NEW FIRM CREATION IN THE UNITED STATES

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Paul D. Reynolds New Firm Creation in the United States is the most comprehensive and detailed assessment of how new business come about. Based on the first US Panel Study of Entrepreneurial Dynamics (PSED I), this study looked at over 130 factors related to business start-ups and focused on nascent entrepreneurs. Some of its findings include: • • • •

The large number and growth of nascent entrepreneurs Major factors involved in the start-up process and becoming a nascent entrepreneur are unrelated to completion of the start-up process of a successful new firm The activities of the start-up process — not the characteristics — impact the transition from start-up to successful new firm Anybody can do this! Any person with the knowledge, skills, ideas, drive and the ability to mobilize resources and organize a business can create a new firm.

now

This book is originally published as Foundations and Trends® in Entrepreneurship, Volume 3 Issue 1 (2007), ISSN: 1551-3114.

3:1 (2007)

New Firm Creation in the United States: A PSED I Overview Paul D. Reynolds

Paul D. Reynolds

New Firm Creation in the United States shows the value of tracking a representative sample of entrepreneurs in a longitudinal study. The implications for public policy are huge in that efforts to increase new start-ups to improve economic growth may be different to those designed to assist disadvantaged groups develop a role in the economy though entrepreneurship.

FnT ENT 3:1 New Firm Creation in the United States: A PSED I Overview

New Firm Creation in the United States: A PSED I Overview

Foundations and Trends® in Entrepreneurship

now the essence of knowledge

New Firm Creation in the United States

New Firm Creation in the United States Paul D. Reynolds Professor and Director, Entrepreneurship Research Institute Florida International University, Miami, FL 33199 [email protected]

Boston – Delft

R Foundations and Trends in Entrepreneurship

Published, sold and distributed by: now Publishers Inc. PO Box 1024 Hanover, MA 02339 USA Tel. +1-781-985-4510 www.nowpublishers.com [email protected] Outside North America: now Publishers Inc. PO Box 179 2600 AD Delft The Netherlands Tel. +31-6-51115274 Library of Congress Control Number: 2006939972 The preferred citation for this publication is P. D. Reynolds, New Firm Creation R in the United States, Foundation and Trends in Entrepreneurship, vol 3, no 1, pp 1–150, 2007 Printed on acid-free paper ISBN: 1-60198-000-7 c 2007 P. D. Reynolds

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R Foundations and Trends in Entrepreneurship Volume 3 Issue 1, 2007 Editorial Board

Editors-in-Chief: Zoltan J. Acs George Mason University [email protected] David B. Audretsch Max Planck Institut [email protected] Indiana University [email protected] Editors Howard Aldrich, University of North Carolina Sharon Alvarez, Ohio State University Mark Casson, University of Reading Per Davidsson, Queensland University of Technology William B. Gartner, Clemson University Sharon Gifford, Rutgers University Magnus Henrekson, The Research Institute of Industrial Economics Michael A. Hitt, Texas A&M University Joshua Lerner, Harvard University Simon Parker, University of Durham Paul Reynolds, Florida International University Kelly G. Shaver, College of William and Mary David Storey, University of Warwick Patricia Thornton, Duke University Roy Thurik, Erasmus University Gregory Udell, Indiana University Sankaran Venkataraman, Batten Institute Paul Westhead, Nottingham University Business School Shaker Zahra, University of Minnesota

Editorial Scope R Foundations and Trends in Entrepreneurship will publish survey and tutorial articles in the following topics:

• Nascent and start-up entrepreneurs • Opportunity recognition • New venture creation process

• Business angels • Bank financing, debt, and trade credit

• Business formation

• Venture capital and private equity capital

• Firm ownership

• Public equity and IPOs

• Market value and firm growth

• Family-owned firms

• Franchising

• Management structure, governance and performance

• Managerial characteristics and behavior of entrepreneurs

• Corporate entrepreneurship

• Strategic alliances and networks

• High technology

• Government programs and public policy

• Technology-based new firms

• Gender and ethnicity

• Small business and economic growth

• New business financing:

• High-tech clusters

Information for Librarians R Foundations and Trends in Entrepreneurship, 2007, Volume 3, 4 issues. ISSN paper version 1551-3114. ISSN online version 1551-3122. Also available as a combined paper and online subscription.

R Foundations and Trends in Entrepreneurship Vol. 3, No 1 (2007) 1–150 c 2007 P. D. Reynolds

DOI: 10.1561/0300000010

New Firm Creation in the United States A PSED I Overview Paul D. Reynolds Professor and Director, Entrepreneurship Research Institute, Florida International University, Miami, FL 33199, [email protected]

Abstract The first US Panel Study of Entrepreneurial Dynamics [PSED I] is the most comprehensive assessment of the firm creation process yet completed. Based on a representative sample of those actively involved in business creation, analysis begins with the consideration of 75 factors that may affect the decision of adults to get involved in the creation of a new business, followed by a detailed exploration of over 130 factors that may be associated with completing the start-up process with a new firm. The results indicate, first, that over ten million persons are involved in the firm start-up phase as nascent entrepreneurs. Second, the major factors associated with entry into the start-up process have little impact on completion of the process with an operating business. Third, activities pursued in the start-up process – not the characteristics of the entrepreneur, the start-up, or the location – have a major impacts on the transition from start-up to a successful new firm. There is little impact associated with being male; being White, Black or Hispanic; having more education; being wealthy; having experience with other start-ups; having an “entrepreneurial personality”; or being in a

supportive environment. This project demonstrates the value of tracking a representative sample of nascent entrepreneurs with a longitudinal study. Implications for future research, entrepreneurs, and public policy are substantial.

Contents

1. Introduction

1

1.1. How Do New Businesses Come About? 1.2. An Author’s Personal View

1 2

2. New Firm Creation: Importance and Need for More Details

7

2.1. What Does the Start-Up Process Look Like?

9

3. Conceptualization of the Process

13

3.1. 3.2. 3.3. 3.4. 3.5.

15 17 21 23

3.6. 3.7. 3.8. 3.9.

Socio-Cultural Characteristics Stable Personal Traits and Orientations Immediate Personal, Social Context Work Related Experiences Procedures, Strategies, and Resources Associated with Firm Implementation Ambient Social, Cultural Community Context Industry and Competitive Context Regional Characteristics and Change Overview ix

25 29 31 32 32

4. Becoming a Nascent Entrepreneur: Conception to the Start-Up Process

35

4.1. 4.2. 4.3. 4.4. 4.5.

35 36 42 48 53

How Many People are Trying to Start New Firms? What Kind of People are Trying to Start New Firms? Life Context and Start-Ups Comparison Group Data Overview

5. Creating a New Business: Results from the Start-Up

55

5.1. What Kinds of People Create and Types of Start-Ups Become New Firms? 5.2. Start-Up Activity 5.3. Interactions: Who They are and What They are Doing? 5.4. Overview

58 68 76 84

6. Overview and Implications

87

6.1. 6.2. 6.3. 6.4.

90 92 93 93

Implications: Implications: Implications: Implications:

Research Entry Into the Start-Up Process New Firm Creation Public Policy

References

97

PSED I Scholarly Works

99

Acknowledgements

109

A. Methodlogical Appendices

111

Appendix.4Ax.1. Notes on Assessment of the Screening Data Appendix.4Ax.2. Comparison of Nascent Entrepreneurs and Typical Adults Appendix.5Ax.1. Constructing Start-Up Time Lines Data Set

111 112 118

Appendix.5Ax.2. Disposition of All Cases and 72 Month Outcome Status Appendix.5Ax.3. Detailed Comparison of Start-Ups Outcomes: New Firms and Others Appendix.5Ax.4. Constructing Start-Up Activity Indices

122 134 153

1 Introduction

1.1

How Do New Businesses Come About?

The most comprehensive and detailed assessment of this question is the first US Panel Study of Entrepreneurial Dynamics [PSED I]. This project started with the screening of 64,000 US adults followed by four extensive two-phase interviews spread over a five year period. Analysis began with the consideration of 75 factors that may affect the decision of adults to get involved in the creation of a new business – to become nascent entrepreneurs. General comparisons were made of those active in start-ups with others interviewed in the screening and detailed comparisons were possible with a small comparison group. The assessment continued with a detailed exploration of over 130 factors that may be associated with completing the start-up process. This study focuses on understanding how the 200 nascent entrepreneurs that reported a new firm within seven years of entering the start-up process were different from the 468 who quit or continued to work on the start-up. There are a number of significant findings from this research program. First is the large number of individuals involved as nascent

1

2

Introduction

entrepreneurs – 10 million in 1998–1999 when the PSED research project began; as many as 16 million in 2005. Second is the finding that the major factors associated with entering the start-up process and becoming a nascent entrepreneur, such as age, gender, educational attainment, household income or net worth, and residence in a community with recent population growth are unrelated to completion of the start-up process with a successful new firm. The third major finding is that the activities pursued in the start-up process – not the characteristics of the entrepreneur, the start-up, or the location – have an impact on the transition from start-up to a successful new firm. Actions associated with implementing a productive process, developing a presence for the new firm, creating an organizational and financial structure for the firm, during an intense investment of time and money – facilitated by same industry work experience – seems to be particularly important in the birth of a new firm. Most important – and encouraging – anybody can do this. There is no magic associated with being male; being White, Black or Hispanic; having more education; being wealthy; having experience with other start-ups; having an “entrepreneurial personality”; or being in a supportive environment. None of these individual attributes, perceptions or attitudes seem to make much difference once an individual is involved in the start-up process. Any person with the knowledge, skill, ideas, drive, and the ability to mobilize resources and organize a business can create a new firm. This project, though expensive, very labor intensive, and requiring considerable patience, has demonstrated the value of tracking a representative sample of nascent entrepreneurs with a longitudinal study. Implications for public policy are substantial. Efforts to increase the firm birth rate to improve economic growth may not have the same focus as those designed to help disadvantaged groups develop a role in the economy through participation in entrepreneurship.

1.2

An Author’s Personal View

This brief text – brief in terms of the scope and importance of the topic – has been written for two reasons. The first is to provide an overview of

1.2. An Author’s Personal View

3

the nature of the business creation process as it existed in the United States at the end of the 20th century. The second is to make clear the nature and significance of the contribution of the Entrepreneurial Research Consortium, the organization responsible for the implementation of the first Panel Study of Entrepreneurial Dynamics. The Panel Study of Entrepreneurial Dynamics [PSED], as it is now called, was the result of the collective efforts of the Entrepreneurial Research Consortium, led by Nancy Carter, Bill Gartner and me, Paul Reynolds. It eventually involved over 120 individuals and 34 member units and raised $620,000 to implement this research program. These funds were supplemented by two NSF grants, one provided to Nancy Carter (NSF Grant SBR-9809841) for an over-sample of women nascent entrepreneurs and the other to Patricia Green (NSF grant SBR9905255) for an over-sample of minority nascent entrepreneurs. The design was an initial screening to locate nascent entrepreneurs followed by a detailed initial and three follow-up interviews. The project was completed with substantial support from the Ewing Marion Kauffman Foundation after data collection responsibilities were shifted from the University of Wisconsin Survey Research Laboratory, following its closure, to the University of Michigan Institute for Social Research. The final versions of all data sets and descriptions on the public domain website [psed.isr.umich.edu] have been well developed and maintained by Richard Curtin.1 A replication, PSED II, was initiated in 2005 with primary support from the Ewing Marion Kauffman Foundation and supplement funding from the US Small Business Administration.2 There are now dozens of peer reviewed journal articles, working papers, dissertations, scholarly monographs and the like that describe the rationale, research procedures, and analysis of data from PSED I.3 These documents make clear the relevance of the data to a wide range of theories, hypotheses, and hunches regarding various aspects of the 1A

comprehensive overview of the project design is provided by Gartner et al. (2004). is in the form of two grants, one to University of Michigan Institute for Social Research (Richard Curtin, Principal Investigator) to collect data and the other to Florida International University (Paul Reynolds, Principal Investigator) to assist in the design of the project and assessment of results, and to supervise an Advisory Committee. 3 A recent overview of scholarly work reflecting this research paradigm is provided by Davidsson (2006). 2 This

4

Introduction

entrepreneurial or firm creation process. There has not, however, yet been a summary of the major focus of the project, a description of what happens when one or more individuals develop and implement a new firm. That is the focus of this book. It is of some interest why no overview has been completed. There are two procedural reasons and one, which predominates, related to the dysfunctional nature of the scholarly reward system that has developed in the social science research community. The first procedural reason is straightforward, reflecting the complexity of the full PSED I data set. Collecting the data involved screening 64,000 US adults, detailed phone interviews and questionnaires collected four times following the screening interview. The final data file has over 5,000 variables on 1,281 individuals. While many researchers are familiar with parts of the data set, very few are comfortable with the entire mass of items, variables, skip patterns and the like. My role, as the coordinating principal investigator throughout the entire project, has given me a unique perspective and understanding of all major – and many minor – aspects of the project design. It seems useful to provide this description – and a review of the solutions to the many technical issues – before this knowledge is lost. The second procedural reason is time; it took over six years from the inception of the screening interview to the completion of the fourth round of data collection and creation of the final data sets for analysis. As the ERC was organized two years before the screening began, the gap from initial commitment to the capacity for complete analysis was almost a full decade. Many of the original ERC participants have been pursing other research options since the program began and many of the most recent analyses and publications have been completed by scholars who had hardly entered higher education when the project was initially proposed. There has been no effort to provide an overview of the entire project; some of the technical problems that required solution, described in the appendices, indicate why this is a complicated challenge. The third problem is perhaps the most significant. The current scholarly reward system places an almost pathological emphasis on peer reviewed journal publications, and these collective products place

1.2. An Author’s Personal View

5

great emphasis on “theory testing.” In most cases, this is generally in the form of testing isolated hypotheses, hunches, or informed guesses, rather than theorems or propositions derived from an explicit, formalized theory.4 It encourages researchers to pretend they are contributing to a research agenda that has emerged within the scholarly community – reflected in extensive literature reviews – and explicate specific research objectives that can be “tested” with data. This leads to, as in the case of the PSED I data, to a number of unrelated analyses, each dealing with one or more specific processes or hypotheses: Does ethnic status affect entry into the start-up process? Does household wealth affect success at completing the process with a new firm? Does a strong internal locus of control influence firm growth aspirations? The result is a great deal of detail regarding a large number of pieces of the puzzle, but no effort to describe the overall puzzle itself. In the philosophy of science this is referred to as “normal science,” the process of adding bricks to a wall that composes “scientific consensus.” It tends to distract individuals from the larger, more critical, issue of just what the wall is for and why it is being built in a particular location. This is, of course, the underlying issue in the development of new paradigms, as so eloquently explicated by Kuhn.5 PSED I, as the test bed for the Global Entrepreneurship Monitor research program,6 has clearly lead to a new paradigm for the study and understanding of firm creation and the entrepreneurial processes; it would not have occurred were the principals solely focused on “normal science.” This text is designed to provide an overview of the business creation process. This summary has required the resolution of a number of technical and substantive issues in order to provide a comprehensive description of the process itself. The details are provided in the footnotes, endnotes, and appendices. As all of the interview schedules, research procedures and data are in the public domain and available at no charge, other scholars who would like to suggest other solutions 4 An

introduction to forms of theories and basic issues in the creation of scientific knowledge is provided in Reynolds (1971b). 5 Kuhn (1962). 6 The data collection procedures are summarized in Reynolds et al. (2005). Major findings in the first five years are presented in annual reports, available at ‘www.gemconsortium.org’: Reynolds et al. (1999, 2000, 2001, 2002, 2004a).

6

Introduction

to these issues are welcome to plunge into the pool, but it may take a while to learn how to swim in this data set. While the total number of individuals that have contributed to the creation of the PSED I project and the final version of the data set is close to two hundred, the author takes full responsibility for the presentation that follows. There are, as in most significant human endeavors, many mistakes and oversights, but the design developed collectively by the ERC in implementing PSED I seems to have avoided any mistakes that would undermine the value of the basic contribution – provision of the first empirically based description of the creation of a representative sample of new firms. The results can be extrapolated to all new firms begun in the United States in 1998–2000. The impact and repercussions of this project have been enormous and, in most cases, positive.

2 New Firm Creation: Importance and Need for More Details

Every day another 5,000 new firms are created in the United States; another 2 million each year. About a third have employees-called “employer firms” by the Small Business Administration. Most of these new business activities are new sources of traditional goods and services; very few provide unique or innovative goods and services. Some are growth oriented; most are not. New firms are, by and large, considered a good thing, and, in most parts of the world, both people and their leaders celebrate when more new firms emerge. While new firm creation has been underway for thousands of years, very little is actually known about just how the basic elements are assembled to create a new source of goods and services. There are a lot of questions about new firm creation: • Are only special people – with “entrepreneurial personalities” – genetically equipped to start new firms? Do they do this by themselves or is a collective effort – a start-up team – required? • Do some situations, locations or communities provide a more fertile context for new firms? 7

8

New Firm Creation: Importance and Need for More Details

• Are some people in a social context – perhaps a family situation that emphasizes small businesses – that encourages them to create new firms? • How critical is money in the firm creation process? • Is there some special sequence of activities that should be followed to create a new business? • If the business idea is the critical feature of firm creation, how does it come about – is it a spontaneous flash of insight or is it the product of detailed data collection and careful assessment? • How long does the process take, from conception to the birth of a new firm? • What proportion of start-up efforts actually become new firms? • What is the impact of government policy and procedures on firm creation? Can and do government programs help? These are just some of the many questions that receive attention from practitioners, policy analysts, and scholars. The lack of answers to these questions is not due to a shortage of speculation – or theory – about why people start new firms; the amount of writing is substantial – and grows every day. While scientific understanding can be advanced when theories are developed and tested, there are many phenomena where the absence of precise descriptions of the phenomena itself can hamper the development of useful “theories” or “explanations.” It is hard to create a theory that makes precise predictions when “what is to be explained” is vague or amorphous. Regarding firm creation, there has been a lack of reliable information on: (1) Who becomes involved in the business creation process? (2) What they do? (3) Which of them complete the process with a going concern? Ideally this information would be available from a sample that represents the adult population and provides the potential for making

2.1. What Does the Start-Up Process Look Like?

9

estimates about all nascent entrepreneurs and all new firms in the United States. A big step in filling this lacuna was the development and implementation of the first US Panel Study of Entrepreneurial Dynamics [PSED I]. This project was the first large scale attempt to develop a representative sample of the US business creation process. Individuals were identified in the start-up phase and tracked – with follow-up interviews – as they pursued business creation and their efforts resulted in a new firm, disengagement from the start-up process, or a continued effort to create a new firm. This report provides an overview of the major results from this project; it focuses on providing a description of how new firms are created.

2.1

What Does the Start-Up Process Look Like?

The simplest formulation presents firm creation as part of the business life course, which can be considered to have a series of stages, presented in Figure 2.1: conception, start-up process, new firm, established firm, and termination. These stages are separated by various transitions, some of which are less precise than others. For example, the shifting from conception to active efforts to start a firm may be gradual, as may be the transition from a new firm to an established firm. In such cases, it may be difficult to identify with clarity those events or activities that would reflect a precise “phase change.” The most precise transition may be from the start-up process to a new firm, the “firm birth transition.” This shift, however, lacks any

Fig. 2.1 Business life course

10

New Firm Creation: Importance and Need for More Details

single event that clearly defines the phase change. Many businesses will keep and frame the first dollar of income, reflecting what might be considered the “birth event.” There are, however, a variety of different indicators that a start-up has become an operating new firm – the first hire, the first month profits occurred, first tax filing, and the like. Equally amorphous is the transition out of the start-up process by those who are no longer interested in creating a new firm. Nascent entrepreneurs may be slow to recognize that their start-up initiative has dissolved. This is similar to the diffuse nature of a business termination; it may take years for all traces of an established firm to disappear. A large number of research projects have attempted to determine the unique features of growth businesses; some have compared operating businesses that differ in age – often using imprecise indicators of a firm birth: “When was your business established?” Analysis proceeded by comparing firms of different ages – or size – and the absence of data on those that have not survived – or not grown – complicated inferences about causal processes. There were also a number of longitudinal studies where the same firms provided data at different points in time. Some of these projects tried to capture new firms and follow them through the early stages of the business life course. The “birth event” in such studies can be very imprecise, often reflected as the initial listing in a business registry or a credit rating file. The value of information about activities prior to the “birth event” is limited by the absence of comparisons with active start-ups that failed to become operating new firms. What was distinctive about the PSED I project was the effort to capture the process from conception and to develop descriptions of the activities during the start-up process. This allowed comparisons of those who entered the process – nascent entrepreneurs – and launched a new firm with those who quit midway through the start-up effort. The US PSED I, and the comparable efforts in other countries, were the first attempts to systematically capture the firm creation process from the very beginning. The results are striking, for they reveal a substantially greater scope of activity than expected; the diversity in the process is overwhelming. About one-third of the nascent entrepreneurs succeeded in

2.1. What Does the Start-Up Process Look Like?

11

implementing new firms and this assessment will summarize their distinctive features. A conceptualization of the process, and a summary of many factors and processes expected to have an impact on the firm creation transitions is provided in Chapter 3. The firm creation process itself is divided into two parts, entry into a start-up effort and completion of the startup effort with a new firm. Entry into the process, from conception to being an active nascent entrepreneur, is the focus of Chapter 4. Completion of the process – with a new firm or disengagement – is reviewed in Chapter 5. An overview of the major features and a commentary on the implications is provided in Chapter 6. Following the references is a list of published works based on PSED I. Methodological appendices describe some of the more esoteric manipulations required to clarify the patterns in the data. For those that wish to complete their own analysis of the PSED I data set regarding these issues, a complete listing of all cases in the nascent cohort, identified by ID number, and their status at the end of six years is provided in the Appendix.

3 Conceptualization of the Process

Creation of a new firm is a two-step process; entry into the start-up process is followed by the actual creation of a new business. Most of the assessments, theories, conceptualizations, models, or perspectives on new firm creation make no attempt to separate these two transitions. As a result, there is considerable ambiguity about how different factors may affect the actual creation of a new firm. Some may have more influence on the decision to participate in the start-up process; others may have more impact on the completion of the start-up process. It is useful to place the business life course, presented in Figure 2.1, into a slightly broader context. Assuming that the key element in the firm creation process is the individuals who enter into the start-up process, the question becomes, where do they come from? Two possible sources are shown in Figure 3.1. One major source of start-up participants, individuals making the first transition, are those who emerge from the adult population and begin, on their own, to create a new firm – labeled as nascent entrepreneurs. The other source is individuals working for existing firms who are expected, as part of their regular jobs, to work on the creation of a new business – labeled nascent intrapreneurs. As a substantial 13

14

Conceptualization of the Process

Fig. 3.1 Business life course and context

proportion of start-ups are team efforts, a given initiative could involve both nascent entrepreneurs and nascent intrapreneurs. One unresolved issue is the criteria for determining if a start-up has completed the transition to a new firm. Established firms can be characterized by a number of properties. When there is evidence of an intention to engage in business activity, the consolidation and coordination of productive resources, economic exchanges with others (suppliers, customers, employees) and social recognition as a business entity there is no question about its existence (Carter, Gartner, and Reynolds, Chapter 28).1 On the other hand, it may take a while for the transition from start-up to new firm to be completed and there is substantial merit to the use of a single criterion to provide a uniform “birth date.” Reports that the start-up has become an operating business are one possible indication of a firm birth and will be utilized in the assessments that follow. The entire process can be considered to take place within a given social, political, economic, or historical context. This may vary across 1 In

this chapter the major sources, identified by author and chapter number, are from Gartner et al. (2004).

3.1. Socio-Cultural Characteristics

15

communities or regions or cultural groups within a country or across nations. Major factors that might affect the two transitions can be considered in broad categories. • • • • •

Socio-cultural characteristics. Stable personal traits and orientations. Immediate personal, social context. Work career related experiences. Procedures, strategies, and resources associated with firm implementation. • Ambient social, cultural community context. • General and specific features of industry sector and competitive situation. • Regional characteristics. Many of the processes linking these factors to the emergence of a new firm are summarized in the Handbook of Entrepreneurial Dynamics (Gartner et al., 2004); this extensive overview is the primary basis for the summary that follows. This work reflects the substantial contributions of the Entrepreneurial Research Consortium teams to the content of the PSED I interview schedules.

3.1

Socio-Cultural Characteristics

Age, gender, and ethnic identity are the most basic socio-cultural characteristics. It is a major intellectual challenge to disentangle personal characteristics uniquely associated with these socially defined attributes from other important capacities, traits, values, and expectations related to these features. For example, age can provide an indication of physical, intellectual, and emotional maturity as well as reflect capacities associated with educational and work experiences. Gender, in a similar fashion, can reflect biological differences as well as differences in life experiences and social expectations. Ethnic background may reflect a diverse set of biological features, a different set of life experiences that can create distinctive personal aspirations and obligations,

16

Conceptualization of the Process

and responses to expectations from those outside the ethnic group that can affect life course opportunities. It is, therefore, complex to develop arguments, hypotheses or theories related to these basic individual characteristics and their relationship to participation in firm creation without incorporating secondary attributes indirectly associated with age, gender, and ethnicity. Secondary features related to age, gender, and ethnicity for which other direct measures may be superior indicators. For example, young adults may have the interest and energy to enter into the start-up process, but older adults may have the experience and maturity to complete the process. There are clearly better measures of experience, maturity, energy or interest than date of birth. It is reasonable to speculate that younger adults have energy, optimism and, perhaps, limited career options. Limited career options would suggest that they have little to lose if the start-up is not successful; with fewer work options they may be more likely to participate in a business start-up. On the other hand, the absence of work experience, career stability, and social maturity, all of which may increase with age, may reduce the successful completion of a start-up with a new firm among younger adults. These complex relationships are more common with arguments associated with gender (Carter and Brush, Chapter 2). If women are more risk averse, have less business experience – particularly as managers, fewer role models for business creation, and more family responsibilities as young and mid-career adults, they may be less likely to participate in the start-up process. Further, it is suggested that the lack of well developed networks in the business community and more difficult access to financing may reduce the potential of women to finishing the start-up process with a new firm. Nothing is more complex than trying to separate ethnicity from ancillary attributes (Green and Owen, Chapter 3). For example, it is widely assumed that Blacks and American Indians may have completed less schooling and have fewer years of work experience, as well as being dependent on households and families with less income and wealth. Most are assumed to be “native born,” i.e., they and their parents were born in the United States. On the other hand, Hispanics and Asians may be more likely to be immigrants. In that case, ethnic attributes

3.2. Stable Personal Traits and Orientations

17

Table 3.1 Socio-cultural characteristics and firm creation transitions Entry into the start-up process Age

Gender

Race and ethnicity

Highest when energy and optimize peak and risk of loss is minimized Conservative, few role models, mid life family obligations, and reduced work options Reduced work options, support from ethnic group, high levels of motivation

Completion of the start-up process with a new firm Increases with maturity and work experience Lack of business networks, problems in obtaining financing Reduced experienced with US business practices, lack of traditional business networks, problems in obtaining financing

may be co-mingled with attributes found among all recent immigrants – whether from Asia, Latin America, or Europe. In general, non-majority ethnic status is assumed to reduce options in traditional work activity and to increase participation in start-up processes. Those tendencies are enhanced among recent immigrants and often encouraged by a distinctive ethnic group that has developed expertise with business creation in a specialized sector (such as Korean grocers in Los Angeles). At the same time, the lack of experience with US business practices and reduced access to financing and traditional business networks suggests that ethnic minorities may have trouble in implementing new firms or, if established, the firms may be constrained regarding growth. Selected descriptions relating the socio-cultural characteristics to the two stages of the start-up process are summarized in Table 3.1.

