomly ordered) bipolar scales. Then they were asked to indicate their opinions of the product itself using three scales (good/bad, like/dislike, favorable/unfavorable). These were averaged to produce an index (a=.97) of attitude toward the product (Ao). Next, they were asked how likely they would be to choose the product that was advertised (very unlikely/very likely) that became the measure of purchase intentions. As noted in the occasion manipulation description, this question regarding the greeting card target ad was modified by the occasion for which the card was to be purchased (birthday versus hospital). Finally, the last four questions for the target ad asked how the respondent would characterize the occasion for which the greeting was to be sent (pleasant/ unpleasant, likable/unlikable, sad/happy, miserable/glad). Responses to these four scales were averaged to produce an index of the strength of the occasion manipulation (a=.90).

4. Results Although the subjects were predominantly U.S. citizens, it was possible that the three foreign students might respond differently to the advertisements; hence, they were eliminated. Subjects had been asked to write down what they believed to be the purpose(s) of the study. Answers generally described the purpose as ‘‘studying what ads people like and dislike.’’ One respondent who thought that the study had something to do with how music affects emotion was eliminated, leaving 71 usable responses.

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4.1. Occasion manipulation

Table 2 Means by treatment condition

Tables 1 and 2 summarize major results for the manipulation check and dependent variables. Subjects told to consider purchasing the greeting card for a friend’s birthday scored lower on the (negative) occasion index (X¯ = 3.55) than did those rating the purchase situation of ‘‘for a friend in the hospital’’ (X¯ = 3.97, F = 3.38, P < .05, one-tail). The scaling of the four items in the occasion index indicates that the lower the score, the more the occasion was seen as pleasant/likable/happy/glad. Hence, the occasion manipulation produced adequate results. Given the modest difference between means and the fact that the birthday occasion was seen as near the midpoint of the situation index, this condition may be appropriately viewed as ranging from a fairly sad occasion to a neutral one.

Measure

‘‘Happy music’’

Happy – sad mood

Pleasant – unpleasant situation perceptions Favorable – unfavorable card attitude Purchase intention

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‘‘Sad music’’

3.38

4.16

Happy occasion (n = 22)

Sad occasion (n = 18)

Happy occasion (n = 14)

Sad occasion (n = 17)

3.31

3.49

3.81

4.73

3.41 2.65

4.23 3.54

3.26

3.50

2.24

3.05 3.17

3.98 3.66

3.35

4.93 3.45

4.2. Impact on mood, attitudes, and intentions A mood index was formed by averaging the seven feelings scales that were highly intercorrelated. This produced an index (a=.92) that may be termed negative mood, as a high score is associated with feeling unpleasant, miserable, bad, gloomy, sad, boring, and weak. A low score is the opposite pattern, with a positive mood. Subjects exposed to the target card ad with a background of the ‘‘happy’’ music scored significantly lower on the (negative) mood index (X¯ = 3.38) than did those (X¯ = 4.16) exposed while listening to the ‘‘sad’’ music ( F = 8.52, P=.003, one-tail, eta2=.11). The lower mean (e.g., ‘‘more positive mood’’) for those exposed to ‘‘happy’’ music is consistent with H1 about the effect of advertising background music on receiver’s mood. Music/mood did not have a main effect on purchase intention ( F=.23, P>.10). It is possible that these effects may be moderated by factors (other than those stressed in the present study) such as degree of central versus peripheral processing and individual variations in need for cognition (Batra and Stayman, 1990). However, purchase occasion’s manipulation did affect purchase intention ( F = 7.72, P < .01, V2=.24), with the greeting card more likely to be purchased for a friend who was sick in the hospital (X¯ = 4.06) than one having a birthday (X¯ = 2.71). Since this

effect occurred when music was ‘‘held constant,’’ this result suggests that the picture and statement may have been viewed as more appealing for the former situation than the latter or that students felt it more important to send cards to ill friends than those with birthdays. Regardless of the relative acceptability of the greeting card for a given situation, the major interest here is on the extent to which music’s emotional meaning and influence on audience mood enhances or inhibits the purchase intentions under situations with varying perceived mood. In fact, there was a significant interaction effect of Music  Occasion ( F = 5.68, P=.02, V2=.17). As shown in Fig. 1, in the (happier) birthday situation, subjects who had viewed the card with the happy background music, who had happier evoked moods, were more likely to choose it (X¯ = 3.17) than those who viewed it with sad musical background, whose evoked moods were sadder (X¯ = 2.24). On the other hand, when choosing a card for a friend who was sick in the hospital, a sadder situation, those who viewed the card ad with a background of sad music had a purchase intention that was substantially higher (X¯ = 4.93) than those exposed to the same ad with happy music (X¯ = 3.50).

Table 1 ANOVA results for treatments Dependent variable

Variation source

F value

Significance of F

V2

Occasion ‘‘mood’’

Music Occasion Music  Occasion Music Occasion Music  Occasion Music Occasion Music  Occasion

9.801 3.379 1.776 1.844 4.473 0.046 0.227 7.717 5.682

.003 .070 .187 .179 .038 .830 .635 .007 .020

.29 .08 .03 .04 .16 .00 .00 .24 .17

Card attitude

Purchase intention

Fig. 1. Purchase intention interaction.

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5. Discussion The results of this study support the hypothesis that variations in the formal music structure of background music in commercials may have significant influence over the emotional responses of an audience. Prior research in consumer behavior had shown that varying specific background music selections along dimensions of familiarity and liking could affect responses to ‘‘advertised’’ products. The present article extends the discussion concerning the effect of musical content that may lead to emotional and affective responses among consumers. It does so by determining whether congruity between musical advertisement ‘‘messages’’ and nonmusical variables that are part of the communications context but outside the advertisement itself (e.g., occasion) increases or blocks affect and behavior. Different profiles of musical structural elements of modality, tempo, dynamics, and rhythm may, all things being equal, lead to a perception of happy or sad musical content. In this study, equally liked musical backgrounds that differed in their profile of these structural elements were shown to affect audience moods in directions predictable from analysis of the musical structure, confirming earlier research by Hevner (1935) and Alpert and Alpert (1990). This finding has direct relevance to those interested in the impact on mood from factors such as the structural elements in background music. It was noted earlier that simultaneous variation of the entire profile of elements (major/minor, tempo, rhythm, and volume) precludes inferences from this study regarding their relative influence on moods and other dependent variables of interest. Other research suggests the dominance of major versus minor melodies (influencing moods to be happy versus sad), all else equal. To test the possibility that other factors might confound the study (Kellaris and Kent, 1993), a second factor of affective responses corresponding to ‘‘arousal’’ was extracted and found to vary in a manner consistent with the fast/slow tempi of the musical excerpts in the treatments. However, individual-level regression analyses showed that the feelings dimension ‘‘happy/sad’’ was correlated with buying intentions while feelings of arousal/nonarousal were not. More important, having found that musical structure does make a difference to moods and behavioral intentions towards products ‘‘shaded’’ with music, it may be appropriate to extend the present work with carefully controlled manipulations of specific structural elements of music. To this end, the methodologies employed by Holbrook and Huber (1979) and Kellaris and Kent (1993) may be productively used. Some advocates of classical conditioning might criticize the use of a single exposure to the messages and lack of reinforcement. However, evidence of mood-induced conditioning is demonstrated by the effect on purchase intent in ‘‘appropriate’’ situations. Perhaps, ‘‘affective transfer’’ (of music to mood to purchase occasion ‘‘fit’’) is an alternative explanation to ‘‘learning.’’ Earlier research has shown that

single exposures to background music-induced moods may affect buying intentions in the absence of significant intervening effects on the perceived sadness and even stated liking for a card and may be supportive of peripheral path processing in this setting (Alpert and Alpert, 1990). Given that the advertisements presented no verbal claims and that subjects were not told they would have to make an actual purchase choice (Petty et al., 1983), motivation to process information via the central route may have been diminished. The presence of music that evokes emotions and other ‘‘noninformational’’ aspects of the ad may also stimulate peripheral processing, and there were no central-route arguments involving objective claims presented in these target ads. Embedding the target ads in a series of control and distracter ads may also lower cognitive ad involvement to levels similar to typical ad viewing behavior. Research on the relevance of ‘‘fit’’ between message elements (Kellaris and Cox, 1993; MacInnis and Park, 1991) would suggest that evaluations might be influenced by congruence between key communication elements. We have manipulated these ‘‘outside the ad’’ by framing the purpose of the greeting card choice in terms of what was interpreted as a happy versus sad occasion. The musicevoked moods congruent with the feelings appropriate in such situations were associated with increases in purchase intentions. This interaction between music-induced mood and the purchase situation is itself an important finding. We have not directly investigated the manner by which this congruity/incongruity is perceived and processed by consumers. Future research may be productively employed to probe the extent to which consumers actively process the extent to which the message elements, thoughts, and/or feelings invoked by an informational versus emotional message (verbal or nonverbal) in a specific communication may lead to subsequent attitudes and behaviors. In this study, sad music-induced negative moods were associated with higher likelihood of sending a greeting card to a hospital than for a birthday. This may have come about because selecting a card that ‘‘made one feel sad’’ is inconsistent (or ‘‘jarring’’) with birthday thoughts. Similarly, subjects whose moods were induced to be happy (by ‘‘happy music’’) were more likely to maintain their moods by sending the card for a birthday than for a friend sick in the hospital. The main purpose of the present study has been to extend the utility of music’s structural analysis to the relationships between hypothetical influences on audience mood and the resulting congruency/incongruity with the purchase purpose or situation. In addition, it is hoped that as more is understood about how consumers process congruent and incongruent musical (or other nonverbal) and verbal information, the more it will be possible for creative efforts to be optimized. Having shown potential application of the concepts expressed, it would be useful to extend this work by testing music’s effects on moods and intentions for products for which decisions might be made in the presence of music.

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Situations similar to the present study’s context are found in television presentations of products to be ordered by phone, or on the Internet, with background music varied to be appropriate to the product or purchase occasion. Here, the influences on mood and intentions might be sufficient to produce buying. In other contexts, repetition of similar advertisements might produce purchase intentions of longer duration, if not toward a specific card (or product), perhaps towards a brand such as Hallmark. Seeing the advertised products in a store could evoke the mood originally stimulated by music in the advertising situation. Although such an outcome is plausible and is supported by the literature (Lutz and Lutz, 1978), further research is needed to test the efficacy of this linking of feelings. As noted earlier, research cited by Gardner (1985) has generally found positive correlations among mood inducers, moods, and a number of dependent variables such as evaluations. However, studies such as Cialdini and Kenrick (1976) found that older children were more generous when self-generated thought made them sad. In a negative emotional ad, there may be more of a payoff. In this case, a sick friend is in the hospital (negative emotion), followed by a resolution (a positive emotion), in the form of a card. The point is made that in a negative emotional ad there is a higher level of activity involvement than with positive ads, where people are in a good mood, have positive thoughts, and want to stay that way with minimum elaboration. It may be likely that both the sad purchase situation and sad music manipulation resulted in more moderate levels of elaboration, leading to higher scores in purchase intentions. In addition, this particular example of a negative emotion and its resolution has high social approval and would increase motivation to purchase a card. As Gardner (1985), Park and Young (1986), and Kellaris and Cox (1993) have stated, a key factor is the congruence between associated feelings and behaviors consistent with that advocated in a message. In this situation, college students may have responded more positively to sad emotional evocations (induced by music) in the context of sending greeting cards to sick friends (with messages like ‘‘friendship is a gift’’). It makes sense intuitively to say that in this study, when happy music was paired with a sad purchase occasion, this was an incongruent situation where unexpected, irrelevant, inappropriate, or perhaps no information was conveyed and where purchase intent was low. The same was true with the other incongruent situations. In the happy music with happy occasion, and sad music with sad occasion, congruency was achieved through both expected and relevant information. The result of increased purchase intent, when there was congruity between happy music/ mood and happy purchase occasion, as well as sad music/ mood and sad purchase occasion is supported by Bower (1981), who points out that people who are happy or unhappy tend to select interpersonal activities as well as social situations that will maintain their mood. Certainly, Hallmark positions (verbally and nonverbally) many of

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their greeting cards to appeal to these market situations. So did AT&T with their memorable ads supported by the song, ‘‘Feelings’’ (a sad song, in minor mode, that helped people resolve distance by phoning). On the other hand, visits to an amusement park may be more effectively advertised with happy music than with sad. In addition, happy and sad may well be multidimensional constructs. Different gradations within these emotions may require different inducers and may in turn produce different responses and behavior. For example, there may be different kinds of happiness (or sadness), influenced by different factors, and may lead to different responses (relaxation after completion of a difficult task, enthusiastic expressions of joy, and the like). In addition, music has a host of elements that may be influential beyond the musical structure. These include the words, artistic interpretation, and specific memories that may be associated with the selection, type and period of music, and the interaction of all of these with the product and use situation stressed in the advertisement. Additional research may eventually be able to decompose overall effects into elements of all of these components, taking into account the effect of moderator variables, such as the respondents’ countries and cultures, demographics, personality and lifestyle, cognitive and affective involvement in the communication setting, and familiarity with the music. The tasks in pursuing these issues are considerable, but it seems worthwhile to decompose factors such as musical influence into theoretical elements and their combinations. It is encouraging in this process of inquiry to find that predictions from musical theory may be derived that show correspondence in the emotional responses of audiences. To the extent that this phenomenon might be validated in future experiments, it may be possible to provide better explanation of this source of emotional response to commercials, as well as screen potential advertisements for predicted influences. As has been shown here and by other researchers, moderating effects such as the role of involvement, prior experience with the product category and specific brands or types, as well as the specific musical and other message elements, are all part of this picture. Programmatic research is needed to evaluate their independent and interacting effects under controlled conditions. There remain a number of issues to be explored in the links between verbal and nonverbal elements of a communication setting. It is hoped that this exposition and empirical study of congruity between advertisement background musical structure, consumer’s evoked mood, and ‘‘mood’’ of the purchase purpose or situation will stimulate future efforts along these lines.

Acknowledgements We thank Kalpesh Desai for the assistance in data collection, the student subjects at the University of Texas at Austin, and Meryl Gardner and Morris Holbrook for the helpful comments. Responsibility for errors is ours.

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References Alpert JI, Alpert MI. Music influences on mood and purchase intentions. Psychol Mark 1990;7(Summer):109 – 34. Batra R, Stayman DM. The role of mood in advertising effectiveness. J Consum Res 1990;17(September):203 – 22. Baumann DJ, Cialdini RB, Kenrick DT. Altruism as hedonism: helping and self-gratification as equivalent responses. J Pers Soc Psychol 1981;40(6): 1039 – 46. Bellizzi JA, Crowley AE, Hasty RW. The effects of color in store design. J Retail 1983;59(Spring):21 – 45. Bower GH. Mood and memory. Am Psychol 1981;36:129 – 48. Bower GH. Mood congruity of social judgement. In: Fargar JP, editor. Emotion and social judgements. Oxford: Pergamon; 1991. p. 31 – 53. Calder BS, Phillips L, Tybout AM. Designing research for application. J Consum Res 1981;8(September):197 – 207. Cialdini R, Kenrick D. Altruism as hedonism: a social development of negative mood state and helping. J Pers Soc Psychol 1976;34(5):907 – 14. Clark M, Isen A. Toward understanding the relationship between feeling states and social behavior. In: Hastorf A, Isen A, editors. Cognitive social psychology. New York: Elsevier/North-Holland; 1982. p. 73 – 108. Dube L, Chebat J-C, Morin S. The effects of background music on consumers’ desire to affiliate in buyer – seller interactions. Psychol Mark 1995; 12:305 – 19. Farnsworth PR. The social psychology of music. Ames (IA): Iowa State Univ. Press; 1969. Gardner MP. Mood states and consumer behavior: a critical review. J Consum Res 1985;12(December):281 – 300. Goldberg ME, Gorn GJ. Happy and sad TV programs: how they affect reactions to commercials. J Consum Res 1987;14(December):387 – 403. Gorn GJ. The effects of music in advertising on choice behavior: a classical conditioning approach. J Mark 1982;46(Winter):94 – 101. Griffitt W, Guay P. ‘Object’ evaluation and conditioned affect. J Exp Res Pers 1969;4(July):1 – 8.

Hevner K. The affective character of the major and minor modes in music. Am J Psychol 1935;47:103 – 18. Hevner K. Experimental studies in the elements of expression in music. Am J Psychol 1936;48:246 – 68. Holbrook MB, Huber J. Separating perceptual dimensions from affective overtones: an application to consumer aesthetics. J Consum Res 1979; 5(March):272 – 83. Holbrook MB, Schindler RM. Some exploratory findings on the development of musical tastes. J Consum Res 1989;16(June):119 – 24. Isen AM. The influence of positive affect on decision making and cognitive organization. In: Kinnear TC, editor. Advances in consumer research, vol. 11. Provo (UT): Association for Consumer Research; 1984. p. 534 – 7. Kellaris JJ, Cox AD. The effects of background music in advertising: a reassessment. J Consum Res 1989;16(June):118 – 28. Kellaris JJ, Cox D. The effect of background music on ad processing: a contingency explanation. J Mark 1993;57(October):114 – 25. Kellaris JJ, Kent RJ. An exploratory investigation of responses elicited by music varying in tempo, tonality, and texture. J Consum Psychol 1993; 2(4):381 – 401. Lutz K, Lutz RJ. Imagery-eliciting strategies: review and implications for research. In: Hunt K, editor. Advances in consumer research, vol. 5. Chicago (IL): Association for Consumer Research; 1978. p. 611 – 20. MacInnis DJ, Park CW. The differential role of characteristics of music on high- and low-involvement consumers’ processing of ads. J Consum Res 1991;18(September):161 – 73. North AC, Hargreaves DJ, McKendrick J. The influence of in-store music on wine selections. J Appl Psychol 1999;84(February):271 – 6. Park CW, Young MS. Consumer response to television commercials: the impact of involvement and background music on brand attitude formation. J Mark Res 1986;23(February):11 – 24. Petty RE, Cacioppo JT, Schumann D. Central and peripheral routes to advertising effectiveness: the moderating role of involvement. J Consum Res 1983;10(September):135 – 46.

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Separate and joint effects of medium type on consumer responses: a comparison of television, print, and the Internet Majorie Dijkstra*, Heidi E.J.J.M. Buijtels, W. Fred van Raaij Department of Marketing Management, Rotterdam School of Management, Erasmus University Rotterdam, P.O. Box 1738, 3000 DR Rotterdam, The Netherlands

Abstract This study explores the effects on consumer responses of single- and multiple-media campaigns consisting of television, print, and the Internet. Multiple media in a campaign are expected to have synergy effects. We examine whether a complementarity effect is present in multiple-media campaigns related to media differences in evoking cognitive, affective, and conative responses. Media contribute differentially to the route to persuasion and may complement each other in a marketing-communication campaign. The results show that TVonly campaigns are superior in evoking cognitive responses. This superiority is probably due to the larger number of senses stimulated as well as the forced exposure associated with television as a delivery medium. Affective and conative responses do not significantly differ between the single-medium campaigns. Product involvement influences brand affect and purchase intention. The analysis of covariance reveals a complementarity effect in multiple-media campaigns compared to the Internet-only campaign. However, compared to the TV-only campaign, multiple-media campaigns are less effective in evoking cognitive responses. For most responses, print-only campaigns are as effective as multiple-media campaigns. D 2003 Published by Elsevier Inc. Keywords: Single-medium campaign; Multiple-media campaign; Affective responses; Cognitive responses; Conative responses

1. Introduction New media, such as the Internet, and better-targeted magazines, radio, and TV channels create new opportunities for marketing communication. Given the available media options, a strong need arises to coordinate the use of media in marketing-communication campaigns to reach the desired communication objectives. To effectively communicate a message by use of multiple media, advertisers, media planners, and advertising agencies need to understand the strengths and weaknesses of each medium and, more importantly, need to understand differences in the way consumers process information ‘‘presented’’ by different media (Buchholz and Smith, 1991; Vakratsas and Ambler, 1999). Research provides evidence of differences between media in processing and consumer responses. Several studies assessed the media effectiveness as well as the joint effects of mass media, such as broadcast (radio and TV) and print media (Buchholz and Smith, 1991, Edell and Keller, 1989,

* Corresponding author. E-mail address: [email protected] (M. Dijkstra). 0148-2963/$ – see front matter D 2003 Published by Elsevier Inc. doi:10.1016/S0148-2963(03)00105-X

1998; Jacoby et al., 1983). In contrast, little research has been done to assess the effectiveness of the Internet compared to traditional media (Sundar et al., 1998). To our knowledge, no research examined how the Internet can be integrated in marketing-communication campaigns and how synergy can be obtained from using media combinations, including the Internet. Given the differences in information processing and consumer responses among media, and based on the idea that each medium possesses modalities and strengths that may be instrumental in accomplishing specific objectives, synergy effects may be expected in multiple-media campaigns. Synergy occurs when different media with their specific strengths complement each other in a campaign or when the strength of one medium compensates for the weakness of another medium. Our research goal is to explore the effects of single- and multiple-media campaigns on consumer responses using television, print media, and the Internet. These responses are cognitive, affective, and conative responses and are related to communication objectives such as creating brand knowledge, brand affect, and purchase intention. We examine whether media complement each other in the route to persuasion because of their differential effects of

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evoking cognitive, affective, and conative responses. We discuss the literature and test research hypotheses in an experimental study, comparing consumer responses to single- and multiple-media messages. Furthermore, we discuss the implications for media planning and marketing-communication management.

2. Theoretical background and hypotheses Several dimensions are instrumental in the processing of information in media. Two of these dimensions are modality of the medium and control over the medium (i.e., pacing).

by handling one sensory mode at a time and switching back and forth between modes in a scanning procedure to piece the message together. Edell and Keller (1989) noted that while television does provide more information to the viewer, this information might require more effort to process. Furthermore, distracters (e.g., discrepant verbal and visual components) may interfere and inhibit cognitive elaboration and critical thinking (Edell and Keller, 1989). According to Wright (1980), the interference or ‘‘negative’’ synergy of concurrent sensory modes depends on the nature of the sensory modes themselves (i.e., their postponability, their interest value, and the absolute information load). 2.2. Control over the medium

2.1. Modality of the medium Modality refers to the mode of presentation (i.e., text, audio, picture, or video) that corresponds to human senses used for processing the presented material. Media differ in the content and number of sensory modes stimulated. Each sensory mode may potentially affect processing by directly evoking cognitive and affective reactions or indirectly influencing the processing of and reactions to other sensory modes (Edell, 1988). Television reaches ear and eye by moving visuals, words, and sounds. The combination of moving visuals and audio gives television other powers than static media such as print with only text and visuals. The Internet may combine the moving visuals of television with the detailed information as given in print media. Two contrasting views exist on the capacity of consumers to process information from different sensory modes. According to Jacoby et al. (1983), the commonsense notion is that the larger the number of sensory modes that are engaged in the communication process, such as with television, the greater the likelihood of effective communication. No or little interference between modes is assumed. According to this view, television should be superior on memory and cognitive responses. Besides, television advertisements contain more visual elements that are easier to process and that support the verbal information delivered in the message. Paivio’s (1971) dual-coding hypothesis suggests that although pictures are coded with more variation than words, pictorial elements are easier to retrieve from memory. Research has shown that consumers have a rather impressive ability to pay attention to what they need to attend to (‘‘focussing’’) and at the same time monitor other less well-attended sources of information at some minimum level of meaning (‘‘scanning’’) (Deutsch and Deutsch, 1963; Triesman, 1964). Furthermore, Kisielius and Sternthal (1984) found that multiple sensory modes facilitate learning, i.e., recognizing the meaning of information in one mode may facilitate the interpretation of meaning in another mode. On the other hand, Broadbent (1958) found that the capacity of the human perceptual system is limited and that it can only process sensory information selectively. In a complex and cluttered media environment, individuals react

Control over the speed and sequence of information transfer (i.e., pacing) is another discriminating media factor. This may be controlled by the sender (external pacing) or by the receiver (internal pacing) (Pieters and van Raaij, 1992). As a consequence of pacing, delivery and retrieval media may be distinguished (Van Raaij, 1998). Television is an example of a delivery medium with external pacing. The advertiser controls the speed of information transfer and the order of the information items in a TV ad. Because of its transient character, television is poor on documentation, that is, it does not facilitate consumers to keep the presented information, such as prices, telephone numbers, and Internet addresses. On the other hand, it is expected that television, as a delivery medium that uses multiple sensory modes, has cognitive impact even on low or uninvolved consumers (Buchholz and Smith, 1991). In this respect, under lowinvolvement condition, consumers may engage in superficial processing and may produce cognitive responses, consistent with Krugman’s (1965) ‘‘learning without involvement.’’ In contrast to television, print media and the Internet allow consumers to process the information at their own pace and sequence (internal pacing). This enhances the opportunity to process the information (Jacoby et al., 1983) if motivation is high. Thus, with high involvement, more elaborate information processing may occur. In addition, retrieval media, such as print media and the Internet, enable consumers to retain the information and to read messages at their own convenience. This facilitates a better cognitive processing of the message and might lead to more cognitive responses. On the other hand, retrieval media have the disadvantage that they have limited opportunity to influence less involved or passive consumers (Buchholz and Smith, 1991). Consumers that are not interested in the message can easily skip the message. But if consumers are interested, they may give more attention to the message and more cognitive processing may take place. In our view, the Internet and print media are now largely similar considering the senses stimulated and the speed and control of information transfer, and therefore, we expect no differences in cognitive response. However, Sundar et al. (1998) found better memory performance for the print

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medium than for the Internet. The difference in delivery mechanism (i.e., paper versus computer) is a possible explanation for this finding. They stated that print ads allow the readers to process the ad in its entirety, whereas, Internet ads must be scrolled through to be processed. In conclusion, it is not evident which medium is most effective in evoking cognitive responses. Paivio’s (1971) dual-coding hypothesis predicts that television lead to more cognitive responses. On the other hand, the nature of print and the Internet as retrieval media with internal pacing suggest that these media are superior on cognitive responses if involvement is sufficient. For this reason, no hypothesis is formulated with regard to the cognitive responses. The data are explored to assess which medium is most effective in evoking cognitive responses. Compared to print media and the Internet, the speed of information transfer in television is relatively high and not under control of the viewer. As a consequence, the cognitive processing and rehearsal of messages transmitted by television will be low. Under these circumstances, it is expected that consumers restrict themselves to global evaluative responses in terms of good/bad or attractive/unattractive (Pieters and van Raaij, 1992). Furthermore, with its communication power, television may transfer moods, feelings, and images that facilitate affective responses. Therefore, it is expected that consumers exposed to television will give more affective responses than exposed to print media or the Internet. H1a: Participants exposed to TV only give more affective responses than participants exposed to print or Internet only. Compared with print and television, the Internet has an additional property. It enables consumers to request more information and to buy the advertised brand or product directly and when it is convenient to them. The Internet enables integration of advertising and purchase. Therefore, the Internet may evoke more conative responses because it facilitates purchase without time delay or other constraints. In other words, we expect that the Internet will facilitate direct ordering and purchase after persuasion and thus, may stimulate impulse buying. H1b: Participants exposed to Internet only give more conative responses than participants exposed to TV-only or print-only. Assuming that media differ to the extent in which they evoke responses because of their differences in communication power, we expect that media complement each other in the route to persuasion. Media are complementary when the strengths of different media are combined in a multiplemedia campaign and when a weakness of one medium is compensated by the strength of another medium. Based on the complementarity effect, we expect that campaigns consisting of three different media build on the strengths of each medium in the campaign and evoke more responses than campaigns with only one medium.

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H2: Media campaigns consisting of three media will evoke more cognitive, affective, and conative responses than media campaigns with only one medium. Note, however, that in this hypothesis, we do not argue that the more media used in an integrated marketingcommunication campaign, the better the results will be. On the contrary, using too many media may result in a fragmentation of the communication budget and thus, result in low attention of the consumer and less effect of the campaign. Integrated communication does not mean that many media should be employed but rather, an optimal number of media with different and complementary characteristics and with consistent messages.

3. Research methodology An experimental approach was used to study the effects of multiple- and single-medium campaigns on consumer responses under controlled conditions. One hundred and forty-six students of Erasmus University Rotterdam participated, of which 85 were male and 61 were female. As a reward for their participation, they received a $5 lottery ticket. 3.1. Procedure A complete experimental design takes all combinations and sequences of the three media (television, print, and the Internet) into account. In this study, an incomplete design was used including 3 one-medium campaigns (television only, print only, and Internet only) and six different sequences of three-media campaigns. This resulted in nine conditions with about 15 participants in each condition. Each participant was exposed three times to news items of the Rotterdam Broadcast and three times to the two target ads and two filler ads. In all conditions, participants were exposed to the target ads three times. The exposure (external pacing) to television was 8 minutes to the news and 2 minutes to the ads. The opportunity to see (internal pacing) the print ads and the Internet ads (and banners) was 10 minutes. During these 10 minutes, participants could read the news and the ads. The participants were told that the news items were sponsored and that there was an arrangement with the sponsors that all participants could make use of the promotions offered in the ads. After exposure to the news items, participants filled out a questionnaire to assess their responses to the ads. 3.2. Stimuli The target ads were for a book and a brand of wine. Ads for unfamiliar brands were obtained and developed in cooperation with an advertising agency and an audiovisual company. Using unfamiliar brands eliminates the differences between the participants due to prior knowledge or

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attitudes associated with existing brands and ads (Edell and Keller, 1998). The filler ads were not related to the target ads. The ads were pretested on appreciation. Three news broadcasts from a local news station were recorded and edited. Based on the informational content of the news broadcasts, the newsletter and news websites were constructed. The informational content of the three news items differed within a condition to get or to keep the attention of the participants. Exposing participants three times in a row to the same news program might diminish their attention to the news while probably increasing their attention to the ads, thereby, distorting the results of the experiment. The book and the wine ad were selected because these products are interesting for the students participating in the experiment and are low-risk purchases for them. The book ad contains a picture of the cover of the book (Milan Kundera’s The Unbearable Lightness of Being), pictures of the leading figures, a voice-over telling what the book is about and that the book is available at a reduced price, and music to create an attractive ambiance. The wine ad consists of a picture of the wine bottle with its label (Oude Kaap, a South African wine), pictures of wine fields, a voice-over giving information about the wine and the price, and music. The book title and the wine label are the ‘‘brands’’ in these ads. The print and Internet ads were consistent with the TV ads. The pictures in the TV ad were used in the print and Internet ads. Furthermore, the spoken words were used as written copy in the ads. Participants in the print- and television-only conditions received a coupon to buy the product at a reduced price. The news websites were in an Intranet environment and consisted of news pages and advertising pages. On each news page, banner ads served as a link to the ad pages. The ad pages contained additional information about the brands and included a response device to order the product at a reduced price. The banners consisted of a picture from the ad, the brand name, and price. The place of the four banners on the news pages differed randomly. The logfile was used to trace how participants moved through the website, how long they stayed at a certain page or ad, and whether they ordered the product. 3.3. Dependent variables The dependent variables of this study are cognitive, affective, and conative responses. Cognitive responses are knowledge items and inferences about the exposed messages. Affective responses are evaluations and emotions related to the exposed messages. Conative responses are behavioral responses to advertising such as purchase and purchase intention. 3.3.1. Cognitive responses The three measures used to assess the cognitive responses are the number of brand claims correctly recalled, the number of ad elements correctly recalled, and brand

claim recognition. Participants were asked to write down everything they remember about the advertised brand (its features, benefits, and uses) and the ad itself to assess the number of brand claims and the number of ad elements correctly recalled. In addition, brand claim recognition measures were collected with seven-point scale items from ‘‘very certain’’ to ‘‘very uncertain.’’ The items contained claims that were or were not mentioned in the ads. 3.3.2. Affective responses Participants were asked to list all thoughts, reactions, and ideas that went through their minds while watching or reading the advertisements. The total number of evaluative thoughts (i.e., the sum of negative and positive thoughts from the thought listing procedure) captured affective responses. In addition, the affective reactions toward the ads were assessed with 4 seven-point semantic differential scales: clear/confusing, interesting/uninteresting, appealing/ unappealing, and likable/dislikable. The affective reactions toward the advertised products were measured with 4 sevenpoint semantic differential scales: high/low quality, likable/ dislikable, good/bad, and pleasant/unpleasant (Edell and Keller, 1998). 3.3.3. Conative responses All participants were asked for their intention to buy the advertised products on a seven-point scale (extremely unlikely to extremely likely). The number of emails received via the Internet and the price coupons turned in captured purchase. The coupons were numbered and could be related to the questionnaires. 3.4. Covariates Three covariates that may affect ad response were also measured. These covariates were product knowledge, product involvement, and general attitude toward advertising (Lutz, 1985; Edell and Keller, 1989). Participants with prior knowledge of the product category and with more favorable attitudes toward advertising in general have more positive attitudes (Edell and Keller, 1989). Participants were asked to indicate their knowledge about the product category on a seven-point scale from ‘‘not at all knowledgeable’’ to ‘‘very knowledgeable.’’ Product involvement may influence the processing intensity and may lead to stronger positive or negative. The two facets of consumer’s product involvement, perceived product importance, and interest (McQuarrie and Munson, 1992) are measured with 2 seven-point scales (very important/very unimportant and very interested/very uninterested). A two-item scale, rather than a lengthy 20item Personal Involvement Inventory attitudes (Zaichkowsky, 1985), is sufficient for measuring involvement with concrete and singular products such as a book and wine. With too many items, we incur the risk of conditioning and satiation of participants. Conditioning and satiation reduce the validity of the measurement. Thus, a multi-item measure

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may increase the reliability of the measurement but decreases the validity of the measurement (Rossiter and Kayande´, 1999). The ‘‘general attitude toward advertising’’ covariate was formed by averaging participants’ responses to three items measuring, on seven-point scales, how informative, enjoyable, and useful they judge advertising in general.

covariates product involvement and product knowledge. First, the single-medium conditions are compared on cognitive, affective, and conative responses to test H1a and H1b. Subsequently, we compare the single-medium conditions with multiple-media conditions on consumer responses to test H2.

3.5. Coding procedure

4.1. Single-medium campaigns: television, print, and the Internet

The thoughts listing and recall measures were coded by two graduate students. A third person solved all disagreements. The thoughts were coded on two aspects (i.e., whether the thoughts were product- or ad-related and whether the thoughts were positive, negative, or neutral). The positive and negative thoughts were classified as affective thoughts. The agreement measure Cohen’s kappa was .82. They also coded the open-questions ‘‘recall of brand claims’’ and ‘‘ad elements.’’ The Cohen’s kappa for book claims recall was .88, for wine claim recall .91, for book ad recall .58, and for wine ad recall .75. 3.6. Reliability To test the internal consistency of the multiple-item scales, Cronbach’s alphas were computed for book affect (=.92), wine affect (=.89), book ad affect (=.76), wine ad affect (=.77), book involvement (=.90), wine involvement (=.88), and general attitude toward advertising (=.66). The low alpha for general attitude toward advertising shows that this concept is not unidimensional. For this reason, this variable is excluded from further analysis. The values of the other alphas indicate a good internal consistency.

4. Analysis and results Analysis of covariance was used to correct for any linear relationship between the dependent variables and the

4.1.1. Cognitive responses Three measures are used to assess cognitive responses: brand claim recall, ad recall, and brand claim recognition. The means and significance tests for the media conditions on the cognitive responses are presented in Table 1. We did not specify which medium would be more effective in generating cognitive responses. The analysis of covariance of the number of correctly recalled brand claims shows that participants in the TV-only condition recalled significantly more brand claims than participants in the Internet-only condition (book, P < .001; wine P < .001). Although the TV-only condition has a higher mean for brand claim recall, the difference between the TV- and print-only conditions is marginally significant for the book (P=.090) and significant for the wine (P < .001). No significant differences in means between the print- and the Internet-only condition are found. Regarding ad recall, participants in the TV-only condition produced more recall of ad elements than in the Internet-only condition (book: P < .001; wine: P < .001). For the book ad, print-only participants had a higher ad recall than Internet-only participants ( P < .001), but the difference between the television- and print-only participants was not significant. For the wine ad, ad recall of the television-only condition was also significantly higher than the print-only condition. No significant difference between the Internet- and print-only conditions was found.

Table 1 Means for cognitive response measures Media exposure1

Internet only Print only Television only I–P–T I–T–P P–I–T P–T–I T–I–P T–P–I T–T–P abc. . .n 1 2

Book

Wine

Brand claim recall

Ad recall

Brand claim recognition

Brand claim recall2

Ad recall2

Brand claim recognition2

1.80abcdef 3.40 5.00a 4.60b 4.31c 4.93d 3.43 4.27e 3.33 4.75f

2.40abcdefghi 6.47a 8.08bjklmn 5.73cj 5.69dk 6.13e 4.71flo 5.20gm 4.73hnp 7.25iop

4.51abcd 4.29efghij 5.08 5.16e 5.62af 5.64bg 4.90 5.38ch 5.09i 5.56dj

2.38ai 2.20bj 5.51abcdefgh 3.28ck 2.88dl 3.47e 3.66f 2.35gm 3.39h 4.89ijklm

4.12abc 4.23dk 9.31adefghij 6.06eo 5.01bfl 6.06gp 5.70h 4.00imop 5.77j 7.53cklmn

5.04 5.00 5.59abc 5.07 5.13 4.91a 4.90b 4.67cd 5.09 5.52d

Means with the same letter within a column differ significantly from each other. I = Internet; P = print; T = television. Brand claim recall, ad recall, and brand claim recognition for wine is adjusted for wine involvement.

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The analysis of covariance of brand claim recognition indicates no differences between the print- and Internet-only conditions for both products. Marginal differences were found between print- and TV-only conditions (book: P=.055; wine: P=.085).

4.1.3. Conative responses Analysis of covariance of purchase intention shows a significant main effect of product involvement ( Fbook = 4.94, P=.028; Fwine = 52.07, P < .001) (Table 2). On the other hand, no significant main effect of medium type is obtained ( Fbook=.62, P=.795; Fwine=.88, P=.549). Similar to our findings for brand affect, product involvement seems to determine purchase intention.

4.1.2. Affective responses To assess the affective responses, the following three measures were used: total evaluative thoughts, affect towards the brand, and affect towards the ad. Table 2 contains the means on these measures and significance tests for all media conditions. The analysis of total evaluative thoughts shows that in the Internet-only condition, as compared with the TV- and print-only conditions, less evaluative thoughts were given. In contrast to H1a, TV-only participants did not have significantly more affective thoughts than the Internet- and print-only participants. Between the single-medium conditions, no significant differences were found for brand affect and ad affect. Contrary to the literature (e.g., Chaudhuri, 1996), analysis of covariance of brand affect indicated no significant main effect of medium type ( Fbook=.830, P=.590; Fwine = 1.38, P=.204) and no more affective reactions for the TV-only participants. However, the analysis showed a significant main effect of the covariate ‘‘product involvement’’ ( Fbook = 8.73, P=.004; Fwine = 21.64, P < .001), consistent with theory (Zaichkowsky, 1985). In our experiment, product involvement seems to determine affect towards the product. The higher the product involvement, the more extreme, positive or negative, the brand affect. Brand affect seems to be a function of product involvement rather than medium type. The analysis of ad affect indicates a marginal significant main effect of product involvement ( Fbook = 3.42, P=.072; Fwine = 3.52, P=.063). Product involvement influences ad affect. Thus, product involvement seems to affect both ad affect and brand affect.

4.2. Single- versus multiple-media campaigns In H2 it was stated that multiple-media campaigns are more effective than single-medium campaigns, both with the same number of message exposures. The results of the experiment will be presented and the most important differences between single- and multiple-media conditions will be discussed. 4.2.1. Cognitive responses For both products, the multiple-media conditions, as compared to the Internet-only condition, have higher means on brand claim recall and ad recall, however, most of these differences are not significant for wine (Table 1). Similarly, no significant differences for brand claim and ad recall were found between the print-only condition and the multiplemedia conditions. The analysis of covariance of the cognitive responses for wine indicates a dominance for television-only campaigns. Participants in the television-only exposure recalled significantly more brand claims and ad elements and had better brand claim recognition than the participants in the three-media exposures. Likewise for the book, the findings indicate a dominance for televisiononly condition although not significant for brand claim recall and recognition. For both products, television-only participants recalled significantly more ad elements than the multiple-media participants.

Table 2 Means for affective and conative response measures Media exposure1

Internet only Print only Television only I–P–T I–T–P P–I–T P–T–I T–I–P T–P–I T–T–P abc. . .n 1 2

Book

Wine

Total evaluative thoughts

Brand affect2

Ad affect2

Purchase intention2

Total evaluative thoughts

Brand affect2

Ad affect2

Purchase intention2

1.47abc 2.40 2.15 3.00a 2.38 3.07b 2.00 2.20 2.87c 2.12

3.54 3.31 2.81a 3.57 4.00b 2.71bc 3.89 3.39 3.52 4.06ac

4.07 3.86 4.58 4.41 4.29 4.13 4.12 4.27 4.34 4.56

1.79 1.48 1.82 1.99 2.15 1.35 1.52 1.80 2.17 1.85

1.54abc 2.80a 2.62 2.20 2.00 2.93b 3.07cd 2.54 1.93d 2.37

5.46abc 4.98d 4.74 4.03adefg 5.02e 5.23fh 4.80 5.12g 4.37b 4.32ch

4.67 4.65 5.05a 4.78 4.13b 4.73 4.94 5.17bc 4.50 4.14ac

3.45 3.90 3.44 2.93a 4.13 3.73 4.34abc 3.89 2.99b 2.74c

Means with the same letter within a column differ significantly from each other. I = Internet; P = print; T = television. The means of the dependent variables are adjusted for product involvement.

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4.2.2. Affective and conative responses For both products, the analysis of covariance did not reveal any significant differences on affective and conative responses between the single- and the multiple-media conditions (Table 2). Hence, H2 is not confirmed. However, compared to some of the multiple-media conditions, the number of evaluative thoughts were significantly lower in the Internet-only condition.

5. Discussion A laboratory experiment was conducted examining the effects on consumer responses of single- and multiple-media campaigns consisting of television, print, and the Internet. 5.1. Cognitive responses The results show that, compared with print and the Internet, television is superior in evoking cognitive responses. This is consistent with the findings of Kisielius and Sternthal (1984) and the view that larger number of sensory modes lead to more effective communication (Jacoby et al., 1983). However, this does not agree with the general notion that television is a low-involvement medium evoking less cognitive responses. Compared with print media and the Internet, television, due to the combination of visual and audio modes, evokes more attention and has thus more impact. As a consequence, probably even low-involved participants processed the brand information of the television ads. This is consistent with Krugman’s (1965) ‘‘learning without involvement’’ of television ads. Furthermore, in contrast to participants in the print- and Internet-only conditions, participants in the TV-only condition were forced to watch the news items and, thus, the ads. With print and the Internet, the processing of information is more under personal control (internal pacing) and thus requires more active and involved participants. Low-involved participants can easily skip the ads and read the news items only. The finding that print-only participants reported more cognitive responses than the Internet-only participants may be explained by differences in the confrontation situation. Both media are retrieval media, though, compared to the Internet, print has some ‘‘delivery’’ characteristics. By turning over the pages of the news magazine, participants were forced to notice the book ad and this might have caused the higher cognitive responses for print-only than for Internet-only. Dre`ze and Hussherr (1999) showed empirically that banner advertising has a significant impact on consumers. In our experiment, participants were forced to notice the banner ads on the news pages and therefore, we might expect them to recall the information on these banners (i.e., the brand name, a picture from the ad, and the price). However, Dre`ze and Hussherr (1999) also found that Internet users tend to avoid banner ads and that only 50%

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of banners are attended to. Another explanation for the finding that print media evoke more cognitive responses than the Internet, is the different delivery mechanism. As Sundar et al. (1998) indicated, a print ad could be processed in its entirety, while the Internet ad has to be scrolled. As a consequence, the processing of Internet ads requires even more involved and active consumers than the processing of print ads. We expect that multiple-media campaigns are more effective than single-medium campaigns (H2). For cognitive responses, this is only true comparing multiple-media, and Internet-only campaigns. However, for multiple-media campaigns, compared to the print- and TV-only campaigns, the findings do not support this hypothesis. The higher means for the TV-only compared to multiple-media conditions indicate the presence of a ‘‘replay effect’’ due to forced exposure. Participants in the TV-only condition were forced to see the ad three times, while the participants in the multiple-media condition were only forced to see the ad once (TV) and could decide for themselves to have a second or third look at the ad (with print and the Internet). In subsequent experiments, we tested the replay effect in two ways. First, in a condition in which participants saw two television ads and one print ad (T– T –P), T –T – P participants reported less cognitive responses than television-only participants but more cognitive responses than participants in three-media conditions (Table 1). Second, we conducted a small experiment with 17 MBA students to test the effect of the confrontation situation. We showed a subgroup of students the TV commercial three times and another subgroup the television, print, and the Internet ads (T – P– I), both times without the news items. If the confrontation situation is kept constant, there are no significant differences in cognitive responses. In the threemedia condition, the means of brand claim recall (M = 6.50) and ad recall (M = 9.00) were higher than in the televisiononly condition (Mbrand recall = 5.60; Mad recall = 6.20) although not significantly. The cell means did not differ on brand claim recognition. These findings indicate that, if the confrontation situation is kept constant, multiple-media campaigns may be as effective as television-only campaigns in communicating brand claims. The superiority of television is likely to depend on the forced-exposure character of this medium and not on its inherent medium power. 5.2. Affective responses For the product wine, participants of the Internet-only condition, as compared to television- and print-only conditions, reported significantly less evaluative thoughts. For the product book, no significant differences were found, but the findings point into the same direction. This finding may be a result of a novelty effect, since online advertising is relatively new and participants may associate the Internet as a channel for news and information (Sundar et al., 1998) and

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therefore, may have paid more attention to the news than to the ads. Another plausible explanation is that the difference in evaluative responses is due to the delivery mechanism (Sundar et al., 1998). No significant medium effect was obtained for brand and ad affect. In contrast to other studies (e.g., Chaudhuri, 1996), our results show no superiority of television in evoking affective responses. Therefore, H1a is not confirmed. For both products, the analysis of covariance did not report any significant differences in affective responses between single- and three-media conditions, with the exception of the Internet-only condition on evaluative thoughts. H2 is thus not supported. An explanation is the strong product-involvement effect on ad and brand affect, overruling the weaker medium effect on ad and brand affect. 5.3. Conative responses According to H1b, we expected participants in the Internet-only condition, as compared to the televisionand print-only conditions, to have more conative responses because products can be purchased directly via the Internet. We did not expect that the Internet as a medium is more effective to persuade consumers (measured by purchase intention), but that if people have been persuaded, the Internet facilitates purchase. In the experiment, 3 participants ordered the book and 13 participants ordered the wine. The frequencies of ordering the products (via the Internet or a coupon) showed that the majority ordered the products by use of the Internet. These figures indicate that the Internet facilitates purchase.

6. Implications Media planners mainly focus on quantitative media planning, that is, the selection of media in a campaign based on the minimization of the costs of these media to reach the target group with the required message frequency. With the advent of new and better-focussed media, media planners should consider, besides this efficiency perspective, an effectiveness perspective. Qualitative media planning takes an effectiveness viewpoint, and is concerned with the fit between the message and the media. The ‘‘proper’’ media, media combinations, and sequences should be selected for the campaign, in terms of how consumers process the message and respond to it. The results of this study indicate that multiple-media campaigns can be as effective in communication as TV- and print-only campaigns. This is a positive finding in the sense that multiple-media campaigns can be as effective as TVand print-only campaigns at a lower cost. Multiple-media campaigns may have lower costs of contact, due to a larger reach and the use of media with lower placement costs, as well as more effectiveness of contact with the target group.

This is only valid for large communication campaigns, because the initial costs of developing advertisements, commercials, and websites must be recovered. Note however that using too many media in a marketing-communication campaign might result in low attention and thus a lower effectiveness of the campaign. Although Internet-only campaigns seem to be hardly effective, the findings for the multiple-media campaigns indicate that the Internet may fulfill a complementary function after traditional media created awareness and interest for the advertised product. The main disadvantage of the Internet as a medium is that it is difficult to get target consumers to the website. As a consequence, the Internet needs traditional media for reaching the target groups, creating attention, and communicating the Internet address (URL). The Internet is thus not a substitute for traditional media such as print and television, but the Internet complements the media plan. Traditional media are needed to complement for the weakness of the Internet to attract attention, whereas the Internet complements for the weakness of traditional media to facilitate purchase. Finally, media planners need to take into account consumer’s product involvement. Consumer involvement is crucial for the differential effects of retrieval (print and Internet) and delivery (television) media. Retrieval media will be effective under conditions of high rather than low product involvement, because retrieval media have limited opportunity to influence uninvolved and passive consumers. Contrary to retrieval media, delivery media are better suited for influencing uninvolved consumers. Delivery media can attract the attention of uninvolved consumers and, as a consequence, may induce superficial processing (Buchholz and Smith, 1991) and low-involvement learning (Krugman, 1965). Note that delivery media may also be effective under high-involvement conditions.

7. Limitations The limitations of this study are similar to other laboratory studies investigating different media: the forced-exposure situation and the short time interval between ad exposure and answering the questionnaire. As in other advertising studies, the measurement of affect through questionnaires has its limitations. In this study, participants gave their cognitive responses before their affective responses written down in a questionnaire. The time interval between their affective experiences and their responses provided ample opportunity to think about these experiences and to rationalize them. The ‘‘cognitive’’ and self-reporting way of measuring affective responses with a questionnaire may also lead to report a ‘‘reasoned affect’’ rather than a primary, spontaneous affect. This may explain the small or nonsignificant effects of medium type on brand and ad affect. In further studies, simultaneous affect measurement (with ‘‘liking’’ or ‘‘disliking’’ buttons or with

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physiological measurement) may provide a more valid indicator of the affect people experience while being confronted with a message in different media. This is especially relevant for measuring affect towards the ad. Another limitation concerns the difference in confrontation situation. In our experiment, participants were forced to watch the TV ads, print ads, and (Internet) banner ads. However, participants were able to decide themselves whether to click-through to the advertising pages behind the banners on the Internet. This affected the results and led to less cognitive responses for the Internet-only condition. Research showed that banner advertising has a significant impact on consumers in terms of brand awareness and advertising recall even in the absence of click-throughs (Dre`ze and Zufryden, 1999). Participants in our experiment, who did not click through, were exposed to less information than the print- and TV-only participants. Participants exposed to the banners only could only recall the brand name, the picture (also shown in the TV and print ads), and the price of the product. Although, the confrontation to ads was held constant across media, the confrontation to the informational content was not. In future experiments, the confrontation to the informational content of ads should be held constant across media to compare the processing differences of media in a more valid way. Finally, although 146 students participated, the total number of participants per cell was still relatively small. This decreases the chance to detect small main effects and interactions.

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campaigns and communication effectiveness. The number of media in an integrated campaign might also be a function of reach, message complexity, duration of a campaign, and consumer involvement. Although in this study multiple-media campaigns do not significantly differ from each other in evoking the different types of responses, some sequences of media had higher means (e.g., the sequence P– I– T). The effectiveness of different sequences in a multiple-media campaign needs further investigation because the complementary effect may be due to sequential integration of media in a campaign. We expect that the effectiveness of a certain sequence of media depends on the type of product, message complexity, communication objectives, and, most importantly, consumer information processing. More research is necessary to gain a better understanding of the unique characteristics of the Internet as an advertising medium, as well as its role in multiple-media campaigns. Currently, the Internet fulfills a complementary role to traditional media. However, changes in technology and consumers’ perceptions of and attitudes toward the Internet may alter the function of the Internet as a communication medium. In the future, the Internet may even become a viable alternative to traditional media. Finally, consumer responses to multiple-media campaigns have to be investigated in a field experiment to obtain higher external validity. In such a setting, media exposure will be more similar to ‘‘real-life’’ media use by consumers. In real life, the advertiser has less control over the frequency and sequence of media exposures. Synergy effects may thus be more difficult to reach.

8. Directions for future research The effects on consumer responses were studied of singleand multiple-media campaigns consisting of print, television, and the Internet. With the advent of new media, investigation of the contributions of media to advertising effects will become more relevant for media planners and advertisers. Especially, the strengths and weaknesses of media in a campaign, and thus their complementarity, need further investigation. Moreover, investigating consumer responses to other media (e.g., radio and outdoor media) and other combinations of media is necessary to get more insights in the effects of multiple-media campaigns. Future research should examine under what conditions positive or negative synergy effects are obtained from multiple-media campaigns. Several factors might mediate the impact of multiple-media campaigns, such as the complexity of the message and consumer’s involvement with the product. For example, a complex message communicated by multiple media might confuse the consumer and therefore, might lead to lower communication effectiveness. An interesting research question related to this is: ‘‘What will be the most effective number of media to be used in a multiple-media campaign?’’ If too many media are included, fragmentation will occur. We expect a curvilinear relationship between the number of media in multiple-media

Acknowledgements We thank Wayne Hoyer, Kaj Morel, and Alain Strazzieri for their valuable comments, Martine van Iperen for designing the websites, Patrick Ubags for preparing the videos, and StadsRadio Rotterdam for recording the voices.

References Broadbent DE. Perception and communication. New York: Pergamon; 1958. Buchholz LM, Smith RE. The role of consumer involvement in determining cognitive response to broadcast advertising. J Advert 1991;20(Spring): 4 – 17. Chaudhuri A. The effects of media, product and message factors on ad persuasiveness: the role of affect and cognition. J Mark Commun 1996;2(December):201 – 18. Deutsch JA, Deutsch D. Attention: some theoretical considerations. Psychol Rev 1963;70:80 – 90. Dre`ze X, Hussherr F-X. Internet advertising: is anybody watching? Working paper, University of Southern California, Los Angeles (CA); 1999. Dre`ze X, Zufryden F. Internet advertising: the medium is the difference. Working paper, University of Southern California, Los Angeles (CA); 1999.

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Edell JA. Nonverbal effects in ads: a review and synthesis. In: Hecker S, Stewart DW, editors. Nonverbal communication in advertising. New York: Lexington Books; 1988. p. 11 – 27. Edell JA, Keller KL. The information processing of coordinated media campaigns. J Mark Res 1989;26(May):149 – 63. Edell JA, Keller KL. Analyzing media interactions: print reinforcement of television ad campaigns. Working paper, Fuqua School of Business, Duke University, Durham (NC); 1998. Jacoby J, Hoyer WD, Zimmer MR. To read, view, or listen? A cross-media comparison of comprehension. Current issues and research in advertising. Ann Arbor (MI): University of Michigan; 1983. p. 201 – 17. Kisielius J, Sternthal B. Detecting and explaining vividness effects in attitudinal judgments. J Mark Res 1984;21(February):54 – 64. Krugman HE. The impact of television advertising: learning without involvement. Public Opin Q 1965;29:349 – 56. Lutz RJ. Affective and cognitive antecedents of attitude toward the ad: a conceptual framework. In: Alwitt LF, Mitchell AA, editors. Psychological processes and advertising effects: theory, research and applications. Hillsdale (NJ): Erlbaum; 1985. p. 45 – 63. McQuarrie EF, Munson JM. Product involvement inventory: improved usability and validity. Adv Consum Res 1992;19:108 – 15.

Paivio A. Imagery and verbal processes. New York: Holt, Rinehart and Winston; 1971. Pieters RGM, van Raaij WF. Reclamewerking (How Advertising Works). Houten: Stenfert Kroese; 1992. Rossiter JR, Kayande´ U. Construct measurement in marketing. Working paper, Australian Graduate School of Management, Sydney, Australia; 1999. May. Sundar SS, Narayan S, Obregon R, Uppal C. Does web advertising work? Memory for print versus online media. Journal Mass Commun Q 1998;75(Winter):822 – 35. Triesman AM. Verbal cues, language and meaning in selective attention. Am J Psychol 1964;77:206 – 19. Vakratsas D, Ambler T. How advertising works: what do we really know? J Mark 1999;63(January):26 – 43. Van Raaij WF. Interactive communication: consumer power and initiative. J Mark Commun 1998;4(March):1 – 8. Wright PL. Message-evoked thoughts: persuasion research using thought verbalizations. J Consum Res 1980;7(September):151 – 75. Zaichkowsky JL. Measuring the involvement construct. J Consum Res 1985;12(December):341 – 52.

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Interactivity and vividness effects on social presence and involvement with a web-based advertisement David R. Fortina,*, Ruby Roy Dholakiab a

Department of Management, University of Canterbury, Christchurch, New Zealand b University of Rhode Island, Kingston, RI, USA

Abstract This article measures the effects of various levels of interactivity and vividness of a message on attitudes and behavioral intentions within a web-based advertisement. As a conceptual foundation, the study introduces the multistep model of the impact of interactivity on advertising effectiveness. The model is termed multistep because of the hierarchy of direct and indirect effects. A 3  3 interactivity by vividness between-subjects factorial design tests the model. A total of 360 responses were collected through an online web interface. Data were analyzed by means of individual analysis of covariance (ANCOVA) procedures. The multistep model was also tested with path analysis to verify the significance of the interrelationships between constructs in a simultaneous equations procedure. Results indicate moderate effects of interactivity and vividness on social presence and, indirectly, involvement that in turn have strong effects on traditional advertising effectiveness measures. The findings suggest that the effects of interactivity reach a ‘‘plateau’’ at medium and high levels, indicating a diminishing returns effect. Conversely, the impact of vividness appears to be linear with a steady increase across low, medium, and high levels. No interaction effect was found between the two treatments. The study also provides some insights on using the web as a gateway for experimental research and data collection. D 2003 Elsevier Inc. All rights reserved. Keywords: Interactivity; Vividness; Involvement; Advertising; Social presence; Web

1. Introduction For over a century, advertisers have used a variety of media to reach specific target markets. With the advent of each new medium, advertisers created messages that exploited the media’s physical capabilities, such as color, audio, and moving images (video). The introduction of computer-mediated environments (CME) has stimulated advertisers to establish commercial web sites but there are still unanswered questions regarding the effective use of this new medium. Early web sites were mostly text-based, but technological developments now allow for a variety of features that can enhance the richness of the interface. Advertisers have the opportunity to combine the advantages of print and electronic media and allow for control of pace and exposure to customized information as well as more vivid forms of communication (motion, audio and video files, etc.). As a new conduit for advertising, CMEs raise the

* Corresponding author. Tel.: +64-3-364-2987x7026. E-mail address: [email protected] (D.R. Fortin). 0148-2963/$ – see front matter D 2003 Elsevier Inc. All rights reserved. doi:10.1016/S0148-2963(03)00106-1

question as to how advertisers will use the capabilities of the new media to achieve their communication objectives. To answer this question, we need to understand how the new media are similar and/or different from traditional media and how these differences might influence advertising effectiveness. Interactivity is one of the key characteristics of the new media that is expected to not only transform the way advertising is designed and implemented but also the manner in which it affects consumers’ opinions and attitudes. As technology evolves, we will probably see an increase in the interactive capabilities of new media approximating the level reached by face-to-face (FtF) interactions. Given that most interactive communication attempts historically have failed in the marketplace (Neuman, 1991) and that the effects of interactivity have been inconclusive in academic research (Shaw et al., 1993), this underscores the need for further investigation regarding optimal levels of interactivity. The research objectives of this article are to provide a review of interactivity and evaluate the effects of incremental levels of interactivity on attitudes about an online advertisement.

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2. Literature review

Table 1 Review of literature on interactivity (partial list)

One could argue that the web is simply another medium to convey commercial information along with other media, such as television, radio, print, etc. However, some researchers believe that the interactive nature of the web, i.e., the ability for the user to respond and react, creates a totally new environment that changes the traditional parameters of mass communication within a CME (Hoffman and Novak, 1996). Central to the issue is the interactive nature of a CME. Many researchers have defined interactivity as it relates to the capabilities of a given technology (Rafaeli, 1988; Williams et al., 1988; Newhagen and Rafaeli, 1996). Because of its unique feature as a medium that cannot only receive but also emit transmissions, the web is labeled as a ‘‘many-to-many’’ channel (Hoffman and Novak, 1996). This new approach clearly differs from the traditional model of mass communication where one source transmits to many receptors in a one-to-many fashion (Rust and Oliver, 1994; Hoffman and Novak, 1996; Venkatesh et al., 1995).

Author (year)

Definition

Wiener (1950)

2.1. Defining interactivity

Williams et al. (1988)

Notion of feedback: a method of controlling a system by reinserting into it the results of its past performance. The capability of new communication systems (usually containing a computer as one component) to offer interchangeability of roles between sender and receiver in real or delayed time thus enabling human control over the pace, structure, and content of the communication. The capability of new communication systems (usually containing a computer as one component) to talk back to the user, almost like an individual participating in a conversation. Within a recursive setting, an expression of the extent that in a given series of exchanges, any later transmission is related to the degree to which previous exchanges referred to, even in earlier transmissions. For full interactivity, communication roles need to be interchangeable. A construct that includes control, exchange of roles and mutual discourse. Control refers to the content, timing, and sequence of communication. Exchange of roles implies that sender and receiver can assume both these roles and mutual discourse that each communication feeds on the previous. Six dimensions of interactivity: 1 = complexity of choices, 2 = level of effort, 3 = media responsiveness, 4 = media monitoring capability, 5 = ability to add information, and 6 = capability for interpersonal communication. The extent to which users can modify the form and content of a mediated environment in real-time. Person interactivity is between humans through a medium and machine interactivity is between human and machine to access hypermedia content. A communication that reflects back on itself, feeds on, and responds to the past.

Due to the rapid growth of the web, there is much ‘‘hype’’ in the popular press about new interactive media. Interactivity is now the buzzword of the day, but the term is used loosely and means many things to many people. The lack of a rigorous definition is problematic for researchers who want to study this area in a more systematic fashion. The definition of interactivity by Williams et al. (1988) is a three-dimensional construct. It includes control, exchange of roles, and mutual discourse. Newhagen and Rafaeli (1996) determine five qualities of communication on the Internet: multimedia, hypertextuality, packet switching, synchroneity, and interactivity. Hoffman and Novak (1996) distinguish two levels of interactivity: person interactivity that occurs between humans through a medium and machine interactivity that occurs between humans and machines to access hypermedia content. Various definitions of interactivity are briefly summarized in Table 1. For the purpose of this research, we propose the following definition of interactivity:

Rice and Associates (1984)

Rogers (1986)

Rafaeli (1988)

Heeter (1989)

Steuer (1992)

Hoffman and Novak (1996)

Newhagen and Rafaeli (1996)

2.2. Interactivity continuum the degree to which a communication system can allow one or more end users to communicate alternatively as senders or receivers with one or many other users or communication devices, either in real time (as in video teleconferencing) or on a store-and-forward basis (as with electronic mail), or to seek and gain access to information on an on-demand basis where the content, timing and sequence of the communication is under control of the end user, as opposed to a broadcast basis.

Based on the proposed definition of interactivity, it becomes apparent that different media can display different levels of interactivity and hence the construct cannot be simply categorized as dichotomous. As Heeter (1989) clearly points out, a single medium can exhibit more than one function and within that, some functions might be at different levels of interactivity. Within a highly interactive media, there are also opportunities for varying levels of interactivity. For example, a web site could simply be a page

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of text without any links, feedback options, or search engine. This site would score very low on the interactivity continuum although it is part of a potentially highly interactive medium. Conversely, some television broadcasts, such as infomercials and shopping channels, allow for immediate response through the use of toll-free telephone numbers or on-the-air live interaction with the show’s hosts; this specific broadcast within the (traditionally noninteractive) television medium would score much higher on the interactivity continuum. Rafaeli (1990) argued that for traditional mass media, once-passive audiences are now more active with letters to the editor, on-the-air talk shows, infomercials, etc. Hence, interactivity is a quality of a communication setting, which can vary within the same medium (Rafaeli, 1990). 2.3. Correlate of interactivity: vividness Vividness relates to the breadth and depth of the message: breadth being the number of sensory dimensions, cues, and senses presented (colors, graphics, etc.), and depth being the quality and resolution of the presentation (bandwidth) as defined by Steuer (1992). It is also referred to as media richness (Daft and Lengel, 1986). Also part of Hoffman and Novak’s (1996) model, vividness is often mistaken for interactivity (Rafaeli, 1988; Steuer, 1992). It differs, however, on the capacity for two-way communication; in fact, certain pieces of communication can be highly vivid but noninteractive (e.g., television, magazine). Similarly, certain forms of communication can be highly interactive but also be low in vividness. Using the case of e-mail, the level of interactivity can fluctuate whether it is part of a oneon-one, Listserv, or newsgroup communication. There appears to be ample evidence to suggest that the interactivity construct is in dire need of a clear conceptualization and many researchers have expressed this view (Rafaeli, 1988; Heeter, 1989; Morris and Ogan, 1996).

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persuasion where involvement is part of the process, the elaboration likelihood model (ELM) of Petty et al. (1983) is particularly appropriate in this context since interactivity has the potential to affect involvement and arousal.

3. Conceptual framework 3.1. Multistep model of the impact of interactivity on advertising effectiveness Fig. 1 displays the conceptual multistep model of the impact of interactivity on advertising effectiveness. The model is termed multistep because of the hierarchy of direct and indirect effects of interactivity on advertising effectiveness. Along with interactivity, vividness is a quality of a communication setting that is part of the multistep model. Because it is often mistaken for interactivity (Steuer, 1992; Hoffman and Novak, 1996), it is critical to consider its effects to verify the discriminant validity of the interactivity construct. The model considers interactivity and vividness as characteristics of communication settings that can, either directly, or indirectly through social presence and involvement, affect arousal that in turn affects attitudes. Hence, the following hypotheses are presented. 3.2. Hypotheses 3.2.1. Direct effects of interactivity As mentioned previously, interactivity is best defined as a variable quality of a communication setting, not necessar-

2.4. Understanding consumer use of interactive media Some studies seem to suggest that although interactive technologies may be available, the consumer interest in using them has been disappointing (Lee and Lee, 1995; Neuman, 1991). Studies that have manipulated the level of interactivity of a stimulus (Bailey, 1992; Ku, 1992; Shaw et al., 1993; Frazer and McMillan, 1996; Ketanurak, 1996) seem to indicate a weak effect of interactivity on learning and cognition. There is also research evidence showing that enhanced vividness of the medium does not translate into increased persuasion or recall (Taylor and Thompson, 1982; Walther, 1996). The uses and gratifications paradigm appears to be the framework of choice to study CMEs as it asks why people engage in this form of communication and what benefits they derive from it (Eighmey and McCord, 1995; Newhagen and Rafaeli, 1996; Morris and Ogan, 1996). When considering advertising effects on

Fig. 1. Multistep model of the effects of interactivity on advertising effectiveness.

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ily of a media per se. Consequently, within the same medium, it is possible that different executions of an advertisement will exhibit varying degrees of interactivity. Interactivity will have a direct impact on three other variables: social presence, involvement, and arousal. Social presence: Social presence represents the degree to which a medium conveys the perceived presence of communicating participants in the two-way exchange (Short et al., 1976). This is also termed telepresence in Hoffman and Novak’s (1996) model of network navigation. Interactivity is likely to create feelings of social presence for the user through the availability of open channels allowing for two-way communication. Hence, our first hypothesis: H1: There is a positive relationship between the degree of interactivity of an advertisement and the social presence it conveys. Involvement: Because interactivity can yield increased control of the content appearing in the ad and offer the opportunity to communicate with the advertiser and/or other consumers, it is likely to affect an individual’s sense of involvement, not necessarily with the product category (enduring), but mostly with the ad directly (Zaichkowsky, 1994). Thus,

level of involvement (Zaichkowsky, 1994) of the user with the ad. Thus, H4: The relationship between the degree of interactivity of an advertisement and the level of involvement will be mediated by social presence. 3.3. Moderator variables An individual trait variable called need for cognition (NFC), developed by Cacioppo and Petty (1982), is an individual’s intrinsic enjoyment of and motivation to engage in effortful cognitive information processing. This trait is likely to be of research interest in a media, such as the web, where communication is initiated by the end-user. It has also been examined as a moderating variable in the context of the ELM in previous research (Raman, 1996; Zhang, 1996; Haugvedt et al., 1992). Hence, high-NFC individuals are more likely to be positively affected by high interactivity features than are low NFC. Conversely, low-NFC individuals are more likely to rely on external cues, such as vividness of the message, which is consistent with the peripheral route to persuasion.

4. Method H2: There is a positive, direct relationship between the degree of interactivity of an advertisement and the level of involvement with the ad. Arousal: Because interactive features of an advertisement are usually quickly identifiable within the ad, there is a possibility that the mere availability of these features might increase arousal directly, unmediated by involvement. Arousal is a psychobiological trait of human behavior and is referred to here as phasic activation, a short-term reaction of enhanced energy that increases the overall cortical processing of information (Kroeber-Riel, 1979). Arousal can be generated by an increase in motor activity or muscular responses (Zajonc and Markus, 1982; Wells and Petty, 1981) required by the increased interactivity of the ad. But it can also be the result of cognitive or affective reactions to a stimulus (Holbrook and Batra, 1987). This direct link between interactivity and ‘‘flow’’ is also part of Hoffman and Novak’s (1996) model. Hence, H3: A positive, direct relationship exists between the degree of interactivity of an advertisement and the level of arousal (phasic activation) observed during exposure to the ad. Social presence: Because interactivity generates feelings of social presence for the user through open channels allowing for two-way communication, it is likely that the enhanced social presence will impact positively on the

4.1. Research context: advertising on the web The web is chosen as a context for this research because it provides an opportunity to investigate the effects of varying levels of interactivity and vividness on advertising effectiveness. A commercial home page is defined as an interactive advertisement (Raman, 1996, Ducoffe, 1996) that can vary widely in interactivity depending on its design configuration and the specific features it provides (Frazer and McMillan, 1996). For experimental purposes, we now have the capability of manipulating interactivity and vividness levels of both web site- and banner-based forms of advertising. 4.2. Experimental design The research consists of a 3  3 between-subjects factorial design. Three levels of both interactivity and vividness (low, medium, and high) were manipulated as independent variables, generating nine experimental conditions. 4.3. Stimulus material The stimuli for the experiment consisted of a banner along with a web site advertisement for a fictitious product of relevance to web users (a power surge protector called PowerStrip) and of a moderate level of involvement to avoid extreme effects (Raman, 1996). Both ad configurations and

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data recording forms were created specifically for the experiment by using HTML, the markup language used as a standard of web communication, JavaScript, and CGI scripts. Based on the factorial design, nine versions of the stimulus material representing three levels of interactivity by three levels of vividness were generated. The goal of the study was to manipulate interactivity and vividness while maintaining other factors constant. To this end, the information content of the stimulus material essentially remained constant throughout all experimental conditions and only the interactivity and vividness features were allowed to vary.

Attitude toward the brand Purchase consideration

Covariate measures Need for cognition

Manipulation checks Perceived interactivity

4.4. Procedure 4.4.1. Recruitment of participants A self-recruited convenience sample of web users was used for this experiment. The target population consisted of actual users of the web, aged 18 years old and older. A small incentive in the form of five $50 prizes was offered to stimulate participation. Participants were invited to join the study by clicking through links to the research site that appeared in e-mail Listservs and newsgroups announcements. 4.4.2. Experiment Once they clicked through to the experimental site, participants were randomly directed to one of the nine experimental cells. After examining a banner ad for the product, participants were instructed to click on it to proceed to section two. This section of the experiment was the actual web site for the PowerStrip product. Participants were told to spend as much time as they required going through the test site. The last phase of the experiment asked the participants to respond to our questionnaire, which involved filling out the dependent measures and a short set of background demographics using an easy and friendly ‘‘point-and-click’’ interface. 4.4.3. Instruments

Dependent measures Involvement with the ad Social presence Arousal

Attitude toward the ad

The revised personal involvement inventory measuring involvement with the ad was adapted from Zaichkowsky (1994). The five-item scale developed by Short et al. (1976) was used to measure this construct. The subscale of nine items that measures arousal derived from advertising was pulled from the Standardized Emotional Profile of Holbrook and Batra (1987). An 11-item scale broken down into three components: hedonism (fun to see/not, unpleasant/pleasant, entertaining/not, enjoyable/not), interestingness (important/not, helpful/not, informative/not, useful/not), and utilitarianism (curious/not, boring/not, interesting/not) of the ad (Batra and Ahtola, 1990; Olney et al., 1991).

Perceived vividness

391

A four-item scale measuring attitude toward the brand was adapted from MacKenzie and Lutz (1983) and Raman (1996). A three-item scale adapted from Raman (1996) was used.

Ten items were selected from the revised and shortened version of the 18-item need for cognition scale of Cacioppo et al. (1984).

A six-item scale was created to evaluate the interactivity manipulation based on perceived control of content, mutual discourse, and exchange of roles. Some items were inspired from the media richness scale of Trevino et al. (1987) and the dimensions previously identified in our interactivity definition. Six items were created to measure the strength of the vividness manipulation based on Steuer’s (1992) dimensions of sensory breadth (number of elements) and depth (resolution).

4.4.4. Pretest The purpose of the pretest was threefold. First, to evaluate the performance of the program and the web server in responding to requests for the experiment pages from outside locations. Second, to verify that the experimental procedure was understood well and that instructions and questions were clearly labeled and written. Third, to empirically check the effectiveness of the manipulation for all levels of vividness and interactivity within the stimulus material. Both measures of perceived interactivity and perceived vividness were used as manipulation checks in the pretest so that corrections to the stimulus material could be made before the experiment went into the field. A convenience sample consisting of undergraduate students at a university in the northeast United States was used for the pretest. A total of 76 usable questionnaires were collected through the web server. An e-mail announcement was also sent to all faculty members in the College of Business so they could provide comments on the experimental stimuli and the wording of the questionnaire. 4.4.5. Manipulation checks To examine the effectiveness of both manipulations, two scales for perceived interactivity and perceived vividness were used as manipulation checks. Both scales were normally distributed and performed quite well with ’s of .88 and .90 for the interactivity and vividness scales, respectively. Using the scale means as dependent variables, two separate ANOVAs were conducted to examine the effectiveness of the manipulation. Results indicate that both manipulations were successful [interactivity: F(2,73) = 48.99, P < .001; vividness: F(2,73) = 40.72, P < .001]. The Scheffe’s post hoc test also shows significant mean differences ( P < .05) among all conditions (low, medium, and high) for both scales. In conclu-

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sion, the experimental procedure successfully implemented nine variations of the stimulus material incorporating three levels of both interactivity and vividness. The manipulation checks showed that pretest participants were able to perceive significant differences among all conditions.

5. Analysis and results 5.1. Sample size and composition The survey was left open for a month and a counter on the first page indicated that over 1000 visits were logged in during that period. Of the 397 questionnaires submitted, 385 were usable, which represents a 39% completion rate in traditional survey terminology. To satisfy basic assumptions of statistical techniques and to avoid other problems caused by unequal cell sizes, 25 cases were randomly deleted to obtain an equal cell size design of 40 participants per cell, yielding a total sample size of 360. Prior to analysis, all data were examined for missing values and outlier contamination. No cases were found with extreme or systematic response patterns. Twenty-eight cases had missing values in some variables so a mean replacement procedure was implemented as recommended by Tabachnick and Fidell (1989) when missing values do not exceed 5% of the cases for that variable.

The sociodemographic information about the sample shows a male/female split of 60/40, which is consistent with Internet user demographics (Gupta, 1997). A total of 55% of the sample is in the 25 –44 age group and 46% described themselves as being in the middle third of the household income scale for their country. Most (77%) of the sample came from the United States, with representation from other regions, such as Canada, Australasia, and the United Kingdom. The sample appears better educated than the national average with 47% reporting a graduate or professional degree and 48% working outside the home. A total of 50% of the sample considered themselves experts in Internet usage, 49% access the web between 1 and 10 hour per week and only 27% have started using the Internet after 1996. The main draw to the experimental site came from email Listserv announcements (53%) and 48% accessed the survey from their workplace. Finally, over two-thirds of the sample accessed the site with a Pentium-based PC, 36% with a high-speed connection (e.g., network, T1). Results indicate that both manipulations were successful although the spread of the means across levels is not as large as that found in the pretest. Both manipulation effects are considered large (Cohen, 1977) as evidenced by the 2 statistic for strength of association (2=.25 for interactivity and 2=.44 for vividness). The Scheffe’s post hoc test also shows significant mean differences ( P < .05) among all conditions (low, medium, and high) for both scales.

Table 2 Source table, univariate tests of direct effects Source and dependent variable Need for cognition Involvement Affective subscale Cognitive subscale Social presence Arousal

Type III SS

3.387E 2.402 1.396 8.224 0.830

02 1

df

3 1 1 1 1

Mean square

0.387E 2.402 1.396 8.224 0.830

02

P

2

0.026 1.472 0.862 5.024 1.378

.872 .226 .354 .026 .241

.000 .004 .002 .014 .004

.053 .227 .152 .608 .216

F

Observed power

Interactivity Involvement Affective subscale Cognitive subscale Social presence Arousal

14.082 20.998 9.083 43.475 3.443

2 2 2 2 2

7.041 10.499 4.542 21.738 1.722

5.420 6.434 2.803 13.279 2.857

.005 .002 .062 .000 .059

.030 .036 .016 .071 .016

.844 .902 .550 .998 .558

Vividness Involvement Affective subscale Cognitive subscale Social presence Arousal

13.644 52.380 2.359E 57.508 14.131

2 2 1 2 2

6.822 26.190 0.179E 28.754 7.065

5.252 16.048 0.007 17.565 11.727

.006 .000 .993 .000 .000

.029 .084 .000 .091 .063

.832 1.000 .051 1.000 .994

4 4 4 4 4

1.323 2.390 0.991 1.798 1.261

1.018 1.464 0.612 1.098 2.093

.398 .213 .655 .357 .081

.012 .017 .007 .012 .023

.321 .454 .201 .346 .621

Interactivity by vividness Involvement Affective subscale Cognitive subscale Social presence Arousal

5.290 9.559 3.963 7.191 5.044

02 2

02

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393

Fig. 2. Profile plots for interactivity at levels of vividness.

5.2. Tests of direct effects on process variables A 3  3 between-subjects analysis of covariance (ANCOVA) is performed for the three dependent process variables (involvement, social presence, and arousal). The two subscales for involvement (affective and cognitive) are also integrated into the analysis. Adjustment is provided by two covariates: NFC and expertise. The two grouping variables (independent) used are interactivity and vividness. The ANCOVA procedure examines main, interaction, and covariate effects at the =.05 level. Standard 2 coefficients are computed to ascertain the individual effect sizes of each independent variable on the dependent variable under examination. The results of the ANCOVA procedure are shown in Table 2. The source table displays the F value, exact P significance, and corresponding strength of association (2) for each effect. The NFC covariate provides a small but significant adjustment for social presence ( P=.026, 2=.01). The interactivity construct, the main variable of interest in our study, has a significant impact on two process variables. The strongest impact is on social presence with a moderate effect (2=.07) followed by a smaller effect on involvement (2=.03), all significant at the P < .05 level. Only the affective component of involvement is significantly affected by interactivity (2=.04) although the cognitive dimension approaches significance ( P =.062). Arousal also appeared marginally affected ( P =.059). The vividness construct exhibits main effects on all three dependent process variables with moderate effects on social presence (2=.09) and arousal (2 =.06) and smaller effects on involvement (2=.03). A further examination of the affective component of involvement reveals a moderate effect of vividness (2=.08) but none for the cognitive component. Based on effect size, it would appear that vividness has greater impact on the affective dimension than interactivity. None of the dependent variables are sensitive to the interaction of interactivity and vividness, only main effects will be examined from this point on. A graphical display of all the significant main effects using interactivity on the horizontal

axis is found in Fig. 2a – c. Visual inspection seems to reveal a direct linear relationship between interactivity and social presence at all levels of vividness. For involvement, there appears to be a ‘‘plateau’’ effect of interactivity for both medium and high levels of vividness where the effect either stabilizes or drops off slightly after a positive effect is found between low and medium levels.

Fig. 3. Results of the multistep model.

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5.3. Tests of the multistep model: path analysis The full multistep model is tested using path analysis to verify the significance of the interrelationships between constructs in a simultaneous equations procedure. Fit is ascertained by the root mean square residual (RMR), the goodness-of-fit index (GFI), and the comparative fit index (CFI), as recommended by Bentler (1991). After optimization, the resulting Model 1 with standardized path coefficients is displayed in Fig. 3. The model exhibits excellent fit with the data. Model 1 (GFI=.972, CFI=.981, RMR=.031) has a 2/df ratio of 2.98, which is within the recommended ratio of 5.00 (2 = 44.74, df = 15, P < .01). In Model 1, the impact of interactivity on social presence is significant ( =.25) as is that of vividness ( =.27); however, both links to involvement are not and the relationship appears to be mediated by social presence ( =.62). In Model 1, involvement ( =.55) and social presence ( =.26) significantly impact arousal as hypothesized in our original model. The most provocative finding resulting from the path analysis is the unmediated and strong impact of involvement on all three measures of advertising effectiveness: attitude toward the ad ( =.62), attitude toward the brand ( =.32), and purchase consideration ( =.28). Our model assumed that arousal would strongly mediate all the antecedent effects but this was not supported.

the literature review. However, few of these studies had manipulated interactivity in an advertising communication context or within a web interface. Our results show a moderate and direct effect of interactivity on the construct of social presence, which in turn has a strong effect on involvement and arousal and ultimately advertising effectiveness measures. 7.2. Linear and nonlinear discoveries

6. Review of hypotheses

All but one significant relationship turned out to be linear in nature. A consistent finding showed ‘‘plateau’’ effects of interactivity on dependent measures between the medium and high levels. Because higher interactivity levels also add to the complexity of the advertisement, it is possible that the observed effect is the result of an ‘‘information overload’’ phenomenon. Previous studies in marketing have shown that the addition of information elements and cues in advertisements do not necessarily translate into better consumer evaluations. A similar effect may be present here, which could suggest an effect of diminishing returns. Our initial contention that arousal is a critical element in the process was not supported, suggesting that the route through involvement might be more typical of an information processing model. Hoffman and Novak’s (1996) model of network navigation proposing that ‘‘flow,’’ which is conceptually stronger than arousal, is a result of both interactivity and vividness is not supported by our findings.

6.1. Direct effects of interactivity

7.3. Effects of covariates

The most significant impact of interactivity is on social presence, the degree to which the stimulus conveyed the perceived presence of participants in the communication exchange. Hence, H1 is supported. Although interactivity does have a significant effect on involvement, the relationship appears to be mediated by social presence; thus H2, which hypothesized a direct link, is not supported by Model 1. The hypothesized direct relationship between interactivity and arousal, resulting from muscular responses or phasic activation is not significant and H3 is rejected.

The NFC covariate had a weak impact generally except for one significant interaction with interactivity in the case of social presence. Those high in NFC displayed a directly proportional relationship between interactivity and social presence while those low in NFC showed a ‘‘plateau’’ effect. The ‘‘overkill’’ phenomenon may not be a problem for those who enjoy cognitive stimulation. Not turned off by increased complexity, those high in NFC actually felt higher social presence levels as interactivity increased. 7.4. Critical role of involvement

6.2. Indirect effects The relationship between interactivity and involvement, as mentioned earlier, appears to be significantly mediated by social presence thus supporting H4.

7. Discussion, conclusions, and implications 7.1. Summary of findings Previous research has consistently demonstrated either weak or nonexistent effects of interactivity as discussed in

Interactivity and vividness both impact significantly on social presence and indirectly, involvement, which turns out to have the most significant effect on all advertising effectiveness measures, greater than arousal, as was initially hypothesized in this study. The pivotal role of involvement discovered here underscores the process by which consumers are likely to interact with the new media, namely a more conservative affective process than was originally thought of, more in line with an information processing perspective and supportive of a uses and gratifications paradigm. If the medium itself is fundamentally more involving than other media from a cognitive point of view, then the incremental

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level of involvement for a particular advertisement within that medium might draw upon more affective than cognitive dimensions. The interaction effect between NFC and interactivity observed for social presence also supports this position. Those higher in NFC tend to respond more positively to enhanced interactivity than those scoring lower on that dimension. 7.5. Implications for advertisers The results have significant implications for advertisers. First, it appears that new media, such as the web, have the capability of impacting on attitude formation and change and therefore can be interesting and potentially powerful outlets for consumer communication. However, as is often the case with advertising in conventional vehicles, the ‘‘more-is-better’’ approach does not necessarily lead to enhanced communication effectiveness. As complexity of the advertisement increases, so does the possibility of diminishing returns on effectiveness. However, if the interactive features and design elements are properly balanced, the new media have the ability to impact favorably on involvement, which has been traditionally hard to achieve in conventional media. Our findings would suggest that providing enhanced vividness of the message by means of colors, graphics, and animation is more likely to generate a favorable impact than comparable levels of interactivity. The optimal mix would seem to prescribe a moderate level of interactivity (such as navigational links, e-mail forms, etc.) and a high level of vividness. By focusing on the enhancement of social presence elements in the design configuration of the advertisement, firms have the unique opportunity of establishing virtual or perceived relationships with their customers on a one-on-one basis, which is formidably achieved in the context of the web. Advertisers also have the opportunity of exploiting the creative flexibility of the new media by incorporating specific versions of a message targeted to consumers varying in NFC. Although it would be futile to try and measure every consumer coming into a web site on that variable, our findings suggest that at least two versions of interactive messages could be designed for low and high cognitivesavvy groups who are likely to have different expectations in terms of information display and interactive features. An advertiser can strategically design both configurations and offer them as options within a site. 7.6. Directions for future research Our results showed significant effects of interactivity, which underscores the need for further research of this construct with a long trend of nonsignificant findings reported in previous literature. As the web evolves into a universal medium and a wider array of technological features makes it possible to enhance the interactive experience, there is a need to pursue the interactivity

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research agenda to monitor how consumers use the new media and how they progress through the adoption and learning curve associated with a new technology. Future studies should strive to make the experimental conditions as real and fully functional as possible; a solution to this is to conduct research in partnership with existing firms already engaged in web-related activities. The research technology is such that we can record, measure, and monitor changes in real-time, which reveals a great opportunity for researchers to refine their data collection strategies based on that. More research, however, is needed on the reliability and validity of this channel for research through replication and cross-validation.

Acknowledgements This project was funded in part by the RITIM Institute at the University of Rhode Island.

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Journal of Business Research 57 (2004) 633 – 634

Editorial

Introduction to the special issue on marketing communications and consumer behavior (selected papers from the 2001 La Londe seminar) 1. Introduction The ‘‘International Research Seminar on Marketing Communications and Consumer Behavior’’ is organized on a biennial basis by the Institut d’Administration des Entreprises d’Aix-en-Provence (IAE Aix), a major French business school (University of Aix-Marseille). It is one of the two conferences emerging from the ‘‘International Research Seminar in Marketing’’ created by IAE Aix in 1974.

2. A small and ‘‘interactive’’ conference The seminar is unlike many other conferences in that it is small (70 participants this year) and is characterized by a friendly and informal atmosphere of exchange among researchers from all over the world (14 countries represented this year). In order to facilitate fruitful exchanges, each presentation lasts 45 min. Participants are scholars with an interest in developing a scientific understanding of consumer behavior in order to better design and implement advertising and other marketing communication tools.

3. An outstanding scientific committee The IAE Aix en Provence and the Conference organizers are very grateful to the respected colleagues who served as members of the Scientific Committee. These persons thoroughly reviewed and constructively commented on the 76 papers submitted. Thirty-six papers were accepted and included in the proceedings. Heartfelt thanks are given to the following scholars: Gerald Albaum (University of New Mexico), Rajeev Batra (University of Michigan at Ann Arbor), Russell W. Belk (University of Utah), Yves Evrard (HEC, France), Wayne D. Hoyer (The University of Texas at Austin), Alain Jolibert (University Pierre Mende`s-France, Grenoble), Michel Laroche (Concordia University, Montreal), Siew Meng Leong (National University of Singapore), Sidney Levy (University of Arizona), Richard J. Lutz (University of Florida), Claude R. Martin (University of Michigan at Ann Arbor), Hans 0148-2963/$ – see front matter D 2002 Elsevier Inc. All rights reserved. doi:10.1016/S0148-2963(02)00305-3

Mu¨hlbacher (Universita¨t Innsbruck), Robert A. Peterson (The University of Texas at Austin), Rik Pieters (Tilburg University), Christian Pinson (INSEAD), Bernard Pras (University of Paris-Dauphine, ESSEC), Don E. Schultz (Northwestern University), Jan-Benedict Steenkamp (Tilburg University), W. Fred van Raaij (Tilburg University), Arch G. Woodside (Boston College). We requested other respected colleagues to be ad hoc reviewers. We strongly appreciated their fruitful cooperation. These colleagues are: Mark I. Alpert (University of Texas at Austin), Eric Arnould (University of Nebraska), Alain d’Astous (HEC Montre´al), Philippe Aurier (University of Montpellier II), Michelle Bergadaa` (University of Geneva), David M. Boush (Unversity of Oregon), Joe¨l Bre´e (University of Caen), Daniel Caumont (Universite´ de Nancy), Jean-Jack Cegarra (Universite´ de Lyon 3), JeanLouis Chandon (University of Aix-Marseille), Jean-Charles Chebat (HEC Montre´al), Terry Childers (University of Minnesota), Anthony D. Cox (Indiana University), Rene´ Darmon (Groupe ESSEC), Patrick De Pelsmaker (Antwerp University), David Fortin (University of Canterbury), Pierre Gregory (University of Paris I), Chris Janiszewski (University of Florida), Jean-Noe¨l Kapferer (Groupe HEC), Richard Ladwein (Universite´ de Lille), Gilles Laurent (Groupe HEC), Gilles Marion (EM Lyon), Jean Moscarola (University of Savoie), Peter Reed (Monash University), Gilles Roehrich (University Pierre Mende`s-France, Grenoble), Greg Rose (University of Mississippi), Elyette Roux (University of Aix-Marseille), Aviv Shoham (Institute of Technology, Haifa), Eric Vernette (University of Toulouse), Monique Zollinger (University of Tours).

4. From individual differences in consumer behavior to cause-related campaigns through the role of emotions in persuasion The six competitive papers selected for inclusion in this special issue address various problems, from measuring innovativeness to testing the brand – cause fit effect in cause-related marketing communication. John W. Pracejus and G. Douglas Olsen (Canada) present the results of two experimental studies aiming at assessing

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‘‘how much’’ (and not only ‘‘if’’) brand – cause fit affects consumer choice, through choice-based conjoint analysis (five other characteristics of the brand being considered). The studies show notably a strong impact of brand – cause fit (5 and 10 times in terms of dollar value trade-off). Using LISREL 8, Elisabeth Cowley (Australia) tests a model where recognition confidence (feeling of accuracy) is influenced by recognition accuracy, knowledge (objective and subjective) and task (encoding instruction), and influences significantly memory-based choice. The results provide strong support to the hypothesized relationships. Recognition confidence is found to be an important factor of choice, while recognition accuracy is not directly predictive of choice. Generally speaking, the paper of Ross Buck, Erika Anderson, Arjun Chaudhury and Ipshita Ray (US) deals with the importance of affect (reptilian, individualistic and prosocial biological emotions) in persuasion. Specifically, the study measures emotions involved in the purchase and use or nonuse of condoms with sexual relationships of varying exclusivity. The results support the idea of an important influence of emotions. They bring to the fore the intricacy of influence of specific reptilian and prosocial emotions. Salvador Ruiz and Maria Sicilia (Spain) examine the relationships between the impact of processing styles (‘‘Need for Cognition’’ and ‘‘Preference for Affect’’) on responses to different types of ad (informational, emotional and both informational and emotional). An experimental study shows notably that ads matching the processing of subjects generate better attitude toward the brand, purchase intention and brand choice. Karen Brunsø, Joachim Scholderer and Klaus G. Grunert (Denmark) study the relationships among values, lifestyle and consumption behavior, using a means – end theory of lifestyle (‘‘intervening system of cognitive structures mediating the relations between personal values and behavior’’). Based on a domain-specific (food) lifestyle instru-

ment, the LOV inventory and a set of food-related behaviors, the model proposed is validated on a sample of 1000 French consumers. Gilles Roehrich (France) offers a state-of-the-art paper on consumer innovativeness. Briefly speaking, he shows that despite a substantial literature, the concept is still not well understood and measured.

5. Final words Finally, as co-chairs and coordinator of this conference, we strongly wish to express our gratefulness to Arch Woodside, Editor-in-Chief of the Journal of Business Research, for instigating in 1995 a special issue devoted to a selection of the La Londe seminar papers. This was a key factor of the success of this biennial meeting of worldwide scholars involved in consumer behavior and marketing communications research.

Christian Derbaix* LABACC Marketing Department Catholic University of Mons (FUCAM) 151 Chaussee de Binche, Mons 7000, Belgium E-mail address: [email protected] Lynn R. Kahle University of Oregon, Eugene, OR, USA Dwight Merunka Alain Strazzieri IAE Aix, University of Aix-Marseille, France

* Corresponding author. Tel.: +32-65-323-325; fax: +32-65-323-426.

Journal of Business Research 57 (2004) 635 – 640

The role of brand/cause fit in the effectiveness of cause-related marketing campaigns John W. Pracejus*, G. Douglas Olsen Department of Marketing, Business Economics and Law, Faculty of Business, University of Alberta, Edmonton, Alberta, Canada T6G 2R6

Abstract Previous studies of cause-related marketing (CRM) have demonstrated that it can impact consumer choice. We replicate and extend these findings using choice-based conjoint. Two studies involving 329 respondents show that fit between brand and charity can impact choice. In terms of trade-offs against price discounts, donation to a high-fit charity can result in 5 – 10 times the value of donation to a low-fit charity. We also find, however, that in both studies, the value of CRM does not justify its cost, at least in terms of short-term sales. Implications for the selection of optimal donation levels for CRM campaigns are discussed. D 2002 Elsevier Inc. All rights reserved.

1. Introduction Cause-related marketing (CRM) is an increasingly common form of promotion. Expenditures on this form of communicating with customers are expected to surpass $828 million in North America in 2002 (IEG, 2001). As defined here, CRM involves the contribution to a cause by a firm which is ‘‘linked to customers’ engaging in revenueproducing transactions with the firm’’ (Varandarajan and Menon, 1988, p. 60). We adopt this definition, and only refer to promotions in which the amount given to a charity by a firm is somehow tied to the purchase behaviour of consumers. CRM has recently received considerable attention in the literature. Drumwright (1996), for example, explored the process organizations go through in the determination of how and when to use advertising with a social dimension. Webb and Mohr (1998) found that most of their sample were aware of CRM and could provide two examples, and that nearly one third said that CRM had some impact on their purchases. More recent work has developed scales to measure individual differences in attitudes toward charitable organizations and attitudes toward helping others (Webb et al., 2000). Several studies have also addressed the impact CRM has on consumer perceptions of the sponsoring brand or firm.

* Corresponding author. Tel.: +1-780-492-2023; fax: +1-780-4923325. E-mail address: [email protected] (J.W. Pracejus). 0148-2963/$ – see front matter D 2002 Elsevier Inc. All rights reserved. doi:10.1016/S0148-2963(02)00306-5

Ross et al. (1992), for example, found that CRM had a positive impact on perceptions of the sponsoring firm and that these effects were stronger for women than for men. This positive impact of CRM was also found to be greater when the association was presented as a local, as opposed to a national, ad. Brown and Dacin (1997) also demonstrate that corporate social responsibility associations can influence product evaluations. This impact, however, was primarily through overall corporate evaluations, as opposed to attribute perceptions. Finally, three articles have directly addressed trade-offs consumers may make when weighing CRM contributions against other considerations. Strahilevitz and Meyers (1998) directly compare price reductions against ‘‘charity incentives’’. Their paradigm involves comparing the effectiveness of a unit contribution to a charity (per item purchased) with a unit reduction in the price of the item. They find that charity incentives work better for frivolous products (e.g., chocolate truffles, theme park tickets) then for practical products (pocket dictionaries, correction fluid). They replicate these experimental findings with a field test using actual coupons. They propose that this effect is due to the fact that ‘‘the altruistic utility offered by charity incentives may be more complimentary with the feelings generated from frivolous products than with the more functional motivations associated with practical products’’ (p. 444). They also consider the possibility that some of their findings may have been driven by ‘‘product –charity complementarity’’ (e.g., if the bookstore in Study 3 was giving money to a literacy fund instead of the March of Dimes, the utilitarian

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product might have benefited more from CRM; p. 444). However, they leave the exploration of whether brand/cause fit can impact choice to future research. Continuing in this stream, Strahilevitz (1999) explores the role of donation magnitude in CRM success. Specifically, she finds that when the amount of the discount/ donation becomes large (i.e., 25 – 50% of the purchase price), a majority of choices are for the discount, especially when the product is practical, as opposed to frivolous. When the amount of the discount/donation remains small, however, (i.e., 1– 5% of the purchase price), more choices are for the donation, and there is no difference between the frivolous and practical products in this regard. Finally, Barone et al. (2000) explore the trade-offs consumers make among CRM, price and quality. They do not make consumers pick choices between a brand engaging in CRM and one that is not, under varying levels of price and quality. Rather, they have subjects trade-off price or quality against varying underlying motivations (selfish/altruistic) of two brands that are both engaged in CRM. They conclude that CRM can impact choice, but only if it does not result in higher prices or lower product performance. We applaud these initial studies in that they (1) demonstrate that CRM can impact consumer choice, and (2) demonstrate that price and quality trade-offs can diminish or eliminate the positive impacts of CRM. We intend to elevate current knowledge about CRM by (1) replicating the finding that CRM can impact choice, and (2) extending these findings by demonstrating that perceived fit between sponsoring brand and cause can also impact consumer choice. Additionally, we use choice-based conjoint to calculate the actual trade-offs consumers are willing to make in order to support a brand that supports a cause. As mentioned above, Strahilevitz and Meyers (1998) have proposed that fit between brand and cause may impact the success of CRM. With the exception of Bendapudi et al. (1996), who address the issue of donor/recipient similarity in the context of charitable giving, no other conceptual or empirical work has been done in the area of brand/cause fit in CRM. Other domains, however, have found robust effects of fit on other types of brand associations. Fit between brand extensions and core brands, for example, has been found to enhance the evaluation of the extension when the core brand is well liked (Aaker and Keller, 1990, 1993). Likewise, in the context of ‘‘composite branding alliances,’’ Park et al. (1996) find that when the two brands in the composite have greater fit in terms of attribute complementary, success is facilitated. Also for celebrity endorsers, increased spokesperson/product fit results in a more favorable product attitude (Kamins and Gupta, 1994) and allows information to be processed in a shorter time (Speck et al., 1988). CRM is similar to these other domains in that brands are intentionally associating themselves with some other object in order to improve brand performance along some dimension. Across all the domains mentioned above, fit has

generally been found to facilitate transfer of positives from an object (celebrity, core brand, etc.) to the object-associated brand. That is, fit is necessary, but not sufficient for success. In keeping with this theoretical tradition, we explore the role of fit between brand and cause on choice when the cause is well liked. We are not only interested in determining if fit affects choice, but also how much it affects choice. We do this by employing discrete choice analysis (choice-based conjoint), a technique which is widely used in industry but has received surprisingly little application to the exploration of theoretical constructs in consumer research. Because many consumer researchers are not fully aware of the assumptions and capabilities of choice-based conjoint, a brief overview is provided below.

2. Choice-based conjoint Conjoint analysis has now come to refer to a broad class of decompositional models that determine utility (part – worth) estimates of individual attribute levels from global responses to a series of alternatives (e.g., a rating of each alternative) or set of alternatives (e.g., a ranking of profiles, or a choice of one from among a set). These techniques allow researchers to (1) present people with novel attribute combinations; (2) obtain demand estimates and price elasticities; and (3) calculate main effects for, and interactions among, product attributes. Discrete choice tasks are analysed using Multinomial Logistic (MNL) regression. While this method may be more difficult to use than regression programs designed for interval data (e.g., Ordinary Least Squares regression), a number of benefits exist, including: (1) the ability to estimate market share predictions directly, rather than passing them through a choice simulator (thereby eliminating one stage of the process and the introduction of more error); and (2) market share estimates are based on choice data, which is what people do in the real world (for a thorough review of the history of discrete choice, see Batsell and Louviere, 1991).

3. Experiment 1 3.1. Purpose The purpose of this study was to determine whether fit between the charity and the brand can impact the success of a CRM campaign in terms of choice behaviour, as well as to measure the magnitude of this effect, if observed. 3.2. Pretesting Since evidence from extant research in other domains suggests that fit generally facilitates or enhances the impact

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of associating a brand with a well-liked object, our strategy was to find two causes that were equally well liked, but differed in terms of fit with some sponsor. Given that previous research had shown that CRM is more likely to impact frivolous, as opposed to utilitarian, brands (Strahilevitz, 1999; Strahilevitz and Meyers, 1998), we decided to focus on frivolous brands. For Study 1, we chose ‘‘Theme Parks,’’ which was one of the frivolous categories shown by Strahilevitz and Meyers (1998) to be significantly impacted by CRM. Theme parks were also a highly salient category for our subjects as it was near the end of the term and many local parks were advertising summer discounts for Florida residents. We first attempted to find a set of causes that were well liked by the target population. Twenty subjects rated their liking of 124 sponsored events, organisations and causes (the pretest was also used for an unrelated study of event sponsorship). Fifteen additional subjects then rated perceived fit between theme parks and the 30 best-liked events, organisations and causes from the first part of the pretest. Fit was assessed using a seven-point scale anchored by very low fit and very high fit. The two causes chosen to be paired with theme parks were the ‘‘Kennedy Center for the Performing Arts’’ (Fit 3.2/7; Liking 6.3/7) and the ‘‘Children’s Miracle Network’’ (Fit 6.1/7; Liking 6.1/7). There is a significant difference in perceived fit of theme parks with the two causes ( F = 45.81, P < .001), but no difference in overall liking of the two causes ( F < 1, P > .38). 3.3. Respondents One hundred twenty-eight undergraduate subjects from the University of Florida took part in Experiment 1. Subjects received course extra credit in exchange for their participation. None of the 35 pretest subjects participated in the main study. 3.4. Procedure and experimental design Prior to beginning the discrete choice task, respondents were presented with sample advertising copy for the two theme parks. Embedded within the copy for one of the parks (either ‘‘Hudson’’ or ‘‘Davis’’) was the sentence ‘‘As part of our continuing support of the Children’s Miracle Network (Kennedy Center for the Performing Arts), we’ll donate five dollars to this worthy cause for every ticket sold until the end of the month.’’ Therefore, each subject was randomly assigned to one of four cells in the 2(Fit: high/low)
2(Name: Hudson/Davis) between-subjects design. Pretesting for an unrelated study found ‘‘Hudson’’ and ‘‘Davis’’ to be neutral and equivalently liked ‘‘brand names’’ in general. However, due to the possibility of category-specific associations, ‘‘name’’ was included in the design so as to provide a check that, within the context of the choice task, there was no confound between CRM and the specific name used (i.e., Hudson vs. Davis).

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Following the description of the theme park and the charity to which the donation would be made, respondents completed a series of 16 discrete choice tasks. All choice tasks required the respondent to choose between the ‘‘Hudson’’ and ‘‘Davis’’ theme park alternatives. These alternatives were described along five different characteristics: admission price ($24.95 and $34.95); driving distance (45 vs. 90 min); number of rides available (32 or 46); food quality (fair vs. good); and hours of operation (8 am – 8 pm vs. 7 am – 11 pm). Subjects were told to consider what they had read about the two hotels in the advertisements, as well as the attribute information, which changed from task to task, in arriving at each of their 16 choices. A full factorial design was used to create all possible profiles (32) for the first option in each choice task. The choice sets were created by matching profiles from this set with a second set of all possible product profiles. This was done in a manner that permitted all attribute levels for the first alternative to remain orthogonal to all attribute levels for the second alternative. Specifically, the matching was conducted in such a way that all attribute levels for each of the attributes in the first set of profiles were paired an equal number of times with all attribute levels for each of the attributes in the second set of profiles. In an effort to reduce respondent fatigue, a blocking technique was used, randomly assigning each of the choice tasks into one of two blocks. Hence, each respondent was only required to complete 16 choice tasks (as opposed to all 32). The order of the choice tasks was randomised within each block. 3.5. Analysis and results MNL regression was employed to arrive at parameter estimates (see Table 1). The r2 value for the model as a whole was 0.70, indicating that it was very effective at explaining the choices made by respondents. The Donation Intercept parameter is based on using a dummy code to represent the amusement park that offered the charitable donation, and reflects the additional amount that an individual would be willing to pay for the low-fit donation. By dividing the coefficient for the Donation Intercept by the Admission Price coefficient, it is possible to directly determine the point at which a consumer would be ambivalent between an amusement park that offered the promotion, but charged more, and an amusement park that offered no promotion. In this particular case, results suggest that the dollar value of offering the low-fit donation is equivalent to $0.62. In order to examine the value of offering a charity that is of high-fit, a similar calculation may be performed by first summing the parameter estimates for Donation Intercept and Fit
Donation Intercept, then dividing this value by the parameter estimate for the Amusement Park Admission Price. This calculation suggests that if the high-fit donation alternative was present, an amusement

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Table 1 Choice task coefficients for amusement park study Variable

Coefficient

Donation Intercept Admission Price (per $) Distance (per minute) Number of Rides Food Hours of Operation Fit
Donation Intercept Fit
Admission Price ($) Fit
Distance Fit
Number of Rides Fit
Food Fit
Hours of Operation Brand Name Intercept Brand Name
Admission Price Brand Name
Distance Brand Name
Number of Rides Brand Name
Food Brand Name
Hours of Operation

0.333*  0.183*  0.039* 0.105* 0.479* 0.229* 0.219* 0.017 0.007** 0.021** 0.191***  0.102*  0.136*** 0.004 0.002 0.003  0.148  0.016

* P < .001. ** P < .01. *** P < .05.

park could charge an additional $3.01. Hence, the dollar value of the high-fit alternative, relative to the low-fit alternative, is $2.39. The interaction terms between fit and park features were estimated to examine whether donating to a high-fit charity would have a differential impact on the parameter estimates for the product characteristics. It is interesting to note that fit interacted at conventionally significant levels with a number of these attributes. Specifically, relative to low-fit conditions, when the charity is high-fit, consumers are significantly less sensitive to the driving distance to the park, the number of rides available, the quality of the food and the hours of operation. Examining the parameters reported further, it is of note that an amusement park offering either donation type would be able to compensate for fewer rides or shorter operating hours relative to a competitor. Further, if the charity was high-fit, such a donation would tend to encourage the consumer to select an amusement park with fair food quality over a competitor with good food quality, all other features being equal. In addition to allowing for the calculation of dollar metric trade-offs, the choice conjoint technique also allows for the direct estimation of market shares. Predicted market shares for the high-fit and low-fit CRM campaigns can be calculated using the following equation: eUia Pia ¼ P Uja e j2Ci

where Pia = is the probability that an individual will choose the ath alternative in choice set i consisting of j alternatives; Uia = is the utility associated with the ath alternative in

choice set i; = BXia + eia, where B is a row vector of parameters and Xia is the design matrix for the ath alternative in choice set i; Ci = is the set of all alternatives. Under conditions where there are two alternatives that are equal on all features, if one alternative offered a low-fit charitable donation, market share for this alternative would go from 50% to 58.3%. However, if the charitable donation is high-fit, the market share would be elevated to 67.3%. In the event that both parks offered donations, relative to a low-fit park, a high-fit park would obtain a 59.6% share.

4. Experiment 2 4.1. Purpose Experiment 2 was designed to accomplish two goals. First, we wanted to replicate the findings of Study 1 with a different product class to increase generalizability. Second, we sought to find a product category for which the Kennedy Center for the Performing Arts would be highfit and the Children’s Miracle Network would be lower in fit. In this way, we unconfound fit with cause across the two experiments. 4.2. Pretesting In order to determine a product class meeting the above criteria, 18 respondents rated the fit between the Kennedy Center and 38 product categories. Twenty additional respondents rated the fit between the same 38 categories and the Children’s Miracle Network. ‘‘Luxury Hotels in Washington, DC’’ were found to be a significantly better fit with the Kennedy Center (4.9/7) than with the Children’s Miracle Network (2.8/7; t = 3.74; P < .001). 4.3. Respondents One hundred twenty-eight additional subjects took part in Experiment 2. They received course extra credit for participation. None of them had participated in Experiment 1 or any of the pretests. 4.4. Procedure and experimental design Just as in Experiment 1, respondents were informed that one of the two hotels would offer a donation for each night stayed ($10 in this experiment). A 2(Fit: high/low)
2(Name: Hudson/Davis) between-subjects design was used. Respondents then completed a discrete choice task. In all cases, the respondent selected from two hotels described along five objective characteristics: price per night ($115 and $95); exercise facilities (fair vs. good); number of free movie channels (one vs. three); complimentary afternoon wine and cheese (present vs. absent); and room service

J.W. Pracejus, G.D. Olsen / Journal of Business Research 57 (2004) 635–640 Table 2 Choice task coefficients for hotel study

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5. Discussion

Variable

Coefficient

Donation Intercept Hotel Price Per Night (per $) Exercise Facilities Number of Movies Wine and Cheese Room Service Hours Fit
Donation Intercept Fit
Hotel Price Per Night ($) Fit
Exercise Facilities Fit
Number of Movies Fit
Wine and Cheese Fit
Room Service Hours Brand Name Intercept Brand Name
Hotel Price Per Night Brand Name
Exercise Facilities Brand Name
Number of Movies Brand Name
Wine and Cheese Brand Name
Room Service Hours

0.255*  0.128* 0.531* 0.675* 1.741* 0.113* 0.241*  0.006  0.041  0.064  0.005  0.004  0.103 0.004  0.125  0.099  0.191 0.006

* P < .001.

hours (6 am to midnight vs. 24 h/day). The same design used in Study 1 was employed to create 32 choice sets. As before, each subject made 16 choices. 4.5. Analysis and results As with the first study, MNL regression was used to analyse the choice frequencies. The r2 statistic for the model was 0.73, suggesting that the parameters generated were extremely effective at capturing an understanding of the choice behaviour observed. Results of this analysis are presented in Table 2. Once again, both donation and brand/cause fit were significant. The impact of offering a charitable donation promotion, in general, and under high fit was calculated as in Study 1. In this case, the value associated with donation to the low-fit charity was $0.38. The value associated with donation to a high-fit charity was $3.88, which equates to $3.50 more than they could charge if the donation was of low-fit. Of further note is that the parameter estimates suggest that either donation type would compensate for offering reduced room service hours relative to a competitor offering room service 24 h/day. It would also be possible to compare these parameter estimates to other hotel features such as exercise facilities. Examining market share issues, if two alternatives were equal on all other parameters, offering a low-fit charitable donation would increase market share to 56.3% and assuming that the competitor offered no donation, a hotel offering a high-fit donation would result in an increase of market share to 67.6%. In the event that both hotels were offering a donation, the one with the high fit would garner 61.8%. Neither the main effect of Brand Name, nor interactions involving Brand Name were significant at conventional levels.

We have demonstrated that CRM may have a significant impact on choice behaviour (as indicated by the associated dollar equivalencies, as well as market share estimates), and that brand/cause fit substantially amplifies this effect. These effects were obtained across two product categories (Theme Parks and Luxury Hotels). While the overall positive effect of CRM had been demonstrated previously (Barone et al., 2000; Strahilevitz, 1999; Strahilevitz and Meyers, 1998), it has not been previously demonstrated in a way that allows the precise calculations of either dollar metric trade-offs or market share. More importantly, the positive impact of brand/cause fit, which we demonstrate in both studies, has not been previously found. While similar positive effects of fit have been found for brand extensions, composite branding alliances and celebrity endorsers, this effect has not been shown in the domain of CRM. Using choice conjoint techniques, we were also able to calculate the magnitude of CRM impact, both in terms of market share and tradeoffs with price. We believe that this is a major improvement over previously employed techniques. The ability of the method employed to estimate dollar trade-offs is especially salient given our results. In both studies, even the high-fit CRM campaign cost more in donations than could be justified in terms of short-term sales (see Table 3). One might interpret these findings as suggesting that the value of CRM is limited. We argue that, without considering the possible long-term impact of CRM and the limited range of donation values explored in the two studies, such a negative interpretation of the results would be premature. While the results of these studies show that even the donations to the high-fit charity have a smaller impact on choice than would an equivalent reduction in price, one must also consider the long-term benefits to brand equity, which may accrue from the CRM option. Individuals who use the brand for the first time during a CRM campaign may become loyal customers, thus creating a long-term income stream. While a price reduction may get a one-time customer, the positive associations with the charity may allow the CRM option to facilitate more long-term customer relationships. Future research addressing whether CRM is especially effective at initiating or enhancing long-term relationships, therefore, seems particularly worthwhile. There is, however, a much more important reason not to assume that these results argue against the viability of

Table 3 Amount donated and value of CRM

Study 1 Study 2

Amount donated ($)

Value of low-fit CRM ($)

Value of high-fit CRM ($)

Value of fit ($)

5.00 10.00

0.62 0.38

3.01 3.88

2.39 3.50

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CRM. This reason is that the amounts donated per transaction in the two studies (10 – 20% of the purchase price) are quite large, and possibly much larger than is typical for actual CRM campaigns. We set the level of donation at this relatively high level so as to maximise the potential for statistically observable effects of both CRM and fit. In this respect, our manipulations were successful. In doing so, however, we may have utilised donation levels far in excess of optimal ‘‘real world’’ levels. In fact, Strahilevitz (1999) found that as the donation/discount amount becomes a high percentage of product price, consumers tend to prefer the discount. The price trade-offs in Table 3 hint at the possibility that the level of donation used in the two studies is well beyond a theoretical ‘‘optimal point.’’ Note that between Studies 1 and 2, donation level goes from $5 to $10 (100% increase), while the dollar value of the high-fit CRM only goes from $3.01 to $3.88 (a 29% increase). While it would be highly speculative to draw any conclusions about the functional relationship between donation magnitude and impact on choice from these two data points, it certainly seems possible that some sort of asymptote may exist. If it does, the 10 – 20% donation levels used here may well be approaching that asymptote. Further research is clearly warranted to determine (1) if optimal donation levels exist, and (2) how to calculate these optimal values. In fact, it is possible that the ‘‘optimal value’’ for CRM donation may not be a number at all. A recent study of actual wording of CRM promotions finds that a minuscule fraction of CRM campaigns reveals an actual dollar amount given for each purchase (Olsen and Pracejus, 2002). The vast majority of campaigns utilise a vague quantifier (e.g., ‘‘A portion of the proceeds’’) to describe how much will be given. Many others state the amount in terms of a percent of profits, which consumers may confuse with percent of price. Finally, many CRM campaigns have a ‘‘cap’’ such that a percent of each sale is donated ‘‘up to’’ some maximum amount (e.g., ‘‘50 cents from each box sold will be donated, up to $10,000’’). Future research should explore the degree to which consumers are capable of understanding and processing CRM donation amounts stated in these ways, as well as the impact of such promotional verbiage on choice. Clearly, such studies would have important managerial and public policy implications. None of this, however, should take away from our primary finding that the fit between the brand and the charity can have a tremendous impact on the success of CRM campaigns. In terms of dollar value trade-offs, the high-fit CRM campaign had roughly 5 times the impact of the low-fit campaign in Study 1 ($3.01 vs. $0.62), and 10 times the impact in Study 2 ($3.88 vs. $0.38). These are not small effects. Clearly, perceived fit between the company

and the charity is an important measure that should always be taken prior to any CRM campaign.

Acknowledgements The authors acknowledge the J.D. Muir fund for financial support of this research and thank Joffre Swait for assistance with the experimental design.

References Aaker DA, Keller KL. Consumer evaluations of brand extensions. J Mark 1990;54(1):27 – 41. Aaker DA, Keller KL. Interpreting cross-cultural replications of brand extension research. Int J Res Mark 1993;10:55 – 9. Barone MJ, Miyazaki AD, Taylor KA. The influence of cause related marketing on consumer choice: does one good turn deserve another. J Acad Mark Sci 2000;28(2):248 – 62. Batsell RR, Louviere JJ. Experimental analysis of choice. Mark Lett 1991; 2:199 – 214. Bendapudi N, Sing SN, Bendapudi V. Enhancing helping behaviour: an integrative framework for promotional planning. J Mark 1996;60: 33 – 49 (July). Brown TJ, Dacin P. The company and the product: corporate associations and consumer product responses. J Mark 1997;61:68 – 84 (January). Drumwright ME. Company advertising with a social dimension: the role of noneconomic criteria. J Mark 1996;60:71 – 87 (October). IEG Sponsorship Reports 2001;2(24):1, 4 – 5. Kamins MA, Gupta K. Congruence between spokesperson and product type: a matchup hypothesis perspective. Psychol Mark 1994;11(6):569 – 86. Olsen GD, Pracejus JW. Consumer estimation of actual donation by companies to charities during cause related marketing campaigns. Working paper. Department of Marketing Business Economics and Law, University of Alberta, 2002. Park CW, Jun SY, Shocker AD. Composite branding alliances: an investigation of extension and feedback effects. J Mark Res 1996;33(4):453 – 66. Ross JK, Patterson LT, Stutts MA. Consumer perceptions of organizations that use cause-related marketing. J Acad Mark Sci 1992;20(1):93 – 8. Speck PS, Schumann DW, Thompson C. Celebrity endorsements—scripts, schema, and roles: theoretical framework and preliminary tests. In: Houston MJ, editor. Advances in consumer research, vol. 15. Provo (UT): Association for Consumer, 1988. pp. 69 – 76. Strahilevitz M. The effect of product type and donation magnitude on willingness to pay more for a charity-linked brand. J Consum Psychol 1999;8(3):215 – 41. Strahilevitz M, Meyers JG. Donations to charity as purchase incentives: how well they work may depend on what you are trying to sell. J Consum Res 1998;24:434 – 46 (March). Varandarajan PR, Menon A. Cause related marketing: a coalignment of marketing strategy and corporate philanthropy. J Mark 1998;52: 58 – 74 (July). Webb DJ, Mohr LA. A typology of consumer responses to cause related marketing: from skeptics to socially concerned. J Public Policy Mark 1998;17(2):226 – 38. Webb DJ, Green CL, Brashear TG. Development and validation of scales to measure attitudes influencing monetary donations to charitable organizations. J Acad Mark Sci 2000;20(2):299 – 309.

Journal of Business Research 57 (2004) 641 – 646

Recognition confidence, recognition accuracy and choice Elizabeth Cowley School of Marketing, University of New South Wales, John Goodsell Building, Sydney, NSW 2052, Australia

Abstract Individuals only use a subset of the information available in memory at choice. It is proposed here that in a memory-based decision setting, information that is most confidently retrieved from memory, regardless of its accuracy, will be most influential in decision making. The results reveal that recognition confidence predicts choice, although there is a relationship between recognition accuracy and choice, it is completed mediated by recognition confidence. Recognition confidence is a function of domain specific knowledge and encoding instruction. D 2002 Elsevier Inc. All rights reserved. Keywords: Memory; Product knowledge and expertise; Confidence; Recognition; Metacognition

1. Introduction While on a protracted shopping trip, Susan was standing in the fifth camera shop of the day, trying to remember if the Pentax camera she was looking at was the same model she had seen in another shop in the morning. She was also trying to remember whether the price was the same. It was late, the other shop was in another shopping mall, she felt pretty sure that the camera model was the same, and that the price was higher in the other store. She bought the camera, which was actually a different model with fewer features. Consumers generally only use a subset of the information they have accumulated and stored in memory when making decision. Identifying the most likely information to be used in a decision is of interest to both psychologists and marketers (e.g., Armacost and Hosseini, 1994; Bastardi and Shafir, 1998; Fischhoff and Downs, 1997; Kardes, 1994; Lee et al., 1999). In the accessibility– diagnosticity framework (Feldman and Lynch, 1988), more accessible information is more likely to be used in decision-making (also see Cohen, 1966). Why? Because more accessible information comes to mind easily, and is, therefore, presumed to be correct (Kelley and Lindsay, 1993; Koriat, 1993, 1994, 1995; Metcalfe, 1996). This feeling of accuracy, or recognition confidence, is an efficient way to determine what information to use in choice because checking the accuracy of recognised information often requires a fair amount of effort, if it is possible at all.

E-mail address: [email protected] (E. Cowley). 0148-2963/$ – see front matter D 2002 Elsevier Inc. All rights reserved. doi:10.1016/S0148-2963(02)00307-7

Like all metacognitive assessments, recognition confidence is prone to error (Metcalfe, 1996). In fact, in the eyewitness testimony literature, the correlation between recognition accuracy and recognition confidence has been found to be low (Bothwell et al., 1987; Cutler and Penrod, 1988). The conclusion drawn in an extensive review by Cutler and Penrod (1995) is that the confidence in one’s ability to retrieve information accurately from memory is a poor predictor of recognition accuracy. Busey et al. (2000) have recently provided an explanation of the lack of correlation between recognition confidence and accuracy with their extension of cue utilization theory. Their results support a multidimensional model of the confidence – accuracy relationship (Fig. 1). In their model, the memory representation includes two dimensions, memory strength and memory certainty. Recognition accuracy varies with memory strength, while confidence varies with both strength and certainty. Hence, any change in certainty can cause a dissociation between accuracy and confidence. If consumers use the confidence – accuracy heuristic, they may be naively using inaccurate information in consumption decisions. Not all representations of accuracy – confidence relationship predict a low correlation; for instance, in the trace access theory (Burke et al., 1991; Hart, 1967; King et al., 1980), retrieval is a process of direct access to memory during confidence and accuracy judgements (see the single dimension model in Fig. 1). Since both confidence ratings and recognition judgements are made using the same information, they can be used to predict each other. In this

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Fig. 1. Two models of the confidence and accuracy relation. Adapted from Busey et al. (2000).

case, consumers should be very confident when accurate, and not at all confident when inaccurately recognising information. The role of accessibility in choice has been investigated by manipulating vividness (Herr et al., 1991), retrieval cues (Keller, 1987; Tybout et al., 1981), interference (Keller, 1987) and frequency (Menon et al., 1995). It is important to note, however, that in these studies confidence is not measured, and incorrectly retrieved information is not included in the analyses. The relationship between recognition accuracy and recognition confidence is unclear in a consumer context. It is proposed here that encoding instructions affects memory strength which, in turn, affects both recognition accuracy and recognition confidence, while domain-specific knowledge affects memory certainty which, in turn, affects recognition confidence and the use of the information in choice.

2. The determinants of recognition accuracy and confidence 2.1. Task at study 2.1.1. Recognition accuracy One of the cornerstones of cognitive psychology is that processes that occur during encoding influence the ability to retrieve information later (Craik and Lockhart, 1972; Hunt and Einstein, 1981; Tulving and Thomson, 1973). Encoding affects retrieval because elaboration occurs during encoding, and cues in the encoding environment affect accessibility. In the material appropriate processing (MAP) framework, people learn information by considering each fact independently (individual-item processing), or by comparing new information with other information either in the learning environment or in memory (relational processing). In a marketing context, individual-item processing occurs when consumers are accumulating knowledge about brands, while relational processing occurs when consumers are evaluating or comparing brands. Although each type of processing facilitates learning and memory for information, memory performance on a recognition test, which is used in

the study presented here, improves with individual-item processing (Einstein and Hunt, 1980; Hunt and Einstein, 1981; McDaniel et al., 1988; Meyers-Levy, 1991). Individual item processing focuses on how each item is different or distinct from other items. Distinctiveness has been demonstrated to improve recognition in other paradigms as well (Guynn and Roediger, 1995; Tulving, 1969; Wallace, 1965). The first hypothesis is, therefore, a replication hypothesis. Hypothesis 1: Recognition will be more accurate when individual-item processing instructions, versus relational instructions, are provided at encoding. 2.1.2. Recognition confidence Individual-item processing encourages the encoding of information that differentiates an item from others in memory (Hunt and Einstein, 1981; Roediger and Guynn, 1996). When consumers are asked to try and recognise information learned with individual-item instructions, they should be more confident because the task at study has facilitated the type of memory necessary for the task at test. The extended cue utilisation theory would predict that the consistency between the task and the test should result in a greater level of confidence in recognition responses. Hypothesis 2: Individual-item processing instructions versus relational processing instructions will result in higher recognition confidence scores. 2.2. Knowledge level 2.2.1. Recognition accuracy Individuals with more domain knowledge can recall more newly learned information than lower knowledge individuals (Alba, 1963; Alba and Hasher, 1983; Ausubel and Fitzgerald, 1963; Chiesi et al., 1979; Voss et al., 1980), particularly when they can use their prior knowledge to organise new information (Srull, 1983). The results for recognition performance are not as clear. The dramatic differences in recall between knowledge levels are attenu-

E. Cowley / Journal of Business Research 57 (2004) 641–646

ated in recognition and, in some cases, disappear (Alba et al., 1981; Chiesi et al., 1979; Zeitz, 1994). Consumer researchers have demonstrated that low-knowledge consumers (LKCs) use explicitly stated goals or usage situations (Huffman and Houston, 1993) to identify differences between items, and are more likely to consider each fact independently (Alba and Hutchinson, 1987; Srull, 1983). Since LKCs tend to process each new statement independently, an encoding style that facilitates recognition, and high-knowledge consumers (HKCs) have a propensity to reorganise information (Srull, 1983), focusing on the gist of the information (Zeitz, 1994), any advantage resulting from more knowledge in the domain will be attenuated. Although HKCs may have a small advantage in recognition performance, knowledge level is not expected to influence recognition performance. 2.2.2. Recognition confidence HKCs are more likely to elaborate on information during encoding (Robertson, 1996; Zeitz, 1994). Elaboration can result in overconfidence because individuals tend to become more confident with the addition of their own inferential reasoning (Wagenaar, 1988). In addition, HKCs are aware that they know a lot about a product category, as is evidenced by the reported significant correlation between subjective and objective measures of expertise (Mitchell and Dacin, 1996). Hence, HKCs are more likely to be confident in their ability to retrieve information (Cowley, 1997). In which case, they may be aware that they are able to more effectively learn information in that same product category. Busey et al. (2000) suggest that a person’s belief that they are knowledgeable ‘‘do[es] not or cannot influence the recognition judgment but give[s] the illusion of accuracy and thus affect[s] confidence’’ (p. 30). Hypothesis 3: Individuals with more domain-specific knowledge will be more confident in their ability to recognise brand information than individuals low in domainspecific knowledge.

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Fig. 2. The hypothesised relationships between retrieval confidence, retrieval accuracy and choice.

the information they most confidently retrieve from memory in their decisions. Hypothesis 4: The probability of choice will increase with recognition confidence. Although there will be a relationship between recognition accuracy and choice, the relationship will be completely mediated by recognition confidence. The hypothesised relationships are shown in Fig. 2.

4. Method Eighty-four undergraduate students participated in the study in exchange for course credit in an introductory marketing course. The sample was 56% male and 44% female. There were two encoding instruction conditions (individual-item, relational). The encoding conditions were manipulated within subject and domain-specific knowledge level was measured. Subjects were exposed to eight brand – attribute statements in each encoding condition. Each of the 16 statements included a different brand and different attribute to reduce inference generation. After a 10-min filler task, subjects participated in a recognition test, a forced choice decision task and a knowledge questionnaire. Subjects were debriefed and thanked for their participation. 4.1. Materials

3. Choice 3.1. Recognition confidence In the extended cue utilisation model, accuracy and confidence are both affected by memory strength, therefore accuracy should have some ability to predict confidence. The degree to which accuracy predicts confidence is expected to be positive and significant. Attitude confidence serves as a ‘‘psychological gatekeeper of sorts, systematically determining whether people translate their beliefs into action (e.g. Berger and Mitchell, 1989; Fazio and Zanna, 1978; Pieters and Verplanken, 1995)’’ (Swann and Gill, 1997, p. 747). If recognition confidence has the same property then consumers will use

4.1.1. Brand names Hypothetical brand names were used to avoid familiarity effects on recognition that could occur with existing brand names. The brand names are five-letter nonsense words. The names were selected from a larger pool because they were found in pretests not to have associations with any existing brand name or to differ significantly in accessibility. 4.1.2. Attribute statements Eight to 10 word statements were selected from promotional materials such that LKCs would understand how the attribute would affect camera performance. For example, ‘‘Brand X has an automatic shutterlock to avoid accidental exposures.’’

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4.2. Encoding instruction condition The MAP processing instruction provided during study varies dramatically from study to study. Individual-item tasks have ranged from pleasantness ratings (Hunt and Einstein, 1981; Hunt and Seta, 1984; Hunt et al., 1986; McDaniel et al., 1988), to imagery (Marschak and Hunt, 1989; Marschak and Surian, 1992; Meyers-Levy, 1991). Relational tasks have ranged from using advance organisers (McDaniel, 1984) to categorising the items, either mentally (Meyers-Levy, 1991), or with sorting and comparison rating tasks (McDaniel et al., 1986, 1988). The encoding instructions used here are relevant to consumption settings. The individual-item encoding instructions was ‘‘Think for a moment about the brand and rate how much you like the brand,’’ on a 110-mm continuous scale anchored with ‘I do not like the brand’ and ‘I do like the brand’. The relational encoding instruction was ‘‘Compare the brand to other brands that you have seen on the screen and rate whether it is better or worse than the other brands,’’ on a 110-mm continuous scale anchored with ‘One of the best brands’ and ‘One of the worst brands’. [To check that the manipulations induced the appropriate type of processing, 21 undergraduate students read either relational or individual-item instructions before they read four of the brand – attribute statements used in the study. They indicated agreement on a sevenpoint scale to the following three statements: (1) I found myself comparing the brands during learning, (2) I thought about each brand independently during learning, and (3) I was thinking about how difficult the statements were to understand. The results indicate that there is a significant difference between the responses to the scales in both Section 1 [ F(1,20) = 17.13, P < .0001, individual-item = 1.95, relational = 5.02], and Section 2 [ F(1,20) = 32.71, P < .0001, individual-item = 5.58, relational = 1.87].] The order of the encoding condition was counterbalanced such that each brand – attribute statement was seen with both encoding conditions. There were no order effects. 4.3. Recognition test Subjects saw 16 statements: eight from the study lists, and eight new statements. Subjects indicated whether they had seen the statement before with a yes/no response, and recognition confidence on a 50-mm continuous scale anchored with ‘‘very sure’’ and ‘‘not at all sure.’’ 4.4. Choice Subjects then made eight choices. Each choice required the subject to choose between a pair of brands. The scale was developed to force a comparison between brands, and to allow subjects a choice between: (1) indicating the magnitude of their preference for one of the brands, and (2) indicating that on the basis of the information accessible for the choice, the brands were essentially indistinguishable.

In each case, subjects indicated their brand preference on a continuous scale anchored with a brand on either end. One brand was processed with relational instructions and the other with individual-item instructions. The pairs of brands used in the choices were counterbalanced on three sets of choices. There was no effect for choice set. 4.5. Knowledge level assessment Subjects responded to both objective and subjective measures. The objective measure included multiple choice questions, terminology questions and brand name listing. The subjective measure included self-reported ratings of familiarity, product usage and product knowledge on 11point scales anchored with ‘expert’ and ‘novice’ for the product knowledge and familiarity measures, and ‘very frequently’ and ‘not at all frequently’ for the product usage measure. The coefficient alpha was .82 indicating an acceptable degree of internal consistency. All of the correlations between the individual objective and subjective measures were significant at P < .0001. The distribution of objective and subjective knowledge scores were approximately normal.

5. Results Hypothesis 1 states that participants will be more accurate in the individual-item processing condition. As expected, subjects were better able to recognise brand-attribute statements when they were encouraged to process each item individually. A simple regression run on recognition accuracy reveals a significant effect for processing condition (t = 2.90, p < .01). The hit rate in the individual-item condition (67%) was significantly higher than in the relational condition (54%). Also expected, the dramatic advantage in recall performance by HKCs reported elsewhere, is attenuated when the task is recognition. When knowledge is added to the regression processing condition remains significant (t = 2.79, p < .01), and as predicted knowledge level was not significant (t = 1.71, p=.09). Hypothesis 2 states that recognition confidence will be higher in the individual-item condition. Hypothesis 3 states that knowledge level will also influence recognition confidence with HKCs indicating more confidence than LKCs. A regression run on recognition confidence including processing condition, knowledge level and accuracy reveals a significant effect for processing condition (t = 5.02, p < .0001). Participants were significantly more confident in the individual-item condition (35.0 mm on a 50 mm scale) compared to the relational condition (30.1 mm). The relationship between knowledge and recognition confidence was positive and significant (t = 2.31, p < .05). Also interesting was that subjects were more confident when they believed that they had seen the statement before (yes = 33.9,

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no = 28.44, p < .0001). This finding is consistent with theories of recognition that include the use of a feeling of familiarity in the recognition judgement (Kinstch, 1967; Mandler, 1980; Tulving, 1976). When the feeling surpasses a threshold, the individual believes that they must have seen the item before. Finally, replicating previous research, accuracy was not significant (t = 0.14, p=.87). Hypothesis 4 asserts that there will be a relationship between recognition accuracy and choice, but that the relationship will be mediated by recognition confidence. Following the three steps outlined in Baron and Kenny (1986) to demonstrate mediation, a simple regression between recognition accuracy and choice reveals a significant effect for accuracy (t = 1.96, p.05), a simple regression between recognition confidence and accuracy shows a significant effect for accuracy (t = 5.43, p < .0001), and finally, a multiple regression on choice including both recognition confidence and accuracy reveals a significant effect for recognition confidence (t = 3.29, p < .001) and a non-significant effect for accuracy (t = 1.53, p=.13). Recognition confidence completely mediates the relationship between accuracy and choice.

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cipants in the study indicate their intended choice. Second, to control for previous attitudes toward a brand, the brand names used in the study were fictitious. It could be that HKCs would be more accurate in retrieving information from memory when real brand names are involved because it would allow for full use of their more elaborate knowledge structures. Third, learning did not occur over time and contexts; there might be many other influences on recognition confidence not explicitly tested here. Limitations aside, the study contributes by considering the role of accessible information in decision-making regardless of its accuracy. Consumers can be very confident that they have seen information about a brand earlier, when the information was actually associated with a different brand. This is important because recognition confidence plays an important role in choice. The implications of the results reported here are twofold. First, recognition confidence is an important measure when testing consumer memory. Second, consumers appear to use confidence as a proxy for accuracy, therefore encouraging consumers to focus on how the brand is different or distinct from other brands should improve recognition confidence and consequently increase the probability of the use of the information in choice.

6. Discussion of the results The results of this study demonstrate that recognition confidence is an important factor in choice. The results also indicate that recognition confidence is a function of both knowledge and the task at study, while recognition accuracy is a function of the task at study only. These results do not support the trace access theory, which suggests that confidence and accuracy be assessed by directly accessing a memory trace. Instead, the results are consistent with the accessibility hypothesis and the multidimensional model. There are many occasions when consumers may be using incorrect information in the subset of information used in choice. It appears that LKCs are better able to judge their accuracy in the individual-item condition, although they are less accurate in this condition. LKCs are actually more accurate in recognition, but not as confident when encouraged to compare across brands. For these consumers, it may be advised to encourage the consideration of individual facts. Of course, consumers need to compare the brands to make a decision, but the comparisons may be more effective after the information has been learned. HKCs are more confident than LKCs, without being more accurate. Although not tested here, this confidence may lead HKCs to confidently make decisions based on inaccurately recognised information.

7. Limitations and contributions There are some obvious limitations to the study. First, the choice task in this study was not an actual choice; parti-

Acknowledgements This research was funded by an ARC Grant 02440-7220, and the School of Marketing at University of New South Wales, Sydney, Australia.

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Emotion and reason in persuasion $ Applying the ARI model and the CASC Scale Ross Bucka,*, Erika Andersonb, Arjun Chaudhuric, Ipshita Rayc a

Communication Sciences U-1085, University of Connecticut, Storrs, CT 06269-1085, USA b University of Southern Maine, Portland, ME, USA c Fairfield University, Fairfield, CT, USA

Abstract Whereas practitioners in advertising and marketing clearly appreciate the importance of affect and emotion, traditional academic approaches to the analysis of persuasion tend to stress rational ‘‘central route’’ or ‘‘systematic’’ processing. However, the notion of two sorts of cognitive process—one rational, the other affective—has gained increasing support. This paper presents a view of the conceptualization and operationalization of the interaction of affect and reason based upon MacLeans’s triune theory of the brain, distinguishing reptilian, individualist and prosocial biological emotions, as well as ‘‘higher level’’ social, cognitive and moral emotions. The interactive role of affect and reason in involvement is described by the affect – reason – involvement (ARI) model, and emotions are operationalized by versions of the Communication via Analytic and Syncretic Cognition Scale (CASC Scale) tuned to the requirements of a given area of investigation. Examples of studies analyzing emotional factors in response to common consumer products and condom use/nonuse are presented. D 2002 Elsevier Inc. All rights reserved. Keywords: Emotion; Reason; Advertising; Persuasion

1. Introduction Traditional academic models of attitude change and persuasion typically approach their subject matter from ‘‘cold,’’ rational, analytic – cognitive points of view. Even those specifically attempting to deal with the role of emotion in persuasion tend to view the ‘‘central route’’ involving analytic cognition as the subject of ultimate interest and emotion as a ‘‘peripheral’’ factor at best. However, inspection of a few television commercials is enough to convince an objective observer that advertising and marketing professionals are well aware of the importance of emotion in the practical realm of persuasion. Arguably, the global village associated with new electronic media has greatly increased the importance of emotion in persuasion. At the same time, in the academic realm, advances in the neurosciences and in the study of nonverbal – emotional commun-

$ Presentation at the Fourth International Research Seminar on Marketing Communications and Consumer Behavior La Londe les Maures (French Riviera), June 5 – 8, 2001. * Corresponding author. Tel.: +1-860-486-4494; fax: +1-860-486-5422. E-mail address: [email protected] (R. Buck).

0148-2963/$ – see front matter D 2002 Elsevier Inc. All rights reserved. doi:10.1016/S0148-2963(02)00308-9

ication have made possible a new level of specificity in the definition of emotion. This paper seeks to apply the newfound academic understanding of emotion and nonverbal communication to the practical realm of marketing communication and persuasion. It addresses the persuasion process in general, and marketing communication in particular, from the viewpoint of the affect – reason – involvement model (ARI model), which defines and describes the relationships between affect, reason and involvement, arguing that both emotional and rational involvement are important in attitude change and persuasion. ‘‘Affect’’ (also termed Emotion III) is defined as the subjective aspect of ‘‘emotion’’ in Developmental Interactionist Theory (Buck, 1985, 1999). That is, emotion is seen to have three aspects, arousal (Emotion I), expression (Emotion II) and subjective experience (Emotion III or affect). Emotional involvement is based upon holistic syncretic cognition, while rational involvement is based upon linear and sequential analytic cognition. Affect is operationalized using the Communication via Analytic and Syncretic Cognition Scale (CASC), developed to capture both analytic rational knowledge and a large number of varieties of syncretic – affective knowledge. That is, the CASC Scale

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is designed with the potential to assess a wide variety (potentially hundreds) of emotions, including biological emotions and many ‘‘higher-level’’ social, cognitive and moral emotions distinguished in recent theoretical analyses (see Buck, 1999). Biological emotions include reptilian emotions (eroticism and power), fearful individualistic emotions (fear, nervous, uncomfortable and unsure), angry Individualistic emotions (angry, insulted and selfish), positive individualistic emotions (confident, secure and satisfied), negative prosocial emotions (guilty, ashamed and embarrassed) and positive prosocial emotions (intimate, loving/loved and caring). Social emotions (e.g., pride, guilt, shame, pity, jealousy) are conceptualized as being based biologically upon prosocial attachment needs and cognitive emotions as being based biologically upon curiosity and interest. Moral emotions are seen as being based upon both cognitive and social emotions, involving the understanding of rules and the judgment that they should be followed. In the research described in this paper, the ARI conceptualization and CASC Scale were applied to studying the beliefs and emotions associated with common consumer products, and with safe sex and condom use. In this research, the CASC Scale was developed into the Brief-CASC, an efficient form applicable to consumer research, and the Safe Sex Communication Scale (SAFECOM) centered on emotions involved in sexual behavior. More recently, a version of CASC termed the Competence – Credibility –Compassion –Charisma Scale (C4 Scale) has been developed to focus upon emotional involvement in the perception of leadership, in a study of the 2000 Presidential election campaign in the US (Buck and Vieira, 2001). This introductory section considers (a) the treatment of emotion and reason in persuasion theory and research, (b) the conceptualization and operationalization of involvement and (c) specific definitions of affect, reason and involvement. It concludes with a description of an application of the ARI model using the Brief-CASC Scale to analyze emotion and reason associated with familiar consumer products.

2. Emotional and rational cognition 2.1. Hot, cold and indifferent: emotion and persuasion research Emotion is a ‘‘hot topic’’ in the social and behavioral sciences, due in part to new capabilities to observe and measure emotional phenomena. These developments have greatly increased the ability to measure emotion in its various manifestations. In particular, the study of ‘‘subjective’’ affective phenomena has long been eschewed by many behavioral scientists because of the apparent impossibility of objective measurement. The new developments in measuring activities of central neurochemical systems put the study of such events on a newly objective basis (Buck, 1993, 2000). Indeed, affect can be defined explicitly in

terms of potentially observable neurochemical systems, leading to the possibility of an affective neuroscience (Buck, 1985, 1999; Panksepp, 1993, 1998). 2.1.1. Two-factor theories and persuasion ‘‘Two factor’’ models of persuasion have recognized that emotion plays a role of in attitude change. The present model suggests instead that there are in effect two persuasion processes that take place simultaneously and interactively: a rational influence process involving analytic cognition that works much as conventional theories in attitude change envision, and an emotional influence process involving a qualitatively different sort of cognition. Emotional cognition involves memory and processing systems that are separate from those of analytic cognitive processing, are organized differently and obey different rules. Moreover, emotional and rational persuasion are associated with two qualitatively different but simultaneous and interacting ‘‘streams’’ of communication: spontaneous and symbolic communication, respectively (Buck, 1984). 2.1.2. Affect as syncretic cognition Based upon neuropsychological theory and research, Tucker (1981) distinguished two sorts of cognition. Syncretic cognition is ‘‘hot,’’ direct and immediate, while analytic cognition involves ‘‘cold,’’ sequential and linear information processing. He related the distinction between analytic and syncretic cognition to processing modes characteristic of the left and right cerebral hemispheres, respectively. Tucker’s distinction is similar in many respects to that made by Le Doux (1994) between cortico-cognitive processes based on the hippocampus and neocortex vs. emotional processing involving the amygdala. Le Doux (1996) distinguished a ‘‘high road’’ and ‘‘low road’’ to cognition, showing that emotion-related structures associated with the amygdala receive input about events that is earlier than and potentially independent of input to relevant neocortical sensory systems. Furthermore, Le Doux outlined two central memory networks that operate simultaneously and in parallel: explicit or declarative memory, which involves the hippocampus, and implicit or emotional memory which involves the amygdala (1994, p. 312). The differentiation of analytic and syncretic cognition blurs the usual distinction between emotion and cognition: the subjective experience of emotion, or ‘‘affect,’’ becomes a type of cognition: a type of knowledge. In the present view, affect is defined as the direct knowledge of feelings and desires, based upon readouts of specifiable neurochemical systems evolved by natural selection as phylogenetic adaptations functioning to inform the organism of bodily events important in self-regulation (Buck, 1985, 1994, 1999). Human beings experience affects immediately and directly, the phenomenological subjective reality of affect is self-evident. Among the strongest and most fundamental of affects is, of course, sex.

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2.1.3. Prosocial affects Theories of emotion emphasize ‘‘individualistic’’ emotions associated with individual survival, and often ignore sex and other ‘‘prosocial’’ emotions associated with species survival posited in MacLean’s (1993) Triune Theory of the brain. Recent studies have supported MacLean’s approach, in that they have focused upon neurobiological systems that regulate social organization involving attachment and bonding (see Buck, 1999; Carter et al., 1997; Panksepp, 1993). The subjectively experienced affects associated with these systems appear to involve specific neurochemicals including serotonin, oxytocin, gonadotropin releasing hormone and the endorphins. These participate in the regulation of a vast array of positive social behaviors involving feelings of erotic arousal, intimacy, caring, playfulness and love. 2.2. Conceptualizing affect, reason and involvement: the ARI model The notion that persuasion involves parallel and interactive processes of affective and rational influence is at the heart of the ARI model of persuasion. The ARI model describes the relationship of affect and reason with one another and with involvement (Buck and Chaudhuri, 1994; Chaudhuri and Buck 1995a,b, 1998). 2.2.1. The A/R continuum The relationship between affect and reason is expressed by Fig. 1. Affective persuasion is associated with spontaneous communication and rational persuasion with symbolic communication (Buck, 1984). The continuum at the base of Fig. 1 is the affect/reason continuum (A/R continuum). It describes the mix of affective and rational persuasion, and therefore also the mix of spontaneous and symbolic communication. At the left of the continuum, the influence of affect is total: reason has no influence. This is the case of pure spontaneous communication. As one goes to the right, reason exerts an increasing influence relative to affect, but affective influence never falls to zero. Attitude objects and messages can be placed on the A/R continuum, reflecting the ratio of affect to reason in the possession and use of that object, or in the message advocating such possession and use (Chaudhuri and Buck, 1993).

Fig. 1. The A/R continuum.

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Fig. 2. The ARI (affect – reason – involvement) solid.

2.2.2. Level of involvement Chaudhuri and Buck (1993) define involvement conceptually following Batra and Ray (1983) as the ‘‘depth and quality of cognitive response’’ (p. 309), but suggest that both affective and rational involvement are possible, constituting the depth and quality of syncretic and analytic cognitive responding, respectively. This can refer to a temporary state, to a general disposition to respond, and/ or to the tendency of an attitude object or message to ‘‘pull out’’ affective or rational responses in people. Given this definition, we suggest that the level of involvement (LI) can be defined operationally as the average of affective and rational involvement: that is, LI=(A + R)/2. In this way, involvement is defined both conceptually and operationally as a combination of affective and rational cognitive processing: if cognitive processing is measured, involvement is measured by definition. This suggests that one can be ‘‘hot, cold or indifferent’’ in response to attitude objects and messages. ‘‘Hot processing’’ is high in affect (high A/R ratio) and high in involvement, ‘‘cold processing’’ is high in reason (low A/R ratio) and high in involvement, ‘‘indifference’’ is low in affect and reason, and low in involvement. 2.2.3. The ARI solid The ARI solid models the relationships between affect, reason and involvement. The ARI solid is a three-dimensional figure bounded on one side by a low-high LI dimension and on the other by the A/R continuum (see Fig. 2). An ARI slice, in which the relative influence of affect and reason remains constant as involvement varies, represents the relative influence of affect and reason at any point on the A/R continuum. The ‘‘floor’’ of the ARI solid is a two-dimensional space with an involvement dimension on the y-axis and the A/R continuum on the x-axis (Fig. 3A). LI and the A/R ratio represent the position of an object on this floor. The floor of the ARI solid is similar in form to the Foot, Cone and Belding grid (FCB grid; Fig. 3B), which contrasts high and low involvement with ‘‘feel’’ and ‘‘think’’ categories (Vaughn, 1980, 1986).

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2.2.5. Evaluation and the ARI model The ARI model aims to conceptualize and measure how attitude objects and messages are cognitively processed, and the level of involvement as defined by the depth and quality of this processing. It provides a representation of the depth of thought and feeling about an object or message. Again, this can be conceptualized in several ways: as a temporary state affected by the situation, an enduring tendency of a person to respond carried across situations and/or the tendency of an object or message to ‘‘pull out’’ a mix of rational and emotional responding in people. The Brief-CASC Scale was designed with the latter in mind: assessing attitude objects. However, the ARI model does not in itself represent evaluation: whether the object or message is liked or disliked, approached or avoided, loved or loathed. The position of an object or message at any point in time may thus be described in three dimensions: LI, A/R ratio and evaluation. This paper concentrates on the former two dimensions. 2.3. Measuring affect and reason: the CASC Scale

Fig. 3. The floor of the ARI solid (A) and the FCB grid (B).

2.2.4. Affective and rational responses to consumer objects: the Brief-CASC Scale Chaudhuri (1993) tested the usefulness of this conceptualization to the analysis of the processing of consumer products. He developed three-item scales from the McQuarrie and Munson (1987) modification of the Zaichkowsky Personal Involvement Inventory: three ‘‘risk’’ items comprised the measure of analytic cognition and three ‘‘hedonic’’ items comprised the measure of syncretic cognition. The analytic items were: ‘‘Not risky vs. risky,’’ ‘‘Easy to go wrong vs. hard to go wrong’’ and ‘‘Hard to pick vs. easy to choose.’’ The syncretic items were: ‘‘Appealing vs. unappealing,’’ ‘‘Unexciting vs. exciting’’ and ‘‘Fun vs. not fun.’’ This ‘‘Brief-CASC Scale’’ was used to assess affective and rational responses to 30 consumer objects ranging from cars and computers, to candy and paper products, to insurance policies (Buck et al., 1995). As expected, affectively loaded objects had high A/R ratios, while objects to be dealt with ‘‘mindfully’’ had low A/R ratios. For example, candy and snack foods had high A/ R ratios (1.36 and 1.43, respectively), automobiles, airline services and paper products had and relatively balanced in A/R scores (1.18, 1.00 and 0.90), and appliances, insurance policies and laundry products had low A/R ratios (0.59, 0.44 and 0.77). At the same time, candy and insurance had relatively high LI scores (3.99 and 4.00), suggesting hot and cold processing, respectively, while paper products had a low LI score (2.60), suggesting indifference.

Affect is usually thought of as undifferentiated relative to reason, but the measurement of affect can be highly specific, involving for example, happiness, anger, eroticism and shame (Buck, 1999). MacLean’s (1993) Triune Theory of the brain suggests that there are reptilian emotions involving ‘‘raw’’ sex and aggression (eroticism, power) based upon subcortical parts of the brain. Paleocortical (limbic system) areas are associated with more complex motivational – emotional systems: individualistic emotions involving selfpreservation (anger, fear) and prosocial emotions involving species preservation (love, caring, intimacy). The prosocial emotions serve as the biological basis of a range of higherorder social emotions, including embarrassment, guilt and shame. The individualistic emotions serve as the biological basis for higher-order cognitive emotions involved in the structuring of the cognitive system (curiosity, surprise, interest, boredom), including emotions such as confidence, security and satisfaction (see Buck, 1988, 1999). These specific emotions can be assessed by the CASC Scale, which can be modified to fit those emotions relevant to a specific area of study.

3. The SAFECOM Scale: application to the study of condom use/nonuse 3.1. Persuasion and HIV/AIDS prevention Conventional persuasion campaigns have succeeded in convincing many if not most in the target audience about the importance of condom use in preventing AIDS and other STDs. However, these messages have often been unsuccessful in altering behavior (Baldwin et al., 1990; DeBro et al., 1994), and there is little evidence that knowledge about HIV/AIDS and its prevention increases condom use

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(DiClemente, 1991; Valdiserri et al., 1989; Rikert et al., 1989). In a meta-analysis of 26 cross sectional studies, Gerrard et al. (1996) concluded that there is ‘‘virtually no support for the hypothesis that perceptions of vulnerability to HIV/AIDS motivate subsequent precautionary sexual behavior’’ (p. 398). We suggest that the consideration of emotional factors may be useful in the promotion of safe sex behavior. Conventional methods of public service communicationbased as they are upon assumptions of rational judgment— may not be adequate in meeting the hazard of the pandemic of HIV/AIDS and other STDs. Sex is hot: it is rarely cold and never indifferent. To explore this, the CASC Scales were applied to the analysis of the emotions and perceptions involved in the purchase and use or nonuse of condoms in specific personal relationships varying in exclusivity. 3.2. Emotions, condom use/nonuse and relationship exclusivity As noted, the CASC Scale can be modified to fit a specific area of study, and the SAFECOM Scale was developed from the CASC Scale to assess emotions particularly relevant to safe sex. Based upon MacLean’s (1993) theory, we used 18 emotion items expecting six emotion clusters to emerge (Buck, 1999). Reptilian emotions included erotic and power; fearful individualistic emotions included fear, nervous, uncomfortable and unsure; angry individualistic emotions included angry, insulted and selfish; positive individualistic emotions included confident, secure and satisfied; negative prosocial emotions included guilty, ashamed and embarrassed, and positive prosocial emotions included intimate, loving/loved and caring. Each of the 18 emotions was measured by a seven-point scale anchored on the left by Not at all and on the right by Very. Also, the questionnaire explicitly included relational exclusivity in questioning Ss about condom use or nonuse. 3.3. Hypotheses 3.3.1. Relational exclusivity We expected that the exclusivity of the relationship would have a major impact upon feelings about condom use, with fears of HIV/AIDS and other STDs being mitigated to the extent that the relationship is perceived as being exclusive. We operationally defined levels of increasing exclusivity by the three sorts of relational context: from a ‘‘one-night-stand’’ to a ‘‘person you know’’ and are considering dating exclusively, to a partner in a long-term ‘‘monogamous’’ relationship. 3.3.2. Reptilian rewards The SAFECOM Scale explicitly asked participants about the reptilian emotions: feelings of eroticism and power. We expected that these feelings play an important role in the motivation for condom use/nonuse, and specifically that

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condom nonuse would be associated with higher feelings of both eroticism and power. 3.3.3. The ASP hypothesis Based upon research and theory regarding gender differences in evolutionary sexual strategies as well as cultural gender roles, we expected reported feelings of anger, selfishness and power to differ for women and men. Specifically, we expected that condom use would elicit feelings of higher anger and lower selfishness and power among men than women, and that nonuse of condoms would elicit the opposite patterns. This was the anger – selfishness –power (ASP) hypothesis. 3.4. Participants, materials and design Participants were 188 undergraduates from three universities in the northeastern United States, including 95 males, 86 females and 7 unknown/missing data. The anonymous questionnaire was administered in classroom settings. The questionnaire initially asked about knowledge about HIV/ AIDS and condoms, and related beliefs, attitudes, perceived risks, behavior intentions and behaviors. The SAFECOM Scale then asked how ‘‘a person would feel’’ (1) discussing condoms with a new sexual partner, (2) purchasing a condom and (3) using or not using a condom within sexual relationships of three levels of exclusivity: a ‘‘one-nightstand,’’ an ‘‘acquaintance’’ and a ‘‘long-term partner.’’ A total of 18 emotions were assessed for each of these situations, with one situation per page for a total of eight pages. These latter, SAFECOM data are the subject of the present analysis. 3.5. Results: feelings about condom use or nonuse across relationships 3.5.1. Structure of emotions Exploratory factor analysis was used in a confirmatory manner to analyze emotion structure. Results indicated that ratings of how ‘‘a person would feel’’ discussing condom use with a new sexual partner produced a factor structure consistent with MacLean’s (1993) theory. Results from a replication study conducted at the University of Hyderabad to the same question produced a factor structure closely comparable to that produced with American participants (Kowta, 1996). The combined factor structure is presented in Table 1. For each of the emotions, data on feelings about condom use/nonuse were examined by 2(2  3) mixed model analyses of variance, with gender of participant crossed with repeated measures on condom use/nonuse and relationship. Results indicated many significant effects with effect sizes ranging from small to quite large. The meanings of significant main effects were often tempered by strong interactions. In the following, main effects are discussed first, followed by the interaction effects, organized by emotion type. Effect sizes

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Table 1 Affect structure associated with how a person would feel discussing condom use with a new sexual partner (SAFECOM version of CASC) Affect

Positive Negative Positive Negative prosocial prosocial individualist individualist Reptilian

Loving/loved .89 Caring .74 Intimate .71 Afraid Nervous Ashamed Embarrassed Guilty Uncomfortable Satisfied Confident Secure Selfish Insulted Angry Unsure Powerful Erotic

.86 .83 .72 .67 .65 .57

.51 .75 .74 .65 .78 .68 .66 .64 .78 .71

Only factor loadings above .50 are illustrated.

(h’s) are given to illustrate the strength of the different effects and to convey something of their relative importance. 3.5.2. Relationships and emotions Main effects indicated that, overall, the increasing exclusivity of relationships was strongly associated with increased positive and decreased negative emotion ratings. Effect sizes were generally high (median h=.68). 3.5.3. Condom use and emotions Main effects indicated that, overall, condom nonuse compared to use was associated with higher ratings of all of the angry and fearful individualistic emotions and the negative prosocial emotions, with high effect sizes (median h=.72). Regarding positive individualistic emotions, condom nonuse was associated with lower ratings of secure and confident (h’s=.73 and .56, respectively). For positive prosocial emotions, condom nonuse was associated with lower ratings of caring (.26), but higher intimacy (.39). As expected from the ‘‘reptilian rewards’’ hypothesis, condom nonuse was associated with higher ratings on reptilian emotions, weakly with power (h=.15, P=.042) and strongly with erotic (h=.54, P < .001). 3.5.4. Negative prosocial emotions Negative prosocial emotions (feeling ashamed, embarrassed and guilty) showed the following pattern, illustrated for ‘‘ashamed’’ in Fig. 4A. When condoms were used, these emotions were low levels across relationships, but when condoms were not used these emotions were high levels in ‘‘one night stands’’ decreasing, as the relationship became more exclusive. The linear components of interactions between condom use and relationship were highly significant in all cases (h=.69 for shame, h=.52 for embarrassment,

h=.67 for guilt; all P’s < .001). Women reported generally higher levels of the negative prosocial emotions. These emotions also showed significant interactions between gender and condom use. Women reported higher levels of shame, embarrassment and guilt relative to men when condoms were not used (h=.23 for shame, h=.17 for embarrassment, h=.17 for guilt; all P’s < .03). Moreover, for less exclusive relationships, women reported relatively higher levels of shame and embarrassment than did men (h=.21 for shame, h=.20 for embarrassment; P’s < .02). 3.5.5. Fearful individualistic emotions Fearful individualistic emotions (feeling afraid, nervous and uncomfortable) showed a pattern similar to those of the negative prosocial emotions. Significant main effects indicated that, overall, these emotions were stronger when condoms were not used. When condoms were used, these emotions were at relatively low levels across relationships. However, when condoms were not used, these emotions showed high levels in ‘‘one night stands,’’ which decreased dramatically as the relationship became more exclusive. The linear components of interactions between condom use and relationship were highly significant in all cases (h’s for fear=.61, for nervous=.58, for uncomfortable=.46; all P’s < .001). Women reported higher overall feelings of nervousness and discomfort, but not of fear. Unlike nervousness and discomfort, fear showed a significant interaction between gender and condom use. Women reported higher levels of fear than men did when condoms were not used, but less when they were used (h=.21, P=.007). 3.5.6. Angry individualistic emotions The angry individualistic emotions (feeling angry, unsure, insulted and selfish) showed a pattern generally similar to that of the negative prosocial emotions, illustrated for anger in Fig. 4B. Again, as noted significant main effects indicated that all of these emotions were stronger when condoms were not used, but there were highly significant interactions with relationship exclusivity. When condoms were used, these emotions were at relatively low levels, but when condoms were not used, they showed high levels in ‘‘one night stands’’ that decreased, as the relationship became more exclusive. Again, the linear components of interactions between condom use and relationship were highly significant (h=.61 for anger, h=.50 for unsure, h=.48 for insulted, h=.35 for selfish; all P’s < .001). Again as noted, main effects indicated women to report feeling more insulted and unsure than men. These emotions and anger also showed significant interactions between gender and condom use. When condoms were not used, women relative to men reported higher levels of anger, being unsure and insulted (h=.26 for anger, h=.16 for unsure, h=.18 for insult; all P’s < .04). Also, for the less exclusive relationships, women reported relatively higher levels of anger and being unsure (h=.16 for anger, h=.16 for unsure; P’s < .04).

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Fig. 4. Emotional responses to using or not using condoms in one-night-stand, acquaintance and long-term relationships.

3.5.7. Positive individualistic emotions Reports of feeling secure, confident and satisfied generally showed a ‘‘mirror image’’ of the pattern shown with the fearful, angry and negative prosocial emotions, illustrated for secure in Fig. 4C. As noted, significant main effects indicated that security and confidence were stronger when condoms were used, but the main effect for satisfaction was not significant, and indeed the tendency was in the opposite direction. Inspection of the data revealed that this was primarily due to males’ greater reported satisfaction associated with condom nonuse. Highly significant interactions indicated that, when condoms were used, these emotions were at relatively high levels, but when condoms

were not used, they showed low levels in ‘‘one night stands’’ that increased, as the relationship became more exclusive. The linear components of interactions between condom use and relationship were again highly significant in all cases (h=.54 for secure, h=.49 for confident, h=.44 for satisfied; all P’s < .001). Similarly, the positive individualistic emotions showed significant interactions with gender. When condoms were not used, women reported relatively lower levels of confidence and satisfaction relative to men (h=.22 for confidence, h=.19 for satisfaction; P’s < .02). Also, for the less exclusive relationships, women reported relatively lower levels of security and satisfaction (h=.18 for security, h=.24 for satisfaction; P’s < .02).

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3.5.8. Positive prosocial emotions The positive prosocial emotions (feeling loving/loved, caring and intimate) increased as relationships became more exclusive, illustrated for intimacy in Fig. 4D. As noted, main effects indicated that rated caring was stronger when condoms were used, but rated intimacy was stronger when condoms were not used, and the main effect for feeling loving/loved was not significant. In the less exclusive relationships, these emotions were at roughly equivalent levels whether condoms were used or not used, but in the long-term relationship these emotions were consistently higher, for both females and males, when condoms were not used. Again, the linear components of interactions between condom use and relationship were highly significant in all cases (h=.33 for loving/loved, h=.40 for caring, h=.44 for intimate; all P’s < .001). Positive prosocial emotions showed no significant interactions between gender and condom use: both for females and males, loving, caring and intimacy tended to be higher in the long-term relationship when condoms were not used. For the less exclusive relationships, women reported relatively lower levels of loving/loved and caring relative to men (h=.18 for loving/ loved, h=.24 for caring; P’s < .02). 3.5.9. Reptilian emotions: eroticism Results for erotic emotions are illustrated in Fig. 4E. As noted, these increased as relationships became more exclusive, erotic feelings were stronger when condoms were not used, and males reported generally higher erotic feelings. Both the linear and quadratic components of the interactions between condom use and relationship were significant in eroticism (h=.26, P=.001 for linear; h=.42, P < .001 for quadratic), indicating that erotic feelings were relatively higher with condom nonuse in the one-nightstand and long-term relationships, particularly the latter. The ratings of erotic feelings showed no significant interactions between gender and condom use or gender and relationship exclusivity. 3.5.10. Reptilian emotions: power Results for power are illustrated in Fig. 4F. As noted, ratings of power increased slightly as relationships became more exclusive, and feelings of power were marginally stronger when condoms were not used. As with eroticism, both the linear and quadratic components of the interactions between condom use and relationship were significant in power (h=.17, P=.031 for linear; h=.29, P < .001 for quadratic), indicating that feelings of power were relatively higher with condom nonuse in the one-night-stand and long-term relationships, particularly the latter. As expected, power ratings showed a significant interaction between gender and condom use/nonuse: females indicated relatively greater power when condoms were used and males indicated relatively greater power when condoms were not used (h=.26, P=.001). This finding is relevant to the ASP hypothesis.

Fig. 5. Gender differences in anger ratings related to condom use/nonuse.

3.5.11. The ASP hypothesis The finding that power was higher for men when condoms were not used and higher for women when condoms were used was consistent with the ASP hypothesis. Examination of the data revealed that ratings of anger were also consistent with expectations: men reported more anger than women when a condom was used and women reported being more angry when it was not used (see Fig. 5). Ratings of selfishness did not however show the expected pattern.

4. Discussion 4.1. Summary To summarize the major findings, results using the SAFECOM scale indicate that positive emotions are high and negative emotions low when condoms are used; when condoms are not used these emotions vary widely with the exclusivity of the relationship. Also, feeling erotic, powerful and intimate are higher when condoms are not used. Finally, when condoms are not used feelings of power are higher for men than women and feelings of anger are higher for women than men. The pattern of results was noteworthy in several respects. First, as a general point, the very strong relationships between reported emotions, relationship exclusivity and condom use/ nonuse reflected in the high effect sizes are consistent with the notion that emotional variables exert important influences on the decision to use or not use condoms. A second noteworthy result concerns the intricacy and subtlety of the influence of specific emotions, including reptilian and prosocial emotions not often recognized in many contemporary emotion theories. As expected, both men and women perceived condom nonuse to be associated with higher reptilian emotions of eroticism and power, but the complex results concerning positive prosocial emotions was not expected. That is, condom use as opposed to nonuse was seen to be associated positively with caring feelings but negatively with intimacy, and loving feelings were not significantly associated with condom use/nonuse. Clearly,

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although condom use is associated with feelings of confidence and security, and lower negative emotions, condom use is also associated with significant emotional penalties as well. It is east to see how condom nonuse could occur when negative emotions are reduced by, for example, the effects of alcohol or other drugs. A related point concerns how the negative emotions associated with condom nonuse are almost entirely mitigated by perceptions that a relationship is exclusive. In this regard the finding of significant quadratic components in the Condom Use  Relationship interactions—indicating that erotic and powerful feelings were relatively higher with condom nonuse in the one-night-stand and long-term relationships—is particularly noteworthy. The ‘‘reptilian rewards’’ appear to be higher in precisely those relationships where the emotional costs of condom nonuse are likely to be mitigated: by the use of drugs/alcohol in the case of the one-night-stand and by the perception of exclusivity in the long-term relationship. This is a case in which specific messages might be targeted to warn of these situations of particular peril. A fourth point concerns gender differences in reported emotion. Overall, women reported feeling more insulted, unsure, nervous, uncomfortable, ashamed, guilty and embarrassed than men, and men reported feeling more satisfied, confident, loving, caring and erotic than women in responding to these questions. These results are generally consistent with expectations from both evolutionary and cultural approaches to gender differences, although as noted the effect sizes in these cases were low to moderate at best. More revealing were the interactions between gender and condom use, with women relative to men reporting greater feelings of shame, embarrassment, guilt, fear, anger, unsureness and insult, and lower feelings of confidence, satisfaction and power when condoms were not used. The interactions with anger and power were consistent with the ASP hypothesis, but it is clear that many other emotions evoked by condom use –nonuse are different in women and men. For example, it is noteworthy that men’s perceptions of high erotic feelings when condoms were not used were particularly strong in the less exclusive relationships. Again, this suggests a need for special messages directed to women and men to help facilitate accurate understanding and communication between women and men. A fifth point is that the positive prosocial emotions and erotic feelings did not show interactions with gender and condom use. Women and men agreed that, not only the ‘‘reptilian reward’’ of erotic feelings, but also the prosocial emotions of intimacy, loving and caring, are higher when condoms are not used in long-term relationships. These perceived emotional rewards associated with condom nonuse, and corresponding perceived emotional penalties associated with condom use, must be recognized and addressed. A specific implication is that there is a need for messages associating condom use with emotional rewards, including eroticism and intimacy as well as loving and caring.

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4.2. Implications One of the major conclusions of the present studies is that an emotion typology based upon brain theory and research worked successfully in an application to human persuasion (Chaudhuri and Buck, 1994). These basic emotion control systems are organized to respond rapidly and coherently, reflecting primal survival needs: thus, as noted, Le Doux (1994) found evidence that the amygdala is ‘‘involved in processing the emotional significance of simple sensory events’’ (p. 220), even in the absence of corticocognitive processing. The present studies demonstrate that these highly conserved neurochemical systems are intimately involved in the persuasion process in a way and to an extent that has not heretofore been appreciated. The neurological approach used here led us to emphasize the importance of emotions that are not widely recognized in contemporary emotion theory, but are arguably crucial in understanding human behavior, particularly behavior relevant to STDs and to political persuasion. Foremost among these are the reptilian emotions: ‘‘raw’’ sex and aggression. The importance of sex is assumed in many psychological theories and is palpable in much commercial advertising: its relative absence in contemporary emotion or persuasion theories is difficult to account for. It is useful to compare the ARI/CASC approach with other attempts to conceptualize and measure emotional and rational involvement, such as the FCB grid (Ratchford, 1997; Vaughn, 1980, 1986) and the Laurent and Kapferer (1985) consumer involvement profile (CIP). The FCB grid classifies purchase decisions into four quadrants: high involvement/thinking, low involvement/thinking, high involvement/feeling and low involvement/feeling. The CIP distinguishes five antecedent conditions producing involvement: personal interest, sign value, pleasure value, risk importance and risk probability (Kapferer and Laurent, 1993). These approaches tend to contrast ‘‘emotional’’ vs. ‘‘cognitive’’ factors, as with the FCB grid contrast of ‘‘feeling’’ vs. ‘‘thinking’’ and the CIP’s distinction between ‘‘pleasure’’ and other variables. The implication is that emotion and cognition are distinct, an assumption with deep roots in Western thought (Buck, 1988, 2000). In contrast, the ARI approach explicitly considers emotion/affect to be a type of cognition (syncretic cognition), and does not consider syncretic cognition to be in any way incompatible with analytic cognition. Indeed, empirically the two are highly correlated: Chaudhuri (1993) found that if participants report making rational distinctions about a product they also report gaining pleasure from it (r=.72). Moreover, the ARI approach does not conceptualize ‘‘involvement’’ as constituting a variable distinct from analytic and syncretic cognition: instead, involvement is defined as the combination of analytic and syncretic cognition: ‘‘involvement is composed of feeling and thinking’’ (Chaudhuri, 1993, p. 154; italics in the original). As noted, this definition is compatible with Batra and Ray’s (1983) definition of in-

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volvement as the quality and depth of cognitive processing: in the view of the ARI model such cognitive processing can be both emotional/affective and rational. In conclusion, the ARI/CASC conception is quite unlike traditional cognitive models of persuasion. However, it is compatible with the new evidence of the importance of emotion in persuasion, and may serve to aid in its conceptualization and measurement in research on health information campaigns that have had uneven success in the past. We submit that the ARI model has the potential to serve as an integrative viewpoint, which will clarify the role of emotion and reason in persuasion, that the CASC Scale represents a new way to conceptualize and operationalize emotion in the context of persuasion research, and that the ARI model and CASC Scale can have a significant theoretical and empirical impact upon the field of persuasion in general. The studies presented here are primarily exploratory. We know too little—and perhaps have not thought sufficiently—about emotional dynamics to make specific predictions or even to explain the difference in patterns obtained in the present studies. The beginning of wisdom is to accept the reality that highly differentiated systems of emotion have profound consequences for attitude formation, maintenance and change.

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Journal of Business Research 57 (2004) 657 – 664

The impact of cognitive and/or affective processing styles on consumer response to advertising appeals Salvador Ruiz*, Marı´a Sicilia Department of Marketing, School of Economics and Business, University of Murcia, Campus Universitario de Espinardo, 30100 Murcia, Spain

Abstract As advertisers increasingly seek greater communication effectiveness and new forms of media emerge, psychological differences amongst individuals are becoming essential criteria in the design of advertising appeals. The present study considers whether individuals differ in their propensity to rely on affective, cognitive or both systems to process information. This research suggests that persuasive appeals tend to be more effective when the nature of the appeal matches, rather than mismatches, the individual personality-type preferences for processing information. Results show that informational and informational-emotional advertising appeals, which match consumer’s processing style (thinking and thinking-feeling processors, respectively), can generate more positive attitudes toward the brand, purchase intention (PI) and brand choice. D 2004 Elsevier Inc. All rights reserved. Keywords: Advertising; Processing style; Cognitive/affective; Attitudes; Purchase intention; Brand choice

1. Introduction As advertisers increasingly seek greater communication effectiveness, more careful consideration needs to be given to the selection of the type of advertising appeal used for each target group. Qualitative factors associated with the content and/or execution of an ad have an impact on its eventual effectiveness (MacKenzie et al., 1986). There exists a long tradition in advertising research of exploring the relationship between personality and response to advertising messages (LaBarbera et al., 1998). In particular, marketing researchers have long been intrigued by two individual characteristics, affect and cognition, which may have an influence on advertising effectiveness (Fabrigar and Petty, 1999; Harris and Moore, 1990; Zhang and Buda, 1999). In the last 20 years, many similar measures have been developed to account for the individual tendencies to engage in affective or cognitive activities (Hadddock and Zanna, 1993; Sojka and Giese, 1997). This distinction has also been a popular means of classifying types of persuasive com-

* Corresponding author. Tel.: +34-968-363802; fax: +34-968-367986. E-mail address: [email protected] (S. Ruiz). 0148-2963/$ – see front matter D 2004 Elsevier Inc. All rights reserved. PII: S 0 1 4 8 - 2 9 6 3 ( 0 2 ) 0 0 3 0 9 - 0

munication (Fabrigar and Petty, 1999), and some work has investigated the extent to which the two types of persuasive communication change attitudes by different processes (Edell and Burke, 1987; Roselli et al., 1995). Previous research suggests that persuasive appeals tend to be more effective when the nature of the appeal matches, rather than mismatches, these two processing styles (La Barbera et al., 1998). Such an idea can provide a rationale for understanding the reasons why some individuals differ in their responses to ad stimuli. This paper presents a framework based on an independent but interactive relationship between affect and cognition as suggested by Sojka and Giese (1997). Our objective is to illustrate how advertising effectiveness, in terms of attitudes and intentions, is affected by the consumer’s processing style. The main contribution of this paper lies in the analysis of the interactive affect-cognition relationship (i.e., thinking-feeling processing style) effects on advertising effectiveness across different executions of advertising stimuli. In the next sections we review the literature on affective and cognitive processing styles, and present our research hypothesis followed by a detailed description of the methodology. Analysis and discussion are presented at the end of the paper.

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2. Affective and cognitive processing styles Consumer behavior researchers have pointed out that individual differences among message recipients may lead to wide variations in the manner in which people respond to advertising appeals (Moore et al., 1995). Some individuals, when exposed to an emotionally charged advertising appeal, may exhibit a characteristic tendency to experience their emotions with greater magnitude of intensity (Aaker et al., 1986). Similarly, some individuals may exhibit a tendency to engage in and enjoy thinking when exposed to an ad (Cacciopo and Petty, 1982). Personality classifications that focus on the cognitive style (tendency to engage in and enjoy thinking) have usually been referred to as need for cognition (NFC) (Cacciopo and Petty, 1982). The NFC scale allows researchers to distinguish between two groups of individuals, high and low NFC individuals. Haugtvedt et al. (1992) demonstrated that individual differences in the NFC significantly influenced the formation of attitudes toward consumer products. High NFC individuals (i.e., those who are more likely to enjoy thinking) have been shown to process and evaluate advertising information more thoroughly than low NFC individuals (Mantel and Kardes, 1999; Peltier and Schibrowsky, 1994). Previously, Petty et al. (1983) indicated that under a low involvement condition, people process information through the peripheral route rather than the central route. To encourage consumers’ acceptance of claim assertions, advertisers often provide arguments as rationale for the ad (Munch et al., 1993). But also, as the NFC increases, diagnostic information increasingly becomes the focus of consumer attention (Maclnnis and Jaworski, 1989; Petty et al., 1983; Suri and Monroe, 2001). More positive responses are found to be obtained in high NFC individuals with factual appeals or more informationally dense ads and those with high-quality arguments (Geuens and De Pelsmacker, 1998). On the contrary, when there is very little information in the ad and it is mainly emotional, both low and high NFC individuals will present similar advertising effectiveness, given that the latter do not have any information to be processed. Therefore, we propose: Hypothesis 1: Higher levels of advertising effectiveness are associated to high NFC individuals, compared with low NFC individuals, when the ad is mainly informational, and no differences appear when the ad is mainly emotional. However, cognition represents only one mode of information processing. Individuals may also differ in their tendencies to process affective or emotional stimuli (Raman et al., 1995). There are several concepts and measurements developed for the affective processing style such as the affect intensity (Geuens and De Pelsmacker, 1999; Larsen, 1984; Moore et al., 1995), the Feeling-Belief measure (Hadddock and

Zanna, 1993) and the Need For Emotion (Raman et al., 1995). Recently, the Preference for Affect (PFA) scale (Sojka and Giese, 1997) was developed to measure affective processing across all situations, given that the affect intensity scale only measures the intensity with which an individual responds to an affective stimulus (Raman et al., 1995) and the other two, the Feeling-Belief measure and the Need for Emotion scale, are situationally bounded. That is, the latter two consider that the affect processing is a function of the situation as opposed to an individual processing trait, which is relatively stable with respect to situations (Sojka and Giese, 1997). Despite this controversy with the measurement of affective processing in the literature, their results are consistent and give us an idea about the way in which different people respond to emotional appeals. In this sense, Larsen and Diener (1987) confirmed that when people are exposed to equal levels of affect producing stimuli, some individuals consistently respond with high levels of emotional intensity while others respond with only moderate levels. Furthermore Moore et al. (1995) obtained that high affect intensity individuals may be more likely to be persuaded by emotionally charged advertising appeals. Harris and Moore (1990) suggested to investigate the influence of AI on emotional versus informational ads. Moore et al. (1995) found that high AI individuals, compared with low AI, manifested significantly stronger emotional responses to the emotional ad appeal and showed no differences in emotional response intensity when exposed to a nonemotional appeal. However, they did not obtain concluding results related to attitudes. We believe it may be due to the fact that they used a scale that may not be as valid for all situations as the PFA scale. Therefore, based on this and using PFA, we propose: Hypothesis 2: Higher levels of advertising effectiveness are associated to high PFA individuals, compared with low PFA individuals, when the ad is mainly emotional, and no differences appear when the ad is mainly informational.

