The Pricing and Revenue Management of Services: A Strategic Approach (Routledge Advances in Management & Business Studies)

The Pricing and Revenue Management of Services

In a world of changing lifestyles brought about by new services, technology and e-commerce, this book enters the arena of contemporary research with particular topicality. Integrating both theory and real world practices, Ng advances the latest concepts in pricing and revenue management for services in a language that is useful, prescriptive and yet thought-provoking. The first part of the book discusses the buyer as an individual, presenting the concepts behind what motivates purchase and the role of price within the motivation. The second part discusses the buyer in aggregate, investigating advanced demand, price discrimination and segmentation in service. Ng’s aim is to offer a strategic guide to increase revenue in services, drawing from various disciplines, whilst maintaining a strong marketing slant. Grounding the book on actual research in services, Ng is keen to highlight how the concepts and theories of pricing strategy can be combined and applied practically in a way that is easy to read and stimulating. This book will be of much interest to professionals and academics alike, specifically for managers in the service industry and as a text for executive training programmes. It would also be a useful supplementary text for students engaged with marketing and revenue and operations management in services. Irene C.L. Ng is an Associate Professor of Marketing and the Director of the Centre for Service Research at the School of Business and Economics at the University of Exeter, UK.

Routledge advances in management and business studies

1 Middle Managers in Europe Yves Frédéric Livian and John G. Burgoyne

7 HRM, Technical Workers and the Multinational Corporation Patrick McGovern

2 Marketing Apocalypse Eschatology, escapology and the illusion of the end Edited by Stephen Brown, Jim Bell and David Carson

8 The Internationalization of Small to Medium Enterprises The interstratos project Edited by Rik Donckels, Antti Haahti and Graham Hall

3 Relationship Marketing in Professional Services A study of agency–client dynamics in the advertising sector Aino Halinen

9 Neo-Industrial Organising Renewal by action and knowledge formation in a project-intensive economy Rolf A. Lundin, Hans Wirdenius, Eskil Ekstedt and Anders Soderholm

4 Job Design and Technology Taylorism vs anti-Taylorism Hans D. Pruijt 5 Regulation and Organisations International perspectives Edited by Glenn Morgan and Lars Engwall 6 Information Technology, Organisations and People Transformations in the UK retail financial services sector Jeff Watkins

10 Perspectives on Public Relations Research Edited by Danny Moss, Dejan Vercic and Gary Warnaby 11 Resources, Technology and Strategy Edited by Nicolai J. Foss and Paul L. Robertson

12 Telecommunications Regulation Culture, chaos and interdependence inside the regulatory process Clare Hall, Colin Scott and Christopher Hood 13 Rethinking Public Relations The spin and the substance Kevin Moloney 14 Organisational Learning in the Automotive Sector Penny West 15 Marketing, Morality and the Natural Environment Andrew Crane 16 The Management of Intangibles The organization’s most valuable assets A. Bounfour 17 Strategy Talk A critique of the discourse of strategic management Pete Thomas 18 Power and Influence in the Boardroom James Kelly and John Gennard 19 Public Private Partnerships Theory and practice in international perspective Stephen Osborne 20 Work and Unseen Chronic Illness Silent voices Margaret Vickers

21 Measuring Business Excellence Gopal K. Kanji 22 Innovation as Strategic Reflexivity Edited by Jon Sundbo and Lars Fuglsang 23 The Foundations of Management Knowledge Edited by Paul Jeffcutt 24 Gender and the Public Sector Professionals and managerial change Edited by Jim Barry, Mike Dent and Maggie O’Neill 25 Managing Technological Development Hakan Hakansson and Alexandra Waluszewski 26 Human Resource Management and Occupational Health and Safety Carol Boyd 27 Business, Government and Sustainable Development Gerard Keijzers 28 Strategic Management and Online Selling Creating competitive advantage with intangible web goods Susanne Royer 29 Female Entrepreneurship Implications for education, training and policy Edited by Nancy M. Carter, Colette Henry, Barra Ó Cinnéide and Kate Johnston

30 Managerial Competence within the Hospitality and Tourism Service Industries Global cultural contextual analysis John Saee

34 Development on the Ground Clusters, networks and regions in emerging economies Edited by Allen J. Scott and Gioacchino Garofoli

31 Innovation Diffusion in the New Economy The tacit component Barbara Jones and Bob Miller

35 Reconfiguring Public Relations Ecology, equity, and enterprise David McKie and Debashish Munshi

32 Technological Communities and Networks International, national and regional perspectives Dimitris G. Assimakopoulos

36 The Pricing and Revenue Management of Services A strategic approach Irene C.L. Ng

33 Narrating the Management Guru In search of Tom Peters David Collins

The Pricing and Revenue Management of Services A strategic approach

Irene C.L. Ng

First published 2008 by Routledge 2 Park Square, Milton Park, Abingdon, Oxon OX14 4RN Simultaneously published in the USA and Canada by Routledge 270 Madison Ave, New York, NY 10016 Routledge is an imprint of the Taylor & Francis Group, an informa business This edition published in the Taylor & Francis e-Library, 2007. “To purchase your own copy of this or any of Taylor & Francis or Routledge’s collection of thousands of eBooks please go to www.eBookstore.tandf.co.uk.” © 2008 Irene C.L. Ng All rights reserved. No part of this book may be reprinted or reproduced or utilised in any form or by any electronic, mechanical, or other means, now known or hereafter invented, including photocopying and recording, or in any information storage or retrieval system, without permission in writing from the publishers. British Library Cataloguing in Publication Data A catalogue record for this book is available from the British Library Library of Congress Cataloging in Publication Data A catalog record for this book has been requested ISBN 0-203-69659-X Master e-book ISBN ISBN10: 0-415-35077-8 (hbk) ISBN10: 0-203-69659-X (ebk) ISBN13: 978-0-415-35077-8 (hbk) ISBN13: 978-0-203-69659-0 (ebk)

Payment is a form of applause

The Economist, 19 December 2006

Contents

List of figures List of tables List of boxes Preface Acknowledgements Chapter synopses 1 Introduction Service pricing in practice 1 The study of pricing 4 The importance of the service sector 7 Definition of service 9 Service pricing – issues and challenges 11 Service characteristics impact on pricing 13 The cost-plus approach in pricing 16 Complexity of service pricing 18

xii xiv xv xvi xix xx 1

PART I

The buyer as an individual 2 The expected net value (ENV) framework Buyer choice 23 The ENV framework 26 Conclusion 39 3 Advanced purchase and the separation of purchase and consumption Risk at the point of purchase: valuation risk 42 Risk at the point of purchase: acquisition risk 46

21 23

41

x

Contents Bringing acquisition and valuation risks into the ENV framework 48 The marketing mix and its role in delivering net value 49 Competition: its influence on the ENV 53 Random components of choice 56 The expectations of service customers 62 Understanding the strategic nature of ENV 66 Trading off benefits and outlays 68 4 Seven strategies for higher revenues Strategy 1: price on value, not cost 70 Strategy 2: convert pareto loss into revenue 72 Strategy 3: decouple purchase (exchange) and consumption 76 Strategy 4: mitigate risk in valuation for advance purchase 78 Strategy 5: change the benefits 79 Strategy 6: customer effort could yield higher revenue 81 Strategy 7: find the highest end-value in intermediating services 85 Conclusion 87

70

PART II

Buyers in aggregate 5 The economics of pricing in services The demand function 91 Understanding price elasticity 93 The role of supply and capacity 96 Price discrimination 101 Advanced selling, demand and price discrimination 104 Dynamic pricing 105 6 The revenue management of services Introduction to revenue management 108 The evolution and scope of revenue management 113 Revenue management and advanced demand behaviour 116 Revenue management practices and tools 120 Competition and revenue management 124 Fairness and revenue management 125 7 Strategic pricing and revenue management: four more strategies for higher revenue The ability to practise revenue management 129

89 91

108

129

Contents xi The new revenue management system 130 The role of capacity 133 Strategy 8: re-segment, re-design and re-price 137 Strategy 9: segmenting and pricing through self-selection 142 Strategy 10: managing demand and supply through re-sale and refunds 145 Strategy 11: selling availability of the service 147 8 Conclusion Strategise with care: the need to understand how buyers and stakeholders view service pricing strategies 149 Service pricing vs goods pricing 149 More channels, more segments, more brands 151 Cross-functional approach towards pricing policies 151 Notes Index

149

153 169

Figures

1.1 1.2 2.1 2.2 2.3 2.4 2.5 2.6 2.7 2.8 2.9 2.10 3.1 3.2 3.3 3.4 3.5 3.6 3.7 3.8 3.9 3.10 3.11 3.12 3.13 3.14 3.15 4.1

Music is now available to subscribers No tangible product Changing expectations after consumption Evaluation of net value Expected benefits Another way of classifying attributes Expected outlays Reducing non-monetary costs by paying The Singapore Airlines Business Class seats Self checkout at Walmart The buyer decision process for services What price would you pay to avoid going? Buyer-seller exchange for a typical good and a service An outdoor concert at the Soundshell in Botanic Gardens, Wellington, New Zealand Discounted theatre tickets at New York’s Times Square – but what type of seats? Sensitising the buyer Information and its influence on value A drive-through automated teller machine (ATM) offered by Citibank in Singapore provides convenience A new channel for postal services Motivation to buy is subject to influence from alternatives and random factors Having the benefit of a fax machine without the machine The full ENV framework Gaps model of service quality Increase in ENV Repeat purchase when a service is below expectations The difference between the traditional understanding and revised understanding of value The augmentation trend and its implication on pricing Options for higher revenue

2 15 25 26 27 30 32 33 34 35 35 40 42 45 49 50 50 51 52 54 56 61 62 63 65 67 68 73

Figures xiii 4.2 4.3 4.4 4.5 4.6 5.1 5.2 5.3 5.4 5.5 5.6 5.7 6.1 6.2 7.1 7.2 7.3 7.4 7.5 7.6

Shuttle service at Hong Kong airport An example of a service purchased in advance that may not be consumed Sushi on a conveyor belt Communicating the value of a university degree How would you value an intermediating service? Demand function Consumer surplus Revenue functions Demand function of a firm with capacity constraints Price discrimination when buyers’ preferences are not known Third degree price discrimination The three characteristics of advanced demand The advanced demand exchange system What a complete revenue management system should look like Interdependence of the four decision sets in revenue management Building a typical service blueprint The service encounter and impact of external stimuli Uncertain waiting is longer than known, finite waiting Occupied time feels shorter Converting from pricing on delivery to pricing on availability

75 77 82 84 87 92 93 98 98 103 104 105 110 111 134 138 139 141 141 148

Tables

1.1 1.2 1.3 2.1 2.2 3.1 5.1 5.2 6.1 7.1

When is a buyer charged different prices? 1 The many different terms for price in services 8 A selection of published articles on services pricing in different industries 12 Key definitions of value, satisfaction and quality 25 Top ten pure service brands 31 Consequences of acquisition risk and valuation risk 47 Demand and marginal revenue for theatre tickets 97 Dutch auction: the bidding process 102 Revenue management practices in different industries 112–113 The ability to practise revenue management 131–132

Boxes

1.1 1.2 1.3 2.1 2.2 2.3 2.4 3.1 3.2 4.1 4.2 4.3 4.4 5.1 5.2 5.3 5.4 6.1 6.2 7.1 7.2 7.3 7.4 8.1

Examples of pricing techniques on the internet 2–3 Some of the objectives of pricing in services 6 Some ways of thinking about services 9 Definition of attributes and benefits 27–28 Attributes of a service experience 28–29 Common risks associated with the consumption of services 36 The complexity of determining what a service is worth 38–39 Challenges in distributing services 52–53 Hygiene factors in services 69 From fair-trade to carbon neutral? 76 Gaining through differentiation 78–79 Involving the customer 83 University – a co-created service 84–85 Social influence on price 95–96 Definition of three revenue functions 97 The strategic use of unused service capacity 99–101 Illustration of a Dutch auction 102 Mathematical formulations in revenue management 124 An email from an airline ticket buyer 126 Determining capacity – an operations perspective 135–137 The psychology of waiting lines 140 Six steps towards separating markets and differentiated pricing 144 Self-selection in the credit card industry 144–145 Pricing airport services 150–151

Preface

To the best of my knowledge, this book is the first in developing insights into the pricing and revenue management across service industries, drawing upon research from various disciplines. It also aims to integrate the theory and practice aspects of the subject. This book is written for both the practitioner and the academic. Its objective is to reach out to an audience that is interested in the pricing of services, both in terms of research and practice. To write a book grounded on research in a language that is accessible to a wider audience has proven to be most challenging and it remains a question if I have actually achieved it. The challenge comes from the diversity of the audience. First, service industries in themselves are diverse – from professional services (e.g. legal, accounting, consulting), transportation, hospitality, leisure to technological services. Hence, to write a book that is not too abstract and that is able to join all the dots and create relevance to any and all service firms is a demanding task. Second, academics and practitioners interested in service pricing are also diverse – from financial controllers, marketing, economists, operations personnel to researchers in various disciplines – they all come from very different backgrounds, and with different skill sets. In light of the diversity of the audience, the book must therefore incorporate some basic concepts before moving on to more advanced ideas. To do so, I have had to make certain assumptions on readers’ backgrounds and parts of the book may explain too much, while other parts may explain too little. That, unfortunately, is the risk I would have to take and since I am quite sure that it would not fully fit the purpose of everyone, I make my apologies to those who find some of the basic concepts in the book unnecessary or if parts of the book were too esoteric. This book does not claim to have an exhaustive coverage of all issues pertaining to the pricing and revenue management of services. Specifically, the more conventional aspects of pricing dealt with more than adequately by other pricing textbooks have been left out. The specific aims of the book are:

Preface xvii

As a strategic guide to increase revenue in services The pricing of services involves to some extent, economics, marketing, and operations research. I have felt for some time now that each discipline does not do the topic justice, and merely to cover the topic through the eyes of one discipline would not be useful. Practitioners of pricing do not operate according to disciplines. Their purpose is to put together a good pricing strategy, implement it and solve any potential problems that might arise. To do so, they would need to draw on tools, techniques and models from as many sources as possible. Consequently, this book attempts to take on relevant lessons from each discipline, with the aim of assisting firms in their pricing decision. There is, however, a strong marketing slant but only because pricing to improve revenues is a marketing objective.

New knowledge from research This book is grounded on research in services. The knowledge it contains takes from academic research papers across various service, operations, economic and service domain journals. It’s then put together in an integrated format, illustrated with examples for ease of prescription.

Integration between concepts, decisions and entities This book aims to show how the various concepts and theories combine for a pricing strategy that can be applied in practice. Instructors are often keen to impart principles and theories, but seldom emphasise how such principles and theories work together to solve a problem. As such, students tend to have a rather polarized view of concepts. For example, any marketing graduate is familiar with the concept of the 4 ‘P’s [Produce, Price, Promotion and Place (channel)]. Yet, the way the 4Ps work together to position the product is not much taught. Furthermore, it is not merely concepts that combine and interact. Interactions exist between decisions (product and pricing strategies) as well as entities (firm, buyer and the competitor). While each of the concepts introduced is to be understood in depth, I endeavor to show how these concepts combine so that they can be better applied to solve problems.

Making theory accountable to practice, and practice grounded in theory This book aims to provide a theoretical account of practice and at the same time, demonstrate through examples, a theory’s applicability to practice. The book aims to stimulate thinking in pricing across service industries and examine critically why practices are the way they are. It also aims to provide deeper insights into the gaps in practice, teaching and research, questioning fundamental ideas that shape knowledge in this area. It is believed that this approach would greatly

xviii Preface benefit both the world of practice and the research community in pricing and services.

Prescriptive, useful and easy to read Finally, this book aims to be prescriptive. Often, academic books focus on abstract principles and general analysis. This is necessary because only abstracted principles can be used to apply to different situations. Also, analysis is important as it is the key to understanding. For managers though, this may not be sufficient; conceptual theories may be too abstract for managers to see how they could be applied. It is a giant leap between knowing theories, and knowing which theories should be used towards solving a problem. In other words, we may perhaps understand the strategies employed by some top service firms but that does not mean that given a different context, we may know how to deliver a strategy that is just as powerful. With this in mind, this book aims to frame the concepts and principles in a more prescriptive framework to aid the pricing decision. My attempt to cut across industries and disciplines means that no industry/discipline is extolled, and indeed there is a sense that each industry/discipline may be diminished somewhat in its role towards the bigger picture i.e. the convergent view of a generic service and issues surrounding the pricing of it. Yet the need to have a book like this, even as an attempt, is pressing. With the service economy accounting for over 70 per cent of GDP in OECD (Organisation for Economic Co-operation and Development) countries, service firms are becoming increasingly competitive with revenue management and pricing becoming central in their focus for sustaining long term profitability. To that end, a major aim of this book is to stimulate creativity and innovative thinking in both research and practice of service pricing and revenue management. Finally, the hope is also that insights from this book would be a useful guide towards the teaching of the subject of service pricing and revenue management at business schools worldwide.

Acknowledgements

This book would not have been possible without my ever-supportive husband, BC, whom has had to be both mum and dad to my children, endured my various expressions of frustration and most of all, helped me carve out the space and time I needed to finish it. My thanks also go to Yin Foong Lim, my sub-editor, research assistant, manager, PA, (in short, everything!), who helped me with all the meticulous details; Nick Yip, Guo Lei and Paul Tseng, my doctoral students and research assistants who have all contributed to the research in the book; Roger Maull, my mentor and friend whose discussions have helped so much in crystallizing some of the main ideas of the book; colleagues at the School of Business and Economics, University of Exeter for their anecdotes and ideas. Acknowledgements also go to the co-authors of my various papers incorporated within the book, i.e. Jochen Wirtz, Khai Sheang Lee and Jeannie Forbes. Finally, special thanks go to my daughter Serene for the comic relief and the distractions without which I could probably have finished this book earlier, but would have been far less entertained.

Chapter synopses

Chapter 1: Introduction Chapter 1 sets the tone for the book, introducing service pricing in practice today. It examines the study of pricing and the study of price theory, and how, despite its importance in helping firms achieve better profits, pricing is still very much a neglected area of research. It discusses the importance of the service sector in today’s global economy, resulting in the growth of service research and the emergence of ‘service science’, a transdisciplinary field aimed at improving the performance of service businesses. It then looks at the elusive definition of a service, given its much-contended characteristics of heterogeneity, intangibility, perishability, and inseparability. Issues and challenges in service pricing are also examined, such as the impact of these service characteristics on the pricing decision, and how the cost-plus approach in pricing may not necessarily be the best approach for services.

Part I: The buyer as an individual Chapter 2: The expected net value (ENV) framework Chapter 2 is the first of three chapters that looks at pricing issues surrounding the buyer as an individual. It looks at the issues of buyer’s choice and buyer’s willingness to pay, and what value means to the buyer. It introduces the Expected Net Value (ENV) framework and its crucial role in forming pricing policies. The ENV is derived from buyers’ expected benefits and expected outlays; expected benefits include tangible and non-tangible attribute-driven benefits, while expected outlays comprise of monetary costs and non-monetary costs. This chapter explains how all this has an impact on the ENV and eventually, on pricing decisions. It also considers risks as an outlay and how risk is a factor in pricing. Chapter 3: Advanced purchase and the separation of purchase and consumption This chapter examines how the separation between the purchase and consumption of a service has implications on pricing, and considers the risks faced by

Chapter synopses xxi buyers at the point of purchase, which could be well in advance of consumption, i.e. advanced purchase. It discusses two types of risks; valuation risk and acquisition risk, and how they factor into the ENV framework. Chapter 3 also looks at the marketing mix and its role in delivering net value, and how competition influences the ENV. The chapter also considers the random component in every buyer’s choice; the psychological factors that influence how buyers perceive price. It discusses the expectations of service customers, and the two critical gaps that influence the pricing of a service; the customer gap and the provider gap. Finally, Chapter 3 presents the strategic use of the ENV, introduces the concept of the pareto loss that assist firms in identifying revenue gains, and also looks at how the ENV framework enables the analysis of trade-offs between benefits and outlays. Chapter 4: Seven strategies for higher revenues This chapter, which concludes the section on the buyer as an individual, summarises the knowledge expounded in the previous two chapters into workable action plans; seven strategies that firms can employ for higher revenue. These strategies include pricing based on value and not cost; how to convert pareto loss into revenue; decoupling purchase and consumption; mitigating valuation risk for advanced purchase; and changing the benefits of the service. It also considers the role of customer effort in pricing and hence yielding higher revenue, and the role of intermediating services in providing the highest end-value.

Part II: Buyers in aggregate Chapter 5: The economics of pricing in services Chapter 5 begins the second part of the book, which deals with buyers in aggregate. In discussing demand, it looks at the traditional demand function and price elasticity, then moves on to the role of supply and capacity, examining marginal analysis and revenue functions. The practice of price discrimination, which is very important for services, is explained with a closer look at its usage in the advanced selling of services. Finally, the chapter presents a discussion on dynamic pricing and its two major research streams; demand-based dynamic pricing, and capacity-based dynamic pricing. Chapter 6: The revenue management of services The subject of revenue management is introduced in Chapter 6, with a look at the systems used in this challenging practice of obtaining the highest revenue from selling the capacity of a service firm. In examining the evolution and scope of revenue management, the chapter reviews research in the subject matter, with a discussion on revenue management and advanced demand behaviour, demand distribution, and the issue of re-selling capacity. Revenue management practices

xxii Chapter synopses and tools are critically analysed, as well as the need to incorporate competition into the practice. The chapter closes with a discourse on one of the major issues in the practice; the perceived fairness of revenue management pricing. Chapter 7: Strategic pricing and revenue management: four more strategies for higher revenue In concluding the section on buyers in aggregate, Chapter 7 continues on the subject of revenue management with a look at the ability of some firms, as well as the inability of others, to practise it. It goes on to introduce the new revenue management system, which incorporates four interdependent decision sets in a service and takes into consideration the crucial role of capacity. This system is then used as the basis to offer four more strategies to help firms achieve higher revenue, including how to re-segment, re-design and re-price; the practice of segmentation and pricing through self-selection; using refunds in advanced selling as a strategic lever; and selling availability of a service, rather than delivery. Chapter 8: Conclusion Chapter 8 concludes the book by advocating a need to implement with care, the pricing strategies presented in the preceding chapters. This is in view of the complexity of the task of service pricing, given the perception of consumers and stakeholders of service pricing strategies in terms of fairness, and also vis-à-vis goods pricing. Other issues that need to be taken into consideration going forward include the advent of more distribution channels, finer market segments and the proliferation of brands, suggesting a cross-functional approach to be adopted by firms towards setting pricing policies.

1

Introduction

Service pricing in practice We live in a world today where a cinema ticket can be obtained for 20p, flight tickets at £1, songs at 55p and where even the most discerning marketer might wonder if the pricing for services has gone mad, or if not, perhaps a little out of control. To top it all, there are now multiple prices for buying any service, depending on where you are, who you are, why, when and how you are buying. With new technologies, the capability of firms to offer even more innovative pricing options is set to grow1 (See Table 1.1). Table 1.1 When is a buyer charged different prices? For consuming the same service, different prices are charged for

Examples

When you buy How much/many you buy

Hotel and flight reservations Size of loan, text or voice bundles on your mobile phone Roaming charges on your mobile, withdrawing cash around the world, internet bookings Child fares, senior citizen discounts Drinks at the club on Ladies night Life insurance premiums EU vs international tuition fees at universities Auctions Low-cost carrier flights Weekend vs weekday hotel rates Home delivery of groceries vs going to the supermarket Haircuts for long hair are more expensive, house cleaning services depend on size of house Phone calls Insurance Cable/satellite TV bundles Medical services, first class vs second class mail Bursaries and scholarships for education Discounted theatre tickets at the last minute or very high price match tickets Agent discounts for travel

Where you buy Your age Your gender Your health Your nationality How many people want it How much capacity is left Time of consumption How much effort you put in How much effort the firm puts in Duration of service How uncertain you are How much choice you want How long you are willing to wait How ‘smart’ you are How desperate you are Whom you buy from

2 Introduction Adding to the complexity of pricing is the fact that many services are bundled with goods, or may be a facilitating service between two or more services and/or goods e.g. a mobile payment service. Yet, price complexity may be useful to service firms, as the customisation (versus commoditisation) of a service arising from a more direct contact with buyers may result in the buyer being less able to compare prices and consequently, provide more market power to the firm.2 In addition, e-commerce has provided firms today with better access to buyers’ data. This enables them to do all sorts of demand-based pricing, and to have far better tailored strategies to reach out to the market. Nowhere is this more obvious than on the internet, with its proliferation of pricing techniques. Dynamic pricing models that capture live data that in turn, feeds into systems that could churn out tailored offerings, are no longer a surprise to the internet buyer. Box 1.1 provides some examples. Box 1.1 Examples of pricing techniques on the internet 1

2

3

Attribute-driven/customisable service pricing allows buyers to choose the attributes they want and the firm prices accordingly, e.g. choosing channels on a satellite or cable service, travel packages where you choose the different types of add-ons etc. Capacity/Time-based pricing is often used when services are sold based on how much capacity has been used up. Hence, when there is ample capacity, the price is low and as the capacity is used up, the price starts moving up too. This is very common with airlines and train companies where the price changes with time as capacity is sold off. Subscription is the charging of buyers on a regular basis for availability and access to a service, e.g. online newspapers, music on demand (see Figure 1.1). This is increasingly popular as it enables the firm to

Figure 1.1 Music is now available to subscribers (source: napster.co.uk).

Introduction 3

4

5

6

establish a relationship with the buyer. Often, subscription is also bundled with usage (e.g. efax.com). This method allows the buyer to have flexibility in terms of when they wish to consume the service. Subscriptions are also used for services that need to be updated, e.g. anti-virus software. Microsoft Windows, interestingly, moved from being a good (i.e. software) to a service with updates given out to subscribers throughout the lifetime of use. A Dutch auction is a multiple-item listing of a product or service, often used in auction sites such as Ebay. To illustrate, suppose a Dutch auction has ten items for sale. The opening price for the items is £10 each. After the listing opens, 20 people place equal bids for the items at £10 each. If the listing were to close at this point, the first ten people to bid would be declared the winners, because earlier bids take precedence over later bids of equal amount (and in this case, quantity). However, before the listing closes, a new bidder places a bid of £30 for one of the items. Because this person has the highest bid, he/she will most certainly win one of the ten items listed. The remaining nine items are won by the first nine bidders who bid at £10. However, because all bids clear at the lowest winning bid, the person who bid £30 will only be required to pay £10 for the item. By bidding over opening price, new bidders can essentially knock the earlier low bidders out of the running. However, if there are not enough bidders to satisfy the total quantity available in the listing, all bids will clear at the opening bid. With English auction listings, the price is raised successively until the listing closes. The bidder must use the next highest bid increment when making a bid. The highest bidder(s) at that time is declared the winner and each bidder is required to pay the seller the amount of their winning bid. Bids (or reverse auction, as some might call it) allow the buyer to name their price. For example, when buying a hotel room night, the buyer chooses the town and dates, select the area where they want to stay, select the star rating and names their price. If a bid is carefully constructed, the buyer could potentially obtain a 4-star hotel at 2-star prices. However, if the bid fails, the buyer has to wait 72 hours to put a bid in with the same area and star rating combination. ‘Distressed inventory’ – the hotel industry term for last-minute unsold rooms – could go cheaply when the bid is made at the last minute. This is a simple idea that came from Priceline.com back in 1998; the website allowed buyers to bid on the many (some 500,000) airplane seats that go unsold each day. The idea was launched by Priceline founder Jay Walker, who firmly believed in the power of the internet, and his concept ushered in a new era of internet pricing.

4

Introduction

Pricing has taken centre stage on the internet, where sites like kelkoo.com assist buyers in finding the lowest prices for a variety of goods and services, and lendingtree.com help find the lowest mortgages. These aggregator sites have brought to the forefront issues of segmentation, channel and price. Where previously, firms could go about segmenting their markets, dealing with channel issues in reaching out to them and finally deciding on pricing strategies, the internet cuts through all boundaries and insist firms look at all marketing strategies – from segmentation, positioning to product/service, channel, price and even promotion – all at once, since a change in one strategy often entails modifications to the others. The B2B (business-to-business) world on the internet is experiencing its own revolution, where purchasing managers can now interact directly with vendors over the Web, often finding vendors at B2B vertical portal sites like verticalnet.com or alibaba.com. Sellers, as a result of having to customise their offerings for each client, could tailor their orders to reap premium prices or confirm high quantities without leaving their chairs. Purchasing managers can now take advantage of the demand-based pricing sites similar to those for consumers.

The study of pricing Pricing is the decision that a firm has to make on how much to charge for its goods and services. The study of pricing involves, amongst others, the value buyers have for the products, the quantity the firm is able to sell, the cost and internal organisational implications, the competitive interaction of the pricing decision and how to set a price that achieves the objectives of the firm. It sits within the marketing discipline as one of the 4 ‘P’s of marketing; the point between the firm and the buyer where the buyer casts a ‘verdict’ on the firm’s overall marketing strategies through their willingness to buy at a particular price. Closely related to the study of pricing is the study of price theory, historically seen as the language of economists.3 There is, however, a stark difference between the two. Price theory. Price theory is concerned with the welfare of society and to predict, with some accuracy, the behaviour of firms and buyers. These predictions should be robust enough for an expert to make public policy recommendations. These recommendations in turn, will then lead to a ‘good society’, where social welfare is optimised. What this means is that prices in the macroeconomic environment play a crucial role to ensure that the market economy functions well for the good of society. Prices are guideposts that indicate to policy makers the health of the economy and how resources are being utilised. There are three macroeconomic functions of price within price theory that leads to a healthy economy4: allocative, stimulating and distributive. The allocative function uses price as a rationing tool, allowing the ‘haves’ to consume more than the ‘have-nots’ and therefore channeling resources towards what to produce and how much should be produced. At the efficient equilibrium, the quantity demanded should be equal to the quantity supplied. This allocative

Introduction 5 function is the primary justification for the perceived fairness of the market system i.e. some people tend to judge that such a method of allocating resources is fairer than to have an ideologically driven state allocating them, for example in the case of a communist state. The stimulative function of price works by incentivising firms to produce more when prices are high (as well as making the market attractive for new firms to enter), and reducing output and investment in industries where prices are low. The price system ideally operates to justify the move of resources to industries that provide the highest returns, thereby ensuring efficiency not just in the allocation of consumption but also of resources. Finally, price has a distributive function. High prices lead to a transfer of income from buyers to sellers while low prices allow for more to be purchased for the same outlay and encouraging firms to increase output further. Academic literature in price theory is often found in economic journals, with the economy and society as the central focus. In the efficient equilibrium, even though firms’ motivations may be profit, the pricing behaviours of firms could still result in a ‘good’ society if competition plays its part. Clearly, the market economy may not always be efficient. Adam Smith’s ‘invisible hand’5 doesn’t always work well especially when firms’ objectives may not be profit maximisation, and if marginal analysis (i.e. marginal revenue equals to marginal cost) is not the mechanism for achieving optimal prices. Hence, regulators may become involved – the Department of Justice in the US and the Office of Fair Trading in the UK would police corporate misbehaviour such as collusion and conflicts of interest that may reduce the effectiveness of the price system. Pricing The study of pricing, however, has a different purpose from that of price theory. The central focus of pricing studies is the firm, and the purpose of pricing is to single-mindedly aid firms in achieving their pricing objectives. This means that although the methodologies such as economic models and quantitative analysis may be used in pricing studies as well as price theory, their objectives are divided. The pricing expert’s priority is only that of the firm, and any societal or buyer considerations will be relevant only if they are useful and form part of the firm’s objectives. Yet, price theory research has an important role in pricing research. Where any of the three macroeconomic functions of price fail to function appropriately in certain industries, regulators would often step in. Hence, pricing experts have to be aware that the pricing strategies they put forward have to be within a well functioning market system (as studied in price theory), and the firms have to operate within the macroeconomic boundaries. It is easy to believe that the objective of pricing is to maximise profit. Unfortunately, that is too simplistic a view. Box 1.2 lists some of the objectives of pricing. Each objective will result in different strategies and would also be strongly influenced by different factors. Yet for commercical organisations, these objectives could be linked back to the need of the firm to enhance its revenue so as to be profitable in the long run (i.e. the original aim of the firm).

6

Introduction Box 1.2 Some of the objectives of pricing in services Profit maximisation Sales maximisation Market share maximisation Market share increase Return on investment (ROI) Coverage of the existing capacity Price differentiation Distributors’ needs satisfaction Price stability in the market Sales stability in the market Discouraging new competitors from entering the market Maintenance of the existing customers Maintaining ‘fair’ prices for customers Achievement of satisfactory profits Achievement of satisfactory sales Achievement of a satisfactory market share Cost coverage Return on assets (ROA) Liquidity maintenance and achievement Service quality leadership Creation of prestige image for the company Price wars avoidance Market development Price similarity with competitors Customers’ needs satisfaction Attraction of new customers Achievement of social goals Source: adopted from Avlonitis G.J. and Kostis K.A. (2005) ‘Pricing Objectives and Pricing Methods in the Service Sector’, Journal of Services Marketing 19 (1), pp. 47–57.

Price is the only avenue through which a commercial enterprise is able to bring revenue to the firm,6 and is therefore critical to the firm’s survival. Getting the pricing right means better profits, but getting it wrong could be disastrous as mistakes are also not easily tolerated. Yet, despite its importance, pricing has been the most neglected area of research within the marketing discipline.7 Part of the problem is the multi-disciplinary nature of pricing. Pricing, it seems, is of interest to almost every major business discipline. Finance and accounting maintains that pricing makes assumptions about costs and pertains to the financial health of the firm, and is therefore within their scope. The business economists model the markets and can provide the optimal price for the firm, in

Introduction 7 varied demand conditions. In the service industry, operations research has also gotten into the act through sophisticated revenue management systems and demand forecasting models, churning out optimal prices and capacity allocations for the firm. In addition, information system developers are able to develop programs to sift through the increasing amount of data flowing into firms, to do everything from predicting buyer reservation prices to proposing bundled offers. Despite the interest shown by the various disciplines, research progress has been slow, particularly in the area of service pricing. It is almost as though the individual disciplines understand the cross-disciplinary nature of pricing and since they can only ‘feel one part of the elephant’ (to paraphrase from the famous sufi story), it is assumed that any research within one discipline can only make a limited contribution to the topic. Given the apparent lack of ownership towards the subject matter, service pricing research in general has not proceeded as swiftly as it should.

The importance of the service sector The lack of research in service pricing is unfortunate indeed, given the current situation. If you are reading this book in the UK, US, Australia, Japan, Germany or any of the Organisation for Economic Co-operation and Development’s (OECD) countries, and you are gainfully employed, chances are your employer is a service firm. In a world traditionally dominated by goods, the services sector has been gaining prominence and significance globally. For starters, it now accounts for about 70 per cent of aggregate production and employment in OECD economies.8 This sector also comprises some of the world’s largest corporations who are major buyers and users of advanced technology and are the most active innovators, facilitating a major re-engineering of a growing number of firms across all sectors of the economy. Service firms are also a major stimulant to productivity and efficiency (through outsourcing services), and, through e-commerce, are having a catalytic effect by transforming and accelerating changes that are already underway in the economy.9 Indeed, the fastest growing service industries went from being 6.3 per cent of world exports in 1985 to 9.4 per cent in 2002.10 These industries include computer and information services, financial services, insurance, telecommunications, and personal, cultural and recreational services. The commoditisation of goods and increasing competitive pressures are also driving firms to differentiate through services. Goods firms are now becoming service firms with a renewed focus on the buyer. Consequently, new service models and strategies are being used to obtain buyer loyalty and revenues are increasingly focused on service components within the firm. The importance of the service sector has led to an expansion in research worldwide on services. Service research spawned through journals such as International Journal of Service Industry Management, Journal of Services Marketing, Service Industries Journal and Journal of Service Research have gained international reputation in their hope of achieving an integrated and globally

8 Introduction accepted vocabulary, logic and approach towards understanding services that could be shared by a global research community. This research culminated in the Services-Dominant logic proposed by Vargo and Lusch (2004) which asserted that the service experience is the benefit that buyers are wanting to buy at all times and that even goods are seen as carriers of the service experience.11 This new ServicesDominant logic has the potential to shift strategic marketing attention away from a transaction and exchange focus to a service and relationship focus. Yet, service research has not had the kind of impact on industry as it could have. This is because within the service economy lies a heterogeneous set of activities such as financial services, telecommunication, retail, restaurants, transportation, entertainment, education, public services, and not to mention not-forprofit activities. Hence, many who attempt to study services have lamented on its diversity, and each industry is still dominated by its own terms and language that are highly contextual; this impedes the transferability of knowledge. For example, the price of a service is termed differently for different types of services (see Table 1.2). Current pricing research appears to be growing within individual industries (telecommunication, tourism, hospitality, finance, airline, professional services, etc.) without any attempt to consolidate or abstract the learning from one industry to the other.

Table 1.2 The many different terms for price in services What service are you buying?

Price

Visiting a museum Getting an education Consulting a lawyer Consulting a tax advisor Getting insurance Getting a loan Taking a flight Sending a letter Sending a courier Withdrawing money Making a call Going to the gym Playing golf Going to a theme park Staying in a hotel Getting a job through a head hunter Renting out your home Getting assistance or skilled help Services rendered by government Using a road A night out at a dance club Utilities/telecommunication Staying in an apartment

Entrance fee Tuition Legal fee/retainer Consultant fee Insurance premium Interest Airfare Stamp Courier charges Surcharge Call charges Subscription Green fee Park pass Room rate Commission Agency commission Salary Tax Toll Cover charge Tariff Rent

Introduction 9 However, aid is starting to come to service industries. Organisations, universities and firms are coming together to talk about ‘service science’, a transdisciplinary field that uses technology, management, mathematics and engineering to improve the performance of service businesses such as transportation, retailing, hospitality and health care. Service science integrates service functions such as management, operations, design, engineering, technology, sociology and other relevant disciplines into the field, with an aim to deliver knowledge that could be meaningful and useful across industries. It is hoped that such knowledge could be shared between researchers and practitioners to help firms advance and compete in the service economy, with more mature services providing lessons to newer ones. As Matthew Realff, director of a new programme at the National Science Foundation (US) to finance university research in the field says, ‘Services is a drastically understudied field. We need a revolution in services’.12

Definition of service What is this ‘service’ exactly? The term has certainly been bandied about for some time. Economists talk about the service industry as firms that ‘don’t make things13,’ but instead, perform activities. It is also common to hear about the ‘civil service’ and the ‘health service’. Others refer to ‘service’ as a performance that should meet some basic expectation, e.g. ‘customer service’. Box 1.3 presents some ways of thinking about services.

Box 1.3 Some ways of thinking about services • • • •

• • •

A change in condition or state of an economic entity (or thing) caused by another.14 Intangible and perishable . . . created and used simultaneously.15 Deed, act, or performance.16 Characterized by its nature (type of action and recipient), relationship with customer (type of delivery and relationship), decisions (customization and judgment), economics (demand and capacity), mode of delivery (customer location and nature of physical or virtual space).17 Deeds, processes, performances.18 An activity or series of activities . . . provided as solution to customer problems.19 A time-perishable, intangible experience performed for a customer acting in the role of co-producer.20

Source: IBM Research on Services Sciences, Management and Engineering www.research. ibm.com/ssme/services.shtml, co-authored by Spohrer, J. and Maglio, P., IBM Almaden Research Center.

10

Introduction

From its frequent usage, it may seem to be common sense what a service is. Yet its definition has been elusive simply because its characteristics are constantly being debated upon. Here follows some of the much-contended characteristics. Tangible vs intangible When viewed as an activity, a service may seem to be intangible. Yet some service firms such as restaurants and those in retailing have a significant tangible component within its service. Hence, as Gummesson (1994) and several other authors have commented, buyers hardly ever purchase a pure service; what is purchased is an offering whose value consists of services and goods.21 Even the purchase of tangible goods would often have a service component if one views the benefit of a good to include how it is made available, and other supplementary elements that enhance or facilitate its core value.22 Hence, a service may operate within a tangibility spectrum23 according to what tangible or intangible elements add value to the buyer. Separable vs inseparable Conventional wisdom also suggests that the production and the consumption of a service are inseparable. Both usually occur simultaneously; for instance, being on a cruise or a flight, or studying a course. Yet, as Lovelock and Gummesson (2004) suggest24, there are many separable services, such as services rendered to our possessions, e.g. lawn care, garage services and the like, where the production is separate from the consumption, the latter typically occurring when the buyer takes delivery of the possession that has been ‘serviced’. Heterogeneity vs homogeneity Largely because of the highly personalised nature of certain services, many have assumed that heterogeneity is another characteristic of services. For instance, service delivery could be inconsistent since the employee–customer interface is often prone to variable performances or distractions. Yet, there are many services that are remarkably homogenous and consistently delivered, due to the fact that they have been automated, such as a phone call or an automatic teller machine. Perishable vs imperishable Finally, services have been considered perishable, i.e. a hotel room on New Year’s eve cannot be salvaged after that date and is deemed to have been ‘perished’. However, even with this characteristic, there are exceptions. Parts of a service may not entirely perish, e.g. a concert performance, a sermon or a lecture could be recorded and replayed later. These characteristics of services have been much critiqued by Lovelock and

Introduction 11 Gummesson (2004), but while they may not necessarily be unique, services have been found to be different from goods. Sampson’s empirical study25 showed that consumers recognise services to be different from goods. It also established that services are economic activities not accounted for by other sectors of the economy such as agriculture, mining and manufacturing. There is existing literature to imply that the absence of a coherent definition of services among developing countries appear to impede the recognition that the services industry so deserve.26 Furthermore, Cave and Varnojen (2004) argue that ‘inappropriate measures in services lead to problems for understanding the sources of growth and damaging consequences for productivity analysis’.27 In an effort to promote a wider understanding of the services industry, it is understood that the OECD has also commissioned a project to regulate the definitions of the service industries statistics to reflect common understanding. This book deals with the pricing of services that exhibit the characteristics of, intangibility, heterogeneity, inseparability and perishability (IHIP). Such services include hospitality, travel, leisure, transportation, professional, telecommunication, financial and other similar services. In addition, service with the IHIP characteristics could also be components of goods – included as part of their value offering e.g. support services for technological goods, customer care services for engine parts or elevators. The impact of the IHIP characteristics on the pricing decision of these services has so far been poorly investigated, and this book aims to address this gap. The most common definition of a service is that of a deed, a process and a performance,28 and it is this definition to which this book ascribes. Accordingly, the service described in this book is a performance that is intangible, perishable, heterogeneous, and whose consumption and production is inseparable. As a matter of convention, I use the word product in this book to mean both goods and services.

Service pricing – issues and challenges One would imagine that pricing ideas such as those highlighted at the beginning of this chapter would stimulate research in pricing. Sadly, academic research in service pricing has not kept pace with its growth. Although there appear to be numerous literatures on the policies and strategies of the pricing of goods29 there is a serious lack of literature in the policies and strategies of services pricing. There has, however, been research in pricing within each service domain. Table 1.3 highlights a selection of industry-specific research in pricing that have been conducted. Part of the problem is also the way knowledge is being imparted at universities and colleges worldwide. Structured disciplines such as computer science, engineering, economics, marketing, management, human resources management (HRM) and operations focus on the knowledge within each discipline without sufficient focus on how they are integrated and applied. A recent speech highlights the problem:

1985

1985

1989 1991

1981

2002 2004

2005 1991

1999

Goetz1

Frank2

Morris & Fuller3 Bonnici4

Crompton5

Hoffman et al6 Kimes et al7

Sturts et al8 Ladany & Arbel9

Ciancimino et al10

1

2

3 4

5

6 7

8 9

10

The Pricing Decision: A Service Industry Experience Pricing and Location of Physician Services Pricing an Industrial Service Pricing Dimensions in Healthcare Services Role of Pricing in the Delivery of Community service Pricing Retail Services Restaurant Revenue Management at Chevys: Determining the Best Table Mix Pricing Engineering Services Optimal Cruise Liner Passenger Cabin Pricing Policy Railway Yield Management Programme

Title

Rail

Engineering Cruise line

Retail Restaurant

Community serv.

Accounting firms Healthcare

Physician

Dry cleaners

Industry

Transportation Science

J. Mgmt in Engineering European J Ops Research

J. Business Research Decision Sciences

Community Development J.