3.2

Stable Personal Traits and Orientations

It is widely assumed that those who implement and manage their own businesses have unique or distinctive orientations, capacities, or personal traits, often summarized as an “entrepreneurial personality.” Such an entrepreneurial personality may include unique sets of motivations, career objectives, entrepreneurial expectations and intensity, perceived locus of control, a variety of social skills, economic sophistication, and, perhaps, decision making styles and strategies for individual problem solving. While these personal traits may change over the human life

18

Conceptualization of the Process

course, they are generally assumed to be stable over the short or medium term – years or decades. Perhaps most basic is the notion that those with distinctive career orientations will gravitate to the firm creation process (Carter, Gartner, and Shaver, Chapter 12). It is assumed that those with a stronger interest in self-realization, financial success, social recognition, meeting distinctive role expectations, implementing innovation, and being independent and autonomous may be more likely to enter into the start-up process. There is much less discussion of how a given set of career goals may facilitate the actual creation of a new firm. It is reasonable to assume distinctive career objectives – if the new firm appears to provide a way to achieve these outcomes – may enhance tenacity in the start-up process or decrease the attractiveness of traditional work options. This orientation, however, emphasizes the perceived attractiveness of an entrepreneurial career option compared with other labor force activities. It does not consider the motives of those with no other way of participating in the economy – necessity entrepreneurs (Reynolds et al., 2002). Two closely related attributes have been proposed as describing distinctive motives for entering the entrepreneurial process. Expectancy – a belief concerning the likelihood that a particular act will be followed by a particular outcome – can be measured in terms of entrepreneurial career choices (Gatewood, Chapter 13). Measures of entrepreneurial expectancy tend to emphasize the perceived consistency, or fit, between the work role of an entrepreneur and the individual’s capacity to satisfy their career goals. Hence, this feature is expected to have a major impact on entry into the start-up process, whereas the impact on completing the process with a new firm is primarily related to motivation. If a person thinks that the work role of an entrepreneur will help them achieve personal goals they may be more tenacious about new firm creation. Closely related to entrepreneurial expectancy – which emphasizes career direction toward entrepreneurship – is the concept of entrepreneurial intensity, defined as the level of commitment and focus of an entrepreneur in leading a new start-up (Liao and Welsch, Chapter 17). The focus of this measure is a determination of the commitment and drive of the person to complete the start-up process

3.2. Stable Personal Traits and Orientations

19

with a new firm. It would appear to be less related to predicting entry into the start-up process itself. Associated with the level of motivation would be confidence in the capacity to create a new firm. If new firm creation is considered to be an activity requiring a great deal of individual, autonomous effort, then an “internal” locus of control – the extent to which people believe they can influence the rewards they received from the external world – may be stronger among those who enter the start-up process (Shaver, Chapter 19). Its role in facilitating completion of a new firm is more amorphous. Creating a new firm is very much a social activity, as success requires a great deal of personal contact and the capacity to convince others to contribute to an initiative with unproven potential. It is reasonable to assume that those who are comfortable in social settings and have emotional control and considerable self-confidence would be more effective in completing the start-up process with a new firm (Baron, Chapter 21). It is not clear, however, if this would have a major effect on entry into the start-up process itself. New firms are also basically new participants in an economic market, and decisions must be made about the acquisition and allocation of economic resources in changing situations. Those who have a better grasp of the “economic value” of resources – their current market value rather than their original cost – or the significance of sunk costs – expenditures that cannot be recovered and are irrelevant to immediate decisions, should be more successful in implementing a new firm (Morgan, 2004, Chapter 20). It is not clear how this would be related to entry into the start-up process. Cognitive style refers to “consistent individual differences in preferred ways of organizing and processing information and experience” (Johnson, Danis, and Dollinger, 2004, Chapter 15). The Kirton Adaptation–Innovation Inventory, one way to measure cognitive style, assumes one’s style develops in childhood and remains the preferred mode of problem solving throughout life, particularly in times of stress. One application separates individuals as preferring – in response to unsatisfactory outcomes – to focus on doing something different versus improving on the current strategy. If entrepreneurs are seen as

20

Conceptualization of the Process

independent, then those preferring adaptive responses may be more likely to enter the start-up process. Whether a new firm is established may reflect whether the start-up is developing a new product or service – which may be facilitated by an adaptive style – or serving a well established, traditional market – which may be facilitated by “doing things better.” The impact of cognitive style, therefore, on new firm success may be contingent on other aspects of the situation. Based on a rational model, individual problem solving can be considered to have two steps – problem identification and problem solution. As with other human activities, there may be substantial variation with how individuals identify problems, the mechanisms they use to develop solutions, and to what extent the individual experiences stress in the process (Ford and Matthews, 2004, Chapter 18). It is appropriate to assume that individuals who are more effective and comfortable with identifying and solving problems may more successful at launching a new firm from the start-up process. It is not clear if they are more likely to enter the start-up process. As can be seen in the summary provided in Table 3.2, the impact of these individual traits or perspectives is quite varied, with some more likely to affect entry into the start-up process, others success at creating a firm, and others both stages. Further, the impact on the start-up outcomes may depend on other factors – such as the type of business being created. Table 3.2 Stable personal traits, orientations and firm creation transitions Entry into the start-up process Career reasons

Major effect

Entrepreneurial expectations Entrepreneurial intensity Internal locus of control Social skills Economic sophistication Decision-making style

Major effect

Individual problem solving

Major effect Less influence Adaptors more likely to enter

Completion of the start-up process with a new firm Conditional on perceived success of new firm characteristics May affect motivation Major impact Major impact Major impact Impact conditional on industry sector More effective individuals more likely to launch a firm

3.3. Immediate Personal, Social Context

3.3

21

Immediate Personal, Social Context

There are a number of features of an individual’s immediate personal and social context that might affect the firm creation transitions. These may include their current household structure – the presence of wageearners, children or other dependents, access to economic resources controlled within the household, family background and expectations, as well as access to role models and potential social support. The immediate context can affect how individuals allocate their time and perceive satisfaction. Household structure covers many different aspects of one’s living and family arrangements (Brush and Manalova, Chapter 4). Aside from the individual’s marital status, the most basic may be household size. Beyond that is the character of the dwelling population; number of young children, adolescents, other dependants – such as the elderly, and how many are making financial contributions to the upkeep of the household. Unequivocal predictions of the effect of the household structure on the firm creation transitions are difficult to develop, as they seem to be related to other external factors. Married people may have more access to networks and financial support to start a business, but they may also have more family responsibilities. Larger household may contain more wage earners and provide more economic resources; they may also reflect more responsibilities and financial demands, reducing the tendency to pursue a firm start-up. All these may vary by the gender of the individual, as women may have more household responsibilities and less time to pursue a start-up; men feel more committed to support a larger household and pursue start-ups to increase income. No topic seems to get more attention regarding firm creation than money; support at the beginning of the start-up process seems particularly important. There is a widespread assumption that access to funds will facilitate new firm creation, and that both household income and net worth are indicators of the availability of funds (Kim, Aldrich, and Keister, Chapter 5). The nature and the strength of the impact may vary for the two transitions. It is clear that most expect higher household income and net worth to facilitate the firm birth transition – the “liquidity effect,” but entry into the process is less obvious. On one hand, households with more income and wealth can subsidize a member

22

Conceptualization of the Process

as they are engaged in the start-up process, which can be a major factor in the decision to invest time and energy into an initiative with an uncertain future. On the other hand, those in households with less income and wealth may be more motivated to purse a new firm as a way of improving the household financial situation, particularly if they feel responsible for the household economic well-being. Aside from the impact of access to money, the tendency to create a new firm may be affected by family influences; it is widely assumed that the sons and daughters of the self-employed, small business persons or entrepreneurs will themselves start new businesses (Matthews and Human, Chapter 8). Such individuals may have the interest and motivation to enter the start-up process – they are comfortable with this career option – as well as the skills to be successful in implementing a new firm – lessons learned at the dinner table. This perspective can be expanded to include not just parents but other relatives, neighbors, friends and other mechanisms of impact as well (Davidsson, 2004, Chapter 16). These could include a positive impression gained from observing others implement and manage their own businesses as well as encouragement from personal social networks on entry into the startup process. This could encourage people to enter the start-up process and motivate them to complete the process with a new firm. Perhaps the most precise descriptions of how people are living their daily lives come from time-use diaries, where people provide a detailed account of activities engaged in during the day (Owen and Greene, Chapter 9). These are typically sorted into “normal work days” and “typical days off” and activities may be timed down to 5 min blocks, although 15 min segments provide reasonable levels of accuracy. As everyone is allocated the same amount of daily time – 24 h or 1,440 min – there are no obvious predictions associated with this descriptive data. It is reasonable to assume that those emphasizing household and child care activities may be less likely to pursue startups. Perhaps those spending more time on a start-up are more likely to complete the process with a new firm. Satisfaction with life and satisfaction with a current job are of continuing interest in advanced economies; they have a modest positive correlation (Johnson, Arthaud-Day, Rode, and Near, Chapter 14). It is reasonable to assume that those who find that their current job

3.4. Work Related Experiences

23

Table 3.3 Immediate personal, social context and firm creation transitions

Household structure Household income, net worth Family background

Role models, perceived social support Time use

Life/job satisfaction

Entry into the start-up process

Completion of the start-up process with a new firm

Mixed Conditional

Mixed Major facilitation

Parents own business experience a major impact Social networks encourage entry into process

Knowledge gained from parents a major advantage

Time on family social obligations reduces entry into start-up process Reduced job satisfaction may increase start-up participation

More time on start-up improves potential for new firm

Positive influence on completing the process

No clear impact

satisfaction is low and unsatisfactory may be more likely to pursue other options, such as create a new firm. As low job satisfaction may lead to a reduced satisfaction with life overall, a change in career directions may be initiated to increase satisfaction on both dimensions. It is not clear if or how job and life satisfaction might affect a successful completion of the start-up process. The effects of these personal and social contextual factors on firm creation are summarized in Table 3.3; they have diverse and heterogeneous effects on the two major transitions.

3.4

Work Related Experiences

A number of personal, educational, and work experiences can provide perspectives and orientations that may affect involvement and success with firm creation. Current and past participation and experience in the labor force, either working or self-employed, general level of education, or specialized education in business or experience in business can facilitate entry into and completion of the process with a new firm. Traditional educational attainment can be considered in terms of five ordinal categories: not completing high school, high school degree, post high school but no four-year college degree – which may include

24

Conceptualization of the Process

completion of community college or vocational and technical degree programs, a college degree, and any level of graduate program experience, MS, MA, MBA, law, medical, veterinary professional training as well as scholarly doctoral programs (Brush and Manolova, Chapter 7). It is generally assumed that more education will provide better preparation for any work activity, but most who receive advanced training – despite the plethora of college programs in entrepreneurship – are prepared for existing roles in established organizations. So while education may be useful for implementing a new firm, it is not clear that more education will increase the tendency to enter into the start-up process. There is substantial evidence that those who have not completed high school are less likely to pursue a start-up in the United States. Beyond the level of education, it is possible that certain types of educational or work experience may increase interest in pursuing business start-ups or may have an impact on success in completing the process with a new firm (Brush and Manolova, Chapter 7). Based on a factor analysis of nine types of coursework or business experience, coursework in the areas of general management, human and financial management, and operations management may be significant. Business experience can be considered in terms of general management or operations management. More coursework and experience may increase confidence in a start-up and, in turn, more participation; it may also increase the skills required to implement the new firm. One specific feature of training and experience is sophistication in financial management (Katz and Cabezuelo, Chapter 32). Tracking and managing financial resources is a critical feature of firm management, perhaps more so with a new firm coping with scarce resources. While skill with financial management may have some impact on encouraging individuals to enter the start-up process, there is strong evidence that sophistication in financial management should improve the potential for a successful firm birth. Labor force participation may focus on past activities, say in the 12 previous years (Davis and Aldrich, Chapter 10), or on current activities pursued as the start-up is being developed (Reynolds, Chapter 6). There is substantial evidence to suggest that current full- or part-time work increases participation in a start-up, suggesting that a history of

3.5. Procedures, Strategies, and Resources Associated with Firm Implementation Table 3.4 Work career experiences and firm creation transitions Entry into the start-up process

Completion of the start-up process with a new firm

Educational attainment

General education may improve skill and confidence increasing participation or increase work options and reduce participation

Education should improve skills and increase potential for firm creation

Diverse business experiences

More administrative and management experience may increase confidence

More administrative and management experience may increase skills and success

Financial sophistication

May contribute to confidence to take action

Should increase success

Labor force participation

Those employed may be in positions to develop good business ideas and business contacts, increasing participation.

Business experience may improve potential for success

Those unemployed may need work and be more likely to be involved Work participation history

A history of work experience, selfemployment and small business management may increase involvement

More work, self-employment and management experience may increase success

work or self-employment may further increase the tendency to become engaged in a start-up. Previous work experience – either as an employee or in self-employment – would be also expected to increase work-related skills and confidence that would contribute to firm creation. Table 3.4 provides an overview of selected work and career effects on the process; the most critical impact would seem to be on the successful completion of the process with a new firm, rather than a decision to become involved with a start-up.

3.5

Procedures, Strategies, and Resources Associated with Firm Implementation

Once the start-up process is initiated, there is a wide range of activities or procedures that must be pursued to assemble the resources – financial and human – to develop procedures for providing goods or a service. Many are interrelated or interdependent and may occur in almost any sequence. Included are the development or discovery of opportunities, a range of specific start-up activities, the development

25

26

Conceptualization of the Process

of a team – present for about half of all start-ups, the use of social networks as an informal source of guidance and support, the location and use of formal programs to help new firms, development of funding for the new firm, identification and resolution of start-up problems, a range of specific new firm characteristics (legal form, location, ownership structure); expectations associated with the new firm as well as the competitive strategy and utilization of new technology. The potential impacts on the firm creation transitions are quite diverse. Many suggest that opportunity recognition is a critical feature of the entrepreneurial process, particularly when a unique or distinctive product or service is developed to serve new markets (Shane and Venkataraman, 2000). Just exactly how the process actually works is more complex, but opportunity recognition is a central feature of many efforts to describe new firm creation (Hills and Singh, Chapter 24). As a critical feature of the process, it is reasonable to assume that recognition of an opportunity perceived as “promising” is likely to encourage individuals to enter into the start-up process. On the other hand, it has been proposed that people often decide they want to create a business, enter the process, and then – as a critical feature of the start-up process – locate and define the business opportunity. It is reasonable to assume that “better opportunities” will facilitate the attraction of resources required to implement a new firm. Start-up activities are those actions pursued to organize and implement a new firm (Gartner, Carter, and Reynolds, Chapter 26). There are dozens of options, the exact mix depends on the nature of the firm, market, and how the start-up evolves. They all have one feature in common – occurrence after a decision has been made to enter the business creation process. As a result, they have little impact on the actual decision to enter the process itself. There is, however, considerable speculation – but little consensus – regarding the most appropriate activities or the optimal sequence for facilitating the implementation of a new firm. This will get considerable attention in Chapter 5. About half of all start-ups are team efforts; the development of a start-up team can be a critical feature for the firm creation process (Aldrich, Carter, and Ruef, Chapter 27). A team effort can provide both a range of expertise – often critical for complex undertakings – and the

3.5. Procedures, Strategies, and Resources Associated with Firm Implementation

presence of like-minded colleagues can reduce uncertainty and anxiety associated with business creation. While the potential for a team effort may encourage individuals to enter the start-up process, the major focus of research has been on how the structure and characteristics of the team may facilitate a successful firm birth. Closely related to working with a team is the help and assistance that may be provided by others in one’s family, personal or workrelated networks; those persons who may provide guidance and support that can facilitate completion of the firm creation process (Aldrich and Carter, Chapter 29). These measures of a social network go somewhat beyond asking if the nascent entrepreneur had received encouragement and support sometime in the past – such as exposure to parents or friends who managed small businesses – to development of detailed measures about the current support and assistance. While expectations of a supportive social network may encourage a person to enter the start-up process, most of the attention has been on the nature and extent of a social network on facilitation of a new firm birth. A complementary effort reflects attention to formal assistance, provided by programs sponsored by governments, educational institutions, or other groups (Dennis and Reynolds, Chapter 30). It is generally assumed, at least by politicians, that the existence of such programs will encourage more people to enter the start-up process and, perhaps, that the assistance provided will increase the chances of new firm success. Implementing a new firm requires financial support, and considerable attention has been given to how new firms develop and utilize financial sponsors (Stouder and Kirchhoff, Chapter 31). There is considerable concern that anxiety about securing financial support may discourage individuals from entering the start-up process. At the same time the ability to assemble adequate resources is assumed to facilitate the actual implementation of a new firm. Few topics associated with new firm creation have received more attention than financial support. There are a number of features associated with any business that may be related to the completion of the firm transition process, including the type of economic activity (Standard Industrial Classification or SIC code), the legal form, the nature of the ownership structure, as well

27

28

Conceptualization of the Process

as the nature of the physical location (Reynolds, Chapter 23). There are no, a priori, assumptions about the role of these features in entering the start-up process. In fact, there are few proposals regarding how these basic characteristics might affect the creation of a new business. In general, establishing these features – choosing a legal form, selecting a site for the initial operation – are considered a necessary part of the start-up but having no major impact on the entry into the process or the final outcomes. Those entering the start-up process may have diverse expectations about the future development of the firm, once it is a going concern (Human and Matthews, Chapter 33). Some may prepare for a stable, low risk operation that will be comfortable to manage and others may plan and hope for a high growth trajectory that will have a major impact on the market and, perhaps, generate significant wealth. Variations in expectations may affect the decision to participate in the start-up process, but there may be a greater effect on the way in which the start-up effort is pursued. For example, those planning for a high growth, major impact new firm may devote more energy to developing financial support and a complex ownership structure compared with a person planning a new business that would be an extension of selfemployment or lifestyle firm. It is not clear which expectation is more likely to lead to an operational new firm. Closely related to growth expectations are the nature and scope of problems encountered in the start-up phase (Brush and Manolova, Chapter 25). The creation of a new firm always involves resolving problems – or overcoming challenges – and these can involve both personal challenges in learning how to be an effective entrepreneur-resource coordinator as well as social challenges in establishing the new firm as a credible business entity. It is clear that high growth aspirations will increase the number and severity of these problems/challenges. Awareness of the problems to be overcome may discourage entry into the business creation process; the severity and number of such problems may reduce the capacity to launch a new firm. One central issue associated with the launch of a new firm is the strategy to be used to enter into and compete in the marketplace (Stearns and Carter, Chapter 37). A great deal has been written about

3.6. Ambient Social, Cultural Community Context

29

competitive strategies, usually associated with existing firms. Previous research on new firms has identified a range of emphases including a focus on lower prices; better service; market responsiveness; technological expertise; superior facilities and customer convenience; more attractive, contemporary products; as well as new or advanced product or process technology. The optimum mix of strategies may depend on the specific business activity and the nature of the competition; there are no unequivocal predictions about the effect on new firm creation. Competitive strategies are not expected to have much impact on entering the start-up process. Closely related to competitive strategy is the emphasis on high technology as the primary focus of a new business (Allen and Stearns, Chapter 38). Though rare, the capacity to use new and sophisticated technology in innovative ways may encourage some to enter the startup process. The skill in commercializing the new technology may have a substantial impact on the potential for implementing a new firm. There are a range of expected impacts, mostly on completion of the start-up process with a new firm, reflected in these different dimensions. The effects are summarized in Table 3.5.

3.6

Ambient Social, Cultural Community Context

Both experience in and perceptions about the local community or region can affect the firm creation transition. Many aspects of the experiences in the region can be summarized by residential tenure – how long the person has lived in the region. Judgments about the host community as a supportive context for entrepreneurship are summarized with the conception of the “entrepreneurial climate.” Discussion of residential tenure is complicated by an enduring focus on international in-migration (Reynolds et al., 2004a, Chapter 6). It is often assumed that new immigrants are often the most talented from their home countries and wish to pursue new firm creation in their new homeland. Correlations between high rates of immigration and new firm births often lead to the conclusion that the new immigrants are creating new firms. While new immigrants may need work to support themselves and their families, it may be faster for them to create

30

Conceptualization of the Process

Table 3.5 Resources, procedures, and strategies associated with firm implementation and firm creation transitions. Entry into the start-up process Opportunity recognition

Considered a precondition by many

Completion of the start-up process with a new firm More promising opportunities should increase probability of success

Start-up activities

Appropriate mix of activities should increase potential for firm birth

Teams

Creation of more complex and sophisticated firm may be facilitated by multi-skilled team

Social networks

Informal help may provide support to encourage enter into process

Informal support may help guide to firm birth

Knowledge and use of assistance

Knowing help is available may encourage enter into start-up

Formal programs may provide expertise and assistance that will promote firm birth

Funding the first year of business

Potential for funding may encourage entry into start-up

Financial critical

Nature of business start-up

support

may

be

Some legal and organizational features may be more helpful than others

Future expectations for the new firm

High aspirations may encourage enter into process

Nature of expectations may affect how and when the firm is established

Start-up problems

Prospect of multiple problems may discourage entry into process

Problems may be unavoidable, but resolution necessary to create a new firm

Competitive strategy Technological entrepreneurs

May be critical for successful birth Entry may reflect desire to pursue innovative technology

Skill at technology may affect potential firm birth

income by taking a job. Some time is required for individuals to become familiar with the local community and develop business networks that can facilitate new firm creation; hence, immediate arrivals may not be likely to immediately enter into the start-up process. Those with some experience in the community may be more successful in completing the start-up with a new firm. An accepted view of the most appropriate work career path may have developed in many communities, such as company towns

3.7. Industry and Competitive Context

31

Table 3.6 Ambient social, cultural community context and firm creation transitions Entry into the start-up process Residential tenure

Immediate arrivals may be less likely to enter process Some years required to develop knowledge, contacts, and financial resources to enter start-up process

Perceptions of entrepreneurial climate

Positive climate increases participation

Completion of the start-up process with a new firm Longer residence facilitates knowledge of local markets, competition, and business networks

where everyone expects to work in an assembly plant, just like their parents and grandparents. It is possible that communities vary in terms of encouragement and support for entrepreneurial initiatives (Carter et al., 2004, Chapter 35). The perception of the community entrepreneurial climate can be considered to have three dimensions, presence of community support, successful entrepreneurial models among friends and family, and successful entrepreneurial models in the community itself. All would be expected to increase participation in the start-up process; the effect on successful completion with a new firm is less certain. A summary of the impact is provided in Table 3.6; major impact would seem to be associated with entry into the process itself.

3.7

Industry and Competitive Context

New firms are implemented in specific communities in specific markets – or industries, which can be considered the context for the new firm birth (Matthews and Human, Chapter 36). These communities and economic sectors may vary in terms of complexity and predictability, which may have an impact on the strategy for implementing a new firm or the success of the initiative. These variations may be related to perceptions of uncertainty regarding financial support, competitive issues, or the capacity to develop effective operational procedures to deliver the goods or services. Successful responses to these sources of uncertainty can affect the success at creating a new venture (Table 3.7).

32

Conceptualization of the Process

Table 3.7 Industry and competitive context and firm creation transitions Entry into the start-up process Economic and community context for entrepreneurship: perceived environmental uncertainty

3.8

Completion of the start-up process with a new firm Capacity for dealing with financial, competitive, and operational uncertainty can affect potential for a successful firm birth

Regional Characteristics and Change

Several projects have considered the role of the economic context on new firm births, focusing on US labor market areas as the unit of analysis. In general, the findings are that greater population growth and more indicators of urbanization appear to facilitate higher new firm birth rates, measured as the number of new firms per 100 existing firms or 1,000 adults in the population (Reynolds et al., 1995, Armington and Acs, 2002). These are reflected in tracking the nature of the county in which a person may begin and complete the start-up process. The greater the population growth, the more there will be demand for goods and services and the more opportunities for creating new firms to meet this demand, often by those well established in the region. Established residents are more likely to recognize a shortage of suppliers. There is also evidence that more urbanized areas have both higher levels of birth rates and more new firms; this seems to reflect a greater proportion of young adults, those with higher levels of education, as well as greater economic and cultural diversity and higher proportions of high income households. The higher levels of new firm creation, however, may increase the competitive pressures and reduce the potential for a new firm launch (Table 3.8).

3.9

Overview

A very wide range of conceptual frameworks, theories, or hypotheses are related to speculation or predictions about the completion of the firm creation process. The variety and scope is considerable but all share several common features. First is a lack of precision about the nature of the role in the new firm creation process, impact on entry

3.9. Overview

33

Table 3.8 Regional characteristics and firm creation transitions

Population growth

Urbanization

Entry into the start-up process Reflects unmet demand and perception of business opportunities

Completion of the start-up process with a new firm Greater demand reduces price pressures and increased probability of a firm birth

Greater cultural, technological, and productive diversity increases the range and uniqueness of demand, both scope and niche opportunities, wide range of other start-ups provide role models for potential entrepreneurs

Increase access to resources required as inputs – human, technical, financial – facilitates organizing the new firm productive processes; increased competition may reduce successful firm creation.

into the start-up process or the completion of the process with a new firm. This reflects, in part, the lack of attention to these details of the process prior to the development of the first PSED project. Second, each orientation or set of variables is considered in isolation, with little attempt to specify their impact under different conditions or in relation to the impact of other processes or variables. Each is presented with a tacit understanding that all other factors are held constant. Third, there is little systematic discussion of the potential interaction between different processes, such as how the presence of a start-up team may ameliorate problems associated with obtaining enough funding for the start-up. As will be seen in the following chapters, the nature and direction of impact can vary substantially, as well as the relative importance of different factors and their interaction. While the propositions and proposals reflected in this brief review represent a useful first effort, enhanced understanding of new firm creation requires a more complete and nuanced multi-process assessment.