3. The interaction between affective and cognitive processing styles The link between cognition and affect in an advertising setting has been demonstrated in several studies (Burke and Edell, 1989; Zajonc and Markus, 1982), which suggested that the cognitive and affective processes may proceed independently as well as work together. For that reason, more recent models integrate affective responses (Vakratsas and Ambler, 1999). There are individual differences in the tendency to use affective and cognitive information in guiding attitude (Hadddock and Zanna, 1993) and the scales of NFC and its

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counterpart, PFA, can be very good instruments in measuring those individual differences as they measure the intensity of cognitive and affective processing styles (Sojka and Giese, 1997). Furthermore, following Sojka and Geise (1997) classification, it is possible to identify four types of individuals according to these two processing styles (affective and cognitive). Their results suggested that affective and cognitive processing systems are independent yet can operate interactively. So, individuals unbounded by a specific situation may demonstrate a propensity to process information using affect, cognition, both or neither (see Fig. 1). Well-known advertising-planning models recommend matching the advertising appeal to the attitude basis, i.e., use rational and informational advertising for ‘‘thinking’’ or ‘‘functional’’ products and emotional appeals for ‘‘feeling’’ or ‘‘transformational’’ products (Dube et al., 1996). In this sense, past research has uniformly suggested that persuasive appeals tend to be more effective when the nature of the appeal matches, rather than mismatches, the basis of the attitude (Fabrigar and Petty, 1999). Extending these findings to the processing styles and using Sojka and Giese’s (1997) classification, we propose that the matching, rather than the mismatching, of the advertising appeal to the groups of processors described in Fig. 1 will produce higher advertising effectiveness. Apart from the two groups strictly based on affect (feeling processors) and cognition (thinking processors) for which the matches represent an advance over the two previous hypotheses, the most interesting issue comes from the combination processors, who tend to use both processing styles, for which ads containing both emotional and informational elements at a significant level should produce higher advertising effectiveness than ads containing only one of these elements. Lastly, for those individuals that present low levels in both variables (i.e. have low interest in processing affective or cognitive information) we cannot predict their behavior. They are passive processors. The foregoing discussion leads to the formulation of the following hypothesis: Hypothesis 3: Higher levels of advertising effectiveness are associated with ads whose composition in terms of emo-

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tional and/or informational elements matches the individual processing style. Hypothesis 3a: For thinking processors, higher levels of advertising effectiveness are associated with ads that are mainly informational. Hypothesis 3b: For feeling processors, higher levels of advertising effectiveness are associated with ads that are mainly emotional. Hypothesis 3c: For combination processors, higher levels of advertising effectiveness are associated with ads that are both emotional and informational.

4. Method 4.1. Design and subjects Two hundred and sixty undergraduate students were recruited to participate in the study. Most of the studies about advertising have been tested with students, as they are very homogeneous and convenient samples for data collection (Brown and Stayman, 1992). The participation in the experiment was voluntary, and students were told that they were going to participate in a testing project about three camera advertisements. A 2 (between subjects)  2 (between subjects)  3 (within subjects) mixed-factorial experiment design comprising two levels of cognitive processing (high and low), two levels of affective processing (high and low) and three advertisements for one product category (camera) was used to test the study hypotheses. 4.2. The product used A compact camera was used in the experiment. In the three advertisements presented to the sample, there was a different compact camera, though all of them share most of the technical characteristics. We used three existing brands for the advertisements (Bronica, Centon and Soligor). However, none of them is a powerful brand in the Spanish market in order to avoid any contamination due to differences in prior advertising exposure or brand usage (Derbaix, 1995; Singh, Lessig and Kim, 2000). We got the names from several photography magazines and tested, after collecting data, that no one student have heard about them. 4.3. The advertisements

Fig. 1. Classification of the individuals according to their processing style. Source: Sojka and Giese (1997).

Each individual was exposed to three camera advertisements. None of them were real advertisements, but most of the characteristics and types were similar from the existing

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ads that appeared in the magazines (most of them advertised well-known brands). Three advertisements were created that differed in their levels of information and emotions elicited. The first advertisement (Centon) was very informational (strong and objective arguments). The second (Bronica) was very emotional (we used a picture with a bear family in a very pleasant scene) without any technical or objective information about the camera. The third ad (Soligor) was both very informational and emotional at the same time. This third ad included the strongest and most objective arguments of the first ad plus a picture depicting some people watching whales jumping in the sea. 4.4. Measures Our dependent variables are related to the concept of advertising effectiveness, being attitude toward the ad (Aa), attitude toward the brand (Ab), purchase intention (PI) and brand choice (BC). The survey used previously developed scales to measure the three first dependent variables. Each of them was assessed using seven-point semantic differential scales. Positive – negative, good –bad, favourable – unfavourable, nice – not nice and I like it –I do not like it were used to measure Aa with a selection of items extracted from the relevant literature (Coulter and Punj, 1999; Lafferty and Goldsmith, 1999; MacKenzie and Luzt, 1989). Attractive – not attractive, bad – good, nice – not nice, it is worse than competing brands – it is better than competing cameras, it is worthy – it is not worthy and I like it –I do not like it were used to measure Ab using also items that appeared in the literature (Batra and Stayman, 1990; Krishnamurthy and Sujan, 1999; Pham, 1996). Finally, Unlikely – likely, improbable – probable and impossible –possible were used for PI (Zhang and Buda, 1999). For the last dependent measure, brand choice, they had to select among the three cameras, Bronica, Soligor or Centon, supposing they had to buy one at that moment. According to our study design, we have three independent variables, NFC, PFA and type of advertisement. NFC was measured via the 18-item scale developed by Cacciopo et al. (1984) to identify a person’s inherent desire to engage in elaborate processing. PFA was measured with the 13 items developed by Sojka and Giese (1997).

At the end of the questionnaire, students had to choose one of the three cameras they had seen.

5. Results Multiple item scales were averaged and reliability was high for both individual characteristics scales, NFC (a=.80) and PFA (a=.86). Subjects then were rank ordered and divided into thirds. For the NFC scale, one major concern in the decision to use a tripartite partitioning was that university students may be more homogeneous than the general population in this characteristic (Zhang and Buda, 1999). For PFA, we opted by the tripartite partitioning in order to be consistent with the procedure applied for NFC, although median splits (Mantel and Kardes, 1999, Zhang, 1996), tripartite partitioning (Geuens and De Pelsmacker, 1999) and quartile splits (Moore et al., 1995) have been used for this variable. The quartiles split was rejected because of cell size reasons. For both variables, the middle one-third of students were teased out from the experimental sample for each independent variable. After dividing the sample using NFC scores, low NFC individuals rated an average of 0.34 and high NFC individuals rated 2.60 in the nine-point scale (ranging from 4 to 4). Similarly, these rates were 0.09 and 2.61 for PFA. These groups (Fig. 2) were similar to those obtained by Sojka and Giese (1997) indicating four types of processing style. Mean differences for each variable (NFC and PFA) are statistically significant ( F = 137.06, P < .01 and F = 148.6, P < .01, respectively) for the four different groups, indicating that respondents can be categorized as high in cognition but low in affect, low in cognition but high in affect and high and low on both affect and cognition scales. For the dependent measures, all multiple-item measures (Aa, Ab and PI) were also averaged, and the resulting composites were used in all subsequent analyses. Reliability analyses showed that these scales achieved high levels of internal consistency, with coefficient alpha’s ranging from .80 to .90. A manipulation check was performed by measuring the information and emotions that were transmitted by the ads.

4.5. Procedure In the first stage of the experiment, subjects were administered the NFC and PFA scales. After that, subjects viewed each ad for 1 minute, and before viewing the next one, they rated the ad according to its informational and emotional contents and then responded to the questions concerning their Aa, Ab and PI. This process was done for the three ads. In order to prevent order effects, the position of the advertisements was varied through the experiment.

Fig. 2. NFC, PFA and cell sizes for the four groups of subjects. Note: The four categories are based on a tripartite partitioning using the 33 and 66 percentiles of the actual state data.

S. Ruiz, M. Sicilia / Journal of Business Research 57 (2004) 657–664 Table 1 Information and emotions transmitted by the ads Ad type

Information transmission

Emotions transmission

Emotional ad (Bronica) Informational ad (Centon) Emotional and informational ad (Soligor)

2.04 * 6.50 * 5.50 *

5.44 * 1.02 * 5.11 *

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showed significantly higher advertising effectiveness than their low counterparts through Aa, Ab and PI when exposed to the emotional ad. Again, for the second part of Hypothesis 2, no difference was found with the informational ad between high and low PFA individuals. Results supporting this hypothesis are presented in Table 3. Finally, Hypothesis 3 was tested comparing the effectiveness of each advertisement within each group of individuals described in Fig. 2. For this hypothesis, we used the three advertisements included in the experiment: Centon (mainly informational), Soligor (informational-emotional) and Bronica (mainly emotional). Results are shown in Fig. 3. Fig. 3a shows that thinking processors have a higher attitude toward Centon (C) at the 5% level, while there is no significant difference at the 10% level between Bronica (B) and Soligor (S) (t = 3.27, 2.28 and 1.18 for C vs. B, C vs. S and B vs. S, respectively). The same happens with PI (t = 3.28, 2.43 and 1.17 for C vs. B, C vs. S and B vs. S, respectively) and brand choice (t = 4, 3.12 and 0.63 for C vs. B, C vs. S and B vs. S, respectively). These results partially confirm Hypothesis 3a, given the exception of Aa that shows opposite results to those previously hypothesized. On the opposite corner of Fig. 2, feeling processors (Fig. 3b) also present a consistent response pattern. But for these individuals, all the three pairwise comparisons are not statistically significant at the 10% level neither in terms of Ab (t = 0.0, 0.31 and 0.25 for C vs. B, C vs. S and B vs. S, respectively), PI (t = 1.15, 1.51 and 0.31 for C vs. B, C vs. S and B vs. S, respectively) nor brand choice (t = 1.65, 0.40 and 1.22 for C vs. B, C vs. S and B vs. S, respectively). Aa shows similar results to those obtained for thinking processors. Therefore, Hypothesis 3b is not supported. Thirdly, Fig. 3c shows that combination processors have lower attitude toward Bronica at the 5% level, while there was no significant difference between Soligor and Centon

* Represents significance of difference with respect to the medium point of the scale (3.5): P < .01.

Using two seven-point scales (none –a lot), we determined the extent to which the target ads were informational, emotional or both. t test analysis revealed that the three ads were correctly transformed, that is, our manipulations in emotions and information transmitted were effective. As shown in Table 1, the emotional ad (Bronica) had a mean score of 5.44 in the emotions and 2.04 in the information transmitted. All mean scores differed significantly (in the expected direction) with respect to the medium point of the scale (3.5). In order to test Hypothesis 1, we used Centon (informational) and Bronica (emotional) ads. As shown in Table 2, high NFC subjects showed significantly higher advertising effectiveness when that effectiveness is measured using Ab and PI but not with Aa. The lower rates found for the informational ad compared with the emotional ad in Aa may be explained by the fact that the ad only contained text without any color or design. For the second part of Hypothesis 1, no difference was expected for the emotional ad among high and low NFC individuals, which is supported with the data included in Table 2. The same approach was used in the second hypothesis, but this time emotional ad was considered first. As could be expected on the basis of previous results, high PFA subjects

Table 2 Advertising effectiveness measures (means) for the two NFC groups Ad type

Informational ad (Centon)

NFC variable

Aa

High NFC individuals (n = 89) Low NFC individuals (n = 86) t test

4.40 4.57 0.86

Emotional ad (Bronica)

Ab

PI 5.21 4.83 2.51* *

4.64 4.29 1.79 *

Aa

Ab

PI

5.28 5.21 0.17

4.63 4.65 0.13

3.82 3.93 0.17

* P < .10. * * P < .05.

Table 3 Advertising effectiveness measures (means) for the two PFA groups Ad type

Informational ad (Centon)

PFA variable

Aa

High PFA individuals (n = 97) Low PFA individuals (n = 86) t test * * * P < .01.

Ab 4.46 4.40 0.11

Emotional ad (Bronica) PI

5.06 4.94 1.15

Aa 4.47 4.38 0.61

5.56 4.92 4.28* * *

Ab

PI 4.88 4.37 3.74* * *

4.13 3.66 2.77* * *

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Fig. 3. Advertising effectiveness and processing style.

(t = 2.52, 2.17 and 0.02 for B vs. S, B vs. C and S vs. C, respectively). The same happens with PI (t = 3.77 1.691 and 1.48 for B vs. S, B vs. C and S vs. C, respectively) and BC (t = 3.85, 2.78 and 0.78 for B vs. S, B vs. C and S vs. C, respectively). Higher scores are therefore obtained by the two ads that provide information (strong and objective arguments, although in different amounts) about the two cameras. Based on these results and the behavior of the variable Aa, Hypothesis 3c is not supported.

6. Discussion After years of researching affect and cognition separately, recent studies on preference formation and attitude change have focused on how cognition and affect work together. Considering affect and cognition as generators either of personality types or of processing styles, these two classifications become a powerful tool for segmenting consumers, which can give marketing managers an idea about the ad type best suited to each group of consumers. In this study, results show that when individuals were exposed to ads congruent with their processing styles, in terms of affect and cognition (Hypotheses 1 and 2), higher advertising effectiveness is obtained. Significant effects 1

P < .10.

were found for Ab and PI. Concerning Aa, there are no concluding results in these two first hypotheses because no differences in this variable were found between high and low NFC subjects. The lack of visual attractiveness of the highly informational advertisement (just a list of written strong and objective claims) provoked low scores in attitude toward it, especially because two-thirds of the subjects had previously seen (during the experiment) another camera advertisement with attractive images, and this comparison effect may be the reason for the absence of significant differences between high and low NFC subjects. Furthermore, the findings of this study offer additional support that affective and cognitive processing systems can operate independent but also interactively (combination processors). While different ads do not seem to generate different advertising effectiveness for feeling processors, informational advertisements are associated with higher effectiveness for thinking processors. For combination processors, advertising appeals based on information or information plus emotions obtained the better results. In summary, informational and informational-emotional advertising appeals, which match consumer’s processing style (thinking and thinking-feeling processors, respectively), can generate more positive Ab, PI and BC. The latter result may be explained through some studies that affirm that the relative importance of cognition and affect depends on the context (Vakratsas and Ambler, 1999).

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Furthermore, according to Sojka and Giese (1997), it is also conceivable that other variables, such as product involvement and risk level, may impact on individual’s actual processing. This may be the reason why the ads containing information have shown greater acceptance. The product used, camera, is a product for which decision making may be more cognitive than emotional, and for that reason, the emotional ad has not demonstrated as much effectiveness as the informational one. Additionally, it is interesting to point out the consistent pattern of results obtained with the variable Aa for the three groups analyzed. Advertisements including pictures (either alone or with information) are always associated with higher levels of Aa than those including only information (text). Even for thinking processors, the informational ad showed the lowest Aa, although brand attitude, PI and probability of choice were the highest for the advertised brand. This result prevent us to think that the simultaneous questioning about attitudes, PI and brand choice may have induced cognitive consistency in the answers. The study findings have several interesting implications for creative advertising decisions assuming knowledge of target personality-type preferences. Although for some subjects the combination of information and emotions can have the same value than only information in the advertisements, especially for consumers who tend to use cognitive as well as emotional information processing systems interactively, others (thinking processors) can consider those emotions as capable of reducing the highly positive effect of strong and objective arguments. Even more, as long as arguments are strong and images are highly emotive, both elements, independently and together, produce the same effect for another group of subjects (feeling processors). Finally, future research should further investigate these four groups of information processors. There is no research concerning passive processors, what types of ads or what combination of emotions and arguments will be more effective for them. Furthermore, considering the four types of processing styles, hypotheses concerning emotional products more than cognitive ones and referring to low versus high involvement products need to be tested.

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Journal of Business Research 57 (2004) 665 – 670

Closing the gap between values and behavior— a means–end theory of lifestyle Karen Brunsø*, Joachim Scholderer, Klaus G. Grunert Centre for Research on Customer Relations in the Food Sector (MAPP), The Aarhus School of Business, Haslegaardsvej 10, Aarhus DK-8210, Denmark

Abstract Means – end chain theory and lifestyle are reconstructed within a dual-process framework, incorporating bottom – up and top – down information processing routes. The bottom – up route is defined as a hierarchical categorization process, and the top – down route as goaldirected action. Lifestyle, then, is a system of individual differences in the habitual use of declarative and procedural knowledge structures that intervene between abstract goal states (personal values) and situation-specific product perceptions and behaviors. Access to the intervening knowledge structures is considered a necessary condition for both information processing routes to reach their ends, predicting a strict mediation model. The model is tested on survey data gathered in France in 1998, using the list of values as a measure of abstract goal states, the food-related lifestyle instrument as a measure of intervening knowledge structures, and a newly constructed behavior list as a measure of behavior. Data were analyzed by means of structural equation modeling. Compared against five alternative model structures, the strict mediation model fitted the data best, thus confirming the predictions derived from the reconstructed theory. D 2003 Elsevier Inc. All rights reserved. Keywords: Values; Lifestyle; Behavior; Structural equation modeling; Mediation

1. Introduction The lifestyle construct has a longstanding history in marketing research. First introduced by Lazer (1964), it was mainly used as an umbrella term for arbitrary assortments of ‘‘activities, interests and opinions’’ items (AIO; Wells and Tigert, 1971) by which marketing researchers sought to describe how consumer segments differed from another. The vagueness of such a definition has annoyed many marketing scholars over the years (e.g., Anderson and Golden, 1984; Lastovicka, 1982). Whilst the theoretical status of the lifestyle construct has recently been elaborated within a means – end framework (Brunsø and Grunert, 1998; Grunert, 1993), its construct validity is still highly uncertain. The aim of the present paper is to fill this gap. 1.1. A means –end theory of lifestyle Brunsø and Grunert (1995, 1998) have proposed a lifestyle definition that clearly breaks with the AIO tradition. Their framework is consistent with the means –end approach * Corresponding author. Tel.: +45-89-486-487; fax: +45-86-150-177. E-mail address: [email protected] (K. Brunsø). 0148-2963/$ – see front matter D 2003 Elsevier Inc. All rights reserved. doi:10.1016/S0148-2963(02)00310-7

to consumer behavior (Olson and Reynolds, 1983), especially in its hierarchical cognitive structure formulation (Grunert and Grunert, 1995). On the top level of their hierarchy, personal values are defined as abstract, transsituationally aggregated cognitive categories. On the bottom level, product perceptions are defined as situation-specific input to a categorization process. Lifestyle is then defined as an intervening system of cognitive structures that link situation-specific product perceptions to increasingly abstract cognitive categories and finally to personal values. The system comprises declarative knowledge (categories, concepts, associative networks) and procedural knowledge (scripts and skills), shaping information processing on bottom – up as well as top –down routes. From a bottom – up perspective, the knowledge structures guide a comprehension process. Declarative knowledge attaches meaning to an incoming product sensation, and procedural knowledge provides behavioral routines to act upon the mental representation of a product. From a top –down perspective, the knowledge structures guide goal-directed action. Personal values are top-level goals that are situationally unspecific (Rokeach, 1968) and not instantiated with respect to a certain object. Declarative knowledge, when activated, yields specific goal instantia-

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tions (Gollwitzer, 1999; Pieters et al., 1995) on the level of a certain product category. Procedural knowledge, when activated, provides behavioral routines for acting upon these instantiations so that a behavioral intention can be formed, adapted to situational constraints, and finally be acted upon (Kuhl, 1985). 1.2. Testable predictions Both information processing routes are formulated on the individual level, and both imply a particular sequence of activation. The bottom – up route is driven by external input (product perception), which is thought to trigger a hierarchical categorization process (activating declarative and procedural knowledge structures) that finally results in the activation of the most abstract conceptual level (personal values). Hence, a valid test of the assumed hierarchy would have to manipulate appropriate stimulus characteristics in an experimental design, and assess whether the observed sequence of activation is consistent with the predicted sequence of activation. The top – down route, on the other hand, is driven by stable individual differences in personal values. Stable individual differences in such superordinate goals imply stable individual differences in the activation of subordinate goals and behavior routines that are instrumental in achieving superordinate goals. Finally, frequent activation of particular subordinate goals and behavior routines implies a higher frequency of observable behaviors that are instrumental in achieving these goals as compared to behaviors that are not instrumental in achieving them. Unlike the bottom – up route (which is driven by external input), the top – down route implies stable individual differences, and can thus be tested by means of survey methods. A valid test would have to establish that lifestyle, as defined above, in a strict sense mediates the relation between personal values and the frequency of instrumental behaviors. In a path model, this would imply that values predict lifestyle, and lifestyle predicts behavior, but that there is no direct effect of values on behavior when lifestyle is included in the model. 1.3. Extensions of the general means –end approach At a first glance, our lifestyle model does not seem to add much to the general means –end approach. On closer inspection, however, three important differences become apparent. The first one is conceptual: The general means – end approach presupposes a certain structure in the subjective ‘‘meaning’’ of product. Due to a lack of theoretical rigor, however, it is not quite clear whether ‘‘meaning’’ is to be understood in a semantic or in a motivational sense (see Grunert and Grunert, 1995 for a detailed discussion). The present approach assumes that semantic aspects are predominant when a means – end chain is primed from the bottom end (initiating a categorization process), but that motiva-

tional aspects are predominant when a means – end chain is primed from the top end (initiating goal-directed action). Secondly, our lifestyle model extends the general means –end approach by including procedural knowledge. Scripts and skills add a pragmatic dimension, linking the mere mental representation of a product or a consumption goal to certain behavioral routines so that goal-directed behavior is also predicted by the model. Thirdly and most importantly, our lifestyle model assumes that lifestyle is a strict mediator of the relationship between values and behavior. As Grunert and Grunert (1995) show, the general means –end approach takes quite a liberal stance on the particular mode of mediation—it is just not clear whether direct links from product perceptions to values are consistent with the theory or not. In contrast to this, our lifestyle model makes explicit predictions that are empirically testable. 1.4. Measurement Operationalized in terms of the top – down perspective outlined above, lifestyle becomes a construct that transcends individual products or brands, but may still be specific to a particular class of consumer goods. Brunsø and Grunert (1995, 1998) have developed a survey instrument to measure food-related lifestyle (FRL). The questionnaire measures 23 lifestyle dimensions in five domains: . Ways of shopping. How do people shop for food products? Is their decision making characterized by impulse buying, or by extensive deliberation? Do they read labels and other product information, or do they rely on the advice of experts, like friends or sales personnel? How do they do their shopping—one-stop shopping versus specialty food shops? . Cooking methods. How are the products purchased transformed into meals? How much time is used for preparation? Is preparation characterized by efficiency, or by indulgence? Is it a social activity, or one characterized by family division of labor? To which extent is it planned or spontaneous? . Importance of quality aspects. This refers not to concrete attributes of individual products, but to attributes that may apply to food products in general. Examples may be healthy, natural, fresh, and tasty. . Consumption situations. How are meals spread over the day? How important is eating out? . Purchasing motives. What is expected from a meal, and what is the relative importance of these various consequences? How important are social aspects, hedonism, tradition, and security? The purchasing motives domain measures individual differences in the importance attached to food-specific instantiations of personal values. The importance of quality aspects domain measures a generalized schema for the evaluation of

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product attributes. The ways of shopping, cooking methods, and consumption situations domains measure individual differences in the habitual use of scripts and skills. Extensive cross-national analyses of the psychometric properties of the FRL (Grunert et al., 1997; Scholderer et al., in press) indicate that the factorial structure is practically universal to European food cultures and remarkably stable over time.

imposed on region. Face-to-face interviews were then conducted with the person mainly responsible for food shopping and cooking in the household, with an additional quota on age. The mean age of the respondents was 48.17 years (S.D.=15.45), 87% were female.

1.5. Aims of the study

Three instruments were used in this study. The list of values (LOV; Kahle, 1983) consists of nine items measuring sense of belonging, fun and enjoyment, warm relationships with others, self-fulfillment, excitement, being well respected, security, sense of accomplishment, and selfrespect. All items were answered on nine-point scales ranging from not at all important (1) to very important (9). Previous analyses suggest a three-factorial structure for the LOV (Homer and Kahle, 1988; Grunert and Scherhorn, 1990; Grunert et al., 1994). The FRL instrument (Brunsø and Grunert, 1995) is a 69item questionnaire measuring 23 lifestyle dimensions in five major life domains, including ways of shopping (WS; six subscales), cooking methods (CM; six subscales), importance of quality aspects (QA; six subscales), consumption situations (CS; two subscales), and purchasing motives (PM; three subscales). Each subscale consists of three items, to be answered on seven-point scales ranging from completely disagree (1) to completely agree (7). The construct validity of the FRL dimensions has been tested extensively (Grunert et a., 1997; Scholderer et al., in press), indicating that the factor structures of the subscales in each FRL domain conform to simple structure models that are stable across cultures and over time. The food-related behavior (FR-BEH) list was newly constructed to measure a broad range of shopping, cooking, and eating behaviors. It consists of altogether 37 behavioral frequency items, to be answered on seven-point scales with scale points never (1), less frequent (2), one to five times every 6 months (3), one to three times a month (4), one to two times a week (5), three to four times a week (6), and every day or almost every day (7). Preliminary analyses suggest that 30 of the FR-BEH items can be reliably represented by a six-factor simple structure model (Scholderer, Brunsø and Grunert, in press). The rest of the items will be excluded from the present analysis.

The empirical relation between personal values and behavior is generally low (Munson, 1984). A number of studies have tried to bridge the gap with different mediating constructs (e.g., Goldsmith et al., 1997; Homer and Kahle, 1988; van Raaij and Verhallen, 1994; Valette-Florence and Jolibert, 1990), intending to show that there is in fact a link from values to behavior, even if it may not be a direct one. In contrast to this, the theory we outlined above predicts the absence of a direct value-to-behavior link. From our point of view, abstract personal values have to be transformed into specific goals and linked to behavioral routines before they can initiate goal-directed action. Thus, the aim of the present study is to test whether lifestyle, as defined above, is a strict mediator of the value-to-behavior relation, or whether other model structures fit the data better. Altogether, six models will compete against each other:  









a ‘‘no-effects’’ model, assuming that values and lifestyle are independent, and that neither affects behavior at all; a ‘‘value-effects’’ model, again assuming that values and lifestyle are independent, that values influence behavior directly, but lifestyle does not influence behavior at all; a ‘‘lifestyle-effects’’ model, still assuming that values and lifestyle are independent, and that lifestyle influences behavior directly, but values do not influence behavior at all; an ‘‘additive-effects’’ model, assuming that values and lifestyle are independent, and that both influence behavior directly; an ‘‘indirect-effects’’ model, assuming that values influence lifestyle, and lifestyle influences behavior, but that there is no direct effect of values on behavior (strict mediation); and a ‘‘total-effects’’ model, assuming that values influence lifestyle, and lifestyle influences behavior, but that there are also direct effects of values on behavior (partial mediation).

2. Method 2.1. Data collection A sample of N=1000 consumers was drawn in France in 1998. Households were selected at random with a quota

2.2. Measures

3. Results To check whether the distributional assumptions of maximum likelihood estimation were met, multivariate skewness and kurtosis statistics were computed for the joint distribution of the 108 observed variables. The distribution deviated significantly from normality. To account for the violation of assumptions, all observed variables were normalized using Tukey’s proportion estimation formula.

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Table 1 Goodness-of-fit statistics for value, lifestyle, and behavior measurement models Model MM.1 MM.2 MM.3 MM.4 MM.5 MM.6 MM.7

List of values (9 items, 3 factors) FRL—ways of shopping (18 items, 6 factors) FRL—cooking methods (18 items, 6 factors) FRL—quality aspects (18 items, 6 factors) FRL—consumption situations (6 items, 2 factors) FRL—purchasing motives (9 items, 3 factors) FR-BEH list (30 items, 6 factors)

c2

df

AGFI

RMSEA

133.080 537.648 504.039 902.362 47.568 180.566 2001.491

22 120 120 120 8 24 391

0.941 0.917 0.921 0.869 0.960 0.929 0.842

0.071 0.060 0.058 0.081 0.069 0.080 0.070

All models were estimated by maximum likelihood. Total N=1000; missing data deleted pairwise.

3.1. Measurement models Measurement models were specified separately for the LOV (MM.1), the FRL domains ways of shopping (MM.2), cooking methods (MM.3), importance of quality aspects (MM.4), consumption situations (MM.5), and purchasing motives (MM.6), and the FR-BEH list (MM.7). All models were estimated by means of maximum likelihood using LISREL 8.30 (Jo¨reskog and So¨rbom, 1996). Goodness-offit statistics are presented in Table 1. The RMSEA values remained within conventional acceptance limits (RMSEA<0.080) for Models MM.1, MM.2, MM.3, MM.5, and MM.7, and were only slightly above for models MM.4 and MM.6. The AGFI values point

into the same direction (conventional acceptance limit: AGFI > 0.900). Taken together, all measurement models showed acceptable fit. 3.2. Structural models Six alternative structures were specified for the relationship among values, lifestyle, and behavior (Fig. 1). In Models 1 – 4, values and lifestyle are exogenous constructs, influencing behavior independently. Value factors, lifestyle factors, and equation errors in the behavior factors were allowed to correlate within their domain boundaries, but not across. In Models 5 and 6, lifestyle is endogenous, assumed to moderate the value – behavior relation. To maintain a

Fig. 1. Alternative structural models of the values – lifestyle – behavior relation.

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comparable error structure, correlations were allowed among value factors, among equation errors in lifestyle factors, and among equation errors in behavior factors, but not across their domain boundaries. All models were specified separately for each of the five FRL domains, providing a test of the hypothesis that each lifestyle domain is a necessary mediator of the value-to-behavior relation. Again, all models were estimated by means of maximum likelihood using LISREL 8.30. Results are presented in Table 2. The RMSEA indicates acceptable fit for all models and is therefore of limited use here. Since the models are not completely nested either, the usual c2 difference tests cannot be applied so that information-theoretic measures have to be used instead. The consistent Akaike information criterion (CAIC) is a maximum entropy measure (Bozdogan, 1987). In situations where several competing models are specified a priori, the one yielding the lowest CAIC is to be selected. The CAIC puts a moderate penalty on model complexity. Consistent Table 2 Goodness-of-fit statistics for alternative value – lifestyle – behavior structures Model

c2

df

RMSEA

CAIC

WS.1 WS.2 WS.3 WS.4 WS.5 WS.6

No-effects model Value-effects model Lifestyle-effects model Additive-effects model Indirect-effects model Total-effects model

5871.715 5726.589 4915.975 4793.297 4798.102 4703.375

1505 1487 1469 1451 1451 1433

0.059 0.058 0.053 0.052 0.052 0.051

7865.488 7767.630 7000.221 6933.971 6913.220 6941.131

CM.1 CM.2 CM.3 CM.4 CM.5 CM.6

No-effects model Value-effects model Lifestyle-effects model Additive-effects model Indirect-effects model Total-effects model

6338.551 6193.426 4923.215 4875.429 4777.425 4738.529

1505 1487 1469 1451 1451 1433

0.061 0.060 0.054 0.054 0.053 0.053

8264.902 8122.289 7158.790 7221.417 7056.619 7131.512

QA.1 QA.2 QA.3 QA.4 QA.5 QA.6

No-effects model Value-effects model Lifestyle-effects model Additive-effects model Indirect-effects model Total-effects model

6526.321 6381.195 5677.567 5602.455 5428.950 5366.468

1505 1487 1469 1451 1451 1433

0.063 0.062 0.058 0.057 0.056 0.056

8643.352 8473.298 7782.685 7832.330 7546.337 7614.946

CS.1 CS.2 CS.3 CS.4 CS.5 CS.6

No-effects model Value-effects model Lifestyle-effects model Additive-effects model Indirect-effects model Total-effects model

4436.375 4191.250 3784.683 3722.979 3602.332 3569.530

925 907 913 895 907 889

0.067 0.065 0.061 0.060 0.058 0.059

5941.752 5774.985 5214.186 5291.890 5007.315 5114.258

PM.1 PM.2 PM.3 PM.4 PM.5 PM.6

No-effects model Value-effects model Lifestyle-effects model Additive-effects model Indirect-effects model Total-effects model

4416.729 4271.604 3959.157 3844.512 3798.784 3697.290

1058 1040 1040 1022 1031 1013

0.064 0.063 0.059 0.059 0.057 0.057

6314.332 6193.995 5745.796 5736.853 5567.578 5583.033

Models were fitted separately for the FRL domains ways of shopping (WS), cooking methods (CM), importance of quality aspects (QA), consumption situations (CS), and purchasing motives (PM). All models were estimated by maximum likelihood. Total N=1000; missing data deleted pairwise.

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across all five FRL domains, the indirect-effects model yielded the lowest CAIC values (Models WS.5, CM.5, QA.5, CS.5, PM.5). Notably, the total-effects model—also assuming direct effects of values on behavior—did not further improve the fit to the data, so that the strict mediation role of lifestyle assumed by the indirect-effects models can be maintained.

4. Discussion This paper has made an ambitious attempt to explain the overall organization of consumer behavior in terms of superordinate goals, mediating cognitive structures, and observable behavior. The risk of mere theorizing in such a way is all too often that it can explain everything, but predict nothing. Only when a theory introduces particular restrictions does it become amenable to empirical falsification and gains the status of a model. We believe that the present study provides an example on how to overcome such limitations. 4.1. Construct validity problems in means – end chain theory and lifestyle We have related two concepts that have proven of great heuristic value to marketing researchers: means – end chain theory and consumers’ lifestyle. In the past, both constructs have suffered from problems of unconfirmed validity. In the case of lifestyle, the absence of construct validation studies is easy to explain: AIO and related approaches have never attempted anything close to a theory, let alone a nomological network (Anderson and Golden, 1984; Lastovicka, 1982; Roos, 1986). And construct validation without a properly defined construct would have been a pointless exercise anyway. In the case of means – end chain theory, the absence of construct validation studies is more difficult to explain. We believe that there are two main reasons (part of them already discussed by Grunert and Grunert, 1995). Firstly, means – end chain theory is formulated in vague terms. For example, it is not clear whether a hierarchical value map is to be read from the top (as a motivational process), or from the bottom (as a categorization process). In such a situation, it is indeed difficult to derive hypotheses that could test the fundamental implications of the theory. Secondly, the methods employed by means – end researchers impose a presupposed structure on the data. In hard laddering as well as in soft laddering, the interviewing technique forces respondents to elaborate their answers in an increasingly abstract way. A particular sequence is assumed (attributes – consequences – values), but earlier levels of abstraction are apparently not considered necessary for later levels of abstraction to be reached. Moreover, reversed paths are not considered to reflect a different cognitive process. Hence, there is no way data gathered by means of a

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laddering interview could disconfirm means – end chain theory. 4.2. A reconstructed model In the present paper, we have reconstructed means –end chain theory and lifestyle within a dual-process model, incorporating a bottom – up and a top – down information processing route. The bottom – up route is defined as a hierarchical categorization process, and the top –down route as goal-directed action. Lifestyle, in our reconstruction, is then a system of individual differences in the habitual use of certain declarative and procedural knowledge structures that on both routes intervene between abstract goal states (personal values) and situation-specific product perceptions and behaviors. Access of the intervening knowledge structures is considered a necessary condition for both information processing routes to reach their ends. This restriction is crucial since it transforms means –end chain theory from a heuristic concept into a falsifiable model. We have tested the model using representative survey data gathered in France in 1998. Predictions were confirmed: Using the LOV (Kahle, 1983) as a measure of consumers’ superordinate goals, the FRL instrument (Brunsø and Grunert, 1995) as a measure of intervening knowledge structures, and a newly constructed instrument (Scholderer, Brunsø and Grunert, in preparation) as a measure of a broad range of food-related consumption behaviors, we could establish for five different subsets of intervening knowledge structures that they were strict mediators of the relationship between goals and behaviors.

References Anderson WT, Golden LL. Life style and psychographics: a critical review and recommendation. In: Kinnear TC, editor. Advances in consumer research, vol. 11. Provo (UT): Association of Consumer Research, 1984. pp. 405 – 11. Bozdogan H. Model selection and Akaike’s information criterion (AIC): the general theory and its analytical extensions. Psychometrika 1987;52: 345 – 70. Brunsø K, Grunert KG. Development and testing of a cross-culturally valid instrument: food-related lifestyle. In: Kardes F, Sujan M, editors. Advances in consumer research, vol. 22. Provo (UT): Association for Consumer Research, 1995. pp. 475 – 80. Brunsø K, Grunert KG. Cross-cultural similarities and differences in shopping for food. J Bus Res 1998;42:145 – 50. Goldsmith ER, Freiden J, Henderson KV. The impact of social values on food-related attitudes. Br Food J 1997;99(9):352 – 7.

Gollwitzer PM. Implementation intentions and effective goal pursuit: strong effects of simple plans. Am Psychol 1999;54:493 – 503. Grunert KG. Towards a concept of food-related lifestyle. Appetite 1993; 21:51 – 5. Grunert KG, Grunert SC. Measuring subjective meaning structures by the laddering method: theoretical considerations and methodological problems. Int J Res Mark 1995;12:209 – 25. Grunert SC, Scherhorn G. Consumer values in West Germany: underlying dimensions and cross-cultural comparison with North America. J Bus Res 1990;20:97 – 107. Grunert SC, Grunert KG, Kristensen K. Une me´thode d’estimation de la validite´ interculturelle des instruments de mesure: le cas de la mesure des valeurs de consommateurs par la liste des valeurs LOV. Rech Appl Mark 1994;8(4):5 – 28. Grunert KG, Brunsø K, Søren B. Food-related lifestyle: development of a cross-culturally valid instrument for market surveillance. In: Kahle L, Chiagouris C, editors. Values, lifestyles, and psychographics. Mahwah (NJ): Erlbaum, 1997. pp. 337 – 54. Homer PM, Kahle L. A structural equation test of the value – attitude – behavior hierarchy. J Pers Soc Psychol 1988;54(4):638 – 46. Jo¨reskog KG, So¨rbom D. LISREL 8: user’s reference guide. Chicago (IL): Scientific Software International, 1996. Kahle LR. Social values and social change: adaptation to life in America New York: Praeger, 1983. Kuhl J. Volitional mediators of cognitive – behavior consistency: self-regulatory processes and actions versus state orientation. In: Kuhl J, Beckmann J, editors. Action control: from cognition to behavior. Heidelberg: Springer-Verlag, 1985. pp. 101 – 28. Lastovicka JL. On the validation of lifestyle traits. J Mark Res 1982;19: 126 – 38. Lazer W. Life style concepts and marketing. In: Greyser SA, editor. Towards scientific marketing. Chicago (IL): American Marketing Association, 1964. pp. 424 – 38. Munson JM. Personal values: considerations on their measurement and application to five areas of research inquiry. In: Pitts RE, Woodside AG, editors. Personal values and consumer psychology. Lexington Books, 1984. pp. 13 – 33. Olson JC, Reynolds TJ. Understanding consumers’ cognitive structures: implications for advertising strategy. In: Percy L, Woodside AG, editors. Advertising and consumer psychology. Lexington: Lexington Books, 1983. pp. 77 – 90. Pieters R, Baumgartner H, Allen D. A means – end chain approach to consumer goal structures. Int J Res Mark 1995;12:227 – 44. Rokeach M. Beliefs, attitudes, and values: a theory of organization and change New York: Free Press, 1968. Roos JP. On way of life typologies. In: Uusitalo L, editor. Environmental impact of consumption patter. Aldershot: Gower, 1986. pp. 38 – 55. Scholderer J, Brunsø K, Bredahl L, Grunert KG. The cross-cultural validity of food-related lifestyles. in press. Valette-Florence P, Jolibert A. Social values, AIO and consumption patterns. J Bus Res 1990;20:109 – 22. van Raaij WF, Verhallen TMM. Domain-specific market segmentation. Eur J Mark 1994;28:49 – 66. Wells WD, Tigert DJ. Activities, interests, and opinions. J Adver. 1971; 27 – 35.

Journal of Business Research 57 (2004) 671 – 677

Consumer innovativeness Concepts and measurements Gilles Roehrich* Ecole Supe´rieure des Affaires, BP 47X, 38040 cedex 9 Grenoble, France

Abstract Consumer innovativeness, as a force that leads to innovative behavior, has often been cited and studied in research on the diffusion of innovation. Surprisingly, it appears that there is still room for discussion about this concept. This article attempts to take stock of this issue. In the first part, the different theoretical definitions of the notion are introduced critically. The second part is devoted to displaying major measurement scales that have been designed with a view to measuring this construct. This review helps in understanding the diversity of approaches to innovativeness. It raises two main questions: (1) Are the different theoretical conceptualizations of innovativeness equally valid and compatible? (2) Do the scales really express each theoretical standpoint? This suggests that the present scales may be imperfect, and construction of a new one may well be of interest. D 2002 Elsevier Inc. All rights reserved. Keywords: Innovativeness; Measurement scales; Innovative behavior; New product; Innovation

1. Introduction As a marketing concept, innovativeness can at the very least be defined as imprecise. Firm innovativeness, or ‘‘creation of newness,’’ depicts a firm’s ability to develop and launch new products at a fast rate (Hurley and Hult, 1998). Product innovativeness, or ‘‘possession of newness,’’ is the degree of newness of a product (Daneels and Kleinsmith, 2001). Consumer innovativeness, or ‘‘consumption of newness,’’ is the tendency to buy new products more often and more quickly than other people (Midgley and Dowling, 1978). In this article, the word ‘‘innovativeness’’ will be used solely with reference to consumer innovativeness. There is no real consensus on the meaning of innovativeness. It may be described as early purchase of a new product (Cestre, 1996), as well as a tendency to be attracted by new products (Steenkamp et al., 1999). Following the distinction made by Midgley and Dowling (1978) between actualized and innate innovativeness, most authors seem to consider innovativeness a trait, the nature of which is still under question. The first part of this article presents the various

* Tel.: +33-4-76-82-78-66; fax: +33-4-76-82-59-99. E-mail address: [email protected] (G. Roehrich). 0148-2963/$ – see front matter D 2002 Elsevier Inc. All rights reserved. doi:10.1016/S0148-2963(02)00311-9

conceptualizations of the consumer innate innovativeness construct found in the literature. Numerous scales have been created for the purpose of measuring innate innovativeness. A comparative analysis of the main scales found in the European and American literature is presented in the second part of this article.

2. The consumer innate innovativeness concept Innate innovativeness is a ‘‘predisposition to buy new and different products and brands rather than remain with previous choices and consumer patterns’’ (Steenkamp et al., 1999). What forces can explain such a predisposition? Four explanations have been proposed: (1) stimulation need, (2) novelty seeking, (3) independence toward others’ communicated experience and (4) need for uniqueness. 2.1. Innate innovativeness as an expression of the need for stimulation Hebb (1955) and Leuba (1955) seem to be the first to suggest that the individual seeks stimulation, and there is an individual optimal level of stimulation. After a thorough review of the different theories concerning this need, Venkatesan (1973) suggested that a relationship of direct

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dependency between the need for stimulation and innovative behavior should be considered. Building on Berlyne’s (1960) approach, he shows how new products can help people maintain their inner stimulation at an optimum level in different situations. Many empirical results (Mittelstaedt et al., 1976; Etzel and Wahlers, 1984; Valette-Florence and Roehrich, 1993, for example) validate this theoretical perspective. Going further, Raju (1980) suggests that innovativeness may intervene between need for stimulation and innovative behavior as a mediator variable. Empirical results showing a positive and significant relationship between need for stimulation and innovativeness support this proposition (Joachimstahler and Lastovicka, 1984; Wahlers et al., 1986; Roehrich, 1993). As a theoretical basis of many human activities, need for stimulation may be perceived as an antecedent of new product adoption, either directly or indirectly, through innovativeness. 2.2. Innate innovativeness as an expression of novelty seeking As proposed by Pearson (1970), inherent novelty seeking is an ‘‘internal drive or a motivating strength,’’ which motivates the individual search for new information. Hirschman (1980) asserts that inherent novelty seeking is ‘‘conceptually indistinguishable from the willingness to adopt new products.’’ She considers it a cardinal trait, linked to different forms of behavioral innovativeness through actualized novelty seeking. Actualized novelty seeking translates into a series of activities aimed at finding new information, which leads to three types of behavioral innovativeness: (1) informative innovativeness is the actual acquisition of new information about a new product, (2) adoptive innovativeness is the adoption of a new product and (3) use innovativeness, which has two expressions: (1) using a product in a different way or (2) knowing all the different uses of a specific product. This proposal broadens the scope of innovativeness from interest in new products to interest in any kind of newness: information, ideas or behavior. Venkatraman and Price (1990) also build on Pearson’s (1970) work to make the distinction between cognitive and sensory innovativeness: cognitive innovativeness is a ‘‘tendency to engage with pleasure in new experiences that stimulate thinking,’’ which may be either internal or external, whereas sensory innovativeness is ‘‘a tendency to engage with pleasure in internal experiences like fantasy, dreaming or stimulating and risky activities like ski jumping.’’ This latter innovativeness may be activated by stimuli, which can be internal (dreaming) as well as external (experiences). By focusing on novelty, Pearson (1970) and Hirschman (1980) push innovativeness beyond the realm of new product consumption. For Mudd (1990), rather than solving

questions about its nature, this adds more ambiguity to the concept. 2.3. Innovativeness as independence toward other’s communicated experience Midgley (1977) makes a clear distinction between innate innovativeness, a trait possessed by every human being, and actualized innovativeness, which is actual innovative behavior. Arguing that an innovator will be the first to use a new product, he defines innate innovativeness as ‘‘the degree to which an individual makes innovation decisions independently from the communicated experience of others.’’ Midgley and Dowling (1978) adopt this approach, but they question whether it might not be better to add ‘‘receptivity to new ideas’’ to Midgley’s definition. They finally choose to consider that ‘‘receptivity to new ideas’’ and ‘‘independence toward others’ communicated experience’’ may probably be equivalent. Certain empirical results tend to invalidate this theoretical position. Hirschman (1980) obtained a negative correlation between ‘‘receptivity to new ideas’’ and ‘‘independence of judgment in innovative decisions.’’ This result leads Hirschman to conclude that ‘‘these two operationalizations of innovativeness address probably two different domains of behavior.’’ Carlson and Grossbart (1984) and Bearden et al. (1986) obtain a positive but weak correlation between independence of judgment and innate tendency toward newness. Finally, the ‘‘independence in innovative decision’’ dimension of Le Louarn’s (1997) innovativeness scale is revealed to be independent of the ‘‘attraction to newness’’ dimension of the scale and of possession of new products. Although attractive, the proposal to consider innovativeness as an expression of independence of judgment lacks empirical support. We conclude that although useful in the innovative decision process, autonomy in decision may probably be neither an antecedent nor a facet of innovativeness. 2.4. Innovativeness as an expression of need for uniqueness Simonson and Nowlis (2000) recall that there is tension between two opposite objectives in decision making: conformity and distinction. According to Fromkin (1968), the need for uniqueness pushes the individual to distinguish himself through the possession of rare items, a socially accepted behavior. Snyder and Fromkin (1980) suggest three consequences of the need for uniqueness: (1) the absence of interest in the reaction of others to one’s own different ideas or acts, (2) the desire not to always follow the rules and (3) the willingness to publicly defend one’s opinions. Fromkin (1971) is the first to suggest a link between innovative behavior and need for uniqueness, whereas Gatignon and Robertson (1985) conclude that ‘‘consumers

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who depend highly on normative influences (desire for conformity) adopt more slowly.’’ Burns and Krampf (1991) provide the first empirical validation of this theoretical proposition. They demonstrate positive correlation between need for uniqueness and the number of new products possessed. Moreover, this correlation was higher for new products than for new brands. Although supported by only a few empirical results, Fromkin’s sound theoretical proposal suggests that the need for uniqueness can be considered to be a credible antecedent of innovativeness. Firstly, because innovativeness is an easy way to satisfy the need for uniqueness and, secondly, because need for uniqueness includes independence in judgment, which is necessary for innovative purchasing.

solutions within an organization. Finally, Hurt and Alii define innovativeness as ‘‘change willingness.’’ Moreover, two of these scales have a ‘‘creativity’’ dimension, which indicates that the innovativeness concept they measure is not limited to newness consumption. Little research has been undertaken on the Leavitt and Walton’s (see Bearden et al., 1993 for a presentation) and Hurt– Joseph – Cook’s (see Pallister and Foxall, 1995 for a recent study) scales. Kirton’s innovators –adaptators inventory (KAI) raised a far greater interest in the research community (see Mudd, 1995; Foxall, 1995 or Bagozzi and Foxall, 1996 for an overview). Some general conclusions can be drawn from these studies:

2.5. Discussion



There is no consensus in the definition of innovativeness. From ‘‘inherent novelty seeking,’’ which may have consequences other than new product buying behavior, to ‘‘predisposition to buy new products,’’ which defines the concept by its main consequence, through ‘‘independence in innovative decisions,’’ which could not be empirically validated, various authors have given different views of the concept. There is no consensus either on the roots of innovativeness. Of the need for stimulation, novelty seeking, independence in judgment and the need for uniqueness, which are true antecedents of innovativeness? Analysis of existing innovativeness scales may provide insights into these questions.

3. Operational measurements of innovativeness Since the mid-1970s, a stream of research has led to the design of innovativeness scales through a structured validation process. Most of these scales are different in terms of their theoretical premise and internal structure. The resulting set of scales therefore lacks homogeneity. The most representative scales are presented below in two groups: firstly, ‘‘life innovativeness’’ scales, i.e., the ability to introduce newness in one’s life, will be briefly described. Then ‘‘adoptive innovativeness’’ scales will be more thoroughly presented.

These scales tap innovativeness at a high level: items describe attraction to any kind of newness, not only new product attraction;  These scales are multidimensional: seven dimensions for Leavitt and Walton’s 24-item scale, three for Kirton’s 32item inventory, four (or five) for Hurt– Joseph – Cook’s 20-item scale;  These scales have good psychometric properties, except for predictive validity: only weak correlations, if any, have been found with new product purchase.  These scales are very close to each other: Goldsmith and Nugent (1984), then Goldsmith (1990) obtain very high correlation coefficients between the Hurt – Joseph – Cook’s and Leavitt –Walton’s scales (between 0.64 and 0.82) and between the Hurt– Joseph – Cook’s and Kirton’s scales (0.55). These scales do measure very similar concepts. The way their authors present them, their poor predictive validity with new product purchase and the reading of their items (face validity) suggests that they tap inherent novelty seeking more than specific innovativeness. 3.2. Adoptive innovativeness scales The scales presented under this heading have been specifically designed to measure innovativeness as a tendency to buy new products.

3.1. Life innovativeness scales

Table 1 Item sample of the RAJU’s innovativeness scale

Leavitt and Walton’s (1975), Kirton’s (1976) and Hurt et al.’s (1977) scales are included in this category. They are named ‘‘life innovativeness’’ because their scopes go beyond the sole adoption of new products. For example, Leavitt and Walton view innovativeness as a trait ‘‘that underlies the intelligent, creative, selective use of communication for solving problems.’’ Kirtons defines ‘‘innovators’’ as those who tend to search for new problems and original

When I see a new or different brand on a shelf, I often pick it up just to see what it is like A new store or restaurant is not something I would be eager to find out about I am very cautious in trying new/different products I would rather wait for others to try a new store or restaurant than try it myself Investigating new brands of grocery and other similar products is generally a waste of time

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3.2.1. Raju’s (1980) scale Raju’s (1980) innovativeness scale is part of a broader scale designed to measure consumer tendencies toward ‘‘exploratory behavior.’’ It consists of 10 items (see items sample in Table 1), 7 of which are common with other dimensions of his exploratory tendencies scale. Only one of these items has any social content: I would rather wait for others to try a new store or restaurant than try it myself. The author’s results show good internal consistency and high correlation with a sensation seeking scale. These results are partly confirmed by Joachimsthaler and Lastovicka (1984), Wahlers and Dunn (1987) and Wahlers et al. (1986). This scale has been criticized for its structure. After a review of the criticisms (Baumgartner and Steenkamp, 1996), the authors propose a modified scale. 3.2.2. Baumgartner and Steenkamp’s exploratory product acquisition These authors distinguish only two dimensions of exploratory buying behavior: exploratory acquisition of products (EAP) and exploratory information seeking (EIS). For them, ‘‘consumers who are high on EAP enjoy taking chances in buying unfamiliar products, are willing to try out new and innovative products, value variety in making product choices, and change their purchase behavior in an effort to attain stimulating consumption experiences.’’ This EAP 10-item scale (items sample are presented in Table 2) is highly correlated with such constructs as stimulation need (.45) and sensory sensation seeking (.43). Its predictive validity is confirmed by correlations with variety seeking behavior (.25) and innovative behavior (.16). Steenkamp and Van Trijp (1996) confirm a significant correlation between EAP and the possession of 46 new products. 3.2.3. Goldsmith and Hofacker’s scale The originality of the scale designed by these authors is that it measures domain-specific innovativeness, which is a ‘‘tendency to learn about and adopt innovations (new products) within a specific domain of interest.’’ They perceive this construct as intermediary between innate innovativeness and innovative behavior, which is empirically, but moderately, validated by Goldsmith et al. (1995). Four of the six items in this scale (Table 3) describe social innovativeness, as the interviewee is compared with others. This scale proved to be unidimensional and highly reliable. Predictive validity is high, with correlations ranTable 2 Item sample of Baumgartner and Steenkamp’s EAP scale I would rather stick to a brand I usually buy than try something I am not very sure of When I go to restaurant, I feel it is safer to order dishes I am familiar with If I like a brand, I rarely switch from it just to try something different I enjoy taking chances in buying unfamiliar brands just to get some variety in my purchase When I see a new brand on the shelf, I’m not afraid of giving it a try

Table 3 Domain specific innovativeness scale Compared to my friends, I own few rock albums In general, I am the last in my circle of friends to know the titles of the latest rock albums In general, I am among the first in my circle of friends to buy a new rock album when it appears If I heard that a new rock album was available in the store, I would be interested enough to buy it I will buy a new rock album, even if I haven’t heard it yet I know the names of new rock acts before other people do

ging from .38 to .63 with new-product purchase. However, the correlation between that scale and an opinion leadership scale (.78 and .80) questions its discriminant validity. Nyeck et al. (1996) used this scale in an international study (Canada, Israel, France). Their results tend to confirm those of Goldsmith and Hofacker, although predictive validity is lower and factorial structure of lesser quality, as for Goldsmith et al. (1995). 3.2.4. Roehrich’s (1995) scale For Roehrich, innovativeness is an expression of two central needs: need for stimulation (Berlyne, 1960) and need for uniqueness (Snyder and Fromkin, 1980). Consequently, his scale comprises two dimensions: hedonist innovativeness (tied to need for stimulation) and social innovativeness (tied to need for uniqueness). Significant items are displayed in Table 4. Internal consistency, trait validity and nomological validity seem acceptable, except for correlations with mental rigidity (up to .42) and dogmatism (from .19 to .37). Correlation with need for stimulation is as expected (from .16 to .18), but surprisingly no correlation with need for uniqueness is presented. Predictive validity tends to be higher (r=.31) with the number of new products purchased than with innovative purchase intention (between 0 and .30). This result is consistent with Midgley and Dowling’s proposal. Other studies using this scale (Roehrich, 1987; D’Hauteville, 1994) confirm these results. 3.2.5. Le Louarn’s scale Building on the works of Midgley and Dowling on one hand and Hirschman on the other, Le Louarn (1997) defines predisposition to innovate as ‘‘a central predisposition to take innovative decisions, which expresses itself at every Table 4 Item sample of Roehrich’s innovativeness scale (free translation) Hedonist innovativeness

Social innovativeness

I am more interested in buying new than known products I like to buy new and different products New products excite me I am usually among the first to try new products I know more than others on latest new products I try new products before my friends and neighbors

G. Roehrich / Journal of Business Research 57 (2004) 671–677 Table 5 Item sample of Le Louarn’s innovativeness scale (free translation) Attraction to newness

Autonomy in innovative decision

Ability to take risks in trying newness

I am the kind of person who tries every new product at least once When I hear about a new product, I try to know more about at the first occasion Before trying a new product, I try to learn what friends who possess this product think about it I seek out the opinion of those who have tried new products or brands before I try them I’d rather choose a brand that I usually buy rather than try something I am not confident in I never buy something I don’t know anything about with the risk of making a mistake

level of human activity.’’ At product consumption level, this predisposition has three main expressions. Table 5 displays items from the three facets of this scale. This scale has proved to have good psychometric properties (internal consistency and validity). Its predictive validity is good: R2 between the score and early new product purchase intention is up to .23. Of the three dimensions, which surprisingly appear to correlate poorly, only newness attractiveness is correlated with innovative behavior.

4. Discussion Except for a few results (relative to factorial structure or some correlations), the scales reviewed in this second part show good psychometric properties. However, they differ in many dimensions. We will concentrate on four of them: dimensionality, implicit content, level of measurement and predictive validity. As a whole, these scales tap different dimensions, the most specific for innovation diffusion are: newness attraction/repulsion (Leavitt and Walton; Hurt, Joseph and Cook; Raju, Baumgartner and Steenkamp; Goldsmith and Hofacker; Roehrich; Le Louarn scales), creativity/originality (Kirton, Hurt, Joseph and Cook scales), risk attraction/ aversion (Leavitt and Walton; Le Louarn scales), attention to others’ opinion (Leavitt and Walton; Le Louarn scales). The implicit content of the scales refers to the ‘‘individual-social’’ dimension of innovativeness. Some items are

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centered on individual innovativeness (I like to buy new products), whereas others imply a comparison (I like to buy new products before others). We call this dimension implicit because, except for Roehrich and for Steenkamp and Baumgartner (whose scale does not include any ‘‘social’’ item), it is not explicitly mentioned in the theoretical description of the innovativeness concept. A study of the wording of the items reveals that innovativeness dimensions are measured at different levels: at general level, any kind of newness (products, ideas, behaviors, etc.) is concerned. At product level, the items are about innovations or new products (except for EAP scale, which mainly concentrates on different products, either new or unknown) . At domain-specific level, the items are about new products in a specific product category. It is not obvious whether a ‘‘yes’’ at one level would be equivalent to a ‘‘yes’’ at the other one. Finally, as already mentioned by Foxall (1995), the scales’ predictive validity may be disappointing. Most scales demonstrate very low correlation, if any, with innovative behavior. Goldsmith and Hofacker’s domain-specific scale appears to be an exception with a correlation of up to .64. However, this latter correlation seems to be exceptional, as most of the coefficients obtained with this scale are significantly lower, but still greater than .30. This correlation therefore appears to be a reasonable level for innovativeness, as it is obtained by scales from Le Louarn, Roehrich, Steenkamp and Baumgartner or Raju. Finally, we try to link predictive validity with dimensionality and level of measurement of the scales (Table 6). This table clearly demonstrates that when measured at a general level, innovativeness has no predictive validity. When measured at product consumption level, attraction toward newness and social innovativeness dimensions have average predictive validity. The best predictive validity is reached by domain-specific measurement of social innovativeness, which dominates individual innovativeness in the Goldsmith and Hofacker’s scale. Dimensions such as independence of judgment, attitude toward risk/ change or creativity have no predictive validity. Midgley and Dowling (1978) distinguish three levels of innovative behavior: (1) the purchase of a single new

Table 6 Predictive validity of the innovativeness scales, depending on their subdimensions and level of measurement

Newness attraction (individual) Social context

Independence of judgement Attitude toward risk/change Creativity

General behavior

Product consumption

Domain-specific consumption

No predictive validity (Leavitt and Walton, Hurt, Joseph and Cook) No predictive validity (Leavitt and Walton, Hurt, Joseph and Cook)

Low to average predictive validity (Raju, Steenkamp and Baumgartner, Roehrich, Le Louarn) Low to average predictive validity (Roehrich)

Average to high predictive validity (Goldsmith and Hofacker, 1991)

No predictive validity (Leavitt and Walton) No predictive validity (Kirton, Hurt, Joseph and Cook)

No predictive validity (Le Louarn) No predictive validity (Le Louarn)

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Table 7 Different levels of predictive validity

Mono products

Mono category

Roehrich (1995)

Le Louarn (1997)

From 0.09 to 0.30 (about 0.15 on the average) 0.26 (perfumes)

From 0.07 to 0.48 (about 0.15 on the average) 0.32 (electronic appliances) –

Multicategories 0.31

Baumgartner and Steenkamp (1996) 0.16

– –

product, (2) the purchase of new products in a single product category and (3) the purchase of new products in any product category. They hypothesize that the role of innovativeness, at the new product attraction level, becomes easier to isolate as the level of innovative behavior rises. Results displayed in Table 7 provide some support for this hypothesis.

5. Summary and future research Of the dimensions which constitute the internal structure of innovativeness scales, two appear to be of great interest: attraction toward newness (individual innovativeness) and speed of adoption (social innovativeness). The former can be found in all the scales presented here, whereas the latter is explicitly included in only one scale, although implicitly present in most. Although common to every scale, individual innovativeness is theoretically linked to different roots: novelty seeking (Le Louarn) or need for stimulation (Raju, Roehrich, Steenkamp and Baumgartner). However, reading the items shows that they are quite similar despite the theoretical differences. Moreover, each scale contains social items, although only one author explicitly identifies this theoretical dimension of innovativeness. These remarks raise the general question of the link between the theoretical foundations of a scale and the wording of the items. Whether individual or social, innovativeness seems to be able to tap on average only about 10% of innovative behavior. Two possible explanations will be pointed out here. Innovativeness is secondary in explaining innovative behavior: most of the explanatory power may come from the way the new product is perceived (Ostlund, 1974; Roehrich, 2001) or from other intervening variables (Midgley and Dowling, 1978). What does ‘‘new product’’ mean for the interviewee? New products belong to a continuum from ‘‘highly continuous’’ to ‘‘highly discontinuous.’’ Do we really know the level at which respondents give their answer? People who want to change their world may not be interested in buying a new detergent; and people who feel adventurous when buying a new perfume may have a low score on innovativeness.





Consequently, further research into the study of innovativeness and its consequences may be helpful. Firstly, an integrative model of innovativeness is needed. This model should simultaneously offer a structured representation of the different levels at which the innovativeness construct has been conceptualized and the theoretical roots of this construct. It should include the different dimensions of innovativeness. Secondly, this model should provide the theoretical foundation for the construction of innovativeness scales, each tapping the phenomena at a specific level and including items specific to the hypothetical dimensions of innovativeness. References Bagozzi RP, Foxall GR. Construct validation of a measure of adaptive – innovative cognitive styles in consumption. Int J Res Mark 1996;13: 201 – 13. Baumgartner H, Steenkamp J-BEM. Exploratory consumer buying behavior: conceptualization and measurement. Int J Res Mark 1996;13: 121 – 37. Bearden WO, Calcich SE, Netemeyer R, Tell FE. An exploratory investigation of consumer innovativeness and interpersonal influences. In: Richard JL, editor. Advances in consumer research, vol. 13. Provo, UT: Association for Consumer, 1986. p. 77 – 82. Bearden WO, Netemeyer R, Mobley MF. Handbook of marketing scales. Newburg Park, California: Sage Publication, 1993. Berlyne DE. Conflict, arousal and curiosity. New York: McGraw-Hill, 1960. Burns DJ, Krampf RF. A semiotic perspective on innovative behavior. Developments in marketing science. 15th Annual Conference, Academy of Marketing Science, vol. 14. 1991;32 – 5. Carlson L, Grossbart SL. Toward a better understanding of inherent innovativeness. In: Russel WB, Robert AP, editors. Proceeding of the A.M.A. educator’s conference. Chicago: American Marketing Association, 1984. p. 88 – 91. Cestre G. Diffusion et innovativite´: de´finition, mode´lisation et mesure. Rech Appl Mark 1996;11(1):69 – 88. Daneels E, Kleinsmith EJ. Product innovativeness from the firm’s perspective: its dimensions and their relation with project selection and performance. J Prod Innov Manage 2001;18(6):357 – 73 (November). Etzel MJ, Wahlers RG. Optimal stimulation level and consumer travel preferences. In: Russel WB, Robert AP, editors. Proceeding of the A.M.A. educator’s conference. Chicago: American Marketing Association, 1984. p. 92 – 5. Foxall GR. Cognitive styles of consumer initiators. Technovation 1995; 15(5):269 – 89. Fromkin HL. Affective and valuational consequences of self-perceived uniqueness deprivation. Unpublished doctoral dissertation. The Ohio State University, 1968. Fromkin HL. A social psychological analysis of the adoption and diffusion of new products and practices from a uniqueness motivation perspective. In: David MG, editor. 2nd annual conference. Ann Arbor, MI: Association for Consumer Research, 1971. p. 464 – 9. Gatignon H, Robertson TS. A propositional inventory for new diffusion research. J Consum Res 1985;11:849 – 67 (March). Goldsmith RE. The validity of scale to measure global innovativeness. J Appl Bus Res 1990;7(2):89 – 97. Goldsmith RE, Hofacker CF. Measuring consumer innovativeness. J Acad Mark Sci 1991;19(3):209 – 22 (summer). Goldsmith RE, Nugent N. Innovativeness and cognitive complexity: a second look. Psychol Rep 1984;55:431 – 8. Goldsmith RE, Freiden JB, Eastman JK. The generality/specificity issue in consumer innovativeness research. Technovation 1995;15(10):601 – 13.

G. Roehrich / Journal of Business Research 57 (2004) 671–677 D’Hauteville F. Un mode`le d’acceptation du nouveau produit par le consommateur: cas du vin alle´ge´ en alcool. Unpublished doctoral dissertation, Montpellier II, 1994. Hebb DD. Drives and the C.N.S. (central nervous system). Psychol Rev 1995;62:243 – 54. Hirschman EC. Innovativeness, novelty seeking and consumer creativity. J Consum Res 1980;7:283 – 95 (December). Hurley RF, Hult GTM. Innovation, market orientation, and organizational learning: an integration and empirical examination. J Mark 1998;62(3): 42 – 54. Hurt HT, Joseph K, Cook C. Scales for the measurement of innovativeness. Hum Commun Res 1977;4(1):58 – 65. Joachimsthaler EA, Lastovicka JL. Optimal stimulation level: exploratory behavior models. J Consum Res 1984;11:830 – 5 (December). Kirton M. Adaptors and innovators: a description and measure. J Appl Psychol 1976;61(5):622 – 9. Le Louarn P. La tendance a` innover des consommateurs: analyse conceptuelle et proposition d’une e´chelle de mesure. Rech Appl Mark 1997; 12(1):3 – 20. Leavitt C, Walton J. Development of a scale for innovativeness. In: Schlinger MJ, editor. Advances in consumer research, vol. 2. Ann Arbor, MI: Association for Consumer Research, 1975. p. 545 – 54. Leuba C. Toward some integration of learning theories: the concept of optimal stimulation. Psychol Rep 1995;1:27 – 33. Midgley D. Innovation and new product marketing. Londres: Croom Helm, 1977. Midgley D, Dowling GR. Innovativeness: the concept and its measurement. J Consum Res 1978;4:229 – 42. Mittelstaedt RA, Grossbart SL, Curtis WW, Devere SP. Optimal stimulation level and the adoption decision process. J Consum Res 1976;3:84 – 94 (September). Mudd S. The place of innovativeness in models of the adoption process: an integrative review. Technovation 1990;10(2):119 – 36. Mudd S. Kirton adaptation – innovation theory: organizational implications. Technovation 1995;15(3):165 – 76. Nyeck S, Sylvie P, Xuereb J-M, Chebat JC. Standardisation ou adaptation des e´chelles de mesure a` travers diffe´rents contextes nationaux: l’exemple d’une e´chelle de mesure de l’innovativite´. Rech Appl Mark 1996;11(3):57 – 74. Ostlund LE. Perceived innovation attributes as predictors of innovativeness. J Consum Res 1974;1:23 – 9 (September). Pallister JG, Foxall GR. Psychometric properties of the Hurt – Joseph –

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Cook scales for the measurement of innovativeness. Technovation 1995;18(11):663 – 75. Pearson PH. Relationships between global and specific measures of novelty seeking. J Consult Clin Psychol 1970;34:199 – 204. Raju PS. Optimum stimulation level: its relationship to personality, demographics and exploratory behavior. J Consum Res 1980;7:272 – 82 (December). Roehrich G. Nouveaute´ perc˛ue d’une innovation. Rech Appl Mark 1987; 2(1):1 – 15. Roehrich G. Les consommateurs innovateurs: un essai d’identification. Unpublished doctoral dissertation. Ecole Supe´rieure des Affaires de Grenoble, 1993. Roehrich G. Innovativite´s he´doniste et sociale: proposition d’une e´chelle de mesure. Rech Appl Mark 1995;9(2):19 – 41. Roehrich G. Causes de l’achat d’un nouveau produit: variables individuelles ou caracte´ristiques perc˛ues? Rev Fr Mark 2001;182(2001/2): 83 – 98. Simonson I, Nowlis SM. The role of explanation and need for uniqueness in consumer decision making: unconventional choice based on reason. J Consum Res 2000;27(1):49 – 68 (June). Snyder CR, Fromkin HC. Uniqueness: the human pursuit of difference. New York: Plenum, 1980. Steenkamp JBEM, Hofstede F ter, Wedel M. A cross-national comparison into the national and national cultural antecedents of consumer innovativeness. J Mark 1999;63(2):55 – 69. Steenkamp JBEM, Van Trijp HCM. To buy or not to buy? Modeling purchase of new products using marketing mix variables and consumer characteristics. Gainesville, FL: Marketing Science Conference, 1996. Valette-Florence P, Roehrich G. Une approche causale du comportement innovateur. Econ Soc Se´r Sci Gestion 1993;19:75 – 106 (October, SG). Venkatesan M. Cognitive consistency and novelty seeking. In: Ward S, Robertson TS, editors. Consumer behavior – theoretical sources. Englewood Cliffs: Prentice Hall, 1973. p. 355 – 84. Venkatraman MP, Price LL. Differentiating between cognitive and sensory innovativeness. J Bus Rev 1990;20:293 – 315. Wahlers RG, Dunn MG. Optimal stimulation level measurement and exploratory behavior: review and analysis. AMA Winter Educators’ Conference, San Antonio, TX.1987;249 – 54. Wahlers RG, Dunn MG, Etzel MJ. The convergence of alternative OSL measures with consumer exploratory behavior tendencies. In: Richard JL, editor. Advances in consumer research, vol. 13. Provo, UT: Association for Consumer Research, 1986. p. 398 – 402.

Journal of Business Research 58 (2005) 1407 – 1408

Editorial

Preface to La Londe 2003 special issue: communications and consumer behavior

This special issue represents the best of the 30th International Research Seminar in Marketing organized by the Aix Graduate School of Management (I.A.E. Aix). The seminar, now better known as the bLa Londe SeminarQ, is devoted to Marketing Communication and Consumer Behavior on a biennial basis. The conference includes indepth discussions of current research topics. There are only two tracks, and each paper is allotted forty minutes for presentation. Audience participation is not only encouraged, it is expected, so that authors may get the best feedback on their work and ideas. A total of 71 papers were submitted for double-blind review to the conference, and 36 papers were selected for presentation by a distinguished group of reviewers. The authors and the reviewers covered all five continents. From the 36 papers, we selected a subset for inclusion to the special issue of the Journal of Business Research that represents a diverse sampling of the best papers. Among them is the article awarded best conference paper: bBehavioral Outcomes from On-line Auctions: Price, Reserve Disclosure and Initial Bidding InfluencesQ by Mathew Walley and David Fortin, University of Canterbury, New Zealand. Their paper is outstanding for several reasons. First, they managed to run a clean field experiment with 120 respondents, without knowledge of their participation. Second, their analyses and reporting of the data and results were very well done and extremely clear. And third, their significant findings are counter to other research in the area, and therefore, this work should lead to replication. This carefully designed experiment must be compared against other works for the field to reconcile the differences reported in the literature about reserve prices and disclosure in on-line auctions. Other papers selected reflect vastly different approaches to topics. bThe Role of Affective Expectations in Memory for a Service EncounterQ by Elizabeth Cowley, Colin Farrell and Michael Edwardson of the University of New South Wales involves the application of luck and chance to interpretations of service. Their results showed that indi0148-2963/$ - see front matter D 2004 Elsevier Inc. All rights reserved. doi:10.1016/j.jbusres.2004.05.005

viduals with different orientations interpreted the same service experience in a different manner. The importance of affective expectations may be just as important as the experience in determining the affective reaction or outcome of the experience for some people. The paper by Flemming Hansen, bDistinguishing between Feelings and Emotions in Understanding Communication EffectsQ, is a synthesis and review of advertising response measures and delves into the distinction between cognitive and emotional information processing. Much of the paper is based on primary studies at the Copenhagen Business School, which makes the leap from pencil and paper reports of feelings to inferences about underlying emotional dispositions. It is suggested that the distinction between central/peripheral, higher/lower involvement or more or less cognitive information processing is useful with respect to measuring advertising effectiveness. It may be that emotional affect makes information processing more efficient. A very interesting partner to the Hansen paper is the Laros and Steenkamp paper, entitled bEmotions in Consumer Research: A Hierarchical ApproachQ. This paper uses the same battery of feelings used by Hansen (Richens CES 1997), but in a different domain, the consumption of food. The results of their analyses expand on the positive and negative emotional response categories to give a richer dimension to each emotion. One of the contributions of the Laros and Steenkamp paper is the exhaustive literature review and classification tables of emotions. Other researchers in this area are sure to find it valuable. The paper by Sintas and Alverez, bFour Characters on the Stage Playing Games: Performing Arts Consumption in SpainQ, looks at the symbolic consumption of art and how it relates to social class. Their paper is based on a fantastic data set of in-home interviews of 12,000 randomly selected households in Spain about their bhabits of cultural consumptionQ. Segments based on consumption habits show how the social status of individuals is linked to the world of arts. Their analyses question some of the classical approaches by Bourdieu.

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Editorial

The final contribution is a contrast in research styles to the other papers. bResearching Cultural Metaphors in Action: Metaphors of Computing Technology in Contemporary U.S. LifeQ by Denny and Sunderland shows how the cultural metaphor is useful as an analytic tool. Using ethnographic research, they demonstrate how the computer and the Internet have come to change the meanings within our day-to-day lives. In sum, these six papers represent a diverse array of research topics and styles that add to our understanding of consumers and how they relate to their environment. We have learned from reading and editing these papers and others that were submitted to the conference. We hope you enjoy reading them and encourage you to submit your work

and future the next La Londe conferences. You will find it an enriching academic experience. Gilles Laurent Carrefour Chair, HEC School of Management, Paris Judy Zaichkowsky Simon Fraser University, Canada E-mail address: [email protected]. Corresponding author. Department of Marketing, Groupe H.E.C., 78351 Jouy-en-Josas Cedex, France. Tel.: +33 1 39 67 74 80; fax: +33 1 39 67 70 87. 1 February 2003

Journal of Business Research 58 (2005) 1409 – 1418

Behavioral outcomes from online auctions: reserve price, reserve disclosure, and initial bidding influences in the decision process Matthew J.C. Walley*, David R. Fortin* Department of Management, University of Canterbury, Private Bag 4800, Christchurch 8004, New Zealand Received 1 November 2002; received in revised form 1 August 2003; accepted 1 October 2003

Abstract This study presents a conceptual model of the online auction consumer decision process and empirically tests some of the model relationships by using an experimental design. The factorial design used a combination of reserve price, reserve disclosure, and initial bidding as treatments to impact two behavioral outcome variables: final price sold and auction interest. The data were gathered via a real existing online auction site where products were auctioned, recreating a true market-based environment. The key finding is that having a $1 reserve price that is disclosed is the optimal strategy to adopt when selling goods in an online auction, if the goal of the seller is to maximize sale price and auction interest. The findings of this research provide insight into how and to what degree these factors influence the dependent variables, ultimately providing online auction hosts and sellers with possible methods for maximizing their potential income from online auctions. This research contributes in synthesizing the developed theories underlying traditional bin personQ auctions, with the emerging and rapidly growing medium of online auctions. D 2004 Elsevier Inc. All rights reserved. Keywords: Auctions; Online; Web; Reserve bidding; Hits; Behavior

1. Introduction Online auctions attract thousands, sometimes millions, of bidders for items ranging from commodities to collectibles (Massad and Tucker, 2000). Investors expect a tremendous amount of growth in online auctioning, assigning huge price/earning multiples to the major players in the industry (Massad and Tucker, 2000). Consequently, from the perspective of auction site owners and the sellers of goods online, it is extremely useful to understand what factors of the auction influence the overall interest in, and ultimately the final sale price of auctioned products. This study presents a conceptual model of the online auction consumer decision process and empirically tests * Corresponding authors. Matthew J.C. Walley is to be contacted at Tel.: +64 3 376 4142; fax: +64 3 376 4142. David R. Fortin, Tel.: +64 3 364 2987x7026; fax: +64 3 364 2020. E-mail addresses: [email protected] (M.J.C. Walley)8 [email protected] (D.R. Fortin). 0148-2963/$ - see front matter D 2004 Elsevier Inc. All rights reserved. doi:10.1016/j.jbusres.2003.10.014

some of the model relationships by using an experimental design tracking observation-based data points. The research focuses on how the factors of auction reserve price, the disclosure or nondisclosure of this reserve price, and the amount of initial bidding history in the auction influence the final sale price, and overall interest in the auction. Practically, the findings of this research provide insight into how and to what degree these factors influence the final sale price, providing online auction hosts and sellers with possible methods for maximizing their potential income from online auctions.

2. Literature review Among the most popular commerce exchange applications of the World Wide Web is the online auction. The availability and convenience of the Internet, in conjunction with the variety of products available has contributed to online auctions sites reporting 600% growth in auctions held

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(Massad and Tucker, 2000). Forrester Research (2002) predicts that the number of online auction buyers will grow from 3 million in 1998 to at least 14 million by 2003. In addition to the growing number of users, the estimated number of auction sites has also increased dramatically, as there are now more than 1660 auction sites listed on the online auction portal web site Internetauctionlist (2002). Online auctions are a new form of transaction that introduces variability into nearly all aspects of a commercial exchange. The process can be mystifying. Prices are unpredictable, consumers and suppliers are strangers, and comparison is difficult because products come packaged with services, and items on offer may be unique or obsolete (Massad and Tucker, 2000). As a consequence, some researchers believe auction itself is an inadequate term for describing relationships powered by advanced algorithmic models (Herschlag and Zwick, 2000). Online auctions represent a model for the way the Internet is shaping the new economy. In the absence of spatial, temporal, and geographic constraints, these mechanisms provide many benefits to both buyers and sellers. They are now an important component of the portfolio of mercantile processes that are transforming the economy from traditionally hierarchical to free market oriented structures (Gupta and Bapna, 2001). Kauffman and Walden (2001) provide a comprehensive review on this topic. According to Gupta and Bapna (2001), online auctions fall under the category of web-based dynamic pricing mechanisms. Under these mechanisms, consumers become involved in the price-setting process and they can experience the thrill of bwinningQ a product, potentially at a bargain, as opposed to the typically relatively tedious notion of bbuyingQ it. For sellers, these mechanisms are likely to bring access to newer markets, help clear aging or perishable inventory, and provide experiential and at times viral marketing capabilities. Nowhere are these trends as visible as in the hugely popular online auction site, eBay.com. The most popular auction sites experience millions of monthly visitors, which provide the necessary critical mass of buyers and sellers to set market prices for their goods. Massad and Tucker (2000) argue that online auctions are inherently less risky than traditional in-person auctions because the perceived risk in a consumer behavior context is largely moderated by the buyer’s ability to search out information online, thus reducing purchase uncertainty. However, Johns and Zaichkowsky (2003) emphasize some relevance of live auctions in understanding online auction buyer behavior. Commonly, in traditional consumer transactions, the most relevant matter over which buyers are uncertain is the appropriate price. Online auctions offer unprecedented access to information regarding previous sales of products, comparable to those for which they are considering placing a bid. This access allows buyers to analyze the market and develop a bidding price with greater confidence. Due to

the reduced price information risk, bidders with more information are likely to be willing to pay more than bidders with less information (Cox, 1963). The disclosure of a reserve price increases the amount of information available to the buyer; accordingly, there is some justification for believing a disclosed reserve will increase the final sale price of the goods. A key factor that makes electronic markets, such as online auctions, interesting is the potential for achieving higher efficiency. On the surface, e-markets such as eBay, with millions of registered users, would appear to be a close approximation to an economist’s idealization of a frictionless, efficient market (Gupta and Bapna, 2001). Auctioning is among the most efficient and fastest concept available to achieve fair and competitive prices and identify the optimal business partner (Rumpe, 2003). Auctioning survives via its networking capability both from a business-to-business (B2B) and a computer-tocomputer perspective (Varadarjan and Yadav, 2002). One thing for certain is that the use of information technology has brought this sphere of economic activity out of the domain of specialists to that of the technologically layperson (Gupta and Bapna, 2001). 2.1. Market segmentation According to Chen and Wilson (2002), the online auction market can be broken down into three subgroups based upon the roles of buyers and sellers; these are person-toperson, business-to-person (B2P), and B2B. First, host auction sites that serve the person-to-person segment mainly provide sellers and buyers with a public marketplace to trade online and sometimes help both parties to deal with the transactions, including billing, shipping, and handling. Popular sites that service this segment are eBay and Yahoo! The revenues of person-to-person auctions from eBay style auction sites accounted for 70% of the US$1.4 billion in goods sold online in 1997 (Chen and Wilson, 2002). Second, business-to-person host auction sites provide a digital marketplace for business suppliers to sell their excess inventories or refurbished goods to end-users. In addition, suppliers can also serve as retailers that actually get involved in the distribution of auctioned items, such as uBid. Third, the B2B segment transacts with both sellers and buyers and treats them as business units. The purpose of executing an auction can be for resale of those items to individual customers or for their own procurement, online sites that use this model include ComAuction. According to predictions made by several research firms, the B2B electronic commerce market will exceed US$4 trillion by the year 2005 (Johnson and Friedman, 2002). The concept of reverse auctions is also making some inroads, especially with the B2B segment Johnson and Friedman (2002). However, as this research focuses on online auctions in the person-to-person segment, the B2P and the B2B segments will not be elaborated upon.

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2.2. The traditional English auction model Single-item auctions are asset exchange mechanisms, which have been extensively theoretically studied, beginning with the seminal article by Nobel laureate William Vickrey (1961). More recent coverage can be found by referring to Rothkopf and Harstad (1994). Researchers studying this auction commonly make use of assumptions, such as the independent private values (IPV) assumption to derive its equilibrium characterization. Such an assumption implies that a single indivisible object is to be sold to one of several bidders (Gupta and Bapna, 2001). Each bidder is risk-neutral and knows the value of the object to him or herself, but does not know the value of the object to other bidders. It also implies that there is a finite population of bidders, each of which draws the bidder’s valuation independently from some given continuous distribution (see Milgrom, 1989, for details). For most goods being auctioned, the IPV assumption is robust. However, for collectibles, it is reasonable to assume that an individuals’ valuation will be dependent on the valuations of fellow bidders (Smith, 1989). Presumably, a profiteering collector will have the objective of at least recovering the cost of the item purchased and thus will implicitly carve his or her valuation distribution dependent on that of other bidders (Gupta and Bapna, 2001). In addition to offering single-item products for auction, English auctions enable the bidders to place open bids on the Internet detailing the amount the individual wishes to bid at, as opposed to sealed tender bids. These bids incrementally increase in value with the product being sold to the highest bidder at the end of the predetermined closing date. Auctions can be either short or long term. Long-term auctions may last up to 4 weeks, where the bidders repeatedly review the current situation. Consequently, such kinds of auctions are mainly of interest during the closing phase. On the other hand, short-term auctions simulate these last few hours immediately, creating immediate interest. These auctions may be as short as 30 minutes (Rumpe, 2003). 2.3. Gaps in the literature Interestingly, the advent of auctions over open Internet Protocol-based networks, such as the Internet, has also facilitated the pursuance of a richer set of empirically derived methodologies by today’s researchers. Most preInternet-based auction research was either purely theoretical in nature (McAfee and McMillan, 1987; Milgrom, 1989; Myerson, 1981) or involved laboratory experimentation (Kagel and Roth, 1997). Empirical research was rare, due the lack of meaningful data sets, which in turn could be attributed to the lack of mainstream appeal of online auctions. Lucking-Reiley (1999) acknowledges the difficulty in obtaining field data for testing long-standing hypotheses, such as the supposed revenue equivalence between the basic auction formats. Given the accessibility

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of the Internet, it opens the opportunity to contribute empirically to the field of online auctions. The benefits of online auctions to both sellers and buyers are undeniable. However, to date, much of the literature has focused on the benefits of individual consumers and businesses. Researchers are only beginning to question what provides benefits to individual online sellers. Specifically, what combination of factors will enable the seller to gain the maximum price for his or her product? This research proposes to narrow the gap in the literature by empirically measuring the impact of external variables or cues on outcome variables, such as the final sale price and amount of consumer interest in the auction. 2.4. Potential independent variables 2.4.1. Reserve price Waehrer et al. (1988) state that the existence of a reserve price may attract more competing merchandise into auction since reserve prices attract risk-averse sellers. Thus, the effect of reserve pricing may be to lower the average price ultimately paid in seller reserve auctions, while increasing the average size of opening bids (Massad and Tucker, 2000). Regarding auction interest, Vincent (1995) argues that higher reserve prices have the effect of bincreasing bidder participation at higher levels since the reserve would have the effect of eliminating low-valuation bidders from contentionQ (Massad and Tucker, 2000). Horstman and LaCasse (1997) argue that the disclosure of the sellers reserve has the effect of conveying information to the bidder regarding the seller’s estimation of the items value, and should therefore result in a higher selling price. Bajari and Hortacasu (2000) also find that the minimum bid is the most significant determinant of whether a bidder enters an auction. Additionally, recent research shows that a zero reserve price provides higher expected profit than a reserve price greater than or equal to the auctioneer’s salvage value for the good (Gupta and Bapna, 2001). According to Massad and Tucker (2000), when seller reserves are present, initial bids at online auctions will supersede those at in-person auctions, and because the bidders have no information to offset the information advantage of buying online, the final selling price at online auctions will exceed that of in-person auctions. Therefore, given the extensive consideration with respect to the influence of reserve price over the amount of interest and final sale price obtained in the auction, we believe there is a need for further investigation of this variable. 2.4.2. Bidding history Engelbrecht-Wiggans et al.’s (1983) early work in bidding theory proposes that it is badvantageous for a bidder to bid more aggressively when the competition increases, that is, when there are more competitors and/or more aggressive bidding competitors.Q Furthermore, Smith (1989) believes that the social inertia created by increased bidding competition will often increase the final sale price

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and overall interest in the auction. This is also supported by Johns and Zaichkowsky (2003) in the realm of online auctions as they state that the bthought of competition increases arousal in consumers and may lead to bidders being swept away in a bidding war they never intended.Q Dholakia et al. (2002) also support these concepts; they determine that potential bidders are susceptible to herding biases in online auctions. Specifically, they found that bidders gravitate toward listings with existing bids, while demonstrating no consideration for listings without any existing bids. Accordingly, we contrive previous bidding levels at the outset of our auction experiments to test if these findings hold true for online auctions. 2.5. Proposed outcome indicators The following explanations justify why we believe the potential dependent measures of final sale price and auction interest are important in increasing the general understanding of online auctions from a seller’s perspective. Accordingly, it is assumed that sellers are concerned with maximizing their financial gain in online auctions. 2.5.1. Price Massad and Tucker (2000), propose that as bidding increases during online auctions bbidders are able to access data regarding previous sales, and therefore the maximum price bidders are willing to pay will increase due to improved information.Q Specifically, they state that bthe existence of seller reserves in online auctions can be expected to moderate this effect,Q moreover, it is proposed that the inclusion of a reserve price in an online auction, will increase the final price obtained and the initial bidding price (Massad and Tucker, 2000). Smith (1989) argues that in most auctions, it is the price that is of paramount concern for sellers. 2.5.2. Auction interest This can be approximated by using the amount of hits received on a particular auction. Massad and Tucker (2000) propose that the increased presence of bidders in a particular online auction will result in higher sale prices being obtained, due to increased bidder competition. Previous research found strong evidence that download counts is used by consumers as surrogates of product quality to download the software. These impacts were nonlinear and dynamic. This result may be applicable to online auctions with regards to the number of hits, and it is hypothesized that more hits on a particular auction will stimulate bidder interest and increase the number of bids placed on the auction. 2.6. Potential influencing factors The factors of gender, previous reputation of individual bidders (labeled purchasing profile in this research), the

aggregate average profile of bidders (labeled average bidding profile), and the number of unique bidders may influence the outcome indicators. 2.6.1. Gender Traditionally, in auction research, it has been noted that there are perceived gender differences in purchasing behavior (Smith, 1989). Current research has found that men participate in online auctions more than women (bDemographics: demographics influence online spending,Q). However, the number of women participating is gradually increasing from 35% to 45% (Crocket, 1999). 2.6.2. Reputation of participants and purchaser Reputation is defined as the boverall quality or character as seen or judged by people in generalQ (Merriam-Webster, 2000). Fombrun (1996) describes how companies (through the public relations function) generate breputational capitalQ by developing strong and consistent images, and thereby compete for prestige and achieve celebrity. Another definition of reputation is brecognition by other people of some characteristic or abilityQ (Johnston, 2002). Reputation is a subjective concept that resides in the mind of the buyer. The inability to observe and quantify reputation makes it difficult to estimate its effect on price. However, it is believed that if two sellers offer the same product, the seller with the bbetterQ reputation should receive a higher price, all other things being equal. Klein (1997) views reputation as a mechanism for rewarding good conduct and punishing misbehavior, and hence is the bglueQ that keeps our relationships together and society functioning. Major auction sites use a feedback system that enables buyers and sellers to read previous auction comments about an individual’s feedback score, such as comments from buyers and/or sellers and the reasons for positive or negative ratings. The feedback system offers a benefit to researchers in quantifying the reputation of the seller (and buyer) when an auction is successfully concluded (Johnston, 2002). According to Chen and Wilson (2002), the feedback ratings also help to improve buyers’ decision making and increase the odds of participation in a successful auction, as buyers prefer to deal with known suppliers to reduce risk. 2.6.3. Unique bidders The number of individual bidders in an online auction stimulates increased interest in the auction, in the same manner as traditional auctions (Smith, 1989).

3. Hypotheses By synthesizing the findings of the literature review, a number of key hypotheses are proposed. The first is that the level of the reserve price in an online auction will exert an influence over the final sale price obtained and the level of

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interest in the auction. It is hoped that if the theory presented by Waehrer et al. (1988) applies to online auctions then a decrease in the reserve price will result in increased buyer interest and final sale price. The following hypotheses are reflected in the conceptual model presented in Fig. 1. Hence, it is hypothesized that H1. A low reserve price results in a higher final sale price and overall interest in an online auction, when compared to a high reserve price (relative to the price of the product). The second is that disclosure of the reserve price will exert an influence over the final sale price obtained and the level of interest in the auction. We believe that if the theory of Horstman and LaCasse (1997) proves to be relevant for online auctions, then the disclosure of the reserve will result in an increase in overall auction interest and final sale price. Hence, it is posited that H2. The disclosure of a reserve price results in a higher overall level of consumer interest in an online auction, and in turn a higher final sale price obtained in the auction. Finally, the initial bidding history of the auction will exert an influence over the final sale price obtained and the amount of interest in the auction. Smith (1989) believes that under the conditions of a traditional auction, a degree of social inertia is created by increased bidding, stimulating higher levels of interest in the auction, and accordingly increasing the final sale price obtained in the auction. Therefore, if the theory of social inertia applies to online auctions, we hypothesize that an increase in the initial bidding history of the auction will result in an increase in

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auction interest and the final sale price obtained. Consequently, it is proposed that H3. An increase in the initial bidding history of an online auction will result in a higher level of auction interest and a higher final sale price obtained in the auction.

4. Method 4.1. Subjects and design To collect data for the experiment, a total of 160 individual auctions were posted on an Internet auction site. Participants in the auctions were not informed of nor selected for the experiment and were therefore behaving as expected under normal auction conditions. The experiment consisted of a 2 (reserve price: $1 or $15)2 (reserve price: disclosed or not disclosed)2 (bidding level: high or low) factorial design, resulting in eight experimental conditions. Each auction was set up to match one of the eight experimental conditions; otherwise, all other controllable auction variables remained constant. Specifically, the data were collected by observing auctions being posted for a 3-day period (Monday 9 p.m. through Wednesday 9 p.m.). This was to ensure that website traffic was relatively constant for all experiments. The product category chosen for all auctions was disk-based media, such as DVD movies and Sony Playstation games. No picture of the product was offered. The product was sold using an established trading account. The text description of the product was constant,

Fig. 1. Conceptual model.

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apart from title differences. Bidder questions regarding the auction were not answered. The auctions were all posted in the same DVD or gaming section of the auction site. Direct bank deposit payment was used to complete all auction transactions and was the only accepted form of payment identified in the auction text. The selection of DVDs and Playstation games as a category is consistent with Massad and Tucker’s (2000) statement that predominant goods traded in online auctions are commodities or products categorized as bsearchQ goods. Furthermore, Smith (1989) believes that due to the rudimentary nature of commodity goods, their final pricing in auctions is only determined by natural market conditions, in contrast to the influence exerted by forces of social classification and manipulation when auctioning collectible goods. Therefore, we decided to use DVDs and Playstation games due to their relatively low cost and high consumer appeal as a commodity. The exact choice of titles for sale was determined by reviewing the top-selling DVD and Playstation game list from a local retailer to ensure that all titles had approximately the same level of consumer desirability in the local market. The DVD and game titles selected all had similar characteristics, that is, familyoriented movies to provide a consistent demographic appeal between experimental conditions. The exact DVD or game title selected for each auction was rotated for each of the 20 experiment rounds to ensure the desirability of the exact DVD or game title was not confounding the results.

a DVD or Playstation game, is expected to be half of full retail price, the expected sale price of the auctions was predicted to be approximately $25. Therefore, the reserve levels of $1 and $15 can be deemed to represent both a low and high reserve price, relative to the expected sale price of the product. Reserve disclosure: The reserve price of the auction was either disclosed or not disclosed in the text of the auction. If the reserve was disclosed, the auction text merely stated breserve price is $. . ..Q In the case of the reserve being nondisclosed, the auction text remained silent in respect to reserve. However, the auction participants would have been aware that the auction did have a reserve, as site rules will not allow an auction to commence without a specified reserve. Bidding history: The bidding history of the auction was contrived using pseudonym bidding accounts established by the researchers. The bidding history was set to either a high or low level for each auction, depending on the relevant experimental conditions. A low bidding history was simulated by placing no bids on the auction, while a high bidding history was simulated by placing 10 bids early in the auction. The selection of the high bidding level was based around the researchers’ previous experience with online auctions suggesting that most auctions for DVD and Playstation game type commodities not often exceeding 15 bids during the entire auction period. 4.4. Dependent measures and covariates

4.2. Data collection procedure The auctions were simultaneously posted on the auction site at 9 p.m. on Monday evening and were set for a 3-day time limit. If a high bidding level was required for the auction’s experimental condition, 10 bids were immediately placed on the auction by pseudonym bidders. If the reserve was to be disclosed, this was specified in the text of the auction. Finally, the reserve price was set during the initial posting of the auction through the auction site registration. The auctions were observed at 3-hour intervals with the amount of interest in the auction being recorded for potential patterns. In addition, due to the anonymous nature of the Internet, online auction participants were not aware that they were being observed. Therefore, aside from observation, no other action was instigated in respect to the auction process by the researchers. At the conclusion of the auction, the winning bidder was contacted by the researcher, bank account details were provided, the goods were then sent to the purchasers delivery address completing the transaction. All information in respect to the auctions was then downloaded from the auction site for analysis. 4.3. Independent variables Reserve price was set at either a $1 or $15 level. Given that the final sale price of a second-hand commodity, such as

The dependent variables were final sale price and auction interest level. The final sale price was considered to be the final bidding level of the auction prior to any additions for postage and auction site fees. The auction interest was measured using an Internet hit counter placed on each auction; this could only be viewed by the researchers, and multiple hits from individual members were allowed. In addition, four covariates were also recorded, namely, gender of the purchaser, number of unique bidders on the auction, profile of the final purchaser, and average profile of bidders on the auction. The profile of the final purchaser and the average profile of all bidders were determined using the positive feedback ratings associated with all individuals who transact on the auction site. These profiles are developed based around the amount of transactions completed successfully by an individual trader.

5. Results All continuous variables were examined statistically to meet assumptions of normal distributions. Two variables appeared to be normally distributed, while three showed skewness and kurtosis levels outside the acceptable range of 2bxb2. To rectify the problems of skewed and highly kurtotic data distributions, these variables were transformed

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using a reciprocal reflex procedure (using the 1 (1/x) formula). The procedure rectified the problem for two out of three variables (final sale price: skewness=3.45 to 0.17, kurtosis=13.09 to 0.65; bidding profile: skewness=7.70 to 0.38, kurtosis=80.8 to 0.60) but only did a slight improvement for the purchaser profile variable (skewness=4.89 to 3.66, kurtosis=34.24 to 14.29). After completing the procedure to satisfy the assumption of normality, ANCOVA tests were conducted on both of the dependent measures, final sale price and auction interest. 5.1. Effects on the final sale price Table 1 includes a number of significant main effects. First, with regards to sale price as a dependent variable, main effects of reserve price and reserve price disclosure were significant at ( Pb.001). Two out of three independent variables appear to have some effect on the final price obtained in the sale of a product in an online auction (see Fig. 2 for a visual representation). Both main effects demonstrated large and moderate effect sizes, respectively, with reserve price disclosure (e 2=.29) showing the largest effect followed by reserve price level (e 2=.13). However, bidding history did not demonstrate any significant effect on the final price obtained by the seller. The descriptive statistics for means and standard deviations are displayed in Table 2. Both main effects observed were significantly adjusted by the average bidder profile ( Pb.05). Although the effect here is small, an examination of the means reveals that the final price obtained is lower as the average experience level of bidders increases. Thus, the final sale price is highest only under a $1 reserve price, which is disclosed ( Pb.001). In addition, if a $1 reserve is not disclosed, then the influence of a $1 auction is significantly eroded. A possible explanation for this effect could be that when the reserve is disclosed, there is typically an increased legitimate interest in the auction leading to an increase in

Fig. 2. Estimated marginal means of final sale price.

final sale price. However, when the reserve is not disclosed, there is a need to create interest in the auction, which can only occur through increased bidder participation. Yet, there is some evidence presented by Smith (1989) suggesting that under some circumstances of increased participation, risk- and competition-averse bidders will withdraw from placing bids at higher reserve price levels. This could possibly be associated with individual bidder’s price expectations being exceeded under the conditions of a $15 reserve auction. In sum, it appears that the optimal strategy to obtain the highest sale price is to use a disclosed $1 reserve price. 5.2. Effects on the overall auction interest Reserve price and reserve price disclosure also register as main effects significant at Pb.001 with respect to overall auction interest, measured here by total hits (Table 1). This means that two of the three independent variables significantly influence the level of hits, and thus the overall level of interest in a particular online auction (see Fig. 3). They

Table 1 ANCOVA results for final sale price and total hits Source of variation

F value, df=1

Dependent variable

Final sale price

Main effects Reserve price value Reserve price disclosure Bidding history

21.8 61.2 2.5

Significance

Effect size (e 2)

F value, df=1

Significance

Effect size (e 2)

Total hits .000 .000 .113

.13 .29 .02

18.9 48.0 2.83

.000 .000 .092

.11 .25 .02

Interaction effects Reserve PriceReserve Disclosure Reserve PriceBidding History Reserve DisclosureBidding History Reserve PriceReserve DisclosureBidding History

1.2 0.04 0.04 0.04

.270 .787 .847 .855

.01 .00 .00 .00

0.32 0.24 0.01 0.34

.538 .627 .975 .559

.00 .00 .00 .00

Covariates Gender Average bidder profile No. of unique bidders Purchaser’s profile

0.94 4.47 0.03 0.01

.335 .036 .760 .839

.01 .03 .00 .00

0.23 1.21 2.99 0.04

.653 .271 .086 .846

.00 .01 .02 .00

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Table 2 Dependent variables: final sale price and total hits Treatments, means (S.D.) Reserve price

$1

Reserve disclosure

No

$15

Bidding history

Low

High

Low

High

Low

High

Low

High

Sample size

n=20

n=20

n=20

n=20

n=20

n=20

n=20

n=20

Final price paid ($) Total hits

23.9 (11.61) 120.1 (37.50)

24.8 (10.37) 126.5 (36.75)

30.8 (14.24) 161.2 (45.15)

32.3 (13.84) 177.6 (48.72)

20.0 (10.73) 72.6 (38.15)

20.9 (10.02) 93.1 (40.59)

26.5 (12.50) 131.1 (44.35)

28.2 (13.22) 142.9 (43.37)

Yes

also showed moderate to large effect sizes with reserve price disclosure (e 2=.25) having the largest effect followed closely by reserve price (e 2=.11). However, bidding history again failed to impact on the number of visits to the online auction. Overall, there appears to be a large degree of consistency with respect to the influence of the independent variables over the dependent measures. The results suggest that total hits are maximized when there is a $1 reserve price that is disclosed. Under conditions of the reserve price being disclosed, the seller will be able to obtain high levels of interest in the auction, and while it is preferable for the auction to have a $1 reserve as well, the disclosure of the reserve remains the critical and dominant element in stimulating auction interest. For total hits, none of the covariates showed any significant effect ( PN.05). To summarize the online auction data thus far, it appears that having a $1 reserve price, which is disclosed, is the optimal strategy to adopt when selling goods in an online auction, if the goal of the seller is to maximize sale price and auction interest. However, generating some bidding history early in the auction did not impact on the outcome of the auction. With respect to the covariate of gender, more research needs to be conducted to determine if this effect was primarily due to the nature of the commodity used for the experiments. Finally, with respect to the covariate of the average bidders’ profile, there is minimal to no control on this covariate by the seller, therefore, the practical implications of being aware of its influence are somewhat limited.

Fig. 3. Estimated marginal means of total hits.

No

Yes

6. Discussion H1 states that a low reserve price ($1) will result in a higher final sale price and overall interest in an online auction, when compared to a high reserve price ($15). As discussed in the Results section, there was strong support for this hypothesis with the final sale price and overall auction interest being consistently higher for $1 reserve auctions, regardless of reserve disclosure or bidding history, when compared to $15 reserve auctions. Hence, we find that the findings of Gupta and Bapna (2001) apply to online auctions, and that a low reserve has the effect of attracting a larger spectrum of potential bidders to the auction. It would suggest that Smith’s (1989) theory of social inertia increases bidder interest and results in increased competition, which in turn results in higher sale prices. This was, however, contrary to the findings of Haubl and Popkowski Leszcyc (2000), who determined that higher seller-specified reserve prices led to fewer bidders per auction, but higher selling prices. It also contrasts with a recent study by Ariely and Simonson (2003) where starting prices for auction of football game tickets lead to higher winning bids but only when comparable items were not immediately available in the same context. Gilkeson and Reynolds (2003) also found some conflicting results for starting price as a relative measure to final winning bid for collectible items. H2 states that the disclosure of a reserve price will result in a higher overall level of consumer interest in an online auction, and in turn a higher final sale price obtained in the auction. The findings support this hypothesis with strong main effects being observed for both dependent measures of final sale price and overall auction interest. Because there is no significant body of literature discussing the effects of reserve price disclosure in online auctions, we have made inferences based around some of the discussions on reserve price by Horstman and LaCasse (1997), who believed the disclosure of a reserve price reveals the seller’s estimation of the good’s value to potential bidders. Consequently, the disclosure of reserve price will result in attracting individuals interested in purchasing the goods at the reserve price indicated. In addition, Horstman and LaCasse, who developed their ideas based around traditional in-person auctions, believed that the disclosure of the reserve price would result in an increase in the final sale price of the goods. Therefore, in light of the results of this research, it can be concluded

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that the conclusions of Horstman and LaCasse also apply in the realm of online auctions. H3 states that an increase in the initial bidding history of an online auction will result in a higher level of auction interest and a higher final sale price obtained in the auction. Overall, the results do not support this hypothesis. Therefore, H3 is not supported for both dependent variables, but further research may be required. It would appear that initial bidding does accelerate the auction process, but does not alter the outcome. 6.1. Managerial implications Theoretically, this research helps to bridge the gap between the expansive literature and theories relating to traditional in person auctions and the newly emergent technology of online auctions. Predominantly, this research has proven that while there are rudimentary physical differences between traditional and online auctions, fundamentally, the underlying consumer psychology of online auctions does not differ greatly from the consumer behavior paradigms of traditional in person auctions. Practically, this research has begun to develop a model of how auction agents, hosts, and sellers can set up auctions to maximize potential sale price and overall auction interest. Clearly, these findings have obvious marketing benefits for either individual resellers or the new breed of small business entrepreneurs emerging from this new peer-to-peer channel of distribution. Summed up in a few words, this initial phase of the research has concluded that an auction with a disclosed, $1 reserve price is most likely to result in a higher final sale price and level of auction interest. 6.2. Directions for future research A number of factors can impact the outcome of an auction and, more importantly, different combinations of these can contribute to varying outcomes. Primarily, there is a need to investigate the influence of other factors related to the online auction process such as the inclusion of pictures, the reputation of the seller through the testing of differing feedback ratings, the impact of reserve price across other currencies, the varying effects of short- and long-term auctions, and the correlation between gender and product interest. As a direct consequence of questions emerging from this research, more research is required to fully understand the influence of bidding history as it accelerates the bidding process. As stated in the Limitations section, person-to-person commodity auctions are typically governed by a distinct set of norms and rules; therefore, further research is required in the area of auctioning with respect to B2B materials procurement and person-to-person collectible auctions. A study of other auction sites in the world would provide useful information about online auction behavior across cultures, especially cultures such as the Dutch who follow a

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vastly differing auction methodology and style compared with the traditional English model. In-depth qualitative analysis of the reasoning underlying the decisions of auction participants and purchasers would provide information as to why certain behaviors were exhibited, and more importantly, if they were consciously affected by the experimental stimulus. In addition, this may provide some insight into the social impacts of online auctions, and in particular how online auctions are changing the relationships and expectations between buyers and sellers. Finally, some consideration needs to be given to the contrasting findings of this research and Haubl and Popkowski Leszcyc’s (2000) research, with each paper implying vastly different approaches to maximizing sale price when manipulating the reserve price. 6.3. Limitations Due to the nature of the product (DVDs and Playstation games) being auctioned, the results of the auction can only be generalized to commodity goods or search goods. The reputation of a seller has also been acknowledged to have a direct influence over the amount of interest in a conventional auction (Smith, 1989). However, whether this claim applies to online auctions has not been established. Therefore, the presence of seller reputation should be considered not only as a limitation to the generalizability of this research, but also as a potential area for future research through explaining the exact influence of seller reputation over the dependent variables of interest.

References Ariely D, Simonson I. Buying, bidding, playing, or competing? Value assessment and decision dynamics in online auctions. J Consum Psychol 2003;13(1–2):113 – 23. Bajari P, Hortacasu A. Winner’s curse, reserve prices and endogenous entry: empirical insights from eBay auctions. Working paper, Department of Economics, Stanford University; 2000. Chen H., Wilson D. Online auctions: are relationships doomed? 2002. Available at: http://www.bath.ac.uk/imp/pdf/xx _ ChenWilson.pdf. Retrieved October 6, 2002. Cox DF. The measurement of information value: a study in consumer decision making. In: Decker WS, editor. Emerging concepts in marketing. Chicago (IL)7 American Marketing Association; 1963. p. 413 – 21. Crocket RO. Going, going. . .richer. Bus Week 1999 December 13;(3659). Demographics: demographics influence online spending; 2002. Available at: http://www.cyberatlas.internet.com/big_picture/demographics/article/ 0,1323,5901_344751,00.html. Retrieved October 10, 2002. Dholakia UM, Basuroy S, Soltysinski K. Auction or agent (or both)? A study of moderators of the herding bias in digital auctions. Int J Res Mark 2002 June;19(2). Available at: http://www.business2.com/articles/ 1999/06/content/editors.html. Retrieved October 8, 2002. Engelbrecht-Wiggans R, Shubik M, Stark RM. Auctions, bidding, and contracting: uses and theory. New York7 New York Univ. Press; 1983. Fombrun CJ. Reputation: realizing value from the corporate image. Boston (MA)7 Harvard Business School Press; 1996. Forrester Research. Available at: http://www.forrester.com. Retrieved October 10, 2002.

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Gilkeson J, Reynolds K. Determinants of Internet auction success and closing price: an exploratory study. Psychol Mark 2003;20(6):537 – 66. Gupta A, Bapna R. Online auctions: a closer look. Handbook of electronic commerce in business and society. Boca Raton (FL)7 CRC Press; 2001 Available at: http://misrc.umn.edu/workingpapers/fullpapers/2001/ 0120_050101.pdf. Retrieved October 10, 2002. Haubl G, Popkowski Leszcyc P. Going, going, gone—determinants of bidding behavior and selling prices in Internet auctions. Paper presented to Division 23, APA Conference, San Francisco, CA, 2000. Herschlag M, Zwick R. Internet auctions—popular and professional literature review. Q J Electron Commerce 2000;1(1). Horstman I, LaCasse C. Secret reserve prices in a bidding model with a resale option. Am Econ Rev 1997;87:663 – 84. Internetauctionlist. Available at: http://www.internetauctionlist.com. Retrieved October 10, 2002. Johns C, Zaichkowsky J. Bidding behavior at the auction. Psychol Mark 2003;20(4):303 – 22. Johnson NA, Friedman HH. Online auctions for business to business transactions. Washington (DC)7 National Public Accountant; June 2002. Johnston T. Reputation price premiums in online auctions; 2002. Available at: http://www.sbaer.uca.edu/Research/2001/SMA/01sma178.html. Retrieved October 9, 2002. Kagel JH, Roth AE. The handbook of experimental economics. USA: Princeton Univ. Press. Kauffman R, Walden E. Economics and electronic commerce: survey and research directions. Int J Electron Commerce 2001;17. Klein DB. Reputation: studies in the voluntary elicitation of good conduct (economics, cognition, and society). Ann Arbor (MI)7 University of Michigan Press; 1997. Lucking-Reiley D. Using field experiments to test equivalence between auction formats: magic on the Internet. American Economic Review 1999 December;89(5):1063 – 80. Massad VJ, Tucker JM. Comparing bidding and pricing between in-person and online auctions. J Prod Brand Manage 2000;9(5):325 – 40. McAfee RP, McMillan J. Auctions and bidding. J Econ Lit 1987;25: 699 – 738.

Merriam-Webster collegiate dictionary. Springfield (MA)7 MerriamWebster; 2000. Milgrom P. Auctions and bidding: a primer. J Econ Perspect 1989;3:3 – 22. Myerson RB. Optimal auction design. Math Oper Res 1981;6:58 – 73. Rothkopf MH, Harstad RM. Modeling competitive bidding: a critical essay. Manage Sci 1994;40(3):364 – 84. Rumpe B. E-Business Experiences with On-line Auctions; 2003. Available at: http://www4.in.tum.de/~rumpe/ps/IRMARumpe.pdf. (2004, August 11). Smith CW. Auctions: the social construction of value. Berkeley (CA)7 University of California Press; 1989. Varadarjan PR, Yadav MS. Marketing strategy and the Internet: An organizing framework. J Acad of Mark Sci 2002;30(4):296 – 312. Vickrey W. Counter-speculation, auctions, and competitive sealed tenders. J Finance 1961;41:8 – 37. Vincent D. What reserve prices may be kept secret. J Econ Theory 1995; 65(2):575 – 84. Waehrer K, Harstad R, Rothkopf M. Auction form preferences of riskaverse bid takers. Rand J Econ 1988;29(1):179 – 92.

For Further Reading Amazon.com. Available at: http://www.amazon.com. Retrieved October 13, 2002. Bromley DB. Reputation, image, and impression management. West Sussex (England)7 Wiley; 1993. Cox DF. Risk taking information handling in consumer behavior. Boston (MA)7 Harvard Univ. Press; 1967. Daly J. Let’s make a deal. Business 2.0, June 1999. Patsuris P. One-to-one auction; 1999 Available at: http://www.forbes.com/ tool/html/98/jan/0116/side1.htm. Retrieved October 08, 2002. Weiss AM, Anderson E, MacInnis DJ. Reputation management as a motivation for sales structure decisions. J Mark 1999;63(4):74 – 89.

Journal of Business Research 58 (2005) 1419 – 1425

The role of affective expectations in memory for a service encounter Elizabeth Cowleya,*, Colin Farrellb, Michael Edwardsonb a

Discipline of Marketing, University of Sydney, Sydney, NSW 2006, Australia School of Marketing, University of New South Wales, Sydney NSW 2052, Australia

b

Received 1 December 2002; received in revised form 1 September 2003; accepted 1 October 2003

Abstract Affective expectations influence affective reactions at the time of an experience and when the individual reflects back on the episode. The study reported here investigates whether a consumer’s uncertainty orientation explains how they use affective expectations. The results reveal that people with an internal locus of control continue to use their expectations after the event. Luck-oriented dinternalsT selectively remember the facts to be expectation-consistent. Chance-oriented dinternalsT reinterpret the facts to be more expectation-consistent. Affective expectations do not influence affective reactions after they are formed for consumers with an external locus of control. In fact, affective expectations have very little impact on the affective reactions of luck-oriented dexternalsT, even when they are initially formed. Implications for service settings are discussed. D 2004 Elsevier Inc. All rights reserved. Keywords: Consumer behavior; Affective expectations; Memory; Uncertainty; Luck

1. Introduction Rob and Janet recently went to see a play; they both had great expectations for a pleasant evening out. They had choice seats in a wonderfully restored theatre. As the scenes progressed, Janet felt the disappointment set in. The acting and scripting were not as she had hoped. She thought it would be such a brilliant experience. Janet left having enjoyed certain aspects of the play, but overall not really feeling as satisfied as she had expected. Their discussion after was tempered, they both wanted to have enjoyed the play more. Over the next few days, Janet heard Rob recount the events of the evening. Each time the story was told it was more positive, the details were correct, but he now found humor in what had been disappointing. Janet began to wonder if his expectations had colored the way he was reflecting on the experience or whether her memory for the details of the evening was failing her. The affective expectation model (AEM: Wilson et al., 1989) asserts that how much a person thinks they will like * Corresponding author. Tel.: +61 2 9384 3384; fax: +61 2 9663 1985. E-mail address: [email protected] (E. Cowley). 0148-2963/$ - see front matter D 2004 Elsevier Inc. All rights reserved. doi:10.1016/j.jbusres.2003.10.011

an experience (affective expectation) is as important as what actually happens during the experience in the determination of how much the experience is enjoyed (affective reaction). The role of affective expectations (AEs) does not always end with the affective reaction (AR) during the experience. AEs may be used to reinterpret or selectively remember the experience (Klaaren et al., 1994). We propose that an individual’s approach to uncertain situations may determine how AEs influence his or her AR to the event and reflection on the experience. This study investigates the role of AEs in forming initial ARs, how the ARs may change over time, and the moderating effect of an individual’s uncertainty orientation.

2. Affective expectations Although AEs influence the evaluation of an experience (Geers and Lassiter, 1995, 2002; Hodges et al., 2000; Klaaren et al., 1994; Wilson et al., 1989), it is unclear whether AEs continue to play in an individual’s willingness to repeat an activity after an AR has been experienced (Klaaren et al., 1994). The initial effects hypothesis purports

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that AEs exert their influence only at the time that people experience an activity, by directing attention toward expectation-consistent information. If a consumer experiences a product or service that is inconsistent with their expectations, they may alter their AR to be more expectationconsistent. According to the initial effects hypothesis, the direct role of AEs ends with the initial AR, no additional effect occurs as time passes. For instance, a consumer’s expectation of enjoying a play will affect their perceptions of the experience, their evaluation of the experience, and therefore indirectly, their willingness to revisit the theatre or tell others to attend the play. However, the evaluation, once formed, will not be further affected by the initial belief that the experience would be pleasant. A second hypothesis posits that AEs continue to influence evaluations of the consumption experience. The reinterpretation hypothesis suggests that people continue to reinterpret aspects of the experience that were inconsistent with expectations. The event becomes more expectationconsistent by altering the meaning of features of the experience, the poor acting of a character becomes a humorous parody, or by adjusting the importance of a feature of the experience, the poor acting played only a small role in the overall experience. Memory of the features does not change, but the interpretation of the features does change. Hodges et al. (2000) and Klaaren et al. (1994) found results supporting this hypothesis. The third hypothesis also proposes that the role of AEs does not end with the initial AR. This proposition includes a change in memory of the features of the experienced episode. According to the selective memory hypothesis expectationinconsistent aspects of the experience are less accessible than expectation-consistent aspects of the experience. Since expectation-consistent memories are more accessible, ARs become more expectation-consistent over time. In this case, the poorly acted scenes become less accessible and therefore less influential on ARs, but the exquisite music and avantgarde sets are accessible, resulting in a more positive AR. In other words, the interpretation of a particular feature does not change, but the ability to remember a particular feature does change. An implicit assumption in the last two hypotheses is that when individuals are responding to the question, bHow much did you enjoy that experience?Q they reconstruct the experience and form an evaluation, as opposed to retrieving the AR stored during the experience. Each of the three explanations is plausible. We assert that the uncertainty orientation of the consumer may determine how, and to what extent, AEs influence ARs. Four uncertainty orientations are described in the next section.

3. Uncertainty orientation Consumption experiences always involve a degree of uncertainty because the outcome is at least partially dependent on the somewhat unpredictable behavior of

others. Not all individuals perceive and react in a similar manner to uncertain situations (Breen and Zuckerman, 1999; Zuckerman and Kuhlman, 2000). We propose an uncertainty orientation framework that uses an individual’s locus of control to further divide Friedland’s (1998) luck versus chance orientation, a tendency to attribute outcomes to either luck or chance. What is the difference between luck and chance? bThe notion of causelessness is so alien to us in the absence of a known because we tend to attribute events to imaginary causes like luck and chanceQ (Wagenaar and Keren, 1988). Luck is a causal category used to explain successes and failures that cannot be attributed to ability and effort, or task difficulty (Weiner et al., 1971). Chance distributes events fairly and evenly, producing all possible outcomes with equal frequencies in the short and long term (Wagenaar, 1989; Wagenaar and Keren, 1988; Keren, 1994; Friedland, 1998). Moreover, chance outcomes are perceived as selfcorrecting, whereby a deviation in one direction causes an equal deviation in the opposite direction to restore equilibrium (Tversky and Kahneman, 1971; Kahneman and Tversky, 1972). Therefore, people misunderstand chance outcomes believing the process displays a memory and sense of justice (Fischhoff, 1982), leading to the belief that outcomes are dependent on one another. 3.1. Luck orientation An individual’s orientation toward luck versus chance determines the use of probabilistic outcomes in forming expectations, particularly under uncertain circumstances (Friedland, 1992, 1998; Keren and Wagenaar, 1985, 1987; Wagenaar, 1989; Wagenaar and Keren, 1988). Luckoriented people pay little attention to probabilities that define the decision problem. They expect carryover from one random or independent event to another. However, all luck-oriented people are not alike; they can have either an internal or external locus of control. Some luck-oriented people, luck internals, believe that luck is a stable internal force that will influence events in their favor (Darke and Freedman, 1997). For example, some people believe they have an advantage betting at the track or playing poker machines because they are lucky. Other luck-oriented people, luck externals, believe that luck comes and goes, but it can be detected (Friedland, 1998; Wagenaar, 1989). For example, if something goes well in the morning, it is a sign of a lucky day, if something goes wrong they wait for two other negative outcomes because bad luck strikes in threes. 3.1.1. Luck internals Luck internals feel personally lucky, and as a result they have more positive expectations for the outcome of events (Darke and Freedman, 1997). This group perceives a strong outcome–person correspondence because they consider an outcome to be dependent on the involved person’s luck

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(Friedland, 1998). This group has a high desire for control and believes that they can control events. Since luck internals have a personal stake in the consistency of expectation and outcome, they are particularly likely to assimilate their AEs into their AR. Over time, luck internals selectively remember positive outcomes in general, but particularly when they are consistent with their initial expectations because an ego defensive motivation directs them to convince themselves they understood their luck. 3.1.2. Luck externals Luck externals believe that when an unusually high frequency of similar outcomes occurs, luck caused the sequence (Wagenaar, 1989; Teigen, 1994; Friedland, 1992; 1998). They think that good and bad luck lasts for certain periods of time, and although they cannot control luck, they can detect the beginning or end of a lucky streak with signs in the environment (Friedland, 1998). Consequently, making the prediction of the outcome in uncertain settings is a task of detecting the presence of good or bad luck (Wagenaar, 1989). Luck externals are least susceptible to the hindsight bias (Farrell et al., 2002), as they are more focused on outcomes and whether the outcome can be used in the detection of the beginning or end of a lucky streak, with an eye to predicting future events. This group is least likely to use their AEs to reinterpret or selectively remember an experience. 3.2. Chance orientation Chance-oriented people see decision making in uncertain settings as a task of guessing what the outcome will be by looking at the decision problem and using information that might assist them in understanding the patterns in chance (Friedland, 1998). Chance-oriented people are likely to believe that the outcome will be the same regardless of the person involved. These people also expect that chance will distribute events evenly such that all possible outcomes will occur with equal frequency (Wagenaar, 1989; Wagenaar and Keren, 1988; Keren, 1994; Friedland, 1998). As is the case with luck-oriented people, not all chance-oriented people are the same. Some chance-oriented people, chance internals, believe that there is a pattern to uncertain outcomes: stability in external probabilistic events. Consequently, they can improve the likelihood of guessing correctly by dseeingT the pattern. Other chance-oriented people, chance externals, hold the more rational belief that there is no reliable process for predicting the outcome of uncertain events (Darke and Freedman, 1997). 3.2.1. Chance internals Chance internals believe they can gain some control by looking for information that will improve their ability to predict random events. They try to understand the environment in which they live and to gain confidence in their understanding using a kind of bcreeping determinismQ by

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Table 1 Summary of the role of affective expectations Internal locus of control

External locus of control

Luck orientation

Chance orientation

Selective memory 1) AEs assimilated into ARs. 2) Good memory for AE-consistent features. 3) AR moves toward AE over time. No effect 1) AEs not assimilated into ARs. 2) Good memory for the features. 3) No change to AR over time.

Reinterpretation 1) AEs assimilated into ARs. 2) Reinterpret events to be AE-consistent. 3) AR moves toward AE over time. Initial effects 1) AEs assimilated into ARs. 2) Good memory for the features. 3) No change to AR over time.

updating their knowledge of a phenomenon with observations of perceived cause and effect. Chance internals are motivated to reinterpret events to be expectation-consistent such that their skill at predicting outcomes is not challenged. 3.2.2. Chance externals Chance externals see little difference between chance and luck because they are most likely to understand the properties of randomness. Although their expectations may affect their perception and evaluation of a consumption experience, these rational externally oriented individuals are not motivated to reinterpret the events that occurred during the experience or to selectively retrieve expectation-consistent aspects of the episode. We hypothesize that the initial effects explanation best describes the behavior of the chance external. In summary, internally focused people are motivated to change the outcome of an experience either by reinterpreting the facts, or selectively remembering them. Luck internals selectively remember events because the outcome is attributable to their own luck status. Chance internals reinterpret events to defend their belief that they skilled at predicting uncertain events. Externally focused people do not believe they have control over events. Luck externals believe outcomes can be predicted by the detection of lucky streaks. Since the outcome does not reflect personally on them, AEs will have little effect during or after the experience. Chance externals view the outcome in an uncertain setting as not predictable. They may be motivated to pay more attention to expectation-consistent information because they hope their AEs are met, but that is where the role of AEs ends. The expected results are summarized in Table 1.

4. Empirical work 4.1. Design A 22 between-subjects design was used. The factors were expectations (positive, negative) and experienced

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outcome (positive, negative). The participants were divided into uncertainty orientation on the basis of their locus of causality scale (internal locus of control and external locus of control) and their responses to four luck/chance orientation scenarios adapted from Friedland (1998). 4.2. Procedure One hundred fifty-two undergraduate students received course credit for participation in the study. Participants were told they would be reading a story about going to a restaurant. They were asked to use their imaginations to picture the events as they were described in the story. Two paragraphs introduced the participant to the restaurant experience as an evening out with a friend. The episode began with them choosing a restaurant. They stepped into one restaurant to look at the menu. They were given an initial impression of the restaurant, the food, the service, and the way the evening might unfold (positive or negative). Thirty-five postgraduate marketing students participated in a pretest of the restaurant stories. They were asked to list events that might occur in a restaurant that were either positive or negative. Their responses were used in the development of the stories. The likelihood that good service, good food, and an enjoyable evening would transpire was used as initial expectations. Participants responded on three 120-mm continuous scales anchored with bnot very likelyQ and bvery likely.Q They were also asked for the likelihood that they would stay at the restaurant. The four variables were combined for the expectations measure with an alpha of .82. Three paragraphs followed providing the participant with further expectation information concerning the evening, their interaction with the waiter, the conversation with their friend, and their impression of the menu options (all were consistent with initial expectations). Expectations for service, food, and overall enjoyment were collected again. Since participants had not yet committed to staying at the restaurant, they were again asked about the likelihood that they would stay. The rest of the evening was described to them either as a positive or negative experience. Participants were asked three times to provide their evaluations of the events. After the description of the outcome, they were asked whether they would be likely to return to the restaurant and whether they would recommend the restaurant on 120-mm scales anchored with bnot very likelyQ and bvery likely.Q Finally, they were asked to provide their overall evaluation of the experience on a 120-mm continuous scale anchored with bnot very goodQ and bvery goodQ. The three scales were combined for the ARs measure with an alpha of .95. Participants then filled out an augmented locus of causality questionnaire (Valecha, 1972) based on Rotter’s (1966) original scale. Participants then completed a 15-min filler task. The scale is comprised of 29 pairs of statements

Exhibit 1.

including six filler items. In each pair of statements, one relates to an internal locus of control and the other an external locus of control. In its original format, participants were asked to indicate which one of the two statements best described their thoughts and behaviours. The augmented scale requires that participants state if the choice is much closer or slightly closer to their actual opinion. The first three questions following the filler task asked about their enjoyment of the evening in the restaurant, these responses will be used to test whether their ARs had changed over time. The first two questions asked the participants to rate the food and service in the restaurant on a 120-mm scale anchored with bnot very goodQ and bvery good.Q The third question asked them to indicate their experience in the restaurant on a 120-mm scale anchored with bnot very goodQ and bvery good.Q These questions were carefully worded to ask for their current evaluation, not their memory for a previous evaluation. The variables were combined for a measure of AR over time with an alpha of .94. Then participants indicated their recognition judgements and their confidence in their response for 17 statements. Seven of the 17 statements were taken from the version of the story they read. Seven of the 17 statements were taken from the other version of the story, in other words, exactly the opposite of what they read. Three of the questions could only be recognized if the participant had reinterpreted the facts. For instance, one statement mentioned how many waiters were working which was in the story, but also stated that the restaurant was either busy or not busy. This information was not provided in the story. Finally, participants completed the chance/luck scenarios which were adapted from Friedland (1992, 1998) to determine their tendency to attribute outcomes to either luck or chance. Participants indicated whether the outcome each of four scenarios was a result of luck or chance by dividing 100 points between the factors (see Exhibit for an example.

5. Results The scores on luck orientation and locus of control were approximately normal. As expected, the correlation between the measure for luck orientation and locus of control was not

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significant (r=.08, p=.33). Where possible, regressions were run with the scale scores, however, for the majority of the analysis, a median split on both scales was used to divide the sample into four groups. The two median splits resulted in approximately equal cell sizes (n=37 for luck internals, n=41 for luck externals, n=38 for chance internals, n=36 for chance externals). The responses to the questions asking about the expectations for service, food, and overall enjoyment were averaged for each participant as a manipulation check. As expected, the average rating was more positive for the participants in the positive expectations condition (M pos=51.15 mm, M neg=29.22 mm, t=9.24, pb0.0001). 5.1. ARs immediately after the episode Assimilation of expectations into the ARs is a necessary, but not sufficient, condition for the initial effects, reinterpretation, and selective memory hypotheses. It was hypothesized that three of the uncertainty orientations would assimilate their AEs into their ARs to the episode, and that only luck externals would not use expectations in their ARs. Separate regressions were run for each of the uncertainty orientation groups on the overall evaluation with expectations and outcome included as factors. The regressions reveal that expectations are a significant determinant of ARs of the luck internals (t=2.15, pb.05), the chance externals (t=2.68, pb0.01), and the chance internals (t=2.33, pb0.05). Expectations did not influence the ARs of luck externals (t=1.18, p=.25). This result for the luck externals is consistent with the no effects hypothesis. The regressions also reveal a significant effect for outcome treatment for all groups: luck internal (t=13.17, pb.0001), luck external (t=10.71, pb.0001), chance internal (t=10.65, pb.0001), chance external (t=10.15, pb.0001). 5.2. Changes in ARs over time The initial effects hypothesis suggests that the role of expectations end at the time of the evaluation of the experience, therefore ARs should not change to be more expectation-consistent. Both the reinterpretation and selective memory hypotheses posit that ARs will change to be more expectation-consistent. To measure whether the AR changed over time, participants were asked to rate how much they had enjoyed the experience with three questions after the filler tasks. These three variables were averaged for each participant. The initial reaction was subtracted from the recent reaction to create a difference variable. A positive number reflects a more positive reaction over time; a negative number reflects a less positive reaction over time. As expected, regardless of initial expectations, AR did not change over time for either chance externals [(M pos=+0.40, n.s.), (M neg= 3.98, n.s.)] or luck externals [(M pos= 4.59, n.s.), (M neg= 4.73, n.s.)]. The pattern of results for chance externals was

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consistent with the initial effects hypothesis. The pattern of results for luck externals was consistent with the no effects hypothesis. As expected, ARs of chance internals did shift in the direction of the initial expectations [(M pos=+4.94, t=2.01, pb.05), (M neg= 7.10, t=2.60, pb0.01)]. As expected, the luck internals also altered their reactions over time, however, we hypothesized that they would alter their reactions to be more consistent with expectations. Instead, luck internals altered their AR to be more positive in both conditions [(M pos=+7.02, t=2.43, pb0.05), (M neg=+8.17, t=2.14, pb.05)]. Although it is counter to our expectations, it is consistent with our assertion that they believe the outcome depends on their luckiness. These people do not want to be unlucky. 5.3. Memory of the episode The selective memory hypothesis asserts that individuals forget those aspects of the experience that are inconsistent with their expectations. In two of the four conditions, expectations were manipulated to be inconsistent with the outcome, only those were included in this analysis. Ten recognition questions included statements about the experience: six were included in the story (three expectation-consistent, three expectant-inconsistent), four were not included in the story (two expectation-consistent, two expectation-inconsistent). The coding of their responses was such that a higher score indicates that the participant is not recognizing expectation-inconsistent information and is incorrectly remembering expectationconsistent information. An ANOVA run on the selective memory score with locus of control and luck groups as the factors reveals a significant effect for group [ F(3,66)=6.13, pb.001]. The luck internal group had the highest score on this test (M luck int=6.55, M luck ext=4.85, M chance int=4.11, M chance ext=4.21) which is significantly greater than chance (t=2.37, pb0.05) and is consistent with the selective memory hypothesis. 5.4. Reinterpreting the event The reinterpretation hypothesis suggests that individuals remember the events correctly, but reinterpret the events such that they are more consistent with their expectations. Three of the recognition questions tested this effect. In each of the questions the stated fact was correct, but a phrase was added that was outcome-inconsistent, but expectation-consistent. For instance, individuals in the positive expectation condition read that bthe music was very loud,Q but the recognition statement read bthe music was very loud, but lively.Q If they incorrectly recognized the statement, they were awarded a point. A higher score reveals a greater propensity to reinterpret events to be expectation-consistent. An ANOVA run on the reinterpretation score with luck orientation and locus of control

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as the independent factors revealed a significant interaction [ F(1,147)=14.73, pb.0001]. Chance internals and luck externals were most likely to reinterpret the experience (M luck int=0.52, M luck ext=0.78, M chance int=0.86, M chance ext=0.43).

6. Discussion The results indicate that luck internals assimilated expectations into the evaluation of an experience, the likelihood of returning and recommending the restaurant to friends. This group changed their ARs over time, but not to be expectation-consistent as hypothesized, instead they altered their reaction to the experience to be more positive as time passed. Correctly predicting the outcome was less important than defending the belief of having the good luck trait. This group selectively remembered expectation-consistent events occurring. The data support the selective memory hypothesis. This is important because the hypothesis has been tabled before, but sufficient evidence was not found to confirm the proposition (Klaaren et al., 1994). Further research is required to test for a relationship between the luck internal orientation and optimism, as optimism has been associated with a similar type of information processing distortion (Taylor and Brown, 1988). Chance internals altered their ARs to be more consistent with their initial expectations. This was expected because it allows them to assure themselves that they are skilled at using the signs to predict the pattern of chance outcomes. Further research should test whether the role of expectations on reactions becomes even greater if the consumer does not commit to an evaluation immediately after the consumption experience. Chance internals tended to reinterpret the events to be expectation-consistent. As chance internals are looking for information to reduce uncertainty and to try and predict outcomes in uncertain settings, it would be interesting to investigate what information they believe is diagnostic while forming expectations. Chance externals assimilated expectations into the evaluation of an experience and their intention to recommend the restaurant to friends, but this appears to be where the role of expectations ends. There was no evidence of selective memory or reinterpretation of the event. In fact, chance externals had the most accurate memory for the service encounter and memory for their evaluation of it. The data support the initial effects explanation. In this case, measuring a consumer’s AR at the end of an experience should predict the consumer’s future behavior as the evaluation appears to be stable over time. Finally, the luck externals group did not assimilate their expectations into their evaluation. They had accurate memory for the events involved in the experience. Unexpectedly, they did show some evidence of reinterpretation. Since this group is concerned with predicting when a good or bad streak of luck will begin or end, they may have

reinterpreted the events to be consistent with their initial detection of luck. Overall, internally focused individuals assimilated their expectations into the evaluation of the experience. In this case, contrary to conventional wisdom, some overpromising may not be a detrimental marketing strategy. For the luck internals, marketing communications, first impressions and WOM used to form expectations influences postpurchase behavior as well, and therefore are extremely important to the success of a service with these consumers. Previous research into the advertising for services, rather than goods, has found that a focus is often placed on factual informational content (Grove et al., 1995; Mortimer, 2000). AE assimilation may require marketing communications to be more specific in detailing the emotional benefits of the service rather than, or in additional to, factual content. This will provide more specific AEs that can be assimilated if performance fails to deliver. The effects of emotional labor for service staff and the possible dissonance between felt emotions and displayed emotions has been extensively researched (Hochschild, 2003). However, if a service worker has positive AEs of the service experience, expectation assimilation may moderate any emotional dissonance. Staff briefing sessions (Gamble and Kelliher, 1999) could therefore be used to reinforce the positive emotions that the service staff will feel as a result of their service provision. Internally focused people either selectively remembered facts or reinterpreted them, possibly to defend their beliefs about self. They also altered their ARs over time, either to be expectation-consistent if they are chance-oriented, or to reflect more positively on self if they are luck-oriented. In both cases, collecting ARs immediately after a service encounter would not provide an accurate indication of the AR used in the future decisions to return. This has implications for the timing of a satisfaction measurement because immediate evaluations may not be predictive of repurchase behavior. Externally oriented people do not have the same personal investment in the consistency between their expectations and the outcome. ARs were more stable over time for externally oriented consumers and therefore may be a more useful tool in predicting future behavior. In the study reported here, participants read a scenario describing an experience, they did not actually live through the episode. Further research is necessary to investigate whether people use their thoughts, feelings, and memories differently for real, as opposed to imagined, experiences. Also, participants’ ARs were measured with scales, future research should allow the respondents to provide information about why they are expecting certain things, what information they are using to interpret the events described, and why they are changing their expectations and reactions. Limitations aside, this research introduces an uncertainty orientation framework that appears to be useful in understanding why consumers react differently in uncertain settings.

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References Breen RB, Zuckerman M. dChasingT in gambling behavior: personality and cognitive determinants. Pers Individ Differ 1999;27(6): 1097 – 111. Darke PR, Freedman JL. Lucky events and beliefs in luck: paradoxical effects on confidence and risk-taking. Pers Soc Psychol Bull 1997;23(4);378 – 89. Farrell C, Cowley E, Edwardson M. A new classification of uncertainty orientation: exploring the susceptibility to the hindsight bias in a gambling context. Working Paper Series, ISBN 1324-68IX. University of New South Wales, Sydney, Australia; 2002. Fischhoff B. For those condemned to study the past: heuristics and biases in hindsight. In: Kahneman D, Slovic P, Tversky A, editors. Judgment under uncertainty: heuristics and biases. Cambridge (UK)7 Cambridge University Press; 1982. p. 335 – 54. Friedland N. On luck and chance: need for control as a mediator of the attribution of events to luck. J Bus Res 1992;5:267 – 82. Friedland N. Games of luck and games of chance: the effect of luck-versuschance-orientation on gambling decisions. J Behav Decis Mak 1998;11:161 – 79. Gamble PR, Kelliher CE. Imparting information and influencing behavior: an examination of staff briefing sessions. J Bus Commun 1999; 36(3):261 – 79. Geers AL, Lassiter GD. Affective expectations and information gain: evidence for assimilation and contrast effects in affective experience. J Exp Soc Psychol 1995;35(4):394 – 413. Geers AL, Lassiter GD. Effects of affective expectations on affective experience: the moderating role of optimism–pessimism. Pers Soc Psychol 2002;28(8):1026 – 39. Grove SJ, Pickett GM, Laband DN. An empirical examination of factual information content amongst service advertisements. Serv Ind J 1995; 15:216 – 33. Hochschild AR. The managed heart: commercialisation of human feeling. Berkeley (CA)7 University of California Press; 2003. Hodges SD, Klaaren KJ, Wheatley T. Talking about safe sex: the role of expectations and experience. J Appl Psychol 2000;30(2):330 – 49. Kahneman D, Tversky A. Subjective probability: a judgment of representativeness. Cogn Psychol 1972;3:430 – 54.

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Keren G. The rationality of gambling: gamblers’ conceptions of probability, chance and luck. In: Wright G, Ayton P, editors. Subjective probability. New York7 John Wiley; 1994. p. 485 – 99. Keren G, Wagenaar WA. On the psychology of playing blackjack: normative and descriptive considerations with implications for decision theory. J Exp Psychol Gen 1985;114:133 – 58. Keren G, Wagenaar WA. Temporal aspects of probabilistic predictions. Bull Psychon Soc 1987;25:61 – 4. Klaaren KJ, Hodges SD, Wilson TD. The role of affective expectations in subjective experience and decision-making. Soc Cognit 1994;12(2): 77 – 101. Mortimer K. Are services advertised differently? An analysis of the relationship between product and services types and the informational content of advertisements. J Commun 2000;6:121 – 34. Rotter JB. Generalised expectancies for internal versus external control of reinforcement. Psychol Mon Gen Appl 1966;80(1):1 – 28. Taylor SE, Brown JD. Illusions and well-being: a social psychological perspective on mental health. Psychol Bull 1988;103(2):193 – 210. Teigen KH. Variants of subjective probabilities: concepts, norms and biases. In: Wright G, Ayton P, editors. Subjective probability. New York7 John Wiley; 1994. p. 211 – 38. Tversky A, Kahneman D. Belief in the law of small numbers. Psychol Bull 1971;2:105 – 10. Valecha GK. Construct validation of internal–external locus of control as measured as an abbreviated 11-item scale. Unpublished Doctoral Dissertation, The Ohio State University; 1972. Wagenaar WA. Paradoxes of gambling behavior. London7 Lawrence Erlbaum and Associates; 1989. Wagenaar WA, Keren GB. Chance and luck are not the same. J Behav Decis Mak 1988;1:65 – 75. Weiner B, Frieze I, Kukla A, Reed L, Rest S, Rosenbaum RM. Perceiving the causes of success and failure. In: Jones EE, Kanouse DE, Kelley RE, Nisbett RE, Valins S, Weiner B, editors. Attribution: perceiving the causes of behavior. Morristown (NJ)7 General Learning Press; 1987. p. 95 – 120. Wilson TD, Lisle DJ, Kraft D, Wetzel CG. Preferences as expectationdriven inferences: effects of affective expectations on affective experience. J Pers Soc Psychol 1989;56(4):519 – 30. Zuckerman M, Kuhlman MD. Personality and risk-taking: common biosocial factors. J Pers 2000;68(6):999 – 1029.

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Distinguishing between feelings and emotions in understanding communication effects Flemming Hansen* Department of Marketing, Center for Marketing Communication, Copenhagen Business School, Solbjerg Plads 3, C.3, DK-2000 Frederiksberg, Denmark Received 1 December 2002; received in revised form 1 October 2003; accepted 1 October 2003

Abstract This article explores measures that may be particularly relevant in connection with peripheral or low-involvement information processing. For FMCG, peripheral information processing is dominant, but in terms of most measures used in communication research, central information processing is more efficient. The only exception relates to emotional responses. The more positive and strong effects are registered following peripheral information processing. This directs the attention towards contemporary neurophysiological research into memory and emotional processing. In addition to measuring emotional processes in terms of behavioural, glandular and autonomous responses, it is possible to infer something about underlying emotional dispositions from analyses of questions about feelings. D 2004 Elsevier Inc. All rights reserved. Keywords: Emotions; Low-involvement information processing; Peripheral information processing; Communication effects

1. Introduction In much research concerned with advertising effect, it being pretesting, posttesting or tracking, cognitive modelling of consumer behaviour has dominated the choice of measures and the models proposed. Awareness preceding interest, information search and evaluation has been assumed to be a fundamental sequence in the consumer’s information processing. Attention leading to brand perception, preferences, purchase intention and eventually buying behaviour are the elements in this assumed chain of events. At the same time, creative advertisers have presented campaigns relying upon irony, emotions, postmodern perception of human values, surprise and provocation. Not only have such campaigns frequently won creative awards, but in many instances, their sales effect has also been well documented. In parallel with presentations of the traditional, primarily cognitive-based model of thinking’s influence on the way in

* Tel.: +45 3815 2134; fax: +45 3815 2101. E-mail address: [email protected]. 0148-2963/$ - see front matter D 2004 Elsevier Inc. All rights reserved. doi:10.1016/j.jbusres.2003.10.012

which advertising works as communication, occasional findings have been presented, suggesting very different aspects of the communication process. Some, mostly theoretically oriented consumer behaviour researchers, have given thought to alternative ways of looking at the advertising communication process. Low involvement (Krugman, 1968; Zaichkowsky, 1985) and attitudes towards the ad (A-ad; Mitchell and Olson, 1981; MacKenzie and Lutz, 1982; Lutz, 1985) have been fundamental concepts, and a distinction between central and peripheral information processing has emphasised the multifaceted nature of advertising information processing (Petty et al., 1983). In more recent years, neuropsychologists, brain researchers and other behavioural scientists have strongly emphasised the importance of emotional response (Damasio, 2000; Le Doux, 1998). In this research, a distinction has emerged between feelings and emotions. Basically, emotions are thought of as very primitive, extremely fast, unconscious mechanisms controlling the individual responses to a wide variety of situations ranging from serious threats (for instance, from an approaching car) to trivial decisionmaking tasks (for instance, choosing a coffee brand in the supermarket; Heath, 2001; Franzen and Bouwman, 2001).

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Feelings, on the contrary, are those conscious and cognitive perceptions we use to describe our more primitive noncognitive emotional control of what we do. We may talk about feelings of sadness, jealousy, happiness, etc. Such feelings are much more detailed in nature than emotions and they can be described verbally in more or less precise terms by the individual experiencing such feelings. In the paper, we shall review some of the findings relating to emotions as well as to feelings and look into the possibilities of gaining insight about emotional response potentials from measurements of feelings.

2. Alternative information processing and other ways of handling incoming information Cognitive psychology has dominated the consumer behaviour researchers’ study of information and information processing since the middle of the century. Early contributions are Hovland et al. (1953), Rogers (1962/1995), Hansen (1976), Fishbein (1966), McGuire (1976) and Bettman (1979). Fig. 1 summarizes some of the major models of this kind. The classical AIDA formulation goes back to the end of the 19th century and is explicitly formulated by Copeland (1925). The hierarchy of effects model is most convincingly presented by McGuire (1976) or W7rneryd (1959). The Defined Advertising Goal for Measured Advertising Results (DAGMAR) model is presented by Colley (1961) on behalf of the Advertising Research Foundation and the product adoption model represents Rogers’ (1962/1995) integration of a wealth of research to explain the way in which new products and ideas are accepted among consumers. Different researchers offer a number of observations that are difficult to interpret in terms of the cognitive effect hierarchy way of thinking (Hansen, 1976). Picture perception has been studied by psychologists and Nickerson

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(1968) presents highly relevant findings for our purpose. Imagine an experiment where you show 200 pictures for 2 s each to an audience of 200 (often undergraduate students). On the following day, you do the same; only this time, you include 200 new pictures to make a total of 400 pictures. Following the exposure of each picture, you ask a question to test if people can recognise the pictures from the day before. The overall observation in such an experiment is that 95–100% of the stimuli presented on the first day are recognised. The research has gone on to look into how such recognition persists over time, the role of the length of the exposure time, the nature of the pictures presented, and the motivation of the subjects in the audience. Provided 2 s are allowed for exposure (or 1 s for exposure and 1 s for undisturbed information processing before the next exposure), the recognition process is extremely efficient and documents an enormous capacity for storing of such information in the brain. This information storage is not limited to short- or medium-term memory and may persist for years. Another line of research has been reported by Zajonc (1968). Here, the purpose was to study how the evaluation of items, to which subjects is exposed, increase with the number of exposures. In a classic study, Chinese characters and nonsense words have been used. The experimental design is simple. On the first day, you show a sequence of, for instance, Chinese characters, but you control your stimuli so that some of the characters are shown 1, 2, 5, 10, or even 25 times. The following day, you ask the same respondents what they think the meaning is of the different Chinese characters in terms of being more or less positive. Findings from such studies have shown a clear dmere exposureT hypothesis. Mere exposure improves evaluation in many situations, but, of course, limits exist. If the words are not nonsense words, but rather meaningful ones, such as names of known

Fig. 1. Information-processing models used in testing of communication.

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persons, cities or brands, what you in advance know and think about the persons or cities may inhibit the mere exposure effect. Zajonc reports finding from students counting the frequency with which different words occurred in a sample of literature from Chicago University Library. With a different sample of students, they ranked the average positive, negative evaluation of the different words. The mere exposure relationship is evident in their data, but, remarkably, exceptions can be observed too. In the 1960s and 1970s, corporate image became a major issue in applied research. Some of the major findings from the Mori group in London are reported in Worcester (1979). The basic observation here is that if you measure how frequently a person has heard about a particular company (self-rated awareness) and how positively/negatively the same person evaluates that company (self-rated attitude), a classical image-positioning picture emerges. Here, it appears that the better known a company is, the more positively it is evaluated. In an extension of the mere exposure research, Zajonc and Markus (1982) studied what they labelled emotions without cognitions. In this line of research, the basic idea is very simple and can be illustrated with one of their classical studies. You ask two groups of respondents to evaluate Walkmans by listening to music and speech from these, which they have mounted on their head. The respondents are told that it is an experiment designed to evaluate the quality of a new type of Walkman. The two groups listen to the same content under the same conditions and with the same instructions. The only difference between the two groups is the following. In the test, it is explained that when you use a Walkman in real life, you will often do so when walking, running or in other ways be occupied with parallel activities. To simulate the effect of these other activities in the listening situation, the respondents are asked to nod their heads while listening, whereas the respondents in the other group are asked to shake their heads. Surprisingly enough, the group nodding their heads evaluate their Walkmans significantly better than those shaking their heads. Finally, research concerned with left- and right-brain information processing should be mentioned also. The whole issue is complicated and it is doubtful whether its applicability to the study of consumer information processing has been properly demonstrated. However, the following are some of the characteristics normally associated with leftbrain versus right-brain information processing. The left brain focuses on conscious, verbal, analytical, sequential and arithmetic information processing or with what psychologists call cognitive information processing. The right brain, in contrast, much more involves unconscious, nonverbal, synthetic, holistic, geometrical or spatial information processing (Sperry, 1982; Hansen, 1981; 1985). These findings suggest that things occur when we receive information in situations like those in which we are exposed to advertising that are very different from the processes that the cognitive psychologists assume.

3. Peripheral and low-involvement information processing In central and peripheral information processing, the concept of low involvement is essential. Emphasised by Krugman (1968) and Mitchell and Olson (1981), involvement has been made operational by Zaichkowsky (1985). In many studies of consumer information processing, it has been demonstrated that with low involvement, consumers are less accessible, have fewer defences and are little motivated to cope with complicated information. Probably one of the more integrated approaches to dealing with low-involvement information processing is found in the Rossiter and Percy (1999) informational grid. Here, two important distinctions are made. One of them has to do with the kind of motivation that drives consumers in connection with different purchases. This distinction relates to positive (such as obtaining good taste in food, feeling happiness by demonstrating good taste in clothes) and negative/avoidance motivation (such as avoiding a headache by using headache remedies, avoiding too much trouble in winter by having a good snow shovel, etc.). The other distinction relates to high and low involvement in the already mentioned terminology of Zaichkowsky (1985). From this platform, the authors propose four different kinds of communication situations shown in Fig. 2. Whereas the high involvement and particularly highinvolvement informational processing comes close to what we traditionally find in the effect hierarchy cognitive type of modelling, the low-involvement transformational kind of processing is of a much more emotional nature, occurs at a low level of consciousness, and is stored in terms of implicit memory (Heath, 2001). In this conceptual framework, a distinction between recognition versus recall is important. In many purchase situations where involvement is low and little factual information is available, recognition of the alternative to be chosen is of major concern. Here, a parallel to the subsequently discussed peripheral processing appears; in contrast, in other purchasing tasks of a more elaborate nature with planning and comparison of alternatives, the ability to recall relevant alternatives is extremely important. It is suggested that communication resulting in recall is structurally different from information solely providing recognition. As we shall see subsequently, this is very relevant for some of the aspects of contemporary thinking about emotional information processing. Another theoretical approach to the study of consumer information processing is presented by Petty and Cacioppo (1986). Here, the distinction between peripheral versus central information processing is fundamental. Central information processing is pretty much what we think of in terms of the cognitive hierarchical treatment of information, whereas peripheral relies on less elaborate, probably less conscious and probably also more emotional types of information processing. The authors themselves write:

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Fig. 2. The Rossiter–Percy grid (Rossiter and Percy, 1999).

bWe have outlined two basic routes to persuasion. One route is based on the thoughtful (though sometimes biased) consideration of arguments central to the issue, whereas the other is based on affective associations or simple inferences tied to the peripheral cues in the persuasion context. When variables in the persuasion situation render the elaboration likelihood high, the first kind of persuasion occurs (central route). When variables in the persuasion situation render the elaboration likelihood low, the second kind of persuasion occurs (peripheral route). Different consequences occur from the two routes to persuasion.

Attitude changes via the central route appear to be more persistent, resistant, and predictive of behaviour than changes induced via the peripheral routeQ. The Petty and Cacioppo (1986) Elaboration Likelihood Model (ELM) is modified by Hansen (1997) in terms of an Elaboration Likelihood Advertising Model (ELAM). This model is illustrated in Fig. 3. Here, central information processing focuses first and foremost on product and brand relevant information, which generates brand awareness, brand perception, image preferences and eventually buying intentions.

Fig. 3. The ELAM (Hansen, 1997).

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Peripheral information processing following exposure and attention concerns itself more with how the message looks, what the story is, what perceptual representations, such as, e.g., music, pictures, etc., appear in the advertisement or commercial. These, in turn, generate attitudes towards the ad (rather than towards the brand) and emotional responses all reflected in ad liking. Attitudes towards the ad and ad liking may influence the extent and nature of the parallel central information processing to the extent that such occur. It may also lead to implicitly stored memories that may eventually be generated as recognition and possible purchase influence in purchase situations. Variables used to reflect the central processing are often brand related in terms of brand recall, brand recognition, brand processing, attitude towards the brand preferences for the brand, purchase intentions and possibly changing purchase behaviour. Measurements more related to peripheral information processing are concerned with ad recall, ad recognition, ad processing, attitudes towards the ad emotions and ad liking. Particularly in connection with advertising processing, different studies have been conducted to identify the characteristics of peripheral versus central processing at the Center for Communication Research at the Copenhagen Business School.

4. The Copenhagen peripheral versus central information processing studies Center for Marketing Communication has had access to 18 standardised advertising pretests for fast-moving consumer goods, conducted by Gallup/TNS in Denmark 1998– 1999. Each of these included 120–150 respondents. They follow the lines described in the ELAM model. In each test, questions are partly formulated at the brand level (e.g., attitudes toward the brand) and partly at the advertising level (advertising recall and A-Ad). A more detailed account of this study is found in Hansen (1997) and Hansen and Hansen (2001). Here, we are particularly concerned with the extent of peripheral versus central information processing and the Table 1 Number of central and peripheral responses in a study of 18 ads (a respondent may be counted both as one with negative and as one with positive central responses, or as one with both negative and positive peripheral responses) Central positive Central negative Central Peripheral positive Peripheral negative Peripheral No. of respondents classified Unclassified respondents Total a

No. of respondents

No. of statements

353 231 540 1209 1068 1627 2167 310a 2477

706 320 1026 1603 1488 3091

4117

Respondents with no classifiable responses are excluded.

Table 2 Self-rated recall, liking and buying intention

Respondents with central information processing Respondents with peripheral information processing

Self-rated recall

Liking

Buying intention

3.9

3.9

2.4

2.3

2.2

1.1

On a 6 point scale, 5–0. All differences significant, Pb.01.

nature of the responses depending upon which data processing approach is dominating. Responses from three open questions asked in the course of the test, partly evaluating positive and negative aspects of the ads and partly asking for what the respondent thinks the advertising is supposed to communicate, were analysed. A standardised procedure for probing respondents was used and responses were coded by two independent coders to their basic elements; for instance a bgood-looking girl in beautiful carQ was divided into bgoodlooking girlQ and bbeautiful carQ. Subsequently, all such informational items were categorised depending on whether they were positive or negative, and depending on whether they primarily related to the product, its use, its advantages (central) or whether they primarily reflected the story in the ad, its pictures, its underlying music, and its execution (peripheral; see Table 1). The relatively few items that were unclassifiable along these dimensions were excluded. On average, around two informational elements were registered for each respondent. The total number of useful statements totalled 4117. Several observations can be made from these figures. First, more than three times as many peripheral statements can be identified relative to the number of central informational ones. Secondly, when central information processing dominated, respondents were mostly positive in their responses. With peripheral information processing however, negative statements near the number of positive ones, and here, 650 or more than 1/3 of the respondents reported positive as well as negative ad-related items. Only 44 respondents (353+ 231
540) repeated both positive and negative, centrally (brand) related statements. Summary results regarding the nature of central versus peripheral communication effects are shown in Table 2. Table 3 Attitudes towards the ad in % of respondents with central or peripheral information processing Exciting Credible Sensitive Warm Entertaining Informative Stupid Irritating

Central, n=540 (%)

Peripheral, n=1627 (%)

22 42 31 22 36 32 19 17

19* 33* 27* 21 32* 29* 24* 24*

* Significant, Pb.01 t test.

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Here, when central information processing dominates, the ad is recalled better, liking is higher, brand preference is higher and buying intention (here measured as positive selfrated changes in buying intention following the exposure) is higher. In addition, attitudes towards the ad show the same picture. The items here are borrowed from the Gallup– Robinson standardised advertising pretesting procedure (Metha, 1994). Two statements from each of the four factors underlying this instrument (informative, entertaining, evaluative and negative attitudes) are used (see Table 3). Five out of six positive attitudes score (significantly) higher when central information processing is involved, and the negative ones do the opposite. All measures suggest that better communication results are achieved when central information processing is generated. One exception occurs. The test included 12 feeling statements (Table 4). Here, we found that peripheral information processing resulted in more positive emotional responses and fewer negative emotional ones. Of the 12 items used, 9 show significant differences in the direction indicated here. Summarizing this second part: when predominantly concerned with fast-moving consumer goods advertising, 75% of the information processing is peripheral. When central information processing occurs, it is always more efficient as indicated by practically all commonly used measurements of the communication effect. When peripheral information dominates, only the emotional responses tend to be more positive. An overall conclusion may be that we may like to generate central information processing as much as we can; however, when we cannot achieve this, we must be concerned particularly with the emotional responses following the peripheral information processing. In designing campaigns, it is likely to be a basic issue whether one should emphasise central information processing by providing lots of relevant product and use information or whether one should focus on creating more attention and thereby possibly also ending up with more peripheral information

Table 4 Self-rated feelings/emotions associated with central and peripheral information processing (in % of respondents) Pleasure Hope Acceptance Happiness Dominate Enjoyment Inspiring Surprising Mistrust Sorrow Anger Fear

Central, n=540 (%)

Peripheral, n=1627 (%)

26 29 22 27 9 46 29 19 8 7 12 3

40* 33* 34* 41* 13* 58* 28 23* 9 5* 7* 5

* Significant, Pb.01 t test.

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processing. The more creative advertising executions may have a tendency to do the latter. That is, high attention is achieved at a price in terms of lesser informational content. Of course, the good, creative solution generates both central and peripheral information, but is difficult to get at.

5. The nature of emotional responses Presenting an extensive review of contemporary neuropsychological research is impossible here. Excellent discussions are available in Damasio (2000), Goode (2002) and Franzen and Bouwman (2001). It is, however, necessary for our discussion of emotional responses to repeat some basic observations from this line of research. Basically, the brain can be seen as composed of three elements. The so-called neo cortex, that is, the outer part of the brain and in humans by far the largest. Cognitive processes are primarily believed to take place here and this occurs with some specialisation in terms of the left and right side of the brain as discussed earlier. The second part, the so-called old cortex, is found in mammals and in all animals as low as at the reptilian stage of development. This system functions as the controlling brain system in most animals and plays an important role in interacting with the cortex in the human brain. Finally, the inner central or oldest part of the brain—the prereptilian brain is where the most basic, elementary, controlling processes occur. Particularly, the prereptilian part of the brain contains thalamus through which most sensory stimulation passes and amygdale, which is shaped like an almond and controls the most elementary responses, such as glandular behaviour and autonomous responses, and hippocampus—named after its shape, which resembles a sea horse (Fig. 4). In the hippocampus, very elementary information is stored, and in interaction with amygdale, it controls the simple emotional responses. It may be the seat of implicit memory. Contemporary neuropsychology refers to the processes controlled by thalamus, amygdale and hippocampus as emotional. They may occur before any cognitive activity is activated in responses to stimuli and they control very elementary approach and defensive, aggressive responses of importance to the survival of the individual. The entire prereptilian brain interacts with the cortex and information is transmitted, coded, edited and stored here. In addition, in this part of the brain, the occurrence of different kinds of feelings (different from emotions) can appear. Whereas the basic emotional responses are of a rather primitive avoidance/approach character, people report in much more detail when asked to describe aspects of the relationship between perceived situations, goals and more basic emotions (feelings). Emotional responses can first and foremost be identified with the use of physiological measurements. Their EEG response, eye movements, heart rate, voice and facial expressions are measures frequently used. Because the emotions seem to be products of the

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Fig. 4. The function of the emotional brain (Le Doux, 1998).

prereptilian brain, our verbal questions about feeling responses do not necessarily relate directly to underlying emotional states. If, for example, an individual in the middle of a road observes a car approaching with fast speed, the perception channelled through the thalamus may, through the amygdale, generate an increased heart rate (autonomous response), sweating in the hands (glandular response) and freezing or running away. All these may occur before any activity in cortex takes place. Only later, when information has been transmitted here, can the more precise nature of the danger be identified and labelled, and possibly, this may influence the further direction of the response. In a more straightforward consumer behaviour case, the individual may—faced with a row of coffee brands—identify the brand usually bought, pick it up and conclude the activity. This may happen before any coffee information processing occurs or prior to the activation of earlier stored information about quality or other aspects of different coffee brands. Emotional responses, mostly unconscious, automatic reactions, are controlled by information stored in implicit memory. Feeling responses, the associated, perceived, cognitive perceptions of what is going on emotionally, involve centrally stored information, cognitive processing and evaluations. In this connection, the distinction, emotions versus feelings, is not synonymous with the distinction, conscious versus unconscious processes. Feelings may be conscious as well as unconscious. Cognitive processes may be of a high- or low-involvement character and may also relate to emotional activities. We realise the automatic, very little demanding, fast and energy-saving emotional responses occur in many situations where cognitions, comparisons and information searches would have been unnecessarily time demanding and complicated.

In earlier psychological theory and in studies of consumer behaviour, emotions and feelings are often used interchangeably. In our terminology, feelings have been studied since the very early days of psychology and a large number of measurement instruments used for identifying different kinds of feelings based upon verbal responses have been developed (Franzen and Bouwman, 2001). The number of feelings identified with a different instrument varies from few (two to four) to as many as 20 or 30. In many of these studies, a factor analysis has been used based upon the respondents’ own rating of words that reflect different kinds of feelings. One such typical set is reported by Richins (1997). Departing from several of the more generally accepted batteries, such as Izard (1977) and Mehrabien and Russell (1974), she identified 16 plus 4 consumption-related feelings. In most cases, these can be reduced to two to three meaningful factors. One case of this kind is Shaver et al. (1987). Here, a hierarchical cluster analysis on a large number of feeling items results in 24 grouped feelings. However, when these are grouped at higher levels, they fall into two (or three) separate sets: a predominantly positive (approach dimension—love and joy); a predominantly negative set (anger, sadness and fear); and possibly an arousal-like dimension labelled surprise. Of course, the amount of variance explained with these lower order levels is less than when a larger number of factors are included, but the uniformity of the dimensions and their face validity is such that the solutions can still be judged to be operationally useful. Some authors have even focussed on these fewer more fundamental dimensions. For instance, Mehrabien and Russell (1974) talk about pleasure versus dissatisfaction. Similarly, in a commercially applied setting introduced by Vaughn (1980), a distinction is made between negative/ positive versus active/passive feelings.

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underlying dimensions identified. Only in the design test was the avoidance dimension less expressed. Here, one might better work with three or four factors. The data give no uniform answer to the question of whether one should ideally work with one, two, three, or maybe even four emotional dimensions. If a need for a more general, basic measurement instrument is felt, more research is needed before such standardised list of items can be identified with the purpose of measuring across very different consumption and communication situations. Still, based on the following case from one of the studies already completed, it is possible to illustrate the usefulness and the strengths of such an emotional battery.

The fundamental observation made here is that in the terminology of an SOR model, and with the use of selfadministered questionnaires, we may identify 10–20 different indicator variables describing aspects of feelings. However, in forcing solutions and fewer dimensions upon the data, more basic dimensions emerge. These dimensions we may rightfully label emotions. Thus, our major observation at this point is that we may still gain some insight into emotional responses based on measurement of feelings and by doing a bconcentratedQ analysis of the data (i.e., looking for fewer factors). Here, some of our own data we present from four different studies of communication effects (see also Hansen, 1997). The design test and the logo tests are reported in more detail in Kristensen et al. (2000), and the two sponsoring studies are reported in more detail in Hansen et al. (2002). All tests are based on the variables used in the ELAM test. In these studies, one statement corresponding to each of the underlying feeling dimensions in the Richins (1997) battery is included. In some of the experiments, the battery has been reduced further, but in each of the tests, at least the same 12 feeling items are used. In addition, there is good reason to look at findings across the different applications in the different contexts involving the short list of 12 items. In all cases, a two- to four-dimensional factor solution is meaningful. All solutions include an approach (positive) and an avoidance (negative) emotional dimension, and one or two dimensions reflecting involvement with the issue, strength of the emotion or arousal. To force comparability upon the data, two-factor solutions are shown for all data in Table 5. The amount of variance explained with the relatively limited number of factors is lower than ideally wished (26– 32%). However, the consistency of the dimensions across the different data sets confirms the general validity of the

6. The value of sponsorships explained by emotions We choose to look into the findings from the study concerned with how possible sponsoring objects (sponsees) are evaluated (Hansen et al., 2002) in a little more detail. Here, the respondents were 169 first-year undergraduate students at the Copenhagen Business School completing a self-administered questionnaire for which they received a book on advertising published by the Center for Communication Research as a reward. The authors involved in this project do not claim that the findings are in any way representative of the Danish population when it comes to evaluating possible sponsees. They do argue, however, that the relationships identified between the different measurements are much less sensitive to the sample bias involved here and thus suggest a more general usefulness of the measurement instrument with larger random samples. Such a project is presently underway. Basically, the 27 feeling items used are derived from Richins’ (1997) study. Some feeling statements obviously less related to consumer information processing are deleted

Table 5 Loadings on two factors in analyses of data on sponsoring, ad-test, design and colours of logo (I=Approach, II=Avoidance) Sponsoring Happiness Joy Pleasure Accept Inspiring Hope Surprise Anger Fear Mistrust Trust Sorrow Dominant Trustworthiness None of these x) indicates missing data.

Ad test

Design

Colours of logo

I

II

I

II

I

II

I

II

.39 .61 .48
.45 .38 .33
.02
.07
.03 x) .32
.07
.10 x) x)

.03
.11 .01
.56
.16
.02 .16 .61 .45 x)
.36 .40 .08 x) x)

.70 .67 .58 .56 .54 .51 .40
.01 .17
.06 x)
.07 .23 x)
.50

.01
.04
.21 .08
.05 .12 .19 .67 .65 .60 x) .50 .44 x)
.13

.72 .78 .75 .06 .62 .43 .16
.84
.73
.71 x)
.76
.47 x) x)


.16
.06 .03
.55 .43
.30 .81
.11
.13 .07 x)
.31 .30 x) x)

.63 .71 .54
.02 .50 .38 .22
.53
.49
.55 x) x)
.25 .08 x)

.07 .23
.05
.68 .13
.13 .51 .47 .48 .53 x) x) .10
.72 x)

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F. Hansen / Journal of Business Research 58 (2005) 1426–1436

and some more appropriate items taken from the Ray and Batra battery (1982) are included. The total list is shown in Table 6. The measurement of the feeling responses took place by having each respondent choose feeling statements they felt agreed with 27 possible sponsoring events divided into sports, culture, television programmes and social aid organisations. The sponsors studied are listed in the first column of Table 7. With the somewhat crude data collection procedure of respondents choosing only a few items to be associated with each possible sponsoring object and with a total of 27 items reduced to four factors, the amount of variance explained in the data is 29% of the total variance. The face validity of the four factors suggest that each of the factors reflect one important emotional dimension when dealing with sponsoring. The four-dimensional solution chosen centres on an avoidance (negative emotional) and approach (positive emotional) dimension (numbers two and three). Loneliness and sadness are the two highest loading items reflecting avoidance, whereas joy, romantic love, enjoyment, happiness are the four items that best represent the approach tendency. The fourth factor in the battery, labelled arousal, reflects feelings, such as excitement, surprise, lack of trust and lack of accept. Finally, the first

Table 6 Varimax factor analytical solution based on a four-factor solution on emotional responses to different sponsoring aspects

Hope Sorrow Worry Fear Inspiring Optimism Dominating Satisfaction Shame Loneliness Anger Sad Envy Desire Guilt Dissatisfaction Joy Romantic love Enjoyment Happiness Peacefulness Excitement Surprising Trust Accept Relief Pride

bUncertaintyQ

bAvoidanceQ

1

2

3

4

59 57 46 45
31 28
23
16 0 4 3 15
2
7 3 24
6 0
14 14
5
12 7 8
8 4
18


19 16 6 14
15
27 17 9 54 40 40 40 37 34 34 28
17 5
5 0 8
8
3
11 10 10
7


19 1
3 4 0
17
6 12
1
4 4
2 7
5
2
2 62 52 51 49 31
17 2
15
21 1
9


19 0
8
2
13 12
6
9
4 11
11 0 0 30 7
3 20 10 0
3
18 64 44
40
35 22 21

Decimals were omitted.

bApproachQ

bArousalQ

Table 7 Standardised scores for 27 different sponsoring objects on awareness, liking and self-rated purchase intention, together with total score for each (geometrical average score) N=169

Awareness

Liking

Purchase int.

Overall score

The Danish Cancer Society Danish Red Cross Save the Children Denmark The AIDS Foundation Danchurchaid The Danish Muscular Dystrophy Association The Danish Heart Foundation Average—social aid organisations Friends (TV2) The Weather Report (TV2) Ally McBeal (TV2) Rejseholdet (DR) Onside (TV3) Big Brother (TVDANMARK) The Hotel (TV2) The Great Mission (TV2) Average—tv programmes Tivoli Eurovision song contest The zoo The royal theatre The Roskilde Festival The Danish National Gallery of Art Arken Average—culture Men’s National Soccer Squad Women’s National Handball Squad Team Danmark FC Copenhagen Brbndby I.F. Average—sport

1.09

1.23

1.16

1.55

1.05 0.99

1.19 1.18

1.10 1.11

1.37 1.30

0.91

1.21

1.15

1.26

0.78 0.68

1.09 1.13

1.03 1.09

0.88 0.84

0.62

1.18

1.11

0.81

0.87

1.17

1.11

1.14

1.33 1.23

0.95 0.86

1.01 0.93

1.27 0.98

1.08 0.99 0.84 1.09

0.89 0.88 0.88 0.67

0.94 0.95 0.97 0.74

0.91 0.82 0.71 0.54

0.72 0.77

0.78 0.76

0.90 0.85

0.51 0.49

1.01

0.83

0.91

0.78

1.41 1.27

1.13 1.02

1.07 1.00

1.69 1.29

1.05 0.98 1.08 0.80

1.07 1.06 0.95 1.04

1.04 1.01 0.96 1.03

1.17 1.05 0.98 0.86

0.70 1.04 1.22

0.94 1.03 1.06

0.96 1.01 1.07

0.63 1.10 1.39

1.11

0.99

0.98

1.08

0.97 1.18 1.05 1.11

1.06 0.95 0.88 0.99

1.05 0.94 0.87 0.98

1.07 1.06 0.80 1.08

item, labelled uncertainty, relies on responses to feelings, such as hope, sorrow, worry and fear. The usefulness of such an emotional battery, of course, depends upon the extent to which it meaningfully describes the different items (sponsoring objects) rated, and the extent to which measurements relate meaningfully to traditional, well-established effect– measures used in the study of sponsorship effects. In the study reported here, different traditional effectrelated measures of sponsoring were included. Awareness of the sponsee was measured on a five-point self-rating scale

F. Hansen / Journal of Business Research 58 (2005) 1426–1436

(bHow well would you say you know. . .Q), the same was done for liking, and persuasion was quantified as selfreported changes in purchase intentions. The question was bdo you think that it is more likely that you would purchase a product sponsoring dxxxxT after having learned about the sponsorship than beforeQ. The measurement, crude as it is, has been applied in most of the studies reported earlier, and on the whole, is sensible and meaningful. On average, 50% of the respondents report that they do not intend to change their purchase intentions. However, the rest do report positive as well as negative purchase intentional changes. These measures in ad testing are in accordance with other research believed to make good sense in evaluating sponsorship attitude based on these. A total score is computed as the geometric average of the evaluations of the sponsorships with the sponsoring objects. Overall effect score Awareness Linking ¼  Average Awareness Average Linking Self
rated change in buying intention  Av: Self
rated change in buying int: The overall score for all of them is 1.00, suggesting that a sponsoring object scoring higher is evaluated as better than average and vice versa. That is, for instance, the liking score for the Danish Cancer Society was divided with the average liking score for all sponsoring objects rated and thereby a score larger than one reflects an above-average evaluation. The same was done with the awareness and purchase intention scores and to arrive at a single overall evaluative score, the three past scores were simply multiplied with each other. The critical question now, of course, is to what extent the emotional responses we have identified are able to explain variations in this overall effect score. This is done by computing a factor score for each sponsoring object on the four dimensions, shown in Table 6. With these as independent variables, and with the total effect score of Table 7 as a dependent variable, a multiple regression analysis was carried out. For the 27 rated sponsoring objects as dependent variables, the analysis provides an adjusted R 2 score of .60. It appears that negative emotions, positive emotions and uncertainty are significantly related to the overall evaluation, with the greatest explanatory power associated with negative emotions (b=
.003, t=
3.54, Pb.001), followed by uncertainty (b=.0024, t=4.34, Pb.001) and positive emotions (b=.0016, Pb.01). We shall not try to extract more far-reaching interpretations from these data, but we do want to emphasise that an adjusted R 2 value of .60 in an analysis with 27 observations, four independent variables and basic ratings simply made by having people choose whether specific feeling statements do or do not relate to sponsoring objects seems to be a strong

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confirmation of the usefulness of the approach. We look forward to work with larger, more representative samples with more sensitive rating procedures applied in other marketing communication contexts than sponsoring. So far, however, we dare conclude that energy spent in this direction seems worthwhile.

7. Conclusion Despite the somewhat tentative nature of the findings reported here, a number of conclusions emerge to which we would like to direct the attention of the reader. (1) More and different measures are available when studying marketing communication responses than what is suggested in AIDA and similar formulations. (2) A distinction between central/peripheral, higher/lower involvement or more or less cognitive information processing seems useful. (3) The central information processing is, when it occurs, by far more efficient in terms of effect scores normally used in marketing communication studies. (4) Only in terms of emotional responses does peripheral information processing seem to have a stronger impact. (5) In the real world, the advertiser may wish to generate strong concentrated central information processing. (6) However, competition from other communication, other advertising, low involvement on behalf of the receivers, etc. set limits to the extent to which this is feasible. (7) In reality, at least when talking about fast-moving consumer goods, peripheral information processing seems to be dominant in most instances. (8) To study emotional responses may be a useful approach, when peripheral responses are dominant. (9) With a distinction introduced between feelings and emotions, it is suggested that an operational measure of more basic emotions may be derived from scores based on statements of feelings of a more cognitive– conscious nature. In any event, emotional activities contribute significantly to the overall effectiveness of communication. This is not least the case when peripheral communication is at stake. It is not obvious from the data analysed here whether the emotional effect primarily makes other information processing more efficient, or whether it is a more direct effect with information being stored at an emotional (implicit) level and reactivated in purchasing and other situations at the same very low prereptilian brain level. In all events, we do not know enough about how emotions are formed or how they influence subsequent consumer behaviour. The area must be a central one for future research in consumer behaviour.

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MacKenzie SB, Lutz RJ. Monitoring advertising effectiveness: a structural equation analysis of the mediating role of attitude towards the ad. Working paper No. 117, Center for Marketing Studies, University of California, Los Angeles, 1982. McGuire WJ. Psychological factors influencing consumer choice. In: Ferber B, editor. Selected aspects of consumer behavior. Washington7 University Press; 1976. p. 319 – 60. Mehrabien Albert, Russell James A. An approach to environmental psychology. Cambridge (MA)7 MIT Press; 1974. Metha Abdilasha. How Advertising Response Modelling (ARM) can increase ad-effectiveness. J Advert Res 1994; 34(3),1994;62 – 74 [May/June]. Mitchell AA, Olson JC. Are product attribute beliefs the only mediator of advertising effects on brand attitude? J Mark Res 1981;18:318 – 32. Nickerson RS. A note on long-term recognition memory for pictorial material. Psychon Sci 1968;11:58. Petty JT, Cacioppo RE. Communication and persuasion. New York7 Springler-Verlag; 1986. Petty RE, Cacioppo JT, Schumann David. Central and peripheral routes to advertising effectiveness: the moderating role of involvement. J Consum Res 1983;10(2):135 – 46 [September]. Richins ML. Measuring emotions in the consumption experience. J Consum Res 1997;24;127 – 42. Rogers EM. Diffusion of innovations. New York7 The Free Press; 1962/ 1995. Rossiter John, Percy Larry. Advertising and promotion management. New York7 McGraw-Hill; 1999. Shaver Philip, Schwartz Judith, Kirson Donald, O’connor Cary. Emotion knowledge: further exploration of a prototype approach. J Pers Soc Psychol 1987;52:1061 – 86 [June]. Sperry R. Some effects of disconnecting the cerebral hemispheres. Science 1982;217:1223 – 6. Vaughn R. How advertising works: a planning model. J Advert Res 1980;20(5):27 – 33 [New York, Oct]. W7rneryd KE. Ekonomisk psykology. Stockholm7 Institute for Economic Research, Stockholm School of Economics; 1959. Worcester R. Strategic decision research: its communications and use at ICI. Paper presented at the ESOMAR Congress, Brussels, September, 1979. Zaichkowsky JL. Measuring the involvement construct. J Consum Res 1985;12(3):341 – 52. Zajonc RB. Attitudinal effects of mere exposure. J Pers Soc Psychol 1968;9(2). Zajonc RB, Markus H. Affective and cognitive reasons factors in preferences. J Consum Res 1982;9(2):123 – 31.