Industrial Mktg Mgmt J. Professional Service Mktg

Economic Inquiry

J. Small Business Mgmt

Journal

Notes 1 Goetz, J.F. (1985) ‘The Pricing Decision: A Service Industry Experience. Journal of Small Business Management, 23 (2), pp. 61–67. 2 Frank, R.G. (1985) ‘Pricing and Location of Physician Services in Mental Health’. Economic Inquiry, 24 (1), pp. 115–133. 3 Morris, M.H. and Fuller, D.A. (1989) ‘Pricing and Industrial Services’. Industrial Marketing Management, 18, pp. 139–146. 4 Bonnici, J.L. (1991) ‘Pricing Dimensions in Health Care Services’. Journal of Professionals Services Marketing, 8 (1), pp. 57–65. 5 Crompton, J.L. (1981) ‘The Role of Pricing in the Delivery of Community Services’ Community Development Journal, 16 (1), pp. 44–54. 6 Hoffman, D.K., Turley, L.W. and Kelley, S.W. (2002) ‘Pricing Retail Services’. Journal of Business Research, 55 (12), pp.1015–1024. 7 Kimes, S.E. and Thompson, G.M. (2003) ‘Restaurant Revenue Management and Chevys: Determining the Best Table Mix’. Decision Sciences, 35 (3), pp. 371–392. 8 Sturts, C.S. and Griffis, F.H. (2005) ‘Pricing Engineering Services’. Journal of Management Engineering, 21 (2), pp. 56–62. 9 Ladany, S.P. and Arbel, A. (1991) ‘Optimal Cruise-liner Passenger Cabin Pricing Policy’. European Journal of Operational Research, 55 (2), pp. 136–147). 10 Ciancimino, A., Inzerillo, G., Lucidi, S. and Palagi, P. (1999) ‘A Mathematical Programming Approach for the Solution of the Railway Yield Management Problem’. Transportation Science, 33, pp. 168–181

Source: Ng, I.C.L. and Yip, N. (2007) An Interdisciplinary Review of Pricing Services. Exeter: University of Exeter.

Year

Author

Table 1.3 A selection of published articles on services pricing in different industries

Introduction 13 Disciplines are like bricks and we teach the subjects within them very well – their composition, how to make them stronger, how to change their colour and how they are used in many different buildings. We don’t talk enough about the cement, or how the different bricks should come together to build different kinds of buildings or solve different kinds or problems. Sometimes, the way the cement brings the bricks together often require changes to the bricks themselves, i.e. all the bricks have to think about the larger picture, the building, the solution, and see how to make that better. But we’re not structured like that. Individual bricks become threatened when asked to change themselves for the bigger picture, then politics set in and that’s the end of that.30 The service world does not box itself easily into the traditional disciplines of engineering, computer science, economics, marketing, management, HRM or the like. Knowledge in advancing the service economy is multi-disciplinary and trans-disciplinary. Yet, except for some journals in service as mentioned earlier, most publications are discipline or industry specific. This creates incentives for researchers to ‘box’ their research within these domains. The problem becomes aggravated particularly when industry-specific research begins to embed the language and jargon of the industry into the knowledge, taking certain industryspecific practices as ‘given’, or becoming tacit. Polanyi (1966)31 makes clear this distinction, which he calls explicit and tacit knowledge. Explicit knowledge is that which is transmittable through a systematic language. Tacit knowledge however, is the knowledge that is normally not easily articulated since it is deeply embedded in action and within a specific context. For pricing research to progress, the knowledge acquired from the research within each industry has to be abstracted into explicit theory and principles that can be meaningfully applied to different industries. Failure to do this may result in the false belief that the research is ‘new’ knowledge when in fact, they are merely the manifestation of a failure to abstract the contextualised and tacit information embedded within that industry. How does one begin to study pricing for such services? Is there a common thread across all services? Does the pricing of a mobile phone service have anything in common with that of an airline ticket? What can we learn from the pricing of one service that we can apply to the pricing of another?

Service characteristics impact on pricing Research in service pricing that uncovers basic constructs and produces abstract knowledge common across service industries has been few. It is important to highlight how some key characteristics shared by service industries have an impact on pricing. While conventional service literature informs us that services are intangible, heterogeneous, inseparable and perishable (IHIP), it isn’t too clear how such specificities affect pricing. Mere descriptions of service characteristics would not be useful therefore, unless they are translated into

14

Introduction

some meaningful insights that assist firms in the pricing decision. Hence, I aim to provide some attempt at this by presenting three key areas where the characteristics would have an impact on the pricing decision. The service encounter (intangibility and heterogeneity) The service encounter is defined as all activities involved in the service delivery process. Managers and service researchers describe this as the ‘moment of truth’ to indicate the defining period when the interaction between the firm and buyer is of crucial importance to determine customer satisfaction and unlocking customer value. This encounter could be very short, e.g. a phone call, or reasonably long, e.g. a cruise, or disjointed, e.g. a court case. The service encounter often involves service employees, systems and processes, use of technology and the environmental setting, thus emphasising the need for disciplines to work together to create and manage the encounter. Hence, unlike consumer goods where the firm’s responsibility often ends at purchase (leaving the buyer to consume whenever they wish), the service firm has a responsibility of delivering the consumption experience. The consumption experience is often heterogeneous and that could add or detract from the benefit buyers expect from a service. A drunk patron can make a pub experience a nightmare just as meeting an interesting person could add to it. Consequently, the firm’s task is not merely to manage the service encounters but also to understand the promise of the service that is made at the point of purchase. That promise (and its credibility) will impact on expectation and therefore price. If a firm promises quality service, and wishes to command a price premium, the firm is in effect not only promising that it is able to deliver superior service, but also to manage the uncertainties and heterogeneity of the encounter to a high level of satisfaction even if such uncertainties are not directly controllable by the firm. Also, services are performances, and are often described as an ‘experience’ with no ownership of anything tangible after consumption (see Figure 1.2). As Berry and Yadav32 puts it, ‘Purchasers of goods buy ownership and use; purchasers of services buy only use’. Research has shown that there seems to be a lack of understanding between the pricing of intangibles and its relationship with buyer behaviour.33 The intangibility could increase the buyers’ perception of risk in purchase. While it may seem at first that due to that risk, the buyer would only be willing to pay a lower price for a service, the opposite could also occur. Since the risk of purchase is generally higher, risk-averse buyers could seek greater assurance from the firm and are generally willing to pay a higher price for that assurance. Consequently, brand promises and reputation that serve as relevant assurances become central in the marketing of services, and service firms promising quality services are often able to obtain higher prices. Chapter 2 will discuss further the experiential risks involved in the encounter, and how these risks impact on the price of the service.

Introduction 15

Figure 1.2 No tangible product: Customers who buy tour packages consume only an experience (source: SA Tours Corp. Pte Ltd Singapore, www.satours.com).

Separation of purchase and consumption (inseparability) The main difference between the purchase of service as opposed to the purchase of goods is the fact that services have two parts to the exchange that involves the firm – the purchase and the consumption. In goods, the state of consumption is in the hands of the buyer, and the firm is often not present nor is it usually responsible, e.g. a consumer taking out of a fridge a drink that has been purchased weeks earlier. However, unlike a can of soda, a service cannot be inventoried by the buyer before consumption, since it has not yet been produced. Hence, buyers cannot buy a service and keep it with them until the time they wish to consume. This means that the inseparability of consumption and production adds a complex dimension to the value of the service at the point of consumption/production, and this in turn has a huge impact on how it should be priced at the point of purchase. Furthermore, the time of consumption is often a factor in service delivery and value. For example, buyers who buy flight tickets in advance have to inform the airline of their date of travel. This seems straightforward enough and the price could be set by the airline on that basis and accepted by the buyer. However, a buyer engaging a divorce lawyer also purchases the service in advance but the price may be uncertain, depending on whether there is an amicable settlement or if the case goes to court. The same goes with a mortgage, where the purchase is made in advance, and yet the price (interest rate) may change along the course of the mortgage period. Chapter 3 will elaborate further such differences and the impact this has on pricing.

16 Introduction Perishable capacity and costs (perishability) The perishability of services implies that no service can be stored after its production. This means that firms can only sell a service before its production, and not after. This is an important point and it alludes to a key difference between goods and services. For goods, the firm retains the choice of being able to sell before or after production. Services have no choice but to sell in advance, even if ‘advance’ could be a matter of minutes, e.g. the sale of movie tickets. Given that services can only be sold in advance34, pricing in services is therefore an issue of advanced pricing. Yet, how far in advance can a service firm sell its services? We can see from practices in the service industry that some services are able to sell far in advance, like hotel rooms and airline tickets, whilst others, like restaurants, may not be able to do so. The ability to sell in advance and the ability to decide when to sell has a great impact on the price. While service firms are not able to inventory the service produced as a result of its perishability, it may be able to inventory demand. If demand for the service streams in at disparate times in advance of production, the firm could manage it well, in order to match it with the supply of its service that is to be produced at a particular time, e.g. having a reservations system. If, on the other hand, all demand arrives at the time the service is produced, and the firm does not have the choice of managing demand and planning ahead, it can only schedule supply and production to match demand levels. To summarise, the perishability of a service therefore results in two consequences in pricing. First, knowing that whatever it produces will be perished, the firm must attempt to sell all its services, at the highest possible revenue before its production, balancing the price and the quantity. And second, pricing for services must necessarily be advanced pricing. These consequences mean that the firm can either manipulate demand to match supply (demand management) or manipulate supply to match demand (supply management). Otherwise, there would be a loss of revenue from either unused or insufficient capacity. Discussions on revenue management and capacity are presented in Chapters 6 and 7.

The cost-plus approach in pricing A discussion on service pricing is incomplete without a look at the issues surrounding the most popular of pricing approaches – cost-plus pricing. Essentially, this approach sets a price that is deemed sufficient to recover the full costs of the product i.e. variable and fixed costs, and adds a sufficient margin above that cost to provide the firm with some profit. However, such an approach poses problems, especially for high fixed cost services. For services like transportation, airlines or 3rd Generation (3G) telecommunication services, the major portion of costs are sunk fixed costs, and variable costs (also called marginal costs) are very small. For example, the variable cost of a night in a hotel room would just be the utilities and housekeeping services consumed for the one night. Clearly, a costplus pricing approach based on marginal costs will not be very useful.

Introduction 17 How should one begin to set a pricing for services that ensures that the fixed costs can be sufficiently covered? With transportation and airline services, fixed costs can include the cost of assets such as a cargo ship or an airplane, whilst for 3G services, the fixed cost can be the cost of acquiring the 3G licence. Aside from the obviously high costs of these assets, the service may reap the benefit of the asset over the long term, whether 20 or 50 years, or an uncertain number of years. The cost-based price set for each unit of the service is therefore an amount that is a contribution towards the overall fixed (and sunk) costs; this is also called a target-return approach. However, this contribution is not only difficult to determine, it is also inconsistent across firms. Hence, when variable costs are negligible, the ‘cost’ assigned to a unit of service e.g. a night in a hotel room could be computed in the cost-based approach as a percentage of the overall fixed costs or perhaps as an activity-based cost,35 and the price is a percentage above that cost, given the volume to be sold. Such a pricing approach may lead to uncertain outcomes when firms begin to compete on price. If a service is not much differentiated from its competitor and there is a price war, how low can one service price vis-à-vis the other, when each firm apportions its costs differently? Cost-based pricing therefore starts unraveling with the onset of competition. Consider the history of the telephone. High costs were initially sunk into infrastructural development for the telephone. Hence, in the early days, only the elite class had access to it which resulted in limited profitability. Prices for long distance calls were initially based on distance and time of call in the US. Under competitive pressure, distance dependence has now been eliminated completely and time of day variation was reduced to only two times (weekdays and weekends/ evenings). This competition has also begun to set in for other communication technologies like internet/broadband as history is set to repeat itself. Similarly, the downward spiraling prices experienced by the airline industry in the 1980s after de-regulation is another example of the unsustainability of the cost-based approach.36 More recently, this situation resurfaced when aggressive pricing by European low-cost airlines resulted in losses for some, prompting the Chief Executive of Easyjet to comment that pricing by budget and full-service airlines is ‘unprofitable and unrealistic’.37 Furthermore, service firms who adopt the cost-plus approach show a lack of understanding of how pricing functions. The simplest criticism38 is that costs per unit cannot be determined without knowing the volume to be produced, and the volume to be produced is dependent on demand that is in turn determined by the price. By setting a ‘cost-plus’ price, the ‘cost’ is at best an approximation. Yet, one may still be tempted to argue in its favour by pointing out that since the future is uncertain, the circularity for pricing can never be squared unless some forecast is made of the uncertain demand. Hence, it is not far-fetched if the firm is to forecast the demand characteristics, based on historical data, and price its product based on the ‘cost’ of producing that forecasted volume. Following this point, a whole stream of research on demand forecasting and yield/revenue management in high fixed-cost services such as airlines and hotels

18

Introduction

has emerged. In the majority of these studies, the yield management problem is structured as one in which firms maximise payoffs/yield, given some forecasted demand profile.39 Over time, increasingly complex demand profiles, which require increasingly sophisticated mathematical algorithms to obtain solutions, have been introduced and investigated.40 Most of these studies deal with how much capacity should be allotted for a given set of prices. Chapter 6 will discuss this in greater detail.

Complexity of service pricing It is clear that service pricing is a complex issue. As the Bank of England’s quarterly report states: some of the new service industries may have special economic properties that do not fit well with the assumptions of conventional economic models. For example, telephony and computer software production have high initial costs but very low marginal costs. As a result, pricing strategies may be more complex, and component services are sometimes embedded in customized packages that can obscure the price actually paid or the services actually bought.41 What this means is that when marginal costs are negligible, as in the case of high fixed cost services such as telecommunication, hotels, or airlines, the cost function is a straight line i.e. it does not matter how much the demand is, the cost is always negligible since all the costs to produce the service has been sunk. Furthermore, since the service perishes immediately upon production, the optimal pricing strategy for the firm is to sell at the point on the demand curve where marginal revenue is zero, i.e., if the maximum capacity of the service has not been reached. Inasmuch as conventional price theory goes, that is the advice. Clearly, the disciplines of accounting, decision sciences and economics take a very different view of pricing in services. Whilst the economists contend that sunk costs are committed and should not feature in pricing decisions, accountants and decision scientists insist that pricing decisions have to take into account the return of fixed costs. Both are correct. To borrow terminology from economics, ex-ante, pricing decisions should not take into account sunk-costs. However, ex-post, prices obtained may be used to calculate the returns to investment using tools such as activity-based costing or time-based activity based costings.42 The confusion arises when managers insist upon using ex-post analyses of costs and returns to investment to influence ex-ante pricing decisions. Pricing should, whenever possible, be buyer or demand based (see Chapter 4 on some of the difficulties in demand-based pricing). Costs have the right of veto as it is important that there is profitability (or at least, projected profitability) for any price level proposed. Yet, despite ex-ante decisions on pricing that do not consider sunk costs, this book argues that service pricing research has over-simplified the service firm’s

Introduction 19 pricing decision. The complex pricing programs available in various service industries today clearly illustrates that more needs to be explored. From here on, the book is divided into two parts. The first part discusses the buyer as an individual, and the issues relevant to the pricing decision. The second part discusses buyers in aggregate in the form of market demand, and the corresponding supply and capacity concerns. The second part will also discuss the revenue management of services.

Part I

The buyer as an individual

2

The expected net value (ENV) framework

It is easy to think of pricing as merely a mechanism for higher revenue and to have with it, a rather detached view of how pricing strategies should be developed. Yet fundamentally, for the firm to get its pricing right, individual buyers must be willing to pay for a service. The market demand for a service must therefore, at the base of it, consist of buyers willing to part with their money to pay for the service. In fact, there must be a sufficient number of such buyers willing to do so for the firm to be able to cover its costs and turn in a profit. Seen in this light, the study of pricing must inevitably be a study of buyers in two respects. First, the buyer as an individual, in terms of the way he or she chooses to buy the service and the role of price in that choice; and second, understanding the buyers in aggregate i.e. market demand. Chapters 2, 3 and 4 will discuss the first and Chapters 5, 6 and 7 will discuss the second. When discussing the individual buyer, two issues are relevant. First, there is a need to understand what motivates a buyer to purchase at a given price i.e. buyer’s choice and second, to determine what influences the buyer’s willingness to pay i.e. the maximum amount an individual is willing to pay for a product.

Buyer choice It is convenient to imagine that a buyer’s choice is dependent on the price and that if the price is lower than the amount the buyer is willing to pay, they will buy. However this oversimplifies the problem and research has also shown that this is not always true. Empirical studies into random utility models show that buyers do not always make the same choices even when the circumstances are the same and the buyer’s final decision is therefore seen as probabilistic. In history models, several researchers have found that buyers are also affected by past choices.1 Some buyers show themselves to be brand loyal where they will choose the same product over and over again, whilst others prefer to be variety seeking where they avoid buying the same product again. Clearly, a buyer’s choice is not merely determined by price. However this does not mean that the study of pricing in choice behaviour is a fruitless endeavour. What we do know is that a buyer’s inclination to purchase increases if there is a larger gap between their willingness to pay, and the costs they have to bear

24 The buyer as an individual to obtain the product – such costs include monetary and non-monetary costs, which will be discussed later in this chapter.This gap is commonly known as consumer surplus and the rational buyer behaves in such a way that will maximise his or her surplus. If however the costs are higher than a buyer’s willingness to pay i.e. the surplus is zero or negative, it is certain that they will not buy. Hence we can conclude that having a price that is lower than a buyer’s willingness to pay is necessary, but not sufficient for the buyer to choose to purchase. For example, if a buyer is willing to pay £30 for a theatre ticket, we can be certain that setting a price of £40 will ensure that the buyer will not buy. However, setting a price at £25 does not mean that the buyer will buy, only that the buyer will probably buy. To obtain a more complete picture of pricing and buyer’s choice, an academic discussion of value is required. Value and the buyer The term ‘value’ has various definitions. In neoclassical economics, the value of a commercial product can be expressed by its price, and the price is determined by its marginal cost and marginal revenue. This view addresses both demand and supply. However, marketing researchers have emphasised the demand-side conception of value. For example, Porter (1985) stressed that value is buyers’ willingness to pay2; Zeithaml (1988) claimed that customer value is customers’ judgment about products3; Monroe (1990) proposed that customer value came from acquisition and transaction.4 Dodds et al. (1991) claimed that customer value could be defined as a trade-off between the benefits received from, and the sacrifice made for the product;5 Finally, Woodruff (1997) argued that customerperceived value came from the attributes and the performance of the product, and also its usefulness.6 Some studies show that the quality of products also changes customer value. For instance, higher quality might lead to higher customer-perceived value.7 Bettman et al. (1998) further concluded that customer-perceived value came from the experience perceived by the customer in using the good or service8; and DeSarbo et al. (2001) defined that customer value is the trade-off between customer-perceived quality and customerperceived price.9 Other researchers further argued that personal difference might lead to the variation in value perception.10 In short, some researchers might argue that customer-perceived value is constituted by benefits11, but more researchers tend to agree that customer value could be defined by the benefits and costs that the customer experiences in consuming the product.12 Gross value and net value, expected value and perceived value Value discussions can be condensed into an understanding of gross value and net value. Gross value is equivalent to expected benefits, while net value is gross value minus outlays. (Table 2.1 serves to bring together the different terms used to ensure consistency.)

The expected net value (ENV) framework 25 Table 2.1 Key definitions of value, satisfaction and quality Key definitions

Description

Perceived net value (PNV)

The buyer’s perception of the net gains of a good or service based on all relevant benefits and outlays upon consumption The buyer’s expectation of the net gains of a product or service based on all relevant benefits and sacrifices upon purchase How well the service level delivered matches buyer expectations. Delivering quality service means conforming to buyer expectations on a consistent basis. A post-choice evaluation of a good or service based on the total consumption experience over time

Expected net value (ENV) Perceived quality Satisfaction

In addition, even for net value, there is a distinction to be made between Expected Net Value (ENV) and Perceived Net Value (PNV), which is the net benefit that the buyer perceives when actually consuming the service. This distinction is necessary because purchasing and price are concerned with ENV rather than PNV, although PNV will influence ENV for repeated purchases (see Figure 2.1). Therefore in deriving its pricing policies, the firm has to be concerned with buyers’ expectations of benefits. ENV and PNV are further discussed in Chapter 3.

First time purchase

Repeat purchase

Perceived service on consumption

Perceived/expected service (same level for consumption and purchase)

Expected service on purchase

Expected net value

Expectations increase on repeat purchase if perceived service level is higher than expected service level

Outlays (Price)

Figure 2.1 Changing expectations after consumption.

Higher expected net value – greater sense of ‘value for money’

Outlays (Price)

26

The buyer as an individual

The higher the ENV, the higher the probability of the buyer buying the service, because the buyer expects that purchasing the service will make him or her better off than if he or she doesn’t buy it. In other words, the higher the ENV, the higher the ‘value for money’. Why is net value rather than gross value (i.e. benefit) the focus of discussion? Net value is important because of the role of competition; competition changes a buyer’s expectation of net value. If a competitor’s product provides the same benefit but requires a lower outlay, the buyer’s expectation of the net value provided by the competitor will increase, and the firm may lose out to the competitor. Hence, whilst firms compete based on who provides the most benefits, buyers make their decisions based on the one that provides the highest ENV i.e. the firm that provides superior value and it is to the ENV that I now turn.

The ENV framework Earlier, I mentioned that as ENV increases, so will the probability that the buyer will purchase (a framework for analysis is provided in Figure 2.2). The expected net value (ENV) for consuming a particular service is high when expected benefits (A) of the service are high and expected outlays (B) low. Each component that contributes to a buyer’s ENV is elaborated further, as follows. (A) expected benefits The maximum that buyers are willing to pay for a product is dependent on the expected benefits. Hence, the greater the benefits, the higher the buyer’s willingness to pay. The term ‘expected benefit’ used in this book is taken to mean utility or use value and refers to the total satisfaction that the buyer receives from the product. As shown in Figure 2.3, buyer expectation of benefits can be further broken down to two components. (A) Expected benefits of service
Evaluation of expected net value (time-dependent)  (B) Expected outlays of service

Figure 2.2 Evaluation of net value.

Motivation to buy at a given price

The expected net value (ENV) framework 27 Tangible attributedriven benefits

Intangible attributedriven benefits

Importance Expected benefits of service

Figure 2.3 Expected benefits.

Tangible attribute-driven benefits Every product has its features or attributes (see Box 2.1). Some of these features are valuable to certain buyers, some are not. For example, a camera may have zoom and auto-focus features, but to a less demanding buyer, these sophisticated attributes mean nothing and therefore they are not willing to pay a higher price for them. A café customer in the UK may wish to have coffee that is fair-trade, organic and decaffeinated, whilst a similar customer in Italy could choose their coffee based on aroma and acidity.

Box 2.1 Definition of attributes and benefits Attributes are features of a good or service. Tangible attributes are features that are objective and can be precisely valued or measured. The Oxford English Dictionary defines tangibility as not merely having the property of being able to be touched, but also that which ‘can be laid hold of or grasped by the mind, or dealt with as a fact’. Hence, colour, size and volume are examples of tangible attributes in goods, while examples of tangible attributes in services include the number of tennis coaching lessons, and the duration of a health massage. Attributes can also be intangible, i.e. not measurable and subjective. Many services have intangible attributes; for example, friendliness, courtesy or helpfulness are some intangible attributes of services, whilst intangible attributes for goods include design and reputation. Buyers however, buy benefits and not attributes. It is what the attributes do for them that matters, not the attributes in themselves. Hence, having wide seats in an airplane is a tangible attribute that might give the benefit of comfort to the passenger, as are longer opening hours for a bank which provide the benefit of convenience to its buyers. The attribute-benefit link is not always so straightforward though, particularly for intangible attributes, since these attributes lead to a subjective evaluation of the benefits. For instance, having the latest haircut style may not suit some people, and not everyone would prefer a hotel room with a view especially if the firm

28

The buyer as an individual intends to charge higher for it. Firms would have to be careful when deciding what attributes should be in a service or good, and how these attributes benefit the segment of the market they wish to target. Core benefit, actual and augmented product Clearly, it is beneficial to know from the outset what attributes deliver the core benefit of a good or service to a buyer. The core benefit is the fundamental reason for the purchase (e.g. getting from point A to point B for a bus service). The actual product (be it a good or service) is created by firms to provide the buyer with the core benefit (e.g. getting from station A to station B on a train), while the augmented product is created to offer additional consumer services and benefits (e.g. meals, seat reservations). However, many marketers make assumptions about what the core benefit of their product is and by doing so, they may limit their market segments. What is the benefit of a university education? Is it the degree certificate or the skills? This question should not be answered by the firm but by the buyer. Similarly, not everyone goes to the gym to get fit or lose weight. Some may just like to socialise or are just there to show off their great physiques. Again, firms have to constantly evaluate the attribute-benefit links and their segmentation strategies.

Attributes that provide actual functional benefits often mean more costs to the firm. For example, a car with a ‘spacious’ attribute might mean it is bigger; ‘lowfat’ milk would mean additional processes; and ‘calcium added’ orange juice implies added ingredients. All these would cost the firm more to produce. The service experience consists of a range of attributes (see Box 2.2) – some that may even surprise the firm. A restaurant may be judged by its patrons, and a spa by the music it plays. Many service firms are now beginning to appreciate the concept of the whole service experience and are starting to manage the attributes not from the delivery of the service, but from the perception of the buyer. Box 2.2 Attributes of a service experience Within a service experience lie many complex attributes that contribute to what a customer would value, as the comment below illustrates Kuala Lumpur–London on 30th Dec 2005, in business class. This flight was with the family, using a very generous promotional offer to redeem frequent flyer (Enrich) points. Lounge in Kuala Lumpur remains very good. It was on one of the newly refitted aircraft. The cabin was comfortable, and the lie flat seat, although a little narrow, permitted a comfortable sleep. The ‘mood lighting’ added to the ambience. The cabin crew were excellent – there were at least 4 on the upper deck, and the service was very slick. The meal service has been altered, and food is brought to you

The expected net value (ENV) framework 29 plated. Choice seemed a little unimaginative – for both meals, there was a choice of a beef, chicken or pasta (differently prepared of course). I can understand why some feel the portion size is small. My daughter had the child meal, and was served spaghetti bolognaise for the first meal, and pasta in a cream sauce for the second. There was plenty to drink, with regular refills. There is a choice of 3 reds and 3 whites (one new world, two old), together with champagne. Crew were genuinely helpful – when my daughters asked for some garlic bread midway through the flight, this was provided promptly. They deserve their 5 star rating. The IFE system is good, as were the noise-cancelling headphones. Nevertheless, a very good experience. Source: Malaysia Airlines, by Arthur Andrews (2 January 2006). Posted on a public discussion forum and reproduced with permission from SKYTRAX www.airlinequality.com. For privacy purposes, the name of the respondent has been changed.

Intangible attributes-driven benefits Some attributes are not as tangible as the spaciousness of a car or the thickness of a wool jacket, but are equally able to provide great benefits to buyers. For example, experience and credence attributes (see Figure 2.4) cannot be easily discerned prior to purchase. Legal services are typically high in experience and credence attributes. The client, to some extent, will never know if the lawyer is as good as they say. Services with credence attributes are often technical in nature and if they are not observed by the buyer e.g. vehicle repair, medical research etc. buyers could be wondering if the work was really done properly. Even goods like a bottle of mineral water may offer a tangible attribute of ‘clear’ water, but a firm could add an experience attribute of ‘tasting better’ or even a credence attribute of ‘good health’. Such attributes promise certain benefits to buyers only upon consumption, and in the case of credence attributes, buyers may not even know if they have really attained such benefits. Yet, if these benefits are important to these buyers, they are often willing to pay more for them. For firms deciding if they wish to improve on quality and value of a product, adding experience and credence attributes to a product is often a double-edged sword. On one hand, firms have difficulty convincing buyers before the purchase that the product will deliver the promise made by these attributes – even if they do fulfil it – since buyers have to purchase and experience the product first before coming to that conclusion. On the other hand, firms can make promises of quality delivery – even if they don’t totally fulfil them – since buyers won’t be able to tell if this is the case, before they buy. This is even more so for credence attributes. Since providing tangible attributes may be costly to the firm, marketers are increasingly trying to influence buyers’ belief of goods or services and the expectations of their benefits by introducing intangible attributes. They communicate them through promotional campaigns and most of all, by making brand promises.

30

The buyer as an individual

Easy to evaluate

Most services

Clothing Jewelry Furniture Houses Automobiles Restaurant meals Vacation Haircuts Child care Television repair Legal services Root canal Auto repair Medical diagnosis

Most goods

Difficult to evaluate

High in search High in experience High in credence qualities qualities qualities Search attributes are those that buyers can evaluate before making a purchase e.g. the clarity of a diamond. Experience attributes are those that buyers can only evaluate during consumption, e.g. the taste of Chardonnay, and credence attributes are those that buyers are not able to evalute even after repeated consumption, e.g. the quality of a dental tratement. Services are usually high or credence and experience qualities (see below).

Figure 2.4 Another way of classifying attributes (source: Zeithaml, V.A., Bitner, M.J. and Gremler, D. (2006) Services Marketing: Integrating Customer Focus Across the Firms, 4th edn. (McGraw Hill International. Reproduced with permission of the The McGraw-Hill Companies).

For instance, a firm could position or brand a product with intangible benefits such as looking ‘cool’, ‘hip’, and ‘fashionable’, and through its communication and promotional efforts, influence buyers’ beliefs about the benefits they attain from buying the product. Many firms now combine tangible and intangible attributes in their product decisions. The decision of what attribute to add is often determined by which attribute incurs a lower marginal cost and delivers the highest marginal revenue. Does branding a gym differently allow the firm to increase its price? Or should the gym charge more by increasing its more tangible attributes e.g. offering more pilates and yoga classes? Which would bring in more revenue at a lower cost? In such decisions, branding is increasingly winning the battle. This is because promises are often cheaper to make and harder to imitate. Moreover, investment in a brand is more enduring, and taking a share of the buyer’s mind, in terms of his beliefs about what the firm’s brand means and what is promised allow firms to sustain a competitive advantage. Brands also provide firms with goodwill, and as a result, allow those holding established brands to be valued higher. Furthermore, goods, if imitated successfully by competitors, become commoditised; buyers cannot tell the difference between them. Price wars are often a result of commoditised goods. To avoid this, firms are increasingly employing a two-prong strategy of increasing experience (and if possible, credence) attributes as well as branding the product. By doing so, they aim to create differentiation and hold on to a competitive advantage. A recent OECD working paper reported that the line between a pure good and a service is blurring, with goods becoming

The expected net value (ENV) framework 31 increasingly ‘service-like’ in nature.13 Productivity growth in the service sector has also increased, compared to the manufacturing sector. The service element of many goods is often the more profitable aspect of the firm. With the delivery of brand promises through experience and credence attributes, the world has seen an explosion of goods that have moved beyond their functional value, and that do battle in the realm of beliefs, promises and services. A casual glance at the top ten brands of 2005 would show that the products of each of these companies deliver far more benefits than their functional and tangible attributes are capable of (see Table 2.2). (B) Expected outlays To enjoy the benefits of a service, buyers are aware that they are required to pay a ‘price’. This price is the expected outlay by the buyer that would result in the buyer’s computation of net value. Expected outlays include monetary and nonmonetary costs (see Figure 2.5). Monetary costs as outlay When monetary costs are discussed, one would automatically think of the price charged by the firm. However, there are often other monetary costs involved Table 2.2 Top ten pure service brands Rank

Brand

Type of business

1 2 3 4

Disney Citi American Express Merrill Lynch

5 6

HSBC UPS

7

Morgan Stanley

8 9

JP Morgan Goldman Sachs

Providing entertainment experience Banking and financial services Global payments, network, travel and banking company Provides capital markets services, investment banking and advisory services, wealth management, asset management, insurance, banking and related products and services on a global basis Banking and financial service Express carrier and package delivery, specialised transportation, logistics, capital and e-commerce services Financial services for individual, institutional and investment banking clients Banking and financial services Global investment banking, securities and investment management Internet search engine

10

Google

Source: adapted from Business Week (2005) “The 100 Top Brands: Here’s How We Calculate the Power in a Name”, 1 August, 2005, pp. 90–94. Note To derive the above list, firms that sell goods together with services were taken out (e.g. IBM (hardware), Microsoft (software), McDonalds (burgers), Cisco (hardware), Oracle and SAP (software)). The list only shows the top ten service firms that are purely experiential. The type of business reported was taken from the companies’ websites.

32 The buyer as an individual

(B) Expected outlays of service

Expected total monetary costs

Price and other monetary costs related to the buying process of the service e.g. car park charges etc.

Expected total nonmonetary costs

Risk, opportunity costs and other non-monetary costs across the buying process

Figure 2.5 Expected outlays.

when a customer consumes a service. Signing up with a gym, for example, may require the buyer to buy gym gear or incur car park charges. Taking a train may mean a taxi ride to the station, while obtaining a degree means additional costs for accommodation, food, and books. If a buyer buys a service well in advance, these monetary costs may be duplicated – once during the purchase of the service, and again during its consumption. Non-monetary costs as outlay Monetary costs are however not the only costs incurred by the service customer. Many buyers are not aware of the non-monetary costs of consuming a service. Perhaps they may moan about the long queues at a restaurant, or even about the uncertainty of satisfaction (‘How would I look if I cut my hair?’), or balk at the idea of going to a dentist. Yet such considerations are unconsciously processed, and the net value outcome may result in the decision of whether or not to purchase the service. There are four main categories of non-monetary costs: TIME COSTS AND OPPORTUNITY COSTS

The purchase or consumption of a service almost always requires the buyer to spend some time. Time costs refer to the direct cost of time incurred when the buyer spends that time consuming the service. This could be time spent standing in a queue waiting to be served, or even searching for information on the internet. This cost varies for different people. For example, a golf game could take up to five hours of a person’s time. For some, this is just too much time wasted. For others, the five hours pass quickly and they wish it was longer (though perhaps not if they were playing badly). Aside from the direct time costs, the consumption of a service often requires sacrifices on the part of the buyer, i.e.

The expected net value (ENV) framework 33 the opportunity costs. The cost of a golf game is not only the green fee or the cost of the time spent on the golf course, but also what the golfer could be doing during that time, which is always changing. Buyers negotiate within themselves to reduce their own outlays and hence would not be playing golf when their time on the course is considered too big a sacrifice. The impact on pricing is huge. How many times have we wished we could ‘buy ourselves out of the queue’? High time-cost buyers are often willing to pay more for speed and convenience. Conversely, low time-cost buyers would prefer to wait if it means they can get a discount. Often, service firms assume one way or the other, resulting in a loss of opportunities. In addition, it is useful to remember that it is the expectation of time costs (and not the time itself) that makes the buyer evaluate their net value. Even when the service is priced cheaply e.g. low cost airlines, passengers may be willing to pay extra for greater convenience or better seats e.g. Easyjet charges a small fee to allow you to be first to board the aircraft (see Figure 2.6). Airlines also recognise that a flight consumes precious time that could be used by busy executives to catch up with some work and have now started looking into mobile phones and internet usage onboard (see Figure 2.7). SENSORY COSTS

For services that are experienced first-hand by buyers, physical discomfort may be an outlay that many may find unacceptable and therefore they will decide not to purchase. Besides just being tired of standing in line, some buyers may find the incense in a beauty salon too strong, chinese restaurants too noisy, or rock concerts too loud. Yet other buyers may like the service for the same reasons that some don’t. For the firm, understanding its market segment and planning the

Worth the price? Easyjet speedy boarding allows you to be one of the first on board so you don't need to wait and select your seat.

Figure 2.6 Reducing non-monetary costs by paying (source: www.easyjet.com).

34 The buyer as an individual

Figure 2.7 The Singapore Airlines Business Class seats: how much more would you value a flight if you could continue with your work onboard? (source: Singapore Airlines).

service environment for that segment is therefore an important aspect of its strategy toolkit. PSYCHOLOGICAL COSTS

Withdrawing cash from an automatic teller machine (ATM) may result in the same outcome as withdrawing cash from a teller at the bank, but many may prefer to use the ATM even if the time spent is the same. This is because some buyers may find it uncomfortable to deal with another person (see Figure 2.8). Perhaps they are shy, feel inadequate, or dislike making small talk. Psychological costs such as fear or loss of control may deter buyers from consuming a service. Again, this is not always the case. When calling a firm’s customer support department, many buyers would prefer to speak with a real person than to listen to a machine. Monetary and non-monetary costs contribute towards the expected outlay for the purchase and consumption of a service at every stage of the buying decision process, once the buyer recognises the need to purchase a particular service (see Figure 2.9). Whether it’s the hassle of looking for information, the mental effort of evaluating alternatives, having to buy tickets before the movie, incurring car park charges, or the discomfort of sitting through a long baseball game – all these add towards the ‘price’ a buyer pays to purchase and consume a service.

Figure 2.8 Self checkout at Walmart: Lower or higher costs to the buyer?

Deprivation – problem recognition

Information search

Evaluation of alternatives

Purchase

Consumption

Monetary and non-monetary outlays

Figure 2.9 The buyer decision process for services.

Postconsumption

36

The buyer as an individual

Buyers mentally evaluate their outlays for the purchase and consumption of a service. However, the outlays are dynamic and temporal, and interact with risk and price. This means that if a buyer values a service highly and encounters a cheap price for it, they may be willing to take the risk and forgo the need to search for information or to evaluate alternatives. In other words, the buyer will purchase when they perceive that their ENV is higher by taking the risk, than if they expend the outlays. Risk as outlay In the consumption of services, buyers face several risks, as presented in Box 2.3.

Box 2.3 Common risks associated with the consumption of services • • • • • • •

Functional – unsatisfactory performance outcomes, e.g. dropped calls on mobile phones. Financial – monetary loss, unexpected extra costs, e.g. paying extra for check-in baggage (for some low cost airlines). Temporal – wasted time, delays lead to problems, e.g. queuing. Physical – personal injury, damage to possessions, e.g. garage, gym. Psychological – fears and negative emotions, e.g. roller coaster rides. Social – how others may think and react, e.g. wine tasting clubs. Sensory – unwanted impacts to any of the five senses, e.g. rock concerts.

Life today is much riskier than before. We are uncertain about the future, whether it is in the next hour, day, or year. This is not to say that life today is more uncertain than it was before; the consequences of that uncertainty, however, seem to be more dire today. We are more wary about what we eat, because there are serious health risks if we are not careful – cancer, obesity, diabetes, just to name a few. Getting a good night’s sleep is more important today than ever before, because tiredness will reduce alertness when driving, or we may be less effective in the office. We are less tolerant of queues, breakdowns or bad food, because the cost of the distress is high. Is the world a more risky place to live in? Yes, but not because there is a higher level of uncertainty; in fact, one would even argue that the level of uncertainty has decreased because of technology. The world is riskier not because of greater uncertainty, but because we perceive the consequences of such uncertainties to be greater than before. As Bernstein (1996) puts it, ‘volatility per se . . . tells us nothing about risk until coupled with consequence’.14 Why do we have such a perception? Two immediate possibilities come to mind. First, we are more aware of pain, suffering and death because of the media. Second, technology has made us accustomed to higher certainty, given

The expected net value (ENV) framework 37 our ability to plan more activities within the time that we have, and this has made us less tolerant of uncertainty. A quote by Stix (2002) in the Scientific American says it all, ‘Time has become to the 21st century what fossil fuels and precious metals were to previous epochs’.15 Little wonder that losing time is such a dreadful consequence. Given the higher risks, one of the best-selling services is the provision of assurance, although many assurances may not be immediately evident. Consuming organic, low-fat, high-calcium and low-carb foods are assurances that you will live long and well. Even buying branded goods could be seen as an assurance of good quality, or higher status. The ultimate assurance can be seen in what I call the service of providing hope, a fast-growing sector indeed. From religion to numerology, geomancy to self-help books, the demand for hope seems to be insatiable, whether it is for a better life or for something beyond life itself. Buying and consuming services have always been riskier than that of goods. This is because there isn’t any ownership in services, and the buyer often goes away with merely an experience and not something tangible. The greater the risk, however, the more buyers are willing to pay to alleviate it. Earlier, I stated that risks in the purchase of services increases the expected outlay for buyers. While that is true, firms often charge more to have that risk alleviated. Hence, for risk-averse buyers, the marginal expected benefit of having a potential risk alleviated is higher than the marginal cost of paying for it. Let us take a simplistic example – say you would like to dry clean a suit? In the past, you’ve always dry cleaned your suit without any problems. However, this particular dry cleaner may provide you with an option of insuring your suit against damage for a slightly higher fee. You might then be willing to pay the higher fee for a guarantee that if the suit is ruined, you will be compensated with a new one of equal value. The dry cleaner would do as they have always done – dry clean your suit as usual. However, their earnings are now higher because of the higher price you pay since you are willing to buy yourself out of any risk. Their additional revenue is costless. Both the creation and alleviation of risk is big business today. Consider the following speculative statements: •

•

We will never be rid of the perceived threat from viruses and hackers because the computer security business (firewalls, antivirus, etc.) is worth billions. We will never be rid of the perceived threat from credit card fraud because the development of technology to protect financial institutions and buyers is too lucrative a business.

Just as there is constant speculation that viruses are perhaps created by antivirus companies so that anti-virus software is still needed, firms may amplify risks so that buyers become more willing to pay to have them alleviated. The victims of such strategies are often the most risk-averse and those whose distress, if the risk materialises, results in high monetary and non-monetary costs.

38 The buyer as an individual Clearly, there are ethical concerns in amplifying risks and profiting from providing assurance. To say that risks do not exist and that it’s the firm that creates them is obviously untrue. Such risks often do exist, although some may be latent and different buyers will be affected by them in varying degrees. Hence, having the choice of buying some assurance is better than not having any choice at all. On the other hand, buyers must also know when firms deliberately amplify risks (or even amplify the risk of buying the service from a competitor), and moderate their own behaviour with some common sense. In the end, buyers have to understand the risks they face, and manage them well. Buyers’ decisions are often heuristically driven.16 Their perception of benefits, outlays and alternatives, and the environment is selective and dynamic. This is also one of the reasons why buyers don’t make the same choices under similar conditions. When asked, some buyers may articulate the factors that would help them determine what a service is worth to them. Box 2.4 illustrates how complex it is to determine the worth of a service experience. The owner of the restaurant featured in the article claimed that the restaurant is profitable because of buyers’ generosity.17 For some patrons it may be less about paying what it is worth and more about paying higher to avoid embarrassment. In the long term, buyers may not be willing to return because the price (including embarrassment avoidance) is too high to be worth it.

Box 2.4 The complexity of determining what a service is worth Cash points At Just Around the Corner, there’s no bill – the diner pays what they think the meal is worth. Polly Vernon puts money where her mouth is. Just Around The Corner, 446 Finchley Road, London NW2 (020 7431 3300). Cost: what you like Julie Goose (who says I can call her ‘my dining companion’ if I make it clear that this isn’t a euphemism) begins worrying about the Just Around The Corner experience days before we get there. ‘There are no prices?’ No. ‘You pay whatever you think the food is worth?’ Yes. ‘Do you pay what the food is worth, or what the meal is worth, or what the restaurant overall is worth?’ Etc. The idea of a pay-what-you-like bistro is novel in theory, but fraught with difficulties in practice. We are 20 minutes late, because the restaurant is not Just Around our Corner, and we’re forced to take an extra bus. Julie is on the point of deducting £1.50 from the future bill for the inconvenience, when she’s struck by the restaurant’s hilarious interior: ‘It’s a Seventies Wolverhampton restaurateur’s approximation of a Greek taverna!’ It’s also worth a fiver. Luridly pink napkins, folded into elaborate fans, are worth a further 75p, we agree.