4 Becoming a Nascent Entrepreneur: Conception to the Start-Up Process

4.1

How Many People are Trying to Start New Firms?

When the initial screening for PSED I was completed in 1998–2000 about 6% of those 18–74 years of age or about 10 million individuals were involved in start-ups. Both patterns are presented for the 1998 to 2005 period in Figure 4.1; the prevalence rate, number per 100 individuals is on the right scale and represented by the line and the total number of individuals is presented on the left scale and represented by the bars. By 2005 participation had grown to about 8% of the population, and reflecting some growth in the population itself, this was about 16 million adults. There has been an abrupt increase immediately following the 1998–1999 period, which may reflect an increase in attention during the “dot com” craze, but the pattern has shown some growth since the 2000–2001 period. These estimates make clear that there are a lot of US citizens involved in the start-up process; which leads to the next question.

35

36

Becoming a Nascent Entrepreneur: Conception to the Start-Up Process

Fig. 4.1 US activity in business start-ups: 1998–20051

4.2

What Kind of People are Trying to Start New Firms?

No variables have more impact on participating in the start up process than age and gender.2 The lines and diamonds in Figure 4.2 indicate the participation rate, number per 100 as shown on the right scale, and the estimated total numbers of individuals involved are represented by 1 Data

for 2000 to 2003 is based on samples developed as part of the GEM research program with samples of 5,018 for 2000 and 2001; 7,059 in 2002; 9,1997 in 2003; see references in Chapter 1, footnote 6. Because of small sample sizes, data for 2000 and 2001 are combined to reduce the sampling error. Data for 2004 is based on a special assessment with a national sample of 12,907 discussed in Reynolds (2007). Data for 2005 is based on the initial screening for PSED II and sample of 26,759. Screening items used for all surveys are used to predict the level of “four-criteria” nascent entrepreneurs based on patterns found in the post-1999 samples. These samples are used to estimate the proportion of PSED I screening respondents meeting four criteria as nascent entrepreneurs: (1) they consider themselves as working on a business start-up, (2) they report some activity in the past 12 months, (3) they expect to own part of the business, and (4) the initiative is not yet a going concern. 2 Variables chosen from the PSED I screening data set are listed in Appendix.4Ax.1. A more complete and detailed discussion of these issues is available in Reynolds et al. (2004b).

4.2. What Kind of People are Trying to Start New Firms?

37

Fig. 4.2 Participation in business start-ups, by age and gender [1998–2000]

the bars, using the scale to the left.3 The general pattern in United States is that men are about twice as likely to be involved as women and there are twice as many men as women trying to start new firm. Those 25 to 44 years in age are a major proportion of the nascent entrepreneur population. Both patterns are remarkably stable across time in the United States – the 2005 estimates have the same structure as those for 1998–1999 – and across countries. The peak of the age distribution is slightly older in Europe. There is more cross-national variation by gender, with poorer countries approaching equal participation by men and women and richer countries have less participation

3 Table

4.6, pg. 507, of Reynolds, Paul and Richard Curtin, Appendix 4Ax, of Gartner et al. (2004). The patterns are based on three criteria measures of entrepreneurship, those with active businesses have not been removed from the data sets, so prevalence rates and estimates of participation will be slightly higher than associated with the four criteria estimates.

38

Becoming a Nascent Entrepreneur: Conception to the Start-Up Process

by women, particularly in Northern Europe.4 This reflects, in part, the larger proportion of necessity entrepreneurs in poorer countries. It is clear that there is no age or gender group where there is NO participation in business creation; although participation in start-ups is relatively rare among those over 65 years of age, particularly for women. On the other hand, business creation is clearly concentrated among young and mid-career adults, those under 55 years of age. Those nascent entrepreneurs 25–54 years old are 78% of all those involved in business creation. The impact of ethnic background on participation in business creation is illustrated in Figure 4.3, for men, and Figure 4.4, for women. The effect of ethnicity on participation is dramatic, with both Black and Hispanic men more involved than White men. Because of small sample sizes, differences among those over 64 years old are not statistically

Fig. 4.3 Participation in business start-ups: men by age and ethnicity [1998–2000]

4 Table

14, page 37, of Reynolds et al. (2004a).

4.2. What Kind of People are Trying to Start New Firms?

39

Fig. 4.4 Participation in business start-ups: women by age and ethnicity [1998–2000]

significant. Black women are generally more involved than White women, again the post 65 years old differences are not statistically significant. Hispanic women, however, have an unusual pattern, those 18–24 are more active than White women, those 24–44 years of age are about equal to White women, and those 45 and older are less active than white women. It is not clear if this interaction effect between age and participation among Hispanic women is a reflection of a major cultural difference – older Hispanic women focusing on home and family rather than work outside the home – or a cohort effect – Hispanic women born before 1950 are less likely to pursue business start-ups as a career option. The effect of higher levels of participation by Blacks and Hispanics on the numbers involved in entrepreneurship, as presented in Figures 4.3 and 4.4, is less dramatic. As the majority of the US population is white, they are the largest proportion – over 70% – of those in the start-up process. Black and Hispanic adults,

40

Becoming a Nascent Entrepreneur: Conception to the Start-Up Process

Fig. 4.5 Participating in business start-ups, by gender, educational attainment, and ethnicity [18–54 Years old only, 1998–2000]

however, are clearly an important segment of the nascent entrepreneur population. The impact of educational attainment on participation in business start-ups is dramatically affected by ethnic background, as shown in Figure 4.5. As many older Blacks and Hispanics may not have been able to pursue education, this presentation is restricted to those 18–54 years of age in 1998–2000, so most were born after 1945. Nonetheless, there is a dramatic difference between Whites, Blacks, and Hispanics, with an interaction associated with gender. There is very little difference among White men with different levels of education; those who did not complete high school participate at the rate of 9 per 100, those with graduate experience at the rate of 11 per 100. Among White women, there is generally a greater participation among those with more education, there is a slight jump among those with graduate experience. Among Black and Hispanic men and women there are much higher levels of participation in start-ups as

4.2. What Kind of People are Trying to Start New Firms?

41

they complete more education. This is most dramatic among those with graduate experience, where Blacks and Hispanics – men and women – are twice as likely to be involved in a start-up as Whites with graduate experience. There has been much discussion about the impact of graduate experience on White women, and Black and Hispanic men and women regarding start-up participation. The most common interpretation is that this may reflect a restriction in career opportunities in existing work organizations. This “glass ceiling effect” – or reduced opportunities for promotion – may be a major motivation for creating a new business. Data from this large scale screening allows attention to a range of other factors that may be considered associated with participation in start-ups. These include findings that:5 • Minorities with higher household income seem to be more likely to be involved in start-ups; the effect is more modest among Whites. • Dwelling ownership seems to increase start-up activity only for Black men. • Those with full-time or part-time jobs are much more likely to be involved in start-ups than those not working – students, housewives, retirees, the unemployed. • Marital status has little impact, but those married are generally more likely to be involved. • There is little impact of household size. • Those in households with young children are more likely to be involved in start-ups. • Those living in more highly urbanized counties – with higher per capita income, more young adults, more college graduates, and greater income disparity – are more likely to report participation in a start-up; the overall effect is, however, not dramatic. The most urbanized counties are in the Northeast and the South, least prevalent in the Midwest. 5 More

details provided at Reynolds et al. (2004b).

42

Becoming a Nascent Entrepreneur: Conception to the Start-Up Process

In general, then, a range of general socio-economic factors have been explored using the full screening data set and the most significant individual factors appear to be age, gender, ethnic background, and educational attainment, with some distinctive and powerful interactions.

4.3

Life Context and Start-Ups

It is possible that a unique combination of factors can have a major impact on whether or not a person becomes involved in a start-up. It is clear that age, gender, and ethnic background are important, but what types of combinations have the greatest impact. These combinations can be determined by organizing the data around a series of questions. For example, What single factor would have the biggest impact on predicting participation in a start-up? In other words, if one could bet on who would be involved in a business start-up and could get one piece of information before the bet, what would be the best choice? The answer, it turns out, is the age of the person. Knowing if they are more or less than 55 years of age will be the biggest help in making the prediction. What would be the second most useful item of information for predicting participation in a new firm start-up? Would it be gender, ethnic background, amount of education, current participation in the labor force? It turns out that this depends on the age of the individual. For those under 55 years old, gender is the next most useful piece of information to predict participation in start-ups, and men are more likely to be involved than women. If they are over 55 years old, whether or not they are engaged in full-time work is the most useful, as those still engaged in full-time work are more likely to be involved in a start-up initiative than those involved in part-time work or who are not in the labor force because they are retired, homemakers, disabled, students, and the like. Such an analysis can be continued, with the number of groups multiplying along with a greater level of detail about each of the subcategories of persons. Two major results are provided by the analysis. First is an estimate of the relative importance of the different factors included in the analysis. Second is the identification of unique combinations of

4.3. Life Context and Start-Ups

43

Table 4.1 Factors selected as important in predicting participation in start-ups Overall importance [Ranked]

Not important

Age Gender Current labor force status [working] Ethnic background Educational attainment Average annual population growth Household income

Martial status Household size Regional population density Urbanization index

factors that have a major impact on the target variable, in this case the proportion of individuals who have entered into the start-up process. The most important factors associated with predicting those who would be involved in the start-up process are indicated in Table 4.1. Seven of the eleven considered to have a significant impact are rank ordered in the left column; four not considered to have a major impact are indicated in the right column. See Appendix.4Ax.1 for details of the source of the variables from the PSED I screening data set. As expected, age and gender are seen as most significant, with labor force activity, ethnic background, and educational attainment having an impact. The influence of annual population growth in the county of residence and household income were relatively minor. The impact of the combinations of these factors on the tendency to be involved in the start-ups is summarized in Table 4.2.6 The results were sixteen unique combinations, rank ordered in terms of the level of participation in business start-ups. While this averages 6.3 per 100 for 6 This

analysis utilized a new version of Automatic Interaction Detection [AID] provided as DTREG Decision Tree Software, developed by Phillip H. Sherrod (2005) “www.ctreg.com.” The procedure is most effective if there are no missing values on any variables. The major source of missing variables was on annual household income, where data was available on 76.2% of the 64,622 cases. A stepwise regression analysis on those cases with household income data was able to account for 23% of the variations with gender, educational attainment, home ownership, workforce participation (working full-time versus not working full-time), and ethnic background (white versus non-white). This linear model was used to estimate household income for those cases with missing data. This increased the number of cases with household income to 96.75%. Only cases with data on all independent variables were included in the analysis, a total of 59,443, with weights re-centered such that the average weight was equal to 1.00. Independent variables included gender, age, ethnic background, labor force participation, martial status, household size, educational attainment, household income, population density in 1992, population growth from 1980 to 1992, and a four item index of urbanization (Chronbach’s Alpha = 0.87).

A B C D E F G H I J K L M N O P

Label yrs yrs yrs yrs yrs yrs yrs yrs yrs yrs yrs yrs yrs yrs yrs yrs

old old old old old old old old old old old old old old old old

Men Women Men Full-time work Men Women Men Women Full-time work Women Full-time work Part-time work, Full-time work Part-time work, Part-time work, Part-time work,

Second level

Average values/totals

18–54 18–54 18–54 55–98 18–54 18–54 18–54 18–54 55–98 18–54 55–98 55–98 55–98 55–98 55–98 55–98

First level

not working not working not working

not working

Black Black White, Hispanic, Other Beyond HS Degree Black White, Hispanic, Other White, Hispanic, Other White, Hispanic, Other Up to HS degree Black Beyond HS degree 55–64 yrs old Up to HS degree 55–64 yrs old 65–98 yrs old 65–98 yrs old

Third level

Table 4.2 Participation in start-ups: characterization by group features

Full-time, part-time work Beyond HS degree Full-time, part-time work Men Not working Top 25% in pop growth Not working Bottom 75% in pop growth HH Inc above $50k/yr Up to HS degree Women Beyond HS degree HH Inc below $50k/yr Up to HS degree Men Women

Fourth level

6.3

15.8 12.3 9.8 7.6 7.4 6.8 5.7 5.1 5.0 4.7 3.9 3.7 1.8 1.5 0.9 0.3

Prop Active NEs(%)

44 Becoming a Nascent Entrepreneur: Conception to the Start-Up Process

4.3. Life Context and Start-Ups

45

the entire sample, it is from 16 per 100 (15.8%) to virtually zero – 0.3% or 3 per 1,000 – for these different groups. Table 4.3 presents selected characteristics of the groups, such as their proportion of all nascent entrepreneurs and the proportion of the total sample, which represents the US adult population. A second result of some importance is when different factors become involved in the analysis. Age clearly has the most impact, but the next two factors with significant impact are gender and whether or not the person is engaged in full-time work. It is not until the third round that ethnic background become important, and then only among those that are under 55 years of age. For those over 55 years, the most important factors are either educational attainment or if they are over 65 years of age, withdrawal from the labor market, usually the retirement transition. By the fourth round of the assessment, a variety of factors become involved for different subgroups, labor force activity, educational attainment, household income, gender, and even population growth patterns in the community – higher growth would provide for more business opportunities. It is useful to consider each of the groups separately. Consider, for example, the most active group, A. These are Black men, 18–54 years of age engaged in full or part-time work, where 15.8% – or one in six – is involved in starting a new firm. This is closely followed by Black women, group B. These women are 18–54 years old, have education beyond high school, and 12.3% – or one in eight – report working on a start-up. While this is a high level of participation, these two groups, A and B combined, are – as shown in Table 4.2 – 11% of those trying to start new firms. The largest single group of nascent entrepreneurs is in group C, composed of White, Hispanic, and Other men, 18–54 years of age, and engaged in full-time work. While 9.8% of this group – one in ten – is active in a start-up, they consist of 46% of all those identified as nascent entrepreneurs. This is somewhat higher than the next group, D, also men who are over 55 years in age, engaged in full-time work, and have education beyond high school. For this group, 7.6% are involved in start-ups, but

Prop active NEs (%) 15.8 12.3 9.8 7.6 7.4 6.8 5.7 5.1 5.0 4.7 3.9 3.7 1.8 1.5 0.9 0.3 6.3

Label A B C D E F G H I J K L M N O P

Avg

Prop of all NEs (%) 7.1 4.3 46.2 2.6 0.6 9.7 2.9 19.2 0.4 1.4 0.9 1.8 0.5 0.9 0.9 0.3

Cum prop NEs (%) 7.1 11.4 57.6 60.3 60.9 70.6 73.5 92.7 93.2 94.6 95.5 97.3 97.8 98.7 99.6 99.9 Totals

Prop total populat (%) 2.8 2.2 29.6 2.2 0.5 8.9 3.2 23.5 0.6 1.9 1.5 3.1 1.9 3.5 6.1 8.6

Cum prop populat (%) 2.8 5.0 34.6 36.8 37.3 46.2 49.5 73.0 73.6 75.4 76.9 80.0 81.8 85.3 91.4 100.0

Table 4.3 Participation in start-ups by socio-demographic emphasis

100.0

2.8 1.9 2.7 12.6

0.7

6.7

61.2 4.5 1.1

Prop men (%) 5.8

100.1

16.6

45.6 0.5 3.6 2.9 3.3 1.8 4.2

17.3

4.3

Prop women (%)

99.9

1.6 3.4 1.9 3.7 6.8 9.5

9.2 3.2 25.9 0.6

31.7 2.4

Prop white (%)

100.1

0.5 20.2 1.0 1.7 2.1 3.6 4.0 5.7

1.0 5.6

Prop black (%) 30.7 24.0

100.0

0.7 1.4 1.4 1.7 1.7 3.3

17.8 5.1 26.7 0.1

39.0 1.1

Prop hispanic (%)

46 Becoming a Nascent Entrepreneur: Conception to the Start-Up Process

4.3. Life Context and Start-Ups

47

these late career individuals are only 2.6% of all those in the start-up process. Groups F and H are significant, for they are the non-Black women, 18–54 years of age, who provide 38% of all nascent entrepreneurs. The only difference is that women in Group F are in the top quartile (highest 25%) of the counties with the highest recent population growth, and 6.8% are involved in start-ups; Group H women are in the other three-quarters of the countries with lower population growth; 5.1% are involved in start-ups. The lowest participation, less than 2%, is found among groups M, N, O, and P. These groups are composed of those over 55 years of age, some over 65 years of age, with little education or low household income. These four groups are less than 2.5% of all those involved in the start-up process, but are 20% of the US adult population. This assessment clarifies a major issue associated with selecting career options – that it is both an individual’s background and situation that have an impact on the decision to become involved in the creation of a new firm. Many of these individual characteristics, however, can reflect a range of attributes. Consider age. Older adults are less likely to become involved in a start-up, but they are also more likely to have completed a satisfying career or accumulated personal wealth that reduces the incentive to enter into a new venture; they are also more likely to have reduced energy and more health concerns that reduce the drive to implement a demanding new initiative. Women are less likely to be involved in a start-up, but this may reflect less work experience and other life responsibilities – such as raising a family when they are 25–40 years old, the age at which business creation is the most prevalent. The analysis makes clear the unique situation of Black men and women, who seem to be predisposed toward involvement in start-ups, regardless of other factors. This may reflect a general dissatisfaction with career options available through typical work organizations. While the capacity to analyze a representative sample of 60,000 to determine which individuals are involved in the start-up process has many advantages, the small number of variables – most of which are traditional socio-demographic characteristics – is a major limitation. The results are able to account for 2.3% of the variance, which suggests

48

Becoming a Nascent Entrepreneur: Conception to the Start-Up Process

that a number of other factors may have a role in affecting the decision to become involved in a business start-up. It is useful, therefore, to have the capacity to compare nascent entrepreneurs and representative sample of those not involved in business creation using a wider range of measures.

4.4

Comparison Group Data

There is a great deal of speculation regarding the unique features or situations of those who chose to work on business creation. As summarized in Chapter 3, they cover a range of topics, such as the individual sociodemographic background, current social and work life setting, personal traits and orientations, as well as the business and economic context. To explore the potential impact of such factors, the PSED I design involved a selection of two types of individuals. First, those active in the creation of a new firm – the nascent entrepreneurs discussed above. Second, a sample of those not involved in new firm creation, a group considered to represent typical US adults. For individuals in both groups specialized information was obtained related to a wide range of attributes. This information is useful in determining the unique and distinctive features of those involved in the firm creation process. The results can be summarized as a series of comparisons, such as that related to current social and work life context in Table 4.4.7 These comparisons are based on a simple comparison of distributions between these two types of individuals and with a relative small sample size, so some differences found to be statistically significant in the large screening sample of over 60,000 are not significant in this assessment. A good example is household size and household income; both had statistically significant impacts with the large sample but not with this specialized comparison. This is an indicator of the modest level of impact of these factors. It should be noted that the comparison of household net worth involved six categories, and the difference was due to the larger proportion of those with negative or very low household net worth 7 For

this and the remaining tables in Chapter 4, the details of the sources and results are provided in Appendix.4Ax.2.

4.4. Comparison Group Data

49

Table 4.4 Nascent entrepreneurs and current social, work life context Statistically significant differences [0.05]

Not statistically significant

Household net worth

Household income

Married

Household structure: • Household size: all ages • Household size: adults only • Kids, dependents in household • Adults earning money

Time spend on work during last day off

Time spend on work on last regular workday

More satisfied with most recent job

More satisfied with life overall

Career mentors in social networks • Smaller proportion report any social network • Smaller number of helpers Less time living in the county Born outside the United States Unless otherwise indicated, the statistical significance is at 0.05, using Chi Square or mean comparisons tests

(below $100,000) or a very high net worth (above $1,000,000) among nascent entrepreneurs; a curvilinear relationship. Those active in start-ups were also more likely to report they worked more hours on their last “day off” – but not on their last work day. They also reported greater satisfaction with their most recent job but were not more or less satisfied with life overall. Perhaps surprising, when asked about those available to help them with their careers – either in established roles or in starting a new firm, those involved in a firm start-up were less likely to report there were any mentors; those that did tended to report a small number. The emphasis on immigration and entrepreneurship would suggest that without immigration there would be little firm creation in the United States. Yet there is no difference between nascent entrepreneurs and the comparison group in the proportion born in the United States, it is about 95% for both groups. While those starting a business report a shorter residential tenure in the county compared with the comparison group, 70% have lived in the county for more than five years and 53% for more than 10 years. Clearly, starting a business is not something that people do as soon as they arrive in a new community. The business background and contextual differences are presented in Table 4.5. Judgments about community support were measured with

50

Becoming a Nascent Entrepreneur: Conception to the Start-Up Process

Table 4.5 Nascent entrepreneurs and business background, experience Statistically significant differences [0.05] Entrepreneurial climate: • Perceived less community support

Not statistically significant Entrepreneurial climate: • Family, friends as models • Role models in the community Government, private helping programs: • Knowledge of programs • Reports of contacts • Number of programs contacted

Family and friends encouraged a start-up

Parents owned a business

Positive impression of business ownership from family and friends

Worked for parents Friends and neighbors owned businesses

More classes in general management

More classes on human relations, financial management

More classes in operational management More years of general management work experience More years of operational management work experience Prior 12 years before interview, years: • Full-time self-employment • Less time unemployed, not seeking work • Less time unpaid volunteer work • Less time homemaker • Less time retired • Fewer number of different activities

Prior 12 years before interview, years: • Full-time employment • Part-time employment • Part-time self-employed • Full-time student • Part-time student • Unemployed, seeking work • Disabled, unable to work

Unless otherwise indicated, the statistical significance is at 0.05, using Chi Square or mean comparisons tests

reliable multi-item indices, and while there was no difference associated with considering family and friends as role models or presence of role models in the community, those starting businesses considered there was less community support – helpful bankers or government agencies – than those not creating new businesses. Perhaps their recent personal experience in the start-up process affected these judgments. Surprisingly, adults not involved in start-ups or new firms were just as likely to know about public and private programs to help startups and just as likely to have made contact; there was no significant

4.4. Comparison Group Data

51

difference in the number of programs contacted. This probably reflects a lack of information among the nascent entrepreneurs and previous behavior of adults who were at one time interested in starting a business, but not pursing this at the time of the interview. The effect of perceptions and experiences as they grew up seemed to have a mixed effect. Those starting new businesses were no more likely to report their parents owned and operated a business, to have worked for their parents’ business(es) or to report their friends and neighbors had businesses. On the other hand, nascent entrepreneurs report more encouragement from friends and family and developed a positive impression of small business ownership from observing friends and family with their own businesses. There is substantial evidence that those starting businesses have both more formal classes and more years of work experience in general management and operational supervision. In providing an overview of their labor force activity in the 12 years prior to the interview, nascent entrepreneurs report more years of full-time self-employment, less time unemployed and not seeking work, less time as unpaid volunteers, homemakers, or retired, and fewer number of different activities – suggesting that they were in stable work roles in this period prior to implementing a start-up. Those starting new businesses are considered to have a wide range of personal attributes, capacities, or orientations; comparisons on a wide range of factors are provided in Table 4.6. On a number of these factors nascent entrepreneurs may be unique. Their cognitive style is to improve on situations by doing things differently – rather than with more care. Nascent entrepreneurs rank higher on two related measures, entrepreneurial intensity – a commitment and focus toward entrepreneurial options – and entrepreneurial expectations – a belief that they have the capacity and drive to implement a new firm. Career motivations show no differences related to an emphasis on self-realization, financial security, and independence, and less of a focus on achieving recognition, meeting role expectations, and an interest in innovation. Nascent entrepreneurs report greater personal confidence in social settings, but no difference related to emotional control or shyness. They

52

Becoming a Nascent Entrepreneur: Conception to the Start-Up Process

Table 4.6 Nascent entrepreneurs and traits, orientations, and attitudes Statistically significant differences [0.05]

Not statistically significant

Cognitive style • Prefers doing things differently Greater entrepreneurial intensity Higher entrepreneurial expectations Career motivations, less focus on: • Achieving recognition • Meeting role expectations • Innovation [0.07]

Career motivations, focus on: • Self-realization • Financial security • Independence

Personal confidence in social settings

Emotional control shyness

Prefers group, collective work activities

Prefers high risk/high payoff firms

Prefers challenging, task focus problems

Emphasis on high personal impact

In choosing an appropriate firm: • Examines financial issues • Examines operational issues

Locus of control

Economic sophistication Frequency of unpredictable situations at work Feeling overloaded at work Strategies for difficult work problems: • Problem identification versus solution development Business problem solving • Calculating versus intuitive Unless otherwise indicated, the statistical significance is at 0.05, using Chi Square or mean comparisons tests

tend to prefer group, collective work activities and challenging, task focused problems. There is no difference from other adults in terms of a preference for high risk, high payoff firms or a strong personal impact. In making a choice between two firms as a potential owner, nascent entrepreneurs tend to focus more on financial and operational issues than other adults. There is, however, a long list of traits on which there are no differences between the nascent entrepreneurs and other adults, including locus of control, economic sophistication, frequency of confronting unpredictable situations at work, feeling overloaded at work, and

4.5. Overview

53

strategies for difficult work problems or strategies for business problem solving. Except that they are trying to create a new business, on many characteristics nascent entrepreneurs are a great deal like other US adults.

4.5

Overview

There is no question that millions of US adults make the decision to become involved in a business creation activity. Both the tendency to become involved and the number of individuals seems to have increased in the past eight years; there may be 16 million or more involved in the start-up process in 2006. Who makes the decision to become involved is another issue. It is clear that a number of factors have a major impact on becoming involved in a business start-up, including: • • • • •

Age Gender Current work activity Ethnic background Educational attainment

A range of other factors seem to have an influence, depending on the unique situation, context, or alternatives of the individual. These moderating factors would include: • • • •

Household income Household net worth Recent population growth in the local community Extend and intensity of management and administrative training and experience • Positive impressions and encouragement from family and friends • Strong expectations and a commitment to entrepreneurial career options

54

Becoming a Nascent Entrepreneur: Conception to the Start-Up Process

There is, however, no clear or simple set of factors that are associated with every decision to become involved in business creation. Many are predisposed – by virtue of their unique background, life stage, or current situation – to pursue a new start-up, but there are unique features associated with every nascent entrepreneur that enters the start-up process. What happens in the process and which actually create new firms is the next part of the story.