Journal of Business Research 58 (2005) 1437 – 1445

Emotions in consumer behavior: a hierarchical approach Fleur J.M. Laros*, Jan-Benedict E.M. Steenkamp Marketing Department, Tilburg University, P.O. Box 90153, 5000 LE Tilburg, The Netherlands Received 1 December 2002; received in revised form 1 September 2003; accepted 1 September 2003

Abstract A growing body of consumer research studies emotions evoked by marketing stimuli, products and brands. Yet, there has been a wide divergence in the content and structure of emotions used in these studies. In this paper, we will show that the seemingly diverging research streams can be integrated in a hierarchical consumer emotions model. The superordinate level consists of the frequently encountered general dimensions positive and negative affect. The subordinate level consists of specific emotions, based on Richins’ (Richins, Marsha L. Measuring Emotions in the Consumption Experience. J. Consum. Res. 24 (2) (1997) 127–146) Consumption Emotion Set (CES), and as an intermediate level, we propose four negative and four positive basic emotions. We successfully conducted a preliminary test of this secondorder model, and compare the superordinate and basic level emotion means for different types of food. The results suggest that basic emotions provide more information about the feelings of the consumer over and above positive and negative affect. D 2004 Elsevier Inc. All rights reserved. Keywords: Consumer emotions; Hierarchy of emotions; Positive and negative affect; Basic emotions; Specific emotions

1. Introduction After a long period in which consumers were assumed to make largely rational decisions based on utilitarian product attributes and benefits, in the last two decades, marketing scholars have started to study emotions evoked by marketing stimuli, products and brands (Holbrook and Hirschman, 1982). Many studies involving consumer emotions have focused on consumers’ emotional responses to advertising (e.g., Derbaix, 1995), and the mediating role of emotions on the satisfaction of consumers (e.g., Phillips and Baumgartner, 2002). Emotions have been shown to play an important role in other contexts, such as complaining (Stephens and Gwinner, 1998), service failures (Zeelenberg and Pieters, 1999) and product attitudes (Dube et al., 2003). Emotions are often conceptualized as general dimensions, like positive and negative affect, but there has also been an interest in more specific emotions. Within the latter stream of research, some researchers use a comprehensive set of

* Corresponding author. Tel.: +31 13 4668212; fax: +31 13 4662875. E-mail address: [email protected] (F.J.M. Laros). 0148-2963/$ - see front matter D 2004 Elsevier Inc. All rights reserved. doi:10.1016/j.jbusres.2003.09.013

specific emotions (Richins, 1997; Ruth et al., 2002). Other researchers concentrate on one or several specific emotions, such as surprise (e.g., Derbaix and Vanhamme, 2003), regret (e.g., Inman and Zeelenberg, 2002; Tsiros and Mittal, 2000), sympathy and empathy (Edson Escalas and Stern, 2003), embarrassment (Verbeke and Bagozzi, 2003) and anger (Bougie et al., 2003; Taylor, 1994). Despite this emerging body of research, progress on the use of emotions in consumer behavior has been hampered by ambiguity about two interrelated issues, viz., the structure and content of emotions (Bagozzi et al., 1999). First, with regard to structure, some researchers examine all emotions at the same level of generality (e.g., Izard, 1977), whereas others specify a hierarchical structure in which specific emotions are particular instances of more general underlying basic emotions (Shaver et al., 1987; Storm and Storm, 1987). Second, and relatedly, there is debate concerning the content of emotions. Should emotions be most fruitfully conceived as very broad general factors, such as pleasure/arousal (Russell, 1980) or positive/negative affect (Watson and Tellegen, 1985)? Alternatively, appraisal theorists (see, e.g., Frijda et al., 1989; Roseman et al., 1996; Smith and Lazarus, 1993) argue that specific emotions

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should not be combined in broad emotional factors, because each emotion has a distinct set of appraisals. The confusion concerning structure and content of emotions has hindered the full interpretation and use of emotions in consumer behavior theory and empirical research (Bagozzi et al., 1999). The purpose of our paper is twofold. First, we integrate seemingly opposing research streams in psychology and consumer behavior by developing a hierarchical model of consumer emotions. We will show that the general dimensions with positive and negative affect are the superordinate and most abstract level at which emotions can be defined. The subordinate level consists of specific consumer emotions. We will develop an intermediate level with basic emotions that links these two levels. Second, we conduct a preliminary test of this proposed structure and compare the means for positive and negative affect with those of the basic emotions for four different food types.

2. Emotions in consumer research This section will briefly discuss an illustrative set of consumer studies on emotions (see Table 1 for an overview). Several studies focused on the emotional responses to ads. Holbrook and Batra (1987) developed their own emotional scale based on an in-depth review of the literature. They uncovered a pleasure, arousal and domination dimension in their data, and showed that these emotions mediate consumer responses to advertising. Edell and Burke (1987) also created their own emotion list and found that feelings play an important role in the prediction of the ad’s effectiveness. They proposed three factors: an upbeat, negative, and warmth factor. Olney et al. (1991)

showed that the emotional dimensions pleasure and arousal mediate the relation between ad content and attitudinal components, and consequently viewing time of an ad. They used part of Mehrabian and Russell’s (1974) scale. Derbaix (1995) replicated the research of Edell and Burke (1987) in a natural setting. His emotion words were based on a prestudy, and uncovered a positive and negative factor. Steenkamp et al. (1996) investigated the relations between arousal potential, arousal, and ad evaluation, with need for stimulation as a moderator. They based their arousal dimension on the scale of Mehrabian and Russell (1974). In the satisfaction literature, Westbrook (1987) was one of the first to investigate consumer emotional responses to product/consumption experiences and their relationship to several central aspects of postpurchase processes. Oliver (1993) extended this work by showing that emotional responses mediate the effects of product attributes on satisfaction. Both studies relied on Izard’s (1977) taxonomy of fundamental affects, and found positive and negative affect as underlying emotion dimensions. Mano and Oliver (1993) investigated the structural interrelationship among evaluations, feelings, and satisfaction in the postconsumption experience. They combined Watson et al.’s (1988) PANAS scale and Mano’s (1991) circumplex scale. Both three dimensions—similar to the upbeat, negative, and warmth factors of Edell and Burke (1987)—and two dimensions—positive and negative affect—were uncovered, but only the latter dimensions were used in the studies. Dube and Morgan (1998) modeled trends in consumption emotions and satisfaction in order to predict retrospective global judgments of services. They used the PANAS scale (Watson et al., 1988) and uncovered positive and negative affect. Phillips and Baumgartner (2002) confirmed the

Table 1 Overview of consumer research using emotions as a main variable Reference

Emotion measure used

Resulting structure

Edell and Burke (1987) Holbrook and Batra (1987) Westbrook (1987) Olney et al. (1991) Holbrook and Gardner (1993) Mano and Oliver (1993)

Edell and Burke (1987) Holbrook and Batra (1987) Izard (1977) Mehrabian and Russell (1974) Russell et al. (1989) Watson et al. (1988); Mano (1991)

Oliver (1993) Derbaix (1995) Steenkamp et al. (1996) Nyer (1997) Richins (1997)

Izard (1977) Derbaix (1995) Mehrabian and Russell (1974) Shaver et al. (1987) Richins (1997)

Dube and Morgan (1998) Phillips and Baumgartner (2002) Ruth et al. (2002)

Watson et al. (1988) Edell and Burke (1987) Shaver et al. (1987)

Smith and Bolton (2002)

Smith and Bolton (2002)

Upbeat, negative, and warm Pleasure, arousal, and domination Positive and negative affect Pleasure and arousal Pleasure and arousal Upbeat, negative and warm Positive and negative Positive and negative affect Positive and negative affect Arousal Anger, joy/satisfaction, and sadness Anger, discontent, worry, sadness, fear, shame, envy, loneliness, romantic love, love, peacefulness, contentment, optimism, joy, excitement, and surprise Positive and negative affect Positive and negative affect Love, happiness, pride, gratitude, fear, anger, sadness, guilt, uneasiness, and embarrassment Anger, discontent, disappointment, self-pity, and anxiety

F.J.M. Laros, J.-B.E.M. Steenkamp / Journal of Business Research 58 (2005) 1437–1445

importance of including positive and negative affect in explaining satisfaction. Smith and Bolton (2002) investigated the role of consumer emotions in the context of service failure and recovery encounters. They used content analysis for the responses of the participants and grouped the (negative) emotion words of consumers in five categories. Holbrook and Gardner (1993) investigated the relation between the emotional dimensions pleasure and arousal and the duration of a consumption experience, which was in their case, listening to music. They used Russell et al.’s (1989) Affect Grid to measure pleasure and arousal of the musical stimuli. Nyer (1997) and Ruth et al. (2002) focused on defining the antecedents rather than the consequences of emotions.

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Nyer (1997) showed that the appraisals of goal relevance, goal congruence, and coping potential are determinants of several basic consumption emotions. These emotions were mainly based on Shaver et al. (1987). Ruth et al. (2002) explored the cognitive appraisals of situations and their correspondence to 10 experienced emotions. They also used emotions based on the hierarchical structure of Shaver et al. (1987). In summary, this overview shows that there is wide divergence in the content of emotions studied in consumer research. Studies often use different scales to measure emotions and focus on different emotions. In spite of this, consumer researchers frequently use, or exploratory data analysis yields, a small number of dimensions (Bagozzi et al., 1999). Among these, the classification of emotions in

Table 2 Emotion words Negative emotion words

Positive emotion words

Aggravationa,b,c, Agitationa,b,c, Agonyb,c, Alarmb,c,d, Alienationb, Anger a,b,c,d,e,f,g, Anguisha,b,c, Annoyancea,b,c,d,e,f,h, Anxietya,b,c,e, Apologeticc, Apprehensiona,b,c, Aversione, Awfulc, Badc, Bashfulc, Betrayalc, Bitternessa,b,c, Bluea,c,i, Botheredc, Cheerlessa, Confusedh, Consternationc, Contemptb,c,e,g, Crankyc, Crossc, Crushedh, Cryc, Defeatb, Deflateda,b, Defensivec, Dejectiona,b,c, Demoralizedc, Depression a,b,c,d,h, Despairb,c, Devastationc, Differentc, Disappointmenta,b,c,e,f, Discomfortc, Discontent a,c, Discouragedc, Disenchantmentc, Disgusta,b,c,e,g,h, Dislikeb,c,g, Dismayb,c, Displeasurea,b,c, Dissatisfieda,c, Distressa,b,c,d,g,i,j, Distrustc,e, Disturbedc, Downa,c, Dreadb,c, Dumbc, Edgyc, Embarrassment a,b,c, Emptya,c, Envy a,b,c, Exasperationb, Fear b,c,d,e,f,g,h,i,j, Fed-upa, Ferocityb, Flustereda, Forlornc, Foolishc, Franticc, Frighta,b,c,h, Frustration a,b,c,d,f,g, Furya,b,c, Gloomb,c,d,h, Glumnessb, Griefa,b,c,f, Grouchinessb,c,i, Grumpinessb,c,i, Guilt b,c,e,g,j, Heart-brokena,c, Hateb,c,Hollowc, Homesickness a,b,c, Hopelessnessb,c, Horriblec, Horrora,b,c,f, Hostility b,c,h,i,j, Humiliation b,c, Hurta,b,c, Hysteriab, Impatienta,c, Indignantc, Inferiorc, Insecurityb, Insultb,c, Intimidatedh, Iratea,c, Irkeda, Irritation a,b,c,h,j, Isolationb,c, Jealousy a,b,c,e, Jitteryi,j, Joylessa, Jumpyc, Loathingb, Loneliness a,b,c,i, Longingc, Lossc, Lovesicka, Lowa,c, Mada,c, Melancholyb,c, Misery a,b,c,d, Misunderstoodc, Mopingc, Mortificationa,b, Mournfulc, Neglectb,c, Nervousness a,b,c,i,j, Nostalgiac, Offendedh, Oppressedc, Outragea,b,c, Overwhelmeda, Painc, Panic b,c, Petrifieda,c, Pitya,b,c, Puzzledh, Rageb,c,e, Regreta,b,c,e,g, Rejectionb,c, Remorsea,b,c, Reproachfulc, Resentmenta,b,c, Revulsionb, Ridiculousc, Rottenc, Sadness a,b,c,d,e,f,g,h,i, Scared a,c,h,j, Scornb,c,i, Self-consciousc, Shame ,a,b,c,e,g,j, Sheepishc, Shocka,b,c, Shyc, Sickeneda,c, Smallc, Sorrowa,b,c,e,i, Spiteb, Startlede,h, Strainedc, Stupidc, Subduedc, Sufferingb,c, Suspensec, Sympathyb, Tenseness b,c,h, Terriblec, Terrora,b,c, Threatenedh, Tormenta,b,c, Troubledc, Tremulousc, Uglyc, Uneasinessa,b,c, Unfulfilled, Unhappinessa,b,c,i, Unpleasanth, Unsatisfiedc, Unwantedc, Upseta,c,e,j, Vengefulnessb,c, Wantc, Wistfulc, Woeb,c, Worry b,c, Wrathb,c, Yearningc

Acceptancec,h, Accomplishedc, Activei,j, Admirationc, Adorationb,c, Affectionb,c, Agreementc, Alerth,j, Amazementb, Amusementa,b,c, Anticipationb,c, Appreciationc, Ardentc, Arousala,b,d, Astonishmentb,d,i, At easea,d, Attentiveh,j, Attractionb,c, Avidc, Blissb, Bravec, Calm a,d, Caringb,c, Charmeda, Cheerfulnessa,b,c,h, Comfortablec, Compassionb,c, Consideratec, Concernc, Contentment a,b,c,d,I, Courageousc, Curioush, Delighta,b,c,d,h, Desireb,c, Determinedj, Devotionc, Eagernessb,c, Ecstasya,b,c, Elationa,b,c,i, Empathyc, Enchantedc, Encouraging c, Energeticf, Enjoymentb,c,f, Entertainedc, Enthrallmentb, Enthusiasm b,c,e,f,i,j, Euphoriab,c, Excellentc, Excitement a,b,c,d,f,i,j, Exhilarationb,f Expectantc, Exuberantc, Fantasticc, Fascinatede, Finec, Fondnessb,c, Forgivingc, Friendlyc, Fulfillment c, Gaietyb,c, Generousc, Gigglyc, Givingc, Gladnessa,b,c,d, Gleeb,c, Goodc, Gratitudec, Greatc, Happiness a,b,c,d,e,f,h,i, Harmonyc, Helpfulc,h, Highc, Hope b,c,g, Hornyc, Impressedc, Incrediblec, Infatuationb,c, Inspiredj, Interestedf,j, Jollinessb, Jovialityb, Joy a,b,c,e,f,g, Jubilationb,c, Kindlyc,i, Lightheartedc, Likingb,c,g, Longingb, Love a,b,c,e, Lustb,c, Merrimentc, Moveda, Nicec, Optimism b, Overjoyeda,c, Passion a,b,c, Peaceful c,f, Peppyi, Perfectc, Pityc, Playfulc, Pleasure a,c,d,f,i, Pridea,b,c,e,f,g,j, Protectivec, Raptureb, Reassuredc, Regardc, Rejoicec, Relaxedc,d,f, Releasec, Relief a,b,c,e,f,g, Respectc, Reverencec, Romantic c, Satisfactiona,b,c,d,f,i, Securec, Sensationalc, Sensitivec, Sensualc, Sentimentality b,c, Serened,c, Sexy c, Sincerec, Strongi,j, Superc, Surpriseb,e,f,i, Tendernessb,c, Terrificc, Thoughtfulc, Thrill a,b,c, Toucheda, Tranquilityc, Triumphb, Trustc,h, Victoriousc, Warm-hearted c,i, Wonderfulc, Worshipc, Zealb, Zestb

Note: The emotion words of Richins’ CES (1997) are in italics. a Morgan and Heise (1988). b Shaver et al. (1987). c Storm and Storm (1987). d Russell (1980). e Frijda et al. (1989). f Havlena et al. (1989). g Roseman et al. (1996). h Plutchik (1980). i Watson and Tellegen (1985). j Watson et al. (1988).

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positive and negative affect appears to be the most popular conceptualization (see Table 1).

3. Positive and negative affect Many papers acknowledge that positive and negative affect are bever present in the experience of emotionsQ (Diener, 1999, p. 804; see also Berkowitz, 2000; Watson et al., 1999). We have content-analyzed 10 seminal studies in psychology on emotions and emotion words (Frijda et al., 1989; Havlena et al., 1989; Morgan and Heise, 1988; Plutchik, 1980; Roseman et al., 1996; Russell, 1980; Shaver et al., 1987; Storm and Storm, 1987; Watson and Tellegen, 1985; Watson et al., 1988). We were able to classify all emotion words as either a positive or negative emotion (see Table 2). Table 2 shows the emotion words and indicates which studies included a particular word as a positive or negative emotion word in their structure. The number of references for each emotion word illustrates to what degree researchers agree that this is an emotion word. For example, the emotion words fear, sadness, and happiness appear almost in every emotion structure, whereas others, like mournful, forlorn, and zeal, are only mentioned occasionally. In addition, Table 2 supports the notion that there are more negative than positive emotion words (Morgan and Heise, 1988). Yet, which of these many emotion words should be used to measure consumer emotions? To address this issue, we can use the important study by Richins (1997). Based on extensive research, she constructed the Consumption Emotion Set (CES). This scale includes most, if not all, emotions that can emerge in consumption situations and was developed to distinguish the varieties of emotion associated with different product classes. Table 2 reveals that the words included in the CES (in italics) are among the most frequently encountered words in the psychological emotion literature, and can be easily divided in positive and negative affect. Advantages of the division in positive and negative affect are that (1) the model can be kept simple and (2) the combination of a person’s positive and negative affect is indicative of his/her attitude. The disadvantage is that important distinctions among different positive and negative emotions disappear (Lerner and Keltner, 2000; 2001). Thus, more precise information about the feelings of the consumer is lost (Bagozzi et al., 1999). Because different emotions can have different behavioral consequences, it is important to know, for example, whether a failure in a product or service elicits feelings of anger or sadness. Both angry and sad people feel that something wrong has been done to them, but whereas sad people become inactive and withdrawn, the angry person becomes more energized to fight against the cause of anger (Shaver et al., 1987). Several studies have shown how important it is to take into account differences across emotions of the same valence (Lerner and Keltner, 2000; 2001; Zeelenberg and Pieters, 1999).

4. A hierarchy of consumer emotions The research streams supporting the different emotion structures (positive/negative vs. specific emotions) seem opposing, but can in fact be seen as complementing. Shaver et al. (1987) and Storm and Storm (1987) have suggested that emotions can be grouped into clusters, yielding a hierarchical structure. The most general, superordinate, level consists of positive and negative affect. The next level is considered as the basic emotion level, and the lowest, subordinate, level consists of groups of individual emotions that form a category named after the most typical emotion of that category. Along the lines of the hierarchical structures of Shaver et al. (1987) and Storm and Storm (1987), we thus propose that consumer emotions can be considered at different levels of abstractness. Our hierarchy of consumer emotions distinguishes between positive and negative affect at the superordinate level. The specific consumer emotions based on Richins’ (1997) CES encompass the subordinate level. Which basic emotions should constitute the intermediate level, however, is less clear. Basic emotions are believed to be innate and universal, but because there are different ways to conceive emotions (facial, e.g., Ekman, 1992; biosocial, e.g., Izard, 1992; brain, e.g., Panksepp, 1992), there is also disagreement about which emotions are basic (Turner and Ortony, 1992). Ortony and Turner (1990) have shown that 14 different emotion theorists proposed 14 different sets of basic emotions. Table 3 shows the usage frequency of the basic emotions in the different structures reviewed by Ortony and Turner (1990). With few exceptions, the basic

Table 3 Basic emotions in the psychological literature (adapted from Ortony and Turner, 1990) Acceptancea, Angera,b,c,d,e,f,g,h,i, Anticipationa, Anxietyf,h,j, Aversionb, Contemptd,i, Contentmenth, Courageb, Dejectionb, Desireb,k, Despairb, Disgusta,c,d,e,f,h,i, Distressd,i, Elatione, Expectancyl, Feara,b,c,d,e,g,h,i,l,m,n, Grief m, Guiltd, Happinessf,h,k,o, Hateb, Hopeb, Hostilityh, Interestd,k, Joya,c,d,g,i,j, Likingh, Loveb,g,h,m,n, Painh,p, Panicl, Pleasurep, Prideh, Ragej,l,m,n, Sadnessa,b,c,f,g,h,o, Shamed,h,i, Sorrowk, Subjectione, Surprisea,c,d,i,k, Tendere, Wondere,k a

Plutchik (1980). Arnold (1960). c Ekman et al. (1982). d Izard (1971). e McDougal (1926). f Oatley and Johnson-Laird (1987) g Shaver et al. (1987). h Storm and Storm (1987). i Tomkins (1984). j Gray (1982). k Frijda (1986). l Panksepp (1982). m James (1884). n Watson (1930). o Weiner and Graham (1984). p Mowrer (1960). b

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emotions from Table 3 are among the most frequently mentioned emotion words in Table 2. To develop a set of basic consumer emotions, we draw on the hierarchical structures of Shaver et al. (1987) and Storm and Storm (1987), and Table 3. Some basic emotion words are mentioned in most of the structures (see Table 3). These are anger, fear, love, sadness, disgust, joy, and surprise. Anger, fear, love and sadness are basic emotions in both the structures of Shaver et al. (1987) and Storm and Storm (1987), and will be retained in our structure. Disgust is not included in the structure of Richins (1997) and therefore excluded as a basic consumption emotion. Surprise was excluded for several reasons. First, it is a neutral emotion (Storm and Storm, 1987) and therefore impossible to classify as a positive or negative emotion. Second, when participants were required to list emotions, surprise was hardly mentioned (Fehr and Russell, 1984). Following Storm and Storm (1987), we added the emotion shame to the basic negative emotions. Anger, sadness, and fear are all emotions elicited by situations caused by others or circumstances, whereas shame is caused by a negative action of consumers themselves (Roseman et al., 1996). The positive emotions can be roughly divided in interpersonal emotions and emotions without interpersonal reference (Storm and Storm, 1987). The interpersonal emotions are covered by love and its specific emotion words, but there are distinct differences between the emotions that are not interpersonal. Following Storm and Storm (1987), we therefore replaced the more general term joy by the basic emotions contentment, happiness, and pride. Contentment is low in arousal and passive, whereas happiness is higher in activity and a reactive positive emotion. Pride, on the other hand, concerns feelings of superiority. Due to these differences, we argue that it is better to include these basic emotions separately rather than all under one large basic emotion of joy. Our proposed hierarchy thus consists of three levels: the superordinate level with positive and negative affect, the basic level with four positive and four negative emotions, and the subordinate level with specific emotions. The final

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result can be seen in Fig. 1. Next, we will conduct a preliminary test of our hypothesized structure.

5. Method 5.1. Sample and procedure Data were collected in a nationally representative sample among 645 Dutch consumers using a questionnaire. The market research agency GfK carried out the data collection. Of the respondents, 53.6% were women, 58.3% were responsible for the daily grocery shopping, and 69.1% were the main wage earner of the household. The average household size was 2.39 persons and all levels of education and income were represented. The average age was 48 years and ranged between 16 and 91 with a fairly normal spread. Respondents were asked to indicate to what extent they experience 33 specific emotions for one (randomly assigned) type of food (genetically modified food, functional food, organic food, or regular food). Thus, we measure emotions at a general, product-type level of categorization. In The Netherlands, these types of foods are widely known, the exception being functional foods (this was confirmed in discussions with industry experts). Therefore, respondents who rated their emotions for functional foods received additional explanation: bFunctional foods are food products that have been enriched or modified. The reason for this is to make the product healthier or to prevent diseases (e.g., milk with extra calcium, margarine with additives to lower the cholesterol level)Q. 5.2. Measures With some exceptions, the emotion words shown in Fig. 1 were used. Emotions were rated on a five-point Likert scale ranging from I feel this emotion not at all (1) to I feel this emotion very strongly (5). In our empirical test, we omitted the basic emotions bloveQ and bprideQ, and the

Fig. 1. Hierarchy of consumer emotions.

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emotion words benviousQ and bjealousQ. bLoveQ is demonstrated to be mainly experienced in the case of sentimental products, like mementos and gifts (Richins, 1997). The latter three emotions are interpersonal and less applicable in the case of widely available food. The emotion bprideQ generally occurs when a consumer feels superior compared to another person, whereas the emotions benvyQ and bjealousyQ occur when consumers feel that another person has something more or better than them. Thus, the basic emotions in our analyses are as follows: anger, fear, sadness, shame, contentment, and happiness, measured in total by 33 specific emotion words. 5.2. Stability of the emotions structure across food types Before we can test our second-order hierarchical model of consumer emotions, we have to establish whether we can pool the data across the four food types. We do this in two ways. First, we assess whether principal component analysis yields the same factor structure in each of the four food groups. The Bartlett’s test of sphericity is significant for all four foods, and the measure of sampling adequacy ranges between .86 (organic food) and .92 (genetically modified food), which means that principal component analysis can be applied. The scree test indicated two factors in all four groups, explaining between 48% (regular food) and 60% (genetically modified food) of the variance. The factor structures (after rotation) were highly similar, Tucker’s congruence coefficient always being greater than .95 ( P b.01; Cattell, 1978). A second way to assess the similarity of the four food groups is to test for the invariance of the covariance matrices across the four groups using LISREL 8.50 (Steenkamp and Baumgartner, 1998). The fit was good, given the large sample and high number of degrees of freedom (Baumgartner and Homburg, 1996): v 2(1683)=3845.90 ( Pb.001); CFI=.86; TLI=.82. Hence, we can pool the data across the different food types.

6. Results 6.1. Testing the proposed model We used LISREL 8.50 to test the proposed hierarchical emotions model. The standardized parameter estimates of the second-order factor analysis are reported in Fig. 2. Model fit is acceptable: v 2(490)=3036.79 ( Pb.001), CFI=.84, TLI=.83. Although the v 2 was highly significant (not unexpected given the large sample size; Anderson and Gerbing, 1988), other indicators suggest reasonable model fit, especially considering that fit is adversely affected by model complexity (Baumgartner and Homburg, 1996; Bollen, 1989; Bone et al., 1989). In addition, the fit measures are in line with simulation results (see Gerbing and Anderson, 1993 for a review) and compare favorably to

other models with similar degrees of freedom (e.g., Netemeyer et al., 1991; Richins and Dawson, 1992; Wong et al., 2003). All factor loadings were significant at P b.001, the average loading being .73. Only the factor loading of the emotion nostalgia on the basic emotion sadness was below .40. A possible explanation for this is that nostalgia involves complex emotional responses and can have both a positive and a negative connotation (Holak and Havlena, 1998). The correlation between the second-order factors positive and negative affect was significant (r= .35, Pb.01), confirming earlier results found in consumer research (e.g., Westbrook, 1987; Phillips and Baumgartner, 2002). These results support the convergent and discriminant validity of our model (Steenkamp and Van Trijp, 1991). The reliability of our measures was high. Cronbach alphas were a=.94 and a=.95 for the dimensions positive and negative affect, respectively. The basic emotions yielded the following reliabilities: anger (a=.88), fear (a=.88), sadness (a=.76), shame (a=.74), contentment (a=.86), and happiness (a=.92). 6.2. Comparison of the superordinate level with the basic emotions Although the emotion structure is similar for the four food groups, that does not imply that the various foods evoke the same emotional intensity. Table 4 provides the mean scores for the superordinate dimensions positive and negative affect and for the basic emotions. ANOVA with multiple comparisons (LSD) was used to investigate whether the mean values across food groups are significantly different. Participants experience significantly more negative affect and less positive affect for genetically modified foods than for the other food groups. Yet, the basic emotions show differences among the food types that would have been lost if only positive and negative affect had been considered. Both the basic emotions fear and contentment contain additional subtle distinctions across the food groups. The negative affect experienced by consumers is similar for functional, organic, and regular food. Yet, consumers feel a lot more fearful concerning functional food than for organic and regular food. Concerning the positive emotions, contentment has very low values for organic food compared to functional and regular food. These nuances, however, are wiped away for positive affect. To demonstrate the usefulness of basic emotions for understanding the consumer’s feelings, we will take a closer look at one of the food groups. Genetically modified food represents a controversial topic in contemporary society, and previous research (e.g., Bredahl, 2001) has shown that consumers have a rather negative attitude towards this type of food. The scores on negative and positive affect support this, but the basic emotions indicate more clearly how consumers feel. Participants do not feel sad or ashamed, but

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Fig. 2. Results of second-order factor analysis.

are very angry and afraid. This means that they feel energized and powerful rather than inactive, and feel that they themselves are not to be blamed, but someone else is.

In addition, genetically modified food elicits strong associations of risk and uncertainty leading to feelings of fear.

Table 4 Differences in the intensity of the superordinate and basic emotions for the food groups Emotion

GMF

Functional

Organic

Regular

F

P value

Negative affect Anger Sadness Fear Shame Positive affect Contentment Happiness

1.99a 2.19a 1.79a 2.16a 1.65a 1.68a 1.82a 1.64a

1.45b 1.51b 1.46b 1.57b 1.32b 2.41b,c 2.69b 2.32b

1.43b 1.47b 1.47b 1.40c 1.29b 2.32c 2.40c 2.29b

1.46b 1.55b 1.47b 1.43c 1.31b 2.48b 2.81b 2.37b

31.25 34.49 11.99 46.06 11.30 40.09 47.38 33.64

b.001 b.001 b.001 b.001 b.001 b.001 b.001 b.001

Note: Different supercripts reflect a significant difference of the intensity at a p-value b0.05.

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7. Conclusion

References

Based on our literature review, we concluded that despite the different ways to measure emotions, positive and negative affect are frequently employed as general emotion dimensions. Important nuances, however, are lost if emotions of the same valence are collapsed together. This paper therefore proposed a hierarchical model of consumer emotions (Fig. 1) to integrate the different research streams concerning emotion content and structure. This model specifies emotions at three levels of generality. At the superordinate level, it distinguishes between positive and negative affect. This is generally considered to be the most abstract level at which emotions can be experienced (e.g., Berkowitz, 2000; Diener, 1999). At the level of basic emotions, we specify four positive (contentment, happiness, love, and pride) and four negative (sadness, fear, anger, and shame). At the subordinate level, we distinguish between 42 specific emotions based on Richins’ (1997) CES. Our empirical study provides support for the proposed model and suggests that the basic emotions allow for a better understanding of the consumers’ feelings concerning certain food products compared to only positive and negative affect. Note that not in all situations this model need be used as a whole. Dependent on the research question, only part of the model may be used. However, even in such cases, the researcher can still relate his/her specific results to the broader structure of our emotions. This makes it easier for emotions research to cumulatively build on each other and to identify gaps in our knowledge. Our study has several limitations, which offer avenues for future research. First, we excluded two basic emotions (love and pride) from our empirical analysis. Future research is needed to validate the whole hierarchy of emotions, and to test our model on other products and services. Second, future research can expand the set of specific consumer emotions. Possible candidates include the negative emotions regret and disappointment that recently received a great deal of attention in consumer research (e.g., Inman and Zeelenberg, 2002; Tsiros and Mittal, 2000; Zeelenberg and Pieters, 1999). Regret stems from bad decisions, whereas disappointment originates from disconfirmed expectancies (Zeelenberg and Pieters, 1999). We thus propose that regret can be positioned under the basic emotion shame, and disappointment under the basic emotion sadness (Zeelenberg et al., 1998), but future research should investigate this. Third, future research can investigate whether the set of basic emotions has greater explanatory power than positive and negative affect. Our exploratory analysis indicates this, but future research should test this hypothesis. Fourth, we tested our emotions model in The Netherlands. The further advancement of consumer research as an academic discipline requires that the validity of our theories and measures and their degree of general validity and boundary conditions be tested in different countries (Steenkamp and Burgess, 2002).

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Journal of Business Research 58 (2005) 1446 – 1455

Four characters on the stage playing three games: performing arts consumption in Spain ´ lvarezb Jordi Lo´pez Sintasa,*, Ercilia Garcı´a A a

Dept. d’Economia de lVEmpresa, Facultat d’Economia, Universitat Auto`noma de Barcelona, Edifici B, 08193 Bellaterra, Barcelona, Spain b IESE Graduate Business School, Universidad de Navarra, Spain Received 1 November 2002; received in revised form 1 September 2003; accepted 1 October 2003

Abstract There are presently three competing hypotheses about the symbolic role played by consumption: the distinction, the boundary-effacement, and omnivore effects. Our research design follows another recently proposed alternate view in which all three effects are working simultaneously, but to differing degrees, and introduces several innovations. We found that in the Spanish performing arts symbolic space, the stage has four characters: sporadic, popular, snob, and omnivorous consumers, playing three symbolic games, namely, boundary-effacement, omnivore, and distinction, but to differing degrees. That is, we found (1) weak evidence for a few popular performing arts events liked by everyone, but not necessarily all lowbrow performances, (2) strong evidence favoring the hypothesis that consumers from the highest social class consume all arts at higher rates than everyone else do, and (3) moderate evidence that social classes use the performing arts’ space of consumption to symbolize status differences. D 2004 Elsevier Inc. All rights reserved. Keywords: Performing arts; Sociology of consumption; Distinction effect; Symbolic roles; Omnivore effect

1. Segmentation of consumers according to lifestyle The symbolic properties of products have been widely acknowledged since Martineau’s pioneer study of the sociology of marketing (Martineau, 1958). This has led to a great deal of interest in marketing to assess the ability of social class indicators to discriminate among patterns of consumption (Curtis, 1972; Schaninger, 1981; Wasson, 1969), with this interest persisting to this day (Dawson et al., 1990; Sivadas et al., 1997). Nevertheless, these findings seem to offer conflicting results, depending on the indicators used to judge consumers’ social class and the product categories researched. In this study, we draw some conclusions from these varied results by theoretically grounding our research design. There are currently three competing hypotheses

about the role played by consumption: the distinction, boundary-effacement, and omnivore effects. Our research design, nevertheless, follows the alternative view of Holbrook et al. (2002), which proposes that all three effects are working simultaneously but to differing degrees and introduces several innovations. In contrast with previous research, ours is the first that (a) is based on individuals’ rate of performing arts consumption rather than geodemographic clusters, (b) uses additional cultural categories, as well as different social class indicators, (c) simultaneously finds patterns of consumption and identifies the relationship to consumer’s social position, and lastly, (d) evaluates whether the three competing hypotheses are operating simultaneously in the performing arts symbolic space.

2. Theoretical framework * Corresponding author. E-mail address: [email protected] (J. Lo´pez Sintas). 0148-2963/$ - see front matter D 2004 Elsevier Inc. All rights reserved. doi:10.1016/j.jbusres.2003.10.013

Social classes can be characterized as groups of agents who are subject to similar conditions of existence (habitus)

J. Lo´pez Sintas, E. Garcı´a A´lvarez / Journal of Business Research 58 (2005) 1446–1455

and conditioning factors and, as a result, are endowed with similar preferences and, therefore, similar practices or lifestyles (Bourdieu, 1987; O’Shaughnessy, 1987). These similar positions in social space are produced by different levels and types of capital, both economic and cultural (Bourdieu, 1998[1979]). Thus, consumers who occupy neighboring positions in this social space are therefore subject to similar conditioning factors: They have many chances of having similar dispositions and interests, which leads to similar patterns of consumption. Here, we make the distinction between consumers’ social space position and consumers’ social class. The latter is indicated by the levels and types of economic and cultural capital, as suggested by the sociology of consumption (Bourdieu, 1998[1979]; DiMaggio and Useem, 1978), whereas the former focuses on the consumer’s social class and other cultural categories (McCracken, 1986). By judging the symbolic properties of consumption spaces (of the performing arts, in this case), we ought to search for consumers’ consumption patterns and see how they are associated to the consumers’ social class and other cultural categories (Boter and Wedel, 1999; van Rees et al., 1999). Below, we take a look at those symbolic properties. 2.1. The distinction effect The sociological analysis of consumption proposes that lifestyles be stratified according to social class (DiMaggio and Useem, 1978; Bourdieu, 1998[1979], 1987). According to Bourdieu, social hierarchy is translated into, and misrecognized as, cultural symbols and lifestyles inherent in individuals through the mediating structure of habitus. The habitus space includes schemes of perception and the evaluation of daily habits, cognitive structures, and evaluation procedures that are acquired from repetitive experience with the consumer’s conditions and position in the social space (see Levy’s pioneer studies on the symbolic properties of consuming the arts, compiled by Roock, 1999). The habitus space is also called the corpus of cultural principles (McCracken, 1986), as they explain the ideas or values that clarify the way in which social classes discriminate between them. People internalize the habitus space, determining cultural, as well as material, choices that reproduce the very class structure itself. choices that reproduce the very class structure itself. The main proposition derived from Bourdieu’s theory, as well as that of DiMaggio and Useem (1978), is that the symbolic space of consumption will be segmented in a homologous way as the society is stratified (Bourdieu, 1998[1979]; DiMaggio and Useem, 1978), i.e., that consumption symbolizes status. Nearly all research conducted until now claiming support for or casting doubts on the distinction hypothesis has used binary indicators of consumption. To our knowledge, the current dispute about the ability of social class indicators to discriminate among

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patterns of consumption is based on the use of binary indicators. For the sake of clarity, we have produced Panel A in Fig. 1, where L1 and L2 stand for two different lowbrow cultural products and H1 and H2 for two highbrow cultural products, D and U for downscale and upscale social class, respectively, and the vertical axis for consumption rate. If we analyze the consumption of lowbrow (L) and highbrow (H) products, basing our judgment on whether the different social classes (D and U) consume each product at least once a year, it would appear that no one uses consumption to differentiate themselves from other consumers because everyone consumes each product at least once. If we take into account how much they consume each product, however, we would see the opposite pattern shown in Panel A. Both lowbrow and highbrow products have a high consumption marginal mean, but with an opposite pattern: Downscale (upscale) consumers really do prefer lowbrow (highbrow) products to highbrow (lowbrow). Thus, intuitively, we see that, although everyone consumes everything, they do so to differing degrees. 2.2. The boundary-effacement or homogeneity effect Both the cultural theorists—particularly those associated with the Frankfurt School—and the postmodernists have foreseen an increase in the consumption of popular cultural products. The former were preoccupied with the rise in the consumption of cultural products offered by the so-called cultural industries (Adorno, 1991; Morin, 1967). These authors pointed out the possibility that the rise of market could greatly erode upscale social classes’ preferences for highbrow cultural products, particularly opera, classical music, ballet/dance, etc., as cultural industries intentionally integrate its consumers, both from high culture to popular (Adorno, 1991, p. 85). The end result is that the status of popular culture is raised, and the status of high culture is lowered (Morin, 1967, p. 65), obscuring social differences through the objective homogeneity of popular mass culture (everyone consumes it), thereby making social class differences invisible. Postmodernists, nevertheless, have a positive view of cultural disorder. The blurring distinctions between levels of culture (high vs. popular) give way to a glutinous mass that stimulates and plays with the overproduction of signs (Featherstone, 1992, p. 271). Consumption, then, is embedded within systems of signification, of making and maintaining distinctions (Firat and Venkatesh, 1995, p. 249). Consequently, it is expected that the salience of social class factors is declining and that consumption patterns are becoming more fragmented (Clark and Lipset, 1991; Featherstone, 1992; Firat and Venkatesh, 1995; Gartman, 1991). These authors, then, suggest that we look for other cultural categories to understand the way in which consumption is stratified—here, we will turn our attention towards gender, age, and marital status to control its effect.

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J. Lo´pez Sintas, E. Garcı´a A´lvarez / Journal of Business Research 58 (2005) 1446–1455

Fig. 1. Boundary-effacement, omnivore, and distinction effects only and all simultaneously. (A) Distinction effect only. (B) Boundary-effacement effect only. (C) Omnivore effect only. (D) All effects operating simultaneously.

The problem we now encounter is how to test the proposition that the consumption of highbrow cultural products decreases as the consumption of mass culture products increases. Again, we have to distinguish between how many products are consumed and how much they are consumed. In this research, we take mass culture products to mean popular cultural products, pop music, flamenco shows, folk music, and jazz concerts (also potentially including films, recorded music, video productions, and, in general, all products classified as part of the cultural industries). If the homology effect works, we should find that everyone does indeed prefer lowbrow or popular cultural products to highbrow, as illustrated in Fig. 1, Panel B: In fact, upscale, as well as downscale, consumers do consume lowbrow cultural products at higher rates than highbrow products. Nevertheless, upscale social class consumers’ rate of consumption is higher than of the downscale. 2.3. The omnivore effect Another more recent line of research, however, has also cast doubts on the homology thesis between high position in social hierarchy and the consumption of high culture products. DiMaggio (1987, p. 444) has proposed

that the variety of cultural products that a person consumes is a function of his or her socioeconomic status (SES). Therefore, although the upper class clearly has more knowledge of, and participates more frequently in, high culture, research has also consistently shown that its members participate in the popular culture as well, and often at levels equivalent to the lower classes (Peterson and Kern, 1996; Peterson, 1992). That is, upper classes show an omnivorous pattern of consumption known as an omnivore effect (Holbrook et al., 2002). Social class status is gained not only by consuming prestigious forms of art, but also by showing off one’s cultural knowledge in a wide variety of genres. As a result, no rigid class boundaries appear to exist in the consumption of popular and high culture. Therefore, the omnivorous consumption thesis proposes that all persons (or at least a group of consumers) consume everything, although at different levels. If this hypothesis is working in isolation, we should find (1) no differences between the level of consumption of lowbrow and highbrow products and (2) differences between downscale and upscale rate of consumption, as in Panel C in Fig. 1; that is, we should see that upscale social classes consumption is always higher than that of downscale consumers.

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2.4. All effects simultaneously operating but at different degrees Until the work of Holbrook et al. (2002), these three effects on consumption had been viewed as in competition. In contrast, these authors proposed a research design in which all three effects are working simultaneously, as shown in Panel D of Fig. 1: The distinction effect operates through the interaction between the type of consumer and the type of product (the lines are not parallel); there is a boundary-effacement effect as all consumers prefer lowbrow to highbrow cultural products (consumed at higher rates by all consumers); and, finally, the omnivore effect also works as everyone consumes every product but at different rates. Consequently, researchers should focus on measuring the extent to which each effect is simultaneously working with the other two.

3. Research Design To measure the extent to which all three effects are operating simultaneously, we should proceed in two steps: First, we ought to look for consumers’ patterns of consumption and see how they are related to their social class’s indicators and other cultural categories as well; and second, given the estimated patterns of consumption, we should test the degree to which the distinction, boundaryeffacement, and omnivore effects work simultaneously in the consumption of performing arts. 3.1. Sample Data were obtained from the bHabits of Cultural ConsumptionQ survey requested by the Sociedad General de Autores Espan˜ oles (SGAE) in 1998. This survey conducted home interviews of over 12,000 individuals of men and women, 14 years old and over, living in Spain, through four quarter waves of about 3000 interviewees, comprising a random sample, stratified by autonomous regions and municipalities according to size. Further technical characteristics of the sample are described in the survey report (SGAE, 2000). 3.2. Indicators of performing arts attendance Nine performing arts indicators were analyzed, with some of them classified as popular or lowbrow cultural products (pop music, flamenco shows, folk music, and jazz concerts) and others as highbrow cultural products (classical music, opera, light opera, ballet/dance, and theater). Interviewees were asked how often they went to each performing arts category within the past 12 months. Attendance to classical music, opera, light opera, ballet, and theater was originally recorded as a six-level ordered factor, and going to pop music concerts, flamenco shows,

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folk music events, and jazz concerts, as a seven-level ordered factor (see SGAE, 2000, for the details). To find the patterns of consumption, we recoded the answers and reduced them to only two levels: attendance and nonattendance during the last 12 months. Nevertheless, to disentangle the functioning of all three effects working simultaneously, we were also interested in the rate of consumption (how much), not only the pattern of consumption (how many). Consequently, the ordered factors were transformed into ratio metric variables using the central value of the interval in the case of closed intervals, or the lower limit for the rest. 3.3. Indicators of social class To approximate consumers’ social class, we used three indicators: SES and educational and income level. In the first case, we employed the Erikson–Goldthorpe procedure (EGP; Evans, 1992), as it is being used to analyze the relation between social class and cultural consumption (Katz-Gerro and Shavit, 1998). We transformed the original SGAE codification into an EGP class classification with five SES categories plus two additional categories that account for students and the unemployed. For the educational and income levels, we created five categories for each factor (see the Findings section for details). 3.4. Indicators of other cultural categories Many authors have found a generational effect in the consumption of cultural products (Holbrook, 1993). To control for this effect, we formed five age categories. Finally, two categories were used for consumers’ gender, and four for marital status (see results for further details). 3.5. Analytical procedure 3.5.1. Step 1 To define our latent class cluster model (Lazarsfeld and Henry, 1968), we used y 1, y 2,. . ., y 9 to denote our nine indicators of cultural activities, and the bold symbol y for the entire set of indicators. S was any possible combination that our nine indicators could produce, each one symbolized as y s . The six independent cultural categories were denoted as z 1, z 2, . . ., z 6, with z representing the entire set of covariates. A latent class cluster model with active covariates looks for a latent variable, x, that splits the original sample in T clusters or classes, such that the original association observed in the whole sample between the indicators of performing arts attendance, in this case, is removed from the clusters estimated, and, at the same time, the T clusters are also homogeneous in their independent cultural categories (see Magidson and Vermunt, 2001, for further details). Additionally, to make us sure that the same patterns of consumption characterize the T latent classes in the four quarter waves, we introduced a grouping variable

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for the quarter waves, v, with four levels and tested this reduced model (measurement homogeneity) against the general one (measurement heterogeneity), with the evidence favoring the reduced model (see McCutcheon, 1987. Due to space restrictions, the appendix for the model selection process will be sent upon request). We then tested the distributional homogeneity of the T latent classes among the four waves, but found no support. As a result, the reduced model estimated was the following:




p ys jv; z ¼

T X t¼1

pð xjv; zÞ

9 Y

pðyis jx; zÞ:

i¼1

3.5.2. Step 2 To analyze the distinction, boundary-effacement, and omnivore effects, we used a mixed-effects general linear model to analyze a repeated-measures design (Rutherford, 2001) to explain the rate of consumption. We modeled the performing arts rate of consumption depending on (1) a within-subjects fixed effect, a j , which is the factor assessing the boundary-effacement effect, (2) an external consumption pattern factor that analyzes the omnivore effect, b k , and (3) an interaction between both factors that evaluates the distinction effect, ab jk . Finally, as we wanted to generalize our result to the Spanish population, we modeled the consumer’s interaction with the types of performing arts as a factor with random effects, a ij . Our final model was the following: yijk ¼ l þ aij þ aj þ bk þ abjk þ eijk :

4. Findings 4.1. Step 1: Lifestyles and consumers’ social space position 4.1.1. Patterns of performing arts attendance Table 1 shows the estimates of the parameters for the four-cluster model with concomitant variables, but only displays the association of the performing arts indicators with each cluster—later, we show the relationship of clusters with cultural categories (the model parameters have been estimated with the LatentGold program, see Vermunt and Magidson, 2000). The first row presents how many attendees have been classified in each cluster, i.e., its relative size, and the following rows indicate the probability of belonging to a particular performing arts indicator, given one’s classification in that cluster; all values are expressed as percentages. For instance, if an interviewee has been assigned to Cluster 1, he or she has a probability of almost 99% of not going to any concert of classical music, and therefore, a 1% chance of having gone to one live performance of classical music. On the other hand, if the interviewee has been allocated to Cluster 4, his or her probability of going to classical music concerts is expected

Table 1 Patterns of consumption according to performing arts attendance (probabilities of attendance are in percentage) Indicators Cluster size Classical music Attend Opera Attend Light opera Attend Ballet/dance Attend Theater Attend Pop music Attend Flamenco Attend Folk music Attend Jazz Attend

Cluster 1

Cluster 2

Cluster 3

Cluster 4

Sporadic

Popular

Snobs

Omnivorous

69

20

8

3

1

5

58

63

0

0

18

23

0

0

21

17

0

0

13

37

10

25

70

85

0

83

0

85

2

9

5

32

2

7

10

41

0

6

5

46

25 25 25 25

25 25 25 25

34 27 22 17

Distribution of quarter waves 1 24 2 25 3 25 4 26

to be higher, 37%, and a 63% possibility of not going. Based on these conditional probabilities, we can characterize the probabilistic behavior of the Spaniards regarding this set of performing arts indicators. The estimated model suggests that in the Spanish population, on average, there are four patterns of consumption or lifestyles as far as performing arts attendance is concerned. There is a very large segment, Cluster 1 (which accounts for 69% of the population), that spends very little of its leisure time attending or going to any performance, whether it is high or low culture. For this reason, this group has been labeled the sporadic class of consumers. The second cluster has been designated the popular class of consumers due to their lifestyle: They have a consistent pattern of attending popular performances, but almost no attendance at highbrow performances. The popular class of consumers accounts for 20% of the Spanish population. Cluster 3 has been labeled the snob class of consumers to facilitate the discussion of our results with those published by other researchers. This group of consumers accounts for almost 8% of Spaniards who attend the performing arts. Its pattern of consumption is consistent with attendance at the highbrow performances, particularly classical music concerts, light opera (the highest probability among the four clusters), opera, and ballet/dance. Finally, consumers of the omnivorous class, Cluster 4, display an insatiable demand for a variety of cultural genres, as much for high culture types as for popular ones. Nevertheless, the group is small

J. Lo´pez Sintas, E. Garcı´a A´lvarez / Journal of Business Research 58 (2005) 1446–1455 Table 2 Patterns of consumption and their cultural categories (probabilities are in percentage)

Mean probability Variables Social class Service 1a Service 2b Nonmanual Entrepreneurs SMEs Manual Not employed Students Age Less than 25 years old 25–34 35–44 45–54 More than 54 years old Gender Male Female Educational level Primary or less Low secondary High secondary College University degree Monthly income Less than 600o ]600o, 900o] ]900o, 1200o] ]1200o, 1800o] More than 1800o Marital status Single Married Widowed Divorced

Cluster 1

Cluster 2

Cluster 3

Cluster 4

Sporadic

Popular

Snobs

Omnivorous

69

20

8

3

35 52 62 69

21 25 28 17

29 14 5 10

15 9 5 4

70 84 41

24 7 53

3 8 2

3 1 4

43

52

1

4

56 72 80 88

32 13 4 1

5 10 14 11

7 5 2 0

66 71

23 17

7 9

4 3

95 77 52 41 33

2 17 37 30 22

3 5 7 19 28

0 1 5 10 17

88 74 65 53 39

7 18 24 29 30

4 6 7 12 22

1 2 4 6 9

46 80 90 72

43 9 1 11

5 9 9 12

6 2 0 5

a

Service 1 includes employers of large firms and employees with a service relationship, like professional, higher technical, administrative and managerial, with a higher grade. b Service 2 only includes employees with a service relationship, like Service 1, but of a lower grade.

and accounts for slightly more than 3%. If we look at the probability of going to every type of performance, consumers of the omnivorous class have the highest chance of going to the high culture performances, except for light opera. Nevertheless, when compared with consumers of the popular class, omnivores also have the highest probability, by far, of going to popular performing arts. 4.1.2. Social class indicators and other cultural categories associated to lifestyles Here, we present the clusters’ profile for the levels of each active concomitant variable once the simultaneous

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model of classification and identification is estimated as is usual (Magidson and Vermunt, 2001). This procedure is equivalent to estimating the row profiles in a correspondence analysis when there is no restriction in the estimated latent class cluster model. For easier reading of Table 2 for each class of consumers, we have underlined probabilities greater than their mean profile (cluster size). The social class indicators—SES and level of education and income—are clear in the construction of a social hierarchy. All indicators of the lower social class are associated with the group of sporadic consumers: the lowest SES and the lowest levels of income and education as well. The indicators of middle class are associated with the popular class of consumers, especially nonmanual workers and a relatively minor proportion of employees from the middle and high managerial hierarchy (SES Services 1 and 2), with a college or university degree and good levels of income. The snob class of consumers is slightly higher on the social ladder, upper–middle class, with members from the highest managerial hierarchies and with university degrees and high levels of income. Finally, omnivorous consumers are associated with the highest social rank: They come from the highest managerial hierarchy, educational level, and income in a greater proportion than snobs do.

Table 3 General linear model with repeated measures with within-consumer performing arts fixed effects Effect

Boundary-effacement effect (within subjects and across activities)a Omnivore effect (between-consumer patterns of consumption)b Distinction effect (performing arts by patterns of consumption)c

Significance tests

Effect size

df

F

P level

g2

8, 94424

1598.49

b.0001

0.119

3, 11803

4324.54

b.0001

0.524

24, 94424

1201.10

b.0001

0.234

a The test reported here assumes bsphericityQ; that is, that the error covariance matrix of the orthonormalized transformed dependent variables is proportional to an identity matrix. The data did not pass Mauchly’s test of sphericity (v 2=29013.81,df=35, Pb.0001). However, the corrected Greenhouse-Geisser (GG) and Huynh-Feldt (HF) tests produce results similar to those shown in the main body of the table; that is, F GG=1598.49, df GG=5.39, 63631.31, P GGb.0001; F HF=1598,49, df HF=5.39, 63679.96, P HFb.0001. b The four multivariate tests, Pillai’s trace, Wilk’s lambda, Hotelling’s trace, and Roy’s largest root, produced the same statistics: F=1117,1, df=8, 11796, P=b.0001; g 2=0.431. c The corrected test again produced results similar to those shown in the table, namely, F GG=19425.86, df GG=16.17, 63631.31, P GGb.0001; F HF=19440.71, df HF=16.19, 63679.96, P HFb.0001.

J. Lo´pez Sintas, E. Garcı´a A´lvarez / Journal of Business Research 58 (2005) 1446–1455

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As far as the other cultural categories are concerned, sporadic consumers are the oldest and include slightly more males than females, typically with a marital status of widowed and divorced. The class of popular consumers consists of mainly single individuals who are younger, with more male than female consumers. The cluster of snob consumers, on the other hand, is made up of consumers over 35 years old, especially between 45 and 54 years old, and generally more females. In terms of marital status, the class is composed of just as many married as widowed persons, with a greater proportion of divorced individuals. Lastly, the class of omnivorous consumers is not as young as the popular consumers are, but are younger than the snobs are, and consequently composed of more singles and divorced persons. As far as gender is concerned, there are more males than females, although the difference is small.

Therefore, there is weak evidence for the boundaryeffacement effect.

4.2. Step 2: Evaluation of distinction, boundary-effacement, and omnivore effects

4.2.2. Omnivore effect When working with the omnivore effect, once we average the consumers’ rate of consumption for all types of performing arts, we should find differences among the types of consumers. This is what the between-subjects factor tries to capture. The omnivore effect is meaningful and the strongest of all three effects (g 2=0.524). Certainly, there is a strong tendency for upscale consumers to show higher consumption rates across all types of performing arts (see Table 4). The omnivorous pattern of consumption has the highest combined rate of consumption, and the combined rate of consumption has also the highest difference measured in standard errors and highest g 2 value. Consequently, we may conclude that our research does provide strong evidence that some people like everything.

4.2.1. Boundary-effacement effect In Table 3, we present the results of testing the hypothesis in a condensed format (SPSS Program, v11, was used to estimate the model). We see that the boundary-effacement effect is meaningful (there are differences in participation rates among the performing arts), although not strong (g 2=0.119). A detailed look indicates that the overall rate of the participation column in Table 4 shows that the highest participation rate corresponds to pop music concerts and theater, two popular performing arts events (in fact, empirically, theatrical performances cannot be classified as either lowbrow or highbrow product, but as between them), followed by classical music, folk events, flamenco shows, jazz, ballet, light opera, and opera. Hence, there are a few lowbrow performing arts categories in which the rate of consumption is consistently greater than the participation rate of some highbrow performing arts for all types of consumers, but not all of them, because classical music is the third highest category in terms of consumption.

4.2.3. Distinction effect The distinction effect works as an interaction among the performing arts factor (the boundary-effacement effect) and the patterns of consumption (the omnivorous effect) on the level of consumption. As far as the performing arts are concerned, it seems to be moderately strong (g 2=0.234) but statistically meaningful. Table 4, where performing arts types are ordered according to the magnitude of the difference in participation rate between sporadic and omnivorous class of consumers (measured in standard errors), shows why the distinction effect is modest. The differences grow as one progresses from the categories of light opera to flamenco, folk, opera, pop music, classical music, ballet, theater, and jazz. Although upscale social classes consume highbrow performing arts events more often than do low class consumers, differences are greater in some popular performing arts, like jazz and theater, and the between-group variability explained (g 2) is greater in the case of attendance to pop music concerts. There is a clear order in the

Table 4 Univariate tests for effects of the class split on combined activity level and on participation rates Category

Combined Light opera Flamenco Folk Opera Pop music Classical music Ballet Theater Jazz

Overall participation rates and by consumer class, along with standard errors (S.E.)

Effect size 2

Overall (S.E.)

Sporadic (S.E.)

Popular (S.E.)

Snob (S.E.)

Omnivorous (S.E.)

g

0.19 0.06 0.12 0.13 0.05 0.53 0.20 0.06 0.51 0.08

0.05 0.01 0.06 0.05 0.00 0.02 0.03 0.00 0.25 0.00

0.43 0.02 0.23 0.20 0.01 2.49 0.10 0.03 0.63 0.18

0.63 0.57 0.14 0.36 0.46 0.03 1.65 0.36 2.01 0.16

1.38 0.40 0.86 1.15 0.54 2.81 1.75 0.87 2.65 1.36

0.52 0.14 0.04 0.08 0.15 0.50 0.30 0.18 0.25 0.15

(0.004) (0.004) (0.006) (0.007) (0.003) (0.013) (0.008) (0.004) (0.011) (0.006)

(0.001) (0.001) (0.05) (0.006) (.001) (0.001) (0.003) (0.001) (0.008) (0.001)

(0.009) (0.005) (0.021) (0.019) (0.002) (0.047) (0.013) (0.006) (0.027) (0.019)

(0.018) (0.042) (0.026) (0.045) (0.037) (0.004) (0.073) (0.034) (0.063) (0.030)

(0.041) (0.056) (0.087) (0.102) (0.060) (0.141) (0.117) (0.072) (0.098) (0.115)

Significance

Differences in S.E.

F(3,11803)

P level

368.89 97.5 114.29 157.14 180 214.62 215 217.5 218.18 226.67

4324.54 631.50 178.96 324.90 711.31 3999.33 1690.93 833.45 1307.13 688.93

b.0001 b.0001 b.0001 b.0001 b.0001 b.0001 b.0001 b.0001 b.0001 b.0001

J. Lo´pez Sintas, E. Garcı´a A´lvarez / Journal of Business Research 58 (2005) 1446–1455

attendance rate among the four classes of consumers in the overall rate of performing arts consumption (see the combined means) that breaks down in some highbrow and popular performing arts categories. Only snob consumers differentiate themselves by just consuming highbrow performing arts; nevertheless, the upscale social class (omnivores) consumes highbrow performing arts not only at higher rates than snobs do but also attend popular performing arts at a higher rate than popular consumers do.

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ordered, that play three different games, but with different intensity: the game of obscuring social class differences through homogenization of consumption, the game of showing off social standing by omnivorous consumption, and the game of building up boundaries between social classes through consumption that symbolizes status.

6. Conclusion and implications 6.1. Theoretical Implications

5. Discussion We have found evidence that consumers buy patterns of consumption products that mold a specific lifestyle. That is, we have found four patterns of consumption or classes of consumers: sporadic, popular, snob, and omnivorous consumers. These patterns of consumption have also been found in different symbolic spaces (van Rees et al., 1999; Lo´pez and Garcı´a, 2002), differing only in their proportions. All studies found an occasional pattern of consumption that accounted for most of the population, the sporadic class of consumers, another segment with a popular taste (between 8% and 20%), and the snob and omnivorous classes of consumers, which had a varying size depending on the symbolic space researched (snobs are a smaller segment than omnivorous in the study of van Rees et al., 1999, of Dutch reading habits). The four patterns of consumption are hierarchically associated to the social class indicators in our findings and in those reported by van Rees et al. (1999) and Lo´pez and Garcı´a (2002). Nevertheless, the association with the other cultural indicators varies, depending on the symbolic space researched. Not only in this research but also in Lo´pez and Garcı´a (2002), omnivores are usually younger than 35, whereas in van Rees et al. (1999), they are older. Nevertheless, in every case, they are mainly men. Hence, we can conclude that although the research as a whole lends support to the omnivorous consumption hypothesis about higher social classes showing off their status through an omnivorous lifestyle (DiMaggio, 1987), the distinction and boundary-effacement effects are also at work. Even so, we do not know if differences found in other research are caused by differences in the symbolic space analyzed or in the social space. When comparing our findings with the ones found by Holbrook et al. (2002), we see that the boundary effacement is not as strong, but the omnivore effect is also the strongest, and the distinction effect is almost of the same size. Taking into account that the research of Holbrook et al. (2002) and ours differ in the procedure used to find social classes’ patterns of consumption, it is curious that the results are convergent. In the symbolic space of performing arts consumption in Spain, there seem to be four types of consumers, hierarchically

In the preceding discussion, we have shown that the four patterns of consumption differ in size according to the symbolic space researched and the country. We can infer that a better understanding of the omnivore phenomenon and its association with the highest social status requires the use of two research strategies. First, an analysis of the consumption of a given symbolic space in different countries. Second, a study of the consumption of the full symbolic spaces for a given country. Additionally, to understand the social development of the omnivore phenomenon (i.e., how omnivore consumption has replaced univore-snob consumption as a marker of the highest social standing), we must research the same symbolic space and the same country over time. 6.2. Implications for marketing strategies The varied symbolic meanings of Spaniards’ performing arts consumption will help marketers to design a proper marketing strategy. On the one hand, the class of consumers labeled univore-snob tries to set themselves apart from the middle and lower social classes (the distinction effect we found). This desire to differentiate themselves means that every initiative targeting this group for the purpose of promoting the popular performing arts will be prone to failure, as reported by Gainer (1995). Fortunately, the other three classes of consumers will respond positively to certain marketing strategies. 6.3. Nonlinear pricing strategy: pure highbrow performing arts subscriptions As we have already seen, omnivore and snob consumers belong to the highest social classes and have the highest rate of attendance to highbrow performances (see Table 4). Therefore, we can expect that they will not only have the highest rate of consuming highbrow performances but also pay the highest reservation price for every additional performance. Moreover, as they are from the highest social classes, these consumers will have the right characteristics for buying a subscription series. Subscriptions allow us to segment the market according to the rate of consumption and marginal value of attending additional performances.

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6.4. Nonlinear pricing strategy: pure popular performing arts subscriptions Popular and omnivore consumers are the targeted group of this strategy: omnivore consumers because they mark their social standing by consuming everything (the omnivorous effect), including popular performances, at rates even higher than popular consumers, and the latter because they are more interested in popular performances (the boundary-effacement effect) due to their age. Consequently, these two groups of consumers will have the highest rate of consumption and reservation price for every additional performance (see Table 4) and will create a stable demand and a target group for subscriptions. Because of their age, however, popular consumers have a more spontaneous behavior than omnivores do, suggesting that a minisubscription series should also be offered. 6.5. Price bundling strategy: mixed subscriptions Given the symbolic properties of snobs, these consumers will not respond positively to an offer of popular performances. However, because of their age and social class, popular consumers will probably be relatively unaware of highbrow performances (although not opposed to them) and, therefore, will pay comparatively low reservation prices. The strategy of mixed subscriptions consists in bundling a reduced number of highbrow performances with a set of popular performances (here, we are fostering the omnivorous effect). The key factor to success is to form a mixed subscription with a price lower than that of popular consumers’ reservation price, which is, nevertheless, not attractive to omnivore consumers. 6.6. Single ticket strategy: massive marketing Finally, although sporadic consumers have a lower rate of attendance, they are important to mass performing arts consumption because they account for up to 70% of potential goers. They are especially important for marketers of light opera, theatre, folk, and other popular performances (the boundary-effacement effect). Sporadic consumers have a low rate of consumption, although their reservation price for these few tickets is higher than the ticket’s mean price in a subscription.

Acknowledgement The authors express their appreciation to two anonymous reviewers, the editors of this special issue, Rube´n Gutie´rrez del Castillo (SGAE’s Research Department and Assistance) and the attendees to the 30th International Research Seminar in Marketing (La Londe les Maures, France, June 11–13, 2003) for their kind and helpful

comments on a previous version. This research was funded by Grant Number BEC2003-04462 of the Spanish Ministry of Science and Technology, Technical Department of the Humanities and Social Sciences.

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Journal of Business Research 58 (2005) 1456 – 1463

Researching cultural metaphors in action: metaphors of computing technology in contemporary U.S. life Rita M. Denny*, Patricia L. Sunderland Practica Group, LLC, 207 E. Ohio, #370, Chicago, IL 60611, USA Received August 2003; received in revised form October 2003; accepted February 2004

Abstract This article presents the utility of cultural metaphor as an analytic tool and theoretical construct in consumer research. Specifically, we extend current applications within consumer research by situating metaphor as a linguistic and cultural practice in consumers’ socially embedded talk and actions (vs. text and self-report) and by foregrounding an anthropological, cultural analytic framework. Based on ethnographic research, we take as our prime example the ways that computer and internet metaphors have had an impact on U.S. consumer meanings and actions in offices and other realms of daily life. We suggest that researching cultural metaphors in situ, in the everyday, naturally occurring context of consumer lives, has the potential to demonstrate highly relevant categories of meaning among consumers and thus represents an important strategy for market research. D 2004 Elsevier Inc. All rights reserved. Keywords: Metaphor; Culture; Ethnography; Computing technology; Computers

1. What is an office? In late 1999, we were asked to speak to a Fortune 100 company about the impact of technology on the ways people organized information in offices, at work or home. As the anthropological voice among the handful of assembled business experts, our assignment was to address bthe human need to organize.Q This company, in the business of paper, file folders (bdividersQ) and labels, was seeing the effects of electronic communication and storage. If the office becomes paperless, then what? Drawing on our experiences as ethnographic researchers in consumer environments, our talk covered the multidimensional aspects of organization—the aesthetic, the functional and the symbolic. We emphasized the fact that organization occurs in a living space—whether office or home. As a living space, an office would be varyingly * Corresponding author. 5538 S. Kenwood, Chicago, IL 60637, USA. Tel.: +1 773 752 2665. E-mail addresses: [email protected] (R.M. Denny)8 [email protected] (P.L. Sunderland). 0148-2963/$ - see front matter D 2004 Elsevier Inc. All rights reserved. doi:10.1016/j.jbusres.2003.10.015

landscaped by symbols of the self (Belk and Watson, 1998) (Figs. 1 and 2). The underlying question the talk raised was dWhat constitutes an office?T. Across much of the last century, the answer would have foregrounded a space that included a desk with drawers, a chair, paper, pens, maybe pencils, a phone, file cabinets or other form of paper storage, a wastebasket; in the last few decades, with the addition of the desktop computer. But today, we argued, the office is the computer—wherever it may sit (on the kitchen counter, park bench, in a backpack, hotel room, airplane, Starbuck’s counter—wherever). We suggested to the company that it was no longer in the bdividerQ business, rather it was in the bcomputerQ business because people looked to the computer not only for functionality but as a model for organization. In short, the computer had become the generative or source metaphor, and in order to develop organizer ideas that would resonate with consumers, one would need to start with the computer as the metaphoric model. It was not clear that the Fortune 100 company found our suggestion to mine the implications of the computing

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Fig. 1. A desktop computer in a home office, adorned with Post-its (in some ways akin to refrigerator art) on a desk. The office as living space and life space; surrounding photos speak of family.

metaphor as promising as we did. But after that time, we observed the generative power of computer and internet metaphors in other quarters. BellSouth, for example, recast their Yellow Pages as a virtual store (Linnett, 2000). In the words of the chief creative officer at WestWayne, the agency responsible for the new Yellow Pages advertising campaign, bWe are calling it dthe big yellow databaseTQ and bThe final tagline that we came up with is dThe original search engine.T It’s a neat way to update the book with an deT word.Q Similarly, a Toronto TV station adopted a Web-like format in its news broadcasting (McClain, 1999). Today, virtually all U.S. news programs have an dinternetT look. Jaron Lanier, a chief architect of internet Two, noted that reality TV in fact is more like a Web page than a television show (Schrage, 2000). This recasting of traditional book or broadcast media in computer terms is just the sort of

Fig. 2. Laptop computer, opened windows on the screen, surrounded by dwindowsT of family, friends, personal life.

Fig. 3. Computer as metaphor and model: bThe original search engineQ.

metaphor-mining we had suggested that our client should be thinking about for the paper-and-desk office (Figs. 3 and 4).

2. Metaphoric constructions and consumer behavior In recent years, the metaphor concept has gained attention in academic as well as applied marketing and consumer research circles. A prime catalyst for this attention can be located in the work of Zaltman and Coulter (1995), Zaltman (1997) and Coulter and Zaltman (2000). Their ZMET technique, a multi-step analytic procedure which uncovers consumers’ metaphors through guided conversation, storytelling, collage building, explorations of visual and other sensory images, leads to the extraction of consumers’ conscious and unconscious (bhidden or deepQ) mental models and reasoning processes (see Zaltman and Coulter, 1995 for a more detailed description of the technique). The concept of metaphor has been utilized by Hirschman (2002) who, in a cultural reading of dog breeds, illustrated forms of metaphoric transference and by Belk (1996), who has analyzed metaphorical tropes for pets as well as metaphors of the body with implications for organ donation practices (Belk, 1990). McQuarrie and Mick (1996) consider metaphor in an analysis of literary tropes in advertising, Hanby (1999) considers the metaphoric constructions of brands, and Dodd (2002) uses metaphor as a tool for constructing a cultural model of entrepreneur-

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Fig. 4. Toronto station news format mimicking a Web page.

ship in the United States. Holt (1995) has also used the notion of metaphor in the development of a typology of consumption practices. (See also Piller, 1999 who analyses metaphoric meanings of U.S. car brands.) In our own ethnographic consumer research practice, we have frequently drawn on the concept of metaphor as one of our analytic and strategic tools. For instance, in 1999, we conducted ethnographic research on the symbolic meanings of drugs and drug practices among American Tweens, ages 10 to 13 (Sunderland and Denny, 2003). Implicit in the Tweens’ talk were five distinct categories of drugs: scary (including LSD, Special K, Ectasy), death (heroin), addiction (cocaine), stupidity (inhalants) and the normative, unmarked category of drugs, which referenced alcohol, cigarettes and marijuana. While marijuana was articulated in terms of plant and organic substance metaphors, other categories were surrounded and permeated with chemical metaphors, framed as much more direct and harmful to bodily function. Inhalants, for example, as prototypical chemicals, bcut off oxygen to the brain.Q But marijuana, as a plant, became dangerous only when blacedQ or combined with a drug from another category. In the unmarked drug category, the effects of pollution on physical appearance, not chemical damage per se, was the worry (e.g., yellow teeth and bad breath from cigarette smoke). Among our recommendations to the client, responsible for creating anti-drug use advertising, we pointed to the need to play on the pollution and chemical metaphors that resonate so powerfully for Tweens. We also pointed to ways the natural (safe, organic, plant) metaphors associated with marijuana posed a challenge in dissuading Tweens of its use. The use of metaphor as a theoretical construct in consumer research (Dodd, 2002; Coulter and Zaltman, 2000; Hanby, 1999; McQuarrie and Mick, 1996; Piller, 1999; Stern, 1989; Zaltman and Coulter, 1995) has relied primarily on cognitive linguistic, psycholinguistic and literary views (Cameron and Low, 1999; Gibbs, 1994;

Ko¨vecses, 2002; Lakoff, 1987; Lakoff and Johnson, 1980; Ortony, 1993), which position metaphor as an organizing principle used by individuals to construct conceptual understandings of the world. Our approach diverges from most others in the consumer research arena by our interest and focus on the cultural (or dsupraindividualT) realm over that of the individual and individual thought processes (but see Hirschman, 2002; Belk, 1990, 1996). Anthropologically trained, we do not stress the understanding of individual thought processes—or the mechanisms of the mind, conscious or unconscious— but rather the cultural level meanings and metaphors that animate consumer lives (Fernandez, 1991; Martin, 1987, 1994). Our work also extends the work of others in that we conduct the research ethnographically, stressing the importance of socially embedded and contextualized consumer action. Other consumer research on metaphor has largely concentrated on consumers’ self-reports, representations and/or texts of various kinds (written, images, advertisements, etc.). We research consumer behavior in situ, and analyze metaphors as they are instantiated in social action through behavior, speech, organization, artifacts, and thoughts. Our research often includes texts (especially photos, images, and video), as well as interview, introspective, and self-report data, but we consistently relate this to real action in real social worlds. Thus, we are primarily interested in understanding the way consumers live out culturally relevant metaphors in their everyday lives, believing that this arena has the potential to demonstrate highly salient meanings for consumers as well as realms of opportunity for marketers. When we search to understand the metaphors that organize behavior (or vice versa), we search for the cultural level meanings—the metaphoric meanings that resonate for consumers and marketers—because these meanings are important threads and patterns in the cultural fabric that is the context for product and brand development and consumption.

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During the last decade, there has been much debate on the privileged position of metaphor in the construction of thought, in which the positions of cognitive linguists and more culturally grounded theorists were in opposition (see Fernandez, 1991; Quinn, 1991; Alverson, 1991). More recently, the role of culture in mediating metaphoric constructions has been increasingly recognized by cognitive psychology (see Gibbs and Steen, 1999). And though the debate continues as to whether metaphors constitute or reflect cultural models (Ko¨vecses, 1999), it seems clear that uses of metaphor in everyday talk are contextualized by cultural realities, whether by discursive conventions and ideology (Eubanks, 1999), historical time (Ohnuki-Tierney, 1991) or socio-cultural experiences (Gibbs, 1999; Emanatian, 1999). Our emphasis on metaphors as they are articulated in conversation and social action assumes language is a social resource and is itself a culturally defined and specified practice (Schieffelin, 1990; Silverstein, 1976). In the end, we take as a premise that language not only reflects cognitive processes but, in its use, is a creative practice of culture, in which artifacts and environment are catalysts for new expression and cultural meanings. Metaphor as a trope of everyday language thus becomes a prism through which to observe and refract consumer behavior. To further illustrate, we return to the example of computing technology.

3. Computing as a cultural metaphor Early design of desktop computers pointed to the potency of paper, filing cabinet, and desk metaphors. Desks and what surrounded them were the source metaphor for computers. ! Starting with Xerox PARC and mainstreamed by Apple and Microsoft, was the bdesktop,Q a two-dimensional space on which file folders (bdividersQ) neatly sat. We could name them and put them wherever we liked. There were even wastebaskets (now brecycle binsQ) and Mac trash included visual and sound effects.

Fig. 5. Mimicking the computer’s desktop: Folders on the floor, opened and closed throughout the day, as needed, then put into the backpack.

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Fig. 6. Actual desktop: information less immediately needed. It might not be touched day-to-day.

! Monitors were designed on a paper icon so that when we opened a word processing application it was as though we were writing a letter. ! Keyboards were like typewriters. But with computers came other organizational opportunities. For instance: ! Endless embedding of file folders within file folders. ! Embedding could be done with impunity because we had search functions for finding things really quickly. ! Visual icons for file types; sorting of bfoldersQ by name listing, icon, or date. ! We could use multiple sorting possibilities. We got instant sorting capability that mixed and matched in any number of ways so that eventually we could spin incoming e-mail by date, author, recipient, etc. With the proliferation of personal computers on desks by the 1990s, the source and target of the desk-computer metaphor could become reversed: it became possible to mimic our computers mimicking our desks. In this scenario, real desktops could be piled high with folders because of an increasing dependence on a visual cue for what is there (as our computer desktops gave us). In 2001, we observed a tech-savvy individual doing just this. On coming into the office he set up a model of his computer ddesktopT on the floor by his desk: File folders were laid out from his backpack, opened up when in use, then dclosedT when tasks were completed or the day was done. His actual desktop was piled with folders of less temporal immediacy (Figs. 5–7). The way of doing things in non-computer realms had begun to metaphorically mimic what we did with computers. Hence, retrieval systems in the non-computer world could suffer in comparison to what had been learned was possible via the computer’s desktop. As one of our research respondents, Travis, commented, bTechnology makes information management easier. You can save virtually forever. You have multiple search tools and search through the hard drive real quick, unlike file cabinets where everything is just kind of stacked there.Q For a client in the filing and bdividerQ

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Fig. 7. Desktop computer screen: Visually parsed with file folders and pictures of son, which once might have been framed and displayed on the desk.

business, it was time to consider these other, metaphorically inspired ways of doing things. What could be invented for floor-based filing systems that mimicked the computer desktop filing systems? What could be invented as computer-inspired ways of embedding, embedding, and embedding within folders? What could be communicated about the specific retrieval properties of paper products, akin to what one does with computers? These are the kinds of questions that we believed the company’s strategists needed to consider as they re-thought their business in 1999.

4. Computing technology: from humanly negative to personally positive In the United States, a metaphoric migration occurred with the proliferation of personal computing technology— from conceptualizing computing technology as humanly destructive to seeing it as personally empowering. Traditionally in the U.S., there reigned an ambivalence vis-a`-vis technology. Technology was seen as a force that drove society forward but, contained within this power to alter the nature of social life, was an equally powerful anti-human force—the one that made technology dcoldT—something that deprived the world of humanity, emotions and feeling. Earlier on in the advent of personal computers and particularly the internet in the U.S., research respondents would recite urban legends (as did the mass media) of people who would stay at their computers and online, no longer caring about their family or friends—for instance, mothers who spent so much time online that the children were neglected and went unfed. But, by the beginning of 2000, when we interviewed consumers we heard about computers and technology as bgood,Q bfriends,Q bhelpers.Q Metaphors of friendship and assistance had become the order of the day. At the base of the positive embrace of computing technology lay a change in the conceptualization of its power. People moved from understanding the technology of computers as a social force (outside of an individual’s power) to understanding it, and

experiencing it, primarily in personal (part of a person’s power) terms. On the cover of a 1972 book, The Computer: How it’s Changing our Lives, we find a man alone in a room with his hands reaching toward the controls of one big (the size of a room) computer (Snyder, 1972). The image, and its attendant associations, is reminiscent of HAL of 2001, A Space Odyssey, produced in about the same cultural time (1968). The (mainframe) computer of these times was crude and inscrutable, something that took over human life (Fig. 8). In the more recent conception, computing technology has moved from being conceived as a large social force outside of us to power on an individual scale, virtually inside of us. We now observe its articulation not as something that masters us, but rather as something that makes us masters— we help ourselves, and even help others, with our own personal computing technology. Thus, an additional array of elements has been foregrounded in talk about computers, as seen below: ! Customizing a homepage, showing specific stock quotes and news means, bI manage the flow of information. I get what I need.Q ! Having a hand-held computer can make me feel: bI’m supremely in control of my destiny.Q ! Using the searchable OED means, bI manipulate the information. I get what I want.Q ! bVia the internet I can find the information myself. I can communicate directly with people all over the world. I can find the medical information I need to assure I get— or stay—well. I can help others with their problems.Q This more celebratory sense of computers and the internet, a positive evaluation fostered by personal use of these personal machines is built on—and builds—the metaphor of computer-as-personal-power. Computer technology does help people in the world today. For the

Fig. 8. Early 1970s book cover image—mainframe computer of that time as inscrutable, and with the potential to take over human life.

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everyday person, computing technology really can expand memory (e.g., a hand-held device takes bthe fear of forgetting out of lifeQ) and it can facilitate communication; with e-mail, respondents maintain that they have increased their contact with others across space and time. It would also seem that the embrace of the technology and its associated metaphors has upped performance antes. Expectations for products, our selves, our worlds have been increased. Gleick (1999) has argued that with computers speed has become the assumed standard for calibrating anything from intelligence to productivity. Faster is better. This standardization of speed paralleled the development of microprocessors—computers offered an ever finer ability to parse time. And so, as a society, we are now in the rather absurd position of finding relevance in chunks of time that are both imperceptible and measurable, e.g., the milliseconds by which races are won, or the seconds by which appliances save time. We would argue that it is not just the computer’s speed that has infiltrated notions of work, productivity and intelligence and that has put us in a perpetual state of immediacy. It is the surfing, the e-mailing, the embedding, the instant messaging and chatting, the finding, the inserting, the linking that give the cues for comprehending and interpreting what is around us, and for enacting and reenacting that reality. Our tropes for how we communicate with one another have also been influenced—we now have online and offline conversations. In our encounters with people, are we becoming more like our e-mail—brief, casual, punctuated and immediate? Are we surfing places much as we do websites? It is not just the idea of speed; it is the native model of what the computer does and the conventions derived from their use of them that makes a computer a potent metaphor and a native model for productivity. A tech-savvy respondent in his 20s tells us that he gets impatient and irritated at red lights not because the lights are slow, but because the lights are not bsmartQ— they should be able to dreadT traffic needs—and therefore be dgreenT when there is no traffic. While a bfastQ processing computer is a bgoodQ computer, a bfastQ computer is also one that allows us to carry out multiple processes, to simultaneously open up multiple windows, to do things like quadruple boot.

5. Conclusion: computing metaphors are reconfiguring the sense of self and society By forging their way into our notions of personal power, computing metaphors are affecting our cultural sense of what it means to be a person. These metaphors have also affected our sense of how our minds work. If people now say that something was not saved on their bhard drive,Q they might not literally mean in their computer, but rather in their own memories. One respondent told us that his wife has accused him of being a bbinary thinker,Q using a computer-

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inspired metaphor to express her exasperation over what, in other times, she might have described as his inability to think in shades of gray or his dblack and whiteT thinking. Since today the internet is increasingly synonymous with the computer, it has become an important source for contemporary mental processing metaphors. bBandwidthQ is now part of the figurative vocabulary, as in bdo you have the bandwidth for that?Q roughly glossed as scope and ability. And if once we bwrapped our heads around an idea,Q we now bdownloadQ and blinkQ to it, as we download and link to sites on the internet. The use of these tropes illustrate, again, the generative or source status of the computer metaphor—which now foregrounds organization, powers of retrieval and productivity of the mind versus more creative, figurative dimensions (even if in programming and artificial intelligence circles, articulations of computer processes have gone far beyond mere retrieval and calculation, see Turkle, 1995). Notably, computing metaphors have also entered professional models of how the brain and mind works (Gleitman et al., 1999; Turkle, 1997). In the well-known work of Turkle (1984, 1995), we also find the argument that people’s sense of self has been affected in light of computer familiarity and use. For instance, she maintains that people have a Windows-influenced sense of themselves as both multiply refracted and flexible (Turkle, 1995). We would add that the current portability of the computer and related technological devices must also be considered. Beyond the sense of self, the portability of contemporary technological devices has allowed us to reconfigure our sense of social space and place. Harvey (1990) has discussed the concept of btime–space compressionQ that has arisen in light of interconnected capital, transportation and communication technologies of the modern and postmodern worlds. As he observed, many have noted—with varying degrees of alarm—the seeming collapse of social space and time in light of these developments. We have observed that portable devices and wireless communications have given people the ability to collapse temporal and physical space between home and office, private and public, work and play. The kitchen counter, park bench, hotel room, airplane and the spot at Starbuck’s do become workspaces when one pulls out the laptop. Cell phones, call forwarding, internet access and dial-up networking allow for the dislocation of white-collar work from set work places. Play at work is also normative. Respondents take personal phone calls on their cell or separate lines, write personal e-mails or privately go to websites of their choice, buy and sell on favorite internet sites. Instant messaging with friends, watching sports events (streaming or with portable TVs) or listening to music with headphones—from radio over the computer or with portable CD players—is also common. Because the spatial divide can be collapsed, and one can work where once one only played or play where once one worked, it does sometimes seem that traditional boundaries between cultural domains such as work and home have

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collapsed. Technology provides the potential for increasing the integration between these domains functionally (Venkatesh et al., 2001) and subsequently, conceptually (see Nippert-Eng, 1996). But, just as Harvey (1990, p. 232) noted that spatial barriers are only overcome through the production of other spaces (e.g., air travel’s reduction of spatial distance is achieved via airport dspacesT) and that even as spatial distance has become less relevant for capital, the search for the most advantageous geographic location remains highly relevant, we would suggest that the seeming elision of boundaries between cultural categories is structured. With Windows as the culturally articulated metaphor, the cultural categories of work and play that were once defined by particular senses of place are maintained in computer windows. Truly interesting are the ways in which the very same technologies that afford the space–time collapse between cultural spheres are simultaneously the means by which their functional and symbolic separation is assured. People’s actions maintain the separation of cultural categories. Cell phones are taken to work for making and receiving personal calls. People have separate e-mail accounts—one for personal, one for business. The very wired have several—the junk mail account, the friends and family account, the chat account, plus the business accounts. But even the not-so-wired with one account know which messages are personal and which are business. People play games, pull up stock quotes, peruse banking sites, download music and watch sports events during work hours, but these are in different windows—a click away from the windows of work. In essence, what we see people doing is not merging, but rather holding up the longstanding cultural boundaries between work and play, private and public, home and office, but doing so with the aid of their technological devices. Taking us full circle, the computer and related technological devices really have become our office dividers. Today, the well-established cultural categories are kaleidoscopic, finely interwoven and parsed in windows. The switch of attention between windows is mediated only by the perceived reaction time of our hand on the mouse, the speed of the computer’s processor, the time it takes to answer a ringing phone. Cultural categories and metaphors have historical roots. The physical separations necessitated by early industrial processes had a huge hand in creating the current symbolic divisions between public and private, work and play. Metaphors, as we have noted, are lenses which refract current cultural beliefs and values. They not only provide a prism through which to understand consumption behavior but, in their use/instantiations by individuals, are creative of ways of seeing. Metaphors change. For marketers, metaphorical representations must be fathomed in order to persuade, speak or resonate with target audiences (see Belk, 1990 in reference to organ donation). Culture and metaphors are lived or practiced, observable in the details of daily life—as new technologies are dconsumedT or inte-

grated into daily life, we can expect new refractions (see Venkatesh, 1998; Venkatesh et al., 2001). Today, Windows give us the current model for a kaleidoscopic lens, in which multi-tasking and a recalibration of linear time are currently framed. We might expect, tomorrow, that what it means to work or to play or what counts as private and public will fundamentally change as post-Windows technology and metaphors offer us a new framework for interpreting the world around us. We do not know what will happen when wireless internet screens are everywhere, everyday computers have the power to simultaneously process in multitudes of windows, broadband allows us to become a seamless part of the show or wireless networks allow us to interface seamlessly between phone, computer, PDAs (all technologies that exist today, but that are not yet fully integrated into everyday life). But we suggest that drawing out the cultural metaphors by turning an acute ear and sensitive eye to how consumers talk and act in everyday life will provide a significant frame for marketers’ attention be it theoretical or practical.

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R.M. Denny, P.L. Sunderland / Journal of Business Research 58 (2005) 1456–1463 Harvey D. The condition of postmodernity. Cambridge (MA)7 Blackwell; 1990. Hirschman EC. Dogs as metaphors: meaning transfer in a complex product set. Semiotica 2002;139(1–4):125 – 59. Holt DB. How consumers consume: a typology of consumption practices. J Consum Res 1995;22:1 – 16. Kfvecses Z. Metaphor: does it constitute or reflect cultural models? In: Gibbs RW, Steen G, editors. Metaphor in cognitive linguistics. Amsterdam7 John Benjamin; 1999. p. 167 – 88. Kfvecses Z. Metaphor: a practical introduction. Oxford7 Oxford Univ. Press; 2002. Lakoff G. Women, fire, and dangerous things: what categories reveal about the mind. Chicago7 Chicago Univ. Press; 1987. Lakoff G, Johnson M. Metaphors we live by. Chicago7 University of Chicago Press; 1980. Linnett R. BellSouth Yellow Pages recast as virtual store. Advertising Age 2000;1: [June 5]. Martin E. Tracking immunity in American culture—from the days of polio to the age of AIDS. Boston7 Beacon Press; 1994. Martin E. The woman in the body: a cultural analysis of reproduction. Boston7 Beacon Press; 1987. McClain D. Toronto TV station adopts web-page format. N Y Times; 1999. C8 [December 27]. McQuarrie EF, Mick DG. Figures of rhetoric in advertising research. J Consum Res 1996;22:424 – 38. Nippert-Eng C. Home and work. Chicago7 University of Chicago Press; 1996. Ohnuki-Tierney E. Embedding and transforming polytrope: the monkey as self in Japanese culture. In: Fernandez JW, editor. Beyond metaphor: the theory of tropes in anthropology. Stanford7 Stanford Univ. Press; 1991. p. 159 – 89. Ortony A, editor. Metaphor and thought, 2nd ed. Cambridge7 Cambridge Univ. Press; 1993. Piller I. Extended metaphor in automobile fan discourse. Poetics Today 1999;20(3):483 – 98.

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Quinn N. The cultural basis of metaphor. In: Fernandez JW, editor. Beyond metaphor: the theory of tropes in anthropology. Stanford7 Stanford Univ. Press; 1991. p. 56 – 93. Schieffelin BB. The give and take of everyday life: language socialization among Kaluli children. New York7 Cambridge Univ. Press; 1990. Schrage M. Jaron Lanier (Interview). Adweek 2000; 41(40): IQ44, Eastern Edition. Silverstein M. Shifters, linguistic categories and cultural description. In: Basso K, Selby H, editors. Meaning in anthropology. Albuquerque7 Univ. of New Mexico Press; 1976. p. 11 – 55. Sunderland PL, Denny R. Psychology vs anthropology: where is culture in marketplace ethnography? In: Malefyt TD, Moeran B, editors. Advertising cultures. London7 Berg; 2003. p. 187 – 202. Snyder GS. The computer: how it’s changing our lives. Washington (DC)7 U.S. News & World Report; 1972. Stern B. Literary criticism and consumer research: overview and illustrative analysis. J Consum Res 1989;16:322 – 34. Turkle S. Computational technologies and images of the self. Soc Res 1997;64:1093 – 111. Turkle S. Life on the screen: identity in the age of the internet. New York7 Simon & Schuster; 1995. Turkle S. The second self: computers and the human spirit. New York7 Simon & Schuster; 1984. Venkatesh A, Stolzoff N, Shih E, Mazumdar S. The home of the future: an ethnographic study of new information technologies in the home. Adv Consum Res 2001;28:188 – 97. Venkatesh A. Cyberculture: consumers and cybermarketscapes. In: Sherry JF, editor. Servicescapes. Chicago7 NTC/Contemporary Publishing; 1998. p. 343 – 76. Zaltman G. Rethinking market research: putting people back in. J Mark Res 1997;34:424 – 37. Zaltman G, Coulter RH. Seeing the voice of the customer: metaphor-based advertising research. J Advert Res 1995;35(4):35 – 51.

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Editorial

Marketing communications and consumer behavior: Introduction to the special issue from the 2005 La Londe seminar

This special issue of the Journal of Business Research includes a selection of papers presented at the 32nd International Research Seminar in Marketing organized by the Aix Graduate School of Management (I.A.E. Aix-en-Provence), a part of the University Paul Cézanne in Aix-Marseilles (France). This seminar, now better known as the “La Londe Seminar”, is devoted to Marketing Communications and Consumer Behavior on a biennial basis. The La Londe seminar encourages intense discussions of specialized topics in consumer behavior and communications among a relatively small group of interested scholars in a relaxed and informal atmosphere. In order to facilitate fruitful exchanges, there are only two tracks, and each presentation lasts 30 min followed by 15 min discussion. Those who have been to La Londe also know the exchange value of the coffee breaks on the terrace overlooking the Mediterranean Sea and the Porquerolle islands. The La Londe seminar is truly internationally oriented. It is always chaired by both a European chair and an American chair. Luk Warlop (Katolieke Universiteit Leuven) and Curtis P. Haugtvedt (Ohio State University) chaired the 2005 edition. Participants came from all over the world, with the five continents and 16 nationalities represented. A total of 70 manuscripts were submitted and double-blind reviewed by both members of the permanent scientific committee of the seminar and ad hoc reviewers carefully selected by the co-chairmen and the coordinator. Thirty papers were presented at the conference. In addition, the thought-provoking keynote address by Robert A. Peterson from The University of Texas at Austin stimulated reflections and discussions concerning the process of researching fruitfully in consumer behavior domains. Bob Peterson shared his rich and outstanding research experience in a talk entitled “Lessons Learned in Later Life”. The eight papers of the special issue follow the dual theme of consumer behavior and marketing communications, albeit with great diversity. The three first papers address advertising-related issues. Elisabeth Cowley (“Processing exaggerated advertising claims”) demonstrates that consumers' brand evaluations are inflated after exposure to exaggerated claims even if they recognize that the claims are not very credible. Exaggerated claims seem to be accepted before being discredited, thus affecting memory. Jae Min Jung and James J. Kellaris 0148-2963/$ - see front matter © 2006 Elsevier Inc. All rights reserved. doi:10.1016/j.jbusres.2006.01.010

(“Responsiveness to authority appeals among young French and American consumers”) examine the authority principle cross-culturally in an advertising context and study how different levels of authority influence consumer attitudes and purchase intentions. They also investigate moderating effects of national culture, source credibility, and individuals' orientations to power distance. Results show a reverse authority effect across two cultures and that both perceptions of spokesperson credibility and power distance positively influence attitudes and purchase intentions. In the third article, Ingrid Poncin, Rik Pieters and Michele Ambaye (“Cross-advertisement affectivity: the influence of similarity between commercials and processing modes of consumers on advertising processing”) run an experiment to examine the issue of cross-advertisement affectivity effects. They find substantial context effects of the ad sequence in the affective reactions elicited by commercials presented in the same pod. They also demonstrate the importance of the similarity between commercials in consumer judgments. The three following articles of this special issue deal with consumer purchasing behavior. Francine V. Garlin and Katherine Owen (“Setting the tone with tune: a meta-analytic review of the effects of background music in retail settings”) study more than 150 papers dealing with the effects on consumer behavior of background music in service settings. They demonstrate through a meta-analysis of research results that appropriate background music induces positive effects on affective, attitudinal, temporal and behavioral variables. In their contribution, Joann Peck and Terry L. Childers (“If I touch it I have to have it: individual and environmental influences on impulse purchasing”) examine individual differences in touch and how these affect impulsive-buying behavior. They designed a study to investigate the link between impulse purchasing and both an environmental encouragement to touch (a sign in a supermarket) and an individual preference for autotelic touch. They find that individuals higher in autotelic need for touch (NFT) purchase more impulsively than their lower autotelic NFT counterparts. In addition, the environmental salience of touch information increases impulse-purchasing behavior. Finally, Bill Jolley, Richard Mizerski and Doina Olaru (“The effects of habit and satisfaction on player retention for online

Editorial

gambling”) experimentally test the effects of past behavior (habit) against customer satisfaction on consumer retention. They developed an online casino and a very nice online gambling experiment to test the drivers of retention. They find that playing habits, not customer satisfaction, have a strong effect on a range of responses tied to retention and add a strong contribution to the literature proving the very limited impact of satisfaction on consumer retention. The two last papers of the special issue address central consumer behavior constructs with a more psychological orientation. Todd A. Mooradian and K. Scott Swan (“Personality and Culture: the case of national extraversion and word-ofmouth”) demonstrate the general value of the personality-andculture paradigm. They hypothesize that cultures characterized by higher levels of extraversion will rely on word-of-mouth for product information more than cultures with lower extraversion. They test this hypothesis using a very impressive database including 15,000 cases from subjects in twelve nations on five continents (for the WOM data) and major cross-cultural databases for the extraversion data and find empirical support for the hypothesis. The final paper is written by Frank R. Kardes, Steven S. Posavac, David Silvera, Maria L. Cronley, David M. Sanbonmatsu, Susan Schertzer, Felicia Miller, Paul M. Herr and Murali Chandrashekaran (“Debiasing Omission Neglect”). Omission neglect (insensitivity to missing information as when products are described by a small amount of information) occurs when consumers form inappropriately extreme evaluations on the basis of weak evidence. This study investigates, through two experiments, the effectiveness of new procedures for reducing omission neglect: asking consumers to consider their criteria for judgment before receiving product information (Experiment 1), and asking consumers to rate presented and missing product attributes before providing overall product evaluations (Experiment 2). The research shows that the proposed procedures are effective in debiasing consumers' tendency for omission neglect. As co-chairs and coordinator of this conference and as coeditors of this special issue, we greatly appreciate the contributions of the international scientific committee of the La Londe seminar which year after year guarantees the quality of the contributions. This permanent scientific committee is composed of the following very distinguished scholars: Gerald Albaum (University of New Mexico), Rajeev Batra (University of Michigan at Ann Arbor), Russell W. Belk (University of

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Utah), Christian Derbaix (FUCAM, Mons), Yves Evrard (HEC, Paris), Wayne D. Hoyer (University of Texas at Austin), Alain Jolibert (University of Grenoble), Lynn R. Kahle (University of Oregon), Michel Laroche (Concordia University), Gilles Laurent (HEC, Paris), Siew Meng Leong (National University of Singapore), Sidney J. Levy (University of Arizona), Richard J. Lutz (University of Florida), Claude R. Martin (University of Michigan at Ann Arbor), Hans Mühlbacher (University of Innsbruck), Robert A. Peterson (University of Texas at Austin), Rik Pieters (Tilburg University), Christian Pinson (INSEAD), Bernard Pras (University of Paris–Dauphine and ESSEC), Don E. Schultz (Northwestern University), Jan-Benedict Steenkamp (Tilburg University), Alain Strazzieri (Aix-Marseille University), W. Fred van Raaij (Tilburg University), Arch G. Woodside (Boston College) and Judy Zaichkowsky (Simon Fraser University). We thank all the other members of the review panel which have done a great reviewing job. Finally, we express our gratefulness to Arch Woodside, editor in chief of the Journal of Business Research, for instigating and approving this special issue. We now look forward to the 2007 seminar that will be cochaired by Joseph Sirgy (Virginia Polytechnic Institute and State University) and Søren Askegaard (University of Southern Denmark in Odense). The 2007 La Londe seminar will take place June 5–8, 2007 in La Londe les Maures, this stimulating and beautiful place on the French Mediterranean coast. Curtis P. Haugtvedt Ohio State University, United States Dwight R. Merunka IAE Aix-en-Provence, Paul Cézanne University of Aix-Marseille, Clos Guiot, 13540 Puyricard, France E-mail address: [email protected] Corresponding author. Tel.: +33 442 280 808; fax: +33 442 280 800. Dwight R. Merunka Euromed Marseille, School of Management, France Luk Warlop Katolieke Universiteit Leuven, Belgium 1 January 2006

Journal of Business Research 59 (2006) 728 – 734

Processing exaggerated advertising claims Elizabeth Cowley ⁎ University of Sydney, Economics and Business Building H69, Sydney NSW 2006, Australia Received 1 April 2005; received in revised form 1 November 2005; accepted 1 December 2005

Abstract Government policymakers allow advertisers to use wildly exaggerated, fanciful or vague claims for a product or service because they believe that nobody could possibly treat the claims seriously or be misled by them. The results demonstrate that although consumers are able to identify exaggerated claims as less credible than factual claims, their brand evaluations are inflated after exposure to exaggerated claims. The explanation is that during the process of comprehension, claims are accepted before being discredited. The temporary acceptance of the claim affects memory, even after the claim is understood as an exaggeration. © 2006 Elsevier Inc. All rights reserved. Keywords: Advertising; Brand evaluation; False claims

1. Introduction Is belief independent of comprehension? Descartes asserted that comprehension precedes, and is independent of, belief. As humans come into contact with claims or opinions, they comprehend them automatically, and then decide whether to accept or reject the information (Gilbert, 1991; Gilbert et al., 1993). Spinoza, on the other hand, believed that comprehending and accepting were part of the same process. “According to Spinoza, the act of understanding is the act of believing. As such, people are incapable of withholding their acceptance of what they understand. They may indeed change their minds after accepting the assertions they comprehend, but they cannot stop their minds from being changed by the contact with those assertions” (Gilbert et al., 1993, p. 222). Why does the disagreement matter in marketing? Selfregulatory industry groups, such as the ASA in the United Kingdom and government regulatory bodies, such as the FTC in the United States and the ACCC in Australia, have created rules using Cartesian logic. Government policymakers allow advertisers to use puffery, defined as wildly exaggerated, fanciful or vague claims for a product or service, because they believe that

⁎ Tel.: +61 2 9351 6433; fax: + 61 2 9351 6732. E-mail address: [email protected]. 0148-2963/$ - see front matter © 2006 Elsevier Inc. All rights reserved. doi:10.1016/j.jbusres.2005.12.004

nobody could possibly treat puffery seriously or be misled by it. Two critical assumptions underly the policy. First, consumers can identify puffed claims as not credible. Second, consumers will not incorporate a puffed claim into their evaluations or beliefs because they understand that the puffery is a ‘wild’ exaggeration. Although Cartesian logic is used by policymakers, empirical evidence supports Spinoza's view. Gilbert et al. (1993) show that interrupting the processing of false claims results in participants believing the claims to be truer. The disturbing implication of the findings by Gilbert et al. (1993) is that every encounter with misinformation or an exaggerated claim can potentially affect future behavior, even if the consumer realizes that the claim is false. The research presented here demonstrates that although consumers are able to identify an exaggerated claim as less credible, exposure to the puffed claim still shifts the evaluation of the brand to be more positive. 2. Processing exaggerated claims 2.1. A Cartesian approach Government policymakers have taken the position that consumers recognize that puffery lacks credibility, even though very little empirical evidence has been presented to support this assumption. Policymakers assume that when consumers process exaggerated claims they understand the lack of credibility and

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ignore the claims. Cartesian logic is implicit in this assumption, as there is no concern for partially processed claims. Previous academic research has focused on conditions under which consumers believe exaggerated claims (Kamins and Marks, 1987; Olson and Dover, 1978; Rotfeld and Rotzoll, 1980; Wyckham, 1985). Most research has shown that consumers do form beliefs based on specific puffed claims such as “the fastest headache relief possible.” Two explanations are offered for the deception. First, consumers believe the claims (Kamins and Marks, 1987; Rotfeld and Rotzoll, 1980; Shimp and Preston, 1981). “Consumers do not recognize them [puffed claims] for what they are …” (Shimp and Preston, 1981, p. 24). Second, consumers process the puffed claims as though they were fact and generate inferences on the basis of those facts (Holbrook, 1978; Shimp and Preston, 1981; Wyckham, 1987). “[Consumers] are prone to interpret evaluative claims [puffery] as constituting factual claims. It is a process of implication in which the consumer accepts an unstated factual claim as being the implied meaning of the stated evaluative claim” (Shimp and Preston, 1981, p. 24). In both cases, the concern is that consumers will make a mistake during the assessment of the accuracy of the claim. Again, Cartesian logic is implicit in the assumption that one representation of the claim will be made in memory. Are consumers unable to differentiate between fact and exaggeration? Is “the public more tolerant of advertising hyperbole and less inclined to counter argue than is the case with other message forms” (Shimp and Preston, 1981, p. 26)? Is it safe to assume that a necessary condition for forming beliefs on the basis of puffed claims is that the claim is judged to be credible? Instead of a Cartesian approach, perhaps the claim is initially represented in memory as true during the comprehension process, affecting other associated beliefs. After determining that the claim is not credible, consumers are able to store the claim with a ‘not credible’ tag, but the corresponding evaluation will not be appropriately adjusted. 2.2. A Spinozian approach Gilbert et al. (1990) provide evidence that people initially represent false information as true. In their research, participants are asked to learn new propositions, both true and false. If participants were interrupted while processing the propositions, they rated a significantly greater proportion of both true and false statements as true, compared to participants that were allowed to completely process the propositions. The result is interpreted as support for the Spinozian explanation. Gilbert and colleagues found the result to hold even when the participants were forewarned that some of the information presented would be false. Perhaps consumers temporarily believe puffed claims as part of the comprehension process. Even though consumers may expect some advertising to lack credibility, they initially represent the claim as true. In the process of determining whether the claim is true, an accepted form of the claim is represented in memory. If the claim is a generalized exaggeration such as “the very best restaurant in town” then the positive global evaluation may be later stored with a ‘not credible tag,’ but is not ignored

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during the evaluation procedure. More specific attribute beliefs may not be affected as they are at a different level of abstraction (Hawkins et al., 2001). The prediction that a global evaluation of the brand will be affected by puffery, even though the claim is ultimately determined to be untrue, is consistent with a larger body of research that finds that people are particularly poor at rejecting, ignoring or failing to believe what they have comprehended (Bjork, 1972; Schul and Burnstein, 1985; Wyer and Budesheim, 1987), even when they are forewarned that the information will be false (Gilbert et al., 1990). The outcome of this comprehension process is also consistent with dissociations found between perceptions of truth and belief (Begg et al., 1992). 2.3. Remembering exaggerated claims Even though consumers may be able to correctly unaccept a puffed claim, it has been shown that thinking about and negating a proposition can lead to false memory (Mayo et al., 2004). Feidler et al. (1996) found that after correctly negating a fact and following a filler task, respondents were more likely to falsely recognize the fact in its non-negated form than they were to recognize unpresented facts. This is counter to the Cartesian explanation. Because under Cartesian logic only the negated claim would be stored in memory, non-negated facts could not be retrieved from memory. If the Spinozian model is correct, then factual claims should be better remembered than puffed claims because there is no alternative representation to cause interference during retrieval. However, if the processing of the exaggerated claims is interrupted, then the puffed claims should be as well recognized as the factual claims because the nonnegated fact is the only representation available in memory. 3. Hypotheses Consumers are able to identify generalized puffed claims as less credible than factual claims if processing is uninterrupted (H1). However, even after identifying the generalized puffed claims as less credible, they are still more positive in their evaluation of the brand associated with the puffed claim (H2a), but no change occurs in their specific brand beliefs (H2b). Support for the Spinozian explanation is expected. When processing is interrupted, puffed claims are rated as credible as the factual claims (H3). Consumers are better able to remember the factual claim compared to the puffed claim in an uninterrupted processing condition (H4a). However, the memory advantage for factual claims should disappear if processing is interrupted because the negation process will not occur (H4b). 4. Methodology 4.1. Design and manipulations Sixty undergraduate students at an Australian university participated in the study for course credit. The design of the study was 2 × 3. The processing at encoding was a between

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subject factor with 2 levels (uninterrupted processing, interrupted processing). The level of puffery was a within subject factor with 3 levels (a ‘the very best’ claim, a ‘the ultimate’ claim, a factual (no puffery) claim).

finished typing their student identification number and pressed the ‘return’ key, they did not return to the screen with the target advertisement. Instead, they advanced to the next task of rating of the credibility of the claims in the advertisement without any further processing of the claim.

4.2. Puffery manipulation 4.4. Dependent measures Each participant saw three target advertisements (one for the Harbor Bistro, one for the Alternative Bar, and one for the City Cruise Line), one advertisement at each level of puffery. The two puffery levels were taken from Preston (1996; 1998), who identified ‘the very best’ and ‘the ultimate’ as two of six levels of puffery. The advertisement for the Harbor Bistro claimed the bistro was ‘the very best bistro in Sydney’, ‘the ultimate dining experience’ or the factual claim of ‘dining with a harbor view.’ The advertisement included a photo of the interior of the bistro with a view of the harbor; this ensured that participants could identify the factual claim as factual. The advertisement for the Alternative Bar claimed the bar was ‘the very best club in Sydney’, ‘the ultimate club experience’ or the factual claim of ‘music in the city.’ The advertisement included a photo of the interior of the bar with a view of the stage with musical equipment to ensure that the participant knew the factual claim was factual. The advertisement for City Cruise Line claimed the cruise was ‘the very best cruise in Sydney’, ‘the ultimate harbor experience’ or the factual claim of ‘see Sydney from the harbor.’ The advertisement included a photo of the interior of the boat with a view of the harbor including the Harbor Bridge and Sydney Opera House. All of the target ads advertised hypothetical brands. 4.3. The encoding manipulation The study was run in a computer lab. Each participant viewed the stimuli on a 17″ computer terminal. All participants were warned that previous participants had experienced some technical difficulties with the software when reading the advertisements. The participants were told that “if a screen disappears, please just follow the instructions as closely as you can.” Half of the participants were allowed to view the target ads for as long as they required before making the credibility and liking judgments without interruption. The other half of the participants were allowed to view the three target ads for 500ms before being ‘interrupted’ by the screen disappearing. A pretest (n = 20) had revealed that 500ms allowed participants to read the screens but not to elaborate on the information in the copy, or to question the claims. A new screen appeared which included an apology and instructed the participant to type their student identification number in a pop-up box in order to continue. Students were forced to use the numbers above the letters on the keyboard instead of the numbers on the number pad to the right of the keyboard. Not using the number pad was important because many students can touch-type their student number on the number pad. Using the keys at the top of the keyboard meant that they had to concentrate on the location of each number key. This provided the desired interruption to the processing of the claim. When the participants

4.4.1. Credibility Directly after viewing the ads, participants were asked to provide a credibility rating for the advertisement. Participants used a 10 point scale anchored with ‘not at all credible’ (0) to ‘very credible’ (9). The instructions encouraged participants to use the entire scale. Although participants were invited to ask questions if they did not understand the instructions, no questions were directed to the study administrator. 4.5. Belief and evaluation ratings After rating the credibility of the ad, the participants were asked to predict the probability of receiving good service and good food, and whether they believed the bistro/bar/cruise would be expensive. Participants used a 10 point scale anchored with ‘not at all likely’ (0) to ‘very likely’ (9). They could find some information in the advertisements about the food and service. Price information was not available, participants had to infer the expense involved with each establishment. Finally, participants were asked for an overall evaluation of the bistro/ bar/cruise on a 10 point scale anchored with ‘not at all good’ (0) to ‘very good’ (9), and to indicate how sure they were in their response on a 10 point scale anchored with ‘not at all certain’ (0) to ‘very certain’ (9). 4.6. Recognition The participants were asked to identify the claim that they saw earlier for each of the target ads. They were presented with all three claims (one old claim seen at study, two new claims) and a “don't remember” option. 4.7. Procedure Participants signed up for a study called the Advertising Study which ostensibly was designed to investigate the relationship between leisure activities and attitudes toward advertising. They were informed that they would see copy for both existing and potential ads. In the introduction they were told that they would be viewing 10 advertisements. They would first view the ad, and then answer some questions about their impressions of the credibility of the ad, the performance of the product or service, and their overall evaluation of the brand. Participants were then warned about the ‘problem’ with the software. Before the first target advertisement, two filler ads were rated for perceived credibility, overall evaluation of the brand and two specific brand beliefs. All participants experienced the ‘disappearing screen problem’ with the software for the second filler advertisement. Experiencing the interrupted processing early in

E. Cowley / Journal of Business Research 59 (2006) 728–734

5. Results 5.1. Credibility ratings Hypotheses 1 and 3 are tested with the credibility ratings. Hypothesis 1 asserts that consumers are able to recognize the reduced credibility of an exaggerated claim. Evidence in support of the hypothesis will be claimed if participants rate the puffed claims as less credible than the factual claims when they had time to process the claims completely. An ANOVA run on credibility ratings in the uninterrupted condition reveals a significant main effect for level of puffery (F(2, 84) = 6.42, p b .01). Participants were able to identify that the puffed claims were less credible than the factual claims (fact = 7.21, ultimate = 6.07, very best = 5.07). Hypothesis 1 is supported. Note that participants did not believe, on average, that the claims were not credible. Therefore, government policymakers would be correct if they assumed that consumers can identify that puffed claims as less credible, but they are wrong to assume that consumers dismiss puffery as not credible. If comprehension and acceptance are part of the same process, then the interruption manipulation should affect credibility ratings such that no differences are found in the assessment of the

Credibility

8 7 6 5 4

Fact

Low Puffery

High Puffery

Interruption

7.26

6.84

6.94

No Interruption

7.21

6.07

5.07

Level of Exaggeration

Fig. 1. Credibility ratings.

8.00 Evaluation

the experimental session was critical because all participants were motivated to try and read as much as they could of the copy as soon as the advertisement appeared on the screen. The third advertisement was the first target ad. One third of the participants saw a factual claim, one third saw a slightly exaggerated claim, and one third saw a highly exaggerated claim. Half of the participants were allowed to process the ads without interruption, the other half had their processing interrupted after comprehension. Participants saw two more target ads amongst the next four ads and then three filler ads. The same ratings were made for each ad. If the first ad included a very best claim then the second was an ultimate claim and the third was a factual claim. Unrelated filler questions about the leisure activities of the participants followed. The questions were included to support the cover story and provide time to clear short term memory. Ten minutes later participants were asked to recognize the ad claims for the three target ads. Participants were asked to guess the hypotheses of the study and then were debriefed. None of the participants suspected that the study was testing the effect of exaggerated claims.

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7.00 6.00 5.00 4.00 Fact

Low Puffery

High Puffery

Interruption

6.10

6.07

7.35

No Interruption

6.52

6.84

7.34

Level of Exaggeration

Fig. 2. Overall evaluation.

credibility of a fact versus puffed claim in the interrupted condition. The acceptance of all claims as credible was hypothesized in this condition because participants did not have a chance to unaccept a decidedly less credible claim. An ANOVA run on the entire sample reveals a significant interaction between puffery and interruption condition (F(2, 174) = 3.63, p b .05). A separate ANOVA was run on credibility ratings in the interrupted condition to investigate the interaction. The ANOVA reveals no significant main effect for level of puffery (F(2, 90) = 1.12, p N .10). Participants were not able to identify that the puffed claims as less credible than the factual claims (fact= 7.26, low puffery = 6.84, high puffery = 6.94). Hypothesis 3 is supported, see Fig. 1. The data support the Spinozian hypothesis that the process of comprehension is not independent from the belief decision. When processing of the claim was interrupted, the merely comprehended claims were believed to be true. 5.2. Overall evaluation Participants were asked to provide an overall evaluation of the bistro/bar/cruise and to indicate how certain they were about their response. Hypothesis 2a predicts that the inherently positive nature of a generalized puffed claim such as “the very best in town” will influence the overall evaluation of the brand. An ANOVA was run on the overall evaluation of the brand with the level of puffery and the interruption condition as the independent variables and the credibility rating as a covariate. The results reveal a significant main effect for puffery (F(2, 174) = 6.85, p b .01), but not for interruption (F(1, 174) = 2.41, p N .10). Consumers in both conditions rated brands with puffed claims as more favorable overall (fact = 6.31, low puffery = 6.71, high puffery = 7.35). Planned comparisons reveal that the “very best” claim was significantly higher than the other claims in the interrupted processing condition, and higher than the fact claim in the uninterrupted condition. A possible explanation for the mixed result for the “ultimate” claim may be that it is a more complicated claim than the “very best” which is easier to understand. The credibility covariate was weakly significant (F(1, 174) = 3.35, p b .10). Perceived credibility of the claim has a positive effect on the overall evaluation of the brand. Hypothesis 2a is supported, see Fig. 2. A separate ANOVA run on the certainty ratings for brand evaluations with puffery and interruption condition as the independent variables revealed a significant effect for the interruption condition (F(1, 174) = 3.99, p b .05), but no significant effect for the level of puffery. The significant effect for the

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interruption condition is interesting because evaluation confidence was higher in the interrupted condition (interrupted = 6.85, uninterrupted = 6.30). This result is consistent with recent evidence that a reduction in attitude confidence can follow the counter argumentation associated with negation of a claim (Petty et al., 2004). The null effect for the level of puffery is interesting because it indicates that an evaluation based on a factual claim is held as confidently as an evaluation based on an exaggerated claim. The result is consistent with previous research finding a low correlation between accuracy and confidence in judgments by consumers (Alba and Hutchinson, 2000; Cowley, 2004). 5.3. Attribute beliefs As expected, the attribute beliefs (good food, good service) and the inference (being expensive) did not vary with puffery level or interruption condition. ANOVAs did not reveal main effects for puffery or interruption or interaction effects. This was predicted in H2b because of the general nature of the puffed claims. Hypothesis 2b is supported, see Fig. 3. The absence of a change in specific beliefs does not support or negate the Spinozian hypothesis, instead the null effects suggest that the specificity of a puffed claim may play a role in generating inferences and changing specific attribute beliefs. Previous work has reported that specific claims affect specific beliefs. Rotfeld and Rotzoll (1980) find that almost half of the consumers in their study believed the puffed claims, but a much reduced, yet still evident percentage believed the puffery implied claims. Rotfeld and Preston (1981) and Shimp (1978) also use specific claims and find that consumers expanded on the claims, possibly because of the multiple interpretations allowing for inference generation. The effects are not found here with generalized exaggeration. The difference in results depending on the specificity of the claims themselves is consistent with related work where plausible specific claims have been found to affect belief in those claims, but that general claims do not affect specific beliefs (Hawkins et al., 2001). 5.4. Memory for the claim Hypothesis 4a states that participants in the uninterrupted condition should be better able to recognize factual claims. The data indicate that there is a difference in memory performance for puffery versus factual claims (χ2(1) = 3.87, p b .05). As ex-

% Not Remembering

732

5

Fact

Low Puffery

High Puffery

Food

5.68

5.75

6.14

Service

6.65

6.74

6.77

Expense

7.07

7.07

7.24

Level of Exaggeration

Fig. 3. Attribute beliefs.

15.00 10.00 5.00 0.00

Fact

Low Puffery

High Puffery

16.13

22.58

19.35

No Interruption

6.90

3.45

3.45

Level of Exaggeration

Fig. 4. Don't remember responses.

pected, participants were more accurate when remembering factual claims (factual = 85% correct, puffery = 64%) when processing was not interrupted. Therefore, H4a is supported. The memory advantage for factual claims was hypothesized because there was no negation process which may cause interference during retrieval. Hypothesis 4b suggests that the memory disadvantage for exaggerated claims should disappear in the interrupted processing condition because the negation process does not occur. The results show no differences in memory performance in the interrupted condition (χ2(1) = .26, p = .61). Although this may seem surprising, a number of influences are at work. First, since the interrupted group had only 500ms to look at the ad, they may have more trouble recognizing the claim and less confidence in their ability to identify the correct claim. On the other hand, the puffed claim may have been the only thing taken away from the exposure because it was prominent: increased attention to the claim may have reduced interference from other aspects of the ad. Second, part of the rationale behind H4b was that in the uninterrupted condition the dual representation of the claim may have caused interference during retrieval resulting in an increase in erroneous recognition judgments. One result that provides evidence consistent with a lack of processing account in the interrupted condition is the number of “don't remember” responses. See Fig. 4. Participants in the interrupted condition more frequently reported that they did not believe they knew the answer. These results are not significant, however. A result consistent with a negation tag account is that participants in the uninterrupted condition were more accurate when remembering factual claims versus the exaggerated claims. Although false recognition went up slightly in the interrupted condition for factual claims (possibly because of the limited processing time), it was less likely in the interrupted condition,

% Incorrect

Ratings

6

20.00

Interruption

8 7

25.00

40.00 35.00 30.00 25.00 20.00 15.00 10.00

Interruption No Interruption

Fact 22.58 13.80

Low Puffery 29.00 34.50 Level of Exaggeration

Fig. 5. Mistaken recognition.

High Puffery 22.50 34.50

E. Cowley / Journal of Business Research 59 (2006) 728–734

see Fig. 5. Taking the results of H4a and H4b together, it appears that the process of negating the initial acceptance of the claim affected recognition memory for the puffed claims. 6. Conclusions

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this data how much of the memory performance difference is based on the negation process and how much is attributable to the encoding time itself. Future research is required to investigate this hypothesis because it is important to know under what circumstances the puffed claim is eventually forgotten.

6.1. General discussion 6.2. Implications The results provide evidence that consumers are able to identify puffed claims as less credible, however, the claims are not judged to be not credible. Only 1 in 180 responses rated the puffed claim as 0 or “not at all credible.” This is counter to previous findings with the exception of Wyckham (1987) who found upwards of 80% of consumers stating that puffed claims were not true. One explanation is that the generalized puffed claims used here are less concrete and more difficult to discredit. More specific claims such as those used in Wyckham's study (1987) refer to a single attribute or benefit, allowing the consumer a better opportunity to mentally test its credibility. Even though consumers can identify a puffed claim as less credible, they still rated the brand more favorably than brands associated with a factual claim. The general finding, that puffery is deceptive because consumer beliefs do change after exposure to puffed claims, replicates a number of past studies (Holbrook, 1978; Kamins and Marks, 1987; Olson and Dover, 1978; Rotfeld and Rotzoll, 1980; Wyckham, 1985) and supports assertions made in research review papers (i.e. Rotfeld and Preston, 1981). The explanation in previous research was that consumers believe the claims and generate inferences on the basis of the implied facts. No support is found here for these explanations. Consumers were able to identify puffery as less true and they did not generate inferences about the quality of food and service or the expense of the bistro/bar/cruise. The explanation offered here is that during the process of comprehending a puffed claim, the initial representation in memory is that the claim is true. Consumers appear to accept the claim initially, and then unaccept or discount the claim after realizing its lack of credibility. This is evidenced by the increased number of puffed claims accepted as credible in the interrupted processing condition. Processing was interrupted before the unaccepting or discounting process was complete. Associations from the initial representation to other brand beliefs may be established in memory, possibly affecting brand evaluations and other generalized beliefs about the brand. After a claim is identified as lacking credibility a negation tag is added to the representation, but other alterations to associated beliefs are not re-adjusted, or at least not completely. Consequently, knowledge that the claim is lacking credibility is stored, but remnants of the claim's persuasive impact linger. Finally, memory for the puffed claim is not as accurate as memory for the factual claims in the uninterrupted condition, but improves in the interruption condition. The explanation is that the memory representation resulting from the negation process can interfere with retrieval. This result is very limited because the processing time was different across conditions confounding the manipulation. It is impossible to establish with

The implications for policy makers are clear. Exposure to incorrect information affects beliefs even when it is identified as lacking credibility. Although puffery defined by policymakers as “wildly exaggerated, fanciful or vague claims for a product or service,” can be identified as less credible, consumers still alter their evaluations of the brand after exposure. As mentioned above, after some time has past, consumers do not recognize the claim. This compounds the deceptive danger of exposure to puffed claims for consumers because they can not correct the inflated overall evaluation at retrieval with the memory that the claims were not credible. One logical suggestion is to forewarn consumers of the effects of exposure to puffed claims as a strategy to safeguard them. The problem with this suggestion is that warnings of impending false information do not seem to alter this process (Gilbert et al., 1990). The implication for marketers is also clear. Puffery works. A legally accepted, but misleading claim, results in consumers liking the brand better and not remembering the exaggeration specifically. Given that the advertising environment is extremely cluttered reducing the amount of processing even in an uninterrupted situation (Gardener et al., 1978), consumers may be even more likely to accept puffed messages in a more natural setting because of the possible interference in the unaccepting process. This would explain the findings of Rotfeld and Rotzoll (1980) who tested brand beliefs based on exposure to puffed claims in ‘natural’ advertising settings and found very high levels of belief amongst a sample of consumers (from 42% to 69%). 6.3. Future work The brands used here were hypothetical. The participants had no knowledge of these brands. The effect of puffery on more established brands and the process by which a claim for a wellknown brand is processed may be different than the process investigated here. No current evidence in cognitive psychology research suggests that this would be true, but it remains possible. Perhaps the most promising avenue for future work is to investigate whether puffed claims heard after product trial will change a consumer's memory and evaluation for their own past experiences with the brand. Braun (1999) has shown that misleading advertising has this effect, but Cowley and Janus (2004) have shown that blatantly misleading advertising can have the opposite effect by improving memory. It would be interesting to know what effect puffed claims have on a consumer's memory for an experience, particularly since policymakers categorize puffery as blatantly misleading, but consumers do not.

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Journal of Business Research 59 (2006) 735 – 744

Responsiveness to authority appeals among young French and American consumers Jae Min Jung a,⁎, James J. Kellaris b a

Department of Marketing, College of Business Administration, North Dakota State University, Fargo, ND 58105-5137, United States b University of Cincinnati, United States

Abstract The “authority effect” is a powerful social influence principle frequently used in advertising to increase compliance. Young adult consumers, however, often resent authority figures. Such resentment can result in negative reactions to authority-based persuasion attempts. This study examines the differential responsiveness to authority appeals among young adults in France and the U.S., as well as the boundary conditions within which such differential responses occur. Results show that before 9 / 11 Americans had more positive attitudes when the spokesperson in an ad is low (vs. high) in authority. This reverse authority effect did not obtain among French subjects, who appear to prefer recommendations from social equals, or among Americans after 9 / 11. Perceived source credibility and power distance moderate the effect of authority on attitudes and purchase intentions. © 2006 Elsevier Inc. All rights reserved. Keywords: Social influence; Cross-cultural differences; Authority appeals; Advertising; Power distance; Source credibility

1. Introduction The “authority principle” refers to the tendency of individuals to comply with the recommendations or directives of authority figures, and is a fundamental social influence principle (Cialdini, 2001). Authority figures may vary across cultures; however, in general, they are the ones who have acquired status through education, experience, talents, or other means (Cialdini, 2001). For instance, in work places, superiors may be regarded as authority figures. Parents can be regarded as authorities by children. High ranking public officials are often regarded as authority figures. Perhaps the classic example is the controversial Milgram (1963) study, which demonstrated the shocking extremes to which individuals will go to obey authority. In the social influence literature, numerous studies have documented authority effects (e.g., Bickman, 1974; Bushman, 1988; Michener and Burt, 1975; Rasinski et al., 1985). However, authority-based appeals have received scant attention in advertising research. Instead, more efforts have been focused on celebrity endorser effects (e.g., Goldsmith et al., 2000; Heath et al., 1994; Kamins et al., 1989; MacCracken, ⁎ Corresponding author. Tel.: +1 701 231 8129; fax: +1 701 231 7508. E-mail address: [email protected] (J.M. Jung). 0148-2963/$ - see front matter © 2006 Elsevier Inc. All rights reserved. doi:10.1016/j.jbusres.2006.01.011

1989). This could be attributed in part to the prevalent use of celebrity endorsers in practice (Agrawal and Kamakura, 1995) and to American cultural traits that promote admiration of successful persons, yet indifferent treatment of high (vs. low) power position holders (Hofstede, 2001). The lack of research on the authority principle in advertising stands in sharp contrast to frequent use of authority appeals in advertising practice. For example, General Mills uses mothers as spokespersons for “Kix” cereal. McNeil Consumer and Specialty Pharmaceuticals features moms for their “Motrin,” children's fever reducer. In France, work place superiors and teachers are often used as spokespersons (Mooij, 1998). In all of these cases, spokespersons are featured as authorities upon whom consumers can rely. Despite the widespread use of non-celebrity authority figures in global advertising, little is known about their effectiveness and their applicability across different segments and cultures. Thus, this study seeks to address these issues using data collected from young adults in France and the U.S. 2. Background and hypotheses We identified three factors that are important to the effectiveness of authority-based advertisements. Under certain circumstances, authority figures may not be as persuasive as the

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authority principle would suggest. The effectiveness of authority may reside 1) within contextual factors (e.g., national culture), 2) within the authority figures themselves (e.g., source credibility), and/or 3) within decoders of messages (e.g., their orientation to power distance). First, national culture is expected to moderate the authority effect. Cross-cultural social influence research suggests that responses to social influence strategies may also vary across national groups, depending on the fit between relevant dimension(s) of national culture and the cultural value that the influence strategy is intended to evoke (Cialdini et al., 1999; Jung and Kellaris, 2004). The authority principle, for example, may be closely related to the “power distance” (PD) dimension of national culture, which is defined as “the extent to which the less powerful members of institutions and organizations within a country expect and accept that power is distributed unequally” (Hofstede, 1991). Consequently, authority figures that influence audiences in high power distance cultures may not exert as much influence in low power distance cultures. Second, source credibility is expected to moderate the influence of authority. Consistent with previous source credibility research (e.g., Grewal et al., 1994), we define credibility as “expertise” and “trustworthiness.” For authority figures to exert power, they must have credibility (Cialdini and Rhoads, 2001). Lastly, values held by audience members are expected to moderate authority effects. Hofstede's seminal work (1991, 2001) and other studies (e.g., Singelis, Triandis, Bhawuk, and Gelfand, 1995; Triandis, 1995) in the cross-cultural psychology literature provide some insights into how individual values may affect the way individuals perceive authority. In summary, we expect authority effects to be moderated by national cultures, spokesperson characteristics, and audience characteristics. In this study, we first examine how different levels of authority influence consumer attitudes and purchase intentions. We further investigate how these authority effects are moderated by national culture, source credibility, and individuals' orientations to power distance. Fig. 1 summarizes our conceptual framework. 2.1. Authority vs. reverse authority effects In general, the authority principle works such that the higher the level of authority portrayed in an ad, the more positive attitudes (towards ads/brands) and purchase intentions should be. Under certain circumstances, however, authority may exert a negative influence. For example, individuals who resent or distrust authority should react negatively to authority-based persuasion attempts. Resentment of authority may be more common among young people who rebel against conventional societal values or among those who question authority as part of the critical world view encouraged by higher education, or among young adults who struggle to gain independence from parents. Moreover, in so much as authority represents an encroachment on the sovereignty of the individual, members of western cultures that place a high value on individual freedom may react negatively to authority. Resentment of authority may be a corollary of valuing freedom. Sources with less authority may

Individual Values (Power Distance) H4

Source Credibility H3

AUTHORITY of Ad Spokesperson

Attitude Towards Ads Attitude Towards Brands Purchase Intentions

H1 H2

Culture (National Level)

Fig. 1. Conceptual model. Dotted lines represent the relationship that are not formally hypothesized in this study.

be perceived as more trustworthy, because their motivations for making a recommendation may seem different from those of an authority figure. The low authority figure bears a greater social risk in making a recommendation and thus may elicit more positive attitudes. Hence young adults may exhibit a reverse authority effect, such that: H1. The higher the level of authority in an advertisement, the less positive young consumers' attitudes and purchase intentions. 2.2. Impact of national culture (France vs. the U.S.) Despite the universal use of authority across cultures, the degree of responsiveness to authority may vary (Manrai and Manrai, 1996). Cialdini et al. (1999) recently examined two social influence strategies (“social proof” and “commitment/ consistency”) in collectivist versus individualist countries (Poland, USA). Both strategies were found to be effective in both countries, however differentially so. A persuasive appeal based on social proof was more effective among collectivists and an appeal based on commitment/consistency more effective among individualists. Jung and Kellaris (2004) recently examined the differential responsiveness of French versus U.S. consumers to scarcity-based ad appeals. They found a positive effect of scarcity on purchase intent, with greater proneness to scarcity effects among low context American (vs. high context French) subjects. In a study of conflict resolution, Tyler et al. (2000) found cross-national differences in reactions to authority that were explained by different levels of PD at the national level. Similarly, we expect the authority principle to manifest differently among young adults across two nations as a function of cultural values (PD). France is classified as a high PD country and the U.S. as a low PD country (68 vs. 40 in PD index, Hofstede, 2001). In high PD countries, parents teach children obedience; teachers initiate communications in school; many levels exist in organizations; and decision making is centralized (Hofstede, 2001). The opposite norms are expected in low PD countries. Parents treat children as equals; students can freely initiate some communication in class; organizational structure is flat; and decision making is decentralized (Hofstede, 2001). Mooij (1998) pointed

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how these cultural differences in PD dimension are manifested in advertising and communication strategies adopted by marketing professionals in the two countries. For example, in French advertising, the elder advises the younger (e.g., mother advises daughter). In the U.S., the younger often advises the elder (e.g., daughter advises mother). In a high PD culture, the source of communication (e.g., authority vs. common people) is important as opposed to reasoning and argument (Mooij, 1998). Further, strong boss–subordinate relationships tend to exist in high PD countries. For these reasons, one might expect a positive authority effect to be observed in a high PD country (e.g., France) and a reverse authority effect observed in a low PD nation (e.g., the U.S.). However, young adults may react more negatively to the authority-based influence attempt because their PD level is lower than that of older groups in each country (Hofstede, 2001). Thus, on the basis of Hofstede (2001) and Mooij (1998)'s work, we anticipate that:

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tolerance of differences in hierarchy (Hofstede, 1991, 2001). High PD individuals are reluctant to refuse a request from or disagree with authority figures. They give priority to the opinions of people in authority. This suggests that those who are high in PD are more likely to accept and less likely to discount message arguments, whereas those who are low in PD are less likely to accept and more likely to discount the message arguments. Therefore, PD is expected to moderate the effectiveness of authority appeals such that individuals characterized by greater PD will be more prone to persuasive effects of authority appeals. H4. PD moderates the authority effect such that the reverse authority effect is less among high (vs. low) PD, young consumers. 3. Study 1 3.1. Methods

H2. The reverse authority effect is more prominent among young U.S. consumers than among their French counterparts. 2.3. Impact of credibility Spokesperson's source credibility (CRED) in ads is defined as the degree to which the spokesperson is perceived to have expertise on a subject and is trusted to provide an impartial opinion about the subject (Dholakia and Sternthal, 1977; MacCracken, 1989). Lack of either expertise or trustworthiness is likely to undermine the credibility of an authority figure's advocacy (Cialdini and Rhoads, 2001). Attractiveness (refer to MacCracken, 1989), which is often included to define celebrities' credibility (e.g., Goldsmith et al., 2000), is excluded in our conception of source credibility because our focus is on non-celebrity authority figures. In the advertising literature, the impact of message source credibility on ad effectiveness has long been established (e.g., Dholakia and Sternthal, 1977; Harmon and Coney, 1982). When consumers decode an advertising message, source credibility positively affects consumers' likelihood of message acceptance (Mizerski et al., 1979). Taking source credulity as a moderator, Grewal et al. (1994) showed that positive effect of price on perceived performance risk is reduced when perceived source credibility is high (vs. low). We propose source credibility as a moderator of authority's effect on attitudes (or purchase intention): the more credible an authority figure is perceived to be, the greater the impact of the authority appeals. H3. Spokespersons' credibility moderates the authority effect such that the reverse authority effect is lower among young consumers perceiving spokespersons as more (vs. less) credible. 2.4. Impact of power distance Power distance refers to the extent to which individuals expect and accept the unequal distribution of power, and

An experiment involving young French and the U.S. participants varied spokesman authority (low, mid, high) using printed descriptions of radio ads. Subjects' nationality, perceptions of source credibility, and PD were measured. Dependent variables were attitudes toward the ad, advertised brand, and purchase intention. 3.1.1. Subjects Subjects were two hundred forty-eight (N = 248) students at universities in the United States (n = 130) and the lower Loire Valley and mid-Pyrenees regions of France (n = 118). One hundred thirty-five were male (54.4%) and 113 (45.6%) female. Ages ranged from 20 to 56 with an average age of 22.9 years. The French sample was slightly older on average than the American sample (23.9 vs. 22.0 years) and had a slightly higher proportion of males; the samples were matched in other important respects. 3.1.2. Stimuli The stimuli were printed descriptions of radio ads in a dialog format. The relationship of the primary spokesperson to the recipient of a recommendation was varied to represent high, mid, and low levels of authority. Three sets of ads were developed to enhance internal validity. In the first (second/ third) ad, a yogurt (software/internet retailer) was recommended by a mother (teacher/boss) to a daughter (student/ subordinate) under the high authority condition, by one woman (person/one employee) to another woman (person/ employee) under the mid authority condition, or by a daughter (student/subordinate) to a mother (teacher/boss) under the low authority condition. The (English) text of the ads appears in Appendix A. 3.1.3. Measures Attitude toward the ad (Aad) was measured via four, sevenpoint items preceded by instructions stating “The following items concern the ad itself, not the product in the ad” and by a

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prompt “The radio ad I imagined was…” The items, taken from Madden et al. (1988) were labeled pleasant/unpleasant, likeable/unlikable, interesting/boring, and good/bad. Responses were summed and averaged to form a composite scale (αCombined = .88; αUS = .89, αFrance = .86). Attitude toward the brand (Ab) was measured using the same four items, preceded by instructions stating “The following questions concern the product represented in the ad” and by a prompt “The product in the ad I imagined was…” Alpha reliability for the four item composite scale averaged .88 (αUS = .91, αFrance = .86). Purchase intent (INT) was measured via a one-item, sevenpoint Likert-type scale (very likely = 7, very unlikely = 1) preceded by the prompt “If it were available in your market, what is the likelihood that you might purchase the advertised product within the next twelve months?” and was summed across ads and averaged. Source credibility, taken from Harmon and Coney (1982), was measured via six-item, seven-point semantic differential scale preceded by the prompt “The spokesperson (party) in the ad was…” In each case the party was specified (e.g., mother for high authority, women for mid authority, or daughter for a low authority condition in ad #1). The items were labeled trustworthy/not trustworthy, open-minded/not open-minded, good/bad, expert/not expert, experienced/not experienced, trained/untrained. The second item was dropped due to a low factor loading (αCombined = .82 across the three ads; αUS = .81, αFrance = .83). Power distance scale was adapted (4 items) from Pretest six of Jung (2002). One item that had factor loading of .26 in CFA was dropped (“Opinions of superiors should be given priority over those of my peers”). Further, six congeneric scale items (Nunnally and Bernstein, 1994) were created to adequately tap the domain of the construct. Thus, the nine items were administered to the samples and two items were further dropped due to low item to total correlation. The resulting seven item PD scale (See Appendix B) produced a unidimensional factor structure with Cronbach's alpha of .86 (αUS = .89, αFrance = .83).

Two additional cultural value scales were included for discriminant validity assessment purposes. Vertical Collectivism (VC) is a cultural pattern in which one sees oneself as part of the collective and accepts inequalities among group members; Vertical Individualism (VI) is a cultural pattern in which individuals are viewed as autonomous, but they are considered different in their status (Singelis et al., 1995). Both constructs were measured originally using eight item scales (Singelis et al., 1995). After one item (Children should feel honored if their parents receive a distinguished award) was dropped, the remaining seven-item VC scale had a Cronbach's alpha of .69. For VI, one item was deleted (Some people emphasize winning; I'm not one of them) due to low factor loading. The remaining seven-item scale had a Cronbach's alpha of .85. Demographic data (sex, age, nationality) were collected to facilitate sample description. 3.1.4. Translation and procedure A French version of the stimuli and questionnaire was constructed via standard back-translation (Brislin, 1980), conducted by two independent, bilingual persons. Self-administered questionnaires containing the ad descriptions and measures were distributed to subjects in regular class sessions in return for course credit. French subjects received a French language version containing the ads. Each ad was followed by measures of attitude toward the ad, attitude toward the advertised brand, and purchase intent. Although each subject saw three ads, the manipulation of authority was completely between-subjects in order to avoid hypothesis guessing. 3.1.5. Integrity check To test the integrity of the treatments, a one-way ANOVA of authority on CRED was conducted for each of the three ads, for the American and French samples separately and combined. Results show a significant main effect of authority in ads 1 and 2 (p's b .05), but not in ad3 (p N .10) within as well as across the samples. Subsequently ad 3 was excluded from analysis. Tables 1 and 2 show correlations and descriptive statistics of variables when ad1 and ad2 are combined.

Table 1 Correlations and descriptive statistics in the combined data set

Aad Ab INT Sex Nation Age Auth Cred PD VI VC Mean SD

Aad

Ab

INT

Sex

1 .50⁎⁎⁎ .24⁎⁎⁎ − .02 − .42⁎⁎⁎ − .10 − .13⁎ .32⁎⁎⁎ .16⁎⁎ .32⁎⁎⁎ .27⁎⁎⁎ 4.12 1.04

1 .49⁎⁎⁎ .04 −.08 −.10 −.11 .37⁎⁎⁎ .17⁎⁎ .23⁎⁎⁎ .13⁎ 4.84 .82

1 .06 .09 − .06 − .07 .20⁎⁎ .06 .17⁎⁎ − .02 3.67 1.23

1 .13⁎ − .15⁎ .04 − .05 − .03 − .23⁎⁎⁎ −.07 1.46 .50

⁎b.05; ⁎⁎b.01; ⁎⁎⁎b.001 (two-tailed).

Nation

Age

Auth

Cred

PD

VI

VC

1 .19⁎⁎ .09 − .06 − .00 2.02 .82

1 .17⁎⁎ .26⁎⁎⁎ .23⁎⁎⁎ 4.41 .94

1 .07 .38⁎⁎⁎ 3.51 1.13

1 .34⁎⁎⁎ 4.39 1.11

1 3.43 .88

1

.23⁎⁎⁎ .05 − .05 − .15⁎ − .36⁎⁎⁎ − .35⁎⁎⁎ 1.48 .50

1

.16⁎⁎ −.06 −.13⁎ −.06 −.05 22.91 .82

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3.2. Analysis and results To test our expectations concerning authority effects, we ran multiple regression analyses for each sample and for the combined sample. For dependent variables, overall average values of Aad, Ab, and INT, respectively, were calculated across ads 1 and 2 and were used in the analysis. For independent variables, we included authority (Auth), Nation, Cred, PD, VC, VI, and the interaction terms (Auth ⁎ Nation, Auth ⁎ Cred, Auth ⁎ PD, Auth ⁎ VC, Auth ⁎ VI). In addition, sex and age were included as control variables. All the independent metric variables were mean centered and Auth was zero centered to avoid multicollinearity problem (Aiken and West, 1991). Thus, each of the three dependent variables was regressed on the independent variables for the combined, American, and French data set, leading to nine regression models. Variables, “nation” and “Auth ⁎ Nation” were excluded from regression models involving single country data. Multicollinearity was not a problem since variation inflation factors were all less than 2.76 with an average of 1.47 across the regressions, which is well below the cutoff point of 10 (Neter et al., 1985). Table 3 shows results for the ad and brand attitude measures. 3.2.1. Reverse authority Results show a negative impact of authority levels on Aad (β = − .27, t = − 3.26, p b .001), Ab (β = − .26, t = − 2.99, p b .005) and INT (β = − .14, t = − 1.44, p = .075, one-tailed) for the combined sample. This means that the higher level of authority, the more negative the attitudes and purchase intentions of the young adults across cultures. Thus H1 regarding a reverse authority effect among young adults was supported. 3.2.2. National culture To test for a moderating influence of national culture on the reverse authority effect (H2), we used regression primarily and ANCOVA secondarily to shed light on the regression results. The multiple regression analysis revealed a marginally significant Auth ⁎ Nation interaction on Aad (βAuth × Nation = .13, t = 1.47, p = .07, one-tailed) and Ab (βAuth × Nation = .13, t = 1.30,

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p b .10, one-tailed), but not on INT. Results suggest that reverse authority effects are slightly stronger among American (vs. French) participants. Standardized coefficients for Auth in each country attest to this interpretation. The reverse authority effect was present among the Americans (βAuth = − .34, t = − 3.49, p = .001 for Aad; βAuth = − .27, t = − 2.67, p b .01 for Ab; model not significant for INT), but not among the French (all three p's N .50). Next we ran a 3 (authority) × 2 (nation) between-subjects ANCOVA on Aad, with CRED as a covariate. Because CRED is an important factor determining persuasion (MacCracken, 1989) and spokesperson credibility might vary across cultures, CRED had to be controlled for to evaluate the differential effect of authority across cultures. However, we first confirmed homogeneity-of-slopes assumption that CRED be linearly related to attitudes and intentions in the same fashion across all the levels of authority and nations. Violation of this assumption would render ANCOVA invalid (Green and Salkind, 2003). Subsequently, we ran a two-way ANCOVA on Aad with CRED as a covariate. Results showed a significant covariate effect (F1, 238 = 43.04, p = .000), a reverse authority effect (MLow auth = 4.31, MMid auth = 4.12, MHigh auth = 3.88; F 2, 238 = 5.02, p b .01), nation effect (M American = 4.53, MFrench = 3.68; F1, 238 = 57.98, p = .000), and authority ⁎ nation interaction effect (F2, 238 = 4.59, p = .01, partial η2 = .04), confirming H2. Separate ANCOVA analyses were also performed for each country. Results showed that when the impact of CRED is controlled for, a reverse authority effect is clearly revealed among the U.S. participants (MLow auth = 4.98, MMid auth = 4.37, MHigh auth = 4.26; F2, 126 = 8.54, p = .000), but not among the French participants (MLow auth = 3.63, MMid auth = 3.87, MHigh auth = 3.50; F2, 111 = 1.82, ns), who seem to have responded most positively under equal authority conditions. However, an Auth ⁎ Nation ANCOVA on Ab and INT did not produce a significant interaction. Additionally, we ran a 3 (authority) × 2 (nation) between-subjects MANCOVA on Aad, Ab, and INT, with CRED as a covariate. Results show a marginally significant Auth ⁎ Nation interaction effect (Hotelling's Trace: F6, 468 = 1.93, p = .074, partial η2 = .02).

Table 2 Correlations and descriptive statistics in the French and the U.S. data

Aad Ab INT Sex Age Auth Cred PD VI VC Mean (U.S)++ SD

Aad

Ab

INT

1 .51⁎⁎⁎ .25⁎⁎ .05 .06 −.21⁎ .34⁎⁎⁎ .18⁎ .14 .17 4.54 .98

.53⁎⁎⁎ 1 .39⁎⁎⁎ .14 − .02 − .14 .33⁎⁎⁎ .20⁎ .15 .13 4.90 .84

.38⁎⁎⁎ .63⁎⁎⁎ 1 .17 − .01 − .10 .11 .06 .08 .02 3.57 1.24

Sex .04 −.04 −.08 1 −.15 .05 −.02 −.06 −.22⁎⁎ −.04 1.39 .49

Age −.04 −.14 −.13 −.23⁎⁎ 1 .09 .01 −.06 .11 −.02 21.97 2.70

Auth

Cred

− .01 − .06 − .05 .02 .21⁎ 1 .21⁎ .12 − .04 − .08 1.98 .83

.34⁎⁎⁎ .41⁎⁎⁎ .30⁎⁎⁎ −.07 −.09 .18 1 .16 .33⁎⁎⁎ .24⁎⁎ 4.45 .89

PD

VI

VC

Mean (FR)+

SD

.02 .12 .11 .04 − .13 .07 .17 1 .05 .44⁎⁎⁎ 3.67 1.14

.27⁎⁎ .29⁎⁎ .39⁎⁎⁎ − .17 − .03 − .06 .19 − .03 1 .32⁎⁎⁎ 4.77 1.10

.13 .11 .02 −.03 .06 .15 .22⁎ .22⁎ .12 1 3.71 .92

3.66 4.77 3.79 1.53 23.94 2.07 4.36 3.33 3.97 3.10

.90 .80 1.21 .50 5.37 .82 1.00 1.09 .97 .71

⁎b.05, ⁎⁎b.01, ⁎⁎⁎b.001 (two-tailed); upper triangle represents correlations among French subjects and the lower triangle represents correlations among the U.S. subjects; +is mean value for French subjects; ++is mean value for U.S. subjects.

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Table 3 Multiple regression results Dependent variables

Independent variables

Combined β

1. Attitude towards ads

U.S. sample β

t

Model 1-1 Intercept Sex Nation Age Auth Cred PD VC VI Auth × Nation Auth × Cred Auth × PD Auth × VC Auth × VI

2. Attitude towards brand

– .094 − .366 .067 − .270 .296 .103 .004 .111 .132 .067 .088 .038 − .067

– .099 − .010 − .010 − .264 .348 .223 − .057 .131 .125 − .004 .114 .026 − .057

β

Model 1-2 12.099⁎⁎⁎ 1.640† − 5.830⁎⁎⁎ 1.150 − 3.255⁎⁎⁎ 4.997⁎⁎⁎ 1.703⁎ .064 1.744⁎ 1.470† 1.145 1.502† .587 − 1.059

.102 – .103 − .337 .402 .197 − .062 .035 – .129 .090 .016 − .044 Model 2-2

17.526⁎⁎⁎ 1.608† − .148 − .156 − 2.986⁎⁎ 5.486⁎⁎⁎ 3.453⁎⁎⁎ − .811 1.930⁎ 1.296† − .059 1.818⁎ .379 − .840

– .174 – .040 − .265 .359 .250 − .102 .066 – .051 .120 − .052 − .031

t

Model 1-3 5.408⁎⁎⁎ 1.222 – 1.257 − 3.488⁎⁎⁎ 4.538⁎⁎⁎ 2.094⁎ − .638 .381 – 1.439† .985 .158 − .463

–

Model 2-1 Intercept Sex Nation Age Auth Cred PD VC VI Auth × Nation Auth × Cred Auth × PD Auth × VC Auth × VI

French sample t

8.260⁎⁎⁎ 1.024 – .335 −.453 2.468⁎⁎ .396 .823 1.828⁎ – .287 1.505† .566 −1.075

– .100 – .033 − .052 .249 .039 .081 .178 – .028 .147 .060 − .114 Model 2-3

7.674⁎⁎⁎ 2.025⁎ – .482 − 2.668⁎⁎ 3.948⁎⁎⁎ 2.592⁎⁎ − 1.028 .699 – .557 1.277† − .515 − .310

15.730⁎⁎⁎ −.063 – −.880 −.293 3.551⁎⁎⁎ 2.682⁎⁎ .375 2.241⁎ – −.744 1.515† 1.310† −.930

– − .006 – − .079 − .031 .325 .238 .034 .197 – − .066 .134 .126 − .089

Notes: †p b .10 (one-tailed); ⁎p b .05 (one-tailed); ⁎⁎p b .01 (one-tailed); ⁎⁎⁎p b .001 (one-tailed). Sex: male = 0, female = 1; Nation: USA = 0, France = 1; Auth: low = −1, mid = 0, high = 1. Model 1-1, Combined sample: R2 = .35; Adjusted R2 = .31; F13, 223 = 9.17; p-value = .000. Model 1-2, U.S. sample: R2 = .28; Adjusted R2 = .21; F11, 116 = 4.03; p-value = .000. Model 1-3, French sample: R2 = .19; Adjusted R2 = .10; F11, 97 = 2.13; p-value = .025. Model 2-1, Combined sample: R2 = .26; Adjusted R2 = .22; F13, 222 = 5.94; p-value = .000. Model 2-2, U.S. sample: R2 = .24; Adjusted R2 = .17; F11, 116 = 3.28; p-value = .001. Model 2-3, French sample: R2 = .35; Adjusted R2 = .27; F11, 96 = 4.60; p-value = .000.

In sum, a reverse authority effect was manifested most strongly on attitude towards ads among the young U.S. adults when effect of CRED is controlled for as shown in Fig. 2. Thus, H2 seems to be supported concerning attitudes, but not purchase intentions. 3.2.3. Credibility As expected, perceptions of source credibility positively influenced Aad (β = .30, t = 5.00, p b .001), Ab (β = .35, t = 5.49, p b .001), and INT (β = .20, t = 2.89, p b .01) for the combined data. The positive impact of credibility on attitudes was also significant among both American and French subjects when analyzed separately. To test our expectation that the reverse authority effect is likely to be attenuated for those respondents who view the spokespersons as more (vs. less) credible, we used both regression and ANOVA analyses. The Auth ⁎ Cred interaction term positively influenced Aad among the American subjects (βAuth × Cred = .13, t = 1.44, p = .076, one-tailed), but the

interaction term was not significant in other regression models. Next, participants were divided into low vs. high credibility groups using median value and then a 3 (Auth) × 2 (Cred: low vs. high) × 2 (Nation) ANOVA on Aad was run. 5 4.5 American

4

French

3.5 3 Low Auth

Mid Auth

High Auth

Fig. 2. Impact of authority and nation on Aad: based on adjusted means controlling for CRED.

J.M. Jung, J.J. Kellaris / Journal of Business Research 59 (2006) 735–744

Results show significant main effect of authority (Mlow = 4.26, Mmid = 4.12 Mhigh = 3.82; F2, 221 = 4.22, p = .01), credibility (Mlow = 3.78, Mhigh = 4.35; F1, 221 = 21.80, p = .000), and nation (MAmerican = 4.50, MFrench = 3.63; F1, 221 = 49.47, p = .000). The Authority × Cred interaction was approaching statistical significance (F2, 221 = 1.89, p = .15). The three way interaction term was not significant, implying a similar authority × Cred interaction pattern in both countries. Similar three-way ANOVA on Ab or INT were conducted, but the results were not statistically significant. Fig. 3 depicts an Auth ⁎ Cred interaction effect on Aad, which shows a stronger reverse authority effect for the low (vs. high) CRED group. In addition, a 3 (authority) × 2 (CRED) ANOVA on Aad, Ab, or INT was conducted for each country. Results revealed a significant main effect of CRED (Mlow = 3.33, Mhigh = 4.06; F1, 104 = 9.54, p = .003) and a significant Auth ⁎ Cred interaction effect (F2, 104 = 3.58, p = .03) on INT among French subjects with clear non-crossover disordinal interaction (similar, but more distinctive than Fig. 3). Thus H3 received partial support.

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5.5 5 Low PD

4.5

High PD

4 3.5 Low Auth

Mid Auth

High Auth

Fig. 4. The interactive influence of authority by power distance on brand attitudes (Ab) — French and U.S. combined data.

Auth ⁎ PD (F2, 235 = 2.34, p b .10). Auth ⁎ PD interaction effect was found to be more significant when the three-way ANOVA was run on Ab (F2, 234 = 3.24, p b .05), which is shown in Fig. 4. The three-way ANOVA model on INT was not significant. Thus ANOVA seem to provide provisional support for our expectations regarding a moderating effect of PD. 3.3. Discussion

3.2.4. Power distance As expected, PD positively influenced respondents' Aad (β = .10, t = 1.70, p b .05, one-tailed), Ab (β = .22, t = 3.45, p = .001), and INT (β = .15, t = 2.15, p = .03) for the combined data. The positive impact of PD was also significant among both American (p's b .05 except for INT, in which the model was not significant) and French (p's b .05 except for coefficient for Aad) subjects. To test our expectation that PD should attenuate reverse authority effect, we used both regression and ANOVA. Regression results show that PD did attenuate reverse authority effect on Aad (βAuth × PD = .09, t = 1.50, p b .10, one-tailed) and Ab (βAuth × PD = .11, t = 1.82, p b .05, one-tailed) but not on INT for the combined data set. The moderating effect of PD seems to be more consistent among French subjects (all three p's b .10, one-tailed) than American subjects (ns for Aad; p b .10, onetailed for Ab; regression model ns for INT). Thus, our expectations were met with mixed support. Next, subjects were divided into low vs. high PD groups via median split and then a 3 (Auth) × 2 (PD: low vs. high) × 2 (Nation) ANOVA on Aad was run. Results show main effects of PD (Mlow = 3.91, Mhigh = 4.21; F1, 235 = 5.97, p = .02), nation (MAmerican = 4.46, MFrench = 3.66; F1, 235 = 44.00, p = .000), and interaction effect of Auth ⁎ Nation (F2, 235 = 3.06, p b .05) and 5 4.5 Low Cred

4

High Cred

3.5

The data for the study 1 were collected about one year before the 9 / 11 calamity, an event that highlighted national security, authority of government, and compromise of personal freedom for the greater good. The calamity and aftermath may have made people more sensitive to the importance of national security and more willing to accept the infringement of personal freedom and human rights by benevolent (domestic) authority. As a result, people may have become more likely to accept intervention by the authorities: e.g., security checks in airports. Does this mean that PD may have shifted upwards across different sectors of society, resulting in a possible attenuation of reverse authority effects among young adults? A longitudinal study is needed to answer this inquiry. Study 2 was conducted almost two years after the 9 / 11 tragedy, using the same design as study 1, but with different subjects of the same age group. 4. Study 2 4.1. Subjects, design, and procedure Data were collected in 2003, three years after study 1 and two years after the 9 / 11 disaster. Participants were 169 undergraduate students enrolled in marketing classes in the U.S. Study design was similar to that used in study one: between subjects, using two ads (yogurt and software) to represent each of three (low, mid, high) authority conditions. Independent and dependent variables were identical to those in study 1. 4.2. Results

3 Low Auth

Mid Auth

High Auth

Fig. 3. Impact of authority and credibility on Aad — French and U.S. combined data.

To examine changes in responsiveness to authority appeals over time among U.S. participants, we again used regression, supplemented by ANCOVA to shed light on regression results. The same regression procedure explained in study 1 was followed.

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J.M. Jung, J.J. Kellaris / Journal of Business Research 59 (2006) 735–744

Regression analyses revealed that reverse authority effect was not present among the post 9 / 11 American participants (p's N .40). A one-way ANCOVA of authority on Aad with Cred as a covariate also confirmed the regression results (Mlow = 4.57, Mmid = 4.51, Mhigh = 4.55; F2, 165 = .12, p N .10). In comparing American subjects across time periods, we first notice that the two groups were not statistically different in their ages (21.9 vs. 22.4 yrs), work experience (6.1 vs. 6.3 yrs), or sex composition (male/female: 61%/39% vs. 62%/38%). Further, multiple groups CFA shows evidence that PD is invariant across the two groups. Due to evidence of measurement invariance across time, standardization within each sample is omitted and the two data sets were combined prior to regression and ANCOVA analyses. To see if the reverse authority effect is reduced over time, we first ran multiple regression analyses as in study 1. We observed a significant Auth (low/mid/high) ⁎ Time (2000/2003) interaction effect on Aad (βAuth × Time = .24, t = 3.15, p b .001, one-tailed) and Ab (βAuth × Time = .21, t = 2.68, p b .01, one-tailed), supporting our speculation. Next, we ran a 3 (Auth) × 2(Time) ANCOVA on Ads with CRED as a covariate. We found a significant Auth ⁎ Time interaction (F2, 292 = 6.67, p = .001; refer to Fig. 5), which corroborates regression results. Thus, the analyses present evidence of a change in response to authority appeals across time periods in the anticipated direction. To see if PD changed over time, we first compared latent variable PD in a multiple CFA model. PD is greater in 2003 U.S. sample than in 2000 U.S. sample (p b .001). Due to the measurement invariance, we directly compared mean composite scale score; large two independent samples Z-tests indicate statistically significant changes in the American cultural values between time 1 and time 2. At least within our samples in the three year span, PD has increased from 3.67 (SD = 1.14) to 4.16 (SD = 1.15) with Z = 3.67 (p b .001, two-tailed). Thus our speculation concerning cultural change was confirmed. 4.3. Discussion We observed no authority effect among Americans at time 2. We suspect that the most significant contributor to this change would be an increase in power distance attendant to the 9 / 11 calamity. We further suspect that the 9 / 11 calamity may have elevated the perceived importance of governmental effort in

5.5 5 2000

4.5

2003

4 3.5 Low Auth Mid Auth High Auth Fig. 5. The influence of authority in two time periods on Aad: based on adjusted means controlling for CRED.

national security and authorities in charge of the job, shifting PD to higher levels among young adults. Our speculation was supported by the observed increase in PD across time periods. As people united under the causes of defending freedom and fighting terrorism, they may have become more receptive to the idea of personal sacrifice for the common good (e.g., standing in long lines for airport security checks or compromising privacy and freedom in the Patriot Act), which would have elevated their sense of respect for authority. 5. Summary This research examined authority effects experimentally in a consumer advertising context using a cross-national sample of young consumers from France and the U.S. Results of study 1 show a reverse authority effect across two cultures, with a stronger effect among American (vs. French) participants. Both perceptions of spokesperson credibility and power distance positively influenced attitudes and purchase intentions. Furthermore, credibility appears to moderate the impact of authority on attitudes and intentions. Most interestingly, power distance moderated authority effects among both nationalities. Study 2 shows that the reverse authority effect observed before 9 / 11 disappeared among post 9 / 11 Americans. In addition, compared to Americans in time 1, those in time 2 exhibited a higher power distance. 6. Theoretical and managerial implications To the best of our knowledge, this study is the first to examine the authority principle cross-culturally in an advertising context. By introducing national culture and individual level cultural values in explaining authority-based influence attempts, we shed light on how membership in a culture and a person's individual cultural values interact to form attitudes and purchase intentions. Specifically, we show that power distance at the level of an individual is important in understanding variations within a culture. In fact, individual-level power distance allowed us to predict attitudes and purchase intentions consistently within each culture: the higher (lower) power distance, the more (less) effective the authority based influence attempt. Thus, future studies that involve authority appeals should consider power distance and the interaction of PD with other possible influencers. Our research suggests that caution should be taken in predicting authority effects in specific segments of the market that might undergo drastic cultural shifts that could have positive or negative impact on the direction of authority appeals. In either case, our study suggests that prediction would be enhanced if we detect the direction of a PD value shift. For example, whereas downward shifts in power distance would predict a greater likelihood of reverse authority effects, upward shifts would predict greater likelihood of positive authority effects. Our study also presents advertisers with some provisional implications. Results imply that the classic authority principle is not likely to be effective in all the segments of the market.

J.M. Jung, J.J. Kellaris / Journal of Business Research 59 (2006) 735–744

Marketers need to know whether or not authority sources will have a positive impact on their target segments. This caution will be especially relevant for marketers who target young or adolescent consumers who view low authority figures more favorably. Additionally, our results enlighten marketers contemplating authority-based ads in countries with different perceptions of power distance. Marketers in multi-national companies should not blindly rely on country level power distance scores; instead, they should examine the effectiveness of authority country by country, segment by segment, and adopt a different level of authority as appropriate.

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our findings using different authority figures that are less vulnerable to the nature of relationships. The present research documents cross-cultural variations in reverse authority effects among young adults in two cultures. Further investigation is required to explain the underlying source of such effects, as well as the circumstances under which one can expect positive versus negative effects of authoritybased appeals. We offer the present findings in hope of fueling wider interest in this topic and commend on-going investigation to future research. Appendix A. Test ads

7. Limitations and future research directions Despite insights gained from this study, several unanswered questions remain. Limits to generality stem from the demographic composition of our sample. We used university students, whose relative youthfulness may be a contributing factor to the reverse authority effect. Future study can include subjects from diverse age, income, education, and occupational groups. According to Hofstede (2001), education and occupation are negatively correlated with power distance. Thus, their impacts on authority appeals should be examined. Second, we argued that the 9 / 11 calamity might have caused a shift in cultural values, which might have caused a more positive orientation to authority and authority-based influence attempts. We propose that the observed differences represent a zeitgeist effect (all members' shift in value due to radical system-wide change in society). However, we acknowledge that our observations are not immune to the influence of unknown, extraneous variable(s). Third, the observed effects may stem from the specific nature of the relationships among speakers represented in the simulated ads. That is, subjects' reactions may have stemmed from specific attitudes towards parents and teachers (the nature of relationships), rather than to “authority figures” in general. Future study might attempt to corroborate

Ad #1: Imagine a radio advertisement in which (a mother/one woman/a daughter) is speaking to (her daughter/another woman/her mother). She tells her about “Soiegourt,” a new brand of yogurt. She says that it comes in a variety of interesting flavors, that it has fewer calories than Yoplait, but that it tastes richer. It sells for about the same price. At the conclusion of the ad, of course, (the mother/she/the daughter) recommends that (her daughter/the other woman/her mother) try the new brand. “I tried it last week and it was great!” Ad #2: Imagine a radio advertisement in which (a teacher/one person/a student) is speaking to (a student/another person/a teacher) about a new software product called “MicroPass-2000.” This product is designed to manage multiple passwords (mots de passes). It works in conjunction with other software products such that a user need remember only one password for all applications. It is easy to use and the cost is surprisingly low. At the conclusion of the ad, of course, (the teacher/the speaker/the student) recommends that (the student/the other person/the teacher) consider buying this software — “I installed MicroPass on my home PC and it works great!” Ad #3: Finally, please imagine a radio advertisement in which (a boss/one employee/a subordinate) is speaking to (his subordinate/another employee/his boss). He tells him about an internet site at which clothing can be purchased: www.smartdress.com. The site features name-brand clothing at discount prices, delivered to your home or office at no extra charge. All items are guaranteed. At the conclusion of the ad, of course, (the boss/he/the employee) recommends that (his subordinate/the other employee/his boss) visit the site — “I did and I think you'd love it.” Inside parenthesis indicate the power distance, either “high” “mid,” or “low” authority conditions, respectively.

Appendix B Power distance scale: scale items retained, factor loadings, CFA model fit statistics, and reliabilities (N = 248)

1. I find it difficult to disagree with someone in a higher position than mine. + 2. It is difficult for me to express my opinions to superiors. + 3. If a boss doesn't ask for my comments, I would rather keep silent. + 4. I tend to conform to the wishes of someone in a higher position than mine. 5. It is difficult for me to refuse a request if my superior asks me. 6. I tend to give priority to the opinions of people in authority. 9. I tend to find it hard to disagree with authority figures. % Variance explained Cronbach α

Combined sample (N = 248)

U.S. sample (N = 130)

F1

Lx

F1

Lx

F1

Lx

.71

.64

.75

.68

.67

.58

.77

.70

.80

.73

.73

.64

.71

.66

.72

.68

.67

.62

.85

.81

.88

.88

.83

.83

.72 .74

.67 .69

.72 .74

.68 .68

.70 .73

.65 .70

.68

.60

.79

.75

.62

.53

55.02% .86

59.80% .89

French sample (N = 118)

50.54% .83 (continued on next page)

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Appendix B (continued) Data set

χ2

df

p

χ2 / df

RMSEA

GFI

AGFI

RMR

CFI

IFI

|SR| N 2

Combined sample American sample French sample

66.35

14

.000

4.74

.12

.93

.86

.13

.92

.93

None

45.46

14

.000

3.25

.13

.91

.82

.12

.93

.93

None

34.24

14

.002

2.45

.11

.92

.85

.16

.93

.93

None

Three scale items denoted as + are adopted from pretest 6 of Jung (2002). F1 = Factor loadings from principal component analysis of seven-point Likert-type scale items. Lx = Standardized factor loadings from CFA. |SR| stands for absolute value of standardized residual.

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Journal of Business Research 59 (2006) 745 – 754

Cross-advertisement affectivity: The influence of similarity between commercials and processing modes of consumers on advertising processing Ingrid Poncin a,⁎, Rik Pieters b , Michele Ambaye c a

Lille Graduate School of Management, Département Marketing-Vente, Avenue W. Brandt, 59777 EURALILLE, France b Universiteit van Tilburg, The Netherlands c Brunel University, United Kingdom Received 1 April 2005; received in revised form 1 November 2005; accepted 1 January 2006

Abstract Due to the increasing brand and product parity and the soaring volume of advertising, not only may products be increasingly similar, but commercials for products may become similar as well. Moreover, commercials frequently appear closely together in pods within and between programs, increasing the likelihood that they influence each other. The question thus becomes if and how the various commercials in pods and their affectivity “cross” influence each other, and what the influence of the similarity between commercials is on advertising processing and effectiveness. Extending assimilation–contrast theory, we find substantial context effects of the ad sequence in the affective reactions elicited by commercials presented in the same pod. The importance of the similarity between commercials as perceived by consumers, and of the interaction between this similarity and the consumers' processing modes during ad exposure are demonstrated. The findings contribute to a better understanding of context effects due to the sequence in which ads appear, and of the role of ad similarity. © 2006 Elsevier Inc. All rights reserved. Keywords: Cross-advertisement effects; Perceived similarity; Affective reaction; Sequence effects; Processing mode

1. Introduction Due to heavy competition in many mature markets, products and brands are increasingly at par, sharing many attributes and features, which may prompt price reductions and other promotional tools pressuring profit margins and the long-term marketing viability. Emotional advertising is frequently used to differentiate such similar products and brands (Rossiter and Percy, 1997), to stop and change the downward profit contribution spiral. However, the frequent use of emotional advertising may in fact have led to the situation that not only products and brands, but also their communication tools become at par, the latter at least with respect to their affectivity. This situation is even aggravated because television commercials, the dominant communication tool in most consumer ⁎ Corresponding author. Tel.: +33 320 215 996; fax: +33 320 215 959. E-mail address: [email protected] (I. Poncin). 0148-2963/$ - see front matter © 2006 Elsevier Inc. All rights reserved. doi:10.1016/j.jbusres.2006.01.012

markets, appear in pods or sets within and between programs, prompting immediate comparisons of commercials and the brands and products that appear in them. This makes it important to understand how ad-evoked feelings influence advertising responses and if and how the affectivity of commercials affects each others processing responses. Quite surprisingly however advertising research appears to have emphasized the influence of television commercials in isolation (Brown et al., 1998). Because the influence of the (other) surrounding commercials in a given sequence is not taken into account, it is not obvious if and how the results of such studies can be generalized to the common situation that ads appear in blocks, and thus when the affectivity of earlier ads might influence the processing and effectiveness of later ones. It is not unlikely that earlier ads might create an affective climate for the later ads in the same sequence. This climate may enhance or reduce the persuasive effects of those advertisements (Brooker, 1981). The advertising surrounding any particular ad

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is, in fact, a key context for that particular ad. Additionally, according to Kent (1993) exposure to competitive clutter appears to have a more damaging impact on ad effectiveness than exposure to ads for non-competing brands. In fact, similar products and similar advertising appeals may generate brand confusion, which in turn can lead to an increase in sales of a competitor's instead of the advertiser's brand. It thus becomes important to avoid brand confusion by examining its possible determinants (De Pelsmacker et al., 2001). Therefore, some network policies provide assurance that ads for direct competitors will not appear in the same pod (sequence) of commercials. Whether such policies are relevant is not clear due to the lack of empirical research on cross-advertisement effects and the role of ad similarity. Our research focuses on the impact of the affectivity of preceding commercials on affective reactions elicited by subsequent neutral (non-emotional) commercials in pods. These latter commercials may be low or high in perceived similarity with the first ad, and we examine the influence of such similarity on ad processing and effectiveness, as measured by attitude toward the ad (Aad). In the conceptual analysis, we will argue that the influence of commercial similarity depends on the specific processing modes that consumers adopt during ad exposure. If we were indeed to find cross-advertisement effects, this would have implications for pretesting practice, among others. Frequently, copy testing is carried out either with a single commercial or in a “random” sequence of commercials. If the preceding ads create a context which influences the affective reactions induced by the subsequent ads, the validity of the pretest results and their diagnostic value are at stake. In fact, we have no guarantee that the affective reactions produced by pretest contexts are equivalent to the reactions caused by the final context. Thus copy testing in isolation might not necessarily be optimal. One solution then, on which we elaborate later, might be to test ads in the context of other ads with a known affective performance. Further, it would then also be useful to test them in different contexts to examine their malleability under different affective ad environments. But let us first examine why and how cross-advertisement effects of affectivity might arise, and how we explored their effects. 2. Cross-advertisement effects of affectivity Little is known about cross-advertisement effects of affectivity, but we do know more about the related issue of program context effects, and we draw on this literature first (Aylesworth and MacKenzie, 1998; Coulter, 1998; Goldberg and Gorn, 1987; Kamins et al., 1991; Pavelchak et al., 1988; Schumann, 1986; Shapiro et al., 2002; Yi, 1990; Tavassoli et al., 1995; De Pelsmacker et al., 2002). With respect to programelicited feelings (Goldberg and Gorn, 1987; Pavelchak et al., 1988; Coulter, 1998), two important dimensions of the affective reactions induced by a program have to be examined: the intensity of the reactions induced (sometimes termed “arousal”, Singh and Hitchon, 1989) and the valence/quality/polarity of the affective reactions (i.e., the pleasantness or pleasure

dimension). In line with previous research, and in view of the dominance of positive emotions in advertising, we focus on positively valenced emotional advertising, and examine the influence on advertising processing of variations in affective intensity, from absent, in case of an affectively neutral commercial to intense, in case of an intensely positive emotional commercial. Does positive affect, induced by the program context (or earlier commercials), improve subsequent ad processing? Both consistency and congruency theory (Pavelchak et al., 1988; Singh and Hitchon, 1989) would predict that experiencing positive feelings due to a program enhances recall, positive affective reactions triggered by the ad, ad liking and subsequent attitudes. In support of this, Aylesworth and MacKenzie (1998) observed that television ad processing was better when people were in a positive mood after seeing a program. Likewise, Goldberg and Gorn (1987) found that happy compared to sad TV programs increased the effectiveness of embedded commercials, for instance, because they were recalled better and produced higher purchase intent. Additionally, Coulter (1998) has examined the effects of emotional responses to television programming (program-induced affective reactions) on the attitude toward the ad (Aad). He found that emotional responses to the ad moderate the relationship between program liking and Aad. Moreover, the program liking–Aad linkage is strengthened if the ad and program are similar in emotional content. These findings show that program-induced positive affect has a systematic assimilative or transfer effect on various attitudes and behaviors with respect to commercials embedded in the program. In contrast, two opposite predictions emerge about the possible influence of affective intensity of program context on advertising processing, which may generalize to cross-advertisement affectivity effects. First, the negative effect hypothesis postulates that high involvement, or arousal in a program, reduces the ability of viewers to process and recall advertisements that appear in the program context. In a study that compared consumers' reactions to ads during the Super Bowl, Pavelchak et al. (1988) found that when the program is too arousing, it has a negative effect on ad and brand recall. In fact, ad responses in the winning city were inhibited in contrast to those in the losing and neutral cities. An opposite prediction can also find support: the positive effect hypothesis. According to this idea, commercials are more effective when viewed in highinvolvement programs, because the high program involvement and the associated arousal transfers to the advertisements, in line with excitation transfer theory (Zillmann, 1971). In fact, the arousal produced by a program might even be misattributed to the embedded commercial as long as the viewer is not aware of the source of the arousal. Thus, according to this positive effect perspective, “commercials embedded in exciting program segments can be expected to demonstrate increased learning (recall and recognition) relative to commercials embedded in bland program segments” (Singh and Hitchon, 1989, p.24). To reconcile these two opposing perspective on program context effects on commercial effectiveness, Tavassoli et al. (1995, p.64) propose an inverted-U relationship arguing that “it is possible that some studies manipulated involvement/arousal on the ascending part of the inverted-U-curve (i.e., comparing

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low to moderate levels of program involvement) while others manipulated the descending part (i.e. comparing moderate to high levels)”. There is some speculation and empirical investigation about the interactive effects of polarity and intensity of affective reactions. These speculations have concentrated on the emergence of assimilation versus contrast effects, which we believe to be important for the present research. For instance, Broach et al. (1995) predicted a two-way interaction between program-induced arousal and pleasantness. According to those authors, a high-arousal program should produce an assimilation effect, whereby viewers shift their evaluations of subsequent commercials (i.e., the target) in the direction of their evaluation of the program (i.e. the stimulus). Thus, if the program were pleasant, the commercials would be viewed as pleasant. If however the program were unpleasant, the commercials would be viewed as unpleasant. On the other hand, a low-arousal program should produce a contrast effect whereby viewers shift their evaluations of subsequent commercials in the direction opposed to their evaluation of the program. Thus if the program were pleasant, the commercials would be viewed as unpleasant; if the program were unpleasant, the commercials would be viewed as pleasant. To prevent any interaction effects between program and affective reactions induced by the ad-itself, they used emotionally neutral commercials to test their hypothesis. The mean commercial pleasantness value for the pod of commercials in the high arousal pleasant program condition was significantly higher than that in the high arousal unpleasant program condition. Furthermore, the mean commercial pleasantness value in the low arousal unpleasant program condition was significantly higher than that in the low arousal pleasant program condition. Thus, the hypothesis was supported since high arousal programs produced an assimilation effect where commercial evaluations were enhanced after pleasant programs and depressed after unpleasant programs. Conversely, low arousal programs produced a contrast effect whereby commercial evaluations were enhanced after unpleasant programs and depressed after pleasant programs. While quite some research has examined program context effects, little is known about ad context effects in advertising (see Broach et al., 1997; Pieters and Bijmolt, 1997; Zhao, 1997). Aaker et al. (1986) suggested and found initial empirical evidence that affective reactions to eliciting stimuli are influenced by the sequence in which they are seen. We build on this work here. Specifically, we base our predictions about cross-advertisement affective effects on the assimilation– contrast theory (Sherif and Hovland, 1961). In the following sections, we present recent developments in this theory that may lead to a better understanding of sequence effects, and we propose specific predictions to be tested in the empirical part.