The expected net value (ENV) framework 39 We’re presented with crudites and bread (which we assume are free, although what do concepts like ‘free’ mean here?) and menus full of French-ish retro dishes. Our mineral water is served in its original twolitre Volvic bottle. Julie Goose and I have our first difficult moment over the entirely serviceable Bordeaux Sauvignon she selects. She sips. ‘Four quid cash and carry, seven in an off licence,’ she announces. ‘But we aren’t in an off licence,’ I point out. ‘We pay what it’s worth!’ she counters sternly. Historically, I’m soft on such matters. Jules likes things fair. Julie orders asparagus with hollandaise sauce, and immediately starts assessing its quality in cash terms. ‘It’s very four quid,’ she says, which I translate as competent. But she thinks the hollandaise might be packet, and knocks a pound off. I like my deep-fried Camembert triangles more because they’re probably frozen (‘Unpretentious,’ I say; ‘Municipal,’ Julie says) and give it a £4.50. I particularly like the berry sauce – perfectly bittersweet. At some point during our mains (an impeccably medium-rare steak for me, an ambiguous beef Wellington for her), we have a contretemps. I give my steak 12 quid, but Julie says I’m wrong and have no taste anyway, and furthermore, she’s going to deduct money off her share to compensate. ‘I like it!’ I say. ‘But you shouldn’t,’ she says. We decide against pudding. Julie and I are too neurotic for Just Around The Corner. This is good enough food, but it would taste much better if it were priced: we’ve done nothing all evening except fret over the bill, and what our assessments of the experience say about our personalities. I try to pay £37.50 (£15 of which is Julie’s share), but am told I’ll have to round up or down because their machine doesn’t do fractions. I round up. Julie Goose sighs, and pockets the leftover Volvic. Source: Vernon, P. (2005) ‘Cash points’, Observer, 3 July, reprinted with permission.

The way payment is made, therefore, can be viewed as an outlay. Consider tipping, often seen as a voluntary payment given after services have been rendered. Lynn and McCall’s research showed that tips are a poor measure of customer satisfaction with a service, and that they are a weak incentive for delivering good service.18 When the amount you pay is transparent, buyers may worry about what the norm is, and what might happen to them if they don’t tip well. This creates a situation of uncertainty and carries risk for the buyer.

Conclusion How is risk a factor in pricing? Whenever a buyer has to purchase a service where there is risk, his or her outlay increases to the extent that if the total outlay rises beyond his or her willingness to pay, he or she will not buy. Hence, any price to be paid for a service has to be discounted to persuade him or her to buy.

40

The buyer as an individual

Obviously, price is merely one component of a buyer’s total expected outlay. However, the greater the non-monetary outlays, the more pressure there is on the firm to lower its price to compensate for the non-monetary outlay that the buyer has to bear. Hence, to price on the basis of benefits alone is too simplistic. If the expected non-monetary outlays are huge in such a way that the total ENV may be zero or negative, the buyer would simply not purchase the service, despite a lower price. For example, some buyers may be unwilling to switch dentists, even if the new dentist opens up right next door to their current dentist, and offers a big discount on its service. This is because the mere possibility of a painful encounter with a new dentist constitutes such a huge non-monetary outlay that the total ENV is lower than that of the current dentist (see Figure 2.10). The current dentist would therefore command a higher ENV if previous visits were satisfactory, not because the current dentist is good, but mainly because there is greater certainty of satisfaction, translated into a lower psychological risk and therefore a lower expected outlay. The risk of pain or discomfort can make a big difference in buyers’ purchase decisions. In fact, many buyers would be willing to pay a higher price to avoid that risk. In the end, the price that a firm is able to charge tells a lot more than it may seem. In summary, any increase in non-monetary outlays will exert a downward pressure on prices, e.g. if a buyer goes through more effort to buy a service, he or she expects to be compensated by a lower price. Conversely, buyers may be willing to pay higher if the purchase or consumption of a service is done with minimum effort, e.g. buying groceries online and willingly paying for delivery charges. The next chapter presents a way to understand other unique risks faced by service buyers due to the separation of purchase and consumption.

Figure 2.10 What price would you pay to avoid going?

3

Advanced purchase and the separation of purchase and consumption

In the previous chapter, I discussed the expected outlays for a buyer considering the purchase of a service, and the pressure that this exerts on price. Many of the outlays are those expected at the point of consuming the service. This chapter examines the risks faced by buyers at the point of purchase which, as I will show, could be well in advance of consumption. The separation between the purchase and consumption of a service would have severe pricing implications. Let us take, as an example of a perishable service, a hotel room on New Year’s Eve. The room could be sold six months, or probably even a year, in advance. The mere fact that it can be sold in advance proves that there must be willingness on the part of the customer to buy before the day of consumption (this willingness is due to several factors that will be discussed later). Hence there is a positive value that the customer attaches to the room in advance and the firm aims to capture that value in the room’s asking price. Now let us label as the service’s selling period, the timeframe which begins when the room holds some positive value to a customer, and ends with its production and consumption on New Year’s Eve (it is widely established in service research literature that the production and consumption of a service occur simultaneously). The service can only be sold during its selling period, i.e. in advance, before its production (and consumption).1 This is an important point because it alludes to a key difference between services and goods. Whilst goods can also be sold before production, the manufacturing firms retain a choice of whether to sell before or after production. This choice is not available to services. Figure 3.1 illustrates a typical difference between a good and a service. Some may argue that certain services are actually produced in advance before sale, e.g. a movie. Undeniably, the creation of a service may require its materials and equipment to be produced in advance, such as a movie theatre, a hotel building or even telecommunication towers. Yet the value of a service is only unlocked at the point when it is performed and consumed by the customer; the same value held by the customer that can be converted into revenue for the firm through the price the customer is willing to pay. For instance, in the case of a movie theatre, the customer values the delivery of the service by the firm (through the provision of the movie, comfortable seating and quiet surroundings, etc.), which is simultaneously consumed by them. Without the customer’s

42 The buyer as an individual Buyer–seller exchange for a typical good Seller Sell (a)

Line of perishability

Production

(c) Buy

Sell (b)

Delivery

(d) Buy

Take delivery

Selling period Buyer

Consumption Inventory

Seller: Option to sell at (a) or (b) Buyer: Option to buy at (c) or (d)

Buyer–seller exchange for a service Sell (e) (g) Buy Advance Buyer

Buying/selling period

Valuation risk

Sell (f)

Production and delivery

(h) Buy

Take delivery and consumption

Spot

Acquisition risk

Seller: Option to sell at (e), (f) or anytime within the buying/selling period Buyer: Option to buy at (g), (h) or anytime within the buying/selling period

Figure 3.1 Buyer-seller exchange for a typical good and a service.

consumption – which can only arise if the firm produces the service – the value of the service cannot be converted into revenue, despite the production of the necessary equipment. It is clear then, that the issue of pricing in services is one of advanced pricing, even though the time in advance may be mere minutes, e.g. the purchase of a movie ticket just before the movie.2

Risk at the point of purchase: valuation risk Since the production and consumption of a service are simultaneous, buyers are unable to buy in advance and store it with the intention of consuming at some later date. Similarly, the firm can only sell in advance and produce later. This is an important point. Conventional economic wisdom informs us that we buy only when the utility we attach to consuming the product outweighs the price we are supposed to pay for it. However, normative economics and marketing literature often implicitly assume that buyers receive utility at the time of purchase. Since

Advanced purchase in services 43 there is now a separation of time between purchase and consumption, it implies that the buyer’s utility is truly obtained not at the time of purchase, but at the point of consumption.3 The fact that service sales exchanges (i.e. purchase) are separate from consumption gives rise to many problems within service industries. Ship owners know that they need to stipulate repair specifications before a ship goes into a dockyard; otherwise opportunistic dockyards could charge them more for ‘extras’ since the ship is ‘captive’. Similarly, uncertainties exist when we hire lawyers, as we may not know the full extent of the work required until the litigation has started. Often, buyers try to reduce uncertainty by negotiating unit rates, such as labour costs per hour and steel per ton for ship repairs, or hourly rates for lawyers. Even when going to a private hospital, buyers would like to know the price of the ward per night. This might help mitigate the uncertainty somewhat, but the true price of the service is often not revealed until after its consumption. At the same time, the uncertainty in the actual price is not always due to opportunism either. The consumption of many services are dependent on several external and unforeseen factors, e.g. how long the court case might be dragged on, or how long a patient needs to stay in hospital to recuperate. Therefore the value of such services is deemed to be ‘state-dependent’, i.e. the value is dependent on the state of the world at that given time.4 Consequently, a buyer faces a dilemma at the time of purchase – how much will they foresee the value of the service at the time of consumption? Will it be more than what they are willing to pay? For instance, a customer considers buying a ticket for an openair concert, but what if there is a storm on that day? In such a case, the state of the world would have rendered the consumption of the service less valuable to the buyer. The uncertainty associated with the consumption of a service is a risk faced by the buyer at the time of purchase, which I call valuation risk. This stems from the separation between purchase and consumption. With the separation, there is a probability that a buyer who has purchased may not be able to consume, or that the actual benefit from consuming the service is not as high as he had expected. Hence valuation risk is not an outlay that can be expected such as those described in the previous chapter. It is a risk that is unforeseen and state dependent. For example, a buyer who purchases a movie ticket a day before the movie might find that they are unable to watch the movie when the time comes because they have fallen ill. Hence, a key difference between a good and a pure service is that for goods, the consumer chooses the time (and the state) that is most suitable for consumption, after they have purchased the good, e.g. taking a can of Coke out of a fridge to drink it on a hot day. Whilst the service consumer needs to buy the service first and then consume it later, when its state is uncertain. Valuation risk is high for services that are able to sell in advance, such as hotel rooms and airline flights, but is relatively low for those that can only be sold at consumption time (also called spot time), e.g. a haircut, dry cleaning or garage services. The risk of low valuation stems from the state dependency of consumption, which in itself has three components, as follows.

44 The buyer as an individual 1 Buyer-state dependency This is when the value of the service is dependent on the buyer’s state e.g. the healthier the patient is, the less time they might spend recuperating in hospital, and therefore the lower the total price paid. Similarly, if a tourist is relaxed, they might enjoy the tour better, thus increasing their valuation of the service. A night out at the theatre may be a miserable experience if the theatre-goer has caught a cold and is sniffling throughout the performance (not to mention reducing the enjoyment of those seated next to them). Buyer-state dependency is therefore able to augment or diminish the value of a service without any action by the service firm. If the buyer’s state is not conducive, they may discount the value (and therefore be less willing to pay) at the time of purchase due to the uncertainty of their own state at the time of consumption. It is not uncommon to hear buyers say ‘I might be moving home/travelling/having a new job, so I can’t decide now’ when considering the purchase of a service such as a concert or tour. 2 Seller-state dependency This is when the value of the service is dependent on the state of the firm. For example, consumers may have a higher valuation risk for a restaurant on weekends because it may be crowded and may lower the perceived benefit of dining there. This, in turn, may deter advanced reservation because buyers may prefer to wait until the day to see how crowded the place is. Similarly, buyers may not trust the company to fulfil its promise when the time of consumption comes along in the case of time-share or vacation packages. Much of seller-state dependency is tacit to both sellers and buyers. The symptom of such a risk is often a low price. 3 External-state dependency This is often the most common risk for services that are at the mercy of the environment or other customers. Services such as open-air concerts (see Figure 3.2), outdoor activities, and emergency services for motor breakdowns and accidents are valued highly only when the external state demands it. Hence fine weather increases demand for outdoor services; an accident increases the value of repair services; and even knowing that a certain celebrity will be patronising a club increases its appeal. Each component of valuation risk adds to the amount of risk faced by the buyer. However it is important to understand that risk is a combination of uncertainty (i.e. probability of occurrence) and consequence (i.e. the damage caused by the occurrence). This combination will result in buyers deciding for themselves how much their willingness to pay may be discounted by the risk. For example, buying a train ticket to travel at a given future time may be high-risk because the buyer might have a meeting beforehand that may result in him

Advanced purchase in services 45

Figure 3.2 An outdoor concert at the Soundshell in Botanic Gardens, Wellington, New Zealand (source: Justine Hall, Wellington City Council).

missing the train. Thus, they are unwilling to pay the price of the ticket, even if it is discounted. However, if the firm offers them a ticket with more flexible travelling time, their risk is lowered and they may be willing to pay a higher price for it. The consequence of high valuation risk is therefore two-fold: 1 2

The buyer is reluctant to buy in advance and would prefer to buy at spot, when valuation risk is at its lowest. If required to buy in advance, the risk of not being able to consume may be so high that the buyer would demand a bigger discount on the price to compensate for this (or choose not to buy).

To mitigate valuation risk, firms often offer discounts to entice buyers to purchase, although the service rendered is still the same. Yet, buyers buy because the expectations they place on the benefits of the service is high enough (or the price of the service is low enough, depending on how you wish to see it) that notwithstanding the discount on their willingness to pay due to the valuation risk, the asking price is still worth it. Thus, many service firms don’t realise that the demand could actually be far higher and the willingness-to-pay far greater (i.e. the firm could get a higher price) if the valuation risk could be reduced.

46

The buyer as an individual

Risk at the point of purchase: acquisition risk The preceding section showed that the best way to reduce valuation risk is to buy at the time when the service is most needed to be consumed, i.e. at spot time. Unfortunately, as many service firms operate with capacity constraints, not all buyers may be able to obtain the service if they all show up at spot. Accordingly, if a buyer waits to buy only at spot time, he faces the uncertainty that the service may not be available. Few travellers would risk turning up at the airport for a popular flight as they are quite certain the seats would have been sold out by then; most of them would make reservations beforehand. Similarly, advanced reservations are common for hotels and concerts. But even if there is capacity available, the firm may price higher at spot, thus rendering the service unattainable to some. I term this risk of not attaining a service as acquisition risk. To alleviate this risk, buyers may be willing to purchase further in advance of consumption, as a form of insurance. Previous theoretical literature in advanced selling has claimed that advanced purchasing is common in many service industries for the reason of capacity limitation.5 Consequently, buyers who want to be sure of obtaining a service may buy in advance. Acquisition risk can be influenced by four factors. First, environmental conditions e.g. perceived popularity of the service could drive the perception of limited capacity and induce buyers to buy further in advance. Second, the firm itself could place fewer restrictions on the conditions of consumption, allowing the buyer to change the time of consumption and thus reducing the risk of acquisition through the availability of substitutes. Third, the acquisition risk could be imposed and controlled by buyers themselves where a time of consumption is personal to the buyer, e.g. a graduation party. Finally, the nature of the service can again contribute to acquisition risk. Some services are incredibly difficult to be substituted at any other times, e.g. a tow truck service during a breakdown. A further anomalous aspect of services is that for the buyer, the element of time can become an important attribute in the value of a service. For instance, a specific service is valued at a particular time, e.g. the venue of an anniversary party and since time of consumption can never be perfectly substitutable, acquisition risk is heightened. This is clearly the case for many important events like weddings, where dates are booked well in advance. Technically, a purchase further in advance and a purchase at spot are both deemed as advanced purchases. However, for clarity’s sake, I will term purchases close to consumption as spot purchases and purchases further in advance as advanced purchases, consistent with the terminology used by extant literature on this phenomenon. In reality, as elaborated by Lee and Ng (2001), the point where advanced purchase ends and spot purchase begins is industry-specific6, and is also dependent on ‘rate fences’ erected by the seller.7 Rate fences are constraints or conditions imposed by service firms to ensure minimal cannibalisation of purchase. Consequently, the service industry is host to a wide range of

Advanced purchase in services 47 advanced prices called forward prices, pre-paid vouchers, super-saver prices, advance ticket prices, early discounted fares, early-bird specials, early booking fares and advance purchase commitments.8 Clearly, there is a trade-off between the buyer’s acquisition risk and valuation risk. Hence, there exists a market for selling the service far in advance for buyers who would like to ensure that the service is available, regardless of whether or not the firm is willing to sell to this market. Similarly, there also exists a market for selling at (close to) consumption time for buyers who would like to ensure that they are able to consume. In practice, a service can face a heterogeneous market of buyers who face both high valuation and acquisition risks. For example, a particular flight from London to New York will have high acquisition risk for a passenger who needs to get on it to attend their child’s graduation. They will therefore purchase their ticket in advance. If the price is too high, they could wait to see if the price drops but they will more likely choose an alternative (perhaps another airline) to avoid the risk of waiting, as they need to be in New York on that particular date. In contrast, business executives who do not know when they may be called to go on business trips to New York will not be swayed to buy in advance, as they are Table 3.1 Consequences of acquisition risk and valuation risk Service

As a result of acquisition risk, buyers

Flights/hotel rooms

Buy early, may not consume

As a result of valuation risk buyers

Buy late, may have no seats/rooms Internet service provider Subscribe monthly, but may Pay as you use – line may be not use busy, or may be expensive Concert tickets Buy early, but may not make it Buy on the day – may have no seats or poor choices DVD rental Rent, but may not watch Rent only when want to watch – need to expend more effort (higher cost) and may not get the title of choice Loan Take out an overdraft, but Get a loan only when needed may not use – may be too late Restaurant Pay in advance for special Go on the day you wish – the meal, but may not make it choice menu/item may not be available Mobile Buy bundled text/voice Buy only when needed – telecommunication minutes, may not finish higher price using before expiry Breakdown service Buy early, but may not use Buy only when needed – high price Medical insurance Buy early, but may not Buy only when needed – high require it price Computer support Buy service, but may not Buy only when needed – need it price is high and technician may not be available

48 The buyer as an individual unsure of the traveling date. Table 3.1 provides some examples of the conflict faced by buyers when deciding when to purchase.

Bringing acquisition and valuation risks into the ENV framework The separation of purchase and consumption of a service leads to the understanding that while the ENV (expected net value) may be known to the buyer, they have a further decision to make i.e. when to buy. This has an impact on the price/outlay they are willing to expend. Based on what was expounded earlier in this chapter, the value of a service is moderated by the acquisition and valuation risks at each point in time. Therefore the value expected by the customer is dynamic across time. One peculiarity in the purchase of services is that buyers can choose to wait until they feel that the value is high enough to warrant purchase. For many non-perishable goods, there is no cause to wait. It doesn’t matter when you buy the detergent, the beer or the soda – they can stay in the cupboard until you need them; waiting doesn’t have such a huge impact on goods firms. For services however, waiting brings the service consumption date closer. This changes the value of the service to the customer and consequently, the amount the firm is able to charge. Valuation risk tempts the buyer to wait, while acquisition risk cautions him not to. Consequently, the ENV although positive, may be reduced due to the buyer purchasing in advance since the valuation risk may discount the expected benefit of the service. Given this, it is not surprising therefore that many service firms that sell in advance, do so at a discount. Yet, the opposite could also be true. Theatre tickets could be priced high in advance when the best seats were available but as the concert date approaches, the prices could be lowered as the remaining seats may not be as good (see Figure 3.3). This example shows that the drivers to pricing in advance are controlled by the ENV, which changes across time according to the trade-off between acquisition risk and valuation risk. Just as one would value an ice-cream more on a hot summer day than when it’s cold and wintry, buyers’ expectations of benefits and outlays and therefore the ENV, are dynamic. This means that the ENV changes with the buyer’s circumstances. If the buyer is tired, having to queue up is a big outlay. On another occasion, it may not even matter. Or perhaps the buyer is looking to get a haircut and asks her friend to recommend a hair salon, thereby reducing the expected outlay in the search for information. The implication of a dynamic ENV is that buyers themselves are able to manage and minimise their outlays (or maximise their benefits) to obtain a higher ENV from a purchase. Hence, buyers may ‘think about it’ when faced with buying anything because they may wish to be more sure of their ENV. The stability of the ENV may be important to the buyer because they do not want to regret the purchase. Indeed, there are those who insist on waiting before making a purchase, just because they believe that ‘the sense of deprivation will pass’. Often, to circumvent this, firms offer a quick

Advanced purchase in services 49

Figure 3.3 Discounted theatre tickets at New York’s Times Square – but what type of seats? (Source: Iris Ng).

discount to stimulate the buyer to purchase, or they convey the message that deferring the decision may render the service unavailable. The idea of a promotional discount valid only on that day may be enticing because the buyer perceives that the discount may not be available at another time. Current research often explores how buyers choose. While this is important, there is also a question of when buyers choose. Buyers are strategic and are able to adjust their conditions so that they experience the highest ENV. In addition, whether the outlay expected by the buyer is too high or too low compared to the actual outlay is irrelevant. The buyer’s decision is dependent on their expectations. How often have we decided to buy a service only to realise later that the outlay was higher than higher than expected, e.g. signing up for gym membership with the notion that going to the gym three times a week should not be a problem, then deciding later that it was just not realistic, given our busy schedule (or lack of will!)?

The marketing mix and its role in delivering net value The ENV also provides a way to understand how the marketing mix plays a role in changing buyers’ perceptions of expected benefits and outlays. The firm’s

Figure 3.4 Sensitising the buyer: promotions such as this Directline ad in newspapers’ travel sections sensitise buyers to their need to purchase insurance before travelling (source: Directline).

Figure 3.5 Information and its influence on value: the understanding of how maple syrup is made influences the customer’s value of the product, and helps customers understand how to make their choices.

Advanced purchase in services 51 product/service strategy in designing the service directly influences its expected benefits. For services, the product strategy includes the delivery of the benefits to buyers including the people, processes and physical attributes involved, and creating the satisfactory service encounter. The firm’s promotion strategy communicates expectations of the service, which influences the expected value. Promotional strategy is also able to sensitise the buyer and enhance his sense of deprivation. For example, seeing the following banner whilst booking an airline ticket online sensitises a buyer’s need for insurance (see Figure 3.4). Promotional strategy may also provide information, and therefore affect buyers’ beliefs about the attributes of a product. For instance, understanding how maple syrup is made and how to tell the difference between different grades of maple syrup changes how a buyer might value it (see Figure 3.5). The distribution strategy – the channel through which the service is purchased and delivered – may increase or decrease the buyer’s expected outlays. In Singapore, Citibank offers a drive-through automated teller machine (ATM) so that working executives do not need to go to too much trouble to withdraw cash (see Figure 3.6). Similarly, stamps are now available through dispensing machines rather than the buyer having to go to the post office (see Figure 3.7). Box 3.1 highlights some of the difficulties in distributing services.

Figure 3.6 A drive-through automated teller machine (ATM) offered by Citibank in Singapore provides convenience.

52

The buyer as an individual

Figure 3.7 A new channel for postal services.

Box 3.1 Challenges in distributing services The intangibility of a service creates problems for the marketer as not only are potential buyers not able to see or touch it before consumption, channel intermediaries may also not be able to convey the idea and the quality of the service to the consumer satisfactorily. The role of channel intermediaries in selling services therefore tends to be more complicated than the physical distribution of goods. As Stone (1990) puts it, ‘How can you rely on the agency to position your product properly, particularly when perceptions and promise are the essence of selling?’9 The inseparability of many services from production and consumption may imply that direct sale/delivery is the only option and channel intermediaries are not required. Regrettably, such an option will severely limit the service firm’s ability to market its service offerings. To overcome this limitation, many tourism services distribute a tangible representation of the service, e.g. a ticket or a voucher. Hence, channel intermediaries do not distribute the actual service but a promise that the service will become

Advanced purchase in services 53 available for consumption at some future time or date, such as that of an airline ticket, a hotel voucher, meal coupons or a cruise ticket. Contracts and transaction cost implications on the distribution of a promise has still not been adequately dealt with in academic literature.10 The heterogeneity of services often results in the lack of standardization in the service delivery process. This may result in dissatisfied customers and thus strain the relationship between independent channel intermediaries and the service firm. Consequently, many service firms resort to vertical integration to solve the marketing problem (Seaton and Bennett, 1996).11 However, due to the intangibility of services, perceived risk of purchase is higher (Murray and Schachter, 1990).12 To reduce that risk, buyers usually look for more information (Lutz and Reilly, 1973).13 This is usually the case for tourism services where the agent’s role is to provide customers with sufficient information to facilitate travel purchase decisions. Perishability of services also creates potential problems. In the effort to maximise yield and reduce unused capacity, many service firms sell in advance. By price discriminating through advanced selling, firms practise yield management with time-based pricing and even overbooking. Channel intermediaries may find that the service may not be available at certain times and prices may vary, resulting in confusion, repeated bargaining and therefore higher transaction costs for channel participants and the service provider.

Finally, the pricing strategy itself has informational value. A price that is too low might be perceived as low quality and one that is high signals a service that is of high quality. A successful service pricing strategy is one that integrates the marketing mix into the decision-making process, with the pricing decision falling within that process. Various combinations of the mix could create different value to different customer segments, resulting in the firm being able to charge different prices.

Competition: its influence on the ENV The ENV framework also provides a way to understand the influence of the competition. It is commonly misunderstood that a product or service is purchased only when it has value to the buyer. The reality is that value alone will not close a sale; in today’s world, only superior value will do so. In other words, a buyer will only purchase a product when he believes that its alternatives are inferior. This is not an easy achievement given that value is dynamic, i.e. it changes according to the situation. Figure 3.8 shows the impact of the competitive offering on the buyer’s motivation to buy. It is important to understand that the influence of the alternatives’

54 The buyer as an individual (C) Expected benefits and outlays of alternatives Perceived substitutability Motivation to buy at a given price AT A GIVEN TIME

(D) Random factors e.g. psychological factors

Figure 3.8 Motivation to buy is subject to influence from alternatives and random factors.

expected benefits and outlays hinges on a critical factor i.e. the substitutability of the alternative. Consider the example of traveling to London from Exeter. You could go by bus, train or take your car. You might prefer to journey by train, which takes approximately two hours but would cost £50. The bus would only cost £21 but the journey takes four hours, an outlay that some would not mind but may be too much for others. If you need to be in London by 10am, the bus would have an even lower degree of substitutability. Finally, there is the option of driving yourself but if you consider the fuel costs, congestion charge and car park fees, and how tired you would be by the time you get there, this option may not even be considered. Buyers constantly face alternatives in their purchase choices. It is a marvel how many choices we actually make, considering that there are so many alternatives available today. Whether a buyer would take the trouble to consider more or less alternatives in every choice would also depend on the ENV. The lower the ENV (perhaps due to a high price or outlay), the more the buyer will consider the alternatives. When making pricing decisions, firms must therefore understand the dynamic interactions between the price/outlay, competitors’ price/outlay and the buyer. Clearly the higher the degree of substitutability, the better a buyer is able to compare. When two services are easily compared, e.g. servicing your car at either one of two garages, the benefits are similar so the only relevant consideration will be the outlay. This is what happens when products become commoditised, i.e. they lose the ability to differentiate from their competitors. The result is often a competition of which firm extracts a higher outlay and often, a price war ensues. It is therefore imperative that firms are able to differentiate their services to obtain higher revenues. A differentiated service creates a unique perception from

Advanced purchase in services 55 the buyer’s point of view, making alternatives less substitutable and therefore less relevant in the buyer’s choice. There are many options for lunch e.g. pizza, sandwich or a salad, and the ENV for each may be quite similar. However a special dinner with a partner at a Michelin star-rated restaurant may have far fewer substitutes. Consequently, successful service firms are often those that are unique and not easily substitutable. Table 2.2 in Chapter 2 lists the top ten service brands in the world. Each firm stands unique within its industry and thus is able to charge premium prices. Interestingly, seven of the ten brands are in financial services, implying that being able to manage money well earns the most revenue in the world today, not surprising given that money is the common denominator for all trade and industry. When a buyer wishes to purchase a service, the service considered faces three types of competition: 1 2 3

competition from alternatives (either directly competing with the firm or substitutes); competition from itself, when the buyer decides to defer the purchase; competition from the buyer’s ability to discard her sense of deprivation (i.e. talk herself out of buying the service).

In any of these three cases, the buyer ends up not purchasing, and the firm will usually be pressured to lower its price to stimulate purchase. Just as increased expectation of benefits raises the buyer’s evaluation of his ENV, so does an expected increase of outlays for going with the alternative. For example, in deciding between two restaurants, if one place is a 20-minute drive away and has limited car park space, the one just a short walk down the road becomes more appealing. In economics, this is depicted by a shift in the demand curve, when the ‘price’ of the competition increases. This is an important point. The cost of increasing a service’s benefits may not yield as much revenue as compared to spending the money to amplify the expected outlay for choosing the alternative. This is because any increase in the expected outlay for going with the competition, will increase the firm’s ENV. And by amplifying the risk of choosing the alternative, the increase in a buyer’s ENV for the firm could actually be even higher. Why is this so? Kahneman and Tversky’s (1979) prospect theory14 showed that buyers’ aversion to loss is greater than their eagerness to acquire gains. Using the example above, the consumer may prefer to walk to the restaurant down the road so as to avoid the risk that he may not find a parking spot at the other restaurant, even if the latter is touted to have better ambience and food compared to the former. If amplifying risks of going to the competition translate to higher revenues, little wonder then that this is a strategy commonly employed today. A few years ago, low-cost airline Southwest.com ran a TV advertisement that likened the alternative to being rendered immobile after a severe kick by a horse. Take a look at ads today that position themselves against the competition; inevitably they would emphasis the risk of purchasing alternatives.

56

The buyer as an individual

Figure 3.9 Having the benefit of a fax machine without the machine (source: www.eFax.com).

In contrast, firms should reduce their outlays whenever possible, since lossaverse buyers will value lower outlays rather than an equivalent increase in benefits, or even expected benefits of alternatives. Finally, services are today more able to compete with goods. E-fax, for example, provides the client with a fax number and when faxes are received, the firm emails the person the image of the document, allowing you access to a fax machine to receive faxes even when you’re on the move (see Figure 3.9).

Random components of choice The ENV framework is not complete without recognising that human beings are erratic when it comes to choice behaviour. While the ENV provides a framework to consider how firms could persuade buyers to purchase at a certain price, every choice made by a buyer has a random component. Contrary to conventional economic theory, buyers do not evaluate prices with perfect rationality; they tend to process prices by using imperfect, but convenient, decision rules.15 Research into choice has held the interest of several disciplines including engineering, economics, psychology and marketing. Quantitative models have been developed for prediction (for economics, marketing, engineering and planning) or deconstruction (psychology). Today, research has concluded that16: • •

choice is a result of perception, cognition and information processing; history (i.e. previous purchases) matters;

Advanced purchase in services 57 • •

buyers are heterogeneous in attitudes and perception and therefore choose differently even in similar circumstances; and psychological factors and external constraints that are latent within a particular context influences choice.

This means that while the firm endeavours to provide the best value for the buyer, the buyer’s actual purchase is still probabilistic. In particular, how prices are presented can affect buyers’ perception of the entire purchase situation. The growing field of research in consumer psychology – more specifically on price perception and evaluation – has many crucial implications for pricing, as discussed here. The importance of reference prices When evaluating the price of a good or service, buyers usually compare the price paid with their reference prices; price levels that they consider fair or reasonable for that particular product. An important concept in pricing, the reference price is usually formulated and influenced by three major factors: 1 Current prices Most buyers would tend to form their reference prices based on the prices to which they are currently exposed. Research has found however, that the relative impact of all prices that a buyer observes on the reference price, depends on the order in which they are presented. This order effect, discovered in the mid1960s, states that buyers who see prices in descending order formed higher reference prices than those who see them in ascending order.17 Apparently, greater weight is given to the first prices that the buyer observes in a range. Several pricing strategies have been found effective in influencing current prices, which in turn could affect the reference price. For instance, product-line pricing, where a high-priced product is added to the top of a line to increase the buyer’s reference price, has been found to enhance buyers’ perceptions of lowerpriced products in the product line, and to encourage low-end buyers to trade up to higher-priced models.18 In their effort to influence reference prices, firms are also known to provide a suggested reference point, be it a manufacturer’s suggested price or recommended retail price, or a comparative frame of reference such as the competitor’s higher price. Hotel ‘rack rates’, airline ‘gross fares’ are all examples of reference points that service firms endeavour to create since researchers have found that this strategy enhances perceptions of value and savings, even if the advertised reference point is exaggerated.19 However this tends to be less effective with more knowledgeable buyers.20

58

The buyer as an individual

2 Recalled prices Prices that the buyer remembers from past exposures can influence their reference price. In particular, the price last paid is more likely to be recalled compared to previously observed prices that were not paid. This means that numerous small price increases for frequently purchased items are more acceptable compared to infrequent large increases, since buyers would raise their reference prices after each small increase. Also, price increases for infrequently purchased durable goods would face greater resistance, as the buyer would likely have an outdated reference price.21 3 The purchase context Buyers’ reference prices are influenced by what they think they should be willing to pay in the purchase context, i.e. the context within which the price is offered. They are also influenced by what they think sellers should reasonably charge; in assessing fairness, buyers would also evaluate what it costs sellers to deliver the good or service. Prospect theory and the influence of framing Kahneman and Tversky’s prospect theory22 has great implications on buyers’ perception of price. Prospect theory, considered a theory of ‘irrational’ economic behaviour, assumes that people are more motivated by losses than by gains and as a result will devote more energy to avoiding loss than to achieving gain.23 At the core of prospect theory is the endowment effect, which argues that individuals place a higher value on items that they already own (becoming part of their endowment) and hence are reluctant to part with the items because they want to retain the status quo. Thaler (1985) examines the endowment effect within specific case studies through which he observes that consumers often fail to behave in accordance with the normative prescriptions of economic theory, instead responding more to perceived changes than absolute levels.24 One of the findings from research relating to the endowment theory is that money that is ‘owned’ by the individual, i.e. money that has been earned (an inheritance, savings or salary) is viewed differently from money ‘not owned,’ such as a loan or credit facility. An individual’s attitude towards loss (i.e. expenditure) was found to be a function of the origin of the money being utilised25. For instance, an individual who values their savings would rather utilise an overdraft facility to pay for a major purchase – even though they know it is a less cost-effective approach – because they considered any withdrawal from the savings as a loss. In such a case, the individual makes the decision based not on logic but on the need to retain money that is ‘owned’. In view of prospect theory, firms can influence purchase decisions by framing

Advanced purchase in services 59 them as either potential gains or losses.26 There are three common ways that firms can use to influence the framing of prices27: Framing buyers’ reference points Firms can overcome the endowment effect by influencing perceptions of what buyers consider to be their status quo. Possible pricing measures include: •

•

•

Presenting price as an opportunity lost rather than an outright loss;28 buyers tend to view out-of-the-pocket costs as a loss of assets already owned, and therefore more painful than foregoing potential gains as represented by opportunity costs. Presenting price differences as discounts from the higher price rather than premiums over the lower price; premiums tend to be viewed as an explicit loss. Decoupling product acquisition and payment by first endowing buyers with the product, i.e. buy-now, pay-later plans used by encyclopedia sellers, and health and fitness clubs. This strategy allows buyers to integrate the new purchases into their reference points, making it difficult for them to terminate the contract or return the product when the payment is due.

Framing decision outcomes in terms of gains or losses – positive and negative framing The effectiveness of this strategy is dependent on the nature of the product category. Positive framing, i.e. framing potential gains, has been found to be more effective on buyers of products that enhance one’s utility, like video cameras, beauty products, and fashion. While negative framing, i.e. framing potential losses, is more effective for product categories that preserve one’s utility, such as medication, insurance, and home security systems. Framing multiple gains or losses as bundles Given the diminishing effect of gains and losses as they grow in size, firms can increase the buyers’ perceived value of the gains or losses by framing multiple gains or losses as bundles. For instance, multiple gains can be unbundled when buyers perceive that they receive more utility from separately offered gains, i.e. offering a bonus or gift with a product purchase. Losses can be bundled when buyers perceive that multiple losses bundled together will lessen the negative impact on their utility, i.e. having to pay £50 for travel insurance may seem painful, but less so when considered together with a £500 holiday travel package. Smaller losses can be bundled with larger gains to help buyers perceive the price as a reduction of a large gain rather than as a loss from incurring the cost

60

The buyer as an individual

alone, i.e. payroll deductions for savings or investment schemes. And smaller gains can be unbundled from larger losses, as separate gains are more highly valued compared to reduced losses. This is also known as the silver lining principle, and is often associated with the use of price rebates off a large expense such as a car. Pricing of probabilistic products Psychology also comes to play when buyers evaluate services with probabilistic attributes, such as financial products. Buyers’ valuations of these probabilistic elements usually differ significantly from their true expected values. In studying probabilistic choice, psychologists have found that when dealing with gains, buyers tend to be risk-averse and would opt for certainty rather than take a risk on an alternative with the potential for better returns. However, when the probabilities involve losses, they are naturally inclined to risk a loss than to pay the necessary price to protect against that loss.29 For instance, they may choose to face possible loss of assets rather than pay for a homeowners’ insurance policy that can help reduce that potential loss. Insurance companies can overcome this by presenting their products as a way to protect future gains rather than cover against a possible loss. This shifts the purchase decision into the domain of gains where buyers are typically risk averse, and thus would be more willing to choose the certainty that insurance provides.30 Individuals also tend to underestimate the value of reducing small probability losses; i.e. not using an infant car seat for a short car ride because they believe the chances of a serious accident occurring on that short trip is extremely small, although the expected value of that loss may be high. On the other hand, they place a higher value on certainty; i.e. opting for a new vaccine that totally eliminates the probability of catching the flu compared to one that is ‘only’ 99% effective.31 How price differences are perceived Research has shown that the same absolute price difference can elicit different behavioral responses from buyers. There are however, several common tendencies in buyer behaviour. For instance, buyers perceive price differences in proportional or percentage, rather than absolute, terms.32 This is in accordance to the Weber–Fechner Law. For instance, a rail company and a coach service raise the fare of their London–Exeter route by an absolute amount of £15; the rail ticket goes up from £50 to £65, while the coach service increases from £20 to £35. Buyers would however weigh the price changes based on the percentage difference; a 30 per cent increase to go by rail, but a 75 per cent increase for the coach service. There are also thresholds above and below a product’s price at which price changes are noticed or ignored.33 Also, buyers are found to respond better to a series of smaller increases below the upper threshold than to one large increase.

Advanced purchase in services 61 However, for price discounts, a large price cut below the lower threshold works better than a series of smaller discount. Research has also found that buyers perceive odd-number prices, i.e. 1.99, 11.99, 1999, to be significantly lower than the slightly higher round numbers, i.e. 2, 12, 2000 that they approximate.34 Studies show however, that this has greater effect on the pricing of products that are purchased quickly, such as groceries, and not for those that need time for evaluation, such as consumer durable goods. Odd-number prices also tend to be associated with discount prices. These implications of the psychology of pricing enable firms/sellers to understand why and how buyers behave differently. These psychological factors add a stochastic (i.e. random) element resulting in buyers deviating from the normal ‘economically rational’ behaviour. Figure 3.10 illustrates the full ENV framework with the moderating impact of acquisition risk and valuation risk on the expected benefits of the service, the role of the marketing mix, and the role of alternatives and random factors. The service marketing mix strategy

Tangible attributedriven benefits

Intangible attributedriven benefits

Perceived substitutability

(A) Expected benefits of service

(C) Expected benefits and outlays of alternatives

Acquisition risk and valuation risk Evaluation of EXPECTED NET VALUE (time-dependent)

(B) Expected outlays of service

Expected total monetary costs Price and other monetary costs

Motivation to buy at a given price AT A GIVEN TIME

(D) Random factors e.g. psychological factors

Expected total nonmonetary costs Opportunity costs, risks, other nonmonetary costs across the buying and consumption process

The service marketing mix strategy

Figure 3.10 The full ENV framework.

62

The buyer as an individual

The expectations of service customers So far, our understanding of the ENV is that it is the expected net value that drives the price (and non-price) outlays that buyers are willing to pay. Buyers purchase a service at a particular price based on expectations because services are experiential – there are very few ways you can tell if the service you purchase will be good for you unless you have already purchased and experienced it. Hence, there is a gap between the firm’s creation of value and the buyer’s expectation of that value before consumption. Zeithaml et al.35 illustrates this through the gaps model of service quality (see Figure 3.11). The model highlights two critical gaps that would influence the pricing of a service; the Customer Gap and the Provider Gap (Gap 1). Customer gap The customer gap is the gap between the ENV and the perceived net value at the point of consumption. This is the gap between expectation and the actual service perceived by the consumer. This occurs because the experiential nature of services does not allow the customer to obtain a closer estimation of the actual service to be performed. For instance, a customer might expect food at a restaurant to be good because of its décor and reputation, and may be willing to pay a higher price but could be disappointed after a meal. Conversely, a tennis instructor might be an Gaps model of service quality

Customer

Expected service Customer gap Perceived service

Service delivery

Company Gap 3 Gap 1

Gap 4

External communications to customers

Customer-driven service designs and standards Gap 2 Company perceptions of consumer expectations

Figure 3.11 Gaps model of service quality (source: Zeithaml, V.A., Bitner, M.J. and Gremler, D. (2006) Services Marketing: Integrating Customer Focus Across the Firms, 4th edn. New York: McGraw Hill/Irwin. Reproduced with permission of the McGraw Hill companies).

Advanced purchase in services 63 excellent coach, but a potential customer is not able to tell that with greater certainty before paying for, and experiencing, the tennis lessons and therefore may have low expectations, thereby translating to a lower willingness to pay. Certainly, for repeat purchases, the customer gap would narrow. Good service providers are able to retain customers simply because a repeat customer might have their expectations adjusted by a previous satisfactory experience. This upwards adjustment contributes towards a higher ENV (see Figure 3.12), even if the price charged remains the same. It is clear therefore that the price the firm is able to charge is not based on its perception of what customers would value, or on what customers perceive the service to be at the point of consumption. Rather, it is based on the expectation customers have for the service. Customers with high expectations of the service may be willing to pay more, while those with low expectations are willing to pay less. To charge higher prices, firms must be able to increase customers’ expectations. However, the risk of increasing expectations is disappointment; what happens when the perceived service fails to meet expectations? It may seem correct to assume that customers will not return, but this may not be true. Why do we continue to patronise the dry cleaning service down the road even though the shopkeeper barely says hello, grunts when you talk to them and always looks dour and nasty? We continue to go there because the next nearest dry cleaner is too far away, and as long as the clothes are satisfactorily dry cleaned, we may be prepared to overlook their demeanour i.e. the expected First-time purchase

Perceived service

Repeat purchase

Perceived/expected service

Customer gap Expected service

Expectations increase in repeat purchase

Customer gap narrows (or disappears) due to increase in expectation to previously perceived level

Higher expected net value – greater sense of ‘value for money’

Expected net value

Outlays (price)

Outlays (price)

When a firm provides good quality service, Expected Net Value (ENV) increases even though price remains the same upon repeat purchase because of the elimination of the customer gap.

Figure 3.12 Increase in ENV.

64

The buyer as an individual

outlay is low. Figure 3.13 shows the reduction in ENV when a service is perceived to fail expectations. In this case, the ENV may not be as high as before the first purchase but as long as the ENV stays positive or zero, there is still a possibility that the customer will purchase. In other words, customers continue to buy a service as long as the price is low enough or the service level is high enough to provide a zero-or-positive ENV. But what if the dry cleaner damages one of your suits? That is when your expectation of the service drops to the point where the ENV is below zero. And that is when you will take your clothes to the dry cleaner across town. This may also happen if the dry cleaner increases his price. This example illustrates two important points: 1 2

Failure to meet expectations does not necessarily lead to customers’ unwillingness to purchase again; and Firms must manage customers’ expectations as well as price. The outlay (price) is important in determining that the ENV remains positive.

Thus, the strategic tool for pricing effectively is the ENV. Provider gap (Gap 1) The provider gap is the gap between the firm’s perception of customers’ expectations and the customers’ actual expectations. This gap contains two dimensions. First, in terms of the standard of delivery, i.e. the customer perception of the standard of service according to the attributes that are important to them. For example, a customer may expect their tax adviser to be available whenever they call them for advice, but the tax adviser is only available at certain times. Second, the gap exists in terms of differing perception of what the firm thinks the customer values in the service and what the customer actually values. In the case of the tax adviser, the adviser may think that having online information will be useful to their clients, but it could be that the clients are not familiar with the internet and would prefer personalised service. It is a fallacy that the firm has a right to charge a higher price when it increases the quality of a service. Will customers pay higher interest to a bank if it improves its frontline customer service and provide more comfortable surroundings for customers visiting the bank? Not if the customers transact online and have not visited the bank in years! The quality of a service may improve, but not the value of the service to the customer. Pricing is based on expected net value (ENV), not quality. In fact, some researchers may even disagree on what constitutes quality for a service, and that the quality of a service itself is perceived, and is heterogeneous according to different consumers and the attributes they value in a service. Firms often forget that their customers are not as knowledgeable as they are about the delivery of the service. Holiday makers at Disneyland do not know much about the detailed processes that go on behind the scenes to ensure the smooth running of the theme park. As consumers, they are only interested in the

Advanced purchase in services 65 Repeat purchase

First-time purchase

Expected service Customer gap

Expectations decrease in repeat purchase

Perceived service

Perceived/expected service Lower expected net value – but custmers may still buy because ENV is still zero or postive

Expected net value

Price and nonprice outlays

Price and nonprice outlays

No repeat purchase

First-time purchase

Expected service Customer gap

Expectations decrease in repeat purchase

Expected net value Price and nonprice outlays

Perceived service

Price and nonprice outlays Negative expected net value – no repeat purchase Perceived/expected service

Even when a service is below expectations, customers may still purchase as long as the ENV is zero or positive. When the ENV is negative, customers will not repeat their purchase.