5 Creating a New Business: Results from the Start-Up

What happens as people start new businesses? What is the final outcome? How long does it take? What types of people complete the startup process to create a new firm? What do they do? Precise answers to such questions require a careful selection of nascent entrepreneurs and systematic follow-ups to determine their activities and the results of their efforts. This was, of course, the major justification for the PSED I project. The data from this representative sample of US start-ups can be used to explore these issues. The outcomes – new firm, disengagement, or continuing with the start-up– for nascent entrepreneurs entering the start-up process is presented in Figure 5.1.1 This exhibit presents the status of these start-up efforts over the first ten years following conception. The initial bar indicates that 100% are active in the start-up process and that after one month 1% have quit and 2% report a going business. All 24 periods up to the end of year six cover 3 month intervals, the last three periods 12 month intervals. 1 Development

of the customized data set for the following analysis is described in Appendix.5Ax.1. The outcome status for every case in the data set is provided in Appendix.5Ax.2.

55

56

Creating a New Business: Results from the Start-Up

Fig. 5.1 Start-up transitions, by time since conception

At the end of nine years and 12 months – or ten years – 37% report they have left the process, 34% report a going business, 28% are still active in the start up effort and 1% are not currently active in the startup process but will not admit that they have completely given up–the undead, as it were.2 As the actual data collection took place over a five year period, the status reported at the end of six years – or the beginning of the seventh year – will be used for subsequent analysis. The major finding, then, is that seven years after entering the firm creation process, about one-third have quit, one-third report a going business, and about one-third are still working on the start-up. Some of the “still working on the start-up” group report that they have been trying for 15 or more years. It would appear that for these nascent entrepreneurs the start-up effort is an interesting hobby, not a serious option for a work career.

2 There

is little change in the pattern out to 20 years.

57 How long does the start-up process last? It is clear that for some it can take decades, as one in five of these nascent entrepreneurs seem to be involved forever. It is possible, however, to track the time involved in the process by those that leave, either by starting a new firm or disengaging from the process. The time from the first start-up activity, conception, to the date when a person reported that they have started a business or disengaged from the effort is presented in Figure 5.2. Time is presented in six month intervals and the total proportion of cases in each category is presented at each time period. As the status at the end of the sixth year is used to classify the start-up efforts, 100% of the new firms and quits are accounted for at the end of the six year period. That small proportion that took longer than six years for a resolution are not included in this analysis. There is a clear difference in the two processes. In the first six months, for example, 18% of the new firms are created but only 2% of those that disengage have quit. The median time for a new firm birth

Fig. 5.2 Time from conception to transition: new firm birth or disengagement

58

Creating a New Business: Results from the Start-Up

is 19–24 months, but it is 25–30 months for disengagement – about six months longer. By 36 months, 75% of the new firms are created, but it takes 42 months for 75% of those who quit to disengage. By 48 months after entry into the start-up the percentages are similar; 10% of the start-ups and 10% of the disengagements take over four years. That there are differences in the time to leave the process is not a surprise, as it may take a while to determine that a given initiative is not economically viable. It is useful, however, to have this more precise information on the typical time required to exit the start-up process.

5.1

What Kinds of People Create and Types of Start-Ups Become New Firms?

The critical issue, of course, is who finishes the process with a going business. To explore this topic, those 200 that reported a going business will be compared with the other 448; 222 that disengaged and 226 still active in the start-up process after seven years. Information for the comparison can be considered in seven categories:3 • • • • • • •

Socio-demographic background Current social, work life context Personal traits, orientations, and attitudes Business background, experience Business, economic context Business activity, investments Ambient community

As before, those statistically significant factors can be compared with those that indicate no statistically significant relationships. Details are provided in the Appendix.5Ax.3. The basic socio-demographic characteristics affecting entry into the start-up process are presented in Table 5.1. Remarkably, almost none have a statistically significant effect on completion of the process with a new firm. In fact, the two most 3 Data

is taken either from the phone interview and mail questionnaires administered as part of the PSED I initial interviews or, for ambient community measures, from federal data on the counties in which the respondent was located.

5.1. What Kinds of People Create and Types of Start-Ups Become New Firms?

59

Table 5.1 Firm creation and socio-demographic factors Statistically significant differences [0.05] Ethnicity

Not statistically significant Gender Age at entry into the start-up Age, gender interaction (subgroups) Educational attainment Parents owned a business Worked for parents business Friends, neighbors owned business Encouraged by friends, family Impression of business ownership from friends, relatives Years lived in county Years lived in state Born outside the United States

Unless otherwise indicated, the statistical significance is at 0.05, using Chi Square or mean comparisons tests

powerful attributes related to participation in the start-up process – age and gender – have NO statistical significance in reports by nascents that a new firm is in place. In this case, age has been computed at the time when entry into the start-up process – or conception – occurred. This may be up to ten years before the initial interview. Given the significance of age and gender on entry into the start-up process, their joint impact is illustrated in Figure 5.3. Almost twice as many young women, 18–24 years of age, report a successful firm birth as their male age peers; more than twice as many older men, 55 years and up, report a successful firm birth as their female age peers. Because of the small number of cases of very young or old nascent entrepreneurs, these differences are not statistically significant. This is, of course, in dramatic contrast to the impact of age and gender on entry into the start-up process, as illustrated in Figure 4.2 in the previous chapter. One background factor with a statistically significant association with the outcome is ethnic identification. The results are dramatically different from those related to entry into the start-up process, and these differences are emphasized in Figure 5.4. While Blacks are almost twice as likely (9.5/100 versus 5.7/100) to report participation in start-ups than Whites, they are much less likely to report completion of the process with a going business. Hispanics are more likely to report start-up

60

Creating a New Business: Results from the Start-Up

Fig. 5.3 New firm prevalence by gender and age at start-up conception

participation than Whites, and are just as likely as Whites to report completion of the process with a new firm. Blacks, on the other hand, are no more likely to have quit than Whites or Hispanics, but are much more likely to report they are still active in the start-up process – they are more tenacious than others. A more precise discussion of differences in ethnic start-up activities is provided later in the chapter. Perhaps, equally significant is the range of background characteristics that do not seem to have any statistically significant impact on which start-ups become new firms: educational attainment, parental ownership of a small business, work experience in the parent’s business, friends and neighbors with businesses, encouragement by friends and family members, a positive impression from observing friends and relatives businesses, years lived in the county or state and whether or not the person was born in the United States. A review of thirteen factors reflecting the current social and work context is provided in Table 5.2. Those who report a new firm birth

5.1. What Kinds of People Create and Types of Start-Ups Become New Firms?

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Fig. 5.4 Entry into start-ups and outcomes: by ethnic identity

are more satisfied with life overall and report LESS time devoted to the start-up on their day off; none of the other factors are statistically significant. These factors include satisfaction with the most recent job, household income, household net worth, martial status, household structure, i.e., size of the household measured three ways, time at work on the last workday or day off and time working on the start-up on the last day off. The relationship of personal traits, orientations, and attitudes to reports of a new firm are summarized in Table 5.3. Six factors reflect a statistically significant association with reporting a new firm birth; internalized locus of control, more confidence in social settings, a cognitive style that emphasizes doing things better rather than a new approach, some level of economic sophistication about the current value of assets, a preference to avoid working in collaboration with a group, and expectations about firm survival for five years. More than twenty-five other factors show no statistical significance, including emotional control, shyness, business problem solving

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Table 5.2 Firm creation and current social, work life context Statistically significant differences [0.05]

Not statistically significant

Satisfied with life overall

Satisfied with recent job Household income Household net worth Martial status Household structure Household size • All persons • Adults only • Persons with income Time use reports, total hours working: • Last workday • Last day off Time use reports, hours on start-up: • Last workday

Time use reports, hours on start-up: • Last day off (fewer hours)

Unless otherwise indicated, the statistical significance is at 0.05, using Chi Square or mean comparisons tests

strategies, defining problem complexity, economic sophistication about sunk costs, a preference for challenging task focused problems compared with a social focus, emphasis on high payoff/high risk choices or high personal impact choices, criteria used to assess choices between firms, six aspects of career motivations (self realization, financial security, recognition, meeting role expectations, innovation, and independence), entrepreneurial expectations and intensity, expectations about firm size in the first and fifth years, preference for firm growth, expectations firm proceeds will be a major source of household income, perception of work demand pressures, the sequence in which the business idea and motivation were activated, beliefs about the sources of good business ideas. The impact of business background and experience is summarized in Table 5.4. There is strong evidence of the benefit of work experience, reflected in more years of full-time paid work experience and work in administrative, supervisory or managerial positions, more experience in the same industry as the start-up, less experience in unpaid volunteer work or unemployed seeking a job, more general management and operational management work experience, and more human relations and finance classes.

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Table 5.3 Firm creation and personal traits, orientations, and attitudes Statistically significant differences [0.05] Locus of control Confidence in social settings Cognitive style • Doing better, not different things Economic sophistication • Focus on current value in decisions, not cost to acquire Prefers individual work activities

Expect firm to be operating in five years

Not statistically significant Emotional control Shyness Business problem solving

Defining problem complexity Economic sophistication • Ignore sunk costs in current decisions Prefers challenge/task focus versus social focus Emphasis on high payoff/high risk choices Emphasis on high personal impact choices In choosing between firms, emphasizes: • Financial issues • Operational issues Career motivations • Six dimensions Entrepreneurial expectations Entrepreneurial Intensity Sales in first or fifth year of operation Jobs in first or fifth year of operation Prefer firm to grow as much as possible Expect firm to major source of HH income Expected equity ownership in five years Perception of work demands • Three measures Motivation/Business idea sequence Belief in systematic search for good ideas Belief good ideas just occur

Unless otherwise indicated, the statistical significance is at 0.05, using Chi Square or mean comparisons tests

There is no evidence that the number of labor force events over 12 years in nine other areas, prior start-up experience, or general and operational management classroom experience is associated with reports of a new firm. Two aspects of the business and economic context, as reviewed in Table 5.5 seem to have an association with completing the startup process; the presence of social challenges among start-up problems and a perception that operational aspects are more challenging in the

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Table 5.4 Firm creation and business background, experience Statistically significant differences [0.05]

Not statistically significant

Years of full-time paid work experience Years of administrative, supervisory, or managerial experience Labor force activity in prior 12 years, less activity as one who is: • Unemployed seeking work • Unpaid volunteer work Same industry experience General management work experience Operations management work experience Human relations, finance classes [0.07]

Labor force activity in prior 12 years • Overall activity counts • Nine specific activities Prior start-up experience General management classes Operational management classes

Unless otherwise indicated, the statistical significance is at 0.05, using Chi Square or mean comparisons tests

Table 5.5 Firm creation and perceived business, economic context Statistically significant differences [0.05] Start-up problems: social challenges

Economic, community contextual uncertainty: • Operational aspects more challenging

Not statistically significant Start-up problem index Start-up problems: personal challenges Entrepreneurial climate • Three dimensions Economic, community contextual uncertainty: • Overall • Financial • Competition

Unless otherwise indicated, the statistical significance is at 0.05, using Chi Square or mean comparisons tests

immediate community. A number have no relationship, including a general start-up problem index, start-up problems associated with personal challenges, three aspects of the perceived entrepreneurial climate (presence of community support groups, friends and family role models, and role models in the community) , and three aspects (financial, competitive, and operational) of the economic, contextual uncertainty in the immediate community. A number of items related to the actual activities or immediate context associated with the start-up, presented in Table 5.6, have a statistically significant relationship with a new firm birth.

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Table 5.6 Firm creation and business activity, context, start-up investments Statistically significant differences [0.05] Total start up team hours, conception to first interview Average hours per start-up team member, conception to first interview Average total hours per month, conception to first interview Average hours per month per team member, conception to first interview Total funds invested at first interview Average funds per month per team member, conception to first interview Average funds per member at first interview Average funds per month, conception to first interview Legal form • Partnership less successful Proportion legal new firm ownership • If over 50% institutional ownership Size of start-up team [0.09] • Four person team less successful Any contact with helping programs

Business plan sophistication Competitive strategy • Hi tech

Low tech emphasis [0.08]

Not statistically significant

Economic sector • Five types Type of location

Number of programs known about Number of programs contacted Nature of helping programs Hours spent receiving program assistance Value of help provided (estimated) Accounting sophistication Competitive strategy • New, quality products • Lower prices • Superior location, convenience • Niche markets • Superior quality Social network • Presence reported • Average number of persons

Unless otherwise indicated, the statistical significance is at 0.05, using Chi Square or mean comparisons tests

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Several measures associated with amount and intensity of activity are related to reports of new firms.4 Measures related to the amount of time or the amount of funds committed to the start-up are tracked from conception to the first detailed interview; this includes total hours devoted to the start-up by all team members, average hours per team member, average total hours per month, and average hours per month per team member. Similar measures are developed regarding funding provided by the team members, as reported in the first interview. These include total funds provided by all team members, the average per team member, the total per month prior to the first interview, and the total per month per team member. Both the amount and intensity are related to reports of new firm births. Partnerships, as one type of legal form, seem to be less likely to lead to a firm birth; if over 50% of the start-up is owned by an existing business or institution a new firm is more likely. Four person start-up teams seem to be less successful than others.5 Contact with helping programs – no matter who is providing the help – seems to facilitate new firm creation. More sophisticated business plans and a competitive strategy based on high technology seem to be helpful, although another measure seems to indicate low technology start-ups are more likely to report a new firm. A number of other factors have little relationship to a new firm birth: the actual industry or market sector, type of location where the firm is “housed,” a number of measures about the sponsorship and intensity of help provided by a helping program, the level of accounting sophistication, five aspect of competitive strategy, and the presence and size of helping social networks. A number of factors related to the county in which the start-up process was taking place were examined to determine the potential 4 Because

of highly skewed distribution of hours and financial commitments, the patterns were classified into four groups and a cross tabulation assessed; the results, as shown in Appendix.5Ax.3, are highly statistically significant. Comparison of average values, reflecting the impact of extreme cases, are less significant. 5 Ironically, substantial research with decision making in discussion groups indicates that four person groups have the most egalitarian influence structures, suggesting that they may have more problems reaching consensus and arriving at a decision. This may have prevented these groups from developing an effective procedure for making the decisions required in moving forward with the start-up (Reynolds, 1971a).

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Table 5.7 Firm creation and ambient community Statistically significant differences [0.05] Population density, persons/square mile • Low density, more new firms Urbanization index, four items • Least urbanized, more new firm

Not statistically significant Per capita total personal income Percent households with annual income of $75,000 or more Percent population 25–44 years old Percent population 25 years and older with college degrees Average annual population growth

Unless otherwise indicated, the statistical significance is at 0.05, using Chi Square or mean comparisons tests

impact of the ambient community using measures based on harmonized data from federal sources; these are presented in Table 5.7. Two measures capture an urban–rural dimension. These include the county population density and a four item county urbanization index based on per capita income, percent high income households, percent population 25–44 years of age, and percent adult population with college degrees. Both urban–rural measures have a statistically significant relationship to the proportion of new firms that emerge from start-ups, but only when the sample is sorted into quartiles. The result, surprisingly enough, is that those in the least urbanized context with the lowest population densities are more likely to report a new firm had emerged from the start-up initiative. This may reflect the absence of competition in these rural areas or the determination of the start-up team to implement the business to avoid moving out of the area. Five other measures, found to have a positive to regional comparisons of new firm birth rates had no statistically significant relationship to the proportion of start-ups that became new firms: per capita total personal income; percent of households with high annual incomes, in excess of $75,000 per year; percent or young adults (25–44 years of age) in the population; percent of the population 25 years and older with college degrees; and population growth. The result of this effort to consider the characteristics of the individuals staring new firms, their situation, and the basic features of the anticipated new business are rather dramatic. About 100 features, depending on how they are counted, have little or no relationship to

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the reports that a new firm was established. About 30 seem to have some statistically significant relationship to the reports of an operating business. But many of these thirty are reflecting the same features – intensity of involvement measured by time and money as well as past work experience – as related to the implementation of a new firm. The large mass of indicators reflecting perceptions, attitudes, sociodemographic backgrounds, strategic focus and the like seem to have very little impact on which nascent entrepreneurs are reporting that a new firm has been created. This suggests that more attention should be given to what these start-up teams are doing, rather than who they are – or think they are. Fortunately, the PSED I data set provides a description of what has been done to implement a new firm – and in some detail.

5.2

Start-Up Activity

What do nascent entrepreneurs do as they work to establish a new business? While the basic task requires the assembly and coordination of human and financial resources to achieve business objectives, a large number of discrete activities are involved. It is possible to ask those active in the firm creation process which types of events they have pursued; twenty-seven are used in this assessment, dozens more could have been included. Table 5.8 provides the PSED I list of activities, indicating those reported in each of the first six years of the start-up effort. The entries represent the proportion of the startup efforts that report the initiation of each activity. Some activities are only done once – such as open a bank account or apply for an Employer Identification Number [EIN]. Other activities may continue for some time – such as revisions of a business plan, updates of financial projections, or hiring individuals as the business is established and expands. The start-up activities in Table 5.8 are rank ordered by the proportion of start-up efforts that reported initiating the activity by the sixth year after they began the start-up process – seven years after the start-up conception. Four are related to filing taxes or listing with a credit rating bureau and are presented at the bottom, 22 reflect

Activity/Event Time thinking about the new business Define market opportunities Investment own money Purchased raw materials, inventory, supplies, components Developed product or service model or prototype Promotion of product or service has started Began to save money to invest Purchased, leased plant, equipment, property Organized a start-up team Received any money, income, or fees Prepared a business plan Develop financial projections Established an exclusive bank account Established supplier credit Devoted full-time to start-up effort, 35+ hrs/week Arranged child care, household help Asked financial institutions or other people for funds Installed dedicated phone line Taken any classes or workshop Initial positive monthly cash flow Initiated a phonebook or internet listing Hired an employee for pay Patent, trademark, copyright application submitted Filed first federal income tax return Paid first federal social security tax payment Paid first state unemployment insurance tax Know firm listed with Dun and Bradstreet

Table 5.8 Business creation activities First month (%) 66.2 20.2 23.8 13.5 22.3 5.0 22.8 8.3 11.2 4.4 15.5 6.1 3.3 2.9 3.9 2.2 3.8 2.6 11.7 0.6 1.9 1.3 1.4 7.3 2.0 1.3 0.1

First year (%) 89.9 61.7 67.1 52.1 59.9 37.8 49.5 36.7 43.6 30.3 45.0 31.6 29.4 23.7 19.4 19.6 21.4 14.8 24.2 8.4 10.9 8.1 10.1 24.5 11.5 6.7 1.9

Second year (%) 96.2 18.3 81.1 69.5 70.7 57.6 61.0 53.7 56.8 50.2 56.4 46.2 43.1 39.3 33.4 29.8 28.6 25.0 30.9 16.7 20.2 17.9 17.1 35.5 22.1 14.3 3.9

Third year (%) 97.3 84.3 86.4 77.7 76.5 66.1 64.1 62.3 62.4 59.7 60.4 53.7 51.2 45.7 40.1 34.6 33.6 30.5 33.3 23.5 25.9 23.7 20.5 43.1 27.6 18.1 6.0

Fourth year (%) 98.0 87.9 87.6 80.1 78.4 71.7 67.2 66.4 65.8 63.8 62.6 58.0 55.0 49.6 44.1 37.4 35.5 34.3 34.5 29.2 28.3 27.2 23.0 46.4 31.1 20.7 6.9

Fifth year (%) 98.9 89.7 89.1 81.3 79.2 73.2 68.9 68.3 67.3 66.4 64.8 59.2 56.8 51.6 46.6 38.9 37.0 36.2 35.5 31.3 30.6 29.1 24.5 48.4 33.3 21.3 8.3

Sixth year (%) 99.2 90.6 90.4 81.7 79.6 74.5 69.8 69.3 68.1 67.5 66.2 61.0 58.4 52.8 47.8 39.7 38.3 37.7 36.2 32.9 31.2 30.3 24.9 48.9 34.0 22.1 8.6

5.2. Start-Up Activity

69

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actions taken to implement the new business, and one, giving serious thought to the new start-up, is related to a personal focus on the initiative. As the proportion initiating each activity in the first month and in each successive year is indicated, the cumulative proportions will either stabilize or increase over time. It should be no surprise that giving thought to the new business is not only the most widely reported activity, but two-thirds (66.2%) report serious thought about the startup by the end of the first month. On the other hand, one-third have not reported serious thought by the end of the first month; it is not reported by over 95% of the nascent entrepreneurs – 19 in 20 – until the third year. Aside from serious thought, no other activity is reported by more than one in four of the nascent entrepreneurs as having occurred in the first month. More than one in five report they have defined market opportunities, invested their own money in the start-up, developed a product or service model, or begun to save money to invest. More than one in ten report they have purchased raw materials, inventory or supplies; started to organize a start-up team; developed a business plan or taken a workshop or class on creating a business. Some activities are reported by less than one in fifty in the first month, including hiring any employee, initial positive monthly cash flow, or the first listing of the firm’s phone or internet address. It is awkward to try to summarize the processes that involve 23 different activities, setting aside the four that involve meeting tax requirements or registration with a commercial credit rating service. A factor analysis, summarized in Appendix.5Ax.3, indicated that these 23 activities could be re-organized into six domains:

(1) Business presence: The emphasis is on formal registration of the firm, full-time attention by the nascent entrepreneur and the beginning of hiring employees. [five items] (2) Production implementation: Attention to acquiring inputs (supplies, inventory, components), use of major assets, actual sale of the product or service. [six items]

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71

(3) Organizational, financial structure: Mobilizing individuals, preparing future plans, and acquisition of outside financial resources. [four items] (4) Personal planning: The nascent entrepreneur’s efforts to prepare for the business and their personal involvement. [three items] (5) Personal preparation: The nascent entrepreneur’s organization of their personal life to become involved, by taking classes, saving money, or arranging for help with childcare or housework. [three items] (6) Focus on task or the product: Attention to developing the product or service to be sold and acquiring formal property rights to same. [two items] For each domain and for each time period, an index was created by computing the average number of activities that had been initiated by the beginning of the time period. For each index, the range in values could be from zero to 100%. The relationships of this index to the three outcomes seven years after conception are presented for six time periods in Table 5.9. The earliest time period is based on reports of activities initiated in the first month, followed by those initiated in the first six months, the first year, and three following years. The statistical significance is presented in brackets below the index values for each outcome. Of the six indices, only one, personal preparation – saving money, arranging child care, taking classes or workshop – appears to have no relationship to the outcome in the seventh year. All other indices have, for some time periods, a statistically significant relationship to the seven year outcome. This seems to occur earliest and be the strongest for indicators of business presence – establishing a bank account, creating a phone book listing and a dedicated phone line, hiring employees and full time devotion to the start-up; those reporting these activities in the first month seem to be more likely to have a new firm six years later. Active engagement in developing a productive mechanism and creating an organizational and financial structure also seems to have a strong association with the emergence of a new firm. Two other

Business presence New firm Disengagement Active start-up Stat sign Production implementation New firm Disengagement Active start-up Stat sign Organizational, financial structure New firm Disengagement Active start-up Stat sign Personal planning New firm Disengagement Active start-up Stat sign Personal preparation New firm Disengagement Active start-up Stat sign Task, product development New firm Disengagement Active start-up Stat sign

Start-up activity index 12.9% 7.0% 9.1% [0.003] 23.6% 18.6% 16.2% [0.006] 27.4% 23.7% 19.0% [0.008] 57.1% 61.3% 53.6% [0.05] 21.2% 25.1% 21.8% [0.21] 28.0% 26.5% 21.8% [0.06]

6.4% 5.6% 5.3% [0.61] 9.8% 8.5% 9.2% [0.72] 36.5% 36.8% 36.9% [0.99] 12.3% 13.6% 13.7% [0.69] 12.1% 12.3% 11.2% [0.86]

Sixth month

3.4% 2.2% 1.8% [0.04]

First month

38.8% 36.4% 29.8% [0.007]

29.7% 33.6% 29.7% [0.26]

75.1% 74.8% 68.7% [0.05]

41.8% 36.7% 28.2% [0.0000]

41.0% 27.9% 26.2% [0.0000]

24.6% 15.1% 10.4% [.0000]

First year

46.2% 45.9% 39.6% [0.05]

39.6% 41.5% 40.5% [0.81]

86.5% 87.6% 81.3% [0.02]

53.8% 49.1% 38.3% [0.0000]

60.7% 44.0% 39.1% [0.0000]

42.5% 23.9% 18.3% [0.0000]

Second year

Table 5.9 Start-up indices and outcomes in the sixth year, by time since firm conception

50.3% 49.5% 45.7% [0.26]

45.0% 42.9% 44.2% [0.79]

91.1% 91.4% 85.4% [0.004]

59.6% 53.7% 44.6% [0.0000]

74.1% 49.0% 45.7% [0.0000]

53.7% 28.3% 22.0% [0.0000]

Third year

58.3% 51.2% 48.2% [0.31]

47.7% 44.9% 46.6% [0.66]

92.4% 93.1% 88.0% [0.01]

63.0% 55.6% 48.1% [0.0000]

79.7% 51.8% 50.3% [0.0000]

59.7% 30.5% 25.2% [0.0000]

Fourth year

72 Creating a New Business: Results from the Start-Up

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73

indices – related to personal planning and task or product development, also seem to have a significant relationship to the six year outcome, although it is not as strong as the other three and, in the case of product development, the association with the outcome after the second year is no longer statistically significant. Based on the statistical significance of these domains of activities with the start-up outcome, it would appear that an emphasis on establishing a public presence for the business and developing a mechanism or process for delivering the goods or services, along with creating an organizational and financial structure, are important in reaching a resolution to the start-up initiative. Personal planning seems to help facilitate a resolution, as does a focus on the product or service itself in the early period. There is little evidence that personal preparation is different among those with different outcomes. Is the level of intensity related to the time required to reach a resolution? Resolution can only be determined for those who report starting a business or quitting the initiative during the study. The relationship of the activity indices to the time between conception and the two outcomes are presented in Table 5.10. The results are quite striking, as it is clear that up through the first year or two more activity in all domains seems to result in a faster resolution – the new firms are implemented sooner or the nascent entrepreneur is quicker to disengage from the start-up. Up through the second year all correlations are negative (more activity reduces the time lag) and most are highly statistically significant. This pattern continues through the third and fourth year for the time lag to an operating business, but is less significant in the later years for the disengagement correlations. Only the level of personal planning has the same pattern across all years in relation to disengagement; the more personal planning the quicker the individuals are to disengage from a start-up. This may reflect a change in the nature of the individuals who are “slow to quit.” There may be a substantial proportion that put intense effort into the start-up and disengage when it appears it may not work out. Another group is less involved and takes much longer to make a decision to quit, a decision made after they have spent a number of

Statistical significance: ∗ 0.05;

−0.29∗∗∗ −0.34∗∗∗ −0.32∗∗∗ −0.37∗∗∗ −0.15∗ −0.18∗∗ −0.11 −0.22∗∗∗ −0.23∗∗∗ −0.44∗∗∗ −0.18∗∗ −0.23∗∗∗

−0.07 −0.00 −0.04 −0.27∗∗∗ −0.11 −0.13∗

Sixth month

−0.16∗ −0.08 −0.17∗∗ −0.29∗∗∗ −0.07 0.02

First month

∗∗ 0.01; ∗∗∗ 0.001.