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psychological scale for judgment. Henceforth, judgment of related stimulus is made in terms of the categories of this reference scale”. Therefore, social judgment views an attitude as consisting of a continuum of evaluations: a range of acceptable positions, unacceptable positions and positions toward which the individual has no strong commitment. In fact, assimilation and contrast are judgmental distortions, i.e., perceptual biases resulting from the tendency to perceive phenomena differently as a function of the reference scale (i.e. the context in which they are judged). Assimilation is the displacement of the judgment toward the anchor (reference scale) (i.e. the judgment that the stimulus is more similar to the anchor than it actually is). In contrast, there is the displacement of the judgment away from the anchor (the perception that the difference between the stimulus and the anchor is greater than it actually is). Developed in a cognitive judgment context, this theory has been recently applied in a more affective context (McMullen, 1997; Abeele and Gendolla, 1999). According to McMullen (1997), an affective contrast effect occurs when an individual's affect is displaced away from the valence/polarity of the reference stimulus. In contrast, an assimilation effect happens when the individual's affect is displaced toward the valence/ polarity of the reference stimulus. In line with this, Abeele and Gendolla (1999) define assimilation effects in terms of mood congruency, such that people in a positive mood make more positive judgments than people in a neutral mood, who in turn make more positive judgments than people in a negative mood. Consequently, assimilation effect led people in a more positive mood to make more positive judgments. In an important study, Stapel and Winkielman (1998, p.634) clarified “Our feelings and evaluations are experienced contextually and thus determined by their relationships to other affects and judgments. The context in which a target stimulus is embedded provides a frame of reference for interpretation and judgment. Hence, the same target can be associated with different responses depending on the context in which it is judged.” Likewise, the same commercial may be associated with different responses depending on the context in which it is judged. In our research, the context is created by the other commercials in the pod. These commercials might influence the affective reaction induced by a specific commercial. We speculate that strong positive affective reactions elicited by a previous commercial in the pod are likely to fade into a positive mood that, in turn, enhances the probability of elicitation of positive affective reactions (Davidson, 1994) and the subsequent evaluation. In the case of neutral or ambiguous commercials for the affective point of view following a strong emotional ad, the assimilation effect is likely to be highly relevant. 2.2. Perceived similarity and assimilation contrast effects

2.1. Assimilation and contrast in cross-advertisement affectivity effects According to Sherif and Hovland (1961, p.179) “an individual confronted with a series of stimuli tends to form a

In a non-advertisement context, Abeele and Gendolla (1999) showed that the use of a reference stimulus such as a standard of comparison produces a contrast effect. Yet, assimilation effects may occur when the reference stimulus induces a specific mood,

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which serves as reference frame for subsequent judgment. In advertising, a specific commercial might induce a positive mood, inducing more positive affective reactions and judgments for subsequent commercials: assimilation. They found that this assimilation effect is stronger in the case of a low thematic similarity between the mood-inducing event (in our case the first commercial) and the judgmental issue (the second commercial (non-emotional). Conversely, in case of high perceived similarity (for instance when the two commercials are from the same product category), the first event (in our case the first commercial) is used as standard of reference to evaluate the second commercial to carry out a contrast effect. In fact, Abeele and Gendolla (1999) demonstrated that assimilation and contrast effect are not mutually exclusive, but rather they are concurrent processes, and thus what is observed is the net effect of the two processes (assimilation effect–contrast effect). Building on this, we predict that in case of low thematic similarity between two commercials in a sequence, a stronger assimilation effect occurs. This stronger assimilation may be between the affective reactions elicited by the first commercial and the affective reactions elicited by the second commercial. In fact, in the case of high similarity between commercials, the possibility to compare the two commercials should favour a contrast effect to occur. This leads to our first hypothesis, namely that if a neutral ad is preceded by a positive emotional ad, but has only low perceived similarity, the second ad will induce more positive affective reactive reactions and will appear more positive in terms of Aad, compared to those with high perceived similarity between the two ads. There is reason to believe that the occurrence of crossadvertisement affectivity effects depends on the processing mode that consumers are into while being exposed to the commercials, and to this topic we turn next. 2.3. Processing modes of consumers Sometimes, consumers during ad exposure focus on the experiential, hedonic qualities of the advertisements themselves, sometimes they are prompted to compare the ads on their merits, and sometimes they desire to memorize the ads, among others. These are examples of processing modes or processing goals, i.e., the specific tasks that consumers are engaged in during exposure to advertising. In 1999, Meyers-Levy and Malaviya proposed a framework describing three fundamental processing strategies that are relevant here. “When the level of mental resources a message recipient allocates to message processing is substantial, moderate or minimal, judgment formation proceeds through a systematic, heuristic or experiential strategy respectively.” In fact, in the majority of processing conditions, the amount of cognitive resources that people are willing or able to devote to processing is so meager, that only the most fleeting and scant message processing occurs. In such cases, the resources people allocate to processing are therefore minimal and they may be unable to attend to any substantive or even superficial content of the message, as they would if a heuristic strategy were employed. Rather, people are

more likely to pay attention to sensations or feelings that might be generated from the process of dealing with the advertisement or from the advertisement itself (Meyers-Levy and Malaviya, 1999). On the one hand, the experiential mode or more affective mode might be considered as the case of the “peripheral processing” of the ad. On the other hand, in the case of evaluative mode, more important resources are allocated and the processing of the ad will be systematic. In this latter case, the consumer focuses their attention on important and diagnostic aspects of the message and, therefore, the ad's evaluation is more cognitive. McMullen (1997) found support that assimilation is more likely to occur when consumers are in an experiential mode because they are focusing on their immediate affective reactions to the mental simulation. 2.4. Ad processing mode and assimilation contrast theory In the case of the evaluative processing mode, more cognitive processing of the ad is expected, which is likely to reduce the affective reactions elicited and might result in a more systematic comparison between the commercials. Consequently, the context – the preceding ads – is more likely to be used as a comparison standard and therefore a contrast effect between the ads. Meyers-Levy and Malaviya (1999) mention the phenomenon of judgment process correction, which might be related to the contrast effect. In some circumstances people will attempt to correct their initial assessment for biases that they perceive. Three conditions need to be met: First the message recipient must become aware that the contextual data may have influenced his/her views about the persuasive message inappropriately. This occurs because salient features of a judgment task or communication context bring the influence to mind. Secondly, the person must be able to identify a naïve theory that might account for why, how and to what extent the biasing data could have this effect (Petty and Wegener, 1993). Thirdly, the message recipient must possess and be willing to expand the cognitive resources required to engage in a correction process (Martin et al., 1990)). In most cases however, the influence of the biasing source on judgments is believed to be assimilation (Martin and Achee, 1992). If any of the required conditions are not met, the presumably spontaneously occurring assimilation effect of context on people's initial judgments remains intact. Moreover if such conditions are met, people will attempt to screen out the inappropriate influence on their initial assessment. Yet, because the process of correcting and screening out bias is imperfect and presumably prone to over-adjustment, a contrast effect may occur. If this is the case, people's updated judgments become fairly extreme and appear to be the opposite direction of the interpretation implied by the contextual data (Martin and Achee, 1992). Therefore, if the consumer thinks that the context biases her evaluation or alters the evaluation to be more positive, she will try to correct this bias by updating her evaluation as more negative. When the processing mode is experiential, affect will dominate. Consequently, the affective context created by the

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preceding commercials is more likely to be used as frame of reference and is likely to influence the quality of the affective reactions perceived as congruent. Therefore, some assimilation effects are expected between the affective reactions elicited by commercials aired in the same pod. These assumptions are in line with the predictions made by McMullen (1997). As was previously mentioned, the essential determinant of the processing mode is the amount of cognitive resources that the consumer is able and motivated to allocate. Therefore, in the everyday advertising context, the consumer is expected to be in an experiential mode most of the time. However, in some specific situations (i.e. situational involvement in a product category, pre-test situation…), the consumer might be in an evaluative mode. For instance, in television copy testing consumers may frequently be in an evaluative mode or systematic processing mode stimulated by the task, the environment, and the fact that they are paid to “judge” commercials. De Pelsmacker et al. (2001, p.229) point out that “most pre-tests take place in an experimental setting. Consumers may behave fundamentally differently when exposed to an ad in a real-life situation. Hence, some pre-test methods, especially the explicit ones such as direct rating method, are susceptible to consumer jury effects.” Therefore, the difference between these two contexts (everyday life versus copy testing) may lead to systematic differences in the affective reactions of consumers to commercials. If this occurs, the validity of pre-testing practices may be in serious doubt. Moreover, it might have implications when ads for directly competing products are included in the same pods. In short, in some contexts, the affective reactions to the commercial might be assimilated or contrasted with the reactions to other commercials aired in the same pod. We anticipate that the use of the experiential mode for processing will lead to more assimilation between the affective reactions elicited by the two commercials in comparison with the use of more systematic processing (evaluative mode). This leads to the second hypothesis to be tested: When the processing mode is experiential, a neutral ad preceded by a positive emotional ad will induce more positive affective reactions and will appear more positive in terms of Aad, compared to an ad which is considered by an evaluative mode. The strongest assimilation effect and the weakest contrast effect are expected, in the case of an experiential mode of ad-processing and low affective/content perceived similarity. The strongest contrast effect is expected in the case of an evaluative mode and high-perceived similarity. At this stage, two main effects are predicted: one for perceived similarity and one for processing mode. Although it is more speculative, an interaction effect between mode and perceived similarity is likely, such that the effect of perceived similarity might be influenced by the processing mode. When perceived similarity is high, the evaluative mode might lead to a stronger contrast effect. When perceived similarity is low, the mode of processing might be less effective. Therefore, we propose that the positive affective reactions induced by a neutral commercial will be more intense (higher) in case of assimilation effect with the preceding emotional commercial. We predict that the attitude toward the neutral ad (Aad) will be more positive in

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comparison with the Aad score for the same commercial when aired alone or in a condition where a contrast effect between the two ads is expected. This leads to the third hypothesis to be tested, namely that in the case of the experiential treatment mode in an ad, if a neutral ad is preceded by a positive emotional ad which shares low perceived similarity, the second ad will induce more positive affective reactions and appear more positive in terms of Aad. This is opposed to the case where commercials might be highly similar and are processed in an evaluative mode. Support for the three hypotheses would demonstrate the importance of cross-advertisement affectivity effects, and would show how the affect evoked by earlier ads may increase or decrease the effectiveness of subsequent ads, under specific but very common situations, namely depending on the similarity of the ads and the processing modes of the consumers. In the following sections, the design and the results of a controlled experiment to test these predictions are described. 3. Methodology Laboratory conditions seemed especially suited, due to the need to examine the causal relationship between the ad processing mode, perceived similarity and the changes observed in the affective reactions induced by the commercials. Moreover, a high level of control was required to correctly assess the respective importance of each variable and limit the importance of extraneous variables. 3.1. Pilot study results A pilot study was carried out with 20 students who rated the degree to which they perceived 6 different commercials as being similar or dissimilar to each other We asked participants to globally judge the perceived similarity between the two commercials (very dissimilar versus very similar). Then we asked them to identify which aspects they concentrated on to make this judgment. Finally we asked them to judge the perceived similarity of several specific characteristics such as product category, affective reactions elicited, ad-type…. During this pilot study, it was noted that consumers used different dimensions to judge the similarity between two ads. Belonging to the same product category is a necessary, but insufficient, condition. The duration, the ad-thematic characteristic, as well as other characteristics, might help to make this judgment. Based on this first result, two pairs being perceived as the most similar, and two pairs perceived as the most dissimilar, were selected. Each of the chosen commercials was also pilot-tested with 20 other participants to evaluate the commercial's ability to elicit affective reactions when aired alone. This method of ad-testing ensures a low variance between the affective reactions elicited by the same ad for the different consumers (homogeneity response of the consumer responses). It also allows the possibility of checking the high variance in the intensity of the affective reactions induced by commercials — described as being emotional versus neutral. Finally, several pilot studies were conducted with other consumers in order to confirm the

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understanding of the instructions used to manipulate the way of processing commercials and to check the understanding of the final questionnaire (see Appendix for the instruction used to manipulate either the experiential mode or evaluative mode). 3.2. Design of the experiment The design used in this study is a “between-consumers” design: a 2 × 2 (experiential mode versus evaluative mode and low versus high perceived similarity), replicated twice. Each block of commercials was designed to present a neutral commercial followed by a strong positive emotional commercial. This, in turn, was followed by either a neutral testcommercial, pilot-tested as being perceived similar to the emotional commercial, or a neutral commercial pilot-tested as being perceived as dissimilar to the preceding emotional commercial. The use of repeated measures in the design, with two sequences of different commercials, allows the possibility of ruling out idiosyncratic effects resulting from the specific characteristics of the ads. Each participant was randomly assigned to one experimental condition and individually exposed to two strings of three commercials. 3.3. Stimuli The stimuli were six 30 s TV commercials. Originally aired in Switzerland, they were unknown in Belgium and advertised unknown brands, therefore removing the concern of a differential familiarity with the stimuli. As in the pilot study, the ads that were judged as being similar were ads that belonged to the same product category. 3.4. Measures and sample In line with previous research in emotion and advertising (Brown et al., 1998), emotional responses were collected using verbal measurements composed of an adjective list of affective reactions. Attitude toward the ad was measured with a simple two-item scale as used by Derbaix (1995). Measures of manipulation effectiveness were added as well (processing mode and perceived similarity). A sample of 60 undergraduate students across academic disciplines at a Belgian university participated in the study. Students are huge TV-media consumers and therefore an ideal target. In addition, the product categories chosen for the different commercials (a travel agency and a soft drinks company) were well-known to them. Participants were randomly assigned to the four cells of the two (high-low similarity) by two (processing mode: evaluative vs. experiential) between-subjects design. 4. Results 4.1. Manipulation checks First of all, checks were performed on the manipulated variables. We examined the perceived similarity between the

commercials and checked the processing mode (used by the participants in the different conditions). On the one hand, two groups (Group 1 and Group 2) needed to be in a condition where perceived similarity would be expected between the emotional commercial and the neutral test commercial. Conversely, perceived dissimilarity was expected in the two other groups. To check if the ads used were perceived as expected, we used a similarity measure. The test (F(1, 55) = 4.62, p b 0.05 (one tailed)) showed that commercial X1 was perceived as more similar to commercial Y1 than to commercial Y2. Similarly, the test (F(1, 55) = 5,65, p b 0.05 (one tailed)) confirmed that commercial X2 was perceived as more similar to commercial Y2 than to commercial Y1, as expected. Therefore we concluded that the check of the perceived similarity supports the initial expectations. On the other hand, the question that tapped the processing mode of the participants during exposure to the commercials was related to the attention to information versus emotion during the ads. One can expect that participants in an experiential mode pay more attention to the emotions compared to participants in an evaluative mode, who are expected to pay more attention to information. The observed means in the different conditions were in the expected direction and the main effect of the processing mode was statistically significant F (1, 55) = 5.52; p b 0.05 (one tailed). Thus, the similarity and processing mode manipulations were effective. 4.2. Effects on affective reactions In order to test our prediction, the main effects of similarity and mode and their interaction on both positive and negative emotions need to be examined. If the theory is supported, we would find significant main effects and an interaction between processing mode and perceived similarity, but only for positive emotions. As expected, for the negative affective reactions, no main effects were observed for either similarity or processing mode. Positive affective reactions elicited in the case of dissimilarity were more intense than in case of similarity. Perceived similarity therefore has an impact in the expected direction. The positive emotions elicited in the evaluative condition appear to be more important in comparison with the experiential condition, which is the reverse of what was expected. However, the dependent measures show only a significant main effect for perceived similarity F(1, 53) = 14.06; p b 0.001 (one tailed). But neither the main effect of a mode, nor the interaction effect of similarity by processing mode is statistically significant. Only the first hypothesis is validated. 4.3. Effects on the attitude toward the ad (Aad) Attitude toward the ad (Aad) was tapped with a two-item scale following a check of internal consistency (α = 0.74 and 0.81), and a single score for Aad was computed. First, we detected heterogeneity between the two replicates (F(1, 53) = 4.28; p b 0.05 (one tailed)). This result might be due to specific characteristics of one or both neutral test

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Table 1 Observed means and MANOVA results

Sequence 1 Similarity Dissimilarity

Sequence 2 Similarity Dissimilarity

Positive affective reactions

Attitude toward the ad (Aad)

Min = 7, Max = 49, a higher value meant that the affective reactions were more positive. One tailed tests were used.

Min = 2, Max = 10, a higher value indicates more positive affective reactions. One tailed tests were used.

Experiential Evaluative mode mode 14.57 14.93 14.75 Similarity b dissimilarity 19.21 22.79 21.00 16.89 18.72 Evaluative N experiential

Experiential Evaluative mode mode 5.43 5.20 5.14 6.29 5.29 5.74 Evaluative N experiential

5.31 Similarity b dissimilarity 5.71

Experimental Evaluative mode mode 18.00 15.80 16.86 Similarity b dissimilarity 21.57 24.00 22.78 19.78 19.75 Evaluative ≈ experiential

Experimental Evaluative mode mode 6.14 5.33 6.36 7.00 6.25 6.13 Experiential ≈ evaluative

5.72 Similarity b dissimilarity 6.68

Main mode effect Main similarity effect F(1, 53) = 0.41; F(1, 53) = 14.06; p = 0.261 p = 0.00 Interaction effect mode ⁎ similarity F(1, 53) = 1.47; p = 0.115

Main mode effect Main similarity effect F(1, 53) = 0.20; F(1, 53) = 2.54; p = 0.329 p = 0.058 Interaction effect mode ⁎ similarity F(1, 53) = 2.82; p = 0.05

commercials. However, while rather small, the main effects of perceived similarity are in the expected direction for both sequences. Conversely, the observed means for the impact of the processing mode are nearly equal in the two conditions (no effect of the processing mode) during the replication. Consequently, the dependent measures indicate a main effect for perceived similarity: F(1, 53) = 2.54; p b 0.1 (one tailed) and an interesting interaction effect between perceived similarity and processing mode F(1, 53) = 2.82; p b 0.05 (one tailed). The main effect of processing mode is nonsignificant F(1, 53) = 0.20; n.s. Table 1 provides more detail To gain better understanding of the interaction between perceived similarity and processing mode, it is graphically presented in Fig. 1. The similarity effect is mainly due to the evaluative mode of processing and nearly non-existent in the experiential mode: (Experiential mode: Mean similarity = 5.78, Mean dissimilarity = 5.75, t = 0.05 n.s.; Evaluative mode: Mean similarity = 5.27, Mean dissimilarity = 6.64, t = 3.00; p b 0.01).

In the evaluative mode, and when the two commercials are perceived as dissimilar, an assimilation effect occurs between the attitude toward the positive emotional ad and the attitude toward the neutral ad. Moreover, in case of perceived similarity, it seems that a contrast effect occurs between the two ads leading to a lower Aad score for the neutral ad. In the experiential mode, the similarity effect is absent, but the observed difference between the two conditions (similarity versus dissimilarity) is not statistically significant. In short, a main effect of processing mode was not present in the current data, which is counter to our second hypothesis. However, and as predicted by our first hypothesis, more assimilation occurs between the affective reactions induced by two commercials perceived as dissimilar, in comparison with two ads described as alike. The main effect of the perceived similarity is also significant for the attitude toward the ad. Moreover and most importantly, our third hypothesis was supported, though less strongly than we had hoped for. Thus, we

6,8 6,6

Similarity Dissimilarity

6,4

Aad

6,2 6 5,8 5,6 5,4 5,2 5 EXPERIENTIAL

EVALUATIVE Mode

Fig. 1. Interaction effect between mode and similarity.

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detected an interaction effect of perceived similarity and processing mode on the positive affective reactions (for both pleasure and arousal dimensions), and on Aad. This indicates that processing modes of consumers during ad exposure may influence the impact of the perceived similarity. Conversely, perceived similarity between commercials may influence ad processing as well. Moreover, it is worth noting that controlling the attention devoted to emotions (by addition of the verbal measure of attention devoted to emotions as covariate) does not drastically modify the results. The covariate strengthens the presence of the main and interaction effects for similarity and mode. 5. Discussion We have found empirical support for the presence of systematic cross-advertisement affectivity effects. Affective responses to earlier commercials in a pod act as the context in which consumers process subsequent commercials. Specifically, we obtained assimilation and contrast effects. When commercials are perceived to be dissimilar (e.g., because they are from different product categories), the positive affect evoked by the first commercial in a pod may assimilate to the next commercial, thus improving its effectiveness. Moreover, the processing mode that consumers are in during ad exposure also impacted on the observed assimilation effect. However, this effect was the reverse of what was expected. In case of an evaluative mode, more assimilation occurred between the positive affective reactions induced by two commercials, than in case of an experiential mode. The analysis of Schwarz and Clore (2003) suggests several potential explanations for this latter finding. Perhaps the result is due to the specific manipulation of the two conditions and to the subsequent measures. In fact, in case of the experiential mode, only the affective reactions elicited by the neutral test commercial were questioned. On the other hand, in the evaluative mode, participants were also asked about the affective reactions elicited by the emotional commercial. Therefore, in case of evaluative mode, the emotions elicited by the emotional commercial were perhaps more salient for the participants. To examine this possibility, a small follow-up study was carried out. In this second study, 75 participants were placed in an experiential mode and only the perceived similarity was manipulated. Based on the result of this second study, it appears that this salience effect may not be due to testing ad-induced affective reactions for both ads, but only due to the way of processing the ad and the instructions given in the evaluative mode. In fact, although in this second study, emotions induced by both ads were measured, no differences were found between the perceived similarity and dissimilarity conditions. Finally, the presence of an interaction effect between the similarity and the mode of processing was very interesting and opened the perspective for possible future research. The impact of the perceived similarity depends on how the ad is processed. This makes sense, for instance, if a particular product category is of interest and if the ad is processed more intensively. The

difference between the two commercials might, depending on the characteristic of the two commercials, appear to be larger or smaller. This effect was also shown for Aad. This effect is particularly interesting in a practical sense since most advertisers accept Aad as a measure of ad effectiveness. In fact, similarity influenced the affective reactions on Aad both directly and indirectly. The existence of assimilation effects between ads is a remarkable result taken into account the limited size of the sample. 6. Conclusion It is important to conduct follow-up research under more natural conditions to improve the ecological validity of the current results. Future research using less direct and reactive measures, such as non-verbal measurement, can be useful to corroborate our results. Finally, we used a small and student based sample. A replication of this study with a more representative sample might be a suggestion for the future. For a fuller understanding of the sequence effects phenomenon, new experiments focusing on other characteristics of ads are necessary. For instance, is the impact of a commercial eliciting positive affect different from the impact of a commercial eliciting negative affect on the affective reactions triggered by subsequent commercials? Are assimilation or contrast effects expected in this case? What happens when the intensity of the affective reactions elicited by the commercial or the product category is varied? It might also be interesting to take into account personal/individual characteristics of the participant, such as mood, involvement in the product category as a moderator of the relationship between the affective reactions elicited by the ad. Continuing this research by looking at the correction process used by consumers when facing several commercials would be interesting. Friestad and Wright (1994) stressed the need to take into account consumers' personal persuasion knowledge in order to understand the advertising process better. It is especially relevant in this context of research since we have observed an interaction effect between the processing mode and the perceived similarity. The current findings have implications for media planning and copy testing as well. Often, copy tests are conducted with single commercials in a random or not strongly controlled sequence of ads. The present results illustrate that the affective reactions elicited vary as a function of the contexts created by other commercials. Thus, it might be useful to test advertisements in sequences, and to control the affective intensity and the similarity to the other commercials in the pod. Moreover, commercials may have to be tested in different ad contexts to examine their malleability to different affective contexts, and with different processing modes. In real life, consumers process advertisements under various conditions, sometimes being focused on experiencing ads, and sometimes on comparing them, for instance. However, advertising research appears to have developed mostly around the implications of an evaluative processing mode (under high and low involvement), partly ignoring the influence that experiential

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processing modes may have on advertising processing and effectiveness (see Meyers-Levy and Malaviya, 1999). As the present findings suggest, cross-advertisement effects differ by processing mode, and we speculate that more generally experiential processing modes may have quite different effects than the well-known evaluative modes. Moreover, since processing modes have indeed different effects on advertising responses, it may be worthwhile in media placement decisions to take this into account, by exploring if and how reception contexts induce different kinds of processing modes and how various advertisement versions can be optimally matched to the these processing modes.

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Following the viewing of the advertisements, the respondents received the following instructions: Could you please now describe how you felt when watching advert X, the previous advert, and what your affective reactions were. Before answering, please try to relive what you felt during the advert. Of course, there is no right or wrong answer. In the experiential mode, the respondents were only questioned about their affective reactions triggered by the neutral test advert. However, in the evaluative mode, they were questioned about the two test adverts (the positive emotional advert and the neutral advert).

Acknowledgement The authors thank Claude Pecheux for useful comments on a previous version of this paper. Appendix A. Instructions To manipulate the ad treatment mode, the following instructions were used. Firstly, to stimulate a systematic and evaluative mode of treatment, the respondents were asked to read the following instructions before watching the ads: Adverts usually try to give a message or information to consumers. Only spectators can judge whether the message really comes across. We therefore need your opinion as a spectator to evaluate the adverts that you are going to see. Please follow the instructions carefully and remember that what we are interested in is your opinion as a spectator. There is of course no right or wrong answer. You will see a series of TV adverts. Please listen to the message and the content of the adverts and observe the techniques used by the advertiser to get the message over to the consumer. In short, please listen to the information being transmitted. Following the viewing of the adverts, the respondents received the following instructions: Some adverts can provoke ‘affective reactions’ in spectators. Only the spectators can judge if they really work. This is why we need your help to analyse these ‘affective reactions’, i.e. the emotions triggered by the adverts. For each reaction, we would like you to try to analyse the extent of this reaction. In order to stimulate an experiential treatment mode, the respondents were asked to read some other instructions before watching the advertisements: We are interested in the affective reactions triggered by adverts, such as how you feel and your emotions. You will now see a series of TV adverts and we would like you to watch these in a relaxed way, letting the emotions you feel when you watch them take over. Please be aware of what you are feeling when you watch these adverts and the affective reactions they have on you. In short, be aware of your emotions.

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Setting the tone with the tune: A meta-analytic review of the effects of background music in retail settings Francine V. Garlin ⁎, Katherine Owen School of Marketing, University of Technology, Sydney, PO Box 123, Broadway NSW 2007, Australia Received 1 April 2005; received in revised form 1 November 2005; accepted 1 January 2006

Abstract Among the many in-store elements purported to impact patrons, background music is a leading feature of academic enquiry [Turley LW, Milliman RE. Atmospheric Effects on Shopping Behavior: A Review of the Experimental Evidence. J Bus Res 2000;49(2):193–211.]. Collectively, research examines a range of retail contexts, focuses on many different dimensions, and, uses different methods to explore the phenomena of background music in commercial settings. Therefore, conclusions are difficult on the extent to which the influences of background music on customer behavior are generalizable. The purpose of this study is to synthesize the results of extant research to identify common effects and the circumstances under which they differ. Our meta-analysis uses a sample size of 148, taken from 32 studies. A conservative approach to the analysis reveal small-to-moderate, yet quite robust effects in terms of background music and the dependents: value returns, behavior duration and affective response. © 2006 Elsevier Inc. All rights reserved. Keywords: Background music; Consumer behavior; Retail; Meta-analysis

Retailers have long been aware of the potential for the perceptual elements in their store environments to influence customers' behavior, and apply a tacit approach based on experience and observation (e.g. Areni, 2003a,b,c; DeNora and Belcher, 2000), or a conscientious design of their trading space to optimise the customer experience and/or maximise business returns (Babin and Attaway, 2000). In their review of sixty published studies on the impact of the purchase and consumption environment, Turley and Milliman (2000, 195) note that, “Music is the most commonly studied general interior cue”. Similarly, our interest is focussed on the effects of background music, and the extent to which this contributes to customer value. We report on the findings of a work-in-progress involving a quantitative meta-analysis that aims to, inter alia, identify common value effects from the use of background music in retail settings. The research has been kindly sponsored by the Australasian Performing Right Association.

⁎ Corresponding author. Tel.: +61 2 9514 3522; fax: +61 2 9514 3535. E-mail address: [email protected] (F.V. Garlin). 0148-2963/$ - see front matter © 2006 Elsevier Inc. All rights reserved. doi:10.1016/j.jbusres.2006.01.013

1. Literature review By providing the right “clues” in the physical setting, customer value is not reducible to “functionality versus price. Instead it is composed of both the functional and emotional benefits customers receive, minus the financial and nonfinancial burdens they bear.” (Berry et al., 2002, 86). These researchers suggest that the emotions derived from the customer's sensory experience of the physical setting can be the primary influence on their response. An emotionally taxing environment can negatively impact patronage even more than price considerations. “[O]rganizations must manage the emotional component of experiences with the same rigor they bring to the management of product and service functionality” else they may be at risk of reducing the overall value of their offer (Berry, Carbone and Haeckel, 2002, 86). The “values” available from such efforts are fully supported by decades of academic research. The dominant underlying theoretical framework for the study of physical consumption settings derives from environmental psychology (DeNora and Belcher, 2000), which

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examines the relationship between the stimulus-organismresponse (SOR). Using this paradigm Mehrabian and Russell (1974) developed a model (M–R Model) representing the influence of environmental cues on mediating emotional states (e.g. degrees of pleasure and arousal), which in turn result in either approach or avoidance behaviors. Simply put, “Consumers avoid unpleasant and approach pleasant environments” (Dube and Morin, 2001, 107). Since this was first adapted to a retail setting (Donovan and Rossiter, 1982), a stream of research has developed in the area. Among others, studies have found atmospheric effects to impact sales, amount spent, gross margin, actual and perceived time in the environment, patronage, unplanned purchases, brand/store image and evaluation, rate of purchase, pace of shopping, brand choice, brand switching and satisfaction (Turley and Milliman, 2000). In terms of background music, Turley and Milliman (2000) suggest that most researchers are concerned with time spent instore as the dependent variable. However the extensive literature search and review for the current study leads to a different conclusion. This is not unexpected since Turley and Milliman's study looked broadly at atmospheric effects and utilised only 16 papers related to music effects. We reviewed 157 papers, from which 150 papers explicitly discuss background music effects. From these 150 papers, we identified five categories of dependent variables, shown in Table 1 together with the proportion of papers examining each variable. Table 1 is followed by a brief overview of exemplar work from each dependent category.

not directly cause people to behave in certain ways … perceptions of the servicescape lead to certain emotions, beliefs and physiological sensations which in turn influence behaviors” (Bitner, 1992, 62). Many studies explore these intermediate relationships, particular music-mood effects (McGoldrick and Pieros, 1998). Enough research has been conducted in both psychology and marketing to confirm the predictive effect of music variables on mood (Tansik and Routhieaux, 1999). This is useful because music is one of the easiest ways managers can influence how their customers feel (Hosea, 2004). The other significant body of work exploring background music and affective variables is that which utilises the M–R Model. This model is most commonly used to represent the effect of music on the degree of pleasure and arousal experienced by customers. 1.2. Financial returns The evidence from both research and practice clearly suggests that customers' affective and cognitive responses to experiences in-store influence the likelihood of behaviors which directly impact an organization's financial returns. The literature reports on studies which highlight managers' implicit beliefs in the ability of background music to facilitate top- and bottom-line returns to business (Areni, 2003a,b; DeNora and Belcher, 2000). Other researchers have secured significant results using more objective measures, such as those included in Table 1 (Areni and Kim, 1993; Lammers, 2003; Milliman, 1982, 1986; North et al., 2000, 2003; Yalch and Spangenberg, 1993).

1.1. Affective variables 1.3. Attitude and perception Music in service settings can reduce even relatively extreme emotions such as intense anxiety (Lee et al., 2004; Tansik and Routhieaux, 1999). However, “the perceived servicescape does Table 1 Dependent variables studied in background music research⁎ Variable category

% Studies Variations or descriptors (n = 150)⁎⁎

Affective Financial returns Attitudinal/ perceptual

41% 25% 24%

Temporal effects

20%

Behavioral

10%

Mood, arousal, pleasure, emotion, nostalgia Value of sales, repeat purchase, items purchased, rate of spend, quantity purchased, gross margin Liking, brand loyalty, product evaluation, quality perceptions, experience satisfaction, perception of visual stimuli, service quality perceptions, price sensitivity, expectations, intentions, social identification, status perceptions Duration perceived/actual, service time, unplanned time, time to serve customers, time to decision-make, time to consume, duration of music listening Patronage frequency, store choice, behavior speed, affiliation, items examined/handled, in-store traffic flow, impulse behavior., recommend service, number of customers leaving before served.

⁎Where studies examine multiple dependent variables they are included in more than one category. ⁎⁎Reference list available on request from the authors.

Background music in-store is attributed to influence customer perceptions, specifically degree of attention and information processing of critical store elements such as visual stimuli and salesperson's arguments (Chebat and GelinasChebat, 1993; Chebat et al., 2001). In addition, North et al. (1999) suggest that music can ‘prime’ the selection of certain products by stimulating customers to recall related knowledge. Feelings of pleasure intensity and customer perceptions generated from background music effects can also enhance or create customers' attitude towards the store and/or its elements (See Dube and Morin, 2001; Gorn et al., 1993; Grewal et al., 2003; Oakes, 2003). 1.4. Temporal effects Several temporal dimensions are examined in the literature, including customer perceptions of time duration, actual time duration, time of day/week/year, wait time, and task completion time (e.g. decision-making, serving, consuming, shopping). Collectively, these studies reveal clear relationships between background music and the various temporal dimensions. Several musical variables have been manipulated in this research stream including tempo (e.g. Akhter et al., 1987; Holbrook and Gardner, 1993; Chebat, Gelanis-Chebat, and Filliatrault 1993), style/genre (North et al., 1999), volume

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(Kellaris et al., 1996), complexity (North and Hargreaves, 1999) and modality (Kellaris and Kent, 1992). In general, the literature provides evidence of the effects of music compositional variables on a range of temporal dimensions. However this is a cautionary tale. The research also highlights the complexity of relationships between musical elements and behavioral outcomes. As with all research domains, this signifies the need for careful methodological design, since confounds and inconsistent findings are often the result of inconsistent operational definitions (see Turley and Milliman, 2000). 1.5. Behavioral variables A substantially smaller collection of papers has been included in the behavioral category. This is because many primary behaviors of interest are captured in the other dependent sets. In brief, the literature reports on the capacity for background music to encourage customers to affiliate with staff (Areni, 2003a; Dube et al., 1995) and with other customers (Mattila and Wirtz, 2001; Sweeney and Wyber, 2002), can increase the likelihood of exploring a store and browsing (Tai and Fung, 1997; Akhter et al., 1987), influence patronage and store choice (Areni, 2003b; Caldwell and Hibbert, 2002; Donovan and Rossiter, 1982; Grewal et al., 2003), and provide potential for increased impulse buying (Mattila and Wirtz, 2001). Lastly, background music has been shown to impact the speed with which customers shop or consume (Milliman, 1982; Oakes, 2000). 2. Purpose of the study The empirical studies that have examined the impact of background music on consumers have been applied in a variety of settings, utilizing a range of research methodologies. Therefore conclusions are not easily made on the extent to which effects are significant and generalizable to other contexts. While inherently difficult to determine an “exact” value of music in business backgrounds, this does not preclude the need for furthering an understanding of these effects and their magnitude. This study aims to synthesize the results of existing empirical studies into the effects of background music in retail settings. From the analysis we anticipate the results will identify common value effects and the circumstances under which they differ.

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which is best suited to the objectives of the research and the outcomes sought. Meta-analysis is a quantitative methodology that seeks to objectively integrate the results of a large volume or complex research area. In the context of the proposed research we aim to identify the key impact and values of background music and, where possible, indicate the magnitude of the effect of these variables on purchase behavior and/or business investment returns. The review includes published studies, but where possible we have sought to identify and obtain unpublished work to minimize bias. Following an initial categorisation of the collection of studies into methodological subsets, we operationalised the research objectives (the impact and value of background music) with working hypotheses and a clear set of criteria on which to assess the studies in each subset. The SAS statistical package was used to undertake the first meta-analysis enquiry. 3. Methodology 3.1. Literature search The literature search focused on identifying all published studies on the effects on customers or staff of background music in retail or other business settings. The collection commenced with Smith and Curnow (1966) who were the first to address background music effect. A total of 11 databases were searched including: ABIInform, Academic Search Elite, Business Source Premier, Communication and Mass Media Complete, Expanded Academic, Google, Hospitality and Tourism Index, Medline, Professional Development Collection, Psychinfo and Science Direct. Keyword combinations applied included: background music or music and customer/consumer, musical effect, marketing, patron, purchase, buying, environment(al), atmospheric(ere), servicescape, retail, restaurant, environmental psychology, duration, behavior. References from bibliographies were also examined to identify further studies. Finally, we pursued non-published studies over the last 5 years through Google, through sites of active authors, and through direct enquiry to authors. 3.2. Inclusion criteria

The overall objectives of the research are to: 1) identify the impact of using music in the retail context; 2) identify the qualitative and quantitative values of using music in the retail context; and, 3) explore the implications for return on investment from the use of music in a retail context.

Studies that were included in the meta-analysis studies had to satisfy the following criteria. They had to: 1) have studied background music affects on patrons/clients/staff; 2) show a direct or clear indirect affect on purchase behavior or customer loyalty; and 3) have reported sample sizes, outcome statistics (e.g. t, F, χ2) or information such as group means and standard deviations that enable computation of the d statistic recommended by Arthur et al. (2001).

2.2. Overview of research design

3.3. Coding scheme

The study uses meta-analysis to provide a comprehensive review of the empirical studies in the research area—a design

The coding scheme developed for the meta-analysis incorporated three sections: effects of background music,

2.1. Research objectives

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known or used moderators, the type(s) of dependent variable(s) used in studies (Table 1), and covariates. Also coded was the type of study and method of analysis. Prior to commencing the coding we collected abstracts from the final collection of studies (150) as an initial check on their eligibility for coding. This resulted in further articles being excluded because of inadequate data, problems in experimental design that negated results, and methods or data not suited to our needs. 3.4. Meta-analysis procedure To compare the effects between studies the outcomes were converted into a common metric. In this analysis we use the sample-weighted mean d statistic developed by Glass (1976 in Glass et al., 1981) and outlined in Arthur et al. (2001): d¼

ME −MC SW

ð1Þ

where ME is the mean of the experimental or manipulated group and MC is the mean of the control or reference group, and SW is the pooled, within-group standard deviation. Although the correlation coefficient (r) is often considered the preferred statistic for meta-analysis, (Hunter and Schmidt, 1990) this method is appropriate for post-test-only studies which is the majority of studies into background music affects. Further, the advantages from the use of r are similarly available from the d statistic, viz, “d is not a function of sample size, and, because it is calculated as a difference of two proportions, also can be interpreted readily” (D'Alessio and Allen, 2000, 139). Where only test statistics were available (e.g. t, F, χ2 ) these were converted to d using the appropriate conversion formula and adjustments were made for unequal group sizes (Arthur et al., 2001; Rosnow and Rosenthal, 2003). In the absence of group sizes we made the assumption they were equal. In instances where only significance levels (e.g. p = .03) and means were reported an estimate was made for the appropriate test, and where only a “not significant” was given, a coarse estimate of the statistic was made (e.g. 1.0 for F). In many studies no variances were reported. These were estimated where means were reported by calculating the differences between means and dividing this by the F test to arrive at an approximation of the means squared error (i.e. MSE = BSE / F test). Prior to analysis we examined the magnitude and variance of effect sizes across the different test statistics. Effect sizes calculated from studies that provided means and standard deviations had the highest mean effect (m = 0.53, standard deviation of 0.25 and number of samples 34 with a mean sample size of 123). The effects for t tests were similar (0.51) while the F tests (F = 1 or F N 1) were lower at 0.35 and 0.42 with average samples of 123 and 138, respectively, and standard deviations of 0.25 and 0.28. The effect most requiring estimation was from the F test. Our concern was to err on the side of conservative estimates of the effects of background music. While a coarse comparison, this indicates that we are more likely to under- than overestimate the effects.

Once all effects were calculated a further adjustment was made to those that had used measurement scales for dependent or independent variables (Arthur et al., 2001). These scales are invariably less than perfect measures of an outcome and so tend to underestimate the effect. Following these adjustments the sample effect is calculated using individual and total sample sizes to provide a sampleweighted mean effect. X d¯ ¼ di ni =NT ð2Þ where d¯ is the mean effect size, di is the effect size and ni the sample size for sample i, and NT is the combined sample size from all studies. This mean is further adjusted to arrive at a mean corrected for unequal sample size, which avoids attenuation of effects due to substantial differences in sample sizes (Hunter and Schmidt, 1990). Hunter and Schmidt (1990) propose the following adjustment in the form of a multiplier (A): A = (1 + (0.75 / N¯ − 3)), where N is the average sample size across studies. 4. Analysis and results The final sample for analysis comprised 148 data points (samples) from 32 studies which are listed in the Appendix. These were then separated into three groups: Value, Affect, and Duration. Of the three, only studies in the value group were directly linked to some form of purchase behavior or intentions. Affect and Duration indirectly effect purchase behaviors as previously outlined, and so are discussed in the context of the links hypothesised in each area. The magnitude of effects is assessed using three criteria. First is the size of the effect. Following Cohen (1988) effects are evaluated as small (0.2), medium (0.5), and large (0.8). In the context of background music we would not expect to see large effects, this being one of many environmental factors that affect behaviour. The expectation is that effects will range from small to medium. To determine whether underlying moderators are influencing the results we assess the percentage of variance that is due to sampling error. For example, if this is around 100% we know that all variance in sample means is simply random and that underlying moderators are unlikely. A general rule of thumb is that if 75% of the variance can be attributed to error, then the likelihood is that the effect is the true effect size for that population (Arthur et al., 2001). Supporting this test is a chisquare test for homogeneity where rejection of the test is a further indication of possible moderators. Finally, we calculate confidence intervals to determine the range the effect sizes can take. The wider the range the more variable an effect can be across studies (also indicating the possibility of underlying moderators). The confidence intervals are graphed for easy reference. 4.1. Value The value sample included studies that examined the effects of background music on sales/purchases, intention to purchase

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or patronise, intention to return or recommend, and evaluation of service/products. Where a study reported several different purchase outcomes we chose the one that would be most consistent with other studies or that was likely to be more reliable. For example, Milliman (1986) reports individual purchases and daily gross sales from a supermarket where each day receives a different music condition. We included the latter to reduce the likelihood of confounding individual specific factors of those they surveyed. Areni and Kim (1993) reported number of purchases and value of purchases. The latter was taken because this is comparable to other studies. The effects examined in these studies included tempo, volume, complexity, genre, liking/familiarity and absence/ presence of music. Of the 20 studies included 13 were from natural settings and five of these in hospitality. In all laboratory settings a service or retail environment was simulated. A total of 41 data points were used in the analysis. Effects were reorganised to reflect the expectation that music as opposed to no music, lower tempo, lower volume and less complexity would be associated with greater purchases or a more favourable view of the venue (e.g. would recommend, return or evaluate favourably). Of these, ‘evaluation’ is likely to be the most ambiguous because of the influence of fit. Similarly, genre per se has no hypothesised direction. In all studies we included, the genre effect “classical” is compared to another form, mostly “popular”. This is because classical with some other genre has been the most common comparison. Differences in genre effects will also be evident in the absence–presence analysis if they are significant because these include a range of genres compared against no music. Highlighted earlier was that in many studies researchers examined several manipulations of an effect (e.g. 3 genre). This results in some overlap in samples because each comparison is treated as a separate data point and coded accordingly (this is particularly the case where comparisons were against a control condition and where we changed genre comparisons to presence–absence of music). In analysis we included each effect regardless of overlap but checked whether results were sensitive to sample size or the omission of one of the effects. In all but one instance including all effects did not impact the overall result. The exception was Wilson (2003) where the study sample was 300 and she reported five genres and no music. For analysis each genre was coded against the no-music group (50 × 2 × 5) resulting in an implicit sample of 500. To counter this inflation the sample of each comparison was reduced so that the sample of the combined groups was 300. Table 2 presents the results for the full sample and each primary effect area. The confidence intervals are illustrated in Fig. 1. We have combined the studies of tempo, volume and complexity because their movement from low-to-high/fast volume/tempo and less-to-more complex music is arousing, although these could have different consequences. Only one of these studies examined complexity, while three examined volume. Turning first to the overall sample, significant variation is evident in the effects of underlying studies given the high rejection for chi square. Familiarity/liking comprised five data

759

points from three studies with a sample-weighted mean of .35 indicating a small but clear positive effect on patronage. All the variance is due to error and so these studies can be considered to be representative of a population of studies. That is, the result is quite robust. This is also the case for the absence–presence of music. Almost regardless of the type of music, its presence has a small positive affect on patronage that is also robust. The result for genre indicates a medium positive outcome from playing classical as opposed to other forms of genre. However, this is clearly not always the case as indicated by the confidence interval. In a study by Lammers (2003) the alternative music was soft rock, with no significant difference between the two genres in terms of patronage outcome. Excluding this study from the sample increases the effect to 0.66 and reduces the variance across studies to only just significant. The final effect given in Table 2 is the combined tempo, volume and complexity comparison. The sample-weighted mean is almost zero with significant variation among the studies. The low mean is persistent whether only tempo or volume is examined and if the studies are separated by sales/ intentions and evaluations. Clearly context plays a significant role and needs to be explored. 4.2. Duration Duration has been examined based on actual time spent (or pace) in a location or at an activity, and/or respondents' perception of time spent. Of 19 studies that had examined duration eight reported affects on actual duration and five of these were in a natural setting. A total of 11 studies examined perceived duration. For the purpose of analysing the results actual duration and perceived duration were separated because the effect of music is different to the outcome. In looking at the effect of music on duration/pace in a retail environment most research has reported that consumers stay longer when some form of background music is present as opposed to no music, when the music is low rather than high in volume (Sullivan, 2002), is slow rather than fast tempo (Milliman, 1982), is liked (Caldwell and Hibbert, Table 2 Value: results for the full sample and corresponding primary effect Statistics

All

Familiar/ like

Tempo, vol, complexity

Absence– presence

Genre

Data points Total sample size Sampleweighted mean Corrected SD % Variance sampling error

39 5338 0.14

5 387 0.35

13 3542 − 0.05

16 1222 0.28

6 454 0.50

0.23 34.99

0.00 100.0

0.20 27.46

0.07 90.83

0.44 22.08

0.35 0.35 3.14

− 0.44 0.33 47.35

0.14 0.43 17.62

− 0.36 1.37 27.17

ns

p = .05

ns

p = .05

Confidence interval 95% Lower 0.60 Upper 111.45 Chi square p = .05 significance

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F.V. Garlin, K. Owen / Journal of Business Research 59 (2006) 755–764 1.50 1.00 0.50 0.00 -0.50

All

Familiar/like

Tempo

Absence-Presence

Genre

-1.00

Fig. 1. Sample-weighted mean and confidence intervals.

2002), and possibly lower in complexity. Seven of the eight studies examined one of these effects and a further study, genre (Areni and Kim, 1993). The latter was excluded from analysis because no hypothesis was established as to how genre per se should affect duration. Table 3 show three sets of results covering the full sample, an adjusted sample and a tempo-only sample. The sampleweighted means are all negative indicating that that reduced tempo/volume and more familiar music resulted in subjects staying marginally longer at a venue than if the tempo or volume was high or the music less familiar. The mean effect of the full sample is higher than the other results but this also has a wider confidence interval, a low error variance, and fails the test for homogeneity of variance. This is indicative of moderating factors that are influencing the results. A primary source of this variance is from a study by McElrea and Standing (1992) in which they examined the pace at which a sample of women (40) consumed a soft drink under slow and fast tempo. The range of tempo was 54–132 which is substantially wider than most studies and resulted in a very high consumption pace under the high tempo condition. In the adjusted sample this study was omitted. Both the adjusted and tempo solutions indicate the sample of studies can be considered to come from the same population (i.e. homogeneous variance with the former just rejected) and so no apparent moderating effects are present (although the error variance is substantially below 75% which conflicts with this). The sample-weighted means are at the lower range of possible effects indicating that the effect of background music on duration of stay is small. However, the range of effect can vary from almost non-existent to moderate as given by the confidence intervals (Fig. 2).

The second area examined under duration is perceived duration. Most of these studies focus on the effect of background music on perceived waiting. For retailers the concern is to minimise waiting time and/or for the time to pass as pleasantly as possible. Perceived duration was examined in 11 studies and most were concerned with perceived waiting time. All but one of these studies was carried out in laboratory or simulated environments. Three studies used simulated retail environments and another used a service environment (student registration). As with actual duration Yalch and Spangenberg, 1993 was excluded because the study tested for genre. All samples indicate the presence of moderators. A major source is the Bailey and Areni (2006) study which manipulated the number and duration of musical pieces under active and passive conditions. Their results are forthcoming and not discussed here. The only study in a natural setting (Smith and Curnow, 1966) examined the effect of volume on perceived duration and had a particularly low effect of .07 and the most substantial sample size (1100). However, no volume levels were given, which raises the question whether this study should remain in the analysis. Omitting both of these studies substantially reduced the underlying heterogeneity and increased the sample-weighted mean to 0.25. The positive mean indicates that the higher the volume, tempo and less liked the music the longer the perceived duration. The effect is more marked for studies examining tempo, with the effect at 0.39. The very low effect of 0.05 for liking/familiarity is a result of the Bailey and Areni (2006) manipulation of length and number of musical pieces. If these are excluded the effect increases to .34 (χ2 = 3.6) with 3 studies and 477 in the sample (Table 4) (Fig. 3). 4.3. Affect

Table 3 Duration: results for the full sample and tempo effect Statistics

Full sample

Adj sample

Tempo

Data points Total sample size Sample-weighted mean Corrected SD % Variance sampling error

9 1518 −0.32 0.28 23.64

8 1478 − 0.28 0.16 44.91

4 1185 − 0.22 0.12 50.19

−0.86 0.23 38.08 p b 0.05

− 0.60 0.04 17.82 p b 0.05

− 0.45 0.01 7.97 ns

Confidence interval 95% Lower Upper Chi square significance

The final area examined is affect. The MR model is the most cited for affect studies, which comprises three dimensions: 0.40 0.20 0.00 -0.20 -0.40 -0.60 -0.80 -1.00 Full sample

Adj sample

Tempo

Fig. 2. Sample-weighted mean and confidence intervals.

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761

Table 4 Perceived duration: results for the full sample and corresponding effects

Table 5 Affect: results for the full sample and corresponding effects

Statistics

Full sample

Adj sample

Tempo

Fam/liking

Statistics

Data points Total sample size Sample-weighted mean Corrected SD % Variance sampling error

19 3178 0.15 0.36 15.61

16 1698 0.25 0.30 29.17

4 497 0.39 0.31 24.95

11 1359 0.05 0.46 13.36

Pleasure absence– presence

Pleasure tempo

Arousal tempo

Data points Total sample size Sample-weighted mean Corrected SD % Variance sampling error

7 698 0.38

7 703 0.27

6 675 0.48

0.22 45.28

0.25 39.45

0.38 20.14

− 0.06 0.81 15.46 p = .05

− 0.22 0.75 17.75 p = .05

−0.27 1.23 29.79 p = .05

Confidence interval 95% Lower Upper Chi square significance

− 0.56 0.85 121.74 p = .05

− 0.35 0.84 54.86 p = .05

− 0.23 1.01 16.03 p = .05

− 0.85 0.95 82.32 p = .05

arousal, pleasure, and dominance. The common hypotheses are that increased pleasure is associated with higher evaluations of a service or venue, and increased arousal with a greater tendency to affiliate with other patrons or with staff, although several other outcomes are possible. Effects that have been examined include, genre, tempo, volume, mode, complexity, familiarity and liking and absence–presence of music. The consensus among many researchers in this stream is to exclude ‘dominance’ from studies, as prior research indicates that dominance is of little predictive value (Sherman et al., 1997). Although studies including dominance were initially coded for analysis they were subsequently excluded. We collected 61 data points from 15 studies that covered pleasure (25), arousal (14), and dominance (9). A further nine studies employed various measures relating to “satisfaction”, but these are not examined here. Despite the high number of data points many of the effects have only been examined in one study or study group (e.g. complexity (North and Hargreaves, 1999, 1996), mode (Kellaris and Kent, 1993). Only three effects had sufficient studies for analysis: absence–presence and tempo for pleasure, and arousal in the pleasure dimension. These represent 6, 5, and 5 studies respectively and 7, 7, 6 data points. 1.50 1.00 0.50 0.00 -0.50 -1.00

Full sample

Adj sample

Tempo

Famil/like

All effects exhibit wide variation as illustrated in Fig. 4. Absence–presence has a small-to-moderate positive effect on pleasure but clearly underlying factors that influence pleasure exist. Most of the variance comes from a study by Yalch and Spangenberg (1988, 1990) where they monitored and then interviewed shoppers in the clothing section of a department store and found age to be a moderating factor in pleasure. The effect for tempo was highest for arousal as would be expected since higher tempo is not always pleasurable. The high variance across studies is primarily from Mattila and Wirtz (2001) where the arousal effect was significantly lower than for other studies. Unfortunately they provided only the source of their music and not its musical characteristics (beyond low and high arousal) and so precluding our ability to assess whether the nature of the tempo differed from the other studies (Table 5). 5. Conclusion The literature indicates numerous influences on customer behavior from the use of music in a retail context. This was supported in the meta-analysis that used standardised measures of the effect of musical characteristics on key financial, behavioral, attitudinal and affective factors to assess how broadly applicable these many findings are. These affects were small-to-moderate but are clearly evident in the following relationships:

Arousal Tempo

• Familiarity/liking has a positive effect on patronage; • The mere presence of music has a positive effect on patronage as well as felt pleasure; • Slower tempo, lower volume and familiar music results in subjects staying marginally longer at a venue than when the tempo or volume are high, or the music less familiar; • A higher volume and tempo, and the less liked the music, the longer customers perceive time duration. This has most implications for waiting customers. • Tempo has the greatest effect on arousal.

Fig. 4. Sample-weighted mean and confidence intervals.

The consistency of the findings in this study with the literature connotes implications for return on investment from

Fig. 3. Sample-weighted mean and confidence intervals.

1.5 1 0.5 0 -0.5

Confidence interval 95% Lower Upper Chi square significance

Pleasure Absencepresence

Pleasure Tempo

-1

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the use of music in a business context. Taken collectively, past research demonstrates the capacity for appropriate background music to illicit positive effects on affective, attitudinal/ perceptual, temporal and behavioral variables. A considerable body of work presents evidence for these effects to provide returns to business in the form of sales value and volume, repeat purchase, rate of spend, quantity purchased and gross margin. Many indirect returns to business are apparent, such as positive perceptions of quality and venue/store brand image. 5.1. Limitations and future research The most significant limitation faced in this study relates to the limitations evident in many of the studies sourced for the meta-analysis. Studies were excluded because they did not report useable statistics, or they had serious design issues that comprised the results. In the main these were a result of confounding effects or poor experimental design, such as the lack of a control group or poor balance across conditions in field studies. This also limited the number of variables we could adequately analyse, and precluded a more comprehensive analysis of moderator effects and complex relationships. Unfortunately, most of these problems arose in field settings which are inherently more difficult to design and control, therefore we could not benefit from a more extensive inclusion of studies undertaken in naturalistic versus laboratory environments. Several studies that were included in the meta-analysis utilized incomparable statistics requiring adjustment. The possibility of inflating results is a consequence; however we countered this possibility by taking a conservative approach with our estimations. Finally, the meta-analysis and review is unlikely to include the population of existing work in this area of research. In particular studies may not have been published, perhaps due to the absence of significant effects. In terms of future research, well-designed replication studies that aim to overcome some of the limitations evident in prior research are clearly required. Despite the inherent difficulties, field studies outside the laboratory could increase our understanding of the background music phenomena. Future research examining the relationship between background music, intermediating cognitive and affective processes, and consequent behaviors are clearly warranted. Currently, the majority of studies have focused on intermediate effects of music alone or have ignored the intermediate effects altogether. The meta-analysis also indicates the need to examine the effects of context, and to explore the types and nature of underlying factors that are influencing or confounding variables of interest. More specifically, what is the relationship of background music with other elements of the ambient environment, and how might this influence behaviour? What are the similarities or differences between the effects of background music on patrons versus staff? Do different facets of the musicscape elicit different responses from patrons compared to staff? For example, ‘familiarity’ of music played in-store could have a very different effect on staff who might be more accustomed to the repertoire than customers might.

Finally, a reviewer of this paper asked “a question that cannot be answered with data: Are researchers studying the right variables … what else should we be studying?” Inspired by this, we suggest that researchers interested in the influence of the music stimulus itself explore the individual qualities of music using a set of non-evaluative attributes rather than genres. In a consumer study conducted by Garlin and McGuiggan (2002) various attributes were used in lieu of genre to describe movie content. Genre use in leisure-media research is criticised as being a highly limited unit of analysis, which is subject to wide interpretations between individuals and between producers and audience (Garlin and McGuiggan, 2002). The same situation clearly exists with music genre. Music researchers have identified the use of genre classifications as highly problematic. “No unique position can be taken regarding genre …. music genre is an ill-defined notion, that is not founded on any intrinsic property of the music, but rather depends on cultural extrinsic habits” (Aucouturier and Pachet, 2003, 83, 84). Like film genre, these authors note that music genre is dynamic and evolves with the appearance of new genres, merging genres and subgenres. Many nuances between musical pieces may also be differentially perceived by consumer researchers into background music effects and their subjects alike. “What is the difference between ‘Classical’ and ‘Opera’? …. What exactly is ‘Modern’ compared to ‘Jazz’”, or could the genre of “an orchestral rendering of Gershwin's Porgy and Bess” be perceived as the same as “a Prokoviev Symphony piece” by the uninitiated customer? (Aucouturier and Pachet, 2003, 87, 88, 90). The reason that genre use is raised as a significant issue for consideration is due to the high incidence of genre as a variable of interest in background music studies when this may be the inappropriate unit of analysis. Using a taxonomic approach, compiling musical attributes derived from consumers' and retailers' own descriptions as well as extant literature, would be a starting point. Appendix A. List of studies included in the meta-analysis Alpert JI. Apert MI. Background music as an influence in consumer mood and advertising responses. Advances in Consumer Research 1989; 16 (1): 485–91. Areni CS. Kim D. The influence of background music on shopping behavior: Classical versus top-forty music in a wine store. Advances in Consumer Research 2003; 20(1): 336. Bailey N. Areni CS. When a few minutes sounds like a lifetime: Does atmospheric music contract perceived time? Journal of Retailing 2006; 82(3). Caldwell C. Hibbert SA. The influence of music tempo and musical preference on restaurant patron's behaviour. Psychology and Marketing 2002; 19 (11): 895–917. Cameron MA. Baker J. Peterson M. Braunsberger K. The effects of music, wait-length evaluation, and mood on a lowcost wait experience. Journal of Business Research 2003; 56(6): 421–530. Chebat J-C. Gelinas-Chebat. C. Fillatrault P. Interactive effects of musical and visual cues on time perception: An application to waiting lines in Banks. Perceptual and Motor Skills 1993; 77(3): 995–1021.

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Milliman RE. The influence of background music on the behavior of restaurant patrons. J Consum Res 1986;13:286–9. North AC, Hargreaves DJ. Situational influences on reported musical preference. Psychomusicology 1996;15(1–2):30–45. North AC, Hargreaves DJ. Can music move people? The effects of musical complexity and silence on waiting time. Environ Behav 1999;31(1):136. North AC, Hargreaves DJ, McKendrick J. The influence of in-store music on wine selections. J Appl Psychol 1999;84(2):271–6. North AC, Hargreaves DJ, McKendrick J. The effects of music on atmosphere in a bank and a bar. J Appl Soc Psychol 2000;30(7):1504–22. North AC, Shilcock A, Hargreaves DJ. The effect of musical style on restaurant customers' spending. Environ Behav 2003;35(5):712–9. Oakes S. The influence of the musicscape within service environments. J Serv Mark 2000;14:539. Oakes S. Musical tempo and waiting perceptions. Psychol Mark 2003;20:685–705. Rosnow RL, Rosenthal R. Effect sizes for experimenting psychologists. Can J Exp Psychol 2003;57(3):221. Sherman E, Mathur LJ, Belk-Smith R. Store environment and consumer purchase behavior: mediating role of consumer emotions. Psychol Mark 1997;4(4):361–78. Smith PC, Curnow R. Arousal hypotheses and the effects of music on purchasing behavior. J Appl Psychol 1966;50(3):255–6. Sullivan M. The impact of pitch, volume and tempo on the atmospheric effects of music. Int J Retail Distrib Manag 2002;30(6):323–30. Sweeney JC, Wyber F. The role of cognitions and emotions in the musicapproach-avoidance behavior relationship. The J Serv Mark 2002;16(1):51. Tai SHC, Fung AMC. Application of an environmental psychology model to in-store buying behavior. Int Rev Retail Distrib Consum Res 1997; 7:311–37. Tansik DA, Routhieaux R. Customer stress-relaxation: the impact of music in a hospital waiting room. Int J Serv Ind Manag 1999;10(1):68. Turley LW, Milliman RE. Atmospheric effects on shopping behavior: a review of the experimental evidence. J Bus Res 2000;49(2):193–211. Wilson S. The effect of music on perceived atmosphere and purchase intentions in a restaurant. Psychol Music 2003;31(1):93-109. Yalch R, Spangenberg E. An environmental psychological study of foreground and background music as retail atmospheric factors. In: Walle AW, editor. AMA Educators' Conference Proceedings, vol. 54. Chicago, IL: American Marketing Association; 1988. p. 106–10. Yalch R, Spangenberg E. Effects of store music on shopping behavior. J Consum Mark 1990;7(2):55. Yalch R, Spangenberg E. Using store music for retail zoning: a field experiment. Advances in Consumer Research, vol. 20. Association for Consumer Research; 1993. p. 632.

Journal of Business Research 59 (2006) 765 – 769

If I touch it I have to have it: Individual and environmental influences on impulse purchasing Joann Peck a,⁎, Terry L. Childers b a

University of Wisconsin-Madison, 3114 Grainger Hall, 975 University Avenue, Madison, WI 53706-1323, United States b University of Kentucky, United States Received 1 April 2005; received in revised form 1 November 2005; accepted 1 January 2006

Abstract This research examines the influence of touch on impulse-purchasing behavior. We first replicate the Rook and Fisher [Rook DW, Fisher RJ. Normative influences on impulsive buying behavior. J Consum Res 1995;22:305–13.] studies about the moderating effect of the normative evaluation of impulse purchase on impulse-purchasing behavior. Extending the impulse-purchasing literature, we examine individual differences in touch and how they affect impulsive-buying behavior. Results from a field experiment suggest that both individual and environmental touchrelated factors increase impulse purchasing. © 2006 Elsevier Inc. All rights reserved. Keywords: Touch; Need for touch; Impulse purchase behavior

Almost all unplanned buying is a result of touching, hearing, smelling or tasting something on the premises of the store (Underhill, 1999, p. 158). This paper focuses on how elements of touch can affect impulse purchasing. Buying impulsiveness is defined as a consumer's tendency to buy spontaneously, unreflectively, immediately, and kinetically. “Highly impulsive buyers are more likely to experience spontaneous buying; their shopping lists are more ‘open’ and receptive to sudden, unexpected buying ideas” (Rook and Fisher, 1995, p. 306). This research has two primary purposes. First, the research is designed to replicate the Rook and Fisher (1995) findings concerning the moderating effect of the normative evaluation of impulse purchase on an impulse-purchase trait and impulse-purchase behavior. This research also extends previous research by examining how the element of touch might affect impulsepurchase behavior. Specifically, individual differences in preferences for touch information are expected to relate to impulse purchasing through their common link to hedonic purchase motivations. In addition, encouragement to touch at point-of-purchase is expected to influence impulse purchasing. ⁎ Corresponding author. Tel.: +1 608 262 3603; fax: +1 608 262 0394. E-mail address: [email protected] (J. Peck). 0148-2963/$ - see front matter © 2006 Elsevier Inc. All rights reserved. doi:10.1016/j.jbusres.2006.01.014

1. Theoretical background 1.1. Impulse purchasing and touch Limited evidence indicates that touch can influence behavior. In studies of the interpersonal touch domain (people touching people), restaurant servers who briefly touched customers received larger tips than servers who did not touch (Crusco and Wetzel, 1984; Hornik, 1992; Stephen and Zweigenhaft, 1986). Individuals who were asked to sign a petition were found to be more compliant if they were briefly touched (Willis and Hamm, 1980), and shoppers who were touched were more willing to participate in mall intercept interviews (Hornik and Ellis, 1988). While interpersonal touch seems to influence behavior, particularly compliance behavior, whether individual differences in touch will be related to impulse purchase behavior is not clear. Indirect evidence, however, suggests that product touch may influence impulse purchases, at least for some people. Kacen and Lee (2002) report that individuals who are more independent engage in greater impulse-purchase behavior than those who are interdependent in self-concept. Recent research by Ramanathan and Menon (2002) also provides insight into the influence that touch may have on impulse purchasing. These researchers posit and find that individuals prone to impulsive

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behavior are driven by hedonic gratification. What's more, impulsive individuals are more inclined to pick up or touch a hedonic target (in this case, a cookie) than are non-impulsives. For instance, in study 2, the researchers report that 58 percent of impulsives picked up the cookie, while only 29 percent of non-impulsives touched the cookie. These results suggest that individual differences in touch are potentially important as we further our understanding of the antecedents of impulsepurchase behavior. 1.2. Impulse purchase and autotelic NFT “It is people, not products, who experience consuming impulses” (Rook and Hoch, 1985, p. 23). The impulse-purchase trait is characterized by the lack of a salient purchase goal, at least at the start of the shopping experience. Researchers appear to agree that impulse buying involves a hedonic component (Cobb and Hoyer, 1986; Hausman, 2000; Rook, 1987; Rook and Fisher, 1995; Thompson et al., 1990; Ramanathan and Menon, 2002). Consumers report that when they purchase impulsively they feel uplifted (Cobb and Hoyer, 1986; Rook, 1987), and that they experience their needs for fun and novelty being fulfilled (Hausman, 2000). These studies offer conceptual support for a link between hedonic shopping motives and impulse-buying behavior. Peck and Childers (2003) have reported individual differences in consumers' “need for touch” (NFT); i.e., their preferences and motivations for gleaning information through touch. While two components of NFT exist, the autotelic component of NFT relates to touch as a hedonic-oriented response seeking fun, arousal, sensory stimulation, and enjoyment (Holbrook and Hirschman, 1982). In the absence of a salient purchase goal, this autotelic component of touch corresponds to a more sensory form of processing. Results from two experiments indicate that individuals who report a preference for autotelic touch chronically access hedonic information from memory (Peck and Childers, 2003). Similarly, Ramanathan and Menon (2002) argue that hedonic gratification underlies most impulse behavior, and that for impulsives, hedonic motives are more chronically accessible. Additionally, a positive and significant correlation is reported between autotelic NFT and an individual trait scale measuring buying impulsiveness (Peck and Childers, 2003). By extension, autotelic NFT would also be positively related to actual impulse-purchase behavior, which leads to Hypothesis 1. Hypothesis 1. Individuals higher in autotelic NFT will purchase more impulsively than individuals lower in autotelic NFT. 1.3. Impulse purchase and environmental salience of haptic information “Planning is a relative term; consumers' plans are sometimes contingent and altered by environmental circumstances” (Rook, 1987, p. 191). Not only may individual characteristics increase impulse purchasing, but also characteristics of the environment

may affect impulse purchasing through increasing the salience of touch. The characteristics of the situation (Bloch and Richins, 1983; Houston and Rothschild, 1978) may increase interest in differentiated aspects of the environment and thus capture the consumer's attention. As Underhill (1999) notes, many consumers are influenced or that they make their decisions instore versus outside of the store. Unique aspects of the in-store environment, such as music, lighting, layout, and signage, may affect a consumer's decision process (Underhill, 1999). In particular, a point-of-purchase sign encouraging touch exploration may increase the salience of touch information motivating individuals to touch and impulsively purchase the displayed product. Support for this comes from Ramanathan and Menon (2002) who report that impulsive behavior occurred for both impulsives and non-impulsives when a hedonic goal was primed. The chronic accessibility of hedonic gratification combined with the primed hedonic goal elevated impulsive behavior for impulsives, while also stimulating hedonic gratification for non-impulsives as well. Thus, we expect that increasing the environmental salience of touch will stimulate increased impulse purchasing for both higher and lower autotelic NFT individuals. This leads to Hypothesis 2. Hypothesis 2. Increasing the environmental salience of touch will increase impulse purchasing for higher and lower autotelic NFT individuals. 2. Overview of study This study was designed to investigate the link between impulse purchasing and both an environmental encouragement to touch and an individual preference for autotelic touch. This study was also designed to replicate the Rook and Fisher (1995) findings concerning the relationship between the impulse-buying trait and impulse-buying behavior. The design was a 2 (high versus low autotelic NFT) × 2 (point-ofpurchase sign “feel the freshness”, or no sign) betweensubjects design. 2.1. Procedure This study took place in two parts. Part one consisted of a field experiment conducted in a Midwestern-city supermarket where shoppers were observed while they purchased peaches or nectarines. Shoppers who purchased at least one peach or nectarine were intercepted and asked to fill out a short half-page survey. (Only two shoppers approached the display but did not purchase the fruit.) The first part of the survey measured shoppers' level of impulse purchase. This survey also included a manipulation check to determine whether shoppers noticed the point-of-purchase sign we had displayed. Finally, shoppers were asked their name and address for a two-page follow-up survey. As an incentive to return the second part of the survey, shoppers were entered into a drawing to win a $100 (U.S.) gift certificate toward supermarket purchases. This part of the study was completed in 3 weeks. The follow-up survey, which was

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mailed, included the autotelic NFT scale, the buying-impulsiveness trait scale (Rook and Fisher, 1995), the normative evaluation of impulse purchase of peaches/nectarines, and demographic measures. 2.2. Sample Two hundred and thirty-nine shoppers participated in part 1 of the study. After 2 weeks, 173 surveys were returned, with three unnamed, resulting in a usable sample size of 170 shoppers, for a response rate of 71 percent. The median age category for the respondents was 35–44 years. The median education level was a bachelor's degree (22 percent). The annual household income of the shoppers ranged from under $10,000 (U.S.) per year to over $100,000 per year. The median annual household income was $60,000 to $69,999 (U.S.). Thirty-eight members of the sample were male (22 percent). 2.3. Independent variables 2.3.1. Environmental touch salience Environmental touch salience was manipulated by either posting a sign encouraging shoppers to “feel the freshness”, or by posting no sign over the fruit display. The sign followed the normal sizing for this supermarket so as not to be conspicuous, and measured only 9 × 6 in. 2.3.2. Autotelic NFT Autotelic NFT was measured using the six-item autotelic NFT scale (Peck and Childers, 2003) with sample items: “Touching products can be fun”, and “I find myself touching all kinds of products in stores”(α = .94). Scale item descriptors ranged from − 3 (strongly disagree) to +3 (strongly agree) with the entire range represented in the sample. Higher and lower autotelic NFT were divided by a median split (eighty-seven individuals below the median were classified as lower in autotelic NFT vs. eighty-three classified as higher in autotelic NFT). 2.3.3. Buying-impulsiveness trait The buying-impulsiveness trait was measured by the nineitem buying-impulsiveness scale (α = .74) developed by Rook and Fisher (1995). 2.3.4. Normative evaluation of impulse purchase The normative evaluation measure assumes that consumers may assess the appropriateness of buying something on impulse along a continuum that ranges from relative neutrality to strong disapproval or encouragement. The measure, also adapted from Rook and Fisher (1995), contained the following question: “You are planning to buy one type of fruit and you end up buying four types of fruit. How would this make you feel?” The shopper is given ten seven-point semantic differential scales (α = .88) with endpoints good–bad, rational–crazy, wasteful– productive, attractive–unattractive, smart–stupid, acceptable– unacceptable, generous–selfish, sober–silly, mature–childish, right–wrong.

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2.4. Dependent variables 2.4.1. Actual impulse purchase behavior In-store buying impulsiveness was measured using three items adapted from Rook and Fisher (1995). The first item stated, “My decision to buy some type of fruit today was – –.” The second item stated, “My decision to buy peaches/nectarines today was – –.” And the third item stated, “My decision to buy the exact number of peaches/nectarines that I ended up purchasing was – –.” All three items had a scale ranging from zero to 4, with zero being “completely planned” to 4 being “completely unplanned.” The three items were summed (α = .72) for a measure of buying impulsiveness. 3. Results 3.1. Replication of Rook and Fisher (1995) One purpose of this study was to replicate Rook and Fisher (1995) concerning the relationship between the impulse-buying trait and consumers' buying behaviors. Rook and Fisher (1995) found that consumers' normative evaluations moderated the degree or strength of the relationship between the buying impulsiveness trait and impulse-buying behavior. This study replicated the analyses used by Rook and Fisher (1995). The mean normative evaluation of purchasing four types of fruit in this study was 24.7, a finding that was slightly lower but comparable to those results obtained by Rook and Fisher (1995) in which study 1 found a mean of 30.4, and study 2 found means of 28.1 for the sweater and 28.7 for the CD. The reliability of the normative evaluation scale in this grocery store study was also comparable to the reliability obtained in the Rook and Fisher (1995) paper: for this study α = .88, while for the Rook and Fisher findings, in study 1 α = .91, and in study 2 α = .90. A median split on shoppers' normative evaluations divided the sample into favorable (normative evaluation greater than or equal to 26, n = 79) and unfavorable (normative evaluation less than 26, n = 90) subsets. Next, we compared product moment correlations across normative subgroups. In the normatively favorable group, the correlation between the buying-impulsiveness trait and actual impulse-buying behavior was significant (r = .29, p b .05); yet, in the normatively unfavorable group, the correlation was insignificant (r = .06, p N .05). A Fisher's z-transformation revealed that the two correlations differed significantly (z = 2.36, p b .05). This finding replicates Rook and Fisher (1995) in both their study 1 and their study 2 (see Table 1). Additionally, Rook and Fisher (1995) used a different basis for defining normative groups to examine the robustness of their findings. They divided the sample into three groups and again computed the within-group correlations for both their study 1 and their study 2. Our observational study, conducted in a grocery store setting, again replicated their findings that consumers' normative evaluations moderated the degree or strength of the relationship between the buying-impulsiveness trait and impulse-buying behavior. Our results are illustrated in Table 1.

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Table 1 Correlations between impulse buying trait and actual impulse purchase

Rook and Fisher, 1995: Study 1

Rook and Fisher, 1995: Study 2

This study

Normatively unfavorable, median split

Normatively favorable, median split

Normatively unfavorable

Normatively neutral

Normatively favorable

r = − .002 p N .10 n = 102 r = −.02 p N .10 n = 48 r = .06 p N .10 n = 90

r = .33 p b .01 n = 110 r = .36 p b .01 n = 52 r = .29 p b .01 n = 79

r = .08 p N .10 n = 74 r = .07 p N .10 n = 35 r = .05 p N .10 n = 64

r = .10 p N .10 n = 69 r = .03 p N .10 n = 33 r = .17 p N .10 n = 59

r = .36 p b .01 n = 69 r = .58 p b .001 n = 33 r = .33 p b .01 n = 46

3.2. Impulse purchase and autotelic NFT The first hypothesis predicted that individuals higher in autotelic NFT would purchase more impulsively than individuals lower in autotelic NFT. Hypothesis 1 was supported with a significant main effect for autotelic NFT on impulse purchase (M = 4.5 and M = 5.5 for lower and higher autotelic NFT, respectively, F[1,166] = 4.9, p b .05). The two-way interaction was not significant (p N .05). In both the no-sign and the “feelthe-freshness” conditions, individuals higher in autotelic NFT purchased more impulsively than individuals lower in autotelic NFT. (In the no-sign condition, M values = 4.6 and 3.8 for high and low NFT, respectively, F[1,166] = 3.2, p b .05; in the “feelthe-freshness” condition, M values = 6.4 and 5.4, F[1,166] = 3.2, p b .05; Fig. 1.) 3.3. Impulse purchase and environmental salience of touch information

BUYING IMPULSIVENESS

We predicted that when a point-of-purchase sign (“feel the freshness”) encouraged shoppers externally to touch, both high and low autotelic NFT shoppers would purchase more impulsively. This was supported with a main effect of environmental salience (F[1,166] = 10.9, p b .05). Individuals purchased more impulsively in the “feel-the-freshness” versus the “no-sign” conditions (M = 5.9 vs. 4.1). We expected that higher and lower autotelic individuals would be influenced by the point-of-purchase sign. As expected, both higher and lower autotelic NFT individuals purchased significantly more impul7 6.4

6 5

5.4 4.6

4 3

3.8

2 1 0 NO SIGN

"FEEL THE FRESHNESS"

POINT OF PURCHASE SIGN HIGH AUTOTELIC NFT

LOW AUTOTELIC NFT

Fig. 1. Buying impulsiveness by autotelic NFT and point of purchase sign.

sively in the “feel-the-freshness” versus the no-sign condition (for higher autotelic NFT, M values = 4.6 and 6.4 for no sign and “feel the freshness”, respectively, F[1,166] = 6.0, p b .05; for lower autotelic NFT, M values = 3.8 and 5.4, F[1,166] = 4.9, Fig. 1). These results support Hypothesis 2 and indicate that both higher and lower autotelic NFT individuals were influenced by the presence of the sign increasing the environmental salience of touch information. 4. General discussion 4.1. Summary of findings This study examines the relationship between impulse purchase and the individual difference in autotelic NFT, as well as an environmental encouragement to touch. In addition, the study replicated the research of Rook and Fisher (1995) with the correlation between the impulse-purchase trait and impulsepurchase behavior moderated by the normative evaluation of the impulse-purchase behavior. Results are consistent with expectations. Overall, individuals higher in autotelic NFT purchased more impulsively than their lower autotelic NFT counterparts. In addition, for both higher and lower autotelic individuals, the environmental salience of touch information induced by the “feel-the-freshness” point-of-purchase sign increased impulsepurchasing behavior. 4.2. Theoretical and managerial implications While all individuals were influenced by increasing the environmental salience of touch information, some individuals (those higher in autotelic NFT) had a higher impulse-purchase baseline; that is, they were more likely to make impulse purchases overall. Puri (1996) describes impulsiveness as a result of the relative accessibility of the costs and benefits of impulsiveness. Perhaps individuals higher in NFT have the benefits of touch more accessible in memory than those lower in NFT. Evidence shows that touch information in general is more accessible to those who are higher versus lower in their NFT (Peck and Childers, 2003). We could argue that buying peaches or nectarines impulsively has minimal costs for individuals. Because of this, the accessibility of the fun and benefits of touch may drive impulse purchase. An accessibility explanation supports the finding that higher NFT individuals purchase more

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impulsively than lower NFT individuals, and the result that increasing the environmental salience of touch information increases impulse purchasing. An interesting extension of this finding would be to repeat this study using a purchase in which the costs would be determined to be greater, perhaps by manipulating different types of products. In this case, the difference in impulse purchasing between higher and lower autotelic NFT individuals may be even more pronounced. Another possible explanation involves the relative influence of affect and cognition. Shiv and Fedorikhin (1999) found that in a decision-making task, if processing resources are limited, affective reactions that are evoked spontaneously have a greater impact on the decision than do cognitions. A grocery store environment could be argued to be a cognitively demanding environment where resources are limited. Shoppers high in autotelic NFT may experience stronger affective reactions relating to the touch experience than those lower in NFT, which may in turn drive the increased level of buying impulsiveness. Examining physiological measures of higher and lower autotelic NFT individuals when they touch products that provide pleasant sensory feedback would be a method to investigate this. For managers, the link between touch and impulse purchase has important implications. Touch in general was found to increase impulse purchasing. Because of this, point-of-purchase signs, displays, and packaging encouraging product touch may increase impulse purchasing for both low and high NFT shoppers. A note of caution is necessary. This research only investigated the link between impulse purchase and product touch for a product high in salience-of-touch attributes. Whether this would translate for a product moderately high or low in touch-attribute salience is not clear. However, increasing the opportunities for consumers to touch products through both instore displays and store layout may increase impulse purchase. This research replicated Rook and Fisher (1995) and extended research on impulse purchasing by looking at the role of touch and its relationship to impulse purchase. Both an individual touch variable (autotelic NFT) and an environmental touch variable (point-of-purchase sign encouraging touch) increased impulse purchasing. Additional research is required to examine further the mechanism by which touch leads to impulse purchase.

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References Bloch P, Richins ML. A theoretical model for the study of product importance perceptions. J Mark 1983;47:69–81. Cobb CJ, Hoyer WD. Planned versus impulse purchase behavior. J Retail 1986;62:67–81 [Winter]. Crusco AH, Wetzel CG. The Midas Touch: the effects of interpersonal touch on restaurant tipping. Pers Soc Psychol Bull 1984;10(4):512–7. Hausman A. A multi-method investigation of consumer motivations in impulse buying behavior. J Consum Mark 2000;17(5):403–19. Holbrook MB, Hirschman EC. The experiential aspects of consumption: consumer fantasies, feelings, and fun. J Consum Res 1982;9(2):132–40. Hornik J. Tactile stimulation and consumer response. J Consum Res 1992; 19:449–58. Hornik J, Ellis E. Strategies to secure compliance for a mall intercept interview. Public Opin Q 1988;52(4):539–51. Houston MJ, Rothschild ML. Conceptual and methodological perspectives on involvement. In: Jain S, editor. 1978 Educator's proceedings. Chicago (IL): American Marketing Association; 1978. p. 184–7. Kacen JJ, Lee JA. The influence of culture on consumer impulsive buying behavior. J Consum Psychol 2002;12(2):163–76. Peck J, Childers TL. Individual differences in haptic information processing: the “need for touch” scale. J Consum Res 2003;30(3):430–42. Puri R. Measuring and modifying consumer impulsiveness: a cost–benefit accessibility framework. J Consum Psychol 1996;5(2):87-113. Ramanathan S, Menon G. Don't know why, but I had this craving: goaldependent automaticity in impulsive decisions. Working paper. New York University; 2002. Rook DW. The buying impulse. J Consum Res 1987;14:189–99 [September]. Rook DW, Fisher RJ. Normative influences on impulsive buying behavior. J Consum Res 1995;22:305–13. Rook DW, Hoch SJ. Consuming impulses. In: Holbrook MB, Hirschman EC, editors. Advances in Consumer Research, vol. 12. Provo (UT): Association for Consumer Research; 1985. p. 23–7. Shiv B, Fedorikhin A. Heart and mind in conflict: the interplay of affect and cognition in consumer decision making. J Consum Res 1999:278–92 [December]. Stephen R, Zweigenhaft RL. The effect on tipping of a waitress touching male and female customers. J Soc Psychol 1986;126:141–2. Thompson CJ, Locander WB, Pollio HR. The lived meaning of free choice: an existential–phenomenological description of everyday consumer experiences of contemporary married women. J Consum Res 1990;17:346–61 [December]. Underhill P. Why we buy: the science of shopping. New York (NY): Simon and Schuster; 1999. Willis FN, Hamm HK. The value of interpersonal touch on securing compliance. J Nonverbal Behav 1980;5(1):49–55.

Journal of Business Research 59 (2006) 770 – 777

How habit and satisfaction affects player retention for online gambling Bill Jolley a,⁎, Richard Mizerski b , Doina Olaru b a

Norwich University, 158 Harmon Dr., Northfield, VT 05663, USA b University of Western Australia, Australia

Received 1 April 2005; received in revised form 1 November 2005; accepted 1 January 2006

Abstract The ability of customer satisfaction to reliably explain and predict actual customer behavior has been an elusive objective to attain. This study tests the effects of past behavior (habit) on customer satisfaction in the prediction of actual behavior (retention). The study used an online gambling experiment accessible 24/7 to test the drivers of behavioral retention. It found that habit, not customer satisfaction, had a strong effect on a range of responses tied to retention. The implications of these findings are applied to issues for gambling managers and those developing public policy. © 2006 Elsevier Inc. All rights reserved. Keywords: Online gambling; Customer satisfaction; Habit; Retention

1. Introduction Marketing academics and practitioners have put satisfaction at the center of Business-to-customer relationships based on a theoretical link between a customer's satisfaction and their retention. This relationship is thought to play an important role in retaining profitable customers using customer relationship management. The retention of customers is often seen as preferable and more profitable than obtaining new ones. The virtues of ‘loyalty marketing,’ and the shift from brand equity to ‘customer equity’ (e.g., Blattberg et al., 2001; Venkatesan and Kumar, 2004), pervades much of the contemporary marketing literature. While the ‘satisfaction-retention-profit’ paradigm continues be popular among many in the marketing community, recent research in Business-to-Consumer relationships has raised questions as to whether their customers' satisfaction is a reliable and valid antecedent of their retention and the firm's profitability. Several investigations into the causal relationship between satisfaction and behavioral outcomes have failed to find a significant association (Georgiadis et al., 2001; Ittner and Harcher, 1998). Alternative models for managing customer franchises have also been developed using stochastic preference for defining customer

⁎ Corresponding author. Tel.: +1 802 485 2517; fax: +1 802 485 2087. E-mail address: [email protected] (B. Jolley). 0148-2963/$ - see front matter © 2006 Elsevier Inc. All rights reserved. doi:10.1016/j.jbusres.2006.01.017

profiles and predicting their response to marketing actions (e.g., Ehrenberg et al., 2004). Extensions of these behavioral models for analyzing transactional data such as data mining and neural networks have helped to advance an alternative form of customer franchise management that has been predictive of future behavior. This latter paradigm may be described as ‘frequency-retentionprofit’. However, critics of exclusively behavioral approaches claim these methods lack sufficient explanatory insight for formulating marketing programs or policy actions (e.g., Baldinger and Rubinson, 1997). These alternative views can be broadly characterized as a conscious cognitive-based customer satisfaction approach for the ‘satisfaction-retention-profit paradigm’, and a behavioral-based purchase frequency approach for the ‘frequency-retention-profit paradigm’. Perhaps a hybrid model that considers the joint effects of the attitudinal aspects of customer satisfaction and the stochastic assumptions of purchase frequency could be more effective for the evaluation and use of customer franchise management. Therefore, the premise that is tested in this research is whether in non-contractual relationships under mature market conditions where consumers’ purchasing patterns are firmly established, the relationship of customer satisfaction with customer retention is moderated by customers’ purchase frequency. Specifically, the research evaluated whether the strength of the relationship between a player’s satisfaction and playing retention was affected by their frequency of play.

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2. Background literature 2.1. Gambling Gambling is a consumer product that has some forms like Lotto that generate the highest penetration of purchase of the population, and frequency of purchase, of all consumer products (Mizerski et al., 2004). The Gambling Industry also generates more revenue than all other forms of entertainment combined (National Gambling Impact Study Commission, 1999), and is a leading source of state and federal/commonwealth taxes wherever it is legal. Gambling activities also tend to impose costs to individuals and society. The small minority (1% to 2%) of gamblers that compulsively gamble are subject to a wide range of serious problems that also affect others (National Gambling Impact Study Commission, 1999; Productivity Commission, 1999). 2.2. Gambler retention The gambling industry has embraced new technology in their game offerings, and an increasing number of gamblers have migrated online (Butterfield, 2005). There are now over 2000 gambling sites that are taking bets although it is against the law to do so in many countries (e.g., US and Australia). The issue of player retention for both off and online gambling is a very significant challenge for both the gambling industry and the government agencies that develop public policy and regulate gambling. The major forms (e.g., racing, lottery) and “brands” (e.g., Bally's, Caesars Palace Las Vegas) are actively marketing to retain profitable customers; however, the incidence of problem gambling is associated with the retention of problem gamblers (National Gambling Impact Study Commission, 1999; Productivity Commission, 1999). The retention of gamblers is made more challenging because the rapid growth of the industry now makes it very difficult for the gambler to differentiate among the many options that are available. New games such as online poker have developed after television coverage and proliferated. Price, in the form of payout to the player, is argued to be a very strong factor in this environment (Eadington, 2004). 2.3. The potential effects in online gambling Online gambling offers a research environment where buyers make frequent decisions over multiple time periods. This condition of frequent and independent choice is similar to the buying behavior of many consumer package goods and noncontractual services (Mizerski et al., 2004). Gambling presents an environment where satisfaction with the gaming experience would appear to play a significant role in determining the player's decision to continue betting. The chance of winning or losing can evoke strong emotions and the cost sacrifice can be significant, both factors are established antecedents of satisfaction (Oliver, 1993). In addition, players generally enter the

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playing venue with expectations that may or may not be met by the playing experience. This environment of online gambling would appear to satisfy the theoretical requirements of performance-expectation disconfirmation that underpins many of the satisfaction-retention models in use today (Anderson and Sullivan, 1993). 2.4. Satisfaction The theory that consumers' satisfaction with a brand or service is determined by the disconfirmation process dominates customer satisfaction research and managerial practice. Adaptation-level theory (comparison of an actual level with a reference level) has been cited as the basis for the disconfirmation model. Using the disconfirmation paradigm, customer satisfaction has been measured by different standards — actual level of performance versus either a norm or ideal (Tse and Wilton, 1988), or versus performance expectations (Oliver, 1980). The Parasuraman, Zeithaml and Berry (1994) ‘gap’ model of perceived service quality has also been used in satisfaction research as a difference score to represent a discrepancy construct. While the disconfirmation paradigm is the predominant form of satisfaction measurement, research has shown the performance–expectations construct to be unnecessary to measure satisfaction. Objective measures of the customer's perceptions of the actual service levels (for example perceived wait times measured in minutes) appear to be sufficient (Cadotte et al., 1987). Cadotte et al. (1987) contend that consumers are more likely to judge post-consumption performance by experiencedbased norms related to need fulfillment. This approach is consistent with the goal-directed evaluative criteria theory investigated by Gardial et al. (1994). Cadotte also concluded that the experienced-based normative standard varies by the consumption situation. In other words, it is not the disconfirmation of expectations, but rather the ability to meet customers' needs that should have more influence on satisfaction ratings. 2.5. Habit In a meta-analysis of prior research on predicting behavior, Ouellette and Wood (1998) found that situations where the behavior is frequently practiced (daily to several times a week), and the choice environment remains relatively consistent, the frequency of past behavior has a stronger direct effect on future behavior than the cognitive-based intention to perform the behavior. In those situations, the individual's frequency of past behavior may be a good indicator of habit formation, and is often referred to as habit (Ouellette and Wood, 1998; Ajzen, 2002). Norman, Conner and Bell's (2000) research on exercise activity supported Ouellette and Wood's 1998 findings that past behavior had direct effects on future behavior, and behavior was not mediated by the respondent's intentions. They also found evidence to support the hypothesis of a moderating role for past

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behavior on constructs in Ajzen's (1991) Theory of Planned Behavior Model. Their findings led them to conclude that repeat behavior was primarily determined by habit (as measured by the frequency of the behavior), was less likely to depend on conscious reasoning and that the predictive value of the Theory of Planned Behavior decreased as the frequency of past behavior increased. Oh and Hsu (2001) use a longitudinal survey on the same sample and tested for the effects of cognitive factors in the Theory of Planned Behavior (Ajzen, 1991) against the frequency of past gambling behavior (habit) in predicting future behavior. Although many of the cognitive-based constructs had a significant influence on future gambling, the direct effect of past gambling to future gambling was almost twice the size of the effect of behavioral intention to future behavior. They also found no direct effect of attitude toward the gambling options to their future gambling. Although Oh and Hsu found that the frequency of past gambling was a better predictor, there is little published on the form that past gambling takes in this process. Mizerski et al. (2004) tested a stochastic explanation for lottery product purchase that has been previously applied to Fast Moving Consumer Package Goods (FMCPG). The authors reported on analyses of the state of Florida Lottery quarterly cross-sectional surveys that showed the distribution of self-report purchase for all three lottery games investigated (Lotto, Cash Three and Instant), fit the Negative Binomial Distribution (NBD) in all nine surveys (n = 7800). Later research by Lam (2005), using meta-analysis on survey-based data on lottery and non-lottery games from five countries, confirmed the fit of the NBD beyond lottery games (e.g., Electronic Gaming Machines or slots). He also found that the data fit the Dirichlet (c.f., Ehrenberg et al., 2004) if one assumed the games were ‘brands’ in a category called ‘Gambling’. When Lam compared the size of the effects of past gambling to cognitive factors for present gambling, he found that past gambling was a much stronger explanation (r = .65) than affect (r = .10) or other cognitions such as beliefs about the lottery games (.06 brN .26). These findings suggest that habit may be expected to be a strong effect in player retention for an online venue, and if supported, represents the ‘frequency-retention-profit’ paradigm. In summary, previous research has relied primarily on intentions or self-reported behavior to measure customer retention. The recognition of the importance of consumers' past buying habits is lacking in much of that work. These limitations are addressed by this research study. 2.6. Retention Despite the extensive literature referring to retention there seems to be no universally accepted definition. Rust and Zahorik (1993) viewed retention as the propensity for a customer to stay with a brand over time. However, they went on to measure retention as the consumer's stated switching behavior. Using Jacoby and Chestnut's definition of loyalty, Mellens, Dekimpe and Steenkamp (1996) established a schema to distinguish between loyalty and retention by

using behavioral and attitudinal components. They postulated that three key characteristics differentiate loyalty from retention: Loyalty Multiple brands Attitude + behavior Biased choices

Retention Single brand Behavior only Independent choices

The critical component in the definition of loyalty that distinguishes it from retention is that loyalty has a basis in psychological processes. Retention has no cognitive component, and is viewed solely as a behavioral phenomenon (Hennig-Thurau and Klee, 1997). The conceptual difference between loyalty and retention was also addressed by East (1997) who argued that definitions should be based on measurement. Retention is a construct measured by the duration of time a customer continued to buy from the company, and is distinct from loyalty that is often measured by share of category requirements. East argued that there was no reason to expect that a large share-of-category customer would stay with a brand any longer than a small shareof-category customer. Almost no empirical research has reported about online gambling behavior. Even the research in off-line gambling is limited, with the vast majority focused on problem gambling (Mizerski et al., 2004). The question of how habit and satisfaction may influence retention of the player has had only trade press coverage at an anecdotal level. In an effort to better understand the factors that influence the retention of a gambler, an online casino (www.ecasinoland.com) was developed and tested with a sample of players. 3. Method The staff and students 18+ years old (legal gambling age) at an Australian university were targeted for the sample of gamblers. Large posters were put throughout the campus that announced the online casino and a $2000 jackpot that was to be won. A picture of a previous winner in an earlier experiment (n = 13) with a $500 jackpot was featured. Ethics approval by the university was granted for the study, and the approval was noted in the ad. The sample required gamblers 18+ years old (legal age to gamble in Australia), and the only method of quick and accurate age approval was through the university registration databank. Nonetheless, the primary student age profile of the gamblers recruited is of great interest to online gambling providers (US Gambling Impact Study). Also, the site was accessible 24/7 from almost anywhere in the world. Although casino table games and Electronic Gaming Machines (slots/fruit machines/ pokies) are forms of online gambling that continues to be banned in Australia, the site was allowed to operate because it was for research purposes. At the time of this experiment, the gamblers recruited could only gamble online with providers outside of Australia and the US. This policy environment still exists today.

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3.1. Research procedure The prospective gamblers were required to register at the research web site with their personal identification, answer an online screening questionnaire to ensure problem gamblers would be screened out of the games, and agree to a set of rules and regulations. Qualified respondents designated a username and password for logging in and then received 100 ‘e-dollar’ credits (typical online gambling incentive) in their account for gambling. In order to help create a sense of risk and sacrifice, gamblers were led to believe they could lose money. If all of a gambler's credits were depleted, he or she had to request additional ‘e-dollars’ from the electronic cashier in $25 increments. They were told that each new $25 credit would cost one hour's administrative office work for the University. At the end of the experiment, all losers were told they did not owe any time for the credits. The player who had the highest net winnings, total payouts less total bets, at the end of the game would win a jackpot of $2000 AUD. The Australian government has determined that there is no difference in players' behavior between free-play or points-play games and real cash/credit for online gambling. The gambling industry also recognizes this close similarity between ‘free play’ and ‘real money’ sites. Free play sites are used, where allowed, as a method for generating players for future cash play games. Thus, the present study achieves a high degree of realism within the University's guidelines for ethical research. 3.2. Research design The research design tested stimuli that have been suggested to directly influence a player's playing satisfaction and their betting behavior. The game options were systematically varied so as to expose a set of discrete choices, among four different slot game configurations, to each respondent. The four factors and levels used in the treatment manipulations were; jackpot payoff ratio at

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three levels (5000, 3000 and 1000 to 1), Return-to-Player percentage at two levels (85% and 95%), warnings about the negative consequences of excessive gambling at three levels (none, weak and strong) and the speed at which the reels would spin at two levels (fast and slow). A fractional factorial design was applied to the four factors to derive thirteen different slot machine configurations used as treatment stimuli. A balanced incomplete block design paired each configuration with all others to determine the set of four machine profiles respondents in a given cell would view. The post-only with control design required 13 test cells and two control cells. Upon their first login, respondents were randomly allocated to one of the 15 experimental cells using software on the server. The procedure was designed to ensure roughly equal cell sizes of randomly allocated respondents any time it was needed (the gambling games were accessible 24/7). Initially, respondents in all cells were exposed to a choice of four slot games, each with an identical configuration of game attributes. Each game was labeled on the game screen as North, South, East, and West. Fig. 1 shows the game and choices as they appeared to the registered visitor. One week into the experiment when stability was established in the gamblers' betting frequency, players in cells 1–13 received a re-configured set of the four game options based on their treatment cell they were assigned by the software. Cells 14 and 15 remained unchanged from the initial baseline, and served as a comparison group on some analyses. Mid-way through the study, an online survey was presented to gamblers. These questions were used to measure the respondents' satisfaction with their playing experience. The online game also offered a real-time satisfaction measure with a sliding scale below the messages. However, few subjects took time to alter the scale during their play so this data wasn't analyzed. The subjects' continued to play until voluntarily ending their participation by cashing out, or when the study ended.

Fig. 1.

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200

0 0 5.00 0 2.25 0 2.75 2.00 9.00 1.00 15.00 0 2.75 6.75

0 0 12 0 9 0 10 8 36 4 31 0 11 18

3.3. Measures Table 1 illustrates an example of a player's betting behavior. ‘Day’ is the number of days from the start of the study that the game was played. ‘Session’ is an event whose beginning is marked by the respondent logging in and ending by the respondent logging out. ‘Game’ is the number of the game being played from 1 to 13, depending on the respondent's cell assignment. ‘Duration’ is the time the player spent playing that game. ‘Bet amount’ is the total money the subject wagered while playing that game for that duration. ‘Bets’ are the number of times the player placed a bet by hitting the spin button. This particular player played a total of 4 sessions over three separate days. He bet on all four games at his ‘casino’ (game profiles 3, 4, 6 and 12). His longest time was on game 4 for 4.5 min where he bet $15 in 31 bets. The pattern of gambling behavior varied widely across the 13 games after the base period. Table 2 shows the difference among both the number of players playing each game and the frequency with which bets were made. An independent sample t-test showed significant differences in the both the penetration (p = .04) and the betting frequencies (p = .003) between games. Over the study period, there were 329 unique visitors to the game's home page, with 193 of those visitors providing valid

100 50 0 31

.63 .99 3.11 .23 2.54 .03 1.64 1.02 3.11 .57 4.59 .08 .86 2.01

28

12 3 6 3 4 3 6 12 3 6 4 6 3 4

25

1 2 2 3 3 3 4 4 4 4 4 4 4 4

22

1 3 3 3 3 3 5 5 5 5 5 5 5 5

150

19

Bets

16

Bet amount ($)

13

Duration (min)

10

Game

7

Session

4

Day

1

Table 1 An example of one respondent's pattern of play

Number of players

774

Day of experiment Fig. 2. Cumulative new gamblers per day.

registrations. Of the 193 visitors that successfully registered, 176 or 96% logged in to the game page and opened at least one of the games. Of those 176, 168 or 95% made at least one bet. Those 168 persons were considered ‘bettors’ and comprise the basis for a majority of the analyses. On average (n = 168), a bettor played 4.7 sessions, changed games 12 times, spent 42.9 min over all sessions, wagered $324 across all bets and hit the spin button an average of 289 times. The rate at which visitors registered for the study followed a fairly typical trial curve with a decreasing slope. For all but one of the subjects, this online gambling experience was reported as their first. Therefore, this trial curve may reflect the diffusion of a new product form. Fig. 2 shows the cumulative build of new players registering for the study. Five permission e-mail promotions were executed to stimulate trial throughout the study. These promotional efforts were delivered so that all respondents had an equal chance of exposure to all promotions. The gambling pattern of respondents also can be looked at as the proportion of the sample that gambled a certain number of times during a session. Sessions when a game was not played accounted for approximately 30% of all sessions. Table 3 shows the observed frequency of playing occasions in the treatment period that followed a positively skewed distribution where many players bet infrequently, while relatively few players bet very frequently. Table 3 also shows the NBD expected frequency Table 3 NBD test of fit (treatment period)

Table 2 Players and betting frequency by game Game

Number of players

Betting frequency (avg. no. of spins)

1 2 3 4 5 6 7 8 9 10 11 12 13

32 29 26 34 34 30 41 34 33 31 31 34 34

29.1 15.3 22.5 22.3 31.5 15.7 21.2 16.5 22.9 16.1 27.4 13.4 25.5

NBD inputs:

Base

Penetration (155 bettors) Average number of occasions Any game was played

(180) 86.1% 8.67

Proportion of base: –Not playing –Playing Once Twice 3times 4times 5times 6times 7times 8+times

Observed 13.9% 86.1% 12.8% 8.9% 6.7% 7.8% 7.8% 6.7% 3.9% 45.4%

Expected 13.9% 86.1% 12.6% 10.6% 9.1% 7.9% 6.9% 6.0% 5.3% 41.6%

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of gambling. The NBD expected distribution was not significantly different from the observed distribution (χ2 = 0.97, p = .99) based on the penetration and average frequency of bettors in the experiment. Gambling occasions for a game are analogous to purchase occasions of a brand, where the units bought per occasion would be comparable to the number of bets a player made on an occasion. 3.3.1. Customer satisfaction Both disconfirmation and direct performance measures were used in this research. To measure satisfaction, seventeen items were developed from the literature and pre-tests for this experiment. These items were factor analyzed resulting in three correlated components. These components had eigenvalues of 6.55, 2.2 and 1.41, and accounted for 66% of the variance. The reliability measures led to the use of only two composite constructs, made up of 13 of the 17 initial items (the items not included were ‘beating the system,’ ‘passing the time,’ ‘winning a lot of money,’ and ‘chances better than a casino’). The two constructs were characterized as ‘Need Satisfaction’ and ‘Commitment Satisfaction.’ Both constructs are consistent with prior theory (Cadotte et al., 1987; Szymanski and Henard, 2001). The factor loadings are shown in Table 4. The two constructs were only mildly correlated (r = .26). Cronbach's alpha measures of reliability for the constructs of need–satisfaction and commitment–satisfaction were .87 and .77, respectively. 3.3.2. Retention Players that bet on a game more than once in a single time period were considered repeat players. Their average betting frequency is a measure of repeat betting for that time period. Retention on the other hand, is the likelihood that a player will repeatedly play for the duration of the study. For the purpose of this research, retention was operationally defined as the probability that a player, who has made at least one bet on any game, will continue to bet over some time period. In this case, the time was to the end of 34 days of online operation. Based on these constraints, Survival Analysis was chosen to construct a dependent measure of retention (Therneau and Grambsch, 2000). The variable of interest was the probability a player will bet on any game for the duration of the study. Players Table 4 Factor matrix for satisfaction constructs Variable

Need satisfaction

Entertainment Privacy Convenience Recreation/mind Enjoyment of competing Not costing Taking risks Different from routine Thrill of reward Overall satisfaction Expectations met Would recommend Would play again

.83 .81 .75 .74 .73 .71 .69 .67 .59

Commitment satisfaction

Table 5 Factor loadings for habit-strength Habit-strength Total number of spins Total betting days Total days logged in Number of sessions played Number of sessions made a bet

.73 .96 .76 .93 .94

that did not end their participation before at the end of the study were considered right-censored observations. Cox-proportional hazard functions estimated the survival curves and the retention probabilities for each player using time spent on the web as a covariate and marketing promotion as strata. The Cox-proportional hazard model provided evidence that the number of hours the subjects' spent weekly on the web was a significant explanatory variable (p = .006), and that different baselines for hazard functions should be fitted for the strata defined by promotion (likelihood ratio p = .01). The diagnostics assessed the adequacy of the model, and there was no obvious structure in the Martingale residual plots, or outliers. Based on the data, the median ‘survival time’ for the entire sample was 9 days. It is worth mentioning that of the five permission email promotions tested, only one made a significant difference (p b .05) on players' behavior. However, it appeared to perform well. The median survival time for players exposed to that promotion was 29 days, an extension of 20 days. 3.4. Habit-strength The literature consistently supports the concept of habit being measured by the frequency of past behavior (e.g., Ouellette and Wood, 1998), and that it appears negatively related to cognitive effects in explaining and predicting repetitive behaviors. Ajzen (2002) has criticized these interpretations and the tests used. He suggests that there is an inherent measurement artifact when using past behavior to explain or predict present or future behavior, and that an ‘independent’ measure of past behavior should be applied. In an attempt to develop measures that would provide an independent metric from the dependent variable, five different behavioral responses in gambling were used to indicate the frequency of gambling. The game server software allocated treatments and collected all behavioral data unobtrusively. No subjects' self-reports of gambling behavior were collected.

Player Satisfaction

.37 .83 .81 .73 .60

775

Customer Retention

Past Behavior (Habit Strength)

Fig. 3. Satisfaction-retention model.

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Table 6 Commitment–satisfaction and habit-strength (groups based on median split) Habit-strength Low Commitment– High Retention probability: 0.49 satisfaction Length of stay: 9.5 days Low Retention probability: 0.53 Length of stay: 10.7days

High Retention probability: 0.57 Length of stay: 20.4days Retention probability: 0.56 Length of stay: 22.1days

This study developed a latent composite variable, ‘habitstrength’, to represent a player's frequency of past behavior (refer to Tables 1 and 2 for examples of the behavior measures). Factor analyses were performed to reduce the observed variables to a single latent construct (with an ultimate eigenvalue = 3.77). The factor matrix resulting from the analysis is shown in Table 5. Cronbach's standardized alpha coefficient for the five-measure construct was 0.91. The composite variable habit-strength was used to test the moderating effects of past behavior on the relationship between satisfaction and retention (c.f., Bolton, 1998). Moderating variables are conditions under which the relationship between a pair of variables varies. The hypothesized relationship between the constructs is shown in Fig. 3. In order to examine the potential moderation effect of habit, the sample was divided into two groups, a low habitstrength and a high habit-strength group, using the median value (0.75) of the uni-dimensional variable habit-strength. To test the significance of habit-strength as a moderator, a target model with all structural parameters fixed was fitted to the two groups. This model was compared with a model in which the paths that were hypothesized as being moderated. The appropriate test statistic for comparing models is the chisquare (Bagozzi and Yi, 1989). The results of the chi-square analysis showed the moderating effect model of habit-strength was not significantly different from the data (χ2 = 98.02, df = 80, p = .08). The fit of the model was good (RMSEA = 0.05, IFI = 0.95, and CFI = 0.94). The path between commitment– satisfaction and retention was significant (p = 0.01), but weak (0.07). However, the coefficient from satisfaction to customer retention was almost twice as strong for the high habit-strength group than for the low habit-strength group (0.136, p = 0.005 versus 0.073, p = 0.04). This result supported the hypothesis that habit-strength has a moderating effect on the relationship between satisfaction and customer retention. Table 6 shows the directional impact on behavior between groups with high and low levels of the factor scores for commitment–satisfaction and habit-strength. There was little difference between the high and low satisfaction groups. The high and low habit groups had a range of higher retention responses than either satisfaction group. 4. Summary and conclusions The primary purpose of this research was to test the moderating relationship of past behavior (habit) on the relationship of customer satisfaction with customer retention.

This research found in an online gambling situation, where the pattern of buying behavior is similar to other frequently purchased products and services, that: Players’ satisfaction had a relatively small effect on their retention. Increasing players’ average “overall satisfaction” rating by 1.0 point on a 5-point scale would increase the probability that they would play until the end of the study by 3.0%. Players’ frequency of past behavior as measured by habitstrength had a significant moderating affect on the relationship between satisfaction and retention. The coefficient from player satisfaction to customer retention was almost twice as strong for the high habitstrength group than for the low habit-strength group (0.136 versus 0.073, respectively). The moderating effect of habitstrength on the relationship between player satisfaction and retention was significant. The findings of this research have shown that in the context of online gambling, the incidence of betting occasions (habitstrength) can have a stronger effect on retention and other betting behaviors than satisfaction. The sample’s satisfaction with the games was found to be significant, but very weak in predicting customer retention. 4.1. Limitations The sample and experimental stimuli obviously limit the findings. Although the age group and education background of the sample is being sought by online gambling providers, there is little data to suggest what the typical demographic profile of the online gambler would be. The game software used for the experiment may be much less experiential than commercial games. Imparting more experiential experiences could affect he development and influence of player/customer satisfaction. One would also expect that commercial game providers have a profile of gamblers that provide much heavier average gambling. However, this study's findings suggest that heavier gamblers would exhibit high levels of habitual behavior that may be even more prevalent in decision-making. Nonetheless, the proportion of heavy gamblers in this sample may not represent commercial online gambling. 4.2. Discussion Although there are limitations with the study, the study's findings suggest a number of implications relating to regular gambling behavior. The weak, and habit-strength moderated relationship of player satisfaction with player retention, questions some of the use of customer satisfaction as a predictor of customer retention under mature market conditions. Given that other forms of gambling follow the NBD pattern (Mizerski et al., 2004; Lam, 2005); the extension of these findings seems most applicable to those games. Obtaining similar findings with other frequently purchased product categories such as consumer package goods would be possible, but more research comparing

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habit and cognitive-based constructs needs to be done (c.f., Wright et al., 1998). The premise that improving your customers' satisfaction will lead to higher retention rates and increased profitability may not be accurate. To the extent that the results are replicated in the online environment, online gambler segments that have routine stable purchase/usage patterns appear unlikely to be influenced by factors designed to raise their level of satisfaction (e.g., speed of the game). If this research can be generalized, one would expect that player satisfaction with a gaming brand has a weak effect in their staying with that brand. When buying habits have been established, managers would benefit from shifting their emphasis from expensive and potentially ineffective satisfactionbased ‘loyalty schemes,’ to developing marketing programs with primarily two objectives. One objective would be to focus any effort in customer satisfaction to new and recently acquired customers with value propositions that satisfy their needs and reinforce their replay/repurchasing habits. A second objective would be to prevent dissatisfaction/defection from occurring with already habitually committed customers (c.f., Hammond and East, 2003). This research provides implications for policy makers regarding problem gambling. Environments that foster habitual levels of gambling appear to facilitate gambler retention. Habitual-based retention may be difficult to manage with the typical tools of public policy-advertising and warnings. None of the warnings used in this experiment had a significant effect in gambling even though the game was taken off the screen while the warnings were presented. Much like customer satisfaction, these remedies appeal more to the conscious cognitive drivers of decision-making and gambling behavior. More work on the measurement and potential effects of habit in gambling needs to be done. References Anderson EW, Sullivan MW. The antecedents and consequences of customer satisfaction for firms. Marketing Science 1993;12(2):125–43. Ajzen I. The theory of planned behavior. Organizational Behavior and Human Decision-making Processes 1991;50:179–211. Ajzen I. Residual effects of past on later behavior: habituation and reasoned action perspectives. Personality and Social Psychology Review 2002;6 (2):107–22. Bagozzi RP, Yi Y. On the use of structural equation models in experimental designs. Journal of Marketing Research 1989;XXVI:271–84 [August]. Baldinger A, Rubinson J. The jeopardy in double jeopardy. Journal of Advertising Research 1997:37–49 [November/December]. Blattberg R, Getz G, Thomas J. Building and managing relationships as valuable assets. Boston, MA: Harvard Business School Press; 2001. Bolton RN. A dynamic model of the duration of the customer's relationship with a continuous service provider: the role of satisfaction. Marketing Science 1998;17:45–65. Butterfield F. Even poolside, casinos entice by hand-held. The New York Times; 2005. July 2. Cadotte ER, Woodruff RB, Jenkins RL. Expectations and norms in models of consumer satisfaction. Journal of Marketing Research 1987;XXIV:305–14 [August].

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Journal of Business Research 59 (2006) 778 – 785

Personality-and-culture: The case of national extraversion and word-of-mouth Todd A. Mooradian ⁎, K. Scott Swan School of Business, College of William and Mary, Williamsburg, VA 23187-8795, USA Received 1 April 2005; received in revised form 1 November 2005; accepted 1 January 2006

Abstract One advantage of the recently revitalized “personality-and-culture” paradigm is its capacity to describe both individual- and culture-level differences. Another advantage is personality-and-culture's foundation in the extensive heritage of theory development and empirics in personality psychology itself, in which traits have been related to a variety of observable behaviors and to underlying physiological, neurological, and genetic structures. Personality-and-culture also builds on recent, substantial methodological and analytic advances specific to cross-cultural research including progress in data collection capabilities, in computational power, and in tools for statistical analyses of bias and equivalence. This article reviews these advances in personality-and-culture and then report preliminary empirics linking nation-level extraversion to differences in preferences for interpersonal sources of product information (i.e., word-of-mouth), thus clarifying national differences in reliance on interpersonal sources of information and, most importantly, demonstrating the general value of the personality-and-culture approach. © 2006 Elsevier Inc. All rights reserved. Keywords: Cross-cultural marketing; International marketing; Consumer behavior; National character; Personality; Consumer word-of-mouth

National character, “the idea that the people of each nation have a distinctive, enduring pattern of behavior and/or personality characteristics” (Clark, 1990, p. 66), offers an important paradigm for theory development in cross-cultural consumer research by connecting consumer phenomena to underlying, universal cultural attributes. The most widely adopted and applied framework of national character has been Hofstede's four- and later five-dimensional model of culture (Hofstede, 1980, 1991). Hofstede's framework and the specific scores he published have been productively applied across business disciplines including marketing and consumer research (see Sivakumar and Nakata, 2001). Nevertheless, Hofstede's work has been criticized (see Bond, 2002; McSweeney, 2002; Roberts and Boyacigiller, 1987; Sivakumar and Nakata, 2001) and, in any case, was never intended for and is not appropriate for individual-level analyses: “The usefulness of the country scores is not for describing individuals, but for describing the social systems these individuals are likely to have built” (Hofstede, 1991, p. 253). ⁎ Corresponding author. Tel.: +1 757 221 2871; fax: +1 757 221 2937. E-mail address: [email protected] (T.A. Mooradian). 0148-2963/$ - see front matter © 2006 Elsevier Inc. All rights reserved. doi:10.1016/j.jbusres.2006.01.015

Nevertheless, regardless of Hofstede's explicit intent, direct correspondence between cultural and individual-level differences is often presupposed (e.g., Carpenter and Radhakrishnan, 2000; Nasierowski and Mikula, 1998). As van de Vijver and Poortinga (2002) note, “country-level indicators that are derived from individual-level data, such as Hofstede's (1980) four dimensions, are repeatedly and almost unavoidably applied at the individual level… It is almost a catch-22 to say that social indicators cannot be applied to the level from which they are clearly derived” (p. 145). In fact, the structure of Hofstede's values and the validity of the associated measures have been shown to be different at different levels of analysis (Bearden et al., 2006). Like many social scientists, marketing and consumer researchers are regularly concerned with understanding and predicting the behavior of individuals rather than or along with understanding cultures or nations. A personality-based approach to national character offers the distinct advantage of mapping both levels of analysis directly. The remainder of this paper has the following organization: first, advances in personality psychology are outlined with special attention to the emergence of the “Five Factor Model” or “Big Five.” Second, advances in cross-cultural psychology and

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in the comparison of social science constructs, including personality traits, across cultures are briefly reviewed. Due to its prominence in the literature and to its centrality in the subsequent empirics, particular attention is given to Extraversion (one of the Big Five) and the establishment of universality and measure comparability for Extraversion across nations, languages, and cultures. That is, Extraversion-and-culture is reviewed in some detail as an archetype of the progress in the personality-and-culture paradigm more generally, which is our central thesis. We then specifically report evidence of personality traits' explanatory power, linking Extraversion with nation-level reliance on word-of-mouth sources of product information across 11 countries and five continents. Finally, we compare Extraversion's predictive power with that of Hofstede's ecological constructs (we find Extraversion to have superior explanatory power). 1. Personality 1.1. Recent resurgence After decades of competing taxonomies and disappointing results, the 1990s saw “a dramatic upsurge” and “vitality” in personality scholarship (Funder, 2001, p. 198) as a result of: important advances in psychometrics and assessment; widespread recognition of the effects of situations, traits, and situation–trait interactions on behaviors; and emerging consensus that personality differences are well organized hierarchically within five broad factors (the “Five-Factor Model” or “Big Five”): Extraversion (E), Neuroticism (N), Openness to Experience/Intellect (O), Agreeableness (A), and Conscientiousness (C) (see Funder, 2001; McCrae, 2004).

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statistical and analytical progress in establishing validity and equivalence, and advancements in computational and communication technologies facilitating data collection and scholarly collaboration across nations and cultures (Church, 2001a; Church and Lonner, 1998a; Harkness et al., 2003; McCrae, 2000a; McCrae and Allik, 2002; van de Vijver and Leung, 1997). 2.1. Concerns regarding bias, equivalence and nomological validity Three types of bias can threaten personality-and-culture studies and intercultural comparisons: construct bias, method bias, and item bias (for recent, thorough reviews and syntheses, see Church, 2001c; Harkness et al., 2003; van de Vijver and Leung, 1997, 2001; Scholderer et al., 2005). Construct bias occurs when constructs are not culturally universal or when the behaviors associated with a construct are not the same across cultures. Method bias arises from characteristics of the instruments or methods used to measure and study a construct; sampling, instruments, and administrations can all contribute to method bias. Finally, item bias refers to item-level differences in the construct measurement. The absence of bias of any type is equivalence and the strongest equivalence is “scalar equivalence” or “full score comparability” (van de Vijver and Leung, 1997, 2001; Scholderer et al., 2005). Generalization of the nomological networks or “criterion-related” validity of intercultural personality traits and trait measures is an important condition toward establishing construct and method validity and equivalence (e.g., Church, 2001c; Church and Lonner, 1998b and van Hemert et al., 2002). These methodological concerns and advances that address them may be clarified with reference to the instance of trait Extraversion.

1.2. The five-factor model 3. Extraversion-and-culture The high-level traits in the “Big Five” explain much of the variance in the numerous traits and trait taxonomies that had been proposed earlier. These “Big Five” subsume myriad narrower, more specific traits, “facets” or “subcomponents”. A growing body of evidence indicates that these five high-level traits are “endogenous basic tendencies” tied to genetically shaped, biologically based response systems, largely unaffected by environmental factors, and remarkably stable throughout adulthood (see Costa and McCrae, 2001; McCrae, 2004). 2. Personality-and-culture The description and comparison of cultures in terms of typical personality profiles date back to the early Greeks and were particularly active during the early-to-mid-20th century among social scientists including such eminent pioneers as Margaret Mead and Edward Sapir (e.g., Mead, 1935; Sapir, 1949; for a thorough history, see LeVine, 2001). After intervening decades of relative inattention and disfavor, the study of personality-and-culture is undergoing a revival. Advances in personality-and-culture include methodological improvements in the cross-cultural measurement of personality,

Most personality-and-culture scholars now agree that the high-level traits in the Five-Factor Model generalize across cultures, coexisting with indigenous traits in some cultures (e.g., Katigbak et al., 2002; McCrae, 2002, 2004; McCrae et al., 2004, 2005). McCrae has asserted that the five factors “are not inventions of Western psychologists; they are part of human nature-dimensions of enduring dispositions that somehow find expression in every culture” (2001, p. 842). Extraversion, in particular, has been well established as a cultural universal (see, e.g., Lucas et al., 2000). Measures of Extraversion have been validated across languages and cultures. Finally, Extraversion has been linked with other nation-level parameters (e.g., work ethic, achievement motivation, and savings) in nomological systems supporting the validity of this trait in describing an important aspect of national character (Kirkcaldy et al., 1998; Lynn and Martin, 1995). 3.1. Extraversion Within that five-factor model, Extraversion is defined as energetic, cheerful, and sociable (i.e., predisposed toward

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positive affect and preferring interpersonal interaction; see, e.g., Costa and McCrae, 2001; Lucas et al., 2000; Watson and Clark, 1997). “The most commonly recurring themes [in definitions of Extraversion] are those of Ascendance and Sociability—in all of these views, extraverts are gregarious, friendly, dominant and socially facile” (Watson and Clark, 1997, p. 771). Lucas et al. (2000) contend that sensitivity to rewards constitutes the core of Extraversion across cultures, but concur that “sociability is undoubtedly an important part of Extraversion” (p. 452). Very similar forms of Extraversion have been identified across myriad cultures: in strictly emic and in emic-etic approaches (e.g., Bond, 2000); in comprehensive studies of natural languages even when the generalization of other domains among the Big Five is more equivocal (Saucier and Goldberg, 2001); and in studies utilizing nonverbal measures (Paunonen et al., 2001). 3.2. Methods and metrics Two extensive research programs have compared personality structure, measurement, and levels across many cultures and have included closely related markers of Extraversion. First, in the earlier research program of cross-cultural extensions, Sybil Eysenck and her colleagues conducted numerous bi-national studies across several decades comparing various nations to an English referent on the Eysenck Personality Questionnaire or EPQ (Barrett and Eysenck, 1984; Barrett et al., 1998; Lynn and Martin, 1995). Barrett and Eysenck (1984) extrapolated comparable scores across 25 countries from those data. Lynn and Martin (1995) augmented that compilation with scores for 12 additional countries. Although those comparisons were criticized (e.g., Bijnen et al., 1986), more recent and more rigorous analyses, some by the same critics, have supported the structure of at least the EPQ-Extraversion and EPQ-Neuroticism scales (Barrett et al., 1998; van Hemert et al., 2002). Applying multilevel factor analysis and extensive nomological tests, van Hemert et al. (2002) conclude that “the constructs of Extraversion and Neuroticism appear to have the same psychological meaning within and across countries” (p. 16) and “two EPQ scales (Extraversion and Neuroticism) were convincingly equivalent at an individual and country level” (p. 18). The second, more recent of the two cross-cultural research programs has extended the Revised NEO Personality Inventory (NEO-PI-R, which includes Extraversion) across at least 50 countries (see McCrae, 2001, 2002). These studies, sampling both college students and general population, have identified parallel structure as well as similar patterns of personality development across age groups and genders. McCrae has declared “(t)he methodology of comparing trait levels is substantially worked out, and the five-factor model provides a framework for comprehensive personality assessment” (2000b, p. 25). It is noteworthy that others are less optimistic about establishing intercultural comparability: “a major challenge for cross-cultural personality studies is that equivalence of constructs and measures will rarely, if ever, be fully met, so future research should focus on the impact of violations of

equivalence on cross-cultural comparisons” (Church, 2001b, p. 798). 3.3. Intercultural correlates of extraversion If full scalar equivalence is resistant to incontrovertible statistical tests, the generalization of nomological networks nevertheless corroborates the validity of intercultural differences (or highlights anomalies and limitations; see, e.g., Church and Lonner, 1998b; McCrae, 2001, 2002; Paunonen and Ashton, 1998). “As in any problem of construct validity, there is no single method that establishes the metric equivalence of translations… but a pattern of evidence can make a compelling case” (McCrae, 2000b, 18–19). Paunonen and Ashton (1998) argue “perhaps the best evidence for the cross-cultural applicability of an imported personality measure is the extent to which it predicts different variables consistently across cultures, variables that have some social significance” (p. 166). Limited research has connected intercultural differences in Extraversion to nomological networks of social behaviors. Lynn and Martin (1995) validated their compilation of country-level EPQ-Extraversion scores by correlating them with countrylevel “work ethic” and national rates of suicide and homicide. Others have linked Lynn and Martin's Extraversion scores with work attitudes including achievement motivation, mastery, and saving (Kirkcaldy et al., 1998), traffic fatalities (Lajunen, 2001), and the number of tipped professions (Lynn, 2000). Yang and Lester (2000) linked Lynn and Hampson's (1975) index of Extraversion with unemployment across 18 countries. McCrae (2001), in validating his 26-country compilation of intercultural NEO-PI-R scores, related NEO-Extraversion with subjective well-being, and Hofstede's Power Distance and Individualism. McCrae (2002) extended those comparisons to 36 countries, replicating the relationships with Power Distance and Individualism and, in addition, linking Extraversion to Long-Term Orientation and EPQ Extraversion. 3.4. Summary of methodological issues Although proof of full-metric equivalence is allusive, the literature appears to be converging on an understanding that certain high-level traits, including Extraversion, are universal and that specific measures appear to tap those traits across cultures and languages (Hofstede and McCrae, 2004). McCrae (2002) argues that, “in a large sample of traits and cultures, all of the various sources of bias might cancel out, leaving reasonably comparable scores” (p. 106). An emerging body of empirics supports the criterion validity of these country-level comparisons. We next review information search before motivating the influence of Extraversion. 4. Consumer external information search Understanding consumer information search “is critical to firms' strategic decision making” (Moorthy et al., 1997, p. 263; Ratchford et al., 2003). External information sources have traditionally been classified using two distinctions: independent

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versus advocate (i.e., “marketer-controlled” or “seller-dominated”) and impersonal (i.e., “mass”) versus personal/interpersonal (i.e., “word-of-mouth;” Andreasen, 1968; Beatty and Smith, 1987; Schmidt and Spreng, 1996). 4.1. The potency of word-of-mouth One of the most important sources of product information is personal/interpersonal. “Informal conversation is probably the oldest mechanism by which opinions on products and brands are developed, expressed, and spread… Word-of-mouth emerges as one of the most important, if not the most important source of information for the consumer” (Arndt, 1967, p. 1 and 70; also see Goodman, 1999). The influence of word-of-mouth has been studied extensively in the marketing management and consumer psychology literatures (e.g., Dye, 2000; Brown and Reingen, 1987). Word-of-mouth has been shown to be particularly important with regard to services (Zeithaml et al., 1996) and the diffusion of innovations (Mahajan et al., 1990), and is a closely related and consequential outcome of consumer satisfaction and loyalty (Oliver, 1997; Reichheld, 1996). Word-of-mouth has been linked with a variety of personality traits or trait-like constructs including Extraversion (Mooradian and Olver, 1997) and traits or facets subsumed by Extraversion such as “sociability” (Lau and Ng, 2001) and “social needs” (Reynolds and Beatty, 1999). Word-of-mouth has also been related to Extraversion in the form of “Opinion Leadership”: “A very consistent attribute of opinion leaders, from the early studies and across numerous areas of leadership and personal influence was their social activity and gregariousness” (Weimann, 1999, p. 79). 4.2. Word-of-mouth across cultures and nations Limited research has considered information search or source preferences across nations or cultures. Money et al. (1998), noting that “(v)irtually no [previous] WOM studies have been undertaken on a cross-national basis” (p. 77), found strong support for the hypothesis that the Japanese firms rely on word-of-mouth referrals more than American firms and on stronger interpersonal ties in sourcing industrial services. They explained those differences with reference to Hofstede's Individualism and Uncertainty Avoidance dimensions and to the High- versus Low-Context cultural distinction, but they did not test those relationships. Dawar et al. (1996), surveying students at a “major European business school,” found that Uncertainty Avoidance and Power Distance (for the students' home countries) predicted reliance on interpersonal sources of product information. Keillor et al. (2001) found that level of economic development was inversely related to the influence of personal sources such as family and friends; they did not consider cultural or individual differences across nations. Pornpitakpan (2000) referenced Hofstede's Uncertainty Avoidance to explain the observation that, “in making purchase decisions, Japanese are apt to rely more heavily on personal sources of information than Thais, and Thais are apt to do so more heavily than Americans” (p. 64).

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4.3. Hypothesis Based on the fundamental tendency of Extroverts to prefer and seek out social interaction – that is, based on the sociability element of Extraversion – we hypothesize that cultures characterized by higher levels of Extraversion will rely on word-of-mouth for product information more than cultures with lower Extraversion. 5. Study 5.1. Word-of-mouth data Word-of-mouth data were obtained from the 1997 DDB Needham World Styles Survey (see Horn, 2000). The database includes 15,520 responses from subjects in 12 nations on five continents (Mexico is excluded from further discussion because of a lack of matching scores on Extraversion). We removed cases with multiple “primary” sources (236 subjects), no source (258), or missing data (65) on these items, leaving 14,961 cases for analysis. A summary of sampling and survey methodology is presented in Table 1. Seven items querying subjects' “primary source of product information” (television; radio; friends or family, newspapers, magazines, the Internet, or direct mail) were included within the extensive World Styles Survey. We computed the dependent variable, reliance on word-of-mouth, as the percent of respondents in each country indicating “friends or family” as their primary source of product information (Table 2).

Table 1 Word-of-mouth sample characteristics by country Country

Subsample size (% of total sample)

Coverage

Data collection format Multi-stage probability sampling, face-to-face Random probability sampling, face-to-face Multi-stage probability sampling, face-to-face Random sample, phone interview

Japan

1362 (8.8)

National

China

1000 (6.4)

Shanghai

Australia

1033 (6.7)

National

Europe:

National

France 1007 (6.5) Germany 1005 (6.5) Italy 1058 (6.8) Spain 1002 (6.5) UK 933 (6.0) US 3462 (22.3)

National

Canada

1389 (8.9)

National

Brazil

1268 (8.2)

Mexico

1001 (6.4)

Sao Paulo Rio de Janiero Mexico City Guadalajara Monterey

Total

15,520

Source: DDB Needham Worldwide (Horn, 2000).

Mail panel, self-administered Mail panel, self-administered Multi-stage probability sampling, face-to-face Stratified sampling, random block, face-to-face

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Table 2 Extroversion and word-of-mouth scores, and sample sizes Country

Extraversion EPQ b

Australia (AU) Brazil (BR) Canada (CA) China (CN) UK (UK) France (FR) Germany f (GR) Italy (IT) Japan (JP) Spain (SP) USA (US)

NEO-PI-R c

SD d

Score

n

Score

ne

23.17 17.58 20.67 13.01 18.94 11.81 18.88 17.46 17.17 17.98 20.83

1452 1396 1652 2097 17,725 866 2538 2609 258 2986 4153

– – 51.70 44.50 – 47.3 47.3 46.6 41.7 48.3 50.0

– – 282/566 115/86 – 333/733 1475/1255 341/349 340/341 89/107 648/741

Word-ofmouth a (%)

Factor score

1.12

– –

1.80

1.38 – – − 0.88 0.29 − 0.60 − 1.06 − 0.38 1.27

– – 0.98 − 0.06 0.83 − 1.21 − 0.51 − 1.42 2.09

15 4 15 8 11 7 14 6 7 9 19

Percent of respondents indicating “friends or family” as primary source of product information. van Hemert, van de Vijver, Poortinga, and Georgas (2002, Table 1, p. 7). c Socio-demographic (SD) markers from Lester (2000, Table 2, p. 37) derived from factor analysis of socio-demographic variables including country-level rates of murder and other crimes, divorce, cigarette consumption, illegitimacy, and accidents. d Men/women. e McCrae (2002, Tables 1 and 3 107, 112). f Scores for Germany on the EPQ and the socio-demographic index are for West Germany. a

b

5.2. Extraversion data

5.3. Analysis and results

From different data sets than the DDB Needham World Styles Survey, intercultural Extraversion scores were drawn from the two major cross-cultural research programs focused on the EPQ and NEO-PI-R, respectively (see Table 2; see van Hemert et al., 2002; McCrae, 2002). A third source of data was Lester's (2000) factor analysis of socio-demographic indicators, which identified Extraversion (along with Neuroticism). Additionally, we computed a single latent Extraversion factor from these three specific scores using Principle Components Analysis using varimax rotation (Eigen value 2.03, 67.6% of variance explained; factor loadings are shown in Table 3). In factor analyses of this type “the increased reliability of aggregate scores may compensate for the small number of observations” (McCrae, 2001, p. 831; also see Hofstede, 1980 and Hofstede and McCrae, 2004).

Correlations between the variables are presented in Table 3. Fig. 1 graphs country-level reliance on word-of-mouth with the Extraversion factor score, which has the highest correlation with reliance on word-of-mouth, and the EPQ-Extraversion score, which had the highest overlap of scores with the DDBNeedham word-of-mouth data. The correlations among Extraversion scores indicate acceptable convergent validity. Most importantly, these analyses identify a strong, direct relationship between various country-level markers of Extraversion and reliance on Word-of-Mouth that are, notwithstanding the small number of cases, significant and meaningful in magnitude.

Measure

NEO

EPQ SD Factor a Word-of-Mouth

0.528 ⁎ [8] 0.588 ⁎ [7] 0.821 [7] 0.691 ⁎⁎

EPQ 0.552 ⁎ [9] 0.781 [7] 0.694 ⁎⁎⁎ [11]

SD

0.863 [7] 0.891 ⁎⁎⁎⁎

Factor

AU CN

CN

Extraversion

Table 3 Country-level correlations of extraversion measures and word-of-mouth

2

UK

0

US

GR

SP IT

JP SP

IT

0.934 ⁎⁎⁎⁎ [7]

Cases (i.e., overlapping countries) in brackets. NEO = McCrae's NEO-PI Extraversion scores (McCrae, 2002). EPQ = EPQ Extraversion (van Hemert et al., 2002). SD = Socio-Demographic Extraversion Factor (Lester, 2000). Factor = Extraversion factor score. a Factor loadings for single-factor Principle Components Factor Analysis. ⁎ p b 0.10. ⁎⁎ p b 0.05. ⁎⁎⁎ p b 0.01. ⁎⁎⁎⁎ p b 0.001.

BR

US

FR JP CH FR

-2 0.0

.1

.2

Reliance on Word-of-Mouth Fig. 1. Plot of reliance on word-of-mouth with Extraversion factor scores and EPQ-E score. ●—standardized (Z) EPQ-E scores; ×—Extraversion factor scores. See Table 2 for country abbreviations.

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made important recent advances. Compilations of intercultural trait comparisons are available from recent, large samples across many countries and cultures. These traits, measures, and scores have been subject to extensive, rigorous psychometric testing and validation. Importantly, these traits describe both intercultural and individual differences. In a preliminary analysis drawing on large samples from 11 countries across five continents, we find empirical support for the robust association between Extraversion, a fundamental and universal personality trait, and reliance on word-of-mouth, an important consumer behavior. Additionally, we find significant marginal predictive power for Extroversion over Hofstede's ecological dimensions of culture at the country level. People in cultures characterized by higher Extraversion are more likely to rely on interpersonal sources of information, that is, on word-of-mouth for product information. This finding should inform managers trying to create “buzz” or hoping to accelerate the diffusion of innovations – some cultures are more predisposed to such information flows than others (Dye, 2000; Gatignon et al., 1989; Mahajan et al., 1990).

5.4. Extraversion versus Hofstede's ecological scores Hierarchical regressions compared country-level Extraversion with Hofstede's dimensions with regard to variance explained in reliance on Word-of-Mouth (Table 4). Step-wise regressions of all four Hofstede variables on reliance on Word-of-Mouth indicate that Power Distance mediated any significant effects of Individualism, Uncertainty Avoidance, and/or Masculinity. Hierarchical regressions, shown in Table 4, indicate that Extraversion explains more variance in reliance on Word-of-Mouth sources than Power Distance. When Extraversion is entered first and Power Distance is entered second (Regression A in Table 4), Power Distance explained no significant additional variance. In comparison, when Power Distance is entered first and Extraversion is added (Regression B in Table 4), Extraversion explains significant additional variance, approximately 30% additional variance; Power Distance becomes insignificant when Extraversion is entered. The same procedure using the other markers of Extraversion (i.e., the NEO, EPQ, and Socio-Demographic scores; not shown) produced comparable results similarly supportive of the predictive power of Extraversion vis-à-vis Hofstede's Power Distance. Although Power Distance clearly mediated the effects of Hofstede's other variables, specific relationships between reliance on Word-of-Mouth and both Individualism and Uncertainty Avoidance have been proposed (as reviewed above; Money et al., 1998; Dawar et al., 1996; Pornpitakpan, 2000). Therefore, we also test Extraversion against those variables in the same hierarchical regression procedure. The results of those analyses indicate that Extraversion was related to significant variance in reliance on Word-of-Mouth beyond that explained by any of those variables. None of those variables predicted significant variance beyond that explained by Extraversion. (These data and analyses are of explanatory power at the country level. As discussed, Hofstede's dimensions, by definition, offer no explanatory power at the individual level.)

6.1. Future research The measure used in the DDB World Styles survey to capture information source preference is coarse but straightforward. Future research into cross-cultural differences in information search and other consumer phenomena will require richer, more complex measures and therefore require similar attention to adapting, validating, and establishing equivalence as has been devoted to cross-cultural personality trait measures, as reviewed above (see Harkness et al., 2003; McCrae, 2002, 2004; McCrae et al., 2004; van de Vijver and Leung, 1997). Finally, due to the nature of our data, our analysis uses nation-of-survey-collection as a surrogate for culture, a precarious supposition for several reasons (see Sivakumar and Nakata, 2001, 559–560). Future research should be improved by differentiating cultures from nations. Future research could also extend intercultural personality analysis to other universal traits, to other important consumer behaviors, and could address differences at both the cultural and individual levels. Such ‘multi-level analyses’ compare factor structures and relationships among variables across levels of aggregation (see van de Vijver and Poortinga, 2002). As noted, Hofstede's (1991) well-known and widely

6. Discussion and contributions We have proposed personality traits as useful descriptors of national character. Traits are grounded in the extensive tradition of theory and empirics in personality psychology and, in particular, in personality-and-culture. Both of these areas have

Table 4 Hierarchical regressions of national character variables on nation-level consumer reliance on word-of-mouth sources of information Regression

Model

Independent variables and βs

A

1⁎ 2 ⁎⁎ 1 ⁎⁎ 2 ⁎⁎

EFS EFS PD PD

B

EFS = Extraversion factor score. PD = Power Distance (Hofstede, 1980). ⁎ p b 0.01. ⁎⁎ p b 0.05.

0.934 ⁎ 0.857 ⁎⁎ − 0.767 ⁎⁎ − 0.100

PD EFS

−0.100 0.857 ⁎⁎

R2

Adj. R2

0.873 0.877 0.589 0.877

0.847 0.815 0.506 0.815

ΔR2 0.04 0.288 ⁎⁎

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adopted framework does not inform our understanding of individual-level behaviors: “the culture of a country – or other category of people – is not a combination of properties of the ‘average citizen’, nor a ‘modal personality’…(c) onfusing the level of the individual with the level of the society is known in the social sciences as the ecological fallacy” (p. 112, emphasis original). Our archival data do not allow testing of relationships at the individual level but future data collections should be planned to facilitate such analyses. 6.2. Associated concerns Finally, several concerns about identified cross-cultural differences are largely beyond the scope of this study. Do dimensions of culture explain differences in traits or do traits explain features of culture? Hofstede contends that culture influences traits while McCrae argues that cultural values tend to be reflections of personality (McCrae, 2004 and Hofstede and McCrae, 2004). Also, a genetic and biological role in shaping traits and behavior suggests ethical as well as empirical challenges that must be considered and investigated further. Are cultural differences genetically determined? “That possibility is likely to make many social scientists uncomfortable because any such genetic differences between groups might fuel racist or eugenicist agendas” (McCrae, 2000b, p. 21). Although these traits have few normative (i.e., evaluative or “good–bad”) connotations and the between culture differences are not particularly large, especially vis-àvis within culture variance, it is important to keep these concerns in mind when comparing cultures along traits or any other characteristics. “A trait perspective on human nature and culture offers great intellectual promise. It addresses fundamental issues with the widest possible applicability; it has already produced provocative findings; and it inspires a rich agenda for future research” (McCrae, 2004, p. 13). We propose that that rich future research will include productive explorations in consumer psychology and cross-cultural marketing. Acknowledgements The authors express appreciation to Marty Horn and Chris Callahan of DDB Needham for their assistance and for making these data available for analysis. The first author also thanks the Austrian American Education Foundation (i.e., the Austrian Fulbright Commission) and the Wendy and Emery Reves Center for International Studies at the College of William and Mary for their support of this project.

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Journal of Business Research 59 (2006) 786 – 792

Debiasing omission neglect Frank R. Kardes a,⁎, Steven S. Posavac b , David Silvera c , Maria L. Cronley d , David M. Sanbonmatsu e , Susan Schertzer a , Felicia Miller a , Paul M. Herr f , Murali Chandrashekaran g a

University of Cincinnati, United States University of Rochester, United States c University of Tromso, Norway d Miami University, United States e University of Utah, United States f University of Colorado, United States Australian Graduate School of Management, Australia b

g

Received 1 April 2005; received in revised form 1 November 2005; accepted 1 January 2006

Abstract Two experiments investigated the effectiveness of two new procedures for improving judgment by increasing sensitivity to missing information. When consumers are insensitive to important missing information, overly extreme product evaluations are formed. However, when consumers are sensitive to important missing information, they form more moderate and appropriate evaluations. Sensitivity to missing information was increased by encouraging consumers to consider their criteria for judgment before receiving product information (Experiment 1) and by asking consumers to rate presented and missing product attributes before providing overall product evaluations (Experiment 2). Both procedures were effective for improving judgment by reducing omission neglect. © 2006 Elsevier Inc. All rights reserved. Keywords: Judgment; Product evaluation; Missing information; Debiasing

1. Introduction Advertisements, brochures, pamphlets, and other promotional materials typically provide information that marketers want consumers to know and typically omit information that marketers do not want consumers to know. Although consumers often recognize that marketers are not impartial providers of information, consumers typically rely heavily on presented information at the expense of other information that marketers fail to mention. Omission neglect, or insensitivity to missing or unmentioned options, attributes, or issues, occurs when consumers form inappropriately extreme evaluations on the basis of weak evidence (Sanbonmatsu et al., 1992, 2003, 1997, 1991). ⁎ Corresponding author. College of Business, University of Cincinnati, Cincinnati, OH 45221-0145, United States. Tel.: +1 513 556 7107; fax: +1 513 556 0979. E-mail address: [email protected] (F.R. Kardes). 0148-2963/$ - see front matter © 2006 Elsevier Inc. All rights reserved. doi:10.1016/j.jbusres.2006.01.016

For example, products described by a small amount of information are often evaluated as extremely and confidently as products described by a large amount of information. This occurs because consumers overestimate the diagnosticity or information value of the presented evidence when the limitations of the evidence are overlooked. Even a little evidence seems like a lot when omissions are not apparent. Under some conditions, consumers are more sensitive to omissions, and this prompts them to adjust their judgments in light of evidential limitations. When consumers are highly knowledgeable regarding the target product, and when the judgmental context contains cues or reference points, the salience of missing information is increased, and judgments are adjusted toward more normatively appropriate moderate evaluations (Muthukrishnan and Ramaswami, 1999; Sanbonmatsu et al., 1991, 1992, 1997, 2003). This study investigates the effectiveness of two new procedures for reducing omission neglect: asking consumers to

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consider their criteria for judgment before receiving product information (Experiment 1), and asking consumers to rate presented and missing product attributes before providing overall product evaluations (Experiment 2). We expected that each of these procedures would heighten cognizance of missing information, and accordingly that each would be a useful technique for debiasing consumers' tendency for omission neglect. 2. Experiment 1 The purpose of Experiment 1 is to investigate the effectiveness of a priori criteria consideration as a technique for improving judgment by increasing sensitivity to omissions. Half of the participants were instructed to consider their criteria prior to receiving product information. We predicted that the activation of standards prior to exposure to the automobile description would reduce evaluation extremity and diminish estimations of the perceived sufficiency of the given information. 2.1. Methods Seventy-one undergraduates participated in groups of 2 to 4 and were randomly assigned to one of two conditions (criteria consideration vs. no criteria consideration). Participants in a study of “product perceptions” read a transcript from a fictional radio program called the “Auto Spot” sponsored by “Consumer Advocates”. All participants received a description of a compact car model labeled the “Model A”. The “Model A” was always described in terms of price (under $12,000) and three positive attributes. The three positive attributes describing the “Model A” were varied with one of three different sets of three attributes being presented. Participants were told that the program had been transcribed exactly, except that the name or names of the automobile model had been replaced with pseudonyms. All of the automobile attributes were highly favorable. Prior to receiving the transcript containing the information about the “Model A”, half of the participants were prompted to consider which attributes are the most important to consider in the assessment of an automobile. Participants were specifically asked to rank order nine automobile attributes in terms of their importance. The nine attributes that were ranked were those making up the three descriptions used in the experiment. In addition to rank ordering the attributes participants were asked to provide a brief (8 lines or less) explanation for their rankings. That is, they were asked to explain “why the attributes that you ranked high are more important to you than the attributes that you ranked low”. After reading the transcript, participants evaluated the “Model A” automobile, assessed the sufficiency of the information presented, and indicated their confidence in their evaluation. Evaluation was measured on a 9 point scale anchored by − 4 = “Highly unfavorable” and + 4 = “Highly favorable”. Confidence was measured on a 9 point scale anchored by − 4 = “Not at all confident” and + 4 = “Highly confident”. Sufficiency was measured on a 10 point scale anchored by 0 = “Not at all enough” and 9 = “Highly sufficient”. The midpoint of the scale (between 4 and 5) was labeled “Somewhat sufficient”.

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2.2. Results and discussion The counterbalancing of the sets of attributes describing the “Model A” automobile is ignored in the reported analyses, as it was not of primary theoretical interest and did not interact significantly with the experimental manipulation to affect any of the primary measurements. We conducted a series of regressions to explore the role of criteria consideration on evaluations, confidence, and the perceived sufficiency of the given information. As expected, evaluations of the Model A tended to be much less extreme (Ms = 1.81 vs. 2.69), b = − .88, t(69) = − 2.82, p = .006, and participants expressed much less confidence in their evaluations, (Ms = 1.02 vs. 1.91), b = − .89, t(68) = − 2.21, p = .03, when the criteria for evaluating an automobile were first considered as opposed to not. Further analysis indicated that participants who were prompted to be cognizant of their evaluative criteria perceived the given information to be much less sufficient than participants who did not first consider their evaluative criteria (Ms = 3.42 vs. 5.46), b = − 2.04, t(69) = − 4.03, p b .001. We performed additional analyses using the procedure recommended by Baron and Kenny (1986) to examine the extent to which the weighting of the evidence mediated the effects of considering the criteria on evaluations of the “Model A” automobile and confidence in evaluations. Because direct measurements of the perceived importance of the presented vs. non-presented attributes were not available, the sufficiency judgments served as the estimate of the weighting of the given evidence. A series of regressions that complement those reported earlier produced outcomes that met all of the Baron and Kenny mediation criteria for both dependent variables. Specifically, there were significant associations between the perceived sufficiency of the given information and evaluations, b = .36, t(69) = 6.57, p b .001, as well as confidence, b = .37, t(68) = 4.70, p b .001. A model in which both the consideration of criteria and the perceived sufficiency of the given information were used to predict evaluations revealed a significant effect of the proposed covariate, b = .35, t(68) = 5.63, p b .001, but the previously significant effect of the consideration of criteria became nonsignificant, b = − .17, t(68) = − .59, p = .60. Similarly, a model in which confidence was regressed on each of these predictors revealed a significant effect of perceived sufficiency of the given information, b = .35, t(67) = 4.01, p b .001, but the previously significant effect of the consideration of criteria became non-significant, b = − .20, t(67) = − .50, p = .62. These results are summarized in the top panel of the Appendix. Finally, Sobel tests confirmed that the effects of consideration of the criteria on evaluation, z = − 3.44, p b .001, and confidence in evaluation, z = − 2.00, p b .05, were mediated by altered perceptions of the sufficiency of the information. Overall, these results demonstrate that heightened cognizance of the standards to be used in judgment prior to stimulus exposure contributes to more moderate judgment by attenuating the subjective weighting of the presented attributes.

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3. Experiment 2 The purpose of Experiment 2 is to investigate the effectiveness of rating presented and missing attributes before providing overall evaluations as a technique for improving judgment by increasing sensitivity to omissions. Half of the participants rated attributes before and half rated attributes after providing overall evaluations. We predicted that the before condition would be effective, particularly for participants low (vs. high) in the need for cognitive closure (Kruglanski and Webster, 1996). A high need for cognitive closure refers to a desire to form judgments as quickly as possible and to maintain these judgments for as long as possible. As the need for cognitive closure increases, consumers are more likely to draw snap judgments that have obvious implications for action. This often involves heuristic processing and focusing selectively on information that is particularly easy to process. Information that is difficult to process, such as missing information, is frequently ignored. Conversely, individuals low in the need for cognitive closure are more concerned about accuracy than speed. Consequently, such individuals are more sensitive to information that is difficult and time-consuming to process, such as missing information. We predict that low need for cognitive closure individuals should be sensitive to omissions across conditions and should therefore be less influenced by debiasing techniques. Because high need for cognitive closure individuals are generally insensitive to omissions, increasing sensitivity using the attribute rating before evaluation debiasing technique should be particularly effective for these individuals. As an exploratory variable, half of the participants received the product information in an attribute list format and half received this information in a narrative format. Prior research suggests that consumers may be less sensitive to omissions when product information is represented holistically rather than in a piecemeal fashion (Adaval and Wyer, 1998). 3.1. Methods One hundred twenty one undergraduates were randomly assigned to order (rate attributes before or after providing overall evaluations) and format (list or narrative) conditions, and were blocked into high or low need for cognitive closure conditions based on a median split performed on their scores on the Need for Cognitive Closure scale (Webster and Kruglanski, 1994). Participants received information, ostensibly excerpted from an ad, about a new digital camera referred to as brand X. Information about five favorable attributes was presented either in an attribute list format or in a narrative format that stated: “Imagine that you are planning a vacation to beautiful Hawaii. With your new [brand X], you now have 3 megapixels of picture resolution at your fingertips. The [brand X] is compact and lightweight (10 ounces), which means you can carry it with you almost anywhere. With its long flash range (15 feet) and long battery life (450 shots), it is easy to take many beautiful pictures of palm trees, beaches,

and all of the wonderful sights you would expect to see in a tropical island paradise”. Half of the participants rated the five presented attributes (number of megapixels, size, weight, flash range, battery life) and three missing attributes (price, picture quality, zoom lens) before providing overall evaluations and half provided overall evaluations first. The attributes were rated on scales ranging from 1 (very bad) to 7 (very good). Overall evaluations were rated on a scale ranging from 1 (very bad) to 7 (very good) and participants rated how confident they were that their overall evaluations would be similar to the rating published in Consumer Reports on a scale ranging from 1 (not at all confident) to 7 (very confident). Participants rated how much information was missing from the ad on a scale from 1 (not very much was missing) to 7 (very much was missing) and they indicated their satisfaction with the amount of information presented in the ad on a scale from 1 (not at all satisfied) to 7 (very satisfied). 3.2. Results and discussion A 2 (measurement order: attribute ratings first or overall evaluations first) × 2 (format: attribute list or narrative) × 2 (high or low need for cognitive closure) ANOVA performed on overall evaluations yielded main effects for order, F(1, 113) = 4.64, p b 0.04, and for format, F(1, 113) = 4.12, p b 0.05, and an order by need for cognitive closure interaction, F(1, 113) = 4.15, p b 0.05. More favorable evaluations were formed in attribute after and narrative conditions. More importantly, the interaction showed that individuals low in the need for cognitive closure were spontaneously sensitive to omissions across conditions, and therefore, did not benefit from rating attributes before versus after overall evaluations (Ms = 4.90 vs. 4.97, respectively, t b 1). By contrast, individuals high in the need for cognitive closure formed more moderate evaluations in before than in after conditions (Ms = 4.78 vs. 5.46), t(119) = 4.00, p b 0.001, indicating that rating presented and missing attributes before providing overall evaluations increases sensitivity to omissions and decreases evaluation polarization. A 2 × 2 × 2 ANOVA performed on confidence judgments showed that overall evaluations were held with greater confidence in narrative than in list conditions (Ms = 4.23 vs. 3.67), F(1, 113) = 3.93, p = 0.05. Confidence also tended to be higher when attributes were rated after rather than before providing overall evaluations, but this trend was non-significant, F(1, 113) = 2.22, p = 0.14. A 2 × 2 × 2 ANOVA performed on perceptions of missing information yielded a main effect for order, F(1, 113) = 10.10, p b 0.01. Participants were more sensitive to omissions and indicated that more information was missing when attributes were rated before rather than after providing overall evaluations (Ms = 5.08 vs. 4.20). Hence, asking consumers to rate presented and missing attributes before providing overall evaluations is an effective technique for increasing sensitivity to omissions. Rating attributes after providing overall evaluations, however, is ineffective because once consumers form a holistic

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mental representation of a product, it becomes difficult to analyze the product in terms of its discrete components (Wyer, 2004). A 2 × 2 × 2 ANOVA performed on satisfaction with the amount of information presented revealed that participants were less satisfied with the amount presented when attributes were rated before rather than after providing overall evaluations (Ms = 2.79 vs. 3.82), F(1, 113) = 17.26, p b 0.001. Satisfaction also tended to be lower when the need for cognitive closure was low as opposed to high (Ms = 3.13 vs. 3.47), F(1, 113) = 2.87, p b 0.10. The order by need for cognitive closure was marginally significant, F(1, 113) = 2.57, p = 0.11. The order manipulation tended to have a larger effect on the satisfaction judgments of individuals high (vs. low) in the need for cognitive closure. Considered together, the results show that rating presented and missing attributes before (but not after) providing overall evaluations increases sensitivity to omissions and results in more moderate overall evaluations. To provide direct evidence that perceptions of missing information mediate the effects of measurement order (attribute ratings first or overall evaluations first) on evaluation extremity, we conducted a mediation analysis using the procedure recommended by Baron and Kenny (1986). First, order predicted evaluation extremity, b = .36, t(119) = 2.10, p b 0.04, and perceptions of missing information, b = − .88, t(119) = − 3.26, p b 0.001. In addition, perceptions of missing information predicted evaluation extremity, b = − .20, t(119) = − 3.60, p b 0.001. When order and perceptions of missing information were entered simultaneously in the regression model predicting evaluation extremity, the effect of perceptions of missing information remained significant, b = − .18, t(119) = − 3.12, p b 0.01, but the direct effect of order did not, b = .21, t(119) = 1.20, p = 0.24. A Sobel test revealed that the difference in the direct effect between the nonmediated and mediated models was significant, z = 2.24, p b 0.03. Hence, the effect of measurement order on evaluation extremity was mediated by perceptions of missing information. These results are summarized in the bottom panel of the Appendix. Although consumers are often insensitive to omissions, detecting omissions is a critical precursor to inference formation. Consumers cannot infer values for missing information if they fail to notice that information is missing. In the present study, perceptions of missing information were higher and satisfaction with the amount of information presented was lower when attribute ratings were measured prior to (rather than after) overall evaluations. Consequently, the omission neglect model suggests that inference formation should be more likely when attributes were measured prior to overall evaluations. In addition, inferences should have a greater influence on overall evaluations when attributes were measured prior to overall evaluations. Both of these effects, however, should occur only when consumers possess an implicit theory that connects the presented information to the missing information (Kardes and Sanbonmatsu, 1993). If consumers assume that presented and missing attributes are correlated, they can infer values of missing attributes from values of presented attributes. To test the hypothesis that inference formation was more likely when consumers were sensitive to omissions, an

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inference judgment index was formed by averaging ratings of the three missing attributes (price, picture quality, zoom lens). A 2 (order) × 2 (format) × 2 (need for cognitive closure) ANOVA performed on this index yielded a significant main effect for order, F(1, 113) = 5.63, p b 0.02. As expected, more favorable inferences were formed when consumers were sensitive to omissions because attribute ratings were measured before (vs. after) overall evaluations (Ms = 4.34 vs. 3.81). An index of ratings of presented attributes was formed by averaging ratings of the five presented attributes (megapixels, size, weight, flash range, battery life). A 2 × 2 × 2 ANOVA performed on this index revealed no significant main effects or interactions. Ratings of the presented attributes were consistent across the experimental conditions. This result is consistent with prior research showing that consumers overestimate the importance of presented attributes regardless of which subset of attributes is presented (Sanbonmatsu et al., 2003). To test the hypothesis that inferences should have a greater influence on overall evaluations when attributes were measured prior to (vs. after) overall evaluations, the correlations between inferences and overall evaluations in attribute ratings first versus evaluations first conditions were examined. Inferences were more strongly correlated with evaluations when attribute ratings were measured first than when overall evaluations were measured first (rs = .56 vs. .18), z = 2.41, p b 0.01. By contrast, correlations between ratings of presented attributes and overall evaluations did not differ as a function of measurement order (rs = .42 vs. .46), z = 0.27, p = 0.79. This pattern suggests that inferences have a greater impact on overall evaluations when consumers are sensitive (vs. insensitive) to omissions. Sensitivity to missing information is an important precondition for the formation of meaningful inferences that influence other judgments. 4. General discussion Consumers have become accustomed to using whatever evidence is readily available to them, even limited evidence, at the expense of other information that marketers fail to mention. Omission neglect — or insensitivity to missing or unmentioned attributes, options, or issues — is particularly problematic given the nature of the world in which we live. The amount of information used to describe different types of alternatives — such as various products, services, political candidates, job applicants, defendants, medical procedures, public policies, etc. — varies dramatically as a function of advertising, interviews, reports, and media coverage. Nevertheless, when people are insensitive to omissions, they form overly extreme judgments regardless of how much or how little is known about the object of judgment (Sanbonmatsu et al., 1991, 1992, 1997, 2003). When information is limited, extreme (vs. moderate) judgments are less accurate (Griffin and Tversky, 1992), less readily updated (Cialdini et al., 1973), and less justifiable (Lerner and Tetlock, 1999). Although people typically neglect omissions, the present research shows that it is possible to debias omission neglect by increasing the salience of missing information. Two new

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debiasing procedures for increasing sensitivity to missing information were investigated: asking consumers to consider their criteria for judgment before receiving product information (Experiment 1), and asking consumers to rate presented and missing product attributes before providing overall product evaluations (Experiment 2). Both debiasing procedures were shown to be effective. The two procedures differ because a priori criteria consideration involves ranking attributes for importance before receiving a product description, whereas a priori attribute rating involves evaluating attributes before providing an overall evaluation. The two procedures are similar because both involve comparing information presented in a product description to a set of criteria. The omission neglect model also suggests that to be effective, both procedures should be implemented before an overall evaluation of a target product is formed. Once an overall evaluation is formed, insufficient adjustment of the evaluation occurs even if the implications of subsequently encountered evidence are inconsistent with the evaluation (Gilbert, 2002; Johar and Simmons, 2000). Moreover, presented information may interfere with the ability to generate or to evaluate missing information. Inhibitory control mechanisms suppress distraction due to cue competition, which may decrease the accessibility of missing information (Anderson, 2003). The present research shows that generating criteria before receiving a product description (Experiment 1) and evaluating criteria before forming an overall evaluation of a product (Experiment 2) result in more moderate evaluations of a target product. In both experiments, the effects of generating or evaluating criteria on evaluation were mediated by sensitivity to omissions. In Experiment 1, sensitivity to omissions was measured via the perceived sufficiency of the presented evidence. In Experiment 2, sensitivity to omissions was measured via perceptions of the amount of information that was missing. The two measures provide converging support for the critical role of sensitivity to omissions in evaluative judgment. The need for cognitive closure was shown to be an important moderator of the effectiveness of evaluating criteria before forming an overall evaluation (Experiment 2). Individuals high in the need for cognitive closure are less sensitive to omissions because thinking about omissions is difficult, and difficult cognitive tasks delay closure. As a consequence, individuals high (vs. low) in the need for cognitive closure benefit more from the use of debiasing techniques that increase sensitivity to omissions. However, the role of the need for cognitive closure in generating criteria prior to exposure to product information is unclear because the need for cognitive closure was not measured or manipulated in Experiment 1. Future research should address this important issue. 4.1. Managerial implications The most general managerial implication arising from this study is that consumers typically are insensitive to the absence of information that would be quite relevant for their judgments

and decisions. Thus, marketers may often find a strategy of selectively presenting information that is favorable to a brand, both absolutely and relative to competitors, while omitting unfavorable information, to be quite successful. The success of a selective presentation strategy, though, is not assured. In our experiments when consumers either were prompted to consider their criteria prior to making judgments or asked to rate the target brand on a more complete set of its constituent attributes prior to judgment making, they were more sensitive to information omission, and made more normatively appropriate moderate brand judgments. Understanding how these factors can disrupt consumers' default insensitivity to missing information is important for marketers, whether they want to encourage or discourage omission detection. Marketers may sometimes wish to leverage consumers' typical insensitivity to omissions. In such instances marketers should endeavor to preclude the omitted information from becoming salient. One means of accomplishing this aim is creating marketing designed to prevent consumers from reflecting on their criteria, and correspondingly generating the desire to acquire relevant information that is absent in the judgmental context. Specifically, impeding consumers' willingness and or opportunity to carefully reflect on the target brand may be fruitful. For example, marketing could be aimed at creating urgency through use of fear appeals, a scarcity manipulation, induced time pressure (“act now!”), or an exploding offer. When consumers are unwilling or unable to carefully reflect on a brand, they are very likely to form fast judgments based on the available information, and unlikely to either consider their criteria or try to generate attributes about which they have no information. The strategies noted above may be particularly useful because they also may induce high need for closure — a condition in which sensitivity to omissions is unlikely. In addition to reducing the likelihood of missing information generation, marketers can facilitate omission neglect by ensuring that context does not make information missing from the description of a particular brand salient. For example, automobile manufacturers offer their brands for sale in exclusive dealerships that present only one brand. Thus, the manufacturer can define the evaluative agenda consistent with brand strengths, while not mentioning liabilities. Moreover, salespeople sometimes offer deals that expire if the consumer leaves the dealership. This is likely to be a useful sales approach if the consumer is prevented from visiting another dealer, who is likely to be highlighting a different set of attributes. As another example, boutique stores often present only one or a few brands in an attempt to reduce the likelihood of competing brands highlighting each other's weaknesses. Finally, marketers should consider obtaining guarantees when making media buys that no competing brands will be advertised in proximity to their advertisements. While marketers may often take advantage of omission neglect, in other instances it may be important to prevent or counter a competitor's selective presentation strategy. One reason why continuous advertising is efficacious in maintaining market share is that the attributes on which a target brand

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excels are less likely to go unconsidered if brand and attribute knowledge are highly accessible in consumers' minds. Market leaders may be particularly susceptible to the selective presentation strategies of weaker competitors, thus it will be important to continue reminding consumers of a target brand's strengths. Indeed, if a marketer fails to make a target brand's relative strengths salient, these features that normatively should favorably impact brand evaluation and choice are unlikely to be weighed in judgment, and competitors are likely to reap market share that rightfully should be enjoyed by the target brand.

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Finally, our results have implications for consumer welfare. To the extent that consumers exhibit omission neglect in their brand judgments, they are likely to make suboptimal decisions. If individuals are taught of their chronic insensitivity to missing information, they may be more critical consumers of marketing, and more likely to evaluate available information using their own preconceived judgmental criteria. Thus, important omissions from product descriptions are likely to be recognized, judgments are likely to be more accurate, which in turn will facilitate more satisfying decision making.

Appendix A. Mediation analyses

Experiment 1 b = –.17 (b = –.88** )

Debiasing Procedure (a priori criteria consideration)

Perceived Insufficiency

b = 2.04**

Product Evaluation b = –.35**

Experiment 2 b = .21 (b = –.36* )

Debiasing Procedure (a priori attribute ratings)

Perceived Missing Information b = .88**

Product Evaluation b = –.20**

Note. ⁎Indicates significant effects at p b .05; ⁎⁎indicates significant effects at p b .001. The values in parentheses represent the direct effect of the debiasing procedure on product evaluations before perceived insufficiency (Exp. 1) and perceived missing information (Exp. 2) were added to the models. References Adaval R, Wyer RS. The role of narratives in consumer information processing. J Consum Psychol 1998;7:207–45. Anderson MC. Rethinking interference theory: executive control and the mechanisms of forgetting. J Mem Lang 2003;49:415–45. Baron RM, Kenny DA. The moderator-mediator variable distinction in social psychological research: conceptual, strategic, and statistical considerations. J Pers Soc Psychol 1986;51:1173–82. Cialdini RB, Levy A, Herman CP, Evenbeck S. Attitudinal politics: the strategy of moderation. J Pers Soc Psychol 1973;25:100–8.

Gilbert DT. Inferential correction. In: Gilovich T, Griffin D, Kahneman D, editors. Heuristics and biases: the psychology of intuitive judgment. Cambridge (UK): Cambridge Univ. Press; 2002. p. 167–84. Griffin D, Tversky A. The weighing of evidence and the determinants of confidence. Cogn Psychol 1992;24:411–35. Johar GV, Simmons CJ. The use of concurrent disclosures to correct invalid inferences. J Consum Res 2000;26:307–22. Kardes FR, Sanbonmatsu DM. Direction of comparison, expected feature correlation, and the set-size effect in preference judgment. J Consum Psychol 1993;2:39–54. Kruglanski AW, Webster DM. Motivated closing of the mind: “seizing” and “freezing”. Psychol Rev 1996;103:263–83.

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Lerner JS, Tetlock PE. Accounting for the effects of accountability. Psychol Bull 1999;125:255–75. Muthukrishnan AV, Ramaswami S. Contextual effects on the revision of evaluative judgments: an extension of the omission–detection framework. J Consum Res 1999;26:70–84. Sanbonmatsu DM, Kardes FR, Sansone C. Remembering less and inferring more: the effects of the timing of judgment on inferences about unknown attributes. J Pers Soc Psychol 1991;61:546–54. Sanbonmatsu DM, Kardes FR, Herr PM. The role of prior knowledge and missing information in multiattribute evaluation. Org Behav Human Decis Process 1992;51:76–91.

Sanbonmatsu DM, Kardes FR, Posavac SS, Houghton DC. Contextual influences on judgment based on limited information. Org Behav Human Decis Process 1997;69:251–64. Sanbonmatsu DM, Kardes FR, Houghton DC, Ho EA, Posavac SS. Overestimating the importance of the given information in multiattribute consumer judgment. J Consum Psychol 2003;13:289–300. Webster DM, Kruglanski AW. Individual differences in need for cognitive closure. J Pers Soc Psychol 1994;67:1049–62. Wyer RS. Social comprehension and judgment: the role of situation models, narratives, and implicit theories. Mahwah (NJ): Erlbaum; 2004.

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Journal of Business Research 61 (2008) 1027 – 1029

Editorial

Marketing communications and consumer behavior: Introduction to the special issue from the 2007 La Londe conference This special issue of the Journal of Business Research includes a selection of papers presented at the 34th International Research Conference in Marketing organized by the Aix Graduate School of Management (I.A.E. Aix-en-Provence), University Paul Cézanne in Aix-Marseilles (France). This conference known as the “La Londe Conference” is devoted to Marketing Communications and Consumer Behavior on a biennial basis. The La Londe conference encourages intense discussions of specialized topics in consumer behavior and communications among a relatively small group of specialized scholars in a relaxed and informal atmosphere. Those who have participated to the La Londe Conference also know the exchange value of the coffee breaks on the terrace overlooking the Mediterranean Sea and the Porquerolle islands. The La Londe conference is truly international. It is chaired by both a European chair and an American chair. Søren Askegaard (University of Southern Denmark, Odense, Denmark) and M. Joseph Sirgy (Virginia Polytechnic Institute & State University, United States) chaired the 2007 conference. A total of 74 manuscripts were submitted and double-blind reviewed by both members of the permanent scientific committee of the conference and ad-hoc reviewers carefully selected by the co-chairmen and the coordinator. Thirty papers were presented at the conference. In addition, the thought-provoking keynote address by Jan-Benedict E. M. Steenkamp (University of North Carolina at Chapel Hill) stimulated reflections and discussions concerning the process of researching fruitfully in consumer behavior/marketing communications fields. Jan-Benedict Steenkamp shared his outstanding research experience in a talk entitled “The Survey Research/ Theory Testing Paradigm.” He presented the major methodological breakthroughs he contributed himself over the past two decades. His research has enabled researchers to develop more reliable and valid research instruments and results in “domestic” and international contexts. He also shared his view concerning the future of consumer behavior research and new methodological developments. The eight papers of the special issue follow the dual theme of consumer behavior and marketing communications. The first three papers address consumer behavior related issues with a psychological orientation. Karolien Poels and Siegfried Dewitte (“Hope and Self-regulatory Goals Applied to an Advertising Context: Promoting Prevention Stimulates Goal-Directed Behavior”) are adding to the emerging stream of research in 0148-2963/$ - see front matter © 2007 Elsevier Inc. All rights reserved. doi:10.1016/j.jbusres.2007.09.012

the phenomenon of hope in consumer research. In a series of thoroughly designed experiments, they investigate two types of hope, prevention hope and promotion hope, and their relevance for goal-directed behavior in an advertising context. Initially, they validate the distinction between prevention hope (hope to avoid an unpleasant situation) and promotion hope (hope to achieve a desirable situation) and demonstrate that they differ in terms of goal-directed behavior in that the former is more related to such behavior than the latter. In other words, hoping to avoid a negative situation seems more likely to lead to goaldirected behavior than hoping to achieve a positive situation. This insight is then checked in two further experiments based on advertising contexts. Advertisements based on prevention hope have a better effect on product information recognition and also leads to better product information recall and willingness to try the product, than advertisements based on promotion hope. Finally, in a fourth experiment, the authors demonstrate that these findings are only valid in a context of high goal relevance for the consumer. Such insights into consumer reactions to different types of messages are of significant relevance to strategic communication planning. Loes Janssen, Bob M. Fennis, Ad Th.H. Pruyn and Kathleen D. Vohs (“The Path of Least Resistance: The Role of Regulatory Resource Depletion in the Effectiveness of Social Influence Techniques”) argue that resource depletion is an important factor in the effectiveness of social influence techniques. They do so by explaining consumers' use of heuristics in a social influence situation and their willingness to comply with a request through resource depletion. In the first of two experiments, they demonstrate how a traditional social influence “foot-in-the-door” technique is indeed characterized by resource depletion, i.e. consumers fell more tired and less resourceful after having completed a series of introductory tasks. In a second experiment, they introduce the element of heuristics in order to study compliance with a request. Here the authors demonstrate that consumers with depleted resources are more inclined to provide a charity donation than other consumers. This effect is demonstrated in the presence of a compliance heuristic (authority) whereas it is not found when absent. The authors conclude that consumers with depleted resources are more vulnerable to the effects of compliance heuristics, and thus more likely to follow social influence techniques as ‘path of least resistance’.