Figure 3.13 Repeat purchase when a service is below expectations.

experience and will pay what they think the experience is worth, regardless of how much the costs are. Since customers may not be aware of the cost of delivering a service, they may also not be willing to pay a higher price for it, believing that even if they do, the firm profits at their expense. As Chapter 1 illustrated, even the concept of delivery cost is debatable in a service. Passengers can argue that when a seat on a flight is empty, even a dollar is better than nothing because it would be worth nothing upon take-off. Despite the difficulty in determining costs, service firms have mostly been driven by value when pricing their offerings. However, the provider gap makes

66 The buyer as an individual it difficult for firms to decide on how an offering is to be delivered. It is not surprising to see firms changing different aspects of their service delivery e.g. reducing the quality of towels in hotel rooms, thinking that this would not be important to the customer. The service experience is a complex combination of attributes along many dimensions (see Chapter 2), and while it might be easy to ascertain the attributes that customers want in a service, it is more difficult to determine the level of importance of each attribute in relation to the price paid. As low-cost airlines have shown, many customers are prepared to forgo frills on airlines to get a lower fare. Some, however, are less willing to do so and are prepared to fork out more for better service. There is as much danger in cutting costs where the firm thinks the customer won’t mind, as there is in spending on what the firm thinks is an enhancement of quality (but without the corresponding increase in revenues). The Baldrige Award is the US government’s effort to recognise companies in the US for their excellence in product or service quality. The award has seven categories totaling 1,000 points, and the seventh (valued at 450 points) was customer satisfaction. However, after a few award winners went bankrupt, the category was changed to outcomes (market share, return on investment, profits, etc). Price and Brodie36 used the term ‘inside-out’ orientation in service to describe how service firms often ‘. . . design . . . build . . . bill . . .’, in making judgments on what constitutes good service and what customers are willing to pay for. By doing so, these firms implicitly target a particular segment and without research, it can only be hoped that the segment exists and more importantly, that it is willing to pay according to what the firm had envisaged. On the other hand, firms can take an ‘outside-in’ perspective where changes to service delivery are mapped on to pricing and revenue implications so that any change is driven by the customer, rather than due to internal processes or constraints. Firms that take this approach can stay customer-focused, and price based on returns on service quality.37 Even for profitable service firms that provide good quality service, the customer gap may result in the firm not being able to price higher. Service customers do not know how good a service is until they actually experience it. Consequently, it is not merely how good your service is, but how you communicate that quality to potential customers.

Understanding the strategic nature of ENV The previous chapter showed that the price obtained by the firm is dependent on the expected benefits and outlays through the ENV framework. The framework demonstrates that price is over-rated as a reflection of the service’s value or benefit to the buyer. Marketers forget that the price – commonly seen as the ‘economic value’ of their products – is usually severely discounted because of outlays required to buy or consume a product, especially if it’s a service. The key strategic value for decision making is the ENV; how the ENV is affected by the expected benefits and outlays, and the construction of the pricing policy within the framework. The traditional understanding of willingness-to-

Advanced purchase in services 67 pay is that price has to be lowered to increase surplus and improve the buyer’s inclination to buy, since the buyer’s willingness to pay cannot be changed for a given product. As earlier discussed, outlays are dependent on the situation and even expected benefits of a product is subject to change for services due to state dependency. Consequently, there is a need for a revised understanding of the key economics concepts relating to price. This revised understanding replaces consumer surplus with the ENV, and incorporates both price and non-price outlays into the expected outlay. The term ‘willingness-to-pay’ is only correct if price is the only outlay (which is unlikely). Otherwise, the term should more accurately be ‘willingness-to-outlay’. The revised understanding provides a more complete understanding of buyers’ choices and the role of price within that choice (see Figure 3.14). Pareto Loss An interesting insight falls out of the revised understanding. Non-monetary costs borne by buyers constitute what I term as a pareto loss. An allocation of resources is pareto optimal when there is no other allocation that can make at least one individual better off, without making any other individual worse off. Pareto loss, conversely, means that there are no gainers. In the case of an exchange where there is a willing buyer and a willing seller of the service, the non-monetary costs borne by the buyer does not benefit either the buyers and sellers. In other words, the firm does not profit from the non-monetary costs borne by the buyer as a result of buying or consuming the service, and neither does the customer. Waiting is a classic example. The firm does not benefit from customers waiting nor do customers like waiting. Waiting is therefore a pareto loss; neither party has anything to gain from it. As a matter of fact, having to wait may incur losses for some service firms, as some buyers may give up on buying the service. There may even be pressure on the price as buyers may Traditional understanding Willingness to pay

Revised understanding Willingness to outlay

Consumer surplus

Price

Expected net value

Price and non-price

Expected outlays

Figure 3.14 The difference between the traditional understanding and revised understanding of value.

68

The buyer as an individual

demand ‘compensation’ for having to wait. The next chapter elaborates on how the pareto loss for the purchase and consumption of services can be used to increase revenue.

Trading off benefits and outlays The ENV framework provides a means of analysing trade-offs between benefits and outlays. Remember that price is merely an outlay and indeed, some buyers may find that price is the least costly of outlays. For example, a car wash may only be priced at £3. However, if you’re sitting comfortably in front of a TV watching a programme, it’s just too much of an effort to take the trip to the car wash. In fact, the effort is so ‘costly’ that you might pay your teenager £5 to do it. So theoretically, someone who is willing to wash your car at your driveway could potentially earn £8. Firms often over-rate the importance of price in a buyer’s decision. Some often discount heavily to motivate buyers to purchase without realising that the discount is to compensate for other non-price outlays that buyers may face. The linkages between attributes and benefits (and finally to value) have been researched extensively, e.g. the use of Means-End Chain Analysis (MECA)38 or through conjoint analysis. MECA is a method to understand why buyers buy certain products or brands, and identifies links between product attributes, benefits and values. Conjoint analysis, on the other hand analyses how buyers rank different attributes according to their degree of importance. Using such methods, marketers are able to develop insights that assist in new product development, positioning strategies and market segmentation. In addition, when a firm is able to find a particular attribute through which it is able to position its service differently, this attribute could initially provide the firm with a differentiation capability. Unfortunately, as time progresses, other firms copy the attribute and it becomes an expected attribute for all services of such nature, and the differentiation factor becomes lost. The consequence of such a phenomenon is also that the value proposition of a service becomes ‘expanded’ and the augmented product may then become the core product of the future (see Figure 3.15). The implication on pricing is severe. If the augmented service creates Time Core service

Expected service

Expected service

Delivery based on (a) core and (b) augmentation (often to create customer delight)

Is there willingness to pay for the expanded service?

Augmentation Price based on core service

Figure 3.15 The augmentation trend and its implication on pricing (source: illustration adapted from Moon, Y. (2006) ‘IKEA invades America’. Harvard Business School Case Study, March 7, (5), p. 504).

Advanced purchase in services 69 customer delight in such a way that that the firm is able to extract a premium in its price, it is logical therefore to offer it. However, if the augmentation is easily copied, its provision could easily fall into becoming a hygiene factor (see Box 3.2), and the firm would reduce its overall profitability in the future. Hence, attributes and the augmentation of a service must always bear in mind interaction with the competition.

Box 3.2 Hygiene factors in services Herzberg et al., in their book The Motivation to Work,39 described Hygiene Factors as factors whereby their absence would result in dissatisfaction but their presence do not result in satisfaction. In the service context, a flight being on time is a hygiene factor in the sense that if it’s not on time, it would create dissatisfaction but if it is, it does not necessarily create satisfaction. Other service hygiene factors may include a clean hotel room, polite service in a restaurant, accurate translation service or correct billing of your utility services. Customer preferences for certain benefits/attributes are also subject to influences. How do buyers judge the value of a service? Often, the buyer evaluates the value of a service by considering its features, and then forming a sense of total value for the service. To understand how this works, let me illustrate this with a buyer’s evaluation of an MBA programme. The student may attach weights to different attributes of the service, for example length of programme, reputation of school, good mix of classmates, relevant subjects, instructor’s reputation, distance of school from home. While the buyer may rank these attributes according to their degree of importance, each attribute could be traded off against another. A good mix of classmates may not be as important if the lack of this attribute can be compensated by a very good school reputation. Or perhaps the length of programme may not be ideal, but this could be compensated by the instructor’s reputation. Finally, the level of importance of each attribute is also weighed against the price of the programme. For instance, an MBA from a school further from home may have all the right ingredients at the same price as the MBA from a school around the corner, but it means that the non-monetary costs (and perhaps monetary too if you include transportation) are higher and the buyer has to consider if the distance is worth the added features. Clearly, for the same price, different attributes would matter for different customers. The only way to analyse the trade-offs between benefits and outlays is to bring all of them, including price, into the analysis. More service companies are now providing buyers the opportunity to selfselect the options that would provide them with the highest satisfaction for the price they pay. From choosing the amount of mobile phone texts (SMS), voice calls and data to selecting the channels on cable or satellite TV, firms are now starting to understand that customers are able to find the highest satisfaction for themselves, rather than being pre-judged on what they value.

4

Seven strategies for higher revenues

Firms develop pricing strategies with the aim of achieving higher revenues. To do so, it is important that they understand what value means to the buyer, and the role of the ENV framework in pricing strategies, as discussed in Chapter 2. More specifically, the pricing of services has to take into account the separation of purchase and consumption which would have an impact on pricing, as explained in Chapter 3. How can the knowledge expounded in the last two chapters be translated into workable action plans? This chapter presents seven strategies that firms can employ for higher revenue.

Strategy 1: price on value, not cost This may seem like common sense, but it is surprising how many firms do not price based on value. For instance, telecommunication companies base their pricing on the volume of data transmitted.1 However, when competitive pressure sets in, pricing based on costs may not be sustainable, as I have highlighted in Chapter 1. While it has been acknowledged that pricing on value provides higher revenue, there are a few reasons why firms do not embark on value pricing Value pricing is difficult First, it is much easier to ascertain the cost of a product than to determine its value to the customer. Firms tend to lean towards the more ‘tangible’ or quantifiable, particularly when motivated by the need to be profitable. Costs can be ascertained by collecting internal data that are less volatile, and which can be put towards a systematic analysis that looks professional and ‘scientific’. It is easier to convince ourselves that pricing based on cost-plus is right, since the figures are all there to see. Value, on the other hand, is not only difficult to determine; it is unpredictable, varied and not easily analysed. The uncertainty of value, and the fact that the understanding of the customer and the market does not lend itself well to scientific analysis, is disconcerting to many. Hence, it is all too easy to abandon value and take on something far easier, like cost. However,

Seven strategies for higher revenues 71 pricing is a constant challenge because human beings aren’t all rational, and we are not predictable. Firms that do very well, however, are those that endeavour to understand the value a customer places on a product as well as understanding the actual benefit that the customer obtains from buying the service and capture that value in prices that customers are willing to pay. There is far less revenue growth in discovering (or reducing) a firm’s cost; the value end of revenue holds far more promise. In addition, revenue from value does not go up in a predictable and linear manner. To go up to the 86th floor of the Empire State Building in New York cost $16. From there, if the customer wishes to go up to the 102nd floor, the price is an additional $14. Not merely value, superior value The value end of revenue is not a bed of roses either. The best value to customers will not earn the company revenue if that same value is offered by a competitor. Hence, it’s not merely value but superior value that translates into revenue. Firms will do well to understand that every decision they make when designing a product or service could be easily imitated by a competitor. When that happens, the customer obtains tremendous value but competition drives prices down to the extent that there is no money to be made. Some of the internet’s biggest names that deliver tremendous value to customers, such as eBay and Google, do not do as well in China, where Taobao (equivalent to eBay) and Baidu (the Google equivalent) are more successful. In 2005, Baidu beat Google in terms of web traffic, making it the world’s fourth largest internet website.2 Undoubtedly, Google provides great value to the internet user (and for free) but clearly in China, Baidu is perceived to be superior (for reasons why, see Barboza (2006)). Revenue, unfortunately, flows towards the superior value provider. Uncertain value The second reason that firms tend to price based on cost rather than value is that a one-time consumption value is impossible to ascertain in some cases. What is the value of a phone call? There isn’t any straightforward answer. It depends on how urgent it is, who the customer is calling and for what reason. Even if the price is too high, the customer might still make the call if it is very important. They will however, definitely seek alternatives for the next call, in which case the firm would lose a customer and the revenue they could have provided over their lifetime. Value only known after consumption Third, a particular service could be disjointed, and the value of the content of the service may not be known till after consumption, e.g. legal or tax advice. In such cases, it is easier to charge by the hour, i.e. by cost. Yet, legal fees could also be hourly (cost-based) or based on success (value-based).

72 The buyer as an individual Value based pricing opens up a whole new world of revenue models. Returning to Google, eBay, Baidu and Taobao, these services are essentially free to the customer despite the fact that they provide value. Hence, value of a service may not be paid by the customer of that same service. For example, Google is of value to an internet surfer, and access to the surfer is of value to another firm wishing to market its offerings to the surfer, e.g. an insurance company to the extent that they are prepared to subsidise or pay for the value received by the surfer to gain access to the surfers. The ‘price’ the surfer pays is therefore transferred to the insurance company that pays Google through ads and access. Technology firms such as Skype and Youtube were sold for $2.6bn and $1.65bn despite the fact that both render their services to customers for free, and were not profitable at the time of purchase. Yet, the community of millions visiting Youtube (measured in clicks) and using Skype make access to them valuable to others, i.e. Google and eBay respectively. Some services may seem to be the same, but are actually quite different. The internet, for example, is usually priced based on bandwidth and quite often the content and information is free. Mobile internet, conversely, is far more sensitive towards services that customers want delivered into their mobile platform (phones, PDA and the like) be it music, information or TV. The value is therefore perceived differently and the firm delivering that value must therefore understand the difference and price accordingly. In dealing with this world of complex technology, firms need to understand how value is created, for whom, and to find a revenue model that works. Working on value-oriented pricing is a challenge, but one that firms should embrace for the payoffs it is able to provide.

Strategy 2: convert pareto loss into revenue In the previous chapter, I presented the concept of the pareto loss i.e. nonmonetary costs borne by the buyer that result in no gains for both the buyer and seller. Figure 4.1 shows two options for higher revenue. First, the firm can attempt to reduce the customer’s non-price outlay and increase the price accordingly, maintaining the total expected net value (ENV) and therefore retaining the number of customers in the market for the service. This is common with services like dry cleaning, where customers willingly pay a higher price for an express (quicker) service, or removal companies that offer packing and unpacking service for an additional charge. Alternatively, the firm can benefit from an increase in demand by reducing the non-price outlay and not increasing the price of the service at all. By doing so, the ENV increases and this may entice more customers to purchase the service. Consider a garage service, and assume that the firm charges a price of P1. However, the buyer has to send the car to the garage, take a taxi to office and return to the garage later to collect the car. This non-monetary outlay makes the expected benefit exactly equal to the expected outlays (see Figure 4.1 (1)). The

Seven strategies for higher revenues 73

Willingness-to-outlay  Expected benefits

(1) Expected outlay  Expected benefits

Pareto loss amount (PLA) = non price outlay

(2) Reduced PLA, increase price

(3) Reduced PLA, maintain price, increased demand

(4) Reduced PLA increase price and increase demand

Value

Value

Improved revenue through demand increase Pareto gains

Improved revenue through some demand increase and some price increase Pareto gains

Ps

Total outlay Price outlay P1

Improved revenue through price increase Pareto gains

Improved revenue through price increase Pareto gains

Figure 4.1 Options for higher revenue.

firm’s benefit is P1 and the net value is zero. The non-monetary outlay is therefore a pareto loss amount (PLA). Consider the situation where the garage charges a service charge of Ps to pick up the car from the office and return it before the close of business. If the buyer feels that paying Ps is equivalent to all the hassle (there may still be other non-monetary costs), the firm benefits from pareto loss conversion to revenue whilst the buyer is in the same situation as before (see Figure 4.1 (2)). However, the firm might not even charge the buyer but provide the pick-up and drop-off service for free, in which case the service is much more appealing to other buyers since the value of the total service is now higher than before. The expansion of demand results in higher revenue for the firm (see Figure 4.1 (3)). Alternatively, the firm could of course, charge slightly less for the additional service, which results in some increased demand as well as some increase in price; the outcome is what economists would term a pareto gain (see Figure 4.1. (4)). Busy buyers also have different time costs, resulting in the demand being downward sloping. Figure 4.1 illustrates the different ways in which the firm could either improve their revenue or motivate buyers to buy through converting the pareto loss. Firms constantly attempt to capture value in their prices. The problem is that value is elusive. Buyers change their valuation of a product all the time; we just like to think that they are constant. Today, innovation and technology allow firms to capture the changes in value. In particular, the surge of technology use over the past 20 years has been impressive, and there are two aspects of such a surge that is relevant to pricing and revenue. First, markets that were previously not easily reached are now far more accessible. By this, I do not just mean geographically. For example, customers

74

The buyer as an individual

who wish to buy antiques may previously have had to undergo a steeper learning curve; joining clubs and learning through other antique collectors, and studying history. With the internet, information is far more accessible and so are antiques. Through information websites, eBay shops and specialised retailers, an antique dealer from France is able to connect with antique buyers in Asia. More importantly, an antique dealer working from their home in London is also able to connect with a buyer down the road, when prior to the advent of the internet, both might not have known of each other’s existence. Hence, technology has created the potential to generate greater demand at a faster pace. Second, technology has been able to convert the pareto loss into higher revenues for firms. Customers who have little time to go to the bank or the post office can now do their banking or bill payments online. No time to pick up a language? Audio CDs that you play on the way to work every day allow you to practise Chinese/French/German. Want to check your emails? Personal Digital Assistants (PDA) enable you to do that while you’re on the move. No time to plan dinner? Your ‘intelligent’ fridge is able to tell you what you have and suggest recipes. And don’t forget that GPS (global positioning system) ensures you don’t get lost; you need never read a map again! Similarly, when there is uncertainty as to whether there is enough snow at ski resorts and the non-monetary cost of travelling to the slopes is high, a webcam and a half-hour report on slope conditions available on the internet provides tremendous value to the skiing customer. Also, providing leisure activities for non-golfers at a golf resort helps to ensure that non-golfing partners are taken care of while golfers enjoy their rounds on the course. Technology has been a key driver in the servitisation of the economy because it allows more non-monetary costs to be converted to revenue-generating service businesses. Where it might be a hassle to go to the supermarket on weekends, you can now do your grocery shopping online at Tesco.com, for example and have it delivered to your doorstep. Clearly, technology has greatly aided the conversion of the pareto loss into services and revenue. This in turn, raises productivity levels across the board and as economists like to observe, increases consumption that would stimulate the economy further. Buyers’ needs today are more complex, with a greater demand on time. The key driver isn’t merely technology, but our need for more time, greater convenience and less risk. Where a trip to the local pub was a once-a-week affair, more people now go daily to ‘chill-out’ and ‘unwind’. TV used to be for information and entertainment. Now it’s also for relaxation, escapism and education. Even without technology, innovative entrepreneurs are able to identify the ‘costs’ that many of us would gladly ‘buy’ our way out of. For example, it is now possible to hire a personal concierge to help with errands that we might not have time to complete. Whether it is returning mail order items, sending parcels by post, collecting tickets, or walking dogs, your own personal concierge is available from the International Concierge and Errand Association (which helps source a personal concierge close to your location). As Cole (2006) for WCBS TV reports, ‘Time is so precious, and this is a way to buy time’.3 Similarly, personal shoppers are available to provide advice on your fashion style and to help you buy clothes.

Seven strategies for higher revenues 75 Converting the pareto loss into a service that is chargeable provides the customer with choice. Sometimes, this conversion could even be free, rendered as a public service. For example, working mothers who hire nannies usually worry that they might not find a good one, or that the nanny might be negligent. HowsMyNanny.com is a service that provides extra peace of mind to parents who employ nannies. As its website reports, a small ‘license plate’ and a unique identifying number is attached to a child’s stroller or pram. Should a concerned citizen wish to report an ‘event’ to the child’s parents (whether a positive or negative incident), they could go to HowsMyNanny.com, key in that child’s unique license plate number, describe what they saw and the parent is notified via email. The reporting person could also choose to remain anonymous. Such a service, borne out of a ‘cost’ that parents bear from hiring nannies, could easily be chargeable but in this case is provided free of charge as a public service. So, whether the conversion of pareto loss is chargeable or otherwise, its conversion into a benefit or a reduction of outlays is an opportunity for service firms to add revenue to their existing business. The result is a win-win situation for both the buyer and seller. The explosion of pricing strategies of recent times has very much been technology-led. Technology has brought buyers closer than ever before to the

The Hong Kong International Airport at Chek Lap Kok provides a shuttle service for passengers, at a price. Passengers can easily walk to the boarding gates, but those who find this tiresome can opt for the buggy ride. Without this service, the walk to the gate is a non-monetary cost embedded within the pareto loss amount; the firm does not benefit from the walk and neither does the passenger. By providing such a service, the firm can convert the non-monetary cost into revenue and passengers, while not compelled to take the ride, now have a choice. Those for whom the walk is an outlay that is higher than the price of the buggy ride will certainly opt for the service. The others will walk.

Figure 4.2 Shuttle service at Hong Kong airport (source: Worldwide Flight Service).

76 The buyer as an individual firm; channels of purchase have increased tremendously over the past 20 years. Consequently, buyers can now purchase through a channel that is most conducive for them, i.e. the channel that gives them the greatest value. Since the expense in purchasing a product is both the price of the product as well as the cost of acquiring it, prices of products could differ from channel to channel, and the outlay (and hence value) held by the customer for a product or service would also vary between channels. Furthermore, the cost of acquisition includes the opportunity cost to the buyer as well. And since opportunity cost could also allude to risk and risk aversion, the permutations in pricing of a given service increases tremendously (see Figure 4.2). Box 4.1 From fair-trade to carbon neutral? Everywhere in the world, innovative companies are taking advantage of buyers’ non-monetary costs and providing services to reduce them. For example, with carbon emissions increasing and fuelling global warming, many people are seeking to minimise their ‘carbon footprint’; finding ways to save energy such as walking more and driving less. A colleague is so concerned about his carbon footprint that he avoids traveling by plane despite the plentiful cheap airfares to holiday destinations. To him, the non-monetary cost of traveling by plane (i.e. harm to the environment) is not worth it. Companies like www.plant-a-tree-today.org, www. co2balance.com and www.carbonfootprint.com sell carbon offsets, which enable people and organisations to reduce their carbon footprint. You can pay for these companies to plant a tree or buy carbon dioxide credits (the right to emit) and not use them, or donate to research in renewable energy. Such services also help to reduce the guilt. Will future airlines consider higher fares with a promise of carbon offsets? Will we see a ‘carbonneutral’ endorsement of companies whose carbon emissions are fully offset? Only time will tell.

Strategy 3: decouple purchase (exchange) and consumption Firms today constantly seek ways to differentiate their products. Marketing successes of highly differentiated products show that differentiation provides a way towards high revenue. Indeed, the market is proliferated with products differentiated across several product ‘spaces’. Services are no different in this respect. Even servicing a car can be differentiated according to the ‘full service’ or ‘express’, and charged accordingly. Cable television companies sell their services in different bundles according to market needs. A service that can only be sold at one time misses the opportunity to differentiate according to the time of purchase. Yet not all services can sell further in advance of consumption, or at least they have not found ways to do so. When buyers perceive that they will not have any risk of unavailability or that the con-

Seven strategies for higher revenues 77

Figure 4.3 An example of a service purchased in advance that may not be consumed (supplied and reproduced with permission of the Automobile Association Limited © The Automobile Association Limited [2007] All rights reserved).

sumption of the service is not time dependent, they will buy only when they wish to consume it. For example, buyers will clearly not buy any motor breakdown service in advance since they don’t know when they might need it (or if they need it at all). Yet they would clearly like to minimise the inconvenience of suffering a breakdown, should it happen. Firms can sell motor breakdown services at a fraction of the price (see Figure 4.3) which will benefit those who actually do experience a breakdown, but serve merely as an insurance amount to buyers who do not consume it. Yet, why would firms sell at such a low price? This is because when buyers’ non-consumption is high, the firm could actually (a) over-sell the service, i.e. sell to more buyers than the firm can actually service, OR (b) earn the revenue when buyers do not consume, and (c) sell the service at high spot prices to motivate the insurance purchase. The decoupling of purchase and consumption results in the firm’s ability to discriminate based on time of purchase (and therefore the heterogeneous trade-offs between buyers’ acquisition risk and valuation risk), and also allow for the re-selling of unconsumed capacity at spot. Notice that the better a firm is able to convince a buyer to buy in advance, the higher the firm is able to charge for spot prices. This strategy will be further elaborated on in Chapter 7, as sellers that are able to sell in advance would then be able to practise revenue management.

78 The buyer as an individual

Strategy 4: mitigate risk in valuation for advance purchase The advance purchase of service highlights a few issues that are critical to pricing in services. Some services are difficult for buyers to ascertain their ENV, such as those with a lengthy duration of consumption, and services that the buyer is uncertain of when they are required. For example, when you sign up for a phone line for your house, how would you know when you will need to call someone or receive a call? Yet, buyers get a phone line because the possibility of missing important calls or not being able to make a call is not acceptable. Someone who receives frequent calls would value the line more than another person who has a mobile phone and perhaps may not require a line in the house at all. Service firms will find that in such instances, the price obtained commensurates with the probability of needing the service and the consequence of not having it when the need arises. Firms can do well to help buyers mitigate the risk. Pay-as-you-go mobile services provide buyers with assurance that the service is available whenever needed, and at the same time they bring in additional revenue for the firm as the rates are often higher, i.e. firms charge for availability. The London Underground has a similar fee structure – pay a (higher) flat fee for unlimited use (within stipulated zones) of the network, or pay for each journey. This however requires the buyer to decide from the outset and calculate which tariff is most suitable. If they are uncertain about the number of journeys they are taking, which tariff should they choose? The Oyster card system takes away that risk. When journeys are few, a per-journey rate is charged. Once the ‘per-journey’ amount adds up to and surpasses the flat rate, the customer would be charged only the flat rate. Buyers are happier not to have to decide beforehand how much they would value the journeys (nor even do they need to think about it, which in itself is a huge benefit). Firms also benefit as often, buyers would not hesitate to increase usage of the service. Conversely, if buyers choose a ‘per-journey’ rate from the onset, they may hesitate to increase usage of the service since they have already committed to buying one journey and might either opt for alternatives and/or change their plans. The second aspect of risk is in the consequence. Buyers may choose not to buy a service in advance because of the probability of not consuming it. To alleviate such a risk, firms could provide greater flexibility. Providing a refund to buyers is one such strategy (see Box 4.2), or allowing the buyer the flexibility to consume on a different date. Remember that time is usually an attribute of the service that adds to its benefits. If the firm allows flexibility of consumption, the buyer may be more willing to buy in advance as his entitlement to use the service is not forfeited. Box 4.2 Gaining through differentiation Andrew is in a dilemma. His show is a sell-out, but customers come at the last minute and he has to turn away many at the door. He sells at £30 per ticket (all seats have the same view so he can’t differentiate between the seats) but he thinks he can get more since demand at spot seems to be

Seven strategies for higher revenues 79 greater than supply. However, he isn’t able to get customers to buy earlier. If he sells his tickets two months in advance, his customers want a discount and he isn’t willing to provide it since he is usually able to obtain a full house of 200 patrons at the £30 charged, come performance night. However, if he doubles his price, he’s afraid that demand will drop. What should he do? Andrew’s associate came up with the solution. He suggested that Andrew increase the price to £50 and sell two months in advance with not only a guarantee of a seat, but also with a full refund guarantee i.e. customers who cannot make the show will get their money back. This gives his customers assurance that they will have seats but if they are not able to make it, they will get a refund. Cassie was the first to buy such a ticket. She has been trying to catch the show for ages but every time she goes to the box office three days before a show, it is always sold out. She wouldn’t have minded paying more if it meant she would get to see the performance, but it was hard for her to buy in advance because she never knew until the last minute, if she could get a baby sitter. Now with the refund guarantee, she is happy to buy earlier. On the day of the performance, ten people did not turn up but Andrew was able to sell the seats for £80 at the door since almost 95 percent of his tickets were already sold in advance. All in all, Andrew obtained £50 for 190 seats and £80 for ten seats. And even though he had to refund a total of £500 to the ten customers who didn’t show up, it was still the highest revenue he had ever obtained! Andrew was able to differentiate between two types of tickets – those with a full refund and those without – and charge for the differentiation.

Buyers are usually willing to trade-off time of purchase with price. For example, a buyer may be willing to buy in advance if the price is lower. Many firms think that advanced selling means discounting when in actual fact, the prices charged by many firms at spot and in advance are a symptom of the underlying risks faced by buyers. Buyers want advanced discounts because (a) they have to part with their money earlier, and (b) they may not consume. However, some may be willing to pay higher to be assured of availability. Yet when these valuation risks are higher than acquisition risks, firms think that they always need to discount. The strategy is not to look at the discount but to mitigate the risks associated with advanced buying.

Strategy 5: change the benefits As early as 1951, Schumpeter said that wants cannot be taken as independent and buyers could be taught by producers to want new things, ‘or things which differ in some respect or other from those which they have been in the habit of

80

The buyer as an individual

using’.4 Hence, perceived benefits can be influenced, and not unchanging. Indeed, firms have been attempting to influence demand since the beginning of trade, through product differentiation. Differentiation was investigated by various early economics. Smith described product differentiation as a way to alter the shape of the price-quantity demand curve facing the firm.5 Hotelling showed how firms choose their ‘locations’ in the product space so as to buffer themselves from direct price competition6, while Chamberlin proposed that buyer perceptions of similar products differ, and whether the perceptions are real or imagined, such preferences led to different demand curves and could be a basis of firms’ attempts to differentiate between their products and those of the competitor.7 Porter, who popularised the notion of product differentiation, further elaborated on the practice, demonstrating that greater revenues can be obtained from differentiation as it increases cross-price inelasticities with respect to competing products.8 Since then, much of the benefits of product differentiation has been extolled and studied by numerous researchers in both economics and marketing streams. The ENV plays a huge role in differentiation. In Chapter 3, I showed that a high ENV may not compel a buyer to buy, particularly when the alternative is easily available and can offer a similarly high ENV. Firms endeavour to distinguish their services from their rivals on attributes that are ‘meaningful, relevant and valuable’ to buyers.9 In services, this may be more complex. This is because with some services such as a flight or a night’s stay at a hotel, the service experience could last a considerable length of time and are subjected to various influences. Consequently, the value attained by the buyer is multi-attribute, incorporating both the main attributes (e.g. one night’s sleep) as well as the peripheral attributes (e.g. check-in, facilities, etc.). Indeed, service literature has long acknowledged that buyers of services are often willing to pay for service augmentation such as supplemental services that complement and facilitate the core service.10 Lovelock and Wirtz (2003) classified supplemental services into eight categories; information, payment, billing, consultation, order-taking, hospitality, safekeeping and exceptions.11 With an augmented service experience that is multi-attribute in nature, it is therefore logical to conceive that a heterogeneous market of buyers would value such attributes differently and would be willing to pay different prices according to the different levels of service attained, e.g. business class vs economy class, cash vs credit card, etc. As many service firms operate with high fixed and low marginal costs, certain aspects of the augmented service can therefore be varied without much increase in costs, e.g. different channels of payment, in-room check-in, etc. Yet, simple variations in service delivery can sometimes lead to higher willingness-to-pay by buyers, i.e. they may be willing to pay higher prices if they don’t have to wait. The point of this discussion is that while it has been acknowledged that differentiation is able to influence demand, its practice is traditionally viewed as one that is both strategic and static. The firm decides on the attributes that are

Seven strategies for higher revenues 81 important to buyers, produces the product according to what has been specified, and prices according to the (differentiated) demand that unfolds. This is because changing attributes to dynamically influence demand for goods may be too costly or impossible to achieve. This may not be true for services. Consequently, the service buyer’s perception of benefits could be influenced through the firm’s manipulation of its service attributes, as the costs in producing such variations of the service may be low while the corresponding increase in buyers’ perception of benefits is high. For example, in providing breakdown insurance, having ‘home start’ as an option (i.e. not being able to start your car from your own home) increases the benefit of the breakdown insurance. The cost of the breakdown service provision is much the same as before i.e. a breakdown is a breakdown, whether at home or on a highway. With current technological advances, such service differentiation practices are becoming increasingly easy and dynamic.12 Accordingly, selling on the internet may be effective not only because it is a low-cost channel for firms13, but also because it lowers the effort costs of buyers, who may be willing to pay higher for purchases through the internet. In fact, the very act of requiring buyers to be present at the consumption of a service would already guarantee that the service consumed is a differentiated one. Since services are inconsistently produced (heterogeneous), it is logical that the consumption of the same service by two customers will be perceived differently, even without the firm’s effort to differentiate. In addition, by having to show up to consume, the price that heterogeneous buyers pay for a service is not the only cost they bear. Non-monetary costs (such as effort) expended by the buyer during both purchase and consumption influences the buyer’s valuation of the service. Hence, even if all buyers buy at the same price, the final ‘price’ paid is different among buyers since they have different time and effort costs. Moreover, services are experiential products, and often a simple change can alter the buyer’s value perceptions. Hence when services, assisted by technology, are able to change their attributes relatively easily, customisation strategies result in the firm’s ability to dynamically (and almost instantly) modify its service offering in response to buyers’ demands. For example, buyers may be willing to purchase a ticket at a higher price if the ticket can be made more flexible in terms of the time of travel (‘open’ ticket). Yet, the marginal cost of providing flexibility (i.e. differentiation) could be lower than the marginal increase in revenue due to a higher valuation by the buyer. In other words, firms have another avenue to improve revenues, i.e. changing buyers’ perception of the benefits so that a higher price can be obtained. When benefits are seen to be unchangeable, firms get stuck in a myopic rut and end up not fully understanding what their product is all about.

Strategy 6: customer effort could yield higher revenue Buyers are not static in their evaluation of value and benefit. They are able to change their surroundings, or modify their situation so that the benefit obtained

82 The buyer as an individual is higher. Firms could assist customers in managing their situation. This could be as simple as giving customers something to do while waiting, e.g. free internet service at airports, self check-in counters or even magazines in waiting rooms. Providing information on what the doctor will be doing could help appease the mind of a patient. Setting out expectations and providing a schedule of deadlines could help students cope with the stress and time pressures of their studies. The relationship between the customer and producer is changing, particularly in services. The customer is no longer seen as a passive receiver, but as an active and knowledgeable participant in a common process. Specifically, customers are supported by some companies so that they can create their own value. In this way, customers are becoming ‘co-producers’. The role of customer effort is still new in service research. Yet customer effort can be a powerful tool for price discrimination and segmentation. Fuel stations could charge higher per litre for full service and less for self-service, allowing some cost savings in producing the service to be passed on to the customer. Would we be prepared to pay less if we had to do more? Perhaps for some, but certainly not for everyone – hence allowing the firm to achieve greater revenues when customers self-select. There is a danger in believing that firms should automatically lower their prices when customers have to put in more effort. Often, firms are surprised to find that the control and independence given to the customer in self-service is worth more, and buyers may actually be willing to pay higher (see Figure 4.4).

Figure 4.4 Sushi on a conveyor belt: customers may create the best value for themselves when they put in the effort to serve themselves.

Seven strategies for higher revenues 83 Customer effort could add value to other customers by co-creating the service with the firm. For instance, customers of Amazon.com provide an online review of the books they have read so that others looking to buy those books will benefit from their comments. Sites with discussion forums and blogs such as Myspace or Youtube allow their customers to be part of the service rendered.

Box 4.3 Involving the customer Companies such as Volvo and BMW offer thousands of options for customers, even down to the finance and insurance schemes. The customer gets to ‘design’ the car on the computer screen, including all the options they want, and then the car is built as ordered. IKEA is also in the service of mass customisation, notably in kitchen design, whereby customers can ‘design’ their kitchens on computer screens and then order it as ‘their’ kitchen, rather than as a standard layout/design. IKEA is even extending this process to individual items of furniture, so that customers can choose fabrics, colours, etc. For the customer, this individualisation reduces risk. For the producer however, it means the need for a flexible production line that is able to produce what is designed as a one-off, and to do so at a competitive cost. But crucially, it also means that the company has to have the right organisational structure and communications channels. From mobile phones to ATMs and internet access, buyers can do things which they could not do before. Wikström argues that: ‘The examples of company–customer interaction and adaptation at the different stages in the overall value-creation process, means in reality that the actors are expanding their traditional roles . . .. This seems to hold true irrespective of what is being created; generally a tangible product or an intangible service’ (p. 370). This process helps customers by making it easier for them to achieve more value, and helps companies who are then able to service their customers in a more efficient way. But Wikstrom believes that there is another advantage, namely the production of generative knowledge. To maximise the impact of this however, organisations need front-line staff who can feed it back most effectively into the organisation. Source: Wikström, S. (1996) ‘Value Creation by Company–Consumer Interaction’, Journal of Marketing Management, 12 (5), pp. 359–374.

Co-creation of a service may lead to a lowering of the firm’s cost as well as the customer’s, or it might not. Opting for customisation when the firm isn’t flexible enough to do it may lead to excessive costs and lower profits. Yet, for some services, the core service has to be a co-creation. For example, the core service offered by a university is a learning experience that is the cocreation of the people within the establishment, i.e. between students, students and teachers, students and administrators, etc. The co-creation of the core

84

The buyer as an individual

service implies that the value is emergent, unstructured, interactive, uncertain and with a hedonic dimension. Furthermore, the co-creation of the core service is too elusive to be captured through systems and processes, and would require accountability by students as well as teachers. Accordingly, students’ expectations should be two-fold: that of the deliverables by the institution (facilities, teaching, support) and the deliverables by themselves (learning, taking exams, understanding) (see Box 4.4).

Box 4.4 University – a co-created service The core service of the university experience is embodied in the learning experience of the student. However, it is important to realize that the learning experience can be mundane and monotonous just as much as it can be a transformative experience. This is because the value of learning is co-created with the student.14 As Bitner et al. (1997) states, ‘service customers themselves have vital roles to play in creating service outcomes and ultimately enhancing or detracting from their own satisfaction and the value received’.15 In co-creating the learning experience, students play two key roles in creating a service outcome i.e. as a productive resource, and as a contributor to quality, satisfaction and value.16 As a productive resource, students bring in their intellect, language and communication skills. A more ‘resource-rich’ student requires less supervision, has greater independence

Figure 4.5 Communicating the value of a university degree.

Seven strategies for higher revenues 85 and confidence. As a contributor to quality, satisfaction and value, students can choose the level of effort they wish to expend. Without students’ participation and involvement, the desired process and outcome for the student is not possible.17 It is important to understand that these two roles are not mutually exclusive and elements of each role may exist in every incident through the course of the learning experience. Bok (2006) makes a similar point in his criticism of the university system for not exploring more innovative methods of actively engaging students in the learning process, and adequately assessing their progress.18 As a result of the co-creation of value, the satisfaction of the learning experience is attributed to both the university and the student (see Figure 4.5). Service research has found that consumers in co-created services sometimes blame themselves if problems occur while other times they may feel that the organization is responsible and could have done something to avoid the problem.19 Source: Ng, I.C.L. and Forbes, J. (2006) ‘Education as Service: The Understanding of University Experience through the Service Logic’, Proceedings of the 9th International Research Seminar in Services Management, 30 May–2 June 2006, La Londe, France.

How does customer effort play a role in pricing? As noted in Box 4.4, customers have two roles when participating in a service. First, the customer could be a productive resource. Carrying your own bags at the airport and checking in yourself for the flight are examples where customers perform the role of ‘partial employees’. Second, customers are contributors to service quality and satisfaction by (a) allowing customer control (b) believing that the way they do it for themselves would enhance their service experience (as they know best what they’d like). By doing so, the firm could charge more or at the very least, enable the provision of better service. Yet, if the customer perceives that the effort is not worth the value enhancements and thus an increase in price, there would be no additional revenue. Firms would therefore need to understand the role of customer effort i.e. one that creates and enhances value for the customer instead of obtaining savings in cost. Hence, even though customer effort could result in lower cost of selling and delivering the service, the cost savings should not be the primary motivation. To improve on revenue, allowing the customer to enhance his own service experience by reducing risk and giving control (or reducing other non-monetary costs) should be the motivation.

Strategy 7: find the highest end-value in intermediating services Within the service economy, intermediating services are beginning to play very important roles. These services add value to the exchange relationship between at least two parties, often using new technologies.20 Internet service providers, smart

86

The buyer as an individual

card payment systems and other electronic data interchange services (e.g. ecommerce systems) are some examples of intermediating services. In the postinternet economy, it is becoming apparent that the disintermediation (i.e. eliminating the middlemen) created by the internet has evolved into a ‘reintermediation’ of sorts where the role of the intermediary changes into that of knowledge and information coordination, a function that is becoming predominantly fulfilled through electronic means.21 With greater technological innovation, intermediating services are appearing with increasing frequency and it is necessary to understand the characteristics of such services as they have the potential to drastically alter the product exchange process in terms of distribution, perceived value and consumer empowerment. First, it is important to note that the purchase of an intermediating service is often in advance. This means that buyers whom buy the service either through a subscription or through a per-transaction fee would be contracting to buy the service without being certain of when they would be consuming it and without being certain how often they will need it. Even if buyers choose to pay according to usage and not based on subscription, that decision needs to be made in advance and usually preclude the possibility of changing their minds. Hence, buyers face uncertainty in both the time of consumption and the volume of consumption, which makes their utility state dependent. Second, the primary product or service creates a derived effect. This means that the intermediating service is a means towards an end i.e. the primary product or service is that end. Where the need from the purchase of the primary product is so high that the buyer is willing to pay for both the primary product and the intermediating service, the firm could get a higher price for the service and the buyer would still purchase both.22 Thus, the higher the value of the primary product, the larger the value placed on the intermediating service and the more the buyer is willing to pay. This derived effect can therefore persuade buyers to pay higher for the intermediating service. Fundamo, a mobile payment service, is a typical intermediating service that allows person-to-person payments or payment from a person to a retailer through a mobile phone. Onmobile, an m-commerce solution provider allows an individual to conduct auctions, buy tickets or shop through a PDA phone (see Figure 4.6). How much should Fundamo and Onmobile charge for their services? How should its revenue model look like if its value is tied to the endproduct/service? Similarly, sites like which.co.uk or whatcar.co.uk are services that add value to the purchase of other items such as cars, houses or insurances and the value of the information to assist in search, comparison and decision making may be worthwhile because of the value attached to the end-product/service. As an analogy, the most common intermediating product is money. Through money, buyers buy services that provide higher value than mere cash (think of how much you’d value a dinner at your favourite restaurant vs the £40 cash equivalent). This is because the dinner invokes ‘images’ or ‘mental pictures’ that trigger emotional responses resulting in greater enjoyment and value.23 Intermediating services are therefore placed in the same position as money. Firms that understand the value attached to the final product will be able to derive higher revenue from strategically pricing their intermediating service.

Seven strategies for higher revenues 87

Figure 4.6 How would you value an intermediating service? (Source: www. OnMobile.com).

Technology as an intermediating service may be recent but intermediating services have been around for sometime, without many noticing it. Retailing services are the most typical. Although we may enjoy the visual displays at the windows of Selfridges on Oxford Street, Saks Fifth Avenue or shopping entertainment at Harrods at Knightsbridge, we don’t pay for them. Goods are placed tastefully for us to browse and choose, and information, wrapping and sometimes even parking is free. Yet we do indirectly pay for such retail therapy – through the goods we buy. We pay a higher price if we obtained the good from a high street store than if we obtained it from a discount store because the high street store provides the service and the shopping experience. Hence, retail services have great similarities to technological intermediating services such as the internet and mobile telephony. Retail services have therefore long understood the strategy of attaching the value of the service to the purchase of the end-product.

Conclusion The profitability of the firm depends not merely on one buyer, but many (unless you count space tourism where so far there have been only five buyers.24) Hence the behaviour of buyers in aggregate i.e. demand, is essential in the pricing decision of the firm; we will discuss this in the next three chapters that form Part II of this book.