Time to operating business Business presence Production implementation Organizational, financial structure Personal planning Personal preparation Task, product development Time to disengagement [Quit] Business presence Production implementation Organizational, financial structure Personal planning Personal preparation Task, product development

Table 5.10 Start-up domains and time to complete transitions

−0.40∗∗∗ −0.46∗∗∗ −0.37∗∗∗ −0.42∗∗∗ −0.15∗ −0.21∗∗ −0.04 −0.12∗ −0.17∗∗ −0.39∗∗∗ −0.07 −0.16∗∗∗

−0.15∗∗ −0.24∗∗∗ −0.27∗∗∗ −0.47∗∗∗ −0.18∗∗ −0.24∗∗∗

Second year

−0.37∗∗∗ −0.45∗∗∗ −0.38∗∗∗ −0.41∗∗∗ −0.13∗ −0.25∗∗∗

First year

0.03 0.02 −0.11 −0.29∗∗∗ −0.02 −0.06

−0.39∗∗∗ −0.49∗∗∗ −0.38∗∗∗ −0.38∗∗∗ −0.11 −0.14∗

Third year

0.08 0.11 −0.04 −0.21∗∗ 0.05 −0.03

−0.36∗∗∗ −0.44∗∗∗ −0.30∗∗∗ −0.30∗∗∗ −0.07 −0.07

Fourth year

74 Creating a New Business: Results from the Start-Up

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75

Fig. 5.5 Cumulative start-up activities by seven year outcomes

years on the effort and have not made much progress. Hence, after the initial “early decision” group has made their choice, the “late decision group” is still making an effort to “get the business organized.” Complementing this information is a presentation of the number of activities reported over time in Figure 5.5. Again, the start-up efforts are presented on the basis of their status at the end of the sixth year. The average number of activities initiated during the first month is about two, regardless of the outcome six years later. The average initiated six years later is 14 to 16 for those who report a going business or who have withdrawn from the effort. Those who continue to be involved in a start-up report initiation of 11 different activities. At no time is there a statistically significant difference between the activities initiated by those with a going business or who quit after seven years. But after six months those in these two groups report a statistically significantly higher level of activity than those still in the start-up process for every time period until six years after conception.

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In summary, then, the following patterns seem to be present: • Some domains of activities appear to be associated with higher proportions of new firm births, such as establishing a business presence, focusing on production of a good or service, or attending to the organizational and financial structure. • Other activities are less associated with reports of a new firm, such as personal planning or task and product development. • The same domains associated with success at creating a new firm are associated with a reduced time to either a new firm or disengagement from the start-up process. • Those that reach a resolution of the start-up success seem to implement more activities sooner in the process. It is, of course, quite appropriate to try to determine the relative importance of the various factors known to have a significant effect on the emergence of a new firm from the start-up process.

5.3

Interactions: Who They are and What They are Doing?

The preceding assessments have emphasized the relative impact of individual variables, considered one at a time; attention was then paid to groups of related start-up activities. This leads to two obvious questions: • What is the relative importance of different individual, team factors or start-up activities? • Is it possible that the interaction between different individual, team factors and start-up activities can have a unique impact on the outcome – implementing a new firm? Both issues can be addressed with the same analysis utilized in Chapter 4 to explore the different factors affecting participation in a start-up (Tables 4.2 and 4.3). The same procedure is followed in this assessment. A set of factors considered to be related to an outcome – in this case reports of a new firm seven years after conception – is explored to identify the single

5.3. Interactions: Who They are and What They are Doing?

77

most important factor. The sample is partitioned into subgroups on this factor and for each subgroup the procedure is repeated using the remaining variables. As the sorting and analysis at each stage is completed independently for each subgroup, as the network of subgroups expands each path can lead to the identification of quite different sets of independent variables for the final set of subgroups. The analysis was implemented using 33 independent variables, chosen to maximize the size of the sample. As 25% of the respondents did not complete the self-administered mail questionnaire, a number of variables were excluded. Even so, missing data reduced the sample of 648 to 566 for this assessment; weights were, of course, re-centered so the sample would continue to represent all US nascent entrepreneurs in the start-up process. The ten variables selected as important in making predictions, as well as the 23 that were not, are presented in Table 5.11. The variables with predictive value are ranked ordered in terms of predictive Table 5.11 Factors selected as important in predicting new firm presence Overall importance [ranked]

Not important

Production implementation activity Business presence activity Nascent same industry experience Total start-up team funds invested Focus on task or product activity Nascent personal preparation activity Start-up team funds invested per month Industry sector [five categories] Nascent age at entry into start-up Length of residence in the state

Start-up team size Proportion of legal entity ownership Gender Labor force participation Household annual income Household net worth Ethnic background Organizational, financial structure activity Nascent personal planning activity Nascent born in/out of US Length of residence in the county Educational attainment Nascent experience with other start-ups Cognitive style [different versus better] Total hours devoted to start-up Avg hours/team member on start-up Avg hours/month on start-up Avg hours month/team member on start-up Funds provided/team member Funds provided/team member/month Average annual population growth Population density, persons/square mile Urbanization index, four items

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Creating a New Business: Results from the Start-Up

usefulness. The emphasis is on major activity domains (production implementation, business presence), industry experience, and funds invested by the start-up team. The long list of factors that have little predictive value include gender, ethnic background, household income and wealth, time devoted to the start-up, and any characteristics of the ambient or host county. The potential interaction and the ability to make distinctions among groups are presented for the first four levels of analysis in Tables 5.12 and 5.13.6 The result is ten groups, four identified by four factors and the others identified by three. To minimize idiosyncratic variation, groups with less than 20 cases were not further subdivided. The groups are rank ordered in terms of the percentage reporting a new firm startup in the seventh year in Table 5.12. The results range from 81% of those in group A to 5.2% of those in Group J; this considerable range – a factor of 16, suggests these features are quite successful in separating start-ups that lead to new firms from those that do not. The resulting “model” explains 21% of the variance in the outcome – firm births. To capture possible differences associated with gender, ethnic background, and age, the differences across these groups are provided in Table 5.13. The cell entries indicate the difference between the actual value and that expected if the overall prevalence was uniform across all groups. The result, for example, indicates that the number of women in Group C (row C) was 28% more than would be expected if there was no variation across groups. The differences across groups are statistically significant for all three factors. This suggests that differences associated with the primary features of these ten groups are reflected in comparisons based on age, gender, and ethnicity. But age, gender, and ethnicity are not – in themselves – the critical source of differences in start-up success. Age, gender, and ethnicity are related to how individuals chose to pursue a firm start-up in terms of activity domains,

6 The

analysis was completed with the DTREG procedure version 3.5 developed and provided by Phillip H. Sherrod “www.dtreg.com.” This model used a single tree with five splitting levels, classification analysis, Gini splitting algorithm, equal priors settings, equal misclassification costs, equal weights on all variables, with a five fold true pruning and validation method with ten folds. All cases with missing values on any independent variables were removed and the results were weighted with WTW1, after it was re-centered.

Production implement: high Production implement: low Production implement: low

Production implement: low

G H I

J

Average values

Production Production Production Production

C D E F

high high low low

Production implement: high

B implement: implement: implement: implement:

Production implement: high

First level

A

Group

invested: under $3,000

Business presence: low Invested: $3,000 and up Invested: under $3,000

Business presence: high Business presence: low Invested: $3,000 and up Invested: under $3,000

Business presence: high

Business presence: high

Second level

Industry exper: none

Industry exper: 0–5 years Personal preparation: high Industry exper: 1+ Yrs

State tenure: 10 or more yrs Industry exper: 6+ years Personal preparation: low Industry exper: 1+ Yrs

State tenure: 10 or more yrs

State tenure: 10 or more yrs

Third level

Table 5.12 Start-ups grouped by second year activity and seven year outcome status

Invested: under $30/month

Invested: over $30/month

Industry exper: 6 or more yrs Industry exper: 0–5 yrs

Fourth level

30.8%

5.2

22.4 11.8 9.9

49.0 47.0 35.6 23.5

53.9

81.3

Prop new firms (%)

5.3. Interactions: Who They are and What They are Doing?

79

80

Creating a New Business: Results from the Start-Up

intensity of focus, and accumulation of the funds needed to implement a new firm. Second, the analysis leads to groups of start-up initiatives with different characteristics and different outcomes, identified in Tables 5.12 and 5.13 by letters, from A to J. The groups can be described as follows: Group A is characterized by a major emphasis on implementing a production process – purchasing raw materials, arranging for assets, supplier credit, initial receipt of income – and establishing a business presence – bank accounts, dedicated phone lines and listings, full time effort of the respondent, and hiring of an employee. These nascent entrepreneurs have lived in the state for more than ten years and have six or more years of industry experience. While they represent only 9% of all start-ups, the fact that 81% are reporting an operating new business indicates they are 23% of all new firms in this sample. Men, Whites, and those 35–54 years of age are slightly overrepresented in this group. Group B is almost identical to Group A except they have less than six years experience in the same industry as the start-up. There is an overrepresentation of Whites, women, and those under 34 or over 55 years of age. They are 4% of the start-up efforts and as 54% report a new firm, they are 6% of all start-ups. Group C reflects a strong emphasis on both the production process and establishing a business presence and more than ten years residence in the state. There is a slight over-representation of Whites, men, and those over 54 years of age. This group is 6% of the start-ups and because 49% report success, they are 10% of new firms. Group D also reflects a strong emphasis on production implementation, but a low emphasis on business presence, and these nascents report six or more years of same industry experience. The group has a slight

81.3 53.9 49.0 47.0 35.6 23.5 22.4 11.8 9.9 5.2

30.8

Group

A B C D E F G H I J

Average

22.8 6.6 9.7 16.0 19.5 8.9 8.6 2.7 3.4 1.8

Prop all new firms (%) 22.8 29.4 39.1 55.1 74.6 83.5 92.2 94.9 98.2 100.0

Cumul prop of new firms (%) 8.9 3.9 6.3 10.8 17.3 12.0 12.2 7.2 10.7 10.8

Prop of start-ups (%) 8.9 12.7 19.0 29.8 47.1 59.1 71.3 78.5 89.2 100.0

Cumul prop of start-ups (%)

61.1

Prop men in start-ups (%) (1) 6.7 −28.4 16.6 3.1 9.9 −2.5 −10.7 −4.0 −5.4 −0.8

Chi-square statistical significance.

Note: (1) Deviation from overall average. (2) Other ethnic omitted.

Prop new firms (%)

Table 5.13 Start-ups groups by socio-demographic emphasis

[0.01]

38.9

Prop women in startups (%) (1) −6.7 28.4 −16.6 −3.1 −9.9 2.2 10.7 4.0 5.4 0.8 72.4

Prop whites in start-ups (%) (1,2) 7.5 24.8 10.1 2.6 6.0 −11.7 8.0 −19.1 −11.5 −5.3 15.6

Prop blacks in start-ups (%) (1,2) −1.4 −12.8 −9.9 −0.8 −6.9 6.9 −4.3 18.6 0.5 7.7

[0.003]

7.7

Prop hispanics in start-ups (%) (1,2) −1.9 −7.7 −0.1 −1.5 1.5 3.8 −4.7 −4.0 5.3 1.9

46.6

Prop 18–34 yrs old (%) (1) −1.8 8.3 −3.0 −19.4 −10.9 3.0 −0.6 7.9 18.9 10.9

48.9

Prop 35–54 yrs old (%) (1) 3.9 −14.8 −2.7 18.8 11.0 −1.3 −1.8 −7.9 −17.5 −6.4

[0.005]

4.4

Prop 55 yrs and older (1) −2.0 6.6 5.8 0.7 0.0 −1.6 2.5 0.0 −1.2 −4.4

5.3. Interactions: Who They are and What They are Doing?

81

82

Creating a New Business: Results from the Start-Up

Group E

Group F

Group G

Group H

Group I

overrepresentation of those 35–54 years of age. This group includes 11% of the start-ups; a success rate of 47% leads to 16% of the new firms. reflects a lack of emphasis on product implementation, a start-up team investment of $3,000 or more, but a low level of personal preparation. There is a slight overrepresentation of men, Whites, and those 35–54 years of age. As 36% of the group reports a new firm, this 17% of the start-ups provides 20% of the new firms. reflects a low emphasis on product implementation, a total investment of less than $3,000, one or more years of industry experience, and a rate of investments in excess of $30 per month. There is a slight over-representation of Blacks and Hispanics in this group. This 12% of all start-ups, however, has a success rate of 24% and accounts for 9% of all new firms. is composed of those with strong attention to the production process but not much effort on the business presence and less than five years of same industry experience. Women are slightly over-represented as are Whites. This group is about 12% of all start-ups and 9% of new firms, reflecting a 22% success rate. is composed of those with little effort on production implementation, a start-up team investment in excess of $3,000, and a high level of personal preparation. There is a substantial overrepresentation of Blacks in this group. While they are 7% of all start-ups, only 12% report an operational new firm; they provide 3% of all new firms. reflects low attention to production implementation, a total investment of less than $3,000, some same industry experience, but a rate of investment of less than $30 per month. There is a slight overrepresentation of women, Hispanics, and a major overrepresentation of those under 35 years of age.

5.3. Interactions: Who They are and What They are Doing?

83

This group is 11% of the start-ups but the 10% success rate leads them to be 3% of all new firms. Group J also reports little attention to production implementation, investments of less than $3,000 and no same industry experience. There is an overrepresentation of Blacks as well as those under 35 years of age. While they are 11% of start-ups they are only 2% of all new firms, reflecting 5% of those that report a new firm is in place.

In summary, then, it would appear that unique combinations of start-up activities, personal experiences and contextual factors are associated with different outcomes. There is little question that “doing it” – taking action to implement a productive process and a business presence – have a major impact, often associated with more same industry experience. Primary personal characteristics are associated with these other features and may lead to differences in actions taken to implement new firms. Of particular note is the greater representation of Whites among those in the groups with higher rates of new firm creation, particularly A, B, and C; these groups tend to be more successful in new firm creation. In contrast, Blacks tend to be overrepresented in groups F, H, and J, those where new firms are less likely to be reported. Hispanics, it is to be noted, seem to be rather evenly distributed among all the groups, which may be why their outcome patterns, as shown in Figure 5.4, are almost identical to Whites. Younger adults, those 18–34 years of age, also seem to be overrepresented among groups with relatively low success rates, i.e., H, I, and J. Older adults, those 55 years and above, seem to be overrepresented in Groups B and C, which are relatively successful. Mid-career adults, those 35–54 years of age, are clearly underrepresented in the less successful groups, F, G, H, I, and J. Women, as a group, seem to be over-represented in Group B, which has a high success rate, but also Groups G, H, and I, which have rather low success rates. This results in an overall success rate that is the same for men and women.

84

Creating a New Business: Results from the Start-Up

One caution in terms of causal interpretations is important. It is convenient to assume productive implementation and business presence activities lead to a successful transition from start-up to new firm, but it could be that as the start-up team begins to focus on the 11 discrete things associated with these two domains they are encouraged by others in their commercial and personal networks. This encouragement could provide an incentive to devote more time and resources to efforts to create a viable new firm. These measures may reflect acceptance of the new firm in the market place and positive reactions across a range of dimensions that lead to a successful firm launch. One thing, however, is quite clear, compared with what is actually done in the start-up process, socio-demographic and conceptual factors do not have a major impact on which start-ups become firms.

5.4

Overview

Tracking the success of a representative sample of those involved in business creation indicates that after seven years about one-third report a new firm, one-third have disengaged, and about one-third are still involved in attempting to create a new firm. Exploration of the impact of over 130 factors, many reflecting reliable multi-item indices, and 23 organized into six activity domains, finds that many have very little association with reports of new firm creation. Those that have the most impact appear to be: • Actions devoted to implementing a process for producing the good or service • Actions devoted to developing a presence for the new business • Start-up team investment of funds into the process • Measures of business experience, particularly a background in the same industry In addition, it would appear that concentration of effort may lead to a speedy resolution, leading nascent entrepreneurs to either implement a new firm or disengage from the start-up process at an earlier point in time.

5.4. Overview

85

There are a number of other factors that may have some impact, often in unexpected ways: • Start-ups in more rural areas report more new firm are created. • Those with an internal locus of control, those that prefer to do things better and on their own, are more sophisticated about economic decision making, and perhaps with more social confidence may be more likely to report new firms. But these influences are more subtle. There is no question that many socio-demographic factors found to have an important impact on determining who enters the start-up process – age, gender, educational attainment, household income, household net worth, and the like – have little or no influence on completion of the process with a new firm. The effects of ethnic background may reflect the strategies adopted for creating a business, rather than any other features associated with ethnic background, such as educational attainment, work experience, or household income.

6 Overview and Implications

How do new businesses come about? The most comprehensive and detailed assessment of this issue is the first US Panel Study of Entrepreneurial Dynamics. This project started with the screening of 64,000 US adults, and was followed by four extensive interviews spread over a five year period. Analysis began with a consideration of 75 factors that may affect the decision of an adult to get involved in the creation of a new business – becoming a nascent entrepreneur. General comparisons were made of those active in start-ups with a sample of typical adults identified in the screening surveys. Additional detailed comparisons between the nascent entrepreneurs and a small comparison group were also explored. The assessment continued with an exploration of over 130 factors that may be associated with completing the start-up process with an operating new firm. This effort focused on understanding how the 200 nascent entrepreneurs that reported a new firm within seven years of entering the start-up process were different from that 468 that had quit or continued to work on the start-up. There are a number of significant findings. First, perhaps, is the large number of individuals involved as nascent entrepreneurs – perhaps, 10 million in 1998–1999 when the PSED research project was 87

88

Overview and Implications

implemented, perhaps as many as 16 million in 2005. Even the finding that one-third of this number may be casual hobbyists – not pursuing a new firm as a serious career option – does not detract from the magnitude of social effort devoted to the entrepreneurial process. This is more US adults than have children or get married in a given year. Clearly participation in business start-ups is a major feature of life in the contemporary United States. Second is the finding that the factors associated with entry into the start-up process are not associated with completion of the process with a new firm.1 The most important factors affecting both processes are summarized in Table 6.1, reflecting the analyses reviewed in Chapters 4 and 5. The major factors associated with entry into the start-up process and becoming a nascent entrepreneur, such as age, gender, educational attainment, household income or net worth, and residing in a community with recent population growth, is unrelated to completion of the start-up with a new firm. In fact, the host community characteristic that seems to increase the presence of start-ups – recent population growth – is inversely related to the level of urbanization; the transition from start-up to new firm seems to occur more frequently in more rural areas. This may reflect a lack of competition for the new firm or a scarcity of career options for the nascent entrepreneur, which may enhance commitment to make the start-up succeed. Two factors seem to be common at both stages of the process. Entry into a start-up and completion with a firm both seem to be facilitated by more work experience or more business classroom experience. Classroom experience is, however, a secondary factor associated with entry into the start-up process and has a small tertiary impact on completion the process with a new firm. Measures of same industry business experience seem to have a major impact on the transition to an operating new firm. The second primary factor is ethnic identity, which has a major impact on which participation in a start-up; Blacks and Hispanics are more involved in start-ups than whites. Blacks are, however, slightly 1

This same pattern has been found in a similar sample of Swedish nascent entrepreneurs (Davidsson and Honig, 2003).

89 Table 6.1 Factors associated with entry into start-ups and new firm creation Factors affecting entry into a start-up

Factors affecting new firm creation

Primary • • • • •

Primary factors: • Start-up activity to produce a good or service • Start-up activity to develop a presence for the new firm • Measures of business experience, particularly in the same industry • Start-up activity to create a financial and organizational structure • Start-up team financial commitments • Concentration of resources (time, money) and speedy completion of start-up activities

factors: Age Gender Current work activity Ethnic background Educational attainment

Secondary factors: • Household income • Household net worth • Recent community population growth • Extent, intensity of management training and administrative experience • Positive impressions, encouragement from friends and family • Strong commitment and expectations from an entrepreneurial career option

Secondary factors: • Presence in a less urbanized, more rural area • Personal traits – Locus of control – Try to do better, not differently – Economic sophistication – Social confidence • Ethnic background

less likely to report a firm birth than Whites or Hispanics, but this seems to reflect an ineffective strategy adopted for start-ups by young Blacks. A third major finding is that the activity pursued in the start-up process – not the characteristics of the entrepreneur or the start-up or the setting – has a major impact on the successful transition to a new firm. Actions associated with the productive process, developing a presence for the new firm or developing an organizational and financial structure, seem to be particularly important. This is, of course, closely related to the intensity of effort devoted to the initiative by the start-up team as well as the funds they assemble to facilitate implementation. Intensity not only is more likely to lead to a new firm, but it is likely to

90

Overview and Implications

accelerate implementation and, in addition, facilitate an earlier decision by those that elect to abandon the process. When a representative sample of adults are asked if they are currently involved in creating a new firm, it is now clear that one-third are treating this as a casual hobby; they may be those who are not investing substantial time and money in the effort and, in turn, a resolution to their initiative is delayed – sometimes for decades.

6.1

Implications: Research

This project demonstrates, in a most powerful form, the benefits of a detailed, multifaceted longitudinal study with a representative sample. Without the effort to develop representative samples, the results could be dismissed as an artifact of the individuals selected for the study. Without identifying individuals at the initial stages of the process and tracking outcomes over time, it would be possible to dismiss the potential for causal interpretations. Without the expansion of data collection to cover dozens of facets proposed as significant in affecting participation in the start-up process and completion with a new firm, it would be possible to consider the options for explanations as “incomplete.” The use of a unique multivariate analysis has facilitated identifying groups of people with great variation in the potential for entering the start-up process. Almost 16 per 100 among the most active group, 18–54 year old Black men engaged in full or part-time work, report participation in new firm creation, compared to 3 per 1,000 among the least active group, women over 65 years old who are not working or working part-time; this is a 58-fold difference in participation rates. Predicting who will be active in the start-up process has two components: who will and who will not become involved. It is clear that predicting who will not be involved is very successful, since 997 per 1,000 in the least active group will not report participation in a startup. However, the majority, five in six, in the most active group are also not active nascent entrepreneurs. To increase the predictive success, consideration of a wider range of personal and situational variables – many identified in the nascent entrepreneur versus comparison group assessment in Chapter 4, might yield some improvements. On the other

6.1. Implications: Research

91

hand, such an effort would be expensive, as it would entail identifying a representative sample of candidates – perhaps limited to those 18–54 years of age – with a strong potential for entering the start-up process and gathering a great deal of information on all respondents in order to compare actual nascent entrepreneurs with all potential nascent entrepreneurs. This could be quite expensive and it might be more cost-effective to add the “nascent entrepreneur interview module” to a comprehensive ongoing labor force survey like the monthly US Current Population Survey. When the technique for identifying the unique interactions among critical variables was applied to exploring transitions from start-up to new firm, it was found that the most successful were those engaged in production implementation and developing a business presence, having over ten years residence in the state, and having six or more years of same industry experience; 81 per 100 of this group reported a new firm had been created. The least successful group were those not emphasizing production implementation, who had invested less than $3,000 in the start-up, and had no same industry experience; 5 per 100 of this group reported a new firm was created. This is a 16-fold difference between the most extreme groups. The most successful groups were more likely to involve mid-career White men; the least successful groups were younger Blacks. This suggests that the modest association between ethnic background and reporting a new firm in place may reflect how the start-up effort is approached and implemented, rather than the ethnicity of the nascent entrepreneur. These findings are a substantial contribution to understanding the business creation process. It is, however, specific to the sample based on a cohort of nascent entrepreneurs that emerged in one time period, 1998–2000. Given the dramatic rise in activity between 1998 and 2005, different transition rates and factors may be present in a later cohort – but it will take a five year follow-up to explore this issue. Results would not be available until 2010. The importance of one factor – same industry experience – and the possibility that this has declined among the post 2000 nascent entrepreneurs suggests that the transition rates to new firms may decline for the most recent cohorts. This possibility is consistent with the counts of new employer firm registrations in

92

Overview and Implications

the federal data, which have been relatively constant over the past decade. Perhaps most significant is the clear indication that the most critical factors affecting new firm creation are those associated with the creation process itself – not individual traits, orientations, attitudes, perceptions of the context (such as the entrepreneurial climate) or the nature of the economic or social context. This is, perhaps, because of the critical impact of the specific situation – the exact nature of the business activity and the precise nature of the competition at hand. As start-up teams get serious about implementation and devote time and energy to adjusting strategy and focus to maximize attractiveness to a specific group of customers – or potential customers – it would seem that the ability to cope with the immediate situation are critical for a successful new firm launch. Whether or not one is male or female; has a high school degree or an MBA; is White, Black or Hispanic; has a substantial household net worth; or is sophisticated about accounting practices may not, in comparison, have much impact. The assessment in Chapter 5 may not identify all the most promising factors to incorporate in the next study, but it does identify a large number that may be of limited value in predicting which start-ups will become operational new firms.

6.2

Implications: Entry Into the Start-Up Process

This assessment is of some value for those who may be planning to enter the start-up process by indicating what lies ahead if they expect to eventually launch a new firm. In particular, nascent entrepreneurs should be apprised of the importance of business experience and the capacity for a period of intense personal and financial commitments. On a positive note, they can be informed that how they conduct the startup process is far more important than any personal attributes – age, gender, ethnicity, educational attainment, household income or wealth, and the like. It would appear that creating a new business is truly an egalitarian opportunity – everyone has a good chance to succeed or fail, regardless of their station in life or social attributes. What will be critical is how the start-up team pursues the development of a new firm.

6.3. Implications: New Firm Creation

6.3

93

Implications: New Firm Creation

The major factors are two: knowledge about business and the industry and intensity of commitment. It may not matter how the knowledge is obtained – formal coursework, apprenticeship in other firms, general business experience – but it is clear that knowing the world of business and the specific industry in which the firm is to be located is a major asset in implementing a new business. Experience with other start-ups, regardless of its intuitive appeal, does not appear to be a major asset. Intensity of effort is also a clear indicator. Both the level of personal commitment and the amount of funds assembled from the start-up team appear to be associated with successful implementation of a new firm. There is also guidance regarding the focus of these efforts. Primary attention should be given to the mechanisms for creation of the good or service to be sold, closely followed by efforts to create a publicly visible business entity, one with a phone listing, a phone line, an employee, etc. In short, a focus on putting the business in place seems to be most effective in having a business in place. Most important – and encouraging – anybody can do this. There is no magic associated with being White, Black or Hispanic, having more education, being a man, experience with an earlier start-up, or having an “entrepreneurial personality” – none of these traits seem to make any difference. Anybody with the knowledge, skill, ideas, drive, and resources that emphasize business creation may establish a new business.