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Editorial

In the third article, Elisabeth Cowley (“Looking Back at an Experience through Rose-Colored Glasses: Selecting moments or distorting facts”) discusses the construction of retrospective evaluations in situations where experiences are mixed, both positive and negative. More specifically, she finds support for the hypothesis that in situations where consumers need to justify repeating an action when there is a disincentive to do so, they will produce a more positive reconstruction of their past experiences than otherwise. In an experimental setting, she demonstrates how memories of a virtual poker game become more positive when subjects who want to replay the game are confronted with a disincentive to do so. Testing a second hypothesis, that people who intend to repeat an activity which is difficult to justify are more likely to produce accurate memories of the most positive moment of the prior experience, she confirms the assertion that people who need to justify a future action, focus heavily on the positive moment when constructing the retrospective. When testing an alternative explanation, no evidence of memory distortion was found. These results provide new insights into the psychology of hedonic consumption, and especially explanatory frameworks of why consumers keep repeating hedonic experiences of mixed positive and negative kind. The three following articles of this special issue deal with consumer behavior from a more managerial perspective. Marieke L. Fransen, Bob M. Fennis, Ad Th. H. Pruyn and Enny Das (“Rest in Peace? The Influence of Brand-Induced Mortality Salience on Consumer Behavior”) produced a very original piece of research concerning the effects of unintended brand associations on consumer behavior. Specifically, they propose that exposure to some brands (such as insurance company brands) may increase mortality salience which provokes greater spending. In a series of three experiments, they were able to demonstrate that different modes of exposure to an insurance brand increase spending intentions (Experiment 1) and charity donation intentions (Experiment 2). Even mere subliminal brand exposure (Experiment 3) impacts preference for domestic products. In all cases, mortality salience was shown to be a mediator between brand exposure and consumer behavior effects. Therefore, unintended brand associations can influence consumer behavior by triggering unconscious consumer motives. The authors show that exposure to a brand (or even to a simple brand logo) can activate unexpected and nonmanaged brand associations (here mortality salience), which in turn could affect consumer behavior in many ways. Noël Albert, Dwight Merunka and Pierre Valette-Florence (“When Consumers Love Their Brands: Defining the Concept and Measuring its Dimensions”) argue that in many instances consumers fall in love with certain brands. Their paper focuses on the conceptualization and operationalization of love in relation to brands. They conducted an exploratory study involving 843 respondents in France. Data analysis including multiple correspondence analysis and cluster analysis of the words consumers use to describe their feeling of love and the “intimate” relationship they have with certain brands reveal the existence of 11 dimensions for the love construct. These dimensions are (1) passion (for the brand), (2) duration of the relationship (the relationship with the brand has existed for a

long time), (3) self-congruity (congruity between self image and product image), (4) dreams (the brand favors consumer dreams), (5) memories (evoked by the brand), (6) pleasure (that the brand provides to the consumer), (7) attraction (felt toward the brand), (8) uniqueness (of the brand and/or of the relationship), (9) beauty (of the brand), (10) trust (the brand has never disappointed), and (11) declaration of affect (feel toward the brand). These dimensions identified in France were compared to dimensions of love found in previous research conducted in a different cultural context—the United States. Finally, Jean-Charles Chebat, Claire Gelinas-Chebat and Karina Therrien (“Gender-Related Wayfinding Time of Mall Shoppers: The Mediating Effects of Shopping Values and Information Sources”) explore the validity of the folklore belief that males are better than females in navigation skills, especially in a shopping mall. In other words, are male shoppers more time efficient in finding their way in a shopping mall than females? They report a shopping mall study designed to test this stereotype. Specifically, they conducted an experiment in which male and female shoppers were intercepted in a shopping mall and asked to find certain stores and the amount of time it took them to find those stores was recorded. The authors hypothesized that the effect of gender on time efficiency in locating the target stores is mediated by shopping values and the use of information sources. The study confirmed their mediating hypotheses. Females were found to be more efficient in finding the targeted store than their male counterparts. This was due to the fact that females were found to be more hedonists (than utilitarians) in their shopping values and used people (as opposed to maps and other landmarks) as the main source of information in navigating through the shopping mall. Being a hedonist and using people as a key source of navigation information were found to contribute significantly to being time efficient in finding the targeted stores. The two last papers of the special issue address communication-related issues. Jean-Marc Lehu and Etienne Bressoud (“Viewers and Brand Placement in Movies: Understanding of the Effectiveness of the Technique”) focus on the psychology of product placement. Specifically, the authors explore viewers’ reactions during a second viewing of a movie. Their study involved a large sample of French viewers of DVDs (N = 3,532). The survey examined respondents’ spontaneous brand placement recall, the day after the movie was watched at home. The study found that a first viewing of the movie at the cinema improves brand placement recall, as does watching it at home on a large home cinema screen. The recall improvement also seems evident when a DVD movie is chosen either because of the movie director or when the viewer likes the movie. These findings have high managerial relevance for marketing managers involved in the product placement industry. The final paper is written by M. Joseph Sirgy, Dong-Jin Lee, J. S. Johar and John Tidwell (“The Effect of Self-Congruity with Sponsorship on Brand Loyalty”) offers a novel extension of self-image congruence research in the domain of corporate sponsorship. They define self-congruity with a sponsorship event as the degree to which consumers think the image of the sponsored event matches with their own self image. They

Editorial

establish a conceptual link between self-congruity with a sponsorship event and brand loyalty and hypothesize this link to be strong under two conditions: (1) when brand customers are aware that the firm is sponsoring the event, and (2) when brand customers are involved in that event. Five surveys involving more than 1500 participants enabled collecting data concerning a major mobile telecommunication company sponsoring the NASCAR Cup Series. The results indicate that self-congruity with sponsored sports events has a positive influence on brand loyalty and that this effect is moderated by customer awareness of the firm sponsoring the event and customer involvement with the sponsored event. This research shows both applicability and importance of self-congruity theory to other domains than brands and services. Managerial implications are strong concerning the selection of sponsored events that need to match the targeted customers’ self image. As co-chairs and coordinator of this conference and as coeditors of this special issue, we greatly appreciate the contributions of the international scientific committee members of the La Londe conference who year after year increase the quality of the contributions. The scientific committee is composed of the following very distinguished scholars: Gerald Albaum (University of New Mexico), Rajeev Batra (University of Michigan at Ann Arbor), Russell W. Belk (University of Utah), Elisabeth Cowley (University of Sydney), Christian Derbaix (FUCAM, Mons), Yves Evrard (HEC, Paris), Curtis P. Haugtvedt (Ohio State University), Wayne D. Hoyer (The University of Texas at Austin), Alain Jolibert (University PMF Grenoble), Lynn R. Kahle (University of Oregon), Michel Laroche (Concordia University, Montreal), Gilles Laurent (HEC, Paris), Siew Meng Leong (National University of Singapore), Sidney J. Levy (University of Arizona), Richard J. Lutz (University of Florida), Hans Mühlbacher (University of Innsbruck), Robert A. Peterson (The University of Texas at Austin), Rik Pieters (Tilburg University), Christian Pinson (INSEAD), Bernard Pras (University of Paris-Dauphine and ESSEC), Don E. Schultz (Northwestern University), JanBenedict Steenkamp (University of North Carolina at Chapel Hill), Alain Strazzieri (Paul Cézanne University Aix-Marseille),

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W. Fred van Raaij (Tilburg University), Luk Warlop (Katholieke University Leuven), Arch G. Woodside (Boston College), and Judy Zaichkowsky (Simon Fraser University). We also wish to thank all the other members of the review panel who performed a great reviewing job. Finally, we wish to express our gratitude to Arch Woodside, Editor-in-Chief of the Journal of Business Research for initiating and approving this special issue. We look forward to the 2009 edition of the La Londe conference. Two outstanding researchers, Chris A. Janiszewski, Jack Faricy Professor of Marketing, University of Florida, Warrington College of Business Administration, Gainesville, Florida and Stijn M. J. van Osselaer, Professor of Marketing, RSM Erasmus University, Rotterdam, the Netherlands, have accepted to co-chair this next conference. The 2009 La Londe conference will take place June 2–5, 2009 in La Londe les Maures, this beautiful and stimulating place on the French Mediterranean coast. Søren Askegaard University of Southern Denmark, Odense, Denmark Dwight R. Merunka University Paul Cézanne Aix-Marseille (IAE Aix), France Corresponding author. IAE Aix-en-Provence, University Paul Cézanne Aix-Marseille, Clos Guiot, 13540 Puyricard, France. Tel.: +33 442 280 808; fax: +33 442 280 800. E-mail address: [email protected]. Dwight R. Merunka Euromed Marseille School of Management, France M. Joseph Sirgy Virginia Polytechnic Institute & State University, United States 1 March 2007

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Journal of Business Research 61 (2008) 1030 – 1040

Hope and self-regulatory goals applied to an advertising context ☆ Promoting prevention stimulates goal-directed behavior Karolien Poels a,⁎, Siegfried Dewitte b a

Eindhoven University of Technology, The Netherlands b Katholieke University of Leuven, Belgium

Received 1 March 2007; received in revised form 1 July 2007; accepted 1 September 2007

Abstract This article proposes the existence of two types of hope which differ in terms of self-regulatory goals: prevention hope and promotion hope. Consistent with the functional emotion approach and regulatory focus theory, we show that prevention hope generates more goal-directed behavior compared to promotion hope. Next, we replicate these findings in an advertising context. Results from three experiments show that prevention hope ads lead to more goal-directed consumer behaviors like (1) greater memory for product information, (2) greater willingness to test the advertised product, and (3) more intentions to focus on product information and undertake product-related action than promotion hope ads. © 2007 Elsevier Inc. All rights reserved. Keywords: Advertising; Hope; Regulatory focus; Goals

1. Introduction Hope is omnipresent in marketing contexts. People suffering from dry and brittle hair can become hopeful after having seen a commercial about a new shampoo that is designed to cure and revitalize dry and brittle hair. No matter how wealthy you are, buying a lottery ticket can also induce a feeling of hope. Youngsters buy specific kind of clothes because they hope to be perceived as cool by their peers. Although the experience of hope in marketing contexts is very common, little research has addressed the question how hope affects (consumer) behavior. MacInnis and de Mello (2005) highlight the important role of

☆

The authors thank Marcel Zeelenberg, Liselot Hudders, reviewers and participants of the La Londe Conference for their comments on earlier versions of this manuscript. The second author was financially supported by the Fund for Scientific Research Flanders (Grant 03.91), and a grant from the university board (grant OT 03/07). Both authors gratefully acknowledge financial support from Censydiam-Synnovate. ⁎ Corresponding author. Eindhoven University of Technology, Human Technology Interaction Group, Faculty of Technology Management, P.O. Box 513, 5600 MB Eindhoven, The Netherlands. E-mail address: [email protected] (K. Poels). 0148-2963/$ - see front matter © 2007 Elsevier Inc. All rights reserved. doi:10.1016/j.jbusres.2007.09.019

hope for consumer behavior, marketing, and public policy. They conclude that hope has a rich potential to provide insight in various marketing related topics. Strange enough, empirical research into the use of hope as a marketing tactic is very scarce. Hope is particularly relevant for advertising. Be it the hope of loosing weight by using a specific brand of dieting pills or the hope of seducing a potential mate by wearing glamorous mascara, inducing hope is a popular persuasion tactic amongst advertisers. Advertising products as a means to achieve certain valuable goals (e.g., loosing weight or getting a partner) is probably more than merely providing information about what consumers can expect of a product. We suggest, in line with MacInnis and de Mello (2005), that such advertisements can trigger the feeling of hope. Concretely, advertisers create hope that using their products will help consumers to attain a desirable goal. To date, it is unclear what type of goals are the subject of hope and how hope affects product-related behavior. Due to this lack of empirical research, several issues with regard to hope in an advertising context remain unresolved. Clarifying these issues is critical from both a theoretical and a managerial point of view. This article fills this gap of empirical research on hope in an advertising context. The article focuses on the goals to which hope can be related and the actions that are associated with

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hope. We draw on well established psychological theories. Concretely, for the study of the goals we base ourselves regulatory focus theory (Higgins, 1997) which distinguishes between prevention goals and promotion goals. To investigate what kind of behavior is associated with hope, we rely on the functional approach of emotions that studies specific emotions and associated action tendencies (Frijda, 1986; Frijda et al., 1989; Lazarus, 1991). By merging these two theories, we develop a conceptual framework and derive predictions for the study of hope and the type of consumer behavior that it triggers. We particularly focus on goal-directed behavior (Bagozzi and Dholakai, 1999; Pieters et al., 1995). Consumers often purchase products because they hope that they enable them to attain certain goals (de Mello et al., 2007). Consequently, products and services are often deliberately marketed as a means to achieve a certain goal (Gutman, 1997). As a result, instigating goal-directed behavior is one of the main purposes of marketing actions. 2. Conceptual background 2.1. Hope and regulatory focus theory Lazarus (1991, 1999) posits that hope is related to goal outcomes. This means, hope arises from the desire to attain a certain goal. For example, you hope that a certain diet will work because you have the goal to loose weight. The condition in which hope arises is not always straightforward, however. Lazarus (1999) argues that hope arises in unsatisfactory situations that are damaging, threatening, or involve deprivation. On the other hand, Snyder (2002) adds that hope can also arise in situations that are already satisfactory but could be enhanced. To us, both situations seem plausible. The nature of the goals that are associated with hope presumably varies. Concretely, hope that stems from an unsatisfactory situation is associated with a goal of avoiding undesirable things, whereas hope that stems from a satisfactory situation is associated with a goal of achieving desirable things. As such, a relevant distinction seems to exist between two types of hope that differ in terms of the goals they are related to. To conceptualize this difference, this study relies on regulatory focus theory. Regulatory focus theory (Higgins, 1997; Higgins et al., 1997) distinguishes between goals with a promotion focus (i.e., ideal goals, achieving desirable things) and goals with a prevention focus (i.e., ought goals, avoiding undesirable things). In this article, we explicitly distinguish between two types of hope varying in terms of self-regulatory focus of the goal they are related to. Concretely, we predict and test the existence of two specific types of hope and we refer to these two types as prevention hope (i.e., hoping to avoid something negative: high in promotion and high in prevention) and promotion hope (i.e., hoping to attain something positive: high in promotion and low in prevention). Other researchers (Nesse, 1999; Madrigal and Bee, 2004; de Mello & MacInnis, 2005) have already suggested similar conceptualizations. Nevertheless, these authors have not yet empirically tested how hope experiences can differ in terms of regulatory focus.

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2.2. Hope and the functional emotion approach Apart from its association with goal outcomes, considerable studies have tried to unravel behavior or behavioral tendencies related to hope. Particularly within the functional emotion approach, hope has been characterized by specific appraisals and action tendencies (Frijda et al., 1989; Lazarus, 1991; MacInnis and de Mello, 2005; Smith and Ellsworth, 1985). Those researchers report substantial evidence about the appraisals that characterize hope. Concretely, a hope-evoking event is appraised as positive in valence, important, uncertain, yet achieving a goal congruent outcome is possible (i.e., a favorable outcome may occur or an unfavorable situation may be prevented or removed). However, it appears to be more difficult to distinguish action tendencies that uniquely characterize hope (Lazarus, 1999). The action tendencies that seem to apply to hope are general approach tendencies, attentional activity, and committed and mobilized actions (Frijda et al., 1989; Lazarus, 1991; Smith and Ellsworth, 1985). In the light of our distinction between prevention hope and promotion hope, we expect that these two types of hope will exhibit different action tendencies because they stem from different selfregulatory goals. Moreover, we suspect that previous research did not succeed well in establishing a set of unique action tendencies characterizing hope, exactly because they did not differentiate between the two types of hope that we posit in this paper. The differences in behavioral patterns that arise in a prevention and in a promotion focus are well documented (for a review of empirical findings and theoretical propositions see Pham and Higgins, 2005). One of the general findings is that prevention focus instigates a vigilant form of action and a promotion focus elicits a more eager form of action (Crowe and Higgins, 1997; Pham and Avnet, 2004). Vigilant action implies risk aversion, reliance on external information, and analytical processing whereas an eager way of action is typically concerns risk seeking, broad exploration, and heuristic processing (Pham and Avnet, 2004). We expect that the action tendencies that have been found to characterize hope in general such as committed action and attentional activity relate more to a vigilant type of hope and thus apply more to prevention hope than to promotion hope. Note that Lazarus (1991), who related hope to committed action, considers hope as an emotion elicited in situations where a negative, threatening situation can be prevented or resolved (cfr. infra). In line with this reasoning, we predict that prevention hope will lead to more vigilant, focused, and goaldirected behavior than promotion hope. 2.3. Specific behavioral effects beyond valence effects Hope is a positive emotion that specific appraisals and action tendencies characterize (albeit the latter may not be very clear yet). As such, this article advances hope from the viewpoints of the specific emotion approach. Differentiating action and cognition patterns between specific emotions is the core research subject within the specific emotion approach (Lerner and Keltner, 2000; Zeelenberg and Pieters, 1999). However, an

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alternative approach reduces the influence of emotions on behavior to the effect of valence. This valence based approach contends that the positive or negative balance of an emotional situation will guide attitudinal reactions and subsequent behavior. This approach has been widely applied when studying the role of emotions in a consumer context (Chaudhuri, 1998; Gorn et al., 2001; Philips and Baumgartner, 2002). Although the value of the valence based approach for studying emotional reactions in consumer contexts is beyond question, it may be limited. Much about the specific effects of different kind of emotions remains unresolved and unexplored. Applied to the study of differences in goal-directed behavior between prevention hope and promotion hope, we argue that this goal-directed behavior arises from the typical nature of the prevention goal. As a result, the differences in goal-directed behavior between prevention hope and promotion hope can be considered as a specific action tendency that applies more to prevention hope than to promotion hope. This difference persists irrespective of valence influences. 2.4. Overview of the studies Four studies test our predictions. Study 1 examines whether the two types of hope can be differentiated in a natural setting by exploring when people experience hope in real life and how they behave in those situations. The aim is to validate the existence of promotion hope and prevention hope and look at whether and how they differ in goal-directed behavioral patterns. In the next three studies, we study how the two types of hope differ with respect to goal-directed behavior in an advertising context. More concretely, we manipulate prevention and promotion hope by embedding the two types of hope in advertisements. Accordingly, Studies 2 and 3 observe real goaldirected behavioral effects (passive and active memory effects and willingness to test the product) after respondents are exposed to a prevention hope or a promotion hope-evoking ad. Study 4 examines goal-directed behavioral intentions after having heard about a hope-evoking service. In this study we also distinguish between the effect of the hope-evoking ads for people with and without goal relevance. In all four studies we test whether valence has an influence on our results. By looking at behavioral intentions and real behavioral effects, we deal both with volitional processes and instrumental behaviors as two parts of goal-directed behavior (Bagozzi et al., 1998). 3. Study 1 Study 1 explores whether promotion and prevention hope can be distinguished in a natural setting. We asked participants to recall and describe a hope episode that they recently experienced. The first aim is to investigate whether it makes sense to distinguish between hope episodes that are high and low in terms of prevention focus. Concretely, the expectation is that hope episodes can be characterized invariably by high levels of promotion focus, but differ more importantly with respect to the level of prevention focus. When measuring the promotion and the prevention focus of those hope episodes, our

expectation implies that the variance in prevention focus will be significantly higher than the variance in promotion focus. To further validate the distinction between the two types of hope, we test whether the two types differ in terms of action tendencies or behavioral strategies that they generate. With respect to these behavioral strategies, we are particularly interested in goal-directed behavior. 3.1. Method 3.1.1. Participants and procedure Sixty-two undergraduates (23 males) aged between 18 and 22 years (Mage = 19.3 years, SD = .85 years) participated in this study as a fulfillment of course credit. They were asked to recall as lively as possible a situation from the recent past in which they had experienced hope. Participants first wrote down a summary of this situation. Next, participants had to indicate on two unipolar seven-point scales to what extent their hope was oriented towards preventing something negative (prevention item) and oriented towards achieving something positive (promotion item). Because we wanted to distinguish two hope types based on both their promotion and prevention orientation, we explicitly chose to measure the self-regulatory orientation items by means of two unipolar scales rather than one bipolar scale, which is the common practice (e.g., Louro et al., 2005). Participants further rated on a five-point scale (after Watson et al., 1988) which other positive emotions (happy, pleasant surprise, excitement, relief: α = .86) and negative emotions (sadness, anger, fear, disappointment, α = .72) they had felt in the recalled hope situation. We then asked them to rate a series of items designed to measure behavioral strategies associated with this situation of hope. These behavioral items were based on the distinction between vigilant and eager forms of behavior. Items based on vigilance were goal-focusing (you were very focused towards your goal) and goal-targeting (your behavior was targeted towards reaching your goal). With these two items we composed a measure of goal-directed behavior (r = .44, p = .002). Further, items based on eagerness were dreaming (you were dreamy with respect to your goal) and risky behavior (your behavior was risky). All behavioral items were measured on seven-point Likert scales. To control for differences in the intensity or the specific nature of the recalled hope episodes, we included four appraisal items that characterize hope (Frijda et al., 1989; Roseman and Evdokas, 2004; MacInnis and de Mello, 2005): uncertainty (the attainment of your goal was uncertain), possibility (the attainment of your goal was possible), expectations (you expected to reach your goal), and importance (attaining your goal was important to you). These appraisal items were measured in a similar way as the behavioral items. 3.2. Results 3.2.1. Description of the recalled hope episodes The nature of the recalled hope episodes showed great variety. Some participants described a feeling of hope they had experienced after an examination period and before grades were announced. Others described being hopeful after they had

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discovered that a negative situation (e.g., a severe illness, a fight, a break-up, etc.) could be resolved. Still others mentioned being hopeful in situations in which they had the potential of achieving something unexpected or extraordinary (e.g., being the unexpected finalist of a tennis tournament and as such having the potential to become a winner, being offered the possibility to make an extraordinary trip, etc.). Most popular themes of the hope episodes involved relationships (i.e., love, friendship, family), studies, and leisure activities. 3.2.2. The occurrence of prevention and promotion hope Because emotion literature considers hope as generally promotion-oriented (Higgins et al., 1997), we expect scores on the promotion item to be invariably high for all participants. For the prevention item, we expect more variation in scores, reflecting a bimodal distribution with high or low prevention focus. Descriptive statistics (Mpromotion = 6.3, SD = .988, VAR = .98; Mprevention = 4.0, SD = 2.44, VAR = 5.97) and visualization of the promotion and prevention scores (Fig. 1) seem to confirm our hypothesis. Statistical testing of the difference between the two variances revealed a substantial difference: F(61,61) = 6,09, p b .01. This implies that the ratings on the prevention item have a significantly larger variance compared to the promotion item. As we could already observe in Fig. 1, this analysis further confirms our hypothesis that scores on the promotion item are high and scores on the prevention items vary considerably. In order to distinguish two types of hope varying in selfregulatory goals, we performed a median-split on the prevention item (median = 4.5) and composed two hope groups: a prevention hope group (n = 31) and a promotion hope group (n = 31). The prevention hope group scored high on prevention (M = 6.2) and high on promotion (M = 6.4), this means, the recalled hope situations in this group were mainly about hoping to prevent something negative. The promotion hope group scored low on prevention (M = 1.8) and high on promotion (M = 6.3), this means, the recalled hope situations in this group were mainly about hoping to achieve something positive. 3.2.3. Behavioral strategies To check whether the prevention and promotion hope group differed in terms of the behavioral strategies, we performed a MANOVA with type of hope as between-subjects factor and all three behavioral variables (goal-directed behavior, dreaming,

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Table 1 Mean scores of action variables Action variable

Prevention hope Promotion hope F-value p-value

Goal-directed behavior 6.02 Dreaming 3.94 Risk behavior 2.35

5.15 4.90 2.06

9.36 3.65 .63

.003 .06 NS

and risky behavior) as dependent variables. Results revealed a main effect of hope type: F(3,58) = 5.71, p = .002. Table 1 depicts the mean values on the three action variables separately. First of all, prevention hope scored higher on goal-directed behavior. Additionally, prevention hope scored marginally significantly lower on dreaming than promotion hope. Tendencies for risky behavior did not differ between the two groups. 3.2.4. Valence check To check whether the differences between prevention and promotion hope were due to differences in valence between promotion and prevention hope, we first composed a valencevariable by subtracting the summed negative emotions from the summed positive emotions. An ANOVA analysis revealed that valence was significantly lower in the prevention hope group (Mprevention = .1, Mpromotion = 4.6; F(1,60) = 9.65, p = .003). We then performed a MANCOVA analysis with all three action variables as dependent variables, with type of hope as a between-subjects factor and the composed valence-variable as a covariate. For the behavioral items the analysis revealed a significant main effect for valence (F(3,56) = 4.74, p = .005) whereas the effect of type of hope remained largely unaffected (F(3,56) = 2.81, p = .048). Further one-way ANCOVA analyses on the behavioral items separately and with valence as a covariate, revealed that only for dreaming the significant impact of hope type disappeared (F b 1). The insignificant result for risk behavior (F b 1) remained. Most important, the significant effect of hope type on goal-directed behavior (F(1,60) = 5.92, p = .018) was unaffected by the inclusion of valence. Moreover, for this factor there was no main effect of valence (F b 1). 3.2.5. Controlling for differences in appraisal We first checked whether the prevention and promotion hope episodes differed in terms of appraisals. We performed a MANOVA with hope type as a between-subjects factor and all four appraisal items as dependent variables. Results reveal a significant main effect of type of hope: F(4, 57) = 2.92, p = .029. Table 2 depicts the mean values on the four appraisal items separately. These results show that prevention hope is significantly higher on importance than promotion hope. The difference in uncertainty was marginally significant in the same Table 2 Mean scores of the appraisals

Fig. 1. Distribution of the promotion item and the prevention item.

Appraisal factor

Prevention hope

Promotion hope

F-value

p-value

Possibility Expectations Importance Uncertainty

6.06 5.03 6.52 5.81

5.87 4.84 5.94 5.13

.77 .27 6.08 3.67

NS NS .017 .06

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direction. Further, possibility and expectation appraisals did not differ between the two types of hope. To check whether these differences in appraisals had an influence on the difference in goal-directed behavior, we performed separate ANCOVA analyses with hope type as a between subjects variable, goaldirected behavior as dependent variable, and one of the two differing appraisals (importance and uncertainty) as a covariate. For both ANCOVA analyses, the appraisal item did not affect the difference in goal-directed behavior between prevention and promotion hope (results for goal-directed behavior remained significant: F values N 4.41, p values b .04). 3.3. Discussion Results of this study demonstrate the viability of distinguishing between two types of hope differing in prevention focus. With respect to behavioral strategies associated with the two types of hope, our results provide initial support for our predictions by showing differences in behavioral strategies between prevention hope and promotion hope. Specifically, we find that prevention hope is more related to goal-directed behavior than promotion hope. For this action variable, our results show that the difference is not due to valence, and suggests genuine differences between the two types of hope. This finding places our study within the specific emotion approach. Additionally, we find that promotion hope yielded more dreaming behavior than prevention hope. However, this difference could be assigned to differences in valence between prevention and promotion hope. We assume that this result is due to broadening of thoughts that occurs under general positive affect (Fredrickson and Branigan, 2005). Further, the recalled hope episodes differ in some appraisals like importance and uncertainty. Because of the correlational nature of the data, it is difficult to decide to what extent these differences in appraisals are essential to distinguish the two types of hopes or follow from the selection of the episodes. To get more insight, we experimentally manipulate the two types of hope in the following studies. 4. Study 2 Study 2 uses advertisements designed to arouse prevention hope or promotion hope. Based on the assumption that prevention hope leads to a more vigilant state of mind than promotion hope, we predict that participants exposed to a prevention hope ad should process product information in a more analytical way than participants exposed to a promotion hope ad. This means that participants in the prevention hope condition will focus more on the details when providing information about the advertised product than participants in the promotion hope condition. Concretely, in the current studies we investigate passive and active memory effects about the product (Product Information Recognition and Product Information Recall) as two measures of goal-directed behavior. Because product information recognition relies on passive memory and possibly interferes with active product information recall, we test both memory effects in separate samples. In Study 2,

we evaluate the effect on product information recognition. In Study 3, we evaluate the effect on product information recall. In general we expect that both passive and active memory effects will be stronger for the participants exposed to the prevention hope ad. 4.1. Method 4.1.1. Stimulus material and manipulation We created two types of advertisements for a fictitious vitamin complex called Actiflex. Actiflex was presented as a product that helps students during examination periods. One of the advertisements reflected prevention hope. In these advertisements two students were shown; one who did not use Actiflex and looked depressed and one who did use Actiflex and looked happy and optimistic. The other advertisement showed the same two students but now both were using Actiflex and both were happy. This advertisement reflected promotion hope. For both the prevention and the promotion type of advertisement we created three versions: one showing two male students, one showing a male and a female student and one showing two female students. We did so to reinforce the manipulation, and to prevent gender differences in terms of identification with the characters in the ad. An example of one of the advertisements reflecting prevention hope or promotion hope is shown in Appendix. The manipulation was first checked in a pretest in which respondents (n = 63) had to rate one of the two advertisements in terms of regulatory focus (bipolar: the ad is oriented towards achieving something positive versus this situation is oriented towards preventing something negative), evoked hope (unipolar: the ad makes me hopeful), importance (unipolar: the product of the ad is important to me), and uncertainty (unipolar: it is uncertain that the product of the ad will work). In Study 1, prevention hope episodes were rated higher in importance and slightly higher in uncertainty than promotion hope episodes. In this study we concentrate on the effect of self-regulatory focus and did not want these appraisals or possible differences in the intensity of evoked hope to affect our results. That is why we aimed to construct two advertisements that were equal in evoked hope, importance, and uncertainty. As intended, the two ads differed only in terms of regulatory focus: participants rated the prevention ads as more oriented towards preventing something negative than the promotion hope ads (Mprevention ad = 4.1 versus Mpromotion ad = 2.9, F(1,62) = 9.59, p = .003). For all other items ratings did not differ significantly (Fs b 1.98), thus validating the manipulation in terms of regulatory focus. 4.1.2. Participants, procedure, and measures One hundred and fifty undergraduate students (26 males) participated in this study for course credit. Ages ranged from 19 to 25 years (M = 21.7 years, SD = 1.46 years). The experiment was run right before the first term examination period (during the month of December) which made the presentation of an vitamin complex a goal relevant product. Participants were randomly assigned to the prevention or the promotion hope advertisements. In both conditions participants saw the three versions of the ad.

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After participants had seen the three advertisements, we measured their emotional state using a list of negative (sadness, anger, regret, and disappointment; α = .61) and positive emotions (joy, pleasant surprise, pride, and relief, α = .80) by means of a fivepoint Likert scale (after Watson et al., 1988). In the following step, we showed participants a slideshow presenting information about the product Actiflex (e.g., ingredients, availability, doses, and effects). They were instructed to read the product information at their own pace. After this presentation participants had to complete an unrelated filler task taking approximately 15 min. Next, we administered a test consisting of 15 true or false statements about the product that referred to the product information provided in the previous step. We consider the number of correct responses as a measure of Product Information Recognition. We assume that when participants recognize more correct product information, they have more carefully focused on the presented product information. 4.2. Results 4.2.1. Hope check Similar to our pretest results, the evoked hope did not differ significantly between the prevention hope advertisement and the promotion hope advertisement (Mprevention hope = 2.7, Mpromotion hope = 2.6, F(1, 149) = .18, NS). Although the level of hope triggered by the ads seems rather low, paired samples t-tests showed that the average level of hope was significantly higher than other positive (t(148) = 3.13, p b .003) and negative emotions (t(148) = 13.13, p b .001). 4.2.2. Goal-directed behavior To test whether Product Information Recognition was dependent on the type of hope depicted in the advertisements, we performed an ANOVA-analysis with Product Information Recognition as a dependent variable and type of hope as a between subjects variable. This resulted in a significant effect (F(1, 143) = 4.12, p = .044). In line with our expectations, the prevention hope ad (M = 10.9, SD = 1.20) resulted in better Product Information Recognition than the promotion hope ad (M = 10.5, SD = 1.56). 4.2.3. Valence check To check for valence effects, we computed a valence-variable by subtracting the negative emotions from the positive emotions. The two conditions differed significantly in terms of valence (Mprevention hope = .7, Mpromotion hope = 1.1, F(1, 146) = 13.2, p b .001). To check for possible valence effects on the Product Information Recognition variable, we included the composed valence-variable as a covariate in the previous ANOVA-analysis. Results revealed that valence did not have an effect on Product Information Recognition (F b 1), while the main effect of Advertisement type remained unaffected (F = 4.60, p = .034). 4.3. Discussion In this study we extend the findings of Study 1 with an experimental procedure and applied it to an advertising context.

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We find that advertising a product that can help people reach a goal that has high relevance to them, induces prevention or promotion hope (depending on the setup of the ad). Further, we find that prevention hope triggers better recognition of the product features than promotion hope, and thus indicates that participants had analyzed the presented product information in a more analytical way. This finding was not due to a difference in valence triggered by the two types of hope. 5. Study 3 Study 2 suggests that prevention hope leads to more analytical processing than promotion hope. Study 3 has three aims. We attempt to replicate this finding by investigating whether the difference generalizes to active recall of product information, which would add further evidence that analytical processing difference drove the recognition differences found in Study 2. We further want to test whether these differences have behavioral relevance. We test whether prevention hope ads lead to higher compliance with a request to test the advertised product, which is an effortful operationalization of information collection. The third aim is to establish that hope is essential in producing the effect. Therefore we add a no hope — control condition in which the advertisements show two subsequent depressed students (see Appendix). We expect hope to be lower in this control condition, and as a result, product recall and willingness to test the product will also decrease. 5.1. Method 5.1.1. Participants, procedure, and measures One hundred and twenty four undergraduate students (29 males) participated in this study for course credit. Their ages ranged from 19 to 34 years (M = 21.5 years, SD = 1.91 years). Again, the experiment was run right before the first term examination period. The procedure and measures were similar to the procedure of Study 2 with two important exceptions. First, we included an additional measure: Willingness to test the product. After participants had read the product information about Actiflex we launched a call for free testing of the product. We told that the producers of Actiflex wanted to use testimonials of students who had used the product into their product launching campaign. Participants were led to believe that they could freely test Actiflex for two months (i.e., during their examination period). To make compliance sufficiently costly, we told them that during those two months they had to gather notes in a dairy and report possible side-effects of Actiflex. Participants who wanted to test Actiflex had to indicate their name and e-mail address unto the call form. Afterwards, we debriefed those participants in an e-mail. After an unrelated filler task of approximately 15 min, participants were asked to freely write down everything they still remembered about Actiflex. They were instructed not to think about it for too long. The number of characteristics they could still remember about the product itself was summed. This is a measure of product information recall. The amount of information that is recalled is an indication of the extent to

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which participants focused on the information about the product. Second, this study adds an all-negative situations control condition (no hope condition — see Appendix). In that condition, subjects saw three advertisements showing two depressed students. The expectation is that hope, and accordingly productrelated action, and product information recall would be low in this condition. 5.2. Results 5.2.1. Hope check Hope differed significantly across the three conditions (F(2,121) = 4.00, p = .021). Tukey contrasts revealed that evoked hope did not differ significantly between the prevention hope advertisement and the promotion hope advertisement (Mprevention hope = 2.6, Mpromotion hope = 2.6) but that both conditions differed from the no hope condition (Mno hope = 2.03, p's b .05). 5.2.2. Goal-directed behavior An ANOVA-analysis revealed that the three conditions significantly differed with respect to Product Information Recall, F(2,121) = 8.53, p b .001. Post hoc Tukey tests showed that participants who were exposed to the prevention hope advertisements could recall significantly more information about Actiflex (Mprevention hope = 8.8) than participants exposed to the promotion hope advertisements (Mpromotion hope = 7.6) and than participants exposed to the no hope advertisments ((Mno hope = 6.7). The latter two conditions did not differ. A logistic regression with type of hope (prevention, promotion, no hope) as predictor and willingness to test the product (yes/no) as dependent variable revealed a significant effect: Wald Chi2 (df = 2) = 9.16, p = .01. This analysis revealed that participants in the prevention hope condition complied significantly more with the request of testing the product (45%) than participants in the promotion hope condition (23%), Wald Chi2 (df = 1) = 8.93, p = .003, and than participants in the no hope condition (14%), Wald Chi2 (df = 1) = 7.91, p = .005. The latter two differed too Wald Chi2 (df = 1) = 4.38, p = .005. 5.2.3. Valence check We first computed a valence-variable by subtracting the negative emotions (α = .60) from the positive emotions (α =.79). Valence differed across the three conditions (F(2, 121) =25.75, pb .001). Valence in the prevention hope condition (Mprevention hope = 2.6) did not differ significantly from valence in the promotion hope condition (Mpromotion hope = 4.1) but both differed from valence in de no hope condition (Mno hope = − 2.1). To check for possible valence effects on the Product Information Recall variable, we performed an ANCOVA analysis with type of hope as between subjects variable, Product Information Recall as an independent variable and the composed valence-variable as a covariate. Valence did not affect Product Information Recall (F b 2.77), while the main effect of type of hope remained significant (F(2, 123) = 10.04, p b .001). Further, a logistic regression with type of hope as predictor variable, valence as a covariate, and willingness to test the product as a dependent variable showed

that there was no main effect of valence (Wald Chi2 b 1.35), whereas the main effect of type of hope remained unaffected and significant (Wald Chi2 (df = 2) = 4.3, p = .019). 5.3. Discussion Again this study shows that compared to promotion hope, prevention hope leads to more goal-directed behavior. Concretely, we approximate goal-directed behavior by looking at product information recall and willingness to test the product. We further clarify that evoking hope is essential in establishing these effects. Our results further consistently show that these effects are not due to differences in valence. 6. Study 4 In Study 2 and 3 we use ads that present a product (a vitamin complex) which can serve as a mean to attain a certain goal (pass the exams). However, passing the exams had high goal relevance to the participants in the previous studies. High goal relevance is crucial to induce hope (Frijda et al., 1989; Lazarus, 1999). In this study we aim to find additional evidence about the difference between prevention and promotion hope in terms of goal-directed behavior by manipulating goal relevance. We expect that our findings do only hold under high goal relevance. 6.1. Method We created two scenarios that either evoked prevention or promotion hope. The hope-inducing scenarios presented a new cell phone provider offering attractive price conditions. In the prevention hope condition a script stressing the high costs of cell phone use preceded the hope-inducing scenario. In the promotion hope condition, people's attention was not drawn to this unsatisfactory starting situation. In this context, the cell phone provider was presented as a means to achieve something positive: low cell phone costs. The exact scenarios are presented below. Participants were randomly assigned to one of the two conditions. 6.1.1. Scenario Phase 1 (only in the prevention hope condition): In our country, cell phone costs are substantially higher compared to our neighboring countries like The Netherlands, the United Kingdom and Scandinavia. A recent survey among 1000 Flemish youngsters, aged between 18 and 26, revealed that more than 70% of them think that their cell phone bill is too high. Furthermore, cell phone costs clearly consume a large part of the youngster's monthly budget. Phase 2 (identical in both hope conditions): In the newspaper you see an advertisement from a new cell phone provider “Free Telecom”. It's a Scandinavian provider that offers very attractive prices. “Free Telecom” operates with an ingenious network that enables to decrease your cell phone costs. This advertisement makes you happy! You're sure that with “Free Telecom” your cell phone costs are going to decrease as well. You will save money that you will be able to spend on much nicer things. The manipulation was first checked in a pretest in which respondents (n = 60) had to rate one of the two scenarios in terms

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of regulatory focus, evoked hope, importance, and uncertainty (similar to Study 2 and 3). Again, we did not want hope intensity and other appraisal items to influence our effect. As we intended, the prevention hope scenario was more prevention-oriented compared to the promotion hope scenario (Mprevention = 3.7 versus Mpromotion = 2.8, F = 7.29, p = .009). Results for all other variables were insignificant (all F's b .56). This means our manipulation was successful and specific. 6.1.2. Participants One hundred and seventy eight college or undergraduate students took part in the experiment as a fulfillment of course credit. We first screened participants on whether they paid their cell phone costs themselves. Participants who did pay the costs themselves were classified as having high goal relevance (n = 107), participants who did not pay the costs themselves were classified as having low goal relevance (n = 78). The prevention and promotion hope scenario about the cell phone provider were randomly assigned to the different types of participants. We expect that participants with high goal relevance who read the prevention hope scenario would be more likely to exhibit action tendencies related to product focusing (i.e., wanting to get to know more details about the provider) and product-related action (i.e., undertake action with respect to the provider) compared to those participants in the promotion hope scenario. For participants with low goal relevance we do not expect a difference between prevention and promotion hope. 6.1.3. Measures We measured participants' emotional state after they read the scenario using a list of negative (sadness, anger, regret, and disappointment; α = .64) and positive emotions (joy, pleasant surprise, pride, and relief, α = .77) by means of a five-point Likert scale (after Watson et al., 1988). As measures of goaldirected behavior, we assessed participants' intention to focus on information about the product (Product Focusing) and participants' intention to undertake product-related action (Product-related Action) on 7-point Likert scales. Concretely, Product Focusing consisted of four items: “you actively look for more information about Free Telecom”, “you want to know the details about Free Telecom”, “you devote a lot of attention to what is being said about Free Telecom”, “you want to get to know as much as possible about Free Telecom”, α = .91). Product-related Action was composed by five items: “by what is being said you want to take action as soon as possible”, “you immediately join Free Telecom”, “you want to join Free Telecom as soon as possible”, “the next day you subscribe to Free Telecom”, “you subscribe to Free Telecom no matter what”, α = .89).

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significantly between the prevention hope and the promotion hope condition (Mprevention hope = 3.6, Mpromotion hope = 3.6, F(1, 171) = .12, NS). However, across hope conditions, participants with high goal relevance experienced more hope than participants with low goal relevance (Mhigh goal relevance = 3.7, Mlow goal relevance = 3.4, F(1, 171) = 4.32, p = .039). 6.2.2. Goal-directed behavior A 2× 2 ANOVA on intentions to focus on the product revealed a significant interaction effect between type of hope and goal relevance (F(3, 176)= 2,67, p =.049). More concretely, participants with high goal relevance, who pay their cell phone costs themselves, had more intentions to focus on the product information when reading the prevention hope scenario compared to participants that read the promotion hope scenario (Mprevention hope = 4.9, Mpromotion hope = 4.2, F(1, 106) =4.46, p = .037). For participants with low goal relevance, who do not pay their cell phone costs themselves, there was no difference between the two hope conditions (Mprevention hope =4.5, Mpromotion hope = 3.9, F(1, 69)= 1.98, NS). Similarly, a 2 × 2 ANOVA on intentions to undertake product-related action produced a significant interaction effect between type of hope and goal relevance (F(3, 176) = 4.12, p = .008). Participants with high goal relevance had more intentions to take immediate action concerning the new cell phone provider when exposed to the prevention hope scenario compared to the promotion hope scenario (Mprevention hope = 2.5, Mpromotion hope = 1.9, F(1, 106) = 6.91, p = .01). For participants with low goal relevance there was no significant difference between the two hope conditions on this measure of goaldirected behavior (Mprevention hope = 1.7, Mpromotion hope = 1.9, F(1, 69) = .028, NS). 6.2.3. Valence check We then checked whether the differences between prevention and promotion hope we found for participants with high goal relevance were caused by differences in valence. First of all, for these participants, the two conditions did not differ in terms of valence (F b 1.5), which implies that valence cannot mediate the effect of type of hope on intentions to focus on the product or intentions to undertake product-related action. Further, an ANCOVA analysis on focusing intentions with type of hope as a between subjects factor and valence as a covariate revealed a significant main effect of valence (F(1, 104) = 42.47, p b .001). However, the main effect of type of hope reduced only slightly and remained marginally significant as well (F(1, 104) = 2.78, p = .099). A similar ANCOVA analysis on action intentions exhibited a similar significant main effect of valence (F(1, 104) = 16.88, p b .001). For this variable the effect of type of hope reduced only slightly and remained significant (F(1, 104) = 4.38, p = .039).

6.2. Results 6.3. Discussion 6.2.1. Hope check We did an additional check of the extent to which participants experienced hope after reading one of the two scenarios. Similar to our pretest, experienced hope did not differ

This study replicates the pattern found in the previous three studies about the difference between prevention hope and promotion hope in stimulating goal-directed behavior. We

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7. General discussion

product information (e.g., information about the product's content, availability, price, etc.). Moreover, prevention-oriented ads seem to enable consumers to undertake direct action (e.g., exploring a website about the product, filling in a coupon to receive further information, or a coupon to test the product, etc.).

7.1. Theoretical implications and contributions

7.3. Limitations and future research

Despite its relevance in daily life, hope is still an understudied emotion. The aim of this article is to add to the study of hope in general and to the study of hope in an advertising context more specifically. Our contribution to the general, psychological study of hope is that we demonstrated that the goal, to which a hope situation is related, can have a promotion or a prevention focus. In this way, we distinguish two types of hope – prevention hope and promotion hope – and show that both types differ in terms of behavioral strategies. Consistent with regulatory focus theory, our results show that prevention hope is more related to goal-directed behavior than promotion hope. This means that people whose hopes are oriented towards a prevention goal will be more vigilant in their actions and narrow their minds towards reaching that goal. To our knowledge, this article is the first to experimentally study hope in an advertising context. In three studies we experimentally manipulate prevention hope and promotion hope in advertisements. Results from these three experiments replicate the findings from the first autobiographical study. Our results show that the amount of product focusing and product-related action, which can both be seen as a form of goal-directed behavior as discussed in Study 1, depend on the self-regulatory goals to which the hope is related. Ads that evoked prevention hope lead to more product focusing and product-related action than ads eliciting promotion hope. This means, our results show that a persuasive message inducing the hope that a negative situation can be changed into a positive situation (i.e., in case of prevention hope) improves the accuracy of product information recall and recognition and energizes more goal-directed action. We do not find these effects when the ad did not trigger hope or when the advertised product had low relevance to the participants. Our finding seems to complement earlier findings showing that emotionally dynamic commercials are more effective than emotionally stable commercials (Rossiter and Thornton, 2004). Related to this, Kamp and MacInnis (1995) showed that commercials in which the character's emotional expression changes from negative to positive during the commercial were more effective than commercials in which emotions did not vary.

The empirical study of hope is relatively new in advertising and consumer behavior studies. The current study has several limitations, and consequently, opens opportunities for future research. Three remarks deserve special discussion. In the current research we mainly focus on how prevention hope differs from promotion hope. This means that we focus on actions and characteristics that are typically prevention-oriented such as vigilant focusing and action. We show that, compared to promotion hope ads, prevention hope ads perform better in terms of product information memory effects and generated action. However, this does not mean that evoking promotion hope never works. Future research should investigate in which circumstances promotion hope will be more effective than prevention hope. The products used in the current studies (a vitamin complex and a cell phone provider) may be inherently more prevention-oriented. Consequently, the prevention hope ads matched better with the advertised product. Also, to increase goal relevance, Study 2 and 3 were conducted right before the examination period which could have induced in itself a more prevention-oriented goal state. This could imply that, in Study 2 and 3, there was a better Regulatory Fit (Lee and Aaker, 2004) between participants' goal orientation and the prevention hope ads. Research on regulatory fit has shown that people process persuasive messages more fluently when the message matches with their own regulatory focus (Aaker and Lee, 2006; Lee and Aaker, 2004). Additional research might further examine the difference between prevention and promotion hope for products that are more promotion-oriented in nature or in situations in which people are more likely to be promotion-oriented. Second, a recent study by de Mello et al. (2007) shows that the level of confidence that someone has in attaining a goal congruent outcome impacts the way in which people will deal with products that purport to enable goal attainment. Concretely, people with low confidence are more inclined to engage in motivated reasoning in which they, for example, will rely more on product-favorable information sources such as advertisements. It would be interesting to see how a manipulation of confidence level would interact with inducing prevention or promotion hope. Finally, the current research only examines the short term impact of inducing hope in an advertising context, that is, behavioral effects only right after exposure to the hope-inducing product. Although the findings show prevention hope to be more effective than promotion hope in the short run, it could well be that, in case of product failure, prevention hope may trigger a larger backfire effect (e.g., more complaining behavior, more negative word of mouth). Bougie et al. (2003) studied the differential effects of dissatisfaction and anger after a failed

further show that these effects do only occur when people have high goal relevance, which is a crucial appraisal for experiencing real hope. This strengthens our point that our findings rely on the experience of hope.

7.2. Managerial implications The current findings have important implications for ad practitioners. Since our results indicate that inducing prevention hope triggers information-seeking behavior among consumers, it is important that ad practitioners, when applying this tactic, design ads that include sufficient and satisfactory

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service. They found that anger led to more negative behavior towards the service provider than dissatisfaction. Dissatisfied customers typically wanted to find out why the service had failed. This means, dissatisfaction triggers an informationseeking tendency. Applying this to the current research, it could be that, in case of prevention hope, information search has already taken place before the product is bought or used. Consequently, product failure may trigger anger rather than dissatisfaction, leading to negative effects for the producer. In case of promotion hope, information search is less elaborated before product use. So it may more likely lead to dissatisfaction and information search after product failure. It would be interesting to test these predictions in future research. Appendix A. Examples of the ads used in Study 2 and 3 For all three ads, the baseline can be translated as: Actiflex, the active solution to exam-related stress. The text above the depressed student is he/she doesn't use it; the text above the happy students is he/she uses it.

References Aaker JL, Lee AY. Understanding regulatory fit. J Mark Res 2006;43:15–9 (February). Bagozzi RP, Dholakai U. Goal setting and goal striving in consumer behavior. J Mark 1999;63:19–32. Bagozzi RP, Baumgartner H, Pieters R. Goal-directed emotions. Cogn Emot 1998;12(1):1–26. Bougie R, Pieters R, Zeelenberg M. Angry customers don't come back, they get back: the experience and behavioral implications of anger and dissatisfaction in services. J Acad Mark Sci 2003;31(4):377–93. Chaudhuri A. Product class effects on perceived risk: the role of emotion. Int J Res Mark 1998;15(2):157–68. Crowe E, Higgins ET. Regulatory focus and strategic inclinations: promotion and prevention in decision-making. Org Behav Human Decis Process 1997;69(2):117–23. de Mello GE, MacInnis DJ. Why and how consumers hope: motivated reasoning and the marketplace. In: Ratneshwar S, Mick DG, editors. Inside consumption: consumer motives, goals, and desires. London: Routledge; 2005. de Mello GE, MacInnis DJ, Stewart DW. Threats to hope: effects on reasoning about product information. J Consum Res 2007;34:153–61. Fredrickson BL, Branigan C. Positive emotions broaden the scope of attention and thought-action repertoires. Cogn Emot 2005;19(3):313–32. Frijda NH. The emotions. Cambridge, UK: Cambridge University Press; 1986. Frijda NH, Kuipers P, ter Schure E. Relations among emotion, appraisal, and emotional action readiness. J Pers Soc Psychol 1989;57(2):212–28. Gorn G, Pham MT, Sin LY. When arousal influences ad evaluation and valence does not (and vice versa). J Consum Psychol 2001;11(1):43–55. Gutman J. Means–end chains and goal hierarchies. Psychol Mark 1997;14 (6):545–60. Higgins ET. Beyond pleasure and pain. Am Psychol 1997;52(12):1280–300. Higgins ET, Shah J, Friedman R. Emotional responses to goal attainment strength of regulatory focus as moderator. J Pers Soc Psychol 1997;72 (3):515–25. Kamp E, MacInnis DJ. Characteristics of portrayed emotions in commercials: when does what is shown in ads affect viewers? J Advert Res 1995;35 (6):19–28. Lazarus RS. Emotion and adaptation. New York: Oxford University Press; 1991. Lazarus RS. Hope: an emotion and vital coping resource against despair. Soc Res 1999;66(2):653–60. Lee AY, Aaker JL. Bringing the frame into focus: the influence of regulatory fit on processing fluency and persuasion. J Pers Soc Psychol 2004;86(2):205–18. Lerner JS, Keltner D. Beyond valence: toward a model of emotion-specific influences on judgement and choice. Cogn Emot 2000;14(4):473–93. Louro MJ, Pieters R, Zeelenberg M. Negative returns on positive emotions: the influence of pride and self-regulatory goals on repurchase decisions. J Consum Res 2005;31(4):833–41.

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Madrigal R, Bee C. Suspense as an experience of mixed emotions: hope and fear while watching suspenseful commercials. In: Menon G, Valdosta AR, editors. Advances in consumer research, vol.31. GA: Association for Consumer Research; 2004. MacInnis DJ, de Mello GE. The concept of hope and its relevance to product evaluation and choice. J Mark 2005;69:1–14 (January). Nesse RM. The evolution of hope and despair. Soc Res 1999;66(2):429–69. Pham MT, Avnet T. Ideals and oughts and the reliance on affect versus substance in persuasion. J Consum Res 2004;30(4):503–18. Pham MT, Higgins ET. Promotion and prevention in consumer-decision making: the state of the art and theoretical propositions. In: Ratneshwar S, Mick DG, editors. Inside consumption: consumer motives, goals, and desires. London: Routledge; 2005. Philips DM, Baumgartner H. The role of consumption emotions in the satisfaction response. J Consum Psychol 2002;12(3):243–52.

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Available online at www.sciencedirect.com

Journal of Business Research 61 (2008) 1041 – 1045

The path of least resistance: Regulatory resource depletion and the effectiveness of social influence techniques Loes Janssen a,⁎, Bob M. Fennis a,1 , Ad Th.H. Pruyn a,2 , Kathleen D. Vohs b,3 a

b

University of Twente, Faculty of Behavioral Sciences, Department of Marketing Communication and Consumer Psychology, P.O. Box 217, 7500 AE Enschede, The Netherlands University of Minnesota, Carlson School of Management, Institute for Research in Marketing, 321 Nineteenth Avenue South, Minneapolis, MN 55455-0438, USA Received 1 March 2007; received in revised form 1 July 2007; accepted 1 September 2007

Abstract Two experiments examine the role of regulatory resource depletion in the effectiveness of social influence techniques aimed at inducing consumer compliance. They test the two-step hypothesis that a) responding to the initial request stage of an influence technique requires selfcontrol, thereby depleting one's limited resource of self-regulatory energy, and b) a state of regulatory resource depletion fosters the use of heuristics present in the persuasion context, which increases the odds of compliance with the target request of an influence technique. A first field experiment shows that yielding to initial requests (answering a series of questions) induces resource depletion. Experiment 2 demonstrates that a lower level of self-regulatory resources increases the extent of compliance with a request through the employment of the heuristic principle of authority. Together these results provide support for the prediction that regulatory resource depletion is important in explaining the effectiveness of social influence techniques. © 2007 Elsevier Inc. All rights reserved. Keywords: Regulatory resource depletion; Social influence; Foot-in-the-door; Persuasion; Consumer compliance

Why is saying “no” to fundraisers and sales representatives often so difficult when they ask for money, to sign a petition, or to buy a product? In many of these situations people are being targeted with a social influence technique, which is a clever persuasion attempt to increase the chance that consumers comply with a request. The present research provides support for the prediction that self-regulatory resource depletion is an important factor in explaining the effectiveness of social influence techniques. ⁎ Corresponding author. Tel./fax: +31 53 4892046/4259. E-mail addresses: [email protected] (L. Janssen), [email protected] (B.M. Fennis), [email protected] (A.T.H. Pruyn), [email protected] (K.D. Vohs). 1 Tel./fax: +31 53 4894051/4259. 2 Tel./fax: +31 53 4892769/4259. 3 Tel./fax: +1 612 625 8331/624 8804. 0148-2963/$ - see front matter © 2007 Elsevier Inc. All rights reserved. doi:10.1016/j.jbusres.2007.09.013

1. Social influence techniques A variety of persuasion strategies can be employed to get consumers to say “yes” to an offer they were not planning to yield to in advance. During the past four decades a variety of influence techniques have been studied, including the Foot-in-the-Door technique (Freedman and Fraser, 1966) and the Door-in-the-Face technique (Cialdini et al., 1975). Like many influence strategies, these techniques present people with one or multiple initial requests before the target request is presented. The Foot-in-theDoor technique first presents the consumer with a small request that is difficult to refuse, followed by a more substantial request. For example, imagine a fundraiser who approaches you in the street and asks you whether you are willing to answer a few questions about a charity. You answer these seemingly harmless questions and then he asks you to support the charity by donating money. According to several studies (see Burger, 1999), the

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chance that you will donate money is now larger than if the fundraiser had asked for a donation right away. The Door-in-the-Face technique starts with a large initial request that probably will be rejected, followed by a milder target request. Studies suggest that the chance that, for instance, a person buys a single lottery ticket to support the local sports club substantially increases when the person previously rejected the request to buy ten tickets (see O'Keefe and Hale, 2001). 2. Automaticity To explain the effectiveness of social influence techniques, persuasion research increasingly emphasizes processes that are subtle, indirect and outside of conscious awareness of the consumer. In fact, the notion of automaticity has been forwarded as the cornerstone of all influence (Cialdini, 1993; Cialdini and Goldstein, 2004). Instead of mindful awareness of the situation, people appear to respond “mindlessly” (Langer, 1992) when confronted with a social influence technique. Under these conditions of reduced mental alertness, people are thought to fall back on habit and routine and hence employ “shortcuts” or simple heuristics to arrive at a decision. Use of these heuristics will generally increase the likelihood of compliance (Cialdini, 1993). As such, several studies on the Foot-in-the-Door technique show that employing the technique generally results in increased compliance, primarily because people want to behave consistently across situations (Burger, 1999). That is, compliance with the first, small request, such as answering a few questions about a charity, induces the self-perception that “one is the kind of person to comply with these kinds of requests”. This self-perception, functioning as a heuristic, increases the odds of compliance with the more substantial second request, like donating money to the charity in question. The Door-in-the-Face technique hinges on the heuristic principle of reciprocity: the ingrained motivation to return a favor (Gouldner, 1960). Generally assumed, the technique works because the influence agent makes a clear concession by downsizing the initial request, which evokes the need for the consumer to make a concession in return and therefore to comply with the milder request (Cialdini et al., 1975). When a request to buy ten lottery tickets is downsized to buying just one, the person will feel obliged to buy that single ticket. Additional heuristic principles include the principles of scarcity (complying because the availability of an offer or a request is limited), liking (complying because one feels sympathy for the influence agent), and authority (complying with an influence agent because he/she is (affiliated with) a highly credible source; see Cialdini, 1993). This latter heuristic principle is featured in the present research. 3. Regulatory resource depletion Given that the principle of automaticity and the reliance on heuristics seem to underlie the effectiveness of many social influence techniques, an appropriate question to ask is: where does this automaticity in these social influence situations stem from? Why do people behave “automatically”, and do people indeed fall back on ingrained heuristics when confronted with

an influence technique? Although automaticity appears to be a requirement for the techniques to work, no study to date has directly addressed this key question. The origin of this automaticity, and thus the effectiveness of many social influence techniques, possibly lies in a characteristic that most techniques have in common: they consist of multiple, sequential requests (Fern et al., 1986), and therefore the target consumer has to respond to one or more initial requests before the target request is presented. Actively responding to the initial request stage of a social influence technique and making decisions regarding one or more initial requests possibly requires self control and causes regulatory resource depletion (Baumeister et al., 1998; Muraven et al., 1998; Vohs and Heatherton, 2000). Hence regulatory resource depletion could be an important underlying factor that accounts for the automaticity, and thereby for the impact of many social influence techniques. The core idea behind this resource depletion is that selfregulatory processes, such as controlled processing, active choice and overriding responses, draw on a limited resource, akin to strength or energy. Therefore, one act of volition will have a detrimental impact on subsequent volition, which draws from the same resource. Comparable to muscle failure after straining, the active self can become depleted up to the point of self-regulatory failure (Baumeister et al., 1998). As a consequence, the self is less able to function effectively which may result in reliance on habit, routine, and automatic processes (Baumeister et al., 2000; Vohs et al., 2005). Several studies show that performing a preliminary act of selfcontrol undermines self-regulation on a subsequent, unrelated task. In a study of Muraven et al. (1998) participants who suppressed thoughts about a “white bear” were subsequently more likely to give up on unsolvable anagrams than participants in control conditions. In experiments of Schmeichel et al. (2003) participants showed poorer performance on a cognitive test when they had previously regulated their attention or suppressed their emotions during a video. Additionally, Vohs et al. (submitted for publication) demonstrate that participants who make a series of choices and decisions (e.g., regarding consumer products) show poorer self-regulation afterwards as compared to people who view or rate similar options without making choices. An initial act of self-regulation also renders people less inclined to make active responses and more prone to favor a passive response option (Baumeister et al., 1998). Finally, research by Vohs et al. (2005, Study 7) demonstrates that depletion of regulatory resources impairs effective self-presentation in dyadic interactions and leads to falling back on habitual, overlearned patterns of self-disclosure. In sum, research demonstrates that capacities for selfregulation are limited. A series of self-regulatory acts depletes one's resource of mental energy, thereby leaving the self with limited resources for self-regulation and reliant on habit, routine, and automatic processes (Baumeister et al., 2000; Vohs et al., 2005). 4. The present research A limited-regulatory-resource perspective suggests that actively responding to the initial request stage of a sequential request

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social influence technique, and making decisions regarding one or more initial requests, requires self control and induces resource depletion. A lower level of self-regulatory resources then possibly fosters the use of heuristics, when present in the persuasion context, which increases the odds of yielding to the target request of the influence technique. The present research tests this two-step hypothesis in two independent studies. In Experiment 1, a field study, people in the streets are presented with a series of questions similar to the initial request stage of what is called a “continuing question procedure”, which is an influence technique akin to the Foot-in-the-Door technique (see Burger, 1999). As hypothesized, answering this series of requests diminishes self-regulatory resources, as compared to a control condition in which participants are not confronted with any initial requests. In Experiment 2 regulatory resource depletion is induced with a selfcontrol task adopted from Schmeichel et al. (2003). Participants are subsequently presented with a request to donate money to a charity organisation, which either is or is not described as a source of high authority, to activate this heuristic principle. According to the hypothesis, participants whose regulatory resources are diminished will be more susceptible to the authority heuristic than participants in the no-depletion condition, thereby showing more compliance when this heuristic is activated. 5. Experiment 1 5.1. Method 5.1.1. Overview and participants In this field experiment people are being presented with a series of initial requests and their extent of resource depletion is measured. The study employs a single factor (initial requests: requests vs. no-requests) between-subjects design. Sixty people (30 men, 30 women) voluntarily participated in this study. Their age varied from 18 to 73 years (M = 34.33, SD = 16.28). 5.1.2. Manipulation One of three confederates (one female, two male) randomly approached passers-by on a market square in the centre of a large town with a request to participate in a short study, being conducted by the health sciences department of the local university. The confederate asked participants whether they were willing to answer a few questions about their health behavior and lifestyle. The confederate randomly assigned participants to the requests or no-requests condition. In the requests condition, the confederate presented participants with a series of initial requests, posed as 11 open-ended questions. These questions asked extensively about behaviors such as sports and exercising, smoking, use of alcohol, and eating habits. Examples of questions are “How much time do you monthly spend on sports and exercising?” and “Do you consciously pay attention to your eating habits?” Participants in the no-requests condition did not receive any initial requests. 5.1.3. Dependent measure Next, participants completed the State Ego Depletion Scale (Ciarocco et al., unpublished) to measure resource depletion.

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Participants in the requests-condition received a copy of this scale after answering the 11 open-ended questions, apparently as a part of the inquiries about their health behavior. Participants in the norequests condition received the scale immediately after the introduction of the confederate. On a seven-point scale (1 = not true; 7 = very true) participants indicated their agreement with each of the 25 items of the State Ego Depletion Scale. Sample items include: “Right now, it would take a lot of effort for me to concentrate on something“, “I can't absorb any more information“, and “I feel sharp and focused“ (reverse scored; see Ciarocco et al. (unpublished) for a complete listing of the items). The average score on this scale served as a measure of resource depletion (α = .90). Finally, participants were debriefed, thanked, and dismissed. 5.2. Results and discussion As predicted, a t-test reveals a significant effect of the requests condition on State Ego Depletion Scale scores (t(58) = 2.25, p b .05, d = .58). Participants who have answered 11 open-ended questions about their health behavior and lifestyle score higher on the State Ego Depletion Scale, and thus are more depleted (M = 2.87, SD = 1.00) than participants in the no-requests condition (M = 2.39, SD = .60). This result of Experiment 1 provides initial support for the first part of the hypothesis, the prediction that yielding to initial requests negatively affects self-regulatory resources. Actively responding to multiple initial requests appears to be a cognitive activity that requires self-control and depletes the self's resource of “mental energy”. The next study tests the second part of the hypothesis: the notion that people comply with a request to a larger extent when their regulatory resources are limited, provided that a heuristic is present in the persuasion context. As hypothesised, resource depleted participants show increased compliance with the target request, as compared to their nondepleted counterparts, but only when the heuristic principle of authority is salient in the influence context. 6. Experiment 2 6.1. Method 6.1.1. Overview and participants In this second, laboratory study people's regulatory resources are being diminished and their extent of compliance with a request is measured, under conditions in which the heuristic principle of authority either is or is not salient. The study employs a 2 (depletion-induction: depletion vs. nodepletion) X 2 (heuristic-activation: authority vs. no-authority) between-subjects factorial design. A total of 107 undergraduate students (37 male, 70 female) served as participants in this study, either in exchange for 6 euros or in exchange for 2 euros and course credit. Their mean age was 20.76 years (SD = 2.15). 6.1.2. Manipulations Upon arrival at the laboratory, the female experimenter randomly assigned participants to one of the four conditions.

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She told participants that the experiment concerned nonverbal assessments of personality. 6.1.2.1. Depletion–induction. A state of resource depletion was induced with an attention control video adopted from Schmeichel et al. (2003). Participants were asked to watch a short videotape. This 4-minute videotape (without audio) featured a woman being interviewed by an off-camera interviewer. According to the instructions, participants would later be judging the women's personality based on her nonverbal behavior. In addition to the woman being interviewed, the tape showed a series of common one-syllable words (e.g., hat) at the bottom quarter of the screen for 10 s each. These words were not related to the woman being interviewed. Participants in the no-depletion control condition received no instructions regarding the irrelevant words, nor were they made aware of the words prior to viewing the video. Participants in the depletion-condition read the instructions “not to read or look at any words that may appear on the screen” and to redirect their gaze to the woman if they found themselves looking at the words. Previous research has shown that regulating attention this way is effortful and depletes regulatory resources (Schmeichel et al., 2003; also Vohs and Faber, 2007). 6.1.2.2. Heuristic-activation. After watching the videotape participants read a short message on their computer screen, asking them to consider donating (part of) their participantmoney to a charity organisation. The heuristic principle of authority either was or was not activated by introducing either a well-known organisation, which was described as renowned and experienced, or a relatively unknown organisation, described as having starting experience in relief work. The domain of charity was the same in both conditions and concerned the development of educational projects in Third World countries. The charity organisation that was presented as an authority would presumably invoke more compliance, since research shows that people are more willing to comply with requests of authority figures, or – more generally – sources of high authority and credibility, either persons or institutions (see Cialdini, 1993). 6.1.3. Dependent measure 6.1.3.1. Compliance. After reading the description of the charity organisation, participants could indicate the amount of money they were willing to donate. Afterwards this amount was subtracted from the amount of money participants would receive for their participation in the experiment and they were paid the difference. The percentage of money that participants actually donated served as a measure of compliance. All participants were debriefed and thanked. The total amount of money donated during this experiment was transferred to the two charity organisations. 6.2. Results and discussion An analysis of variance on the percentage of money donated, with depletion-induction (depletion vs. no-depletion) and

Fig. 1. Percentage of money donated to charity, as a function of depletioninduction and heuristic-activation.

heuristic-activation (authority vs. no-authority) as independent variables shows a main effect of depletion as well as an interaction-effect. Participants who are depleted of their regulatory resources by the attention control video are willing to donate a larger percentage of their money (M = .73, SD = .38) than participants in the no-depletion control condition, who did not have to control their attention during the video (M = .57, SD = .43; F(1,103) = 5.31, p b .05, d = .39). Of main interest for the hypothesis is the finding that the interaction between depletion-induction and heuristic-activation is significant (F(1,103) = 4.46, p b .05). Analysis of the simple main effects shows that the effect of resource depletion on compliance is only significant when the authority principle is activated (F(1,103) = 8.69, p b .01, d = .94). In these conditions, resource depleted participants donate a larger percentage of their money (M = .81, SD = .32) than non-depleted participants (M = .46, SD = .42). When the authority-principle is not activated, depletion does not affect compliance: the difference in percentage of money donated between participants in the depletion-condition (M = .66, SD = .42) and no-depletion condition (M = .64, SD = .43) is not significant (F b 1, see Fig. 1). These results provide support for the second part of the hypothesis, the notion that regulatory resource depletion increases the odds of compliance with a target request, through the use of heuristics. That is, people comply with a request to a larger extent when their self-regulatory resources are low, provided that a heuristic is present in the influence setting. 7. General discussion The results of the present studies provide initial support for the prediction that resource depletion is an important factor in explaining the effectiveness of sequential request social influence techniques aimed at inducing consumer compliance. Experiment 1 shows that responding to a series of initial requests which involves answering a series of questions, affects the extent of resource depletion. Experiment 2 demonstrates that a lower level of regulatory resources increases the extent of

L. Janssen et al. / Journal of Business Research 61 (2008) 1041–1045

compliance with a request, provided that a heuristic is present in the persuasion context. Together these results support the prediction that regulatory resource depletion is a consequence of responding to initial requests and fosters the use of heuristics, which increases the odds of compliance with a target request. Since the two proposed steps in this process (initial requests cause resource depletion and resource depletion causes compliance) have been studied independently, future research may profitably examine whether regulatory resource depletion is the or merely a mediator of the effect of initial requests on compliance with a target request. Other ways to strengthen the assumption that resource depletion underlies the effectiveness of these techniques would be to use more objective (less intrusive) measures of depletion (self-control tasks) instead of the State Ego Depletion Scale in Experiment 1, and use various manipulations of resource depletion, other heuristic principles, and different measures of compliance in addition to the ones used in Experiment 2. The present research is the first to show that responding to initial requests induces resource depletion. The results of Experiment 2 are in line with previous research in showing that people employ heuristics in social influence situations (Cialdini, 1993; Cialdini and Goldstein, 2004), but the present research is the first to show that a state of regulatory resource depletion underlies this reliance on heuristic principles. As such the results of the present studies corroborate the often stated (but seldom tested) notion that mindlessness drives the effectiveness of compliance-gaining procedures. In Experiment 2 the presence of the heuristic principle of authority was manipulated by introducing a renowned and experienced organisation that participants could donate money to, as compared to a relatively unknown organisation with starting experience in the no-authority control condition. Participants appear to be only susceptible to the authority heuristic when they are depleted of their regulatory resources, donating a larger percentage of their money compared to the nodepletion control condition. Though not significant, Fig. 1 shows a slight trend of non-depleted participants tending to donate more money to the no-authority organisation than to the authority organisation. Possibly the no-authority organisation invoked more sympathy with participants because the organisation was described as a newcomer, which is generally more in need of support. If so, then perhaps the absence of a clear authority may foster the employment of alternative bases for judgment, such as the liking principle. Future research could more directly address this possibility. Finally, an interesting point to consider is how the results of the present research can be applied in practice. Sales representatives and fundraisers are probably more successful if they make use of initial requests to such an extent that consumers become deprived of their regulatory resources. In this state of mind the consumer will be likely to “follow the path of least resistance” and will be

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more vulnerable for the heuristics that social influence techniques are built on. Important for consumers is to keep their wits about them; seeing through a persuasion attempt and responding in a mindful way will likely reduce or undo the effect of resource depletion. Perhaps consumers will then easier say “no” to unwanted persuasion attempts, and “yes” when they have ascertained that the offer will bring wanted benefits. References Baumeister Roy F, Bratslavsky Ellen, Muraven Mark, Tice Dianne M. Ego depletion: is the active self a limited resource? J Pers Soc Psychol 1998;74:1252–65 (May). Baumeister Roy F, Muraven Mark, Tice Dianne M. Ego depletion: a resource model of volition, self-regulation, and controlled processing. Social Cogn 2000;18(2):130–50. Burger Jerry M. The foot-in-the-door compliance procedure. A multiple-process analysis and review. Personal Soc Psychol Rev 1999;3(4):303–25. Cialdini Robert B. Influence: Science and practice. (3rd ed.). New York, NY: Harper Collins; 1993. Cialdini Robert B, Goldstein Noah J. Social influence: compliance and conformity. Annu Rev of Psychol 2004;55:591–621 (February). Cialdini Robert B, Vincent Joyce E, Lewis Stephen K, Catalan José, Wheeler Diane, Darby Betty Lee. Reciprocal concessions procedure for inducing compliance: the door-in-the-face technique. J Pers Soc Psychol 1975;31 (2):206–15. Ciarocco Natalie J., Twenge Jean M., Muraven Mark, Tice Dianne M. Measuring state self-control: Reliability, validity, and correlations with physical and psychological stress. Monmouth, NJ: Monmouth University; unpublished. Fern Edward F, Monroe Kent B, Avila Ramon A. Effectiveness of multiple request strategies: A synthesis of research results. J Mark Res 1986;23:144–52 (May). Freedman Jonathan L, Fraser Scott C. Compliance without pressure: the foot-inthe-door technique. J Pers Soc Psychol 1966;4:195–202 (August). Gouldner Alvin W. The norm of reciprocity: a preliminary statement. Am Sociol Rev 1960;25:161–78 (April). Langer Ellen J. Matters of mind: mindfulness/mindlessness in perspective. Conscious Cogn 1992;1:289–305 (December). Muraven Mark, Tice Dianne M, Baumeister Roy F. Self-control as a limited resource. Regulatory depletion patterns. J Pers Soc Psychol 1998;74:774–89 (March). O'Keefe Daniel J, Hale Scott L. An odds-ratio-based meta-analysis of research on the door-in-the-face influence strategy. Communication Reports 2001;14 (1):31–8. Schmeichel Brandon J, Vohs Kathleen D, Baumeister Roy F. Intellectual performance and ego depletion: role of the self in logical reasoning and other information processing. J Pers Soc Psychol 2003;85:33–46 (July). Vohs Kathleen D, Faber Ronald J. Spent resources: self-regulatory resource availability affects impulse buying. J Consum Res 2007;33:537–47 (March). Vohs Kathleen D, Heatherton Todd F. Self-regulatory failure: a resourcedepletion approach. Psychol Sci 2000;11:249–54 (May). Vohs Kathleen D, Baumeister Roy F, Ciarocco Natalie J. Self-regulation and self-presentation: Regulatory resource depletion impairs impression management and effortful self-presentation depletes regulatory resources. J Pers Soc Psychol 2005;8:632–57 (April). Vohs Kathleen D., Baumeister Roy F., Twenge Jean M., Nelson Noelle M., Rawn Catherine D., Schmeichel Brandon J., Tice Dianne. Making choices impairs subsequent self-control: A limited resource account of decision making, self-regulation, and active initiative. J Pers Soc Psychol (submitted for publication).

Available online at www.sciencedirect.com

Journal of Business Research 61 (2008) 1046 – 1052

Looking back at an experience through rose-colored glasses☆ Elizabeth Cowley ⁎ Discipline of Marketing, Faculty of Economics and Business, University of Sydney, Sydney, NSW 2006, Australia Received 1 March 2007; received in revised form 1 July 2007; accepted 1 September 2007

Abstract The benefit of looking on the bright side of an experience is part of everyday vernacular and is supported empirically in academic research. The proposition here is that when people need to justify repeating an activity, they will try to reconstruct the past as more positive. The positive memory provides them with ammunition to rationalize a desired activity. Participants were offered either an incentive or a disincentive to replay a game. Participants in the disincentive condition who indicated a desire to replay, needed to justify the replay decision more than other participants. These participants were more likely to strategically select moments from a previous experience to construct a positive retrospective evaluation. A plausible alternative explanation for the results, distorting the salient moments of the experience, is tested and rejected. © 2007 Elsevier Inc. All rights reserved. Keywords: Memory reconstruction; Motivation; Retrospective evaluation

1. Introduction: Using the past to justify the future Imagine that you would like to do something that has had negative ramifications in the past. For instance, every time you go to a buffet restaurant you eat more than you know you should and leave the restaurant feeling guilty and a little too full. However, at the moment, you are thinking about the variety of flavors and the chance to ‘sample’ different dishes as well as not having to commit to one particular dish. One of the techniques you might use to justify the decision to visit the favored ‘allyou-can-eat’ establishment is to construct positive retrospective evaluations of previous visits to buffet style restaurants. The research presented here investigates whether strategically reflecting on the past such that previous experiences are remembered as more pleasant may be used to support decisions

☆ This research was funded by an Australia Research Council Linkage Grant and the industry linkage partner Russell Corporate Advisory. The author gratefully acknowledges the insightful comments of Donnel Briley, the Behavioral Finance group at the University of Sydney, and the participants at the LaLonde conference. ⁎ Tel./fax: +61 2 9351 6433/6732. E-mail address: [email protected].

0148-2963/$ - see front matter © 2007 Elsevier Inc. All rights reserved. doi:10.1016/j.jbusres.2007.09.018

which are not easily justified. Finding a justification for an action is important because people are less likely to consume without an adequate rationalization for the action (Okada, 2005). In the empirical work presented here, a (dis)incentive manipulation and a decision to repeat a behavior are combined to create a situation where the justification to engage in the desired activity is difficult to generate. The results show that when participants want to engage in a behavior, but are faced with a disincentive, they remember a more positive retrospective evaluation of the initial experience. How does this happen? The positive evaluation is the result of strategically selecting the most pleasant moments associated with the event. Specifically, when participants want to engage in an activity, but face a disincentive, they are more accurate in their memory for the peak positive moment compared to other participants because they focus on this moment during the construction of the retrospective evaluation. Another possible explanation, distorting the remembered details of the experience, is tested and rejected. The first section briefly reviews the literature on justifying a decision which may be tempting in the short term, but not beneficial in the long term. The second section builds a motivational argument for memory reconstruction by extending previous work on motivated reasoning. Hypotheses are developed and tested with an experiment.

E. Cowley / Journal of Business Research 61 (2008) 1046–1052

2. Justifying a hedonic activity 2.1. Hedonic consumption People prefer to have reasons for the things they do and the decisions they make. If a reason is not presented to them, then they will construct one. This is particularly true when people feel a need to justify the decision (Shafir et al., 1993) which is often the case with hedonic consumption (Kivetz and Simonson, 2002). In fact, hedonic consumption frequently requires a strong justification such as ‘earning the right’ to indulge (Kivetz and Zheng, 2006; Kivetz and Simonson, 2002) which occurs when the individual justifying the decision believes that he or she has expended enough effort during a task to entitle him or her to a reward after the hard work is complete. Working for the right to indulge relieves the guilt that often accompanies hedonic consumption (Kivetz and Simonson, 2002). Another strategy to rationalize engaging in a hedonic pursuit is to use a windfall to pay for the activity (Arkes et al., 1994). This is the opposite of earning the right to indulge since the decision maker is thinking “I'm not really paying for this anyway.” A windfall allows the winner to finance the activity with funds that are not the fruits of his or her labor which are generally reserved for the procurement of the necessities of life. Arkes et al. (1994) describe a windfall as more spendable, and is therefore, easier to justify spending on a hedonic activity. Another approach to justifying a hedonic activity is to increase the degree to which pleasure was experienced when engaging in the activity in the past. If the cost remains the same (in terms of time or money), but the pleasure derived increases, then the individual looking to repeat the hedonic activity is facing a lower cost per unit of pleasure. The strategy of magnifying the retrospective evaluation is investigated here. How might an individual construct a more positive retrospective evaluation? 2.2. Retrospective evaluations Given that people do not construct retrospective evaluations by summing the total amount of pain or pleasure felt during an experience, but instead, by selecting a few particular moments (Ariely, 1998; Ariely and Carmon, 2000; Chapman, 2000; Fredrickson and Kahneman, 1993; Hsee and Abelson, 1991; Kahneman et al., 1993, 1997; Redelmeier and Kahneman, 1996; Schreiber and Kahneman, 2000; Ross and Simonson, 1991; Varey and Kahneman, 1992), then they are able to strategically select moments to reflect most positively on an experience. Specifically, in an experience including both positive and negative moments, the evaluator can select the most positive moments when constructing a retrospective evaluation of an experience. An alternative method for remembering a more positive episode is to inflate the positive moments, or even confabulate new positive moments and/or reduce or eliminate negative moments in the experience. Why might people strategically select moments instead of distorting them? The strategic selection of moments is consistent with a motivated reasoning framework (Kunda, 1990) where people use the information stored in memory that is most likely to advocate

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their desired outcome. In their review of motivated reasoning research, Higgins and Molden (2003) assert that people are not only motivated in terms of the outcome they desire, “but also with respect to the manner in which they make their judgments. Therefore, beyond favoring particular conclusions, people may be independently motivated to reach these conclusions using strategies that “feel right” given their current motivational orientation” (p.214). Strategically selecting moments allows people to build a more positive retrospective evaluation without actually falsifying details of the past which facilitates “feeling right” about the evaluation. The positive retrospective evaluation allows people to justify a judgment or a preferred alternative to themselves as well as to others. The proposition here is that if people are motivated to repeat an activity that is difficult to justify, they will be motivated to reconstruct their memory for past experiences such that past experiences provide support for engaging in a desired activity. 3. Hypotheses Given that hedonic activities are more difficult to justify (Prelec and Loewenstein, 1998; Thaler, 1980), they present an ideal context to investigate motivated memory construction. Using the strategic selection of moments to construct a more positive retrospective evaluation may strengthen an otherwise weak justification to repeat a behavior. Remembering a more positive experience will provide support for the decision to engage in an activity that can be difficult to rationalize. The construction of an edited retrospective evaluation will allow players to “feel right” about the replay decision. H1. When people want to repeat an activity that is difficult to justify, they report a more positive retrospective evaluation of the initial experience than people who want to repeat an activity that is easy to justify. Although the retrospective evaluation is expected to be constructed as more positive, this does not occur because the peak moment of positive affect (or the largest win) is exaggerated or that the person remembers a better final moment. Instead, strategic editors of the retrospective evaluations will be more accurate in their reported memory of the details of the experience, particularly for a positive moment if they lost overall. Enhanced memory may be the result of greater attention or rehearsal of the event. The second hypothesis, therefore, is that people looking to justify a future behavior will more accurately remember a large win in a mixed loss experience. H2. When people want to repeat activity that is difficult to justify, they more accurately remember the most positive moment of a previous experience if the experience was negative overall. 4. Method 4.1. Sample and procedure One hundred and twenty two university students participated in exchange for course credit. Participants were told that they

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would not be playing for money for the first game, but that they would be offered a chance to play for money after the first game. Participants then played a simulated poker machine. After the game was played and participants had been provided with a (dis)incentive to replay, they indicated whether they would like to replay the game or not. Participants also provided a retrospective evaluation of the experience, a rating of their perceived performance, their memory of the largest win, the largest loss, and the final outcome. Finally, players entered a draw to replay in the future. Ten of the players reporting a desire to replay the game were contacted and allowed to play the game for money. Each of these players won between $10.00 and $15.00. Players that wanted to replay the game in the disincentive condition found themselves in a situation where their desired behavior was difficult to justify. For this reason, participants who reported a desire to replay in the disincentive condition were expected to use editing strategies to remember a more enjoyable experience. The design also includes two levels of game outcome: winning and losing. The losers face an even more difficult challenge in terms of justifying a replay decision. The addition of the outcome manipulation provides a stronger test of the hypotheses. 4.2. Design The design of the study is a 2 × 2 × 2 design with 2 types of incentive (incentive, disincentive), 2 levels of outcome (win, loss), and 2 levels of desire to replay (desire, no desire). The incentive and outcome were manipulated. Participants were randomly allocated to condition. The desire to replay was determined with a division of the desire to replay measure. 4.3. The stimulus 4.3.1. The game Participants played a poker machine for 300 games. Each player started with 3000 credits on the machine. Winners won 2000 credits (i.e. final credit position of 5000 minus 3000) and losers finished 2000 credits behind (final credit position of 1000 minus 3000). Each participant experienced one large win and one

large loss. The large win and the large loss were operationalized with a feature game. The feature included 15 free games and a Black Jack card decision. At the end of the free games, 500 points had been accumulated on the credit meter. Participants then had to play a double or nothing game where they pick either black or red as the suit color of the next card in a game of Black Jack. For the large win, the participants won the double or nothing game. The total win was 1000 credits. For the large loss, the participants lost the double or nothing game. The loss resulted in eradication of the 500 credits accumulated during the free games and a further reduction of 500 credits from the credit meter. The total loss was 1000 credits. All other wins and losses were less than 100 points. 4.3.2. Manipulation of a difficult situation to justify After a filler task, participants were provided with either an incentive or a disincentive to replay the game before retrospectively evaluating the experience. In the incentive condition, participants were told the following: “You may be given a chance to play the gambling game for 10 minutes when the study is complete…this time for money! If you win, you can keep the winnings at a rate of 1¢ per credit. If you lose you will be required to fill in some survey questions six weeks from now (5 minutes for each $10.00 lost).” The incentive condition instructions were accompanied by a photo of money. See Fig. 1. In the disincentive condition, participants were told the following: “You may be given a chance to play the Maid Marion® game six weeks from now. If you want to play you need to earn some credits now. To earn credits, you will be required to fill in some survey questions for 30 min. If you win, you can keep the winnings at a rate of 1¢ per credit.” The incentive condition instructions were accompanied by a photo of paperwork. See Fig. 1. The incentive conditions were pre-tested on 48 different students from the same participant pool. Pre-test participants read one of the incentives and indicated the degree to which they found the incentive appealing by marking an X on a 100 mm scale anchored with ‘not at all appealing’ (0) and ‘very appealing’ (100). As expected, the incentive condition was considered to be significantly more appealing than the disincentive condition (Mincentive = 74.12, Mdisincentive = 37.83, t = 4.80, p b .0001).

Fig. 1. Photos accompanying the motivation manipulation.

E. Cowley / Journal of Business Research 61 (2008) 1046–1052

4.3.3. Measuring the desire to replay Participants were then asked if they would like to play again. The replay decision was posed as follows: “If you are eligible, would you be interested in playing again?” Participants indicated their desire to replay by placing an X on a 100 mm continuous scale anchored with ‘not at all interested’ (0) and ‘very interested’ (100). People in the disincentive condition that wanted to play again (answered between 51 and 100 on the scale) were expected to distort their memory such that they could justify a replay decision, particularly in the loss condition. Players not wanting to replay were expected to be relatively accurate in their reconstruction of the gaming experience because they have no motivation to distort the past. The pattern of results does not change when the scale is divided into thirds and participants responding in the middle third are omitted from the analysis. Fifty nine participants chose to replay and 63 participants did not. The replay decision was not significantly correlated to the incentive condition (r = .02, p b .10) or whether the participant won or lost (r = .01, p b .10). 4.4. Dependent measures Participants were asked to rate their enjoyment of the experience playing the poker machine by placing an X on a 100 mm continuous scale anchored with ‘not at all enjoyable’ (0) and ‘very enjoyable’ (100). Participants were then asked to estimate how well they thought they played by placing an X on a 100 mm continuous scale anchored with ‘not at all well’ (0) and ‘very well’ (100). They were asked to remember the credits gained in the biggest win, the credits lost in the biggest loss of their gaming session, and the final score (credits remaining on the meter). 5. Results Importantly, no correlation was found between the disincentive condition and the desire to replay (r = − 0.08, n.s.). The manipulation did not affect the participants desire to replay. This is critical because the manipulation was designed to affect the need to justify the decision to replay, not the motivation to replay. If the correlation was significant, skeptics could argue that the manipulation provided the participants the right to indulge as the disincentive necessitates hard work before playing. If participants felt they had a right to replay, they would need no further justification. The test for H1 will investigate whether the manipulation + the desire to replay affected the incidence of retrospective editing amongst participants. An even stronger test of the hypothesis is to consider whether the manipulation + the desire to replay + the outcome affected the incidence of retrospective editing amongst participants, such that losers that wanted to replay in the disincentive condition were most likely to wear rose-colored glasses.

revealed a significant two-way interaction between incentive and replay decision was also significant (F(1, 114) = 14.67, p b .001): participants in the disincentive condition that chose play again remembered the most positive experience. Not surprisingly, the main effect for the replay decision was also significant (F(1, 114) = 43.88, p b .0001): participants choosing to play again remembered a more positive experience. Interestingly, the three-way interaction between outcome, the type of incentive, and replay decision was also significant (F(1, 114) = 5.77, p b .05): the losers in the disincentive condition that wanted to play faced an even more disagreeable situation reported the most positive retrospective evaluation. This is compelling because they could not even use a positive outcome as a justification for wanting to play again. See Fig. 2. Individual ANOVAs for each incentive condition were run to assist in understanding the three-way interaction. As expected, an ANOVA of retrospective evaluations with outcome and replay decision when a disincentive was provided revealed a significant interaction effect (F(1, 57) = 3.97, p b .05): players that chose to replay remembered a more positive experience when they lost. Hypothesis 1 is supported. As expected, an ANOVA of retrospective evaluations with outcome and replay decision when an incentive was provided revealed no significant interaction effects. Not surprisingly, the analysis revealed a main effect for the desire to replay (F(1, 57) = 4.85, p b .05): those reporting a desire to replay remembered a more positive experience. 5.2. Hypothesis testing — H2 Memory for the big win was most accurate for the participants that needed to justify their decision to replay, but faced a disincentive and lost the game. The absolute value of the accuracy of the reported big win was used as a dependent variable in an ANOVA with the outcome, the type of incentive, and replay decision as independent factors. The ANOVA revealed a significant three-way interaction (F(1, 114) = 4.65, p b .05). This was expected because increased attention to the moments during the construct of the retrospective evaluation should result in more accurate memory.

5.1. Hypothesis tests — H1 An ANOVA of retrospective evaluation with the outcome, the type of incentive, and replay decision as independent factors

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Fig. 2. Retrospective evaluation by incentive and replay desire.

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the experience which is commonly found in research considering memory for observed events (Loftus, 1996). See Table 1. 5.3. Additional analysis It is noteworthy that perceived performance was also affected by the need to justify a replay decision. The pattern of results is consistent with the retrospective evaluation results for the two-way interaction created by the manipulation of the incentive and the reported desire to replay. See Fig. 4. Participants in the disincentive condition that decided to replay believed they performed better when they choose to replay (F(1, 114) = 4.97, p b .05). Although a main effect was found for the outcome (F(1, 114) = 15.51, p b .0001); where winners believed that they performed better than losers, no significant interactions with outcome was revealed.

Fig. 3. Memory for the salient moment.

Individual ANOVAs for each incentive condition were run to assist in understanding the three-way interaction. An ANOVA of memory accuracy for the big win with outcome and replay decision when a disincentive was provided revealed a significant interaction effect (F(1, 57) = 5.95, p b .05): players that chose to replay were most accurate when they lost. Hypothesis 2 is supported. An ANOVA of memory accuracy for the big win with outcome and replay decision when an incentive was provided revealed no main effects or interactions. See Fig. 3. Did memory distortion occur? An alternative explanation for the results is that the change in the retrospective evaluation for participants that wanted to replay, but were faced with a situation that made the decision difficult to justify simply exaggerated the big win and/or reduced the big loss. Support for the alternative explanation would require a significant interaction of the desire to replay and the incentive condition, and possibly three-way interactions between the outcome, the desire to replay and the incentive condition for the actual reported memory of the big win and the big loss and the final outcome. ANOVAs run on memory of the big win, the big loss, and the unsigned final outcome with outcome (win, loss), type of incentive, and replay decision as independent factors revealed no main effects or interactions. Apparently the motivation to justify the decision does not affect the memory for the details of

5.4. Discussion of results Participants that indicated a desire to replay in the disincentive condition reported more positive retrospective evaluations for the experience, particularly when they lost the game. Participants who were provided an incentive to replay did not have to edit their memory for the experience as the incentive was sufficient in providing justification for the replay decision. Results for the players' perceived performance mirrored the results for retrospective evaluations. Objectively speaking, skills that will improve a player's score in a games of pure chance, such as those played on poker machines, are nonexistent. However, people have been shown to demonstrate an illusion of control (Langer, 1975) in their belief that something they did during the game influenced the outcome. How does the need to justify an activity foster beliefs in erroneous skills? Perhaps replaying is easier to justify if the player believes they can use their skills to win. An interesting question for future research is whether the strategic selection of moments has a role to play in this erroneous belief. The strategic selection of moments affects the accuracy of memory for the details of the game (size of the big win or the big loss). This is consistent with the notion that the strategy is a matter of attention, as opposed to memory distortion of the facts

Table 1 Memory for the big win and big loss Memory measures

Outcome Loss

Win

Incentive

Absolute error (big win) Actual (big win) Absolute error (big loss) Actual (big loss) Absolute final outcome

Disincentive

Incentive

Disincentive

No replay

Play again

No replay

Play again

No replay

Play again

No replay

Play again

443.0 1010.1 239.2 985.5 2248.9

548.5 879.8 479.3 919.9 1957.7

658.2 1117.1 484.9 1012.7 2167.3

263.3 1085.0 380.5 859.5 2400.5

537.5 874.2 274.3 943.4 2117.2

483.7 985.2 433.5 859.3 2313.8

400.4 1165.8 423.3 889.5 2056.2

433.1 886.1 485.4 749.3 2483.7

Absolute errors are calculated by taking the absolute difference between the remembered amount and the actual amount.

E. Cowley / Journal of Business Research 61 (2008) 1046–1052

Fig. 4. Perceived performance.

of the experience. Perhaps distorting the facts is unnecessary when trying to justify repeating a behavior to one 's self. The justification is required to convince other people of the wisdom of the decision, perhaps the strategies to produce decisionsupporting evidence become more extreme. In this case, tinting their glasses to a rose color may demand more tangible evidence. 6. General discussion Participants wanting to repeat an activity, but faced with a disincentive, strategically selected moments when evaluating a previous experience, in order that the evaluation was more positive. The result is consistent with Thaler's (1985) notion of looking for a silver lining in an experience as a strategy to maximize happiness. Interestingly, participants that did not have any desire to play the game again did not show any evidence of wearing brown-colored glasses. In other words, those not wanting to play the game again did not actively select moments to construct a more negative retrospective evaluation as a selfcontrol device. Nor did these players remember losing more points or attribute the loss to a less skilled performance on their part. However, they were directionally more accurate in their memory for the big loss, suggesting that certain instances where moments are selected to support a ‘no repeat’ decision could potentially exist. Investigating whether the strategic selection of moments is used to justify non-participation in a hedonic activity is an intriguing question for further research. Situations where people feel the need for a stronger rationale to not do something may require more dramatic strategies. For instance, if social pressure was applied to an individual who does not want to repeat a hedonic activity, then perhaps a more negative retrospective evaluation would be constructed to justify not participating. Another possible scenario for the occurrence of looking through brown-colored glasses might be if a precommitment has been made to engage in activity, but the initial experience is such that repeating the behavior is undesirable, yet planned. Perceived performance is higher when a justification is necessary. Perhaps players in the disincentive/desire to replay group are trying to convince themselves that not only will they

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enjoy repeating the activity, but that a good chance that they will win money if they play again. As was stated earlier, performance is not under the control of the participant, but most people believe that at least a degree of skill or luck is involved. Increasing the odds of winning may further support the decision to play again. Alternatively, perhaps perceived performance is higher for the participants that wanted to play again because their memory for the most positive moment is very accurate. The feature game which resulted in the big win did require a decision. Focusing on that moment could inflate the evaluation of performance. Two limitations to this work should be mentioned. Participants were randomly assigned to the incentive condition, but not to the desire to replay group. Therefore, no assurance can be provided that systematic differences do not exist between people wanting to play again and those indicating that they do not want to play again. Another limitation of the design is that the degree to which the incentive was appealing or the disincentive was unappealing was pre-tested, but not measured as a manipulation check in the main study. The results of this research contribute to the literature considering the construction of retrospective evaluations in a mixed positive and negative experience. Previous work considering retrospective evaluations has focused on the inclusion of post-experience information (Braun, 1999; Cowley and Janus, 2004) or the selection of accessible moments (Ariely, 1998; Kahneman et al., 1993, 1997; Redelmeier and Kahneman, 1996; Schreiber and Kahneman, 2000). The research reported here uses motivated reasoning to explain retrospective evaluations. The outcome alone does not explain the results, which is interesting. If readers had been asked “Who is more likely to want to replay — winners or losers?” before reading the results, the author would wager that the majority of readers would have chosen the winners. Apparently, a positive outcome is not the only fodder used to endorse repeating a hedonic activity.

References Ariely D. Combining experiences over time: the effects of duration, intensity changes and on-line measurements on retrospective pain evaluations. Journal of Behavioral Decision Making 1998;11:19–45 [March]. Ariely D, Carmon Z. Gestalt characteristics of experiences: the defining features of summarized events. Journal of Behavioral Decision Making 2000;13:191–201 [June]. Arkes HR, Joyner CA, Pezzo MV, Nash JG, Siegel-Jacobs K, Jones E. The psychology of windfall gains. Organizational Behavior and Human Decision Processes 1994;59:331–47. Braun KA. Postexperience advertising effects on consumer memory. Journal of Consumer Research 1999;25:319–34 [March]. Chapman GB. Preferences for improving and declining sequences of health outcomes. Journal of Behavioral Decision Making 2000;13:203–18 [June]. Cowley E, Janus E. Not necessarily different, but certainly better: a limit to the advertising misinformation effect. Journal of Consumer Research 2004;31 (1):229–35. Fredrickson B, Kahneman D. Duration neglect in retrospective evaluations of affective episodes. Journal of Personality and Social Psychology 1993;65:45–55. Higgins ET, Molden DC. How strategies for making judgments and decisions affect cognition: motivated cognition revisited. In: Bodenhausen Galen V,

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Lambert Alan J, editors. Foundations of Social Cognition: A Festschrift in Honor of Robert S. Wyer, Jr. Mahwah, New Jersey, NY: Lawrence Erlbaum Associates; 2003. p. 211–35. Hsee CK, Abelson RP. Velocity relation: satisfaction as a function of the first derivative of outcome over time. Journal of Personality and Social Psychology 1991;60(3):341–7. Kahneman D, Fredrickson BL, Schreiber C, Redelmeier DA. When more pain is preferred to less: adding a better end. Psychological Science 1993;4:401–5 [November]. Kahneman D, Wakker PP, Sarin R. ‘Back to Bentham? Explorations of experienced utility. Quarterly Journal of Economics 1997;112:375–405. Kivetz R, Simonson I. Earning the right to indulge: effort as a determinant of customer preferences toward frequency program rewards. Journal of Marketing Research 2002;39:155–70 [May]. Kivetz R, Zheng Y. Determinants of justification and self-control. Journal of Experimental Psychology. General 2006;135(4):572–87. Kunda Z. The case for motivated reasoning. Psychological Bulletin 1990;108:480–98 [November]. Langer E. The illusion of control. Journal of Personality and Social Psychology 1975;32:311–28. Loftus EF. Eyewitness testimony. Cambridge, MA: Harvard University Press; 1996. Okada EM. Justification effects on consumer choice of hedonic and utilitarian goods. Journal of Consumer Research 2005;32:43–53 [September].

Prelec D, Loewenstein G. The red and the black: mental accounting of savings and debt. Marketing Science 1998;17(1):4-28. Redelmeier DA, Kahneman D. Patients' memories of painful medical treatments — real-time and retrospective evaluations of two minimally invasive procedures. Pain 1996;66:3–8 [July]. Ross Jr WT, Simonson I. Evaluations of pairs of experiences: a preference for happy endings. Journal of Behavioral Decision Making 1991;4:273–82 [October]. Schreiber CA, Kahneman D. Determinants of the remembered utility of aversive sounds. Journal of Experimental Psychology. General 2000;129:27–42 [March]. Shafir E, Simonson I, Tversky A. Reason-based choice. Cognition 1993;49 (1):1-36. Thaler RH. Toward a positive theory of consumer choice. Journal of Economic Behavior and Organization 1980;1:39–60 [March]. Thaler RH. Mental accounting and consumer choice. Marketing Science 1985;4 (3):199–214. Varey C, Kahneman D. Experiences extended across time: evaluations of moments and episodes. Journal of Behavioral Decision Making 1992;5:169–86 [July–September].

Available online at www.sciencedirect.com

Journal of Business Research 61 (2008) 1053 – 1061

Rest in peace? Brand-induced mortality salience and consumer behavior ☆ Marieke L. Fransen a,⁎, Bob M. Fennis a,1 , Ad Th. H. Pruyn a,2 , Enny Das b,3 a

University of Twente, Department of Marketing Communication and Consumer Psychology, P.O. Box 217, 7500 AE Enschede, The Netherlands b Free University, Amsterdam, Department of Communication, De Boelelaan 1081, 1081 HV Amsterdam, the Netherlands Received 1 March 2007; received in revised form 1 July 2007; accepted 1 September 2007

Abstract The present research examines the hypothesis that brands can automatically activate mortality-related thoughts and, in turn, affect consumer behavior. Terror Management Theory (TMT; [Greenberg Jeff, Pyszczynski Tom, Solomon Sheldon. The Causes and Consequences of a Need for Self-esteem: A Terror Management Theory. In: Baumeister Roy F, editor. Public Self and Private Self. New York/Berlin: Springer-Verlag, 1986. pp. 189–192.]) predicts that brand-induced mortality salience leads to increased spending and worldview defense. The present findings show that explicit exposure to an insurance brand increases the accessibility of death-related thoughts, which, in turn, increases personal spending intentions (Experiment 1). Experiment 2 demonstrates that (implicit) insurance brand exposure positively affects charity donations. Additionally, the results of Experiment 3 reveal that subliminal brand exposure affects worldview defense in such a way that individuals who unconsciously observe an insurance brand rate domestic products more favorably and foreign products less favorably than individuals in the control condition. Brand associations can affect (unconscious) consumer behavior in various unanticipated ways. © 2007 Elsevier Inc. All rights reserved. Keywords: Brand Associations; Consumer behavior; Mortality salience; Spending; Worldview defense

Imagine buying a new car. You are looking for a fast one that will augment your driving experience and impress your friends. Two brands that automatically come to mind are “Porsche” and “Dodge Viper”, because you associate them with all the qualities you are looking for in a car. After some consideration you decide to purchase the “Porsche”. You start looking in the yellow pages to find an insurance company that offers a car insurance that provides security and safety. Whilst scrutinizing the relevant pages and seeing the brand names and logos of all the different insurance companies, you find yourself thinking about the terrible things that could happen to you and your ☆ The authors thank Frans van der Sluis, Monique Snellink, Monique van Rijn, and Hilde van Wijk for their assistance in data collection in Study 2. ⁎ Corresponding author. Tel./fax: +31 53 4892157/4259. E-mail addresses: [email protected] (M.L. Fransen), [email protected] (B.M. Fennis), [email protected] (A.T.H. Pruyn), [email protected] (E. Das). 1 Tel./fax: +31 53 4894051/4259. 2 Tel./fax: +31 53 4892769/4259. 3 Tel./fax: +31 20 5986858/6820.

0148-2963/$ - see front matter © 2007 Elsevier Inc. All rights reserved. doi:10.1016/j.jbusres.2007.09.020

precious new car: theft, damage, vandalism and even a fatal accident. This scenario shows that brands may activate a plethora of associations, which is congruent with the idea that consumers associate brands with related constructs such as a particular product attribute, usage situation, brand spokesperson, and the brand's logo. Aaker (1991) defines brand associations as “anything linked in memory to a brand”. These associations are assumed to be organized in a network similar to associative memory models (Anderson, 1993). For example, “Porsche” and “Dodge Viper” may trigger associations such as the pleasure of driving, speed and impression management, just as insurance brands can evoke associations involving security and belongingness. Such positive associations are often the result of enduring marketing strategies that repeatedly stress these brand characteristics, and they are often the focus of consumer research (e.g., Kohli et al., 2005; Punj and Moon, 2002; Van Osselaer and Janiszewski, 2001). However, as follows from the example above, not all brand associations originate from intentional tactics by marketers.

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Brand associations also seem to arise unintentionally as a consequence of, for instance, negative publicity or a product's attributes. For example, insurance brands are likely to remind us of disaster, illness, and even mortality. Whereas the effects of intentionally designed marketing strategies and consciously created brand associations on brand equity and consumer behavior received much attention, (e.g., Belén del Río et al., 2001; Brown and Dacin, 1997; Cobb-Walgren et al., 1995; Keller, 1993, 2003; Krishnan, 1996; Yoo et al., 2000), one cannot say the same about the effects of brand associations that originate spontaneously and are not part of a well-designed marketing strategy. Do such unintended, and perhaps undesired, brand associations affect consumer behavior? The present paper argues that they do. More specifically, the current research shows that brands can sometimes automatically trigger unconscious, hidden motives, desires, and fears that have a significant impact on consumer behavior. The present research focuses on one very powerful hidden motive: the fear of death (Greenberg et al., 1986). Although previous work stresses the relevance of the construct of mortality salience for the field of consumer behavior (e.g., Arndt et al., 2004; Solomon et al., 2004), various important questions have been left unaddressed in the literature. The present series of studies focuses on the notion that brand attributes may (unintentionally) induce the fear of death under various conditions. Moreover, the present research aims to extend earlier findings on the effects of deathrelated anxiety on various forms of consumer behavior. The next section briefly reviews previous research on the relationship between death-related anxiety and consumer behavior, and identifies several gaps in the literature. The section that follows discusses three experiments that tested the notion that brands can induce mortality salience and subsequently influence consumer behavior. 1. Consumer behavior as terror management According to Terror Management Theory (TMT: Greenberg et al., 1986), much human behavior emanates from the fear of death that becomes salient when confronted with mortality. The will to survive and the knowledge that life is transient results in an unsolvable conflict, often referred to as terror. Terror Management Theory postulates that individuals deal with this terror by endorsing a cultural worldview that gives meaning, order and permanence to the self. Living up to these standards provides high levels of self-esteem which functions as a buffer against existential anxiety. Various studies support the proposition that reminders of mortality intensify the desire to express cultural values and to engage in culturally prescribed behavior (see Greenberg et al., 2004 for a recent overview). For example, mortality salience leads to overestimation of consensus for one's attitudes on culturally relevant issues (Pyszczynski et al., 1996), more positive evaluations of charities (Jonas et al., 2002), a higher level of emotional distress when behaving counter to cultural values and norms (Greenberg et al., 1995), and more favorable attitudes of those individuals who exemplify cultural values or praise the culture (e.g., Greenberg et al., 1990; Rosenblatt et al., 1989). Moreover, research shows

that reminders of death not only intensify the desire to express and praise cultural values, but also the inclination to defend the values and norms of one's cultural worldview (in-group-bias) and, at the same time, the tendency to derogate values of other cultures (out-group derogation). For example, Germans who thought about their mortality reported less support for the European currency, the Euro, and greater support for the German Mark (Jonas et al., 2005). Expressing cultural values and defending one's cultural worldview seem to serve as mechanisms that regulate experienced existential terror. Recent research explores TMT assumptions in the realm of consumer behavior (Arndt et al., 2004; Rindfleisch and Burroughs, 2004; Maheswaran and Agrawal, 2004). In the current western society, consumerism and materialism can be seen as important values intrinsic to a western worldview. Accordingly, thoughts about death intensify the desire to meet these values by acting in accordance with them because this will boost self-esteem. In line with these notions, research shows that participants who consciously think about their mortality evaluate their financial future more positively, and expect to spend more money on luxury items in the next fifteen years than participants in the control condition (Kasser and Sheldon, 2000). Reminders of death also increase the attraction of high status products, presumably because these kinds of possessions show that one is doing well and meeting the standards of one's society (Heine et al., 2002; Mandel and Heine, 1999). Research on the effects of death reminders is still in its infancy, however, and little is known as yet about other worldview defense strategies that may be directly relevant to the consumer domain. For example, it remains unclear how the previously discussed impact of mortality salience on in-group bias and out-group derogation manifests itself in the consumer domain. One rather straightforward possibility would be that mortality salience leads to a general preference for national (own-country) products and a devaluation of foreign products. The present paper will address this issue. Furthermore, most research in the domain of Terror Management activated mortality-related thoughts by confronting participants with a threatening video about death or by instructing participants to write or think about (their) mortality (for an overview see: Pyszczynski et al., 2004). However, research left unaddressed whether marketing stimuli, such as brands, physical products, or advertisements can automatically activate mortality-related thoughts as well. The present series of studies focuses on one specific type of marketing stimulus and assesses the role of brands in inducing consumer mortality salience. In sum, this research aims to establish the missing causal links between three constructs: brands, mortality salience and consumer behavior. The present research adds to the literature in two ways. First, the hypothesis that mere brand exposure can function as an (unintended) reminder of mortality by triggering associations of disaster, fatal accidents and illnesses will be tested. Research on automatic construct activation (e.g., Bargh and Pietromonaco, 1982; Higgins et al., 1985; Macrae et al., 1994; Wheeler and Petty, 2001) supports the idea that subtle environmental cues can influence construct accessibility. For example, Kay,

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Wheeler, Bargh, and Ross (2004) show that implicitly presented material business objects, like boardroom tables and briefcases, increase the cognitive accessibility of related constructs such as competition. Likewise, brands–considering their broad scope of associations–may trigger various constructs related to unconscious consumer motives, such as a fear of death or a need to belong. To validly establish the specific relationship between brands and unconscious consumer motives, the present research examines the effects of different priming procedures on the accessibility of mortality-related thoughts. Across studies, priming procedures are varied from extensive and explicit, that is, supraliminal priming, to subtle and below the threshold level of conscious perception, that is, subliminal priming (Bargh and Chartrand, 2000). These procedures offer the possibility to learn more about the effects of brand associations that are not part of a well-designed marketing strategy, and are not controlled by marketers, but arise automatically from links with related constructs. This approach extends previous research in the realm of terror management by providing a first test of the role of marketing stimuli as inductors of mortality perceptions (i.e., brands and brand logos). Second, this research extends previous TMT research by providing explicit tests of the various ways in which mortality concerns affect consumer behavior. In western countries where consumerism is deeply interwoven with cultural beliefs and money is a pervasive barometer of self-worth (Bauman, 1995), excessive spending can function as a coping-strategy for dealing with existential anxiety (see also Arndt et al., 2004). In line with these notions, the hypothesis is that increased personal spending and charity donations are a function of brand-induced mortality salience. Moreover, the present studies take in-group favoritism and out-group derogation into the consumer domain by proposing that mortality salience induces a more positive perception of products and goods that are produced in one's own country and a more negative perception of products originating from abroad. In other words, individuals who (unconsciously) think about their mortality, through brand exposure, will be motivated to defend their own culture by expressing greater appreciation for their “own” products and lower appreciation for other cultures' (“their”) products. 2. Overview This research has two aims, (1) to test whether priming participants with an insurance brand logo can automatically activate death-related thoughts, and (2) to replicate and extend research on consumption-related mechanisms to reduce existential anxiety. This paper reports three studies that used different priming procedures: Experiments 1 and 2 used an explicit and implicit supraliminal brand priming method, respectively, to make mortality salient. Experiment 3 used a subliminal brand priming method to activate death-related thoughts. Using these different priming procedures, ranging from very explicit to very implicit, offers the possibility to validly establish the effectiveness of different forms of brand exposure, while providing and extending the knowledge about the effects of unintended and unmanaged brand associations.

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Accordingly, the present study is one of the first to assess the effects of brands on mortality salience and subsequent consumer behavior. The studies measure four different types of coping strategies, aimed at reducing existential anxiety, which are relevant to the consumer domain: increased spending (Experiment 1), increased donation to charity (Experiment 2), increased appreciation for national products, and decreased appreciation of foreign consumer goods (Experiment 3). The expectation was that exposure to an insurance brand increases the accessibility of mortality-related thoughts, which, in turn, would increase various types of coping strategies relevant to the consumer domain. Finally, Experiment 1 used a mediation analysis (cf. Baron and Kenny, 1986) to establish the mediating role of mortality salience in the relation between brand exposure and consumer worldview defense strategies. 3. Experiment 1 Experiment 1 aimed to test three hypotheses. First, this study examined the effect of explicit-supraliminal-brand priming on mortality salience. The first hypothesis was that extensive exposure to an insurance brand increases the accessibility of mortality-related thoughts. The second hypothesis was that this brand-induced mortality salience would affect personal spending on other items than the branded ones. Finally, the third hypothesis stated that mortality salience mediates the relation between brand exposure and spending intentions. 3.1. Method 3.1.1. Design and participants The experiment employed a single factor between-subjects design (brand: insurance brand logo vs. no brand logo). Fortythree participants (23 males and 20 females) with a mean age of 22 years (SD = 2.69) took part in the experiment. Participants received € 2 for their participation. 3.1.2. Procedure On arrival at the lab, the experimenter told the participants that the study consisted of a series of unrelated studies. The experimenter placed each participant in a separate room with a computer that provided all further instructions. After answering some demographic questions, participants in the experimental condition observed a brand logo, whereas control participants did not. After brand exposure, participants completed several measures assessing mortality salience, mood and spending intentions. Finally, participants responded to the “funneled debriefing” procedure (Bargh and Chartrand, 2000) to ascertain that nobody identified the real purpose of the study. After completing the different parts of the study, the experimenter debriefed, paid, and thanked participants for their attendance. 3.1.3. Brand exposure The computer program randomly assigned participants to either the brand exposure or the control condition. In the brand

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manipulation condition, participants saw the brand logo of a well-known insurance company, whereas participants in the control condition did not. To ascertain a thorough and extensive confrontation, the exposure lasted for five minutes and participants wrote down all the thoughts that came to mind during the brand logo exposure (Macrae et al., 1994). 3.1.4. Mood To assess whether the brand exposure would lead to unintended mood effects, participants responded to the 20items Positive Affect Negative Affect Schedule (PANAS; Watson et al., 1988), which consisted of 10 positive items (α = .79) and 10 negative items (α = .78). This questionnaire, designed to measure participants' feelings at that particular time, also served as a delay and distraction measure. This was important because previous research shows that standard mortality salience effects mainly occur after a (short) period of delay (Arndt et al., 1997). 3.1.5. Mortality salience To measure the accessibility of death-related thoughts, participants responded to the word fragment completion task (Greenberg et al., 1994) in which they completed a set of 15 incomplete words by filling in one or more syllables. Participants could complete ten of these words as either neutral or death-related words, and the remaining 5 words served as filler items. Examples included “De…”, which participants could complete as either “Death” or “Dean”, and “…ave” which they could complete as “Grave” or “Wave”. The summed total of death-related words that participants completed served as an index for mortality salience (M = .8, SD = .91, range = 0–3). 3.1.6. Spending intentions Participants indicated their inclination for excessive spending by reporting how much money they were planning to spend on entertainment and food in the upcoming month. Consumption and hedonism are currently seen as the most essential values in Western countries (Baumann, 1995). Therefore, the expectation was that spending money on consuming luxury food in a restaurant and entertaining oneself are adequate ways of expressing these current Western values. The summed scores on the items entertainment and food served as a measure of short-term spending intentions. 3.2. Results and discussion The results of the debriefing procedure revealed that none of the participants recognized the real purpose of the experiment. This enabled us to include all participants in the analyses. 3.2.1. Mood Analysis of variance on the positive items of the PANAS, (F(1, 41) = .83, ns) and the negative items of the PANAS, (F(1, 41) = 1.77, ns) indicated that participants' mood states were not affected by brand exposure. Hence, mood states cannot account for the difference in cognitive accessibility of deathrelated words and spending intentions.

3.2.2. Mortality salience An ANOVA on the number of completed death-related words showed that participants in the brand manipulation condition completed more death-related words (M = 1.2, SD = 1.0) than participants in the control condition (M = .4, SD = .66; F(1, 41) = 8.9, p b .01). Participants who explicitly saw the insurance brand logo indeed had more mortality-related thoughts than participants in the no-brand control condition, thus confirming that explicit brand exposure increased mortality salience. 3.2.3. Spending intentions In line with the predictions, an ANOVA on the measure of spending intentions revealed that participants in the experimental condition planned to spend more money on entertainment and food (M = 204, SD = 95.83), than participants in the control condition (M = 130, SD = 59.96; F(1, 41) = 9.58, p b .01). 3.2.4. Mediation analysis A mediation analysis tested the hypotheses that mortality salience mediates the relation between brand exposure and spending (cf. Baron and Kenny, 1986). The first regression analysis, with spending intentions as the dependent variable and brand manipulation (dummy coded) as the predictor, yielded a significant relation (β = .44, p = .004). A second regression analysis, with the mediator (mortality salience) as the dependent variable and brand manipulation as the predictor, showed that brand manipulation influenced mortality salience significantly (β = .40, p = .005). Subsequently, following the procedure outlined by Baron and Kenny (1986), a regression analysis with brand manipulation (dummy coded) and mortality salience (centered, see Aiken and West, 1991) as predictors and spending intentions as the criterion revealed that the previously found relationship between brand manipulation and spending intentions became insignificant (β = .22, p N .10), whereas the mediator retained its significance (β = .50, p = .001), which indicates full mediation. A Sobel test (Baron and Kenny, 1986; Preacher and Hayes, 2004) confirmed that mortality salience mediates the relation between brand manipulation and spending intentions (Z = 2.27, p b .05). These results suggest that mortality salience is a significant mediator of the relation between brand manipulation and spending intentions. These findings support the hypothesis that mortality salience can be induced by explicit priming with an insurance brand logo. Measuring the accessibility of death-related thoughts, enabled the possibility to show that brand exposure indeed induces mortality salience directly. Additionally, in accordance with the second hypothesis, the results showed that participants in the experimental condition indicated to spend more money in the near future than participants in the control condition, which offers further support for the effects of mortality salience on consumption-related intentions. Moreover, the mediation analysis revealed that the effect of brands on spending intentions is fully mediated by the accessibility of death-related thoughts. In sum, these results show that brand logos can influence spending intentions via mortality salience. Individuals confronted with an insurance brand, are unconsciously reminded of their mortality and use spending as a means to regulate their experienced terror.

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This is the first study to show that effects of mortality salience on consumer behavior are mediated by mortality-related thoughts. Given the fact that this study contrasted a brand exposure condition with a non-brand exposure control condition, one could argue that brand exposure as such, regardless of the specific type of brand, may have been sufficient to activate associations such as spending and purchasing, which could have led to increased spending intention. To rule out this alternative explanation, Experiment 2 uses a neutral brand in the control condition. To further validate the results of Experiment 1, and mimic a more “real world” situation, Experiment 2 uses a more implicit brand exposure by presenting the brand logo as a subtle and incidental environmental cue. Finally, Experiment 2 tests whether mortality salience can have effects other than increased consumerism, by examining the relationship between mortality salience and donations to charity.

Finally, the experiment contained a funneled debriefing procedure, to uncover any suspicions of the experiment's real goal. After the experiment, the experimenter debriefed, paid, and thanked participants for their attendance.

4. Experiment 2

4.1.4. Mood Participants responded to the 20-item PANAS questionnaire to check for design confounds (alpha positive items = .77, alpha negative items = .79).

Experiment 2 aimed to extend the results of Experiment 1 in a more natural setting by using a more implicit, subtle exposure of the insurance brand logo. Furthermore, Experiment 2 used a control brand in the control condition to rule out the alternative explanation that exposure to any brand influences spending behavior. To guarantee the implicit presence of the brands, the brand logos were printed on a mouse pad that was used during the experiment yet was not the focus of attention during any part of the experiment. Hence, the logos were only accidentally present in the experimental setting. Moreover, the present experiment investigated whether mortality salience affects actual behavior by measuring the amount of money participants were prepared to donate to charity. Donating behavior can be seen as desirable behavior in western culture (see Jonas et al., 2002), which makes it a suitable strategy for expressing cultural values. The expectation was that individuals who used the mouse pad with the printed insurance logo would donate more money to charity than participants using a mouse pad with a control brand. 4.1. Method 4.1.1. Design and Participants This experiment employed a single factor between-subjects design (brand manipulation: mouse pad with printed insurance logo vs. mouse pad with printed control brand logo). A total of thirty-seven participants (20 males and 17 females) with a mean age of 22 years (SD = 2.39) took part in this study. The experimenter paid the participants € 2 for their participation. 4.1.2. Procedure As in Experiment 1, the experimenter told participants that they would take part in a sequence of short, unrelated studies. The entire experiment took place on a computer and participants used either a mouse pad with the printed insurance logo or a mouse pad with the logo of a control brand (a brand for a personal care product). Subsequently, participants responded to the Positive Affect Negative Affect Schedule (PANAS) and indicated how much money they wanted to donate to charity.

4.1.3. Brand manipulation The experimenter randomly assigned participants to a room in which the mouse pad with the insurance brand logo was present or to a room in which the mouse pad with the control brand was present. Hence, during the entire experiment, participants used the mouse pad with either the printed insurance brand logo or the mouse pad with the printed control brand logo. To ascertain the implicit character of the experimental treatment, neither the experimenter nor the instructions provided by the computer program made any reference to the mouse pad or logo during any part of the experiment.

4.1.5. Charity donation At the end of the experiment, participants read some information about a charity foundation concerned with environmental protection and climate issues and indicated how much money they wanted to donate. 4.2. Results and discussion The results of the debriefing procedure revealed that none of the participants identified the true purpose of the experiment. 4.2.1. Mood As in Experiment 1, analysis of variance on the positive items (F(1, 35) = .22, ns) and the negative items (F(1, 35) = 1.56, ns) of the PANAS showed there were no significant differences in mood states between the experimental condition and the control condition. Hence, mood states cannot account for the observed results. 4.2.2. Donations An ANOVA revealed that participants in the experimental condition indicated to give more money to the charity foundation (M = 22, SD = 22.45) than participants in the control condition (M = 9, SD = 9.17; F(1, 35) = 5.22, p b .05). These findings extend the results of Experiment 1 by showing that brand-induced mortality salience leads to expressing cultural values by more generous donations to charity. This means that brands can function as subtle environmental cues that may affect consumer-related worldview defense strategies in ways that were unintended by the brand owner. Moreover, the use of a control brand in the control condition ruled out that general brand associations such as consumption and spending caused the effects on spending behavior. The findings of Studies 1 and 2 imply that consumers may use spending, specifically on culturally valued items, as a coping

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mechanism to reduce experienced terror triggered by the subtle presence of brands in the environment. However, there may be more ways in which brand-related mortality reminders affect consumer behavior. Terror Management Theory states that another coping strategy exists of support for one's own culture and worldview and derogation of other cultures (Greenberg et al., 1986). These mechanisms may translate to a consumer context, as they may affect the evaluation of foreign and local products. Specifically, as a consumption-related worldview defense mechanism, individuals exposed to the insurance brand may evaluate domestic products more favorably and foreign products less favorably. Experiment 3 tests this hypothesis. Additionally, Experiment 3 employs a subliminal brand priming procedure, in order to test the hypothesis that even brands presented on an unconscious level can affect mortality salience and corresponding consumer behavior. 5. Experiment 3 Experiment 3 applied a common worldview defense mechanism following a mortality salience manipulation to a consumer context: in-group bolstering and out-group derogation (Greenberg et al., 1986). More specifically, this experiment tested whether mortality salience affects the evaluation of domestic and foreign products. The experiment used subliminal brand exposure to establish that mortality-related associations become active even when consumers are completely unaware of being exposed to a brand stimulus. 5.1. Method 5.1.1. Design and participants To test the hypotheses, this experiment used a 2 (subliminal exposure: insurance brand vs. control brand) × 2 (products: domestic vs. foreign) design with repeated measures on the second factor. Seventy-seven participants (22 male and 55 female), with a mean age of 21 years (SD = 2.38) participated in the present study. They received €2 for their participation. 5.1.2. Procedure As in the previous studies, the experimenter told participants they would participate in a sequence of unrelated studies. The experimenter seated the participants in a separate room at individual computer desks. After responding to demographic questions, participants performed a lexical decision task in which a subliminal priming procedure took place. Subsequently, participants evaluated typical domestic products and typical foreign products. A debriefing procedure to assess whether participants had noticed the subliminal brand manipulation concluded the experiment. 5.1.3. Brand exposure The experiment used a subliminal priming task based on a standard priming procedure (Bargh and Pietromonaco, 1982; Strahan et al., 2002). Participants performed a masked lexical decision task in which they had to indicate as quickly and accurately as possible (by pressing the “a” or “;” key,

respectively), whether a string of letters shown to them on a computer screen constituted an existing word or not. The string of letters appeared in the middle of the computer screen. Between the presentation of forty words and non-words, brand logo primes flashed in the middle of the screen in half of the trials. The brand logos appeared on screen for a period of 10 milliseconds each. In the experimental condition, participants received a subliminal presentation of the insurance brand logo whereas participants in the control condition received a subliminal presentation of the logo of a soft drink brand. The experiment used this brand in the control condition because the colors of the brand logo matched those of the insurance brand logo, which facilitated the masking technique. Moreover, the use of another control brand than the one used in Experiment 2 ascertained that the earlier results are not attributable to the use of one particular control brand. A “sandwich” mask, consisting of a series of X's in the same colors as the brand logo primes, appeared before and after the primes in the exact same spot as the brand logo primes. Both masks appeared on screen for 300 ms each. 5.1.4. Product attitudes To measure participants' attitudes towards typically domestic (i.e., Dutch) food products and typically foreign food products, participants rated–on a 5-point scale–how positive (versus negative) they evaluated each of the products concerned. A picture–on which the product's name was clearly visible–of each product was displayed on the computer screen. Participants rated a total of five typically domestic products (e.g., “Gouda Cheese” and “Grolsch Beer”) and five foreign products (e.g., “Carbonell olives” and “Corona beer”). A summation of the five scores on the domestic products served as the attitude score towards the domestic products and a summation of the five scores on the foreign products served as the attitude score towards the foreign products. 5.2. Results and discussion The results of the debriefing procedure confirmed that none of the participants identified that they had been exposed to a subliminal brand manipulation. 5.2.1. Product attitudes A 2 (brand: insurance brand vs. soft drink brand) × 2 (product: domestic vs. foreign) ANOVA with repeated measures on the last factor yielded a significant main effect of product (F(1, 75) = 4.05, p b .05), indicating that the domestic products were generally evaluated more positively (M = 17, SD = 2.83) than the foreign products (M = 16, SD = 3.22). This main effect was qualified by a significant interaction effect between brand and product (F(1, 75) = 8.76, p b .01). Simple main effect analyses showed that participants in the insurance brand condition rated the domestic products more positively (M = 18, SD = 2.10) than participants in the control brand condition (M = 16, SD = 3.28, F(1, 75) = 5.20, p b .05). Conversely, participants in the insurance brand condition rated the foreign products less positively (M = 16, SD = 3.34) than participants in the control brand condition (M = 17, SD = 2.96, F(1, 75) = 4.05, p b .05). These

M.L. Fransen et al. / Journal of Business Research 61 (2008) 1053–1061

Fig. 1. Attitude scores on domestic and foreign food products as a function of brand exposure.

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without (Experiments 2 and 3) any concomitant instructions and even nonconsciously (Experiment 3), can have these dramatic and far-reaching effects on man's ultimate fear: his or her death. Second, the present research shows that consumers have several response options to deal with induced existential terror. Experiments 1 and 2 revealed that exposure to an insurance brand enhanced spending on items that one values positively in current western society. A mediation analysis confirmed that the relation between brand associations on the one hand, and spending on the other, was mediated by mortality salience. Hence, excessive spending on culturally valued items is a direct response to mortality salience. Experiment 3 showed that a subliminal brand prime increased preference of domestic over foreign products, thus demonstrating how worldview defense mechanisms, such as in-group favoritism and out-group derogation can pervade a consumer context. 6.1. Terror management theory and consumer behavior

findings suggest that participants in the insurance brand condition showed in-group favoritism, by expressing a more positive attitude towards domestic products, as well as outgroup derogation, by expressing a more negative attitude towards foreign products (see Fig. 1). These findings demonstrate that unintended brand associations can affect the evaluation of different products. The present findings may thus be the first to provide a clear demonstration of consumption-related in-group favoritism and out-group derogation as a function of brand induced mortality salience. Hence, the results attest to the various forms in which consumer behavior may function to reduce existential terror that is experienced when individuals are confronted with a mortalityrelated brand. Furthermore, the present findings show that these effects can even be induced when the brand stimuli have been presented subliminally. 6. General discussion The present research investigated whether unintended brand associations can influence consumer behavior by triggering unconscious consumer motives. The hypotheses were that exposure to an insurance brand would activate mortality-related thoughts and that mortality-related thoughts, in turn, would increase consumer spending, increase consumer preference for domestic products, and decrease consumer preference for foreign products. The present findings support these hypotheses. First, the current research is the first to show that exposure to marketing stimuli, like brands, is sufficient to induce mortality salience. This is a clear extension of earlier research that has underscored the relevance of the mortality salience construct for understanding various forms of consumer behavior (e.g., Solomon et al., 2004; Arndt et al., 2004) but thus far has ignored the role of marketing stimuli as causal agents in this process. The present results align with earlier findings indicating that brand stimuli are capable of activating direct and indirect consumer associations. In this regard, it is noteworthy that something so subtle and perhaps trivial as a simple brand logo that is presented with (Experiment 1) or

Effects of mortality reminders have been under frequent investigation since Greenberg, Pyszczynski, and Solomon (1986) formulated Terror Management Theory. The main focus of this research has been on the general consequences of mortality salience, such as self-esteem striving, group affiliations, and self-serving biases (for a review see Pyszczynski et al., 2004). More recently, mortality salience has also grasped the attention of consumer researchers, but work in this domain has remained on the conceptual level for a long time (e.g., Arndt et al., 2004; Maheswaran and Agrawal, 2004), and has only scarcely included empirical demonstrations of mortality salience directly pertaining to consumer behavior (Ferraro et al., 2005; Heine et al., 2002; Jonas et al., 2005; Kasser and Sheldon, 2000; Mandel and Smeesters, 2007). The present findings offer empirical support for the notion that mortality salience can lead to “the urge to splurge”, which was suggested, but not tested by Arndt et al. (2004). Mortality salience not only results in overestimating one's financial position in the future (Kasser and Sheldon, 2000), but mortality salience also influences spending intentions on culturally prescribed items in the short term. Participants anticipated spending more money in the coming month when they perceived a mortality-related brand. These results suggest that mortality salience directly motivates individuals to reduce their experienced terror. Moreover, these findings empirically verify that reducing existential anxiety is conceivable through lavish consumption. Additionally, the experiments demonstrated that mortality-related brand-priming influences consumer behavior in more ways than one. Although other studies in this domain showed instances of in-group favoritism (e.g., Nelson et al., 1997), the current study presents evidence for both in-group favoritism as well as out-group derogation in a consumer context. Specifically, mortality salience influenced attitudes towards both domestic and foreign food products by boosting the evaluation of domestic products while simultaneously lowering the evaluation of foreign products. These findings demonstrate that one's daily shopping behavior may be pervaded by motives and considerations that are hidden to the

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eye and the conscious mind. Accordingly, even subtle reminders of mortality may directly affect the amount of money one plans to spend, the extent to which one is keen to support charity, and the kinds of products one likes and dislikes. As such the present results provide empirical evidence for the notion that the fear of death can be induced and managed by entities that are commonly and even ubiquitously found in the consumer-behavior domain. 6.2. Brand associations and consumer behavior From the somewhat broader perspective of unconscious activation (i.e., priming) of perceptions and behavior (see Bargh, 2002), the present study is the first that directly measures mortality salience after brand priming. The findings show that mere brand logos can serve as primes in activating constructs. This means that brand associations, even without the physical presence of the accompanying product, can become active by exposing participants explicitly to the brand as well as by implicit, incidental brand exposure. Brand confrontation not only has an effect on construct accessibility but also on preferences and the tendency to spend more money. This finding offers support for a full causal chain of brand exposure, inducing unintended brand associations (mortality salience), which spurs concomitant consumer behavior. Marketers try to influence consumer behavior by creating positive brand associations on the assumption that this will increase both sales and brand loyalty. The results found that unintended (even unknown) associations can direct consumer decisions as well. Whether these kinds of unintended brand associations are harmful or fruitful to a certain company will depend on the kind of associations that spontaneously arise around a brand or product. The present studies used one particular brand to induce mortality salience. For future studies, it would be interesting to verify whether other types of brands can engender similar effects so that the present results can be generalized to other product categories and brands. However, for now, it seems wise for brand managers to bear in mind that brands may have a host of unknown (and possibly undesirable) associations that might facilitate or interfere unintentionally with their brand strategies, especially because these unintended brand associations can become activated by very subtle and even subliminal exposure. Stretching this point results in the provocative notion that brand advertising for product A may directly benefit sales for brand B (either in or outside the product category of A) to the extent that consumers buy brand B as an effective defense strategy to manage the mortality salience induced by brand A. Additionally, in the realm of consumer behavior, different priming methods have been used for influencing brand and product choices. It has been established that (supra- and subliminally) priming various concepts can affect consumer decision-making and brand preference (e.g., Strahan et al., 2002). The present results contribute to this body of knowledge by demonstrating that brands themselves can also function as primes and indirectly affect different forms of consumer behavior. Moreover, brands are capable of activating a host of associations that can lead to consumer behavior unrelated to the advertised product.

To date, most priming research focused on activating mental constructs that were semantically related to the intended behavior (e.g., Bargh et al., 1996; Dijksterhuis et al., 2000; Dijksterhuis and van Knippenberg, 1998). For instance, Bargh, Chen, and Burrows (1996), demonstrate that activating the concept of “rudeness” facilitates interrupting the experimenter. The present research extends these findings by showing that the activated construct needs not necessarily be semantically related to the intended behavior. Specifically, the findings showed that death-related thoughts can trigger semantically unrelated behavior, such as increased spending. In other words, there seems to be a direct relation between the accessibility of deathrelated thoughts and spending intentions, though this relation cannot be viewed as semantic. Although the present research did not directly measure any activated motivations, the underlying assumption is that the activated death-related thoughts induced the motivation to regulate experienced terror. This finding opens a new reservoir of behavior, motivations and needs that might be susceptible to activation by brand exposure. In sum, marketing-related stimuli can serve as primes that trigger unconscious consumer motives. In the present research, a seemingly trivial stimulus such as a brand logo activated different worldview defense strategies when participants thought about the brand very thoroughly, when the brand was an incidental part of the environment, and even when participants perceived the brand logo at a subliminal level. 6.3. Concluding remarks Brands are capable of automatically activating related constructs and presumably motivations as well. This might open a new way of looking at brand marketing strategies. Consumers are certainly not aware of all the effects that brand exposure might have on them, regardless of whether this exposure was a conscious or unconscious experience for them. None of the participants in our studies made any connection between the brand exposure and their spending intentions or product evaluations. This may be a blessing in disguise, given the abundance of brands and the plethora of effects that they might unconsciously evoke. Perhaps consumers are better off remaining “comfortably ignorant” rather than constantly realizing that such seemingly trivial stimuli as brand logos can remind them about the inevitable end that lies ahead, and can shape their behavior in more ways than one. References Aaker DA. Managing Brand Equity. New York: Free Press; 1991. Aiken LS, West SG. Multiple regression: Testing and interpreting interactions. Sage Publications, Inc; 1991. Anderson JR. The architecture of Cognition. Cambridge, MA: Harvard University Press; 1993. Arndt Jamie, Greenberg Jeff, Solomon Sheldon, Pyszczynski Tom, Simon Linda. Suppression, accessibility of death-related thoughts, and cultural worldview defense: exploring the psychodynamics of terror management. J Pers Soc Psychol 1997;73(1):5–18. Arndt Jamie, Solomon Sheldon, Kasser Tim, Sheldon Kennon M. The urge to splurge: a terror management account of materialism and consumer behavior. J Consum Psychol 2004;14(3):198–212.

M.L. Fransen et al. / Journal of Business Research 61 (2008) 1053–1061 Bargh John A. Losing consciousness: automatic influences on consumer judgment, behavior, and motivation. J Consum Res 2002;29(11):280–5. Bargh John A, Pietromonaco P. Automatic information processing and social perception: the influence of trait information presented outside of conscious awareness on impression formation. J Pers Soc Psychol 1982;43(3): 437–49. Bargh John A, Chartrand Tanya L. The mind in the middle: a practical guide to priming and automaticity research. In: Reisand Harry T, Judd Charles M, editors. Handbook of research methods in social and personality psychology. Cambridge: University Press; 2000. p. 253–85. Bargh John A, Chen Mark, Burrows Lara. Automaticity of social behavior: direct effects of trait construct and stereotype activation on action. J Pers Soc Psychol 1996;71(2):230–44. Baron Reuben M, Kenny David A. The moderator–mediator variable distinction in social psychological research: conceptual, strategic, and statistical considerations. J Pers Soc Psychol 1986;51(7):1173–82. Bauman Zygmunt. Life in Fragments: Essays in Postmodern Morality. Oxford: Blackwell; 1995. Belén del Río A, Vázques Rodolfo, Iglesias Victor. The effects of brand associations on consumer response. J Consum Mark 2001;18(5):410–25. Brown Tom J, Dacin Peter A. The company and the product: corporate associations and consumer product responses. J Mark 1997;61(1):68–84. Cobb-Walgren Cathy J, Ruble CA, Donthu N. Brand equity, brand preference, and purchase intent. J Advert 1995;24(3):25–40. Dijksterhuis Ap, van Knippenberg Ad. The relation between perception and behavior, or how to win a game of trivial pursuit. J Pers Soc Psychol 1998;74 (4):865–77. Dijksterhuis Ap, Aarts Henk, Bargh John A, van Knippenberg Ad. On the relation between associative strength and automatic behavior. J Exp Soc Psychol 2000;36(5):531–44. Ferraro Rosellina, Shiv Baba, Bettman James R. Let us eat and drink, for tomorrow we shall die: Effects of mortality salience and self-esteem on selfregulation in consumer choice. J Consum Res 2005;32(1):65–75. Greenberg Jeff, Pyszczynski Tom, Solomon Sheldon. The causes and consequences of a need for self-esteem: a terror management theory. In: Baumeister Roy F, editor. Public Self and Private Self. New York: SpringerVerlag; 1986. p. 189–92. Greenberg Jeff, Pyszczynski Tom, Solomon Sheldon, Rosenblatt Abram. Evidence for terror management theory II: the effects of mortality salience on reactions to those who threaten or bolster the cultural worldview. J Pers Soc Psychol 1990;58(2):308–18. Greenberg Jeff, Pyszczynski Tom, Solomon Sheldon, Simon Linda. Role of consciousness and accessibility of death-related thoughts in mortality salience effects. J Pers Soc Psychol 1994;67(4):627–37. Greenberg Jeff, Porteus Jonathan, Simon Linda, Pyszczynski Tom. Evidence of a terror management function of cultural icons: the effects of mortality salience on the inappropriate use of cherished cultural symbols. Pers Soc Psychol Bull 1995;21(11):1221–8. Greenberg Jeff, Koole Sander L, Pyszczynski Tom. Handbook of experimental existential psychology. Guilford Press; 2004. Heine Steven J, Harihara M, Niiya Y. Terror management in Japan. Asian J Soc Psychol 2002;5(3):187–96. Higgins E Tory, Bargh John A, Lombardi Wendy J. Nature of priming effects on categorization. J Exper Psychol, Learn, Mem, Cogn 1985;11(1):59–69. Jonas Eva, Schimel Jeff, Greenberg Jeff, Pyszczynski Tom. The Scrooge effect: evidence that mortality salience increases prosocial attitudes and behavior. Pers Soc Psychol Bull 2002;28(10):1342–52. Jonas Eva, Fritsche Immo, Greenberg Jeff. Currencies as cultural symbols — an existential psychological perspective on reactions of Germans toward the Euro. J Eco Psychol 2005;26(1):129–46. Kasser Tim, Sheldon Kennon M. Of wealth and death: materialism, mortality salience, and consumption behavior. Psychol Sci 2000;11(4):348–51. Kay Aaron C, Wheeler S Christian, Bargh John A, Ross Lee. Material priming: the influence of mundane physical objects on situational construal and

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Available online at www.sciencedirect.com

Journal of Business Research 61 (2008) 1062 – 1075

When consumers love their brands: Exploring the concept and its dimensions Noël Albert a,b , Dwight Merunka c,d,⁎, Pierre Valette-Florence e,f a

c

University of Grenoble (IAE), France b University of Lyon-1, France University Paul Cézanne Aix-Marseille, IAE Aix en Provence, France d EUROMED Marseille School of Management, Marseilles, France e University of Grenoble (IAE), France f CERAM Nice, France

Received 1 March 2007; received in revised form 1 July 2007; accepted 1 September 2007

Abstract Consumers may develop feelings of love toward some brands, but the meaning and underlying dimensions of this construct require further development. Through an exploratory Internet study of 843 respondents in France, this research used both qualitative and quantitative approaches to explore the concept of love. Eleven dimensions emerge through a correspondence analysis and the concomitant use of a multiple correspondence analysis and cluster analysis of the wording that respondents use to describe their feeling of love and the special type of relationships they have with the brands they love. These dimensions identified in France compare to dimensions of love found in previous research conducted in the United States. © 2007 Elsevier Inc. All rights reserved. Keywords: Love; Brand–consumer relationship; Brand management; Cultural differences

Brands are omnipresent in the everyday life of consumers. Recent research focus on understanding and explaining the type of relationships consumers have with branded products. Constructs and measures of brand sensitivity (Kapferer and Laurent, 1992), brand attachment (Thomson et al., 2005), brand commitment (Samuelsen and Sandvik, 1998), brand trust (Chaudhuri and Holbrook, 2001), and brand loyalty (Jacoby and Chesnut, 1978), for example, distinguish among various consumer–brand relationship concepts and segment consumers into groups on the basis of the intensity of those relationships (Fournier, 1998). In contrast, the concept of love is more recently investigated (Ahuvia, 2005b; Fournier, 1998) and relatively less researched. In turn, questions remain, such as whether consumers can experiment feelings of love for a brand. Is the feeling of love for a brand similar to a feeling of love for a ⁎ Corresponding author. IAE Aix en Provence, Clos Guiot, 13540 Puyricard, France. Tel./fax: +33 442 280 808/800. E-mail addresses: [email protected] (N. Albert), [email protected] (D. Merunka), [email protected] (P. Valette-Florence). 0148-2963/$ - see front matter © 2007 Elsevier Inc. All rights reserved. doi:10.1016/j.jbusres.2007.09.014

person? What dimensions characterize the feeling of love toward an object (brand)? Do people feel this love relationship in the same manner across countries or cultures? During the past decade, marketing research has investigated the concept of love and established that such a feeling may exist from a consumer's perspective when the loved object is a possession or a brand. Based on the relational paradigm and the notion that consumers may attribute human characteristics to brands (Aaker, 1997; Fournier, 1998), the academic community started paying attention to the concept of love. Practitioners also express interest in the concept (Roberts, 2004, 2006). However, extant research seems to be solely of U.S. origin, even though cross-cultural differences are very likely. For example, research based on interpersonal relationship theory (Beall and Sternberg, 1995; Deschamps et al., 1997) shows that culture influences the conceptualization and dimensions of the love construct. This research investigates the feeling of love toward a brand by exploring the nature of the construct and uncovering the main dimensions of a feeling of love for brands among a large sample of French consumers. Because culture may affect the results, this research also compares findings with recent U.S.

N. Albert et al. / Journal of Business Research 61 (2008) 1062–1075

research results. The first section provides a literature review pertaining to the concept of love in interpersonal relationships, reviews the development of available (American) conceptualizations of love toward a brand, and comments on their limitations. The second section details the method developed to avoid these limitations, measures the love construct, and determines its underlying dimensions. Finally, the third section presents and discusses results related to the dimensions of love uncovered in the French data and compares them with concepts developed from U.S. data. 1. The feeling of love 1.1. The feeling of love in interpersonal relationships Theories of love suggest its cultural and historical underpinnings. For example, one view that emerges from the industrial revolution construes love with the same intensity and faith required of religion (Hatfield and Rapson, 1987). According to this view, love cannot be theorized or understood. Nevertheless, since that period in history, different sciences seek to study the love construct. For example, sociology uses observable manifestations (e.g., marriages, fertility rates), and psychoanalysis places sexuality at the heart of the love construct. However, because these approaches are of little use to our understanding of love in consumer behavior, our research concentrates on social psychology's conceptualization of love, within which a relationship paradigm applies. 1.1.1. Love as a psychological state Aron and Aron (1986, 1996) describe love as a psychological state. Because the union of two persons characterizes love, they use the inclusion of an other into the self as a means to understand this feeling and refer to three main principles: (1) people extend themselves, (2) by including others within themselves through intimate or close relationships, and (3) people seek situations or experiences associated to an experience of extension of the self. According to these principles, the expression of a feeling of love entails a two-stage process whereby the self expands to new persons and the object of the extension becomes included in the self. Love therefore is “the constellation of behaviors, cognitions and emotions associated with the desire to enter or maintain a close relationship with a specific other person” (Aron et al., 1991, p. 26). However, the feeling of love is not necessarily romantic and may apply to many others (e.g., family members, friends). 1.1.2. Love as an independent psychological construct Two main influential theories by Rubin (1970) and Sternberg (1986) break with the tradition and consider love as a superior form of friendship. Rubin defines love as “an attitude held by a person toward a particular other person, involving predispositions to think, feel, and behave in certain ways toward that other person” (Rubin, 1970, p. 265). Love is a three-dimensional construct composed of affiliation and need for dependence, predisposition to help, and exclusivity and absorption (inclusion of the other). Sternberg (1986, 1997) proposes a triangular theory of love with three components: intimacy, passion, and

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decision/commitment, which appear in most conceptualizations of love. Intimacy refers to closeness and connectedness, being happy together, and being able to rely on the partner. Passion involves romance, physical attraction, arousal, and needs such as self-esteem, nurturance, or self-actualization. Finally, decision/commitment refers to the short-term decision to love someone and the will to maintain that relationship over the long term. Combining the three components leads to eight love styles, depending on the presence or absence of each component in interpersonal relationships (see Table 1). Many studies (Fehr, 1988; Luby and Aron, 1990; Regan et al., 1998) offer lists of adjectives that can capture the feeling of love. These lists consist of many items (e.g., 68 in Fehr, 1988, including trust, caring, honesty, friendship, respect, concern for other's well-being, loyalty, commitment, accepting the other, and supportiveness; 119 in Regan et al., 1998) but fail to provide us with a clear picture of prototypical love (Ahuvia, 2005b). Aron and Westbay (1996) factor analyzed Fehr's (1988) list of adjectives and find a three-dimensional structure of passion, intimacy, and commitment—corroborating Sternberg's (1986) theory. 1.2. The feeling of love in consumer behavior 1.2.1. Feelings of love toward objects Shimp and Madden (1988) propose a conceptual model of “consumer–object relationships” inspired by the triangular theory of love (Sternberg, 1986), in which Sternberg's three components of love (intimacy, passion, and decision/commitment) become liking, yearning, and decision/commitment in a consumption context. When these three components exist, they strongly contribute to loyalty toward the object. However, Shimp and Madden do not empirically test the validity of their construct. Later, Ahuvia (1993, 2005a,b) provides empirical support for this construct by proposing a conditional integration of the theory of love based on work by Aron and Aron (1986). Specifically, Ahuvia (1993) posits that a person may feel love for an object when the level of integration and desire for that object reaches a critical threshold. Ahuvia (2005b) also compares interpersonal love and love for an object based on the notion of a “prototype” of love (e.g., Aron and Westbay, 1996; Fehr, 1988; Fehr and Russel, 1991). He acknowledges that these two types of love have more similarities than differences. Table 1 Taxonomy of kinds of love Kind of love

Nonlove Liking Infatuated love Empty love Romantic love Companionate love Fatuous love Consummate love

Components Intimacy

Passion

Decision, commitment

− + − − + + − +

− − + − + − + +

− − − + − + + +

Source: Adapted from Sternberg (1986).

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Whang et al. (2004) conduct a study using the construct of love based on the interpersonal paradigm and measure this feeling by employing a shortened version of the love attitude scale, its origin being from the “The Colors of Love” typology proposed by Lee (1977) (Hendrick and Hendrick, 1986). The love a biker feels for his or her motorcycle consists of three variables: eros (passionate love), mania (possessive love), and agape (altruistic love). Because they use a measure of love directly derived from interpersonal relationship studies, they conclude that the relationship between a biker and his or her motorcycle represents romantic love. The Whang et al. study is the first to capture consumer's love toward a product. 1.2.2. Feelings of love toward a brand Fournier (1998) reveals that consumers develop and maintain strong relationships with brands and proposes six major categories of relationships, including love and passion, defined as a richer, deeper, more long-lasting feeling than simple preference. Caroll and Ahuvia (2006, p. 5) define love for a brand as “the degree of passionate emotional attachment that a person has for a particular trade name.” Consumers' love includes the following characteristics: (1) passion for a brand, (2) brand attachment, (3) positive evaluation of the brand, (4) positive emotions in response to the brand, and (5) declarations of love toward the brand. These studies help better understand the construct of love in a consumer behavior context but yet have some theoretical, methodological, and managerial limitations. The study of love in marketing employs two main frameworks: the interpersonal theory of love applied to consumer situations (Ahuvia, 1993; Whang et al., 2004) and an empirical approach consisting of a conceptualization of consumers' declarations of “love” toward brands (Fournier, 1998). This second framework is mostly a-theoretical, and interpretations based on this approach are vulnerable to criticism. For example, why are not concepts of intimacy, commitment, or connection to the self (i.e., potential relationships between consumers and brands) connected to the love relationship (Fournier, 1998)? Although these dimensions are not unique to feelings of love, they appear in various interpersonal studies pertaining to love (Aron and Aron, 1986; Hatfield, 1988; Sternberg, 1986). In contrast to this empirical approach, several studies (Ahuvia, 1993; 2005b; Shimp and Madden, 1988; Whang et al., 2004) construe love in marketing on the basis of theories of interpersonal relationships. Overall, love appears to represent a complex phenomenon, and no single interpersonal theory may claim to capture all the emotions linked to this feeling, which means choosing any particular theory of interpersonal relationships may be theoretically constraining at this point. The study of love relationships should begin with little or no preconceived notions and proceed on an exploratory basis, especially if the study occurs in a new cultural context. Such results should then be interpreted using existing interpersonal (or consumer/brand) theories of love. Adopting such a method avoids focusing on one theory and provides the opportunity to establish a link between the empirical results and different conceptualizations of love.

In many exploratory studies that use qualitative interviews (e.g., Ahuvia, 1993, 2005b; Fournier, 1998), the interviewers actually employ the word “love” and thereby introduce a bias in the sense that subjects may formulate their responses in reference to a feeling of love for a person and exclude dimensions of love specific to an object or a brand. Although Ahuvia proposes several dimensions that do not match prototypical love, the method still casts doubt on the reliability of the data. An exploratory study using projective methods avoids this potential pitfall. Therefore, the measurement of love should be approached without the explicit use of the word itself and without directly referring to concepts that link naturally to interpersonal relationships (unless testing a previously established theory). Finally, several important studies in this area (Ahuvia, 1993, 2005b) examine objects in a broad sense rather than brands specifically. Even though these studies develop an understanding of the construct of love, their managerial utility is limited. In another vein, Shimp and Madden (1988) simply adopt Sternberg's (1986) vocabulary and apply this lexicon to a consumer–object relationship. The method proposed here is an attempt to circumvent these limitations. 2. Research methodology Choosing a data collection tool represents an important research step. A first data collection stage using semi-directed interviews revealed that consumers poorly understand the notion of love toward a brand and perhaps, for some, reject this kind of love. For many consumers in France, love represents a sacred feeling that cannot be felt toward a brand. Therefore an innovative survey method is implemented to avoid consumer reluctance or unfamiliarity with the concept. 2.1. Data collection procedures The use of an Internet survey enables collecting data to investigate the dimensions of love for a brand and this is conducted in the French market. The diagram in Fig. 1 shows the overall structure of the survey method applied in this research. The first step is designed to reveal subjects' opinions relative to brands in general. Subjects then indicate 1 to 3 brands they wish to discuss (step 2). For each brand, subjects select one image among 19 possible ones. The chosen image symbolizes their relationship with the brand (step 3.1) and they explain their choice (step 3.2). The objective of this step is to identify the relationship the consumer has with the brand. Subjects then view three images (from the initial 19) that tentatively symbolize love (images numbered 3, 9, and 16 and circled in Fig. 2) and describe their perceptions of these images (step 3.3). This step validates subjects' recognition of love as expressed by these images. For subjects who chose an image symbolizing love during step 3.1 and therefore potentially having a love relationship with a brand, the meaning of that love relationship is further investigated (those who did not choose one of these symbols move to step 4.1, as indicated in Fig. 1). Specifically,

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Fig. 1. Structure of Internet survey.

they indicate if they feel the brand is “special” and justify their perception (step 4.2.1), which elucidates the relationship between the consumer and the brand without using the word “love.” The following text then appears: “The choices you have made suggest that you are really in love with [brand name]. Do you agree with this statement?” Note that this point marks the first time the survey explicitly uses the word “love.” Subjects respond to this question (step 4.2.2) and justify their answer (step 4.2.3). This method is based on the theory that consumers who have a love relationship with a brand will choose an image symbolizing love to represent and explain their relationship. However, to guard against respondents who do not experience a love relationship and may nevertheless select one of these images, the final step in the methodology allows to distinguish consumers who have from those who do not have a true love relationship with brands.

The Internet is used as a data collection medium because it enables the adaptation and personalization of the survey based on subjects' responses (i.e., some questions appear only after subjects select an image symbolizing love). This data collection technique is also highly effective for communication with respondents (e.g., reminding them of brand names they mention or brand images they previously select). With respect to sampling, an Internet snowball procedure is used, in which the online link for the survey questionnaire is sent to a list of direct contacts, together with a personal message requesting that the recipients answer the survey and transmit the link to others they know. This leads to the participation of 880 individuals and the selection of 843 fully completed questionnaires used for further analysis. Overall, 2340 observations are obtained, and the mean number of brands cited by each participant equals 2.77.

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Fig. 2. Images submitted to respondents.

2.2. The use of projective images A projective method is used, which exposes people to different stimuli they are asked to describe. This method is effective in encouraging subjects to project hidden opinions,

attitudes, or feelings about an object or situation. Projective methods are appropriate when direct methods cannot acquire the required information precisely or researchers need a better understanding of the phenomenon (Malhotra, 2004). Consumers may experience difficulty acknowledging or confessing

Fig. 3. Methodology.

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their love relationship with a brand, and projective methods that avoid the use of the word “love” but offer possibilities to express this feeling do not prejudice subjects' answers. In addition, because this study is designed as exploratory, a projective method should be effective in helping conceptualize the concept of love for a brand. The hybrid survey methodology used here employs both quantitative (many respondents, close-ended questions) and qualitative (production of text, exploratory) methods. This helps circumvent two biases observed in previous research: (1) the word “love” only appears at the very end of the data collection procedure and does not bias subjects' responses, and (2) the results are truly exploratory because no interpersonal love theory is used to guide the development of data collection procedures. 2.3. Analysis of data through correspondence analysis Correspondence analysis provides a spatial representation of qualitative profiles in a reduced Euclidean space. A simple correspondence analysis (CA), a descriptive technique, can analyze and depict the relationships between the row and column profiles in a two-way table. In practice, the method decomposes the overall chi-square statistic by identifying a small number of dimensions to represent deviations from the expected values. Multiple correspondence analysis (MCA) analyzes multi-way tables. Both forms are used in this research. In a first stage, CA is used to study the connections between the lexicons and the images singled out to represent the nature of the relationship with the brand. The use of CA enables understanding the structure of the lexicons used for brands for which consumers have varying levels of love intensity. In a second stage, for those respondents who express their love for a particular brand, MCA is applied to estimate the coordinates in a multidimensional space of the words that express the feeling

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of love. Then the words are clustered through the use of cluster analysis applied to their spatial coordinates, which is analogous to the concomitant use of factor analysis and clustering for quantitative variables. A method referred to as “de-doubling,” such that each word appears twice (evoked or not evoked) in the configuration is used to analyze the data. This procedure helps guarantee equal weight for all words (Morineau et al., 1984). 3. Results A validity check is initially realized in order to assess that the association of images to brands is meaningful and that the images that subjects select are associated with contrasting lexicons. A manipulation check serves to verify that the images selected to symbolize love actually represent symbols of love for the consumers (and that the other images do not). The dimensions of the concept of love toward a brand are then uncovered. The different steps of the procedure appear in Fig. 3. 3.1. Manipulation checks To confirm the validity of the procedure, the meanings associated with the images selected to represent love are verified. Although marketing experts did select these images, an understanding of how consumers perceive the three images that tentatively symbolized love is necessary. Study participants (n = 843) indicate the feelings they experience when exposed to each of the three “love” images and the frequencies of the words used to describe each image are shown in Table 2. For example, descriptions of image 3 include the following terms: complicity, love, happiness, friendship, tenderness, couple, simplicity, trust, togetherness, and joy. Because the distinction between love and friendship is ambiguous, this image is treated as somewhat vague. In contrast, image 9 communicates love in terms of loyalty and commitment since respondents use words such as

Table 2 Twenty most frequently cited words describing the three images associated with love (number and percentage of citations in columns 2 and 3) Image 3 Complicity Love Happiness Tenderness Couple Joy To be Friendship Trust Happy Two Pleasure Life Simplicity Amorous Relationship Moment Meeting To live Good

Image 9 289 116 101 71 68 55 50 26 24 23 20 19 16 16 12 11 10 9 10 9

32.8% 13.2% 11.5% 8.1% 7.7% 6.3% 5.7% 30.0% 2.7% 2.6% 2.3% 2.2% 1.8% 1.8% 1.4% 1.3% 1.1% 1.0% 1.1% 1.0%

Love Marriage Happiness Commitment Life Couple Loyalty Union Image Family Trust Beginning Two Day Happy Joy Future History Beautiful Enduring

Image 16 175 157 109 98 51 41 40 39 15 15 15 14 14 12 12 12 9 9 8 8

19.9% 17.8% 12.4% 11.1% 5.8% 4.7% 4.5% 4.4% 1.7% 1.7% 1.7% 1.6% 1.6% 1.4% 1.4% 1.4% 1.0% 1.0% 0.9% 0.9%

Sensuality Passion Sex Desire Love Pleasure Eroticism Couple Sexuality Hot Image Warmth Relationship Perfume Happiness Intimacy Carnal Physical Tenderness Two

152 143 86 83 78 70 39 27 21 19 14 13 13 12 11 11 10 10 10 8

17.3% 16.3% 9.8% 9.4% 8.9% 8.0% 4.4% 3.1% 2.4% 2.2% 1.6% 1.5% 1.5% 1.4% 1.3% 1.3% 1.1% 1.1% 1.1% 0.9%

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marriage, commitment, love, couple, confidence, and union to describe it. Finally, the lexicon employed to describe image 16 relates to passion and desire, including words such as sensuality, passion, sex, desire, love, pleasure, and eroticism. Therefore, images 9 and 16 clearly reflect the concept of love described by existing theories of love, and image 3 reflects both love and friendship, though love appears to dominate. Another manipulation check consists of performing a CA of the 52 words that consumers use most frequently to justify the choice of an image that represents their relationships to brands. Conducted with 2340 observations (participant × brand chosen), the analysis clearly shows differences in the words associated with different clusters of images (Fig. 4). Five homogeneous groups of images and associated words emerge from a configurational analysis based solely on the first plane (Borg and Lingoes, 1987): words associated with the three images symbolizing love (group 1); consumers for whom the brand communicates elegance and fashion (group 2); those who use words linked to brand trust, reliability, and quality (group 3); those for whom the brand relates to price (group 4); and consumers for whom the brand indicates sports or a relaxed atmosphere (group 5). Consumers who choose images symbolizing love tend to explain their choices with words closely related to love. Therefore, they are aware that these images represent the concept of a love relationship. 3.2. Uncovering the dimensions of love 3.2.1. Correspondence analysis Two open-ended questions help to clarify the feeling of love for a brand. The first (“Why is brand X so special to you?”) avoids using the word love. The second question (“Why do you have a real feeling of love for brand X?”) enriches the consumers answers. Correspondence analysis (CA) enables summarizing and visualizing the lexicons used by respondents for each open-ended question. Among the 2340 observations (843 participants citing 1, 2, or 3 brands), 659 observations correspond to a chosen “love” image for a brand. More than 50% of these observations completely agree (15.3%) or agree (40.1%) that they are really in love with their brands (30.8% rather disagree and 13.8% completely disagree). Two CAs are conducted, one associating the lexicons used to describe why the brand is “special” and the four love groups described above (according to their degree of agreement concerning a love relationship with the brand) and the other associating the lexicons used to describe why respondents may be in love with their brand and the similar four love groups. The results of both CAs are similar (results for the latter correspondence analysis appear in Fig. 5). Correspondence analyses explain 51.07% (axis 1) and 34.69% (axis 2) of the variance for the first association and 58.76% (axis 1) and 17.08% (axis 2) for the second. The CAs also reveal differences in the vocabulary employed by the four love groups. Of particular interest is the unique position of participants who fully agree that they are in love with their brand. They fall distant from the other groups and are the only ones to use words such as pleasure, dream,

personality, memories, number of years, always, attraction, childhood, or family. This unique position calls for a better understanding, as do the specific dimensions of the feeling of love. 3.2.2. Tandem use of multiple correspondence analysis (MCA) and cluster analysis To uncover the dimensions of love, consumers who declared they completely agree or rather agree they have a feeling of love toward a brand (n = 365) are selected for further analysis. Separate MCAs are conducted, one for the words used to express why the brand is special, and another for the wording consumers used to explain why they feel love toward the brand. In both cases, according to a clear elbow displayed in a scree plot of the eigenvalues, the MCAs lead to a solution with 22 dimensions explaining more than 60% of total variance. As a result, each word is described by a vector of coordinates on 22 dimensions which enables to cluster analyze the words in an effort to uncover grouping or dimensions (one cluster analysis is conducted for each MCA result; see Figs. 6 and 7 for the dendograms). For a better understanding, we incorporate the product categories mentioned by the participants when describing their brands as supplementary points in the MCA analysis. In this special case, the analysis employs “predictive mapping,” in that meaningful associations among active variables (lexicons) and external variables (product categories) are displayed. Both cluster analyses reveal the existence of nine clusters that enable uncovering the underlying dimensions of the love feeling among consumers who either fully agree or rather agree they have such a feeling toward their brand. However, these two categories of agreeing respondents are distant one from the other. Consequently, a focus is made on the “fully agree” category which best represents the feeling of love. Product categories that are strongly associated with the feeling of love include shoes, cars, lingerie, watches, perfumes, food items, music, cigarettes, and furniture. 3.3. Main dimensions of love toward a brand On the basis of the results of the two cluster analyses, previous results obtained from the words associated with love images and the results from the correspondence analyses, the dimensions of love are named individually by each author. A simple process is followed, in which concepts are associated to each of the 9 clusters in both cluster analyses, on the basis of the words grouped together to form the clusters. Final concepts appearing in Fig. 6 result from discussion and agreement among the three judges. Finally, all concepts that are related to the fully agree category are selected as key dimensions of the feeling of love. The dendogram in Fig. 6 (first cluster analysis) shows that the first seven clusters (to which “fully agree” belongs) join together at a higher level, whereas the two last clusters join together and are related to the rather agree category. For the dendogram in Fig. 7 (second cluster analysis), these groupings are six and three clusters, respectively. Due to the exploratory nature of the research, the constructs appearing at least once in the first groups of clusters (clusters related to full agreement with a love relationship with the brand) are retained as the dimensions of love.

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Fig. 4. Results of the correspondence analysis between images and associated lexicon.

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Fig. 5. Results of the correspondence analysis for the expression of the feeling of love toward a brand.

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Fig. 6. Cluster analysis of the words used to explain why the brand is special for the consumers.

As a result of this analysis, 11 dimensions of love toward a brand are identified: • Passion (for the brand). • Duration of the relationship (the relationship with the brand exists for a long time). • Self-congruity (congruity between self-image and product image).

• • • • • • • •

Dreams (the brand favors consumer dreams). Memories (evoked by the brand). Pleasure (that the brand provides to the consumer). Attraction (feel toward the brand). Uniqueness (of the brand and/or of the relationship). Beauty (of the brand). Trust (the brand has never disappointed). Declaration of affect (feel toward the brand).

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Other dimensions emerge but relate to consumers who rather agree (vs. fully agree) that they have a love relationship with the brand. The following dimensions therefore are not retained as major dimensions of love: • Functional perceptions (quality of the brand, good price). • Commitment (will to maintain a relationship with the brand in the future). • Well-being (the brand makes the consumer feel good). • Attachment. The exploratory nature of this study does not enable an identification of the number of dimensions necessary to infer the

existence of a love relationship. However, in all likelihood, not all dimensions must be simultaneously present for a loving consumer–brand relationship to exist. To examine these dimensions more closely, they are compared to dimensions of interpersonal love identified in the literature (Aron and Aron, 1986; Fehr and Russel, 1991; Hatfield, 1988; Hendrick and Hendrick, 1989; Sternberg, 1986). 3.3.1. Passion Often associated to the feeling of love (Hatfield, 1988; Lee, 1977; Sternberg, 1986), passion maintains different names, such as eros (Hendrick and Hendrick, 1986; Lee, 1977) or romantic love (Rubin, 1970). Passionate love is “a state of

Fig. 7. Cluster analysis of the words used to explain why consumers have a real feeling of love for a brand.

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intense longing for union with another” (Hatfield and Walster, 1978, p. 9). 3.3.2. Duration of the relationship The duration of the relationship is often linked to intimacy which refers to in-depth knowledge about the partner, generally as a result of time spent together (Ahuvia, 2005b; Aron and Westbay, 1996; Fehr, 1988; Hendrick and Hendrick, 1989, 1992; Sternberg, 1986). This long-lasting relationship suggests the existence of a feeling of satisfaction with its established impact on duration of the relationship (Hendrick et al., 1988). 3.3.3. Self-congruity Several studies provide evidence that members of a couple tend to be similar in terms of ethnic, social, or religious profile, as well as their values, centers of interest, humor, or even physical aesthetics or personality (Byrne et al., 1986; Cappella and Palmer, 1990; Galton, 1984; Rushton, 1989). The concept of self-congruity is of similar nature since the notion indicates congruity between the self-image of the consumer and product image (Sirgy, 1985). Love with the brand may be driven by both self-consistency motives and self-esteem motives. 3.3.4. Dreams Consumers in love reveal that they dream about the brand or that the brand favors their dreams, which indicates the dominant presence of the brand in their thoughts. In interpersonal relationships, a clear link exists between loving and thinking of the partner; constant thinking about a partner is a good indicator of future love (Shea and Adams, 1984, qtd. in Ahuvia, 1993). The synthesis of the love prototype (Ahuvia, 2005b) also integrates thinking of the partner as an antecedent of love, though this antecedent does not disappear after the relationship begins. Finally, research shows that interpersonal love is linked with positive emotions (Fehr and Russel, 1991), and dreaming of the brand can represent a manifestation of these positive emotions. 3.3.5. Memories A brand may remind consumers of certain important and positive memories and link to sentiments of nostalgia (according to expressions of words such as history, childhood, or first). This specific characteristic of love suggests a non-interpersonal context, because this concept has not been addressed in current interpersonal theories of love. 3.3.6. Pleasure Fehr and Russel (1991) show that love is linked to positive emotions, including pleasure, and that pleasure fosters affectionate love (Hatfield, 1988). In the case of love toward a brand, pleasure has a positive influence on the duration of the relationship. 3.3.7. Attraction A dimension of interpersonal love, attraction is “an orientation toward or away from a person that may be described as having a value (positive, neutral or negative). The orientation

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consists of a cognitive structure of beliefs and knowledge about the person, affect felt and expressed toward him or her, and behavioral tendencies to approach or avoid that person” (Hendrick and Hendrick, 1992, p.23). 3.3.8. Uniqueness Respondents indicate that their preferred brand is different or unique, which may relate to the feeling of idealization often mentioned in interpersonal love theories (Murray and Holmes, 1993; Murray et al., 1996; Sternberg and Barnes, 1985). Lovers often consider their partners unique or different. 3.3.9. Beauty Beauty is a determinant of love relationships (Walster et al., 1966). Beauty plays a role both in favoring a relationship and maintaining the relation in the long term (Hatfield and Sprecher, 1995; Sangrador and Yela, 2000). 3.3.10. Trust Consumers in love seem to declare they have never been disappointed and express their satisfaction with the brand, which is in line with Hendrick et al. (1988) who provide insights into the link between satisfaction and specific styles of love (i.e., eros and agape). Trust is also a key dimension revealed in studies of prototypical love (Fehr, 1988; Aron and Westbay, 1996). 3.3.11. Declaration of affect The fact of declaring love or deep sentiments before or after the love relationship takes place is reported in research on the feeling of love (Vincent, 2004). This dimension “declaration of affect” is named rather than “declaration of love” because many different words are employed by the consumers to express their love relationship toward brands: adore, amorous, love, appreciate, or like. Concerning the dimensions that are not associated to the love feeling (the dimensions only related to the category “rather agree”), some appear in the interpersonal love literature such as commitment (Fehr, 1988; Sternberg, 1986), well-being (Kim and Hatfield, 2004), and attachment (Fehr, 1988). Attachment and commitment are also well-known and important concepts in research on brand/consumer relationships (Garbarino and Johnson, 1999; Thomson et al., 2005), but they are not directly related to a feeling of love toward the brand. This research being exploratory in nature, the lack of relationships between these dimensions and the overall feeling of love needs further investigation. 4. Discussion and conclusion The dimensions of love toward a brand, as found with French consumers declaring a love relationship with a brand are compared with the results from previous research conducted in the United States. This comparison should enhance the external validity of the construct and may point to the possible influence of culture. Several dimensions of love toward a brand found among French consumers also appear in U.S. studies. Two dimensions are explicitly shared by both cultures: passion (Ahuvia, 2005b;

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Caroll and Ahuvia, 2006; Fournier, 1998; Whang et al., 2004) and pleasure (Ahuvia, 1993, 2005b). In addition, three other French dimensions are linked to American ones, specifically dream, declaration of affect, and duration of the relationship. The dream dimension relates to the “fixated thought” concept (Ahuvia, 2005b) as well as to positive emotions toward a brand (Caroll and Ahuvia, 2006). Declaration of affect appears in both cultures but with possibly different intensity: the word “love” is explicitly employed in the U.S. (declaration of love) whereas French consumers rather use “adore” or “like” when talking about the loved brand. The French duration dimension also appears to relate to the concepts of intimacy that appear in several American studies (Ahuvia, 1993, 2005b). Beauty, attraction, uniqueness and self-congruity also appear in Ahuvia (1993). However, the comparison with Ahuvia's study (1993) is not straightforward since this study encompasses love relationships linked to a number of objects including places, ideas, music pieces and brands. It may be that some of the dimensions of love are activated for only certain types of objects (Ahuvia, 1993). Many differences also exist between French and U.S. participants. The memory and trust dimensions do not appear in U.S. studies but are clear in France, as evidenced by the respondents' use of words such as memories, childhood, images, or history (for memory) and of words of trust and loyalty (for trust). Attachment is cited in one U.S. study (Caroll and Ahuvia, 2006). The dimension appears in only one of the MCAs and attachment is linked to the category “rather agree” which explains why the concept is not retained in this study. Consumers using the term admit they are only attached to the brand and therefore not really in love with the brand. Finally, a distinction between possessive love and altruistic love is not uncovered here, as suggested by Whang et al. (2004). This research reconsiders the concept of consumers' love for a brand outside the “silo” of U.S.-based research (Steenkamp, 2005). Because love and the expression of love are culturally grounded, this relatively new concept of love toward brands is tested in a cultural and consumption context other than that of the United States. In France, the concept of love toward a brand does not fit with theories that define this feeling as a person's psychological state (Aron and Aron, 1986; see also Tennov, 1979 with regard to interpersonal relationships; see Ahuvia, 1993, for non-interpersonal relationships). Rather, the French conception more closely matches research streams that conceptualize love as a set of characteristics and dimensions (Rubin, 1970; Sternberg, 1986, for interpersonal relationships; Caroll and Ahuvia, 2006, for non-interpersonal relationships). The approach in this research further differs from the American perspective because it employs an exploratory method rather than applying a selected interpersonal theory of love to the marketing field. The results demonstrate that dimensions of love toward a brand among French consumers align with main dimensions identified in several interpersonal studies (Hatfield, 1988; Rubin, 1970; Sternberg, 1986), which does not seem to be the case for most American findings. This exploratory study suggests several extensions for further research. Firstly, researchers could use this study as a first step to develop a measurement scale of the concept of love toward a

brand, which would enable identifying both brands and product categories that might benefit from such a consumer–brand relationship, as well as consumer groups who are willing or eager to develop love-based relationships. The results of the MCAs indicate that consumers may treat product categories differently in terms of their ability to generate love feelings. A formal study of this phenomenon should help practitioners develop specific marketing programs toward consumer segments open to love relationships. Practitioners as well as researchers could also investigate the reasons underlying the fact that some product categories are more likely than others to enable the building up of love relationships between brands and consumers. Such studies could also give new insights and provide a better understanding of key concepts activated within specific brand communities within which brand–consumer relationships and brand love relationships might be particularly strong. Secondly, a measurement scale will result in a better understanding, both theoretically and empirically, of the love concept in relation to a brand, compared to other constructs widely applied in the consumer behavior or consumer psychology literature and probably linked to love (e.g., attachment, commitment, trust). In particular, future research should distinguish productively between affectionate love and attachment (Fisher, 2006). Thirdly, both academics (Caroll and Ahuvia, 2006; Fournier, 1998; Whang et al., 2004) and practitioners (Roberts, 2004, 2006) emphasize the managerial importance of the feeling of love toward a brand. Therefore, additional research should propose and test a conceptual model to assess the influence of the feeling of love on dependent attitudinal and behavioral variables, such as brand loyalty, resistance to change, or positive word of mouth. Finally, the exploratory nature of this research does not enable clarifying the relationships among the different dimensions of the feeling of love. Which are the most important dimensions for love to be strong? Are these levels of importance stable, or do they vary with categories or brands? Within that vein of interrogations, fruitful investigations should rely on longitudinal surveys in order to delineate specific love trajectories (i.e. are there some love dimensions more fluctuant than others?). In addition, are there minimum levels on these dimensions to achieve the love status? What possible co-occurrences or correlations exist among these dimensions? Could there be a second-order structure? Are there important differences between consumer groups, and what explains these differences? Ultimately, the application of nonlinear models may be interesting, such as those relied on within the catastrophe theory framework, in order to get a finer understanding of relationships between love towards a brand and some possible determinants or consequences such as loyalty. Such questions require further exploration to provide a better understanding of the feeling of love toward brands. Quantitative analyses of the feeling of love toward brands represent a necessary next step. References Aaker JL. Dimensions of brand personality. J Mark 1997;34(3):347–56. Ahuvia AC. I love it! Towards an unifying theory of love across divers love objects. Doctoral dissertation. Northwestern University; 1993.

N. Albert et al. / Journal of Business Research 61 (2008) 1062–1075 Ahuvia AC. Beyond the extended self: love objects and consumer's identity narratives. J Consum Res 2005a;32:171–84 [June]. Ahuvia AC. The love prototype revisited: a qualitative exploration of contemporary folk psychology. Working Paper. University of MichiganDearborn; 2005b. Aron A, Aron EN. Love as the expansion of self: understanding attraction and satisfaction. New York: Hemisphere; 1986. Aron A, Aron EN, Tudor M, Nelson GN. “Close relationships as including other in the self”. J Pers Soc Psychol 1991;60:241–53. Aron A, Aron EN. Love and expansion of the self: the state of the model. Pers Relatsh 1996;3:45–58. Aron A, Westbay L. Dimensions of the prototype of love. J Pers Soc Psychol 1996;70:535–51. Beall AE, Sternberg RJ. The social construction of love. J Soc Pers Relatsh 1995;12:417–38. Borg I, Lingoes JC. Multidimensional similarity structure analysis. New York: Springer-Verlag; 1987. Byrne D, Clore GL, Smeaton G. The attraction hypothesis: do similar attitudes affect anything? J Pers Soc Psycho 1986;51:1167–70. Cappella JN, Palmer MT. Attitude similarity, relational history and attraction: the mediating effects of kinesic and vocal behaviours. Commun Monogr 1990;57:161–83. Caroll BA, Ahuvia AC. Some antecedents and outcomes of brand love. Mark Lett 2006;17:79–89. Chaudhuri A, Holbrook MB. The chain of effects from brand trust and brand affect to brand performance: the role of brand loyalty. J Mark 2001;2:91–3. Deschamps J-C, Carmino L, Neto F. Différences entre les conceptions des relations amoureuses d'etudiants(tes) Brésiliens(nes) et Suisses. Cah Int Psychol Soc 1997;36:11–27. Fehr B. Prototype analysis of the concepts of love and commitment. J Pers Soc Psychol 1988;55:557–79. Fehr B, Russel JA. The concept of love viewed from a prototype perspective. J Pers Soc Psychol 1991;60:425–38. Fisher HE. Pourquoi nous aimions? Paris, France: Ed. Robert Laffont; 2006. Fournier S. Consumers and their brands: developing relationship theory in consumer research. J Consum Res 1998;24:343–73 [March]. Galton F. The measurement of character. Fortn Rev 1984;36:179–85. Garbarino E, Johnson MS. The different roles of satisfaction, trust, and commitment in customer relationships. J Mark 1999;63:70–87 [April]. Hatfield EC. Passionate and companionate love. In: Sternberg RJ, Barnes ML, editors. The psychology of love. New Haven, CT: Yale University Press; 1988. p. 191–217. Hatfield E, Walster E. A new look at love. Lantham, MA: University Press of America; 1978. Hatfield E, Rapson RL. Passionate love: new directions in research. In: Jones WH, Perlman D, editors. Advances in Personal Relationships, 1. Greenwich, CT: JAI Press Inc.; 1987. p. 109–39. Hatfield E, Sprecher S. Men's and women's preferences in marital partners in the United States, Russia, and Japan. J Cross-Cult Psychol 1995;26 (6):729–50. Hendrick C, Hendrick SS. A theory and method of love. J Pers Soc Psychol 1986;50:392–402. Hendrick C, Hendrick SS. Research on love: does it measure up? J Pers So Psychol 1989;56(5):784–94. Hendrick C, Hendrick S. Romantic love. Newbury Park, CA: Sage; 1992. Hendrick S, Hendrick C, Adler NL. Romantic relationship: love, satisfaction and staying together. J Pers Soc Psychol 1988;54(6):980–8. Jacoby J, Chestnut RTW. Brand loyalty: measurement and management. New York: Ronald Press; 1978.

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Available online at www.sciencedirect.com

Journal of Business Research 61 (2008) 1076 – 1082

Gender-related wayfinding time of mall shoppers ☆ Jean-Charles Chebat a,⁎, Claire Gélinas-Chebat b , Karina Therrien a a

b

HEC Montreal, Canada University of Quebec at Montreal, Canada

Received 1 March 2007; received in revised form 1 July 2007; accepted 1 September 2007

Abstract The relative superiority of males over females with respect to wayfinding performance in real life is not clearly established in the literature. The present study aims at clarifying the issue in the specific case of wayfinding in shopping malls environment. An experimental study using actual shoppers in a mall showed that the relationship between gender and time necessary to find a store within a mall is mediated by both shopping values and the use of information sources. Compared to male shoppers, female shoppers were found to be more hedonist and use people as a source of information, which in turn was instrumental in reducing wayfinding time. Crown Copyright © 2007 Published by Elsevier Inc. All rights reserved. Keywords: Wayfinding; Shopping mall; Shoppers; Wayfinding efficiency

1. Gender and wayfinding strategies Which gender is the most time efficient in wayfinding, especially within shopping malls? “Factors [of wayfinding performance] derived from paper-and-pencil tests account only very weakly for performance on large scale spatial tasks” (our emphasis), as pointed out by Montello et al. (1999 p. 517). The present study was undertaken in a mall with actual shoppers in order to test which gender is able to find the way to stores more efficiently time-wise. More specifically, based on the reviewed literature, we test if the difference between male and female shoppers in terms of wayfinding efficiency, if any, can be explained by two potential mediators: information sources and general attitude toward shopping. A tenacious stereotype is that males are more efficient for several reasons. First males have a better knowledge of geographical maps (e.g., Harris, 1981; Ward et al., 1986) and draw better maps (Harrell et al, 2000), which is usually ☆ The authors gratefully acknowledge the financial and logistic help from Ivanhoe-Cambridge Corp. Corresponding author. Chair of Commercial Space and Customer Service Management Holder, HEC-Montreal School of Management, 3000 Côte SteCatherine, Local 4.348, Montreal, Québec, Canada, H3T 2A7. Tel.: +1 514 340 6846. E-mail address: [email protected] (J.-C. Chebat).

attributed to the fact that men are more socialized with maps (Lawton, 1994). Second and consequently, men are found to be more confident in their use of maps and in their wayfinding using maps (Harrell et al., 2000; Lawton and Charleston, 1996; Harris, 1981; Miller and Santoni, 1986; Ward et al., 1986). Conversely, women show a higher level of anxiety (Lawton, 1994) and uncertainty (Lawton and Charleston, 1996) in wayfinding tasks. However, these findings do not say much about the performance of the genders in real-life wayfinding tasks, as discussed below. In experiments in large-scale real-life environments, Waller et al. (1998) found a significant effect of gender in their wayfinding experiment; similarly, Passini et al. (1990), Beaumont et al. (1984), and Lawton and Charleston (1996) found few gender differences in terms of wayfinding skills. In terms of distance estimation, males could prove to be better but the evidence for this is not clear (Evans, 1980). A number of experimental studies related to landmarks and gender showed that women recall more landmarks (Galea and Kimura, 1993), rely more on landmarks (McGuiness and Sparks, 1983; Miller and Santoni, 1986), and refer more to landmarks (Miller and Santoni, 1986), while men are more accurate than women in locating the direction of landmarks (Bryant, 1982; Holding and Holding, 1989), and in placement of buildings on a map (McGuiness and Sparks, 1983).