Part II

Buyers in aggregate

5

The economics of pricing in services

How do we go from one buyer to many buyers? Recall that each buyer has a level of willingness to outlay. Embedded within the outlay is the price charged by the firm. Economists are usually only interested in the buyer’s willingness to pay. For a normal good or service, there would be less people willing to pay a higher price. Hence, if you accumulate the number of people willing to pay for a good or service at each price point, the number of people willing to pay at that price point (demand) should increase with a reduction in price. For example, in Figure 5.1(a), there might be just one buyer willing to buy at P1. If the firm lowers its price to P2, there might be another buyer so there would be two buyers who would buy at P2. If you take it to the limit (i.e. there exist dots that are very close together), it becomes a continuous line, which makes up a downward sloping demand function. This is of course the most simplistic characterisation of demand for most consumer goods and services. In reality, for different goods and services, demand functions may or may not exist, and even if they do, may not be downward sloping, linear or continuous. However, for our purposes here, I will stay with the traditional and simplest form – that of the downward sloping demand function.

The demand function The demand function exists due to a few assumptions. First, there must be many buyers in the market, and each buyer must believe that he is not able to influence the price in any way. This means that the buyer is a price taker, and his decision is merely to buy or not to buy i.e. take it or leave it. Using the original example of the demand function, what this means is that if the firm moves its price from P2 to P1, one buyer ‘drops off’, i.e. they leave because they are not willing to pay that price. This inverse relationship is the law of demand. Second, the relationship between price and quantity assumes that all other factors are constant. From the preceding chapters in Part 1, we know that the firm can reduce buyers’ non-monetary costs. In this case, the demand function shifts to the right, from D1 to D2 as illustrated in Figure 5.1(b). Buyers willing to buy at P2, are suddenly willing to pay higher and the firm could price at P3, thereby maintaining the number of buyers and increasing revenue. Alternatively,

92 Buyers in aggregate Price

(a)

Price

(b)

P3

P1 P2

P2

D1 1 2

Quantity demanded

2

D2

4 Quantity demanded

Figure 5.1 Demand function.

the firm could keep the price at P2, and sell to double the number of buyers. For instance, a popular beauty salon that decides to offer valet parking (hence reducing buyers’ non-monetary costs of having to look for parking space in a busy area) could either raise prices by charging a premium rate for its services, or it could maintain its pricing to attract more customers with its valet service. The decision of whether to increase price or to expand demand depends on whether the total revenue from P3  2 buyers, is higher or lower than P2  4 buyers, i.e. which is bigger. This is represented by the narrow rectangle area under P3, and the wider rectangle area under P2, respectively. This example illustrates a very important point. At an individual level, one could discuss about how much a buyer is willing to pay and the price to charge, if possible, would be the highest price the buyer is willing to pay. Yet, when we discuss buyers in aggregate, we look not only at their willingness to pay but also at the differences in their willingness to pay. We look at how many of such buyers there are at each price level, which in turn leads to the firm having to choose which price is ideal. Since very few firms can charge each buyer a different price (we will get to that discussion later), the firm has to choose a price that balances the number of buyers with the price they are paying. Inevitably, this would lead to buyers who are willing to pay more actually paying less, because the firm may prefer to have a higher quantity of buyers albeit at a lower price, so that total revenue is high. Figure 5.2(a) shows that if the firm prices at P4, the buyers less than q who could have paid more (higher willingness to pay), actually paid a lower price, hence resulting in the firm losing potential revenue equivalent to the triangular area above P4. This area is termed the consumer surplus. The firm would clearly choose to sell at a price where the rectangle (q  P4) is at the highest on the demand curve, thereby maximising the total revenue. In doing so, revenue is lost through consumer surplus given back to the buyer. To economists, consumer surplus is a measure of welfare in a society and the objective is often to engineer a system whereby welfare is at the highest

The economics of pricing in services 93 Price

(a)

Price

(b)

P4 P3 P2 P1

P4

D1

0

q

Quantity demanded

Quantity demanded

Figure 5.2 Consumer surplus.

level. In contrast, a pricing strategist aims to extract all consumers’ surpluses, if possible, to maximise revenue. Firms constantly endeavour to do that – through differentiation and price discrimination. This brings us to the third assumption of the demand function – that all buyers must have the same information (and perception) about the quality and availability of the good or service, i.e. all buyers perceive the good or service the same way. Otherwise, the same good or service could be sold at a variety of prices. This is precisely the case for services. Not all buyers of services often perceive a service in the same way and indeed, it is in the firm’s interest that they don’t. For instance, buying a service without having to wait is almost like buying a different service. Indeed, even when a firm is selling the same service e.g. a flight from London to New York, it is able to sell the seats at very different prices because different buyers consider the same service to be different; it is a difference created intentionally by the firm. Thus, in Figure 5.2(b), a firm could sell at P1 to advanced buyers, at P2 to last-minute buyers, at P3 to buyers who want a one-year validity for their return ticket, and at P4 to a buyer who wants a fully refundable ticket if they cannot make the flight. And all these buyers could be on the same flight, i.e. the same service!

Understanding price elasticity (ED) The price elasticity of demand measures the sensitivity of the quantity demanded, to changes in the price. Demand is inelastic if it does not respond much to changes in price, and elastic if it does. Firms are always keen to know the elasticity of demand, because how much demand changes due to any changes in price would have an impact on profitability. The price elasticity of demand is calculated in the following manner: % change in quantity demanded Q/Q ED =  =  % change in price P/P

94 Buyers in aggregate Demand is elastic because of customers’ sensitivity to price. What causes this sensitivity? The list below highlights the factors that affect elasticity of demand. •

•

•

•

•

•

•

Availability of substitutes. Clearly, if there are many substitutes in the market, demand would be rather elastic, i.e. a slight change in price would result in a bigger change in demand. If there are only very few substitutes, the firm enjoys inelastic demand, i.e. only a slight change in demand following a change in price. Taking the lessons in Part I of this book, it is in the firm’s interest to differentiate its product or service to the extent that elasticity of demand is very low, i.e. buyers do not wish to switch to an alternative because they perceive the service to be different from the competition. For instance, a bookstore differentiates itself from other bookstores by specialising in first editions, and therefore experience less elasticity in demand for its products. The degree of necessity is also a factor influencing elasticity, e.g. demand for luxury services like cosmetic surgery are usually more elastic than a service that is considered necessary, such as dental services. Habitual services. The more the customer finds that a service has become habit, the less elastic its demand is, e.g. tanning salons, beauty spas, taxi services. Proportion of the income spent on the service. The larger the portion of income spent on a service, the larger the elasticity, eg a tour package/travel destination for a family holiday. Time span in the purchase/consumption of the service. When a power or utility supplier increases its price, the demand would be rather inelastic because buyers are in great need for the utility service. However, over the long run, buyers could adjust and switch to cheaper providers, so demand elasticity over the long run would be higher. Price points are important in the purchase of services as they are in goods – a price drop from £2 to £1.80 may result in a different effect on demand, compared to a reduction from £1.80 to £1.60. Short-term price changes. A change in price due to a promotion exercise may result in a different impact on demand than if the price change was effected over time. For instance, offering a one-week ‘buy one meal get another free’ promotion may bring in more customers to a restaurant for that period, but may not necessarily result in higher demand for the restaurant over the long term compared to if it brings down its prices permanently for select items on the menu.

Another important concept in price elasticity is the cross elasticity of demand, which measures the sensitivity of the quantity demanded, to changes in the price of a related product. This means that if a competitive product increases its price, buyers may shift over to the firm’s product, thus increasing demand. Therefore, if a coach service decides to raise prices for its inter-city bus routes, nationwide buyers may opt to shift over to another coach service or even to rail services if their ticket prices end up being cheaper after their competitor’s price hike.

The economics of pricing in services 95 Weaknesses in the demand function However, the demand function is not very practical because it assumes a linear relationship between price and quantity which is too simplistic, and often leads the tendency to overrate the importance of price as a principle determinant of quantity. There are many other factors that could result in a change in demand function. For example, additional advertising and increasing distribution and promotional activities would shift the demand function. Other uncontrollable factors – such as competitors’ activities, new entrants to the market or the availability of substitutes and activities of channel members – can affect attitude towards price and willingness to pay. In addition, as was illustrated in Part I of the book, the buyer’s willingness to pay is part of his/her willingness to outlay, so if the firm is able to reduce overall outlays, the buyer may be willing to pay more which may translate to a shift in the demand curve. Finally, the demand function could exist due to social influence and may not be continuous as Becker (1991) has shown (see Box 5.1)

Box 5.1 Social influence on price When a service or a good experiences consumer demand that is in excess of supply, the firm has the opportunity to increase prices in order to maximise profits. In certain situations however, the firm chooses not to do so, and this pricing behaviour could be due to the influence of social interactions. Certain services or goods – such as a play, a sports event, a restaurant dining experience, a book club, a concert, or a movie – involve social activities where people consume the product or service together and partly in public. Becker (1991) noted that demand by a typical consumer for such services depends on the quantities demanded by other consumers.1 More specifically, a consumer may demand for a service or product when many others also do so. Therefore, the more popular a good or service is, the greater the consumer demand for it. This could be due to the fact that the consumer may want to remain ‘trendy’ or in step with what’s popular, or perhaps consumers’ confidence in a good or service is greater when that service or good is more popular. Hence, demand for a popular restaurant, play or sporting event may well persistently exceed that of its supply; there are constantly long queues at the entrances of the restaurant, theatre or stadium. The obvious action would be to raise prices in order to reduce the queue but expand profits. However, instead of doing so, the firms ration demand instead. Why is this so? Becker found that after a maximum set price, demand becomes discontinuous for further price increases, and can fall to zero even for minor increases. This could be tied to the fickleness of consumer

96 Buyers in aggregate demand, which can also be explained by the influence of social interactions. When a consumer demands a service or good because it is popular with other consumers, and not because he or she has a real need for it, the demand is fickle. Hence, this also makes it easier for a service or good to go from being ‘in’ (i.e. popular) to being ‘out’ than from ‘out’ to ‘in’. Similarly, the firm also chooses not to expand output to close the gap between the excess demand and the available supply or capacity, because it recognises the fickleness of consumer demand; any expansion of capacity that cannot be sustained by demand can have adverse effects on a booming firm, i.e. financial difficulties and bankruptcy. Also, by narrowing the gap between supply and demand, firms may be unable to charge the optimal price available to them. Becker further contends that the demand-supply gap can also affect demand when consumers get utility from competing for goods that are not available to everyone who wants them, or when they obtain utility from the camaraderie on a queue itself. Source: adapted from Becker, G. S. (1991) ‘A Note on Restaurant Pricing and Other Examples of Social Influences on Price. Journal of Political Economy. 99 (5), pp. 1109–1116.

In a sense, the demand function could be counter-productive in helping firms – managers may believe its seemingly robust nature and make pricing decisions on the basis of price-quantity relationships, when a better strategy is to change the demand function itself. However, despite the fact that most goods and services in the world do not conform fully to the assumptions of the demand function, it still works as a useful tool as it is able to capture both the heterogeneity of buyers (different willingness to pay) as well as their aggregate sensitivity to demand (i.e. the number of buyers that would ‘drop off’ for a unit change in price). Hence, unless a better analytical tool is made available, this seems to be as good as it gets.

The role of supply and capacity So far, I have not talked about supply. There is a reason for this. Whilst there is a law of demand, there isn’t a law of supply. The seller is certainly not a price taker and since the seller is able to choose the quantity it wishes to sell, the supply curve would not exist. How much of a service then, would a firm wish to sell? This decision is based on marginal analysis. Box 5.1 provides a definition of three revenue functions. It is important to remember that many services operate with high fixed and low variable costs. Hence, the ‘cost’ to produce one unit of capacity (whether it is a seat on a flight, a hotel room, or a theatre ticket) within its available capacity, is close to zero. The decision of how much to price is dependent on marginal revenue, and conventional wisdom states that the firm should sell its service at

The economics of pricing in services 97 Box 5.2 Definition of three revenue functions • • •

Total revenue (TR) is the price of the service multiplied by the quantity sold. Average revenue (AR) is the total revenue divided by the quantity sold, i.e. price. Marginal revenue (MR) is the increase to the total revenue by selling one extra unit of the service.

the point where marginal revenue is equal to marginal cost. This means that the increase in total revenue as a result of any drop in price (for the sake of higher quantity) i.e. marginal revenue, must be equal to the increase in the total cost of producing that quantity of service i.e. marginal costs. Since much of the costs to deliver the service are already committed (i.e. sunk), there is often a negligible increase in the costs for producing an additional unit of service capacity. Hence, the price should be set where marginal revenue is zero. Table 5.1 illustrates the concept of marginal revenue. Clearly the theatre should lower its price to £20 because marginal revenue is positive. However, it should not reduce its price to £15 because marginal revenue is below zero. Figure 5.3 is a more formal treatment of revenue. Notice that the firm should continue to lower its price until P (which is when marginal revenue is zero) so that total revenue is maximised. In selling services, the firm also has to be mindful of an important attribute of services – capacity constraint. Services often operate on short-term capacity constraint, e.g. the number of cases a legal firm can handle, the number of passengers an aircraft can seat, or the number of tables in a restaurant. Figure 5.4 shows a demand function for a firm with capacity constraints. Let’s start with a firm that has a capacity of K2. If the profit-maximising price and quantity is at P* and Q* and the firm sets its price at P*, it will only obtain K2 and will need to turn away Q* – K2 customers. Clearly, that’s not ideal and the firm could easily price at P1 and get more revenue from the capacity. Even at P1, it is not the highest total revenue the firm could obtain from the market because if it had more capacity, it could then obtain the actual optimal revenue. This is why economists like to make the assumption of no capacity constraints – it brings to light the highest revenue obtainable. Table 5.1 Demand and marginal revenue for theatre tickets Price

Quantity

Marginal Revenue

£30 £20 £15

100 160 210

(Increase of) £200 (Reduction of) £50

98 Buyers in aggregate

Price/revenue

Total revenue

Average revenue

P*

Marginal revenue

Quantity demanded

Figure 5.3 Revenue functions.

Price

P1 P* P2

0

K2

Q*

K1

Quantity demanded

Figure 5.4 Demand function of a firm with capacity constraints.

What if the firm has a capacity of K1? Conventional economic wisdom suggests that the firm should not sell to fill capacity, i.e. at P2, since that is less optimal than selling at P1; total revenue is lower. The appropriate strategy then, is to sell at P1 and waste the unutilised capacity. Yet, many service firms do not do that. Instead, they rely on differentiated perceptions, and price discriminate to fill capacity. However, service firms do keep unused capacity as it does have a strategic purpose (see Box 5.3).

The economics of pricing in services 99 Box 5.3 The strategic use of unused service capacity Capacity of service firms has to be managed to consistently achieve maximum and/or optimum utilisation and to improve business performance; i.e. increasing sales or improved margins. Current literature prescribes two ways of coping with supply and demand imbalances. Firms can deal with excess or idle capacity by either (1) managing supply to fit demand, e.g., reducing a firm’s manpower costs, schedule the service so as to match the peaks and the troughs, taking on sub-contracted jobs; or (2) managing demand to fit supply, e.g., offering discounts, lowering prices, diversify to segments where demand is less fluctuating. Or they can choose to stay with a fixed capacity that is capable of handling peak business. However, Ng, Wirtz and Lee (1999)2, prescribed 7 capacities used by service firms in such a way that unused capacity could be put to use in a more strategic manner to improve business performance. Seven capacity strategies 1 Capacity for customer development. Unused capacity can be utilised to develop customer loyalty; i.e. hotels giving free room nights to their regular patrons. The benefits: it may (a) increase sales by encouraging further purchases; (b) trigger an emotional response in the customer that he attaches a higher value to similar future rewards; (c) cause the customer to perceive that he has received a greater loyalty benefit3; and (d) be more cost-efficient compared to other loyalty rewards that may need to be purchased. Unused capacity can also be used to provide free trials to develop new customers; trials enable potential customers to experience the service before making a purchase decision. Using idle capacity as trials can also help develop distribution channel relationships, i.e. inviting travel agents on free ‘familiarisation trips’ to new destinations can help amplify their ability to sell them in their home markets. 2 Capacity for bundling Employing unused capacity to practice bundling (the offer of two or more services, at a package or discounted price) can help service firms to: (a) provide better service value, as bundled services help reduce customers’ search costs with a convenient ‘one-stop shop’; (b) increase demand by creating a new ‘bundled’ product from two existing ones, and hence attracting customers who would have bought only one product, to both. Bundling also provides opportunities to attract customers to ‘trade-up’ to higher-priced bundles, and with discounts provided through bundling, raises customers’ switching costs and reduce their motivation to try a service elsewhere4; (c) reduce selling risk, as bundling provides services like airlines with a discrimination tool to lower prices and target a segmented market willing to buy the service in advance;

100

Buyers in aggregate

(d) reduce marketing costs and provide scope economies, as most service firms have a high level of cost sharing5 and hence, marginal costs of selling additional services (through bundling) are lower than the total cost6; and (e) obscure hefty discounts provided through the cross-selling of unused capacity to obtain a larger market share. This is commonly practiced by multi-service firms. 3 Capacity for employee endowment. Unused capacity can be utilised in employee endowment programmes to increase staff motivation, loyalty and commitment. Commonly practiced by cruise lines, hotels and airlines, such endowment policies which provide free or discounted services to staff and family/friends, can help lower staff turnover. This in turn reduces learning curve effects, and hence contributes to better service performance. 4 Capacity for exchanging. Using idle capacity to participate in some form of exchange allows service firms to: (a) reduce costs, by bartering capacity for advertisement space in print media, promotional campaigns, and in some cases, even for entertainment expenses; (b) extend their product range, i.e. airlines barter capacity through code-share agreements that allow them to increase their number of flights and offer more destinations; and (c) improve revenue by facilitating yield management. This could be in the form of airlines exchanging future or alternative capacity (at a discount) to free up existing capacity for customers who are willing to pay more (i.e. ‘voluntary bumping’); or for hotels that overbook, by providing some of one hotel’s capacity for the other overbooked hotel in exchange for a portion of the latter’s capacity should the same problem arise with the former hotel. 5 Capacity for pledging The unique characteristics of services can compound the difficulties in building a meaningful relationship between firms and their intermediaries. Unused capacity can be pledged as a strategy to build channel relationships. Airlines and hotels for instance, often pledge some of their capacity to channel intermediaries as a form of commitment to the relationship, in exchange for specific displays of commitment to the supplier. This also helps reduce potential opportunism that can arise from conflicts between service firms and their intermediaries. 6 Capacity for entry deterrence. Capacity can be expanded to deter new entrants into an industry, and also to dissuade existing firms from entering a particular market segment. Incumbents can increase capacity with lower marginal costs, enabling it to lower prices.7 In doing so, the incumbent signals its capability of constantly increasing outputs to lower prices to a level where it may not be commercially viable for potential new entrants to enter the market.8 Using capacity to deter new entrants is said to be most effective in industries characterised by high fixed costs, large economies of scale and high producer concentration, like hotels and airlines.9

The economics of pricing in services 101 7 Capacity for differentiation. Unused capacity can be used to enhance service quality, and hence allow the firm to differentiate itself on that level. Due to the inseparability of services, other customers can directly affect a customer’s evaluation of a service.10 Also, research shows that waiting for service negatively affects customers’ evaluation of a service.11 Keeping some capacity idle enables firms to ensure that customers enjoy greater comfort when consuming a service, and to provide improved customer satisfaction through lower waiting times. These proactive strategies utilise capacity itself as a strategic resource to improve business performance and is particularly advantageous for small and medium service enterprises, where resource constraints are a major obstacle in developing their businesses. Source: adapted from Ng, I.C.L., Wirtz, J. and Lee, K.S. (1999) ‘The Strategic Role of Unused Service Capacity’, International Journal of Service Industry Management, 10 (2), pp. 211–238.

Price discrimination Price discrimination, despite its negative connotation, only means charging different buyers different prices. The firm is able to do this if it is able to effectively segment its market and charge each segment a different price. Here follows the three most common price discrimination practices. 1 First-degree price discrimination This is as illustrated in Figure 5.2 (b), where buyers from the same market could be charged different prices because of their different willingness to pay. In this practice, buyers have their consumer surplus taken from them, and firms do not need to lower their price for higher quantities. This often happens when bargaining is allowed e.g. negotiating to buy a second-hand car, or in the bid-and-offer system used in the sale of real estate. The internet has made this sort of price discrimination possible even amongst a large number of buyers, e.g. Dutch auctions on eBay. In a Dutch auction (name derived from the process used in Holland to bid for tulips), the buyer makes a bid on what they would pay for the product and how many shares they would like. This system compels the buyer to reveal what they are willing to pay for the product – any less and the buyer will be annoyed they do not get it as they could have paid more, and any more and the buyer would be unwilling to pay for it. The best strategy for the buyer therefore is to bid exactly what they are willing to pay, thereby allowing the firm to extract all the surpluses from the buyers (see Box 5.4). Google, in its IPO (Initial Public Offering), used a modified Dutch auction to sell its shares.

102

Buyers in aggregate

Box 5.4 Illustration of a Dutch auction Assuming that an individual has ten units of a rare coin that they are looking to sell through a Dutch auction. They open their auction with a maximum price of £200 per coin. Buyers would enter their bids at the prices they are willing to pay and the quantities they want. While the seller hopes to sell all ten coins at their maximum price of £200, there are no bids at this level. Hence, the seller lowers their price until they receive a bid; in this case, to £180 which is the price that Bidder A bids for one coin. Subsequently, more bids come in (see Table 5.2). Bids will be filled from the highest price until all ten coins are sold. However, the coins are sold at a single price to all bidders; the auction will clear at the final price at which all ten coins would have been sold, which is £100. Hence, Bidders A, B, C and D would have purchased their coins at prices lower than their bid prices.

2 Second-degree price discrimination This form of price discrimination implies that firms are not able to tell the difference between the different types of buyers. The most common variable is quantity, where firms will provide incentives for buyers to select themselves into two segments; those who wish to buy more (e.g. through quantity discounts or non-linear pricing), or those who prefer to buy less but pay higher unit costs. Similarly, effort is another variable where buyers could choose between selfservice or full-service options, with the latter being more expensive. Seconddegree price discrimination allows the supplier to set different prices for the different groups, and capture a larger portion of the total market surplus. This is Table 5.2 Dutch auction: the bidding process Bidder

Price (£)

No of coins bid

No of coins won

Final price paid by bidder(s) (£)

A B C D E F G H I

180 160 140 120 100 80 60 50 40

1 1 2 5 3 5 2 6 1

1 1 2 5 1* 0 0 0 0

100 100 100 100 100 0 0 0 0

Note * Bidder E only receives one coin although they bid for three, as there is only one coin remaining after Bidders A, B, C and D claim their coins.

The economics of pricing in services 103

Figure 5.5 Price discrimination when buyers’ preferences are not known.

the sort of price discrimination highlighted in Strategy 4 in Chapter 4. In the Figure 5.5, a firm may not be able to tell who might be a higher consumer of Herbal Bath, but providing a discount for purchasing two bottles not only stimulates demand but also allows the market to reveal the truth about their consumption. 3 Third-degree price discrimination This is the most frequent form of price discrimination, and involves charging different prices for the same product in different segments of the market. The market could be separated by time, or by location (e.g. different prices for different buyers from different countries). For example, charging cheap weekend rates for telephone calls, advanced selling of hotel rooms and charging overseas students higher fees would all constitute third-degree price discrimination (see Figure 5.6). This type of price discrimination aims to sell more capacity in a market where elasticity of demand is high, and extract more consumer surplus from buyers in another market where the price elasticity could be lower. For example, weekday calls during working hours are priced higher (low elasticity of demand) whilst weekend calls are priced lower to take advantage of higher demand elasticity. Price discrimination is very important for services, as it is the very foundation upon which revenue management is based, a topic discussed in the next chapter.

104

Buyers in aggregate

Figure 5.6 Third degree price discrimination (source: www.CartoonStock.com).

Advanced selling, demand and price discrimination The most common price discrimination tool used in services is to discriminate on the time of purchase. As Chapter 3 has shown, there is a separation in the purchase and consumption of services, and many such as airlines and hotels charge different prices according to when buyers buy in advance. For instance, when selling a route that is popular with business travellers, an airline may offer a lower price for bookings made more than a month in advance. It then raises the price for tickets bought at the last minute, because it is aware that business travellers, who tend to be unsure of their travel plans, often book flights closer to their travel dates and hence have no qualms about paying more. To encourage advanced purchase, some hotel chains offer cheaper rates for rooms booked in advance; customers of the Novotel group travelling in Europe can benefit from its Early Break rates if the room booking is made 14 days in advance.12 As Chapter 3 has shown, the trade-off between acquisition risk (which drive buyers’ willingness to buy further in advance) and valuation risk (which drive buyers’ willingness to buy closer to consumption) means the demand for services is not merely one demand function but continuous demand functions distributed across the advanced selling period (assuming the advanced selling period exists). Hence, firms face uncertainty both in the demand distribution across time and the elasticity of demand for the service at each point in time

The economics of pricing in services 105 Advanced demand

Buyers’ perceptual differences

Probabilistic

Stochastic

Buyers’ erratic arrival times

Deterministic

Buyers’ behaviour from firm’s pricing policy

Figure 5.7 The three characteristics of advanced demand.

during the selling period. Since marginal cost is zero, and since there could potentially be an infinite number of demand functions distributed across the advanced selling period, service firms face great difficulty in trying to ascertain what the optimal price is at each point in time. There are three parts to advanced demand (see Figure 5.7). First, there is the deterministic aspect of advanced demand, where quantity purchased could be determined by the firm’s pricing policy. Second, there is a stochastic (random) aspect of advanced demand, since firms are not able to predict when buyers ‘arrive’ during the advanced selling period. Finally, there is a probabilistic aspect of advanced demand, where even if buyers arrive at a particular time, they may decide to buy, not buy, or wait till closer to consumption time due to perceptual factors. With better technologies and increased connectivity between sellers and buyers, firms are endeavouring to reduce the uncertain nature of advanced demand through forecasting and the development of dynamic pricing models.

Dynamic pricing Dynamic pricing model development has had a surge of interest in recent years. Several factors have contributed to this: 1 2 3

The internet has created a critical mass of buyers that sellers can reach out to without going through conventional channels. Since buyers buy electronically, there is an increased availability of demand data, from buying to surfing behaviour. New technologies have made it easier to change prices of goods and services on the internet.

106 4

Buyers in aggregate More research has gone into the development of better decision-support tools for analysing demand and supply data to aid dynamic pricing.

Dynamic pricing refers to prices that are updated in real time, as a response to changing buyer/demand information and conditions. This often happens in free markets where both buyers and sellers are able to respond to supply and demand conditions. In today’s connected economy, new methods of transacting (e.g. internet, mobile phones, etc.) have made dynamic pricing much more possible. Sellers are now able to extend their geographical reach as well as sell direct to buyers without middlemen and buyers are able to access a variety of goods and services even without leaving their home.13 There are two major research streams in dynamic pricing, each stream having a different perspective. Demand-based dynamic pricing In this stream of literature, dynamic pricing is a pricing strategy whereby prices change over time, across buyers or across the different bundles of products/ services.14 There are three such types of dynamic in use today. Dynamic posted pricing is the take-it-or-leave-it pricing whereby the seller may change the price at any time. This is often used by book retailers where the posted prices are updated frequently on the internet following information obtained about the buyers and the competition.15 One variation of this type of pricing is the dynamic pricing through e-coupons, where buyers that enter a website are tracked and their search and surfing behaviour may result in an offer of an e-coupon of different value. Through dynamic coupons, sellers are able to offer different prices to different segments of buyers and such prices are not easily tracked by competitors, thereby reducing the intensity of competition. Auction, as explained earlier, is another form of dynamic pricing on the internet. Sellers often use this strategy to sell obsolete or overstock products, which is why most services with limited capacity are not often sold in this manner. Reverse auction, such as that offered by priceline.com where buyers name their own price, is more conducive to services, as it is a way of extracting customer value and willingness to pay. Bundle pricing, the third dynamic pricing strategy involves either a quantity discount from buying a large amount or including another good/service with the buyer’s purchase of one good/service, often at a lower bundled price. For example, just before confirming the purchase of a hotel room in London from lastminute.com may result in an offer for theatre, restaurant or car rental service bundled into the hotel room purchase at a price that could be higher if the two services were purchased separately.

The economics of pricing in services 107 Capacity-based dynamic pricing Current capacity-based dynamic pricing practices are mostly encouraged by the dynamic pricing optimisation solution providers (DPOSP) such as PROS. The focus of models in this stream is to optimise capacity allocation and prices across multiple segments where the capacity is perishable and fixed in the shortterm. Demand data that is now much more easily available, feeds into such models so that the firm is able to forecast future demand so that capacity is allocated to the highest price buyers. Such data is then analysed through sophisticated algorithms and prices offered are updated on that basis. For example, Elmaghraby and Keskinocak (2003) investigated inventory considerations, effect of time and the myopic customer versus the strategic customer in discussing dynamic pricing16 and Kimes and Thompson (2004) formulated a model to determine the ‘optimal supply mix’ that would maximise revenues.17 Similarly, McAfee and the Velde (2006) identified innovative approaches to dynamic pricing optimisation models in the airline industry looking at profitmaximisation allocation model versus the efficient-allocation model.18 Other similar models have been presented.19 Researchers have noted that there is reluctance on the part of firms to completely entrust pricing decisions on a pricing-decision tool.20 Part of the problem is that such decision-making tools are optimisation models and offers forecasted dynamic pricing based on input scenarios. Users of such tools have to exercise their discretion on whether the forecasts make sense based on the prevailing market conditions. Capacity-based dynamic pricing models are generally found within the field of revenue management. While the above techniques may seem like rocket science, there are questions regarding their fundamental assumptions. The next chapter will discuss revenue management in services.

6

The revenue management of services

Introduction to revenue management Revenue management is the practice of obtaining the highest possible revenue in the selling of a service firm’s capacity. Capacity of a service firm, in turn, is the highest possible output in a given time period with a pre-set level of staffing, facilities and equipment. This could be seats on an airplane, concert hall, train or a stadium; employees delivering professional accounting or legal services; the maximum amount of data transmitted through cable; the space available for exhibition or conferences; the rooms in a hotel or cruise ship; employees delivering banking services and the amount of liquidity for loans, the list goes on. Capacity amongst service firms has one commonality. For each day a service is not put to profitable use, it cannot be saved.1 This perishability suggests a need for careful planning and management, as idle capacity due to slack demand, as well as turning away buyers due to insufficient capacity, are serious problems critical to the success of many service firms.2 Practitioners of revenue management use tools such as targeted pricing, market segmentation and demand forecasting to ensure that the limited capacity of the firm is sold in such a way that would lead to the highest possible revenue. This means that either the capacity is sold at the highest possible price or the prices are lowered in return for a higher volume for each of the segments the firm sells to in order to fill capacity. Since many buyers buy in advance, the firm sets prices based on forecasted patterns of demand so that capacity sold to earlier (and perhaps lower paying) buyers would not deprive the firm of obtaining higher revenue from buyers buying later. This practice is starting to find favour with many service firms that face relatively fixed capacity, e.g. restaurants, hotels, cruise lines, electric power supply, and railways.3 Revenue management is the reason why flights can be sold at £5 or cinema tickets at 20p. The logic is simple. Since there are many seats on airlines and cinemas that would be perished on the day itself because there are insufficient customers, any amount would be better than nothing. Yet, if airlines and cinemas sell cheap at the last minute, buyers may be conditioned to come at the last minute, and refuse to buy in advance. Hence it is better to turn the problem on its head – sell cheap early on and as capacity fills up, raise the price until all

The revenue management of services 109 seats are filled up. The last person to buy a seat should be paying the highest and the seats will (ideally) all be filled. This simple theory works on the basis that it is always possible to fill the plane or the auditorium or the cinema – it’s just starting at a low base and pushing it up to the point where the market can bear. The two biggest motivations to practise revenue management are the perishability of services and the inseparability of production and consumption. Perishability disallows the firm from building inventory after production, thereby pressuring the firm to obtain the highest revenue for its capacity beforehand. Inseparability disallows buyers from taking inventory after purchase, whereby they would then have to show up at spot time to consume the service. This then results in buyers deciding on when they should buy, as highlighted in Chapter 3. Since buyers are heterogeneous, the aggregate of such buyers would form the advanced demand for the service. The advanced demand exchange system Earlier, I presented the two risks faced by buyers buying in advance. The firm, by choosing to sell in advance also faces two types of risk. Given that distribution of demand is uncertain during the selling period, if the firm sells too much in advance, it may not be able to take advantage of the potential to earn higher revenue from the buyers who purchase closer to consumption (assuming that those who buy closer to consumption pay a higher price, an assumption that is challenged later in this chapter). I term this risk as revenue loss risk. However, if the firm waits to sell closer to consumption, it may run the risk of holding unused capacity that could have been sold earlier. I term this risk as unused capacity risk. The firm then has to decide how much of its capacity should be sold in advance and at what price, and how much should be kept to be sold closer to consumption at a higher price. The essence of revenue management is to set a pricing and selling policy in such a way that at each point in time: • • •

how much to sell at (price); how much of capacity should be sold at the determined price (quantity); and how many segments could the firm sell into and that it could price discriminate on (segmentation);

that would maximise revenue. Figure 6.1 shows the mapping of the firm’s risks onto buyers’ risks as presented in Chapter 3. The task of revenue management is to maximise the revenue according to the exchange system presented. To maximise revenue, firms have looked at various revenue management strategies, including ways to inventory advance demand, price discriminate, and de-market peak capacity loads into low capacity times.

110

Buyers in aggregate Firm’s capacity

Pricing and selling policy Unused capacity risk Seller

Revenue loss risk

Line of perishability

Sell (e)

Selling period

Sell (f)

Production and delivery

(g) Buy

Buying period

(h) Buy

Consumption

Advance Buyer

Valuation risk

Spot

Acquisition risk

Figure 6.1 The advanced demand exchange system.

De-marketing and pricing Another revenue management task is to improve revenue not merely for a particular service time but across the entire system. Service firms often use their fixed assets and infrastructure to operate various types of services, e.g. the employees in the office deliver various professional services, a restaurant serves several meals, gyms have weekday and weekend capacity etc. De-marketing occurs when firms attempt to reduce the demand for a good or service when the demand is greater than the firm’s ability to produce the good or service. This is often employed with the use of price, i.e. increasing the price for particular service times so as to ‘push’ demand towards other service times where congestion could be less. This could be as simple as telling a client that an ‘express’ service would be priced higher or having a promotional discount for off-peak services. The simplest of this model is the Paris Metro Pricing (PMP) model, inspired by the Paris Metro in the early days where the first-class cars that were identical in number and quality of seats to the second-class cars but were double in price. The result was that there was less congestion in the first class cars. The system was also self-regulating. Whenever the first-class cars became a little too popular, some customers would decide that they weren’t getting value for money and would switch to buying second class, thereby reducing the congestion and maintaining the difference between the two cars. The PMP model is popular for the pricing of internet services, as it is relatively cheap to implement. Congestion pricing, where customers are charged based on how congested

The revenue management of services 111

Overall management Volume How much to charge (for each segment)? (Price)

How many to accept (at each time)? Price bucket

Value

Attributes

Technology RM systems and optimization algorithms

Time, effort, burdens (costs), etc.

Capacity

Forecasting History

Figure 6.2 What a complete revenue management system should look like.

the service is, is another possibility but may be more costly to implement as monitoring systems have to be put in place, and the prices have to be dynamic and communicated clearly to customers. In the airline and hotel industry, models, decisions and objectives are fed into a technologically advanced revenue management system (see Figure 6.2) which then advises the firm on the decisions to take. Over time, revenue management has developed into a sophisticated practice as researchers use complex mathematical algorithms, coupled with technology, to allocate capacity, set prices and/or forecast demand. This practice is starting to catch on in other service industries. Table 6.1 shows the practices of revenue management in different industries. Since the essence of revenue management lies in price discrimination, various industries have found different ways through which they could price discriminate their service so that revenue management practices could be brought in to improve revenue. However, it is necessary to revisit the fundamentals of revenue management, despite its highly sophisticated practices of using rocket science algorithms. The next section provides a review of research in revenue management in terms of how the scope of how revenue management has evolved through time.4

112

Buyers in aggregate

Table 6.1 Revenue management practices in different industries Industries Hospitality organisations Hotels Restaurants Attractions Cruise lines and Ferry lines Casinos Saunas Resort Golf Sports events and entertainment events Conference

Example of practices Provide special rate packages for period of low occupancy; use overbooking policy to compensate for cancellations, no-shows Move customers to off-peak periods by offering discount coupons, or charging reservation fees and higher meal prices on Friday and Saturday nights Set different admission charge levels, provide joint-entry tickets, group discounts, coupons, membership rates Provide luxury class, economy class; change prices frequently according to demand; sell more tickets than seats to avoid cancellation and no-show Customise offers such as complimentary room, tickets, gifts, discounts, etc. based on customers profitability Determine price based upon factors such as room type, duration and service type Provide different resort packages to attract different customers Use different prices to reflect the value of different times of the golf course Determine ticket price for an event based on factors such as customer tastes and area of seating; determine the price of season tickets; determine the number of tickets sold for each seat segment Provide different packages and rates to satisfy different customers requirements

Transportation-related industries Airlines Provide business class, economy class; adjust prices frequently according to demand; provide more tickets than seats to avoid cancellations and no-show Rental cars Adjust prices frequently according to demand; serve high valued fleet utilisation with priority; accept or reject booking requests based on length-of-rent controls Boat Provide discounts to stimulate demand Railways Divide customers into standard class and first class; provide different prices based on the day of travel and the time of the day Cargo and Freight Determine price based on cabin space, location and comfort; determine the optimal ship size and capacity for each class Subscription services IT services and internet services Cellular network services

Allocate resources such as human resource, computing capacity, storage and network capacity among segments of customers and determine appropriate price for each segment, high class customers will be served with priority Control call admission based on customer priority, higher class customers will be served with priority

The revenue management of services 113 Table 6.1 continued Industries Miscellaneous Retailing Manufacturing Natural gas, petroleum storage and transmission Project management Apartment renting Inclusive holiday industry

Example of practices Use early discount pricing to maximise the revenue from sales of a ‘seasonal’ product Determine the right price for every product to every customer segment through every channel in response to changing market conditions Make the right price for the transportation services so that the pipelines stay full Use capacity planning and scheduling to reserve specific capacity for customers willing to pay higher prices to have critical activities Establish optimal rates for individual units, adjust prices based on competitor’s price, supply and demand, optimal renew price adjustment Provide early booking discount, child discounts, late sales reductions to stimulate demand

Source: Chiang, W.C., Chen, J.C.H. and Xu, X. (2007) ‘An Overview of Research on Revenue Management: Current Issues and Future Research,’ International Journal of Revenue Management, 1 (1), pp. 97–128, reproduced with the permission of Inderscience Publishers

The evolution and scope of revenue management Definition of revenue management One of the most cited definitions of revenue management is taken from American Airlines: to maximise revenue by ‘selling the right seats to the right customer at the right time’,5 although this definition was subsequently modified to include ‘and at the right price’.6 While this definition might seem broad enough to encompass everything, it is not scientifically useful, as what is right in one regard may not be right in another. Hence, despite its widespread use, other researchers have asserted that there is no satisfactory definition of revenue management that represents the standard in literature.7 There are a few reasons for this. It has been acknowledged that revenue management research has evolved over the past 30 years, and its definition has similarly evolved.8 Also, depending on the focus of a particular revenue management paper, the definitions would either widen or limit the scope of revenue management. Finally, many revenue management tools and practices have been incorporated into the actual definition itself. The first two reasons will be examined further below while the third reason will be examined later in this chapter.

114

Buyers in aggregate

How revenue management has evolved Research into revenue management started in the seventies with Rothstein9 and Littlewood,10 who investigated practices of revenue management in airlines and hotels. When the airline industry was deregulated in 1978, interest in the topic strengthened, as many airlines reported revenue increases of 5 per cent or more after implementing a revenue management programme.11 This led to the seminal papers of Belobaba (1987a, 1987b and 1989)12 that served to propel revenue management into mainstream operations research (OR). However, the understanding of revenue management back then was largely on a computational and operational level, with literature dominated by operations researchers.13 Hence, the scope of revenue management was limited to capacity planning and allocation, for a given set of prices.14 The problem with the original OR-centred approach was that an exogenous demand profile, where the profile was divorced from both the capacity allocation and pricing decision of the firm, was fallacious.15 When a firm changes the capacity allocated to a particular price level, the firm should optimally revise its pricing policies. In turn, demand conditions would similarly adjust. Consequently, revenue management research was pressured to bring in the pricing policies of firms, and also to make demand or buyer behaviour endogenous to revenue management.16 It also became clear that revenue management practice was applicable to other service firms besides airlines and hotels. This led to more research on its practices in other industries such as car rental and internet service providers.17 By applying such practices to other firms, it became apparent that revenue management practices had to deal with prices that, again, should not be separated from capacity allocation.18 Revenue management also became increasingly complex due to the advent of the internet and other advances in technology.19 There were great leaps in computation power, allowing for the emergence of more complex optimising algorithms. Additionally, the internet allowed for data to be collected constantly, and hence feeding the algorithms with much-needed fodder to generate better forecasts that would aid firms in both capacity allocation and pricing. This resulted in the possibility of instantaneous decision making, allowing revenue management systems to be more efficient and responsive. Also, as the internet became ubiquitous, the information asymmetry between supply and demand reduced. Previously, demand data was far more difficult to obtain and less systematic to process. Consequently, supply-driven revenue management was a natural research orientation. With more demand data being made available, a balanced view of revenue management became necessary. The expanding scope of revenue management As the scope of revenue management began to expand beyond being an optimisation issue to include pricing and demand behaviour, revenue management

The revenue management of services 115 became multi-disciplinary in nature, with pricing/demand and consumer research as one stream of focus and capacity allocation, and booking policies and related supply-driven issues as the other.20 However, even without revenue management, pricing has already attracted considerable research interest, particularly in the area of dynamic pricing, where prices could be changed quickly and with ease, on the internet.21 Researchers realised that the revenue management problem was not adequately dealt with within just one discipline. Pricing and demand behaviour were important, but then so was capacity allocation and planning, and both needed to be brought into revenue management. Despite the need for integration, there were few who attempted it.22 This is also reflected in practice whereby, in commenting on the airline industry, Cary (2004)23 claimed: Pricing and revenue management – function so differently within the US airline industry. Pricing is almost entirely outwardly focused on the actions and reactions of competitors. Revenue management is almost entirely inwardly focused on the patterns and trends in historical demand data. Both are in need of adjustment. Seen from a political angle, it is commonly believed that the power for disciplines often comes from control over ideas.24 Consequently, contribution to revenue management knowledge depended on how the revenue management problem was described. OR-centred revenue management problems dealt primarily with supply issues of overbooking, capacity allocation and demand forecasting.25 For example, as recent as 2004, Gorin and Belobaba’s26 definition of revenue management within the airline industry was ‘the combination of forecasting and optimisation algorithms which enables the airline to maximise revenues, given a set of fares, by determining how much seat inventory to make available to specific fare products based on forecasts of expected demand for each fare product’. In contrast, other disciplines framed the revenue management problem to deal with maximising profit through pricing or consumer choice models.27 For example, Subramanian et al.28 defined revenue management as ‘a commodity or service (such as the use of a hotel room on a particular date) that is priced differently depending on various restrictions on booking (e.g. advance purchase requirements) or cancellation (e.g. nonrefundability or partial refundability)’. Since definitions are often more exclusive than inclusive, the definition of revenue management tend to indicate which domain is in control of knowledge within that topic. In the early days of revenue management research, the definition of revenue management was clearly accepted as one that was firmly entrenched in the OR domain.29 Even up to 1999, in the editorial introduction to yield management30 for the Journal of the Operational Research Society, Yeoman et al.31 claimed that a commonly recognised broad definition of yield management was ‘the process of allocating the right capacity or inventory unit to the right customer at the right price so as to maximise revenue or yield’.