6.4

Implications: Public Policy

Implications depend, of course, on the policy objectives. Policy efforts tend to emphasize new firm creation – the entrepreneurial process – often reflects two different objectives. One is to promote overall economic growth and adaptation, usually at the national level, but often for specific regions. The other is to facilitate the work careers or economic advancement of certain groups – women, minorities, immigrants, etc. Implications are slightly different for these two objectives for the two major transitions in the business creation process – entry into the

94

Overview and Implications

Table 6.2 Policy implications and transitions to new firm creation Promote national economic growth

Promote economic status of disadvantaged groups

Entry into start-up process

Encourage those with higher potential for new firm creation

Provide training to compensate for gaps in experience

Complete start-up process with a new firm

Focus on speed of implementation for a timely resolution

Focus on quality of the implementation to compensate for gaps in business experience and subsidize financial needs

start-up process and completion of the process with a new firm. This is illustrated in Table 6.2. For general advancement of overall economic growth, it could be more efficient to encourage those to enter the start-up process – complete the transition to nascent entrepreneur – who are most likely to complete the process with a new firm, that is, those with the skills and experience that will increase the likelihood they will be successful. As presented in Table 5.11, this is likely to be those that have lived over a decade in the state and have some years of same industry experience as the proposed start-up. Gender may not be critical, but it seems that Whites may be slightly more likely to have these characteristics. The dilemma for government policy-makers is that these individuals are not only in full or part-time jobs, but often the most desirable employees. It is not clear how government programs can encourage valued, experienced employees to become involved in creating new firms – which may compete with their existing employers – in a way that will be acceptable to established employer firms. If the objective is to help the socially disadvantaged, then it may be necessary to develop programs that compensate for a potential lack of business experience – either formal business classes or work experience. This training may be in the form of classes or internships in existing businesses. While there is little evidence in the United States that more education beyond the high school degree has a major impact on successful new firm creation, there is evidence that those without basic skills – reading, writing, and arithmetic – are not good candidates for creating a new business. Those without basic skills, and it appears

6.4. Implications: Public Policy

95

that over one-quarter of US junior high graduates do not finish high school (Greene and Winters, 2005), may benefit from remedial work in reading, writing, and arithmetic. Once the business creation process has begun, the emphasis might be slightly different. Those programs designed to enhance economic growth will have encouraged the most skilled and energetic employees to pursue new firm creation. The major cost may be the time foregone from other career options. To minimize this cost, these startup teams should emphasize moving quickly to develop and implement a productive mechanism and create a presence for the business. A timely resolution of the central question, “Is this new business idea viable?” will reduce the aggregate human and financial investment. This “testing cost” will be minimized if the time to resolution – new firm or disengagement – is reduced. Strong evidence suggests that the greater the intensity and breadth of activities implemented, the sooner the issue is resolved. The experienced and well-connected persons in these programs might benefit from assistance in the search for start-up funding, but they may not require substantial financial subsidies. A slightly different focus might be more suited to assistance for the disadvantaged groups. As they may not have the business background or skills, more attention might be paid to the development of the implementation strategy – reflected in creation of a detailed business plan – and provision of an experienced mentor who might guide them through the start-up process. As this group may include those with limited work experience and modest financial resources, it may be appropriate to provide some financial subsidy, perhaps in conjunction with funds provided by established commercial sources. It is, of course, an open question whether government policies and programs are needed to encourage experienced workers and administrators to pursue new business creation in the United States. Large numbers of Americans, 16 million or more, are currently pursing these options without much direct encouragement or significant assistance from any federal, state, or local government initiatives. A more appropriate emphasis might be to ensure that government policies and

96

Overview and Implications

procedures do not hinder the speedy resolution of the central question – “Is this business viable?” Other countries, where the rate of new firm creation is quite low, are another matter. Many advanced countries in Europe – as well as Japan – have a very low rate of participation in business creation. They may benefit by implementing policies to promote entrepreneurship and, in turn, national economic growth and adaptation. Assistance for disadvantaged groups, however, may be a challenge in all countries. In most countries, there are distinctive groups or regions where economic growth or well-being is sub-optimal. The basic strategies for assisting these groups – training to compensate for a lack of business experience, assistance in developing a appropriate business plan, and help in securing the resources for implementation – is likely to be the same in all countries. Major variations may be related to the need to acquaint the potential entrepreneurs with the social and cultural norms of the potential customers; an issue to be addressed with new immigrants.

References

Armington, C. and Z. Acs (2002), ‘The determinants of region variation in new firm formation’. Regional Studies 36(1), 33–45. Davidsson, P. (2006), ‘Nascent Entrepreneurship’. In Foundations and Trends in Entrepreneurship Series. Vol. 2. Hanover, MA: now Publishers, Inc, p. 1. Davidsson, P. and B. Honig (2003), ‘The role of social and human capital among nascent entrepreneurs’. Journal of Business Venturing 18(3), 301–331. Delmar, F. and S. Shane (2003), ‘Does business planning facilitate the development of new ventures?’. Strategic Management Journal 24, 1165–1185. Gartner, W. B., K. B. Shaver, N. M. Carter, and P. D. Reynolds (eds.) (2004), Handbook of Entrepreneurial Dynamics: The Process of Business Creation. Thousand Oaks, CA: Sage. Greene, J. P. and M. A. Winters (2005), Public High School and College-Readiness Rates: 1991–2002, Education Working Paper No. 8. New York, NY: Manhattan Institute for Policy Research. Kuhn, T. S. (1962), The Structure of Scientific Revolutions. Chicago, Ill: University of Chicago Press. Reynolds, P., N. Bosma, E. Autio, S. Hunt, N. D. Bono, I. Servais, P. Lopez-Garcia, and N. Chin (2005), ‘Global entrepreneurship 97

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monitor: Data collection design and implementation: 1998–2003’. Small Business Economics 24, 205–231. Reynolds, P. D. (1971a), ‘Comment on “The distribution of participation in group discussions” as related to group size’. American Sociological Review 36(4), 704–706. Reynolds, P. D. (1971b), A Primer in Theory Construction. New York: MacMillan. reissued by Allyn and Bacon in 2006. Reynolds, P. D. (2007), Entrepreneurship in the United States: The Future is Now. New York: Springer. Reynolds, P. D., W. D. Bygrave, E. Autio, L. Cox, and M. Hay (2002), Global Entrepreneurship Monitor: 2002 Executive Report. Kansas City, MO: Kauffman Center for Entrepreneurial Leadership. Reynolds, P. D., W. D. Bygrave, E. Autio, and Others (2004a), Global Entrepreneurship Monitor: 2003 Summary Report. Babson Park, MA: Babson College. Reynolds, P. D., S. M. Camp, W. D. Bygrave, E. Autio, and M. Hay (2001), Global Entrepreneurship Monitor: 2001 Executive Report. Kansas City, MO: Kauffman Center for Entrepreneurial Leadership. Reynolds, P. D., N. M. Carter, W. B. Gartner, and P. G. Greene (2004b), ‘The prevalence of nascent entrepreneurs in the United States: Evidence from the panel study of entrepreneurial dynamics’. Small Business Economics 23(4), 263–284. Reynolds, P. D., M. Hay, W. D. Bygrave, S. M. Camp, and E. Autio (2000), Global Entrepreneurship Monitor: 2000 Executive Report. Kansas City, MO: Kauffman Center for Entrepreneurial Leadership. Reynolds, P. D., M. Hay, and M. Camp (1999), Global Entrepreneurship Monitor: 1999 Executive Report. Kansas City, MO: Kauffman Center for Entrepreneurial Leadership. Reynolds, P. D., B. Miller, and W. Maki (1995), ‘Explaining regional variation in business births and deaths: U.S. 1976–1988’. Small Business Economics 7, 389–407. Shane, S. and S. Venkataraman (2000), ‘The promise of entrepreneurship as a field of research’. Academy of Management Review 25, 217–226. Sherrod, P. H. (2005). DTREG: Classification and Regression Trees for Data Mining and Modeling. www.dtreg.com.

PSED I Scholarly Works

Publications and Papers based the Panel Study of Entrepreneurial Dynamics Research Protocol, including the PSED I (U.S.) Data Set Initiated by Per Davidsson (July 2005) Update by Paul Reynolds (August 2005) NOTE: Papers reflecting the Global Entrepreneurship Monitor research program are excluded. Books [Edited and monographs] Gartner, W. B., K. G. Shaver, N. M. Carter, and P. D. Reynolds (2004), Handbook of Entrepreneurial Dynamics: The Process of Business Creation. Thousand Oaks, CA: Sage. [NOTE: The 38 individual chapters and 3 appendices from this work are not listed.] Reynolds, P. D. and S. B. White (1997), The Entrepreneurial Process: Economic Growth, Men, Women, and Minorities. Westport, CT: Quorum Books. 99

100

PSED I Scholarly Works

Dissertations Meeks, M. D. (2004), Antecedents to the Entrepreneurial Decision: An Empirical Analysis of Three Predictive Models. Doctoral dissertation. Boulder, CO: University of Colorado at Boulder. Samuelsson, M. (2004), Creating New Ventures: A Longitudinal Investigation of the Nascent Venturing Process. Doctoral dissertation. J¨onk¨oping, Sweden: J¨onk¨oping International Business School. Stouder, M. D. (2002), The Capital Structure Decisions of Nascent Entrepreneurs. Doctoral dissertation. Newark, NJ: Rutgers The State University of New Jersey-Newark. Peer Review Journal Articles Acs, Z. J. and A. Varga (2005), ‘Entrepreneurship, agglomeration and technological change’. Small Business Economics 24, 323–334. Alsos, G. A. and L. Kolvereid (1998), ‘The business gestation process of novice, serial and parallel business founders’. Entrepreneurship Theory and Practice 22(4), 101–114. Brush, C. G., L. F. Edelman, and T. Manolova (Forthcoming), ‘Properties of emerging organizations: An empirical test. Journal of Business Venturing. Brush, D. G., L. F. Edelman, and T. Manolova (Forthcoming), ‘The effects of initial location, choice on resource assembly on likelihood of first sale in nascent firms’ Journal of Small Business Management. Carter, N. M., W. B. Gartner, and P. D. Reynolds (1996), ‘Exploring start-up event sequences’. Journal of Business Venturing 11, 151–166. Carter, N. M., W. B. Gartner, K. G. Shaver, and E. J. Gatewood (2003). ‘The career reasons of nascent entrepreneurs’. Journal of Business Venturing 18, 13–29. Chandler, G. N., B. Honig, and J. Wiklund (2005), ‘Antecedents, moderators and performance consequences of membership change in new venture teams’. Journal of Business Venturing 20, 705–725.

Publications and Papers based on the Panel Study

101

Davidsson, P., P. D. Reynolds (2005), ‘Entrepreneurship research innovator, coordinator and disseminator’. Small Business Economics 24 351–358. Davidsson, P. and M. Henreksson (2002), ‘Institutional determinants of the prevalence of start-ups and high-growth firms: Evidence from Sweden’. Small Business Economics 19(2), 81–104. Davidsson, P. and B. Honig (2003), ‘The role of social and human capital among nascent entrepreneurs’. Journal of Business Venturing 18(3), 301–331. Delmar, F. and P. Davidsson (2000), ‘Where do they come from? Prevalence and characteristics of nascent entrepreneurs’. Entrepreneurship and Regional Development 12, 1–23. Delmar, F. and S. Shane (2004), ‘Legitimating first: Organizing activities and the survival of new ventures’. Journal of Business Venturing 19, 385–410. Eckhardt, J., S. Shane, and F. Delmar (In press), ‘Multi-stage selection and the financing of new ventures’ Management Science, forthcoming. Edelman, L. F., C. G. Brush, and T. Manolova (Forthcoming), ‘Entrepreneurship education: Correspondence between practices of nascent entrepreneurs and textbook prescriptions for success’. Academy of Management Learning and Education. Honig, B. (2001), ‘Learning strategies and resources for nascent entrepreneurs and intrapreneurs’. Entrepreneurship Theory and Practice 24(Fall), 21–35. Honig, B., P. Davidsson, and T. Karlsson (2005), ‘Learning strategies of nascent entrepreneurs’. Journal of Competence-Based Management 1(3), 67–88. Honig, B. and T. Karlsson (2004), ‘Institutional forces and the written business plan’. Journal of Management 30(1), 29–48. Liao, J. and H. Welsch (2003b), ‘Social capital and entrepreneurial growth aspiration: A comparison of technology- and nontechnology-based nascent entrepreneurs’. Journal of High Technology Management Research 14, 149–170. Newbert, S. L. (2005), ‘New firm formation: A dynamic capability perspective’. Journal of Small Business Management 43(1), 55–77.

102

PSED I Scholarly Works

Reynolds, P. D. (1997), ‘Who starts new firms? Preliminary explorations of firms-in-gestation’. Small Business Economics 9, 449–462. Reynolds, P. D., N. M. Carter, W. B. Gartner and P. G. Greene (2004), ‘The prevalence of nascent entrepreneurs in the United States: Evidence from the panel study of entrepreneurial dynamics’. Small Business Economics 23(4), 263–284. Reynolds, P. D. and B. Miller (1992), ‘New firm gestation: Conception, birth and implications for research’. Journal of Business Venturing 7, 405–417. Ruef, M., H. E. Aldrich, and N. M. Carter (2003), ‘The structure of organizational founding teams: Homophily, strong ties, and isolation among U.S. entrepreneurs’. American Sociological Review 68(2), 195–222. Shane, S. and F. Delmar (2004), ‘Planning for the market: Business planning before marketing and the continuation of organizing efforts’. Journal of Business Venturing 19, 767–785. Shaver, K. G., W. B. Gartner, E. Crosby, K. Bakalarova, and E. J. Gatewood (2001), ‘Attributions about entrepreneurship: A framework and process for analyzing reasons for starting a business’. Entrepreneurship: Theory and Practice 26(2), 5–33. Singh, R. P. and L. M. Lucas (2005), ‘Not just domestic engineers: An exploratory study of homemaker entrepreneurs’. Entrepreneurship: Theory and Practice 29(1), 79–91. Peer Review Conference Presentations, Proceedings Aldrich, H. E., N. M. Carter, M. Ruef, and P. H. Kim (2003), ‘Hampered by homophily? The effects of team composition on the success of nascent entrepreneurs’ organizing efforts (Summary)’. In Frontiers of Entrepreneurship Research 2003, W. D. Bygrave et al. (eds.). Wellesley, MA: Babson College. Alsos, G. A. and E. C. Ljunggren (1998), ‘Does the business startup process differ by gender? A longitudinal study of nascent entrepreneurs’. In Frontiers of Entrepreneurship Research 1998, P. D. Reynolds et al. (eds.). Wellesley, MA: Babson College.

Publications and Papers based on the Panel Study

103

Baltrusaityte, J., Z. J. Acs, and G. E. Hills (2005), Opportunity Recognition Processes and New Venture Failure: Examination of the PSED Data. Paper presented at the Babson College/Kauffman Foundation Entrepreneurship Research Conference, Wellesley, MA. Brush, C. G., L. F. Edelman, and T. Manolova (2004), ‘Properties of emerging organizations: An empirical test’, At Academy of Management Research Conference, New Orleans, LA, Academy Highlighted Show Program Session. Brush, C. G., L. F. Edelman, and T. Manolova (2003), ‘Home or away: The impact of initial location decisions on resource assembly in nascent firms’. Academy of Management Research Conference, Seattle, WA. Brush. D. G., T. Manolova and L. F. Edelman (2003), ‘Home or away: Initial location decisions and the construction of new ventures’ resource base’. Babson College-Kauffman Foundation Entrepreneurship Research Conference, Wellesley, MA. Cassar, G. (2004), Entrepreneur Motivation, Growth Preferences and Intended Venture Growth (Summary). Paper presented at the Babson College/Kauffman Foundation Entrepreneurship Research Conference, Strathclyde, Scotland. Crosa, B., H. A. Aldrich, and L. A. Keister (2002), ‘Is there a wealth effect? Financial and human capital determinants of business start-ups’. In Frontiers of Entrepreneurship Research 2002, W. D. Bygrave et al. (eds.). Wellesley, MA: Babson College. Delmar, F. and P. Davidsson (1999), ‘Firm size expectations of nascent entrepreneurs’. In Frontiers of Entrepreneurship Research 1999, P. D. Reynolds, W. D. Bygrave, S. Manigart, C. Mason, G. D. Meyer, H. J. Sapienza, and K. G. Shaver (eds.). Vol. 19, pp. 90– 104. Wellesley, MA: Babson College. Delmar, F. and J. Gunnarsson (2000), ‘How do self-employed parents of nascent entrepreneurs contribute?’ In Frontiers of Entrepreneurship Research 2000, P. D. Reynolds et al. (eds.). Wellesley, MA: Babson College. Delmar, F. and S. Shane (2002), ‘What founders do: A longitudinal study of the start-up process’. In Frontiers of Entrepreneurship

104

PSED I Scholarly Works

Research 2002, W. D. Bygrave et al. (eds.). pp. 632–645. Wellesley, MA. Delmar, F. and S. Shane (2003b), ‘Does the order of organizing activities matter for new venture performance?’ In Frontiers of Entrepreneurship 2003, P. D. Reynolds et al. (eds.). Wellesley, MA: Babson College. Diochon, M., M. Menzies, and Y. Gasse (2003), Insights Into the Dynamics of Canadian Nascent Entrepreneurs’ Start-Up Efforts and the Role Individual Factors Play in the Process. Paper presented at the 20th Annual CCSBE Conference, Victoria. Edelman, L. F., C. G. Brush, and T. Manolova (2006), ‘One size doesn’t fit all growth expectancies of U.S. women and men nascent entrepreneurs’. Academy of Management Research Conference, Atlanta, Georgia. Edelman, L.F., C. G. Brush, and T. Manolova (2005), ‘Entrepreneurial education: Do they practice what we teach?’ Academy of Management Research Conference, Honolulu, Hawaii. Gartner, W. B., K. G. Shaver, and E. J. Gatewood (2000), ‘Doing it for yourself: Career attributions of nascent entrepreneurs’. In Frontiers of Entrepreneurship Research 2000, P. D. Reynolds et al. (eds.). Wellesley, MA: Babson College. Hills, G. E., G. T. Lumpkin, and J. Baltrusaityte (2004), Opportunity Recognition: Examining Search Formality, Search Processes and the Impact on Firm Founding (Summary). Paper presented at the Babson College/Kauffman Foundation Entrepreneurship Research Conference, Strathclyde, Scotland. Kim, P. H., H. A. Aldrich, and L. A. Keister (2003), If I Were Rich? The Impact of Financial and Human Capital on Becoming a Nascent Entrepreneur. Paper presented at the Annual Meeting of the American Sociological Association, Atlanta. Kim, P. H. and H. E. Aldrich (2004), Teams That Work Together, Stay Together: Resiliency of Entrepreneurial Teams (Summary). Paper presented at the Babson College/Kauffman Foundation Entrepreneurship Research Conference, Strathclyde, Scotland. Liao, J. and H. Welsch (2002), ‘The temporal patterns of venture creation process: An exploratory study’. In Frontiers of

Publications and Papers based on the Panel Study

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Entrepreneurship Research 2002, W. D. Bygrave et al. (eds.). Wellesley, MA: Babson College. Liao, J. and H. Welsch (2003a), ‘Exploring the venture creation process: Evidence from tech and non-tech nascent entrepreneurs’. In Frontiers of Entrepreneurship Research 2003, W. D. Bygrave et al. (eds.). Wellesley, MA: Babson College. Liao, J. and H. Welsch (2002), ‘Exploring the venture creation process: Evidence from tech and non-tech nascent entrepreneurs’. Frontiers of Entrepreneurship Research 2002. Wellesley, MA: Babson College. Liao, J. and H. Welsch (2004), Start-Up Resources and Entrepreneurial Discontinuance: An Empirical Investigation of Nascent Entrepreneurs (Summary). Paper presented at the Babson College/Kauffman Foundation Entrepreneurship Research Conference, Strathclyde, Scotland. Lichtenstein, B. B., N. M. Carter, K. Dooley, and W. B. Gartner (2004), Exploring the Temporal Dynamics of Organizational Emergence (Summary). Paper presented at the Babson College/Kauffman Foundation Entrepreneurship Research Conference, Strathclyde, Scotland. Manolova, T., C. G. Brush, and L. F. Edelman (2002), ‘Nascence to newness: The influence of internal and external factors on the likelihood of first sales’. Academy of Management Research Conference, Denver, CO. Matthews, C. H., M. W. Ford, and S. E. Human (2001), ‘The context of new venture initiation: Comparing growth expectations of nascent entrepreneurs and intrapreneurs’. In Frontiers of Entrepreneurship 2001, W. D. Bygrave et al. (eds.). Wellesley, MA: Babson College. Matthews, C. H. and S. E. Human (2000), ‘The little engine that could: Uncertainty and growth expectations of nascent entrepreneurs’. In Frontiers of Entrepreneurship Research 2000, P. D. Reynolds et al. (eds.). Wellesley, MA: Babson College. Menzies, T., Y. Gasse, M. Diochon, and D. Garand (2002), Nascent Entrepreneurs in Canada: An Empirical Study. Paper presented at the ICSB 47th World Conference, San Juan, Puerto Rico.

106

PSED I Scholarly Works

Palit, C. and P. D. Reynolds (1993), ‘A network sampling procedure for estimating the prevalence of nascent entrepreneurs’. Proceedings of the American Statistical Association International Conference on Establishment Surveys, pp. 657–661. Reynolds, P. D. and S. B. White (1992), ‘Finding the nascent entrepreneur: Network sampling’. In Frontiers of Entrepreneurship Research 1992, N. C. Churchill, S. Birley, W. D. Bygrave, C. Wahlbin, and W. E. J. Wetzel (eds.). pp. 199–208. Wellesley, MA: Babson College. Samuelsson, M. (2001), ‘Modelling the nascent venture opportunity exploitation process across time’. In Frontiers of Entrepreneurship Research 2001, W. D. Bygrave, E. Autio, C. G. Brush, P. Davidsson, P. G. Greene, P. D. Reynolds, and H. J. Sapienza (eds.). pp. 66–79. Wellesley, MA. Shaver, K.G., N. M. Carter, W. B. Gartner, and P. D. Reynolds (2001), ‘Who is a nascent entrepreneur? Decision rules for identifying and selecting entrepreneurs in the panel study of entrepreneurial dynamics’. Babson-Kauffman Entrepreneurship Research Conference. Smith, B. (2005), The Search For and Discovery of Different Types of Entrepreneurial Opportunities: The Effects of Tacitness and Codification. Paper presented at the Babson College/Kauffman Foundation Entrepreneurship Research Conference, Wellesley, MA. Van Gelderen, M., N. Bosma, and A. R. Thurik (2001), ‘Setting up a business in the Netherlands: Who starts, who gives up, who is still trying?’ In Frontiers of Entrepreneurship Research 2001, W. D. Bygrave et al. (eds.). Wellesley, MA: Babson College. Wagner, J. (2004), Nascent Entrepreneurs. IZA DP No. 1293. Bonn, Germany: Forschungsinstitut zur Zukunft der Arbeit. Welter, F. (2001), ‘Who wants to grow? Growth Intentions and growth profiles of (nascent) entrepreneurs in Germany’. In Frontiers of Entrepreneurship Research 2001, W. B. Bygrave et al. (eds.). Wellesley: Babson College. Welter, F. (2001), Would-Be Entrepreneurs in Germany. Paper presented at the RENT XV Conference, Turku, Finland.

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Book Chapters Davidsson, P. (2005), ‘Method issues in the study of venture start-up processes’. In Entrepreneurship Research in Europe: Outcomes and Perspectives, A. Fayolle, P. Kyr¨o, and J. Ulijn (eds.). pp. 35–54. Cheltenham, UK: Edward Edgar. Gartner, W. B. and N. M. Carter (2003), ‘Entrepreneurial behavior and firm organising processes’. In Handbook of Entrepreneurship Research, Z. J. Acs and D. B. Audretsch (eds.). pp. 195–221. Dordrecht, NL: Kluwer. Greene, P. G., N. M. Carter, and P. D. Reynolds (2003), ‘Minority entrepreneurship: Trends and explanation’. In New Movements in Entrepreneurship, C. Steyaert and D. Hjorth (eds.). pp. 239–257. Cheltenham, UK: Elgar. Reynolds, P. D. (2000), ‘National panel study of US business start-ups. Background and methodology’. In Advances in Entrepreneurship, Firm Emergence and Growth, J. A. Katz (ed.), Vol. 4, pp. 153–227. Stamford, CT: JAI Press. Research Reports de Rearte, A. G., E. Lanari, and P. A. A. J. Atucha (1998), El proceso de creaction de empresas; Abordaje methodologico y primeros resultados de un studio regional. Argentina: Universidad Nacional de Mar del Plata. Honig, B. and T. Karlsson (2001), Business Planning and the Nascent Entrepreneur: An Empirical Study of Normative Behavior. J¨onk¨oping: J¨onk¨oping International Business School. Reynolds, P. D. and S. B. White (1993), Wisconsin’s Entrepreneurial Climate Study. Milwaukee, WI: Marquette University Center for the Study of Entrepreneurship. Van Gelderen, M., A. R. Thurik, and N. Bosma (2003), ‘Success and risk factors in the pre-startup phase’. SCALES paper N200314. Zoetermeer, NL: EIM.

Acknowledgments

The first Panel Study of Entrepreneurial Dynamics was organized and implemented by the Entrepreneurial Research Consortium [ERC], a voluntary association of 34 member units with over 120 members; the ERC was able to support the implementation of the project as well as the first follow-up. The Ewing Marion Kauffman Foundation provided support for the second and third follow-up interviews and the cost of shifting the operational base of the program from the University of Wisconsin to the University of Michigan Institute for Social Research. Additional support was provided by the National Science Foundation for two enhancements, an over sample of women [Dr. Nancy Carter, Principal Investigator, Grant SBR-9809841] and an over sample of minorities [Dr. Patricia Green, Principal Investigator, Grant SBR9905255]. Substantial support was provided to the author during the completion of the research by Marquette University, Babson College, and Florida International University.