0148-2963/$ - see front matter. Crown Copyright © 2007 Published by Elsevier Inc. All rights reserved. doi:10.1016/j.jbusres.2007.09.021

J.-C. Chebat et al. / Journal of Business Research 61 (2008) 1076–1082

Some studies about gender and landmarks report no gender differences in the use of landmarks or buildings to assist wayfinders (Harrell et al., 2000; Yeung and Ravage, 1995), or in accuracy of pointing to landmarks along a route (Montello and Pick, 1993; Sadalla and Montello, 1989). Only Kozhevnikov et al. (2005) offered a partial explanation for these confusing findings: “females tend to be object visualizers and males tend to be spatial visualizers” (p. 725), in other words, females use more object properties (such as shape and colors) while males use more spatial properties (such as location and spatial relations). In other words, this distinction between object-vsspatial visualizers could explain why females would be more inclined to use landmarks and men more (physical or cognitive) maps to find their way. This distinction is supported empirically by some studies. For example, Montello et al. (1999) showed that, in a wayfinding experiment on a University campus (as compared to paper and pencil tests of spatial abilities), males are better at estimating metric distances and females at recalling landmarks. In terms of global wayfinding efficiency, Golledge and Stimson (1997) suggest that: there is “no overwhelming evidence at this stage of the consistent dominance by one sex” (p. 546); the differences in spatial abilities of males vs. females are “often mitigated by training, reinforcement, and repeated trials” (p. 546). Montello et al. (1999) attributed the problem to methodological procedures used in previous studies: “ males and females differ on average in their spatial abilities and styles on particular tasks and not only on abstract and artificial spatial tasks that may have little relevance to spatial tasks that may have little relevance to spatial relevance performance in realistic, ecologically valid settings” (p. 529; our emphasis). In other words, the sex-related differences may be real but have to be tested in a real-world environment. Following Montello et al. (1999), we suggest that each gender has developed a relation with specific environments, which reflects their own learning processes. In our study, we focus on actual shopping malls and actual shoppers. 2. Wayfinding in shopping malls One key criticism concerning how shopping malls are managed in North America is this notion of time scarcity (LeHew and Fairhurst, 2000; Wakefield and Baker, 1998). Shopping in malls is perceived as being insufficiently timeefficient, which is seen as a significant factor of the commercial stagnation of malls (Cavanaugh, 1996). Paradoxically, time efficiency was one of the main advantages of shopping in the first malls, due to the short distance between stores located in a mall for the convenience of shoppers. However, the very success of shopping malls has led mall management to increase the size of malls, which in turn reduced the time advantage. Shopping trips, if perceived as excessively long, trigger irritation because of wayfinding difficulties (Passini, 1996). Irritation stemming from wayfinding problems may also reduce

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the amount spent in malls (D'Astous, 2000; Hackett et al., 1993). While shopping is stereotypically a female activity (Buttle, 1992), men and women search shopping information similarly (e.g., Avery, 1996). As sexual roles gradually merged (Darley and Smith, 1995), and as women are almost as numerous as men in the labor market (Roberts and Wortzel, 1979), shopping efficiency is perceived as increasingly important for both genders. This may explain why no gender differences in wayfinding were found in a shopping mall context, even though women are more familiar with the landscape of shopping malls (Dogu and Erkip, 2000). Because the effect of gender on spatial ability can be moderated by training, (Golledge and Stimson, 1997), familiarity with the shopping environment should be taken into account in the study of the relation between gender and wayfinding ability, which we do in the present study. The literature on wayfinding in malls suggests that shopping values could be a mediator to be considered (Titus and Everett, 1995). We review the concept and its potential effects in the next section. 3. Shopping values and wayfinding Titus and Everett (1995) conjectured that wayfinding could be influenced by (utilitarian and hedonist) shopping values, as defined by Babin et al. (1994), that is, utilitarian shoppers are expected to strive to complete shopping tasks in an efficient way, whereas hedonist shoppers are expected to enjoy shopping and take more time shopping. For Titus and Everett (1995), utilitarian shoppers' wayfinding strategies are based on the use of landmarks and/or other persons, while hedonist shoppers' strategies aim at enhancing the enjoyment of the shopping space and sensorial excitement. Similarly, utilitarian shoppers are hypothesized by Titus and Everett (1995) to have specific behaviors, such as moving rapidly, not changing their way, not stopping, and limiting their contact with the environment to persons and things essential to their problem solving. On the opposite, hedonist shoppers are hypothesized to move more slowly, to stop frequently, and to change their routes. Hedonist shoppers enjoy browsing through the stores, which enhances their experiential pleasure of shopping, at the expense of time efficiency. Is gender related to shopping values? Some prominent retailing researchers (Babin et al., 1994; Babin et al., 2001) found that women are more hedonist oriented. Some other studies show that women consider shopping very seriously, not as a “fun” activity, and that they are “professional shoppers” (Laermans, 1993), more involved in their role of shoppers (especially during the Christmas season). Shopping is an imposed obligation for women, proper to females' role and not always felt as a leisure activity (Jansen-Verbeke, 1987). As for men, they see Christmas gift shopping as ‘play’ (Fischer and Arnold, 1990). These findings lead us to consider shopping values as a mediating variable between gender and wayfinding efficiency. In other words, female shoppers could differ from male shoppers in the sense that they enjoy more the shopping activity and/or they are more cognitively alert when shopping. In addition, as

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already reported at the inception of the article, we may also assume that gender-related differences in wayfinding stem from a different relation to the environment, which leads to our research propositions. 4. Research propositions Following the literature reviewed, we assume that the two genders do not use the same wayfinding strategies within shopping centers. While women are hypothesized to explore the environment and rely on landmarks more than men do, men are hypothesized to rely more on their use of maps. Such strategies should mediate the relation between gender and wayfinding time (WFT). Second, as proposed by Titus and Everett (1995), shopping values are also assumed to mediate this relation. In other words, if the two potential mediators (information sources and shopping values) prove to actually mediate the gender → WFT relation, the effects of gender could be masking the effects of these two constructs. We test two hypotheses, each relates to one of the two potential mediators, namely information sources (IS) and shopping values (SV): Hypotheses related to the mediating effects of shopping values H1. Shopping values mediate the relation between gender and wayfinding time. Hypotheses related to the mediating effects of information sources H2. Information sources mediate the relation between gender and wayfinding time. Fig. 1 summarizes the model. 5. Methodology 5.1. Overview Actual shoppers were intercepted in a mall. The numbers of males and females were approximately equal and that shoppers

familiar and unfamiliar with the mall were also equally represented. They were requested to find a store within the mall and were instructed to describe orally on a tape recorder their actions and their thoughts at the very moment when they came to their mind, during the wayfinding process. More precisely, shoppers indicated what they do (e.g., I turn left); why they do what they decide to do (e.g., I read the map to locate myself ). The data collection took place in three subsequent afternoons of the same week (Monday, Tuesday and Wednesday), in order to control for crowding; during the three afternoons crowding was low, which cancels the additional logistic and psychological hurdles to find one's way through a dense crowd, like that of a Friday evening. The mall where the data was collected was a regional mall of average size, the architectural structure of which was neither excessively simple (e.g., linear) nor too intricate. This approach seems more appropriate than the observation of what shoppers do, since simple observations cannot tell why shoppers decide to come back on their way or what information they ask a passer-by. This method is also more appropriate than self-reporting once the whole wayfinding process is over, since self-reports imply rationalization after the fact and loss of memory of certain steps in the process. 5.2. Sample One hundred and fifty six shoppers in a regional mall located in the suburbs of a major Canadian city, were recruited during their visit to the mall. They were offered Can$20 to participate in the study. They were first administered a short questionnaire, described below, related to their gender, familiarity with the mall (frequency of visits) and the questionnaire on shopping values (Babin et al., 1994). In addition, the intercepted shoppers indicated their level of education and occupation. All the shoppers lived in the area of the shopping mall. The interviewers, who were graduate students at the School of the first author, were instructed to recruit four groups of similar size (i.e., N = 40 in each of the four cells): two levels of familiarity with the mall and two genders. Since we are mostly interested in the effects of gender, the effects of familiarity have to be cancelled in further analyses, as explained in the results section. 5.3. Wayfinding task All shoppers started the wayfinding process from the same place where the intercept took place. They were requested to reach a given shop as efficiently as possible. Time at which the shoppers started the wayfinding process was recorded, as well as the time when the shoppers reached their target store. The time recorded varied between 10 and 65 min with an average of 18 min. 5.4. Familiarity with the mall

Fig. 1. The model tested.

The shoppers' familiarity with the mall was measured with a 5-point Likert scale, that is the perceived frequency of visits to this mall (several times a week = 5; never = 1): 84 participants scored 3 or less and were classified as “non familiar” and the other 72 as “familiar” with the mall. Familiarity had a marginal

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Table 1 Means and standard deviations of the variables used in the model Gender Wayfinding time mean and (S.D.)

Not familiar with the Familiar with the shopping mall shopping mall

Hedonist scores

Men 20.21 (9.40) Women 16.93 (4.82) Total 18.39 (7.37)

36 48 84

− 0.41 (0.87) 0.28 (1.03) 0.13 (0.37) 0.34 (0.99) − 0.19 (0.94) 0.034 (0.32) 0.016 (1.00) 0.02 (1.00) 0.08 (0.34)

32 40 72

impact on wayfinding time (F1,157 = 2.02; p = 0.098). Note that neither occupation nor education had significant effects on wayfinding time (respectively F1,157 = 0.20; p = 0.82; F1,157 = 1.33; p= 0.270). 5.5. Shopping values The Babin et al. (1994) “shopping values” scale was slightly modified for this study to reflect the values that shoppers attribute to shopping in general, not to the specific shopping trip: Instead of “this shopping trip was truly a joy,” we used “shopping is truly a joy”; similarly, instead of “I continued to shop not because I had to, but because I wanted to”, “I shop not because I have to, but because I want to”. 5.6. Tasks The shoppers were instructed to find one of the four stores predetermined by the researchers (i.e., a movie theater, a bank, a liquor store and a boutique). Since some stores are easier to find than others (e.g., department stores are easier to find than boutiques), the four stores selected for the wayfinding task were rotated systematically among the shoppers. 5.7. Content analysis of information sources Once all the recordings were fully typed, they were contentanalyzed by the second author, a professional linguist, with a linguistic computer program (SATO), used in a number of previous studies (e.g., Chebat et al., 2003). Two independent graduate linguistics students, trained by and under the supervision of the second author had to build two repertories: what shoppers do and think, and the information sources they use. In the present paper, we focus on the second type of data recorded by the subjects, namely, the information sources they used to find their way. From a linguistic viewpoint, only nouns characterizing the information sources were taken into account (e.g. “I spoke with a salesclerk to ask my way”; “I stopped by a map”; “I remember I passed by this fountain”; “I remember that the store is located close to a fast food ”). Originally, 53 nouns were used to identify the information sources. The two graduate students in linguistics, under the supervision of the second author, were instructed to classify the nouns in a smaller number of categories; some nouns were classified as synonymous or as covering very similar semantic area (e.g., salesclerks and employees; restaurant and fast foods). This allowed us to reduce the nouns used as information sources to 15. For each respondent, we built a vector of 15 cells, corresponding to each of the information sources, the entry of

Utilitarian scores

Cognitive processes

Landmarks People

Maps

1.98 (2.46) 0.482 (1.08) 2.402 (2.77) 1.14 (1.66) 1.470 (1.41) 1.750 (3.05) 1.64 (2.09) 0.958 (1.54) 2.040 (2.94)

which was the frequency used by a given respondent. This process lead us to regrouping the 15 nouns into factors, as described in the next paragraph. 5.8. Factor analyses on information sources and shopping values A factor analysis was performed on the 15 variables of “information sources”; it showed four factors, explaining 74% of the variance. The first factor was related to landmarks (fountain, restaurants), the second to people (employees, passers-by), the third to maps (maps and posters), and the fourth to “internal sources” (memory, instinct and guess). A factor analysis was also performed on the shopping values scale (Babin et al., 1994). It showed the two expected factors explaining 59% of the total variance: the first one was related to the hedonist dimension (37% of the variance), while the second was related to the utilitarian values (22% of the variance). 6. Results The main purpose of the statistical analyses is to verify if “shopping values” and “information sources” mediate the relationship between gender and time. We followed the procedure proposed by Baron and Kenny (1986), for both potential mediators, that is, to assess the degree to which the following relations are significant: i. the relation between gender and time ii. the relation between gender and each of the two mediators (i.e., either “shopping values” or “information sources”) iii. the relation between each of the two mediators and time iv. the relation between gender and time, with each of the two mediators as covariate. In the present study, two variables are candidates for mediation: “shopping values” and “information sources.” For a variable (i.e., “shopping values” or “information sources”) to be considered as a genuine mediator, the first three relations should be significant, while the fourth should not. Note that in all analyses, familiarity was used as a covariate in order to cancel its effects (Table 1). H1 relates to “shopping values” as mediator between gender and wayfinding time. i. relation between gender and time An ANOVA shows that gender affects wayfinding time (WFT) significantly (F1,157 = 5.43; p b 0.02); men spend more time than women (20.21 min-vs-16.93 min).

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ii. relation between gender and “shopping values” A MANOVA shows that gender has significant effects on both shopping values (F2,157 = 15.26; p b 0.001), and on each of the shopping values, that is, hedonist values (F1,157 = 21.92; p b 0.001) and utilitarian values (F1,157 = 8.99; p = 0.003): men score lower on the factor “hedonist values” (− 0.41 vs 0.34) and higher on the factor “utilitarian values” (0.28 vs − 0.19). iii. relation between “shopping values” and wayfinding time A linear regression shows a significant effect of shopping values on WFT (F1,157 = 5.36; p b 01; r = 0.30): only “hedonist values” significantly predicted WFT (beta = − 0.30; p b 0.001), not “utilitarian values” (beta = − 0.06; p = 0.53). iv. the relation between gender and wayfinding time with “shopping values” as covariate. The introduction of “shopping values” as covariates in the ANOVA used above in section “i” makes the effects of gender on wayfinding time nonsignificant (F1,157 = 0.49; p = 0.49). In summary, all test conditions were met rendering “shopping values” a genuine mediator (Baron and Kenny, 1986). H2 relates to “information sources” as mediator between gender and wayfinding time. The testing procedure was the same as above. Since we already know that the relationship between gender and wayfinding time is significant; we have to test only the next three relations. ii. relation between gender and information sources A MANOVA shows that gender affects significantly the use of information sources (F4,157 = 5.16; p = 0.001). Two types of information sources are related to gender: landmarks (F1,157 = 6.06; p = 0.01) and people (F1,157 = 13.08; p b 0.001); men use more landmarks (1.98 vs 1.14) and less people, in particular, salesclerks, other shoppers (0.48 vs 1.47) than women. No significant effects of the other two factors (i.e., “internal sources” and “maps,”) were found (F1,157 b 1.8; p N 0.18). iii. relation between “information sources” and wayfinding time A linear regression shows that the effects of information sources on WFT is significant (F1,157 = 9.07; p b 0.001; r = 0.19); “people” predicted WFT significantly [beta (people) = −0.37; p b 0.001] and “maps” had a marginal effect on WFT [beta (maps) = 0.17; p = 0.09]. Neither “landmarks” (beta = 0.038; p = 0.72) nor “internal sources” (beta = 0.07; p = 0.62) had significant effects. iv. relation between gender and wayfinding time with “information sources” as covariates The introduction of “information source” as covariates in the ANOVA used above in section “i” make the effects of gender on wayfinding time nonsignificant (F1,157 = 0.602; p = 0.44).

In summary, all test conditions were met to consider “information sources” as a genuine mediator (Baron and Kenny, 1986). 7. Discussion The main conclusions are that women are more efficient in wayfinding in shopping malls and that the significant difference in wayfinding time is not directly due to gender. The effects of gender on wayfinding time are mediated by the two characteristics of shoppers' gender: hedonist shopping values, and use of information sources. Female shoppers score higher on hedonist values and use information sources that prove to be reduce wayfinding time, which, in turn reduce wayfinding time in malls. A key element of this demonstration is that, as shown above (section “iv” of both mediators), the direct effects of gender on WFT, which are significant, cease to be significant once each of the two mediators (i.e., hedonist scores and “people” as information source) is entered as covariates. Whenever wayfinding is inefficient time-wise, shopping becomes less enjoyable (e.g., D’Astous, 2000), which triggers a circular process: because male shoppers are less efficient, they are also less hedonists. Should male shoppers be more efficient in terms of WFT (for instance by using other people as information sources), they may enjoy their shopping experience more. While the literature leads us to expect women to use more landmarks, the opposite was found: men were found to use more this information source than women. Similarly, while we expected men to use more maps, no significant difference was found. However, none of these information sources was proven to reduce the wayfinding time; only the use of “people” as information sources, was shown to reduce it. Some of the conjectures proposed by Titus and Everett (1995) [i.e., utilitarian shoppers strive to complete shopping tasks in an efficient way and these shoppers use more people] are not supported by our study. Women, who score higher on hedonist values, also use more people as information sources, and find their way more efficiently. They also hypothesized that utilitarian shoppers use more landmarks; in fact, this is confirmed here; men, who score higher on utilitarian values, also use more landmarks, but that does not impact WFT. The finding that the more hedonist the shoppers the less time they spend in their wayfinding, sheds some light on the welldocumented positive relation between hedonist shoppers and time spent in stores (e.g., Donovan et al., 1994). Hedonist shoppers are not less efficient than utilitarian shoppers; unexpectedly they are more time-efficient. They stay longer in malls because they enjoy the very activity of shopping more intensely. In fact, the hedonist shoppers enjoy shopping all the more since they spend less time in their wayfinding. The relation we found between hedonist shoppers and time efficiency [that contradicts the proposition by Titus and Everett (1995)] is neither surprising nor really new, for two reasons. First, when exploring a mall, hedonist shoppers enjoy their shopping experience, which implies more than a cognitive process. We suggest that the reason why they prove to be more efficient is not solely based on better cognitive processes, but also emotional

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processes. Hedonist shoppers may associate positive emotions with public places. For instance, hedonist shoppers may characterize places as “lovely,” or “the place where I smelled fresh bread,” or “the place where they play rock music of my adolescence,” and so on. In other words, the emotions felt by hedonist shoppers toward the places serve as labels (or bookmarks) of the information filed in long term memory, which facilitates the recognition of places and wayfinding. Second, shoppers called “mall enthusiasts” by Bloch et al. (1994) in their famous study on shopping mall as “habitat” (i.e., those who intrinsically enjoy shopping in malls) were also those who received and processed more information from the mall environment. Mall enthusiasts were also found to perceive malls as a “source of many benefits” (Bloch et al., 1994, p. 34) from which they are more likely to learn the layout. Being time-efficient is a concern for both genders, which impacts all other roles of both genders, including shopping activities. Montello et al. (1999) stressed that wayfinding differences are not inherent to the very nature of each gender. The authors rather insisted on the necessity of “training and education of both sexes to enhance their abilities and compensate for their different modes of acquiring and employing spatial information” (p. 532). It is also our contention that, should men be more used to shopping in malls, should they enjoy this specific shopping activity as women do, should they use other people to find their way through malls, it's likely they would be as time-efficient as women are in wayfinding in malls. 8. Limitations and future research This finding cannot be extended to environments other than malls. In addition, age has not been taken into consideration, which would affect wayfinding efficiency in terms of walking capability and sensitivity to visual and auditory cues. Future studies could be conducted in shopping malls with bigger samples where age could be varied. The fact that respondents were requested to find a specific store puts them in a utilitarian attitude toward the trip to the mall. Future studies should address this methodological bias. In addition, emotions triggered by wayfinding experience should also be taken into account. The pleasure of finding the place searched for, and, conversely, the irritation of not finding it, should impact the identification of shoppers with the place, and in the long run, affect their wayfinding learning. References Avery RJ. Determinants of search for nondurable goods: an empirical assessment of the economics of information theory. J Consum Aff 1996;30(2):390–421. Babin BJ, Darden WR, Griffin M. Work and/or fun: measuring hedonic and utilitarian shopping value. J Consum Res 1994;20(4):644–57. Babin BJ, Boles S, Griffin M. The moderating role of service environment on the customer share–customer commitment relationship.”Dev Mark Sci 2001;24:266–71. Baron RM, Kenny DA. The moderator–mediator variable distinction in social psychological research: conceptual, strategic, and statistical considerations. J Pers Soc Psychol 1986;51(6):1173–82. Beaumont PB, Gray J, Moore GT, Robinson B. Orientation and wayfinding in the Tauranga departmental building: a focused post-occupancy evalua-

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Available online at www.sciencedirect.com

Journal of Business Research 61 (2008) 1083 – 1090

Effectiveness of brand placement: New insights about viewers Jean-Marc Lehu a,⁎, Etienne Bressoud b a

Paris 1 Panthéon-Sorbonne University, CEREM, 17 rue de la Sorbonne 75005 Paris, France b European Business School Paris, IREBS, 37-39 boulevard Murat 75016 Paris, France Received 1 March 2007; received in revised form 1 July 2007; accepted 1 September 2007

Abstract Since traditional media have become saturated, the technique of product placement has been attracting growing interest. This research explores new insights concerning viewers' reactions during a second viewing of a movie. A sample of 3532 French viewers of DVDs has been used to link the way the movie was chosen, viewed and appreciated (or not) with a spontaneous brand placement recall, the day after the film was watched at home. Results make a contribution to strengthening professionals' interest in the technique, and to adding to academic knowledge of the topic. A first viewing of the movie at the cinema improves brand placement recall, as does watching the movie at home on a large home cinema screen. Such an improvement also occurs when a DVD movie is chosen either because of the movie director or when the viewer likes the movie. © 2007 Elsevier Inc. All rights reserved. Keywords: Consumer; Product placement; Brand placement; Movie; Film; Branded-entertainment; Spontaneous day-after recall

1. Introduction Product placements (a product and/or a brand intentionally placed in a cultural medium) are mushrooming in movies nowadays. In 2007 alone, the fact that in the movie Sleuth, Bvlgari jewels are a key element of the plot, that MSNBC is the favored news channel in The Invasion, that the Porsche car brand is used as a reference in Transformers, that the New York Post is the unavoidable newspaper in the movie The Brave One, and that a Sony video camera is used in Vantage Point, a Columbia picture (subsidiary of the Sony Group), is not coincidental at all. Those products are part of a so-called product placement deal. Product placement in movies has become a communication technique which is used more than ever by advertisers (Karrh et al., 2003; PQ Media, 2007). A recent Association of National Advertisers (ANA) survey indicates that 63% of the American advertisers who responded already integrated product placement actions in their communication plan, 52% specifying that financing for those actions ⁎ Corresponding author. Tel.: +33 169 030 680. E-mail addresses: [email protected] (J.-M. Lehu), [email protected] (E. Bressoud). 0148-2963/$ - see front matter © 2007 Elsevier Inc. All rights reserved. doi:10.1016/j.jbusres.2007.09.015

had been transferred from their TV advertising budget (Consoli, 2005). A great deal of research is already devoted to product placement in all its forms (Nelson, 2002; La Ferle and Edwards, 2006; Gupta and Gould, 2007) and more specifically to product placement in movies (Karrh, 1998). This paper strives to present new insights into the viewer's contact with the movie and the brand placement. This approach originally focuses on the impact of brand placement on the potential second viewing stage (Brée, 1996; Bressoud and Lehu, 2007a), by using an innovative study of DVD viewers instead of the usual movie theatre viewers. The terms product placement and brand placement are sometimes used interchangeably. In this paper, new findings are presented to advertisers about the links existing between the viewers' exposure conditions and the impact of brand placements. 2. Brand placement in movies Since the first brand placements appeared in novels two centuries ago, they have developed with the movie industry (Turner, 2004; Newell and Salmon, 2004). Product placement is a crossbreed technique, that combines different communication techniques into one, taking place in a cultural and/or entertainment

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environment. Placing a product consists of putting a product and/or a brand into a movie scene where it can be seen and/or its name heard. The placement can either be paid for by the advertiser or be part of a barter deal concerning products and/or services such as logistics facilities (Karrh, 1998). Ford paid for an Aston Martin car to be featured once again in the James Bond films from Die Another Day (2002) onwards, but BMW at no charge supplied 32 Minis with specific features for The Italian Job (2003). Mainly since the end of the 1980s, several papers contribute to a better understanding of this communication technique which is dubbed hybrid by Balasubramanian (1994) since brand placement puts an ad message in entertainment medium. Its positive effect on attitude (Fontaine, 2005; Redondo, 2006) and especially its potential impact on brand recall (Brennan et al., 1999; d'Astous and Chartier, 2000) represent the main core of the research knowledge. 2.1. The reasons for product placement growth Confronted with the fragmentation of media and their audiences on the one hand (Deloitte, 2005) and with the rise of electronic video devices allowing viewers to skip commercials (O'Neill and Barrett, 2004) on the other, advertisers are increasingly seeking to re-establish the link between products and their consumers. As brand placement in movies seems to be well accepted (O'Reilly et al., 2005), sometimes less expensive than a 30-second TV spot and also more effective (Jaffe, 2005), this communication technique is becoming more frequently used. Ways of placing the brand may differ, but the main purpose of obtaining brand recall and improving brand image remains (Lehu, 2007). That is why in 2006, for instance, Heineken beer was generously drunk in Madea's Family Reunion, why Chief Inspector Clouseau drove a Smart car in The Pink Panther and why Dole bananas were eagerly eaten in Curious George. Movies are not the only medium used for brand or product placement. Some can be found in television series or shows, theatre plays, songs, videogames, novels… (Kretchmer, 2004; Moser et al., 2004). The primary reason remains the same: generating complementary income for the author, the medium or the production on the one hand, while offering an opportunity of branded entertainment to the advertiser (Russell and Belch, 2005). Car makers were among the first to use the technique because of the potentially very large audience for a low cost (Parrish, 1976). Moreover the same movie can now be seen in theatres, on DVD, cable/satellite TV, syndication and reruns. Besides, building a fake car would be too costly for a production and somehow could appear too obvious to the audience (Moser et al., 2004). 2.2. Modalities and effectiveness of a product placement Research into product placement usually focuses on effectiveness or spectators' acceptance of this hybrid technique. Nevertheless, most research in this field explains and gauges effectiveness by the way the placement is made, meaning that most of the results show how the characteristics of the brand placement affect its effectiveness (effects from the placement).

Balasubramanian et al. (2006) identify several measures of effectiveness: brand typicality/incidence, placement recognition, brand salience, placement recall, brand portrayal rating, identification with brand/imitation, brand attitude, purchase intention, brand choice, and brand usage behavior. Three placement modalities are usually distinguished: prominence, audiovisual and plot insertion. Prominent placements occur when the product is made highly visible by the virtue of the size and/or position on the screen or its centrality to the action in the scene (Gupta and Lord, 1998). The audiovisual characteristic refers to the appearance of the brand on the screen and/or to the brand being mentioned in a dialogue (Russell, 2002). Finally, plot insertion refers to the degree to which the brand is integrated into the story itself (Russell, 1998). Such research contributes to a better understanding of product placement effectiveness (Vollmers and Mizerski, 1994; Russell, 2002; Karrh et al., 2003; Bressoud and Lehu, 2007b), and more specifically brand communication effectiveness. Several researchers have worked on placement effectiveness, and still do, either in movie theatres (Ong and Meri, 1994) or in TV program, including series (Stern and Russell, 2004). However, even if they recognized that a movie placement has a first life in theatres and a second life in the home (Vollmers and Mizerski 1994), little research has focused on this topic (Brée, 1996). Research into product placement concentrates on placement conditions which can be partly controlled by the advertiser. 2.3. Research objective Because the link between a spectator's conditions of exposure and brand placement effectiveness cannot be controlled, less research focuses on this relationship. But a spectator's attitude influences such effectiveness (Johnstone and Dodd, 2000; Fontaine, 2002), and the advertiser could have chosen the movie on the basis of the attitude the story was supposed to generate. This primary analysis leads us to one goal: exploring the influence of the spectator's attitude on the effectiveness of a second life brand placement in a film on DVD watched in the home. This goal is achieved by explaining the effectiveness of the brand placement in terms of the spectator's attitude while watching the movie during this second viewing; the effectiveness is analyzed using an experiment with DVD viewers. 3. Hypotheses The extent of spontaneous day-after recall (SDAR) in terms of number of brand placements seen on screen and remembered is used in this research as the measure of brand placement effectiveness. In determining this, the role of the consumer becomes pregnant, discussing how many brands a consumer should remember, given the conditions pertaining when he or she was exposed to the movie. The advertiser's objective is obviously to make sure that the consumer recalls the specific brand and that he or she does so regardless of the modalities of the brand placement.

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Four hypotheses have been formulated to link brand placement and the consumer who has been exposed to this communication technique. The main innovation in this research is to focus on the second wave of potential exposure—DVD as opposed to the cinema. The first two hypotheses focus on this aspect, before and during the exposure to the movie. The last two hypotheses concentrate on the spectator's attitude towards the movie before and after viewing the movie in which brands are placed. 3.1. Second life of the placement Among the respondents, some may have seen the movie previously, in cinemas. Johnstone and Dodd (2000) first test the hypothesis that SDAR might be higher if viewers were watching the movie for the second time. Unfortunately, they conclude that prior exposure has too little impact upon brand salience level to support this hypothesis. Their hypothesis is tested on a sample of 53 viewers. The present research employs a sample of 3532 viewers. A brand placement has several lives (Brée, 1996) which interact through the many viewings of the movie. Consequently: Hypothesis 1a. The extent of brand placement SDAR on DVD viewing is favorably influenced by a first viewing of the movie at the cinema. Consistent with this first hypothesis that links TVand theater, and the wish to focus on the TV second viewing, the difference of size of a TV screen, smaller than that of a theatre screen, must be considered. Two of the three modalities of product placement, plot integration and audiovisual remain the same whether the movie is shown on a theatre screen or on a TV screen. However, the third modality, prominence, may be drastically changed, given the difference in absolute screen size. Depending on the size of the screen, the product placement may appear less prominent on TV than on a cinema screen. Of course, the relative size of the placement in the movie scene always remains proportionally the same. In a cinema all the spectators are seeing the movie on a large screen, but this is not the case when it is viewed at home. However, pre-tests informed us that a certain number of viewers use video widescreen projection instead of a traditional TV set. This is not a problem if the size of the placement has no impact on its recall. Nevertheless, several researchers insist on the role of placement prominence (Gupta and Lord, 1998; Brennan et al., 1999; d'Astous and Chartier, 2000). They demonstrate that the more prominent the placement, the greater the impact. Thus the size of the placement in relation to the size of the screen – which is part of the placement prominence definition – influences the placement recall. This led us to question whether the absolute size of the placement could play the same role: that is, whether the larger the screen on which the respondents have been watching the movie, and thus the bigger the brand placement's appearance, would, via this prominence, result in better recognition and recall. Consequently: Hypothesis 1b. Watching the movie at home, on a large home cinema screen, improves the extent of brand placement SDAR.

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3.2. Spectator's attitude towards the movie The two following hypotheses concern the choice of the movie and its appreciation. Some movie viewers choose their movie (in movie theatres or on DVD) because of the film's director (Ainslie et al., 2003). Those movie fans may be more interested than the average in the direction, the set and/or the acting, their supposedly higher attention could lead to a greater degree of SDAR for brand placements. The purpose of this hypothesis is not to analyze the impact of the director's contingent fame on the SDAR. All the selected movies could be considered as successful in their domestic market, but the fame of the director was obviously very different from one film to another. So the goal is just to identify the possible impact of the movie director, whoever he or she was. Based on a direct effect due to vigilance: Hypothesis 2a. Choosing a DVD movie because of the director improves the extent of brand placement SDAR. Fontaine (2002) shows that appreciation of a movie has a positive impact on attitude change. This result is still accurate for recall and then, for a viewer who has enjoyed the movie, details might be better perceived and then be better recalled. This hypothesis is also inspired by Johnstone and Dodd's work (2000) stressing the fact that placements could increase brand salience, and particularly so if the audience liked the movie. Consequently: Hypothesis 2b. The more the DVD viewers appreciate the movie, the more they spontaneously recall placed brands. This set of hypotheses is summarized in Fig. 1. 4. Research design This section presents the original method adopted of collecting data following a second stage viewing of a movie and the methodology used to test the four hypotheses. 4.1. Data collection The purpose of this research is to innovate by using a large, convenient sample of video viewers questioned the day after watching a movie on DVD, when leaving one of the three French video rental shops chosen for the study. The intention is to collect answers from single respondents only. This means that the DVD viewers are each interviewed about one film only. The final sample includes 3532 video viewers questioned about one of the following 11 American movies: Men in Black II, Minority Report, Analyze That, Banger Sisters, Fashion Victim, Austin Powers in Goldmember, Johnny English, Intolerable Cruelty, Mr. Deed, Hardball and Paycheck. These movies were selected for the research because they were newly released DVDs (meaning heavy rentals during the data collection process), because they were successful (meaning many copies

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Fig. 1. The research model.

were available at the time, facilitating the data collection) and essentially because the placements were easily and clearly recognizable. This research covers a period from 2003 to 2005 partly because the decision to choose real motion pictures meant that they had to be selected carefully to ensure their maximal usefulness. All the brand placements identified and used in the research were strictly isolated, meaning that the link between an SDAR and a specific placement is exclusive, because each brand placement occurs just once in the movie considered. The movies have not been modified in order to control brand placements. This point was crucial to ensure that, during the interview with the respondent, questions were referring to the same brand placement. Furthermore, American movies represented 55% of the 2003 French DVD market by volume, and 69% by value (CNC, 2005). 4.2. Measurements The SDAR of each placement was added to calculate the extent of SDAR per movie for one respondent, that is the dependent variable. The previous watching of the movie in a cinema was measured by a dichotomous question. Respondents were asked whether they watched the movie on a TV or on a large home cinema screen. They were also questioned about the reasons for their DVD choice, which were considered as “director: yes or no”. Finally, appreciation of the movie was evaluated on a 0 to 20 scale (0 meaning a total dislike and 20 an absolute liking). The data collection process took place from January 2003 to February 2005 focusing on the selected just released DVDs. The questionnaire was systematically submitted to every person renting one of the DVDs employed in the research. Every respondent freely chose the movie he or she wanted to watch. Owing to the small size of the video clubs, their proximity and the appeal of the research subject, only six individuals refused to answer the questionnaire. 4.3. Methodology Since the four hypotheses are not independent, all of them have been tested in the same model rather than individually. Hypotheses are validated using an ANCOVA, which allows us to study the simultaneous impact of each independent variable

on the dependent variable. Independent variables are mentioned in each of the four hypotheses presented above. The dependent variable is the number of brands recalled by the respondent (SDAR) in one movie. A hypothesis is validated when the relationship between the studied variable and the dependent variable is significant, that is p-value is less than 5%, and produces the expected mean of the value. Because the number of placements varies from one movie to another (indeed from 4 to 22 in the movies considered), the total number of brand placements in the movie has been included in the model as a control variable. 5. Results and discussion Of the respondents questioned, 34% noticed and, the following day, recalled at least one brand placement in the movie they watched. The size of the sample, 3532 DVD viewers, appears sufficiently large compared with the number of respondents surveyed in the reviewed research in this field, from 62 (Sabherwal et al., 1994) to 378 (Fontaine, 2002), to allow us to diversify spectators, movies and placement modalities. This seemed necessary partly to compensate for the constraints arising from the fact that, when using real movies rather than films created especially for the research or simply excerpts, researchers do not have full control of the placement modalities. Table 1 Model parameters of the ANCOVA Source

Value

Standard error

Intercept Brands_in_movie Evaluation_Rank Projection—TV Projection— HomeCinema Choice_Director—No Choice_Director—Yes Shown_Cinema—No Shown_Cinema—Yes

0.13 0.00 0.02 0.00 0.86

0.07 0.00 0.01 0.00 0.05

0.00 0.83 0.00 0.85

0.00 0.06 0.00 0.05

Dependent variable: Number of SDAR.

t

PrN|t|

Lower bound (95%)

Upper bound (95%)

2.00 0.15 3.77

0.05 0.88 0.01

0.00 −0.01 0.01

0.26 0.01 0.03

17.39

b0.01

0.76

0.96

13.86

b0.01

0.71

0.95

15.64

b0.01

0.74

0.96

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First of all, according to the ANCOVA results (see Table 1), the control variable – that is the total number of brand placements in the movie – does not explain the degree of SDAR (probability associated is 0.88), which means that a profusion of brand placements does not automatically increase the number of brands recalled. 5.1. Extended time potential for product placement Because of the specific characteristics of DVD viewers, this research took place during a potential second exposure to product placements. Validating Hypothesis 1a (“Shown_Cinema—Yes” parameter N 0; p b 0.01) means that the respondents who have previously seen the movie in a cinema show more SDAR than respondents who have seen the movie for the first time on DVD. On the one hand, this analysis shows that product recall is stronger among viewers watching the movie on DVD a few months after viewing this same movie in cinemas. On the other hand, because some 15% of the respondents (representing 522 viewers) rented a DVD even after having seen the film in cinemas the previous year, this result supports the product placement professionals' view as well as the academic research which argues that the potential total audience could be far bigger than the one calculated from cinema tickets alone (Brée, 1996). Of the sample 17% saw the movie on a large screen (home cinema). Since the extent of SDAR was significantly greater among these 587 respondents, Hypothesis 1b is validated (“Projection—HomeCine” parameter N 0; p b 0.01). Indeed, the large dimensions of the screen allow the brand placement to appear significantly greater in size, that is more prominent, and hence to be more effective (Brennan et al., 1999; d'Astous and Chartier, 2000). Considering only the size of the placement, independent of its duration, placements seen for the first time at the movie theatre might be more effective than placements seen for the first time on a regular TV screen. 5.2. Benefits from spectators' positive attitude The findings relating to choice of a DVD because of the movie's director support Hypothesis 2a (“Choice_Director— Yes” parameter N 0; p b 0.01). Logically, a movie fan who prefers a specific director is more alert to certain details, and thus to various brand placements. Nevertheless, the 10.4% of respondents who chose their DVD for this reason were knowledgeable about movie directing. They were attracted by the director's name, leading to a direct effect. For advertisers, these results therefore invite them to favor well-known and accomplished directors for their branded entertainment deal. This partly explains why the $25 million global product placement deal for Steven Spielberg's Minority Report appears quite suitable and logical (Lehu, 2005). Hypothesis 2b, about the evaluation of the movie by the respondents, is validated (“Evaluation_Rank” parameter N 0; p b 0.001). Here, also, such a validation means that the more the viewers liked the movie they watched, the better they recalled the brand placements. The validation of this hypothesis leads us

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to conclude that a positive environment influences the degree of SDAR for brand placements. Thus, not only are advertisers invited to select the type of movie in which to place their products and brands, bearing in mind their intended target audience, but they are also called upon to evaluate the chances of getting a good movie at the end. Some might hesitate when validating Hypothesis 2b about the liking of the movies, as the success or failure of a movie can rarely be predicted (Bressoud, 2007). Even if its components (theme, story, director, editor, actors…) seem to be a high quality combination during preproduction, numerous movies are ultimately what professionals call a bomb, becoming a real box-office failure. 6. Main managerial implications These results can contribute to reinforcing advertisers' favorable attitudes towards brand placement as a rather profitable technique (Lubbers and Adams, 2004), considering its global impact as well as the fact that the placement efficiency increases with the second viewing, namely, in this research, watching the movie on DVD. In addition, in France, home cinema equipment seems to be a consumer favorite, notably since the number of DVD players in French homes grew by 28.3% between 2002 and 2003, and 26% between 2003 and 2004 (Médiamétrie, 2005). This is also an increasing trend in developed countries (Schimetits, 2005), enabling viewers to enjoy films in the comfort of their own homes. When viewers watch their movies on bigger screens at home, the likelihood of noticing and recalling the placements during the second viewing also increases. This finding can also stimulate advertisers to consider a placement in a movie, even after the release in movie theatres. If domestic conditions are improving and if viewers are more and more addicted to home cinema, the growing possibilities of digitally inserting placement for DVD releases and TV showing can attract their attention (Brown, 2003; Moser et al., 2004). A director's reputation can influence the consumers' evaluation, especially if the movie critics are positive (d'Astous and Touil, 1999). As respondents attracted by a famous director's name when choosing their movie presented more SDAR, the present research invites advertisers to favor famous directors who usually team up with a famous cast. This partly explains why, for instance, 28 different brand names appeared in Steven Spielberg's War of the Worlds (2005) with Tom Cruise and Dakota Fanning, no fewer than 41 advertisers had their brands shown in Sydney Pollack's The Interpreter (2005) with Nicole Kidman and Sean Penn, and as many as 50 of them appeared on screen in Martin Scorsese's The Departed (2006) with Leonardo DiCaprio, Matt Damon and Jack Nicholson among other stars. This can spell bad news for unknown directors or for low-budget movies in general. Nevertheless, although a director's appeal is already known by advertisers when choosing the movie in which they could make placements, the success of the movie will remain uncertain. But if large multinational advertisers are no longer interested or willing to take risks, this can offer a real chance for smaller brands. Barn discerned that countless Bollywood movies also

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generate valuable opportunities for product placement (Barn, 2005). 7. Limits and further possible research The external validity of this research remains naturally limited. Spectators solicited for the research have not been differentiated according to their possible personal characteristics. Even if a perception difference occurs from one gender to another (Schmoll et al., 2006) and, that under certain circumstances, children respond specifically to product placement (Auty and Lewis, 2004). Moreover, this research was conducted in France, and previous research about product placement in movies teach us that disparity can occur when comparing results from different countries, (Gould et al., 2000; McKechnie and Zhou, 2003; Devanathan et al, 2003). Furthermore, choosing genuine movies as the material for the research offers greater realism in the study, because respondents can supply us with more natural answers. Unfortunately, that choice also implies a natural structural limit: the lack of control over the material used, which means that not every movie can be used in such an experiment. The appearance of the product and/or the brand cannot be modified because the shooting is of course already complete. That's why the movies used for this research were very carefully chosen to present clear and indisputable brand placements. Nevertheless, the sample of respondents is large compared with those usually employed. That is why the results, obtained through the use of real movies, are strong, in partial compensation for the limits implied by reduced control. Moreover, working with genuine full-length movies and natural exposure conditions opens a new perspective of research in this field. The liking of the movies has no predictive value because the success of a movie can never be foreseen. Nevertheless, the validation of Hypothesis 2b appears very interesting given the rise of digitally inserted product and brand placements. Some placements can now be elaborated, replaced or even erased after the movie has been shot (Brown, 2003; Sivic and Zisserman, 2004). In the near future, this could lead to a more systematic use of previews to analyze the relevance of integrating a brand or otherwise; not right from the outset but after watching the final edited motion picture. This could then allow some sort of pre-testing with elaborate concrete material, the kind traditional advertising already offers. Extending this research to a greater number of movies, to different countries and to the next stages of viewing (television programming, for instance) would be interesting in order to validate the correlation between better placement recall and the number of viewings. A further contribution could be made by explaining brand placement recall according to the individual characteristics validated in this research and to brand placement characteristics already found to be relevant. 8. Conclusion The marketing communications environment is increasingly using practices borrowed from the entertainment business, to try

to lure more complex and more marketing-aware targets towards an experiential consumption (Hackley and Tiwsakul, 2006). Recommending that advertisers consider as much as possible the viewer's characteristics in order to conceive their product and/or brand placement operations may sound technically difficult at first sight. But the consumer's identity and specific characteristics are becoming increasingly known, recorded and used. No doubt that, in a near future, producers and advertisers will be able to adapt the placements to the target, especially when the movie is watched on DVD. An interaction already occurs. The DVD main menu already offers the viewer a choice of version (short, long, director's cut…), type of screen (pan and scan or widescreen), language, subtitles… Advertisers sometimes request adaptations relating to areas where the movie is running in cinemas. Examples include Pepsico changing a Dr Pepper placement in Spider-Man 2 (2004) to Mirinda (another soda) in areas where the latter was much better known than Dr Pepper (Lehu, 2007). Considering their real communication potential, product placement and brand placement in movies have become indisputably attractive techniques of branded entertainment. The deeper the research delves into its impact and its modalities of usage, the more product and brand placement is revealed as a sophisticated communication technique. This crossbred technique has been increasingly and legitimately appreciated by movie producers, communication consultants and of course advertisers looking to solve problems of media and audience fragmentation through new efficient ways of contacting and seducing their potential consumers. The new insights offered by this research will confirm the value of the technique for advertisers, as they can obviously count on repeated product exposure with a heightened impact as multiple opportunities to see the movie are offered to the consumer. Appendix A. Table of statistical results Summary statistics Variable

Obs.

Minimum Maximum Mean Standard deviation

Number_SDAR 3532 0 Brands_in_movie 3532 4 Evaluation_Rank 3532 0

8 22 20

0.7 12.4 12.1

1.22 5.81 4.04

Variable

Categories

Frequencies

%

Projection

TV HomeCinema No Yes No Yes

2945 587 3166 366 3010 522

83.38 16.62 89.64 10.36 85.22 14.78

Choice_Director Shown_Cinema

Goodness of fit statistics Observations Sum of weights DF R2 Adjusted R2

3532 3532 3526 0.24 0.24

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Analysis of variance Source

DF

Sum of squares

Mean squares

F

Pr N F

Model Error Corrected total

5 3526 3531

1261.8 4009 5270.9

252.4 1.1

221.9

b0.01

Standardized coefficients Source

Value Standard error t

Brands_in_movie Evaluation_Rank Projection—TV Projection— HomeCinema Choice_Director—No Choice_Director—Yes Shown_Cinema—No Shown_Cinema—Yes

0.01 0.06 0.00 0.26

0.01 0.01 0.00 0.01

0.00 0.21 0.00 0.25

0.00 0.01 0.00 0.02

0.15 3.77

Pr N |t| Lower Upper bound bound (95%) (95%) 0.88 −0.02 0.04 0.01 0.03 0.09

17.39 b0.01

0.23 0.29

13.86 b0.01

0.18 0.24

15.64 b0.01

0.22 0.28

Analyzed with XLSTAT 2007.

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Available online at www.sciencedirect.com

Journal of Business Research 61 (2008) 1091 – 1097

Effect of self-congruity with sponsorship on brand loyalty ☆ M. Joseph Sirgy a,⁎, Dong-Jin Lee b , J.S. Johar c , John Tidwell d a

Department of Marketing, Pamplin College of Business, Virginia Polytechnic Institute & State University, Blacksburg, Virginia 24061-0236, USA b Yonsei University, Republic of Korea c California State University-San Bernandino, USA d Resources-V, USA Received 1 March 2007; received in revised form 1 July 2007; accepted 1 September 2007

Abstract The purpose of the paper is to extend self-image congruence research into the corporate sponsorship literature in marketing communications. We do this by developing a conceptual model showing how self-congruity with a sponsorship event affects brand loyalty. The model posits that self-congruity with a sponsorship event has a positive influence on brand loyalty, especially under two conditions: (1) when customers are aware of the firm sponsoring the event, and (2) when customers are involved with the event. The model was tested using data collected from five different surveys (total N = 1588) involving Nextel mobile communications services (brand) in relation to NASCAR Nextel Cup Series (the sponsorship event). The results provide some degree of support for the model. © 2007 Elsevier Inc. All rights reserved. Keywords: Self-congruity; Self-image congruence; Sponsorship

1. Introduction With the diversification of consumer needs, marketers increasingly use sponsorship for their marketing activities. Generally, corporate sponsorship can be defined as a firm's provision of assistance, either financial or in kind, to an activity (e.g., sport, musical event, festival, or arts) for achieving commercial objectives (Meenaghan, 1991). Recently, there has been rapid increase in sponsorship marketing as marketers try to enhance their brand image and increase brand loyalty by sponsoring various cultural and sports events (Cornwell and Maignan, 1998). According to the Performance Research 2001/ IEG Study Highlights What Sponsors Want (2001), sponsors indicated that the number one objective for their sponsorships is increasing brand loyalty. The research reported here deals with self-image congruence and makes a contribution to self-image congruence research in ☆ The authors gratefully acknowledge the contribution of NEXTEL Inc. in providing us with the data used in this paper. ⁎ Corresponding author. Tel.: +1 540 231 5110; fax: +1 540 231 3076. E-mail addresses: [email protected] (M.J. Sirgy), [email protected] (D.-J. Lee), [email protected] (J.S. Johar), [email protected] (J. Tidwell).

0148-2963/$ - see front matter © 2007 Elsevier Inc. All rights reserved. doi:10.1016/j.jbusres.2007.09.022

consumer behavior by extending this concept into the sponsorship arena in marketing communications. Self-image congruence refers to the match between consumers' self-concept (actual self, ideal self, etc.) and the user image of a given product, store, sponsorship event, etc. “Self-congruity” is commonly used to mean self-image congruence. We will use “selfcongruity” throughout the paper. Consumers purchase products not only for the utilitarian benefits but also for self-expressive benefits (e.g., Park et al., 1986). The motivation to express their own self is often the driving force that prompts consumers to purchase goods and services (e.g., Sirgy, 1982). Research on self-image congruence has shown that self-congruity with a product or store (match between brand user image and consumer's actual self-image) has a positive influence on a variety of consumer behaviors such as brand attitude, brand preference, purchase motivation, brand satisfaction, and brand loyalty (for literature reviews, see Bauer et al., 2006; Claiborne and Sirgy, 1990; Sirgy, 1982, 1985; Sirgy et al., 2000; Sirgy and Su, 2000). Little has been done so far on how self-congruity with a sponsorship event affects consumer behavior. This paper seeks to establish the conceptual link between self-congruity with a sponsorship event and brand loyalty. Specifically, we make the conceptual argument that

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self-congruity with a sponsorship event contributes significantly to brand loyalty, especially under two conditions: (1) when brand customers are aware that the firm is sponsoring the event, and (2) when brand customers are involved in that event. We then report data collected from five surveys to test these hypotheses. From a managerial point of view, our research addresses the important question that many marketers raise: Should marketers invest resources in developing marketing communications campaigns designed to increase their customers' involvement with the sponsorship event and heighten their awareness that the firm is sponsoring the event? Our study provides an answer to these managerial questions. 2. Conceptual development, model, and hypotheses Our conceptual model is graphically shown in Fig. 1. The model posits that self-congruity with sponsorship events contributes to brand loyalty, and this relationship is moderated by two factors: customer awareness (awareness that the firm is sponsoring the event) and customer involvement (involvement in the sponsorship event). In other words, customers of a particular product who can identify with the people attending the sponsorship event are likely to feel more loyal toward the brand, especially when they are emotionally involved with the sponsorship event and aware that the firm is sponsoring the event. According to self-congruity theory (Sirgy, 1986), people select to purchase and use goods and services that have a user image consistent with their own self-image. Doing so allows consumers to reinforce their own personal identity, their own view of themselves (i.e., their self-concept). By holding positive attitudes toward and purchasing brands perceived to be similar to their self-concept consumers achieve “self-consistency” (cf. Aaker, 1997; Graeff, 1996; Grubb and Grathwohl, 1967). In other words, people are motivated to hold a set of beliefs about themselves (a self-concept) and act in ways (e.g., purchase and use goods and services) to reinforce their self-concepts. Behaviors and events that result in self-perceptions inconsistent with one's self-concept cause dissonance—a state of mental stress that motivates people to restore consonance. This motivational tendency has been coined as the need for self-

Fig. 1. A model linking self-congruity with sponsorship and brand loyalty.

consistency (Epstein, 1980). The need for self-consistency is a self-concept motive that motivates people to behave in ways consistent with how they see themselves—consistent with their actual self. People have beliefs about their own identities, values, lifestyles, preferences, and habits. Once their “selftheories” (meta-beliefs) are established, they become highly motivated to protect them. Major threats to their self-theories account for mental breakdown and psychosis (Epstein, 1980). In the same vein, consumers' need for self-consistency motivates purchase behavior and brand loyalty. Consider the example of purchasing clothes. Most people purchase clothing outfits that fit their actual self-image, irrespective of whether these self-images reflect their ideal self. Consumers who view themselves as sloppy looking are likely to buy clothes (and repeatedly do so) that reinforce themselves as sloppy looking, even though they may not like themselves as sloppy looking (Ericksen and Sirgy, 1989, 1992). Much research in consumer behavior has demonstrated that actual self-congruity (match between consumer's actual selfimage and the user image associated with a particular good, service, or store) is positively related to consumer behavior constructs such as brand attitude, brand preference, brand choice, purchase motivation, purchase intention, brand purchase, brand satisfaction, and brand loyalty (for literature reviews of this research in relation to different goods, services, and stores see Bauer et al., 2006; Claiborne and Sirgy, 1990; Sirgy, 1982, 1985; Sirgy et al., 2000; Sirgy and Su, 2000). 2.1. The effect of self-congruity with sponsored events on brand loyalty Self-congruity with a sponsorship event refers to the degree to which consumers think the image of the sponsored event matches with their own self-image. That is, self-congruity with sponsorship reflects the degree of congruity between the consumer's self-image and the image of the event. Self-congruity with a sponsorship event differs from self-congruity with the brand in that the latter reflects the fit between consumer selfimage and the firm or brand image. Brand loyalty is determined by many factors, corporate sponsorship is one of those factors (e.g., Bhattacharya and Sen, 2003; Javalgi et al., 1994; Madrigal, 2001). How does this come about? We propose that the relationship between corporate sponsorship and brand loyalty is mediated by a self-congruity process. That is, customers of a particular brand are likely to develop feelings of brand loyalty when they recognize that the firm is sponsoring an event that they can identify with (i.e., experience self-congruity with that event). Self-congruity with the sponsorship event helps create a favorable attitude toward that event, and these positive feelings spill over to the firm sponsoring the event. Such feelings are more easily transferred to the firm that the consumer recognizes as having transacted with (i.e., being a customer of that firm) than other firms (Gwinner, 1997; Gwinner and Eaton, 1999). Functional attitude theory (e.g., Ashforth and Mael, 1989; Shavitt, 1990; Shavitt et al., 1992) posits that a distinct function of an attitude is to symbolize and express a person's self-image

M.J. Sirgy et al. / Journal of Business Research 61 (2008) 1091–1097

through identification with salient reference groups. People tend to have favorable attitudes toward issues that are congruent with salient aspects of their own positive identities and also support the institutions that embody those identities. That is, there is transference of affect such that identification with a sports team is positively related to attitudes toward a corporate sponsor of that property. Based on the discussion, we propose the following hypothesis: H1. A customer's self-congruity with a sponsored event has a positive influence on his or her loyalty to the firm (brand) sponsoring the event (see Fig. 1). 2.2. The moderating role of customer involvement Madrigal (2001) has argued effectively that an important factor impacting sponsor loyalty is passion. Passion means constant involvement and interest. Sponsors make attempts to connect with that passion—identify emotional linkages and attach themselves to that. When customers are involved with the sponsored event, they are more likely to spend more time and energy for the event. Customers who are highly involved with the sponsored event are likely to actively watch the event (e.g., a sports game), purchase event related products, and closely follow scores. When customers do not have a positive attitude towards a specific sponsored event they care less about the event and are less likely to be involved in the event. We believe that when customers are highly involved with the sponsored event, the positive feelings they have towards the event are more likely to transfer to the firm (brand) than when customers are not highly involved. When customers are cognitively and emotionally involved with a sponsored event and identify with it, this self-identification may lead to a strong sense of attachment with the sponsored brands (cf. Arnett et al., 2003; Burke, 1980, 2000; Gwinner and Eaton, 1999; Johar and Sirgy, 1991; Meenaghan, 1991). Based on this discussion, we propose following hypothesis: H2. The positive influence of a customer's self-congruity with a sponsored event on the loyalty with that sponsored firm (brand) is likely to be greater when the customer is highly involved with the sponsored event than when the customer is less involved. 2.3. The moderating role of customer awareness We posit that self-congruity with a sponsorship event is likely to have a positive influence on brand loyalty when consumers are well aware of the fact that the firm (brand) is sponsoring the event. When consumers are well aware of the fact that the firm is sponsoring the event they identify with, the consumer's positive feelings about the event will spill over to the firm's or brand's image. For example, a strong feeling of identification with a sports event will evolve into the feelings of identification with the firm or the brand, which in turn positively influences brand loyalty and positive word of mouth (cf. Cardador and Pratt,

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2006; Gwinner and Eaton, 1999). Based on this discussion, we propose the following hypothesis: H3. The positive effect of self-congruity with a sponsored event on customer brand loyalty is likely to be greater when customers are well aware of the firm's sponsoring of the event than when consumers are not well aware of it. 3. Method 3.1. Sampling and data collection Our three hypotheses were tested using data collected from a series of surveys conducted by a research contracted by Nextel (a major mobile telecommunication company in the U.S.). The sponsorship event was the Nextel/NASCAR Cup Series (car racing sports event). A total of five surveys were conducted within an interval of 3 months. The sampling frame involved Nextel customers. The sample size of each sample was in the range of 244 to 475 with a total of 1588 respondents. Among them, 948 (59.7%) were male and 640 (40.3%) were female. In terms of age, 100 (6.3%) respondents were 18 to 24 years old, 410 (25.8%) respondents were in the 25–34 age group, 675 (42.5%) respondents were in the 35–49 age group, and 403 (25.4%) were in the 50–70 age group. The demographic profile of the sample was compared to the demographic profile of Nextel customer population (using a series of Chi-square tests), and the results show that the demographics of the sample is not significantly different from the demographics of the customer population. 3.2. Construct measures embedded in the survey questionnaire The measures pertaining to self-congruity, customer involvement, customer awareness, and brand loyalty measures were embedded in the context of a large survey questionnaire containing many other measures (e.g., media habits, demographics, lifestyle, and preference for particular telecommunication goods and services). Self-congruity with the sports event was measured using the following three items: 1. I feel like I am part of the NASCAR family, 2. I can relate to NASCAR drivers in a way I can't relate to other athletes, and 3. I would not feel at home in a crowd of NASCAR race fans (reverse coded). Responses to those items were captured on 5-point Likerttype scales. The reliability coefficients (Cronbach Alpha) for the self-congruity measure across five samples were 0.984, 0.986, 0.981, 0.986, and 0.984, respectively. These results show that the self-congruity measure is highly reliable. Therefore, a composite self-congruity score was computed by averaging the scores of these three items. Customer involvement with a sporting event included customer experience of attending the sporting event, purchasing

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goods at the sporting event, and checking game results. Specifically, customer involvement was measured using the three items:

Table 2 Involvement moderation effect Survey

Moderator effect: customer involvement Low involvement

1. Have you ever attended to NASCAR? 2. Have you ever purchased NASCAR goods? 3. Have you ever checked NASCAR game results? Responses to these three items were captured using a dichotomous scale: never = 0, more than once = 1. Because these three items capture different aspects of customer involvement, we treated this measure as formative rather than reflective. Hence, we did not make an attempt to test for reliability (internal consistency). Customer involvement scores were computed by summing the three items. Customer awareness of the firm's sponsoring the event was measured as a single-item measure: “Did you know the company is the official sponsor of NASCAR and a NASCAR racing team?” (no = 0, yes = 1). Brand loyalty was also measured as the converse of switching intention: “How likely are you to change wireless service providers anytime soon?” The response scale was a 4-point rating scale with the following bi-poles: “definitely will change (1) and “definitely will not change” (4). Note that these measures were embedded in the context of a large survey questionnaire. Hence, we could not afford to use multiple indicators of customer awareness and brand loyalty. 4. Results We will describe the study results by hypothesis. 4.1. The effect of self-congruity on brand loyalty (H1) We hypothesized that customers' self-congruity with a sporting event is likely to have a positive influence on customers' brand loyalty. As shown in Table 1, the results indicate that selfcongruity has a positive influence on brand loyalty in 3 out of 5 samples used in this study (beta = 0.214, t = 3.503 for sample 1; beta = 0.209, t = 3.579 for sample 2; beta = 0.076, t = 1.189 for sample 3; beta = 0.098, t = 1.787 for sample 4; beta = 0.012, t = 0.259 for sample 5). The five samples were pooled, and the results from the pooled sample also indicate that self-congruity does indeed have a positive influence on brand loyalty (beta =

Table 1 Self-congruity effect on brand loyalty Survey

Fifth survey: 4Q2004 Fourth survey: 3Q2004 Third survey: 2Q2004 Second survey: 1Q2004 First survey: 4Q2003 Pooled data

The main effect: the self-congruity effect on brand loyalty Beta

t-value

R2

N

0.214 0.209 0.076 0.098 0.012 0.084

3.503 3.579 1.189 1.787 0.259 3.357

0.460 0.044 0.006 0.100 0.000 0.007

257 283 244 329 475 1588

4Q2004 3Q2004 2Q2004 1Q2004 4Q2003 Pooled data

High involvement 2

Beta

t-value

R

N

Beta

t-value

R2

N

0.138 0.130 0.049 − 0.009 0.006 0.055

1.254 1.145 0.499 − 0.095 0.091 1.337

0.019 0.017 0.002 0.000 0.000 0.003

83 78 106 116 219 602

0.239 0.209 0.142 0.175 0.003 0.176

3.227 3.040 1.674 2.584 0.046 5.595

0.057 0.044 0.020 0.031 0.000 0.030

174 205 138 213 256 986

0.084, t = 3.357). These results provide reasonable support for H1 (see Table 1). 4.2. The moderation effect of customer involvement (H2) H2 posits that the positive influence of a customer's selfcongruity with a sponsored event on brand loyalty is likely to be greater when the consumer is highly involved with the sponsored event. As shown in Table 2, the results indicate that self-congruity did not have a positive influence on brand loyalty when customer's involvement with the sports event was low for all five samples (beta = 0.138, t = 1.254 for sample 1; beta = 0.130, t = 1.145 for sample 2; beta = 0.049, t = 0.049 for sample 3; beta = − 0.009, t = − 0.095 for sample 4; beta = 0.006, t = 0.091 for sample 5). The results from the pooled sample also indicate that self-congruity did not have a positive influence on brand loyalty when customer involvement was low (beta = 0.055, t = 1.337 for pooled sample). Furthermore, the results indicate that self-congruity had a positive influence on brand loyalty when customer's involvement was high in four samples (beta = 0.239, t = 3.227 for sample 1; beta = 0.209, t = 3.040 for sample 2; beta = 0.142, t = 1.674 for sample 3; beta = 0.175, t = 2.584 for sample 4; beta = 0.003, t = 0.046 for sample 5). The results from the pooled sample also indicate that self-congruity did have a positive influence on brand loyalty when customer involvement was high (beta = 0.176, t = 5.595 for pooled sample). The results of the beta coefficient difference test also indicate the beta coefficients in high and low involvement groups are significantly different (t = 2.337; p b 0.05). Using the pooled sample, we further conducted an ANOVA to plot the interaction between self-congruity and involvement by categorizing both self-congruity and involvement into two groups (using a median split). The plot is shown in Fig. 2. As shown in the figure, the interaction was significant [F(1, 1576) = 3.82, p b 0.05] and is in the right direction. Collectively, these results provide support for H2 (see Table 2 and Fig. 2). 4.3. The moderation effect of customer awareness (H3) H3 posits that the positive effect of a sponsored event on brand loyalty is likely to be greater when customers are well aware of the firm's sponsoring of the event than when consumers are not. As shown in Table 3, the results indicate that

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Fig. 2. The moderation of involvement on the self-congruity effect.

Fig. 3. The moderation of awareness on the self-congruity effect.

when customers did not have knowledge of the firm's sponsoring of the event, self-congruity did not have a positive influence on brand loyalty for all five samples (beta = 0.025, t = 0.215 for sample 1; beta = 0.136, t = 1.349 for sample 2; beta = 0.158, t = 1.506 for sample 3; beta = 0.089, t = 1.044 for sample 4; beta = − 0.011, t = − 0.028 for sample 5). The results from the pooled sample also indicate that self-congruity had a marginally significant influence on brand loyalty when customer awareness was low (beta = 0.069, t = 1.842 for pooled sample). The results also indicate that when customers had knowledge on the firm's sponsoring of the event self-congruity did have a positive influence on brand loyalty for 2 out of 5 samples (beta = 0.190, t = 2.599 for sample 1; beta = 0.162, t = 2.222 for sample 2; beta = 0.003, t = 0.035 for sample 3; beta = 0.108, t = 1.492 for sample 4; beta = 0.027, t = 0.354 for sample 5). The results from the pooled sample also indicate that self-congruity had a significant influence on brand loyalty when customer awareness was high (beta = 0.095, t = 2.842 for pooled sample). Using the pooled sample, we further conducted an ANOVA to test plot the interaction between self-congruity and awareness by categorizing both self-congruity and awareness into two groups (using a median split). The plot is shown in Fig. 3. As shown in the figure, the interaction although nonsignificant [F (1, 1584) = 0.81, p N 0.05] is visually evident and is in the right

direction. Loyalty scores are highest in the high self-congruity and high awareness condition and the slope of the high awareness condition across the high and low self-congruity condition is steeper than the slope of the low awareness condition. Collectively, these results provide partial support for H3 (see Table 3 and Fig. 3). Still using the pooled sample, we conducted a 3-way ANOVA analysis to test the combined moderation effects of both involvement and awareness. The 3-way interaction effect approached significance [F(1, 1572) = 1.11, p = 0.2). As expected, brand loyalty scored highest (Mean = 3.34) in the high self-congruity condition given high involvement and high awareness more so than any other condition. Also as expected, the low selfcongruity condition given low involvement and low awareness generated the lowest brand loyalty mean score (Mean = 3.01). Again, although these results are not statistically significant, the overall pattern of the data seems to provide some support of the combined moderation effects of involvement and awareness.

Table 3 Awareness moderation effect Survey

Moderator effect: customer awareness Low awareness

4Q2004 3Q2004 2Q2004 1Q2004 4Q2003 Pooled data

High awareness

Beta

t-value

R2

N

Beta

t-value

R2

N

0.025 0.136 0.158 0.089 −0.028 0.069

0.215 1.349 1.506 1.044 − 0.489 1.842

0.001 0.018 0.025 0.008 0.001 0.005

74 99 91 138 302 704

0.190 0.162 0.003 0.108 0.027 0.095

2.599 2.222 0.035 1.492 0.354 2.840

0.036 0.026 0.000 0.012 0.001 0.009

183 184 153 191 173 884

5. Discussion The results of this study indicate that self-congruity with sponsored sports events has a positive influence on brand loyalty moderated by customer awareness of the firm sponsoring the event and customer involvement with the sponsored event. Should marketers invest resources in developing marketing communications campaigns designed to increase their customers' involvement with the sponsorship event and heighten their awareness that the firm is sponsoring the event? The findings of this study suggest the answer should be a resounding yes. Our model suggests that the marketing communications campaign should aim to enhance self-congruity with the sponsored event. That is, images of people attending the sponsorship event should be consistent with customers' self-concept. Customers can be exposed to promotional messages in which the attendees of the sponsorship event are depicted as highly akin to customers. Of course, research should be conducted first to identify the personal characteristics of those that regularly attend the target

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sponsorship event. Once these personal characteristics are identified, the firm's marketing manager should select to use images that customers can identify with. In other words, the firm's customers have to see the ad and feel that the kind of people that attend the sponsorship event are very much similar to them (i.e., they can identify with them—experience selfcongruity). Once customers experience self-congruity, further promotional messages should make those customers aware that the firm is sponsoring the event and make every attempt possible to get their customers more involved with the event. Awareness can be easily generated through advertising, but getting customers more emotionally involved with the sponsorship event can be challenging. Running games and contests for their customers at the location of the event is perhaps an example of a method to increase customer involvement with the event. The study has the following limitations. This study has focused on congruity with the sponsored sports event and customer self-image. One can argue that congruity with brand image also plays a role in this. Thus, one can postulate three types of congruity experiences that may impact brand loyalty: the congruity between sponsored event image and the customer's self-image (we can call this “sponsored event selfcongruity”), the congruity between the sponsored event image and the brand user image (we can call this “sponsored event brand congruity”), and the congruity between the brand image and the customer's self-image (we can call this “brand selfcongruity”). Future research should be conducted to test the theoretical proposition that these three types of congruity experiences play an important role in brand loyalty. The managerial implications of this proposition is to select sponsored events that match the customer's self-image followed by promotion that reinforce the sponsored event self-congruity, sponsored event brand congruity, and brand self-congruity. Doing so should heighten brand loyalty. Future studies should also examine the role of ideal selfcongruity, social self-congruity, and ideal social self-congruity. The present study focused on actual self-congruity and the role of the need of self-consistency in establishing relationship between customer's self-concept and the sponsored event image. That is, the focus was on the actual self, not the ideal self, the social self, and the ideal social self. Self-congruity involving the ideal self involves a different self-concept motive, namely the self-esteem motive (Sirgy, 1986). Consumers are motivated to purchase and re-purchase brands with a user image that is consistent with their ideal self. Doing so enhances their selfesteem. For example, a consumer perceives the people who drive a Mazda sports car to be young, wild, and attractive (brand user image). They may have an actual self-image of not being young, wild, and attractive, but they like to become young, wild, and attractive. Buying and driving a Mazda sports car may help attain that ideal self, and doing so boosts the person's sense of selfesteem. Similarly, consumers are motivated to remain loyal to brands with user images consistent with their social self (the image they think they present to others). The self-concept need related to social self-congruity is social consistency. In other words, people are motivated to engage in behaviors that satisfy the need for social consistency (Sirgy, 1986). For example, a

consumer may feel motivated to watch detective movies and television shows because he believes that he is seen by significant others as being the kind of person who enjoys detectivetype stories. Engaging in further behaviors that reinforce his social image of being that kind of person satisfies the need for social consistency. Lastly, there is the need for social approval that is related to the ideal social self. People are motivated to engage in behaviors that allow them to gain approval and avoid disapproval from others, especially significant others (Sirgy, 1986). Thus, they purchase and use goods and services that have brand user images consistent with their ideal social self. Doing so helps satisfy the need for social approval. Thus, future research should extend the model described in this paper by focusing on the role of other types of self-concepts besides the actual self: ideal self, social self, and ideal social self. One can hypothesize that brand loyalty is likely to be greatest when the image of sponsored event (stereotypic image of those that regularly attend the sponsored event) is consistent with the brand user image and the customer's actual, ideal, social, and ideal social self. The conceptual model of this study was tested using a sports sponsorship event by a well-known firm (NEXTEL). What would be the effect of sports sponsorship event on brand loyalty when the sponsorship is with a lesser-known firm? In other words, how does firm sponsor familiarity moderate the relationships in the model? One can argue that the effect of self-congruity with the sponsorship on brand loyalty is likely to be greater with lesserknown firms than with well-known firms. Perhaps this may be due to the possibility that there is more room for improvement in brand loyalty in the case of less-known brands. In contrast, one can counter argue that the effect of self-congruity with the sponsorship on brand loyalty is likely to be greater with a wellknown brand. This may be due to the image spillover from the sports event unto the brand image (Javalgi et al., 1994). Future studies should test these alternative hypotheses. Methodologically, this study used a single-item measure for brand loyalty and customer awareness. Future studies should incorporate multiple indicator measures (and perhaps more demonstrably valid) to capture these constructs. Also, the model of this study was tested in a single sponsorship event context (NASCAR). In general, the degree of spillover from a sponsorship event on brand image is influenced by many factors including the degree of congruity between the sponsorship event image and brand image, frequency of sponsored events, and extent of sponsorship efforts (Gwinner 1997; Gwinner and Eaton 1999). Future studies should test the model in the contexts of various sponsorship events. Furthermore, this study examined the effects of selfcongruity with sporting events on brand loyalty. Given the cross-sectional nature of the data, this study fails to measure customer brand loyalty before the firm's sponsoring of the sports event. Future longitudinal study should examine the changes of brand loyalty before and after the sports sponsorship. Despite these limitations, the findings of the present study do shed some light on the role of self-congruity with sponsored events in relation to brand loyalty. We hope that the present study generates a stream of research on sponsorship event congruity.

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Editorial

Editorial: Marketing communications and consumer behavior: Introduction to the special issue from the 2009 La Londe conference

This special issue of the Journal of Business Research includes a selection of papers presented at the 36th International Research Conference in Marketing organized by the Aix Graduate School of Management (I.A.E. Aix-en-Provence), University Paul Cézanne in Aix-Marseilles (France). This conference known as the “La Londe Conference” is devoted to Marketing Communications and Consumer Behavior on a biennial basis. The La Londe conference encourages intense discussions of specialized topics in consumer behavior and communications amongst specialized and top level scholars in a relaxed and informal atmosphere. Those who have participated to the La Londe conference know the exchange value of the sessions and of the get togethers and coffee breaks on the terrace overlooking the Mediterranean Sea and the Porquerolle islands. The La Londe conference is truly international. It has always been chaired by a duo of first class researchers, one from Europe and one from America. Professor Chris A. Janiszewski (University of Florida, USA) and Professor Stijn M. J. van Osselaer (RSM Erasmus University, Rotterdam, The Netherlands) chaired the 2009 conference. A total of 93 manuscripts were submitted and double-blind reviewed by both members of the permanent scientific committee of the conference and ad-hoc reviewers carefully selected by the co-chairmen and the coordinators of the conference. Forty-two papers were presented at the conference. In addition, the provocative, thoughtful and very entertaining keynote address by Professor Tanya L. Chartrand (Fuqua School of Business, Duke University, USA) stimulated reflections and discussions concerning the process of non-conscious mimicry and implications for human relationships and consumer behavior. The eleven papers selected for this special issue follow the dual theme of consumer behavior and marketing communications. The first four papers deal with communication effects and advertising effectiveness. Rafi Chowdhury, G. Douglas Olsen and John W. Pracejus (“How many pictures should your print ad have?”) examine the impact of increasing the number of images in a print advertisement on affective and cognitive consumer responses. The results of two experiments show that in advertisements with only positive or only negative images, increasing the number of positive (negative) images does not increase positive (negative) affect. For this type of advertisements, advertisers should select only one suitable image which provides a clear example of the benefit being advertised. However, in advertisements with both positive and negative pictures, increasing the number of positive (negative) images increases positive (negative) affect. Therefore, scope effects only occur in oppositely valenced affect integration and more is not necessarily better for pictures in advertising. Karine Gallopel-Morvan, Patrick Gabriel, Marine Le Gall-Ely, Sophie Rieunier and Bertrand Urien, (“The 0148-2963/$ – see front matter © 2009 Elsevier Inc. All rights reserved. doi:10.1016/j.jbusres.2009.09.010

use of visual warnings in social marketing: The case of tobacco”) explore the ideal combination of self-efficacy and fear appeal warnings (as inserted on cigarette packs) according to Protection Motivation Model principles. The exploratory study conducted demonstrates that visual messages, as opposed to text warnings, are more effective. The mostly used fear appeals need to be combined with self-efficacy and cessation support messages because they provoke avoidance reactions when used alone. Jane McKay-Nesbitt, Rajesh Manchanda, Malcolm Smith and Bruce Huhmann (“Effects of age, need for cognition, and affective intensity on advertising effectiveness”) explore the moderating effects of individual characteristics (age, need for cognition and affective intensity) on the effectiveness of ad appeals that are framed emotionally versus rationally. Younger adults find emotional appeals more persuasive than rational appeals and older adults develop more positive attitude towards the ad when exposed to rational appeals. Moderating effects are also found for need of cognition and affective intensity. Finally, Boon Lim and Cindy Chung (“The impact of word-of-mouth communication on attribute evaluation”) extend the media congruence hypothesis and study the impact of word-of-mouth (WOM) communication on the WOM recipient's ratings of search and credence attributes. The experiments run in two different service contexts demonstrate, as hypothesized, that WOM has greater impact on attribute ratings for credence attributes than for search attributes. This relationship seems to be limited to negative WOM. The three next papers deal with promotions. Don Schultz and Martin Block (“How U.S. consumers view in-store promotions”) study the impact of a wide variety of promotional activities on consumer behavior, from the consumer perspective. Based on the SIMM (Simultaneous Media Consumption) studies conducted among a nationally projectable sample of U.S. consumers twice yearly (200,000+ individual responses), they show the importance of both external-to-the-store promotional activities and in-store promotional activities on self-reported behavior. Also, they establish that the relative importance of the promotional activities varies across product categories. Priya Raghubir and Kirti Celly (“Promoting promotions: Does showcasing free gifts backfire?”) examine the effect of the visual size of a gift in a free gift promotion on consumer quality judgments and purchase intentions. Results from two experiments show that promotional offers that highlight the free gift (rather than the product) are less effective than those that highlight the product to be purchased. Increasing the visual size of the free gift leads to perceptions of poorer product quality and has unfavorable consequences for purchase intentions of the offer. Pierre Valette-Florence, Haythem Guizani, and Dwight Merunka (“The impact of brand

2

Editorial

personality and sales promotions on brand equity”) study the relative impact of a long-term brand management instrument (brand personality) and a short-term marketing mix instrument (sales promotions) on brand equity formation. They find a positive impact of brand equity and a negative impact of sales promotion intensity on brand equity at the aggregate level. They identify and describe three homogeneous consumer groups which differ according to the relative impact of brand personality and consumer promotions on brand equity, following the application of a finite mixture partial least square procedure. The remaining four articles of this special issue focus on consumer behavior. Marieke Fransen, Dirk Smeesters and Bob Fennis (“The role of social presence in mortality salience effects”) add to Terror Management Theory's proposition that people need self-esteem to deal with unconscious existential anxiety, which they achieve by following the rules, norms, and values of one's cultural worldview. They argue that people can experience extra self-esteem when they act in accordance with cultural norms while others can observe this behavior. The results of two studies show that the presence of others increases the effects of mortality salience on brand evaluations that affirm one's cultural worldview. This reveals that consumers derive self-esteem indirectly from the knowledge that others observe them following cultural norms rather than directly from following cultural norms per se. JungKun Park, HoEun Chung and Brian Rutherford (“Social perspectives of e-contact center for loyalty building”) propose that an e-contact center can be used for establishing and maintaining desired relationships with customers. In particular, e-contact centers enhance the relationship between e-retailers and online customers by providing social values and quality interpersonal service to customers. Using a panel of online consumers, they demonstrate that interpersonal service quality and social value greatly influence satisfaction with e-contact centers which, in turn, influences e-loyalty. Boris Bartikowski and Gianfranco Walsh (“Investigating mediators between corporate reputation and customer citizenship behaviors”) study the influence of corporate reputation and customer citizenship behavior (CCB) and hypothesize that the influence of customer-based corporate reputation (CBR) on CCB is mediated by commitment and loyalty. Data collected on service customers reveal that commitment and loyalty mediate the relationship between CBR and one type of CCB, namely helping the company. They do not mediate the other dimension of CCB (willingness to help other customers). Sigal Kaplan, Shlomo Bekhor and Yoram Shiftan (“Eliciting and estimating reservation price: A semi-compensatory approach”) develop and test a two-stage model to elicit consumers' price acceptability range. The proposed model is well suited for choice situations containing many alternatives, typical of the digital economy. The method retrieves the price acceptability range simultaneously for different multi-attribute product variations from cross-sectional data. It assumes a two-stage cognitive choice process consisting of a conjunctive strategy followed by utility maximization. The model is applied to a students' rental apartment case study, as an example of a multi-attribute product with many variations. As co-chairs and coordinators of this conference and as co-editors of this special issue, we greatly appreciate the inputs of the international scientific committee members of the La Londe conference who year after year contribute to the paper selection process and help to guarantee the quality of the contributions through their

reviews. The scientific committee is composed of the following very distinguished scholars: Gerald Albaum (University of New Mexico), Søren Askegaard (University of Southern Denmark, Odense), Rajeev Batra (University of Michigan at Ann Arbor), Russell W. Belk (University of Utah), Elisabeth Cowley (University of Sydney), Christian Derbaix (FUCAM, Mons), Curtis P. Haugtvedt (Ohio State University), Wayne D. Hoyer (The University of Texas at Austin), Alain Jolibert (University of Grenoble), Lynn R. Kahle (University of Oregon), Michel Laroche (Concordia University, Montreal), Gilles Laurent (HEC, Paris), Siew Meng Leong (National University of Singapore), Sidney J. Levy (University of Arizona), Richard J. Lutz (University of Florida), Hans Mühlbacher (University of Innsbruck), Robert A. Peterson (The University of Texas at Austin), Rik Pieters (Tilburg University), Christian Pinson (INSEAD), Bernard Pras (University of Paris-Dauphine and ESSEC), Don E. Schultz (Northwestern University), M. Joseph Sirgy (Virginia Polytechnic Institute & State University), Jan-Benedict Steenkamp (University of North Carolina at Chapel Hill), Alain Strazzieri (Paul Cézanne University in Aix-Marseille), Pierre Valette-Florence (University of Grenoble), W. Fred van Raaij (Tilburg University), Luk Warlop (Katholieke Universiteit Leuven), Arch G. Woodside (Boston College) and Judy Zaichkowsky (Simon Fraser University). We also wish to thank all other members of the review panel who have done a great reviewing job. Finally, we wish to express our gratitude to Arch Woodside, editor in chief of the Journal of Business Research for initiating and approving this special issue. We look forward to the 2011 edition of the La Londe conference. Two outstanding researchers, Michel Tuan Pham, Professor of Marketing at the Graduate School of Business, Columbia University, New York, USA and Siegfried Dewitte, Professor of Marketing at the Faculty of Economics and Business, K.U. Leuven, Belgium, have accepted to co-chair this next La Londe Consumer Behavior and Communications conference. The 2011 La Londe conference will take place early June 2011 in the totally renovated resort of La Londe les Maures on the French Mediterranean coast. Virginie De Barnier University Paul Cézanne Aix-Marseille (IAE Aix) and Wesford Business School Grenoble, France Chris A. Janiszewski University of Florida, USA Dwight R. Merunka University Paul Cézanne Aix-Marseille, (IAE Aix), France Euromed Management, Marseilles, France Corresponding author. IAE Aix-en-Provence, University Paul Cézanne Aix-Marseille, Clos Guiot, 13540 Puyricard, France. Tel.: +33 442 280 808, fax: +33 442 280 800. E-mail address: [email protected]. Stijn M.J. van Osselaer RSM Erasmus University, Rotterdam, The Netherlands 1 April 2009

Journal of Business Research 64 (2011) 3–6

Contents lists available at ScienceDirect

Journal of Business Research

How many pictures should your print ad have? Rafi M.M.I. Chowdhury a,⁎,1, G. Douglas Olsen b,⁎,2, John W. Pracejus c,⁎,3 a b c

School of Management and Marketing, 40.144, Faculty of Commerce, University of Wollongong, NSW 2522, Australia Department of Marketing, W.P. Carey School of Business, Arizona State University, Main Campus, PO Box 874106, Tempe, AZ 85287, United States Department of Marketing, Business Economics, and Law, 3-30G, School of Business, University of Alberta, Edmonton, AB, Canada T6G 2R6

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Article history: Received 1 April 2009 Received in revised form 1 July 2009 Accepted 1 September 2009 Keywords: Images Print advertising Scope effects Affect Attitude

a b s t r a c t This study examines the impact of increasing the number of images in a print advertisement on affective and cognitive responses. In advertisements with both positive and negative pictures, increasing the number of positive (negative) images increases positive (negative) affect. However, consistent with theory regarding the mechanism underpinning affect integration in a simultaneous presentation context, in advertisements with only positive or only negative images, increasing the number of positive (negative) images of similar affective intensity does not increase positive (negative) affect. For both types of advertisements, additional pictures have no effects on attitude toward the ad when they exemplify a product attribute or benefit that an existing picture(s) already depicts. © 2009 Elsevier Inc. All rights reserved.

1. Introduction Pictures in advertising attract attention (Pieters and Wedel 2004), generate emotional responses (Chowdhury et al., 2008) and create beliefs about product attributes (Mitchell and Olson, 1981). In many instances print advertisements employ multiple images. For example, an advertisement for a clothing store with multiple pictures of models wearing the stylish attire available at the store. This research investigates the potential benefits of increasing the number of pictures in a print advertisement. In the marketing literature, only two studies look at the effects of multiple pictures in print advertising. Singh et al. (2000) compare an eight-page advertising spread with multiple pictures to a four-page version of the ad. Their results suggest that reducing pictures that do not generate relevant imagery does not decrease advertising effectiveness. A number of limitations are present with this study. First, only peripheral pictures are eliminated. Second, the images are spread out over multiple pages and presented sequentially, as opposed to a single page ad with pictures presented simultaneously. Third, the pictures are not separately pre-tested to measure the affect they generate, making it impossible to understand how viewers integrate the affect from different pictures into an overall response.

⁎ Corresponding authors. R.M.M.I. Chowdhury is to be contacted at Tel.: +61 2 42213377. Olsen, Tel.: +1 480 9654011. Pracejus, Tel.: +1 780 4922023. E-mail addresses: rafi@uow.edu.au (R.M.M.I. Chowdhury), [email protected] (G.D. Olsen), [email protected] (J.W. Pracejus). 1 Tel: 61 2 42213377. 2 Tel: 1 480 9654011. 3 Tel: 1 780 4922023. 0148-2963/$ – see front matter © 2009 Elsevier Inc. All rights reserved. doi:10.1016/j.jbusres.2009.09.011

Chowdhury, Olsen, and Pracejus (2008) investigate affective responses to a print advertisement containing either one or two images. Results indicate that for advertisements using only univalenced pictures (only positive or only negative pictures), the peak affect from any one of the pictures determines the overall affective response to the ad. However, for advertisements with oppositely valenced pictures (both positive and negative pictures) a compensatory mechanism determines overall emotional response. This study does not consider the impact of additional pictures on important cognitive responses such as attitude toward the ad. The study examines a maximum of two pictures, reducing the ability to determine the underlying method of affect integration. For example, a careful consideration of the compensatory findings reveals two possible outcomes when increasing the number of pictures in advertisements with oppositely valenced pictures. One possibility is that viewers: (1) process positive pictures and negative pictures separately, and then (2) integrate the affect generated by these separate types of pictures. This process may seem reasonable given that positive pictures generate primarily positive affect and negative pictures generate primarily negative affect and as positive affect and negative affect are independent constructs (see Watson and Tellegen, 1985). This process implies that one positive picture and one negative picture will generate the same overall affect as five positive pictures (of similar intensity) and one negative picture. However, rather than processing positive and negative images separately, individuals may utilize the additional positive images as separate sources of positive affect to counteract the negative affect generated by negative images. This would imply that increasing the number of positive pictures would increase overall positive affect. Both mechanisms would appear to have some merit

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and the exact outcome of the proposed compensatory mechanism for oppositely valenced pictures in a print advertisement needs further examination. The purpose of this research is: (1) to examine the impact of more than two images in a print advertisement, (2) to investigate the differing mechanisms of affect integration in univalenced and mixed valenced contexts, and, (3) to further investigate the disjuncture between affect and cognition. The next section develops predictions regarding the effects of increasing pictures in mixed valenced and single valenced advertisements. The effects are examined for both affective and cognitive measures, as affective responses and cognitive responses are separate constructs (see Malhotra, 2005) and both are important dependent variables in terms of measuring advertising effectiveness (see Chowdhury et al., 2008). 2. Theory development in brief 2.1. Increasing the number of images in a mixed valence context 2.1.1. Affective response Research on positive emotions shows that individuals use positive emotions as a resource to undo the effects of negative emotions (e.g., Fredrickson and Levenson, 1998). Other research on how individuals integrate positive and negative events (e.g., Linville and Fischer, 1991) also demonstrates that individuals use positive events to cope with negative events. In a print advertisement with oppositely valenced images the most effective approach is to treat each positive affective element as a separate source of positive affect than to average across the positive elements. Having more positive elements allow for a greater number of sources of positive affect to counteract the negative affect, thus decreasing overall negativeness and increasing overall positiveness. Thus, affect integration of oppositely valenced images should follow a compensatory mechanism where the number of positive images and negative images are taken into consideration. 2.1.2. Cognitive response Unnava and Burnkrant (1991) demonstrate that an advertisement that uses both words and pictures to describe a product attribute is not more effective that an advertisement with only pictures to describe the same attribute, as the words do not generate any additional imagery in the mind of the viewer. Similarly, if additional pictures in an advertisement exemplify a benefit already depicted by an existing image then the extra pictures should not generate additional imagery that is more relevant in the mind of the viewer. A separate stream of research also shows that when affective stimuli influence decisions, these decisions tend to be “sensitive to the presence or absence of affect producing stimuli but relatively insensitive to further variations in the magnitude of the stimuli” (Cohen et al., 2008, p. 312, based on Hsee and Rottenstreich, 2004). A mixed valenced pictorial print advertisement has a set of positive pictures and a set of negative pictures. A prototypical member of each set should affect evaluations, and having a greater number of positive or negative images rather than just one of each should not impact liking for the advertisement. 2.2. Increasing the number of images in a single valence context 2.2.1. Affective response In the context of affective psychology, scope refers to the quantitative aspect of affective stimuli (Hsee and Rottenstreich, 2004). Scope neglect implies insensitivity to the number of a type of stimuli (positive or negative). Chowdhury, Olsen, and Pracejus (2008), show that in the case of the integration of only positive or only negative images in a print advertisement, a peak effect determines overall affective response. In a set of same valenced

affective stimuli, the stimulus with the highest affective intensity determines overall affective response. This peak effect predicts scope neglect for univalence affect integration. For example, the integration of multiple positive images of similar intensity should generate the same positive affect as one positive image of equal intensity. 2.2.2. Cognitive response Positive images generate relevant positive imagery in the viewer's mind, while negative images generate relevant negative imagery in the mind of the viewer. This leads to a liking for ads with positive pictures (e.g., Mitchell and Olson, 1981). However, for ads with only positive or only negative images, additional positive or negative images used as examples of the same product attribute/benefit should not create additional imagery that is more relevant. Research also demonstrates that when affective stimuli impact evaluations, decisions are sensitive to the type of affective stimuli (positive versus negative) but insensitive to the number of affective stimuli (Hsee and Rottenstreich, 2004). This implies that viewers evaluate advertisements with positive pictures more favourably than those with negative pictures, but additional pictures of similar valence have negligible effects on evaluations. Two experiments test the predictions. Experiment 1 examines advertisements with both positive and negative images, while Experiment 2 investigates advertisements with univalenced images. 3. Experiment 1 3.1. Participants and design 150 undergraduate students participated for course credit. The three between-subject conditions were: 1 Positive-1 Negative (1 Pos1 Neg), 3 Positives-1 Negative (3 Pos-1 Neg), and 1 Positive-3 Negatives (1 Pos-3 Neg). 3.2. Stimuli development The experiment utilized 10 images (five positive and five negative). In a separate pre-test, 46 participants (participants from the same student population as those in this study) had rated the images on a scale from −5 (extremely negative) to + 5 (extremely positive). The selected images were moderate in intensity (i.e., the positive pictures were all rated between + 2 and + 3 on the scale and the negative pictures were all rated between − 2 and −3 on the scale). The five moderate positive images were: children leaving school (m = 2.54, sd = 1.46), man with pigeons (m = 2.37, sd = 1.58), man and woman at party (m = 2.41, sd = 1.33), woman dancing (m = 2.37, sd = 1.39), and woman holding champagne glass (m = 2.5, sd = 1.39). The five moderate negative images were: man pulling cart (m = − 2.89, sd = 1.52), man leaning against wall (m = − 2.17, sd = 1.34), little girl looking sad (m = −2.67, sd = 1.56), man holding head (m = − 2.83, sd = 1.12), and child crying during game (m = −2.41, sd = 1.69). The pictures were used in a print advertisement for a digital camera. The copy in the ad read, “For over 75 years, [Brand Name] has been the leading choice of photo-journalists. The images captured are not always pretty, but they are always of high quality. [Brand Name] builds a camera with a reputation for being reliable even under the most difficult conditions.” Different experimental conditions had a different number of positive and negative images used in the ad. In conditions with more than one picture, the additional pictures are additional examples of the brand's key benefit (i.e., being able to take high quality pictures). The advertisement was 8.5″ × 11″, black and white, printed on plain white paper. Each picture was approximately 3″ × 3″. As five different images were used for both categories of pictures (positive and negative), the 1 Pos-1 Neg condition employed all 25 possible

R.M.M.I. Chowdhury et al. / Journal of Business Research 64 (2011) 3–6

combinations of images. In the 3 Pos-1 Neg condition and the 1 Pos-3 Neg condition, all possible image combinations were used resulting in 50 unique ads for each of these conditions.

Table 2 Experiment 2: positive affect, negative affect, and attitude toward the ad across conditions.

3.3. Procedure and dependent variables Positive affect

Participants viewed the advertisement for thirty seconds and then completed a questionnaire with the dependent measures. The positive and negative affect scale was taken from Pham, Cohen, Pracejus, and Hughes (2001). The scale consisted of ten items anchored “1(not at all)” and “7 (very strongly)”. The negative affect scale included the following six items: “I had unpleasant feelings viewing the ad”; “I was disgusted by the ad”; “I was fearful viewing the ad”; “The ad made me feel bad”; “The ad made me feel angry” and “The ad made me feel sad”, α = 0.88. The positive affect scale included the following four items: “The ad made me feel happy”; “The ad made me feel good”; “The ad made me feel joyful” and “I had pleasant feelings viewing the ad”, α = 0.88. Three items were used to measure attitude toward the ad (Aad), with seven-point rating scales for each item. The items were: likeable, favourable, and appealing, α = 0.89. The average responses to the items defining positive affect, negative affect, and attitude toward the ad determined overall scores for each construct.

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Negative affect Aad

3 Pos (n = 48)

1 Pos (n = 30)

3 Neg (n = 48)

1 Neg (n = 32)

ANOVA F (3, 154)

Partial η2

4.17 (1.17) 1.61 (0.81) 4.32 (1.38)

3.80 (1.69) 1.57 (0.89) 4.61 (1.44)

1.86 (0.93) 3.46 (1.28) 3.63 (1.25)

1.99 (0.95) 3.33 (1.21) 3.75 (1.40)

42.78**

0.46

38.08**

0.43

4.43*

0.08

Standard deviations within each cell are indicated in parentheses. **p < .001, *p < .01.

Four different images were used for both categories of pictures (positive and negative) in an effort to keep the number of combinations manageable. The 1 Pos and 1 Neg conditions each had four unique advertisements. The 3 Pos and the 3 Neg condition also each used all four possible combinations of pictures. 4.3. Procedure and dependent variables The procedure and dependent variables were similar to Experiment 1. 4.4. Results

3.4. Results Table 1 presents the results of Experiment 1. An analysis of variance (ANOVA) indicates that the experimental conditions differ in terms of positive affect, F (2, 147) = 14.90, p<.001. The 1 Pos-1 Neg condition is lower than the 3 Pos-1 Neg condition, t (98)=2.20, p<.05 and higher than the 1 Pos-3 Neg condition, t (98)=3.31, p<.01. The 3 Pos-1 Neg condition is higher than the 1 Pos-3 Neg condition, t (98)=5.43, p<.001. The conditions also differ in terms of negative affect, F (2, 147)=17.97, p<.001. The 1 Pos-1 Neg condition is higher than the 3 Pos-1 Neg condition, t (98)=2.93, p<.01 and lower than the 1 Pos-3 Neg condition, t (98) = 3.06, p < .01. The 3 Pos-1 Neg condition is lower than the 1 Pos-3 Neg condition, t (98) = 5.98, p < .001. The conditions do not differ in terms of attitude toward the ad, F (2, 147)= 0.96, ns. The findings support the predictions. 4. Experiment 2 4.1. Participants and design 158 undergraduate students participated for course credit. The four between subject conditions were: Positive Single (1 Pos), Three Positives (3 Pos), Negative Single (1 Neg) and Three Negatives (3 Neg). 4.2. Stimuli development The same type of print advertisement as utilized in the previous experiment was used. The difference was in the subset of images used.

Table 1 Experiment 1: positive affect, negative affect, and attitude toward the ad across conditions.

Positive affect Negative affect Aad

3 Positive1 Negative (n = 50)

1 Positive1 Negative (n = 50)

1 Positive3 Negative (n = 50)

ANOVA F (2, 147)

Partial η2

3.56 (1.23) 1.83 (0.90) 3.95 (1.36)

3.04 (1.11) 2.42 (1.12) 3.79 (1.44)

2.35 (0.99) 3.17 (1.31) 3.57 (1.32)

14.90*

0.17

17.97*

0.20

0.96

0.01

Standard deviations within each cell are indicated in parentheses. *p < .001.

Table 2 presents the results of Experiment 2. An analysis of variance (ANOVA) indicates that the experimental conditions differ in terms of positive affect, F (3, 154)=42.78, p<.001. However, the 1 Pos and the 3 Pos condition do not differ, t(76)=1.15, ns. The 1 Neg and the 3 Neg condition also do not differ t(78)=0.62, ns. The conditions differ in terms of negative affect, F (3, 154)=38.08, p<.001. However, the 1 Neg and the 3 Neg condition do not differ, t (78)=0.47, ns. The 1 Pos and the 3 Pos condition also do not differ t(76)=0.21, ns. The conditions differ in terms of attitude toward the ad, F (3, 154)=4.43, p<.01. However, the 1 Pos and the 3 Pos conditions do not differ, t(76)= 0.90, ns. The 1 Neg and the 3 Neg conditions also do not differ, t(78)= 0.42, ns. The findings support the predictions. 5. Discussion The results show that for advertisements with univalenced images, advertisers should select one image that has the requisite affective valence and intensity and provides a clear example of the benefit being advertised. When advertisements use oppositely valenced images a higher number of positive or negative pictures can generate greater affective response. However, in advertisements with oppositely valenced pictures one positive and one negative image should be adequate to provide information or produce liking unless the extra pictures depict additional product benefits. In terms of theoretical implications, the results imply that scope neglect occurs in univalence affect integration, however scope effects occur in oppositely valenced affect integration. This is due to the peak mechanism that drives univalence affect integration, while a compensatory mechanism drives oppositely valenced affect integration. The findings support the view that cognitive evaluations based on affective stimuli are insensitive to scope. The results establish that more is not necessarily better for pictures in advertising. Rather any benefits of additional pictures depend on whether the advertisement uses univalenced or oppositely valenced pictures and on whether advertisers measure feeling responses or liking responses.

References Chowdhury RMMI, Olsen GD, Pracejus JW. Affective responses to images in print advertising: affect integration in a simultaneous presentation context. J Advert 2008;37(3):7-18.

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Cohen JB, Pham MT, Andrade EB. The nature and role of affect in consumer behavior. In: Haugtvedt CP, Herr PM, Kardes F, editors. Handbook of consumer psychology. Mahwah (NJ): Lawrence Erlbaum; 2008. p. 297–348. Fredrickson BL, Levenson RW. Positive emotions speed recovery from the cardiovascular sequelae of negative emotions. Cogn Emot 1998;12(2):191–220. Hsee CK, Rottenstreich Y. Music, pandas, and muggers: On the affective psychology of value. J Exp Psychol Gen 2004;133(1):23–30. Linville PW, Fischer GF. Preferences for separating or combining events. J Pers Soc Psychol 1991;60(1):5-23. Malhotra NK. Attitude and affect: new frontiers of research in the 21st century. J Bus Res 2005;58(4):477–82. Mitchell AA, Olson JC. Are product attribute beliefs the only mediator of advertising effects on brand attitude? J Mark Res 1981;18(3):318–32.

Pham MT, Cohen JB, Pracejus JW, Hughes GD. Affect monitoring and the primacy of feelings in judgment. J Consum Res 2001;28(2):167–88. Pieters R, Wedel M. Attention capture and transfer in advertising: brand, pictorial and text size effects. J Mark 2004;68(2):36–50. Singh SN, Lessig VP, Kim D, Gupta R, Hocutt MA. Does your ad have too many pictures? J Advert Res 2000;40(1/2):11–27. Unnava HR, Burnkrant RE. An imagery processing view of the role of pictures in advertisements. J Mark Res 1991;28(2):226–31. Watson D, Tellegen A. Toward a consensual structure of mood. Psychol Bull 1985;98 (2):219–35.

Journal of Business Research 64 (2011) 7–11

Contents lists available at ScienceDirect

Journal of Business Research

The use of visual warnings in social marketing: The case of tobacco Karine Gallopel-Morvan a,⁎, Patrick Gabriel b, Marine Le Gall-Ely c, Sophie Rieunier d, Bertrand Urien b a

University of Rennes 1, IGR-IAE, CREM, 11, rue Jean Macé, CS 70803, 35708 Rennes Cedex 7, France University of Brest, IAE de Brest, ICI, 12, rue Kergoat, 29238 Brest, France c University of Rennes 2, ICI, 12, rue Kergoat, 29238 Brest, France d University of Paris Sorbonne, GREGOR, 21, rue Broca, 75005 Paris, France b

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Article history: Received 1 April 2009 Received in revised form 1 July 2009 Accepted 1 September 2009 Keywords: Social marketing Visual warnings Fear appeal Tobacco

a b s t r a c t Despite strong interest on the part of tobacco health practitioners, the effect of graphic warnings inserted on cigarette packs is unclear on several levels. First, the most effective themes for such messages have not been clearly identified by researchers. Second, no research has identified the ideal combination of self-efficacy and fear appeal warnings that should be inserted on cigarette packs, according to Protection Motivation Model principles. The exploratory study we conducted with French consumers to test the effectiveness of new graphic warnings proposed by the European Union in 2004 clearly demonstrates that visual messages, as opposed to text warnings, are more effective. This study also enabled us to identify the most effective themes of the European set: health warnings and social messages. Regarding future public health applications, if fear appeals are used, they need to be combined with self-efficacy and cessation support messages since they provoke avoidance reactions. © 2009 Elsevier Inc. All rights reserved.

1 . Introduction

2 . Literature review

Cigarette smoking is a major cause of premature death: tobacco use kills 5.4 million people a year and accounts for 1 in 10 adult deaths worldwide (www.who.int), while within the European Union it accounts for over half a million deaths each year. Since 2003, the World Health Organization has proposed the Framework Convention on Tobacco Control (FCTC) in order to decrease the number of smokers worldwide. The FCTC aims to help and guide countries in developing effective tools for tobacco control policies. In order to improve the effectiveness of tobacco prevention campaigns, the FCTC encourages use of graphic warnings on tobacco packs. More than 20 countries have introduced them: Canada, 2000, Brazil, 2002, Thailand, 2005, Belgium, 2006, UK, 2008, etc. Studies have been conducted to assess the impact of these visual warnings. Researchers have underlined the main objectives and basic principles for the elaboration of such messages, but their effects remain unclear on several levels. For example, the possible adverse effects of fear appeals or the most effective themes for such messages have not been clearly identified. The aim of the present study is to deal with these questions by determining the impact of new graphic warnings proposed by the European Commission since 2004 on French consumers and provide new insights in the field of social marketing.

Research on product warnings started in the eighties and most studies focus on the impact of textual and rational warnings (Cox et al., 1997, Argo and Main, 2004). The first scientific publication on pictorial tobacco warnings appeared in 2003 (Hammond, Fong, McDonald, Cameron and Brown) and was followed by other studies, mainly by public health researchers. These studies underline that graphic warnings are more effective than textual labels on cognitive and emotional reactions as well as behavioral intentions. Regarding cognitive reactions, graphic warnings are more visible (O'Hegarty et al., 2007; Hoek et al., 2005), easier to understand and increase awareness and knowledge of the health hazards of smoking (Hammond et al., 2006; Trasher et al., 2007). In the same way, graphic warnings proposed in Canada since 2000 are read by a great majority of smokers (Hammond et al. 2003) or make young people think about trying to quit smoking (Koval et al., 2005). As for emotional reactions, graphic labels activate responses that have an impact on behavior. Indeed, Hammond et al. (2004a), Crespo et al. (2007), Gallopel-Morvan et al. (2006) or Goodall and Appiah (2008) highlight that loss-framed graphic warnings generating emotions of fear, disgust, or anxiety have a positive impact on quitting, attempting to quit or reducing smoking. Finally, concerning behavioral intentions, graphic labels are more effective than texts in motivating smokers to quit (Kees et al., 2006), to help former smokers remain smoke-free (Hammond et al., 2004b; O'Hegarty et al., 2006) and to prevent non-smokers from starting (Sabbane et al., 2009a,b; Koval et al., 2005).

⁎ Corresponding author. E-mail addresses: [email protected] (K. Gallopel-Morvan), [email protected] (P. Gabriel), [email protected] (M. Le Gall-Ely), [email protected] (S. Rieunier), [email protected] (B. Urien). 0148-2963/$ – see front matter © 2009 Elsevier Inc. All rights reserved. doi:10.1016/j.jbusres.2009.09.012

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Despite these promising results in international research, the influence of graphic labels remains unclear on several points. First, Hastings et al. (2004); Ruiter and Kok (2001) and Stewart and Martin (1994) consider that insufficient attention has been paid to unintentional consequences of warnings and especially the possible adverse effects of fear appeal messages. Very few studies have dealt with this issue and their conclusions diverge: Peters et al. (2007) or Goodall and Appiah (2008) find no defensive reactions to graphic loss-framed and fear appeals on tobacco labels whereas Hammond et al. (2004a) find that 1% of smokers reported smoking more when seeing threatening visual warnings: 36% reported making some efforts to avoid the labels and 13% felt that the warnings were not credible. These defensive reactions are probably part of the fear control process highlighted by many researchers in social marketing and psychology (Witte and Allen, 2000). To prevent this problem, the Protection Motivation Model suggests combining the fear appeal with another message oriented toward the efficacy of the recommended response (i.e. “stopping smoking reduces the risk of fatal heart and lung diseases”) and self-efficacy (i.e. “the target's ability to perform the response”) (Tanner et al., 1991; Floyd et al., 2000). Applied to tobacco warnings, this means that if a fear appeal is inserted on one side of a cigarette pack, a message oriented toward self-efficacy or the efficacy of quitting must be inserted on the other side. No research to date has identified the ideal combination of positive and negative labels that should be inserted on cigarette packs. Secondly, while many studies on graphic tobacco warnings have concluded that visual labels in general are more effective than text messages on persuasiveness variables, current literature is not conclusive in terms of which graphic warnings are the most suitable and effective: health warnings, social messages, physical safety messages, etc. However, themes in antismoking media messages differ significantly in effectiveness (Devlin et al., 2007; Smith and Stutts, 2003). For instance, Pechmann et al. (2003) identify that normbased appeals were the most effective on teenagers. Regarding tobacco warnings, very few studies have dealt with this issue. Hoek et al. (2005), Trasher et al. (2006) and Crespo et al. (2007) underline that health and physical well-being messages (lung tumor, cancer of the larynx, yellow teeth, open heart surgery) and/or social messages (healthy children in reference to the dangers of second-hand smoke, a dead fetus in a specimen jar) seem to be the most effective warnings. Thirdly, studies on effectiveness of visual warnings in countries other than Canada or the USA are very limited (Crespo et al., 2007; Gallopel-Morvan et al., 2006). Yet some authors find cultural differences with respect to the meaning of visual symbols in advertising (Mikhailitchenko et al., 2009), anti-tobacco media campaigns (Laroche et al., 2001) and tobacco graphic warnings (Sabbane et al., 2009a,b). Considering the cultural differences between France, Canada and USA underlined by Hofstede (1983), reactions of French people toward graphic warnings may not be the same as in these countries. Given all these limitations, the present research aims to explore the way French people consider graphic or textual messages on cigarettes packs, especially loss-framed messages, self-efficacy warnings or a combination of these. The intentional and unintentional consequences of threat appeal messages will also be explored as well as the reactions toward the different themes proposed by the European Union in the new graphic warnings. 3 . Methodology In France, like most European countries, current warnings are only texts and cover 30% of the front of cigarette packs and 40% of the back. The front pack warnings are “smoking kills” or “smoking seriously harms you and others around you” and the back of the pack must contain one of 14 other text warnings. Since October 2004, the European Union has developed 42 new visual warnings that may be

voluntarily used by member states in addition to the two existing text warnings for the front of the pack. These illustrations concern different problems (health, sexual, social or physical and cessation support messages). Belgium was the first European country to adopt these labels in December 2006 and the UK and Romania introduced them in 2008. In order to achieve our research goals, new European graphic warnings were tested on French people. This study was funded by the French National Cancer Institute. A qualitative method was chosen to better identify effects and consequences of these new graphic labels. This method was also chosen because it provides in-depth data. It is suitable for exploring attitudes, perceptions and reactions and is useful for evaluating complex phenomena such as how audiences process and make sense of messages in a social marketing context (Miles and Huberman, 2002). Six focus group discussions were conducted in Rennes, Paris and Brest (France) with a total of 50 people (26 smokers, 24 non-smokers, 25 women, 25 men). Each group was composed of 7 to 9 individuals. Non-smokers were included in the sample since, according to social cognitive theory, they can influence smokers, and warnings can help them refrain from or not start smoking. People from age 15 to 46 were interviewed because they are a target group for French health practitioners. Indeed, they are heavy smokers compared to the general population (40% vs. 30%). Group discussions lasted about 2 h. The materials for the focus groups were divided into 3 sets (see Table 1): 3 real Marlboro packs (the leading brand in France) with different warnings (current French texts and/or new European messages), 12 new European visual warnings that address different smoking problems and 2 new European warnings on cessation support. These 14 graphic labels were selected among the 42 messages proposed by the EU as they proved the most effective warnings according to a French survey implemented by the French National Institute for Health Prevention and Education in 2006 with a representative national sample. Based on these materials, the discussion was divided into several stages. Participants were first asked to give their opinion on the 3 Marlboro packs. Then, respondents were asked to express their feelings on the 12 new European negative visual warnings and the 2 cessation support messages. All discussions were video and audiorecorded. Verbatim accounts were transcribed and analyzed using thematic content analysis. The main themes and sub-themes defined provide insight into perceptions of these warnings.

4 . Results When comparing the 3 packs of Marlboro (materials in Set 1), participants said that pictorial warnings reached them more and were more effective than texts, which were overexposed (20 occurrences). Moreover, the pack of Marlboro with visual warnings was judged less attractive than the ones with verbal messages (17, more for people age 15 to 24). The warning with a picture of external cancer tumors inserted on 2 Marlboro packs provoked numerous reactions: negative (184, more for smokers, women and people 15 to 34 years old: lack of credibility of the picture, too shocking) and positive ones (105: it attracts attention, it ruins the attractiveness of cigarette pack, it is effective in preventing young people from smoking). This warning also provoked strong emotional responses (69 occurrences, more women and smokers: rough, harsh, frightening and shocking). The visual message “your doctor or your pharmacist can help you stop smoking” inserted on the back of one Marlboro pack generated fewer reactions. Some people perceived it as humane, educational and reassuring (24) whereas others considered it totally flat, invisible (10) and an ineffective way to help people quit smoking (9). Regarding the 12 new visual and loss-framed messages (materials in Set 2), people were first asked to individually write down their feelings (see Table 2 for results).

K. Gallopel-Morvan et al. / Journal of Business Research 64 (2011) 7–11 Table 1 Materials: tested packs and graphic warnings.

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Table 2 The most effective warnings and themes (materials in Set 2). Teeth and mouth

External tumor on the neck

Clean and dirty lungs

A man and a woman in a bed

A child with a mask

▪The most striking (20 respondents) ▪The most effective in preventing young people from smoking (18) ▪The most effective in motivating smokers to quit (11) ▪The most effective in preventing non-smokers from smoking (13)

▪The most striking (13)

▪The easiest to understand (22)

▪The most effective in preventing young people from smoking (13)

▪The one that solicited the most concern (17)

▪The easiest to understand (11)

▪The most credible (14)

▪The most effective in motivating smokers to quit (13) ▪The most effective in preventing non-smokers from smoking (15)

▪The most effective in motivating smokers to quit (14) ▪The most effective in preventing non-smokers from smoking (14)

During the ensuing discussion of these 12 warnings, some of them generated significantly more negative reactions than positive ones. The face of a woman and a skeleton (skin problems) provoked 9 positive reactions and 30 negative ones (more women, more smokers and more 15 to 24-year-olds). The main criticisms stemmed from a lack of understanding and the image, which was judged too beautiful. In the same way, the man and the woman in bed (sexual problems) generated 5 positive reactions and 27 negative ones (more among people from age 35 to 45): people did not feel concerned and the picture was not clear without the text. Conversely, warnings that resulted in more positive reactions than negative ones referred to social concerns. The child with a mask (46 positive reactions and 2 negative ones) and a baby in an incubator (20 positive reactions and 9 negative ones) were perceived as relevant, credible and important. Warnings that provoked the strongest fear appeal reactions were the picture of teeth and mouth (18) and external tumors on the neck (16). Like reactions to the tumor discussed above, attitudes toward the picture of mouth and teeth were also extremely mixed. While this warning was seen as addressing a tangible problem and effective on young people (24 occurrences), it was also perceived as not credible and highly exaggerated (31). Reactions to the 2 cessation support warnings (materials in Set 3) were more even. The message “get help to stop smoking: 0 825 309 310” (the French help line) with the two hands received a total of 70 positive reactions (more non-smokers) and 63 negatives ones (less for people age 25 to 34). Most people liked the number of the quit line (it is helpful, easy, practical and anonymous) and the visual of the joined hands that evoked support and help. Main criticisms also concerned the quit line, which was perceived as impersonal, and the visual, which was judged unclear. The warning “your doctor and your pharmacist can help you stop smoking” totaled 9 positive reactions and 40 negative ones (more women, more smokers and more age 35 to 45). It was perceived as more humane than a quit line, but the link between a doctor checking someone's blood pressure and tobacco use was not clear for many people. Moreover, some people considered that a doctor cannot help smokers quit smoking.

5 . Discussion and conclusion While previous research has identified the basic principles for enhancing the effectiveness of tobacco graphic warnings, the present study explores this topic further. Indeed, this work provides new academic contributions by adding external validity to the existing literature, by testing the use of fear appeals and self-efficacy messages in a product warning context, and finally by proposing some precise and efficient themes for prevention messages. First, this study reveals that French people no longer react to current text warnings because these messages are old and tired (they have been implemented in European countries since 2003). To deal with problems of overexposure, as in advertising (Scott and Solomon, 1998), and to improve effectiveness, tobacco warnings must be changed and a system of rotating messages must be developed to prevent weariness.

Secondly, this research highlights the added-value of illustrations and text above text-only messages in a social marketing and warning context. These results are in line with marketing studies. Indeed, research has demonstrated the positive impact of pictures introduced in advertising (Miniard et al., 1991; Unnava and Burnkrant, 1991; Childers and Houston, 1984). The elaboration likelihood model provides one explanation for the superiority of pictorial and textual over text-only messages (Petty et al., 1983). This model shows that people can be persuaded by the merits of the arguments in a message (central route of persuasion) or by factors around the central message and that generate emotion (picture, music, popular spokesperson…) (peripheral route of persuasion). Regarding pictorial warnings, both routes are activated (the peripheral route with the pictures and the central route with the text), thus, messages are perceived as more effective. Thirdly, while tobacco visual warnings in general appeared more effective than texts alone, strong differences were noted between the 14 messages tested. It is interesting to note that fear appeals, both health and socially oriented, were often cited as the most effective. Results on socially-oriented warnings are in line with TRA (theory of reasoned action, Ajzen and Madden, 1986; Finlay et al., 1997). This model predicts that people are more likely to adopt a behavior if they think a relevant group values the behavior (social norms). There is evidence that it is socially valued to protect children from secondhand smoke and to be a good lover. The findings are also consistent with fear appeal theory. Indeed, in their meta-analysis, Witte and Allen (2000) conclude there is a positive relationship between fear and effectiveness of a message. However, it is important to note that the fear appeals also provoked many defensive reactions. In order to prevent this problem, combination of a self-efficacy warning with a fear appeal was tested on a real pack of Marlboro. In spite of this association, numerous defensive reactions were observed. This result may be explained by the fact that French society has a strong score of uncertainty avoidance (86) compared to Canada (48) or the USA (46) (Hofstede, 1983). This means that French society is more rigid, inflexible and probably less open to changes and thus, more resistant towards new graphic tobacco warnings. The Extended Parallel Process Model can also explain this phenomenon of defensive reactions (Witte, 1998). The author proposed that when perceived efficacy and/or self-efficacy are inferior to a perceived threat, people feel unable to escape the threat and employ techniques that resolve dissonance crises and reduce the emotion of fear (defensive avoidance). The self-efficacy message with a doctor was probably unable to increase the smokers' self-efficacy. The same problems occurred with the message get help to stop smoking. As a result, it is recommended to re-write these two self-efficacy messages. Moreover, precise instructions on quitting smoking should be inserted in the pack of cigarettes to reassure smokers, as is the case in Canada (e.g. information on cessation programs, a quit line number or a website) and media campaigns with testimonials or advices on quitting may be necessary. The main negative reactions toward visual warnings were generated by the lack of credibility of some messages, the lack of links between pictures and texts or unclear visuals. As these problems may reduce the

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persuasiveness of warnings, some European labels need to be adapted and re-written before use. Regarding credibility, the mention of highly credible sources on visual warnings, like the World Health Organization or the European Union, may enhance the persuasive impact of messages (Gotlied and Sarel, 1991). While this research highlights results that can help develop more effective tobacco warnings, it remains limited due to its exploratory nature. Indeed, the effects of warnings were not measured on real behavior nor on a representative sample. Moreover, further research on warnings is also needed in other cultures and other fields of social marketing (e.g. alcohol prevention and food products in the context of obesity). Finally, studies on TMT (terror management theory) and risky behavior could also be integrated. These theories could help interpret contradictory results that offset the effect of fear appeal warnings (Shehryar and Hunt, 2005). Acknowledgments The authors thank the French National Cancer Institute for funding this research. The authors also like to thank Professor P-J Benghozi, the participants in the qualitative seminar organized by the FNEGE (Fondation Nationale pour l'Enseignement et la Gestion des Entreprises) and the reviewers of the 2009 La Londe conference for their helpful advice, which contributed to improving the quality of this article. References Ajzen I, Madden JT. Prediction of goal-directed behavior: attitudes, intentions and perceived behavioural control. Journal of Experimental Psychology 1986;22: 453–74. Argo JJ, Main KJ. Meta-analysis of the effectiveness of warnings labels. Journal of Public Policy and Marketing 2004;23(2):193–208. Childers T, Houston M. Conditions for a picture-superiority effect on consumer memory. Journal of Consumer Research 1984;11:643–54 Sept. Cox III EP, Wogalter MS, Stokes SL, Tipton Murff EJ. Do product warnings increase safe behavior? A meta-analysis. Journal of Public Policy and Marketing 1997;16: 195–204 Fall. Crespo A, Barrio A, Cabestrero R, Hernandez O. Cognitive processing and assessment of anti-smoking combined warning labels set by the European Commission: an empirical study with a Spanish sample. Clinica y Salud 2007;18(2):163–80. Devlin E, Eadie D, Stead M, Evans K. Comparative study of young people response to anti-smoking messages. International Journal of Advertising 2007;26(1):99-128. Finlay KA, Trafimow D, Jones D. Predicting health behaviors from attitude and subjective norms: between subjects and within-subjects analyses. Journal of Applied Social Psychology 1997;27:2015–31. Floyd DN, Prentice-Dunn S, Rogers RW. A meta-analysis of research on protection motivation theory. Journal of Applied Social Psychology 2000;30(2):407–30. Gallopel-Morvan K, Rieunier S, Dion D, Le Gall-Ely M, Debenedetti S. Impact des avertissements sanitaires dans la lutte contre le tabagisme : synthèse théorique et résultats d'une étude qualitative. Revue Française du Marketing 2006;26:7-25. Goodall C, Appiah O. Adolescents' perception of Canadian cigarette package warning labels: investigating the effects of message framing. Health Communication 2008;23 (2): 117–27. Gotlied JB, Sarel D. Comparative advertising effectiveness: the role of involvement and source credibility. Journal of Advertising 1991;20(1):38–45. Hammond D, Fong GT, McDonald PW, Cameron R, Brown SK. Impact of the graphic Canadian warning labels on adult smoking behaviour. Tobacco Control 2003;12: 391–5. Hammond D, Fong GT, McDonald PW, Brown KS, Cameron R. Graphic Canadian cigarette warning labels and adverse outcomes: evidence from Canadian smokers. American Journal of Public Health 2004a;94(8):1442–5. Hammond D, McDonald PW, Fong GT, Brown KS, Cameron R. The impact of cigarette warnings labels and smoke-free bylaws on smoking cessation. Evidence from former smokers. Canadian Journal of Public Health 2004b;95(3):201–4. Hammond D, Fong GT, McNeill A, Borland R, Cummings KM. Effectiveness of cigarette warning labels in informing smokers about the risks of smoking: findings from the

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Journal of Business Research 64 (2011) 12–17

Contents lists available at ScienceDirect

Journal of Business Research

Effects of age, need for cognition, and affective intensity on advertising effectiveness Jane McKay-Nesbitt a,⁎, Rajesh V. Manchanda b, Malcolm C. Smith b, Bruce A. Huhmann c a b c

Bryant University, College of Business, 1150 Douglas Pike, Smithfield, RI, 02917, United States Department of Marketing, I. H. Asper School of Business, University of Manitoba, Winnipeg, MB, Canada R3T 5V4 New Mexico State University, College of Business, MSC 5280, P.O. Box 30001, Las Cruces, NM 88003-8001, United States

a r t i c l e

i n f o

Article history: Received 1 April 2009 Received in revised form 1 July 2009 Accepted 1 September 2009 Keywords: Need for cognition Affective intensity Age Persuasion Involvement Recall

a b s t r a c t This paper explores how individual characteristics of age, need for cognition (NFC), and affective intensity (AI) interact with each other and with advertising appeal frames (i.e., rational, positive-emotional, negativeemotional) to influence ad attitudes, involvement, and recall. The mixed design study reveals that younger adults recall emotional messages, especially negative ones, better than rational ones, but recall does not differ for older adults across appeal frames. Older adults prefer rational and positive messages to negativeemotional messages but ad attitudes do not differ among younger adults across appeal frames. Finally, age interacts with AI, but not NFC, to influence ad responsiveness. Both age and AI influence ad attitudes such that older adults exhibit the most positive ad attitudes across all appeal frames. © 2009 Elsevier Inc. All rights reserved.

1. Introduction Consumers today are bombarded with marketing messages and the sheer abundance of these messages causes marketers to be increasingly concerned with advertising effectiveness. Consequently, researchers exploring advertising effectiveness have identified message framing as a factor contributing to persuasion (e.g., Chandran and Menon, 2004). How ad information is presented, or framed, influences consumers' willingness to attend to and remember ad content. Marketing messages can be framed in various ways (Bagozzi et al., 1999). For example, rationally-framed messages provide information to persuade through appeals to recipients' thoughts. Alternatively, emotionally-framed messages attempt to persuade through appeals to emotions. Emotional appeals can be further differentiated in terms of valence: positive (e.g., joy, warmth, happiness) or negative (e.g., fear, guilt, worry). Research shows that both thoughts and feelings contribute to advertising effectiveness (Edell and Burke, 1987). However, conditions under which thoughts versus positive or negative feelings are more important for advertising effectiveness are not fully understood. This research addresses this issue by exploring moderating effects of three

⁎ Corresponding author. E-mail addresses: [email protected] (J. McKay-Nesbitt), [email protected] (R.V. Manchanda), [email protected] (M.C. Smith), [email protected] (B.A. Huhmann). 0148-2963/$ – see front matter © 2009 Elsevier Inc. All rights reserved. doi:10.1016/j.jbusres.2009.09.013

specific individual differences on the relationship between message framing and ad effectiveness. Specifically, this work explores the interaction of age, need for cognition (NFC), and affective intensity (AI) with advertising message frames (positive-emotional, negativeemotional, and rational) to influence ad attitudes (Aad), ad involvement (Iad), and ad recall (Rad). This research both replicates and extends previous work. Involvement's inclusion extends Williams and Drolet's (2005) work on older adults. Consideration of positive and negative emotions, versus positive and negative information in ad appeals extends Zhang and Buda's (1999) work on NFC. Inclusion of involvement and recall extends Moore and Harris's (1996) work on AI. Finally, this work contributes to understanding factors that influence advertising effectiveness by exploring how previously identified moderators interact with each other (i.e., age and NFC, and age and AI) and with message appeal frames to influence ad attitudes, involvement, and recall. 2. Theoretical background 2.1. Emotional versus rational message frames and ad effectiveness Some researchers argue that informational properties of messages are more influential than emotions in generating positive attitudes (Holbrook, 1978). Other researchers contend that emotions can influence behavior independent of cognitions and accord greater importance to emotion's role in determining advertising effectiveness (Brown et al., 1998). Affective processes, however, are most likely to

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take precedence over cognitions for low-relevance attitudes and objects (Zajonc, 1984). Age also moderates the effectiveness of emotionally-framed advertising appeals. Older adults better like and recall emotional than rational appeals, whereas younger adults better like and recall rational than emotional appeals (Williams and Drolet, 2005). Together, these findings suggest that, under low-involvement conditions, emotionally-framed appeals will be more effective than rationally-framed ones, especially for older than younger adults. Therefore, Hypothesis 1a. For low-involvement products, emotionally-framed ad appeals will produce more positive Aad, and greater Iad, and Rad than rationally-framed ad appeals. Hypothesis 1b. Age will moderate the effects of emotional appeals on Aad, and Iad, and Rad, such that the effects will be stronger for older than younger adults. 2.2. Positive- versus negative-emotion appeal frames The valence of ad-evoked feelings influences attitudes toward the ad and the brand. Some suggest that positive-appeal frames produce more favorable attitudes toward ads, and that positive emotions increase attitudes toward ads and brands, while negative emotions do the opposite (e.g., Edell and Burke, 1987; Cotte et al., 2005). However, both the mood as information hypothesis (Schwarz and Clore, 1988) and the mood repair hypothesis (Isen, 1984) propose that cognitive elaboration is greater when negative emotions predominate, suggesting that negative ad frames will be more effective than positive ones in influencing Aad. Indeed, negative emotions cause consumers to process information effortfully and systematically (Keller et al., 2002). Together, these findings suggest that whereas a positive frame may cause one to like an ad, a negative frame that evokes greater elaboration, will generate greater Iad and Rad. Age also moderates the effectiveness of positive- versus negativeemotional appeals. Older adults are more likely than younger adults to attend to and remember emotionally meaningful information, especially positive information (Fung and Carstensen, 2003). However, older adults recall emotional appeals that focus on avoiding negative-emotional outcomes better than ones that focus on achieving positive-emotional outcomes (Williams and Drolet, 2005). Therefore, this study predicts an age by framing interaction. Specifically, Hypothesis 2a. Older adults will have more positive Aad, and greater Iad, and Rad when ads are framed positively versus negatively. Hypothesis 2b. Younger adults will have more positive Aad, and greater Iad, and Rad when ad appeals are framed negatively versus positively.

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Thus, although younger and older should not differ in NFC, this study predicts: Hypothesis 3a. An NFC main effect will produce more positive Aad, greater Iad, and Rad among higher- compared to lower-NFC individuals, regardless of the message recipient's age. Interestingly, positive and negative information equally persuades higher-NFC individuals, whereas negative information persuades lower-NFC individuals more than positive information (Zhang and Buda, 1999). Thus: Hypothesis 3b. NFC will interact with appeal framing such that rationally- versus emotionally-framed ad appeals will heighten Aad, Iad, and Rad of higher-, not lower-NFC individuals, regardless of age. 2.4. Affective intensity AI refers to the intensity or strength with which individuals experience both positive and negative emotions (Larsen and Diener, 1987). When individuals are exposed to positive-emotional appeals, higher-AI individuals exhibit more positive ad attitudes than lower-AI individuals (Moore and Harris, 1996). Higher-AI individuals also exhibit stronger emotional responses to ads than lower-AI individuals. They also experience higher levels of empathic involvement with ads (Moore and Homer, 2000). Therefore, Hypothesis 4a. AI will interact with appeal frames such that, higherAI individuals will have more positive Aad, and greater Iad, and Rad than lower-AI individuals, when ad appeals are framed emotionally versus rationally. The socioemotional selectivity theory suggests that older adults manage both experience and emotions to ensure positive-emotional outcomes and that emotionally meaningful information is more important for them than for younger adults (Carstensen et al., 2003). In addition, emotional intensity of negative emotions tends to decrease with age (Barrick et al., 1989). Therefore, Hypothesis 4b. Age will moderate the AI by appeal frame interaction on Aad, Iad, and Rad such that when higher-AI adults view emotionallyversus rationally-framed ad appeals, older adults will exhibit more positive Aad, and greater Iad, Rad than younger adults. Hypothesis 4c. An age by AI by appeal frame interaction will encourage the most positive Aad, and greater Iad, Rad among older adults when AI is higher, and appeal frames are positive versus negative. Hypothesis 4d. The three-way interaction will encourage the most positive Aad, and greater Iad and Rad among younger adults when AI is higher, and appeal frames are negative versus positive.

2.3. Need for cognition 3. Method NFC is the tendency of an individual to derive intrinsic enjoyment from engaging in effortful information processing (Cacioppo and Petty, 1982). Cacioppo et al.'s (1996) meta-analysis shows that in general, higher-NFC individuals better recall information, think more about substantive arguments in a persuasive communication, are less influenced by heuristic message cues, exhibit more positive attitudes toward stimuli requiring thought, and have attitudes that are more predictive of subsequent behavior than lower-NFC individuals. Thus, higher-NFC individuals should exhibit more positive Aad, and greater Iad, and Rad, than those with lower NFC. Additionally, higher-NFC individuals are expected to find ad appeals containing factual information more appealing and persuasive than messages containing emotional information. The weak negative relationship between age and NFC (Cacioppo et al., 1996) suggests that NFC is stable over time.

3.1. Study design Hypotheses were tested in a 2 (age: older versus younger) × 2 (AI: higher versus lower) × 2 (NFC: higher versus lower) × 3 (appeal frame: rational, negative-emotional, or positive-emotional) mixed design with age, AI, and NFC as between-subjects factors and appeal frame as a within-subjects factor. 3.2. Participants Older participants were recruited from community groups and younger adults from a North American university where they received course credit in return for participation. One hundred and fifty-one

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younger (51 % female, median age = 20, age range 18–36) and 124 older adults (68% female, median age = 70, age range 48–89) participated in the study. 3.3. Stimuli Ads were created for orange juice, milk, and margarine. Three appeal frames were prepared for each product: positive-emotional, negative-emotional, and rational. All brands were fictitious and pictures in the ads were consistent for each product type. Ad text was manipulated to evoke different emotions. The rationally-framed appeals focused on factual information about the product. Positivelyframed appeals focused on warm emotions associated with using the product. The tone of the ad was optimistic and upbeat (MacInnis and Stayman, 1993). Negatively-framed appeals focused on problems resulting from not using the product. Ad copy was extensive; words ranged from 126–138 for the margarine ad versions, 158–160 for milk, and 162–176 for orange juice. The number of idea units ranged from 54 to 95 per appeal. Ads were matched in terms of likeability and text in all ads was matched for word count, vocabulary, and reading level.

3.6. Individual difference variables 3.6.1. Affective intensity (AI) Affective intensity was assessed with Larsen's (1984) 40 six-point item Affective Intensity Measure (AIM) with end points of never and always. Confirmatory factor analysis (CFA) of the 40 indicator, singlefactor AIM construct indicated a poor fit to the data: CFI .459; NNFI .430; RMSEA .094 (.091, .097); and χ2 3317, df = 740, p < .05 (Kline, 2005). Some researchers suggest that AIM is more appropriately a three-factor construct and that 27 of the 40 questions should be used as indicators (Bryant et al., 1996). A CFA of this 27 item construct revealed an improved fit: CFI .798; NNFI .779; RMSEA .068 (.063, .073); and χ2 905.23, df = 321, p < .05. The reliability of the 27-item measure was acceptable (α = .89), all of the factor loadings were significant, and the index was retained for use in the analysis. A median split on AIM scores (median = 4.3) divided participants into higher- and lower-AI groups. A comparison of AIM score means revealed differences between the two groups (Mlow = 3.8, Mhigh = 4.8, F(1, 274) 468, p < .00).

Participants read an ad for each of the products. The appeal-type differed for each product seen by the participants and thus each participant was exposed to all three appeal frames. Product and appeal frame, as well as presentation order were counterbalanced to create nine product–appeal frame–order combinations. Participants were randomly assigned to one of these nine conditions. Participants read each ad at their own pace and first wrote everything they could recall and then a summary statement about each ad. Participants then responded to a series of questions about the ads, including three manipulation check items. The questionnaire concluded with items to assess AI, NFC, education, age, gender, and language spoken at home.

3.6.2. Need for cognition (NFC) This study used the frequently cited, 18-item version of the NFC scale (Cacioppo et al., 1996). Questions were anchored with end points disagree (1) to agree (9). The CFA indicated that the 18-item, single-factor NFC construct did not fit the data well: CFI .728; NNFI .692; RMSEA .080 (.072, .087); and χ2 464.23, df=135, p<.05. As a result, modification indices were reviewed, questions were examined for face validity, and factor loadings were evaluated. All indicators with loadings less than .5 were removed. The modified 8-item construct was then tested and results indicated an improved fit and an acceptable model. Although the χ2 value was still significant, the values of the fit indices were substantially improved: CFI .896, NNFI .855, and RMSEA .091. As factor loadings were significant at the .05 level and α=.84, the eight-item measure was retained for this analysis. A median split on NFC scores (median=5.6) divided participants into higher- or lower-NFC groups. Comparison of NFC score means revealed differences between the two groups (Mlower =4.6, Mhigher =6.7, F(1, 274) 431, p<.001).

3.5. Dependent variables

3.7. Covariates

3.5.1. Ad recall Participants completed an open-ended recall protocol for each ad. The researchers had previously identified discrete phrases (idea units) for each product–appeal frame combination. Recall scores increased with the proportion of idea units participants recorded. Recalled idea units were considered to be correct as long as the participant recorded the gist of the idea unit (Adams et al., 1997).

Because verbal ability is a known correlate of text-memory performance and a measure of cognitive capacity, verbal ability of participants was assessed with the short-form of the WAIS vocabulary test (Jastak and Jastak, 1964).

3.4. Procedure

4. Results 4.1. Preliminary analyses

3.5.2. Involvement toward the ad Participants completed a three-item involvement scale, adapted from the Personal Involvement Inventory (Zaichkowsky, 1985), for each ad. The nine-point scale items had end points of: not at all meaningful/very meaningful, not at all relevant/ very relevant, of no interest at all/of interest to me. The items for each ad were averaged to create a single score with acceptable internal validity for each product type (αorange juice = .88, αmilk = .87, αmargarine = .91) and for each ad appeal-type (αrational = .89, αnegative = .89, αpositive = .91).

4.1.1. Cognitive capacity controls Attempts were made to control for participants' cognitive capacity. Because younger participants were university students, the analysis excluded older adults who had not completed high school. Analysis also excluded participants who did not commonly speak English at home. Analysis of Variance (ANOVA) revealed no differences between older and younger adults' vocabulary scores (Myounger = 23.3, Molder = 22.5, F(1, 274) 1.18, p = .28). For parsimony, subsequent analyses excluded verbal ability.

3.5.3. Attitude toward the ad Nine-point semantic differential items, adapted from the Attitude Toward the Ad (Overall) scale (Mitchell and Olson, 1986), measured attitude: good/bad, like/dislike, favorable/unfavorable. The scores were averaged to create a single score with acceptable internal validity for each product type (αorange juice = .93, αmilk = .93, αmargarine = .95) and ad appeal-type (αrational = .92, αnegative = .94, αpositive = .95).

4.1.2. Manipulation check Three nine-point items measured manipulation effectiveness of each ad: the ad could best be characterized as one using a positive rather than a negative approach, the ad focused on bad or frightening outcomes, the ad was designed to create negative feelings. End points were anchored with disagree and agree. The first item was reverse-scored. Combined scores formed a manipulation check of the appeal frame used in the ad.

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Analyses of manipulation check indices revealed acceptable internal validity: αorange juice = .78, αmilk = .75, αmargarine = .78. The manipulations were effective. The ANOVA with manipulation score as the dependent variable and ad-appeal frame as the factor, revealed a main effect for all three products (orange juice: F(2,397) =39.65, p < .001; milk: F(2,396) = 45.36, p < .001; margarine: F(2,396) = 61.92, p<.001). Post hoc tests revealed that negative ads for all products were viewed as significantly more negative than positive ads (orange juice: Mnegative =4.0, Mpositive =2.5, F(1, 266) =44.31, p<.001; milk: Mnegative = 5.1, Mpositive =3.2, F(1,263) =56.62, p<.001; margarine: Mnegative =5.2, Mpositive =2.8, F(1,262) =113.01, p<.001), and significantly more negative than rational ads (orange juice: Mnegative =4.0, Mrational =2.4, F(1,263) = 56.05, p < .001; milk: Mnegative = 5.1, Mrational = 3.1, F(1,262) = 60.61, p < .001; margarine: Mnegative = 5.2, Mrational = 3.5, F(1,266) = 49.68, p<.001). 4.2. Hypotheses tests H1a and H1b predicted that both older and younger adults would have more positive Aad, and greater Iad, and Rad of emotionally- versus rationally-framed ad appeals, and that these effects would be stronger for older adults. A repeated-measures multivariate analysis of variance (MANOVA) with Aad, Iad, and Rad as dependent measures, age as a between-subjects factor, and appeal frame as a withinsubjects factor revealed an age by appeal frame interaction (λ = .88, F(6,237) = 5.51, p < .001) as well as main effects for age (λ = .38, F(3,240) = 129.97, p < .001) and appeal frame (λ = .87, F(6,237) = 5.71, p < .001). Further analysis using paired-sample t-tests to compare positive- and negative-appeal frames with rational-appeal frames revealed that younger adults recalled more idea units when they read an emotional- versus a rational-appeal frame (Table 1). However, emotional appeals did not generate more positive Aad or greater Iad in younger adults. In comparison, older adults did not differ in Iad or Rad across appeal frames. However, older adults had more positive Aad toward rational-appeal frames than negative-appeal frames, but they did not differ in their Aad toward rational- versus positive-appeal frames. Thus, results partially supported H1a and H1b. Paired-sample t-tests used to test H2a and H2b revealed that older adults had significantly more positive Aad when they read a positiveversus a negative-appeal ad (Table 1). However, although positive appeals produced better Rad and greater Iad than negative appeals for older adults, differences were not significant. As expected, for younger adults, Rad recall was greater for negative- than positive-emotional

Table 1 H1: Emotional versus rational appeals on ad response by age. Mrational Younger adults

Older adults

Recall

.16

Mnegative .21⁎

Mpositive .18⁎

Involvement

4.03

4.09

3.83

Attitudes

5.43⁎⁎

5.14

5.18

Recall

.07

.06

.07

Involvement

5.16

5.07

5.14

Attitudes

6.34⁎⁎⁎

5.92

6.27

⁎⁎⁎ p < .001. ⁎⁎ p < .01. ⁎ p < .05.

t(df) Mpos-rat t(148) = 2.17⁎ Mneg-rat t(147) = 6.93⁎⁎⁎ Mneg-pos t(150) = 3.10⁎⁎ Mpos-rat t(150) = 1.42 Mneg-rat t(150) = .41 Mneg-pos t(152) = 1.89 Mpos-rat t(149) = 1.34 Mneg-rat t(149) = 1.79 Mneg-pos t(151) = .44 Mpos-rat t(111) = .05 Mneg-rat t(112) = 1.17 Mneg-pos t(107) = 1.06 Mpos-rat t(122) = .22 Mneg-rat t(121) = .77 Mneg-post(122) = .63 Mpos-rat t(117) = .76 Mneg-rat t(115) = 2.25 Mneg-pos t(117) = 2.48⁎

15

appeals. Similarly, younger adults exhibited marginally greater Iad with negative- than positive-emotional appeals (p = .062). However, viewing positive- or negative-appeal ads resulted in no differences in Aad for younger adults. Thus, results partially supported H2a and H2b. H3a predicted that, compared to lower NFC, higher NFC would result in more positive Aad, and greater Iad, and Rad in both older and younger adults. H3b predicted that higher-NFC individuals would have more positive Aad, and greater Iad, and Rad of rational than emotional ads, regardless of age. The repeated-measures multivariate analysis of covariance (MANCOVA) with Aad, Iad, and Rad as dependent measures, age group as a between-subjects factor, appeal frame as a withinsubjects factor, and NFC as a covariate, revealed that NFC was not related to Aad, Iad, or Rad (λ = .99, F(3,238) = 1.02, p = .39), nor did NFC interact with appeal frame (λ = .12, F(6,235) = .99, p = .99). A repeated-measures MANOVA with Aad, Iad, and Rad as the dependent measures, age and NFC (higher/lower) as between-subjects factors, and appeal frame as a within-subjects factor also revealed that NFC was not related to Aad, Iad, or Rad (λ = .98, F(3,236) = 2.03, p = .11), nor did NFC interact with appeal frames (λ = .10, F(6,233) = .11, p = .10) or age (λ = .10, F(3,236) = .28, p = .10). A follow-up, repeated-measures MANOVA with Aad, Iad, and Rad as dependent measures, NFC as a between-subjects factor, and appeal frame as a within-subjects factor, indicated a main effect for NFC on Aad, Iad, and Rad (λ = .96, F(3,239) = 3.21, p < .02). Thus, results supported H3a. Follow-up ANOVAs for each appeal frame with Aad, Iad, and Rad as dependent measures and NFC as the factor, revealed an NFC by appeal frame interaction for Rad. Compared to lower, higher NFC increased recall of positive-emotional- but not rational-appeal ad appeals (Table 2). Results did not support H3b. Under higher NFC, Rad increased with negative - (Mnegative = .15, Mrational = .13; t(131) = 4.0, p < .001) and positive-emotional (Mpositive =.14, Mrational =.13; t(131) =1.98, p<.05) versus rational appeals. Under lower NFC, Rad increased only with negative-emotional versus rational appeals (Mnegative =.13, Mrational = .11; t(128) = 3.13, p < .002). Lower, but not higher NFC influenced Aad of rational versus emotional appeals: (lower NFC: Mnegative =5.42, Mrational =5.87; t136) =2.42, p<.02; higher NFC: t(131) =1.48, ns). H4a and H4b predicted that higher-AI individuals would be more persuaded by emotional-appeal appeals than lower-AI individuals and that these effects would be more pronounced among older adults. The repeated-measures MANCOVA with Aad, Iad, and Rad as dependent measures, appeal frame as a within-subjects factor, age group as a between-subjects factor, and AI as a covariate revealed that AI has an impact on Aad, Iad, and Rad (λ = .94, F(3,238) = 5.11, p < .01). A follow-up repeated-measures MANOVA with age and AI as between-subjects factors, appeal frame as a within-subjects factor, and Aad, Iad, and Rad as dependent measures indicated an AI by age interaction (λ = .96, F(3,230) = 3.46, p < .05) and main effects for both AI and age (AI: λ = .93, F(3,230) = 5.86, p < .001; age: λ = .38, F(3,230) = 126.84, p < .001). When age groups were combined, higher-AI individuals had more positive Aad and Iad than lower-AI individuals, regardless of appeal frame. However, AI did not affect Rad for any appeal frames (Table 3). Thus, results partially supported H4a as higher-AI individuals exhibited more positive

Table 2 H3: Need for cognition on ad response by appeal frame.

Involvement

Attitude

Recall

⁎⁎ p < .01.

Appeal frame

Lower NFC

Higher NFC

F-test

Rational Negative Positive Rational Negative Positive Rational Negative Positive

4.51 4.39 4.39 5.85 5.39 5.77 .11 .13 .12

4.60 4.66 4.48 5.80 5.51 5.61 .13 .15 .14

F(1,271) = .24 F(1,274) = 2.4 F(1,275) = .22 F(1,271) = .04 F(1,271) = .23 F(1,270) = .53 F(1,266) = 3.23 F(1,267) = 3.43 F(1,266) = 8.23⁎⁎

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Table 3 H4a: Affective intensity (all ages) on ad response by appeal frame.

Involvement

Attitude

Recall

Appeal frame

Lower AI

Higher AI

F-test

Rational Negative Positive Rational Negative Positive Rational Negative Positive

4.25 4.26 3.92 5.52 5.08 5.10 .12 .14 .13

4.84 4.76 4.92 6.15 5.78 6.25 .11 .14 .12

F(1,267) = 10.73⁎⁎ F(1,267) = 6.48⁎ F(1,268) = 29.88⁎⁎ F(1,264) = 7.05⁎ F(1,263) = 7.19⁎ F(1,265) = 23.68⁎⁎⁎ F(1,259) = .14 F(1,260) = .63 F(1,259) = .64

⁎⁎⁎ p < .001. ⁎⁎ p < .01. ⁎ p < .05.

Aad and greater Iad than lower-AI individuals. Unexpectedly, these effects appeared with all appeal frames, not just emotional appeals. Separate repeated-measures ANOVAs for Aad, Iad, and Rad with appeal frame as a within-subjects factor and age and AI as betweensubjects factors, revealed an age by AI interaction for Aad (F(1,241), = 4.06, p < .05), but not for Rad (F(1,241), = 1.57, p = .21) or Iad (F(1,241), = 1.53, p = .51). A follow-up ANOVA with Aad as the dependent variable, appeal frame, age, and AI as between-subjects factors, revealed that higher-AIolder adults had more positive Aad toward all appeals than higher-AIyounger adults, regardless of appeal frame (Table 4). However, Aad did not differ between lower-AI-younger and older adults for any of the appeal frames. Similarly, higher-AI-older adults had more positive Aad toward all the ads than lower-AI-older adults. Higher-AI-younger adults also had more positive Aad toward positively-framed appeals than did lower-AI-younger adults. Thus, results partially supported H4b as higher-AI-older adults had more positive Aad toward emotionallyframed ad appeals than higher-AI-younger adults. In addition, however, higher-AI-older adults had more positive Aad than higher-AI-younger adults toward rationally-framed ad appeals. Higher-AI-adults prefer positive to negative ad appeals (Mpositive =6.3, Mnegative =5.8; t(127) =3.06, p<.003) whereas lower-AI-adults show no preference (Mpositive =5.10, Mnegative =5.10; t(133) =.10, p=.92). Both older- and younger-higher-AI adults prefer positively-framed ad appeals. Further analysis revealed that higher-AI-older adults had more positive Aad towards positive than negative appeals (Mnegative =6.3, Mpositive =6.8; t(67) =2.23, p<.03). Higher-AI-younger adults also had more positive Aad towards positive- than negative-emotional appeals (Mnegative =5.2, Mpositive =5.7; t(59) =2.08, p<.05). However, lower-AI-adults did not exhibit any Aad differences toward negative- or positive-emotional appeals (younger: t(84) =.77, ns; older: t(48) 1.31, ns). Thus, results supported H4c but not H4d. 5. Discussion This study has explored the moderating effects of age, NFC, and AI on the effectiveness of ad appeals that are framed emotionally versus rationally. Surprisingly, younger adults find emotional appeals more persuasive than rational appeals; they remember emotionally-framed appeals better than rationally-framed appeals. Interestingly, older adults develop more positive Aad when exposed to rational appeals than to negative ones. Older adults' preference for an informative ad over a negative ad is consistent with socioemotional selectivity theory (Carstensen et al., 2003) which suggests that older adults will respond more positively to rational, informational ads than to ones that evoke negative emotions. As expected, higher-NFC individuals, regardless of age, exhibited more Iad, Aad, and Rad overall than lower-NFC individuals. Surprisingly, when looking at each appeal frame separately, NFC effects were observed only for emotional appeals. Forced ad exposure likely encouraged a similar degree of processing among both lower- and

Table 4 H4c and H4d: Negative versus positive message frame on attitudes by affect intensity.

Lower AI Higher AI

Younger Older Younger Older

Mnegative

Mpositive

t(df)

5.06 5.13 5.19 6.29

4.85 5.50 5.66 6.77

t(84) = .77 t(48) = 1.31 t(59) = 2.08⁎ t(67) = 2.23⁎

⁎ p < .05.

higher-NFC individuals. A logical extension of the mood as information viewpoint (Schwarz and Clore, 1988) is that emotional appeals increase cognitive load required to process an ad (Huhmann, 2007). The current study's NFC findings support this idea. All ads had extensive copy. Lower-NFC individuals who possess less intrinsic motivation to tackle both an emotional appeal frame and long copy, showed similar recall for positive-emotional and rational ad appeals and difference in liking between emotional and rational ad appeals. Higher-NFC individuals, who possess more intrinsic motivation to overcome the high cognitive load of emotional information combined with long copy, recalled more of negative- and positive-emotional than rational ad appeals, likely due to increased central processing (Cacioppo et al., 1996). Although prior research found more positive Aad with positive- than negative-appeal frames (e.g., Cotte et al., 2005), which is consistent with the view of emotional-appeal frames influencing hedonic value or pleasure from ad processing (Huhmann, 2007), the current study places boundary conditions on the emotional-appeal–Aad link beyond NFC's previously discussed role. First, age matters; emotional-appeal frames influence Aad direction among older, but not younger, adults. Second, AI matters; emotional-appeal frames influence Aad direction among higher- but not lower-AI, adults. This study extends Moore and Harris' (1996) work on AI's effect on Aad with emotional television ad frames. The current data also revealed an interaction between AI and age. Regardless of appeal frame, higher-AI-older adults exhibited more positive Aad than higher-AI- younger adults. The current study's results make a case for revisiting Plutchik's (1982) theory that emotions are motivational in nature. Among higherAI individuals, especially older adults, positive- but not negativeemotional appeals increased Aad compared to rational appeals. Interestingly, positive-emotional appeals enhanced Rad for higher-NFC individuals. Results for lower-NFC individuals did not exhibit the same pattern. If emotions are general motivators, they should motivate regardless of AI or NFC. However, consistent motivational advantages of emotional versus rational appeals appear only among higher-AI and higher-NFC individuals. This study also explored the moderating effects of age, NFC, and AI on the effectiveness of emotional ad appeals that are framed with a positive versus a negative valence. As expected, older adults found positive appeals more persuasive (Aad) than negative appeals and younger adults found negative appeals more persuasive (Iad and Rad) than positive appeals. This increasing preference for positive- versus negativeemotional appeals with age is consistent with the socioemotional selectivity theory and explains age-related changes to emotional appeal effects documented previously (Burke and Edell, 1989; Cotte et al., 2005; Fung and Carstensen, 2003; Moore and Harris, 1996). As expected, no NFC–emotional valence relationship emerged. However, a relationship between AI and emotional valence demonstrated that both older- and younger-higher-AI adults exhibit more positive Aad when exposed to positive- than negative-emotional appeals. Marketers carefully frame advertising messages to evoke certain emotions. This study provides important information to help understand how these ad-evoked emotions influence individuals. Understanding the relationships between ad-evoked emotions and individual characteristics such as age, need for cognition, and affective intensity allows marketers to increase their advertising messages' effectiveness.

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However, the generalizability of these findings to other contexts, other media, and to known brands may be problematic. Although ads are commonly viewed within a context that evokes emotions (e.g., Brumbaugh, 2002), ads in this study were presented alone rather than being embedded in an editorial context. Additionally, although not unusual in many magazine contexts (e.g., Family Circle, Men's Health, Parenting, etc.), three ads for low-involvement food products were presented within a short time period. Furthermore, print ads for fictitious brands were employed to generate ad-evoked affect without the contaminating influence of prior brand exposure. However, effects for established brands may be different than those uncovered in this study. In conclusion, these findings draw attention to noteworthy individual characteristics (i.e., age, NFC, and AI) that moderate the effectiveness of emotionally- (positive or negative) and rationally-framed advertising appeals. Understanding how individual characteristics interact with adappeal framing should assist advertisers to design messages and researchers to understand persuasion. References Adams C, Smith MC, Nyquist L, Perimutter M. Adult age-group differences in recall for the literal and interpretive meanings of narrative text. Journal of Gerontology: Psychological Sciences 1997;52B(4):187–95. Bagozzi RP, Gopinath M, Nyer P. The role of emotions in marketing. J Acad Mark Sci 1999;27(2):184–206. Barrick AL, Hutchison RL, Deckers LH. Age effects on positive and negative emotions. J Soc Behav Pers 1989;4:174–80. Brown SP, Homer PM, Inman JJ. A meta-analysis of relationships between ad-evoked feelings and advertising responses. J Mark Res 1998;35(1):114–27 February. Brumbaugh AM. Source and nonsource cues in advertising and their effects on the activation of cultural and subcultural knowledge on the route to persuasion. J Consum Res 2002;29(2):258–70 September. Bryant FB, Yarnold PR, Grimm LG. Toward a measurement model of the affect intensity measure: a three-factor structure. J Res Pers 1996;30(2):223–47. Burke MC, Edell JA. The impact of feelings on ad-based affect and cognition. Journal of Marketing Research 1989;26(2):69–83. Cacioppo JT, Petty RE. The need for cognition. J Pers Soc Psychol 1982;42:116–31. Cacioppo JT, Petty RE, Feinstein JA, Jarvis WB. Dispositional differences in cognitive motivation: the life and times of individuals varying in need for cognition. Psychol Bull 1996;119(2):197–253 March. Carstensen LL, Fung HH, Charles ST. Socioemotional selectivity theory and the regulation of emotion in the second half of life. Motiv Emot 2003;27(2):103–23.

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Journal of Business Research 64 (2011) 18–23

Contents lists available at ScienceDirect

Journal of Business Research

The impact of word-of-mouth communication on attribute evaluation Boon C. Lim ⁎, Cindy M.Y. Chung Nanyang Business School, Division of Marketing and International Business, S3-01B-73, Nanyang Avenue, Singapore 639798, Singapore

a r t i c l e

i n f o

Article history: Received 1 April 2009 Received in revised form 1 July 2009 Accepted 1 September 2009 Keywords: Word-of-mouth communication Search attributes Credence attributes Services Attribute evaluation Media congruence hypothesis

a b s t r a c t Wright and Lynch (1995) propose that the medium that best communicates the type of attributes is the one most congruent with that type of information. This paper extends on this media congruence hypothesis by examining the impact of word-of-mouth (WOM) communication on the WOM recipient's ratings of search and credence attributes in two different service contexts. Results from two experiments suggest that negative WOM (but not positive WOM) is more effective in changing the evaluation of credence attributes than that of search attributes for unfamiliar brands. This finding implies that marketers of such unfamiliar brands need to have different approaches to deal with the impact of negative WOM on different attribute types. © 2009 Elsevier Inc. All rights reserved.

1. Introduction Even though marketers may not have control over WOM communication the way they do over other forms of marketing communication such as advertising and sampling, they still have the need to understand the impact of WOM and manage WOM well. However, the extant literature has only limited research on the impact of WOM on the recipient compared to research on the impact of marketing communication, such as advertising, on consumers (Bansal and Voyer, 2000). The current paper aims at enriching the literature in this direction. WOM is particularly important in service marketing due to the heterogeneity of service quality, the higher associated risk, and the intangible nature of services (Bansal and Voyer, 2000; Ekeland et al., 1995; Jolson and Bushman, 1978). But the effectiveness of such interpersonal influence may still depend on the nature of the specific attributes (e.g., the degree of information asymmetry) that the consumers are evaluating (Wagenheim and Bayón, 2004). This paper focuses on the distinction between search and credence attributes. A service may have one or both of the above types of attributes. For example, the price of a restaurant meal is likely to be a search attribute and the long-term health benefit of the meal is likely to be a credence attribute. In this paper, the authors investigate the differential impacts that WOM may have on consumer's evaluation of these attributes. Results from two experiments suggest that negative WOM (but not positive WOM) is more effective in changing ratings on credence attributes than on search attributes. These findings bring conceptual and managerial implications. Conceptually, the current research extends the media congruence ⁎ Corresponding author. E-mail addresses: [email protected] (B.C. Lim), [email protected] (C.M.Y. Chung). 0148-2963/$ – see front matter © 2009 Elsevier Inc. All rights reserved. doi:10.1016/j.jbusres.2009.09.014

hypothesis by studying the impacts of WOM on the evaluation of different types of service attributes. The results suggest that WOM (at least negative WOM) is more effective in communicating information about credence attributes because WOM is more congruent to credence belief communication. In terms of managerial implications, marketers of unfamiliar brands must have an understanding of how consumers may implicitly categorize different attributes into search and credence attributes. This understanding will allow marketers to identify attributes whose pre-purchase evaluations are more likely affected by negative WOM. These marketers will then be able to better manage and mitigate the possible impact of negative WOM on purchase decision.

2. Conceptual background and hypothesis development 2.1. WOM WOM is an informal mode of communication between noncommercial parties concerning the evaluation of products and services (Arndt, 1967). As WOM is a low cost and reliable way of transmitting information about products and services, WOM plays an important role in information diffusion in consumer markets and shaping consumers' attitudes (e.g., Brown and Reingen, 1987; Mizerski, 1982; Mourali et al., 2005). Consumers search for information from knowledgeable others, such as friends and relatives, to make more informed decisions (Berger, 1988; Jolson and Bushman, 1978). The information from relevant others is taken as evidence of reality (i.e., informational influence) (Deutsch and Gerard, 1955), supporting and/or adding to what the consumers already believe about some salient aspects of the products and services.

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2.2. Attribute types In the economics of information (EOI) literature, goods and services have been categorized as search, experience, and credence (Darbi and Karni, 1973; Nelson, 1970; Nelson, 1974). However, this classification may not always be appropriate, as many products and services consist of one or a combination of search, experience, and credence attributes (Ekeland et al., 1995; Sheffet, 1983). Therefore, a multi-attribute description of products and services seems more appropriate and realistic. Translated from the EOI literature, search attributes are attributes that consumers can accurately determine prior to product purchase; experience attributes are attributes that can only be evaluated after purchase or during consumption; and credence attributes are attributes that the consumers are unable to evaluate confidently even after purchase or consumption (Blankson and Kalafatis, 1999; Ford et al., 1990; Srinivasan and Till, 2002). For example, Babakus et al. (2004) classify various attributes for banking services into search, experience, and credence attributes. Search attributes include the interest rates on deposits and the banking hours. Experience attributes include the helpfulness of tellers and the timeliness of the provision of services. Credence attributes include the confidentiality of the customers' banking information and the integrity of the bank. The amount of information available to the consumers varies for the different types of attributes (Darbi and Karni, 1973; Nelson, 1974), with the highest amount of pre-purchase and post-purchase information available for search attributes and the lowest for credence attributes. Thus, the focus of this current research is on search and credence attributes in order to maximize the effect size of the expected differences. Consumers are able to acquire information on the performance of search attributes easily and confidently from secondhand sources, such as advertising, prior to purchase (Hsieh et al., 2005; Wright and Lynch, 1995). As search attributes are relatively unambiguous and difficult for marketers to get away with making inaccurate claims (Nelson, 1974), consumers are the least skeptical of such marketers' claims (Ford et al., 1990). In contrast, claims about performance on credence attributes cannot be verified even after purchase or immediate consumption (Ekeland et al., 1995; Nelson, 1974), because consumers do not have the technical expertise or resources to do so (Sheffet, 1983). As the information asymmetry between buyers and marketers for credence attributes may create strong incentives for the sellers to cheat (Emons, 1997), consumers are highly skeptical of marketers' claims about credence attributes. Therefore, consumers are likely to seek alternative information sources that do not have any ulterior motive (Friestad and Wright, 1994). Consumers may have come to rely on WOM from a trusted source as one of the few ways to help them evaluate credence attributes. In the absence of diagnostic information on credence attributes to process, the consumers may use signals and/or heuristics to a greater extent to evaluate such attributes (e.g., “It must be good/bad because others whom I trust say so”) (Babakus et al., 2004; Srinivasan and Till, 2002; Sheffet, 1983).

2.3. Hypotheses Wright and Lynch (1995) propose a media congruence hypothesis under which the medium that best communicates the type of attributes is most congruent with that type of information. They find evidence that direct experience is more congruent with experience attribute belief communication, and advertising is more congruent with search attribute belief communication. Extending on their research, this paper examines the impact of WOM on the evaluation of search and credence attributes in two experiments. Following the logic of the media congruence hypothesis, this research proposes that WOM is more congruent with credence attribute belief communication as compared to search attribute belief communication.

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Consumers may rely less on WOM or direct experience for judging search attributes, as the credibility of the source matters less to enhance persuasion for search attributes (Jain and Posavac, 2001). Consumers are able to acquire information on the performance on search attributes prior to purchase from other sources (e.g., directly from marketers and retailers) easily at a low cost comparable to that of WOM. Moreover, WOM on search attributes is likely to be less reliable and accurate than that from the marketers and retailers, as this WOM is dependent on the memory of the WOM giver. As defined, consumers are normally unable to assess the performance of credence attributes despite their direct experience with the product or service (Washburn et al., 2004). Consumers may then resort to signals and/or heuristics to evaluate credence attributes. When the characteristics of the focal object cannot be adequately assessed from direct observation and contact, the consumers may use the reactions of others towards the focal object as evidence about the unobservable characteristics of the object (Burnkrant and Cousineau, 1975). Moreover, WOM is generally perceived as trustworthy and credible by the consumers, because WOM is based on the experiences of other consumers who are independent of the marketers (Bansal and Voyer, 2000; Mourali et al., 2005; Smith et al., 2005). Therefore, consumers may rely more on the position advocated in the WOM as an important informational cue (rather than direct experience or advertising) to form their evaluation on credence attribute of an unfamiliar brand. With a familiar brand, consumers may still rely on the brand name as a signal of quality. For an unfamiliar brand, WOM is predicted to have a higher impact on the evaluation of credence attributes than on the evaluation of search attributes. H1. The impact of WOM on attribute evaluation will be higher for credence attributes than for search attributes. WOM normally contains positive and/or negative evaluations on products discussed (Smith et al., 2005). Furthermore, WOM is an important, common, and realistic source of negative information of brands, as engaging in WOM is one of the main ways consumers use to express dissatisfaction (Smith and Vogt, 1995). In the extant literature, negative information is commonly believed to have a greater influence on a decision maker than positive information. Such a negativity effect (i.e., the greater weighing of negative as compared with equally extreme positive information in the formation of overall evaluations) appears to be a well-proven phenomenon in consumer psychology (Ahluwalia, 2002). Negative information has been found to be more credible and diagnostic than positive information (Herr et al., 1991). Negative WOM has also been found to be a stronger influence on customers' brand evaluations than positive WOM (e.g., Mizerski, 1982). Therefore, consistent with the current literature, H2. The impact of negative WOM on attribute evaluation will be greater than that of positive WOM. As suggested before, the incentive for marketers to misrepresent information is higher for credence attributes than for search attributes. As the ambiguity of attribute evaluation and the risk from a lack of information and knowledge increase, WOM becomes a more important source of information to the consumers (Bansal and Voyer, 2000; Hsieh et al., 2005). Increased perceived risk may increase the saliency of the diagnosticity and credibility of the information that can help consumers to avoid some negative consequences that marketers' opportunistic behaviors can bring. Since negative WOM is more diagnostic and credible than positive WOM, the increase in its impact from search to credence attributes ought to be greater than the increase brought about by its positive counterpart. Therefore, H3. The expected increase in the impact of WOM from search to credence attributes will be greater for negative WOM than for positive WOM.

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3. The present research 3.1. Overview and participants The type of attributes (search vs. credence) and valence of WOM (positive vs. negative) were manipulated between-subjects in two experimental studies to test the hypotheses. The subjects considered the two chosen contexts (i.e., travel and consumer banking) to be relevant to them as consumers. The subject pool included undergraduate students from a major university in Singapore. Subjects (n = 107) in Experiment 1 were given course credits for their participation and subjects (n = 96) in Experiment 2 were paid 6 SGD (1 SGD = 0.68 USD) each.

After the filler task, the subjects read a WOM scenario, which included the manipulation of WOM valence and attribute type. Focal attributes and some peripheral information about the travel destination were included in the scenario. An example of the Negative WOM/Search Attribute condition is as follows (the parts in italics were not included in the scenario presented to the subjects): “You want to know more about Belize? Oh sure, I went to Belize last year. Well, there are various attractions such as ancient temples, forests and mountain ranges. I also got a chance to swim with the stingrays and sharks at the Shark Ray Alley. However, the cost of accommodation (search attribute 1) was really high (negative). The cost of traveling to and from Belize (search attribute 2) was also really high (negative). By the way, the majority of the locals do speak English, so communication wasn't an issue. I also did some shopping over there and got some interesting local products. Perhaps I should show them to you someday.”

3.2. Experiment 1 3.2.1. Procedure and measurements This experiment put the subjects in the context of considering Belize as a travel destination. A pretest with 15 subjects that were different from those participating in the experiment indicated that only 13.3% of them had heard of Belize as a country. Moreover, general impression on Belize as a travel destination is fairly neutral. The use of unknown and neutrally rated brand names can help to maximize the impact of interpersonal influence such as WOM and avoid any possible biases and prior impressions the subjects might have (Zemborain and Johar, 2007). The pretest subjects gave a mean rating of 4.3 on a seven-point scale from very negative (1) to very positive (7). They were also asked to list all the important attributes for them to choose a travel destination. A second pretest (n = 15) was conducted to identify search and credence attributes. A list of attributes was first generated through discussion based on the responses from the first pretest. The pretest subjects in the second round were asked to categorize these attributes into search, experience, and credence attributes, and rated their importance. Subjects in the pretest were also given the definition of search, experience, and credence attributes and asked to categorize each of the attributes into the three types. The purpose was to identify two focal attributes each for search and credence conditions. Attributes that were categorized in one type for at least 60% of the time were chosen for the experiment. The four resulting attributes were Cost of the Accommodation (search), Cost of the Trip to and from Destination (search), Likelihood of Terrorist Attack (credence), and Likelihood of Civil Unrest (credence). On a seven-point scale from totally unimportant (1) to totally important (7), the mean importance scores for the four chosen attributes range from 5.7 to 6.0. Subjects in the experiment were randomly assigned to one of the four conditions in a laboratory setting. They were asked to imagine that they were considering Belize as their travel destination. They were first given a general description of Belize as follows: The capital of Belize is Belmopan. Most visitors travel to Belize by air but visitors can also get there by road or sea. Visitors to Belize are required to apply for Visa and are permitted to stay in Belize for a period not exceeding 30 days. Even though the currency used in Belize is the Belize Dollar (BZ$), most hotels, resorts, restaurants and tour operators do accept U.S. currency, traveler's checks and major credit cards. Then they were asked to rate the focal attributes (i.e., attributes from the attribute type to which they had been assigned) and other attributes (i.e., attributes that were focal for subjects in other conditions) on four seven-point scales (Cost of the Accommodation: very low/very high; Cost of the Trip to and from Destination: very low/ very high; Likelihood of Terrorist Attack: very low/very high; and Likelihood of Terrorist Attack: very low/very high). All the attributes were reverse-scored for higher scores to indicate more positive evaluations. These ratings formed the baseline against which the post-WOM ratings were compared. The rating task was followed by a filler task.

The peripheral information made the WOM scenario more realistic and was available in all conditions. This peripheral information was presented as neutral sounding as possible. The two focal attributes were always presented in the middle of the WOM message and were positively or negatively phrased depending on the condition. All the statements used for describing the different focal attributes are presented in Table A1 in Appendix A. Subjects rated the focal attributes again after reading the WOM scenario. Subjects also filled out various items (e.g., involvement and the importance of the attributes) to check for their likely effects on the main dependent variable. For the manipulation check, the subjects categorized the various attributes into search, experience, and credence attributes. Finally, the subjects wrote down their thoughts about the purpose of the study. The experimenter then thanked and dismissed them.

3.2.2. Results and discussion Analysis on the change scores for each of the attributes (i.e., the difference between the post-WOM and pre-WOM ratings) shows that the WOM valence manipulation is effective. For subjects who read negative WOM, one-sample t-tests show that the means of their untransformed attribute rating change scores are significantly different from zero in the negative direction for each of the four attributes (all ps < 0.001). Another series of one-sample t-tests confirm that the mean of the change scores from those reading positive WOM are significantly different from zero in the positive direction (all ps < 0.001). In contrast, the manipulation of attribute type is only marginally effective for the two credence attributes (Table 1). This issue will be discussed later in this section. Also, no subject was able to guess the overall objectives or the hypotheses of the experiment. In order to compare the impact of negative WOM and positive WOM, analyses were done on the absolute value of the change score

Table 1 Categorization of attributes by subjects in Experiment 1a. Type of attributes

Credence (%)

Cost of the accommodation 1.9 (n = 53) Cost of the trip to and back from 3.8 the destination (n = 53) Likelihood of terrorist attack 57.4 (n = 54) Likelihood of civil attacks 46.3 (n = 54) a

Experience (%)

Search (%)

Not sure (%)

1.9

96.2

–

13.2

83.0

–

7.4

27.8

7.4

9.3

40.7

3.7

These percentages include only subjects who rated the specific focal attribute.

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of the attribute ratings. Other analyses including covariates such as involvement and attribute importance did not yield significantly different results. These additional analyses are not presented in this paper. The main analysis was done using the Linear Mixed Models (LMM) module in SPSS and the parameters of the model was estimated with the restricted maximum likelihood estimation algorithm. The individual attributes were nested within the corresponding attribute type (i.e., search and credence). This analysis strategy was adopted instead of averaging the change scores of the different attributes rated by the same subject, because preliminary correlational analyses indicate that averaging the change scores of the focal attributes in the same condition is not appropriate. The readers should note that LMM module in SPSS applies corrections for random effects and multiple levels that result in fractional values for the degrees of freedom for the denominator (Tabachnick and Fidell 2007). However, the presentation of the denominator degrees of freedom in this paper is rounded to the nearest integer. The attribute type main effect is significant (F(1,103) = 8.44, p < 0.01). The marginal mean of Search Attribute is lower than that of Credence Attribute (Table 2), thus supporting Hypothesis 1. The significant interaction effect (F(1,103) = 8.34, p < 0.01) and individual cell means indicate that the relationship under Negative WOM is significantly steeper than that of the relationship under Positive WOM. Additional post-hoc analyses show that the cell mean of Search Attribute is significantly lower than that of Credence Attribute for Negative WOM. The cell means do not differ significantly under Positive WOM. Hence, these results support Hypothesis 3. The WOM valence main effect is significant (F(1,103) = 4.69, p < 0.05), but the marginal mean for Positive WOM (M = 1.9) is greater than that of Negative WOM (M = 1.5). Thus, Hypothesis 2 is not supported. The unexpected result for Hypothesis 2 may have been due to the context used in Experiment 1. Recent research has found that some factors attenuate the negativity effect (Ahluwalia, 2002). For example, Laczniak et al. (2001) find that negative WOM decreases brand evaluation only when the WOM recipients attribute the negativity of the message to the brand and not to the WOM giver. In Experiment 1, the subjects might have attributed the negative WOM to the WOM giver rather than Belize as a travel destination. The subjects were likely to have made this attribution in this context, because the performance of some of the attributes would depend on the choices the WOM giver made. For example, the attribute of Cost of the Accommodation depends on the service provider that the WOM giver chooses. Therefore, the context for Experiment 2 was chosen to be less dependent on the choices made by the consumers. A large proportion of the subjects still considered the credence attributes as search attributes (Table 1). An additional analysis without these subjects shows results that are consistent with the conclusions drawn from the results of the main analysis. However, the subjects might have perceived the search and credence attributes to be different on some other dimensions. Thus, a more stringent criterion was adopted for the choice of attributes to be used in Experiment 2. Industry experts and academics have also categorized these chosen attributes as search and credence attributes.

Table 2 Statistics for change in attribute rating in Experiment 1. Attribute

Marginal mean of absolute value of change score

Cell mean of absolute value of change score for NWOM

Cell mean of absolute value of change score for PWOM

Search Credence

1.4 (53, 0.13)a 2.0 (54, 0.13)

1.0 (26, 0.18)b 2.0 (27, 0.18)b

1.9 (27, 0.18) 1.9 (27, 0.19)

a

Cell size, standard error of the mean). The individual cell means with the same superscripts are significantly different from each other, after adjusting for multiple comparisons using Bonferroni procedure with the overall error rate at 0.05. b

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3.3. Experiment 2 3.3.1. Procedure and measurements The context of consumer banking services was used in Experiment 2. The scenario in Experiment 2 focused on a choice situation, whereby the subjects were to consider a single type of financial service from a single service provider. In this scenario, consumers are more likely to attribute any negative information about the service quality to the service provider rather than the WOM giver. In several exploratory interviews with students from the subject pool, all of the subjects identified the savings account as the most relevant financial service to them. All of the pretest subjects also indicated that they had at least one savings account (n = 25). Subjects in the main experiment were asked to imagine that they were considering opening a new savings account with the Royal Bank of Canada (RBC). A pretest with 25 subjects that were different from those participating in the experiment indicates that only 4% of them had heard of the Royal Bank of Canada (RBC). General impression on RBC in the pretest is fairly neutral with a mean rating of 5.0 on a seven-point scale from very negative (1) to very positive (7). From the existing literature, a list of search and credence attributes was generated. Industry experts and academics have categorized these attributes into search and credence attributes (e.g., Babakus et al., 2004). However, consumers may not perceive and understand the differences between the search and credence attributes in the way researchers do (Krishnan and Hartline, 2001). Hence, pretest subjects were still asked to categorize the list of attributes into search, experience, and credence attributes, and rated their importance. Compared to Experiment 1, a more stringent criterion in this experiment was adopted in order to minimize the possibility of poor operationalization of the attributes. As such, attributes that the pretest subjects categorized in one type for at least 70% of the time were chosen for the experiment. The four resulting attributes were Interest Rate (search), Convenience of the Branches (search), Competency of the Management (credence), and Integrity of the Bank (credence). On a seven-point scale from totally unimportant (1) to totally important (7), the mean importance scores for the four chosen attributes range from 5.4 to 6.1. The experimental procedure was similar to that of the previous experiment. Each of the focal attributes was measured on a sevenpoint scale prior to and after the WOM scenario (Interest Rate: very low/very high; Convenience of the Branches: very inconvenient/very convenient; Competency of the Management: very incompetent/very competent; and Integrity of the Bank: very low/very high). Higher scores indicate more positive evaluations for all attributes. The following shows the general description of RBC before WOM was presented: RBC Bank is a full service bank that provides a full range of financial services, aimed at fulfilling the total banking and financial needs of both businesses and individuals. RBC Bank is present in various countries in the Asia-Pacific region, through a network of subsidiaries and associated companies. As of 28th Dec 2006, RBC Bank and its subsidiaries have total assets in excess of billions of Singapore dollars. An example of the WOM scenario is as follows (the parts in italics were not included in the scenario presented to the subjects): “You want to know more about RBC Bank? Oh sure, I do have a savings account with RBC Bank. Well, let me see… The opening hours are from about nine in the morning to four in the afternoon on a normal workday. The bank branches are opened on Saturday mornings as well. The interior of the bank branches is fairly modern looking too. Oh yes! I feel that the interest rate (search attribute 1) for the savings account is really low (negative). I also feel that the bank branches are really inconvenient for me to get to (search attribute 2 and negative). What else is there for me to tell you about RBC Bank? Mmm… When I first opened the savings account, I received a RBC ATM card. But I guess that is what you will typically get from other banks, for starting any savings account. Besides savings account, RBC Bank provides other kind of financial services too.”

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All the statements used for describing the different focal attributes in Experiment 2 are presented in Table A1 in Appendix A. 3.3.2. Results and discussion On the whole, majority of the subjects categorized the given attributes into their intended types (Table 3). The manipulation of attribute types was fairly successful compared to Experiment 1. The effectiveness of the WOM valence manipulation was also evaluated. For subjects who read negative WOM, one-sample t-tests show that the means of their untransformed attribute rating change scores are significantly different from zero in the negative direction for each of the four attributes (all ps < 0.001). Another series of one-sample ttests confirmed that the means of the change scores from those reading positive WOM are significantly different from zero in the positive direction (all ps < 0.05). Also, no subject was able to guess the overall objectives or the hypotheses of the experiment. As with Experiment 1, the analyses were done on the absolute change score of the attribute ratings. The attribute type main effect is significant (F(1,92) = 8.45, p < 0.01) with the marginal mean of Credence Attribute greater than that of Search Attribute (Table 4), supporting Hypothesis 1. The attribute type by valence interaction effect is significant (F(1,92) = 10.64, p < 0.01). Additional post-hoc analyses were done to examine the simple effects under the different levels of WOM valence. Under Negative WOM, the cell means of Credence Attribute and Search Attribute are significantly different (Table 4). Under Positive WOM, the cell means are not significantly different. Therefore, the results support Hypothesis 3. The WOM valence main effect is significant (F(1,92) = 103.29, p < 0.001). Negative WOM (M = 2.8) has a greater impact on attribute evaluation than Positive WOM (M = 0.8), supporting Hypothesis 2. As per Experiment 1, an additional analysis without these subjects who did not classify the focal attributes to the intended categories shows results that are consistent with the conclusions drawn from the results of the main analysis. 4. General discussion, limitations, and future directions For both experiments, the results support Hypothesis 1. The cell means for negative WOM show a similar pattern. However, the cell means do not differ significantly under positive WOM in both experiments. In summary, negative WOM has a significantly lower impact on the evaluation of search attributes than on the evaluation of credence attributes. A possible alternative explanation to the results is that the strength of the manipulation differs across the different attributes (i.e., different wording in the WOM message for each focal attribute to manipulate the evaluation). This explanation is unlikely for the pattern of results in the two experiments. If the significant differences across different attributes under negative WOM are due to the strength of the manipulation, differences across different attributes under positive WOM should be significant too. In both experiments, the differences across different attributes under positive WOM were not significant. The statements for positive and negative WOM for each of the focal attributes are the same except for the valence (refer to Appendix A, Table A1). Another possible alternative explanation is that the importance of the different attributes

Table 4 Statistics for change in attribute ratings in Experiment 2. Attribute

Marginal mean of absolute value of change score

Cell mean of absolute value of change score for NWOM

Cell mean of absolute value of change score for PWOM

Search Credence

1.5 (48,0.14)a 2.1 (48,0.14)

2.2 (24,0.20)b 3.4 (24,0.19)b

0.9 (24,0.20) 0.8 (24,0.19 )

a

Cell size, standard error of the mean). The individual cell means with the same superscripts are significantly different from each other, after adjusting for multiple comparisons using Bonferroni procedure with the overall error rate at 0.05. b

differs across the different attributes. This explanation is unlikely for the pattern of the significant differences in the main dependent variables of interest under negative WOM in both experiments, as the importance of the different attributes do not differ significantly under negative WOM for either experiment. The conceptual contributions of this research include expanding on the idea behind the media congruence hypothesis by Wright and Lynch (1995). Wright and Lynch (1995) examine the effectiveness of the different media to communicate product information in terms of the recognition of the claims made, belief accessibility, and belief confidence. However, this research is able to demonstrate that WOM is more effective in communicating information on credence attributes than on search attributes in terms of greater impacts on attribute rating. This expected relationship seems to be only limited to negative WOM. Extending on the media congruence hypothesis, this research examines the effectiveness of a medium on communicating information about credence attributes and search attributes. Even though the average consumer may not be able to verify the performance on credence attributes due to the cost and time required, negative WOM does seem to provide a signal for poor performance on these dimensions. In terms of managerial implications, the results from the two studies suggest that marketers of unfamiliar brand have to be aware that certain aspects of their services are more susceptible to negative WOM than others. If the attributes are of equal importance to the customers, marketers need to prioritize providing better customer service and after-sales support to address potential issues with credence attributes. Moreover, the marketers can adopt different approaches to mitigate the impact of negative WOM. As the consumers do not rely heavily on WOM for information for search attributes, accurate and positive information on these dimensions through advertising and other forms of marketing communication can easily mitigate any negative WOM regarding these attributes. Therefore, marketers should make relevant positive information on search attributes readily available to consumers (Blankson and Kalafatis, 1999). Credence attributes pose a major challenge for the marketers, as consumers are unlikely to accept any marketing communication (including product trial) from the marketers at face value. With the information asymmetry between buyer and seller regarding credence attributes, the marketers will need to build a strong brand in terms of trust to assure their customers about the performance on these attributes (Blankson and Kalafatis, 1999). 5. Limitations and directions for future research

Table 3 Categorization of attributes by subjects in Experiment 2a. Type of attributes

Credence (%)

Convenience of the branches 2.1 (n = 48) Interest rate (n = 48) 4.2 Competency of the management 79.2 (n = 48) Integrity of the bank (n = 48) 68.8 a

Experience (%)

Search (%)

Not sure (%)

14.6

83.3

–

8.3 14.6

87.5 2.1

– 4.2

22.9

6.3

2.1

These percentages include only subjects who rated the specific focal attribute.