116

Buyers in aggregate

Similarly, Desiraju and Shugan’s 1999 paper in the Journal of Marketing32 compared strategic service pricing with yield management, taking them as two disparate practices. In recent years, pricing and demand behaviour have been brought into revenue management research33 and the lack of a standard definition of revenue management claimed by Jones (1999)34 served to demonstrate the tension between the disciplines researching in the area. Notwithstanding the influences from other disciplines, the literature in revenue management is still heavily dominated by OR. Although OR-researchers now acknowledge that demand and the buyer is endogenous to the revenue management problem,35 definitions are still supply-centric as evidenced by the following definition by Kimes and Thompson:36 ‘Revenue Management is a form of capacity management in which demand and supply are managed by manipulating length of usage and price’ (emphasis added). This is in contrast to Fleischmann et al.: ‘Revenue Management . . . is concerned with pricing a perishable resource in accordance with demand from multiple customer segments so as to maximize revenue or profit’.27 One of the main difficulties in integrating pricing research with capacity allocations is that historically at least, OR research in revenue management assumes advanced demand is random or probabilistic. Pricing research would tend towards assuming demand to be deterministic, i.e. determined by price, or by the pricing policy of the firm. Fundamental assumptions about advanced demand therefore drive the results obtained by the research. But are they realistic? A random or probabilistic demand seemed justified on the basis that buyers ‘arrive’ at random times before consumption. For example, it is impossible for the firm to predict when buyers would buy, how much capacity would be bought and why these buyers would buy at a certain time. Even at an individual level, it would seem ‘random’ when a buyer might need dry cleaning, or be called to go to London on a business trip. From the deterministic perspective though, a theoretical structure was needed to explain how demand is shaped or why it would follow a particular pattern across time, instead of conveniently electing demand to be ‘random’. With ‘random’ demand, there was no assurance that the past is able to predict the future.38 Accordingly, despite tremendous computing power available today, pricing and demand forecasts based on assumptions of randomness face the same old problem in conventional probability theory, where according to Bernstein (1996), ‘the raw material of the model is the data of the past’.39

Revenue management and advanced demand behaviour Some research studies, mainly dominated by marketing literature, have attempted to shed light on the behaviour of the advanced buyer. Here are some of the main research and their findings: 1

In their evaluation of strategic pricing in advanced selling, Desiraju and Shugan (1999) found that yield management strategies such as discounting,

The revenue management of services 117

2

3

overbooking and limiting early sales work best when price-insensitive buyers buy later than price-sensitive buyers.40 Shugan and Xie (2000) showed that due to the state dependency of service utility, buyers are uncertain in advance and become certain at consumption time, while sellers remain uncertain of buyer states at consumption time because of information asymmetry. They suggest that advance selling overcomes the informational disadvantage of sellers and it is therefore a strategy to increase profit.41 Xie and Shugan (2001) also studied when advanced selling improves profits and how advanced prices should be set.42 They have also investigated the optimality of advanced selling, investigating selling in a variety of situations, buyer risk aversion, second period arrivals, limited capacity, yield management and other advanced selling issues. Png, on the other hand, showed that costless reservations in advance is a profitable pricing strategy as it induces truth revelation on the type of valuation that buyer has for the service (which is private information).43 If the buyer has a high valuation i.e. ability to consume, they will exercise the reservation and pay a higher price. If not, the buyer will not exercise. In another paper, Png (1991) compared the strategies of charging a lower price for advanced sales and attaching a price premium at the date of consumption versus charging them a premium and promising a refund should consumption prices be lower than what was purchased.44

Despite these models that aim to capture primitive advanced demand behaviour, not much effort has been made to integrate them into a unified framework nor have there been any attempt to bridge the behavioural aspects of demand with revenue management research. These models capture individual buyer behaviour (or homogeneous buyer segments), and it was difficult to see how that could be aggregated and applied to revenue management that mostly dealt with stochastic heterogeneous market demand. Lee and Ng (2001) attempted to model the demand phenomenon at a market level, but it was unclear why their demand function was shaped the way it was.45 Some revenue management researchers have therefore highlighted the need for better models of demand.46 Revenue management and demand distribution Chapter 3 highlighted that buyers at an individual level face a trade-off between acquisition risk (which drives buyers’ willingness to buy further in advance) and valuation risk (which drives buyers’ willingness to buy closer to consumption). This implies that at an aggregate level, the distribution of demand across the selling period of the service becomes important in the firm’s pricing decision. In this respect, firms face uncertainty in demand distribution across time. For many revenue management consultants, the key to better pricing decisions and improving profitability for service firms would be accurate demand forecasting, coupled with dynamic optimisation algorithms across time. Although some

118

Buyers in aggregate

researchers have pointed out that demand forecasts should be adjusted when there are price changes,47 revenue management researchers in almost all instances have assumed advanced demand to be random in nature, and/or the buyer choice behaviour as probabilistic. In Chapter 3, I noted that this assumption is usually justified on the basis that buyers ‘arrive’ at random times before consumption, and this drives the belief that forecasts should aim for greater accuracy. However, striving for greater forecast accuracy may be missing the point. There is a distinction to be made between buyers’ discovery of their need for a service and when they choose to purchase, a distinction that traditional revenue management ‘arrivals’ do not take into account. In other words, ‘arriving’ may not always mean ‘buying’. A buyer might be aware that they would like to buy a theatre ticket but decides to wait and see if the prices go down. Similarly, an overworked executive may recognise the need to take a vacation to rest and rejuvenate themself, but they may not necessarily make their holiday bookings at that point in time. In fact, it may be months before they actually ‘buy’ a holiday package, as they will need to plan their work and obtain approval for annual leave before they are able to book their holiday. Accordingly, advanced demand may not be all random in nature. There is an aspect of advanced demand where it could be determined by behaviour. It is therefore possible that the deterministic aspect of demand lies in the trade-offs between acquisition and valuation risks explained in Chapter 3. The deterministic aspect of advanced demand The revenue management/pricing problem does not end there. The firm’s decision on price also has an effect on the buyers. For simplicity, it is assumed that only two times exist in the service’s selling period for it to sell – advanced time, denoting selling the service far in advance; and spot time, denoting the selling of the service at a time closer to consumption. If the firm lowers advance price, some buyers who might ordinarily wait till spot to buy might be persuaded to buy in advance. For example, companies may not need any IT support service until equipment starts breaking down, i.e. buy only when the service is needed at spot. Yet, some IT support service companies have managed to sell service packages to clients. This means that the clients have actually purchased the services in advance, without knowing when such support services are needed. Similarly, theatre tickets lower their prices at spot, resulting in buyers that may choose to wait till spot rather than buying in advance. This goes to show that there is some degree of cross-time dependence between advanced and spot demand. Once this principle is extrapolated across multiple selling times in a service’s selling period (i.e. beyond two times), the full extent of the firm’s complex pricing decision can be appreciated. Moreover, what has been discussed is based on the assumption that prices are segmented on time alone. Many services offer discriminatory prices across various service attributes or channels.48 This means that instead of merely charging prices that are different according to the time of purchase, many service firms charge prices

The revenue management of services 119 that are different over a myriad of channels. Take hotels, for instance, which offer different room rates through different distribution channels. These include a walk-in rate, travel agent rate, corporate rate, hotel website rate, internet distributor rate, tour package rate, airline tie-in rate, credit card tie-in rate, etc. When all these are considered, the demand behaviour across time is even more confounding. Re-selling capacity A crucial difference between pricing for services and for goods is embedded in another effect of inseparability. Even if buyers are to purchase in advance, advanced selling requires the buyers to still present themselves (or at least, the item that requires the service) at spot time. In other words, since services are inseparable in consumption and production, each advanced buyer has to ‘showup’ to consume. Especially when the purchase is conditional upon a particular time of consumption, there will be a fraction of advanced buyers that may not be able to consume the service during that specified time. This is commonly acknowledged in various revenue management literatures, where attempts have been made to structure various reservation policies to minimise the impact of the cancellation and ‘no-show’ concept of advanced selling.49 What has not been discussed is that the existence of a non-zero probability of non-consumption by advanced buyers provides a service firm with a unique opportunity not presented to goods firms, i.e. the ability to sell the capacity that was already sold in advance – again at spot. This re-selling capability may then translate into additional profit for the firm either in the additional spot sales or through overselling beyond the firm’s capacity in advance. This point can be illustrated through two examples. First, tow truck services operate with limited capacity but sell (albeit at a very low price) through the Automobile Association (AA) an enormously large number of its services in advance, often through emergency services insurance. Since the fraction of the market that actually requires a tow truck service may be low, the firm obviously oversells its capacity in advance as well as re-sells it at spot (at a high price for those who did not subscribe to the insurance). Similarly, IT support services are usually oversold to buyers in advance since the fraction of non-consumption may be high, especially if the IT hardware and software is reliable and operates well. Hence, when advanced selling is possible (which could be due to high acquisition risks as highlighted in Chapter 3) and ceteris paribus, advanced buyers are preferred because every advanced buyer provides the firm with a non-zero probability of being able to re-sell. The ability of firms to re-sell relinquished capacity of advanced buyers can be executed in a few ways. First, the firm can re-sell to spot demand, if spot demand exists. In the earlier example of IT support services, if the client’s IT equipment are functioning well, there may be no need to call the IT support company at all. This ‘nonconsumption’ of the service by the IT firm leaves the IT firm the ability to service other clients who may not have bought the advanced package but who

120

Buyers in aggregate

are prepared to pay higher spot prices. This phenomenon also often occurs at theatres staging popular shows, where there is usually a queue of theatregoers hoping to buy tickets for the seats relinquished by those that didn’t show up. Second, the firm could have inventoried advanced demand and re-sells the capacity to those on the ‘waiting list’. This means that instead of selling relinquished capacity at spot, the firm sells the relinquished capacity to advanced buyers that have been kept on a waiting list. For example, popular fine-dining restaurants that are fully booked for months, often maintain a waiting list so that it is able to accommodate other buyers when there is a booking cancellation. Finally, the firm could try to forecast the proportion of non-consuming advanced buyers and oversell that proportion to advanced buyers. In revenue management, this final option is commonly referred to as overbooking.50 This means that instead of selling the capacity at spot or to a waiting list as indicated above, the firm actually oversells in advance in anticipation of no-shows at spot. Clearly advanced demand occurs at every point during the advanced period and there is (theoretically at least) multiple demand functions over the entire advanced selling period. How, then, should prices be set? The common perception of advanced price being lower than spot price may not be altogether true. In services where there are more buyers facing low valuation risk and high acquisition risk, it is possible that advanced price is higher than spot, ceteris paribus. For example, a concert that is incredibly popular may price its tickets lower, closer to spot time, when the best seats have already been sold. Furthermore, pricing is dependent on price sensitivity. A firm may find that demand conditions may render it optimal to trade-off higher prices for greater demand, if the firm’s capacity is large. Hence, the traditional view that a firm needs to entice buyers to buy in advance through lower prices may not be an optimal one, as the strategic levers to advanced demand lie in how to manage the trade-off with the risks perceived by buyers, and not in the price/quantity relationship alone. Without doubt, buyers can still be enticed by low prices, but if valuation risks are high, the firm may need to lower its advanced prices considerably and this may be more damaging to revenue. The firm could perform better by employing strategies to lower valuation risks instead. In other words, the demand function could be changed through the manipulation of the risks, rather than just by looking at a discount on price. (A discussion on why and how firms should mitigate risk in valuation for advance purchase can be found in Chapter 4.) Then again, the ability of firms to re-sell its capacity would perhaps result in advanced prices being typically lower than spot prices, because advanced selling gives the firm the potential opportunity to sell twice. What is important is to recognise why that could be so, rather than assume advanced discounting as a priori.

Revenue management practices and tools With all that has so far been discussed about the issues within advanced demand, little wonder therefore, that demand seems random, resulting in researchers

The revenue management of services 121 constructing demand forecasts of greater complexity. This section aims to provide a critique of current revenue management tools. In her research, Kimes (1989) highlighted various conditions for a firm to be able to practise revenue management. These conditions are relatively fixed capacity, perishable inventory, reservations made in advance, low marginal costs, variable demand, and segmentable markets.51 This was corroborated by Lieberman, Upchurch et al. and many other researchers.52 In the context of what has been discussed above, it is clear why these conditions are necessary. Fixed capacity and perishable inventory provide a credible threat towards heightening acquisition risk, resulting in the existence of advanced demand for the practice of revenue management. Yet, some revenue management literature has shown that revenue management could be practised even when there is no fixed capacity, or even with high cost of incremental capacity.53 As I have presented, the key towards the practice of revenue management is not necessarily fixed capacity, but purchase across a meaningful advanced selling period. Fixed capacity may encourage buyers to buy in advance because of acquisition risk, but the threat of non-acquisition (from the buyer’s perspective) may also be generated through buyers’ inability to afford higher spot prices.54 Consequently, the firm may heighten acquisition risk if it can credibly commit to high spot prices. Reservations made in advance and variable demand allude to a distribution of demand in advance of consumption, so that there are variations in prices to manage, and segmentable markets ensure that the firm is able to discriminate on prices. Essentially, it is a firm’s ability to sell in advance that allows it to practise revenue management. Hence, the conditions provided by researchers on when revenue management could be practised are therefore symptoms of the underlying theory of why and how advanced demand would exist in the first place. What about the practices of revenue management such as overbooking, cancellations/no-shows and demand forecasting? Are such techniques truly optimal practices? I will examine each one of them in turn. Overbooking and cancellations/no-shows Overbooking, i.e. accepting more reservations than one has the physical capacity to service as a hedge against cancellations and no-shows, has been claimed as one of the oldest and, from a revenue standpoint, most important of yield management tactics.55 Various authors have examined how firms could insure themselves against no-shows or cancellations by buyers, through appropriate reservation policies.56 Other researchers, like Pfeifer (1989),57 have also examined the pricing implications associated with such reservation policies. Research in this area proposes that buyers purchase at different times in advance of consumption, i.e. some arrive early, and some arrive later (closer to consumption date). For the firm, the challenge is how to optimise revenue by pricing and/or setting capacities to be sold at each point in advance, taking into account the arrival times of the buyers.58

122

Buyers in aggregate

However, it is important to understand the implicit assumptions of this tactic. Without looking at the possibility of re-selling capacity, traditional overbooking assumes that advanced demand is preferred over spot demand (hence the firm overbooks on advanced demand). In other words, when there is a no-show, the traditional view states that it is better to fill the no-show capacity with advanced buyers than to sell it off at spot. This could be for various reasons; most commonly that there is either very little spot demand, that spot prices are uncertain, too low, or that if buyers know that prices could be lower at spot, they will be less willing to buy in advance. Within the above analysis presented, it is clear that these reasons may not be the case. Within a heterogeneous market, some segments may experience high valuation risk and low acquisition risk, making it possible to create demand at spot, and perhaps extract higher prices. As pointed out earlier, the firm could sell to advanced buyers on waiting lists, spot buyers or overbook on advanced buyers. A further point to be made is not how overbooking should be practised – as that is surely driven by demand conditions – but also to realise that there is an alternative to overbooking: Change demand conditions through service attributes in such a way that there exists spot demand (buyers that face high valuation risks) to fill the no-show capacity, that would not cannibalise advanced sales. To the extent that if spot demand is high and can command superior prices (subject to demand sensitivity), this could potentially drive greater flexibility and lower prices for advanced buyers, since no-shows could lead to higher revenue from the re-selling of capacity. Demand forecasting One of the key principles of revenue management lies in the firm’s ability to forecast demand.59 Revenue management systems must be able to advice on demand conditions by analysing reservation patterns, arrivals, departures and a score of other demand characteristics.60 Recent literature has suggested that revenue management systems with demand forecasting algorithms are increasingly expensive to implement, both in real terms and in lost opportunities.61 A typical system costs between US$1 million to $3 million and takes more than two years to implement.62 Moreover, research has suggested that these complex and sophisticated revenue management systems are not infallible. In fact, with demand forecasts using the data of the past, and sales departments using present day information, conflicts often occur,63 and many revenue management systems operate with some level of human intervention, often using these systems as merely a guide. Current research in demand forecasting may not be very effective for four reasons: 1

Demand characteristics, upon which many revenue management studies are premised, should be based on fundamental concepts of buyer behaviour.64

The revenue management of services 123

2 3

4

Within a historical pattern of demand, why buyers behave the way they do is just as important as how they are behaving. Consequently, the past may not be a good indicator of the future.65 Demand forecasting, at its best, is still an aggregation of multiple segments that could, if possible, be desegregated and targeted for higher revenue. Past demand profiles are subject to many factors, not least the actions and pricing strategies of the competitors at that time, and the firm’s own reaction to them. To assume that demand based on historical data can still hold for the future could be assuming too much. Finally, as stated in Chapter 4, demand can be influenced, not merely be known. It could, therefore, be more profitable to understand buyer attributes as antecedents of demand. By manipulating acquisition and valuation risks as strategic levers, advanced demand could be influenced and managed for higher revenue. For example, a simple matter of changing a fixed time ticket to allow flexible consumption times immediately lowers valuation risk, as buyers can negotiate within themselves to choose the ideal travel time. Where the business executive was facing high valuation risk by not being certain about which date they are to fly, a flexible flight time (e.g. open tickets) might persuade them to buy in advance as their valuation risk is lowered, thus increasing their willingness to pay in advance. Similarly, if there are many flights available for the parent who needs to fly to New York for their child’s graduation, their acquisition risk is lowered, and they might decide that they do not need to buy in advance.

The analysis presented here accentuates a point. Revenue management tools such as demand forecasting and overbooking to manage uncertainty may not be the only tools on hand to obtain optimal revenue. By assuming that all revenue management, even including its definition, must subscribe to these tools, is akin to a potter risking becoming slave to his/her clay. Moreover, using complex demand forecasting techniques and optimisation techniques that are based on flawed assumptions may result in a decrease in revenue. As Boyd66 puts it: a ‘wrong forecasting model’ does not refer to the relative merits of linear regression versus exponential smoothing, but to using a method which properly interprets how customers are purchasing so that it can correctly infer future demand from observed data. It is not the intention of this chapter to diminish the role of demand forecasting models. On the contrary, my thesis is to provide a better conceptual understanding of what drives advanced demand, so that researchers would see the need to understand the data of the past before inferences can be made about future demand. This is a call that has been made by some existing revenue management researchers.67

124

Buyers in aggregate

Box 6.1 Mathematical formulations in revenue management Mathematical models are commonly used in revenue management. This chapter aims to provide an understanding of revenue management in a critical manner, through synthesis and analysis, without the use of mathematics. This is because most revenue management research is divided into three streams: descriptive (application to industry), pricing control (development and improvement of pricing) and inventory control (management of arrivals).68 Thus, in the interest of neither narrowing the audience nor losing the message of the chapter, the use of mathematics has been avoided. Also, models often simplify, and findings differ according to how demand is being modelled,69 as well as the context within which the model is embedded. In addition, many of such models do not usually reveal their implicit assumptions. For example, in modelling demand behaviour, buyers that choose to buy in advance or at spot time could be myopic (i.e. consider only short term benefits) or strategic (consider the future and changing their behavior at the present)70, or be modelled as having strategic interactions with the firm (i.e. consider the firm’s possible reaction from their own actions).71 In addition, buyers, in aggregate, could also be price takers in the form of demand functions across time so do not have any market power.72 Yet, a traditional demand function where buyers are price takers may not completely capture the phenomenon. In the traditional goods view, price-taking buyers may be acceptable because it is costly for buyers to gain information. Nowadays, prices and information are far more easily available and buyers are also more strategic. Moreover, there is currently no mathematical model that completely captures the complete advanced selling phenomenon.73 Yet, it is clear that future revenue management should be more demand- or customer-centric, as highlighted by van Ryzin.74 Yet this does not in any way mean that mathematical models are not useful. On the contrary, advances in revenue management would not have been possible without them. Presenting an analysis of revenue management in this manner, however, does not limit how a subset of the phenomenon can still be modelled.

Competition and revenue management One of the most well known flaw in revenue management is the fact that it almost always assumes that there is no response from the competitor that could alter the firm’s optimal behaviour be it in pricing or capacity allocation. Bringing in the effect of competition into revenue management is tricky and attempted by few.75 Research has shown that pricing behaviour by firms as well as competitors become erratic once competition is factored in.76 The most common technique used to include competition within pricing or revenue management is

The revenue management of services 125 through the techniques introduced by game theory. Game theory models interactions among agents, where each party is strategic and behaves rationally and produces an action only after considering the impact of its action on the competitor and the competitor’s reaction which in turn impacts on the firm and so on, until infinity. Most game theoretic models are exactly that – theory. Empirical testing of such models is near impossible since so many confounding factors would exist. Yet, even at the theoretical level, there isn’t a clear solution for two service firms with capacity constraint deciding on price as well as capacity allocation, unless a rationing rule (i.e. how buyers are divided between the two firms) is specified. Much more research is required in this area.

Fairness and revenue management This chapter on revenue management would not be complete without a look at one of the major issues in the practice; the perceived fairness of revenue management pricing. The perception of fairness has been shown to be related to firm profitability.77 Studies have found that fair behaviour on the part of firms is instrumental to the maximisation of their long-term profits.78 Revenue management practices are aimed at bringing in increased yields, but this may be a short-term benefit if buyers view the practices as being unfair. In explaining buyers’ perception of fairness, researchers use the concept of reference price/transaction, and the principle of dual entitlement. Reference price/transaction describes how buyers think a transaction should be conducted, or how much a particular service should cost. To assess the fairness of a price, buyers often rely on the last paid price, most frequently paid price, and market or posted prices.79 Under the principle of dual entitlement, most buyers believe that they are entitled to a reasonable price while firms are entitled to make reasonable profit.80 Also, buyers feel that the value they derive from a service must be equal to the value that the firm derives from the service. Hence, buyers would consider a pricing strategy fair under the following circumstances: 1

2

When the pricing does not deviate far from the reference price of that particular service, as any price deviation will create an imbalance in terms of the value to both buyer and firm. This is however a tricky condition to fulfil at times, particularly if the lower prices used during low-demand periods are taken as the reference price; future transactions at regular or peak rates may seem unfair.81 If there are price deviations, more specifically any price increase which raises value for the firm, there must be a corresponding increase in value for the buyer. For example, a restaurant that increases its menu prices should offer additional value, be it in the form of larger food portions, better quality ingredients, or improved amenities/ambience. Failure on the part of

126

3

Buyers in aggregate the firm to do so would violate buyer beliefs about dual entitlement, and the transaction may be considered unfair. Any price increase must also be considered justifiable. For instance, a price hike for airline tickets to cover an increase in costs due to rising fuel prices and to maintain the airline’s profits is considered as fair, while raising prices merely to increase the firm’s profits is not.

Box 6.2 illustrates a situation where a buyer considers the price increase to be unfair.

Box 6.2 An email from an airline ticket buyer Dear all I encountered pretty blatant price discrimination on [the] internet. I bought a ticket for my mother to visit the family for Easter/Passover. I used [name of company withheld] to buy the tickets. On the site, you had to choose which address your credit card was from. If one chose England it was about £650. If one chose US, it was about $750. More shocking was if one chose Israel, it was about $1,150 and the price was LISTED in dollars. Naturally, I called up my sister [in the US] and used her credit card (saving me lots of money). My other idea was to log into the website of one of my credit cards, change the address to a US address, buy the ticket and change it back. Wasn’t sure if that would work. Just another UK customer Essentially, revenue management uses different prices for fundamentally the same service,82 and practices such as price discrimination may violate some of the acceptable terms of fairness as stated above. For instance, demand-based pricing or variable-pricing schedule as practised under revenue management, may be perceived as being unfair when the prices turn out to be more than the buyer’s reference price. And if buyers believe that the transaction varies from the reference transaction only in price, they may feel that the firm is receiving more than its reference profit and is behaving unfairly.83 Also, a common revenue management practice is to set different prices for different segments of the market (usually via the use of rate fences), and when a buyer pays more for a similar service and cannot perceive a difference in the service, he or she may view the situation as unfair.84 Researchers in revenue management have found that the following factors/issues influence the fairness perception of revenue management practices: Role of information Access to information plays a crucial role in enabling buyers to assess the fair market price. Hence, for revenue management practices to be perceived as fair,

The revenue management of services 127 information on the different pricing options should be made available to buyers. In other words, there must be transparency. For instance, some hotels may offer upon request, discounts on their room rates for walk-in customers. This may be considered unfair practice, as the information on discounted rates has not been freely given (i.e. only upon request). Buyers also feel that it is unacceptable for the firm to make the information known, but not take the additional step of offering it directly to customer.85 Use of rate fences A common practice in revenue management is the use of rate or price fences, which according to Hanks et al., are designed to allow buyers to self-segment based on their willingness to pay, their behaviour, and their needs.86 They help justify why different buyers pay different prices, and this can help increase the perceived fairness of revenue management practices. With rate fences, prices are discounted but restrictions are imposed at every level of discount to ‘balance the perceived value for the different market segments’.87 These restrictions or ‘fences’ can include physical fences such as location, furnishings or amenities, i.e. a street-facing hotel room is cheaper than one with an ocean view, or business vs. economy class on an airline. Or it can be non-physical restrictions that involve time and availability (i.e. limitations to time-of-use/validity; a cheap air ticket may only be valid during non-peak season, and allows travel only on weekdays); or transaction characteristics (i.e. required advanced purchase, refund penalties). In most cases, to qualify for the lower price or rate, buyers must be willing to accept these restrictions. Reasonable restrictions For rate fences to work effectively however, the restrictions imposed in exchange for a discounted rate must not be too severe. According to Kimes (2002), the imposition of restrictions causes buyers to lose some of the value they would otherwise gain from the transaction, while increasing value for the firm.88 Hence, balance must be restored to fulfil dual entitlement. Discounted prices benefit the buyer but to ensure fairness, this benefit must be sufficient to make up for the penalty suffered in the form of restrictions. For instance, a cruise line may offer special discounted packages, but with a restriction in the form of a high cancellation charge policy. For the transaction to be deemed acceptable to buyers, the discount must be substantial enough to justify the high cancellation cost. Framing of the price differential How a price difference is termed or ‘framed’ also affects its fairness perception. Studies have found that buyers consider a price change more acceptable when it is termed as a discount, rather than a surcharge or premium. According to

128

Buyers in aggregate

prospect theory, buyers have a better fairness perception of prices framed as gains (i.e. discounts) compared to those framed as losses (i.e. surcharges/premiums), even if they are economically equivalent.89 Hence, firms should highlight price differentials as discounts off higher rack rates or full fares, and not those that are surcharges for peak seasons. Fencing condition A relatively new area of research in revenue management literature, the concept of fencing condition proposes that price differences can lead to perceptions of advantaged inequality (when a buyer is able to benefit from a lower price through an effective rate fence, i.e. fence-advantaged) and disadvantage inequality (when a buyer is prevented by the same fencing mechanism from benefiting from the lower price, i.e. fence-disadvantaged).90 Research has found that fence-advantaged buyers would have a fairer perception of the price they pay compared to those who are fence-disadvantaged.91 Hence, a 65-year-old buyer who is able to benefit from a senior citizen rate (hence, fence-advantaged) may feel that he pays a fair price, compared to a 30year-old paying full price (and hence, fence-disadvantaged). Recent research by Wirtz and Kimes (2007) has shown that buyers’ familiarity with revenue management practices play a great role in moderating the effects of the framing and fencing condition on perceived fairness.92 Their study suggests that as a market becomes more familiar with revenue management practices, over time it is less likely to perceive these practices as unfair. How is this so? When buyers are familiar with revenue management practices such as rate fences, they are more likely to view two rate-fence conditions as different transactions that carry different reference prices. Hence, they are less likely to make social comparisons with buyers in a different fencing condition, and are also more likely to have already adjusted their reference transaction and price with less or even no impact on perceived price fairness. Thus, the issue of loss and gains (from a framing perspective), and equality/inequality (in terms of fencing), will matter less to them. Given this, it is clear that buyers need to be informed and educated on a firm’s revenue management pricing practices, so that they can become familiar with them. Increasing familiarity with revenue management practices in one service industry also bodes well for others. For instance, buyers have become familiar with revenue management pricing in the hotel and airline industries, which makes it easier for them to accept similar practices by other services. This in turn will go a long way in improving the perceived fairness of revenue management practices in service industries. The next chapter looks at the future of revenue management and pricing in services and suggests new ways of improving revenue through the new revenue management system.

7

Strategic pricing and revenue management Four more strategies for higher revenue

Revenue management has evolved from the days when it used to be called yield management. Today, revenue management encompasses various strategies to improve and manage revenues from pricing, segmentation, capacity allocation down to even the design of services to create differentiation for price discrimination.

The ability to practise revenue management Yet, not all services are able to practise revenue management. Applying the concepts of valuation and acquisition risks presented in Chapter 3, this could be an explanation why certain services are not able to practise revenue management. By the term revenue management, I do not mean price discrimination alone. Almost all services can price discriminate between different buyer segments. Revenue management requires the firm not merely to be able to price discriminate, but to be able to sell in advance and spot as well as inventory demand for its limited capacity. Not all services are able to do that. Buyers’ valuation risks can result in the firm not being able to sell the service in advance, since buyers cannot be certain of the value in advance. This uncertainty could be so great that it could substantially reduce advanced demand, and as a result, the firm is unable to practise revenue management through advanced selling. For example, buyers may have no idea when they might need a lawyer, so their valuation risks are high compelling them to buy at spot (i.e. only when they need it). In addition, buyers believe that when they do need a lawyer, they will be able to get one without too much trouble so there is no acquisition risk and the buyer does not therefore have any incentive to buy the service in advance. Under such circumstances, it is not surprising that many professional services are not able to practise revenue management. In addition, even if some services have limited capacity, the service itself may not be critically time dependent. For example, restaurants may be limited by capacity but patrons might find that if the place is full, they could always come another day. This, in turn, results in a lack of advanced demand. Conversely, banquet rooms in a hotel may have advanced demand as buyers are more sensitive to the date/time of their event.

130

Buyers in aggregate

On the other hand, service firms that exhibit high acquisition risks drive buyers to buy in advance. For example, it is the sense that buyers may not be able to get the flight or seats in a show that creates a demand for the service well in advance of consumption. When a buyer faces the risk of not being able to acquire a service at spot time, advanced demand usually exists, allowing many firms to practise revenue management. These would include most travel industry services like airlines, hotels, and public transportation companies such as trains and buses. To practise advanced selling, buyers must be assured that the value at the time of consumption is unchanging and less state-dependent. To do so, service firms could try to ‘unitise’ their service with a consistent outcome, whereby the value of the service can be much more obviously observed. For example, loan agreements could be a unit of service rendered by the firm where the outcome is an agreement duly drafted, processed and executed by the firm. The firm could sell loan agreements in advance, e.g. buyers buy them like they buy insurance, and call on them to be delivered perhaps up two or three times through their lives (depending on how it is packaged). Motor companies sell such ‘service care’ packages for their cars where vehicle owners send their cars for servicing at lower rate than if they were to buy the services whenever they want it. Hence, as was also presented in Chapters 3 and 4, service firms that wish to practise revenue management must attempt to: 1 2 3 4

decouple purchase and consumption; create an advanced market demand by ensuring that acquisition risks exist; the value of the service must be tied to a fixed time of consumption with a low degree of substitutability; and ensure that the value of the service at consumption is unchanging, easily observable and has a consistent outcome.

Table 7.1 provides some explanations why certain services may not be able to practise revenue management and how such services could begin to develop some revenue management strategies. As always, such proposals need to be carefully thought through. Creating advanced demand may be useful to increase revenue but it could also result in a drop in revenue and may also backfire (e.g. if the firm’s effort to limit its capacity is not credible).

The new revenue management system For firms that are able to practise revenue management, practice and research in this area have become much broader, and the linkages between the various concepts have begun to emerge. Revenue management today needs to embrace a new era where operations management, operations research, marketing, economics and technology all play an important role. Indeed, revenue management is challenged to organise the end-to-end solutions, from supply and capacity of the firm to the value and demand for the service by buyers.

Yes

Hotel and cruise lines

Yes

Yes

Mortgage services

Cinema

Yes

Yes

Would NOT normally practise revenue management and advanced selling

Restaurants

Telecommunication services

Yes

Yes

Airline, rail

Legal and professional services

Would normally practise revenue management and advanced selling

Service

Table 7.1 The ability to practice revenue management

Acquisition risk is high not because of capacity (capacity is scalable), but because costs to buy at spot is too high Criticality of consumption time may not be high, advanced demand may therefore not exist. Criticality of consumption time may not be high, also, no perception of limited capacity, advanced demand may therefore not exist Capacity constraint creates a perception of acquisition risk, advanced demand exists

Capacity constraint creates a perception of acquisition risk, advanced demand exists Capacity constraint creates a perception of acquisition risk, advanced demand exists Criticality of consumption time may not be high, advanced demand may therefore not exist

Possible reasons for practise/not practising

continued

Limit capacity and increase spot prices and provide advanced discounts to create advanced demand Limit capacity for mortgages and increase spot prices

‘Unitise’ some legal services (e.g. house loan agreement) and sell in advance to a bigger market with possible nonconsumption

Possible ways to practise revenue management

Yes

Yes

Medical outpatient service

Downloadable services, e.g. music, software

Would NOT normally practise revenue management and advanced selling Yes

Would normally practise revenue management and advanced selling

Education

Service

Table 7.1 continued

Criticality of consumption time may not be high, also, no perception of limited capacity, advanced demand may therefore not exist.

Ethical reasons, criticality of consumption time may not be high Ethical reasons

Possible reasons for practise/not practising

Limit capacity and increase spot prices to create advanced demand, manage perceptions Evaluate and factor in the long term revenue from acting responsibly, manage perceptions. Limit capacity and increase spot prices to create advanced demand, sell through subscription in advance (this is already the strategy for some services)

Possible ways to practise revenue management

Strategic pricing and revenue management 133 The new revenue management system consists of four decision sets and various components, as represented in Figure 7.1. From the demand end, buyers pay a price according to the benefits they obtain; such benefits are provided through the attributes of the service. This value set requires the firm to choose the most appropriate attributes that would result in the highest possible benefit to buyers. Conversely, the benefits buyers require will inform the type of attributes chosen by the firm. However, firms will also have to decide on the types of benefits to provide that would appeal to different segments of the market, so that it is able to price discriminate for each segment, i.e. the segmentation set has an influence on the value set. That means it’s not merely which attributes provide what types of benefits but how the benefits are able to help the firm separate markets in the various segments. For instance, most airlines segment their buyers according to first class, business class and economy class passengers. Each market segment value different benefits; economy class passengers look for the best value for money, while business class passengers would value comfort and personalised service, and first class passengers value the additional benefit of exclusivity. As the latter two buyer segments are willing to pay more for the additional benefits they value, airlines are able to charge different prices for the three different segments. Yet, some segments do not result in the service being priced higher but instead, provide higher demand. Consequently, whatever the prices charged must be dependent on how many buyers would show for each price point. Hence the sensitivity set involves the price/quantity set which determines how much the firm should price to obtain its required quantity. In the above example on airlines, the different prices set for the different market segments result in different volume of purchase. The highest volume is advanced fare economy class where the firm obtains higher revenue not from high price but high demand. Conversely, the firm obtains higher revenue from higher prices in first class. Finally, even if the price/volume relationship is known, the sale of the service in advance would result in uncertainty. Hence, the forecasting set involves how much of the firm’s capacity should be filled with the different quantity/price from different segments based on the forecasted distribution of demand. Using the above example of the airlines, it is important to understand that the firm might forecast more last minute higher fare economy class passengers and therefore might not sell all their capacity to advanced fare buyers earlier. The new revenue management system therefore captures the interdependence of the four decision sets in a service. However, the interdependence does not end here, as the following discussion will show.

The role of capacity Services differ across industries and although they share many similar characteristics, there has been no concerted attempt to understand how capacity is constituted in different service firms. Yet, as presented in Figure 7.1, capacity is an integral aspect of pricing and revenue management.

134

Buyers in aggregate

Value set

Attributes

Segmentation set

Benefits

Price

Sensitivity set

Allocation and forecasting set

Quantity

Capacity

Figure 7.1 Interdependence of the four decision sets in revenue management.

To understand the nature of the capacity problem, let me illustrate this with an example. Consider a cinema that has 300 seats. If there was no need for any ushers or a box office or other facilitating service, the capacity of the cinema would be 300. Suppose now that there is a need to sell the seats or usher the customers into the hall. If all customers arrive ten minutes before the film, there may not be enough time to sell 300 tickets before the film starts and perhaps after 200 seats are sold, the film would have started and 100 customers may just walk away as they would not want to miss any part of it. Of course, the firm should re-design the process, but the point I am making is that capacity is not merely the seats, but also the processes and operations that deliver the service. Consider the same cinema deciding to offer the attribute of having drinks served at your seat. Buyers who purchase tickets may do so because of such an attribute. However, if it is impossible to serve drinks to everyone, some customers may be disappointed. What this example illustrates is that a service firm’s capacity could be defined by its bottlenecks, and that processes and operations should not be excluded when considering how the capacity of the firm should be defined. In other words, when the supply of a service firm’s capacity is linked to the benefits delivered to the buyer, the delivery of the service and the capacity to deliver it depends on what attributes have been promised (i.e. the dashed arrow in Figure 7.1). Thus, the definition of a firm’s capacity may not be as simple as seats on a flight or the capacity of a lecture theatre for the delivery of an educational programme. Although the costs of delivering that capacity may be sunk at the point of sale, firms are now able to bring in flexibility of capacity in such a way that influences the design of the service. This allows the firm to use service design as a way of price discriminating between segments of markets, e.g. a service that you wait for might be cheaper than one that does not require you to wait, but the service processes and designs would be different and so would be the ‘capacity’ to deliver them. Consequently, even if the fixed costs are sunk and marginal costs are negligible, there is an argument for understanding how the fixed costs are spent to

Strategic pricing and revenue management 135 create the firm’s service capacity. This is because such costs could be spent on ensuring flexibility in capacity, which in turn could be used to create different value propositions for the market for second-degree price discrimination and more effective revenue management. While those conducting activity-based costings would attempt to calculate such costs, there has been no attempt to model the capacity (see Box 7.1). Bitran and Caldentey (2003)1 provided a general resource base model of capacity, though it remains a challenge how it could be manifested in practice across service firms. Box 7.1 Determining capacity – an operations perspective It can at least be argued that the study of capacity is the central concept of the management discipline termed operations management. All major operations text books begin with a discussion of the transformation of inputs into outputs, be that in the public, private, manufacturing or service context. It is this transformation that is capacity constrained. The study of operations strategy attempts to decide how to best use that capacity. Operations strategy is often divided into outside-in and insideout 2 perspectives. Outside-in is exemplified by Hill.3 Here, the organisation analyses the marketplace, then decides on its order qualifiers and order winners and then configures the internal operation to deliver on that market requirement. For example, in a situation where price is crucial, the internal operation will be organised as a flow line to achieve lower unit costs. This is the concept of strategic fit; a company configures its resources to the demands of the market. This once-dominant view however, has been challenged by those taking an inside-out perspective. For example, Hayes and Pisano (1994)4 argue that companies should develop capabilities that are hard for competitors to imitate; the focus should move from products to one where capabilities provide the competitive advantage. This debate is central to the study of capacity. In the outside-in world, capacity is relatively fixed, with resources (IT, machines and people) being combined in the best way to meet a market need. In the inside-out world, the goal of operations is to be capable of moving between different competitive positions. Whilst much of this analysis comes from manufacturing, it has resonance with the service sector. Take for example, the case of the internet bank dedicated to the provision of low-cost banking. It configures its operations in such a way as to process large volumes of applications. It applies dedicated IT, tightly couple its internal systems, train staff and is geared up to process high volumes at low unit costs. As long as the customer is of a certain type, the bank can process that application and deliver the product (mortgage, loan, insurance etc) very quickly. It does this by limiting variety; it filters out unwanted applicants through a series of decision rules. The capacity in terms of volume is relatively unconstrained. The capacity limitation is on the variety the bank can deal with.

136

Buyers in aggregate

However, this outside-in perspective begins to break down when we consider the case of the financial institution that takes applications from customer groups normally refused a loan, eg for being too old, holding a dangerous job or one with huge earnings fluctuations, or sociodemographic profile, etc. This company might have much lower volumes but much greater variety; it finds it difficult to ply specialisation. IT systems continue to hold data on the customer, but the decision process required to process a loan application is far more complex: What is their credit history? How many previous loans have they had? Do they have loans with other companies? Have they frequently changed addresses? Are they on the electoral role? Many of these questions can only be answered through face-face enquiry which involves multiple interactions and many different forms of evidence. These applications then often go to ‘wide of scheme’ units which make further investigations into the customer’s background. In such circumstances, activities become de-coupled, some staff become experts at one ‘type’ of problem whilst others act as a general first line, then processes become fragmented with multiple hand-offs. Identifying capacity in this scenario is challenging. The issue is one of matching variety, best expressed as Ashby’s Law of requisite variety, ‘The variety in the control system must be equal to or larger than the variety of the perturbations in order to achieve control’.5 Put more simply, the control system must be able to match the variety of inputs (things we sell) and the dynamism of those inputs. This has huge implications for capacity. If we want to sell a large amount of product variants, we need to be able to match that internally. Not only that, but we must be able to match the alternative states of those variables. Organisations do this through their internal processes; product signals get sent to back-office processes which deliver those products. Often, such is the variety in inputs that identifying the capacity of any service process is highly problematic. Some companies solve this problem by attenuating variety, both in the sales and operations activities. Take the case of a logistics company delivering parcels. The various product offerings relate to such aspects as parcel size, delivery location and time, e.g. before 10am, next day, threeday, etc. The company can in fact take anything anywhere (e.g. through buying space on commercial airlines at a significant premium) but capacity within its standard routes is constrained. Planes can fly to a range of destinations; its motor vehicles (trucks, vans, etc.) have considerable potential but are constrained by EU law on driving distances; and whilst the staff can adapt to load the vehicles according to need, the size of the pallet is fixed and so is the number of pallets per vehicle. There is however, substitutability of resource. For example, because of the unknown nature of the variety in demand, it is impossible to know until late evening where its planes need to fly to next day to make optimal parcel delivery. The actual capacity loading of the resources – people,

Strategic pricing and revenue management 137 planes, lorries, trucks, small vans, and cars – is unknown until a cut-off point is reached around 8pm for flights that take off at 10pm. Finally, some companies allow almost limitless variety in inputs. Take the case of the car insurance company that processes claims. It has a staff force of around 200 people but claims never arrive in standard forms; all are unique, and the daily capacity depends not only on the volume of calls but more importantly, the circumstances of the claim, eg type of accident, type of policy, was anyone else involved, etc. The capacity of that facility depends on the nature of the inputs, when the calls occur, what the variety is and what the volume is. The question is, does demand follow or lead capacity? Historically, operations management has taken the view that demand leads and capacity follows, and that capacity is relatively fixed.6 In an environment where significant variety is necessary, determining that capacity is highly complex. In an environment where variety is significant and rapidly changing, Hayes has argued that operations must develop capabilities to switch between different types of capacity, and it is this capability to switch that provides the competitive advantage for organisations. Source: Maull, R.S., Centre for Strategic Operations & Research, University of Exeter.

With the new revenue management system, other strategies could be employed on demand for higher revenues, and I present the following four strategies (following from the seven strategies in Chapter 4).

Strategy 8: re-segment, re-design and re-price Much of the consumer market today is unpredictable. Merely 20 years ago, certain behaviours were often positively correlated with certain lifestyles, ages, income levels or even geographical locations. In other words, the young behaved young, the old behaved old, people with money spent more, families had a father and mother and so on. Today, the old act young and vice versa, people with less money tend to spend more (as rising credit card debt can attest), and many families have only one parent. With globalisation, even cultural behaviours and lifestyle attributes are becoming more complex. Faced with such changing times, traditional segmentation through geographic, demographic and even some psycho-graphic approaches are proving to be less effective in predicting purchasing behaviour. Even when sophisticated data-sensitive software is used, many market segmentation schemes are not very successful.7 It seems ironic that in a world where so much information can be obtained, marketers are becoming less able to understand their customers. The lack of understanding leads to firms being unable to identify who they should be marketing to and how markets should be segmented. Service buyers could be consuming a particular service, and yet the firm may not know what about the service that is attractive or satisfactory to these buyers. This in turn

138

Buyers in aggregate

impedes the firm’s ability to customize and price for market segments that could want more out of the same service. As buyers have varied needs, the benefits and outlays mentioned in the earlier chapters in Part I are not uniform across all buyers. They also differ in terms of what attributes are important and which outlays are costly, to whom non-price outlays in particular, serve as a useful tool in price discrimination. Not all buyers have the same outlays and not all outlays are convertible at the same price. This is where the pareto loss becomes a tool to segment markets and discriminate on pricing. Firms should endeavour to understand their buyers by blueprinting the ‘service encounter’ – the period of time during which buyers experience a service. The service encounter could be short, e.g. a minute for a phone call, or a month-long cruise. The encounter could also be made up of disjointed service components such as health care, where customers return to a hospital or a clinic over a period of time. Most services management or marketing books will encourage the firm to manage the service encounter for a pleasant and satisfying experience. Customer satisfaction impacts on expectations when the customer is repeating his purchase, and also builds word of mouth and reputation. Since price is based on expectation, the amount of revenue a firm is able to derive from buyers is very much influenced by how well the service is delivered (see Figure 7.2). What is also important in the pricing of a service is that there are two service encounters – the time when the buyer purchases a service, and the time when the buyer consumes the service. Some services are purchased online and consumed at another location, sometimes they are both located in the same place. However, the service encounter at purchase is subject to many influences that could dissuade the buyer from buying, including the presence of a competitor, i.e. purchasing online or through a travel agent. Hence, the service encounter is heterogeneous and is subjected to influences. Research has also shown that how buyers perceive a service has much to do with the impact of environmental stimuli. These include the density of people (crowds), lighting, sound, scents, Step 1

Step 2

Step 3

Step 4

Step 5

Step 6

Identify the process to be blue printed

Identify the customer or customer segments

Map the process from the customer’s point of view

Map contact employee actions, onstage and backstage and/or technology actions

Link contact activities to needed support functions

Add evidence of service at each customer action step

Figure 7.2 Building a typical service blueprint (source: Zeithaml, V., Bitner, M.J. and Gremler, D. (2006) Services Marketing: Integrating Customer Focus Across the Firm 4th edition. New York: McGraw-Hill International. Reproduced with permission of the The McGraw-Hill Companies).