109

A Methodlogical Appendices

Appendix.4Ax.1

Notes on Assessment of the Screening Data

The following lists the actual variables used in the analysis presented in Figures 4.2, 4.3, 4.4, 4.5, and Tables 4.1 and 4.2. All are from the

Table 4Ax.1.1 Variables used from PSED I screening data file Screening interview dataset variable labels

Variable label Active in start-up process [0 = not active, 1 = active] Gender Age categories Ethnic background Educational attainment Household income Labor force participation Martial status Household size Annual rate of population growth: 1980–1992 [four categories] Population density [persons per square mile in 1992, four categories] Urbanization index, composed of average value of four items [Chronbach’s alpha = 0.87], continuous index then placed in four ordinal quartiles

111

SUOWNACT USGENDER USAGE7C USRACE4 USEDUC5 USHHINC6 USLABFR3 USMARR USHHSZE3 US8092A4 USPDN924 PCINC93, HH75K89, PC254490, PCOLL90

112

Methodlogical Appendices

screening interview data set, with data for full sample comparison group [RTYPE = 20] omitted (Table 4Ax.1.1).

Appendix.4Ax.2

Detailed Comparison of Nascent Entrepreneurs and Typical Adults

All comparisons based only on the nascents identified and interviewed for the initial full sample [n = 446; RTYPE = 10] and the initial comparison group selected to represent all US adults [N = 219; RTYPE = 20]; weights re-centered to an average of one for each group. The table columns represent the following: Dimension, characteristics, factor: Summary of dependent variable. Nascent entre’s: Value for nascent entrepreneur sample. Comp group: Value for the comparison group. Stat signif: statistical significance is provided from a Chi-Square test for cross tabulations and the F-test for the means comparisons. Alpha: reliability, where appropriate, computed as Chronbach’s Alpha. Table: The table in this chapter in which the results are summarized. Hand’k chapter: The chapter in the Gartner et al. (2004) Handbook of Entrepreneurial Dynamics in which the background and rationale for measure(s) is/are discussed. Variable label: The variable labels from the phone and mail interview schedules as found in the full PSED I data set, or the items used to compute multi-item indices. Dimension, characteristics, factor HH income: 0–$20,000/Yr HH income: $20–40,000/Yr HH income: $40–60,000/Yr HH income: $60–100,000/Yr HH income: $100,000–Up/Yr

Nascent Comp entre’s group 9.7%

10.3%

31.1%

27.4%

23.8%

29.5%

25.0%

25.4%

10.5%

7.4%

Stat signif

0.3987

Alpha

Table

Hand’k chap

N/A

4.3

5

Variable labels HHINCR5

Appendix.4Ax.2. Comparison of Nascent Entrepreneurs and Typical Adults Dimension, characteristics, factor HH net worth: Negative HH net worth: $0–100,000 HH net worth: $100,000–250,000 HH net worth: $250,000–500,000 HH net worth: $500–1,000,000 HH net worth: $1,000,000 and up

Nascent entre’s 5.5% 51.9%

Comp group 4.5% 46.0%

14.0%

20.0%

7.9%

4.1%

16.8%

23.4%

4.0%

2.1%

Never married Married or living as married Other: divorced, widowed, separated etc.

17.7% 68.4%

16.4% 62.3%

13.9%

21.3%

Single adult

16.6%

15.0%

Two or more adults: no children Adults and children less than 19 years old

35.8%

33.7%

47.5%

51.3%

0.6474

Household size: all ages Household size: adults only Household: total earning money in previous week Last work day: ave hours on work plus travel Last day off: ave hours on work plus travel

2.96 2.15

2.93 2.13

1.70

Satisfaction with most recent job [Z-score] Satisfied with life overall [Z-score] Reporting social network present (proportion) Number in social network (average)

Stat signif

113

Alpha N/A

Table 4.3

Hand’k chap 5

Variable labels HHNETR6

N/A

4.3

4

Q385

N/A

4.3

4

Q380, Q381, Q382, Q383

0.8379 0.6687

N/A N/A

4.3 4.3

4 4

Q380 Q384

1.60

0.1108

N/A

4.3

4

Q384A

7.25

7.45

0.5761

N/A

4.3

9

QM5D1

0.51

0.24

0.0284

N/A

4.3

9

QM5D2

0.37

−0.58

0.0000

N/A

4.3

14

QI8

0.02

−0.03

0.6025

N/A

4.3

14

QL1M

64.0%

75.6%

0.0027

N/A

4.3

29

Q241

3.17

5.11

0.0014

N/A

4.3

29

Q242

0.0292

0.0517

114

Methodlogical Appendices

Dimension, characteristics, factor

Nascent Comp entre’s group

Alpha

Table

Hand’k chap

Lived in county 0–2 years Lived in county 2–5 years Lived in county 5–10 years Lived in county 10–20 years Lived in county 20–40 years Lived in county 40–75 years

15.4%

10.3%

N/A

4.3

6

Q353A MT

14.1%

12.8%

17.9%

18.5%

19.4%

20.8%

26.6%

22.9%

6.6%

14.6%

94.1

96.4%

N/A

4.3

6

Q358

5.9%

3.6%

0.2117

Entrepreneurial climate: community groups support

2.72

2.89

0.0082

0.69

4.4

35

2.50

0.3930

0.65

4.4

35

QB1B, QB1C, QB1D, QB1E, QB1I QB1G, QB1H

Entrepreneurial climate: friends and family models Entrepreneurial climate: community models

2.59

3.80

3.83

0.6203

0.38

4.4

35

QB1A, QB1F, QB1J

Knowledge of assistance programs Actual contact with assistance programs No of assistance programs contacted

52.6%

59.0%

0.1546

N/A

4.4

30

Q315

15.3%

15.8%

0.8664

N/A

4.4

30

Q303

2.55

1.89

0.2372

N/A

4.4

30

Q305

Parent’s own a business Worked for parent

51.6% 29.5%

52.9% 25.2%

0.7693 0.3732

N/A N/A

4.4 4.4

16 16

Family friends encouraged start-up Friends and neighbors own businesses (four point scale) Impression of owning a business from friends, relatives (five point scale)

73.4%

34.9%

0.0000

N/A

4.4

16

Q362 Q367, Q371, Q375 Q379

2.14

2.06

0.2692

N/A

4.4

16

Q377

4.14

3.70

0.0000

N/A

4.4

16

Q378

Born in the United States Not born in the United States

Stat signif

Variable labels

0.0159

Appendix.4Ax.2. Comparison of Nascent Entrepreneurs and Typical Adults Dimension, characteristics, factor

Nascent Comp entre’s group

115

Stat signif

Alpha

Table

Hand’k chap

Variable labels QF1A1, QF1B1, QF1H1, QF1I1 QF1D1, QF1F1

General management classes, average taken

1.76

1.44

0.0617

0.64

4.4

7

Human, financial management classes, average taken Operations management classes, average taken

0.82

0.73

0.5312

0.61

4.4

7

0.75

0.35

0.0013

0.27

4.4

7

QF1C1, QF1E1, QF1G1

General management work experiences, average years

4.25

3.22

0.0351

0.84

4.4

7

Operations management work experiences, average years

3.25

2.22

0.0104

0.65

4.4

7

QF1A2, QF1B2, QF1D2, QF1F2, QF1H2, QF1I2 QF1C2, QF1E2, QF1G2

Total activity count: over 12 prior years No yrs in which full-time employment No yrs in which part-time employment No yrs in which full-time self-employment No yrs in which part-time self-employment No yrs in which full-time student No yrs in which part-time student No yrs in which unemployed seeking work No yrs in which unemployed not seeking work No yrs in which doing unpaid volunteer work No yrs in which a homemaker

18.50

20.14

0.0205

N/A

4.4

10

7.39

7.80

0.3169

N/A

4.4

10

2.08

1.69

0.1443

N/A

4.4

10

1.58

0.65

0.0004

N/A

4.4

10

QO1A87QO1D91

1.57

1.21

0.1777

N/A

4.4

10

QO1A87QO1D91

1.51

1.62

0.7121

N/A

4.4

10

0.85

1.02

0.3189

N/A

4.4

10

0.25

0.26

0.9047

N/A

4.4

10

QO1A87QO1D91 QO1A87QO1D91 QO1A87QO1D91

0.22

0.55

0.0125

N/A

4.4

10

QO1A87QO1D91

0.90

1.86

0.0008

N/A

4.4

10

QO1A87QO1D91

1.60

2.58

0.0118

N/A

4.4

10

QO1A87QO1D91

QO1A87QO1D91 QO1A87QO1D91 QO1A87QO1D91

116

Methodlogical Appendices

Dimension, characteristics, factor

Nascent Comp entre’s group

Stat signif

Table

Hand’k chap

Variable labels

No yrs in which disable and unable to work No yrs in which retired

0.30

0.22

0.5497 N/A

4.4

10

0.0133 N/A

4.4

10

QO1A87QO1D91 QO1A87QO1D91

0.25

0.69

30.7%

16.2%

N/A

4.5

15

Q327

69.3%

83.8%

0.0026

Entrepreneurial intensity

3.34

2.73

0.0000 0.72

4.5

17

QL1D, QL1E, QL1F, QL1G

Entrepreneurial expectations

4.22

3.57

0.0000 0.83

4.5

13

QK1A, QK1B, QK1C, QK1D, QK1E, QK1F

Self realization

3.94

3.95

0.9166 0.78

4.5

12

Financial security

3.61

3.50

0.2189 0.78

4.5

12

Recognition

2.58

3.29

0.0000 0.76

4.5

12

Role expectations

1.83

2.69

0.0000 0.60

4.5

12

Innovation

2.65

2.83

0.0842 0.71

4.5

12

Independence

4.13

4.12

0.8942 0.66

4.5

12

QG1R, QG1O, QG1P, QG1H QG1K, QG1G, QG1J, QG1N QG1L, QG1E, QG1A QG1D, QG1L QG1C, QG1M, QG1Q QG1B, QG1F

Confidence in social settings (three items)

3.87

3.74

0.0303 0.48

4.5

21

Emotional control (two items) Shyness (two items)

3.01

2.93

0.3188 0.57

4.5

21

2.85

2.87

0.8110 0.04

4.5

21

Cognitive style: different Cognitive style: better

Alpha

QL1T, QL1X, QL1Y QL1S, QL1V QL1U, QL1W

Appendix.4Ax.2. Comparison of Nascent Entrepreneurs and Typical Adults Dimension, characteristics, factor Emphasis on high payoff/high risk Emphasis on high personal impact Prefers collective/group efforts Prefers challenge/task focus

Nascent Comp entre’s group 2.51 2.53

Stat signif 0.6484

Alpha 0.52

Table 4.5

Hand’k chap None

117

Variable labels QH1, QH2 QH5, QH6 QH4, QH8

1.72

1.70

0.5902

0.44

4.5

None

1.42

1.56

0.0003

0.19

4.5

None

1.48

1.41

0.0017

0.17

4.5

None

QH3, QH7, QH9

2.35

2.45

0.0679

0.60

4.5

None

2.44

2.56

0.0005

0.58

4.5

None

QH10B, QH10C QH10A, QH10D, QH10E, QH10F, QH10G

Locus of control

4.00

4.01

0.8925

0.47

4.5

19

QL1H, QL1I, QL1J

Ignore sunk costs in decision making Focus on current value when selling asset, not cost

3.07

2.98

0.3771

N/A

4.5

20

QL1K

3.48

3.43

0.6344

N/A

4.5

20

QL1L

Frequency of new, unpredictable situations at work Feel overloaded, pushed to limits at work Delay decisions on difficult problems to gather more information

2.31

2.44

0.1647

N/A

4.5

18

QJ2A

3.10

2.96

0.1452

N/A

4.5

18

QJ2B

3.62

3.68

0.4019

N/A

4.5

18

QL1R

Problem complexity: identifying problems for priority Problem complexity: developing solutions

37.9%

33.1%

N/A

4.5

18

QI9

62.1%

66.9%

Business problem solving: calculating and analytical Business problem solving: intuitive Business problem solving: varies by situation

21.3%

19.3%

N/A

4.5

18

QJ1

16.7%

13.9%

61.9%

66.8%

Financial issues in firm choice Operational issues in firm choice

0.4640

0.5375

118

Methodlogical Appendices

Appendix.5Ax.1

Constructing Start-Up Time Lines Data Set

Constructing the time lines for the start-up processes reported by nascent entrepreneurs in the PSED I project was somewhat involved. A customized data set was prepared as follows: (1) Data on start-up activities, outcome of the start-up effort and date of change in status (when start-up became an operating firm or the respondent quit the project) was consolidated for all four waves of data collection. (2) For those events where a year was provided, the month was assumed to be June. For those events where a year and season was reported (winter, spring, summer, or fall) rather than a month, an appropriate month (February, May, August, or November) was assumed. (3) All dates were transformed into a common metric and the earliest occurrence reported for each activity was identified from all four waves of data collection. (4) The first eight behaviors (omitting serious though about the start-up) were identified and the time lag between each pair in the sequence was established. (5) For all cases with two or more start-up behaviors (serious thought was not considered a behavior), the earliest activity in any pair where both were initiated within a 12 month period was considered the “conception date.” (6) Based on reports of the respondent of that date when the start-up became an “operating business” or “no longer being worked on by anyone” the time between conception and new firm birth, quit, or continuation of the start-up activity was computed for each case. (7) Starting with the first month following conception and for 3 month or 12 month time periods following, the proportion of cases in each time segment were computed. Those cases considered an “operating business” or “no longer being worked on by anyone” were removed from the base for periods following their transitions out of the “start-up phase” status.

Appendix.5Ax.1. Constructing Start-Up Time Lines Data Set

119

Table 5Ax.1.1 PSED I sample attrition Criteria for inclusion All cases in original data file Retain cases that did not report going business prior to initial interview [See Table C.3, page 499, in Reynolds and Curtin, Appendix C, Gartner et al., 2004]. Retain cases with at least one follow-up interview Retain cases with three or more start-up acts Retain cases with two start-up acts within a 12 month period Retain cases that do not report positive monthly cash flow two years prior to any other start-up event Retain cases where initial act was reported less than ten years before the initial interview

Cases 830 824 690 682 669 668 648

To confine the assessment to only those cases that met the initial criteria, the sample was systematically reduced, the case reduction criteria is presented in the following Table 5Ax.1.1. The distribution of selected variables before and after the attrition criteria developed above is presented in the following Table 5Ax.1.2. The distributions for most variables are quite similar and none of the differences are statistically significant. The biggest differences are with ethnic status, with a lower proportion of minorities in the consolidated sample; this probably reflects the additional difficulty of locating minorities for follow-up interviews. Based on this assessment, it would appear that this customized data set was representative of the initial sample that met the criteria for nascent entrepreneurs in the initial interview. For analysis the wave one weights were utilized, adjusted so the average weight equaled one. Most of the “conception dates” occurred prior to the initial detailed interview. Even though those that appeared to begin the process more than 10 years (120 months) prior to the first interview were deleted, there was still a considerable variation in the “conception to first interview” gap. The mean of this time lag was 26 months, the median 20 months, and the range from minus 45 months (occurring four years after the first interview) to 120 months. For seven it was actually negative, as their conception date occurred after the first detailed interview. This operational feature of the procedure may affect two aspects of the analysis: (1) the likelihood that a start-up would be reported as an operating new firm and (2) the relationship between the various

120

Methodlogical Appendices

Table 5Ax.1.2 Comparison of PSED I samples: pre and post attrition Pre attrition Number of cases Gender Males Females

824

Post attrition 648

51.3% 48.7%

49.7% 50.3%

Age 18–24 years old 25–34 years old 35–44 years old 45–54 years old 55–up years old Missing data

8.3% 26.6% 31.3% 23.7% 9.1% 1.1%

8.2% 24.1% 31.6% 26.2% 8.8% 1.1%

Ethnic background White Black Hispanic Other Missing data

59.3% 26.1% 10.1% 3.2% 1.3%

63.3% 23.3% 8.8% 3.2% 1.4%

Educational attainment No high school degree High school degree Post high school, no college degree College degree Graduate experience Missing data

4.5% 23.2% 32.6% 25.2% 14.0% 0.5%

3.7% 21.8% 32.4% 25.6% 15.9% 0.6%

Labor force status Working full-time Working part-time Not working, retired Missing data

69.9% 14.7% 15.2% 0.2%

68.2% 15.9% 15.6% 0.3%

86.9% 0.8% 6.2%

85.8% 0.8% 6.8%

5.2% 0.8%

5.7% 0.9%

Expected business ownership Full ownership by one or more natural persons Independent start-up, legal persons own up to 50% Franchise or multi-level marketing, legal persons own up to 50% Business sponsored, legal persons own up to 50% Legal persons own 51–100%

independent variables and the likelihood that a start-up would be reported. The pattern related to reports of operational new firms is presented in Table 5Ax.1.3.

Appendix.5Ax.1. Constructing Start-Up Time Lines Data Set

121

Table 5Ax.1.3 Conception to first interview time lag and start-up outcomes Conception to first interview time lag Up to 12 months 12 to 36 months 36 to 120 months

Percentage of cases (n = 648) (%) 30.8 47.7 21.6

Average lag (months) 6.8 22.2 61.1

Percentage reporting a new firm in a follow-up interview (%) 28.0 34.4 30.7

This pattern is slightly curvilinear, with more new firms reported by those initiating conception 12 to 36 months prior to the first interview; the differences in the proportions reporting a new firm, however, are far from statistically significant. The second issue was explored by considering the potential impact of the conception-interview time lag on the relationship between 89 independent variables and the measure of outcome, reports of an operating new business. It was found that for 60 variables (67%) the lack of statistical significance was present for the overall relationship as well as for each of the three conception-interview time lag subgroups. For one variable (1%) the positive relationship was found for both the overall sample and for each time lag subgroup. For 19 variables (21%) the overall relationship was statistically significant, but it was not significant for one or two of the time lag groups. This appeared, in most cases, to reflect differences in sample size. For nine variables (10%) the overall relationship was not statistically significant but it was significant for one of the time-lag sub-groups. There was no apparent pattern in these differences, suggesting that no major biases were introduced into the analysis by the use of all cases where the start-up was initiated up to 120 months prior to the first interview. This suggests that the strategy adopted in other similar analyses, to restrict analysis to those cases initiated no more than nine months prior to the first detailed interview may have lead to an unnecessary reduction in the sample (Delmar and Shane, 2003). Based on the analysis developed to explore the impact of the conception-interview time lag, it would seem that incorporating start-ups initiated up to 60 months (five years) prior to the initial detailed interview should not provide any serious bias in the subsequent analysis.

122

Methodlogical Appendices

Appendix.5Ax.2

Disposition of All Cases and 72 Month Outcome Status

A listing of all cases in the nascent entrepreneur cohort is provided below. For each case, eleven variables are provided, described as follows: RESPID ID CASEKEEP WT_72MT

830 830 830 648

CPT_YR CPT_MTH PHYR PHMTH STAT_72M GBLG_MTH QTLG_MTH

830 804 830 830 648 200 221

INITIAL NE CASE ID NUMBER: P3281 DATA SHORT CASE ID NUMBER 0 = GOOD CASE, DROP VALUES > 0 WAVE 1 WEIGHT RE-CENTERED FOR 72 MO OUTCOME CASES START-UP CONCEPTION YEAR : CALCULATED START-UP CONCEPTION MONTH: CALCULATED INITIAL DETAILED PHONE INTERVIEW: YEAR INITIAL DETAILED PHONE INTERVIEW: MONTH START-UP OUTCOME STATUS AT 72 MONTHS CONCEPTION TO GOING FIRM BIRTH LAG: MONTHS CONCEPTION TO QUIT START-UP LAG: MONTHS

The variable CASEKEEP was computed to identify those cases to be excluded from the analysis. The value label and reasons for exclusions are provided in the following frequency distribution. Cases with a CASEKEEP value of “0” were retained for the analysis. Value label GOOD CASE 1ST ACT >10 YR B4 INTERVIEW +MTH CSH FL 24 MTHS B4 INTR >12 MTH ACT GAP <3 START-UP ACTS NO WAVE 2,3,4 INTERVIEWS EARLY +MTH CASH FLOW

Value .00 40.00 50.00 60.00 70.00 80.00 90.00 Total

Frequency 648 23 1 26 2 125 5 ------830

Percent 78.1 2.8 .1 3.1 .2 15.1 .6 -----100.0

The following listing is available from the author as an SPSS Portable file and an Excel spreadsheet file.

Appendix.5Ax.2. Disposition of All Cases and 72 Month Outcome Status

123

124

Methodlogical Appendices

Appendix.5Ax.2. Disposition of All Cases and 72 Month Outcome Status

125

126

Methodlogical Appendices

Appendix.5Ax.2. Disposition of All Cases and 72 Month Outcome Status

127

128

Methodlogical Appendices

Appendix.5Ax.2. Disposition of All Cases and 72 Month Outcome Status

129

130

Methodlogical Appendices

Appendix.5Ax.2. Disposition of All Cases and 72 Month Outcome Status

131

132

Methodlogical Appendices

Appendix.5Ax.2. Disposition of All Cases and 72 Month Outcome Status

133

134

Methodlogical Appendices

Appendix.5Ax.3

Detailed Comparison of Start-Ups Outcomes: New Firms and Others

All comparisons based only on the 648 nascents identified as qualified, reviewed in Appendix.5Ax.1, n = 648, as of their personal reports at the end of six years after entry into the start-up process. Some assessments are based on self-administered questionnaire data and the same size may be reduced by up to 30%. They can be identified by those variable labels that have a letter following the initial “Q.” Details of creation of multi-item indices or complex transforms are not provided, but vary

Appendix.5Ax.3. Detailed Comparison of Start-Ups Outcomes: New Firms and Others

depending on the nature of the feature being described. The column headings can be described as follows: Dimension, characteristics, factor: summary of dependent variable. New firm: Those nascents reporting a new firm at any time before the end of six years. Active SU, quit: those nascents reporting they have disengaged from the effort at any time the end of six years or, by default, are considered to be still active in the start-up effort. Stat signif: Statistical significance is provided from a Chi-Square test for cross tabulations and the F-test for the means comparisons. Alpha: Reliability, where appropriate, computed as Chronbach’s Alpha. Table: The table in this chapter in which the results are summarized. Hand’k chapter: The chapter in the Gartner et al. (2004) Handbook of Entrepreneurial Dynamics in which the background and rationale for measure(s) is/are discussed. Some features are not covered in this handbook. Variable label: The variable labels from the phone interviews and mail questionnaires or as transformed and provided in the full PSED I data set; in some cases items used to compute multi-item indices or transforms are listed.

Dimension, characteristics, factor All

New firm 31.6%

Active SU, quit 68.4%

Men Women

31.4% 32.0%

68.6% 68.0%

18–24 yrs at conception/ interview 25–34 yrs at conception/ interview 35–44 yrs at conception/ interview 45–54 yrs at conception/ interview

25.9%

74.1%

29.7%

70.3%

34.2%

65.8%

34.4%

65.6%

Stat sign

Alpha

Table

Hand’k chap

N/A

5.1

2

N/A

5.1

None

Variable labels NCGENDER

0.8824 AGE CPT5

135

136

Methodlogical Appendices

Dimension, characteristics, factor 55–80 yrs at conception/ interview

New firm 30.6%

Active SU, quit 69.4%

Men: 18–24 yrs at conception/ interview Men: 25–34 yrs at conception/ interview Men: 35–44 yrs at conception/ interview Men: 45–54 yrs at conception/ interview Men: 55–80 yrs at conception/ interview Women: 18–24 yrs at conception/ interview Women: 25–34 yrs at conception/ interview Women: 35–44 yrs at conception/ interview Women: 45–54 yrs at conception/ interview Women: 55–80 yrs at conception/ interview

22.3%

77.7%

29.2%

70.8%

35.4%

64.6%

33.3%

66.7%

37.5%

62.5%

34.0%

66.0%

30.4%

69.6%

32.3%

67.7%

36.0%

64.0%

15.7%

84.3%

White Hispanic Black Other

34.2% 31.7% 22.3% 17.6%

65.8% 68.3% 77.7% 82.4%

Lived in county 0–2 years Lived in county 2–5 years

34.4%

65.6%

30.3%

69.7%

Stat sign 0.5831

Table

Hand’k chap

5.1

None

N/A

5.1

3

PGRACE

N/A

5.1

6

Q353A MT

Alpha

Variable labels

NCGENDER, AGE CPT5

0.7971

0.0497

Appendix.5Ax.3. Detailed Comparison of Start-Ups Outcomes: New Firms and Others Dimension, characteristics, factor Lived in county 5–10 years Lived in county 10–20 years Lived in county 20–40 years Lived in county 40–75 years

New firm 29.7%

Active SU, quit 70.3%

27.5%

72.5%

35.0%

65.0%

30.7%

69.3%

Lived in state 0–2 years Lived in state 2–5 years Lived in state 5–10 years Lived in state 10–20 years Lived in state 20–40 years Lived in state 40–75 years

38.1%

61.9%

24.6%

75.4%

26.6%

73.4%

27.8%

72.2%

33.9%

66.1%

35.1%

64.9%

Born in the United States Not born in the United States

31.2%

68.6%

39.0%

61.0%

Up to HS degree Post HS, Pre college degree College degree Graduate experience

26.8% 31.0%

73.2% 69.0%

36.8% 31.3%

63.2% 68.7%

0.3516

53.4%

52.4%

44.6%

Parent’s own a business Worked for parent Family friends encouraged start-up Friends and neighbors own businesses Impression of owning a business from friends, relatives

Stat sign

Alpha

Table

Hand’k chap

Variable labels

N/A

5.1

6

Q354 MT

N/A

5.1

6

Q358

N/A

5.1

7

ITRWEDU4

0.8244

N/A

5.1

16

Q362

39.3%

0.3612

N/A

5.1

16

64.9%

64.0%

0.8653

N/A

5.1

16

Q367, Q371, Q375 Q379

2.22

2.13

0.6418

N/A

5.1

16

Q377 (4-point)

4.16

4.13

0.6699

N/A

5.1

16

Q378 (5-point)

0.7810

0.4159

0.3089

137

138

Methodlogical Appendices

Dimension, characteristics, factor Never married Married or living as married Other: Divorced, widowed, separated etc.