The lack of a significant effect for positive WOM may be due to an artifact of the manipulation method. The vignettes in these two experiments are in a printed format and the WOM description of each focal attribute is only a single sentence that is relatively uninformative. Moreover, both experiments do not provide the subjects with any opportunities for clarification and immediate feedback. Thus, the subjects may not find the WOM in the experiments helpful in gauging the performance of the credence attributes as compared to relatively unambiguous search attributes. Hence, the use of vividly presented information can lead to a significant simple effect for positive WOM and

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an even stronger significant simple effect for negative WOM (as compared to the significant effects for negative WOM obtained in these experiments). Future studies can look into presenting WOM to the consumers in a more vivid manner. Finally, besides the WOM scenario, limited information is given to the participants of the experiments. Even the brand names of the services to be evaluated were unknown to the majority of the subjects. Future studies should consider the presence of other sources of information. For example, Srinivasan and Till (2002) find that brand name increases consumers' perception of performance evaluations of experience and credence attributes but not that of search attributes. But trial of the brands can reduce (but not eliminate) the advantage branded products have in enhancing consumers' perception of experience and credence attributes. Therefore, future research can look into how WOM may interact with brand name in affecting consumers' perception about the different attributes. Moreover, whether WOM is congruent with the other sources of information (e.g. direct experience, advertisements) can have a considerable impact on the effectiveness of WOM (e.g., Smith and Vogt, 1995).

Acknowledgments The authors thank Peter Darke, Ringo Ho, Shun Yin Lam, and Sharon Ng for their valuable feedback on the paper. In addition, the authors thank Marvin Boey, Shu Pei Ong, and Li-Yean Phuah for their invaluable help in data collection for Experiment 1.

Appendix A

Table A1 WOM statements used in Experiments 1 and 2. Attribute type Experiment 1 Cost of the accommodation (Search) Cost of the trip to and from Destination (Search)

Valence type

Statements

Negative The cost of accommodation was really high. Positive The cost of accommodation was really low.

Negative The cost of traveling to and from Belize was also really high. Positive The cost of traveling to and from Belize was also really low. Likelihood of terrorist Negative I did not feel safe in Belize, as there was attack (Credence) really high possibility of a terrorist attack. Positive I felt safe in Belize, as there was really low possibility of a terrorist attack. Likelihood of civil unrest Negative The possibility of civil unrest was also really (Credence) high. Positive The possibility of civil unrest was also really low. Experiment 2 Interest rate (Search)

Convenience of the branches (Search)

Competency of the management (Credence) Integrity of the bank (Credence)

Negative I feel that the interest rate for the savings account is really low. Positive I feel that the interest rate for the savings account is really high. Negative I also feel that the bank branches are really inconvenient for me to get to. Positive I also feel that the bank branches are really convenient for me to get to. Negative I feel that the management is really incompetent. Positive I feel that the management is really competent. Negative I also feel that the integrity of the bank is really low. Positive I also feel that the integrity of the bank is really high.

23

References Ahluwalia Rohini. How prevalent is the negativity effect in consumer environment. J Consum Res 2002;29(2):270–9. Arndt Johan. Word-of-mouth advertising and of informal communication. In: Cox DF, editor. Risk taking and information handling in consumer behaviour. Cambridge, MA: Harvard University Press; 1967. Babakus Emin, Eroglu Sevgin, Yavas Ugur. Modeling consumers' choice behavior: an application in banking. J Serv Mark 2004;18(6/7):462–70. Bansal Havir S, Voyer Peter A. Word-of-mouth processes within a service purchase context. J Serv Res 2000;3(2):166–77. Berger Lawrence A. Word-of-mouth reputations in auto insurance markets. J Econ Behav Organ 1988;10:225–34. Blankson Charles, Kalafatis Stavrios P. Issues and challenges in the positioning of service brands: a review. J Prod Brand Manag 1999;8(2):106–18. Brown Jacqueline J, Reingen Peter H. Social ties and word-of-mouth referral behavior. J Consum Res 1987;14(3):350–62. Burnkrant Robert E, Cousineau A. Informational and normative social influence in buyer behavior. J Consum Res 1975;2:206–15 (December). Darbi Michael R, Karni E. Free competition and the optimal amount of fraud. J Law Econ 1973;16:67–88 (April). Deutsch Morton, Gerard Harold B. A study of normative and informational influence upon individual judgment. J Abnorm Soc Psychol 1955;51:629–36 (November). Ekeland Jr Robert B, Mixon Jr Franklin G, Ressler RandW. Advertising and information: an empirical study of search, experience, and credence goods. J Econ Stud 1995;22 (2):33–43. Emons Winand. Credence goods and fraudulent experts. RAND J Econ 1997;28(1):107–19. Ford Gary T, Smith Darlene B, Swasy John L. Consumer skepticism of advertising claims: testing hypotheses from economics of information. J Consum Res 1990;16(4):433–41. Friestad Marian, Wright Peter. The persuasion knowledge model: how people cope with persuasion attempts. J Consum Res 1994;21(1):1-31. Herr Paul M, Kardes Frank R, Kim John. Effects of word-of-mouth and product-attribute information on persuasion: an accessibility–diagnosticity perspective. J Consum Res 1991;17(4):454–62. Hsieh Yi-Ching, Chiu Hung-Chang, Chiang Mei-Yi. Maintaining a committed online customer: a study across search-experience–credence products. J Retail 2005;81(1): 75–82. Jain Shailendra Pratap, Posavac Steven S. Prepurchase attribute verifiability, source credibility, and persuasion. J Consum Psychol 2001;11(3):169–80. Jolson Marvin A, Bushman F Anthony. Third-party consumer information systems: the case of the food critic. J Retail 1978n;54(4):63–79. Krishnan Balaji C, Hartline, Michael D. Brand equity: Is it more important in services? The Journal of Services Marketing 2001;15(4/5):328–41. Laczniak Russell N, DeCarlo Thomas E, Ramaswami Sridhar N. Consumers' responses to negative word-of-mouth communication: an attribution theory perspective. J Consum Psychol 2001;11(1):57–73. Mizerski Richard W. An attribution explanation of the disproportionate influence of unfavorable information. J Consum Res 1982;9(3):301–10. Mourali Mehdi, Laroche Michel, Pons Frank. Antecedents of consumer relative preference for interpersonal information sources in pre-purchase search. J Consum Behav 2005;4(5):307–18. Nelson Philip. Information and consumer behavior. J Polit Econ 1970;78:311–29 (March–April). Nelson Philip. Advertising as information. J Polit Econ 1974;82(4):729–54. Sheffet Mary J. An experimental investigation of the documentation of advertising claims. J Advert 1983;12(1):19–29. Smith Robert E, Vogt Christine A. The effects of integrating advertising and negative WOM communications on message processing and response. J Consum Psychol 1995;4(2):133–51. Smith Donnavieve, Menon Satya, Sivakumar K. Online peer and editorial recommendations, trust, and choice in virtual markets. J Interact Market 2005;19:15–37. Srinivasan Srini S, Till Brian D. Evaluation of search, experience, and credence attributes: role of brand name and product trial. J Prod Brand Manag 2002;11(6/7):417–31. Tabachnick Barbara G, Fidell Linda S. Using multivariate statistics. Boston, MA: Pearson Education Inc; 2007. Wagenheim Florian V, Bayón Tomas. The effect of word of mouth on services switching. Eur J Mark 2004;38(9/10):1173–85. Washburn Judith H, Till Brian D, Priluck Randi. Brand alliance and customer-based brand-equity effects. Psychol Mark 2004;21(7):487–508. Wright Alice A, Lynch Jr John G. Communication effects of advertising versus direct experience when both search and experience attributes are present. J Consum Res 1995;21(4):708–18. Zemborain Martin R, Johar Gita V. Attitudinal ambivalence and openness to persuasion: a framework for interpersonal influence. J Consum Res 2007;33:506–14.

Journal of Business Research 64 (2011) 24–28

Contents lists available at ScienceDirect

Journal of Business Research

The impact of brand personality and sales promotions on brand equity Pierre Valette-Florence a, Haythem Guizani b, Dwight Merunka c,d,⁎ a

University of Grenoble (IAE Grenoble - CERAG), France Wesford Business School and CERAG, Grenoble, France c University Paul Cézanne Aix–Marseille (IAE Aix-en–Provence, CERGAM), France d Euromed Management in Marseille, France b

a r t i c l e

i n f o

Article history: Received 1 April 2009 Received in revised form 1 July 2009 Accepted 1 September 2009 Keywords: Brand personality Promotional deals Brand equity Finite mixture–PLS models

a b s t r a c t This research assesses the relative impact of a long-term brand management instrument (brand personality) and a short-term marketing mix instrument (sales promotions) on brand equity formation. The authors measure consumer perceptions of promotional intensity and brand personality and model their impact on brand equity. They find a positive impact of brand personality and a negative impact of sales promotion intensity on brand equity at the aggregate level. In line with research that identifies varying consumer responses to promotional deals, this study posits that the relative impact of the two elements varies across consumer groups. Three homogeneous consumer groups differ according to the relative impact of brand personality and consumer promotions on brand equity, following an application of a finite mixture partial least squares procedure. © 2009 Elsevier Inc. All rights reserved.

1. Introduction More marketing dollars accrue, over time, to operations that can produce sales in the short term. In particular, marketing expenditures for consumer promotions keep gaining importance in the marketing budgets of most consumer and durable goods. In contrast, advertising expenditures linked to brand-building activities appear to diminish over the years (Mela et al., 1997; Neslin, 2002; Srinivasan et al., 2004). This evolving allocation of resources across marketing activities poses a problem with regard to the return on marketing investments. To calculate the return on marketing investments, companies could use sales or profits, but they also might turn to several other equities (e.g., relational, brand, customer) (Seggie et al., 2007). This debate raises the question of the most effective strategy for mixing consumer promotions and brand-building activities. Therefore, this study compares the relative impact, on brand equity, of consumer promotions and a more stable set of brand associations that have hedonic and symbolic proprieties, as reflected in brand personality. Current literature treats the impact of each element separately (Chandon et al., 2000; Kim, 2000), without exploring the question of the relative impact of both set of variables on brand equity. Yet the question is critical in response to the increasing demand for marketing accountability (Lim et al., 2005) and trends toward spending more on short-term operations rather than brand-building activities. Prior

⁎ Corresponding author. University Paul Cézanne Aix–Marseille, IAE Aix-en–Provence, Clos Guiot, 13540 Puyricard, France. Tel.: +33 442 280 808; fax: +33 442 280 800. E-mail addresses: pierre.valette-fl[email protected] (P. Valette-Florence), [email protected] (H. Guizani), [email protected] (D. Merunka). 0148-2963/$ – see front matter © 2009 Elsevier Inc. All rights reserved. doi:10.1016/j.jbusres.2009.09.015

research examines the impact of consumer promotions and advertising on brand choice or consumer behavior using econometric data (Mela et al. 1997; Mela et al., 1998). This research instead tests consumer perceptions of both promotional intensity and brand personality and measures their impact on consumer-based brand equity. Much research focuses on developing brand equity measurement tools (e.g., Keller, 2003; Park and Srinivasan, 1994; Yoo and Donthu, 2001); little empirical research attempts to understand or measure the process of brand equity formation over time through an examination of antecedents (Barwise, 1993). Consumer promotions have positive effects on brand equity, because promotions develop brand awareness for the entire product category and the promoted brands (Blattberg and Neslin, 1990). In contrast, promotions might have a negative impact on brand equity, because repeated promotions offer signals of lesser quality or indications that the brand needs promotions to justify consumer consideration and purchase. Some studies establish that promotions correlate negatively with brand loyalty, a dimension of brand equity (Bawa and Shoemaker, 1987); however, other research finds positive, more complex relationships. Joshy and Sivakumaran (2009) indicate that consumer promotions enhance brand equity, especially among market segments dominated by spuriously loyal consumers. Rothschild (1987) instead establishes that deals reinforce search behavior and deal proneness rather that loyalty behavior. Price promotions also appear to increase both price and price-promotion sensitivity, whereas non-price promotions increase price and deal sensitivity among non-loyal consumers (Mela et al. 1997). Together with consumer promotions, which the brand management team can manage in the short term through frequency and magnitude decisions, this study considers the impact of brand personality on brand equity. Brand personality is ‘the set of human

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characteristics associated with a brand’ (Aaker, 1997, 347). Both researchers and practitioners suggest brand personality is an important concept that helps differentiate a brand in a product category (Plummer, 1984), enhances consumers' preference and loyalty to a brand (Fournier, 1998), and creates brand equity (Keller, 1993). Brand personality also influences brand recognition, brand beliefs such as perceived quality (Ramaseshan and Tsao, 2007), and brand associations (Freling and Forbes, 2005). Moreover, brand personality has an impact on some important marketing concepts that Keller (2003) includes in his brand equity model, such as brand–consumer relationships and brand attachment (Sung et al., 2005) or brand trust (Hess et al., 2007). However, Swaminathan, Stilley, and Ahluwalia (2009) demonstrate that the effect of brand personality on brand attachment, purchase likelihood, and brand choice depends on the attachment style of the consumer, including anxiety and avoidance features. The congruence between the ideal and actual self-concepts also plays a key role in terms of the accuracy of brand personality-based judgments. The effects of brand personality dimensions on consumer behaviors therefore may relate to situational and individual variables, which suggest heterogeneity in consumer responses. This study examines how perceived sales promotions and brand personality affect brand equity. In addition, this investigation assesses heterogeneity in consumer responses to these two elements across consumer groups. To identify consumer segments that exhibit different responses to marketing instruments, this research implements an innovative methodology. That is, as Ringle, Wende, and Will (2008) recommend, a finite mixture partial least squares (PLS) procedure identifies distinct customer segments for which the strength of the relationships between brand personality, sales promotions' intensity, and brand equity varies. The remainder of this paper proceeds as follows: The next section contains a brief theoretical overview of promotional activities, brand personality, and their impact on consumer-based brand equity. After the research model and the methodology, this article provides the main research results. Finally, the paper concludes with limitations and further research suggestions. 2. Theoretical background and hypotheses 2.1. The impact of promotions on brand equity Sales promotions are marketing events and tools designed to stimulate quicker and greater purchases for a limited period of time (Kotler, 1988). Much research on consumer responses to sales promotion examines immediate effects on consumer purchases (Gupta, 1988; Inman et al., 1990; Nijs et al., 2001). However, studies of the long-term effects of promotions reveal some adverse effects on brand equity, including reinforcement of switching behavior (Papatla and Krishnamurthi, 1996), increased price and deal sensitivities (Mela et al., 1997), and lost brand equity (Yoo et al., 2000). Aaker (1996) establishes that repeated promotions decrease brand equity over time, and Mela, Ataman, and Van Heerde (2006) find that among five selected marketing mix variables, repeated monetary promotions negatively affect brand equity. In contrast, DelVecchio, Henard, and Freling (2006) demonstrate that sales promotions can either increase or decrease brand preference, and Ailawadi, Neslin, and Lehmann (2003) provide empirical evidence of the positive long-term impact of price promotions on purchase reinforcement and brand performance.

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research (Garretson and Burton, 2003) show that consumer groups react differently to sales promotions in general or to specific forms of promotions, such as coupons or everyday low prices. Therefore, this study explores possible heterogeneity in consumer responses to promotions across consumer groups. 2.2. Brand personality and brand equity Consumers use brand personality dimensions as relevant determinants of the brand's added value. Brand personality ensures a stable brand image over time (Aaker, 1996) and allows consumers to express their own personalities (Aaker, 1997). Brand personality associations, when strongly activated in consumer memory, also affect consumer behaviors and attitudes toward the brand (Wysong, 2000). Although no evidence relates brand personality dimensions directly to brand equity, various studies explore the impact of brand personality on elements that reflect components or consequences of brand equity. For example, brand personality affects brand preferences (Kim, 2000), brand attachment (Sung et al., 2005), brand trust (Hess et al., 2007), and brand loyalty (Brakus et al., 2009). H2. Brand personality positively affects brand equity. The hypothesized relationships appear in Fig. 1. After testing and comparing the relative impact of the two independent variables, this investigation identifies homogeneous consumer groups, as designated by the impact of promotional deals and brand personality on their brand equity perceptions. 3. Research method An initial sample of 150 volunteers (students and staff members of a large French university, 55% women, average age = 28 years) tested the research questionnaire and enabled testing measurement scales for reliability and validity. These participants rated three brands (coffee, athletic shoes, and cars) in terms of promotion intensity, brand personality, and consumer-based brand equity. This stage enabled the purification of the measurement instruments. The second stage consisted of a large-scale, Internet-based survey. Two questionnaire versions (one with two major laptop brands [Sony Vaio and Acer] and one with two major French coffee brands [Grand'mère and Carte Noire]) were available to the survey participants (i.e., university students and staff). The data analysis relies on 538 completed questionnaires (respondents: 52% women, 71% students, 29% university staff). The overall response rate was 24%. 4. Measurements The existing scales for the three constructs (brand equity, brand personality, perceived deal intensity) use five-point Likert agreement scales for each item.

H1. Consumer promotion intensity negatively affects brand equity. Another stream of research examines consumers' deal proneness. Studies reveal that consumers differ in their responses to sales promotions, which implies the existence of a deal-prone consumer profile (Grover and Srinivasan, 1992; Lichtenstein et al., 1997). Both empirical behavioral research (Ailawadi et al., 2001) and survey

Fig. 1. Relationships between brand personality, sales promotion intensity, and brand equity.

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4.1. Brand equity Most studies show that the brand equity measurement is global and corresponds to the definition of a ‘value-added’ to the product. Measurements tools such as price premiums (Aaker, 1996), collections of consumer-based perceptions (Agarwal and Rao, 1996), or purchase behavior (Kamakura and Russell, 1993) correspond with this view. In contrast, Yoo and Donthu (2001) develop a multidimensional consumer brand equity scale and identify three dimensions: Loyalty, perceived quality, and brand association/attention (confirmed by Washburn and Plank, 2002). Guizani, Triguero, and ValetteFlorence (2008) add a fourth dimension, the social value of the brand, which reflects that customers may share the same values or that the brand can gather a group of consumers, such as in a brand community (Muniz and O'Guinn, 2001). This research uses the 12-item scale with four dimensions (brand loyalty, brand knowledge, social value, and perceived quality). Yoo and Donthu (2001) propose an overall brand equity measure in addition to their multidimensional brand equity scale, so the four dimensions also aggregate into a second-order factor that measures brand equity or overall added brand value. 4.2. Promotional deals Measures of sales promotions might rely on either actual or perceived marketing efforts (Van Heerde et al., 2004). Consumers have little knowledge of real marketing efforts, such as promotional expenditures or even real prices. Perceived marketing actions provide strong predictors of brand evaluation (Kirmani and Wright, 1989) and likely link directly to consumer psychology. In their research, focused on the influence of marketing mix elements on brand equity, Yoo et al. (2000) use perceived marketing efforts rather than real marketing actions. Similarly, this study measures consumer promotional activities as perceived promotion intensity and adapts the three-item scale developed by Yoo and Donthu (2001). 4.3. Brand personality Culture influences brand personality dimensions (Sung and Tinkham, 2005), so this study turns to the brand personality scale of Ambroise (2006), which reflects the same French context. This scale, which achieves good reliability and validity across product categories and brands, consists of 23 adjectives (e.g., introverted, warm, affectionate, sophisticated) and contains five dimensions (agreeability, conscientiousness, sophistication, fallaciousness, and introversion). The dimensionality of the brand personality construct does not exclude the use of a global measurement to indicate brand personality's valence. Analogous to the framework of Allport (1961), which introduces the concept of a ‘whole personality,’ brand personality in this study, as represented by a revealed second-order factor, stands for a general evaluation of the anthropomorphic inferences that consumers develop toward the brand. Brakus et al. (2009) similarly adopt a second-order conceptualization of brand personality that influences loyalty and satisfaction positively. 5. Analysis and results Prior to testing the structural relationships, exploratory and confirmatory factor analyses serve to pretest the measures and ensure the robustness of the selected scale structures. The coefficient alphas of each multi-item scale are greater than .75. All scales are reliable and valid across product categories and brands. The goodness-of-fit indexes (GoF; Tenenhaus et al., 2005) are high (Table 1), which indicates that the scales' structures are parsimonious and that the factors fit the data well. Brand personality dimensions aggregate into one meta-factor through regrouping of the five revealed dimensions (agreeability = .845, conscientiousness = .584, sophistication =.625, fallaciousness =

Table 1 Reliability and validity of measurement scales.

Perceived sales promotion intensity Brand personality (second-order) Agreeability Conscientiousness Sophistication Fallaciousness Introversion Brand equity (second-order) Brand social value Brand knowledge Brand loyalty Perceived quality

Reliability Jöreskog rhô

Convergent validity (% of shared variance)

Goodness-of-fit parameter (GoF)

.610

.542

578

.907

.553

584

.879 .836 .861 .891 .877 .876

.538

609

.891 .880 .878 .842

−.521, introversion = −.623; p b .05; GoF =584). The same analysis applies to brand equity. The higher-order brand equity structure is statistically strong; all dimensions correlate highly with the overall brand equity factor, and the model achieves a good fit index (brand loyalty = .75, brand knowledge = .61, brand social value = .83, perceived quality= .56; p b .05; GoF = 609). 5.1. Aggregate effects The tests of the hypotheses rely on partial least square path modeling (PLS). The overall fit of the structural model in Fig. 1 is very good, as the GoF (647) and R2 (.26) indicate. Brand personality associations and the perception of promotion intensity explain 26% of the overall brand equity construct. Regarding structural relationships, consumer promotions have a negative impact on brand equity (path coefficient = − .22; p b .001) in support of H1. DelVecchio et al. (2006) also find that consumer promotions erode brand equity, despite their immediate positive effect on sales. Brand personality has a high, positive impact on brand equity (path coefficient = .49; p b .001), in support of H2. At the aggregate level, brand personality has a stronger impact on brand equity than do consumer promotions. 5.2. Variations across consumer segments Following extant literature on promotional effectiveness, which indicates varying responses from consumers to promotional deals, this study postulates the existence of consumer segments, defined by different path coefficients that link consumer promotions and brand personality to their perceptions of brand equity. Rather than introducing theoretically based segmentation variables, which is appropriate when research seeks to uncover the ideal profile of dealprone consumers (Schneider and Currim, 1991), a latent class approach attempts to uncover and describe consumer segments that are homogeneous in terms of the impact of consumer promotions and brand personality on their judgments of brand equity. Furthermore, this study exploits the recent developments that extend the mixture model methodology to PLS structural equation models (Ringle et al. 2008) and applies the finite mixture PLS approach (FIMIX-PLS). The mixture procedure applied with Smart PLS software results in an optimum solution composed of three segments. The model selection derives from the entropy index, which indicates a good separation in the estimated individual class probabilities and the smallest values for the Akaike and Bayesian Information Criteria (AIC and BIC). The entropy index is high (EN = .62), and the AIC and BIC statistics are the smallest across all other solutions. The specific path coefficients indicate the characteristics of each revealed group (Table 2).

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Table 2 Path coefficients and fit indexes for FIMX-PLS revealed segments. Segment 1: Nonsymbolic, non-deal-prone consumer (26%)⁎ - R²=.354 Brand personality dimensions Consumer promotions Goodness-of-fit indices

Segment 2: Deal-prone consumer (41%) - R²=.499

Segment 3: Symbolic non-deal-prone consumers (33%) - R²=.345

.037⁎⁎ .567 .565 − .658 .201 − .163 Akaike information criterion = 4851.34; Bayesian information criterion = 4862.22; constant Akaike information criterion = 4902.01; entropy index = .62

⁎ Segment size. ⁎⁎ Insignificant at p b .05.

Segment 1 is relatively small (26% of participants), characterized by a strong negative path coefficient between perceived sales promotions' intensity and brand equity (−.66). Brand personality does not affect brand equity (insignificant coefficient). Brand equity judgments do not result from symbolic brand personality judgments, and too many promotions degrade brand equity. Consumers form their brand equity judgments on the basis of variables other than those included in the proposed model. Functional considerations might provide the basis for overall brand judgments in this segment (Sirgy et al., 1991). Consumers in Segment 2 (largest segment, 41% of the sample) are sensitive to both brand personality (coefficient = .57) and promotional deals (coefficient = .20). The high positive impact of perceived promotional intensity on brand equity indicates deal-prone consumers who also value brand personality dimensions. These sales promotion-prone consumers seek both shopping enjoyment (Garretson and Burton, 2003) and brand enjoyment. Segment 3 (33% of the sample) exhibits a significant negative structural relationship between sale promotions' intensity and brand equity (coefficient= −.16), but brand equity depends strongly on brand personality judgments (coefficient = .56). As in Segment 1, consumers in this group believe that too frequent and intense consumer promotions signal weak brand value. However, unlike Segment 1 (but as in Segment 2), they evaluate brand equity on the basis of symbolic associations. Among deal-averse consumers (Segments 1 and 3), brand personality provides a key segmentation variable.

6. Conclusion The objective of this research is to test the differential effects of brand personality and consumer promotions on brand equity. At the aggregate level, brand personality dimensions positively affect brand equity, whereas consumer promotion attractiveness has a negative influence. The positive impact of brand personality is greater than the negative impact of consumer promotions. This overall view of relationships with brand equity becomes clearer with segmented consumer groups. The proposed segmentation uses a finite mixture PLS procedure, based on the impacts of the brand personality dimensions and perceived sales promotions on brand equity. This procedure consists of testing different mixture models and detecting any heterogeneity between groups, while taking into account significant differences between the path coefficients that link the independent variables to brand equity. The results reveal three segments with heterogeneous path coefficients. This distinction challenges general findings about brand equity formation and the overall impacts of brand personality and consumer promotions on brand equity. The impact of brand personality on brand equity is positive at the aggregate level; however, one segment seems insensitive to it. Although the impact of consumer promotions on brand equity is negative in general, for one important segment, consumer promotions together with brand personality judgments positively influence brand equity. Further research therefore should focus on understanding or explaining these differences. The probabil-

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Journal of Business Research 64 (2011) 29–33

Contents lists available at ScienceDirect

Journal of Business Research

The role of social presence in mortality salience effects Marieke L. Fransen a,⁎, Dirk Smeesters b,1, Bob M. Fennis c,2 a b c

University of Amsterdam, Amsterdam School of Communication Research, Kloveniersburgwal 48, 1012 CX, Amsterdam, The Netherlands Erasmus University, Rotterdam School of Management, Department of Marketing Management, P.O. Box 1738, 3000 DR, Rotterdam, The Netherlands Utrecht University, Department of Social and Organizational Psychology, Heidelberglaan 1, 3584 CS, Utrecht, The Netherlands

a r t i c l e

i n f o

Article history: Received 1 April 2009 Received in revised form 1 July 2009 Accepted 1 September 2009 Keywords: Terror management theory Social presence Self-esteem Consumer behavior Brand evaluation

a b s t r a c t Terror management theory (TMT; Greenberg et al., 1986) suggests that reminders of death intensify the desire to express cultural norms leading to culturally prescribed behavior such as charitable giving, church attendance, and exorbitant spending. Living up to these norms provides high levels of self-esteem, which can serve as a buffer against existential anxiety. The present paper argues that people can experience an extra self-esteem boost when they act in accordance with cultural norms while others can observe this behavior. More specifically, the present studies hypothesized and found that the presence of others (i.e., social presence) moderates mortality salience effects on consumption-related behavior. Study 1 demonstrates that consumers, under conditions of mortality salience, express more favorable attitudes towards a luxury brand (valued in Western cultures) when they know that other can observe their behavior. Study 2 extended these results to non-luxury brands. Under conditions of mortality salience, consumers express less favorable evaluations of non-luxury (non-valued brands) when they are aware of the presence of others. These results imply that consumers derive self-esteem indirectly from the knowledge that others observe their appropriate behavior rather than directly from following the cultural values or norms of one's society. © 2009 Elsevier Inc. All rights reserved.

1. Introduction The fear of death is so fundamental to human beings that it pervades all aspects of life. People tend to cope with the aversive thought of one's own death in various ways (see Pyszczynski et al., 2004 for a review). Several recent studies provide empirical evidence that mortality-related thoughts also affect consumer behavior. For example, research demonstrates that people are more attracted to high status products and brands (Heine et al., 2002; Mandel and Heine, 1999), show a preference for domestic over foreign products (Fransen et al., 2008; Liu and Smeesters, in press), and intend to purchase and actually eat higher quantities of food products (Mandel and Smeesters, 2008) when they are reminded of their mortality. But are these coping strategies invariant across different consumption situations? The current paper argues that they are not. Rather, the present paper presents evidence showing that consumption-related terror management strategies are especially likely to unfold when consumption is public, and can be witnessed by others, rather than when consumption is private. More specifically, the current studies

⁎ Corresponding author. Tel.: +31 20 525 2110. E-mail addresses: [email protected] (M.L. Fransen), [email protected] (D. Smeesters), [email protected] (B.M. Fennis). 1 Tel.: + 31 10 408 2952. 2 Tel.: + 31 30 253 9189. 0148-2963/$ – see front matter © 2009 Elsevier Inc. All rights reserved. doi:10.1016/j.jbusres.2009.09.016

investigate the role of social presence in consumer-related mortality salience effects.

1.1. Terror management theory Terror management theory (TMT; Greenberg et al., 1986) provides a theoretical explanation for behavior that is induced by death-related thoughts. This theory is based on the notion that human beings are (unconsciously) aware of the inevitable end that lies ahead. This awareness of one's transient life combined with the human ‘will to survive’ leads to an insolvable conflict often referred to as terror. According to TMT, people manage this experienced terror by gaining high levels of self-esteem that can serve as a buffer against deathrelated concerns. People can attain high levels of self-esteem by endorsing, protecting, and living up to a cultural worldview that gives meaning, order and permanence to the self; this allows people to feel like important members of their meaningful cultural world. Abundant research shows that people who are unconsciously reminded of their mortality engage in self-esteem striving leading to culturally prescribed behavior like, charitable giving (Fransen, et al., 2008; Jonas et al., 2002). People who are reminded of their mortality are also more eager to protect their cultural norms and values by disassociating themselves from people who hold distinct worldviews (e.g., Dechesne et al., 2000). Hence, defending and protecting one's cultural norms on the one hand, and self-esteem striving by following

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the valued norms of the society on the other seem to be suitable strategies for coping with unconscious death-related thoughts. According to Arndt et al., (2004) consumerism and materialism are important values intrinsic to the contemporary western worldview. The current western society turned into a consumer society in which the defining activity of people is consuming; money and possessions are transformed into measures of self-worth (Bauman, 1995). People can therefore derive self-esteem by living up to these ‘new’ culturally valued norms of being wealthy, spending loads of money and live exorbitantly. 1.2. Mortality salience and social presence As mentioned before, TMT states that people derive self-esteem from living up to culturally prescribed values and norms because meeting these norms allows people to feel like valuable persons in a valuable society. However, it remains unclear whether one directly derives self-esteem from looking at oneself and knowing that one behaves according to valued norms or that self-esteem is derived more indirectly from the fact that other society members witness how ‘correctly’ one behaves. Social Impact Theory (Latané, 1981) states that people desire to be viewed in a positive light by others (Baumeister, 1982; Frey, 1978; Leary and Kowalski, 1990; Riordan et al., 2001), and therefore have the tendency to engage in impression management strategies when other persons are present or only imagined to be present (Latané, 1981). For instance, people show more helping behavior (Van Rompay et al., 2009) when they know a security camera is observing them. Hence, consumers are motivated to gain the approval of others, which can be achieved by behaving in ways that are approved within a situation or cultural worldview (Kallgren et al., 2000). But why do people need social approval? Research on Sociometer theory (e.g., Leary, 2003; Leary et al., 2000; Leary et al., 1995; Leary et al., 1998) demonstrates that social approval positively affects self-esteem, which according to TMT is essential for dealing with mortality-related thoughts. Therefore, the present paper argues that not only behaving according to cultural norms but also the knowledge that others see and witness one's culturally approved behavior is essential in dealing with existential anxiety. Hence, social presence might be an important factor in explaining mortality salience effects. In accordance with TMT, the current studies propose that people derive self-esteem from living up to cultural norms which makes them valuable persons in their society. In extension, these studies proffer that self-esteem receives an even greater boost when others (can) witness their socially approved behavior. Based on the notion that social approval leads to enhanced levels of self-esteem (e.g., Leary, 2003; Leary et al., 1995), the current studies expect that people are especially prone to show culturally prescribed behavior under conditions of mortality salience when other members of their cultural worldview can witness their behavior but less so when others are not present. Study 1 tests this proposition by investigating whether social presence moderates the relationship between mortality salience and brand evaluations. As observed in previous research the current study expects that mortality salience leads to more favorable evaluations of luxury brands (Heine et al., 2002; Mandel and Heine, 1999). Moreover, this study hypothesizes that the effect of mortality salience on luxury brand evaluations is stronger when people are aware of the presence of others. 2. Study 1 2.1. Method 2.1.1. Design and participants The present study used a 2 (mortality salience vs. control) × 2 (social presence vs. control) between-participants design. A total of

one hundred and eleven undergraduate students (41 male) with a mean age of 21.4 (SD = 2.15) participated in the study. 2.1.2. Procedure Participants were seated in a room behind a computer providing all further instructions. After answering some demographic questions, participants were randomly assigned to one of the four experimental conditions. Participants in the experimental condition received a mortality salience manipulation while participants in the control condition were questioned about taking an exam. Previous research has shown that mortality salience effects mainly occur after distraction from conscious thoughts about death (Greenberg et al., 1994), hence participants were asked to respond to an extensive personality questionnaire to distract them from conscious thoughts about their mortality. After the mortality salience manipulation, participants evaluated a luxurious product. To make participants aware of the social presence it was stated, in the experimental condition, that their answers would be seen and evaluated by another participant. In the control condition no such statement was made. 2.1.3. Mortality salience Mortality salience was induced by asking participants in the mortality salience condition to answer two open-ended questions regarding their own death: ‘Please briefly describe the emotions that the thought of your own death arouses in you’ and ‘Jot down as specifically as you can, what you think will happen to you when you physically die’ (cf. Greenberg et al., 1997). Participants in the control condition answered the same questions concerning taking a difficult exam (cf. Heine et al., 2002). 2.1.4. Social presence Social presence was manipulated by informing half the students that another participant would evaluate their ratings. The other half of the participants did not receive this message. This manipulation served to give participants the feeling that another person would see their answers and therefore could approve or disapprove their evaluation. 2.1.5. Brand evaluation Participants were exposed to an advertisement of a luxurious Mercedes car. In a pretest with different car brands Mercedes was rated as the most luxurious car brand (M = 5.7 as compared to, for example, Opel, M = 3.7). Attitude towards the advertised car was measured using an 8-item product attitude measure. Participants indicated, on 7-point scales, the quality, appeal, and reliability of the product (α = .85). The mean score on this measure served as the dependent variable. 2.2. Results and discussion 2.2.1. Brand evaluation To test the hypotheses a 2 (mortality salience vs. control condition) × 2 (social presence vs. control condition) ANOVA on brand evaluation was performed. The results yielded the expected interaction effect between mortality salience and social presence (F(1, 107) = 4.66, p < .05). This indicates that the mortality salience manipulation particularly affected product evaluation when social presence was activated. Additional simple main effect analysis showed that participants in the social presence condition rated the luxurious brand more positive when mortality was salient (M = 5.5, SD = .61) than when they thought about a difficult exam (M = 5.1, SD = .99; F(1, 107) = 4.31, p < .05). Participants in the control condition (no social presence condition) did not show such an effect (M = 5.2, SD = .75 and M = 5.4, SD = .74; F(1, 107) < 1, ns). No significant main effects of both mortality salience and social presence (Fs < 1, ns) on brand attitude were observed.

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Although the results did not show a significant main effect of mortality salience on product attitude in this study, the expected interaction effect between mortality salience and social presence was observed. This indicates that social presence indeed plays a crucial role in the process of dealing with mortality-related thoughts. The effects of mortality salience only appeared when participants were made aware of the presence of others. Knowing that others observe how one performs ‘correct’ behavior seems to serve as an extra selfesteem boost serving as a buffer against existential anxiety. This is a novel finding in the mortality salience literature, as previous research did not systematically manipulate the factor social presence. This suggests that mortality salience effects mainly occur for behaviors that provide a source of self-esteem (e.g., consuming luxury products, tanning) when these behaviors are publicly observable. Study 2 extends these findings by arguing that not only luxury brands are rated more favorable (Heine et al., 2002; Mandel and Heine, 1999) but that non-luxury brands are evaluated less favorable when thoughts about death are activated. Non-luxury brands do not function as a solid source of self-esteem, and hence should not be rated more favorable when death-thoughts are activated. Moreover, under the public scrutiny of others, non-luxury brands may completely be dysfunctional to bolster one's self-esteem in the face of death, and, hence, might be evaluated more negatively. Thus, the present study expects that people reminded of their mortality evaluate luxury brands more positively and non-luxury brands more negatively especially when they are aware of the presence of others. 3. Study 2 3.1. Method 3.1.1. Design and participants In Study 2 a 2 (mortality salience vs. control condition) × 2 (social presence vs. control condition) × 2 (luxury brands vs. non-luxury brands) design with the first two factors as between-participant factors and the last factor as a within-participants factor was used. Seventy-seven participants (43 male) with a mean age of 23.8 (SD = 4.37) took part in the study. 3.1.2. Procedure Participants were invited by email to take part in a study on consumer behavior. The email included a link of a website where participants could respond to the questionnaire. Upon entering the website, participants were randomly allocated to one of the four experimental conditions. After answering some demographic questions, all participants responded to a filler questionnaire that served to distract participants from the real goal of the study. This questionnaire was followed by a mortality salience manipulation after which

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participants (in both conditions) solved five mathematical questions which were used to remove the death-related thoughts from focal conscious attention (see Arndt et al., 1997). Next, all participants evaluated two luxury brands and two non-luxury brands. To make participants aware of the presence of others it was stated (before actually rating the brands) that their brand evaluations would be made public; in the control condition no such statement was made. 3.1.3. Mortality salience Participants in the mortality salience condition responded to the same death-related questions as the ones used in Study 1. In the control condition, participants answered questions regarding dental pain (as in the classical paradigm developed by Greenberg et al., 1997). The mathematical problems were used to distract participants from their focal death-related thoughts. 3.1.4. Social presence Informing half of the participants that their brand evaluations would be made public served as a social presence manipulation. The other half of the participants did not receive this message. This manipulation served to give participants the feeling that others could see (and therefore approve or disapprove) their ratings. 3.1.5. Brand evaluation Primarily, a pilot study (N = 20) to examine which brands are regarded as luxury and non-luxury was conducted. The brands Medion (M = 3.5) and Tawa (M = 2.5) were evaluated as least luxurious and the brands Armani (M = 6.2) and Mercedes-Benz (M = 6.0) were rated as most luxurious. A t-test between the mean score of the two non-luxury brands and the mean score of the luxury brands confirmed that Armani and Mercedes-Benz were indeed evaluated significantly more luxurious than Medion and Tawa (t(19) = 15.00, p < .001). To measure participants' attitudes towards the luxury and nonluxury brands, participants evaluated each of the four brands on 5point scales. They indicated how positive, interesting and important they rated the brand and how likely it was that they would buy the brand in the future. A measure of luxury brand attitude was formed by calculating the mean score on the questions regarding the two luxury brands (α = .86); a measure of non-luxury brand attitude was constituted by calculating the mean score on the items regarding the two non-luxury brands (α = .83). 3.2. Results and discussion 3.2.1. Brand evaluation A 2 (mortality salience vs. control condition) × 2 (social presence vs. control condition) × 2 (luxury brands vs. non-luxury brands) ANOVA with repeated measures on the last factor, was performed to

Fig. 1. Brand evaluation as a function of mortality salience and social presence.

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test the hypotheses. The results demonstrated a significant main effect of brands (F(1, 71) = 57.39, p < .001) indicating that the luxury brands were generally evaluated more positively (M = 3.2, SD = .82) than the non-luxury brands (M = 2.3, SD = .64). Moreover, the results yielded a significant interaction effect between mortality salience and brands (F(1, 71) = 12.49, p < .01). Most focal to the main hypothesis, the expected three-way interaction between mortality salience, brands, and social presence was found (F(1, 71) = 8.21, p < .01). This indicates that the interaction between mortality salience and brands was more pronounced when people were aware of the social presence than when such awareness was absent (Fig. 1). Additional analysis of the simple main effects demonstrated that among participants in the social presence condition, mortality salience led to a more positive evaluation of the luxury brands (M = 3.7, SD = .96) than the control condition (M = 2.8, SD = .65; F (1, 71) = 13.28, p < .01). Conversely, participants in the social presence condition rated the non-luxury products more negatively when mortality was salient (M = 2.0 SD = .61) than when mortality was not salient (M = 2.6, SD = .50; F(1, 71) = 9.91, p < .01). This pattern of results was not found when social presence was absent (both Fs < 1, ns). 4. General discussion According to TMT people need self-esteem to deal with unconscious existential anxiety, which they can achieve by following the rules, norms, and values of one's cultural worldview. One important norm in current society is consumerism (Arndt et al., 2004; Bauman, 1995). People can therefore derive self-esteem, serving as a buffer against existential threat, through consumerism. The purpose of this research was to explore whether one derives self-esteem directly from following the cultural values or norms of one's society or from the fact that one knows that others observe one's appropriate behavior. The results of Studies 1 and 2 show that the (imagined) presence of others increases the effects of mortality salience on brand evaluations. People who are reminded of their mortality evaluate luxury brands more positive (Studies 1 and 2) and non-luxury brand more negative (Study 2) under conditions of social approval. This implies that self-esteem receives an extra boost when one knows that others observe and are aware of one's culturally prescribed behavior. These results extend work by Heine et al., (2002) and Mandel and Heine (1999) who demonstrate that people reminded of their mortality evaluate high status products and luxurious brands more favorably than participants in a control condition. The current studies show that not only luxury brands are evaluated more positively under conditions of mortality salience but also non-luxury brands are simultaneously evaluated more negatively when mortality-related thoughts are activated. This means that people not only reduce their experienced terror by expressing positive attitudes towards culturally valued items (ingroup favoritism) but also by expressing negative evaluations of items that are not valued in ones culture (outgroup derogation). In addition, the present results also show an important extension to this past work; the effects of activated death-thoughts on the evaluation of (non)luxury brands only occur when social presence is made salient. Without the scrutiny of others, luxury brands seem not to provide a solid source to bolster one's self-esteem. The present studies herewith contribute to the knowledge of terror management effects on consumer-related behavior. In future research it would be interesting to further unravel the effects of social presence in TMT-effects. Social impact theory predicts, for instance, that the total impact of others on a target person is a function of the strength, number and immediacy of the other (Latané, 1981). Jackson and Latané (1981) report that the effects of social presence increase when the number of observers increases. In the present context, it is plausible to assume that the effects of social presence, under conditions of mortality salience, become stronger

when the persons observing the behavior are significant others with whom one shares cultural norms and values. One would probably derive more self-esteem from the notion that similar others ‘approve’ one's behavior than when one receives approval from others that are dissimilar and don't share cultural norms and values. These results are of practical relevance because numerous omnipresent environmental stimuli, such as television programs (Liu and Smeesters, in press) and brands (Fransen et al., 2008) can activate mortality salience. The presence of these different stimuli may therefore influence consumer behavior through the activation of mortality-related thoughts. This influence seems particularly strong under conditions of social presence, that is, when consumers are not alone in a consumer situation (e.g., when shopping with friends or family). Acknowledgments The authors thank Karin Ludwig, Sarah Lehmann, Manuela Schliek and Andreas Bremer for assistance in data collection. References Arndt Jamie, Greenberg Jeff, Solomon Sheldon, Pyszczynski Tom. Suppression, accessibility of death-related thoughts, and cultural worldview defense: exploring the psychodynamics of terror management. Journal of Personality and Social Psychology 1997;73(1):5-18. Arndt Jamie, Solomon Sheldon, Kasser Tim, Sheldon KennonM. The urge to splurge: a terror management account of materialism and consumer behaviour. Journal of Consumer Psychology 2004;14(3):198–212. Bauman Zigmund. Life in fragments: essays in postmodern morality. Oxford: Blackwell; 1995. Baumeister RoyF. Self-esteem, self-presentation, and future interaction: a dilemma of reputation. Journal of Personality 1982;50(1):29–45. Dechesne Mark, Janssen Jacques, van Knippenberg Ad. Derogation and distancing as terror management strategies: the moderating role of need for closure and permeability of group boundaries. Journal of Personality and Social Psychology 2000;79(6):923–32. Fransen MariekeL, Fennis BobM, Pruyn AdTh, Das EnnyH. Rest in peace? Brand-induced mortality salience and consumer behaviour. Journal of Business Research 2008;61(10): 1053–61. Frey Dieter. Reactions to success and failure in public and in private conditions. Journal of Experimental Social Psychology 1978;14(2):172–9. Greenberg Jeff, Pyszczynski Tom, Solomon Sheldon. The causes and consequences of a need for self-esteem: a terror management theory. In: Baumeister Roy F, editor. Public self and private self. New York/Berlin: Springer-Verlag; 1986. p. 189–92. Greenberg Jeff, Pyszczynski Tom, Solomon Sheldon, Simon Linda. Role of consciousness and accessibility of death-related thoughts in mortality salience effects. Journal of Personality & Social Psychology 1994;67(4):627–37. Greenberg Jeff, Solomon Sheldon, Pyszczynski Tom. Terror management theory of selfesteem and cultural worldviews: empirical assessments and conceptual refinements. In: Zanna Mark P, editor. Advances in experimental social psychology, 29. Academic Press; 1997. p. 61-139. Heine StevenJ, Harihara Motoke, Niiya Yu. Terror management in Japan. Asian Journal of Social Psychology 2002;5(3):187–96. Jackson JeffreyM, Latané Bibb. All alone in front of all those people: stage fright as a function of number and type of co-performers and audience. Journal of Personality and Social Psychology 1981;40(1):73–85. Jonas Eva, Schimel Jeff, Greenberg Jeff, Pyszczynski Tom. The scrooge effect: evidence that mortality salience increases prosocial attitudes and behaviour. Personality and Social Psychology Bulletin 2002;28(10):1342–52. Kallgren CarlA, Reno RaymondR, Cialdini Robert. A focus theory of normative conduct: when norms do and do not affect behaviour. Personality and Social Psychology Bulletin 2000;26(8):1002–12. Latané Bibb. The psychology of social impact. American Psychologist 1981;36(4): 343–56. Leary MarkR. Interpersonal aspects of optimal self-esteem and the authentic self: comment. Psychological Inquiry 2003;14(1):52–4. Leary MarkR, Baumeister RoyF, Zanna MarkP. The nature and function of self-esteem: sociometer theory. Advances in experimental social psychology, vol. 32. San Diego, CA, US: Academic Press; 2000. p. 1-62. Leary MarkR, Downs DianeL, Kernis MichaelH. Interpersonal functions of the selfesteem motive: the self-esteem system as a sociometer. Efficacy, agency, and selfesteem. New York, NY, US: Plenum Press; 1995. p. 123–44. Leary MarkR, Haupt AlisonL, Strausser KristineS, Chokel JasonT. Calibrating the sociometer: the relationship between interpersonal appraisals and the state selfesteem. Journal of Personality and Social Psychology 1998;74(5):1290–9. Leary MarkR, Kowalski RobinM. Impression management: a literature review and twocomponent model. Psychological Bulletin 1990;107(1):34–47. Liu Jia, Smeesters Dirk. Have you seen the news today? The effect of death-related media contexts on brand preferences. Journal of Marketing Research (in press).

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Riordan CA, James MK, Dunaway FA. Interpersonal determinants of helping and the transgression–compliance relationship. The Journal of Social Psychology 2001;125(3): 365–72. Van Rompay ThomasJL, Vonk DoretteJ, Fransen MariekeL. The eye of the camera: effects of security cameras on pro-social behavior. Environment & Behavior 2009;41(1): 60–74.

Journal of Business Research 64 (2011) 34–38

Contents lists available at ScienceDirect

Journal of Business Research

Social perspectives of e-contact center for loyalty building JungKun Park a,⁎, HoEun Chung b, Brian Rutherford b a b

College of Technology (HDCS) University of Houston, Houston, TX 77204-6020, United States Purdue University, 812 W. State Street 314, West Lafayette, IN 47907, United States

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Article history: Received 1 April 2009 Received in revised form 1 July 2009 Accepted 1 September 2009 Keywords: E-contact center Interpersonal service quality Social value Satisfaction Loyalty

a b s t r a c t Recently, e-contact centers have gained popularity among online companies as a preferred channel to communicate with their customers. E-contact centers are respected among e-retailers and online customers because they provide customers value within a social construct. This research suggests that an e-contact center serves as an effective marketing vehicle, which can be used for establishing and maintaining desired relationships with customers. E-contact centers enhance the relationship between e-retailers and online customers by providing social values and quality interpersonal service to customers. Despite the strategic importance of e-contact centers in relation to customer loyalty, little attention has been given to the topic. To remedy this, the primary objective of this study is to assess the impacts of social elements (i.e. perceived social value and interpersonal service quality) delivered by e-contact centers on customers' loyalty formation processes. Loyalty formation process is parsimoniously explained by an integrative model, which incorporates interpersonal service quality, social value, retailer satisfaction, and e-contact center satisfaction constructs. Published by Elsevier Inc.

1. Introduction With the growth of online shopping, many e-retailers have begun to offer e-contact centers to reach their customers (Scholler and Larkin, 2001). With the help of advanced information technology, e-retailers can communicate with their customers more effectively via various types of interactive media: e-mails, text chatting, web-calls using computer-generated voice, virtual agents, and so forth. The forms of e-contact will keep evolving because customer service is subject to the development of technology (Parasuraman and Grewal, 2000). This development will undoubtedly be in the direction of enriching the interactive experience of customers. Responding to these trends, the e-interactive tools used in e-contact centers are replacing the roles of service employees in traditional retail settings, which provide a feeling of social presence to online customers. This characteristic of e-contact centers is important since the factor of human-to-human contact is associated with high levels of perceived service quality and customer satisfaction (Sergeant and Frenkel, 2000). An e-contact center can help to redeem e-retailers because a lack of human presence has been identified as one of the major problems faced by consumers wishing to engage in building loyalty. According to early research of online shopping (Goldwyn, 2003), most e-retailers have a low conversion rate, only 2 to 3%. One of the ⁎ Corresponding author. Tel.: +1 765 463 0151; fax: +1 713 743 4033. E-mail addresses: [email protected] (J. Park), [email protected] (H. Chung), [email protected] (B. Rutherford). 0148-2963/$ – see front matter. Published by Elsevier Inc. doi:10.1016/j.jbusres.2009.09.017

primary reasons for the low conversion rate is the lack of real-time customer service (Bernett and Jaramillo, 2001). Moreover, customers who use online interactive tools are more likely to complete an online transaction. Their conversion rates increase from 2% ∼ 3% to around 20% (Dukcevich, 2005). Given this increased conversion rate, it is meaningful for researchers and marketers to investigate how the emergence of e-contact centers influences the customer loyalty building process. In the current hyper-competitive online era, customer loyalty is the desired goal for companies because high loyalty coincides with consumers' positive behavioral intentions, such as spreading positive word-of-mouth (Dick and Basu, 1994), increased repurchasing intentions, and a willingness to pay price premiums (Aaker, 1991). In order to systemically examine the loyalty generation processes via e-contact centers, this study adapts the quality–value–loyalty chain (Parasuraman and Grewal, 2000), a key marketing construct that has been widely accepted as an effective battery for explaining the customer loyalty generation process (Cronin et al., 2000). Although investigating the influence of e-contact centers on each construct of the chain is worthy of research attention, little research has investigated the effects of social aspects of e-contact centers. The effects of computer-mediated interpersonal interaction between customers and e-agents on the perceived interpersonal quality, social value, and satisfaction chain have also been neglected. To fill this gap, the purpose of the present study is to investigate the following: (1) the effect of the service quality–satisfaction–loyalty chain/value– satisfaction–loyalty chain in the context of online service in an e-retail

J. Park et al. / Journal of Business Research 64 (2011) 34–38

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setting, and (2) to provide an integrated model to assess the effect of social aspects of e-contact centers on the e-loyalty formation process.

quality, value, and satisfaction chain on loyalty in the context of online retailers.

2. Conceptual framework

2.3. Service quality and interpersonal service quality

2.1. E-contact center

Service quality has long been a subject of interest for researchers examining consumer behavior (Cronin and Taylor, 1992). Different ways have been suggested in terms of defining the terms and measuring dimensions of service quality. While some researchers define service quality as attitudes on an overall evaluation (Cronin and Taylor, 1994), the widely accepted and most-used definition in the literature seems to be the one by Parasuraman et al. (1985), which defines service quality as a function of the differences between expectation and performance along the quality dimensions. Past research suggests that service quality is directly linked to loyalty (Bloemer et al., 1998). Although the term interpersonal service quality has not appeared in the literature, similar terms do exist. Brady and Cronin (2001) stress the importance of interaction quality when assessing overall service quality contending that the quality of service should include considering the quality of the interaction in service delivery. In other words, service is rendered by humans and for humans, which is interaction quality between customers and front line employees. In the present study, this concept is applied to the interaction between customers and e-agents. Some research delineates service quality as having two aspects. One aspect is a technical dimension, what is provided, and the other is a functional dimension, how the service is provided (Grönroos, 1983). For instance, Donabedian (1998) reports that patients heavily depend on the strength of relationship with service providers to evaluate overall service quality. In similar venues, e-contact centers with superior interpersonal service quality could be associated with delivering excellent functional service quality. The following hypotheses are generated from the previous discussion:

The call center has long been regarded as a powerful method for firms to connect with their customers (Feinberg et al., 2000). In today's Internet marketplace, e-contact centers have replaced this position. Seemingly serving similar functions as traditional call centers, e-contact centers are now equipped with completely transformed features. Compared to a traditional contact center, which relies on the limited source of the phone call or face-to-face interaction, e-contact centers usually have an integrated multichannel service encompassing the website, call center, email, webchat, and/or voice automated web-calls (Deitel et al., 2001). Through this breakthrough technology, online customers are now better served with more personalized support and reduced response time. Today's e-contact center not only connects a company with its customers, but also provides human-touched service, which is lacking in the general e-shopping experience. Past research has underscored the pivotal role of delivering human interactive services of e-contact centers in the context of online retailing where shoppers should experience solitude during the purchase period (Singh et al., 2001). Although it seems that consumers who experience human interactive features of e-contact centers are more likely to purchase (Dukcevich, 2005), that is not a direct indicator of consumer loyalty. However, it can be speculated that e-contact center users become loyal to an online firm because online consumers who experience “high-touch” customer service are more likely to be satisfied (Massad et al., 2006). Based on Kalakota and Whinston's (1997) work, e-contact center can influence to consumers from the the initial purchasing process while traditional contact centers are more involved with post purchase stages. Based on this research, examining the role of the e-contact center on online consumer consumption process is important as it may have significant implications for e-buying behavior. Effectively managed e-contact centers might be powerful weapons in the hypercompetitive online market where product differentiation or price competition becomes less meaningful compared to the brick-andmortar market (Rust and Lemon, 2001). 2.2. Quality, value, satisfaction, and loyalty Researchers have examined three key variables' impact on loyalty within a traditional marketing setting: quality, value, and satisfaction. Parasuraman and Grewal's (2000) work proposes a model comprised of quality, value, and loyalty. Meanwhile, Sweeney et al. (1999) investigates the relationship between service quality and perceived value. Patternson and Spreng (1997) examine the link between perceived value and satisfaction. Taylor and Baker's (1994) research assesses the relationship between service quality and satisfaction as a purchase intention process and Fullerton (2005) tests the relationship between service quality and loyalty with consideration of commitment in the context of retail service. Cronin et al. (2000) attempt to provide a holistic picture of the effects of quality, value, and customer satisfaction on consumer behavioral intention in the context of a service environment. Utilizing the three competing models from the extant literature, the current research concludes that a direct effect exists between service value, satisfaction, and behavioral intention and an indirect effect exists between service quality and behavioral intention mediated by service value and satisfaction. Despite the above trials, the intricate interrelationship between the service encounter constructs still needs to be probed and clarified. The issue needs more critical investigation in the context of the Internet environment. In fact, little attention has been given to the effect of the

H1. Consumer's perceived interpersonal service quality is likely to positively influence consumer satisfaction with the e-contact center. H2. Consumer's perceived interpersonal service quality is likely to positively influence consumer social value for online shopping. H3. Consumer's perceived interpersonal service quality is likely to positively influence consumer loyalty behavior to an e-contact center. 2.4. Social value The role of value has gained increasing attention as a means to achieve better market shares. While the argument of placing value among the quality, satisfaction, and loyalty chain is still ongoing, the resolution becomes simpler when the matter is considered from the consumers' perspectives on value because they usually are willing to complete transactions when perceived values are high (Holbrook, 1994). Researchers often define perceived value as a ratio of perceived benefits to perceived costs (Zeithaml, 1998). While consumer value is expressed as the trade-offs between give and take, the economic and emotional aspects of the concept are recognized in the literature (Gallarza and Saura, 2006). Therefore, it is logical to say that socially rewarding service from an e-contact center should give customers the emotional value they pursue. As for theoretical linkages, past research identifies a direct link between perceived value and loyalty (Parasuraman and Grewal, 2000) and linkages in the value–satisfaction–loyalty chain (Ryu et al., 2008). The present study takes the latter approach. 2.5. Satisfaction Satisfaction is recognized as a fundamental concept in understanding consumer behavior in the service context (Yi, 1990). The

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J. Park et al. / Journal of Business Research 64 (2011) 34–38

dominant underlying theme in defining customer satisfaction is the expectancy disconfirmation paradigm (Oliver, 1980). According to this paradigm, consumers form an expectation towards a product or service in advance and utilize it as a standard to make a comparison with actual performance. The discrepancy between prior expectation and perceived performance generates disconfirmation. Positive disconfirmation and confirmation tends to lead to satisfaction, while negative confirmation is likely to lead to dissatisfaction. While a shift of focus from satisfaction to loyalty strategies has occurred in the marketing literature (Oliver, 1999), the relationship between the concepts has been discussed thoroughly. In terms of observing the path from customer satisfaction to brand loyalty, direct and indirect effects have been researched. The traditional approach was to take satisfaction as an immediate antecedent of brand loyalty, whereas other studies have examined mediators such as perceived quality (Bitner, 1990) or attitude between the two variables (Oliver, 1997). The aforementioned background leads to the following hypotheses: H4. Consumer's social value is likely to positively influence satisfaction of e-contact center satisfaction. H5. Consumer satisfaction with an e-contact center is likely to positively influence loyalty behavior toward the e-contact center. H6. Consumer satisfaction with an e-contact center is likely to positively influence loyalty behavior toward the e-retailer.

Table 1 Reliabilities and confirmatory factor analysis properties. Factors Interpersonal service quality ISQ1 ISQ2 ISQ3 ISQ4 Satisfaction with e-contact center SEC1 SEC2 SEC3 Social value SV1 SV2 SV3 SV4 Loyalty to e-contact center LEC1 LEC2 LEC3 LEC4 Loyalty to e-retailer LTE1 LTE2 LTE3 LTE4

Factor loading

Item reliabilities

0.93 0.96 0.88 0.80

0.87 0.91 0.78 0.61

0.94 0.94 0.95

0.88 0.88 0.90

0.86 0.91 0.97 0.96

0.74 0.83 0.93 0.93

0.90 0.96 0.88 0.91

0.81 0.93 0.77 0.84

0.96 0.98 0.86 0.83

0.92 0.97 0.74 0.70

Cronbach's alphas

AVE

0.94

0.79

0.96

0.89

0.96

0.86

0.96

0.84

0.96

0.83

Goodness-of-fit: χ 2 138 : 290.18 = 0.00; CFI = 0.977; NFI = 0.958; GFI = 0.903; RMSEA = 0.064.

H7. Loyalty behavior for an e-contact center is likely to positively influence loyalty behavior for the e-retailer. Overall, the proposed conceptual model is presented in Fig. 1.

satisfaction with the customer service center (Eroglu and Machleit, 1990), social value (Babin et al., 1994), and loyalty (Atchariyachanvanich et al., 2006).

3. Methodology 4. Analysis and results A sample of respondents from an online panel was purchased from an independent marketing company with a nationwide pool of online consumers. The sample population was composed of consumers who had contacted at least one e-contact center operated by e-retailers within last three months. Two thousand randomly selected potential respondents were invited to participate. The obtained usable respondents totaled 343 (r = 17.15). Characteristics of the respondents included a mean age of 23 (males—40.5 and females—59.5). Measurement items were used with seven-point Likert-type scales (see Table 1). Interpersonal service quality was adapted from the service quality scale developed by Parasuraman et al. (1988),

4.1. Measurement model The measurement and structural models were performed with a two-step approach (Anderson and Gerbing, 1988). Using AMOS 16, confirmatory factor analysis (CFA) was performed with maximum likelihood estimation to analyze the constructs' underlying structures. Relevant measurement properties, such as confirmation factor loadings and reliabilities, are presented in Table 1. The average variance extracted (AVE) for the constructs with multiple measures all exceed the minimum level of 0.50 (Fornell and Larcher, 1981). All

Fig. 1. The proposed model of Social Influence on quality–value–satisfaction–loyalty chain.

J. Park et al. / Journal of Business Research 64 (2011) 34–38

the construct alphas exceed the suggested minimum level of 0.70 (Nunnally, 1978). Factor loadings of each construct are statistically significant and sufficient so that the underlying constructs are acceptable (see Table 1).

Table 3 Structural model results. Hypothesis Structural path H1

4.2. Hypotheses testing

H2

As the next step, the structural equation model examines the proposed model. The model shows acceptable goodness-of-fit (see Table 3). Overall fit of the structural model was assessed initially by examining the χ2 statistics with additional measures of goodness-offit: comparative fit index (CFI), normalized fit index (NFI), goodness of fit index (GFI), and root mean square error of approximation (RMESA). The indices reveal that the model is relatively well fitted (χ2 = 290.18 (df = 138), p = 0.00; χ2/df = 2.10; CFI = 0.98; NFI = −0.96; GFI = 0.90; RMSEA = 0.064). The normed chi-square statistic is 2.44 (see Table 2). The suggested acceptance level of a good fit model requires that the obtained CFI, NFI, and GFI should be greater than or equal to 0.90 and an acceptable value of RMSEA should range from 0.05 to 0.08 (Hair et al., 2006). Table 3 summarizes the results from testing the hypotheses. The results of the path coefficient support all the hypotheses except H3. Hypothesis 1, which proposes a positive causal relationship between interpersonal service quality and satisfaction with e-contact centers is supported (γ = 0.98, t = 19.84, p < 0.01). As expected in H2, interpersonal service quality significantly affects social value (γ = 0.30, t = 4.31, p < 0.01). However, a positive relationship between interpersonal service quality and loyalty to e-contact centers is not supported in H3. The results of the first three hypotheses indicate that high levels of interpersonal service quality may boost customer satisfaction levels and create some degree of social value, but are not sufficient for engendering loyalty. This may be because interpersonal touches in the technology might contribute to gratifying customers on the spot. This could be a reconfirmation of effect of the quality– satisfaction–loyalty chain. H4, which hypothesizes a positive causal relationship between social value and satisfaction with e-contact centers is supported (γ = 0.13, t = 3.49, p < 0.01). Customers who perceived high social value during the contact are more likely to be satisfied with the e-contact center experience. H5, the positive relationship between satisfaction with an e-contact center and loyalty to the e-contact center, is supported (γ = 0.74, t = 8.40, p < 0.01). H6, which hypothesizes a positive causal relationship between satisfaction with the e-contact center and loyalty to the e-retailer, is also supported (γ = 0.55, t = 5.28, p < 0.01). Finally, loyalty to the econtact center influences loyalty to the e-retailer, supporting hypothesis 7 (γ = 0.45, t = 7.24, p < 0.0.05). 5. Conclusion and implications The primary purpose of this study is to explore the role of social aspects of e-contact centers for e-loyalty building. To test the social

Table 2 Construct means, standard deviations, and correlations. ISQ ISQ SV SEC LEC LTE

1.00 0.29⁎ 0.86⁎ 0.71⁎ 0.37⁎

SV 1.00 0.34⁎ 0.55⁎ 0.17⁎

SEC

1.00 0.80⁎ 0.40⁎

LEC

1.00 0.38⁎

LTE

Means

SD

1.00

4.93 3.37 4.68 4.28 4.98

1.49 1.68 1.61 1.73 1.43

Note: ISQ indicates interpersonal service quality; SV indicates social value; SEC indicates satisfaction with e-contact center; LEC indicates loyalty with e-contact center; LR indicates loyalty to e-retailer. ⁎ p < 0.05.

37

H3 H4 H5 H6 H7

Interpersonal service quality → satisfaction with e-contact center Interpersonal service quality → social value Interpersonal service quality → loyalty to e-contact center Social value → satisfaction with e-contact center Satisfaction with e-contact center → loyalty to e-contact center Satisfaction with e-contact center → loyalty to e-retailer Loyalty to e-contact center → loyalty to e-retailer

Coefficient t-value

Test results

0.98

19.84⁎⁎ Accepted

0.30

4.31⁎⁎ Accepted

0.13

1.36

0.13

3.49⁎⁎ Accepted

0.74

8.40⁎⁎ Accepted

0.55

5.28⁎⁎ Accepted

0.45

7.24⁎⁎ Accepted

Rejected

Goodness-of-fit: χ2 = 291.314, p = 0.00; CFI = 0.977; NFI = 0.958; GFI = 0.902; RMSEA = 0.064. **p < 0.01.

aspects, interpersonal service quality and social values were examined. In addition the traditional service quality–satisfaction–loyalty chain and the value–satisfaction–loyalty chain apply in online retail settings. The test results achieve partial support of the initial predictions. First, the results reconfirm the strategic importance of the service quality– satisfaction–loyalty chain in the context of e-contact centers. The chain is effective despite only using interpersonal service quality. In addition, value–satisfaction–loyalty is also supported, which agrees with previous research (Patternson and Spreng, 1997). The results provide additional evidence for robustness of the chains. Second, it seems clear that high interpersonal service quality and social value greatly influence satisfaction with e-contact centers and this, in turn, influences e-loyalty. So, adding human interactive features to e-contact centers not only provides fiscal benefits, by reducing or eliminating the number of front line employees, but also contributes to gaining more satisfied patrons. Despite the similar positive effect on satisfaction, interpersonal service quality has no direct effect on increasing customer loyalty levels, while social value has direct and indirect effects on loyalty. These results suggest the possibility of social value becoming the ultimate strategic weapon to e-retailers in achieving e-loyalty. After all, the missing element in the popular contemporary retail platform, the Internet, is human contact. Third, e-contact centers play an important role in forming e-loyalty. Customers who are satisfied with their encounters with e-contact centers are likely to be loyal to the e-contact center and prone to return to the e-retailer. While the debate of determining factors for creating e-loyalty is still ongoing, investing in e-centers are a necessity in today's highly competitive online market. In practice, established companies such as IBM and AT&T are already moving ahead by implementing intelligent virtual agents for contact center automation systems. The study of combinations of variables of the quality–value– satisfaction–loyalty chain at traditional call centers has received considerable attention. However, the e-contact center setting has not been examined as extensively. This study extends existing service quality, value, and satisfaction theories by focusing on the online environment, a vastly popular channel of communication and business transactions. As more and more e-retailers adopt new technologies for e-contact centers, knowledge about what customers perceive as high service quality will be crucial. E-retailers need to be informed of the specific customer expectations of the e-contact center, which, as this study has shown, are different from those at the traditional call center. E-contact centers can lower demand for traditional call centers and, therefore, provide significant cost savings to e-retailers. This study also offers further support for the links

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among perceived service quality, satisfaction and loyalty, and also interpersonal service quality and social value of customers. This should offer e-retailers further motivation to understand how they can improve service quality and create customer value through their e-contact centers. 6. Limitation and future research As in all research, the present study is subject to some empirical limitations. First, this study was conducted based on general online markets and is not industry specific. The magnitude with which consumers perceive the effects of e-contact centers on the loyalty formation process may vary depending on industries. Second, due to the limitation of the survey method, this study is unable to identify the specific types of feelings or the level of attachment respondents experienced during their interactions with e-contact centers. These issues provide challenging topics for future studies. Future considerations may also include a more complicated relationship between customer satisfaction and loyalty toward the e-retailer. In other words, satisfaction with service at the e-contact center may not lead to loyalty toward the e-retailer as measured by purchasing intentions, but simply loyalty toward the e-contact center as measured by repeated visits to the e-contact center. While the present study tests both types of loyalty, it does not examine them separately. A future study that would examine these two cases separately would be significant in making this clarification. Finally, customer services that are offered through the Internet evolve very rapidly. Future research must focus on keeping up with latest technological advancements and their effects on contact centers. References Aaker DA. Managing brand equity: capitalizing on the value of a brand name. NY: The Free Press; 1991. Anderson JC, Gerbing DW. Structural modeling in practice: a review and recommended two-step approach. Psychol Bull 1988;103(3):411–23. Atchariyachanvanich K, Okada H, Sonehara N. What keeps online customers repurchasing through the Internet. ACM SIGecom Exch 2006;6(2):47–57. Babin BJ, William RD, Mitch G. Work and/or fun: measuring hedonic and utilitarian shopping value. J Con Res 1994;20(4):644–56. Bernett H, Jaramillo ML. Assessing web-enabled call center technologies. IEEE 2001;3 (3):24–30 May/June. Bitner MJ. Evaluating service encounters: the effects of physical surroundings and employee responses. J Mark 1990;54:69–82 April. Bloemer J, Ruyter K, Wetzels M. On the relationship between perceived quality, service loyalty and switching costs. Int J Ind Manag 1998;9(5):436–53. Brady MK, Cronin J. Some new thought on conceptualizing perceived service quality: a hierarchical approach. J Mark 2001;65(3):34–9 July. Cronin JJ, Taylor SA. Measuring service quality: a reexamination and extension. J Mark 1992;56:55–68 July. Ryu K, Han H, Kim TH. The relationships among overall quick-causal restaurant image, perceived value, customer satisfaction, and behavioral intentions. Int J Hosp Manag 2008;27:459–69. Cronin JJ, Taylor SA. SERVPERF versus SERVQUAL: reconciling performance based and perceptions-minus-expectations measurement of service quality. J Mark 1994;58: 125–31 January. Rust RT, Lemon KN. E-service and the consumer. Int J Elecron Comm 2001;5(3):85–101.

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Journal of Business Research 64 (2011) 39–44

Contents lists available at ScienceDirect

Journal of Business Research

Investigating mediators between corporate reputation and customer citizenship behaviors Boris Bartikowski a,⁎, Gianfranco Walsh b a b

Euromed Management, France University Koblenz-Landau, Germany

a r t i c l e

i n f o

Article history: Received 1 April 2009 Received in revised form 1 July 2009 Accepted 1 September 2009 Keywords: Commitment Customer-based corporate reputation Customer citizenship behavior Loyalty Multiple mediation

a b s t r a c t Recent corporate reputation research focuses on customers as an important stakeholder group for whom firm reputation matters. The authors hypothesize that customer-based corporate reputation (CBR) may affect customer citizenship behaviors (CCB) and that both commitment and loyalty mediate the CBR–CCB relationship. The tests of the hypotheses use a sample of 583 service customers who evaluate the reputation of service firms. These results suggest that commitment and loyalty mediate the relationship between CBR and one type of CCB, that is, helping the company. The authors discuss the implications for marketing research and practice. © 2009 Elsevier Inc. All rights reserved.

1. Introduction Research into the causal relationships between corporate reputation and customer-outcome variables remains incomplete. Despite agreement that positive perceptions of a firm's reputation relate positively to customer satisfaction, trust, loyalty, and word-of-mouth behavior (e.g., Oliver and DeSarbo, 1988; Roberts and Dowling, 2002; Walsh et al., 2009), the way in which corporate reputation affects downstream variables, in terms of customers' discretionary behaviors, is not clear. Customers patronizing highly reputed firms tend to be more loyal and more committed (Sung and Yang, 2008; Walsh et al., 2009). These customers may also support highly reputed organizations with various voluntary, extra-role behaviors, such as helping other customers improve the service delivery or providing valuable feedback to the company. Such customer citizenship behaviors (CCB) increasingly appear conductive to effective organizational functioning (e.g., Bove et al., 2009; Gouthier and Schmid, 2003; Groth, 2005; Singh, 2000) and thus seem especially relevant to service firms, which cannot achieve significant productivity gains through capital substitution (Oliva and Sterman, 2001). So does a good corporate reputation directly improve CCBs? If so, how are reputation and CCBs causally related to other behaviorally relevant variables, in terms of commitment and loyalty? Services marketing research underlines the importance of mediator effects of relational variables, such as satisfaction or commitment, that account for variations in behavioral outcomes (Hennig-Thurau et al., 2002; Walsh et al., 2006; Wang et al., 2003). The importance of mediator variables arises from their ⁎ Corresponding author. E-mail address: [email protected] (B. Bartikowski). 0148-2963/$ – see front matter © 2009 Elsevier Inc. All rights reserved. doi:10.1016/j.jbusres.2009.09.018

ability to enhance the understanding of causal relationships between variables. Insights into how corporate reputation, customer commitment, and loyalty work together to unleash different types of CCBs represent important steps for increasing understanding of the drivers of discretionary consumer behaviors. However, no empirical study to date explores the mediator effects of commitment and loyalty on the relationship between firm reputation and CCBs. Against this background, this study extends previous research by embedding customer-based corporate reputation (CBR) in a conceptual model that examines the direct effects of CBR on commitment, loyalty, and CCBs. In addition, the authors explore whether the postulated direct effects of CBR on CCBs may experience mediation by customer commitment and loyalty. The findings offer new insights into the role of CBR and the effects on key marketing outcomes, with important implications for marketing theory and practice. 2. Customer-based corporate reputation A strong corporate reputation provides a company signal and encourages reduced transaction costs, as well as other outcomes that benefit the company (e.g., Caruana et al., 2004; Einwiller et al., 2006; Rose and Thomsen, 2004; Shapiro, 1983). Fombrun (1996) and Sung and Yang (2008) suggest that customers of well-reputed organizations engage in supportive behaviors. Therefore, a good reputation pays off because customers attribute higher levels of competence and quality to the firm and therefore support that firm. To capture the reputation perceptions of customers, Walsh and Beatty (2007, p. 129) advance the concept of customer-based corporate reputation (CBR), which they define as “the customer's overall evaluation of a firm based on his or her reactions to

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the firm's goods, services, communication activities, interactions with the firm and/or its representatives or constituencies (such as employees, management, or other customers) and/or known corporate activities.” Their CBR scale captures five dimensions of reputation, as perceived by current customers of the firm: customer orientation employer quality, financial strength, product and service quality, and social responsibility. 3. Hypotheses The conceptual model in Fig. 1 draws on signaling, cognitive consistency, and self-concept theories to explain the direct effects of CBR. Motivated reasoning theory (Kunda, 1990) provides a basis for explaining the mediator effects of commitment and loyalty in CBR– CCB relationships. 3.1. Direct effects Cognitive consistency theories (e.g., Heider, 1946; Osgood and Tannenbaum, 1955) suggest that people strive to maintain psychological harmony among their beliefs, attitudes, and behaviors. Inconsistencies cause psychological discomfort, which people seek to avoid by developing intentions and engaging in behaviors that are consistent with their beliefs. When customers attribute a good reputation to a service firm, they likely have belief-consistent feelings of commitment, favorable intentions to continue doing business with the company, or other forms of goodwill to express toward the company (e.g., Bettencourt, 1997; Zeithaml et al., 1996). For example, Einwiller et al. (2006) posit that customers' identification with a company results in commitment, such that customers with high identification should have positive thoughts and feelings about the company. Similarly, Bennett and Gabriel (2001) argue that a favorable corporate reputation provides customers with repeated positive reinforcement, which creates commitment-inducing emotional bonds. Hypothesis 1. CBR has a positive impact on customer commitment. A firm's good reputation also is a signal of sound company behavior toward market transactions overall, such that a better reputation engenders not only higher levels of commitment but also greater loyalty intentions. A firm's good reputation can reduce customers' perceived risk and motivate them to do business with the firm (Fombrun and Shanley, 1990; Spence, 1973). Companies may

increase the likelihood that customers grant them future business by serving them with high-quality services, integrity, and honesty (e.g., Andreassen and Lindestad, 1998; Barich and Kotler, 1991; Walsh et al., 2009). Hypothesis 2. CBR has a positive impact on customer loyalty. Fombrun (1996) also argues that a good corporate reputation can translate into stakeholder goodwill toward the firm. In this context, customer citizenship behaviors may represent an expression of a customer's goodwill that results from a good firm reputation. This investigation considers two dimensions of CCBs: customers' willingness to help other customers and to help the company (e.g., Bove et al., 2009; Groth, 2005; Gruen, 1995). A customer who holds a firm in high esteem may support this firm through discretionary engagement, or beliefconsistent behavior. In addition, CCBs may result from a customer's desire to exhibit an affiliation with a highly reputed firm (Gruen, 1995). Specifically, research into symbolic consumption behavior suggests that customers use value-expressive criteria to enhance their self-concepts. The ideal social self-concept is an image of the self that the person hopes others will perceive (Sirgy, 1982). Firms with a good reputation possess attributes that customers may want others to associate with their own selves, so supporting a highly reputed firm through discretionary behaviors that either the firm or other customers recognize may help customers reach greater congruity with their ideal social selves. In turn, a good reputation should prompt CCBs in the form of helping other customers and helping the service firm. Hypothesis 3. CBR has a positive impact on the helping other customers dimension of customer citizenship behaviors. Hypothesis 4. CBR has a positive impact on the helping the company dimension of customer citizenship behaviors. 3.2. Mediated effects By drawing on previous literature, the conceptual model (Fig. 1) suggests mediations of the relationships between CBR and CCB by customer commitment and loyalty. Morgan and Hunt (1994) consider commitment a key mediating variable in successful business relations that promotes efficiency, productivity, and effectiveness. Partners committed to a business relationship increase their cooperative behaviors because of their desire to make the relationship work and to achieve mutual goals.

Fig. 1. Conceptual model.

B. Bartikowski, G. Walsh / Journal of Business Research 64 (2011) 39–44

Similarly, Raj (1982) shows that customer loyalty mediates the effect of advertising signals on future purchase intentions. Prior studies also reveal that loyal customers possess more experience with and knowledge of the provider than do non-loyal customers. This knowledge may enable them to contribute more effectively to the coproduction of the service (e.g., Lengnick-Hall, 1996) or provide social benefits to other customers (e.g., Goodwin and Gremler, 1996). The potential mediating effects of commitment and loyalty in the CBR– CCB relationships reflect motivated reasoning theory (Kunda, 1990), which suggests that two types of goals motivate behavior: accuracy and directional. An accuracy goal is the desire to form or hold valid, accurate attitudes, whereas directional goals stem from a defense motive. Both commitment and intentional loyalty may result from purchase or ego involvement (e.g., Beatty et al., 1988; Chiung-Ju and Wen-Hung, 2008; Olsen, 2007; Schramm-Klein et al., 2008). High involvement relates to indepth information processing and the desire to increase conclusion accuracy. However, according to Kunda (1990), systematic in-depth processing does not eliminate biased conclusions. Highly involved persons may have strongly anchored attitudes, which lead them to reject alternative opinions (Greenwald and Leavitt, 1984; Sherif and Hovland, 1961). Thus, highly committed and intentionally loyal customers may maintain both accuracy and directional goals related to preserving and defending their beliefs about the firm's reputation. Customer commitment and intentional loyalty are similar constructs, to the extent that both associate with greater preference stability, the formation of defense motives, and directional goals, all of which may bias cognitive evaluations of reputation signals to support desired conclusions (e.g., Crosby and Taylor, 1983; Kunda, 1999). Thus, both variables may mediate the effects of CBR on CCBs. Hypothesis 5. Customer commitment mediates the effect of CBR on the (a) helping other customers dimension and (b) helping the company dimension of customer citizenship behaviors. Hypothesis 6a. Customer loyalty intentions mediate the effect of CBR on the (a) helping other customers dimension and (b) helping the company dimension of customer citizenship behaviors. 4. Method 4.1. Data collection and measures Survey data gathered from a sample of 583 French service customers help test the hypotheses. Respondents completed a paper-and-pencil questionnaire about a current provider in one of three service categories (banking, retailing, or fast-food restaurants). They used five-point Likert scales (1=strongly disagree, 5=strongly agree). The five dimensions of CBR, adapted from Walsh and Beatty (2007), each contain three-item measures. The measures of the remaining constructs also include three items. Items for commitment come from Hennig-Thurau et al. (2002), those for customer loyalty are from Arnold and Reynolds (2003), and the two dimensions of customer citizenship behavior come from Groth (2005). All items appear in the Appendix. 4.2. Measurement evaluation In the confirmatory factor analysis (CFA) run to evaluate the measurement, CBR represents a reflective, second-order construct that consists of five dimensions (Walsh and Beatty, 2007). The CFA indicates excellent model fit (χ2 (309)=2.27; root mean squared error of approximation [RMSEA]=.047; confirmatory fit index [CFI]=.95; Tucker– Lewis index [TLI]=.94), and the composite reliability (Jöreskog's ρ) is greater than .79 for all constructs (Table 1). All constructs also achieve discriminant validity, because the variance extracted by the factors is greater than the squared correlation between them (Fornell and Larcker, 1981).

41

Table 1 Convergent and discriminant validity.

(1) (2) (3) (4) (5)

CBR Commitment Loyalty CCB 1 (help other customers) CCB 2 (help the company)

(1)

(2)

.61 .38 .49 .07 .25

.68 .50 .04 .31

(3)

.56 .04 .27

(4)

.72 .15

(5)

ρ

.67

.88 .86 .79 .88 .85

Notes: values on the main diagonal are the average variances extracted, values below the diagonal are the squared correlations. CBR = customer-based corporate reputation. CCB = customer citizenship behavior.

4.3. Hypotheses testing The test of the study's hypotheses entails a two-step analysis. First, structural equation modeling (SEM) and bootstrapping in AMOS 7.0 serves to investigate the direct effects of CBR on commitment, loyalty, and the two dimensions of CCB. As mediator variables, commitment and loyalty must relate positively to both types of citizenship behaviors. This basic condition of mediation (Baron and Kenny, 1986) i tested with SEM. Second, the investigation of the specific mediated effects associated with commitment and loyalty relies on Preacher and Hayes's (2008) approach. The specific mediated effect of a variable represents the ability of that variable to mediate the effect of an independent variable on a dependent variable when the model includes further mediators. Results from the previous CFA show that commitment and loyalty correlate strongly (Table 1). Therefore, employing a series of mediation analysis (one for each mediator) across the causal steps proposed by Baron and Kenny (1986) is critical. Summing separately calculated, specific mediated effects cannot reveal the accurate total mediated effect, because the separate effects may be due to several (correlated) mediators (Bollen, 1987; Cheung, 2007). Thus, this study uses Preacher and Hayes's (2008) application of the Sobel test to investigate the specific mediated effects of multiple mediators. 4.3.1. Direct effects In the specification of the structural model (Fig. 1), the residuals of the two mediators may covary (Preacher and Hayes, 2008). The model fit indices fall within the commonly accepted ranges for very good fit (χ2 (310)=2.41; RMSEA=.049; CFI=.95; TLI=.94). Bootstrapping with 2000 samples enables the computation of the unstandardized estimates of the direct effects, 95% bias-corrected confidence intervals, and p-values (Jones et al., 2008). The direct relations between CBR and the four dependent variables are all positive and significantly different from 0 (Table 2), in support of Hypotheses 1–4. A good reputation improves loyalty, as previous research shows (Walsh et al., 2009), as well as commitment and both dimensions of citizenship behaviors. Regarding the direct effects of the putative mediator variables on CCBs (not reported in Table 1), strong and statistically significant (p<.01) direct effects exist from commitment (.35) and loyalty (.20) to helping the company. However, the effects on helping other customers are considerably weaker Table 2 Unstandardized direct and specific indirect effects. Effect CIlow CIhigh Support?

Hypothesis Direct effects (SEM) H1 CBR H2 CBR H3 CBR H4 CBR

➔ ➔ ➔ ➔

Commitment Loyalty intentions Helping other customers Helping the company

.95 .79 .32 .38

Specific indirect effects (procedure according to Preacher and H5a Commitment ➔ Helping other customers – H5b Commitment ➔ Helping the company .11 H6a Loyalty intentions ➔ Helping other customers – H6b Loyalty intentions ➔ Helping the company .15 *p < .05. **p < .01.

.79 .66 .08 .05

1.14 .94 .59 .71

Yes Yes Yes Yes

Hayes, 2008) – – No .07 .16 Yes – – No .11 .20 Yes

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(commitment .06; loyalty −.01) and statistically not distinguishable from 0 (p>.05). Because neither commitment nor loyalty relates statistically to helping other customers, mediation does not receive support for this outcome variable, and this study must reject Hypotheses 5a and 6a. 4.3.2. Indirect effects Preacher and Hayes's (2008) propositions for investigating multiple mediation are based on bootstrapping procedures with the observed variables. This approach therefore cannot account for measurement error, as SEM does. Their application instead can quantify specific indirect effects associated with each mediator, which currently is not possible in AMOS. This study therefore uses regression-based factor scores as the data pertaining to CBR, commitment, loyalty, and helping the company. Again, bootstrapping with 2000 samples provides the effects, 95% bias-corrected confidence intervals, and p-values for the indirect and the contrast effects. The results show that CBR explains a substantial proportion of variance (R2 = .37; F(3, 579) = 114.03, p<.01). All direct and indirect effects are statistically significant (p<.01), and their confidence intervals are narrow (Table 2). Both, commitment and loyalty intentions mediate the relationship between CBR and customers' willingness to help the company. The specific indirect effects of .11 for commitment and .15 for loyalty (p <.01; see Table 2) offer support for Hypotheses 5b and 6b. Evidence of partial mediation derives from the direct effect of CBR on helping the company, which is strong (.16) and statistically significant (p <.01) (not reported in Table 1). 5. Discussion and implications Although corporate reputation attracts considerable attention in marketing practice and research, marketers know little about its effects on important downstream variables when the individual customer represents the unit of analysis. To address this void, this study offers a model of direct and multiple mediated effects that links CBR to customer commitment, loyalty, and citizenship behaviors. All but two of the Hypotheses 5a and 6a receive support from the data (Table 2). In the following, the authors discuss some implications of these results for marketing research and practice, and highlight the study's limitations. 5.1. Theoretical implications Customer-based corporate reputation positively influences customer commitment (Hypothesis 1), loyalty (Hypothesis 2), and citizenship behaviors with regard to helping other customers (Hypothesis 3) and helping the company (Hypothesis 4). The findings therefore support the idea that a positive reputation represents a quality signal and promise, which increases the likelihood that customers engage in favorable behaviors toward the service firm. Establishing a strong relationship between CBR and CCB represents an important extension of existing reputation literature, which hitherto neglects most discretionary customer behavior (Helm et al., 2005; Walsh et al., 2009). This study's findings also provide evidence that indirect relations between reputation and discretionary customer behaviors are not straightforward. As mediators, commitment and loyalty function differently, depending on the type of CCB. Mediated effects exist only for customers' willingness to help the company, not for their willingness to help other customers. This unexpected finding may reflect opportunistic behaviors; that is, committed, loyal customers may prefer discretionary behaviors that the service firm can observe, because they believe such actions will lead to future benefits for them. In contrast, helping other customers prompts no reward from or palpable service improvements by the firm for the customer. Relational variables thus may derive from a customer's conviction that remaining in a relationship yields higher net benefits than does terminating it (e.g., Hennig-Thurau et al., 2002). A growing body of literature differentiates the emotional, hedonic or affective aspects from more rational, calculative commitment, and

researchers also underline differences between attitudinal and intentional loyalty (e.g., Evanschitzky et al., 2006). The affective, emotional, or hedonic and rational or calculative aspects of commitment and loyalty may differentially mediate the relationships between reputation and CCB. Further research should explore conditions in which a good reputation leads to altruistic behaviors in the form of helping other customers. A strong and significant direct effect also exists from CBR to helping other customers, as hypothesized. This finding is in line with the rationale derived from self-concept theories. According to these theories, customers may use the reputational characteristics of the firm to enhance their selfconcepts, in which case customers of a highly reputed firm may help other customers because doing so enables them to represent good causes. This finding has great practical relevance. Although this study highlights the importance of corporate reputation in relation to key marketing outcomes, further work could extend the findings. The clarion call for increased marketing accountability (Ambler, 2000) demands that corporate reputation managers demonstrate how investments in reputation affect the bottom line. Additional studies could explore the relationship between CBR and monetary outcomes as an important extension of reputation literature, which hitherto focuses mostly on non-monetary outcomes. Another enlightening research path might determine category effects in reputation–outcome relationships. For example, researchers could consider factors such as the degree of customer participation in service delivery or the risk related to a service type as potential moderators of the CBR–outcome relationships. Although not stated as a primary goal, this study demonstrates that the CBR scale has sound psychometric properties and is applicable in France, whereas previously, studies apply the CBR scale only in the United States and Germany (Walsh and Beatty, 2007; Walsh et al., 2009), Further studies in other countries could determine if service firms and consumers' perceptions differ. Finally, studies using the CBR scale could opt against an ad hoc replication and instead attempt to identify additional, perhaps culture-specific, CBR dimensions. Using exploratory interviews, researchers could develop a CBR scale that encompasses the original five CBR dimensions, as well as new, potentially country-specific dimensions. For example, in the United States and many countries in the European Union, more and more organizations use diversity management to retain valuable human resources, increase productivity, and generate a culture of growth (Harris et al., 2003). A new dimension in some countries therefore may refer to customers' expectations of diversity in a service firm's workforce, pertaining to gender, age, or ethnic group, as well as the company's adherence to diversity management principles. 5.2. Managerial implications Perhaps the most important managerial implication that arises from this study's findings is the return on reputation. The findings show that a good reputation prompts CCB and positively affects customer commitment and loyalty. For practitioners, the CBR–CCB link is particularly intriguing. Customer integration appears to provide the most effective way to increase service productivity (Gouthier and Schmid, 2003; Lovelock and Young, 1979), such that service firms that invest in improving their reputation may reap benefits that positively affect their bottom line. Yet the results of this study show unexpectedly that only CBR has a direct positive effect on helping other customers. Commitment and loyalty building programs may improve customer collaboration in terms of helping the firm but be less effective in increasing customers' willingness to help other customers. These results clearly suggest that managers who want to increase helpful customer-to-customer interactions should promote reputation-building programs. The strong relationships between CBR and customer commitment and loyalty appear equally relevant. As services marketing literature notes, fostering customer commitment to the service firm is crucial for the positive effects on important marketing outcomes (e.g., Hennig-Thurau et al., 2002). The findings herein highlight the role of CBR in fostering commitment; service firms thus should monitor and, when necessary,

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improve their corporate reputation. Managers can use the CBR scale to gather benchmark data about the levels of customers' perceived corporate reputation and conduct periodic checks to measure changes or improvements in the outcomes. Such reputation monitoring could rely on an online panel, which would enable the firm to engage with and learn from customers over time. 5.3. Conclusion and limitations Several limitations exist in this study. First, the conceptual model derives from extant literature but not qualitative fieldwork. An approach involving interviews with service customers and managers might provide additional insights that current literature does not reveal (Song et al., 2008). Second, this research focuses only on the affective and intentional aspects of commitment and loyalty as mediator variables in reputation– outcome relationships. Third, customer citizenship behavior appears as a two-dimensional construct in this study, though other research proposes a greater variety of citizenship behaviors (e.g., Bove et al., 2009; Groth, 2005). Expressions of such behaviors, such as the propensity to engage in word-of-mouth recommendations (Groth, 2005) or arriving on time for appointments (Bove et al., 2009), may lead to different results. Researchers therefore should continue to consider these important issues. Appendix A Latent constructs Measure

Adapted from

CBR Customer orientation Has employees who treat customers courteously Is really concerned about its customers Treats its customers fairly Good employer Treats its people well Has management who pays much attention to the needs of its employees Maintains high standards in the way that it treats people Reliable and financially strong company Clearly outperforms competitors Recognizes and takes advantage of market opportunities Has strong prospects for future growth Product and service quality Offers high quality products and services Stands behind the services that it offers Develops innovative services Social and environmental responsibility Would reduce its profits to ensure a clean environment Is environmentally responsible Is a company that supports good causes Commitment I am very committed to this company. My relationship with this company means a lot to me. If this company would not exist any longer, it would be a hard loss for me. Loyalty I am a truly loyal customer of this company. I have a very good relationship with this company. I will certainly remain a customer of this service firm. Customer citizenship behavior: helping other customers Based on your past experience with this firm, how likely are you to…? … teach a friend how to use the service correctly. … help other shoppers when they don't know how to use this service. … explain to other customers how to use the service correctly. Customer citizenship behavior: helping the company Based on your past experience with this firm, how likely are you to…? … provide information when surveyed by the business. … provide helpful feedback to customer service. … inform the firm about the service provided by this employee.

Walsh and Beatty (2007)

Hennig-Thurau et al. (2002)

Arnold and Reynolds (2003)

Groth (2005)

43

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Journal of Business Research

Eliciting and estimating reservation price: A semi-compensatory approach☆ Sigal Kaplan ⁎, Shlomo Bekhor, Yoram Shiftan Transportation Research Institute, Technion-Israel Institute of Technology, Technion Campus, Haifa 32000, Israel

a r t i c l e

i n f o

Article history: Received 1 April 2009 Received in revised form 1 July 2009 Accepted 1 September 2009 Keywords: Price acceptability range Ceiling reservation price Direct elicitation methods Two-stage model

a b s t r a c t This study proposes a two-stage method to elicit consumers' price acceptability range. The method combines a conjunctive stage to elicit price acceptability limits with a utility-based stage to choose a preferred product variation. The method is efficient in choice situations entailing many multi-attribute product variations under partial information conditions. A semi-compensatory model complements the method by jointly representing the conjunctive stage with multiple ordered-response models and the choice stage with a multinomial logit model. A case study of ceiling reservation price (CRP) elicitation for students' rental apartment choice shows (i) CRP distribution for different product variations, (ii) model estimation unraveling CRP determinants, and (iii) linkage between CRP and transaction price. © 2009 Elsevier Inc. All rights reserved.

1. Introduction The immense variety of product variations typical of digital economy poses a new challenge for eliciting price acceptability range in a behaviorally realistic and efficient manner with existing methods. Direct surveys, namely buying-response to priced products (Gabor and Granger, 1969), own-category procedure (e.g., Cox, 1986; Monroe, 1971), and open-ended questions (e.g., Janiszewski and Lichtenstein, 1999; Rao and Sieben, 1992), refer to a single product variation. Encompassing a wide range of product variations by using pre-specified product descriptions is burdensome and expensive. Using instead general product descriptions generates inconsistencies since people may conceptualize different reference product variations. Conjoint analysis (e.g., Jedidi and Zhang, 2002; Kohli and Mahajan, 1991) and choice-based experiments (e.g., Chung and Rao, 2003; Jedidi et al., 2003) handle several product variations simultaneously. However, these methods assume that consumers use utility maximization as sole cognitive decision process while being fully informed regarding every product variation in the universal realm. This assumption is behaviorally realistic only in choice situations involving a limited number of alternatives (Payne, 1976; Shocker et al., 1991). Market data analysis relies on recurrent actual transactions. Traditional disadvantages are high operating costs, dependency on historical price fluctuations and inability to encompass new products (Breidert et al., 2006). In digital economy, using recurrent choices for

☆ The authors thank Jean-Louis Chandon and two anonymous reviewers for their insightful comments on an earlier version of this manuscript. ⁎ Corresponding author. E-mail addresses: [email protected] (S. Kaplan), [email protected] (S. Bekhor), [email protected] (Y. Shiftan). 0148-2963/$ – see front matter © 2009 Elsevier Inc. All rights reserved. doi:10.1016/j.jbusres.2009.09.019

eliciting price acceptability range is impractical, due to the large number of on-line retailers. This study proposes a direct elicitation method for choice situations entailing many alternatives, typical of digital economy. The method retrieves the price acceptability range simultaneously for different multi-attribute product variations from cross-sectional data and assumes a two-stage cognitive choice process consisting of a conjunctive strategy followed by utility maximization. As a complementary analysis tool, this study develops a semi-compensatory model that jointly reveals the determinants of the price acceptability range and the importance of transaction price relative to other attributes. This study applies the method and the model to a students' rental apartment case study, as an example of multi-attribute product with many variations.

2. Two-stage elicitation method The proposed two-stage elicitation method relies on cumulative evidence from decision making studies showing that, when faced with many alternatives, individuals use a sequence of an attribute-based heuristic (e.g., conjunctive) and an alternative-based strategy (e.g., utility maximization) (Payne, 1976; Olshavsky, 1979). At the first stage, consumers overtly select their tolerated criteria cut-offs concerning acceptable price and product quality from a fixed list of values to delimit the universal realm of product variations to a viable choice set. This stage is similar to the own-category procedure (Monroe, 1971), as consumers differentiate between “acceptable” and “unacceptable” values. At the second stage, consumers choose their preferred product variation from their retained choice set. If consumers do not find their ideal product variation within their choice set, they may select their preferred available variation, update

46

S. Kaplan et al. / Journal of Business Research 64 (2011) 45–50

Fig. 1. Two-stage elicitation method.

their cut-offs, or decide not to choose and thus reveal the need for market expansion. Fig. 1 illustrates the elicitation procedure. A questionnaire supplements this procedure by collecting consumers' socio-economic characteristics, attitudes and perceptions in order to associate cut-off selection to consumers' observed heterogeneity. At the criteria specification stage, consumers do not receive full information about attribute values and price of all the product variations within the universal realm. Rather, they are only aware of the general product category delimited by the range of criteria values. At the choice stage, consumers receive complete information regarding product variations that satisfy their cut-offs. Partial information conditions are behaviorally realistic when consumers face a large universal realm, due to information search costs and time consumption. These conditions lead to consumers conceptualizing a product variation by specifying their tolerated quality criteria cut-offs solely based on their intrinsic constraints, instead of specifying their acceptable price for a fully-specified product variation. Hence, given a sizeable sample of consumers, the method enables eliciting price acceptability limits simultaneously for different product variations and identifying their market shares in a cost-efficient manner. Computer-aided recording of two-stage choice protocols allows tracking consumers' price acceptability limits and quality criteria cutoffs, as well as attributes and transaction price for the chosen product variation. Specifically, a web-server records a series of consumer's typing actions during the two-stage procedure. The main benefits include preventing inconsistency and misinterpretation usually associated with verbal choice protocols (Olshavsky, 1979), avoiding interference to the natural choice process since consumers do not need to think aloud, and guaranteeing schedule and location flexibility to consumers. The method is suitable for retrieving both stated preferences from hypothetical choice experiments and revealed preferences from actual consumer transactions. When the method is applied to hypothetical choice experiments, strategic response bias and incentive compatibility bias may interfere. Survey design elements

aim at mitigating strategic response bias by decreasing the attention to the pricing question as consumers (i) engage in a choice task that masks the importance of acceptable price range elicitation as main research purpose, (ii) choose from a fixed product inventory, (iii) do not see the price listed first among the criteria, and (iv) have complete discretion in selecting the criteria to form their viable choice set and are neither obliged nor advised to select price cut-offs. Similarly to Wang et al. (2007), associating a hypothetical choice with an actual transaction probability can be used in the proposed method to mitigate incentive compatibility bias, although only for relatively low cost products. When the method is applied to retrieve the price acceptability range from actual consumer transactions, it is bias free. 3. Semi-compensatory model The proposed model represents a two-stage process consisting of a conjunctive heuristic followed by utility maximization to express the probability of consumer q (q = 1, 2,…, Q) to choose product variation i, as Q consumers face the same universal realm G: Pq ði jGÞ = Pq ðijSÞPq ðS jGÞ

ð1Þ

where Pq(S|G) is the probability that consumer q delimits the universal realm G to a viable choice set S, and Pq(i|S) is the probability that consumer q chooses product variation i from S. Although the choice depends on the retained choice set, the two stages represent distinct cognitive processes and thus their error terms are assumed to be uncorrelated. The model differs from Manski's formulation (1977), although is inspired by its expression, by assuming that the choice set is observable and derives from a conjunctive heuristic. The probability to select a choice set S derives from the selection probability of a combination of cut-offs:

⁎ Þ∩Pðt ⁎ Þ∩…∩Pðt ⁎ Þ∩…∩Pðt ⁎ Þ Pq ðS jGÞ = Pðt1q Kq 2q kq

ð2Þ

S. Kaplan et al. / Journal of Business Research 64 (2011) 45–50

where Pq(t⁎kq) is the probability that consumer q selects cut-off t⁎of criterion k (k = 1, 2,…, K). A function of individual characteristics accounts for observed population heterogeneity in representing consumer specific cut-off t⁎kq:

⁎ =α Z +ε tkq k kq kq 0

ð3Þ

where Zkq contains the characteristics of consumer q (i.e., socioeconomic variables, attitudes and perceptions) relevant to the selection of cut-off t⁎kq, αk encompasses estimated parameters, and εkq is an error term. Criteria cut-offs, similarly to response thresholds for physical stimuli, are revealed when inducing a response (Monroe, 1971), such as the refusal to purchase a product. Assuming that the error term for criterion k is identically and independently distributed normal across consumers, the ordered-probit model represents the probability that consumer q selects cut-off t⁎kq :

⁎ ≤ θ Þ = Φðθ Pðθðm−1Þk < tkq mk ðm−1Þk −αk Zkq Þ−Φðθmk −αk Zkq Þ 0

0

ð4Þ

where θ(m − 1)k and θmk are the lower and upper bounds of the cut-off category mk (mk = 1, 2,…, Mk) that represents cut-off t⁎kq, and Φ is the cumulative normal distribution. The probability to choose alternative i from J viable alternatives within choice set S is represented by a multinomial logit model: expðβ′ Xi Þ

Pq ði jSÞ =

J

ð5Þ

′

∑ expðβ Xj Þ j∈S

Q

Q

q=1

q=1

d

dm

LL = ∑ log½Lq ðijSq ÞLq ðSq jGÞ = ∑ log½Pq ðijSq Þ qi Pq ðSq jGÞ

Q

q=1

8 > <

non-reserved parking). Price cut-offs reflect the price range, currency and resolution level of local real-estate databases. This study elicits the maximal rent price since a decreasing price acceptability function (“lower is better”) is reasonable for expensive products and relatively low income population groups (Ofir, 2004). Following Wang et al. (2007), this study considers the maximal rent price as Ceiling Reservation Price (CRP), namely the “minimum price at or above which a consumer will definitely not buy the product (i.e., 0% purchase probability)”. Respondents revise their tolerated cut-offs until they obtain a satisfactory choice set from which they choose their preferred apartment, defined as the apartment that they most wish to visit in order to complete a prospective rental transaction. Respondents that do not find their ideal apartment (e.g., quiet low cost apartment) either choose a sub-optimal alternative (e.g., noisy low cost apartment) or abort. The latter case does not appear in the data since identifying the need for market expansion is out of scope. The web-server automatically records into a database respondents' cut-offs and chosen product variation, as well as answers to a questionnaire regarding respondents' socio-economic characteristics, price perceptions, travel preferences and study preferences. 5. Results Results are based on a sample of 631 respondents searching the database according to the three most frequently selected criteria (i.e., CRP, apartment sharing and neighborhood) and choosing an apartment within a universal realm of 200 alternatives in the two most popular neighborhoods, named Neveshaanan and Carmel. 5.1. CRP distribution

where Xj represents the product attribute values of alternative j, and β encompasses the estimated parameters. Assuming independence of the error terms across criteria, the loglikelihood for the model defined in Eq. (1) is:

= ∑ log

47

2

0

3d

6 expðβ Xi Þ 7 ∏4 5 0 > :i∈Sq ∑ expðβ Xj Þ j∈Sq

qi

K

∏

Mk

0

kq



0

dm

∏ ½Φðθðm−1Þk −αk Zkq Þ−Φðθmk −αk Zkq Þ

k = 1 mk = 1

kq

9 > = > ;

ð6Þ where dmkq equals one if consumer q selects cut-off category m of criterion k and zero otherwise, and dqi equals one if consumer q chooses alternative i and zero otherwise. A custom code in GAUSS matrix language simultaneously estimates α, β and θ by maximum likelihood. 4. Students' rental apartment case study A web-based experiment replicating actual on-line transactions illustrates the application of method and model to rental apartment choice by students living in the city of Haifa, Israel. In the experiment, respondents access a custom designed website to search a synthetic real-estate inventory according to a pre-specified list of criteria cut-offs. The inventory textually details 18 attributes for each apartment, including neighborhood, rent price, structural features, location amenities, roommate policy and electrical appliances. The distribution of apartment attributes relies on the statistical analysis of local real-estate databases. The criteria for the inventory search are apartment sharing (vacant versus shared), neighborhood, maximal monthly rent price ($150– $700 in $10 increments), number of rooms (1–5), walking time to campus (5–30 min), noise level (rear versus street facing apartments in local and arterial roads), and parking availability (reserved versus

Most respondents (78.6%) select CRP cut-offs in multiples of $50 (i.e., $200, $250,…,$700), which reflects their sensitivity to rent price changes. The mean of selected CRP cut-offs (M = $417, SD = $161.7) is only 7.4% lower than the mean rent price of the 200 apartments (M = $450, SD = $159.9) in the synthetic inventory, which is based on market prices. Reasonably, elicited CRP values are unbiased. Each respondent searches the database according to two binary nonprice criteria (i.e., apartment sharing and neighborhood), thus selecting among four mutually exclusive product categories for which CRP are elicited. Market shares of the four categories are 42.3% and 38.8% for respectively shared and vacant apartments in Neveshaanan, and 1.9% and 17% for respectively shared and vacant apartments in Carmel. As illustrated in Fig. 2, the categories differ with respect to their mean CRP, as CRP is moderately correlated with neighborhood (Spearman's Rho = 0.42) and apartment sharing (Spearman's Rho = 0.68). Only respondents' perceptions regarding criteria linkage explains these correlations, since the experimental design does not suggest the linkage existence. 5.2. Correlation between CRP and transaction price Transaction price, equal to the price of the preferred alternative, is strongly correlated with the CRP (Pearson's r = 0.75). Moreover, for 28.4% and 47.9% of the respondents the difference between CRP and transaction price is respectively less than 10% and 25%. Since respondents specify their CRP under partial information, the available price range may be narrower than the specified one. In fact, for almost 60% of the respondents the highest available price within the viable choice set is approximately 15% lower than the elicited CRP. Interestingly, transaction price is strongly correlated with the minimum (Pearson's r = 0.83), maximum (Pearson's r = 0.87) and average price (Pearson's r = 0.91) of the apartments included in the choice set, and according to Jarque-Bera test results is normally distributed around the average price. Likely, after selecting CRP under partial information,

48

S. Kaplan et al. / Journal of Business Research 64 (2011) 45–50

Fig. 2. Distribution of CRP cut-off values per product variation.

respondents adjust their willingness to pay by anchoring to either the maximum or the average price within the choice set. 5.3. Model estimation results An ordered-probit model with 11 categories (i.e., 200, 250,…,700) represents the CRP and binary-probit models represent the non-price criteria. Socio-economic explanatory variables are directly inserted into the model, whereas perceptions and attitudes are incorporated after performing factor analysis. The best estimation results are presented in Table 1. The coefficients of the CRP ordered-probit model reveal consumers' characteristics influencing the selection of CRP cut-offs. The probability of selecting higher CRP increases according to: (i) progression of the student's lifecycle and socio-economic status, as respondents who are married or have higher monthly expenses tend to select higher CRP values; (ii) reference to status quo product, as respondents currently paying higher rents in the center of Israel tend to select higher CRP values; (iii) product quality, as respondents associate higher CRP values with apartment sharing and neighborhood; (iv) self-reported price knowledge, in accordance with the literature (Rao and Sieben, 1992). The probability of selecting lower CRP increases according to: (i) habit to travel daily to campus, likely related to shorter time spent in the apartment with respect to the campus; (ii) greater apartment search

experience, likely reflecting a greater propensity to undergo the burden of replacing a status quo product with a more cost-efficient product. The coefficients of the utility-based model allow inferring the importance of rent price in the choice process relative to other attributes. 6. Conclusions, limitations and further research This study elicits the price acceptability range and unravels its determinants in choice situations entailing a large number of alternatives by jointly developing a novel two-stage direct elicitation method and a semi-compensatory model. Using a sample of 631 respondents and a universal realm of 200 alternatives, the method jointly elicits CRP, transaction prices and market shares for four product categories in a webbased experiment of rental apartment choice by students. Results show: (i) CRP distribution and market shares for four mutually exclusive product categories; (ii) CRP correlation with product quality; (iii) unbiased elicited CRP values, (iv) strong correlation between CRP and transaction price, and between the available price range within the choice set and transaction price; (v) consumers' characteristics influencing CRP cut-offs selection, including socio-economic characteristics, price knowledge, paid price for respondents' status quo product and switching propensity to a new product; (vi) joint estimation of the CRP determinants and the role of price in the choice process. The method is extendable to other multi-attribute products, although only to products characterized by multiple attributes that are tangible and

S. Kaplan et al. / Journal of Business Research 64 (2011) 45–50 Table 1 (continued)

Table 1 Estimated model. Variable Apartment sharing criterion Marital status Gender Age Car availability Trip frequency to campus Study on-campus to benefit from teacher-student interaction factor Monthly expenses

Current residential arrangement

Current residential location

Location criterion Price-quality ratio consciousness factor Age Car availability Faculty location

Monthly expenses

Income source

Variable Description/categories

Parameters

Married (1 = yes, 0 = no) Male (1 = yes, 0 = no) Years Daily (1 = daily, 0 = monthly/weekly) Daily (1 = daily, 0 = monthly/weekly)

Price-knowledge factor Apartment search experience Trip frequency to campus Current residential arrangement

Current residential location

Non-price search-criteria cut-offs

t-stat.

1.257 5.21 − 0.518 − 3.45 0.020 1.83 0.391 2.48

Ceiling reservation price criterion Non-price search-criteria cut-offs

Cut-off points

− 0.414 − 2.76 − 0.124 − 2.63

<$750 a $750–$1000 $1000–$1750 Dormitories/parentsa Roommates Alone Spouse Haifa metropolitan core Haifa suburban cities Haifa northern outskirts Center of Israel

– – 0.503 2.06 0.605 2.79 – – − 0.646 − 3.14 0.793 2.64 0.986 5.15 – – − 0.610 − 1.75 − 0.917 − 3.84 – –

− 0.290 − 4.44 Years Daily (1 = daily, 0 = monthly/weekly) Medical campus (1 = medical campus, 0 = main campus) < $750a $750–$1500 > $1500 No income/scholarshipa Part-time job Full-time job

1.92 2.45

0.472

1.70

0.211

4.15

− 0.133 − 3.21 − 0.286 − 1.87 0.639

Married (1 = yes, 0 = no) <$500a $500–$750 $750–$1500 >$1500 ≤4 apartment changes a >4 apartment changes Daily (1 = daily, 0 = monthly/weekly) Dormitories/parentsa Roommates Alone Spouse Haifa metropolitan core Haifa suburban cities Haifa northern outskirts Center of Israel Shared apartment in Neveshaanana Vacant apartment in Carmel

0.031 0.410

– – 0.243 1.30 0.479 2.20 – – − 0.385 − 1.92 – – 0.083 1.99

Difference in job opportunities between Carmel and Neveshaanan Difference in parks availability between Carmel and Neveshaanan Study on campus due to increased studying efficiency factor Trip frequency to campus Daily (1 = daily, 0 = monthly/weekly) Retaining only vacant apartments (1=yes, 0=no) Ceiling reservation price criterion Marital status Monthly expenses

49

3.21

0.388 2.57 – – 0.288 2.33 0.366 2.66 0.640 3.45 0.124 3.78 – – − 0.508 − 2.32 − 0.342 − 3.41 – – – 0.339 – – – 0.476 –

– – – 2.46 – – – 3.40 –

1.885

9.08

(continued on next page)

Description/categories Vacant apartment in Neveshaanan Shared apartment in Carmel $200a $250 $300 $350 $400 $450 $500 $550 $600 $650 $700

Utility maximization choice stage Rent price (U.S.D.) Size (square meters) Number of roommates Walking time to campus (minutes) Quiet apartment (1 = quiet, 0 = noisy) Parking (1 = private parking, 0 = no private parking) Floor number Number of balconies Smoking allowed (1 = yes, 0 = no) Security bars (1 = yes, 0 = no) View (1 = a view to the bay or mountain, 0 = urban view) Renovated (1 = yes, 0 = no) Air conditioner (1 = yes, 0 = no) Solar water heater (1 = yes, 0 = no) Number of observations Log-likelihood with initial parameters equal to zero Log-likelihood with final estimated parameters McFadden's adjusted R2 a

Parameters

t-stat.

1.355

9.65

1.193

4.41

– – − 0.235 − 1.79 0.263 2.002 0.601 4.45 0.860 6.40 1.375 9.85 1.891 13.26 2.551 17.85 2.802 19.28 3.187 21.24 3.340 21.75

− 0.004 0.034 − 0.740 − 0.073 1.438 0.398 − 0.194 0.177 − 0.345 0.331 0.465 0.751 0.617 0.606 631 − 6831.62 − 3498.54 0.479

− 4.56 9.23 − 4.36 − 8.08 13.89 3.03 − 4.16 2.54 − 2.25 3.45 4.13 6.93 5.81 4.10

Base category.

easily quantifiable (e.g., travel fares, electrical appliances and electronic devices). In addition, when applied to actual on-line transactions, the method may over-represent consumers who are familiar with a webbased environment and on-line shopping. Future research directions include: (i) application of the developed method and model for different products by using actual on-line transactions from commercial shopping websites; (ii) accounting for unobserved heterogeneity by estimating either a finite mixture model or a mixed ordered-response model for criteria representation, as the current study accounts only for observed heterogeneity in cut-off selection and thus parameter estimates are assumed to be the same across the population; (iii) investigation of whether absence of bias in the elicited CRP values is a general trait of the method, necessary to apply the method for eliciting the price acceptability range of expensive products. References Breidert C, Hahsler M, Reutterer T. A review of methods for measuring willingness-to-pay. Innov Mark 2006;4:8–32. Chung J, Rao VR. A general choice model for bundles with multiple-category products: application to market segmentation and optimal pricing for bundles. J Mark Res 2003;40(2):115–30. Cox AD. New evidence concerning consumer price limit. Adv Consum Res 1986;13:268–71. Gabor A, Granger CWJ. The attitude of the consumer to prices. In: Taylor B, Wills G, editors. Pricing Strategy. London: Staples; 1969. Janiszewski C, Lichtenstein DR. A range theory account of price perception. J Consum Res 1999;25(4):353–68. Jedidi K, Jagpal S, Manchanda P. Measuring heterogeneous reservation prices for product bundles. Mark Sci 2003;22(1):107–30. Jedidi K, Zhang JZ. Augmenting conjoint analysis to estimate consumer reservation price. Manag Sci 2002;48(10):1350–68. Kohli R, Mahajan V. A reservation-price model for optimal pricing of multi-attribute products in conjoint analysis. J Mark Res 1991;28(3):347–54.

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Manski CF. The structure of random utility models. Theor Decis 1977;8(3):229–54. Monroe KB. Measuring price thresholds by psychophysics and latitudes of acceptance. J Mark Res 1971;8(4):460–4. Ofir C. Reexamining latitudes of price acceptability and price thresholds: predicting basic consumer reaction to price. J Consum Res 2004;30(4):612–21. Olshavsky RW. Task complexity and contingent processing in decision making: a replication and extension. Organ Behav Hum Perform 1979;24(3):300–16. Payne JW. Task complexity and contingent processing in decision making: an information search and protocol analysis. Organ Behav Hum Perform 1976;16(2):366–87.

Rao AR, Sieben WA. The effects of prior knowledge on price acceptability and the type of information examined. J Consum Res 1992;19(2):256–70. Shocker AD, Ben-Akiva ME, Boccara B, Nedungadi P. Consideration set influences on consumer decision-making and choice: issues, models and suggestions. Mark Lett 1991;2(3):187–97. Wang T, Venkatesh R, Chatterjee R. Reservation price as a range: an incentive compatible measurement approach. J Mark Res 2007;44(2):200–13.

Journal of Business Research 64 (2011) 51–54

Contents lists available at ScienceDirect

Journal of Business Research

How U.S. consumers view in-store promotions Don E. Schultz ⁎, Martin P. Block Northwestern University, United States

a r t i c l e

i n f o

Article history: Received 1 April 2009 Received in revised form 1 July 2009 Accepted 1 September 2009 Keywords: Promotion analysis CHAID Predictive Results In-Store

a b s t r a c t Most sales promotion analysis, either at the external-to-the-store or in-store level, has been conducted based on what marketers have done and how consumers have responded in specific retail situations and for specific promotional techniques. Most studies, therefore are reported as, point-in-time and point-of-place specific, historical, after-the-fact results and imply a consumer preference for the measured activity. This paper provides a holistic view of how U.S. consumers regard all forms of promotion, both external-to-thestore in the form of 31 media alternatives and 23 in-store techniques across thirteen broad product categories. Data comes from twice a year online studies of representative groups of U.S. consumers, conducted since 2002. Consumers report on which in-store activities most influence their purchase decisions. From that, predictive models of consumer response to alternative promotional combinations are developed using CHAID analysis. This predictive approach is superior to traditional after-the-fact measures. © 2009 Elsevier Inc. All rights reserved.

1. Introduction

2.1. Three primary research streams

Research on how in-store promotional marketing works has a long and storied history both academically and professionally. (Schultz, 1998; Blattberg and Neslin, 1995; Totten and Block, 1994; Bogart, 1984; Sass, 2007). Most previous studies have focused on trying to determine how consumers respond to various pre-store and in-store promotional activities, generally separately and independently. (Uncles and Ehrenberg, 1988; Friestad and Wright, 1994; Dickson and Sawyer, 1986; Krishna et al., 1991; Raghubir and Corfman, 1999). Thus, most research has been technique and location specific, afterthe-fact and has assumed the consumer preferred the promotional alternative being measured. The SIMM research focuses on consumer reported evaluations of both prior-to-store-visit and in-store promotional activities and how they impact their personal purchasing behaviors.

Previous in-store promotional research has developed along three lines. (1) matched sample tests where the promotional alternative either was or wasn't present, with changes in consumer purchase behavior assumed to indicate a preference of the technique employed, (2) single focus research which measured either (a) prior-to-retail shopping promotional activities which were then measured in terms of changes in consumer in-store behaviors or (b) stand alone in-store activities which assume the consumer had no previous promotional exposure to the product or situation and is responding only to the in-store activity and (3) specific research studies on various types of retail operations (classes of trade,) assuming they are unique promotional situations with little transferability between them. Most all studies, therefore, have taken the marketer's view of trying to determine which promotional alternative was the most effective or efficient method of influencing consumer behavior. Little consideration has been given as to how consumers view these promotional activities and how they incorporate them into their shopping needs.

2. Background No shortage of research and analysis of in-store promotion. (Moreau et al., 2001; Kumar and Leone, 1988; Guadagni and Little, 1983; Leeflang et al., 2000) exists. Yet, most focus on a marketer view. This study however approaches in-store promotion the way consumers see in-store promotion, how they use it and the value they place on it.

⁎ Corresponding author. Northwestern University, 1870 Campus Drive, 3rd Floor, 3-103 MTC, Evanston, IL, 60208-2175, United States. E-mail address: [email protected] (D.E. Schultz). 0148-2963/$ – see front matter © 2009 Elsevier Inc. All rights reserved. doi:10.1016/j.jbusres.2009.09.021

2.2. A consumer view of in-store promotion This study focuses on how consumers view in-store promotional activities and, how they believe these activities influence their purchasing behaviors at retail. Data has been collected in two forms: (a) the impact and influence of marketer activities delivered to consumers prior to their retail store visit and how that influences their in-store behaviors, i.e. promotions as pre-cursors to the in-store shopping experience and (b) which in-store activities consumers believe are the most influential once they are in the shopping situation. The premise is that the combination of these two elements,

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D.E. Schultz, M.P. Block / Journal of Business Research 64 (2011) 51–54

Table 1 Influence by external-to-the store by media and product category. Source: SIMM, June, 2008.

Coupons Retail inserts Newspaper TV/broadcast In-store Direct mail Magazines Cable Radio Internet Email

Apparel

Car

Eating out

Electronics

Grocery

HBA

Home

Medicines

Telecom

27.7 32.9 22.6 20.8 30.1 24.1 26.5 13.6 8.8 15.6 18.8

8.6 9.5 19.7 21.1 7.8 10.2 16.4 13.0 13.8 10.7 6.5

52.3 23.5 29.1 24.2 12.7 32.4 14.3 14.6 27.1 11.4 14.6

22.5 28.9 22.7 25.6 26.1 19.8 23.0 17.3 15.8 22.5 20.4

66.4 36.1 33.5 23.0 41.7 28.9 17.4 14.2 13.5 10.4 10.6

18.9 23.6 20.0 21.0 19.2 18.7 20.4 15.4 10.5 9.8 9.1

16.3 9.1 8.6 14.1 8.7 7.1 10.0 9.2 4.9 5.9 4.3

6.9 6.8 8.2 12.8 6.5 10.0 5.7 9.5 7.3 9.2 6.6

27.4 21.3 20.5 20.3 19.1 18.9 16.7 13.3 12.7 11.9 11.4

i.e., promotional exposure prior to the store visit and in-store activities truly provide a holistic view of how in-store promotion works in the U.S. today. The unique feature is that this study views promotion from the consumer perspective, not from the view of the marketers planning and implementation. 3. The data source This research is based on the SIMM (Simultaneous Media Consumption) studies conducted among a nationally projectable sample of U.S. consumers twice yearly. Conducted since 2002 by BIGresearch, Columbus, OH, the authors have been continually involved in the data analysis since collection commenced. Currently, the SIMM database contains 200,000+ individual responses. All data is gathered online through a double opt-in methodology, keeping respondent's identity anonymous, the methodology is based on accepted online research techniques. Respondents are not paid for their participation but participate in a quarterly drawing for modest prizes. The questions asked in the SIMM studies are based consumer views of several promotional and media areas. They also include demographics, census region, leisure time activities, media usage in minutes per day, media and promotional influence on purchases, web site most often shopped, planned major purchases in the next ninety days and so on. A proprietary software system weights and balances all participant responses in each study using the fourteen age and sex cells from the U.S. Census. This assures a nationally projectable sample in each wave. The studies are on-going and this report is based on the data set gathered in June, 2008. 3.1. SIMM media consumption characteristics The SIMM studies gather consumer reported information on thirtyone external-to-the-retail location media forms ranging from over-theair television to word-of-mouth to Web radio. Data is gathered on which media forms are used, how much time is spent with each daily, what media forms are used together and simultaneously and which have the most influence on purchase decisions. In addition, consumers also report on the use and influence of twentythree in-store promotional forms ranging from shelf-talkers to floor signs to in-store television. All are related to the thirteen major product categories studied in each wave. In addition, many traditional demographic and leisure time questions are asked, making this one of the most comprehensive consumer promotional studies in the country. The premise for the SIMM studies is that in-store response to marketing and communication programs is a complex mix of what the consumer brings into the in-store retail environment, which is then impacted and mediated by their promotional experience inside the store. The only person who can provide this type of information is the consumer. Thus, the issue is not what promotional materials and offers

marketers distribute; instead, the consumption of those offers by the consumer is the focus. Thus, the key ingredients in understanding how in-store promotion works depends on what promotional forms consumer take in, process and then use in their retail purchase decisions. Schultz and Pilotta developed and presented a media consumption model at the 2004 ARF and ESOMAR conferences (Schultz and Pilotta, 2004; Schultz et al., 2005). This model forms the basis for the SIMM studies and the resulting findings. 3.2. External-to-the-store and in-store promotional influences Illustrated above are the consumer aggregated and averaged responses for some of the Product Categories found in the SIMM studies. They show which media or promotional form consumers report as having the greatest influence on their purchase decisions prior to entering the retail shopping situation. Note: Word-of-Mouth has been deleted from the table, although the top rated influence. Marketers have limited ability to impact or influence W-OM, thus the deletion (Table 1). As shown, the influence of external-to-the-store promotional activities varies greatly by product category. For example, coupons are very influential in the Grocery and Eating Out categories but have limited influence in the purchase of cars and medicines. Internet has a major influence in Electronics purchasing decisions but is relatively unimportant in Home Improvements. An understanding of how consumers view the various promotional alternatives is unique to the SIMM data. A second important factor is the presence of in-store promotional activities. The combination of what has occurred prior to the store visit with in-store customer experiences that determine in-store results. In-store influences in SIMM studies are shown in Table 2. When the consumer enters the retail environment, a wide variety of promotional elements become apparent. Some of those are shown

Table 2 In-store shopping influences (what influenced you during your last shopping trip?). Source: SIMM, June, 2008. Total Used a list Up and down Coupons In-store spec Brands Inserts Read labels Point of sale Displays Shelf coupons Store staff Register tape

35.9 31.7 24.8 21.7 21.3 15.1 9.2 6.4 6.4 4.8 4.5 3.5

Total Sample Prices from web Products from web Pharmacist Online res In-store events Parking lot Cause offer In-store TV In-store radio Other

3.0 1.9 1.6 1.6 1.5 1.5 0.9 0.7 0.5 0.4 14.3

D.E. Schultz, M.P. Block / Journal of Business Research 64 (2011) 51–54

above. Their reported influence on purchase decisions is reported in the SIMM studies. As shown, “Used a List” is the top ranked influence with “Up and Down the Aisles” ranking second. While marketers have little influence on these promotional elements once consumers are in the store, clearly the list was constructed from external-to-the-store experiences which the customer brought with him or her. Those previous experiences are further reinforced or discarded as the consumer walks through the aisles. Knowing that Lists and Aisle Walking are the two primary promotional tools consumers use in the store, helps retailers understand why and how responses to in-store promotion are likely to occur. Clearly pre-shopping promotional activities have a major impact on in-store promotional results. Thus, only by combining the external promotional influences with the internal experiences is one able to really understand what drives instore consumer behaviors. Of those elements which the marketer can control in the store, Coupon and In-Store Specials have the greatest reported consumer influence on purchases. While most in-store promotional analysis has dealt primarily with what activities the manufacturer or retailer has developed and implemented. From the consumer view, however, many other factors really drive their responses, resulting in sales and profits. For example, Brands, Read Labels and Store Staff all have major influences on consumers, yet they are rarely considered by most marketing and promotional managers as being critically important instore retailing activities. This type of consumer understanding is critical in optimizing the in-store promotional investments for both manufacturers and retailers.

4. Building predictive in-store promotional models One of the greatest values of using SIMM data in understanding instore promotion, is to develop predictive models of what combinations of promotional elements might be most effective by product category prior to the store visit. Most current in-store promotional planning approaches are based on “trial and error” or analysis of promotional effects well after the fact. Major changes in results and efficiencies of development and implementation can come from knowing what promotional activities are likely to succeed before they are implemented. More importantly, most in-store promotions are made available to all shoppers, assuming a “one size fits all.” The SIMM studies provide

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the data which enables a unique promotional development process that can be employed to achieve promotional goals against specific consumer groups. An illustration follows.

4.1. Identifying best combinations of in-store promotional activities by customer group How in-store promotion works, for both the manufacturer and the retailer, is a complex mix of external-to-the-store activities to which shoppers are exposed before entering the store and the activities which are present during the shopping experience. SIMM data shows these situations are far more complicated than the typical “off-or-on” promotional measures which have been used in the past. Following is an example of how consumer-based information might be used to optimize in-store promotional activities. To illustrate the process, SIMM data collected from customers of a very large U.S. mass merchandiser was analyzed over two SIMM waves (June and December, 2007). Since SIMM data is collected twice yearly, and many of the respondents are repeat responders, the possibility to identify shoppers for the retail firm through questions such as “Who is your favorite retailer in __________(product category)” exists. From this, shopper classifications of Loyals, New Shoppers, Lost Shoppers and Prospects were created. Loyal shoppers are those who shopped at the same retailer in both waves of the SIMM studies. New Shoppers are those who shopped with the retailer in the December, 2007 SIMM wave but not in the June, 2007 wave. Lost Shoppers are those who purchased from the retailer in the first SIMM study (June, 2007) but not the second December wave. Prospects are those who purchased in the product category but did not shop with the retailer in either of the SIMM waves. From this simple set of data points, a set of CHAID (Chi Square Automatic Interaction Detection) trees were created by identifying the combination of media and promotional forms each of the four customers groups said had the most influence on their purchase decisions in that product category. Obviously, the value of this type of information is that the retailer can begin to identify, in advance, which external-to-the-store and which in-store combinations would most likely be effective with each of the four customer groups. In the following discussion, for the sake of clarity and simplification, only the in-store elements are reported and they are reported as “pruned CHAID trees.” CHAID is a statistical methodology which sorts

Fig. 1. Media influence pruned CHAID tree for loyal customers.

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D.E. Schultz, M.P. Block / Journal of Business Research 64 (2011) 51–54

the available variables based on which ones have the greatest explanatory capacity in descending order. The algorithm continues until all alternatives have been exhausted or until the level of explanatory value decreases to the point of little value. CHAID analysis results in very large trees as variables come into the equation. For purposes of this example, the CHAID trees have been pruned to show only the interactions among the more important variables. 4.2. CHAID tree outputs CHAID trees were constructed for each of the four customer categories described above, Loyals, Gains, Losses and Prospects. Space does not permit discussion of all four customer groups. The analysis of the Loyals segment is taken as an example (Fig. 1). The illustration above shows the output of the pruned CHAID tree for loyals. That illustrates which media activities customers loyal to the retailer say have the most impact on them when all of the retail categories are aggregated. As shown, the Loyals account for 19.1% of the total SIMM respondents who shopped with the retailer during both waves of the studies. 72.7% of SIMM respondents reported Coupons most influenced them when shopping at the retailer across all categories. The other 27.3% of the respondents said other promotional activities influenced them more than coupons, in other words, No Coupons. The CHAID analysis provides a fairly easy way for managers to see that if the goal is to impact loyal customers with in-store promotional activities, the choices would be Coupons, Internet and In-Store activities. Promotional tools such as Direct and Newspapers would have less impact on these groups and likely should not be employed. While illustrations of the other CHAID trees for the Gains, Losts and Prospects, are not shown, all groups have widely varying promotional preferences. For example, the Lost Customers CHAID tree revealed that those customers prefer No Coupons or Newspapers. They do prefer Magazines. Whether Magazines are a viable promotional choice for the retailer is a managerial decision that would have to be made. From this brief review of the CHAID analysis, factoring in consumer preferences in terms of the promotional vehicles to be used within the store should improve promotion results. Consumers drive purchases and providing them with the promotional alternatives they prefer would seem to advance the planning of in-store promotion substantially. Perhaps the most intriguing factor in this consumer-based in-store promotional approach using SIMM data is the great diversity among the influential media forms among the four types of customers. Based on the analysis, no one media form was found which all of the four groups, say influence them the most. Thus, the retailer's goal with all forms of promotional activities and media must be to satifice, that is to clearly identify the groups of customers who are most important and then try to build programs and activities that fit them rather than trying to develop some type of “one size fits all” approach which seems to have become the industry standard. Of particular interest in this analysis of SIMM data is that most of the traditional media forms preferred by the marketer such as Television, Newspapers and even the new media such as the Internet and Email, show little positive influence with either of the four groups analyzed for this retailer. Thus, the caution to both manufacturers and retailers is that major differences exist between the media distribution approaches they have developed and used in the past and the consumption of those media and promotional forms by their customers and other consumers. Consumer preferences will likely win out. Thus, marketers should take note of their preferences, not what has historically been done or even what is the most efficient

promotional tool. This is a new arena in in-store promotion and everyone must listen to the voice of the customer. 5. Summary and conclusions This initial use of SIMM data, which provides consumer-based evaluations of in-store promotional activities, is a major step in improving the return on in-store promotional investments for both retailers and manufacturers. Five major advantages flow from the methodologies outlined in this paper. 1. Identifying consumer promotional preferences assures the methodologies used are relevant to the customers, not just marketers. 2. Consumer's views of the value and importance of in-store activities vary by type of customer and product category. Few if any promotional activities can be used across the board with any expectation of success. One size does not fit all. 3. Understanding how in-store promotion works requires knowledge of the combination of prior-to-the-store-visit exposures and instore activities. Neither one individually can provide a useful explanation. 4. The development of predictive methodologies, using SIMM data and CHAID analysis, can provide major enhancements to in-store promotional planning for both the retailer and the manufacturer. 5. While not demonstrated in this paper, longitudinal consumer views of the impact and effect of in-store promotional activities can greatly improve marketer returns. Promotional importance changes over time and managers must have their finger on the consumer's pulse to truly create effective in-store promotional programs. In summary, starting with customers and their views of the promotional alternatives, particularly in in-store, can provide a major improvement in the planning, managing and evaluation of in-store promotion going forward. References Blattberg Robert C, Neslin Scott A. Sales promotion: concepts, methods, and strategies. Upper Saddle River, NJ: Prentice Hall; 1995. Bogart Leo. Strategy in advertising: matching media and messages to markets and motivations. 2nd ed. Chicago, IL: Crain Books; 1984. 222–225. Dickson Peter R, Sawyer Alan G. Point-of-purchase behavior and price perceptions of supermarket shoppers. Cambridge, MA: Marketing Science Institute; 1986. Friestad Marian, Wright Peter. The persuasion knowledge model: how people cope with persuasion attempts. J Consum Res 1994;21 June. Guadagni Peter M, Little John DC. A logit model of brand choice calibrated on scanner data. Mark Sci 1983;2:203–38 Summer. Krishna Aradhna, Currim Imran S, Shoemaker Robert W. Consumer perceptions of promotional activity. J Mark 1991;55:4-16 April. Kumar V, Leone Robert P. Measuring the effect of retail store promotions on brand and store substitution. J Mark Res 1988;25:161–9. Leeflang Peter SH, Wittink Dick R, Wedel Michel, Naert Philippe A. Building models for marketing decisions. New York, NY: Springer; 2000. Moreau Page, Krishna Aradhna, Harlam Bari. The manufacturer–retailer–consumer triad: differing perceptions regarding price promotions. J Retail 2001;77:547–69 April. Raghubir Priya, Corfman Kim. When do price promotions affect pretrial brand evaluations. Journal of Marketing Research 1999;2:211–22 May. Sass Erik. Nielsen rolls out in-store measurement. Media Daily News (May 8); 2007. Schultz Don E. Sales promotion essentials: the 10 basic sales techniques… and how to use them. 3rd ed. New York, NY: McGraw-Hill; 1998. Schultz Don E, Pilotta Joseph J. Developing the foundation for a new approach to understanding how media advertising works. 3rd Annual ESOMAR/ARF World Audience Measurement Conference, Geneva: June 13–18; 2004. Schultz Don E, Pilotta Joseph J, Block Martin P. Implementing a media consumption model. 4th Annual ESOMAR/ARF World Audience Measurement Conference, Montreal: June 22–25; 2005. Totten John C, Block Martin P. Analyzing sales promotion: text and cases. 2nd ed. Chicago, IL: Dartnell Corporation; 1994. Uncles Mark D, Ehrenberg Andrew SC. Patterns of store-choice: new evidence from the USA. In: Wrigley Neil, editor. Store choice, store location and market analysis. London, UK: Routledge; 1988. p. 272–99.

Journal of Business Research 64 (2011) 55–58

Contents lists available at ScienceDirect

Journal of Business Research

Promoting promotions: Does showcasing free gifts backfire? Priya Raghubir a,⁎, Kirti Sawhney Celly b a b

Stern School of Business, New York University, 44 West 4th Street, Suite 809 Tisch, New York, NY 10012-1126, United States College of Business Administration & Public Policy, California State University, Dominguez Hills, 1000 E. Victoria Street, Carson, CA 90747, United States

a r t i c l e

i n f o

Article history: Received 1 April 2009 Received in revised form 1 July 2009 Accepted 1 October 2009 Keywords: Consumer promotions Inferences Free gifts Visual information processing

a b s t r a c t Two experiments examine the effect of the visual size of a gift in a free gift promotion on consumer judgments. Results show that promotional offers that highlight the free gift (rather than the product) are less effective than those that highlight the product to be purchased. Increasing the visual size of the free gift leads to perceptions of poorer product quality and has unfavorable consequences for purchase intentions of the offer. We propose that the larger the size of the gift in a promotional ad, the higher the perceived component of gift value in the total promotional offer, and accordingly the lower the value of the promoted product. Therefore, visually larger gifts can backfire and hurt the overall promotional offer. The presence of price information about the product moderates these effects. Implications for the use of visual cues to draw inferences, and managerial implications for advertising free gift offers are discussed. © 2009 Elsevier Inc. All rights reserved.

Free gift promotions account for a substantial part of many companies' sales (e.g., 50% of Esteè Lauder's sales are through free gift promotions, Trager, 1984). Consider a free gift promotion offered by Ralph Lauren: a large backpack comprises the full-page ad with the headline that it is a free gift with purchase of a Ralph Lauren fragrance. A small inset on the top left suggests a Ralph Lauren product that could be purchased to avail of the free gift. Such promotions are commonplace. Frequently, the value of the free gift advertised is high (e.g., White Diamonds offered a gift worth 67% of the minimum price required to avail of the promotion, Raghubir, 2005, Study 2), and even a multiple of the price that a consumer needs to pay to buy a product to get the free gift. The question is: Is there a drawback to showcasing a free gift rather than a company product in a free gift promotion? This paper attempts to answer this question, starting with the simple model: Promotion Percent ¼

Free Gift Value Product Price

When the value of any one of the three variables (promotional percentage, free gift value or product price) is unknown, consumers can use memory-based information (e.g., beliefs regarding average discount rates) or context-based information (e.g., product price and stated value of the free gift) for any two of these variables to estimate the third. Consistent with this reasoning, prior research shows that consumers use the size of promotional offer (e.g., coupon value) to infer the price of the product; leading to higher coupons leading to inferences of higher product price which undercuts their perceived value (“coupon value effect,” cf. Raghubir, 1998, 2004a). Further, consumers infer the value of the free gift given the price of the product ⁎ Corresponding author. Tel.: +1 212 998 0727. E-mail address: [email protected] (P. Raghubir). 0148-2963/$ – see front matter © 2009 Elsevier Inc. All rights reserved. doi:10.1016/j.jbusres.2009.09.022

and their beliefs regarding discount rates, leading to free gifts being devalued when offered by cheaper brands (“value discounting effect,” cf. Raghubir, 2004b, 2005). This paper investigates if consumers estimate different promotional percentages based on perceptions of the ratio of the value of the free gift vs. the product, with the relative ratio itself based on the relative visual size of the free gift vs. the product in an advertisement. Specifically, consumers could make three inferences from larger free gifts. 1. Consumers may believe that since the gift is larger it is more valuable, and, given the value of the promoted product, represents a better deal. This belief is presumably what drives most free gift promotions as it implies that larger free gifts lead to perceptions of higher offer value that should, in turn, increase purchase intentions. 2. Consumers may believe that the value of the promoted product is lower given that it has not been showcased in the ad. This belief would imply a higher promotional percent given gift value. 3. Consumers may infer that a showcased promotional offer implies a higher discount rate, based on their persuasion knowledge that the more valuable aspects of an offer are likely to be highlighted in advertising (Friestad and Wright, 1994). Such a route does not involve making price inferences of either the product or the gift; just their relative value. All three inferences should lead to larger gifts leading to perceptions of higher discount rates. Based on this argument, it is suggested that when a free gift is showcased and visually salient, consumers will infer that it is a significant component of the entire offer, that is, offers a substantial promotional percentage, even if consumers do not infer prices of either the promoted product or the free gift itself. To illustrate with an example: assume a retailer is offering a free gift valued at $10

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(e.g., free vase) with a purchase of a $50 item (e.g., two dozen roses). If the value of the free gift is discounted, consumers may believe it is worth <$10, say $5, or a promotional percentage of 10%. If consumers add the value of the product that they are purchasing ($50) to the stated value of the free gift ($10), they would receive a value of $60 for a price of $50, or 20% more than their outlay. If they discount the value of the free gift ($5), they would receive a value of $55 for an expense of $50, or 10% more. However, if consumers' beliefs regarding the value of the product they are purchasing are tensile, then they may infer the value of the product from the value of the free gift itself. In that event, if they believe that the discount offered is 10%, and the value of the gift is $5, they would infer that the value of the product is $50. However, if they believe that the discount offered is 20%, then a gift value of $5 translates into a product value of only $25. Said differently, the higher consumers presume the discount percentage, the lower they will perceive the value of the product. If visually larger gifts are associated with beliefs of higher discount rates, this inference translates into larger free gifts being associated with lower product value. Promoting the promotion (the free gift) could backfire in terms of consumers' deal evaluations and purchase intentions. If prices of the promoted product are provided, then a different pattern should be found. In such a context, inferential thinking is likely to be impeded given the presence of contextual price information. In the absence of inferential thinking, the visual size of the free gift should be less likely to affect judgments about the value of the product, the free gift or discount rates. However, even if inferential thinking were to occur, while consumers are unlikely to infer the price of the promoted product from the free gift promotion (route 2 discussed above), they may continue to draw inferences about the value of the free gift and the discount rates. If they draw inferences about the value of the gift such that a visually larger gift cues a higher gift value, then consumers should add the perceived value of the gift to the value of the product. This should lead to promotions with visually larger free gifts being evaluated more favorably than those with visually smaller free gifts. Similarly, if they infer that visually larger gifts represent higher discount rates, then given a fixed price of the product, this would imply that the gift is of greater value and represents a better deal. Both routes should lead to visually larger gifts being perceived to be of higher value and leading to higher deal evaluations and purchase intentions than visually smaller gifts. Thus, in the absence of price information, the visually larger the free gift in a free gift offer, the lower the intentions to purchase the product being promoted. However, the presence of prices of the promoted product will attenuate or reverse this effect. Two studies test this hypothesis.

backfires: that is, visually focal gifts lead to consumers discounting the value of the offer, and lower deal evaluations and purchase intentions as compared to gifts that are not showcased. The study also examines the implications of providing or not providing the price of the fragrance. Based on the argument that value discounting is more likely to occur when consumers make price and quality inferences, that is, when product price is absent, the backfiring effect of showcasing free gifts should be greater when price information is absent. Formally: H1. The greater the visual size of the free gift, the less favorable consumer judgments, especially when price information is absent. 1.1. Method 1.1.1. Study participants Eighty-six undergraduate students of an introductory Marketing course participated in this study for partial course credit. Seventy-five respondents completed all measures and were used for analysis. 1.1.2. Design The design is a between subjects 2 (Size of Gift: Large/Small) × 2 (Price of Promoted Product: $35/Absent) × 2 (Gender: Male/Female) full factorial design. The third factor (gender) is a replicate, with participants being handed a different questionnaire according to their gender (female = 36 and male = 50). Measures include purchase intentions (1 = Definitely Not/7 = Definitely Will), and quality perceptions of Ralph Lauren products in general, and the gift offered by the promotion in particular (1 = Poor Quality/7 = Good Quality) using standard seven-point scales. Participants were asked to indicate how frequently they purchase fragrances for themselves or someone else (1 = Never, 2 = 1–2 times, 3 = 3–4 times, 4 = 5–6 times, and 5 = > 6 times in an average year), which was used as a covariate in the analyses. Finally, participants estimated the average discount rate for the offer using an open-ended scale. 1.2. Results Means by condition and ANOVA F statistics are presented in Table 1. The results of a multivariate 2 × 2 (gift size × price) ANOVA on all the dependent measures, incorporating the covariate of purchase frequency are reported below. 1.2.1. Purchase intentions As predicted, when the price of the fragrance was absent, respondents' purchase intentions were higher when the free gift

1. Study 1 This study examines the effect of the visual salience of a free gift in relation to the promoted product in the presence and absence of product price information on consumers' product quality judgments, deal evaluations, purchase intentions, and the prices they are willing to pay for the free gift if it is offered as a standalone product. The context chosen is a free gift promotion modeled on one conducted by Ralph Lauren. The promoted products are Ralph Lauren Polo Sport fragrances (either men's or women's), priced at $35. The free gift offer with the women's fragrance is a “sleek backpack and cosmetics case.” The free gift offer with the men's fragrance is a “gear bag” for men. Both free gifts are branded with the Ralph Lauren logo and name. This study examines the effect of using the free gift offer (the backpack or gear bag) as the focal item in the advertisement as compared to using the promoted product (the fragrance) as the focal item in the advertisement and placing the free gift in the inset on the top right corner of the ad. In the actual promotion, the free gift was the focal item in the advertisement and the fragrance was placed in the right topmost corner inset. The primary hypothesis is that showcasing gifts

Table 1 Results of study 1. Visual Focus

Purchase intentions

Quality of Quality of the Ralph Lauren free gift

Average deal percentage

Price given @$35 Gift 4.9 Product 4.9 Total 4.9

6.2 6.1 6.1

5.5 5.1 5.3

15.2 16.3 15.8

No price mentioned Gift 4.1 Product 5.5 Total 4.8

5.4 6.4 5.9

4.2 4.7 4.4

17.6 25.1 21.1

4.98 0.03 2.19 3.72

4.41 2.13 2.04 2.33

Analysis of variance results: F statisticsa Price 0.05 1.00 Size 3.00 4.59 Price x Size 4.18 5.55 Covariate 3.32 0.07

a F(1, 70) statistics in bold are significant at p < .05, bold italics are significant at p < .10.

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was small (M — = 5.5) vs. large (M — = 4.1). When the price of the promoted product was given, there was no difference in purchase intentions as a function of the size of the gift (M —s = 4.9 for both). This pattern is reflected in a significant price × size interaction (F(1, 70) = 4.18, p < .05; see Fig. 1a). 1.2.2. Ralph Lauren quality perceptions Mirroring the pattern for purchase intentions, in the condition where price of the fragrance was absent, respondents rate Ralph Lauren as lower quality when the free gift is focal (M — = 5.4), vs. not (M — = 6.4). There is no difference in perceived quality when the price is mentioned (M — s = 6.1 vs. 6.2 for product focal vs. gift focal). This pattern is shown in Fig. 1b, and is reflected in a significant interaction (F(1, 70) = 5.55, p < .01). The pattern suggests that consumers infer that Ralph Lauren fragrances (the promoted product) are of higher quality when the free gift bag in the ad is small vs. large. 1.2.3. Quality of gift Quality perceptions of the gift are higher when product price is present (M — = 5.3) vs. absent (M — = 4.4). This is consistent with the idea that the presence of prices leads to perceptions of higher gift value (either through a direct route or through the indirect route of inferring gift value from a discount percentage).

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1.2.4. Deal percentages Participants estimate a higher average deal percentage when the price of the fragrance is absent vs. present (M — =21.1% vs. 15.8%; F(1, 70)=4.41, p<.05). 1.2.5. Mediation analysis An ANCOVA on purchase intentions incorporating the perceived quality of Ralph Lauren products as a covariate showed a significant effect of the covariate (F(1, 69) = 19.48, p < .001), while the previously significant interaction effect reduced to non-significance (F(1, 69) = .20, p = .65). This is a pattern of perfect mediation of purchase intentions via quality perceptions (Baron and Kenny, 1986), given significant interaction effects between the size and price for both quality perceptions and purchase intentions in individual ANOVAs reported above. 1.2.6. Discussion To summarize, Study 1 finds that when the price of the promoted product is absent, then the larger the gift, the lower the purchase intentions for the offer, and the lower the perceptions of quality of Ralph Lauren products. Study 2 now tests whether the size of a gift affects judgments when the gift is not focal in the ad but is presented in different sizes. 2. Study 2 This study examines the moderating effect of visual salience of the free gift using Raghubir's (2004b) stimuli. Raghubir had examined the effect of offering a pearl bracelet as a free gift with purchase of a cognac in a duty free catalog, on purchase intentions of an unrelated pearl necklace and bracelet set (see also Raghubir, 2005 who used these stimuli to manipulate the framing of a free gift offer). Study 2 examines if larger gifts can backfire not only for the product offering the gift (the cognac), but also for an unrelated brand in the same product category (unrelated pearl necklace). 2.1. Method 2.1.1. Participants Ninety undergraduates at a large west coast university participated in this study for partial course credit. 2.1.2. Design As in Raghubir (2004b), participants saw a set of ads copied from a leading airlines duty free catalog. This set included the target ad for a Majorica Pearl necklace and bracelet, and the ad that served as a manipulation—a cognac ad offering a double strand pearl bracelet as a free gift with purchase. Participants flipped through the set of ads as though they were flipping through a duty free in-flight magazine, and then responded to dependent measures. The design is a between subjects 2 (Size of Gift: Large/Small) × 2 (Order: Majorica Pearls first/later) holding constant the brand offering the free pearls: Napoleon Courvoisier. Measures include purchase intentions (elicited on a seven-point scale) for both the cognac and the Majorica pearls, reservation prices or price willing to pay (PWP) (elicited on an open-ended scale) for the cognac, and brand quality perceptions (elicited on a seven-point scale) for the Majorica pearls. 2.2. Results

Fig. 1. Study 1 results. a. Purchase intentions of Ralph Lauren fragrances. b: Quality perceptions of Ralph Lauren fragrances.

2.2.1. Judgments about the cognac A 2 × 2 analysis on purchase intentions of the promoted product, the cognac, show that purchase intentions of the cognac are higher the smaller the visual of the gift (M —s = 3.4 vs. 2.6; F(1,86) = 4.51, p < .05). These results replicate Study 1 results.

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An analysis on the price that consumers were willing to pay for the cognac showed a main effect of gift size (F(1,79) = 3.39, p < .10) reflecting higher PWP for the cognac when it offers a visually smaller gift ($65.34 vs. $50.29). An unexpected main effect of order (F(1,79) = 4.26, p < .05) shows that PWP is higher when the cognac ad precedes the pearls ad ($65.98 vs. $48.85) in the set. 2.2.2. Judgments about the Majorica Pearls A 2 × 2 analysis on purchase intentions of the Majorica pearls reveals a marginal main effect of size of gift (F(1,86) = 3.06, p < .10), reflecting higher intentions when the gift is small vs. large (M —s = 2.8 vs. 2.2). This is consistent with the effect found in Study 1 even though price of the promoted product is given ($52). A visually larger gift offered by the cognac, leads to a lower purchase intention for an unrelated pearl necklace offered by Majorica. Consistent with Study 1, consumers evaluate the quality of Majorica pearls higher when the gift is small vs. large (M —s = 4.3 vs. 3.6; F(1,85) = 5.14, p < .05).

suggest that manufacturers promote the product that is on sale, rather than the promotion, as the reason to purchase. 3.2. Study limitations and areas for future research This paper did not examine alternate routes through which a promotion could affect sales, such as affect or attention (Chandon et al., 2000, Raghubir et al., 2004), or reasons justifying purchase or nonpurchase (Simonson et al., 1994). It is plausible that larger visuals of free gifts create excitement and feelings of joy that exert the opposite effect to the inferences about value, or that larger free gifts lead to counterargumentation that leads to the backfire effect. It is necessary to conduct future research to gain greater insight into the mediating process underlying the effect of visual size of gift on consumer judgments. As both studies are in the domain of hedonic products using student samples, these should be replicated using utilitarian products and services with a non-student population to assess their generalizability.

2.2.3. Discussion To summarize, it appears that large gift sizes appear to backfire. They lead to a value discounting inference that leads to lower purchase intentions for the product.

Acknowledgement

3. General discussion

References

This paper reports the results of two experiments that examine the effect of the visual size of a free gift promotion on consumer judgments. Results show that promotional offers that highlight the free gift (rather than the product) are less effective than those that highlight the product to be purchased. Increasing the visual size of the free gift leads to perceptions of poorer product quality and has unfavorable consequences for purchase intentions of the offer.

Baron ReubenM, Kenny DavidA. The moderator–mediator variable distinction in social psychological research: conceptual, strategic, and statistical considerations. Journal of Personality and Social Psychology 1986;51:1173–82 Dec. Chandon Pierre, Wansink Brian, Laurent Gilles. A benefit congruency framework of sales promotion effectiveness. Journal of Marketing 2000;64(4):65–81. Friestad Marianne, Wright Peter. The persuasion knowledge model: how people cope with persuasion attempts,. Journal of Consumer Research 1994;21(1):1-31. Raghubir Priya. Framing a price bundle: the case of buy/ get offers. Journal of Product and Brand Management 2005;14(3):123–8 June. Raghubir Priya. Coupons in context: discounting prices or decreasing sales? Journal of Retailing 2004a;80(1):1-12 January. Raghubir Priya. Free gift with purchase: promoting or discounting the brand? Journal of Consumer Psychology 2004b;14(1&2):181–5 January. Raghubir Priya. Coupon value: a signal for price. Journal of Marketing Research 1998;35:316–24 Aug. Raghubir Priya. An information processing review of the subjective value of money and prices. Journal of Business Research 2006;59(10–11):1053–62. Raghubir Priya, Jeffrey Inman J, Grande Hans. The three faces of price promotions: economic, informative and affective,. California Management Review 2004;46(4): 23–42. Simonson Itamar, Ziv Carmon, Suzanne O'Curry. Experimental evidence on the negative effect of product features and sales promotions on brand choice. Marketing Science 1994;13(1):23–40 Winter. Trager Cara S. Promotions blemish cosmetics industry. May 10Advertising Age 1984;55(23):M26 M-22-23.

3.1. Managerial implications The results of this paper suggest that manufacturers and retailers should be careful about the inferences drawn from a promotional offer, as these can be non-obvious and backfire. Specifically while earlier research has shown that consumers draw inferences about product price from promotional offers (Raghubir, 2006), and discount the value of the offer itself (Raghubir, 2004b), this paper adds to the literature by showing that consumers may make inferences about the implied discount rate (promotion value/product value) based on the relative visual size of the free gift vs. the promoted product. Results

The authors thank Chau Ly for her research assistance in this project.

Journal of Business Research 64 (2011) 59–60

Contents lists available at ScienceDirect

Journal of Business Research

Marketing and society: Preface to special section on volunteerism, price assurances, and direct-to-consumer advertising Easwar S. Iyer a,⁎, C.B. Bhattacharya b a b

Department of Marketing, Isenberg School of Management, University of Massachusetts, Amherst, MA 01003, United States Department of Marketing, School of Management, Boston University, Boston, MA 02215, United States

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Article history: Received 1 July 2009 Received in revised form 1 September 2009 Accepted 1 September 2009 Keywords: Societal welfare Stakeholder welfare Social responsibility Consumption Volunteerism Price Direct advertising

a b s t r a c t We discuss the reasons why this call for papers was issued and describe the process of selecting the three articles presented in this special section. We argue that maximizing stakeholder welfare and not just consumption maybe a new goal for marketing that will be consistent with emerging societal trends. Three articles on volunteerism, price assurances, and direct-to-consumer advertising result from our call and are presented in this section. This introduction is an overview of the three articles. © 2009 Elsevier Inc. All rights reserved.

Almost ten years after Wilkie and Moore's (1999) evaluation of marketing's contribution to society, the call for papers resulting in this special section raises the same issue. Simply put, what is marketing's contribution to society? Is its contribution negative, neutral or positive? Does context moderates marketing's contribution? Marketing enjoys two opposing images in the popular culture: an evil enticing force and a benevolent informational agent. Why marketing has the image of an evil enticing force, one that somehow entices unwary consumers into buying something s/he had no need for in the first place, is easy to see. After all, the logic goes, increasing consumption is the path to increased profits and so marketing's main objective becomes one of increasing consumption. This logic is consistent with the view that gives exclusive importance to shareholder value. Friedman (1970) famously argues that the only social responsibility of a business was to increase its profits. In contrast, marketing's benevolent side has received less attention. Recently, scholars have proposed the concept of “stakeholder marketing” (see, e.g., Bhattacharya and Korschun, 2008) to argue that marketing can be a positive, transformative force in society. Per the stakeholder view, companies recognize that there are multiple entities (e.g., customers, suppliers, employees, regulators, society) that have a stake in the success of a particular business. Rather than maximize consumption, the goal of marketing in this case is to

⁎ Corresponding author. E-mail address: [email protected] (E.S. Iyer). 0148-2963/$ – see front matter © 2009 Elsevier Inc. All rights reserved. doi:10.1016/j.jbusres.2009.10.001

maximize stakeholder welfare which may necessitate promoting responsible (even reduced) consumption and a variety of pro-social and pro-environmental behaviors. There is some evidence now that firms that invest in enhancing the welfare of multiple stakeholder groups may experience “increased cash flow, lower cost of capital, and increased firm value” (Agarwal and Berens, 2009, p. 19). Obviously the choice of such strategies and the manner in which it gets implemented will matter, but overall, it is possible for business and society to have a symbiotic relationship. The three articles in this special section address and elaborate on three specific issues related to stakeholder welfare. In response to the call, numerous manuscripts were received although only three came out of the rigorous review process. Before an overview of these three articles, we thank all the authors who submitted their work and the reviewers who diligently worked in anonymity to help the authors improve the final manuscript. The first article by Basil, Runte, Basil and Usher is “Company Support for Employee Volunteerism: Does Size Matter?” In this article, the authors focus on one of the key stakeholders (i.e., employees). They investigate the extent of support extended by firms to their employees who wished to volunteer for their favorite social causes. It seems that more and more North American businesses—reportedly between 50% and 80%—provide support to employees who volunteer (Brudney and Gazney, 2006) and that offering such support was seen to positively motivate employees (Lindgreen et al., 2008). However, the size of the firm plays a critical role—larger firms tend to have more formal policies and programs in regards to their support for employees

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volunteering. Although greater formalization may boost employee volunteering for preexisting programs, it tends to be inflexible and becomes a barrier in cases that are new or informal. Larger firms also tend to leverage their support for employees in a targeted and strategic manner. Overall therefore, firm size may moderate the positive impact that Agarwal and Berens (2009) document. The second article by Lindsey-Mullkin and Petty is “Marketing Tactics Discouraging Price Search: Deception and Competition.” Lower prices will likely enhance consumer welfare and hence tactics that discourage price search reduce stakeholder welfare. Price shopping is a simple yet effortful way in which a consumer can search for a bargain and save in the process. Knowing fully well the onerous nature of price shopping, many marketers advertise their willingness to match competitor's prices with the hope of locking up that sale. Lindsey-Mullkin and Petty call these bargain assurances (BA), which come in many guises. They identify 12 variations that have been placed in four categories. They analyze the degree of deception present in BAs and its potential to suppress price competition and identify the types of BAs that are more problematic than others. They conclude that the current regulations vacillate between extreme vagueness and excessive detail thus rendering them ineffectual. Conflicting state regulations allow, maybe even encourage, marketers to easily engage in deceptive practices. They close by recommending a thorough review and overhaul of the regulatory policies governing price competition in a manner that increases consumer welfare without being unduly burdensome or confusing for businesses. The third and final article is by Matear and Dacin and is “Issues, Challenges and Implications of Marketing's Impact on Societal Welfare: The Case of Direct to Consumer Advertising of Prescription Drugs.” As of 2006, direct-to-consumer advertising (DTCA) was prevalent only in New Zealand and the United States; thus prior experience is rather limited. In this article, Matear and Dacin's primary task is to identify, define and measure the relevant constructs. The authors also go on to learn if and how this practice

advances societal welfare. They correctly point out that societal welfare is a multidimensional construct that involves, amongst other things, trade-offs between the individual and the collective. This tension is present in many aspects of DTCA but is best seen in its goals. Pharmaceutical companies do not want their ads to be interpreted as devices used to enhance sales; rather they would prefer them to be seen as informational. In other words, they believe that DTCA simply empowers consumers by adding to their knowledge. However, not all stakeholders see it this way. In particular, doctors and physicians—an important stakeholder community—report having to defend their recommendation in response to patients' clamoring for a prescription. This special section examines the interaction between certain marketing practices and stakeholder welfare. These articles raise as many questions as they answer. For instance, should companies allow their employees to volunteer on company time? Should we regulate the different price assurances offered by retailers? And should consumers really know more about the availability of various drugs in the marketplace? The underlying friction between individual and group welfare is the common thread that cuts across all these articles. Obviously this tension exists in other marketing practices as well and we hope that more researchers will address such issues in the future. References Agarwal ManojK, Berens Guido. How corporate social performance influences financial performance: cash flow and cost of capital. Marketing Science Institute Report No. 09-100; 2009. Bhattacharya CB, Korschun Daniel. Stakeholder marketing: beyond the four Ps and the customer. J Public Pol Mark 2008;27(1):113–6 Spring. Brudney JL, Gazney B. Moving ahead or falling behind? Volunteer promotion and data collection. Nonprofit Manag Leadersh 2006;16(3):259–76. Friedman Milton. The social responsibility of business is to increase its profits. The New York Times Magazine, September 13, 1970; 1970. Lindgreen Adam, Swaen Valerie, Johnston Wesley J. Corporate social responsibility: an empirical investigation of U.S. organizations. J Bus Ethics 2008;85:303–23. Wilkie WilliamL, Moore Elizabeth. Marketing's contributions to society. J Mark 1999;63:198–218.

Journal of Business Research 64 (2011) 61–66

Contents lists available at ScienceDirect

Journal of Business Research

Company support for employee volunteerism: Does size matter? Debra Basil ⁎, Mary Runte 1, Michael Basil 2, John Usher 3 University of Lethbridge, 4401 University Drive, Lethbridge, Alberta, Canada T1K 3M4

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Article history: Received 1 November 2006 Received in revised form 1 May 2007 Accepted 1 September 2009 Keywords: Volunteerism Company-supported volunteerism Corporate volunteerism Corporate social responsibility Organizational ecology Organizational stages theory Nonprofits

a b s t r a c t This article examines the relationship between company size and support for employee volunteering. Based on organizational ecology and organizational stages theory, the study hypothesizes that larger versus smaller companies demonstrate greater formalization and codification of their support for employee volunteering. Similarly, larger versus smaller companies use employee volunteering efforts more strategically; this finding is consistent with a need to justify decisions. These outcomes in turn impact the nature of volunteering and the organizations benefiting from such programs. Survey data from a size-stratified sample of 990 randomly selected Canadian businesses indicates that large companies support employee volunteerism in a more formalized and strategic manner than small companies. This behavior includes having formal policies and programs, as well as exercising greater influence over the causes which benefit from employee volunteering. Additionally, large companies are more likely to tie other forms of charitable support to employee volunteering. The article discusses how the more formalized approach of large companies may impact society. © 2009 Elsevier Inc. All rights reserved.

1. Introduction Companies in North America are increasingly supporting their employees' volunteering efforts in various ways (Davidson, 1994; Finney, 1997). Company support for employee volunteering (CSEV) may serve as a valuable resource for charities, nonprofit and voluntary organizations (hereafter jointly referred to as NVOs). Companies, however, have their own structures and agendas that may influence the nature and extent of support they provide. The size of a company may impact its policies and procedures, and this may in turn impact which organizations receive voluntary support, and how this support is executed. This research examines the extent to which companies support employee volunteering, and how company size impacts this support by applying both an organizational stages model and an organizational ecology framework. The research uses a large, nationally representative telephone survey of Canadian companies to examine the hypotheses.

2. Company support for employee volunteerism Corporate social responsibility (CSR) is becoming an essential practice for businesses. Both companies (The Trustees of Boston ⁎ Corresponding author. Tel.: +1 403 329 2164; fax: +1 403 329 2038. E-mail addresses: [email protected] (D. Basil), [email protected] (M. Runte), [email protected] (M. Basil), [email protected] (J. Usher). 1 Tel.: +1 403 329 2367; fax: +1 403 329 2038. 2 Tel.: +1 403 329 2075; fax: +1 403 329 2038. 3 Tel.: +1 403 329 2759; fax: +1 403 329 2038. 0148-2963/$ – see front matter © 2009 Elsevier Inc. All rights reserved. doi:10.1016/j.jbusres.2009.10.002

College, 2003) and consumers (Cone/Roper, 1999; Globescan Inc., 2004) believe socially responsible behavior is important for companies. Companies practice CSR in a variety of ways. These include (but are not limited to) charitable donations, cause-related marketing, sponsorships, codes of ethics, health and safety practices, environmentalism, and support for employee volunteering (e.g. Basil and Erlandson, 2008; Lafferty and Goldsmith, 2005; Maignan and Ralston, 2002). Support for employee volunteerism is emerging as an important tool through which companies demonstrate their CSR (Burnes and Gonyea, 2005). Support for employees' volunteerism is prevalent across North America. Between 55% and 80% of US companies are estimated to support employee volunteering in some way (Brudney and Gazney, 2006). In Canada, more than half of the employed volunteers responding to a nationwide survey report receiving one or more forms of support from their employer (Canada Survey of Giving, Volunteering and Participating, 2004) and over 2/3 of Canadian companies report supporting employee volunteering in some way (Basil et al., 2008). Some companies, such as Timberland (USA), have a CSEV strategy that includes direct support for employee volunteerism through paid work time for volunteer endeavors (http://www. timberland.com/corp/index.jsp?page=communityInvolvement, accessed May 22, 2007); others, as a component of their CSEV program, provide leadership through company-initiated volunteer projects, such as CIBC (Canada)'s support for the ‘CIBC Run for the Cure’ in aid of breast cancer research (http://www.cibc.com/ca/ inside-cibc/cibc-your-community/sponsorship/cibc-run-for-the-cure. html, accessed May 22, 2007). Many companies provide a variety of forms of indirect support for employee volunteerism including allowing employees to use company resources such as photocopiers

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to support their volunteer endeavors, or by rescheduling work shifts to accommodate a volunteer schedule (Basil et al., 2008). Companies can benefit from their support of employee volunteering in several ways. CSEV can enhance public image (Basil et al., 2008), relations with consumers, and relations with the surrounding community (Cone/Roper, 1999; Maignan et al., 1999). Such volunteering can also enhance employee morale, productivity, skills, retention, and recruitment (e.g. Basil et al., 2008; Davidson, 1994; Finney, 1997; Geroy et al., 2000; Peterson, 2004; Points of Light Foundation and Allstate Foundation, 1999). Finally, return on assets and investment positively correlate with company community involvement (Dowell et al., 2000; Margolis and Walsh, 2001; Waddock and Graves, 1997). Nonprofits also benefit from employee volunteering. For example, NVOs gain valuable volunteer hours from CSEV. Since many rely on, but have a difficult time securing, sufficient volunteers (NSNVO, 2004), this is a valuable asset. NVOs can also benefit through increased familiarity resulting from CSEV. The mere exposure effect suggests that exposure may create preferences (Zajonc, 1968). Branding research suggests that familiarity enhances confidence and purchase intention (Laroche et al., 1996). Charitable donations research suggests an advantage for more familiar charities (Harvey, 1990). Applying this to the context of NVOs, volunteering can increase familiarity, which may increase donation likelihood. CSEV presents some risks for both the company and the NVO however that may act as barriers to the support of corporate volunteerism within organizations (Points of Light Foundation and Allstate Foundation, 1999). For companies, loss of employee time is a concern (Basil et al., 2008; Points of Light Foundation and Allstate Foundation, 1999). Administrative costs also pose a concern for companies (Points of Light Foundation and Allstate Foundation, 1999). Another risk for companies and NVOs is alienating customers, donors, and/or employees. If companies select particular causes to champion, they risk alienating those who may not view the selected cause positively. Brand alliance research demonstrates that spillover effects from brand alliances can significantly affect both partnering brands (Simonin and Ruth, 1998). Similarly, pairing with certain companies may negatively affect NVO attitudes (Basil and Herr, 2003), suggesting that both NVOs and companies must ally with caution. America Gives Back, an initiative of Fox Television Network's “American Idol” (USA), received criticism for supporting causes that encourage family planning (Elfman, 2007). To avoid negative spillover effects, some company volunteerism programs require project approval, and carefully screen the causes for eligibility. For example, Filipowski (1993) reports the exclusion of political and religious organizations from employee volunteerism programs. Previous research in both the U.S. (Witter, 2003) and in Canada (Basil et al., 2008; Rostami and Hall, 1996) provides a description of the nature and extent of company support for employee volunteering. This research extends that descriptive work by providing a theoretical rationale that begins to explain differences between companies' support for employee volunteering.

3. The impact of size This research assesses the extent and nature of participation in CSEV with regard to company size. Although previous studies suggest a relationship between company size and participation in CSEV (Points of Light Foundation, 2004; The Trustees of Boston College, 2003), this relationship has not been rigorously assessed. Moreover, this research advances two theoretical bases in support of the relationship; these are organization stages theory (Greiner, 1972; Child and Kieser, 1981) and organizational ecology (Hannan and Freeman, 1977).

The study uses these two perspectives as representative of the two general approaches that prevail to describe organizational change: adaptation and selection (Barnett and Carroll, 1995). The adaptation stream proposes that organizational change occurs as an adaptive response to both internal forces (such as organizational growth) and external forces (such as environmental decline). Organization stages models (also called developmental or life cycle models) thus explain the structural characteristics of organizations as adaptive responses to predictable crises brought on by increasing age and size (Aldrich, 1999). The second approach, selection, assumes great difficulty and risk in organizational change. Change can lead to failure followed by selective replacement of old failures (Barnett and Carroll, 1995). Organizational ecology, positioned within the selection stream of research, explains that the structural characteristics of organizations are outcomes that are driven by the need of organizations to achieve stable, reproducible routines that do not expose them to unnecessary risk (Hannan and Freeman, 1984). What is most interesting, however, is the extent to which each of these perspectives, despite quite dissimilar underlying assumptions, makes similar predictions about the presence of formalization and strategic usage of CSEV in organizations. The following section describes each of these perspectives in more detail and presents hypotheses based on their convergent arguments. The foundational assumption of Hannan and Freeman (1984) is that “Selection in populations of organizations in modern societies favors forms with high reliability of performance and high levels of accountability (p. 154).” They propose that the reliability with which an organization delivers products or services demonstrates accountability to society and are key determinants of the organization's survival. Reliability suggests that products or behaviors will be duplicated with minimal variance. This allows actors to develop expectations regarding performance, providing a level of certainty in what will be received. To attain reliability, companies create standardized routines and formalize policies and procedures to assure reproducibility. Formalization helps to assure consistent output. Accountability requires that organizations be able to justify their actions and the allocation of resources (Hannan and Freeman, 1984). Preference for accountability stems from the emphasis on rationality in modern bureaucratic organizations (Weber, 1968). Accountability necessitates that proper rules and procedures exist; these rules then serve as justification for an action or decision. High reliability suggests a lack of change, or inertia. Hannan and Freeman (1984) propose that this inertial tendency increases with company size. Echoing this sentiment, Aldrich and Auster (1986) discuss the need for internal consistency and control in organizations, a need that increases with size independent of age. Similarly, Germain, Droge, and Daugherty (1994) find that larger companies tend to have a higher level of formalization in business practices. Due to their larger number of operations and resulting complexity, larger organizations have more potential sources of variability, so greater formalization is needed. To maintain reliability, larger companies can therefore be expected to implement greater formalization and standardization. This internally-driven line of reasoning suggests the second perspective, organizational stage theories. The best known of the models from this perspective is probably the organization life cycle model (Greiner, 1972; Quinn and Cameron, 1983). In this model, organizations are seen to move through four stages of development as organizational size increases and to experience predictable crises which must be resolved before successful transitions can be made from stage to stage. This research addresses the third stage of development, the formalization stage. As described by the standard text of Daft (2007: 328), “(t)he formalization stage involves the installation and use of rules, procedures, and control systems.

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Communication is less frequent and more formal. Engineers, human resource specialists, and other staff may be added. Top management becomes concerned with issues such as strategy and planning…” This tendency toward formalization in larger companies should carry through to CSEV and therefore more formalized CSEV should be evident in larger companies compared to smaller companies. Having official CSEV programs and having written policies for these programs are evidence of formalization in CSEV. Microsoft, for example, has a formalized Employee Engagement program that profiles corporate support for philanthropy and volunteerism and clearly delineates program scope and eligibility parameters (http://www.microsoft.com/ about/corporatecitizenship/citizenship/giving/programs/employee. mspx, accessed May 25, 2007). Larger companies are likely to demonstrate less flexibility in the implementation of CSEV than smaller companies. Bank of America, for example, targets specific categories of nonprofits through its Volunteer Grants program (http://www.bankofamerica.com/foundation/index.cfm?template=fd_grantprograms, accessed May 25, 2007). This focus supports the premise that companies are seeking consistency and reproducibility. Flexibility runs counter to such goals and thus should be lower for larger companies that seek to control their many potential sources of variability. H1. Company size relates positively to formalization of CSEV. Specifically, company size relates positively to (A) the existence of CSEV programs supported by company resources; (B) written CSEV policies; and (C) less flexibility regarding CSEV implementation. Hannan and Freeman (1984) stress the importance of accountability for successful organizations. Accountability requires that organizations have justifiable reasons for their actions. Strategic decision making can help an organization attain accountability, based on the assumption that strategic planning provides both a framework for action and a means of evaluating the effectiveness of actions taken. In this context, strategic decisions are defined as decisions based upon some given company strategy that are made in an effort to attain certain ends. A strategic foundation relates to company success (Robinson and Pearce, 1988; Zeithaml and Fry, 1984). For example, the strategy of following a marketing orientation that makes salient differentiable product attributes enhances company profit (Narver and Slater, 1990). Although not all findings support a clear relationship between profit and strategy (see Bantel and Osborn, 1995), the entire field of strategic management is built around the premise that a positive relationship does exist. In examining the debate between a resourcebased view of the firm (Barney, 1986) and those examining industry level forces (Porter, 1980) as the source of abnormal firm returns, Roberts (1999) finds that firm strategies based on innovation are almost entirely responsible for the sustained profitability of the U.S. pharmaceutical industry. Applying the concept of a strategic approach to CSEV suggests that strategically selecting charitable causes could be beneficial to the company directly and indirectly by increasing consumer support. When a company makes a strategic choice to support a cause with which they fit, consumer response is more positive than when the company aligns itself with a cause that does not have a perceived fit (Basil and Herr, 2006). Moreover, research supports that companies do use CSEV strategically for the purpose of benefiting the company (Points of Light and Allstate, 1999; Wild, 1993). Wal-Mart, for example, provides grants to nonprofits for which their employees volunteer, if the supported program is located in a community served by a Wal-mart (http://walmartstores.com/GlobalWMStoresWeb/navigate.do?catg=435, accessed May 25, 2007). Strategic orientation toward CSEV suggests that accountability for CSEV is mainstream corporate thinking. Support for NVOs through CSEV is also symbolic. Hannan and Freeman (1984) suggest that the need for accountability is greater

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when more symbolic, intangible products, such as education, are involved. CSEV efforts demonstrate particular values toward altruism and social responsibility, suggesting a strong need for accountability relative to CSEV. Strategic use of CSEV can better assure accountability because justifiable reasons for CSEV decisions should be evident when a particular strategy is followed. The relationship between strategy and performance relates to company size (Smith et al., 1989). Larger companies follow an identifiable strategy more frequently than smaller companies (Bantel and Osborn, 1995). Similarly, large companies engage in strategic planning more than small companies (Ballentine et al., 1993). With respect to the life cycle model, organizations entering the formalization stage of growth are characterized by heightened managerial concern for strategy and planning. The study includes the expectation that this pattern carries into CSEV as well. Large companies should be more likely to use CSEV in a strategic manner, in comparison to small companies, for the same reasons that greater formalization is expected of them. Specifically, large organizations face more potential sources of variation and more potential decisions that require justification. Following specific, identifiable strategies can provide the necessary justification for decisions, thus assuring accountability. Therefore, large companies should be more likely to use CSEV strategically. Many routes offer evidence that support the strategic use of CSEV. Targeting certain causes for CSEV is a strategic choice, reflecting desired associations. McDonalds's corporate website, for example, currently features a photo of a Ronald McDonald costumed employee playing basketball with youth in promotion of their balanced active lifestyles orientation (http://walmartstores.com/GlobalWMStoresWeb/navigate. do?catg=435, accessed May 25, 2007). Similarly, deliberately excluding certain NVOs from support is a strategic choice signaling the causes with which the company wishes to avoid association. Finally, companies may strategically choose to present a consistent message in terms of their cause support by linking their CSEV with other altruistic company behaviors such as linking corporate financial donations to employees' volunteer priorities. H2. Company size relates positively to the strategic use of CSEV. Specifically, company size relates positively to: (A) targeting specific cause types; (B) excluding specific cause types; and (C) linking other forms of charitable support to their CSEV efforts. In summary, using the convergent predictions of organizational ecology and organization stages theories, reliability and accountability are important for CSEV. Reliability is attainable through formalization. Accountability is attainable through strategic decision making. Since large companies face more potential decisions and sources of variability, reliability and accountability are more important to them. Higher levels of formalization and strategic decision making regarding CSEV characteristics and outcomes should occur in large versus small firms, as the hypotheses state. 4. Method The study includes a major nationwide telephone survey of Canadian companies to test the hypotheses. A telephone survey offered a relatively high response rate and random selection of participants from across the country. The telephone survey also allowed direct access to company CSEV decision makers, helping to assure that the appropriate individual responded. 4.1. Sample A comprehensive list of Canadian businesses was purchased through InfoCanada, a reputable list provider. From this, a stratified random sample was selected. Companies were sampled at the establishment level, with only one response per company. This is

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the level of business at which accounting data are collected (Statistics Canada, 2006). The sample was stratified based on company size. Small businesses were defined as having fewer than 100 employees, medium businesses were defined as having 100 to 499 employees, and large businesses were defined as having 500 or more employees. Since the vast majority (98%) of Canadian businesses are classified as “small” (Industry Canada, 2005), an over-sampling of medium and large businesses was collected to assure a sufficient number of respondents in these categories for statistical analysis. The final sample contained 586 small, 204 medium, and 200 large companies, for a total of 990 responses. For analyses based on company size, results are within plus or minus 4.1% for small businesses, 6.9% for medium businesses, and 4.0% for large businesses. 4.2. Survey instrument The final survey had 35 questions that were either adapted from prior similar surveys (e.g. Rostami and Hall, 1996; Witter, 2003) or developed by the researchers. . Nine questions were open-ended and 26 questions utilized nominal scaling (primarily “yes,” “no,” “I don't know,” and “refused to answer”). Nominal measurement was selected to assure the questions would be easy to comprehend, enhancing data validity. Given that survey respondents were busy professionals, the survey was relatively short and simple. Only a portion of these questions was used in the present analysis. They are specified below. 4.3. Procedure The telephone survey was conducted by Pollara Inc., an established Canadian research firm. The interviewer requested to speak with “the person who is responsible for coordinating your company's volunteer program.” If the company had no such person, then the person responsible for human resources was requested. If the respondent indicated “don't know/refused” when asked about the company's position with regard to employee volunteering during regular work hours, and “don't know/refused” when asked whether the company encourages employee volunteering outside of work, then the company's industry was recorded and the interview was terminated because the respondent's level of knowledge regarding volunteering within the company was deemed insufficient. Similarly, if the respondent indicated that the company discourages employee volunteering during regular work hours and the company does not encourage volunteering outside of regular work hours, the company's industry was recorded and the interview was terminated because the survey questions focus on company activities supporting volunteerism which are not applicable to this group of respondents.