Strategic pricing and revenue management 139

Customer


/


/

Employee

Encounter (during purchase and consumption)
/


/

Environment

Process

Figure 7.3 The service encounter and impact of external stimuli.

queues. Figure 7.3 highlights how the environment, the employee, the process and even the buyer himself can enhance (+) or inhibit (–) an encounter, resulting in positive or negative experience of the service. In designing service encounters that would ensure the highest revenue, the firm would do well to blueprint the service-buying decision, as well as the consumption process. Service blueprinting isn’t merely tracking the processes of how the service is being purchased and consumed from the firm’s perspective, it’s about tracking the buyer’s physical, emotional and cognitive states through the purchase and delivery process.8 By blueprinting the firm’s selling and delivery function and mapping it onto buyers’ purchase and consumption and including emotional states, the firm can identify the moments of truth (i.e. when buyer and firm interacts), critical points of satisfaction and dissatisfaction, and add up the ‘costs’ of purchase and consumption to see how such costs could be converted into revenue. In doing so, firms would be able to re-segment buyers by selecting different types of variables obtainable through the preferences in the purchase and consumption process (e.g. cash vs credit card buyers), re-design their service based on different processes and above all, re-price for the new buyer segments. The result could be much higher revenue from very much the same costs of delivery. Ikea is an example of this. At the time where the conventional wisdom for furniture retailing was about quality, variety, delivery and in-store assistance, Ikea chose not to provide in-store service and delivery. Instead, Ikea shoppers are able to dine in a café that serves delicacies such as lingonberry tarts, smoked salmon and meatballs; mothers can drop their children off at a well-designed and well-managed daycare with lots of activities for kids. The company recognised that value lay in the shopping experience, i.e. not the gloomy warehouse-like environment of discount furniture retailers, but while still being in the discount furniture retailing market, is able to command market share. The Ikea story also illustrates an important point – that providing better value does not always mean higher revenue by increasing price (Ikea is proud of being a ‘low-price’ retailer) but by increasing demand.9 Often, firms assume that high revenue means market segments that are willing to pay a higher price. In reality, improving quality and the value offering of a service may mean higher revenue from increased demand. This is important

140

Buyers in aggregate

because if a firm pursues a strategy where it is able to improve quality but not be able to increase price, it must have sufficient capacity to cater for the increased demand, otherwise revenues will not improve. It is for this reason that services having a large capacity (e.g. a 40,000-seat stadium) may choose lower price customers that turn out in droves over high price customers (with less of them around). Box 7.2 The psychology of waiting lines Waiting is a huge non-monetary cost for many people. We spend our time waiting for the bus, waiting at the photocopier, waiting for food, waiting to pay, waiting for someone else, etc. Although the best solution to reducing this cost is to find a way to eliminate waiting, this may not be possible. When service firms aren’t able to prevent waiting, they may be able to minimise its inconvenience. The following is a list of effective waiting strategies based on the psychology of waiting lines: 1 Unoccupied time feels longer – is there a way you can occupy your customer while they are waiting? 2 Pre- and post-process waiting feel longer than in-process – can you receive their forms and note their requests before attending to them fully? 3 Anxiety makes waiting seem longer – have you given them enough information about how long it would take, and what the process entails? 4 Uncertain waiting is longer than known, finite waiting – can you tell them how long it will be to their turn (see Figure 7.4)? 5 Unexplained waiting seems longer – can you tell them why the queues are so long? 6 Unfair waiting is longer than equitable waiting – do you have ways to ensure that no one cuts the queue? 7 People will wait longer for more valuable services – are you making your customers wait in the same line for important enquiries vs smaller and more trivial ones? 8 Waiting alone feels longer than in groups – can you attend to families at the same time? 9 Physically uncomfortable waiting feels longer – have you made sure that the customer is comfortable while waiting, e.g. seated down with a number, providing a television and/or music for entertainment, ensuring the right temperature, etc? (see Figure 7.5). 10 Waiting seems longer to new or occasional users – can you distribute leaflets or play a video to explain how your service will be delivered and the processes that customers are going through? Source: Maister, D. (1985) ‘The Psychology of Waiting Lines’. In (Zepiel, A.S., Solomon, M.R. and Suprenant, F.C. (eds) (1985) The Service Encounter. Lanhan, MD: Lexington Books.

Figure 7.4 Uncertain waiting is longer than known, finite waiting.

Figure 7.5 Occupied time feels shorter.

142

Buyers in aggregate

Strategy 9: segmenting and pricing through self-selection Yet, when buyers are less predictable, so is their valuation of the attributes within a service. Hence, even when employing benefit segmentation, firms are still left trying to predict which groups of buyers would benefit from which types of service attributes. Consequently, it may not be commercially prudent to tailor a service only for pre-determined segments. In this respect, a menu of services with flexible attributes allows the market to self-select. Let’s take as an example, the sale of garlic. In many supermarkets, garlic is available in various forms; you can buy them peeled, diced, in pre-selected packets of whole bulbs, or you can buy them loose, which gives you the freedom to select your preferred bulbs. All four forms of garlic are usually priced differently, with a premium on the first three. Taking a random group of 100 customers, the firm will have no idea which of the 100 would prefer one form to the other. Yet if all 100 customers were to walk into the supermarket to buy garlic, they would each self-select their segments. Those who may not know how to choose garlic may prefer pre-selected packets, while others who do not like the smell of garlic on their hands may choose the diced option. Still others with high time costs may not want to waste their time choosing garlic, and would opt for one of the first three options. Whatever the reason, the product choices available have performed a major marketing function. They have effectively segmented, separated and immediately targeted the market with discriminating prices. Furthermore, as buyers self-select the segment to which they belong, there is no cannibalisation. Whatever was previously private information (i.e. preferences) has now been revealed to the firm, which in turn is able to obtain a price premium from the segment that is willing to give that premium. Consider yet another example; a retailer in a ski resort with a local population. By selling their products at a low price, the local population makes up the bulk of demand but the retailer loses the opportunity to charge wealthy ski vacationers a premium. If the retailer prices high, vacationers will buy but locals will probably go down the mountain to stock up for their needs. A simple self-selection segmenting strategy of posting high prices and yet providing coupons in the local newspaper that lowers the final price would usually separate the market quite effectively. Vacationers, who are usually more well-off and do not mind paying a premium, would not normally seek out the local newspaper to cut out the coupons, even if they knew about it. The locals therefore get their lower prices and the retailer profits from both market segments with minimum cannibalisation. Clearly, there is more to coupons than merely promotion. This idea of segmentation through self-selection originated from the economics concept of a ‘designed contract’ for compensating an agent who possesses more information than the agent who offers the contract. By choosing a contract, the agent with more information reveals the truth about their preference. In marketing, this ‘designed contract’ can be deemed to be a produce-price pair and the product-price line as an array of contracts offered by the firm who

Strategic pricing and revenue management 143 does not know the identity of the buyers in his market.10 From the array, buyers choose to buy different pairs, thus revealing what they truly value. This concept was proposed by the Nobel Laureates of Economics (2001) – Akerlof (1970),11 Stiglitz12 (with Rothschild 1976) and Spence13 (1973) – on asymmetric information and developed for market segmentation purposes by Moorthy (1984).14 As theoretical models go, translations into real world applications are often slow in coming. However, the above two examples provide an illustration of how good theory can translate into innovative and efficient marketing practice. Service choices (i.e. a service that is differentiated on several dimensions), if cleverly designed, are able to separate markets to the degree that traditional segmentation approaches could never have achieved.15 How does a firm design product choices to aid segmentation based on selfselection? This is certainly easier said than done. As many marketers would attest, the product is often a “given” and not easily changed. Indeed, as Crawford and Di Benedetto (1999) put it: ‘new products process is exceedingly difficulty. Hundreds of individuals are involved in the creation of a single product but all are from separate departments (sales, engineering, manufacturing, etc.) where they may have their own agenda’.16 Service delivery, however, often require departments such as marketing, operations, human resources and finance to work together to sell and deliver the service. Hence, the firm needs to be much more flexible to cater to the market. To design products that could result in segmentation through self-selection, three principles need to be followed: 1

2

3

There must be sufficient incentives within each service, for market segments to separate on their own. This means that the attributes that differentiate between segments must be clear. This could be achieved through various means, e.g. a conjoint analysis of the market where preferences and tradeoffs between one attribute and another can be discerned. Most importantly, what I term to be the separating variable that helps the firm to separate markets must be found and the firm can then act on re-designing the service around that variable. For two different market segments to choose different services, care must be taken to ensure that it is not in the interest of either segment to mimic the behaviour of the other. In the example of the ski resort, the vacationers may know that they could get a lower price if they were to get a newspaper but may not be willing to do so because it requires more effort. Finally, the array of service options presented must be in such a way that each buyer’s choice is truth-revealing. Buyers choosing one option over another inform the firm which segment they belong to.

The benefit of such a policy extends beyond the cost savings the firm would enjoy. When buyers self-select, they also enable the firm to price-discriminate and obtain higher revenues. The Robinson–Patman Act (US) (1936) specifies that a firm cannot deny a segment access to what is being offered to another

144

Buyers in aggregate

segment, unless legally allowed to do so. Through self-selection, all product choices are accessible to all segments, yet each segment willingly pays a different price because they have no interest in mimicking the other segment (see Box 7.3 on steps to create separating markets). Box 7.3 Six steps towards separating markets and differentiated pricing 1 2 3 4 5 6

Blue-print the entire service purchase and consumption from the buyer’s perspective. Blue-print the emotional and psychological states of the buyer. Identify the benefits obtained by the buyer and what attributes have delivered them. Identify how the attributes are delivered. Analyse which attribute could be a separating variable. Provide the service with and without the attribute at different prices.

Traditional revenue management tends to rely on market segmentation practices that may not be efficient, resulting in cannibalisation between segments. ‘Rate fences’, as it is commonly known in revenue management literature, becomes more common to reduce such cannibalisation. Yet, erecting such fences may result in perceived unfairness.17 Furthermore, such segmentation efforts would result in increased monitoring and coordinating of costs. By adopting an approach of changing the attributes of a service, or providing a menu of service-attribute choices, buyers would self-select, as all product/service choices are accessible to all segments. In the earlier example in Chapter 3, a simple matter of changing a fixed-time ticket to allow flexible consumption times immediately reduces the buyer’s risk of not being able to consume a service, as buyers are not constrained on when they can travel. Since the choice of ideal travel time is known only to the individual (and therefore is private information), different degrees of flexibility at different prices allow buyers to self-select, and this could help to increase revenues. In other words, by tweaking service attributes, the firm can better meet the needs of different buyers. All this means that although the ability to segment is necessary to be able to practise revenue management, the segmentation does not have to be performed by the firm. With an increasing amount of data available about buyers, firms could provide a menu of choices that could be less costly than the traditional costs of targeting, coordinating, erecting and managing rate fences.18 Box 7.4 Self-selection in the credit card industry How do you segment credit card users? Ideally, firms would like to attract the biggest spenders since they would provide the highest revenue in terms of merchant fees and perhaps interest on delayed payment. Yet, big

Strategic pricing and revenue management 145 spenders are hard to locate. It doesn’t necessarily correlate with income (big spenders could run up huge debts amongst those with low income), nor lifestyle (the firm may not know what the buyer is spending on) or merchandise (almost everything could be purchased with a credit card nowadays). One way the credit card industry have found to be most effective is to give back the most freebies to those who spend the most. Hence, frequent flier miles, points and gifts are copiously bestowed upon those who charge the most on their cards. This tactic can only attract those who spend; those who don’t spend enough on their credit cards would not be eligible for the freebies and therefore would not be drawn to the card.

Strategy 10: managing demand and supply through re-sale and refunds Chapter 6 discussed how one consequence of the separation of purchase and consumption is that buyers may not be able to consume. Hence, depending on the demand distribution across time and the level of non-consumption and capacity firms might be prepared to manipulate advanced and spot prices to optimise profits. For example, if non-consumption is high and spot demand is strong, the firm may have an incentive to sell at discounted prices to advanced buyers because non-consumption allows the firm to earn additional re-selling revenue on top of the discounted prices. This may be a strategy firms could employ to stimulate demand, particularly when competition is keen. Paradoxically, it may even be more profitable for the firm if advanced buyers do not show up. Consequently, there could be instances where the firm could provide partial or even full refund to advanced buyers should they be unable to consume. Providing refunds for the buyer’s inability to consume is widely practised in the airline industry. Some tickets even provide a full refund to the buyer. Generally, a full refund means that the ticket purchased can be returned to the airline for a complete reimbursement of the price at any time – even after the proposed date of travel. Furthermore, many airlines allow a refund on non-utilised sectors (e.g. if the buyer has purchased a return ticket but only utilised one leg of the ticket). There is a fundamental difference between a full refund of this nature and those given out by retail shops for goods purchased. In the latter, the refund is given (or promised) if the firm fails the buyer, i.e. the compensation is provided to the buyer due to the firm’s failure to deliver the benefits, according to the buyer’s perception. In the former, refunds are promised for buyer failure i.e. the buyer’s inability to consume. Png’s model19 attempted to shed some light on this phenomenon. While he found that firms’ advance orders are not optimal, his study showed the profit maximising strategy is to insure the risk-averse buyers by compensating them when their valuation is low and charging them high when their valuation is high.

146

Buyers in aggregate

However, this strategy requires the advanced buyer to face the risk of unavailable capacity at the time of consumption. In other words, Png’s advanced buyer does not actually buy the service; he merely buys the option of purchasing the service at the time of consumption, at a stipulated price, i.e. a price option. This is in contrast to the buyer failure refund of the type practised by airlines, where it is clear that the buyer buys with a firm advance order (i.e. capacity is guaranteed) with a refund in the event of a low valuation. Xie and Shugan (2001) showed that firm advanced orders with a refund offer may be optimal as the firm is able to obtain a higher price in advance to compensate for the cost of refund, as well as derive greater profits from cost savings in not having to serve these buyers.20 Providing a refund is a useful strategy since high valuation risk buyers may be enticed to buy in advance, instead of seeking substitutes, and buyers may be prepared to pay higher for a refund offer. However, both the Png and Xie–Shugan models do not take into account the fact that there may be advanced buyers not consuming and that non-consumption frees up the capacity to be resold. Furthermore, buyers in aggregate form a heterogeneous market, and demand dynamics may influence the premium for refund. Hence, offering a refund to advanced buyers allows the firm to earn higher revenue in four ways. Refunds for higher price Firms can often obtain a higher price from buyers who buy in advance because buyers value the refund as insurance. If they are not able to consume, they get their money back. Since buyers are risk averse and firms are risk neutral, the firm is often able to get a premium for the refund offered. In addition, if buyers do turn up, firms would have obtained a higher price for the service. Refunds for higher demand The market for the service in advance could be very small because buyers are not willing to buy for fear of non-consumption. Hence, a mere offer of a refund may expand the market to the extent that the firm might not even wish to increase their price (this, of course, would depend on demand elasticity and the firm’s capacity). This could be a useful strategy for services with large capacity, e.g. stadiums, etc. Refunds to benefit from the re-selling of capacity relinquished Even when the firm has to refund buyers who cannot consume, the firm may be able to re-sell the capacity to spot buyers. Recall that service buyers buy use, and not ownership. Hence, the capacity unutilised may be re-sold for higher revenues. Last minute offers and standby buyers are ways to increase spot demand so that there are buyers at spot for re-sale.

Strategic pricing and revenue management 147 Partial refunds for higher price The firm could offer partial refunds for the portion of the service that is unutilised. For example, a flight that has a returning sector may not be used by the buyer. If the firm allows partial refunds, the firm would be able to return some of the price to the buyer and re-sell the seat not used. More importantly, the buyer would have paid higher for the used portion of the service because of the refund being only partial. The buyer is happy because they would have just wasted the return ticket so getting something would have been better than nothing. Of course, the firm could have just let it happen and not have to pay the buyer anything, but that misses the point. The point is that if the offer to allow partial refunds is made from the beginning and buyers know about it, they may be more willing to buy multiple services thereby increasing demand and revenue for the services overall. Firms sometimes forget that demand is not static and fail to see what demand they could have from such a refund offer.

Strategy 11: selling availability of the service There are many services where it is impossible for buyers to know in advance how much they value it. A phone call is a typical example. The buyer often does not know when they need to make a phone call. Yet, when it is necessary to make that call, the buyer cannot afford to pay the high costs of getting the service at that moment, e.g. the time required to sign up for a mobile or home phone service. Instead, the buyer buys the assurance that the ability to call is available whenever the buyer wants it. This they do through subscribing to a mobile phone or home phone service. Previously in Chapter 3, I presented that the buyer’s utility from consuming a service is state dependent, i.e. there is uncertainty in whether the buyer will actually consume the service, or when the buyer will value the service. However, this assumes that the buyer can contract to buy for a specified future time where they wish to consume the service and barring any unforeseen circumstances, the value should be what is expected. This reasoning seems to hold as long as buyers of a service are certain of the time that they are consuming it, e.g. a hotel room or a flight. However, the assumption seems inadequate to explain continuous ‘always-on’ services such as mobile telecommunication. Here, buyers purchase in advance (through subscription) without knowing for certain when they will be consuming the service. In such services, unavailability risk is high, as buyers do not wish to run the risk of the service being unavailable at the time they need it. Similarly, valuation risk is also high since buyers cannot ascertain when they wish to consume nor can they predict the state at the time of consumption. Hence, the perception of ‘always-on’ seems to be convenient in overcoming the buyers’ risk of unavailability and state dependent valuation risk. The former is alleviated through the perception of availability of capacity at all times, and the latter is alleviated through flexibility and allowing buyer choice of consumption time, despite buyer value being uncertain at any point in time. In

148

Buyers in aggregate

truth, such services may not be ‘always-on’; merely that they are always available whenever the buyer chooses to consume it, such as telecommunication services. From a capacity standpoint, there is a need to differentiate between the demand for availability and the demand for delivery. The firm could sell availability as a separate service (insurance) whilst the delivery may or may not materialise, resulting in more capacity than can be consumed. This could result in the selling of capacity way over the firm’s capability and improving revenues overall. Clearly, such a strategy carries risks of not being able to deliver when demand for delivery suddenly goes up. This could be resolved by planning the capacity of the service and working out strategies to scale it (e.g. buying in additional capacity when the demand for consumption is high). For example, Toucan (see Figure 7.6) charges a flat rate for the availability of the service. Is this a profitable strategy? Firms may have to calculate the number of buyers who do not use the service and those that do to ascertain how much they should charge but that would miss the point. The point of charging a flat rate is that buyers themselves are willing to pay a flat rate for the availability to make unlimited calls (in the case of weekend calls) and in the long term, the rare times that such numerous phone calls are made during the weekend is of substantial value to the buyer that they may be willing to pay for the weekends when the service is not used at all.

Figure 7.6 Converting from pricing on delivery to pricing on availability: Toucan charges a flat rate whether or not you use the service (source: www.Toucan.com).

8

Conclusion

With all that has been discussed in the preceding chapters, it is clear that service pricing is a complex task. Yet, research has shown that pricing is more credible when they are easily understood and simple.1 Hence, service firms are tasked to communicate value without unnecessary complexity even if the process of arriving at the prices charged could be complex. From the buyer’s perspective, the risk of buying a service is already higher than that of a good so buyers expect pricing strategies to be more transparent so that they have greater trust and confidence in the firm. Hence, pricing strategies presented in this book have to be deliberated carefully before being considered for implementation.

Strategise with care: the need to understand how buyers and stakeholders view service pricing strategies In Chapter 1, I made a note that where any of the three macroeconomic functions of price fail to function in certain industries, regulators would often step in. Regulation is not the only penalty for what may be perceived to be unfair pricing. In the US where there isn’t a free national health service, but where much of healthcare is provided through insurance, hospitals have been accused of charging the uninsured exorbitantly high prices, while large health care companies such as Medicaid and Medicare are charged much lower.2 In environments like these where hospitals are increasingly being asked to be responsible for providing care to those with lower financial means (to justify their taxexempt status), pricing strategies could backfire. Lawsuits have been filed against hospitals and the lack of transparency in pricing has contributed to the increase in litigation.

Service pricing vs goods pricing In many service firms, financial controllers, accountants and other senior managers have had difficulty in grasping how services should be priced. This is because profitability of a price level can only be ascertained ex-post (after the event), where the amount of capacity utilised at the price charged can be ascertained only then. This can certainly be disconcerting to firms that need to know

150

Conclusion

beforehand if the price charged will result in profitability. Unlike goods where the production of the good comes with its variable cost, and profitability can be ascertained on a per unit basis, services often have negligible variable costs and the profitability can only be ascertained on an overall basis and only after the sales and production are concluded. As an example, how does Ryan Air or Easyjet stay profitable by selling a seat for only £5? Only because very few seats are sold at that price level and as the capacity fills, prices become progressively higher and by the time the flight departs, the average price of a seat is probably much higher to the extent that the revenue of the entire flight makes it lucrative for the airline to fly on that route. Conversely, the airline could sell at a high price initially and drop prices down to £5 a day before departure but strategic buyers would then wait till the last minute and revenues may not be as high. Clearly, setting a price that would lead to profitability requires the firm to accept uncertainty as part of the pricing decision, and to invest in demand modeling/forecasting, and other decision support tools that could aid the pricing decision. With services being perishable and having no stock or inventory as assets after production to speak of, the anxiety to get the price right is further compounded; it is no wonder that making pricing decisions for services are regarded to be more perilous. Box 8.1 shows how Belgium’s Charleroi airport got into trouble when it tried to price its service rather differently. Box 8.1 Pricing airport services In February 2004, The Times3 reported that a secret deal between low-cost airline Ryanair and Belgium’s Charleroi airport involving subsidies and aids had been declared illegal. The low-cost carrier had purportedly been charged only C1 per passenger by the airport, instead of the normal C8–C18. It had also been offered a one-off aid of hotel and subsistence, pilot recruitment and training, bonus for opening new routes, and funds for promotional activities. The European Commission ordered Ryanair to refund the illegal subsidies of up to C4.5 million from this special deal, declaring that it broke EU laws on state aid. This ruling however, clearly demonstrated how little-understood is pricing in the service industry. An airport, like an airline, is often saddled with high fixed costs and low marginal costs, and its capacity to handle a fixed number of flights based on those fixed costs, is the only means by which the airport is able to obtain revenue. Just how one would begin to price that service in order to sufficiently cover the fixed costs, has been a conundrum to many a revenue manager. Just like airlines, airport services can be charged differently depending on the time of purchase (closer or further from perishability) and the time of consumption (the actual day the ground handling services are required). Therefore, airports – and any other service – could and should price-

Conclusion 151 discriminate between those who can bring them volume and those who can’t. They could price low for airlines that can commit to buying that capacity early, since every day of unused capacity cannot be stored and is perished. Hence, the problem in the Charleroi–Ryanair deal was labelling; the low prices given to Ryanair should not have been considered ‘subsidies’ and ‘aids.’ Instead, they were merely market-penetrating price decisions that may allow the airport to raise prices for airlines that come later. Charleroi was merely doing a ‘Ryanair’ in the way it priced its services (no doubt, inspired by its client), and ended up being penalised for it. Source: adapted from Ng, I.C.L. (2004) ‘EC Judgement on Ryanair shows pricing ignorance’ Travel Trade Gazette, U.K. and Ireland Edition, 1 March 2004, Issue 2603.

More channels, more segments, more brands Many service industries are starting to change traditional lifestyles, creating value that is elusive to capture. There are now more ways than ever to sell and deliver services. From the selling perspective, supermarkets can now sell insurance and broadband services and the mobile phone can now be a channel to sell news, music and books. From the delivery perspective, technology is now able to bring healthcare and education to the home, and banking to the beach via your laptop. With the proliferation of sales and delivery channels, service entrepreneurs and innovators are able to discover ways and means to uncover latent need for convenience and time, and meet them in innovative ways. Markets are now being divided into finer segments, leading to the term micro-segmentation, where it is now possible to price for each of these micro-segments. Adding to the complexity is the proliferation of brands worldwide. Brands create unique perceptions, appeal to segments through their identity, personality and meaning. Capturing that intangible brand value in the price of a service is a monumental task. Furthermore, the impact of globalisation is increasingly being felt the world over. While more markets are accessible thereby increasing potential demand, there is also greater pressure on firms to provide the same services at lower costs since companies abroad can now offer the same services as the firm down the road. Accountants in India are able to assist Americans in completing their tax return without leaving their country and X-rays taken in Britian could be analysed by radiologists in Russia. The landscape of the service economy is changing fast, posing a challenge to economists, regulators and marketers.

Cross-functional approach towards pricing policies With such challenges, it is clear that the pricing decision is not one that is made by a single person or even department. Firms need to evaluate their current organisational model to achieve their pricing objectives.4 This includes addressing the following needs:

152 1

2 3

Conclusion The need to understand the risks in making the pricing decision within the service firm, and how the risks and accountability is shared between customers, employees, technology and senior management. Otherwise, the uncertainty in the pricing decision would lead to decisions taken based on politics or risk-aversion behaviour (such as letting technological systems set prices, etc.). The need to create transparency within the firm on how prices are actually set and the objectives of each price point. The need to build a cross-function pricing council within the firm to identify opportunities, evaluate threats and make strategic decisions. Otherwise, pricing will be relegated to become a crude, tactical tool for convenience and quick results.

Service firms need to evolve and adapt to the constant change sweeping through their industries. Top companies now ensure that their pricing policies are decided by departments that are stakeholders of the pricing decision. By ensuring that executives from across the organisation are involved in the intricacies of pricing discussions, more opportunities can be discovered and pricing policies could be more creative, allowing for greater choice and better ability to serve customers’ needs. Cross-functional pricing decisions provide opportunities to understand buyer’s choice, and allow the firm to pull in all departments to ensure an optimal pricing policy that generates higher revenue. With third-generation mobile telephony, TV on the web, music on the move, convergence of mobile and internet as well as other technologies, new pricing strategies have to be clever, creative and innovative.5 Firms that are any less dynamic run the risk of being left behind.

Notes

1 Introduction 1 Xie, J. and Shugan, S.M. (2001) ‘Electronic Tickets, Smart Cards and Online Prepayments: When and How to Advance Sell’, Marketing Science, 20 (3), pp. 219–243. 2 Bank of England Quarterly Bulletin ‘Inflation and Growth in a Service Economy’, November 1998. 3 Liebhafsky, H.H. (1968) The Nature of Price Theory, revised edn. The Homewood: Dorsey Press, Inc. 4 Diamantopoulos, A. and Mathews, B. (1995) Making Pricing Decisions: A Study of Managerial Practice. London: Chapman and Hall. 5 Smith, A. (1776) An Inquiry into the Nature and Causes of the Wealth of Nations. London: Methuen and Co. 6 Potter, D.V. (2000) ‘Discovering Hidden Pricing Power’. Business Horizons, 43 (6), pp. 41–48. O’Connor, P. (2003) ‘On-Line Pricing: An Analysis of Hotel-Company Practices’. Cornell Hotel and Restaurant Administration Quarterly, February, pp. 88–96. 7 Nagle, T.T. and Holden, R.K. (1995) The Strategy and Tactics of Pricing, 2nd edn. Englewood Cliffs, NJ: Prentice-Hall. Rao, V. (1987) ‘Pricing Research in Marketing: The State of the Art’. Journal of Business, 57 (1) part 2, pp. S39–S60. 8 Wölfl, A. (2005) The Service Economy in OECD Countries, STI Working Paper2005/3. Paris: OECD. 9 OECD Business and Industry Policy Forum Series (2000) The Service Economy, Final Report of the Business and Industry Policy Forum on Realising the Potential of the Service Economy. Paris, France: OECD. 10 World Trade Organization (2004) Recent Trends in International Trade Policy Developments. Geneva: WTO. 11 Vargo, S.L. and Lusch, R.F. (2004) ‘Evolving to a New Dominant Logic for Marketing’. Journal of Marketing, 68 (January), pp. 1–17. 12 Lohr, S. ‘Academia Dissects the Service Sector, but Is It a Science?’. New York Times, April 18, 2006. 13 Silvestro, R., Johnson, R. (1990) The Determinants of Service Quality – Hygiene and Enhancing Factors. Warwick: Warwick Business School. 14 Hill, T.P. (1977) ‘On goods and services’. Review of Income and Wealth, 23, pp. 315–38. 15 Sasser, W.E., Olsen, R.P. and Wyckoff, D.D. (1978) Management of Service Operations. Boston: Allyn & Bacon. 16 Berry, L.L. (1980) ‘Service Marketing is Different’. Business, 30 (May–June), pp. 24–29. 17 Lovelock, C.H. (1983) ‘Classifying Services to Gain Strategic Marketing Insights’. Journal of Marketing, 47, pp. 12–17. 18 Zeithaml, V.A. and Bitner, M.J. (1996) Services Marketing. New York: McGraw-Hill.

154

Notes

19 Gronroos, C. (2000) Service Management and Marketing: A Customer Relationship Management Approach. Chichester: John Wiley & Sons. 20 Fitzsimmons, J.A. and Fitzsimmons, M.J. (2001) Service Management, Operation Strategy and Technology Strategy. New York: McGraw Hill. 21 Gummesson, E. (1994) ‘Making Relationship Marketing Operational’. International Journal of Service Industry Management, 5, pp. 5–20. 22 Grönroos, C. (2000). Service Management and Marketing. A Customer Relationship Management Approach, 2nd edn, Chichester: John Wiley & Sons. Lovelock, C. and Wirtz., J. (2003) Services Marketing: People, Technology, Strategy, 5th edn. Englewood Cliffs, NJ: Prentice Hall. 23 Shostack, G.L. (1977) ‘Breaking Free From Product Marketing’. Journal of Marketing, 41 (April), pp. 73–80. 24 Lovelock, C.H. and Gummesson, E. (2004) ‘Whither Services Marketing? In Search of a New Paradigm and Fresh Perspectives’. Journal of Service Research, 7 (August), pp. 20–41. 25 Sampson, S. (2006), ‘Paradigms for the Study of Services’ Proceedings of the 9th International Research Seminar in Service Management, La Londe, pp. 708–735. 26 Gronroos, C. (2001) Service Management and Marketing: A Customer Relationship Management Approach, 2nd edn. Chichester: John Wiley and Sons. 27 Cave, B. and Varnojen, S. (2004) ‘International Services Statistics Strategy and Coordination – Problems and Progress with Price and Volume Measurement in the Services Industry’. Statistics Journal of the UN, ECE21, p. 259. 28 Zeithaml, V.A., Bitner, M.J. and Gremler, D.D. (2006) Services Marketing, 4th edn. New York: McGraw-Hill. 29 Dean, J. (1950) ‘Pricing Policies for New Products’. Harvard Business Review, 28, pp. 45–53. Oxenfeldt, A.R. (1960) ‘A Multi-stage Approach to Pricing’. Harvard Business Review, 38, pp. 125–133. Oxenfeldt, A.R. (1973) ‘A Decision-making Structure for Price Decisions’. Journal of Marketing, 37 (January), pp. 48–53. Oxenfeldt, A.R. (1983) ‘Pricing Decisions: How They Are Made and How They Are Influenced’. Management Review, November, pp. 23–25. Tellis, G.J. (1986) ‘Beyond the Many Faces of Price: An Integration of Pricing Strategies’. Journal of Marketing, 50 (October), pp. 146–160. 30 Ng, I.C.L. (2006) Introduction to the Centre for Service Research. Unpublished paper. Exeter: University of Exeter. 31 Polanyi, M. (1966) The Tacit Dimension. New York: Doubleday. 32 Berry, L.L. and Yadav, M.S. (1996) ‘Capture and Communicate Value in the Pricing of Services’. Sloan Management Review, Summer, 37 (4), pp. 41–51. 33 Hoffman K.D., Turley, L.W. and Kelley S.W. (2002) ‘Pricing Retail Services’. Journal of Business Research 55, p. 1015–1023. 34 By advanced sale, we mean the moment where the consumer is contracted to pay. I acknowledge that the actual payment may well be after consumption, depending on the nature of the service and the credit terms, if applicable. However, the sale contract must always be in advance of production, if the consumer means to consume the service. 35 Kaplan, R.S. (2004) ‘Time-Driven Activity-Based Costing’. Harvard Business Review, November, pp.131–138. 36 Levine, M.E. (1987) ‘Airline Competition in Deregulated Markets: Theory, Firm Strategy and Public Policy’. Yale Journal on Regulation, 4 (Spring), pp. 393–494. 37 International Herald Tribune ‘Low Fares Cut into Easyjet Sales’, 6 May 2004. 38 Nagle, T. and Holden, R. (2002) The Strategy and Tactics of Pricing, 3rd edn, Englewood Cliffs, NJ: Prentice Hall. 39 Badinelli, R.D. and Olsen, M.D. (1990) ‘Hotel Yield Management Using Optimal Decision Rules’. Journal of the International Academy Hospitality Research, 1 (Nov.), URL – http://borg.lib.vt.edu/ejournals/JIAHR/90–11–26.jiahr.html. Belobaba,

Notes 155 P.P. (1989) ‘Application of a Probabilistic Decision Model to Airline Seat Inventory Control’. Operations Research, 37, pp. 183–197. Bodily, S.E. and Weatherford, L.R. (1995) ‘Perishable-asset Revenue Management: Generic and Multiple-price Yield Management with Diversion Omega’. International Journal of Management Science, 23 (2), pp. 173–185. Hersh, M. and Ladany, S.P. (1978) ‘Optimal Seat Allocation for Flights with One Intermediate Stop’ Computers and Operations Research, 5, pp. 31–37. Pfeifer, P.E. (1989) ‘The Airline Discount Fare Allocation Problem’. Decision Sciences, 20, pp. 149–157. Toh, R. (1979) ‘Airline Revenue Yield Protection: Joint Reservation Control Over Full and Discount Fare Sales’. Transportation Journal, 19 (2), pp. 74–80. 40 Alstrup, J., Boas, S. Madsen, O. and Vidal, R. (1986) ‘Booking Policy for Flights with Two Types of Passengers’ European Journal of Operations Research, 27, pp. 274–288. Hersh, M. and Ladany, S.P. (1978) ‘Optimal Seat Allocation for Flights with One Intermediate Stop’. Computers and Operations Research, 5, pp. 31–37. 41 ‘Inflation and Growth in a Service Economy’, Bank of England Quarterly Bulletin: November 1998. 42 Kaplan, R.S. and Anderson, S.R. (2004) ‘Time-Driven Activity-Based Costing’. Harvard Business Review, November, pp. 131–138. 2 The expected net value (ENV) framework 1 Raj, S.P. (1985) ‘Striking a Balance Between Brand Popularity and Brand Loyalty’. Journal of Marketing, 49, pp. 53–59. DuWors, R.E. and Haines, G.H. (1990) ‘Event History Analysis Measures of Brand Loyalty’. Journal of Marketing Research, 27, pp. 485–493. Krishnamurthi, L. and Raj, S.P. (1991) ‘An Empirical Analysis of the Relationship Between Brand Loyalty and Consumer Price Elasticity’. Marketing Science, 10 (2), pp. 172–183. 2 Porter, M.E. (1985) Competitive Advantage: Creating and Sustaining Superior Performance. New York: The Free Press. 3 Zeithaml, V.A. (1988) ‘Consumer Perceptions of Price, Quality and Value: A MeansEnd Model and Synthesis of Evidence’. Journal of Marketing, 52 (3), pp. 2–22. 4 Monroe, K.B. (1990) Pricing, Making Profitable Decisions. New York: McGraw-Hill. 5 Dodds, W.B., Monroe, K.B. and Grewal, D.J. (1991) ‘Effects of Price, Brand, and Store Information on Buyers’ Product evaluations’. Journal of Marketing Research, 28, pp. 307–319. 6 Woodruff, R.B. (1997) ‘Customer Value: The Next Source for Competitive Advantage’. Journal of the Academy of Marketing Science, 25 (2), pp. 139–153. 7 Chang, T. and Wildt, A.R. (1994) ‘Price, Product Information, and Purchase Intention: An Empirical Study’. Journal of the Academy of Marketing Science, 22, pp. 16–27. Sinha, I. and DeSarb, W.S. (1998) ‘An Integrated Approach Toward the Spatial Modeling of Perceived Customer Value’. Journal of Marketing Research, 35, pp. 236–249. 8 Bettman, J., Luce, M. and Payne, J. (1998) ‘Constructive Consumer Choice Process’. Journal of Consumer Research, 25 (3), pp. 187–217. 9 DeSarbo, WS., Jedidi, K. and Sinha, I. (2001) ‘Customer Value Analysis in a Heterogeneous Market’. Strategic Management Journal, 22, pp. 845–857. 10 Hirschman, E. and Holbrook, M.B. (1982) ‘Hedonic Consumption: Emerging Concepts, Methods and Propositions’. Journal of Marketing, 46, pp. 92–101. Holbrook, M.B. (1994) The Nature of Customer Value, an Axiology of Services in the Consumption Experience. Thousand Oaks, CA: SAGE Publications. Ravald, A. and Gronroos, C. (1996) ‘The Value Concept and Relationship Marketing’. European Journal of Marketing, 30 (2), pp. 19–30. 11 Hunt, S.D. and Morgan, R.M. (1995) ‘The Competitive Advantage Theory of Competition’. Journal of Marketing, 59, pp. 1–15.

156

Notes

12 Keon, J.W. (1980) ‘The Bargain Value Model and a Comparison of Managerial Implications with the Linear Learning Model’. Management Science, 26 (11), pp. 1117–1131. Urbany, J.E., Bearden, W.O. and Weilbaker, D.C. (1988) ‘The Effect of Plausible and Exaggerated Reference Prices on Consumer Perceptions and Price Search’. Journal of Consumer Research, 15 (1), pp. 95–110. Zeithaml, V.A. (1988) ‘Consumer Perceptions of Price, Quality and Value: A Means-End Model and Synthesis of Evidence’. Journal of Marketing, 52 (3), pp. 2–22. Lichtenstein, D.R., Netemeyer, R.G. and Burton, S. (1990) ‘Distinguishing Coupon Proneness from Value Consciousness: an Acquisition-transaction Utility’. Journal of Marketing, 54 (3), pp. 54–67. Dodds, W.B., Monroe, K.B. and Grewal, D.J. (1991) ‘Effects of Price, Brand, and Store Information on Buyers’ Product Evaluations’. Journal of Marketing Research, 28, pp. 307–319. Bolton, R.N. and Drew, J.H. (1991) ‘A Multistage Model of Customers’ Assessments of Service Quality and Value’. Journal of Consumer Research, 17, pp. 375–384. Gale, B.T. (1994) Managing Customer Value: Creating Quality and Service That Customers Can See. New York: Free Press. Woodruff, R.B. (1997) ‘Customer Value: The Next Source for Competitive Advantage’. Journal of the Academy of Marketing Science, 25 (2), pp. 139–153. 13 OECD Business and Industry Policy Forum Series (2000) The Service Economy, Final Report of the Business and Industry Policy Forum on Realising the Potential of the Service Economy. Paris, France: OECD. 14 Bernstein, P.L. (1996) Against the Gods: A Remarkable Story of Risk. New York: John Wiley and Sons. 15 Stix, G. (2002) ‘Real Time’. Scientific American, September, URL http://scientificamerican.com/article.cfm?chanID=sa006&colID=1&articleID=00071AFE-CEBF1D4E-90FB809EC5880000 16 Heuristics – decisions based on ‘rule of thumb’ rather than logical calculation. 17 People Weekly ‘Priceless: London restaurateur Michael Vasos lets diners pay what they choose–but woe unto those who choose cheap’. 15 February 1999, p. 114. 18 Lynn, M. and McCall, M. (2000) ‘Gratitude and Gratuity: A Meta-analysis of Research on the Service-tipping Relationship’. Journal of Socio-Economics, 29, pp. 203–214. 3 Advanced purchase and the separation or purchase and consumption 1 Ng, I.C.L. (2007) ‘Advanced Demand and a Critical Analysis of Revenue Management’. Service Industries Journal, 27 (5), forthcoming. 2 Edgett, S. and Parkinson, S. (1993) ‘Marketing for Service Industries: A Review’. The Service Industries Journal, 13 (3), p. 19–39. 3 Shugan, S.M. and Xie, J. (2000) ‘Advance Pricing of Services and Other Implications of Separating Purchase and Consumption’. Journal of Service Research, 2(3), pp. 227–239. 4 Karni, E. (1983) ‘Risk Aversion for State-dependent Utility Functions: Measurement and Applications’. International Economic Review.24(3), pp.637–647. Fishburn, C. (1974) ‘On the Foundations of Decision Making under Uncertainty’ in Balch, M., McFadden, D. and Wu, S. (eds) Essays on Economic Behavior under Uncertainty.Amsterdam: North Holland Publishing Co. Cook, P.J. and Graham, D.A. (1977) ‘The Demand for Insurance and Protection: The Case of Irreplaceable Commodities’. Quarterly Journal of Economics, 91 (February), pp. 143–154. 5 Png, I.P.L. (1989) ‘Reservations: Customer Insurance in the Marketing of Capacity’. Marketing Science, 8 (3), pp. 248–264. 6 Lee, K.S. and Ng, I.C.L. (2001) ‘Advanced Sale of Service Capacities: A Theoretical Analysis of the Impact of Price Sensitivity on Pricing and Capacity Allocations’. Journal of Business Research, 54 (3), pp. 219–225. 7 Lovelock, C. and Wirtz, J. (2003) Services Marketing: People, Technology, Strategy, 5th edn. Englewood Cliffs, NJ: Prentice Hall.