New firm 35.1% 32.9%

Active SU, quit 64.9% 67.1%

21.8%

78.2%

Single adult

41.8%

58.2%

Two or more adults: no children Adults and children less than 19 years old

29.9%

70.1%

30.4%

69.6%

0.1003

Household size: all ages Household size: adults only Household: total earning money in previous week

3.04

3.14

2.18

Stat sign

Alpha N/A

Table 5.2

Hand’k chap 4

Variable labels Q385

N/A

5.2

4

Q380, Q381, Q382, Q383

0.3973

N/A

5.2

4

Q380

2.14

0.3645

N/A

5.2

4

Q384

1.73

1.72

0.8344

N/A

5.2

4

Q384A

HH income: 0–$20,000/Yr HH income: $20–40,000/Yr HH income: $40–60,000/Yr HH income: $60–100,000/Yr HH income: $100,000–Up/Yr

29.9%

70.1%

N/A

5.2

5

HHINCR5

26.2%

73.8%

33.2%

66.8%

33.6%

66.4%

42.9%

57.1%

HH net worth: negative HH net worth: $0–100,000 HH net worth: $100,000– 250,000 HH net worth: $250,000– 500,000 HH net worth: $500–1,000,000 HH net worth: $1,000,000 and up

41.6%

58.4%

N/A

5.2

5

HHNETR6

28.5%

71.5%

39.3%

60.7%

36.8%

63.2%

29.6%

70.4%

27.7%

72.3%

0.0855

0.1394

0.2648

Appendix.5Ax.3. Detailed Comparison of Start-Ups Outcomes: New Firms and Others Dimension, characteristics, factor Last work day: ave hours on work plus travel Last work day: ave hours on start-up firm Last day off: ave hours on work plus travel Last day off: ave hours on start-up firm

New firm 6.58

Active SU, quit 7.07

Stat sign 0.2205

Alpha N/A

Table 5.2

Hand’k chap 9

Variable labels QM5D1

2.15

2.12

0.9103

N/A

5.2

9

QM5E1

0.62

0.64

0.9287

N/A

5.2

9

QM5D2

1.53

2.25

0.0061

N/A

5.2

9

QM5E2

Satisfaction with most recent job [Z-score] Satisfied with life overall [Z-score]

0.34

0.37

0.7983

N/A

5.2

14

QI8

0.18

−0.09

0.0061

N/A

5.2

14

QL1M

Self realization

3.86

3.95

0.2884

0.78

5.3

12

QG1R, QG10, QG1P, QG1H

Financial security

3.54

3.59

0.6225

0.78

5.3

12

Recognition

2.57

2.53

0.7497

0.76

5.3

12

Role expectations

1.92

1.85

0.4791

0.60

5.3

12

Innovation

2.61

2.63

0.8583

0.71

5.3

12

Independence

4.14

4.14

0.9449

0.66

5.3

12

QG1K, QG1G, QG1J, QG1N QG1L, QG1E, QG1A QG1D, QG1L QG1C, QG1M, QG1Q QG1B, AG1F

Entrepreneurial expectations

4.32

4.18

0.0112

0.83

5.3

13

QK1A, QK1B, QK1C, QK1D, QK1E, QK1F

34.5%

65.5%

N/A

5.3

18

QI9

Problem complexity: identifying problems for priority

139

140

Methodlogical Appendices

Dimension, characteristics, factor Problem complexity: developing solutions

New firm 32.9%

Active SU, quit 67.1%

Business problem solving: calculating and analytical Business problem solving: intuitive Business problem solving: varies by situation

33.2%

66.8%

36.0%

64.0%

32.5%

67.5%

Cognitive style: different or mixed Cognitive style: better

25.6%

74.4%

35.1%

64.9%

0.0471

Entrepreneurial intensity

3.41

3.28

0.0403

Prefer to grow as large as possible Prefer to stay a manageable size

18.3%

22.4%

81.7%

77.6%

0.2349

Projected Jobs in first full year of operation Projected Jobs in fifth full year of operation Projected Sales in first full year of operation ($1,000) Projected Sales in fifth full year of operation ($1,000)

4.5

27.6

29.1

Percent equity ownership in five years Proportion expect firm to primary HH income

Stat sign 0.7247

Alpha

Table

Hand’k chap

Variable labels

N/A

5.3

18

QJ1

N/A

5.3

15

Q327

0.72

5.3

17

QL1D, QL1E, QL1F, QL1G

N/A

5.3

33

Q322

0.4126

N/A

5.3

33

Q318, Q319

30.6

0.9394

N/A

5.3

33

Q320, Q321

194.2

692.8

0.0975

N/A

5.3

33

Q317

1,542.7

2,386.1

0.3077

N/A

5.3

33

Q317A

68.3%

67.6%

0.7912

N/A

5.3

33

Q323

66.7%

64.4%

0.4036

N/A

5.3

33

Q324

0.8400

Appendix.5Ax.3. Detailed Comparison of Start-Ups Outcomes: New Firms and Others Dimension, characteristics, factor Estimated probability firm operating in five years

New firm 85.2%

Active SU, quit 80.0%

Stat sign 0.0117

Alpha N/A

Table 5.3

Hand’k chap 33

Frequency of new, unpredictable situations at work Feel overloaded, pushed to limits at work Delay difficult problem decisions to gather more information

2.34

2.42

0.4535

N/A

5.3

18

QJ2A

3.22

3.11

0.2883

N/A

5.3

18

QJ2B

3.54

3.63

0.2936

N/A

5.3

18

QL1R

Locus of control

4.09

3.96

0.0143

0.47

5.3

19

Ignore sunk costs in decision making Focus on current value when selling asset, not cost

3.07

2.98

0.4001

N/A

5.3

20

QL1H, QL1I, QL1J QL1K

3.61

3.40

0.0309

N/A

5.3

20

QL1L

Confidence in social settings

3.95

3.83

0.0419

0.48

5.3

21

Emotional control Shyness

3.04 2.74

2.97 2.82

0.4499 0.2830

0.57 0.04

5.3 5.3

21 21

QL1T, QL1X, QL1Y QL1S.QL1V QL1U, QL1W

Belief in incremental, systematic search Belief that good ideas just occur

3.29

3.29

0.9937

0.43

5.3

24

QK1J, QK1L

2.83

2.81

0.8970

N/A

5.3

24

QK1K

Desire for business preceded idea Desire/idea occurred together Idea for business preceded desire

31.3%

68.7%

N/A

5.3

24

QA2

32.7%

67.3%

35.4%

64.6%

0.6881

Variable labels Q325

141

142

Methodlogical Appendices

Dimension, characteristics, factor Emphasis on high payoff/high risk Emphasis on high personal impact Prefers collective/group efforts Prefers challenge/task focus Financial issues in firm choice Operational issues in firm choice

No same industry experience 1–5 years same industry experience 6–14 years same industry experience 15–60 years same industry experience Helped start no other businesses Helped start one other business Helped start 2–4 other businesses Helped start 5–60 other businesses Full time paid work experience: years Managerial, supervisory, administrative work exper: years

Active SU, quit 2.53

Stat sign 0.9384

Alpha 0.52

Table 5.3

Hand’k chap None

Variable labels QH1, QH2

1.73

1.70

0.3782

0.44

5.3

None

QH5, QH6

1.35

1.47

0.0016

0.19

5.3

None

QH4, QH8

1.46

1.47

0.6766

0.17

5.3

None

QH3, QH7, QH9

2.38

2.39

0.8135

0.60

5.3

None

2.42

2.47

0.2064

0.58

5.3

None

QH10B, QH10C QH10A, QH10D, QH10E, QH10F, QH10G

20.9%

79.1%

N/A

5.4

6

Q199, Q213 1

31.0%

69.0%

37.2%

62.8%

38.1%

61.9%

31.1%

68.9%

N/A

5.4

6

Q200, Q214 1

28.7%

71.3%

35.6%

64.4%

31.6%

68.4%

0.6875

18.75

16.98

0.0570

N/A

5.4

None

Q340

9.81

7.94

0.0080

N/A

5.4

None

Q341

New firm 2.54

0.0025

Appendix.5Ax.3. Detailed Comparison of Start-Ups Outcomes: New Firms and Others Dimension, characteristics, factor General management classes, average taken Human, financial management classes, average taken Operations management classes, average taken

Active SU, quit 1.78

Stat sign 0.5148

Alpha 0.64

Table 5.4

Hand’k chap 7

0.99

0.72

0.0704

0.61

5.4

7

0.75

0.60

0.2586

0.27

5.4

7

QF1C1, QF1E1, AF1G1

General management work experiences, avg years

4.54

3.56

0.0328

0.84

5.4

7

Operations management work experiences, avg years

3.58

2.57

0.0159

0.65

5.4

7

QF1A2, QF1B2, QF1D2, QF1F2, QF1H2, QF1I2 QF1C2, QF1E2, AF1G2

Total activity count: over 12 prior years Yrs in which full-time employment Yrs in which part-time employment Yrs in which full-time self-employment Yrs in which part-time self-employment Yrs in which full-time student Yrs in which part-time student Yrs in which unemployed seeking work

18.34

18.99

0.3847

N/A

5.4

10

QO1A87QO1D91

4.21

4.30

0.1750

N/A

5.4

10

QO1A87QO1D91

1.98

2.17

0.4961

N/A

5.4

10

QO1A87QO1D91

1.72

1.27

0.1007

N/A

5.4

10

QO1A87QO1D91

1.74

1.62

0.6854

N/A

5.4

10

QO1A87QO1D91

1.46

1.91

0.1332

N/A

5.4

10

QO1A87QO1D91

0.83

0.90

0.7162

N/A

5.4

10

QO1A87QO1D91

0.16

0.34

0.0524

N/A

5.4

10

QO1A87QO1D91

New firm 1.90

Variable labels QF1A1, QF1B1, QF1H1, QF1I1 QF1D1, QF1F1

143

144

Methodlogical Appendices

Dimension, characteristics, factor Yrs in which unemployed not seeking work Yrs in which doing unpaid volunteer work Yrs in which a homemaker Yrs in which disable and unable to work Yrs in which retired

New firm 0.15

Active SU, quit 0.27

Stat sign 0.2165

Alpha N/A

Table 5.4

Hand’k chap 10

Variable labels QO1A87QO1D91

0.60

1.15

0.0367

N/A

5.4

10

QO1A87QO1D91

1.78

1.91

0.7238

N/A

5.4

10

0.13

0.32

0.2924

N/A

5.4

10

QO1A87QO1D91 QO1A87QO1D91

0.22

0.23

0.9844

N/A

5.4

10

Start-up problem index (five items)

3.17

3.22

0.5316

0.51

5.5

Start-up problems: social challenges Start-up problems: personal challenges

2.87

3.10

0.0342

0.54

5.5

25

QC1A, QC1B

3.36

3.29

0.3848

0.41

5.5

25

QC1C, QC1D, QC1E

Entrepreneurial climate: community support groups Entrepreneurial climate: friends and family models Entrepreneurial climate: community models

2.68

2.70

0.7464

0.69

5.5

35

2.48

2.49

0.9192

0.65

5.5

35

QB1B, QB1C, QB1D, QB1E, QB1I QB1G, QB1H

3.76

3.77

0.9161

0.38

5.5

35

QB1A, QB1F, QB1J

Econ/Community context, uncertainty: overall

2.92

2.89

0.7582

0.73

5.5

36

QD1A, QD1B, QD1C, QD1D, QD1E, QD1F, QD1G, QD1H, QD1I, QD1J, QD1K

QO1A87QO1D91 QC1A, QC1B, QC1C, QC1D, QC1E

Appendix.5Ax.3. Detailed Comparison of Start-Ups Outcomes: New Firms and Others Dimension, characteristics, factor Econ/Community context, uncertainty: financial Econ/Community context, uncertainty: competitive Econ/Community context, uncertainty: operational

New firm 2.35

Active SU, quit 2.36

Stat sign 0.9526

Alpha 0.72

Table 5.5

Hand’k chap 36

3.90

3.91

3.7258

0.05

5.5

36

2.16

2.34

0.1644

0.44

5.5

36

Total team start-up time committed: 0–100 hours

19.7%

80.3%

N/A

5.6

None

Q197, Q211 1, Q211 2, Q211 3, Q211 4, Q211 5

Total team start-up time committed: 101–500 hours Total team start-up time committed: 501–2,000 hours Total team start-up time committed: 2,001–7, 500 hours

34.3%

65.7%

34.3%

65.7%

38.7%

61.3%

Start-up time committed/ member: 0–80 hours Start-up time committed/ member: 81–300 hours Start-up time committed/ member: 301–1,000 hours Start-up time committed/ member: 1,001–5,000 hours

17.3%

82.7%

N/A

5.6

None

TEAMZP

36.0%

64.0%

39.1%

60.9%

36.8%

93.2%

Variable labels QD1C, QD1D, QD1J, QD1K QD1F, QD1G, QD1H, QD1I QD1A, QD1B, QD1E

0.0016

0.0001

145

146

Methodlogical Appendices

Dimension, characteristics, factor Total team start-up time committed/ month: 0–8 hours Total team start-up time committed/ month: 9–36 hours Total team start-up time committed/ month: 37–80 hours Total team start-up time committed/ month: 81–700 hours

New firm 22.0%

Active SU, quit 78.0%

31.0%

69.0%

36.9%

63.1%

37.3%

62.7%

Start-up time committed/ member/month: 0–6 hours Start-up time committed/ member/month: 7–20 hours Start-up time committed/ member/month: 21–50 hours Start-up time committed/ member/month: 51–426 hours

23.0%

77.0%

29.4%

70.6%

39.7%

60.3%

37.2%

62.8%

Extractive sectors Transformative sectors Distributive sectors Business services sectors Consumer services sectors

38.4% 29.0%

61.6% 71.0%

43.2%

56.8%

32.8%

67.2%

29.2%

70.8%

Stat sign

Alpha N/A

Table 5.6

Hand’k chap None

Variable labels Conception to 1st interview

N/A

5.6

None

TEAMSZP; Conception to 1st interview

N/A

5.6

23

0.0084

0.0044

0.3831

SUSIC 5

Appendix.5Ax.3. Detailed Comparison of Start-Ups Outcomes: New Firms and Others Dimension, characteristics, factor Sole proprietorship Partnership Corp, LLC Other, not yet

New firm 34.4%

Active SU, quit 65.6%

25.1% 38.7% 14.7%

74.9% 61.3% 85.3%

Private home Exist business location Dedicated new firm location Other/not needed

30.5% 38.0%

69.5% 62.0%

39.4%

60.6%

23.8%

76.2%

Natural persons: 100% ownership Natural persons: 51–99% ownership Natural persons: 0–50% ownership

31.5%

68.5%

28.5%

71.5%

74.1%

25.9%

One person start-up team Two persons start-up team Three persons start-up team Four persons start-up team Five persons start-up team

28.7%

71.3%

37.2%

62.8%

35.3%

64.7%

15.9%

84.1%

34.2%

65.8%

0.0922

Reporting social network present (proportion) Number in social network (average)

66.7%

64.2%

3.37

3.24

Contact helping programs: four waves No contact with helping programs: four waves

35.3%

23.3%

64.7%

76.7%

Stat sign

Alpha N/A

Table 5.6

Hand’k chap 23

Variable labels Q189

N/A

5.6

23

Q194

N/A

5.6

27

AUTONSU

N/A

5.6

27

TEAMZP

0.5372

N/A

5.6

29

Q241

0.8057

N/A

5.6

29

Q242

N/A

5.6

30

Q303, R755, S755, T755

0.0098

0.1042

0.0340

0.0017

147

148

Methodlogical Appendices

Dimension, characteristics, factor Program sponsor: government

New firm 38.8%

Active SU, quit 61.2%

Program sponsor: educational institution Program sponsor: business association Program sponsor: for profit organization

43.7%

56.3%

42.2%

57.8%

26.9%

73.1%

0.7073

Number programs contacted: four waves

2.21

3.68

Hours spend most recent program: four waves

116.35

Estimated value of help in dollars: four waves Number of programs known about: four waves

Stat sign

Alpha N/A

Table 5.6

Hand’k chap 30

Variable labels Q306, R759, S759, T759

0.1370

N/A

5.6

30

89.03

0.7260

N/A

5.6

30

1991.08

1980.48

0.9839

N/A

5.6

30

11.05

13.58

0.6598

N/A

5.6

30

Total team funds invested: $0–$500

21.5%

78.5%

N/A

5.6

31

Q198, Q212 1, Q212 2, Q212 3, Q212 4, Q212 5

Total team funds invested: $501–$3,000 Total team funds invested: $3,001–$12,000 Total team funds invested: $12,001–$56,000

27.0%

73.0%

38.1%

61.9%

40.6%

59.4%

Funds invested/ member: $0–$500

22.0%

78.0%

N/A

5.6

31

TEAMSZP

Q305, R757, S757, T757 Q309, R762, S762, T762 Q311, R764, S764, T764 Q316, R769, S769, T769

0.0003

Appendix.5Ax.3. Detailed Comparison of Start-Ups Outcomes: New Firms and Others Dimension, characteristics, factor Funds invested/ member: $501–$2,000 Funds invested/ member: $2,001–$7,500 Funds invested/ member: $7, 501–$164,000

New firm 32.7%

Active SU, quit 67.3%

34.6%

65.4%

41.3%

58.7%

Total team funds invested/month: $0–$30 Total team funds invested/month: $31–$150 Total team funds invested/month: $151–$500 Total team funds invested/month: $501–$28,000

21.5%

78.5%

26.7%

73.3%

38.2%

61.8%

38.9%

61.1%

Funds invested/ member/month: $0–$25

24.1%

75.9%

Funds invested/ member/month: $26–$100 Funds invested/ member/ month: $101–$500 Funds invested/ member/ month: $501–$10,000

27.9%

72.1%

34.0%

66.0%

43.0%

57.0%

Accounting sophistication: cash accounting Accounting sophistication: bank account, not accrual Accounting sophistication: bank acct, accrual

24.4%

75.6%

35.6%

64.4%

22.6%

77.4%

Stat sign

Alpha

Table

Hand’k chap

Variable labels

N/A

5.6

31

Conception to 1st interview

N/A

5.6

31

TEAMSZP; Conception to 1st interview

N/A

5.6

32

QE1A, QE1C, QE1E

0.0020

0.0008

0.0046

0.2504

149

150

Methodlogical Appendices

Dimension, characteristics, factor Business planning: none, market assessment only Business planning: market assessment and buss plan Business planning: financial and marketing or plan Business planning: financial, mkt assessment, plan Competitive strategy: hi technology processes Competitive strategy: new, quality products Competitive strategy: lower prices Competitive strategy: superior location, convenience Competitive strategy: niche market Competitive strategy: superior quality No technology emphasis Low technology emphasis Medium technology emphasis High technology emphasis

New firm 31.8%

Active SU, quit 68.2%

26.7%

73.3%

43.8%

56.2%

36.0%

64.0%

0.0540

2.92

2.76

2.81

Stat sign

Alpha N/A

Table 5.6

Hand’k chap 32

0.0576

0.49

5.6

37

Q302G, Q302I

2.75

0.5224

0.58

5.6

37

Q302D, Q302E

2.61

2.55

0.5323

N/A

5.6

37

Q302

2.69

2.85

0.1152

N/A

5.6

37

Q302C

3.15

3.17

0.7695

N/A

5.6

37

Q302B

3.69

3.60

0.0993

N/A

5.6

37

Q302A

35.5%

64.5%

0.32

5.6

38

Q299, Q300, Q301

30.4%

69.6%

24.9%

75.1%

28.4%

71.6%

0.2079

Variable labels Q111, Q112, Q134, Q135

Appendix.5Ax.3. Detailed Comparison of Start-Ups Outcomes: New Firms and Others Dimension, characteristics, factor No and low tech

New firm 32.9%

Active SU, quit 67.1%

Stat sign

Medium and high technology

25.8%

74.2%

0.0820

Per capita total personal income, 1993: 0–25%-tile Per capita total personal income, 1993: 25–50%-tile Per capita total personal income, 1993: 50–75%-tile Per capita total personal income, 1993: 75–100%-tile

30.9%

69.1%

35.0%

65.0%

31.0%

69.0%

30.0%

70.0%

Per cent HH w/ income $75,000-up, 1989: 0–25%-tile Per cent HH w/ income $75,000-up, 1989: 50–75%-tile Per cent HH w/ income $75,000-up, 1989: 50–75%-tile Per cent HH w/ income $75,000-up, 1989: 75–100%-tile

39.9%

60.1%

27.0%

73.0%

31.7%

68.3%

29.8%

70.2%

Per cent population 25–44 years old, 1990: 0–25%-tile Per cent population 25–44 years old, 1990: 25–50%-tile

33.2%

66.8%

32.0%

68.0%

Alpha

Table 5.6

Hand’k chap 38

Variable labels Q299, Q300, Q301

N/A

5.7

None

PCINC934

N/A

5.7

None

HH75K894

N/A

5.7

None

P2544904

0.7854

0.1179

151

152

Methodlogical Appendices

Dimension, characteristics, factor Per cent population 25–44 years old, 1990: 50–75%-tile Per cent population 25–44 years old, 1990: 75–100%-tile

New firm 35.8%

Active SU, quit 64.2%

Stat sign

26.0%

74.0%

0.2312

Per cent 25+ yrs w/college degrees, 1990: 0–25%-tile Per cent 25+ yrs w/college degrees, 1990: 25–50%-tile Per cent 25+ yrs w/college degrees, 1990: 50–75%-tile Per cent 25+ yrs w/college degrees, 1990: 75–100%-tile

34.6%

65.4%

33.2%

66.8%

33.4%

66.6%

26.1%

73.9%

Urbanization index, four items: 0–25%-tile Urbanization index, four items: 25–50%-tile Urbanization index, four items: 50–75%-tile Urbanization index, four items: 75–100%-tile

40.2%

59.8%

26.2%

73.8%

34.1%

65.9%

27.8%

72.2%

Population density, persons/sq mile, 1992: 0–25%-tile

41.2%

58.8%

Alpha

Table

Hand’k chap

Variable labels

N/A

5.7

None

PCOLL904

0.87

5.7

None

PCINC934, HH75K894, P2544904, PCOLL904

N/A

5.7

None

POPDN924

0.3319

0.0447

Appendix.5Ax.4. Constructing Start-Up Activity Indices Dimension, characteristics, factor Population density, persons/sq mile, 1992: 25–50%-tile Population density, persons/sq mile, 1992: 50–75%-tile Population density, persons/sq mile, 1992: 75–100%-tile Population growth, avg annual: 1980–1992: 0–25%-tile Population growth, avg annual: 1980–1992: 25–50%-tile Population growth, avg annual: 1980–1992: 50–75%-tile Population growth, avg annual: 1980–1992: 75–100%-tile

New firm 27.8%

Active SU, quit 72.2%

26.6%

73.4%

32.4%

67.6%

29.9%

70.1%

35.3%

64.7%

31.2%

68.8%

29.5%

70.5%

Appendix.5Ax.4

Stat sign

Alpha

Table

Hand’k chap

N/A

5.7

None

153

Variable labels

0.0231

PC8092A4

0.6498

Constructing Start-Up Activity Indices

The procedure for developing the indices involved attention to both the results of standard factor analysis and reliability measures using SPSS PC 5.0.1. Final allocations of items to factors involved consideration of results from both assessments. Factors analysis was run on the acts initiated at 1 month, 6 months, and 1, 2, 3, 4, 5, and 6 years following conception. There were few clear patterns across the early periods, one and six months, but the results for years two through six reflected considerable stability; a six factor solution appeared in most assessments, using the standard default criteria. The weakest loading – split between two factors – was for initiating a bank account. The final allocation of items is as followed in

Items Established an exclusive bank account Devoted full time to start-up effort, 35+ hrs/week Installed dedicated phone line Initiated a phonebook or internet listing Hired an employee for pay Purchased raw materials, inventory, supplies, components Purchased, leased plant, equipment, property Promotion of product or service has started Received any money, income, or fees Established supplier credit Initial positive monthly cash flow Organized a start-up team Prepared a business plan Develop financial projections Asked financial institutions or other people for funds Time thinking about the new business Define market opportunities Investment own money Began to save money to invest Arranged child care, household help Taken any classes or workshop Developed product or service model or prototype Patent, trademark, copyright application submitted Paid first state unemployment insurance tax Paid first federal social security tax payment Filed first federal income tax return Know firm listed with Dun and Bradstreet

Domain

Business presence

Production implementation

Organizational, financial structure

Personal planning

Personal preparation

Task or product

Formal registration

Table 5Ax.4.1 Items included in the start-up activity domains

R573; R568; R594; R602;

R585; R588; R579; R619; R606; R621;

R617; R610; R632; R629; R612;

S573; S568; S594; S602;

S585; S588; S579; S619; S606; S621;

S617; S610; S632; S629; S612;

T573 T568 T594 T602

T585 T588 T579 T619 T606 T621

T617 T610 T632 T629 T612

Q175; Q178; Q179; Q181;

R633; R636; R637; R639;

S633; S636; S637; S639;

T633 T636 T637 T639

Q120; R577; S577; T577 Q124; R582; S582; T582

Q139; R596; S596; T596 Q151; R608; S608; T608 Q167; R625; S625; T625

Q109; r566; S566; T566 Q134; R591; S591; T591 Q143; R600; S600; T600

Q116; Q111; Q137; Q145;

Q128; Q131; Q122; Q162; Q149; Q163;

Q160; Q153; Q174; Q171; Q155;

PSED I: Variable labels

154 Methodlogical Appendices

Appendix.5Ax.4. Constructing Start-Up Activity Indices

155

Table 5Ax.4.2 Reliability for start-up activity domain indices, by year First month Business presence Production implementation Organizational, financial structure Personal planning Personal preparation Task, product development

Sixth month

First year

Second year

Third year

Fourth year

0.43 0.45 0.21

0.58 0.67 0.58

0.70 0.66 0.59

0.72 0.72 0.59

0.75 0.72 0.58

0.75 0.74 0.58

0.37 −0.02 0.22

0.55 0.38 0.26

0.52 0.31 0.25

0.54 0.36 0.25

0.52 0.36 0.24

0.51 0.38 0.22

Table 5Ax.4.1 [first letter of PSED I variable labels indicates the data collection wave: Q = 1, R = 2; S = 3; and T = 4]. Once the six factors were established, reliability to determine Chronbach’s Alpha was completed on all eight time periods. “Initiating a bank account” was allocated to equalize the reliability for the first two factors. The reliabilities for the measures for the first six time periods is presented in Table 5Ax.4.2, the results for years five and six were almost identical to that for the fourth year. It is clear that reliabilities stabilized after the first year for all items. The level is acceptable for business presence and production implementation, marginally acceptable for organizational, financial structure and personal planning, and less than satisfactory for personal preparation and the two item task, product development indices. The final indices were created by computing the percentage of activities reported in each domain at each time period, a value which could range from 0 to 100%. Given the benefit of simplifying the assessment, these six indices appear to provide a useful mechanism for describing the start-up activities of nascent entrepreneurs.