17.8, p = .001), supporting Hypothesis 1A. Responses to the question, “Does your company have a written policy regarding employee volunteering?” address Hypothesis 1B. Results demonstrate significantly greater likelihood of a written policy within large companies, comparing to small (21% vs. 3% respectively; X2 (2, 735) = 54.8, p < .001). To assess H1C, which proposes less flexibility among large companies; respondents indicate whether they allow employees to adjust work schedules to accommodate their volunteer activities. Large companies are less likely to do so than small companies (67% vs. 78% respectively; X2 (1, 531) = 5.3, p < .05), supporting Hypothesis 1C. Taken together these results suggest that large companies have more formalized support for employee volunteering, supporting Hypothesis 1. Hypothesis 2 proposes that company size is positively related to the strategic use of CSEV. Three tests assess this. First, Hypothesis 2A proposes large companies are more likely to target particular causes. To assess this, respondents indicate “What specific types of organizations or causes do your company target for support, if any?” This open-ended question is dichotomously coded according to whether they do or do not target. Large companies are significantly more likely to target specific causes, compared to small companies (78% vs. 66% respectively; X2 (1, 563) = 6.9, p < .001). Addressing Hypothesis 2B, respondents indicate “What specific types of organizations or causes does your company exclude from support, if any?” This open-ended question is dichotomously coded according to whether they do or do not exclude. The majority of companies indicate that they do not exclude any types of NVOs from their employee volunteering programs (79%). For those who do make exclusions, large companies are significantly more likely to do so than small companies (23% vs. 12% respectively; X2 (1, 500) = 8.6, p < .005). To assess whether large companies are more likely to strategically link CSEV with other forms of charitable and nonprofit support consistent with Hypothesis 2C, companies indicate if they have provided cash support to charitable causes or nonprofit organizations in the past 12 months, and if they have provided donations of services, goods or facilities to charitable causes or nonprofit organizations over the past 12 months. If they indicate yes to either question, they then respond to the question “Is this support linked to employee volunteering? That is, do you donate cash, services, goods or facilities to organizations that your employees volunteer for?” Large companies are significantly more likely to link charitable support to CSEV, compared to small companies (65% vs. 60% respectively; X2 = 5.2, p < .05). Taken together these results support Hypothesis 2. Large companies appear to use CSEV more strategically than small companies. 6. Discussion 6.1. General discussion

4.4. Analyses Company size was assessed as a dichotomous variable, comparing small (fewer than 100 employees) and large (500+ employees). Medium-sized companies were not used in these analyses, as the hypotheses do not make clear predictions for them and the margin of error was too high. Questions were dichotomized as “yes” and “no” and chi-square analyses were run to assess the existence of significant differences between the two groups. 5. Results Hypothesis 1 proposes that company size relates positively to formalization of CSEV. Three questions assess this. The first question is: “Does your company have an employee volunteer program that is supported by company resources?” Large companies are more likely to have a formal volunteer program supported by company funds, compared to small companies (32% vs. 16% respectively; X2 (1, 546) =

The results of this research demonstrate that large companies apply greater levels of formalization to their employee volunteering programs. This is evident in the existence of volunteering programs and the existence of written policies for these programs. Additionally, large companies demonstrate less flexibility in their CSEV, compared to small companies. These outcomes support the study predictions and are consistent with both organizational ecology and developmental stages theories. Having greater formalization and less flexibility in CSEV suggests both positive and negative implications. Employees may be more aware of formalized programs, compared to informal programs. As such, formalization may encourage greater employee participation. Employees may also be more willing to participate in formalized programs, not having to fear being seen as opportunists seeking special privileges. Conversely, however, formalized programs may have qualifying rules and regulations that are difficult for employees or NVOs to meet, therefore potentially reducing participation.

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The lack of flexibility in these programs may help meet the needs of the company at the expense of the needs of the NVO. A more rigid program allows the company greater control over employees. A lack of flexibility may also mean that NVOs are not able to secure volunteers at times when they are most needed, thus reducing the value of these employees to the NVOs. This research also supports the proposition that large companies use CSEV in a more strategic manner than small companies. Large companies are more likely to target specific causes or NVOs for support, and to exclude specific causes or NVOs. This has interesting implications for society. This result suggests that, to some extent companies may be steering volunteerism. Some causes and NVOs, most likely those that are perceived to be more socially acceptable, will benefit as a result of corporations steering volunteerism towards their organizations However other causes and NVOs may suffer, at least in relative terms. These will likely be the smaller and more controversial causes; often those most in need of additional volunteers. This outcome is particularly troubling considering such causes and NVOs oftentimes serve the most marginalized groups in society and a nonprofit's ability to serve these less favored groups may be compromised by diminished fiscal and volunteer support. Large companies are also more likely than small companies to strategically link CSEV to other charitable behaviors. This result suggests that the selective influence that large companies exercise by targeting and excluding some NVOs from their programs will be magnified in terms of overall impact on NVOs. That is, those NVOs which are not favored for volunteering efforts may also be less likely to receive other forms of company support. Company programs supporting employee volunteerism may impact society by providing a larger pool of volunteers to the NVOs that need them or by steering them away from other NVOs that are in equal or even greater need of support.

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6.4. Future research Future research should assess the impact of CSEV from an NVO perspective. The research is not positioned to assess the particular types of inclusions and exclusions companies use in their CSEV. Further research is needed to assess the types of NVOs that are targeted or excluded, and what impact this has on NVOs, companies, employees, and society. Testing the association between CSEV and employee behavior warrants additional research. Do employees modify their volunteer endeavors to match CSEV program parameters? The perception of support for personal time volunteerism with company-supported causes/charities may result in the shaping of personal time volunteerism as employees seek to maximize personal reward or the charitable benefit for supported causes. For causes that corporations explicitly exclude supporting, or even implicitly favor less, the potential for further erosion of volunteer support exists. Also, as employees satisfy their desire to volunteer for work-sponsored or endorsed endeavors; does a net gain or loss occur to volunteer hours? Do employees decrease personal time volunteering if engaged in CSEV programs that allow them to volunteer during working hours? Thinking about CSEV at the corporate level, rich opportunities to examine the boundary conditions of organization theory's core paradigms may exist. To what extent are transaction cost economics useful in understanding why organizations seem to be bureaucratizing CSEV? Conversely, to what extent does the social legitimation hypothesis of institutionalization theory, which sees businesses gaining social credits through relatively altruistic philanthropy, explains CSEV activities? Comparing these two perspectives might be a useful way to explore the reasons that the corporate sector appears to be co-opting a private activity (volunteering) from the public sphere. Acknowledgments

6.2. Conclusion The research provides an explanation for CSEV activities based on company size by applying the work of Hannan and Freeman (1984), operationalizing reliability and accountability in the context of CSEV with support from the predictions of organization stages theory, especially life cycle models (Greiner, 1972). The results demonstrate that large companies are typified by more formalization in their use of CSEV, and that large companies use CSEV in a more strategic manner than small companies. The research identifies that companies can have an impact on society through CSEV but also suggests that the form of CSEV may differ depending upon company size. The more strategic and formalized approach used by larger companies may lead to a selection process whereby less favored NVOs suffer in a relative sense as causes benefiting from employee volunteerism are shaped by company strategy rather than societal need.

6.3. Limitations Of course, this research has certain limitations that should be acknowledged. First, the survey itself is relatively short. Second, data are collected primarily at the nominal level of measurement. Finally, although each hypothesis is tested through three different measures, each measure is assessed with only a single item. All of these factors limit the richness of the data. Respondents, who are company executives, are unlikely to have the time or inclination to answer a longer survey, or a survey with more detailed response options. By using a short, relatively simple survey, this research increases the response rate thus enhancing the validity of the data. This brevity sacrifices richness for validity and a higher response rate.

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Contents lists available at ScienceDirect

Journal of Business Research

Marketing tactics discouraging price search: Deception and competition Joan Lindsey-Mullikin a,⁎, Ross D. Petty b,⁎ a b

California Polytechnic State University, San Luis Obispo, USA Babson College, USA

a r t i c l e

i n f o

Article history: Received 1 December 2008 Received in revised form 1 July 2009 Accepted 1 September 2009 Keywords: Deception Pricing Competition Marketing tactics Search behavior Legal

a b s t r a c t Retailers attempt to assure consumers that their deals are bargains using a variety of marketing tactics. Because consumers continue information and price searches until satisfied with the amount of the information to make a purchase, such bargain assurances (BAs) can change consumers' shopping behavior. This article identifies twelve common BAs and reviews extant marketing literature to derive evidence of how BAs affect consumers' purchasing behavior. It then examines how these practices are regulated to prevent consumer deception or a reduction in competition. This article concludes by offering three policy recommendations: BAs influence consumers and require regulation; the regulation of BAs demands a comprehensive rather than a piecemeal approach; and consumer policy should facilitate and encourage accurate price comparisons. © 2009 Elsevier Inc. All rights reserved.

1. Introduction Consumers often make purchases not based on price but because a retailer assures them that a deal is a bargain. This occurs when marketers use such tactics as communicating a price is on sale, or when the retailer highlights the relative savings compared with the prices of competitors (e.g., “Compare Our Price $X with Their Price $Y”), offers a price-matching guarantee, or bundles products at a lower price than when purchased separately (e.g., buy 1, get 1 free). This paper examines the relevant marketing and legal literature to show that these bargain assurances (BAs) change consumers' purchasing behavior and may deceive consumers. Consumers engage in information and price search until satisfied with the amount of the information they obtain. BAs alter the nature and flow of consumers' shopping behavior and influence consumer price search behavior. Since some BAs may mislead consumers into prematurely terminating price search, they may impede competition and warrant oversight by the FTC.

twelve basic BA tactics into four broad categories of fundamental strategies: ongoing values, component value, price comparisons, and buy now as shown in Table 1. The use of these BAs creates two main public policy concerns. First, consumers select a price offering because the BA misleads them regarding the degree to which the offering represents a bargain. Second, the use of BAs partially substitutes for actual price competition, which public policy steadfastly recognizes as beneficial to consumers and the sine qua non of competition. This article examines twelve BAs in terms of both marketing impact, legal, and regulatory issues. 2.1. Ongoing values These tactics are ongoing in nature rather than limited time offers. They do not try to create a sense of urgency or immediacy to prompt a purchase. The implicit assumption behind this set of tactics is that many consumers don't want to invest too much time to find the lowest prices. For them, the convenience of one-stop shopping compensates for slightly higher prices on a few items.

2. Analysis of bargain assurances Petty and Lindsey-Mullikin (2006) suggest that BAs represent a form of compensation that marketers use to develop consumer interest in brands. For the ease of discussion, this paper organizes the ⁎ Corresponding authors. Lindsey-Mullikin is to be contacted at the Orfalea College of Business, California Polytechnic State University, San Luis Obispo, CA 93407-0302, USA. Tel.: +1 805 756 1179; fax: +1 805 756 1473. Petty, Department of Accounting and Law, Babson College, Babson Park, MA 02457, USA. Tel.: +1 781 239 5529; fax: +1 781 239 5230. E-mail addresses: [email protected] (J. Lindsey-Mullikin), [email protected] (R.D. Petty). 0148-2963/$ – see front matter © 2009 Elsevier Inc. All rights reserved. doi:10.1016/j.jbusres.2009.10.003

2.1.1. Loyalty/frequency program rewards Airlines initiated the modern surge of loyalty programs in 1981 (Kivetz and Simonson, 2002). Most airline programs offer free or reduced prices on future purchases from the company or partner companies after consumers earn points by making purchases. Many shoppers use loyalty grocery cards, for example, in which the grocer gives discounts on groceries in exchange for valuable shopping data. Loyalty programs attempt to increase purchases by existing consumers because retaining customers is less expensive than acquiring new ones (Grewal, 2008; Kivetz and Simonson, 2002; Reichheld and Sasser, 1990). According to Lewis (2004), in the long

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Table 1 Bargain assurances. Ongoing values

Component values

Price comparisons

Buy now

Loyalty programs Everyday low pricing Price-matching guarantees

Partitioned prices Product bundling

To value, cost or list To rival prices

Limited time price Limited quantities

To own prices Percentage off Tensile pricing (up to $5 off)

term, loyalty programs coupled with other marketing tactics increase annual purchasing amounts. In high-involvement situations, loyalty programs increase brand loyalty both directly and indirectly (Yi and Jeon, 2003). However, lower-quality rewards can interfere with preexisting favorable brand associations (Roehm et al., 2002). These programs provide the perception of added value, designed to make consumers less sensitive to rival price promotions. Kim et al. (2001)) suggest that when most industry members adopt a loyalty program, they enter tacit agreements with each other to avoid price-cutting because such tactics presumably make consumers less price sensitive. If a retailer fails to honor a loyalty reward program, the failure represents false advertising or breach of contract. For example, when General Motors (GM) refused to honor points that consumers earned by using GM credit cards for their purchase or lease of a GM vehicle, the New York Attorney General sued and obtained a settlement to pay consumers the rebates that GM originally promised (New York State Attorney General, 2002).

2.1.2. Every day low pricing (EDLP) In pure EDLP strategies, the retailer charges a constant, lower, everyday price with no temporary price discounts, in contrast with competitors that offer periodic sale promotions (Hoch et al., 1994). Thus, EDLP programs attract both large basket consumers who buy a variety of goods (Bell and Lattin, 1998) and bargain hunters who tire of reviewing individual ads and shopping at multiple stores (Lal and Rao 1997). The successful EDLP format results in higher profits for the retailer than other pricing promotions (Lal and Rao, 1997). For example, Wal-Mart uses the EDLP format to simplify merchandising and market prices approximately 20–25% lower than competitors' prices (Bell and Feiner, 2002; USB Warburg, 2002). Although consumers cannot easily verify such claims, law enforcement agencies rarely challenge EDLP claims. Only Ohio specifically regulates EDLP claims by prohibiting advertisers from characterizing a business, store, or store department as discount unless that characterization is accurate (OAC Ann. 109:4-3-12(C)). Agencies that consider EDLP claims often find the claims are merely puffing. For example, the National Advertising Division of the Council of Better Business Bureaus (NAD) supported Wal-Mart's argument that customers understood the slogan “Always The Low Price. Always” to mean Wal-Mart maintained a general policy of offering low prices, not that the retailer would always have the lowest prices (Wal-Mart Stores, Inc., 1994). Similarly, courts held that the phrase, “We are the low cost commercial collection experts,” is puffery (Cooke, Perkiss and Liehe, Inc. v. Northern California Collection Service, Inc., 1990). Challenges to comparative low prices include Winn-Dixie's claim of “Everyday Lower Prices” in conjunction with specific price comparisons with Wal-Mart's prices; the claims deceptively communicated that the grocer's prices were lower than those of Wal-Mart (Winn-Dixie Stores, Inc., 1996). The FTC also challenged a grocery store's comparison of a typical market basket of its goods with a market basket of the same items from a rival, because the comparison excluded goods on which the surveying store performed poorly on

price (Kroger Co., 1981). Even when another retailer truthfully compared savings on two grocery baskets, the NAD indicated the ads suggested lower prices storewide and recommended discontinuing the unsubstantiated claim (Tops Markets, LLC, 2004). 2.1.3. Price-matching refunds Price-matching policies or low-price guarantees are promises by firms to match competitors' prices. Although such guarantees might apply to a limited time sale or a few items, many retailers make these offers as ongoing policies covering all products. Price-matching guarantees often include a time limitation, (e.g., find a lower price within 30 days of purchase) and a specific reward such as matching or exceeding the lower price and a specific award (e.g., a bottle of champagne). Consumers view price-matching refunds as signals of low store prices (Srivastava and Lurie, 2001). For this reason, this tactic increases consumer purchase intentions, likelihood of purchase, and the likelihood of discontinuing further price search (Jain and Srivastava, 2000). Firms can discriminate among consumers who rely on the refund policy and pay the offered (higher) price and those who test the policy and obtain the reward for finding a lower price (Jain and Srivastava, 2000). However, when an entire industry uses pricematching refunds, the incentive to compete on price declines (Eldin, 1997; Hess and Gerstner, 1991; Salop 1986). At least one private lawsuit and an NAD case mirror the findings of these marketing studies; lowest price guarantees indicate that the offering firm's prices are the lowest available and such claims must be accurate (Lenscrafters, Inc. v. Vision World, 1996; The Home Depot, 2005). The Better Business Bureau (BBB) Code (2003) takes a less sweeping approach and argues that price guarantees create an implicit obligation to reduce the price of any product after finding that a rival offers a lower price. Both the BBB Code and Missouri law suggest that price guarantee advertising must clearly disclose all material conditions and limitations and not place an unrealistic or unreasonable burden on consumers (15 CSR 60-7.110 Mo. 2005). 2.2. Component values Marketers may choose to emphasize the most favorable aspect of their offering, such as a single price component rather than the overall price of the offering or a product component that may be of greatest interest to consumers. 2.2.1. Partitioned prices Partitioned prices consist of two or more mandatory parts of price, such as a base price of $30 and shipping and handling of $4.95 (Morwitz et al., 1998). The normal practice emphasizes the base price in advertising but discloses additional charges less prominently. Partitioned pricing also encompasses post purchase rebates where the advertiser promotes the lower post-rebate net price rather than the higher actual purchase price. Fewer than 25% of consumers can calculate the two prices accurately and nearly 25% of consumers ignore any extra charge beyond the base price. Thus, more than half of consumers use some heuristic to combine the base price and the surcharge, which often results in a lower total recalled price (Morwitz et al., 1998). Authorities generally allow sellers to advertise partitioned prices if the advertiser clearly discloses any additional charges without obscuring them through small print or confusing language (Coral Telecom, Inc. 2003; Schnall v. Hertz Corp., 2000). Sellers cannot misrepresent the idea that a price includes delivery and then add a delivery fee (Market Development, 1980). Marketers cannot add third-party fees or exaggerate the amount of sales tax and then fail to pay the same amount to the appropriate party (Hartigan v. Stianos, 1985; Jim Walter Homes, Inc. v. White, 1981). If the low advertised price includes a higher selling price and a rebate, the seller must

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disclose those two elements (Caldor, Inv. v. Heslin, 1990; Gateway, Inc., 2003). 2.2.2. Bundling products and prices Bundling occurs when two or more separate products are offered as one unit, typically at a discount compared with their individual prices. The added product might be the same as the original product (two for one), a complementary product, or a simple prize premium. Marketers often package both products together, but sometimes consumers must send in a proof of purchase and perhaps a handling fee to receive the second product. In contrast with partitioned pricing, bundle pricing entails a single price (though the seller also may disclose the prices of items if sold separately). Stremersch and Tellis (2002) distinguish price bundling where the seller offers two or more separately sold products together, from pure bundling where the seller offers at least one product only as part of a bundle. Consumers evaluate bundles on the basis of the item within the bundle that they consider most important (Yadav, 1994). Savings on the important product influences consumers' perceptions of the transaction value more than do savings on the items sold separately (Yadav and Monroe, 1993). Furthermore, the consumer behavior literature suggests that price bundling often decreases price sensitivity and increases purchase likelihood (Soman and Gourville, 2001), such that consumers might purchase a bundle even if they do not consume all of each part. Bundling raises both deception and antitrust exclusion issues. Because consumers evaluate the value of the bundle on the basis of the dominant product, FTC Guides (16 C.F.R. § 233.4; § 251.1(b)) suggest that retailers cannot raise the price to accommodate the second product. Although FTC guides are not legally binding, courts often defer to them because of the FTC's expertise in regulating deceptive advertising (B. Sanfield, Inc. v. Finlay Fine Jewelry Corp., 1999). The Better Business Bureau (2003) further notes that a free offer should be temporary; otherwise, the bundle becomes a regular offering, and no part is free. In a classic case, the Supreme Court affirmed the FTC's holding that a paint seller's promotion of “Buy one can, get a second for free” was deceptive because the seller's continuous promotion excluded any single can sales. Thus, the promotion deceptively described the price for two cans as a single can price (FTC v. Mary Carter Paint Co., 1965). Recent NAD decisions similarly condemn continuous “buy one, get the second one for free” or “percentage-off” tactics (e.g., NBTY, Inc., 2005). Deception cases involving pure bundling often allege that the offer fails to disclose that consumers must purchase a second product to receive the first (e.g., low car price with a high interest loan) (New York State Attorney General, 2002). The antitrust challenge to pure bundling argues that in some cases, this approach restricts the ability of rivals to sell the second product by itself (Stremersch and Tellis, 2002). A well-known example involves Microsoft, which bundled various accessory programs within the Windows operating system. Consumers had little incentive to buy those accessories separately. The settlements of the U.S. lawsuits regarding this issue did not require unbundling of the web browser, whereas the EU order requires Microsoft to offer the operating system without a media player. 2.3. Price comparisons In this largest category of BAs, from both the marketing and legal perspectives, marketers develop an array of targets for comparisons such as list price, cost, market value, rival prices and the seller's own price at another time, as well as different methods of comparison, (e.g., side-by-side, percent off, and “up to” savings). Reference price ads strongly influence consumer perceptions of value (Blair and Landon, 1981; Kaufman et al., 1994; Lichentstein et al., 1991; Urbany et al., 1988). Consumers often increase their internal reference prices in response to higher comparison prices, which may make reference prices even more powerful tools than EDLP (Grewal

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et al., 1998). Consumers also attend to comparative ads more than noncomparative ads and recall more of the messages in comparative ads (Grewal et al., 1997). Lastly as advertisers increase the level of an advertised reference price, consumers' internal reference prices increase, their perceptions of value and purchase intentions increase, and their intention to conduct additional price search decreases (Grewal et al., 1998; Kopalle and Lindsey-Mullikin, 2003). However, if comparative price advertising communicates a misleading perception of value, consumers cannot assess the actual value of the offering accurately. Furthermore, consumers may misunderstand the meaning of the type of reference price (Compeau and Grewal, 1998; Grewal and Compeau, 1992). 2.3.1. Vague referent price comparisons Marketers often compare their prices with vague referents, such as the manufacturer's suggested list price (MSLP), invoice cost, or estimates of comparable value. Two studies reveal that consumers believe the MSLP represents the price at which most stores sell the product (Compeau et al., 2003; Grewal and Compeau, 1992). Regulating price comparisons requires identifying the reference price. Illinois, Louisiana, Massachusetts, Missouri, and Ohio require advertisers to identify the basis for any price comparison or savings, unless the comparison refers to the seller's former price (14 Ill. Adm. Code 470.210 (2005); LAC 16.111.303 (2003); 940 CMR 605(2) (Mass. 2005); 15 CSR 60-7.060 (Mo. 2005); OAC Ann. 109:4-3-12(E)). The general rule for comparisons to vague reference prices, such as comparable value or list price, requires advertisers to base a reference price on facts so that the referent price does not exceed the price at which substantial sales occur in the area (16 C.F.R. § 233.2-3). Several states also require that the advertiser make substantial sales at the list price, document that the list price is prevalent, or disclose that the list price may not be representative of prices in the area (Komensky and Wegener, 1991; 9 Alaska Admin. Code 05.030 (2005); Regs. Conn. State Agencies § 42-110b-13a (2005)). According to the NAD, WalMart.com misled consumers by providing list prices when the manufacturer did not issue a list price (Wal-Mart.com, Inc., 2002). A second common referent is product cost or wholesale price, which should be the price the seller paid to acquire the product (16 C. F.R. § 233.5; Better Business Bureau, 2003; 940 CMR 605(12) (2005)). Florida requires that prices in a below wholesale or cost sale fall below the seller's net cost or average wholesale price (Fla. Stat. § 817.41 (2005)). Alaska requires that references to wholesale cost include the cost of shipping (9 Alaska Admin. Code 05.030 (2005)). Some states even prohibit price comparisons to the invoice price or dealer cost for automobile advertising because the multitude of meanings makes the deception of some consumers inevitable (Adams Ford Belton, Inc. v. Missouri Motor Vehicle Com., 1997; Barry v. Arrow Pontiac, Inc., 1985). 2.3.2. Comparison to rival prices The most specific and therefore credible tactic in comparative price advertising involves a comparison with a named rival's price. From the consumer's perspective, this tactic is most credible when it specifies a verification of the rival's price. Pechmann (1996) argues that when a marketer makes a single or small number of price comparisons, a halo effect leads consumers to believe that all that marketer's prices are lower. By supporting specific comparative advertising, the FTC appears to have decided that the value of the specific information in brand name comparisons generally exceeds the costs of consumer deception from any halo effect (16 C.F.R. § 14.15). When making comparisons with competitor prices, all guidelines and state regulations mandate that the marketer must substantiate the competitor's prices before running the ad. In addition, the cited competitor's prices may not exceed those of representative retailers in the area (Komensky and Wegener 1991). Advertisers also must are

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condemned if they fail to change their price comparisons after a targeted rival changes its prices (Lenscrafters, Inc. v. Vision World, 1996) and they may not or use outdated price surveys to support their comparative price claims (Menard, Inc., 2003; Tops Markets, LLC, 2004; Winn-Dixie Stores, Inc., 1996). Similarly, an advertiser is liable if it compared its limited time promotional price with a rival's regular price or includes the rival's distribution fee but not its own (U-Haul Int'l, Inc. v. Jartran, Inc., 1984). Comparative price advertising also raises competitive concerns because a firm with market power might price items artificially low to drive out rivals and then raise prices to recoup its losses. The Supreme Court favors price competition by requiring that the probability of recoupment must be realistic, (i.e., no further market entry or re-entry by lower priced sellers and proof that prices are below some appropriate, but unspecified, measure of cost) (Brooke Group v. Brown & Williamson Tobacco Corp., 1993). Similarly, the Supreme Court of Arkansas overturned a finding against Wal-Mart regarding its pricing of some pharmacy items below its acquisition cost and comparing those prices to the prices of local pharmacies in advertising. The court found that Wal-Mart's intent was not to destroy competition, as required by the Arkansas statute, but rather to offer attractive loss leaders to encourage consumers to shop at Wal-Mart. The complaining pharmacies all remained profitable, and pharmacy sales and the number of pharmacies both increased during the period of price comparisons (Wal-Mart v. American Drugs, et al., 1995). Rather than actually conducting an expensive price war, sellers also might compare their low prices to the prices of particular rivals to signal the possibility of a price war against those rivals if they discount (Heil and Langvardt, 1994). 2.3.3. Comparison with seller's own, former, or future prices A comparison to a former or future higher price is essentially an announcement of a current sale, so both the BBB and FTC (16 CFR § 233.1) require that the former price must be bona fide and in effect for a reasonably substantial time period in the regular course of business. A Lanham Act court decision also agrees with the general policy of bona fide former prices in effect for a substantial period of time (B. Sanfield, Inc. v. Finlay Fine Jewelry Corp., 1999). The FTC Free Guides (16 CFR § 251.1(b 2)) further note that when the price fluctuates, the regular price is the lowest price at which the seller made any substantial sales during the previous 30 days. The BBB Code and the state of Connecticut further request disclosure of any interim markdowns from the advertised original price (Better Business Bureau, 2003; Regs. Conn. State Agencies § 42-110b-10a (2005)). Kaufman Department Stores settled a complaint with the New York Attorney General for posting deceptive regular prices, because it sold no products at those prices (New York State Attorney General, 2005). Similarly, K.B. Toys recently settled a lawsuit alleging inflated former prices for $40 million (Dade, 2003). The NAD also reviews such cases (J.C. Penney Co., 1999; Zale Corp., 2000). When Kmart argued that it kept regular prices for jewelry in effect for the substantial period of 183 days, the NAD applied a tough standard and required that Kmart show substantial sales at those regular prices (Kmart Corp., 2001). State laws heavily regulate comparisons with former prices in a similar fashion. Vermont requires both that the former price remains in effect for a substantial period of time and that the seller achieves substantial sales at that price or a good faith opens effort to make sales at the former price (Vt. Att'y Gen. Cons. Fraud Rule CF 110.02(a) (2005)). Illinois and Louisiana are more generous requiring either a substantial number of sales at the comparison price or that the price be offered for a substantial period of time (14 Ill. Adm. Code 470.220 (2005); LAC 16.111.305 (2003)). Oregon's rule is similar except that it specifies the good faith offer period as the preceding 30 days or any other identified period (Or. Admin. R. 137-020-0010 (2005)). Other states impose specific time periods as well (30–90 days) or require a minimum percentage of sales in the past year at the regular price (Komensky and Wegener, 1991). Still other states set up regulations

too complex to summarize here (N.J.A.C. 13:45A-9.6 (2005); Regs. Conn. State Agencies § 42-110b-12a (2005); 940 CMR 605(3) (Ma. 2005); 15 CSR 60-7.060 (Mo. 2005); D.C. Code § 28-3904 (2005); Md. Commercial Law Code Ann. § 13-301 (2004)). Comparisons with future prices are more difficult to regulate because no one can verify future prices at the time of the sale. The FTC Guides request that an advertiser expects in good faith to increase the price in the future (16 C.F.R. § 233.5). The Better Business Bureau Code (2003) recommends that if advertisers announce a future price increase, they also should sustain that increase for a reasonable time (Better Business Bureau, 2003). Some states agree and others specify a particular period of time, (e.g., within 90 days of the advertisement in Connecticut and Oregon) (Regs. Conn. State Agencies § 42-110b-10a (2005); Or. Admin. R. 137-020-0010 (2005); Komensky and Wegener, 1991). The District of Columbia takes a less specific approach; the law simply prohibits misleading statements of fact about price in comparison to future prices (D.C. Code § 28-2904 (2005)). 2.3.4. Percentage-off claims Many people try to avoid the effort of calculating percentages (Morwitz et al., 1998) by using a different processing strategy (Johnson et al., 1988). For example, when they see surcharges as percentages, consumers often use an ignoring strategy and recall lower total costs than if they saw dollar amounts (Morwitz et al., 1998). Consumers react more positively to more definitive claims (e.g., 50% off versus up to 50% off) (Mobley et al., 1988). Although New Jersey requires that claims specify the amount of savings for goods over $100 in dollars as well as the percentage off, minimal regulation applies to such claims beyond general state prohibitions of misleading statements. Colorado and New Mexico prohibit any false or misleading statements about the prices of goods or services (C.R.S. 6-1-105 (2004); N.M. Stat. Ann. § 57-12-2 (2005)), and many states prohibit false or misleading statements of fact regarding the amounts of price reductions. A large percentage-off savings claim might only apply to inexpensive items producing a small absolute amount of savings thereby misleading consumers. 2.3.5. Up to claims Tensile pricing (Mobley et al., 1988) refer to price ads that include a range of prices or savings, such as save up to $5 or as low as $5 per item. Such claims often appear in combination with percentage-off claims (e.g., save up to 50% off); though the limit provides some specificity, ambiguity remains about which prices on what products actually match the limit. Consumers generally react more positively to more definitive pricing claims, such as 50% off the regular price, than to vague up to savings claims (Mobley et al., 1988). However, one study suggests that before a particular threshold, consumers value tensile price claims more highly than precise claims for the same price or discount. Low-price stores tend to benefit more from these price claims. Consumers tend to assume a uniform distribution of sale items across the range of prices or discounts. Therefore, retailers benefit when they offer more sale items at the lower end of the range (Dhar et al., 1999). Among department store advertisements, tensile pricing claims appear more frequently for discounts on relatively small subsets of merchandise, which make consumers optimistic about receiving a substantial discount closer to the upper limit (Dhar et al., 1999). Advertising law requires that an appreciable number of consumers must be able to obtain the maximum savings in normally expected circumstances (Plaskolite, Inc., 1983). According to the Better Business Bureau Code (2003) the number of items available at the maximum savings must constitute at least a significant percentage of the offering — typically 10%. The Code further requests that advertisers include both a minimum and maximum amount off without an undue emphasis on the latter (Better Business Bureau, 2003). Several states enforce similar requirements (Komensky and

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Wegener, 1991). For example, Alaska and Ohio prohibit the use of these claims unless the advertised reduction provides a reasonable representation of the items in the group (9 Alaska Admin. Code 05.050 (2005); OAC Ann. 109:4-3-12(E)(2) (Anderson 2005)). New Jersey requires disclosure of the lowest discount, and Connecticut and Massachusetts require that the advertisement disclose the minimum percentage reduction as conspicuously as it does the maximum and that the maximum savings apply to at least 10% of all of the goods (Regs. Conn. State Agencies § 42-110b-12a (2005); 940 CMR 605(11) (2005); N.J.A.C. 13:45A-9.4 and 13:45A-9.5 (2005)). 2.4. Buy now Marketers encourage consumers to stop their price search and buy immediately by emphasizing that a particular offer may not be available in the near future, the sale may last only for a limited time, or the quantity of the specially priced items may be limited. 2.4.1. Sale signs Sale signs increase demand by suggesting that a low price is temporary. The effectiveness of this easily executed price promotion is surprising (Anderson and Simester, 1998). For some consumers, a promotion signal alone, without regard to the depth of the price cut, may stimulate a change in choice behavior (Inman et al., 1990). A sale sign reduces perceptions of the likelihood that the item will be available at a lower price in the future, but this effect diminishes when many items have sale signs. Therefore, category sales reach a maximum when only some items have sale signs (Anderson and Simester, 2001). The primary consumer policy question is whether the sale is genuine. The Better Business Bureau Code (2003) advises that price reductions should be significant compared with the advertiser's customary and reasonable price (e.g., not advertising a product at $9.99 when the usual price is $10) and should comply with any stated expiration period. If the sale exceeds 30 days, the seller must substantiate that the prices are special reductions, not regular prices. The FTC (16 C.F.R. § 233.5) simply requests bargain offers that are genuine and truthful. Older FTC cases challenged advertising of the same sale prices more or less continuously (Joseph Mill Trading, 1966; Royal Construction Co., 1967; Simmonds Upholstery Co., 1953). The New York Attorney General recently settled with Jos. A. Bank Clothiers after accusing the retailer of offering some suits on sale almost continuously for an 18-month period (New York State Attorney General, 2004). Ohio requires that sales terminate within the stated or implied period of time, unless the advertiser extends the sales period in good faith and clearly discloses that extension (OAC Ann. 109:4-3-12(D) (1). Massachusetts limits sale advertising to 21 days, except for comparative price claims and clearance sales that continue until inventory is depleted (940 CMR 604(4) (2005)). Most state regulations focus on the significance of the alleged price reduction. Illinois and Missouri recognize the rebuttable presumption that a price reduction of 5% or more is sufficient to constitute a sale (14 Ill. Adm. Code 470.290 (2005); 15 CSR 60-7.050 (Mo. 2005)); Vermont requires a minimum 10% reduction in price (Vt. Att'y Gen. Cons. Fraud Rule CF 110.02(b) (2005)) or disclosure of the former price or reduction (940 CMR 605(5) (2005)). New Jersey's statute requires a sufficiently large price reduction so that the consumer believes he or she receives a genuine bargain (N.J.A.C. 13:45A-9.3 (2005)). Any reason for a sale (e.g., clearance, liquidation, going-out-ofbusiness) should be accurate (Better Business Bureau, 2003). Michigan regulations go so far as to distinguish clearance and closeout sales (Mich. Admin. Code R. 14.201). Iowa and South Dakota limit goingout-of-business sales to 120 days (Iowa Code § 714.16 (2004); S.D. Codified Laws Ann. § 37-24-6(3) (2005)), whereas Alaska and Connecticut simply prohibit such sales unless the price reduction is

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permanent (9 Alaska Admin. Code 05.020 (2005); Regs. Conn. State Agencies § 42-110b-12a (2005)). Some areas require a license to conduct a going-out-of-business sale (People v. Federated Dep't Stores, Inc., 1970), and a lawsuit in New Jersey enjoined a sale past 90 days and threatened to order the company to go out of business if it did not comply (Lower Main Street Merchants Ass'n v. Paul Geller & Co. 1961). A New Jersey court ordered a company that advertised a goingout-of-business sale to cease doing business at that location (Giant Carpet Stores of American Inc v. Retail Kane Carpet, Inc., 1991). 2.4.2. Quantity limitations Retailers often advertise a limit on the quantities available at the sale price (e.g., three items per consumer while supplies last). According to unavailability theory, promoting a product with restricted quantities increases the purchase likelihood depending on the consumer's need for cognition. Low need for cognition consumers use the restriction as a heuristic for a reduced price and increase their purchase rate. In contrast, high need for cognition consumers is more thoughtful and less likely to automatically react to quantity limitations (Inman et al., 1997). As with other promotional pricing tactics, the primary consumer policy concern is whether the use of the tactic is genuine. If an advertisement promises or suggests a limit on the quantity a consumer can purchase at a particular low price and the marketer actually has a large stock, the communication deceives consumers into perceiving urgency to obtain one of the few available items at the bargain price, comparable to a false going-out-of-business sale. Most regulations in this area address the opposite problem. Namely, advertising a sale without sufficient quantities to meet reasonably anticipated demand is a possible prelude to bait-and-switch tactics. Bait-and-switch advertising features an item that the seller does not intend to sell. When a consumer enters the store seeking the item, the seller encourages the consumer to purchase a more expensive item by emphasizing its higher quality. 3. Policy recommendations After he was Director of the FTC's Bureau of Consumer Protection, Robert Pitofsky wrote a seminal article on the regulation of advertising in which he argued that consumers would evaluate an offering by examining the selling price alone. Price was a search attribute that could be fully evaluated before purchase. Therefore consumers would ignore what this paper calls BAs. He concluded that the FTC should curtail the number of deceptive pricing cases it brought (Pitofsky 1977). The FTC adopted his recommendation in the 1980s (Petty 1992). However, Pitofsky's analysis assumes that consumers have perfect or at least reasonable knowledge of all market prices — price search is essentially costless. This paper examines numerous marketing studies that contradict Pitofsky to show that BAs do influence consumers to cut short their price search and buy the advertised bargain. The marketing literature also shows numerous instances where consumers do not fully understand the advertiser's meaning of a particular BA so they believe facts that are not true. This deception of consumers can impede price competition if the deception is substantial by a single or unified group of sellers. For these reasons, continuing study and regulation of BAs are necessary. However, as this paper demonstrates, current regulation is either vague (FTC or BBB Guides) or incredibly detailed providing very specific rules for a few specific practices. For marketers that operate in multiple states, compliance with various specific state rules is problematic. In addition, unethical marketers can adjust their BA tactics on a state-by-state basis to avoid specific regulations, but still deceive consumers. A comprehensive approach to regulating BAs is necessary. This approach would allow consumer protection authorities in a locale to scrutinize the most common practices in their area and

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consider which specific market, product, consumer, and purchase situations are mostly like to cause consumer injury without worrying about whether or not the enactment of a specific regulation addresses the most problematic practices. Both marketers and regulators would benefit from further study of BAs, particularly studies that compare the relative effectiveness of different types of BAs in one industry or of one BA across several industries. With the possible exception of different types of comparative price advertising, the marketing literature does not yet include such broader based studies. BA tactics may mislead consumers along five dimensions: availability, coverage, urgency, substantiality, and understandability of the advertised BA. Marketers and regulators should analyze every BA along these dimensions to uncover potential problems. Ethical marketers can then avoid those problems and regulatory entanglements while regulators pursue marketers who appear to intend to confuse or mislead consumers. Consider a simple rule for addressing these five dimensions. Marketers should be as specific as possible to minimize any possible consumer deception. Marketers who choose to assert bargain assurances that are vague along one or more of these dimensions must be able to show that their conduct meets reasonable consumer expectations. First, is the BA actually available to consumers without undue effort or cost? The Better Business Bureau (2003) states that rain checks cannot replace the advertiser's duty to maintain a sufficient quantity of specially priced items for reasonably anticipated demand. Rain checks should only be needed when demand exceeds the reasonable and documented expectations of the marketer. Marketers also have an obligation to offer BAs without unreasonable restrictions. Rain checks as well as price guarantees, reward programs, and rebates become suspicious if the consumer's proof or documentation burden becomes unrealistically difficult or restrictive. Marketers should be able to demonstrate that their proof or documentation requirements are the minimum needed to substantiate that the consumer genuinely qualifies for the BA. Second, what is the extent of coverage of the BA tactic? Advertisements should be as specific as reasonably possible in defining the included goods. A marketer that advertises everything is on sale should make sure that every product price is a significant discount (at least 10%) from the regular selling price. Does the BA tactic cover all products in a store or just a select few? If marketers decide to be vague about the coverage, then they should bear the burden of showing that their actual coverage is consistent with consumer expectations. Marketers can avoid deceiving consumers if they clearly disclose their BA coverage (e.g., one hundred items are priced for maximum savings advertised up to 30% off). Third, is the BA genuinely urgent? Various authorities suggest that special sale prices and/or limited quantities at a specified price should occur only for a limited time consistent with consumer interpretation of such BAs. Again, marketers can specify the time period or quantity limitations for the special prices or run the risk that their conduct is not consistent with reasonable consumer expectations and may mislead consumers into a false sense of urgency. Fourth, is the BA as substantial as consumers interpret it to be? Some price reductions are too small to constitute a sale. This varies depending on the product and other circumstances. A 10% reduction in the price of expensive jewelry or a car would be large discount compared to 10% off the price of a candy bar. Marketers who are uncertain about what sort of price reduction is considered substantial to reasonable consumers should choose to be specific about the price reduction they offer. Similarly, price guarantees suggest that the offering firm has a policy to make sure its prices are lower, yet some studies suggest that firms that offer such guarantees charge higher, not lower, prices (Anderson and Simester 2003). Marketers who wish to offer a price guarantee, but not perform periodically check rival prices should disclose their full policy to consumers. Otherwise, they should periodically check rival prices to ensure their prices are

generally lower. Fifth, some BA tactics are simply incomprehensible to or not easily useable by consumers. For example, comparable value defined in vague generalities provides little guidance to consumers. Policymakers should prohibit inherently incomprehensible comparisons. Furthermore, some consumers may be unable to calculate or even estimate the savings from a percentage-off claim or disregard additional fees when they face partitioned pricing. Marketers should disclose typical examples of actual lower prices and for partitioned pricing make sure that the total price be the most prominent part of any partitioned price. The use of these five dimensions of analysis does not completely avoid the ambiguity of determining what is reasonable for a particular product or industry. Marketers can conduct a survey of their customers to make this determination and then phrase their BAs consistently with consumer expectations. Alternatively, marketers can be specific about the details of their BAs to avoid consumers relying upon their own expectations — guesses about the specifics of the advertised BA. Most marketing literature pertaining to individual BA tactics ignores competitive consequences, yet because BAs serve as partial substitutes for price competition, they might interfere with price competition. If most firms in an industry use BAs to mislead consumers about prices, they avoid or dull the effects of price competition. If a large firm uses BAs to target particular rivals, it might be conducting a predatory pricing campaign or signal that it would conduct one if the rival doesn't change its current pricing or BA tactics. Any sort of limited time or limited quantity sale might cause consumers to stock up on products, preempting rival offerings in the short run. Because of this potential to interfere with price competition, regulators should consider not only the specifics of BA tactics employed and their likelihood to mislead consumers, but they also should consider industry circumstances. Indeed, Pitofsky (1977) noted that most FTC actions against misleading BAs seemed to target firms that actually did offer lower prices to the benefit of consumers. Historically, the FTC looked too closely at the practice and not enough at the industry context. The goal of BA regulation should be to benefit consumers through both informed decision-making and the encouragement of price competition. Lastly, the ability of BAs to mislead consumers in some cases and to interfere with price competition in others suggests the importance of a regulatory policy that encourages comparative price shopping, whether by consumers, price checkers from rival firms, or independent sources such as shopping bots on the Web. Consumer policy should condemn efforts by marketers, particularly those using BAs, to avoid disclosing their prices or attempts to make it more difficult for consumers and others to obtain price information.

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Journal of Business Research 64 (2011) 74–80

Contents lists available at ScienceDirect

Journal of Business Research

From hierarchy to hybrid: The evolving nature of inter-firm governance in China's automobile groups Yue Wang a,⁎, Akira Tanaka b,1 a b

School of Strategy and Entrepreneurship, Australian School of Business, University of New South Wales, Sydney, 2052, Australia Faculty of Economics, Nagoya City University, 1 Yamanohata, Mizuho-cho, Mizuho-ku, Nagoya, 467-8501, Japan

a r t i c l e

i n f o

Article history: Received 1 August 2009 Received in revised form 1 December 2009 Accepted 1 December 2009 Keyword: Automobile groups China Hierarchy Hybrid Inter-firm governance

a b s t r a c t Despite the rapid growth of automobile industry in China, much remains to be known about the governance structure especially the inter-firm relationship within the Chinese automobile groups. Against China's changing institutional environment and compared to the established knowledge on automobile group governance in Japan, this study provides a case analysis of the evolving nature of inter-firm relationship in one of China's major automobile groups, Tianjin Automotive Group (TAG). A top-down hierarchical administration characterizes the inter-firm relationship in TAG before 1999 due to the heavy influence of the old institutional arrangement. Over time, especially entering 2000, weakening institutional ties between the state and TAG forced the group to be more responsive to market changes and to systematically learn Japanese-style supplier management from a joint venture with Toyota Group. The paper provides rare insights into the evolution of governance structure among the emerging Chinese automobile groups and extends the institution-based view of strategy into the studies of inter-firm relationship in automobile industry. © 2009 Elsevier Inc. All rights reserved.

1. Introduction Despite the rapid growth of the automobile industry in China, little is known about the governance structure of the emerging Chinese automobile groups especially the governance of inter-firm relationship within these groups. In addition, how the current theories that build heavily on the comparative studies of Western and Japanese automobile groups can help us understand the inter-firm governance of the new players in the world's automobile industry remain unclear. Answering the increasing call for more context-specific theory-based research (as opposed to theory-driven context-free research) to make business and management research more relevant to the wider community (Meyer, 2007; Peng, 2005; White, 2002), this study uses the classical single case study method to contextualize the general knowledge of the existing theoretical perspectives in the new setting of the automobile groups in China. The study asks a basic research question. How do the emerging Chinese automakers manage the buyer–supplier relationship within the group in a dynamic business environment? Through an intensive case study of one of China's major automobile groups, Tianjin Automotive Group (TAG), the paper identifies three major factors that shaped the governance of inter-firm relationship, including institutional arrangements between the Chinese state and TAG, the market conditions in the automobile industry, and learning ⁎ Corresponding author. Tel.: +61 2 9385 4934. E-mail addresses: [email protected] (Y. Wang), [email protected] (A. Tanaka). 1 Tel.: +81 52 872 5731. 0148-2963/$ – see front matter © 2009 Elsevier Inc. All rights reserved. doi:10.1016/j.jbusres.2009.12.005

from joint ventures with Toyota Group. The authors demonstrate that the three existing theoretical perspectives are conceptually complementary in explaining the evolving nature of inter-firm governance in TAG. While macro-level governance perspective (and to the less extent learning perspective) offers an explanation for the causes of the evolving inter-firm governance in TAG, micro-level governance perspective captures the effects. The paper provides managerially relevant insights into the evolving nature of inter-firm governance in the rapidly developing Chinese automobile industry. The paper begins with a review of existing theoretical perspectives on inter-firm governance in automobile industry in Section 2. Section 3 explains the research method. Section 4 reports findings from the case study of Tianjin Automobile Group (TAG), with a comparison to the practices typically adopted by Japanese auto groups. Section 5 discusses three inter-related factors that shaped the changing structure of interfirm governance within TAG and establishes the causes and the effects of such changes and their theoretical explanations. Section 6 concludes with theoretical and empirical implications. 2. Theoretical background The extant literature on inter-firm governance in the context of automobile industry draws upon three theoretical perspectives: micro-level governance perspective, macro-level governance perspective and learning perspective. The micro-level governance perspective follows Williamson-type transaction costs-comparative contracting approach (Williamson, 1975, 1979) to classify inter-firm governance into the hierarchical, relational and market-based arm's-length modes

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according to the nature of transactions between assemblers and suppliers. Researchers have used this approach to compare the buyer– supplier relationships in Japan with that in the US (Helper, 1990; Helper and Sako, 1995; McMillan, 1990) and the UK (Sako, 1992; Thoburn and Takashima, 1992), where the buyer–supplier relationships in the US and the UK are often characterized as recurrent but market-based, and the relationship between assemblers and suppliers in Japan is described as relational or obligational (Dyer, 1996a; Sako, 1992). But this body of literature remains descriptive and fails to explain why international differences exist for governing basically similar types of transactions in automobile industry. The explanation of such a contrast often lies in the broader discussion on the differences between these countries' macro-level institutions (both formal and informal) rather than transactions themselves. Built upon both economic branch (North Douglass, 1990, 1991) and sociology branch (DiMaggio and Powell, 1991; Scott, 2001) of institutional theory, the macro-level governance perspective highlights a country's macro-level institutions in shaping the formation and evolution of the inter-firm relationships in automobile groups and argues that international differences in the transactional modes are attributed to different institutional settings in respective countries (Hemmert, 1999). For example, the US corporate governance institutions and the US business culture induce the US automakers to adopt an arm's-length approach toward managing their supplier relationships — the weak bank–firm ties, the reliance on capital markets for finance that push the US firms to pursue short-term profitability, and the low incidence of cross-shareholding, all contributed to the arm's-length approach toward managing inter-firm relationships. By contrast, the strong bank–firm ties and the lower reliance on capital markets for finance, plus the high incidence of cross-shareholding allow Japanese automakers to develop a longterm, stable relationship with their affiliated suppliers based on reciprocity and trust (Gerlach, 1992). In addition, the relationships between group affiliated companies in Japanese automobile industry are often historically embedded and socially complex (Gerlach, 1997). For a long time these informal but institutionalized relationships between assemblers and suppliers have served as an effective substitute for both hierarchical and arm's-length organization for buyer–supplier interface in Japan (Ahmadjian and Lincoln, 2001; Dore, 1987). Thus, the formal and informal institutions in Japan collectively shaped the legally independent, yet organizationally closely affiliated, nature of inter-firm governance in the post-war Japanese auto industry. Interestingly, therefore, the extant literature often relies on the macro-level institutional theory of industrial organization to explain the microlevel differences in inter-firm relationships across different countries' automobile groups (Hemmert, 1999). Finally, although the macro-level governance perspective explains the cause of the differences in governance structures between Japanese and Western automakers, such a perspective appears unable to provide insights into the temporary changes in such governance features within one country. For example, recent studies show that the changes in the Japanese institutional environment did not lead to significant changes in the Keiretsu-type of inter-firm system (McGuire and Dow, 2003). Instead, a learning perspective was used to explain a movement toward establishing Japanese-style long-term purchasing arrangements in the US (Dyer, 1996b) and in the UK (Oliver and Wilkinson, 1988). Similarly, Ahmadjian and Lincoln (2001) show the learning perspective suits better than both governance perspectives to account for the recent shift from hybrid governance modes toward the extremes of market-based contracting and top-down hierarchical administration in Japanese automakers such as Toyota. The remainder of the paper provides a detailed case study that examines the relative power of the existing theoretical perspectives in explaining the inter-firm relationship in China's emerging automobile industry. The paper also assesses the extent to which the new Chinese context provides opportunities to refine or extend the current theories.

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3. Case study method To deliver the paper's promise to contextualize the general knowledge of the existing theories in a new empirical setting, this study adopts the classic single case study method aiming to provide richness in descriptions of context (Meyer, 2006). Like any qualitative research, the case method is subject to the critiques on their reliability/ replicability and external validity. But these stringent criteria of nomothetical social science can be only met when researchers find an invariant law and the possibility of establishing invariant laws for social phenomena is questionable (Numagami, 1998). By contrast, rich qualitative descriptions through a single case study do a greater job than statistical demonstrations of ideas and claims in uncovering underlying dynamics of the phenomenon (Van Maanen, 1979). The in-depth study of a single case also serves the purpose of gaining managerially relevant insights better than alternative qualitative methods such as multiple cases study (Eisenhardt, 1989) or comparative case study approach (Yin, 1989). Resembling the logic of large-sample quantitative methods, the multiple or comparative case study approach takes a more objective and positive theory building stance (Eisenhardt and Graebner, 2007) and focuses on the constructs development at the expense of the context — because the more case contexts the researcher investigates the less contextual insight he or she can communicate (Dubois and Gaddle, 2002; Dyer and Wilkins, 1991). Such a method inevitably deviates from the classic case study and misses the context. For classical single case research, the truth always lies in the context and the perspective. Instead of searching for an invariant law through larger sample quantitative or multiple cases study, we return to the classics to allow the reflective dialogue among practitioners and researchers, which should be the focus of management studies (Tsoukas, 1989) and which will improve the relevance of our research by generating insight practitioners find useful for understanding their own organizations and situations (Vermeulen, 2007). Adopting an “abductive” approach to case research, the present study aims at refining existing theories rather than building new ones and emphasizes the continuous interplay between theory and empirical observation (Dubois and Gaddle, 2002). The goals are not only to provide a rich description of the phenomenon and to describe the context in which events occur (Light, 1979) but also to gain theoretical insights into the deeper social dynamics and reveal how extant theory operates in particular examples (Gephart, 2004). The case study involved 67 onsite interviews with executives, managers, engineers and administrators etc. (see Appendix for the complete list of interviewees) in Tianjin Automobile Group (TAG) and its affiliated companies from different hierarchical levels and functional areas over the period of 1996 and 2004. The authors also consulted documents provided by both TAG's Group Corporation (the group's holding company) and Toyota headquarters (Toyota was TAG's JV partner for many years) to gauge the differences in the two automobile groups' engagement with their suppliers. The interview protocol includes open-ended questions in three areas: (1) main practices TAG used to manage its buyer–supplier relationship, and the reasons for the adoption of such practices, (2) main changes in these practices since the establishment of the group in 1996 to the merger of TAG into First Automotive Works (FAW) in 2002, and the reasons for the changes, and (3) main differences between TAG's practices and those typically adopted in Japan (especially in Toyota Group). Using the opencoding techniques (Coffey and Atkinson, 1996; Jones, 1985), an analysis of the recordings and transcripts resulted in the emergence of four mutually exclusive categories of data on TAG's supply management practices, including contracting, payment settlement, pricing and intra-group dealing. To state anything practically meaningful about ‘Chinese’ interfirm governance, the study compared TAG's methods of parts supply management in these four areas with well-established knowledge of how they are practiced in Japan (particularly Toyota).

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4. Results A good case study should not only report important facts to advance managerially relevant knowledge (Hambrick, 2007) but also should be a good storytelling with theoretical import (Dyer and Wilkins, 1991). The documentation of the case story should be intertwined with the theory to demonstrate the connection between empirical evidence and theory (Eisenhardt and Graebner, 2007). This section reports and interprets the case study through the theoretical perspectives reviewed in Section 2. Formally incorporated in 1996, the history of Tianjin Automotive Group (TAG) can be traced back to Tianjin Automobile Industry Company (TAIC) established by Tianjin municipal government in 1956. Table 1 below provides a brief history of TAG and its predecessors. In 2002, TAG and China's largest automobile group First Automotive Works (FAW) merged after a government-initiated industry restructuring. Our observation of the formation and evolution of TAG's inter-firm relationship started with 1996 when TAG was formally established and ended with 2002 when TAG was merged with FAW. But as elaborated later in the discussion section, the pre-1996 history matters in explaining the evolving nature of TAG's governance structure. 4.1. The formation of TAG: 1996–1999 An intensive analysis of the four major aspects of inter-firm relationships in contracting, payment settlement, pricing and intragroup dealing revealed that unlike the automobile groups in Japan hierarchical coordination characterized the inter-firm relationship in TAG at the formation stage. In Toyota, the contracting practice that rules parts-related business incorporates a “basic contract” and “monthly schedules.” The basic contract sets out general obligations that both parties must follow and is normally reviewed every year. The monthly schedules are individual contracts that determine the variety, design and delivery dates for the parts which are traded (Asanuma, 1989). This kind of contracting is peculiar to continuous purchasing/supplying relationships with the “monthly schedule” acting as a built-in mechanism to allow for adjustment in unforeseen circumstances and leave less room for dispute on each purchasing transaction (Smitka, 1991). This contracting practice is consistent with the broad relational contracting approach described in the literature about the Japanese inter-firm system (Williamson, 1985). In TAG there was no equivalent form to the “basic contract” of Toyota. The General Corporation (GC) and each parts subsidiary reached an individual contract on a yearly basis, which confirmed the amount, cost and design of parts. The yearly contract resembles European and American practices (Sako, 1992), where the general rule is to have a contract which confirms all matters pertinent to the business such as amount, cost and design. But there was notable

difference between the Chinese practice and the Western arm'slength approach. In the West, negotiation and bargaining between the two parties determined these contract terms. But in TAG, GC determined the contract terms in “consultation” with subsidiaries and implemented through hierarchical procedure as if they were “production plans” rather than contracts. Though GC was created as a holding company, in reality it operated as the de facto headquarters. Put simply, the true inter-firm contracting was absent because there was a lack of recognition of both assembling and parts subsidiaries as independent companies. The payment settlement practice is the second feature under investigation. Unlike in Japan, the settlement of TAG's parts payment did not correspond to each purchasing transaction in parts. Instead, TAG Sales Company (which was treated as a sales department) collected and distributed income from finished car sales to the group's affiliated companies. After collecting revenue from directly-managed stores and independent dealers, the Sales Company's accounting centre made payments, according to the costs of sold parts, to the core companies, who in turn would make payments to subordinate suppliers to cover their parts and components costs. Although monthly settlement was also a feature commonly observed in Japan, but in China payment did not necessarily correspond to the quantity of parts supplied. In TAG, a lag between business results and the estimation of demand or the production plan often produced an increase of stocks of finished cars. If the costs of finished cars were not recovered, payment was not made for parts costs. The arrangement resulted in the so-called “triangle debts” which expanded upstream as a chain reaction. This was a serious issue, as suppliers' dependence on group sales was extremely high in China. The reason that the settlement of TAG's parts payment did not correspond to each purchasing transaction was because GC did not treat the group's affiliated suppliers as independent profit centers. Instead GC treated the supplier companies as internal departments or factories (like they were before TAG was formally established in 1996) to bear the costs for the whole group. Both GC and affiliated suppliers still considered any inter-firm purchasing/supplying exchanges as “business within the group.” In Japan, where assemblers often encouraged suppliers to share costs, the assemblers cannot impose the cost-reduction through hierarchical means. Car makers can only use a combination of market incentives and other relational mechanisms such as supplier associations to work with suppliers to reduce costs through continuous innovation of parts and components production and pass the savings on to the assemblers (Nishiguchi, 1994). The arrangement provides a win–win situation for assemblers and parts suppliers, an example of what relational contracting means in Japan. In the case of TAG, such features of relational contracting were completely absent prior to 1999, and the payment settlement practice reflected the administrative nature of relationship between GC and its subsidiaries despite their nominal independent legal status.

Table 1 A brief history of Tianjin Automotive Group (TAG) and its predecessors. Year

Event

1956 Tianjin Automotive Industry Company (TAIC) was established in the city of Tianjin 1964 TAIC commenced complete car production 1982 In an administrative-driven merger, TAIC “absorbed” other car manufacturers and parts factories in Tianjin; Parallel with this developments, in 1982 under the central government's policy to establish “seven consolidated business groups” in automobile industry, TAIC, together with Beijing Automobile and Beijing Second, became an affiliated company of the Jing-Jin-Ji Automobile Consolidated Company 1985 The “seven business groups” policy failed due to local government resistance, and the Jing-Jin-Ji Automobile Consolidated Company was broken up. TAIC was again under the administrative oversight of Tianjin municipal government 1986 TAIC commenced the production of small car model Xiali, which was for a long period of time ranked second by sales in the small car sector. 1995 The lower body (suppliers) of TAIC started JVs with Toyota for parts production 1996 TAIC was granted “independence” from the Tianjin municipal government and renamed the “Tianjin Automotive Industry (Group) Corporation” — Tianjin Automotive Group (TAG) as a shorthand 2000 Tianjin Toyota Motor Company (TTMC) was established for finished car manufacturing 2002 TAG was merged into First Auto Work (FAW) Group Corporation after another industry restructuring. After the merger, however, the TAG still held independent corporate rights and continued to conduct its business as it was accustomed to

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Thirdly, GC held the right to set the parts prices, although suppliers could negotiate for price changes at the end of every year. Sometimes the demand for price cuts by GC during these negotiations was so aggressive that they completely siphon off the fruits of any improved efficiencies by suppliers. In some cases, the prices set for the parts were lower than the production costs. This kind of price-setting practice would not be possible if GC treated the supplier companies as independent firms. As a result, negotiations on parts cost between GC and some suppliers could extend for prolonged periods during which suppliers had already delivered parts and components to the assemblers in the absence of fixed prices. In Japan, renewal negotiations on parts unit prices are usually held every six months. The reduction in the purchase price for parts is less than any reduction in suppliers' production costs gained from rationalization conducted by suppliers. This method encourages suppliers to invest in rationalization. If the price cut for purchasing is too large, suppliers will not have the capacity to invest in further rationalization. Inversely, if it is too small, they will have less incentive to invest in rationalization. Again, on pricing, the case study found TAG's inter-firm relationship was hierarchical, in contrast to the quasi-market, quasi-hierarchy feature of the Japanese practice. Finally, in TAG each affiliated company dealt almost 100% within the group. This exclusiveness was partly due to the fact that most suppliers in TAG were spin-offs from its predecessor TAIC's branch factories and partly attributed to Tianjin Municipal Government policies known as “The priority of dealing within the group” and “The priority of dealing within the city”. Although Tianjin municipal government granted “independence” to TAG since 1996, in reality the local government maintained heavy policy influence over TAG's operation through its extensive organizational and personal ties with GC and core-affiliated companies. While intra-group business dealings were once a core feature of the Japanese system, the exclusiveness of such dealings has weakened dramatically as the competition for buyers significantly intensified since the 1980s. Within automobile industry, for example, the buyer– supplier relationship has shifted from more of a quasi-hierarchy system to more of a quasi-market based (Sako et al., 2004). 4.2. The evolution of TAG: since 2000 The top-down hierarchical structure of TAG caused some problems during the formation stage, including the above-mentioned triangle debts within the group's supply chain. In theory, TAG planned its production “according to market-trend forecasts”. Every year TAG's sales company and its dealers made a joint estimate, based on the dealers' sales records in the previous year and the macro-projections for the following year. GC's production planning section then made a yearly production plan based on the yearly demand estimate. However, two unstable factors persisted. First, the information supplied by dealers tended to be inaccurate. Dealers often inflated the sales figures because most of the dealers were not exclusive and often involved in the sale of both Xiali and its competing model Santana (made by Shanghai Volkswagen). Second, the Tianjin Municipal Government often amended the production plan through “administrative guidance”. As a result, illinformed by inaccurate market intelligence, the production plan often led to an excess stock of finished cars. The excess stock led directly to a lack of cash flow in the sales company, which in turn resulted in an increase in triangle debts among suppliers (due to the payment settlement practice explained above). The inefficiency produced accumulated debts along the supply chain throughout the whole group. This problem was not serious up until 1999 because TAG's main model, Xiali, enjoyed robust sales. But, from 1999 to 2000 events unfolded dramatically. Xiali suffered a notable slump in sales. In the latter half of 1999, Xiali's monthly sales ranking dropped to third in the small car sector, and its market share fell at an increasing rate. The sales slump made the latent weaknesses in the supply chain apparent. Sales

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information showing the true state of the market was not appropriately fed back to the production plan. The slump in the sales of Xiali, which normally accounted for two thirds of TAG's sales volume, contributed directly to a management crisis, forcing the company to improve its efficiency. Without the technology to develop a new product to replace Xiali, GC made a desperate decision to increase its collaboration with Toyota in 2000. The company started a top-down systematic overhaul, introducing Toyota's methods to improve TAG's supply payment management. Joint ventures between the two groups began in the latter half of 1995, even before TAG was formally established. But the collaboration remained among group affiliated parts and components suppliers at the lower levels of both groups. TAG did not seek to learn Japanese practices in managing supplier relationship systematically through these early joint ventures because TAG's main model Xiali had been enjoying a comfortable market position. The systematic diffusion of Japanese-style supply chain management only started with the establishment of a joint venture Tianjin Toyota Motor Company (TTMC) in 2000 in finished car production. The establishment of TTMC meant the creation of another core firm in TAG, parallel to GC, which led to significant changes in the governance of TAG's inter-firm relationships. Although TTMC was a 50:50 joint venture, Toyota Group seized the initiative in the management of TTMC and the car models produced by TTMC were sold under Toyota brand names. With regard to the sales channels for TTMC, Toyota first selected 100 candidate shops that met Toyota's standards for sales dealers and Chinese executives then selected dealers from this pool. TTMC adopted the selection standard that matched Toyota's global practice, and abolished sales customs peculiar to China. As for suppliers, many companies affiliated with Toyota stepped forward. As a result, TAG has taken on a double-head structure, encompassing the Chinese “Tianjin Auto Group” with GC as its core firm, and the “Tianjin Toyota Group”, with TTMC as its core firm. Both groups share suppliers of Japanese descent. The Japanese-style inter-firm system advanced dramatically within TAG as Tianjin Toyota was empowered to administratively coordinate market research, estimation and supply of parts, and production and sales across the value chain. A number of important changes in the governance of TAG's interfirm relationship resulted from the systematic introduction of Japanese-style purchasing practices. First, price negotiation between GC and suppliers became more often, held in every six months rather than once a year, allowing quick response to changes in the market conditions. Second, the suppliers enjoyed a fair say in the negotiation of the price for the parts. Third, the group set up a new subsidiary sales company, Tianjin Xiali Sales Co. Ltd., which was responsible for selling Xiali and preparing the ground for an exclusive dealers' network. In 2000, between 80 and 100 exclusive dealer shops were set up under the direct control of the new sales company. These shops engaged in sales, parts supply and after-sales service. Thus, the sales company had more direct control over the market information gathering. Fourth, supplier dealing outside the group was liberalized and their exclusive reliance on sales within the group was generally lessening. This trend was first triggered by Xiali's sales slump in 1999, but it was widely expected that the trend would continue as long as the market remains competitive as the TAG management started to realize that it would be unrealistic to expect suppliers to be able to survive on business generated within the group. These changes (e.g., the price negotiation practice, the reduction of intra-group sales and the increase in sales to non-group affiliated firms) signal that the relationship between TAG and its affiliated companies was gradually transformed into truly inter-firm relationship between legally independent firms, with lower level suppliers being treated as independent companies first and group members second. A quasi-market governance structure consisting of a core firm and quasi-independent associated companies took the shape and replaced the old hierarchical governance structure for member companies.

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5. Discussion The case study demonstrates that in TAG, the inter-firm system has shifted from hierarchy-based administrative control prior to the late1990s to a quasi-hierarchy, quasi-market type of governance entering 2000. The changing nature of TAG's inter-firm governance structure is best understood through a combination of three inter-related factors: institutional arrangements between the Chinese state and TAG, the market conditions in the automobile industry, and the role of learning from Toyota. In particular, the specific institutional settings in China serve as the most critical explanatory variable for TAG's response to market conditions and its decision to learn from joint venture partner Toyota. TAG was formally established in 1996, but its governance structure took shape under the old planned economy system and the group inherited its initial inter-firm relationship from its immediate past practices. Therefore, the starting line of the inter-firm governance features under investigation is not so clear-cut — they did not really start in 1996, but basically adopted the same practices employed by TAIC before 1996. The formation of large auto groups in China such as TAG was part of the government's broad agenda to reform property rights in large inefficient state-owned enterprises (SOEs). The evolution of the inter-firm governance in TAG also reflects the changing institutional arrangement between the Chinese state and automobile groups. Before the 1988 Law on SOEs, the nature of the relationship between TAG and its controlling body as well as the relationship among different units (e.g., assembling factories, parts and components factories) within TAG was purely administrative. Indeed, TAG and its affiliated companies were themselves administrative bodies (known as work units) under the old planned economy system. After the introduction of the SOE Law, state enterprises such as TAIC were in theory separated from the state and became independent legal entities. But in reality, with the state as the sole or majority owner, these enterprises only acquired quasi-independent legal status with the fulfillment of state production quotas remaining as their main responsibilities. In the case of TAIC, the Tianjin municipal government was the nominal owner representing “the whole people”, but it still exercised significant influence or indirect control over the production and sales of the company. Managers had to contend with the pervasive influence of local government on their business activities (Boisot and Meyer, 2008). When TAG was formed in 1996 to replace TAIC, the embedded hierarchy–administrative ties made it difficult to transform the relationship among group members to a truly inter-firm relationship between legally independent firms. With the deepening SOE reform in the late 1990s, the relationship between the state and TAG as well as between TAG's member companies was increasingly governed by ownership and less by administrative control, which weakened the administrative ties between TAG and the government bodies as well as the administrative ties between group member companies. The weakened administrative ties also meant weakened institutional support in areas such as financing. Coupled with the slump in the sales of its main model Xiali in 1999, the group was desperate to change in order to survive in the increasingly competitive passenger car market. Thus, the increasing institutional distance between the state and TAG and changes in market conditions induced the group's organizational changes towards managing its supplier relationship. Since 2000, systematic learning from Toyota altered the way TAG governs its intra-group transactions. The changes in payment settlement method and the price negotiation practice, the reduction of intra-group sales and the increase in sales to non-group affiliated firms all showed a shift from top-down administrative control toward market-based governance for inter-firm relationship, resembling closer to the quasi-market feature of inter-firm governance commonly observed in Japanese auto groups. But on the other hand, the initial institutional arrangement created a powerful path dependence effect

that allowed GC to continue to affect most of the contract terms for parts supply. As a result, the inter-firm relationship within TAG retained quasi-hierarchy characteristic distinctive from Japanese practices. The discussion helps to establish the theoretical explanations of the causes and the effects of TAG's changing governance structure for its buyer–supplier relationship. Specifically, the authors identify institutional arrangement between the state and TAG and its changes as the causes of the adoption of different governance modes over time within TAG. The changing macro-level institutional environment also explains TAG's initial slack in learning as well as the eventual adoption of the Japanese practices in managing buyer–supplier interface. The existing theoretical perspectives, taken in concert, offer the full explanation of the observed phenomena, with macro-level governance perspective explaining the causes and micro-level governance approach capturing the effects of TAG's evolving governance structures. The learning perspective provides partial explanation of the changes since 2000 but the learning phenomenon itself was a consequence of the combined effect of the institutional change and the market shift since the late 1990s. 6. Conclusion Compared to the established knowledge on inter-firm governance in Western and Japanese automobile industry, little is known about the structure of inter-firm relationship in the emerging Chinese automobile groups. By combining existing theoretical perspectives with a deep knowledge of the Chinese context, the present study provides a rich description and explanation of the formation and evolution of the inter-firm governance in one of the major automobile groups in China. A single case study design enabled authors to look deep into the nature of the inter-firm relationship inside the company and offers a rare and true comprehension of the inner-running of the emerging Chinese automobile groups and the underlying institutional environment that shaped their governance structures. The case study of Tianjin Automobile Group (TAG) examines the operation of four major practices in managing buyer–supplier relationship within the group and explores how the dynamics of institutional change impact on the way TAG organize these practices. A top-down hierarchical administration characterizes the inter-firm governance in TAG before 1999 due to the heavy influence of the old institutional arrangement between the state and TAG. Over time, especially entering 2000, the weakened institutional ties between the state and TAG forced the group to be more responsive to market changes and to systematically learn Japanese-style supplier management from Toyota Group. As a result, inter-firm relationships within the group shifted from hierarchy to hybrid governance. In examining how the different theoretical perspectives explain the causes and the effects of the formation and evolution of TAG's governance structure, the authors found the three extant theoretical perspectives are conceptually complementary in providing relevant empirical insights to the case but macro-level governance perspective is more fundamental than alternative theories in explaining the evolving nature of the inter-firm governance in TAG — specifically, China's changing macro institutional environment largely shaped TAG's evolving strategy towards organizing the buyer–supplier relationships with group affiliated companies. Theoretically, the case study highlights a conceptual dilemma that the extant inter-firm governance literature faces. This literature relies on macro-level institutional theory of industrial organization to explain the micro-level international differences in the governance of inter-firm relationship, especially in automobile industry. Nishiguchi (1994) takes the first step to point out that the ex ante firm strategy toward the management of inter-firm relationships affects the ex post transaction features between buyers and suppliers in the Japanese automobile groups, not vice versa.

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The analysis of the TAG case extends this important yet often neglected observation and establishes a link between macro-level and micro-level governance perspectives in explaining the inter-firm relationship in China's automobile groups. Why did the Chinese automobile groups such as TAG and Japanese automakers like Toyota adopt quite different practices in managing their intra-group buyer– supplier relations? The nature of transactions under discussion is basically very similar, and according to TCE, the similar types of transaction-specific or relationship-specific investments would lead to the similar types of governance (Williamson, 1979, 1985). The Chinese firms and the Japanese firms should use the same kind of governance structure to manage the buyer–supplier interface. The marked difference in the governance structures of automobile groups in China vs. Japan simply does not support the proposition as TCE (or micro-level of governance perspective) predicts. Thus, instead of thinking about the nature of transactions first and then developing an appropriate governance structure to match the transactions and to economize on transactions costs, the present study proposes — based on the case study — that the institutional environment faced by the emerging economy firms shape the firm strategies, which in turn determine the method these firms organize their transactions. The study therefore extends the general institution-based view of strategy (Peng, 2002, 2003) into the studies of automobile groups' inter-firm governance by highlighting the role that institutional arrangements play in shaping the evolving nature of the inter-firm relationship in the emerging automobile groups in China.

Appendix A (contitnued) (continued) Company name

Interviewee position

Tianjin Automotive Industrial (Group) Co. Ltd.

Director, Joint Venture & Cooperation Dept. Chief Representative GM

Toyota Motor Corp./Tianjin Office Toyota Tsusho Corp. Toyota Tsusho (Tianjin) Co., Ltd. Tianjin Toyoda Gosei Automobile Hose Co. Ltd. Tianjin Denso Engine Electrical Products Co. Ltd. Toyota Motor Technical Center (China) Co. Ltd.

Tianjin FAW Toyota Motor Co. Ltd.

Tianjin Denso Air-Conditioner Co. Ltd.

Tianjin Fujitsu Ten Electronics Co. Ltd. Tianjin Tokai Rika Automotive Parts Co. Ltd. Aisin Tianjin Body Parts Co. Ltd. Tianjin Toyoda Gosei Co. Ltd. Tianjin Denso Engine Electrical Products Co. Ltd. Tianjin Aisin Automobile Parts Co. Ltd.

Tianjin Toyota Motor Engine Co. Ltd. Tianjin Kahou Automobile Decoration Co. Ltd.

Acknowledgments The authors thank Peter Murmann, Grahame Dowling, Elizabeth Maitland, Geoff Eagleson (University of New South Wales), and Timothy Devinney (University of Technology Sydney) for the comments and suggestions on the earlier drafts of the paper.

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Tianjin Aisan Automobile Parts Co. Ltd. Aisan (Tianjin) Auto Parts Co., Ltd. Tianjin Fengjin Auto Parts Co. Ltd. Tianjin Toyota Forging Co. Ltd. Tianjin Toyota Steel Process Co. Ltd.

President/GM Deputy GM Special Consultant VP GM Manager, Purchasing Division Assistant GM, General Affairs & Human Resources Division GM VGM VGM Administration Director Deputy GM, Project Promotion Dept. Section Chief Plant Manager Assistant GM Deputy GM Manager Manager Manager Director, Member of the Board/ President Director/President Director/Senior Manager Senior Manager No.2 Dept. Senior Manager Management Dept. Director/President Director/President Manager, Administration Dept. Manager, Manufacturing Dept. Director/GM Assistant to President

Appendix A. The list of interviewees References Company name Shougang Corp./Liaison & Reception Office Tianjin Aisan Automobile Parts Co. Ltd.

Interviewee position

Engineer Director/President Director/VGM/Senior Engineer Director/Manager Tianjin Denso Engine Electrical Products Co. Ltd. Deputy GM Tianjin Fengtian Steel Process Co. Ltd. VP Financial Manager Tianjin Toyota Motor Engine Co. Ltd Trustee/GM Tianjin Jinling Steel Co. Ltd. CEO Sales GM Production Dept. Director Tianjin Rihua Steel Products Co. Ltd. Director VGM VGM Tianjin Huazhu Metal Products Co. Ltd. GM VGM Tianjin Mini-Auto Works Director of Reception Section Tianjin Automotive Industrial (Group) Co. Ltd. Deputy Director Tianjin Denso Engine Electrical Products Co. Ltd. Deputy GM Tianjin Aisan Automobile Parts Co. Ltd. Director/President Director/Manager Tianjin Kahou Automobile Decoration Co. Ltd. Director/VP Tianjin Toyoda Gosei Automobile Hose Co., Ltd. VP Manager Toyota Tsusho Corp./Tianjin Office Tianjin Aisan Automobile Parts Co. Ltd. Director/President Director/Manager Tianjin Toyota Motor Engine Co., Ltd Trustee/GM Tianjin Toyota Steel Process Co. Ltd. VP Financial Manager Tianjin Kahou Automobile Decoration Co. Ltd. Director/VP Director/Manager Toyota Motor Technical Center (China) Co. Ltd. President

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Journal of Business Research 64 (2011) 81–86

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Journal of Business Research

Antecedents of patent value using exchange option models: Evidence from a panel data analysis Ming-Cheng Wu ⁎ Department of Business Education, National Changhua University of Education, No. 1, Jin-De Road, Changhua 500, Taiwan, ROC

a r t i c l e

i n f o

Article history: Received 1 April 2009 Received in revised form 1 September 2009 Accepted 1 December 2009 Keywords: Patent Citation Exchange option Panel data

a b s t r a c t This paper examines the patent impact factor by an empirical study using panel data. To investigate the impact factor of patent value, this study conducts a sensitivity analysis of a patent evaluation model within the framework of a real option, while considering the uncertainties associated with both patent counts and the amount of R&D per patent, and develops an empirical analysis method for examining the impact factor of a patent using an unbalanced two-way fixed effects model. The empirical results indicate that the increase of patent value accords with the increase in the patent counts, volatility and patent lifetime. Although patent value declines with the amount of R&D per patent, the impact is not significant. However, reducing cost, raising patent counts and enhancing innovation efficiency offer a feasible method for a firm to increase patent value. © 2009 Elsevier Inc. All rights reserved.

1. Introduction Patents are important in many fields of business, especially in hitech industries. Nevertheless, many patent evaluation methods fail to analyze the related investments properly and accurately. Taking net present value (NPV) and discount cash flow (DCF) for examples, such traditional project evaluation methods tend to lose sight of the high uncertainty embedded in most IT projects (Stark, 2000). This study aims to develop the theoretical model and build the empirical analysis methods for valuing patents by virtue of the real options approach. This investigation not only performs a sensitivity analysis of the patent evaluation model when considering the uncertainties regarding the patent counts and the amount of R&D per patent, but also conducts an empirical analysis in order to examine these relationships through panel data. Option pricing theory (OPT) works well within applications of capital budgeting. This method is the real option approach. Numerous academics and practicing managers are now aware that traditional financial analysis tools are inadequate for capital budgeting. The NPV and DCF methods can merely capture the value of current operations, while remaining incapable of evaluating future growth opportunities. Consequently, traditional discount methods could underestimate projects. In fact, firms' market value depends mainly on two factors: the value of current operations and the value of future growth opportunities. Growth or strategic options are regarded as opportunities available in the future by executing a project, but are not part of that project at the outset. ⁎ Tel.: +886 4 723 2105x7321; fax: +886 4 721 1290. E-mail address: [email protected]. 0148-2963/$ – see front matter © 2009 Elsevier Inc. All rights reserved. doi:10.1016/j.jbusres.2009.12.006

For example, launching a patent may have a negative NPV during the process, but the project may generate huge profits when it succeeds and proceeds to production and marketing. Many studies note that announcements of increases in capital spending could contribute to positive price reactions for firms through valuable investment opportunities. The capital budgeting theory postulates that a firm, for the sake of sustaining value or attaining growth, must continually allot capital expenditures to existent business or create fresh business (Nwaeze, 2005). A valuation method, for the purpose of capturing the managerial flexibilities and growth opportunities embedded in strategic investments, lies in the kernel of the real options approach. The real options approach not only captures the value of managerial flexibility to determine investment planning, but also revises future decisions as long as preferable information emerges. Evaluating patent value is more difficult than other traditional investment projects. R&D investments, for instance, are asymmetrically positioned to maximize upside opportunities as well as minimize downside losses, implying that increased uncertainty is beneficial in relation to option value. Consequently, opportunities in highly uncertain or volatile markets are more valuable since exceptional upside potential could be obtained; on the other hand, downside losses remain limited in that managers can annul investment projects. Considering future investment opportunities by use of real options offers insight into corporate resource allocation, then making great progress towards such allocations. With regard to capital budgeting, real options tools seem to be function competently (Shackleton and Wojakowski, 2002). Howell and Jagle (1997) construct a questionnaire to examine a manager's viewpoint concerning the real growth options and reveal the effect

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factors involved with option model parameters. They implement the option model developed by Black and Scholes (1973) to assess investment projects. Moreover, Perlitz et al. (1999) employ a compound option pricing model to evaluate a pharmaceutical company's R&D project. Furthermore, Kellogg and Charnes (2000) bring forward decision tree and binomial lattice methods and apply them to value a biotechnology company. Kellogg and Charnes further compare their calculated values with actual market values at selected time points during the development of Viracept, an Agouron drug used to treat HIV-positive patients. A general real growth option model advanced by Wu and Yen (2007) for evaluating R&D investments, which takes the R&D uncertainty pertinent to project value, investment cost, and jump diffusion processes into consideration. Based on the literature mentioned above, it seems reasonable to conclude that the real options approach could be suitable for valuating biotechnology firms. Furthermore, the toolbox of security analysts, in combination with the use of a real options approach with more detailed information, turns out to be effective. A patent has a great impact on market structure. For example, new firms by the help of patents could gain access to a new market. Pakes (1986) investigates the concept of patents as options on inventions with uncertain returns, and presents empirical evidence as for the influence of patent renewal fees. Moreover, Bloom and Van Reenen (2000) probe into whether the patents have a great effect upon productivity and market value using patent citations as a proxy for innovation. Also, Bloom and Van Reenen (2002) adapt the real options approach for interpreting the adoption of new products and processes covered by patents, and furthermore establish empirical predictions regarding the relationship between patents and uncertainty. Bloom and Van Reenen reveal that higher market uncertainty appears to increases the value of real options and reduces the impact of new patents on productivity. According to the “IT industry competitiveness index” by the EIU (The Economist Intelligence Unit), Taiwan ranks second globally in “Information Technology Industry Competitiveness” in 2008, behind only the US. Furthermore, the Foundry Service contributes 68.1% of global production output and ranks number one in the world, so does the IC packaging industry. The IC design industry is ranked number two in the global market and takes up 26.5% of global production. Meanwhile, Taiwan is in the first position in supplying both IT hardware and TFT-LCD. These impressive achievements reinforce technological innovation in Taiwan and contribute to the industrial upgrading of the Taiwanese electronic industry. In addition, the number of US utility patents bestowed upon Taiwanese claimer rises from 6128 in 2007 to 6339 in 2008, ranking the country fifth globally. Citing the Global Competitiveness Report released by the World Economic Forum, Taiwan attains eminence in its innovation competitiveness internationally. For example, Taiwan acts as the major Supplier in 3G + Mobile Phones and is the Largest Wireless Terminal Product Supplier in the world. Therefore, this study examines panel data grounded on Taiwanese information technology (IT) firms for the valuation of patents. Most studies of real options only assume uncertainty in regard to future payoffs. Nevertheless, the cost of an investment is uncertain, particularly for large projects that may take a long time to complete and involve high uncertainties pertaining to R&D and patent investments (Pindyck, 1993; Lukach et al., 2007). Taking regard of the uncertainties tied up with patent counts and the amount of R&D per patent, this study builds a sensitivity analysis. This study applies cross-sectional and time-series data, deriving from 312 Taiwanese electronics firms sampled between 1990 and 2008, to the fixed effects analysis in the panel data model for examining the established relationships of sensitivity analyses. The remainder of this paper is structured as follows: Section 2 presents a pricing model, constructs sensitivity analyses of patents, and establishes basic propositions. Section 3 then uses panel data to

perform empirical tests, and expounds upon the selection of variables. Section 4 describes the sample used for the analyses, and reveals the empirical outcomes. Finally, Section 5 summarizes the results and presents the conclusions. 2. The model and sensitivity analyses Real options analysis can capture the flexibility to manage uncertainties related to patents. The Black–Scholes Model developed in 1973, as the first method for determining fair prices of options, is widely used nowadays. The B–S model is represented as follows: S is the symbol of the stock price, dS S = αdt + σdz; where α represents the instantaneous expected return of the stock price; σ is the instantaneous volatility rate of the stock price, and dz denotes the standard Gauss–Wiener process. Then the option value is: −rτ

C = SNðd1 Þ−Ke Nðd2 Þ
   S 1 2 + r+ σ τ ln 2 K pffiffiffi d1 = σ τ pffiffiffi d2 = d1 −σ τ

ð1Þ

In the above equations, C represents the value of an option (real options); S denotes the underlying asset price (project value); K is the exercise price (investment cost); r is the risk-free rate; σ is the volatility of S; τ is the time to maturity, and N(·) represents the cumulative standard normal distribution function. Insomuch as option holders know the exercise price in advance, future stock price is the only uncertainty that they face. However, the patent manager encounters two types of uncertainty: project value (expected benefits) and investment costs (expected costs). Differing from the previous study conducted by Wu and Tseng (2006) with the aid of Black and Scholes (1973), which captures only one uncertainty regarding the project value, this paper considers both two uncertainties regarding project value and investment cost, and then estimates the patent counts and the amount of R&D per patent separately. Moreover, because investment cost may appear to be more volatile than project value, this study pays more attention to the fluctuation of investment costs. Consequently, the manager must confront two uncertainties, one for project value and another for investment cost, in making an accurate decision about the patent project. Nevertheless, the exercise price of the B–S model is fixed so that the B–S formula fails to capture variation in investment cost. The exchange option model developed by Margrabe in 1978, is more general than the B–S model, considering the uncertain exercise price, and succeeds in recognizing the uncertainties derived from the project value and investment costs. This model's expression follows. Define S as the stock price (project value), dS S = αS dt + σS dzS ; and define K as the exercise price (investment cost), dK K = αK dt + σK dzK , where αi represents the instantaneous expected return of the stock price or exercise price; σi denotes the instantaneous volatility rate of the stock price or exercise price, and dzi is the standard Wiener process. The option value then is: C = SNðd1 Þ−KNðd2 Þ
 S 1 2 + σ τ ln pffiffiffi 2 K pffiffiffi d1 = ; d2 = d1 −σ τ σ τ

ð2Þ

σ 2 = σS2 + σK2 −2ρSK σS σK In the above equation, C is the value of options; S denotes the underlying stock price; K represents the exercise price; σ is the volatility, namely the standard deviation of the percentage change in S and K; ρ is the correlation coefficient between S and K; τ is the time

M.-C. Wu / Journal of Business Research 64 (2011) 81–86

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to maturity, and N(·) is the cumulative standard normal distribution function. This above equation considers the variation in both project value and investment cost. Moreover, this study conducts a sensitivity analysis of the evaluation model and establishes an empirical analysis for investigating these relationships by means of a panel data. Sensitivity analyses for the evaluation model are constructed as follows. First, the partial derivative of option price with respect to the project value, is:

where the subscript i indexes the ith firm, while t indicates the tth time period; βj denotes the coefficient on independent variables, and e stands for the effects of unobservable factors (namely, an error term). A specification originating from the observation, according to both the cross section (i) and the time series (t), is known as a model with twoway effects. Y and X are the dependent and independent variables in the time series and cross section. Therefore, the specification of the two-way effects is shown below.

∂C = Nðd1 Þ N 0 ∂S

ei;t = μi + vt + εi;t

ð3Þ

The value indicates that patent value would vary, accompanying the change of project value. This study sets forth Proposition 1 as follows: Proposition 1. The patent value increases with the increase in project value. Second;

∂C = −Nðd2 Þb0 ∂K

ð4Þ

This result suggests that patent value decreases corresponding to an increase in the investment cost. Hence, this study constructs Proposition 2 as follows: Proposition 2. The patent value decreases with the increase in the investment cost. Third, the partial derivative of option price in connection with the volatility is represented as follows: 2 pffiffiffi ∂C 1 −d1 = S⋅ τ⋅nðd1 Þ N 0 where nðd1 Þ = pffiffiffiffiffiffi e 2 ∂σ 2π

ð5Þ

This result implies that patent value increases in accordance with an increase in the volatility. Therefore, this study constructs Proposition 3 as follows: Proposition 3. The patent value increases with the increase in the volatility. Fourth, the partial derivative of option price with respect to the time to maturity τ is represented as follows:

ð8Þ

The two-way effects model represents that these unobservable factors (ei,t) can be categorized into three terms, including the observable firm specific effect (μi), the observable time specific effect (vt), and the unobservable random time and individual variant effect (εi,t); these three terms are independent of each other (Baltagi, 2008). In terms of the two-way effects model, the fixed effect model and the random effect model are two of the most widespread estimation methods. Making the choice between fixed effects and random effects models can be determined based on Hausman's test on the vector of estimated coefficients and variance–covariance matrices derived by using different estimation methods (Hausman and Taylor, 1981). The advantages of the fixed effects model are emphasized by Greene (1997), Oum, Park, Kim, and Yu (2004). The IT industry in Taiwan includes numerous sub-sectors such as integrated circuits, computers and peripherals, telecommunications, optp-electronics, and others. Due to a great diversity of IT firms, this study attempts to take account of the variances of individual firms in the number of patents being granted. That is, using a fixed effects model in the panel analyses should take inter-individual differences among firms into account. By comparison, the random effects model fails to consider variables that may exert a significant influence on the dependent variable. In other words, if these variables and the independent variables are closely correlated, then the parameter estimates could produce biased outcomes (Hsiao, 2003; Ernst, 2001). The establishment of time of Taiwan IT firms is more difficult owing to the missing data of some firms' data for certain years. Consequently, different number of observations may occur regarding per individual stock. To solve this problem, this study, following the example of Wansbeek and Kapteyn (1989), adopts quadratic unbiased estimators of the variance components for the unbalanced two-way effects model. The estimate of the regression slope coefficients (β) is formulated below.

2

∂C S⋅nðd1 Þ⋅σ 1 −d1 pffiffiffi N 0 where nðd1 Þ = pffiffiffiffiffiffi e 2 = ∂τ 2 τ 2π

ð6Þ ′ −1 −1 ′ −1 ˆ β XÞ X Σ y GLS = ðX Σ

This result implies that patent value increases corresponding to the increase of time to maturity τ. Accordingly, this study constructs Proposition 4 as follows:

ð9Þ

Given the above, the main empirical methodology used in this study is an unbalanced two-way fixed effects model.

Proposition 4. The patent value increases with the increase in the time to maturity. Table 1 Summary of five variables and their definitions.

3. Empirical method 3.1. Unbalanced fixed effects model This study develops empirical models for patent value (Y) for examining the relationships among project value, investment cost, volatility, time to maturity and patent value. The model comprises four independent variables (X): the project value (Xj = 1), investment cost (Xj = 2), volatility (Xj = 3), and time to maturity (Xj = 4). Yi;t = Xj;i;t βj + ei;t

ð7Þ

Variables

Codes Indicators

Definitions

Patent value Project value Investment cost Volatility

Ci,t

Number of a firm's patents (Si,t) cited by later patents in other firms. Number of patents a firm i has been granted at time t. R&D expenditures divided by patent counts at time t. Standard deviation implicitly weighted according to the influence of patent value. Time until the expiration date of patent.

Time to maturity

Si,t Ki,t σi,t τi,t

Patent citations Patent counts R&D per patent Standard deviation Patent lifetime

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3.2. Variable definitions Table 1 lists and defines the five variables used in this study. Seeing that financial data are available, numerous studies have asserted that patent value, dependent upon market value and profits, could be approximated (Ernst, 2001). This study adopts patent citations as the most reliable proxy of patent value (C or Y) for the following reasons. First, although numerous studies demonstrate that patents play a positive role in market value or profits, patents constitute only one influence among numerous others. In brief, patent value is indirectly correlated with market value or profits. Second, patents are of heterogeneous; few are of high quality, while most are of low quality (Schankerman and Pakes, 1986). The study examines patent citations to measure patent quality; the assumption is that if patents receive frequent citations, with references in many subsequent patents, this activity implies important technological advances of being contained (McMillan, 2001). Bloom and Van Reenen (2002) propose that citation is a valuable proxy for assessing patent value. Additionally, patent citations at foreign patent offices may bear witness to patent quality (Ernst, 2001), and patent count is an unqualified proxy for the value of the underlying asset (S or Xj = 1). Granted patents, compared with patent applications, are more valuable because the granting of patents may demonstrate a major breakthrough in technological innovations and an achievement of exceeding an original level (Sherry and Teece, 2004). Patent count, one of the variables, is defined as the number of patents granted to a firm at a specific time. Research and development (R&D) is comparable to a production process metaphorically. As research inputs are transformed into research outputs, so R&D expenditure turns out to be patents. Total R&D expenditures divides by patent counts at a specific time for the purpose of making a calculation of the amount of R&D per patent. R&D per patent is adopted as the most reliable proxy of investment cost (K or Xj = 2) in this study. What is more, time to maturity (τ or Xj = 4), depending on patent lifetime, is measured. In respect to the measure of volatility, (σ or Xj = 3) this study tries to examine the relationships among firm volatility and future prices, wage rates, technologies, consumer tastes, government policies, etc (Ray and Bhaduri, 2001; Bloom and Van Reenen, 2002). Lastly, considering the volatility of firm environment and the advancement of technology, a forward looking proxy is used, which, in an impliedly way, is weighted in line with the influence of these variables imposing on patent value. Early research is the pioneer in the examination of patents in the USA (United States Patent and Trademark Office; USPTO) Europe (Europe Patent Office; EPO), and Japan (Japanese Patent Office; JPO) that are ratified as the best indicators, performing well for comparing and contrasting the international analysis (Grupp and Schmooh, 1999). US patents are the most reliable proxy for patents in this study in view of the following reasons (Grupp and Schmooh, 1999; Watanabe et al., 2001). First and foremost, the statistics offered by USPTO are sifted through the US Patent Office examination in the process of patent registration, as a token of approbation, which has turned into a global standard presently. Next, US patents have been proven to be an outstanding indicator of economic value. More specifically, US patents, verified as an extremely authentic index for innovation output, act an important role in the evaluations of patents. 4. Data and empirical results 4.1. Sample selection The initial sample consists of 375 Taiwanese IT firms listed on the Taiwanese stock market during the period of 1990–2008. Firms included in the sample are required to measure up to two criteria. First, the firm must have at least two time series observations on which variables during the sample period from 1990 through 2008

should be compatible with the minimum data requirements for estimation and the unbalanced fixed effect model (Baltagi, 2008). Second, the confounding effect of financial distress is omitted in this study. According to the Taiwan Stock Exchange (TSE), companies under financial crisis are identified as bankrupt companies and are therefore eliminated from the sample. The final sample, 312 firms in total, is selected in light of the above criteria. Financial data on the final sample of 312 firms are gathered from the Taiwan Economic Journal (TEJ), which contains information derived from a private agency collecting financial and stock data on publiclytraded companies. The data set is tantamount to the COMPUSTAT data set collected in the USA. The download of patent and citation data from the USPTO (United States Patent and Trademark Office) database is accessible. To calculate patent value, this study examines all records of the granted patents throughout the period 1990–2008. The number of citations made by the 312 selected sample firms over the whole span of 19 years was 76,130, whereas the number of granted patents was 23,118. 4.2. Description of data Founded on the panel data for 312 firms from 1990 through 2008, Table 2 displays descriptive statistics for all of the variables. The sample firms have a mean citation of 64.63 and mean patent counts of 19.35. In addition, the mean R&D per patent is NT$19.66 million, the average volatility is 1.46 and the average patent lifetime is 12.98 years. The large standard deviation relevant to mean values discloses significant variability in three variables: patent citations, patent counts, R&D per patent among the firms, along with the presence of a few firms with individual variant and lifetime variant effect. Fig. 1 compares patent citations and counts during 1990–2008. Citations decline from approximately 2002, because in many cases citations may occur more than 10 years after the original patent is issued (Hall, 2006). To improve the analysis of the model parameter values, Table 3 compares the results for full samples (Panel A) with those for restrictive samples (Panel B). The former comprised firms during 1990–2008, while the latter comprised firms during 1990–2000.

4.3. Empirical results for full samples In this study, the results of the Hausman-test attest to the accuracy of applying a fixed effect model to the proposed data. Namely, the panel estimate should consider inter-individual differences between firms. Table 3, grounded on the unbalanced two-way fixed effects model, reveals the effects of four explanatory variables on patent value. The result of the subsequent t-test is highly significant, and helpful for interpreting the individual parameters in the future. In Panel A, the adjusted R2 value (goodness-of-fit) is 43.25%. The adjusted R2 value is relatively high compared with previous similar research (McMillan, 2001).

Table 2 Descriptive statistics.

Patent citations Patent counts R&D per patent Volatility Patent lifetime

Mean

Standard deviation

64.63 19.35 19.66 1.46 12.98

278.24 64.70 105.77 1.75 5.48

Patent citations is the number of a firm's patents cited by later patents in other firms. Patent counts is the number of patents that a firm has been granted. R&D per patent is the R&D expenditures divided by patent counts. Volatility is the standard deviation implicitly weighted according to the influence of patent value. Patent lifetime is the time until the expiration date of patent.

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Fig. 1. Comparison between patent citations and counts during 1990–2008. Plots of patent citations and counts from 1990 to 2008. The number of citations made by 312 sample firms during 1990–2008 was 76,130, while the number of patents counts was 23,118.

The findings of empirical models indicate that patent counts (β1 =1.7754, t-statistic=9.51), volatility (β3 =6.3278, t-statistic=1.74), and time to maturity (β4 = 27.5997, t-statistic = 5.20) are related positively and significantly to patent value. Hence, the results corroborate Propositions 1, 3 and 4. That is to say, patent value increases with patent counts, volatility and patent lifetime. The coefficient estimation for R&D per patent (β2 = −0.0567, tstatistic = − 1.43) while negative, is not statistically significant. Hence, the evidence is not significant enough to support Proposition 2. 4.4. Empirical results of additional tests from restricted samples Additional tests are carried out for assessing the robustness of the main result. As for restricted samples, the results are exhibited in Table 3 below. The results of restricted samples with the remaining coefficient estimated are analogous to the results of full samples. That is, Propositions 1, 3 and 4, with the exception of Proposition 2, are also confirmed according to the results of the respective samples. 5. Conclusions Numerous academics and managers appear to approve the capability of real options to capture the value of flexibility in relation to patent projects. Notwithstanding, few studies attempt to establish empirical methods and test their application in real circumstances. For one thing, this study adopts the exchange option pricing model on the basis of the consideration of the uncertainties associated with both

Table 3 Results of unbalanced fixed effected models. Variable

Coefficient

Standard error

Panel A: full samples (from 1990 to 2008) Patent counts 1.7754*** 0.1866 R&D per patent − 0.0567 0.0396 Volatility 6.3278* 3.6345 Patent lifetime 27.5997*** 5.3071 Panel B: restrictive samples (from 1990 to 2000) Patent counts 10.3191*** 0.1931 R&D per patent − 0.2350 0.1880 Volatility 51.3413*** 16.9252 Patent lifetime 34.2548*** 8.0437

t-statistic

Adjusted R2

9.51 − 1.43 1.74 5.20

43.25%

53.43 − 1.25 3.03 4.26

45.12%

The dependent variable is patent value; *, ** and *** denote significance at the 10%, 5%, and 1% levels, respectively. The panel A has F-statistic 5.86, and panel B has F-statistic 9.38. Both panel A and panel B have Prob.NF = 0.0000.

the patent counts and the amount of R&D per patent; for another, estimations are constructed for empirical analysis within a real options framework. To examine patent value, this investigation filters the entire record of patents granted throughout the period from 1990 to 2008 for each backwards citation made by firms. During 1990–2008, the number of backwards citations made by the 312 sample firms totaled 76,130, while the number of patents granted is 23,118 in total. Cross-sectional and time-series data taken from the 312 Taiwanese electronic firms sampled during 1990–2008, are adopted for the fixed effects analysis in the panel data model to examine the established sensitivity analyses relationships. Additional tests use restricted data during 1990–2000 so that the robustness of the main results is examined. The use of the unbalanced two-way fixed effects model attests to the fact that patent value increases with patent counts, volatility and patent lifetime. The impact of the above three factors on patent value corresponds to the theoretical model. Although the patent value decreases with the amount of R&D per patent, the estimator is of little significance. However, reducing cost, raising patent counts and enhancing innovation efficiency would offer a feasible method for a firm to increase patent value.

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Nwaeze ET. Replacement versus adaptation investments and equity value. J Corp Finance 2005;11:523–49. Oum TH, Park JH, Kim K, Yu C. The effect of horizontal alliances on firm productivity and profitability: evidence from the global airline industry. J Bus Res 2004;57:844–53. Pakes A. Patents as options: some estimates of the value of holding European patents stocks. Econometrica 1986;54:755–84. Perlitz M, Peske T, Schrank R. Real options valuation: the new frontier in R&D project evaluation? R&D Manage 1999;29:255–69. Pindyck RS. Investments of uncertain cost. J Finan Econ 1993;34:53–76. Ray AS, Bhaduri S. R&D and technology learning in Indian industry: econometric estimation of the research production function. Oxf Dev Stud 2001;29:155–71. Schankerman M, Pakes A. Estimates of the value of patent rights in European countries during the post-1950 period. Econ J 1986;96:1052–77. Shackleton M, Wojakowski R. The expected return and exercise time of Merton-style real options. J Bus Finance Account 2002;29:541–55.

Sherry EF, Teece DJ. Royalties, evolving patent rights, and the value of innovation. Res Policy 2004;33:179–91. Stark AW. Real options, (dis)investment decision-making and accounting measures of performance. J Bus Finance Account 2000;27:313–31. Wansbeek T, Kapteyn A. Estimation of the error components model with incomplete panels. J Econ 1989;41:341–61. Watanabe C, Tsuji YS, Griffy-Brown C. Patent statistics: deciphering a real versus a pseudo proxy of innovation. Technovation 2001;21:783–90. Wu MC, Tseng CY. Valuation of patent: a real options perspective. Appl Econ Lett 2006;13:313–8. Wu MC, Yen SH. Pricing real growth options when the underlying assets have jump diffusion processes: the case of R&D investments. R&D Manage 2007;37:269–76.

Journal of Business Research 64 (2011) 87–95

Contents lists available at ScienceDirect

Journal of Business Research

Customer participation and citizenship behavioral influences on employee performance, satisfaction, commitment, and turnover intention Youjae Yi a, Rajan Nataraajan b,⁎, Taeshik Gong a a b

College of Business Administration, Seoul National University 599 Gwanak-ro, Gwanak-gu, Seoul, 151-916, Republic of Korea Department of Marketing, College of Business, Auburn University, 415 W. Magnolia Ave., Auburn, AL 36849-5246, United States

a r t i c l e

i n f o

Article history: Received 1 November 2009 Received in revised form 1 December 2009 Accepted 1 December 2009 Keywords: Customer participation behavior Customer citizenship behavior Employee performance Employee satisfaction Employee commitment Turnover intention

a b s t r a c t Despite increasing awareness of the importance of customer behaviors in service delivery, understanding consequences relating to employees receives little attention. Therefore, using data from a large electronic firm relating to customers, employees, and managers, this study examines the effects of customer participation and citizenship behavior on employee performance, satisfaction and commitment, as well as indirect effects on turnover intention. Furthermore, the study examines how similarity and likeability moderate the effects of customer participation and citizenship behavior on employee satisfaction. The study also includes a laboratory experiment and provides further support for causal direction. The article discusses marketing implications of the results. © 2010 Elsevier Inc. All rights reserved.

The service literature recognizes the importance of service encounters. Service encounters involve a dyadic interaction of frontline service employees (FSEs) and customers (Kelley et al., 1990). Although customers play a critical role in service co-creation, research on service encounters has focused almost exclusively on employees. However, interest in customer behavior in service cocreation has been growing in the literature (Bendapudi and Leone, 2003). More recently, researchers focus on what has become known as service-dominant logic which views customers as a co-creator of value in the service provision process (Vargo and Lusch, 2004). Against this background, various attempts focus more on understanding the role of customer behavior in service co-creation than on customer behavior in buying decision process. Recent literature on customer behavior focuses on the merits of understanding customers as human resources in the firm. The service marketing literature identifies at least two types of customer behavior in service delivery process (Bove et al., 2008; Groth, 2005): (a) customer participation behavior, which is “expected and required behaviors necessary for the successful production and delivery of the service” (Groth, 2005, p. 11) and (b) customer citizenship behavior, which is “voluntary and

⁎ Corresponding author. E-mail addresses: [email protected] (Y. Yi), [email protected] (R. Nataraajan), [email protected] (T. Gong). 0148-2963/$ – see front matter © 2010 Elsevier Inc. All rights reserved. doi:10.1016/j.jbusres.2009.12.007

discretionary behaviors that are not required for the successful production and delivery of the service but that, in the aggregate, help the service organization overall” (Groth, 2005, p. 11). Several studies have examined which variables affect customer participation and citizenship behavior (e.g., Ahearne et al., 2005; Bove et al., 2008; Yi and Gong, 2008). Previous research has also shown that these two types of customer behavior influence customer-related outcomes such as service quality and customer satisfaction as well as firmrelated outcomes such as firm performance (e.g., Ennew and Binks, 1999; Skaggs and Youndt, 2004). Nevertheless, few investigations examine how customer behaviors affect employee-related outcomes. More specifically, little research investigates how customer behavior, such as customer participation behavior (CPB) or customer citizenship behavior (CCB), affects employee performance and satisfaction theoretically and empirically. This gap in the literature is surprising because the collaborative activities of employees and customers create value (Vargo and Lusch, 2004). The service marketing literature has an impressive research tradition of investigating FSE outcomes such as employee performance, satisfaction, commitment, and turnover intention (Bettencourt and Brown, 2003). Given the importance of these employee attitudes and behaviors, identifying additional determinants of these employee outcomes is necessary. Previous research in this area has not examined the effects of customer behaviors on FSEs. Therefore, this paper focuses on how customer behaviors affect FSE performance, satisfaction, commitment, and turnover intention.

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1. Theoretical background 1.1. Customers as human resources The service marketing literature recognizes the importance of customers as human resources. This study integrates different facets of several streams of research regarding customers as human resources and describes how each of these theoretical perspectives justifies the influence of customer behavior on employee attitude and behavior. The first contains studies on how customers can enhance firm productivity. Lovelock and Young (1979) are the first to highlight the issue of customers as human resources, suggesting that service managers should look to customers to increase productivity. Customers can increase firm productivity through cost reductions associated with a lower need for FSEs. Customers supply what is, in effect, productive labor in the form of information or effort that directly substitutes for FSE labor (Rodie and Kleine, 2000). Previous research has shown consistently that customers provide the resources that FSEs typically provide (Kelley et al., 1992). The second theme is the open system approach in organizational science. This approach views the firm as a component that interacts with its environment (Thompson, 1967). From this perspective, firms are dependent on their environment for resource inputs, because all firms import various kinds of energy from their environment and return some form of service (Rousseau, 1979). Furthermore, the open system approach stresses “the interdependence of the organization and its environment” (Scott, 2003, p. 101). Many organizational theorists argue that customers are an essential component of the firm's environment (Larsson and Bowen, 1989). The third theme is the servuction model (Eiglier and Langeard, 1987). This model posits that the service firm comprises two elements: invisible and visible parts. The invisible part involves the firm and its system, while the visible part has to do with the physical environment, FSEs, and customers, which constitute the servuction system (Bateson and Hoffman, 1999). This model suggests that effective service delivery depends on the interaction of customers with the firm, and FSEs. Consequently, in order to create value within the servuction system, customers should be an integral part of the system and act as a human resource (Bateson and Hoffman, 1999; Eiglier and Langeard, 1987). The fourth theme is the customer contact theory which views customers as having a physical presence in the service system and as contributing to the creation of the service (Chase, 1981; Schneider and White, 2004). An underlying assumption is that the interaction between FSEs and customers drives the efficiency of service operations, in that the firm is able to design its processes better and deploy its resources more effectively by decoupling and regrouping lowcontact from high-contact subunits in the firm (Bowen, 1986; Chase, 1981). Research on customer contact argues that, because customers are an integral variable affecting service delivery decisions, firms should employ contact enhancement strategies to design processes maximizing productivity (Chase, 1981; Schneider and White, 2004). The fifth theme regarding customers as human resources centers on the dramaturgical metaphor. This metaphor views service marketing phenomena as a form of drama, because it can account for the dynamics of the human interactions (Grove et al., 1992). Drama is a collaborative activity, just as the interaction of FSEs and customers forms the core of service experience. The drama metaphor provides further support for the relevance of customers as human resources. According to the drama metaphor, “the development and maintenance of an interaction (e.g., a service experience) relies on the audiences' input as well as the actors' presentation” (Zeithaml et al., 2006, p. 319). The final theme is the social capital theory. The organizational literature defines social capital as “the sum of the actual and potential resource embedded within, available through, and derived from the

network of relationships possessed by an individual or social unit” (Nahapiet and Ghoshal, 1998, p. 243). In the relationship between the firm and customers, customers become a valuable resource derived from the interpersonal relationships among firm members. Bolino et al. (2002, pp. 506–507) suggest that social capital is valuable because “it solves problems of coordination, reduces transaction cost, and facilitates the flow of information … makes collective work easier … contributes significantly to organizational advantage.” Most notably, social capital enables both customers and employees to work together more effectively and efficiently through knowledge, understanding, and trust. Table 1 summarizes the characteristics of each theoretical perspective. These perspectives commonly suggest that customers are actually human resources and influence employees. Among them, the productivity enhancing perspective captures an interdisciplinary perspective. This view harmonizes all the other theoretical approaches because it deals with the mechanism how customers substitute employees. It further encompasses the aspects of marketing, organizational behavior, and operation management. However, this perspective does not reveal any concrete evidence on how it actually occurs. Five other theoretical perspectives propose different theoretical reasoning of how customers constitute human resources in the firm. All in all, customers are not passive recipients, but rather part-time employees, actively influencing employee attitude and behavior. 1.2. Customer participation behavior and customer citizenship behavior In a broad sense, customer participation behavior refers to all forms of customer involvement and engagement in the value-creation process. This research uses customer participation behavior in a narrow sense, which includes only required behaviors necessary for the successful service creation. This usage is consistent with previous research on customer participation behavior. For example, Ennew and Binks (1999) propose that one of the dimensions of customer participation behavior is responsible behavior, which means that, as one of the parties that can do the job, customers have duties and responsibilities for successful service delivery. Echoing this, Zeithaml et al. (2006) suggest that customers have mandatory production roles that can ensure a successful service outcome. Indeed, firms need customer participation to create the service successfully (e.g., piano lessons, personal fitness training, physical therapy, a weight reduction program, pumping their own gas, self-check in at an airport and providing answers to questions). While customer participation behavior relates to enforceable or explicit required in-role behavior, customer citizenship behavior entails voluntary or non-explicit behaviors that benefit the firm and go beyond customer role expectations (Gruen, 1995). Customer citizenship behavior provides extraordinary value to the firm. Although the exact dimensionality of customer citizenship behavior is not yet clear (Bove et al., 2008), the literature suggests various forms of customer citizenship behavior, such as positive word-ofmouth communication, constructive involvement in suggesting service improvements, and other polite and courteous behaviors exhibited toward FSEs (Bettencourt, 1997; Rosenbaum and Massiah, 2007). Therefore, customer citizenship behavior is different from customer participation behavior that customers need to perform in creating a service. Customer citizenship behavior encompasses only voluntary customer behavior that is not required for successful service creation. Customers perform citizenship behavior at their sole discretion (Bettencourt, 1997; Groth, 2005). Similarly, previous studies provide empirical evidence that such in-role and extra-role behaviors exhibit different patterns of behavior and different antecedents, and contribute independently to overall firm performance (Motowidlo and van Scotter, 1994).

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Table 1 Overview of theoretical perspectives of customers as human resources. Theoretical perspectives

Source

Components

Characteristics

Examples of studies

Productivity enhancing perspective

Information Effort

Customers substitute for FSE labor costs.

Open system approach

Marketing Organizational behavior Operation management Organizational behavior

Environment Interdependence Interaction

Customers are viewed as firm environment so that customers can be a source of materials, energy, and information.

Servuction model

Marketing

Invisible part Visible part

Customer contact theory

Operation management

Dramaturgical metaphor

Marketing

Social capital theory

Organizational behavior

Customer contact (high-contact and low-contact subunits) Physical presence Actors Audience Set Structural dimension Relational dimension Cognitive dimension

Service creation involves the customer interaction with the firm, FSEs, and other customers Physical presence of customers leads to the interaction between FSEs and customers, which in turn drives the efficiency of service operations. Service creation is viewed as drama so that customer reactions as audience provide valuable feedback to employees as actors. The interpersonal relationships of customers with firm members enable customers to act as social capital which is valuable resource for the firm.

Fitzsimmons (1985) Lovelock and Young (1979) Mills and Morris (1986) Larsson and Bowen (1989) Rousseau (1979) Scott (2003) Thompson (1967) Bateson and Hoffman (1999) Eiglier and Langeard (1987)

2. Conceptual model and hypotheses Fig. 1A depicts the main effects model. Social cognitive theory suggests that observing someone else performing a behavior increases individuals' perceived confidence in their ability to perform it success-

Fig. 1. Conceptual framework: main effects model (A) and moderating effects model (B).

Bowen (1986) Chase (1981) Schneider and White (2004) Soteriou and Chase (1998) Grove et al. (1992) Williams and Anderson (2005) Zeithaml et al. (2006) Bolino et al. (2002) Nahapiet and Ghoshal (1998)

fully by learning appropriate and effective strategies for coping with challenging situations and by acquiring new skills (Compeau and Higgins, 1995). In turn, this outcome expectation increases individuals' actual performance, because beliefs in abilities generally intensify people's efforts and persistence (Bandura, 1986). Within the context of service delivery, employees might observe customer participation and citizenship behavior. Employees then have the opportunity to learn effective tactics with respect to how customers contribute effort, time, and other resources to the service creation process. Moreover, encouragement and assistance from customers can affect both their ability to function effectively and the nature of their cognitive and affective states. For example, customer behaviors could make employees' job easier, or perhaps the social interaction among employees and customers may inherently please the FSE. Customer participation behavior can effectively remove or substitute for some of the labor tasks performed by FSEs (Bendapudi and Leone, 2003; Lovelock and Young, 1979; Rodie and Kleine, 2000). The more FSE's works are shifted to customers, the more FSEs have time to engage in social interaction with customers, specifically, a more rewarding interaction. The marketing literature frequently examines the importance of social interaction with customers. Positive social interaction with customers are likely to increase the effectiveness of FSEs because it enables FSEs to share information with customers, demonstrate an understanding and concern for customers' need and cultivate better understanding of mutual needs (Homburg et al., 2007). Therefore, this study argues that customer participation behavior improves employee performance. Customer participation behavior can enhance customer satisfaction by increasing “the likelihood that needs are met and the benefits the customer seeks are actually attained” (Zeithaml et al., 2006, p. 397). Customer satisfaction, in turn, influences employee satisfaction through an emotional contagion process, meaning that satisfaction displayed by customers can transfer to FSEs (Pugh, 2001). Customer participation behavior also affects employee commitment. According to Johnston et al. (1990), the greater the level of employee stress is, the lower the level of employee commitment is. FSEs are prone to high levels of stress, which make FSEs “view the organization in adversarial terms and tend to withdraw psychologically from it … not believe their job provides them with a sense of accomplishment” (Singh et al., 1994, p. 561). Because customer participation behavior reduces employee workload, customer participation would affect employee commitment positively.

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H1. Customer participation behavior relates positively to employee performance.

likeable or similar to themselves, the more effective the message (i.e., CPB and CCB) is.

H2. Customer participation behavior relates positively to employee satisfaction.

H7. Similarity between FSEs and customers strengthens the relationship between customer participation behavior and employee satisfaction.

H3. Customer participation behavior relates positively to employee commitment. In the context of the study, social exchange relationships evolve when customers take care of employees, thereby engendering beneficial employee consequences. In other words, when customers provide employees with a benefit such as customer citizenship behavior, employees feel an obligation to reciprocate; effective employee behavior and positive employee attitudes might occur as a form of reciprocation (Cropanzano and Mitchell, 2005). If FSEs acquire assistance or valuable feedback from their customers, they can learn the ropes and spread best practices throughout the firm. As a likely result, FSEs become more productive and better performing (Podsakoff et al., 2000). Customer citizenship behavior may influence employees indirectly by enhancing role clarity and fostering a sense of stability. Helping fellow employees perform their responsibilities improves their understanding of role requirements, which, in turn, increases their satisfaction and commitment (Tepper et al., 2004). Customer citizenship behavior might also be associated with FSE perceptions that the firm is the place where customers treat them with kindness and consideration, which results in higher satisfaction and commitment. H4. Customer citizenship behavior relates positively to employee performance. H5. Customer citizenship behavior relates positively to employee satisfaction. H6. Customer citizenship behavior relates positively to employee commitment. The model includes several additional paths to avoid any model misspecification (Fig. 1A). In particular, the model includes the effects of employee performance, satisfaction, and commitment on turnover intentions (e.g., Johnston et al., 1990), the effect of employee performance on employee satisfaction (e.g., Christen et al., 2006), and the effect of employee satisfaction on employee commitment (e.g., Johnston et al., 1990). Social cognitive theory views human functioning as a reciprocal interplay among three factors: environmental influences, personal factors, and behavior. Service co-creation does not operate in a vacuum. Therefore, the moderating effects model in Fig. 1B posits that environmental factors (e.g., customer behaviors) exert an influence on personal factors (e.g., employee satisfaction) by interacting with other environmental influences, such as similarity and likeability. Although various factors can contribute to interpersonal influence, similarity and likeability have received a great deal of attention to date (e.g., Doney and Cannon, 1997; Holzwarth et al., 2006). According to McGuire (1985), similarity refers to the resemblance between the source (i.e., customers) and the receiver (i.e., FSEs) of the message (i.e., CPB and CCB). Likeability refers to people's assessment that the other party is friendly, nice, and pleasant to be around (Doney and Cannon, 1997). Previous research shows that attractiveness such as similarity and likeability facilitates attitude change (Kahle and Homer, 1985). Attractive people can induce more opinion change and exert a greater influence on individual attitudes (Ahearne et al., 1999). Therefore, customers who are similar to their employees or simply likeable would be more influential in changing employee attitudes than dissimilar or dislikable customers. In line with McGuire (1985), this study argues that the more FSEs perceive the source (i.e., customers) as

H8. Similarity between FSEs and customers strengthens the relationship between customer citizenship behavior and employee satisfaction. H9. Likeability of customers strengthens the relationship between customer participation behavior and employee satisfaction. H10. Likeability of customers strengthens the relationship between customer citizenship behavior and employee satisfaction. 3. Study 1: survey 3.1. Sample and data collection A large household electronic firm with several major branches was contacted in order to obtain a sample. The firm employs frontline service employees (FSEs), each of whom manages a portfolio of customers. FSEs visit customers regularly and make sure that products are in the optimal condition. In addition to the initial service interaction, FSEs are responsible for ongoing customer contacts. To reduce the possibility of common method bias, data were collected from three separate sources; customers (to rate their own CPB and CCB), managers (to report on FSEs' performance), and FSEs (to describe their attitude and behavior). First, the firm's management provided support for data collection. A list of managers, a list of FSEs supervised by those managers, and a list of customers served by each FSE were obtained. Then, FSEs were approached during their daily meetings and questionnaires were distributed to their customers. Using full customer contact information, customers for each FSE were randomly selected not to allow the FSE to select customers for the study, thus eliminating a selection bias. Three weeks later, the managers of FSEs evaluated the participants' performance. Finally, FSEs rated their satisfaction, commitment, and turnover intention at meetings held at the firm's facilities three weeks later. The respondents were assured that individual responses would remain confidential and that they could withdraw at any time. A total of 332 customers, 142 FSEs, and 31 managers produced the data and were used to test the hypotheses. The customer sample consisted of 6% males and 94% females. The mean age of customers was 38 (range = 28–66 years). The FSE sample consisted of 24% males and 76% females. The mean age of FSEs was 36 (range = 26–44 years). The mean job tenure was 4.2 years. The manager sample consisted of 29% males and 71% females. The mean age of managers was 45 (range = 39–55 years), and the mean job tenure was 10.5 years. For the subsequent data analysis, customer responses for each FSE were aggregated, using the mean as suggested in the literature (Homburg et al., 2009). To ensure that customer responses are reasonably stable within each FSE, the intraclass correlation coefficient (ICC) (1) (.15 for CPB and .16 for CCB) and ICC (2) (.37 for CPB and .31 for CCB) were estimated. These values were comparable to similar studies (Homburg et al., 2009; James, 1982; Schneider et al., 1998). Therefore, the legitimacy of aggregating customer responses for each FSE was supported (Bliese, 2000). 3.2. Measurement For all constructs, previously validated measures were used. Participants responded on a seven-point Likert-type scale, ranging from strongly agree to strongly disagree.

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3.2.1. Customer measures CPB was assessed with three items based on Groth's (2005) measures. In line with the definition, the items essentially cover expected and required customer behaviors for successful service delivery. Example items include: “I perform all the tasks that are required of me” and “I fulfill customer responsibilities to employees of the firm.” CCB was measured using three items that gauged the extent to which customers recommend the employee to others, make constructive suggestions, and give full cooperation to the employee. These items represent voluntary and discretionary customer behaviors that are not required for the production of the service. The items were based on those developed by Bettencourt (1997), which were also used by Rosenbaum and Massiah (2007). 3.2.2. Manager measures Employee performance was measured with five items adapted from Wayne et al. (1997). Scale items captured the extent to which a manager feels that an employee gets his or her work done effectively and fulfils his or her roles and responsibilities. Managers are deemed appropriate to evaluate employee performance, because they generally supervise fewer than 10 employees and they have a daily meeting with employees. Accordingly, they are very knowledgeable about the performance of their employees. 3.2.3. Employee measures Employee satisfaction was measured with three items that represent the level of overall satisfaction. The items were based partly on the work of Netemeyer et al. (1997). Employee commitment was measured with four items adapted from Maltz and Kohli (1996). Scale items measured the extent to which employees report a strong sense of personal identification with and dedication to a company. Turnover intention was measured with three items from Ganesan and Weitz (1996) for capturing the extent to which employees believe that they will be leaving a company within a short period of time. With regard to moderator variables, similarity was measured with four items (Doney and Cannon, 1997; Turban and Jones, 1988). The selected items specifically measure the degree to which an employee perceives a customer as having similar outlook, perspectives, values, age, and gender. Likeability was measured with three items adapted from Doney and Cannon (1997) and Wayne and Ferris (1990). This scale measures the extent to which an employee likes the customer as a person and perceives the customer as a friend. Table 2 provides the descriptive statistics, reliability information, and correlations. The composite reliabilities of measures are greater than the recommended .7, indicating acceptable properties in terms of internal consistency (Bagozzi and Yi, 1988). The average variance extracted for each measure is greater than .5, suggesting convergent validity (Bagozzi and Yi, 1988). A comparison between the average variance extracted by each of the constructs and the shared variance indicates discriminant validity (Fornell and Larcker, 1981). In addition, the loading of each indicator is higher than all of its crossloadings, thus indicating discriminant validity (Chin, 1998b). 3.3. Results Main effects: The partial least squares (PLS) method was employed to test the research model. A PLS analysis was deemed appropriate in this study because the goal of the model is to predict the variables of employee satisfaction, performance, and commitment. Also, restrictions on sample size and potential violation of normality (e.g., studies using employee commitment, satisfaction, turnover tend to involve non-normal data) lead to the application of PLS. Table 3 summarizes the results of hypothesis tests. The fit measures indicate an adequate fit of the structural model. The R2 values for endogenous constructs range from .20 to .37, which indicate an acceptable explanatory power of the model. In addition, the Stone–

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Table 2 Descriptive statistics, reliability, and correlations. Constructs

Correlations 1

2

3

4

5

6

1. CPB 1.00 2. CCB .68 1.00 3. Employee performance .36 .38 1.00 4. Employee satisfaction .37 .39 .55 1.00 5. Employee commitment .12 .25 .34 .43 1.00 6. Turnover intention − .05 − .13 − .23 − .33 −.48

7

8

1.00

Moderator variables 7. Similarity 8. Likeability

.49 .43

.59 .66

.11 .31

.06 .42

.03 − .07 1.00 .25 − .07 .49 1.00

Reliability Composite reliability Average variance extracted

.88 .64

.85 .65

.85 .53

.93 .76

.95 .86

3 5.03 .91

3 5.18 .94

5 5.84 .63

3 5.21 1.09

4 5.84 1.19

Summary statistics Number of items Mean Standard deviation

.86 .67

.85 .64

.90 .72

3 4 3 3.22 3.95 4.86 1.53 1.25 1.21

Geisser criterion (Q2) values, using the cross-validated redundancy option, range from .08 to .28 and are significantly different from 0, which implies that the latent variables in the model have high predictive ability (Chin, 1998b). A bootstrapping method with 500 re-samples was conducted to test for path significance (Chin, 1998a). A one-tailed test was employed, because this study tests directional hypotheses based on strong theoretical bases. Most hypothesized paths are statistically significant. The results support H1–H3, suggesting that customer participation behavior has positive and significant effects on employee performance (β = .22, p b .001), employee satisfaction (β = .12, p b .05), and employee commitment (β = .17, p b .01). H4–H6 involve the effects of customer citizenship behavior. Consistent with expectations, customer citizenship behavior has positive and significant effects on employee performance (β = .27, p b .001) and employee commitment (β = .23, p b .05) supporting H4 and H6. However, customer citizenship behavior does not have a significant effect on employee satisfaction (β = .10, p N .05). Thus, H5 is not supported. With respect to the additional paths in the model, the results confirm the well-established relationships between employee performance and employee satisfaction (β = .49, p b .001), between employee satisfaction and employee commitment (β = .40, p b .001), between employee satisfaction and turnover intention (β = −.16, p b .05), and between employee commitment and turnover intention (β = − .42, p b .001), However, the present study fails to find statistical Table 3 PLS structural model results.

CPB CCB EP ES EC Construct R2 Stone–Geisser criterion Q2

EP

ES

EC

.22 (3.09)⁎⁎⁎ .27 (3.30)⁎⁎⁎

.12 (1.96)⁎ .10 (1.42) .49 (11.96)⁎⁎⁎

.17 (2.40)⁎⁎ .23 (2.97)⁎⁎

.20 .08

.37 .28

.40 (5.80)⁎⁎⁎ .21 .17

TI

.01 (.14) − .16 (1.97)⁎ − .42 (6.42)⁎⁎⁎ .25 .16

Notes: Standardized coefficients are shown. The t-values are given in parentheses. CPB = customer participation behavior; CCB = customer citizenship behavior; EP= employee performance; ES = employee satisfaction; EC= employee commitment; TI = turnover intention. ⁎ p b .05, one-tailed. ⁎⁎ p b .01, one-tailed. ⁎⁎⁎ p b .001, one-tailed.

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support for the link between employee performance and turnover intention (β = .01, p N .05). One might also wonder whether customer behaviors influence turnover intention directly. This possibility was therefore examined. In an additional analysis, an alternative model including these direct paths (customer participation behavior → turnover intention and customer citizenship behavior → turnover intention) was run in order to validate the implicit assumptions of the hypothesized model. The results show that both paths are not significant. Moderating effects: The PLS product-indicator approach was adopted to assess the influence of moderator variables (Chin et al., 2003). Compared with the commonly used multiple regression analysis, this approach produces more accurate estimates of interaction effects by accounting for the measurement error that attenuates the estimated relationships (Chin et al., 2003). The PLS productindicator approach is also preferable to the LISREL moderator approach, because LISREL is technically demanding, resulting in analytical errors and incomplete solutions (Bollen and Paxton, 1988; Chin et al., 2003). This study followed the procedure proposed by Chin et al. (2003). The first step entailed standardizing (mean-centering) the indicator of main and moderating variables. The second step then created all pair-wise product indicators where each indicator from the main construct was multiplied with each indicator from the moderating construct. Finally, the product indicators were used to reflect the interaction construct. The results of the moderator analyses are presented in Table 4. The CPB × similarity interaction has a positive and significant effect on employee satisfaction (β = .24, p b .05), supporting H7. On the other hand, H8 is not supported, because the latent interaction between CCB and similarity is not significant (β = .03, p N .05). The results indicate that the more similarity employees perceive with respect to customers, the more customer participation behavior leads to employee satisfaction. The interaction between CPB and likeability has a positive and significant effect on employee satisfaction (β = .24, p b .05). Thus, H9 is supported. The CCB × likeability interaction has a positive and significant effect on employee satisfaction (β = .33, p b .01), thereby supporting H10.

4. Study 2: experiment Establishing the causal nature of the relationship between customer behaviors and employee outcomes in a cross-sectional survey like Study 1 is difficult. Thus, this study is a laboratory experiment. If the manipulation of customer behaviors directly influences employee behaviors, then H1–H6 receive further support for causal direction.

Table 4 Tests of the moderating effects. Dependent variable: employee satisfaction Independent variable

Standardized coefficients

t-values

Main effects CPB CCB Similarity Likeability

.27 .12 .18 .07

(2.38)⁎⁎ (1.96)⁎ (1.45) (.56)

.24 .03 .24 .33

(1.92)⁎ (.16) (1.82)⁎ (2.33)⁎⁎

Interaction effects CPB × Similarity CCB × Similarity CPB × Likeability CCB × Likeability

H7 H8 H9 H10

Notes: CPB = customer participation behavior; CCB = customer citizenship behavior. ⁎ p b .05, one-tailed. ⁎⁎ p b .01, one-tailed.

4.1. Participants and design This study used a 2 × 2 between-groups design with two levels of customer participation behavior (high vs. low) and two levels of customer citizenship behavior (high vs. low). One hundred and six part-time MBA students were recruited, and they were randomly assigned to the 4 treatment levels. Sixty-eight percent of the participants were male, their average age was 29 years, and they had an average of four years of business experience. 4.2. Procedure and manipulations Upon arrival, participants were provided with an experimental package. Participants were exposed to the manipulations, provided ratings, were debriefed and released. The scenarios describe hypothetical situations in which participants are frontline service employees who are responsible for customer service and visit their customers regularly. In the high CPB condition, the activities of customers are depicted as performing all the tasks that are required of them. In contrast, in the low CPB condition, the activities of customers are depicted as lacking willingness to engage in fulfilling their responsibilities as customers. In the high CCB condition, activities of customers are depicted as being active in providing suggestions and feedback to the employee, giving the employee full cooperation, and promising to say positive things about the employee to others. In contrast, in the low CCB condition, activities of customers are depicted as exhibiting low levels of voluntary citizenship behavior toward the employee. After reading the manipulations, participants were asked to indicate their performance, satisfaction and commitment toward their job on a set of rating scales from the perspective of an incumbent of that job. These measures are basically the same as those used in Study 1 and slightly modified to fit the purpose of the current research. Furthermore, the questionnaire includes manipulation and realism check items. 4.3. Manipulation and realism checks The manipulation effectiveness was assessed using the following items: “The customer performs all the tasks that are required of him/ her,” and “The customer performs all expected behaviors adequately” with seven-point scales ranging from “strongly disagree” (1) to “strongly agree” (7) (α = .95). An analysis of variance (ANOVA) of the composite score supports the effectiveness of the manipulation (MhighCPB = 5.71, Mlow-CPB = 2.66; F(1,104) = 198.43, p b .001). Likewise, customer citizenship behavior manipulation was tested using two items: “How frequently does the customer engage in tasks that are not formally required of him/her?” (1 = “not at all frequently” to 7 = “very frequently”) and “To what extent are the customer willing to go above and beyond his/her call of duty?” (1 = “not at all willing” to 7 = “very willing”) (α = .93). Again, results show that the manipulation was effective (Mhigh-CCB = 5.46, M low-CCB = 2.10; F(1,104) = 192.36, p b .001). The realism of experimental design was also checked using two items: “I could imagine an actual workplace situation described in the scenario,” and “I believe that the described situation could happen in real workplace” with seven-point scales ranging from “very unlikely” (1) to “very likely” (7) (α = .72) (Wagner et al., 2009). The results suggest that participants perceived the experimental design as realistic (Mcomposite score = 5.37, SD = 1.35). 4.4. Results Results for the effects of customer participation behavior and customer citizenship behavior on employee performance, satisfaction, and commitment appear in Table 5; cell means are in Table 6.

Y. Yi et al. / Journal of Business Research 64 (2011) 87–95 Table 5 Effects of customer behavior measures and employee-related outcomes.

Independent variables

MANOVA results

Univariate F values

Wilks' λ F value

Employee Employee Employee performance satisfaction commitment

Customer .54 participation behavior (CPB) Customer .55 citizenship behavior (CCB) CPB × CCB .84

21.43⁎⁎⁎ 66.34⁎⁎⁎

47.26⁎⁎⁎

35.55⁎⁎⁎

19.93⁎⁎⁎ 48.18⁎⁎⁎

35.88⁎⁎⁎

48.35⁎⁎⁎

.32

.71

4.70⁎⁎

15.54⁎⁎⁎

⁎p b .05. ⁎⁎p b .01. ⁎⁎⁎p b .001.

Multivariate effects of customer participation behavior (Wilks' lambda = .54, F = 21.43, p b .001) and customer citizenship behavior (Wilks' lambda = .55, F = 19.93, p b .001) are significant. The interaction between customer participation behavior and customer citizenship behavior is also significant (Wilks' lambda = .84, F = 4.70, p b .01). Follow-up univariate analyses reveal that customer participation behavior has a significant effect on employee performance (F (1, 102) = 66.34, p b .001), employee satisfaction (F(1, 102) = 47.26, p b .001), and employee commitment F(1, 102) = 35.55, p b .001). The results also show a significant main effect of customer citizenship behavior on employee performance (F(1, 102) = 48.18, p b .001), employee satisfaction (F(1, 102) = 35.88, p b .001), and employee commitment F(1, 102) = 48.35, p b .001). In addition, customer participation behavior interacts with customer citizenship behavior to influence employee performance (F(1, 102) = 15.54, p b .001). However, customer participation behavior does not interact with customer citizenship behavior to influence employee satisfaction (F (1, 102) = .32, p N .10) and employee commitment (F(1, 102) = .71, p N .10). 5. Discussion This study develops and tests a conceptual model of how customer behaviors influence frontline service employees. This study applies a PLS structural equation modeling to the field data consisting of 332 customers, 142 FSEs, and 31 managers. Consistent with the social cognitive theory, results of this investigation suggest that customer participation behavior has direct, positive effects on employee performance, satisfaction and commitment. The results also indicate that customer citizenship behavior has direct, positive impacts on employee performance and commitment. In turn, these employee variables decrease turnover intention. Among the hypotheses that have not been confirmed, this study expected that customer citizenship behavior would increase employ-

Table 6 Cell means and standard deviations.

Employee performance Employee satisfaction Employee commitment Cell sizes

Low customer participation behavior

High customer participation behavior

Low customer citizenship behavior

High customer citizenship behavior

Low customer citizenship behavior

High customer citizenship behavior

3.12 (1.29) 2.71 (.84) 2.90 (.91) 26

5.23 (.93) 4.08 (.92) 4.50 (.94) 24

5.47 (.88) 4.27 (1.26) 4.30 (1.29) 27

6.05 (.83) 5.40 (1.19) 5.56 (1.03) 29

Notes: Standard deviations are in parentheses.

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ee satisfaction. One explanation for the lack of a significant relationship may be that the present study restricted its focus to beneficial customer behaviors. However, customer behaviors can also take a negative form, such as negative word-of-mouth, uncooperative, and unprovoked behavior (Bettencourt, 1997; Groth, 2005; Yi and Gong, 2008). As a result, in reality, such dysfunctional customer behaviors can cause great damage to FSEs, which might then negatively affect their satisfaction. This study makes several significant and theoretical contributions. Although a lot of service scholars mention the importance of customer behavior in service co-creation, little research exists on how customer behavior affects employees. This research contributes to the social cognitive theory by proposing and empirically establishing a link between customer behaviors (i.e., customer participation and citizenship behavior) and employee outcomes (i.e., performance, satisfaction, and commitment). This study answers the calls for research on the link between customer behaviors and firm performance. Indeed, Bowen and Schneider (1988, p. 72) note that “the consequences of customer contact and participation for individual employee satisfaction and productivity are less well understood.” This research also attempts to determine experimentally how customer participation and citizenship behavior influence employee attitude and behavior. An important finding is that the manipulated customer participation and citizenship behavior cause significant differences in employee performance, satisfaction, and commitment. This study is one of the very few empirical tests of this causality issue. The present research demonstrates that the relationship between customer behaviors and employee satisfaction varies across relational contingencies. Specifically, this research shows that the relationship between customer participation behavior and employee satisfaction is particularly strong in the case of a high level of similarity and likeability with respect to customers. The relationship between customer citizenship behavior and employee satisfaction is also strong when customers are likeable. This study also makes a methodological contribution by collecting a matched triadic sample avoiding the potential for common method bias, while using appropriate respondents to obtain valid assessments of the variables. Indeed, as Edwards (2008, p. 476) notes, “common method variance is problematic because … [it] inflates the relationships among measures, such that the actual relationships among the underlying constructs are smaller than they appear.” The use of data from separate sources in this study should prevent common method bias. The findings also yield several managerial implications. Given the crucial impact of customer behaviors on employees, managers should motivate customers to reveal participation and citizenship behavior in order to improve employee performance and firm performance. Companies should view customers not as passive audience but as active partners in service delivery. Such perspectives reflect the recent move from “What can we do for you?” to “What can you do with us?” (customer participation behavior) (Bendapudi and Leone, 2003), or even to “What can you do for us?” (customer citizenship behavior). The present article demonstrates that focusing on customer behaviors is a managerial imperative. Firms can apply the employee management practice to customers, enhancing customer role clarity (customers knowing what is expected of them), motivation (being motivated to engage in desired behaviors), and ability (to fulfill their responsibilities). Also, rewarding customers for a job well done in service co-creation and delivery could be useful. For example, managers could restructure customer reward programs to reinforce participation behavior as well as citizenship behavior. Such effective customer behavior management could increase employee performance and satisfaction and could create a competitive advantage for firms. Managers should carefully select, train and socialize customers, just the same as the firm would do with respect to employees. Managers

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should also provide customers with empowerment and resources to serve employees or other customers successfully. Furthermore, firms need to develop and establish effective mechanisms for controlling customer behaviors. Communication for customers might be helpful in this respect. Indeed, effective communication between customers and employees can yield successful customer behavior management, because managers can recognize customer needs and expectations better. The results show managers how to strengthen the positive effects of customer participation behavior on employee satisfaction, as well as those of customer citizenship behavior on employee satisfaction. This study reveals that these positive relationships may change, depending on similarity and likeability of customers. Firms may benefit by paying more attention to relationship characteristics when assigning customers to employees. Indeed, both employees and customers need to devote more time, effort, and energy to managing their various relationships, which is critical to the development of cocreating services. The results also suggest the importance of pairing employees and customers based on similarity. This requires that a firm look at points of similarity between the two. Where might these arise? In rural communities, ensuring that customers deal with FSEs from the same area might facilitate this. Some telecommunications companies ensure that call center requests are handled by employees from the same area as the customer. Likeability may mean segmenting the customer base according to the preferences of employees. As a first step, managers should discuss with FSEs about what customer behaviors are good for the firm, good for the relationship, citizenship-like, or even harmful. Despite the usefulness of this study, the research has limitations. First and most significantly, the present research needs to articulate the longitudinal and circular feedback loop effects that are likely to occur in the model. Although gathering multi-wave data from matched pairs of managers, employees, and customers is a substantial challenge, such data would greatly help address reciprocal or directional relationships among the variables. Second, further research could also investigate the effects of customer behaviors on objective performance data of the firm, such as sales, profits, market share, shareholder value and financial performance. In principle, customer participation behavior and customer citizenship behavior should increase the financial performance of a firm. However, little research has explored how customer behaviors affect specific financial measures of marketing effectiveness. Customer behaviors may increase firm productivity by enhancing the effectiveness of services co-creation. Third, future research should examine the impact of customer behavior on employee satisfaction, commitment and performance while controlling for the direct impact of the environment and rewards that the organization provides to its employees so that the effects of customer behavior can be interpreted as beyond the effect of other organization-related factors. Finally, the present study regards employee commitment as onedimensional. However, many researchers adopt employee commitment as a multidimensional construct. Therefore, future research might investigate the effects of different commitment sub dimensions (e.g., affective, continuance, and normative commitment). In addition, this research measures employee commitment to the firm only. However, the effects of customer behaviors may be directed at employee commitment to profession, career, and occupation. Thus, an important avenue for future research would be to measure the more appropriate targets for gaining employee commitment. Acknowledgements The authors thank Hoseong Jeon and Daniel Sersland for constructive comments on the earlier version of this manuscript.

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Journal of Business Research 64 (2011) 96–102

Contents lists available at ScienceDirect

Journal of Business Research

What motivates consumers to participate in boycotts: Lessons from the ongoing Canadian seafood boycott Karin Braunsberger a,⁎, Brian Buckler b,1 a b

University of South Florida St. Petersburg, College of Business Administration, 140 Seventh Avenue South, Bayboro Station 306, St. Petersburg, FL 33701-5016, United States Avila University, School of Business, 11901 Wornall Road, Kansas City, MO 64145, United States

a r t i c l e

i n f o

Article history: Received 10 February 2009 Accepted 15 December 2009 Keywords: Consumer boycott motivations Canadian Seafood Boycott

a b s t r a c t Despite the tremendous growth in consumer boycotts, marketing has paid relatively little attention to consumer boycott motivations. Addressing this deficiency, this study uses netnography to investigate boycott motivations and perceived boycott participation costs by analyzing consumer comments submitted to an online boycott petition. The results show that boycott pledgees explicitly express their desire for the target to abolish its egregious behavior, their anger about the behavior in question, and their desire for punitive actions. Signatories also pledge participation for moral reasons and identify with the cause reflected by the boycott. Boycott motivations also include the belief that consumers have the power to impact the boycott target's bottom line and/or behavior as well as the belief that the boycott will succeed in forcing the target to cease its egregious behavior. Signatories, however, rarely refer to the costs of boycott participation. © 2009 Elsevier Inc. All rights reserved.

1. Introduction A boycott occurs “when a number of people abstain from purchase of a product, at the same time, as a result of the same egregious act or behavior, but not necessarily for the same reasons” (John and Klein, 2003, p. 1198). This egregious behavior can either directly impact the wellbeing of the boycotter or cause harm or injustice to a third party (Friedman, 1999). Thus, consumers participate in boycotts to express severe dissatisfaction with a company or country's actions and/or policies (Shaw et al., 2006). Recent boycotts seem to focus on establishing “political or social/ethical control” over the boycott target and on trying to force the target to change or abandon behaviors that are deemed to be unethical or socially irresponsible (Sen et al., 2001, p. 400). Although there has been increased interest in consumer boycotts (Cromie and Ewing, 2009; Lee et al., 2009), “the factors that motivate individual boycott decisions remain largely unexplored” (Hoffmann and Műller, 2009, p. 239). Here, motivation is defined as “the desire or want that energizes and directs goal-directed behavior” (McNair-Connolly et al., 2009, p. 26). This lack of research is unfortunate because the number of boycotts and the number of consumers participating in them has been increasing (Sen et al., 2001) from 18% in 1992 (Miller et al., 1992) to almost 67% in 2005 (Glickman, 2005) in the U.S. alone. This

⁎ Corresponding author. Tel.: +1 727 873 4082; fax: +1 727 873 4192. E-mail addresses: [email protected] (K. Braunsberger), [email protected] (B. Buckler). 1 Tel.: +1 816 501 3723; fax: +1 816 501 2463. 0148-2963/$ – see front matter © 2009 Elsevier Inc. All rights reserved. doi:10.1016/j.jbusres.2009.12.008

increase is partially attributed to the widespread adoption of the Internet which has become an inexpensive and quick way of educating millions of consumers about boycotts (Glickman, 2005) and has helped to facilitate the pervasiveness and power of boycotts (Yuksel and Mryteza, 2009). Although over 40% of Fortune 50 companies may be boycott targets at any given time (John and Klein, 2003), marketing managers and policy makers often have little understanding of consumer protest behavior in general, and boycott motivations specifically (Yuksel and Mryteza, 2009). Consequently, the main purpose of this investigation is to study consumer boycott motivations by exploring consumer intent to participate in an ongoing boycott as well as the perceived costs of boycotting. Empirical research focusing on consumer boycott motivations generally utilizes consumer surveys or laboratory experiments (Hoffmann and Műller, 2009; Sen et al., 2001), whereas only one study to date uses a qualitative technique (Kozinets and Handelman, 1998). Since examination of boycotts should place “more reliance on qualitative research methods” … “to supplement the survey methods already in use” (Friedman, 1999, p. 31), one of the major contributions of this research is that it provides—to date—the most comprehensive examination of consumer boycott motivations that utilizes a qualitative approach. The boycott chosen for this investigation, the Canadian Seafood Boycott, began on March 29, 2005, the first day of the spring seal hunt that year. This boycott was called to force a permanent end to the Canadian seal hunt. The Canadian fisheries are the primary boycott target because seal hunters are generally fishermen—90% of whom live in Newfoundland—who hunt seals to earn off-season income. The boycott petition, however, is directed at the Canadian Government because it regulates the hunt and has the power to end it (Harpseals.org, 2007).

K. Braunsberger, B. Buckler / Journal of Business Research 64 (2011) 96–102

2. Success of consumer boycotts According to the business press, boycotts are often successful in forcing the boycott target to change an egregious behavior. This perception is probably due to a number of high-profile boycotts that have led to “spectacular successes for relatively powerless groups” (Klein et al., 2004, p. 92), such as the Montgomery bus boycotts, the 1965–70 California grape boycott (Friedman, 1999), and the boycott of Shell, which had a participation rate of only 6%, but prevented the company from sinking at sea its Brent Spar oil platform (Clouder and Harrison, 2005). Although the literature appears replete with success stories, determining the impact of a boycott is difficult, partly because few targets publicly admit that their revenues and profits have been adversely affected (John and Klein, 2003). An exception is the case of Danish dairy giant Arla Foods which became a target of widespread boycotts in the Muslim world approximately six months after a Danish newspaper printed a series of caricatures depicting the prophet Muhammad. Arla Foods' annual sales were reduced from $430 million to practically zero in just a few days (Ettenson et al., 2006). This might be the reason why 33% to 50% of companies targeted by a boycott adjust their behaviors when facing a boycott threat or launch (Davidson et al., 1995; Friedman, 1985). 3. Consumer boycott motivations 3.1. Instrumental boycott motivations Friedman (1999) theorizes that one of the major boycott motivations is the instrumental motivation of desiring to force the boycott target to change or discontinue the egregious behavior. Consequently, we examine whether individuals who pledge boycott participation will, without being prompted to specifically address certain boycott motivations, explicitly discuss this desire to effect social change. The widespread adoption of information and communication technologies has made information much more available and empowered consumers to hold companies accountable for their egregious acts and/or force organizations to change their behavior. This development has led to an increase in consumer sovereignty (Klein et al., 2004), “the power of consumers to determine, from among the offerings of producers of goods and services, what goods and services are and will be produced and capitalized” (Shaw et al., 2006, p. 1052). We investigate whether boycott pledgees seem aware of their sovereignty and believe that they can yield considerable power over organizations. The purpose is to explore whether consumers are confident that they—as individuals—have the power to make a noticeable impact that is likely to aid in forcing the desired change. This motivation is related to “high perceived efficacy,” defined by Sen et al. (2001, p. 402)) as a consumer's belief that each boycotter can, by him/herself, “make a difference to the boycott's outcome,” and less contingent on the belief of whether other consumers are likely to join the boycott. Sen et al. (2001) find that consumers who believe that a boycott is likely to succeed in forcing the boycott target to change its egregious behavior are more likely to participate in that boycott. This belief may be influenced—in addition to perceived efficacy—by consumer expectation of overall boycott participation. Thus, we investigate whether boycott pledgees appear motivated to participate in a boycott because they believe that it will succeed in forcing the boycott target to change or discontinue an egregious behavior and why they hold this belief.

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might participate in a boycott simply to express their anger about the egregious behavior (Friedman, 1999). Anger can be a more powerful boycott motivation than the belief that a boycott can coerce the target to change its policies and behaviors (Ettenson and Klein, 2005) as demonstrated by the Muslim boycott of Danish companies. Thus, we investigate whether boycott participation can be the result of expressive motivations. Consumers may also be motivated to participate in a boycott because they wish to punish the boycott target for having committed an irreversible act (Friedman, 1999). Klein et al. (1998, p. 90), who study the impact of consumer animosity toward a foreign country on products manufactured in that country, find that consumers tend to shun products from countries that have “engaged in military, political, or economic acts that a consumer finds both grievous and difficult to forgive.” Hence, we explore whether boycott participation seems to be provoked by punitive motivations. Klein et al. (2004) find that consumers boycott because of a desire for self-enhancement, which is driven by a multitude of psychosocial variables. Boycott participation can enhance social self-esteem because it allows boycotters to identify with the social group that fights the egregious behavior or the cause that prompted the boycott (i.e., stopping cruelty to animals). Accordingly, we examine whether boycott pledgees seem driven by a desire to boost social self-esteem. Personal self-esteem, another psychosocial variable, can be enhanced because boycott participation allows an individual to view him/herself as a moral person. This is important if consumers believe that “certain brand management policies have a negative impact on society” (Lee et al., 2009, p. 172). The need to perceive oneself as a moral person is likely to lead consumers to believe that it is their moral duty and personal responsibility to disassociate from the boycott target and that participating in the boycott is the right thing to do (Shaw et al., 2006). Thus, we probe whether boycott pledgees seem motivated by a desire to increase personal self-esteem. A psychosocial variable that negatively impacts self-enhancement is the feeling of guilt (Klein et al., 2004), the “negative emotion which results from a consumer decision that violates one's values or norms” (Burnett and Lunsford, 1994, p. 33). To avoid this feeling, consumers are motivated to refuse purchasing the boycott target's products, even if the target cannot change the egregious act (John and Klein, 2003). Hence, we examine whether boycott pledgees seem motivated by a desire to avoid feeling guilt. 3.3. Costs of boycotting It has been found that there are costs associated with boycotting that impact consumer willingness to participate. The higher a potential boycotter considers these costs to be, the less likely s/he is to participate (Klein et al., 2004). Consumers seem more likely to participate in a boycott if the targeted product has satisfactory substitutes (Sen et al., 2001). Another cost that might be of relevance is the perception of how difficult it will be to identify the targeted product and its substitutes. Here the country-of-origin labeling legislation that was introduced in the U.S. in 2004 might act to minimize this cost. Consequently, we investigate whether boycott pledgees appear more likely to participate in boycotts if they believe that there are satisfactory substitutes available for the targeted product and/or that it is fairly easy to identify the targeted product and its substitutes. 4. The Canadian seafood boycott

3.2. Noninstrumental boycott motivations 4.1. Commercial sealing in Canada Noninstrumental motivations may not only be independent from the desire to change the boycott target's behavior, they can also be the manifestation of an “individual act,” independent from the desire to have others participate (John and Klein, 2003, p. 1203). Consumers

Five nations allow the hunt of seals for commercial purposes, namely Norway, Russia, Greenland, Namibia, and Canada; all of these hunts have been controversial (PACE, 2006). Although several seal

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K. Braunsberger, B. Buckler / Journal of Business Research 64 (2011) 96–102

species are hunted in Canada, the Northwest Atlantic harp seal is the major target of the annual seal hunt (Fisheries and Aquaculture Management, 2002). Though harp and hooded seals in Canada can be commercially hunted from November 15 to May 15, the majority of sealing normally begins in early March and extends to May 15. It is this spring season—generally referred to as the Canadian Seal Hunt— that attracts the most attention. The total allowable catch was 335,000 for 2006, 270,000 for 2007, and 275,000 in 2008 (CBC News, 2008).

restricted to the U.S. market, yet exports to other countries did not experience such a pronounced drop, the boycott probably has had an effect (Harper 2007); especially considering that total U.S. imports of edible fishery products increased from $11.3 billion in 2004 to $13.4 billion in 2006 (or by 18.58%) (NOAA, 2007). This reasoning is further supported by the increase in total Canadian exports to the U.S. from $350.576 billion CAD in 2004 to $361.442 billion in 2006 (or 3.1%) (Statistics Canada, 2009).

4.2. The first seal war

5. Methods

The “official” beginning of the anti-sealing movement can be traced to 1964, when the production company Artek, commissioned by the Quebec Government and the Canadian Broadcasting Corporation, produced a film that focused on the seal hunt. The film, Les Phoques (The Seals), included “a scene in which a seal is skinned alive and its carcass left flailing on the ice” (Canadian Geographic, 2000). As the film made its way across Europe and the U.S., public outcry was immense and brought anti-hunt expeditions to the ice. The antisealing movement kept growing, and the European Community (EC) banned the import of whitecoat (harp seal pup) and blueback (hooded seal pup) pelts in 1983. This led to a collapse of the seal pelt market, and the Canadian Government restricted the hunting of seal pups in 1987 (Canadian Geographic, 2000). Hence, whitecoats and bluebacks can no longer be hunted until they begin moulting (i.e., shedding), which begins at ages 10 to 14 days for whitecoats, and 15 to 16 months for bluebacks (Fisheries and Aquaculture Management, 2002). This measure reduced sealing, but it never completely stopped.

5.1. Research methodology

4.3. The second/current seal war Although Canadian Fisheries Minister Brian Tobin announced the revival of the seal hunt on December 18, 1995 (International Marine Mammal Association, 1995), and significant government subsidies were used to rebuild the industry (Canadian Institute for Business and the Environment, 2001), the seal war did not heat up again until the early 2000s. Since then it has led Canadian politicians to charge governments, NGOs, celebrities, and consumers who oppose the seal hunt of being ignorant and uninformed (CBC News, 2006; CBC News, 2007). Considering that marketing theory and practice generally focus on satisfying consumer needs and wants, such harsh reactions by government officials to U.S. consumers—one of Canada's most important target markets—are puzzling and counterproductive, especially since sealing contributes very little to the value of the Newfoundland fishery (CBC News, 2008; DFO, 2007). The value of the hunt has been estimated at 0.06% to 0.09% of the gross domestic product (GDP) of Newfoundland (DFO, 2007; Southey, 1997). Even in 2006, when harp seal pelts brought a record price of $104 CAD each, the contribution of the hunt to the GDP of Newfoundland was reported at 0.12% (DFO, 2007; Government of Newfoundland and Labrador, 2007), and its contribution to Canada's GDP was 0.0022% (CIA, 2007). In contrast, the seafood boycott might prove to be costly. During the first two years of the boycott (i.e., the period of time passed between the day the boycott started and the day the boycott petition that is the focus of the current research was posted online), the sales of snow crabs—which are the main focus of the seafood boycott—fell by $353.6 million CAD, or 36% (Harper, 2007). During the same time period Canadian exports to the U.S. of all non-processed fish on the boycott list (harpseals.org, 2007) fell from $1.291 billion CAD to $1.026 billion CAD (20.53%); while exports of all non-processed fish decreased from $2.336 billion CAD to $2.063 billion (11.67%) (Industry Canada, 2007). Part of the decline in sales numbers was likely due to currency fluctuations, changes in market taste, and increases in transportation costs. However, since these three factors were not

Netnography, the online equivalent of ethnography, was used in securing and analyzing the data for this study. Netnography is based on the premise that consumers are increasingly turning to online communities to gain access to information that is viewed as more objective than information dispensed by corporations (Kozinets, 2002). Netnography can also lead to more timely information than other qualitative techniques, be conducted entirely unobtrusively, and give insights into actual behaviors in natural settings. Further, the process of data collection is cheaper, shortened, and simplified. Since it focuses on the behavior/act—rather than the individual—as the ultimate unit of analysis, the lack of social and demographic cues often associated with online data should not impede trustworthiness (i.e., validity) (Kozinets, 2002). Since its inception by Robert Kozinets in 1998, netnography has increasingly been used in studies ranging from the exploration of cross-cultural ambivalence on brides-to-be through the analysis of postings on intercultural electronic message boards (Nelson and Otnes, 2005) to the identification of new product ideas through the absorption of the knowledge and creativity found in online communities (Jawecki and Fuller, 2009). 5.2. Description of the dataset The textual discourse of the present research is the outcome of an online petition posted on a virtual community that was frequented by over seven million consumers interested in ethical and social issues, including those relating to animal welfare and rights. The petition was posted by the Humane Society of the United States (HSUS) and showed a picture of a sealer poised to club a juvenile harp seal as the seal looked up at him. It informed that of the 325,000 seals killed during the 2006 seal hunt, most were “as young as 12 days of age.” It stated that more than 440,000 consumers had joined the boycott to date, and that snow crab exports to the U.S. had declined by $350 million CAD since the beginning of the boycott. It asked consumers to pledge participation in the Canadian Seafood Boycott. Posted online on March 22, 2007, it reached its stated goal of 50,000 valid signatures on May 20, 2007. Although signatories have to be registered users of the virtual community to sign any of the petitions, they can specify whether they want a petition to publicly display their names. Signatories were asked to declare their country and state of origin, and also to add a message to the Canadian Government explaining why they were pledging to use their buying power to end the seal hunt. By the time the goal of 50,000 valid signatures was reached, individuals from 112 countries had signed the petition. To help streamline the data analysis, we focused on the messages generated by U.S. consumers. Of the 50,000 consumers, 46,228 originated from the U.S, and 17,525 of these left a message for the Canadian Government. Of these messages, 2018 were left by consumers who chose to remain anonymous; 15,478 by consumers who identified themselves; 29 were either unrelated or pro-sealing. Although the HSUS did not ask consumers to provide demographic data, some of the comments show that signatories come from varied age groups, educational and professional backgrounds. There are a

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number of signatories who identify themselves as members of the clergy, Ph.D.s, MDs, and DVMs. Others report that they own or manage companies and no longer buy Canadian supplies; some are in the travel business and steer clients away from vacations in Canada; and some are teachers and college professors who have committed to educating their students about the seal hunt. 5.3. Data analysis The data were coded and analyzed using Atlas.ti, Version 5.2. A random sample of 1200 of the 17,496 boycott pledges generated by U.S. consumers was used for the data analysis. One of the goals of the analysis was to use content analysis to identify key word(s) that represent a certain boycott motivation. For example, signatory 1 expressed “disgust.” Since the word “disgust” is commonly used to communicate repulsion, outrage, and distress (http://www.merriamwebster.com/), it was categorized as signifying an expressive boycott motivation and all pledges within the dataset that displayed the word were categorized accordingly. Following this method, we carefully read each of the 1200 statements to search for words that commonly signify this type of boycott motivation. We followed this process for all ten of the previously identified boycott motivations. Thus, we spent six very intensive weeks reading each of the 1200 messages several times and iteratively analyzed all messages for expected (and evolving) themes (Kozinets and Handelman, 2004) while tallying frequencies and percentages for all ten boycott motivations (see Table 1). Here we used the iterative process of qualitative data analysis as outlined by Glaser and Strauss (1967), which has frequently been used when analyzing netnographic data (Kozinets and Handelman, 1998; Nelson and Otnes 2005). Do individuals explicitly state that they are motivated to participate in boycotts because they desire to force the boycott target to change or discontinue an egregious behavior? A total of 842 of the 1200 (70.17%) consumers do ask explicitly for an end to the seal hunt. Some signatories focus solely on this desire, such as signatory 671 (female), who maintains: “Stop the killing of these seals!” Other signatories disclose additional boycott motivations. Signatory 32 (male), for example, exclaims: “I will NEVER purchase anything from Canada again ... I will convince my friends to also boycott all Canadian products until the murders of innocent lives is stopped.” Are individuals motivated to participate in boycotts because they believe that they—as individuals—have the power to make a noticeable impact that is likely to force the boycott target to change or discontinue an egregious behavior? Only one of the signatories states that she does not believe that her participation will make any difference, although it does not stop her from joining (signatory 165, end of this section); whereas 365 (29.67%) of the 1200 signatories

Table 1 Stated boycott motivations. Motivation

Frequency Percentage n = 1200

Want to end the seal hunt Believe they have the power to force an end to seal hunt Believe that the boycott will force an end to the seal hunt Wish to express their anger Wish to punish the boycott target Enhance social self-esteem through identification with the cause Enhance personal self-esteem by viewing themselves as moral persons Avoid feeling of guilt that would be associated with purchase of targeted product Believe that the targeted product has satisfactory substitutes Believe that targeted products and substitutes are easy to identify

842 365 225 675 263 529

70.17 29.67 18.75 56.25 21.92 44.08

854

71.16

2

.17

5

.42

5

.42

99

voice the belief that they have the economic power to impact the boycott target's revenue and/or actions. Signatory 614 (female) refers to the economic power she believes to wield: “I am an American consumer and by that I have a purchasing power that is both feared and wanted by other countries as well as my own ... I will boycott all Canadian products...” Are individuals motivated to participate in boycotts because they believe that a boycott will succeed in forcing the boycott target to change or discontinue an egregious behavior? Of the 1200 pledgees, 225 (18.75%) clearly express the belief that the boycott will be successful. Signatory 297 (female) trusts in the power of the many to make a difference: “As long as you continue the barbaric practice of slaughtering seals, I will never purchase seafood from Canada, nor will I ever visit your country. You're probably of the opinion that one person cannot make a difference. However, there are [a lot] more people that agree with me than agree with you, so eventually you will feel the effects of your brutality...” Are individuals motivated to participate in boycotts because they wish to express their anger about a boycott target's egregious behavior? Of the 1200 signatories, 675 (or 56.25%) voice their anger. Signatory 1172 (female) exclaims: “I am more than angry about the slaughter of these babies after gathering petitions in the 1970s to end this brutal practice. This must end once and for all. I will not buy seafood from Canada and plan to encourage everyone I know to do the same.” Are individuals motivated to participate in boycotts because they wish to punish the boycott target for having engaged in irreversible, egregious behavior? Of the 1200 signatories, 263 (21.92%) want to penalize the Canadian Government and/or fishermen. Signatory 433 (female) appears to be so angry that she wants to punish the Canadian economy: “The Canadian govt. needs to stop these barbaric killers. Is there anything else we can boycott from there and let them know it is because of the seal killing[?]. I would be willing to cut off buying everything imported from there to accomplish that. [Let's] hit them back where it will hurt them, instead of the poor innocent babies they are allowing to be slaughtered. The blood on their hands needs to be shown to the whole world. To hell with just a seafood boycott, boycott Canada, period!!!” Are individuals motivated to participate in boycotts because participation leads to enhanced social self-esteem through identification with either other consumers who support a boycott and/or with the cause that has ignited a boycott? A total of 529 (44.08%) of the 1200 signatories address issues related to social self-esteem. Signatories appear more likely to identify with the cause than other consumers or organizations who fight the seal hunt. References to animal cruelty, animal abuse, the seals' right to live in peace, and refuting sealers' right to kill are prevalent. Signatory 434 (male) is very representative: “I refuse to support any kind of animal cruelty-it needs to stop!” Are individuals motivated to participate in boycotts because participation leads to enhanced personal self-esteem by allowing them to view themselves as moral persons doing the right thing? Here, 854 (or 71.16%) of the 1200 signatories state that they cannot support the seal hunt out of moral reasons. Statements such as that made by signatory 30 (gender unknown) are common: “I am horrified to learn that Canada continues with the cruelty and brutality of the seal hunt. In good conscience I cannot buy [Canadian] products or travel to Canada until this horrible hunt is ended forever.” Are individuals motivated to participate in boycotts because participation allows them to avoid feelings of guilt that would be associated with the purchase of the targeted product(s)? Only two (or 0.17%) of the 1200 signatories address this issue. Signatory 165 (female) states: “I'm not sure I really understand the point. There are enough animals already being killed that we eat every day, why the seal? Not that it matters for me speaking up, but if I don't I would feel like what if my say did matter.” And signatory (1181, female) maintains: “I rather not buy Canadian sea food then sit back and watch innocent seals die.”.

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Are individuals more likely to participate in boycotts if they believe that there are satisfactory substitutes available for the product targeted by a boycott and/or that it is fairly easy to identify the product targeted by a boycott as well as its substitutes? The five signatories (0.42%) who express concerns about product substitutes address both issues simultaneously, and it seems they are more concerned with letting the Canadian Government know that they would rather eat no seafood at all than accidentally eat Canadian seafood. Signatory 432 (female) states: “This is sickening to even imagine. I don't really eat red meat or chicken but I have always loved seafood. From now on though, I vow to make sure what I am eating does not come from Canada. If they can't tell me where it's from, I won't eat/ buy it. These creatures do not deserve this. It is not whether they can reason (although I think they can), but whether they can suffer.” 6. Discussion and implications The results of the present research show that consumers who pledge boycott participation do so because they wish the boycott target to discontinue its egregious behavior or policy (70.17%). Further, a fairly high number of signatories (29.67%) inform the boycott target that their individual purchasing power will eventually impact the target's financial bottom line and/or behavior. Shaw et al. (2006) discover a similar attitude and find that consumers have come to view their purchasing power as a vote for or against a specific organization based on its ethical/political behavior. Consumers seem to believe that it is their responsibility to use their dollar votes to enforce desirable ethical behavior, and many apparently consider these dollar votes more effective than votes in political elections. Consumers feel that they are empowered and can influence the actions of domestic and foreign organizations in the market place. Also, 18.75% of the pledgees have no doubt that boycott participation is high and that the collective action of many likeminded individuals will force the boycott target to abandon the egregious behavior. This aligns to Klein et al.'s (2004) findings which show that the greater the number of individuals a consumer believes to participate in a boycott, the more likely the consumer is to boycott as well and the more likely s/he is to think that s/he will be able to make a difference. Our results expand Klein et al.'s (2004) findings by illustrating why consumers may feel that way. Many of the signatories plan to forward the boycott petition to all of their e-mail contacts. Pledgees apparently believe that this snowball-alert system will result in informing large numbers of like-minded consumers about the boycott, substantially increase participation, and ultimately force the target to change the egregious behavior. Pledgees thus display trust and reliance in cyberactivism, which suggests that Fang et al.'s findings (2009) concerning web survey participation might transfer to consumer reaction to online boycott petitions. It seems that consumers who trust the sponsor of an online boycott petition are likely to respond positively to the petition. Online trust is based on consumer awareness of the organization and consumer perception of the organization's reputation (Yoon, 2002). When the HSUS posted the petition it had about ten million members—or one in every 30 persons—and was thus the largest NGO focusing on animal welfare in the U.S. (HSUS, 2007). Many of the pledgees were likely aware of the HSUS and thought highly of its reputation. Thus, trust beliefs in the HSUS could have shaped behavioral intentions, which then may have driven use behavior (see Klein, 2007). The results also show that many pledgees (56.25%) are motivated to participate in this boycott because they wish to vent their anger. The resulting degree of hostility displayed toward the seal hunters, the Canadian Government, and Canada itself, is high. Many of the pledgees expressing their anger state explicitly that they would not consider buying any Canadian products or even visit Canada until the country abolishes the seal hunt. This finding resonates with Ettenson and Klein's (2005) results which show that consumer animosity

toward a specific country is a predictor of willingness to buy that country's products. Even for those consumers who are only mildly angry, animosity still predicts product preferences (Klein, 2002). Of interest to boycott targets and policy makers is that consumers who boycott because they are angry about a country's behavior and policies do not necessarily denigrate the quality of that country's products (Klein et al., 1998), but that those who remain angry even after the egregious policy has been cancelled have a tendency to belittle product quality and remain unlikely to purchase (Ettenson and Klein, 2005). The results further show that 21.92% of the pledgees wish to punish the boycott target for having committed the egregious behavior, and that for many, expressive and punitive motivations go hand-in-hand. For these signatories a seafood boycott is not enough; they wish to penalize the country's overall economy by extending the boycott to other industries and the country itself. Some even name what other Canadian products they used to enjoy and/or considered pertinent to their health, such as hockey gear and games, clothing, and medications. However, they have now moved these items from their shopping to their boycott list. Our findings thus contrast with previous research which shows that consumers are less likely to participate in a boycott if participation results in a sufficiently large sacrifice (Klein et al., 2004). Prior work, however, has aimed to establish the relationship between perceived costs and boycotting by comparing behaviors of non-boycotters and boycotters whereas the current study focuses on consumers who have pledged boycott participation. Apparently, the angrier individuals get about the egregious behavior, the more involved they become in the boycott, and the more they are willing to sacrifice. It almost seems as if this willingness to make a greater sacrifice enhances the value of the public boycott pledge to themselves and others. A majority (71.16%) of pledgees are motivated to participate in the boycott because it allows viewing themselves as moral individuals who are doing the right thing, thereby boosting their personal selfesteem. Consumers are sending a clear message to the boycott target, namely that they feel the need to distance themselves from the target's egregious behavior by refusing to purchase the products sold by the offending industry, or even the whole country. Anything less would be perceived as supporting the behavior in question, in this case the seal hunt. Also, the moral issue at stake—the prevention of cruelty to and the welfare/rights of animals—is one that many signatories explicitly identify with (44.08%) and the pursuit of which further allows pledgees to experience an increase in their social self-esteem. Considering that concern for the welfare and/or rights of animals has been moving more into the mainstream (Zwerdling, 2007), this is an issue companies can expect more and more consumers to tackle. As a case in point, Singer (2006) finds that millions of consumers in Europe and the U.S. are allowing their concern for animal welfare/rights to transform their diets and lifestyles. This number will probably increase since many young people seem to appreciate the efforts from NGOs like People for the Ethical Treatment of Animals (PETA) (Severson, 2007). Signatories are not pledging boycott participation because they are driven by an attempt to avoid feelings of guilt (0.17%), but because they feel so strongly about the cause that being able to perceive themselves as moral individuals is overriding possible thoughts concerning non-participation and negative personal consequences or costs of such an action. This reasoning seems supported by the low number of signatories who address the issues of product identification and substitution (0.42%). The prevention of animal cruelty seems so critical that pledgees do not appear concerned about personal consequences or costs other than “doing the right thing.” These results strongly support Kozinets and Handleman (1998, p. 475) who find that “boycotting serves as a vehicle for moral self-realization” and that this motivation is more important than the experience of consumption. The egregious act is perceived in such a strong negative

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light that pledgees view the benefits of boycott participation as so powerful that no mention is made of any possible sacrifices; nor do the vast majority of boycott pledgees consider any potential costs. The findings of our qualitative study—while in line with Kozinets and Handleman's (1998) qualitative study—contrast expectations and findings of quantitative studies that have addressed the cost of boycotting. For example, Klein et al. (2004) find that the cost of constrained consumption negatively impacts boycott participation. And Sen et al. (2001, p. 411) show that consumers consider costs of boycott participation, both in terms of intrinsic product preferences and substitutability, and are less likely to boycott if perceived costs are high. The latter, however, admit that they “assumed that the boycott decision is largely a rational rather than an emotional one,” whereas our findings show that this particular social-issue boycott appears to be a very emotional one, which could be why consumers ignore cost issues. It could also be that quantitative research is too structured to allow boycott participants to address the full range of emotions they experience, and that qualitative research is needed to more fully research and understand emotional issues that motivate boycott participation. The results also show that consumers who pledge boycott participation can be driven by different boycott motivations and might boycott for a multitude of reasons. Some of the pledgees express their desire for the egregious act to end, while others verbalize their anger and/or wish to punish the target. Likewise, many consumers desire an end to the egregious behavior and also communicate their belief that they will be able to make a difference in the target's bottom line and/or behavior. This result supports Ettenson and Klein (2005) who find that consumers who participate in a boycott express their anger and believe that they will bring about an end to an egregious behavior by displaying that anger. The research design as well as the above discussion illustrate that the present research offers a number of major contributions. First, it is one of the few qualitative studies that investigate consumer boycott motivations. Using netnography has allowed unobtrusive data collection in an environment that is natural for consumers who choose to participate in virtual communities. This has made it possible to investigate boycott motivations as they were actually experienced by consumers, and thus has aided in discovering that the cost of boycotting does not seem to impact consumers as they decide to participate in such an emotionally laden boycott as the Canadian Seafood Boycott, a finding that can be considered a second major contribution of the present study. A third major contribution of this study is that the research design and data analyses have allowed determining to what extent consumer boycott participation is driven by specific boycott motivations (see Table 1). To date, empirical research has focused on identifying consumer boycott motivations, but the present study is the first that has identified the prevalence of each. 7. Limitations and suggestions for future research Although studying actual boycott pledges collected in an unobtrusive manner has its advantages (i.e., dealing with genuine consumer emotions, reactions, and intentions in a natural setting rather than having to elicit and manipulate moral outrage in an artificial environment), it also has its disadvantages. For example, pledgees could not be prompted to directly express attitudes and beliefs concerning the boycott motivations of interest. However, the current study takes prior work one step further by investigating whether boycott motivations established through experimental or survey research hold when intentions are unobtrusively observed. Further, since our study focuses on one specific boycott, its generalizability needs to be addressed. Pledgees seem to feel very strongly about the boycott cause, and future research should investigate whether consumers are likely to feel this strongly about

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