Notes 157 8 Xie, J. and Shugan, S.M. (2001) ‘Electronic Tickets, Smart Cards and Online Prepayments: When and How to Advance Sell’. Marketing Science, 20 (3), pp. 219–243. 9 Stone, M. (1990) ‘Marketing Strategies for Leisure Services’. Long Range Planning, 23 (5), pp. 76–90. 10 Ng, I.C.L. (2007) ‘Establishing a Service Channel: A Transaction Cost Analysis of a Channel Contract between a Cruise Line and a Tour Operator’. Journal of Services Marketing, 21 (1), forthcoming. 11 Seaton, A.V. and Bennett, M.M. (1996) The Marketing of Tourism Products: Concepts, Issues and Cases. London: International Thomson Business Press. 12 Murray, K.B and Schachter, J.L (1990) ‘The Impact of Services Versus Goods on Consumers’ Assessment of Perceived Risk and Variability’. Journal of the Academy of Marketing Science, 18 (winter), pp. 51–65. 13 Lutz, R.J. and Reilly, P.J. (1973) ‘An Exploration of the Effects of Perceived Social and Performance Risk on Consumer Information Acquisition’ in Ward, S. and Wright, P. (eds) Advances in Consumer Research, Vol. 1. Urbana, IL: Association of Consumer Research, pp. 393–405. 14 Kahneman, D. and Tversky, A. (1979) ‘Prospect Theory: An Analysis of Decision under Risk’. Econometrica, 47 (2), pp. 263–292. 15 Nagle, T. and Holden, R. (1987) The Strategy and Tactics of Pricing, 2nd edn. Englewood Cliffs, NJ: Prentice Hall. 16 Ben-Akiva, M. McFadden, D., Train, K., Walker, J., Bhat, C., Bierlaire, M., Bolduc, D., Boersch-Supan, A., Brownstone, D., Bunch, D.S., Daly, A., de Palma, A., Gopinath, D., Karlstrom, A. and Munizaga, M.A. (2002) ‘Hybrid Choice Models: Progress and Challenges’. MIT, URL (accessed, 2 January 2007) http://orion.oac.uci.edu/~dbrownst/asilomar.pdf 17 Bitta, A.J.D. and Monroe, K. (1974) ‘The Influence of Adaptation Levels on Subjective Price Perceptions’ in Wright, P. and Ward, S. Advances in Consumer Research, 1973 Proceedings of the Association for Consumer Research, Volume 1. Urbana, Illinois: ACR, p.359–369. 18 Nagle, T. and Holden, R. (1987) The Strategy and Tactics of Pricing, 2nd edn, Englewood Cliffs, NJ: Prentice Hall 19 Urbany, J.E., Bearden, W.O. and Weilbaker, D.C. (1988) .The Effect of Plausible and Exaggerated Reference Prices on Consumer Perceptions and Price Search’. Journal of Consumer Research, 15 (June) pp. 95–110. 20 Smith, G.E. (1992) ‘Prior Knowledge and the Effectiveness of Message Frames in Advertising’. Unpublished dissertation, Boston: Boston University. 21 Nagle, T. and Holden, R. (1987) The Strategy and Tactics of Pricing, 2nd edn, Englewood Cliffs, NJ: Prentice-Hall. 22 Kahneman, D. and Tversky, A. (1979) ‘Prospect Theory: An Analysis of Decision under Risk’, Econometrica, XLVII, pp. 263–291. 23 Economics A-Z, www.economist.com 24 Thaler, R. (1985) ‘Mental Accounting and Consumer Choice’. Marketing Science, 4 (3), pp. 199–214. 25 Ng, I.C.L. (2005) ‘Non-rational Behaviour in Financial Services’. Unpublished paper, Exeter: Centre for Service Research, Exeter University. 26 Thaler, R. (1980) ‘Towards a Positive Theory of Consumer Choice’. Journal of Economic Behavior and Organization, 1, pp. 39–60. 27 Nagle, T. and Holden, R. (1987) The Strategy and Tactics of Pricing, 2nd edn. Englewood Cliffs, NJ: Prentice-Hall. 28 Thaler, R. (1980) ‘Towards a Positive Theory of Consumer Choice’. Journal of Economic Behavior and Organization, 1, pp. 39–60. Tversky, A. and Kahneman, D. (1981) ‘The Framing of Decisions and the Psychology of Choice’ Science, 211 (4481), pp. 453–458.

158

Notes

29 Kahneman, D. and Tversky, A. (1984) ‘Choices, Values, and Frames’. American Psychologist, 39, (4), pp. 341–350. 30 Hershey, J.C. and Schoemaker, P. (1980) ‘Risk Taking and Problem Context in the Domain of Losses: An Expected-Utility Analysis’. Journal of Risk and Insurance, 47, pp. 111–132. 31 Nagle, T. and Holden, R. (1987) The Strategy and Tactics of Pricing, 2nd edn. Englewood Cliffs, NJ: Prentice-Hall. 32 Nagle, T. and Holden, R. (1987) The Strategy and Tactics of Pricing, 2nd edn. Englewood Cliffs, NJ: Prentice-Hall. 33 Monroe, K.B. and Petroshius, S.M. (1981) ‘Buyers’ Perceptions of Price: An Update of the Evidence’ in Kassarjian H. and Robertson, T.S. (eds) Perspectives in Consumer Behaviour, 3rd edn. Glenview, Illinois: Scott-Foresman, pp. 43–55. 34 Nagle, T. and Holden, R. (1987) The Strategy and Tactics of Pricing, 2nd edn. Englewood Cliffs, NJ: Prentice-Hall. 35 Berry, L.L, Parasuraman, A. and Zeithaml, V.A. (1990) ‘Guidelines for Conducting Service Quality Research’. Marketing Research, December, pp. 34–44. Zeithaml, V.A, Parasuraman, A, and Berry, L.L. (1990). Delivering Quality Service: Balancing Customer Perceptions and Expectations. New York: The Free Press. 36 Price, R. and Brodie, R.J. (2001) ‘Transforming a Public Service Organization from Inside Out to Outside In: The Case of Auckland City, New Zealand’. Journal of Service Research, 4 (1), pp. 50–59. 37 Rust, R. and Oliver, R. (1994) ‘Service Quality: Insights and Managerial Implications from the Frontier’ in Rust, R. and Oliver, R. (eds) Service Quality: New Directions in Theory and Practice. Thousand Oaks, CA: SAGE Publications, pp. 1–20. 38 Vriens, M. and Frenkel T.H. (2000) ‘Linking Attributes, Benefits and Consumer Values’. Marketing Research, Fall, pp. 5–10. 39 Herzberg, F., Mausner, B. and Snyderman, B.B. (1959) The Motivation to Work, 2nd edn. New York: John Wiley & Sons. 4 Seven strategies for higher revenues 1 Bond, K. and Robson, J. (2001) ‘Pricing GPRS Services’ A Report by Analysys Research Limited. URL http://www.the-infoshop.com/pdf/an8502.pdf accessed 20 December 2006. 2 Barboza, D. ‘The Rise of Baidu (That’s Chinese for Google)’. New York Times, 17 September 2006, URL www.nytimes.com 3 Cole, K. (2006) ‘Personal Concierges Becoming A New Trend’. WCBS.TV, 26 September, 2006, 2:51 pm, US/Eastern. 4 Schumpeter, J.A. (1951) ‘Economic Theory and Entrepreneurial History’ in Clemence, R.V. (ed.) Essays on Economic Topics of Joseph Schumpeter. Port Washington, NY: Kennikat Press. Liebhafsky, H.H. (1968) The Nature of Price Theory, revised edn, Homewood: The Dorsey Press, Inc. 5 Smith, W. (1956) ‘Product Differentiation and Market Segmentation as Alternate Marketing Strategies’. Journal of Marketing, 21, pp. 3–8. 6 Hotelling H. (1929) ‘Stability in Competition’. Economic Journal, 39, pp. 41–57. 7 Chamberlin E.H. (1965) The Theory of Monopolistic Competition. Cambridge, MA: Harvard University Press. 8 Porter, M. (1976) Interbrand Choice, Strategy and Bilateral Market Power. Cambridge, MA: Harvard University Press. 9 Carpenter, G.S., Rashi G. and Kent N. (1994), ‘Meaningful Brands from Meaningless Differentiation: The Dependence on Irrelevant Attributes’. Journal of Marketing Research, 31 (3), pp. 339–350. 10 Shostack, G.I. (1981) ‘How to Design a Service’ in Donnelly, J.H. and George, W.R. (eds) Marketing of Services. Chicago: American Marketing Association, pp. 221–229. Storey, C. and Easingwood, C.J. (1998) ‘The Augmented Service

Notes 159

11 12

13 14

15 16 17 18 19

20

21 22 23 24

Offering: A Conceptualization and Study of its Impact on New Service Success’. Journal of Product Innovation Management, 15, pp. 335–351. Lovelock, C. and Wirtz, J. (2003) Services Marketing: People, Technology, Strategy, 5th edn. Englewood Cliffs, NJ: Prentice Hall. Prabhaker, P.R. Joel, D. and Goldhar, D.L. (1995) ‘Marketing Implications of Newer Manufacturing Technologies’. Journal of Business and Industrial Marketing, 10 (2), pp. 48–58. Kannan, P.K. and Kopalle, P.K. (2001), ‘Dynamic Pricing on the Internet: Importance and Implications for Consumer Behavior’. International Journal of Electronic Commerce, 5, pp. 63–84. Boyd, E.A. (2004) ‘Dramatic Changes in Distribution will Require Renewed Focus on Pricing and Revenue Management Models’. Journal of Revenue and Pricing Management, 3 (1), pp100–103. Bitner, M.J., Faranda, W.T., Hubbert, A.R. and Zeithaml, V.A. (1997) ‘Customer Contributions and Roles in Service Delivery’ International Journal of Service Industry Management, 8 (3), pp. 193–205. Gummesson, E. (1994) ‘Service Management: An Evaluation and the Future’. International Journal of Service Industry Management, 5 (1), pp. 77–96. Bitner, M.J., Faranda, W.T., Hubbert, A.R. and Zeithaml, V.A. (1997) ‘Customer Contributions and Roles in Service Delivery’ International Journal of Service Industry Management, 8 (3), pp. 193–205. Bitner, M.J., Faranda, W.T., Hubbert, A.R. and Zeithaml, V.A. (1997) ‘Customer Contributions and Roles in Service Delivery’ International Journal of Service Industry Management, 8 (3), pp. 193–205. Astin, A.W. (1984) ‘Student Involvement: A Developmental Theory for Higher Education’. Journal of College Student Development, 40 (5), pp. 518–529. Bok, D. (2006) ‘Turn Classes into Labs of Learning for Lecturers’. The Times Higher Education Supplement, 27 January 2006. Bitner, M.J. (1990) ‘Evaluating Service Encounters: The Effects of Physical Surroundings and Employee Responses’. Journal of Marketing, 54, pp. 69–82. Folkes, V.S. (1988) ‘Recent Attribution Research in Consumer Behavior: A Review and New Directions’. Journal of Consumer Research, 14, pp. 548–565. Hubbert, A.R. (1995) ‘Customer Co-creation of Service Outcomes: Effects of Locus of Causality Attributions’.Unpublished doctoral dissertation, Arizona: Arizona State University. Plouffe, C., Hulland, J. and Vandenbosch, M. (2001) ‘Research Report: Richness Versus Parsimony in Modelling Technology Adoption Decisions – Understanding Merchant Adoption of a Smart Card-based Payment System’. Information Systems Research, 12, pp. 208–222. Middleton, M. (2000) ‘Self Service: What is the Function of the New Intermediary?’. ALIA2000: Capitalising on Knowledge, the Information Profession in 21st century, Canberra, 24–26 October . Guiltinan, J.P. (1987) ‘The Price Bundling of Services: A Normative Framework’. Journal Of Marketing, 51 (April), pp. 74–85. Alonzo, V. (1996) ‘The Trouble with Money’. Incentive, February, pp. 26–30. To date, only five people have paid for a flight to space – they paid between US$20 million and US$25 million per person, and also underwent six months of training to prepare for their journeys.

5 The economics of pricing in services 1 Becker, G.S. (1991) ‘A Note on Restaurant Pricing and Other Examples of Social Influences on Price’. Journal of Political Economy, 99 (5), pp. 1109–1116. 2 Ng, I.C.L., Wirtz, J. and Lee, K.S. (1999) ‘The Strategic Role of Unused Service Capacity’. International Journal of Service Industry Management. 10 (2), p. 211. 3 cf. Alonzo, V. (1996) ‘The Trouble with Money’, Incentive, February, pp. 26–30.

160

Notes

4 Eppen, G.D., Hanson, W.A. and Martin, R.K. (1991) ‘Bundling – New Products, New Markets, Low Risk’. Sloan Management Review, Summer, pp. 7–14. 5 cf Dearden, J. (1978) ‘Cost Accounting Comes to Service Industries’ Harvard Business Review, 56 (September–October), pp. 132–140. 6 Guiltinan, J.P. (1987) ‘The Price Bundling of Services: A Normative Framework’. Journal Of Marketing, 51 (April), pp. 74–85. 7 Gruca, T.S. and Sudharshan, D. (1995) ‘A Framework for Entry Deterrence Strategy: The Competitive Environment, Choices and Consequences’. Journal of Marketing, 59 (Jul), pp. 44–55. 8 Wenders, J.T. (1971) ‘Excess Capacity as a Barrier to Entry: An Empirical Appraisal’. Journal of Industrial Economics, 20 (Nov.), pp. 14–19. 9 cf. Thomas, D.R.E. (1978) ‘Strategy is Different in Service Business’. Harvard Business Review, 56 (July–August), pp. 158–165. 10 Bitner, M.J., Booms, B.H. and Tetreault, M.S. (1990) ‘The Service Encounter: Diagnosing Favorable and Unfavorable Incidents’. Journal of Marketing, 54 (January), pp. 71–84. 11 Taylor, S. (1994) ‘Waiting for Service: The Relationship Between Delays and Evaluations of Service’. Journal of Marketing, 58 (April), pp. 56–69. 12 http://www.novotel.com/novotel/gb/breaks/hotel-early-breaks.shtml URL accessed on 22 December 2006. 13 Srivastava, A. (2001) Dynamic Pricing Models: Opportunity for Action. A report by Cap Gemini Ernst and Young Center for Business Innovation. 14 Kannan, P.K. and Kopalle, P.K. (2001) ‘Dynamic Pricing on the Internet: Importance and Implications for Consumer Behavior’ International Journal of Electronic Commerce, 5 (Spring), pp. 63–84. 15 Brynjolfsson, E. and Smith, M. (2000). ‘The Great Equalizer? Consumer Choice at Internet Shopbots’. Working Paper, Cambridge, MA: Massachusetts Institute of Technology. 16 Elmaghraby, W. and Keskinocak, P. (2003) ‘Dynamic Pricing in the Presence of Inventory Considerations: Research Overview, Current Practices, and Future Directions’. Management Science, 49 (10), pp. 1287–1309. 17 Kimes, S.E. and Thompson, G.M. (2004) ‘Restaurant Revenue Management at Chevys: Determining the Best Table Mix’. Decision Sciences, 35 (3), pp. 371–392. 18 McAfee, R.P. and te Velde, V. (2007) ‘Dynamic Pricing in the Airline Industry’ in Hendershott, T.J. Handbook on Economics and Information Systems. Amsterdam: Elsevier. 19 For a review, see Talluri and van Ryzin (2004), Elmaghraby and Keskinocak (2003), Bitran and Caldentey (2003), and McGill and van Ryzin (1999)). 20 Elmaghraby, W. and Keskinocak, P. (2003) Dynamic pricing in the presence of inventory considerations: Research overview, current practices, and future directions, Management Science, 49 (10), pp. 1287–1309. 6 The revenue management of services 1 Bateson, J.E.G. (1977) ‘Do We Need Service Marketing?’. Marketing Consumer Services: New Insights, Marketing Science Institute Report, pp. 77–115. Thomas, D.R.E. (1978) ‘Strategy is Different in Service Business’. Harvard Business Review, 56 (July–August), pp. 158–165. 2 Harris, F.H and Peacock, P. (1995). ‘Hold My Place, Please’. Marketing Management, 4 (Fall), pp. 34–46. 3 Bitran, G. and Caldentey, R. (2003) ‘An Overview of Pricing Models for Revenue Management’. Manufacturing and Service Operations Management, 5 (3), pp. 203–229. 4 Ng, I.C.L. (2007) ‘Advanced Demand and a Critical Analysis of Revenue Management’. Service Industries Journal, 27 (5), forthcoming.

Notes 161 5 Weatherford, L.R. and Bodily, S.E. (1992) ‘A Taxonomy and Research Overview of Perishable-Asset Revenue Management: Yield Management, Overbooking, and Pricing’. Operations Research, 40, pp. 831–844. 6 Kimes, S.E. (1989) ‘Yield Management: A Tool for Capacity Constrained Service Firms’. Journal Of Operations Management, 8, pp. 348–363. Pak, K. and Piersma, N. (2002) ‘Overview of OR Techniques for Airline Revenue Management’. Statistica Neerlandica, 56 (4), pp. 479–495. Kimes, S.E. and Thompson, G.M. (2004), Restaurant Revenue Management at Chevys: Determining the Best Table Mix, Decision Sciences, 35 (3), pp. 371–392. Yeoman, I., Ingold, A. and Kimes, S.E. (1999) ‘Yield Management: Editorial Introduction’. Journal of Operational Research Society, 50, pp. 1083–1084. Upchurch, R.S., Ellis, T. and Seo, J. (2002) ‘Revenue Management Underpinnings: An Exploratory Review’. Hospitality Management, 21, pp. 67–83. 7 For instance: Jones, P. (1999) ‘Yield Management in UK Hotels: A Systems Analysis’. Journal of the Operational Research Society, 50 (11), pp. 1111–1119. Weatherford, L.R. and Bodily, S.E. (1992) ‘A Taxonomy and Research Overview of Perishable-Asset Revenue Management: Yield Management, Overbooking, and Pricing’. Operations Research, 40, pp. 831–844. 8 Kuhlmann, R. (2004) ‘Why is Revenue Management not Working?’. Journal of Revenue and Pricing Management, 2 (4), pp. 378–387. 9 Rothstein, M. (1971) ‘An Airline Overbooking Model’. Transportation Science, 5, pp. 180–192. Rothstein, M.(1974) ‘Hotel Overbooking as a Markovian Sequential Decision Process’. Decision Sciences, 5, pp. 389–394. 10 Littlewood, K. (1972) ‘Forecasting and Control of Passenger Bookings’ AGIFORS Symposia, Alliance Group of the International Federation of Operational Research Scientists, 12, pp. 95–117. 11 Kimes, S.E. (1989) ‘Yield Management: A Tool for Capacity Constrained Service Firms’. Journal Of Operations Management, 8, pp. 348–363. 12 Belobaba P.P. (1987a) ‘Air Travel Demand and Airline Seat Inventory Management’. Doctoral dissertation, Cambridge, MA: Flight Transportation Laboratory, Massachusetts Institute of Technology. Belobaba P.P. (1987b) ‘Airline Yield Management: An Overview of Seat Inventory Control’ Transportation. Science, 21, pp. 63–73. Belobaba, P.P. (1989) ‘Application of a Probabilistic Decision Model to Airline Seat Inventory Control’. Operations Research, 37, pp. 183–197. 13 Desiraju, R. and Shugan, S.M. (1999) ‘Strategic Service Pricing and Yield Management’. Journal of Marketing, 63, pp. 44–56. 14 For an overview of revenue management, see Weatherford and Bodily (1992) – note 53, Chapter 5. 15 Ng, I.C.L (2004) ‘The Pricing of Services: A Theoretical Framework’. Proceedings of the8th International Research Seminar in Services Management, 4–6 June 2004, La Londe, France. Talluri, K. and van Ryzin, G. (2004) ‘Revenue Management Under a General Discrete Choice Model of Consumer Behavior’. Management Science, 50, pp. 15–33. Weatherford, L.R. (1997) ‘Using Prices More Realistically as Decision Variables in Perishable-asset Revenue Management Problems’. Journal of Combinational Optimization, 1, pp. 277–304. 16 Fleischmann, M., Hall, J.M. and Pyke, D.F. (2004) ‘Smart Pricing’ MIT Sloan Management Review, 45 (2), pp. 9–13. 17 Carroll, W.J. and Grimes, R.C. (1995) ‘Evolutionary Change in Product Management: Experiences in the Car Rental Industry’. Interfaces, 25 (5), pp. 84–104. Nair S.K. and Bapna, R. with Nair, S. (2001) ‘An Application of Yield Management for Internet Service Providers’. Naval Research Logistics, 48 (5), pp. 348–362. 18 Weatherford, L.R. (1997) ‘Using Prices More Realistically as Decision Variables in Perishable-Asset Revenue Management Problems’. Journal of Combinational Optimization, 1, pp. 277–304. 19 Elmaghraby, W. and Keskinocak, P. (2003) ‘Dynamic Pricing in the Presence of

162

20 21

22

23 24 25 26 27

28 29 30 31 32 33

Notes

Inventory Considerations: Research Overview, Current Practices, and Future Directions’. Management Science, 49 (10), pp. 1287–1309. Kimes, S.E. (2003) ‘Revenue Management: A Retrospective’. Cornell Hotel and Restaurant Administration Quarterly, 30 (3), pp. 14–19. For a review on the practices of dynamic pricing with revenue management, see Elmaghraby, W. and Keskinocak, P. (2003) ‘Dynamic Pricing in the Presence of Inventory Considerations: Research Overview, Current Practices, and Future Directions’. Management Science, 49 (10), pp. 1287–1309. For a review of dynamic pricing, and its implications for consumer behavior, see Kannan, P.K. and Kopalle, P.K. (2001) ‘Dynamic Pricing on the Internet: Importance and Implications for Consumer Behavior’. International Journal of Electronic Commerce, 5, pp. 63–84. Fleischmann, M., Hall, J.M. and Pyke, D.F. (2004) ‘Smart Pricing’. MIT Sloan Management Review, 45 (2), pp. 9–13. Kimes, S.E. and Wirtz, J. (2002) ‘Perceived Fairness of Demand-based Pricing for Restaurants’. Cornell Hotel and Restaurant Administration Quarterly, 43 (1), pp. 31–37. Kimes, S.E. and Wirtz, J. (2003) ‘Has Revenue Management Become Acceptable? Findings from an International Study on the Perceived Fairness of Rate Fences’. Journal of Service Research, 6 (2), pp. 125–135. Cary, D. (2004) ‘Future of Revenue Management: A view from the Inside’. Journal of Revenue and Pricing Management, 3 (2), pp. 200–203. Martin, B. (1998) The Politics of Research, Information Liberation. London: Freedom Press. Pak, K. and Piersma, N. (2002) ‘Overview of OR Techniques for Airline Revenue Management’ Statistica Neerlandica, 56 (4), pp. 479–495. Gorin, T. and Belobaba, P. (2004) ‘Revenue Management Performance in a Low Fare Airline Environment: Insights from the Passenger Origin-destination Simulator’. Journal of Revenue and Pricing Management, 3 (3), p. 216. For example, Lee, K.S. and Ng., I.C.L. (2001) ‘Advanced Sale of Service Capacities: A Theoretical Analysis of The Impact of Price Sensitivity on Pricing and Capacity Allocations’. Journal of Business Research, 54 (3), pp. 219–225. Elmaghraby, W. and Keskinocak, P. (2003) ‘Dynamic Pricing in the Presence of Inventory Considerations: Research Overview, Current Practices, and Future Directions’. Management Science, 49 (10), pp. 1287–1309. Talluri, K. and van Ryzin, G. (2004) ‘Revenue Management under a General Discrete Choice Model of Consumer Behavior’. Management Science, 50, pp. 15–33. Subramanian, J., Stidham Jr, S. and Lautenbacher, C.J. (1999) ‘Airline Yield Management with Overbooking, Cancellations and No-shows’. Transportation Science, 33 (2), pp. 147–167. Bertsimas, D. and Perakis, G. (2001) ‘Dynamic Pricing: A Learning Approach’. Working Paper, Cambridge, Massachusetts: Operations Research Center, OR355–01, MIT. Subramanian, J., Stidham Jr, S. and Lautenbacher, C.J. (1999) ‘Airline Yield Management with Overbooking, Cancellations and No-shows’. Transportation Science, 33 (2), pp. 147–167. Williams, L. (1999) ‘Revenue Management: Microeconomics and Business Modeling’. Business Economics, 34 (2), pp. 39–45. Yield management and revenue management are terms used interchangeable throughout the book. Yeoman, I., Ingold, A. and Kimes, S.E. (1999) ‘Yield Management: Editorial Introduction’. Journal of Operational Research Society, 50, pp. 1083–1084. Desiraju, R. and Shugan, S.M. (1999) ‘Strategic Service Pricing and Yield Management’. Journal of Marketing, 63, pp. 44–56. For example, Feng, Y. and Gallego, G. (2000) ‘Perishable Asset Revenue Management with Markovian Time Dependent Demand Intensities’. Management Science, 46 (7), pp. 941–956. Radjou N., Orlov, L.M. and Herbert, L. (2003) ‘Helping Supply Chain Cope with Demand.’ TechStrategy Report. Cambridge, Massachusetts: Forrester Research.

Notes 163 34 Jones, P. (1999) ‘Yield Management in UK Hotels: A Systems Analysis’. Journal of the Operational Research Society, 50 (11), pp. 1111–1119. 35 Boyd, E.A. and Bilegan, I. (2003) ‘Revenue Management and E-commerce’. Management Science, 49, pp. 1363–1386. 36 Kimes, S.E. and Thompson, G.M. (2004) ‘Restaurant Revenue Management at Chevys: Determining the Best Table Mix’. Decision Sciences, 35 (3), pp. 371–392. 37 Fleischmann, M., Hall, J.M. and Pyke, D.F. (2004) ‘Smart Pricing’. MIT Sloan Management Review, 45 (2), pp. 9–13. 38 Bernstein, P.L. (1996) Against the Gods: A Remarkable Story of Risk, New York: John Wiley and Sons. Ng, I.C.L (2004) ‘The Pricing of Services: A Theoretical Framework’. Proceedings of the 8th International Research Seminar in Services Management, 4–6 June 2004, La Londe, France. 39 Bernstein, P.L. (1996) Against the Gods: A Remarkable Story of Risk. New York: John Wiley and Sons. See p. 334. 40 Desiraju, R. and Shugan, S.M. (1999) ‘Strategic Service Pricing and Yield Management’. Journal of Marketing, 63, pp. 44–56. 41 Shugan, S.M. and Xie, J. (2000) ‘Advance Pricing of Services and Other Implications of Separating Purchase and Consumption’. Journal of Service Research, 2 (3), pp. 227–239. 42 Xie, J. and Shugan, S.M. (2001) ‘Electronic Tickets, Smart Cards and Online Prepayments: When and How to Advance Sell’. Marketing Science, 20 (3), pp. 219–243. 43 Png, I.P.L. (1989) ‘Reservations: Customer Insurance in the Marketing of Capacity’. Marketing Science, 8 (3), pp. 248–264. 44 Png, I.P.L. (1991) ‘Most-Favored-Customer: Protection versus Price Discrimination over Time’. Journal of Political Economy, 99 (5), pp. 1010–1028. 45 Lee, K.S. and Ng., I.C.L. (2001) ‘Advanced Sale of Service Capacities: A Theoretical Analysis of The Impact of Price Sensitivity on Pricing and Capacity Allocations’. Journal of Business Research, 54 (3), pp. 219–225. 46 Van Ryzin, G. (2005) ‘Future of Revenue Management: Models of Demand’. Journal of Revenue and Pricing Management, 4 (2), pp. 204–209. 47 For example, Talluri, K. and van Ryzin, G. (2004) ‘Revenue Management Under a General Discrete Choice Model of Consumer Behavior’. Management Science, 50, pp. 15–33. 48 Botimer, T.C. and Belobaba, P.P. (1999) ‘Airline Pricing and Fare Product Differentiation: A New Theoretical Framework’. Journal of the Operational Research Society, 50, pp. 1085–1097. Weatherford, L.R. (1997) ‘Using Prices More Realistically as Decision Variables in Perishable-asset Revenue Management Problems’. Journal of Combinational Optimization, 1, pp. 277–304. 49 For example, Alstrup, J., Boas, S., Madsen, O. and Vidal R. (1986) ‘Booking Policy for Flights with Two Types of Passengers’. European Journal of Operations Research, 27, pp. 274–288. Belobaba, P.P. (1989) ‘Application of a Probabilistic Decision Model to Airline Seat Inventory Control’. Operations Research, 37, pp. 183–197. Hersh, M. and Ladany, S.P. (1978) ‘Optimal Seat Allocation for Flights with One Intermediate Stop’. Computers and Operations Research, 5, pp. 31–37. Subramanian, J., Stidham Jr, S. and Lautenbacher, C.J. (1999) ‘Airline Yield Management with Overbooking, Cancellations and No-shows’. Transportation Science, 33 (2), pp. 147–167. Toh, R. (1985) ‘An Inventory Depletion Overbooking Model For the Hotel Industry’. Journal of Travel Research, Spring, pp. 24–30. 50 For example, Karaesmen, I. and van Ryzin, G. (2004) ‘Overbooking with Substitutable Inventory Classes’. Operations Research, 52 (1), pp. 83–104. 51 Kimes, S.E. (1989) ‘Yield Management: A Tool for Capacity Constrained Service Firms’. Journal Of Operations Management, 8, pp. 348–363. Kimes, S.E. (2003) ‘Revenue Management: A Retrospective’. Cornell Hotel and Restaurant Administration Quarterly, 30 (3), pp. 14–19.

164

Notes

52 Lieberman, W.H. (1993) ‘Debunking the Myths of Yield Management’. Cornell Hotel and Restaurant Administration Quarterly, 34 (1), pp. 34–41. Upchurch, R.S., Ellis, T. and Seo, J. (2002) ‘Revenue Management Underpinnings: An Exploratory Review’. Hospitality Management, 21, pp. 67–83. 53 Weatherford, L.R. and Bodily, S.E. (1992) ‘A Taxonomy and Research Overview of Perishable-asset Revenue Management: Yield Management, Overbooking, and Pricing’. Operations Research, 40, pp. 831–844. Weatherford, L.R. (1997) ‘Using Prices More Realistically as Decision Variables in Perishable-asset Revenue Management Problems’. Journal of Combinational Optimization, 1, pp. 277–304. 54 Weatherford, L.R. and Bodily, S.E. (1992) ‘A Taxonomy and Research Overview of Perishable-Asset Revenue Management: Yield Management, Overbooking, and Pricing, Operations Research’ 40, pp. 831–844. Png, I.P.L. (1989) ‘Reservations: Customer Insurance in the Marketing of Capacity’. Marketing Science, 8 (3), pp. 248–264. Lee, K.S. and Ng, I.C.L. (2001) ‘Advanced Sale of Service Capacities: A Theoretical Analysis of The Impact of Price Sensitivity on Pricing and Capacity Allocations’. Journal of Business Research, 54 (3), pp. 219–225. 55 Karaesmen, I. and van Ryzin, G. (2004) ‘Overbooking with Substitutable Inventory Classess’. Operations Research, 52 (1), pp. 83–104. 56 Alstrup, J., Boas, S., Madsen, O. and Vidal, R. (1986) ‘Booking Policy for Flights with Two Types of Passengers’. European Journal of Operations Research, 27, pp. 274–288. Belobaba, P.P. (1989) ‘Application of a Probabilistic Decision Model to Airline Seat Inventory Control’, Operations Research, 37, pp. 183–197. Hersh, M. and Ladany, S.P. (1978) ‘Optimal Seat Allocation for Flights with One Intermediate Stop’ Computers and Operations Research, 5, pp. 31–37. Lieberman, V. and Yechiali, U. (1978) ‘On the Hotel Overbooking Problem: An Inventory Problem with Stochastic Cancellations’. Management Science, 24, pp. 1117–1126. Rothstein, M. (1971) ‘An Airline Overbooking Model’. Transportation Science, 5, pp. 180–192. Rothstein, M. (1974) ‘Hotel Overbooking as a Markovian Sequential Decision Process, Decision Sciences, 5, pp. 389–394. Rothstein, M. (1985) ‘Operations Research and the Airline Overbooking Problem’. Operations Research, 33 (2), pp. 237–248. Thompson, H.R. (1961) ‘Statistical Problems in Airline Reservation Control’. Operational Research Quarterly, 12, pp. 167–185. Toh, R. (1985) ‘An Inventory Depletion Overbooking Model For the Hotel Industry’. Journal of Travel Research, Spring, pp. 24–30. 57 Pfeifer, P.E. (1989) ‘The Airline Discount Fare Allocation Problem’. Decision Sciences, 20, pp. 149–157. 58 Kimes, S.E. (1989) ‘Yield Management: A Tool for Capacity Constrained Service Firms’ Journal Of Operations Management, 8, pp. 348–363. 59 Jauncey, S., Mitchell, I. and Slamet, P. (1995) ‘The Meaning and Management of Yield in Hotels’. International Journal of Contemporary Hospitality Management, 7 (4), pp. 23–26. Pak, K. and Piersma, N. (2002) ‘Overview of OR Techniques for Airline Revenue Management’. Statistica Neerlandica, 56 (4), pp. 479–495. Kimes, S.E. (1999) ‘Group Forecasting Accuracy in Hotels’. Journal of the Operational Research Society, 50, pp. 1104–1110. Kimes, S.E. (2003) ‘Revenue Management: A Retrospective’. Cornell Hotel and Restaurant Administration Quarterly, 30 (3), pp. 14–19. 60 Jauncey, S., Mitchell, I. and Slamet, P. (1995) ‘The Meaning and Management of Yield in Hotels’. International Journal of Contemporary Hospitality Management, 7 (4), pp. 23–26. Donaghy, K., McMahon, U. and McDowell, D. (1995) ‘Yield Management: An Overview’. International Journal of Hospitality Management, 14 (2), pp. 139–150. Donaghy, K., McMahon, U. and McDowell, D. (1997) ‘Implementing Yield Management: Lesson from the Hotel Sector’. International Journal of Contemporary Hospitality Management, 9 (2), pp. 50–54. Gorin, T. and Belobaba, P. (2004) ‘Revenue Management Performance in a Low Fare Airline Environment:

Notes 165

61

62 63 64

65 66 67

68 69 70 71 72 73 74 75

76

Insights from the Passenger Origin-Destination Simulator’. Journal of Revenue and Pricing Management, 3 (3), p. 216. Anderson, C.K. and Blair, M. (2004) ‘Performance Monitor: The Opportunity Costs of Revenue Management’. Journal of Revenue and Pricing Management, 2 (4), pp. 353–367. Desiraju, R. and Shugan, S.M. (1999) ‘Strategic Service Pricing and Yield Management’. Journal of Marketing, 63, pp. 44–56. Lahoti, A. (2002) ‘Why CEOs Should Care About Revenue Management: How to Minimize the Implementation Pains and Maximize the Benefits’. OR/MS Today, February, URL http://www.lionhrtpub.com/orms/orms-2–02/frrm.html accessed on 27 May 2005. Ng, I.C.L, Wirtz, J. and Lee, K.S. (1999) ‘The Strategic Role of Unused Service Capacity’. International Journal Of Service Industry Management, 10 (2), pp. 211–238. Chase Jr., C.W. (1999) ‘Revenue Management: A Review’. Journal of Business Forecasting Methods and Systems, 18 (2), pp. 2–28. Lieberman, W.H. (1993) ‘Debunking the Myths of Yield Management’. Cornell Hotel and Restaurant Administration Quarterly, 34 (1), pp. 34–41. Relihan, I.I.I. and Walter, J. (1989) ‘The Yield Management Approach to Hotel-Room Pricing’. Cornell Hotel and Restaurant Administration Quarterly, May, pp. 40–45. Boyd, E.A. (2004) ‘Dramatic Changes in Distribution will Require Renewed Focus on Pricing and Revenue Management Models’. Journal of Revenue and Pricing Management, 3 (1), pp. 100–103. Desiraju, R. and Shugan, S.M. (1999) ‘Strategic Service Pricing and Yield Management’. Journal of Marketing, 63, pp. 44–56. Cary, D. (2004) ‘A View from the Inside’. Journal of Revenue and Pricing Management, 3 (2), pp. 200–203(4). Boyd, E.A. (2004) ‘Dramatic Changes in Distribution will Require Renewed Focus on Pricing and Revenue Management Models’. Journal of Revenue and Pricing Management, 3 (1), p. 100–103. van Ryzin, G. (2005) ‘Models of Demand’. Journal of Revenue and Pricing Management, 4 (2), pp. 204–209. Boyd, E.A. (2004) ‘Dramatic Changes in Distribution will Require Renewed Focus on Pricing and Revenue Management Models’. Journal of Revenue and Pricing Management, 3 (1), p. 101. Kimes, S.E. (2003) ‘Revenue Management: A Retrospective’. Cornell Hotel and Restaurant Administration Quarterly, 30 (3), pp. 14–19. Fleischmann, M., Hall, J.M. and Pyke, D.F. (2004) ‘Smart Pricing’. MIT Sloan Management Review, 45 (2), pp. 9–13. Jagpal, S. (1999) Marketing Strategy and Uncertainty. New York: Oxford University Press. Png, I.P.L. (1989) ‘Reservations: Customer Insurance in the Marketing of Capacity’. Marketing Science, 8 (3), pp. 248–264. Ng, I.C.L (2004) ‘The Pricing of Services: A Theoretical Framework’. Proceedings of the 8th International Research Seminar in Services Management, 4–6 June 2004, La Londe, France. Talluri, K. and van Ryzin, G. (2004) ‘Revenue Management Under a General Discrete Choice Model of Consumer Behavior’. Management Science, 50, pp. 15–33. van Ryzin, G. (2005) ‘Future of Revenue Management: Models of Demand’. Journal of Revenue and Pricing Management, 4 (2), pp. 204–209. For example, Mookherjee, R. and Friesz, T.L. (2005) ‘An Evolutionary Game Theoretic Dynamic Model of Network Revenue Managmenet Competition under Demand Uncertainty’ 5th Annual INFORMS Revenue Management and Pricing Section Conference, 16–17 June 2005. Kephart, J.O. (2002) ‘Agents and Dynamic Pricing’. INFORMS Conference on OR/MS Practice: Analyzing and Enhancing the Extended Enterprise, Montreal, Canada, 19–21 May 2002.

166

Notes

77 Kahneman, D., Knetsch, J.L. and Thaler, R. (1986) ‘Fairness as a Constraint on Profit Seeking: Entitlements in the Market’. American Economic Review, 76 (4), pp. 728–741. Thaler, R.F. (1985) ‘Mental Accounting and Consumer Choice’. Marketing Science, 4(3), 199–214. 78 Kimes, S.E. (2002) ‘Perceived Fairness of Yield Management’ Cornell Hotel and Restaurant Administration Quarterly, 43 (1), pp. 21–30. 79 Kahneman, D., Knetsch, J.L. and Thaler, R. (1986) ‘Fairness as a Constraint on Profit Seeking: Entitlements in the Market’. American Economic Review, 76 (4), pp. 728–741. 80 Kahneman, D., Knetsch, J.L. and Thaler, R. (1986) ‘Fairness as a Constraint on Profit Seeking: Entitlements in the Market’. American Economic Review, 76 (4), pp. 728–741. 81 Kimes, S.E. and Wirtz, J. (2003) ‘Has Revenue Management Become Acceptable? Findings from an International Study on the Perceived Fairness of Rate Fences’. Journal of Service Research, 6 (2), pp. 125–135. 82 Wirtz, J. and Kimes, S.E. (2007) ‘The Moderating Role of Familiarity in Fairness Perceptions of Revenue Management Pricing’. Journal of Service Research, 9 (3), pp. 1–12. 83 Kimes, S.E. (2002) ‘Perceived Fairness of Yield Management’ Cornell Hotel and Restaurant Administration Quarterly, 43 (1), pp. 21–30. 84 Kimes, S.E. (2002) ‘Perceived Fairness of Yield Management’ Cornell Hotel and Restaurant Administration Quarterly, 43 (1), pp. 21–30. 85 Kimes, S.E. (2002) ‘Perceived Fairness of Yield Management’ Cornell Hotel and Restaurant Administration Quarterly, 43 (1), pp. 21–30. 86 Hanks, R.B., Noland, R.P. and Cross, R.G. (2002) ‘Discounting in the Hotel Industry: A New Approach’. Cornell Hotel and Restaurant Administration Quarterly, 33 (3), pp. 40–45. 87 Kimes, S.E. and Wirtz, J. (2002) ‘Perceived Fairness of Demand-based Pricing for Restaurants’. Cornell Hotel and Restaurant Administration Quarterly, 41 (1), pp. 338. 88 Kimes, S.E. (2002) ‘Perceived Fairness of Yield Management’ Cornell Hotel and Restaurant Administration Quarterly, 43 (1), pp. 21–30. 89 Kahneman, D. and Tversky, A. (1979) ‘Prospect Theory: An Analysis of Decision under Risk’. Econometrica, 47 (2), pp. 263–291. Chen, S.S., Monroe, K.B. and Lou, Y. (1998) ‘The Effects of Framing Price Promotion Messages on Consumers’ Perceptions and Purchase Intentions’. Journal of Retailing, 74 (3), pp. 353–72. Thaler, R.F. (1985) ‘Mental Accounting and Consumer Choice’. Marketing Science, 4 (3), pp. 199–214. 90 Wirtz, J. and Kimes, S.E. (2007) ‘The Moderating Role of Familiarity in Fairness Perceptions of Revenue Management Pricing’. Journal of Service Research, 9 (3), pp. 1–12. Xia, L., Kent B.M. and Cox, J.L. (2004) ‘The Price Is Unfair! A Conceptual Framework of Price Fairness Perceptions’. Journal of Marketing, 68 (October), pp. 1–15. 91 Wirtz, J. and Kimes, S.E. (2007) ‘The Moderating Role of Familiarity in Fairness Perceptions of Revenue Management Pricing’. Journal of Service Research, 9 (3), pp. 1–12. 92 Wirtz, J. and Kimes, S.E. (2007) ‘The Moderating Role of Familiarity in Fairness Perceptions of Revenue Management Pricing’. Journal of Service Research, 9 (3), pp. 1–12. 7 Strategic pricing and revenue management: four more strategies for higher revenue 1 Bitran, G. and Caldentey, R. (2003) ‘An Overview of Pricing Models for Revenue Management’. Manufacturing and Service Operations Management, 5(3), pp. 203–229.

Notes 167 2 Tranfield, D. and Smith, S. (1998) The Strategic Regeneration of Manufacturing by Changing Routines. International Journal of Operations & Production Management, 18 (20, pp. 114–129. 3 Hill, T. (1985) Manufacturing Strategy. London: Macmillan. 4 Hayes, R.H. and Pisano, G.P. (1994) ‘Beyond World-Class: The New Manufacturing Strategy’. Harvard Business Review, January–February, pp. 77–86. 5 Ashby, W.R. (1958) ‘Requisitve Variety and Implications for Control of Complex Systems’. Cybernetica, 1, pp. 83–99. 6 Skinner, W. (1974) ‘The Focused Factory’. Harvard Business Review, May-June, pp. 113–121. 7 Neal, W.D. and Wurst, J. (2001) ‘Advances in Market Segmentation’. Marketing Research. A Magazine of Management and Applications, Spring, 13 (1), pp. 14–18. 8 Matilla, A. (2002) ‘The Role of Emotions in Service Encounters’. Journal of Service Research, 4 (4), pp. 268–277. 9 Moon, Y.M. (2004) ‘Ikea invades America’. Harvard Business School Case Study, 9–504–094. 10 Moorthy, K.S. (1984) ‘Market Segmentation, Self-selection, and Product Line Design’. Marketing Science, 3 (4), pp. 288–307. 11 Akerlof, G. (1970) ‘The Market for Lemons: Quality Uncertainty and the Market Mechanism’ Quarterly Journal of Economics, 84 (3), pp. 488–500. 12 Stiglitz, J. and Rothschild, M. (1976) ‘Equilibrium in Competitive Insurance Markets: The Economics of Markets with Imperfect Information’. Quarterly Journal of Economics, 90 (4), pp. 629–649. 13 Spence, M. (1973) ‘Job Market Signaling’. Quarterly Journal of Economics, 87 (3), pp. 355–374. 14 Moorthy, K.S. (1984) ‘Market Segmentation, Self-selection, and Product Line Design’. Marketing Science, 3 (4), pp. 288–307. 15 Ng, I.C.L. (2005) ‘Does Direct Marketing Need to have a Direction?’. Marketing Intelligence and Planning, 23 (7), pp. 628–635. 16 Crawford, C.M. and Di Benedetto, C.A. (1999) New Products Management, 6th edn. New York: McGraw-Hill/Irwin. 17 Kimes, S.E. and Wirtz, J. (2002) ‘Perceived Fairness of Demand-based Pricing for Restaurants’. Cornell Hotel and Restaurant Administration Quarterly, 41 (1), pp. 338. Kimes, S.E. (2002), Perceived Fairness of Yield Management. Cornell Hotel and Restaurant Administration Quarterly. Vol. 35, No. 1, pp. 22–29. 18 Ng, I.C.L. (2006) ‘Differentiation, Self-selection and Revenue Management’. Journal of Revenue and Pricing Management, 5 (1), pp. 2–9. 19 Png, I.P.L. (1989) ‘Reservations: Customer Insurance in the Marketing of Capacity’. Marketing Science, 8 (3), pp. 248–264. 20 Xie, J. and Shugan, S.M. (2001) ‘Electronic Tickets, Smart Cards and Online Prepayments: When and How to Advance Sell’. Marketing Science, 20 (3), pp. 219–243. 8 Conclusion 1 Berry, L.L. and Yadav, M.S. (1996) ‘Capture and Communicate Value in the Pricing of Services’. Sloan Management Review, Summer, 37 (4), pp. 41–51. 2 Wichmann, R. and Clark, R. (2006) ‘Developing a Defensible Pricing Strategy: Hospital Pricing is a Science, not an Art’. Healthcare Financial Management, October issue, 2006. 3 The Times ‘EU Orders Ryanair to Repay £3m’. 3 February 2004, URL http://business.timesonline.co.uk/tol/business/enterprise/article1010309.ece 4 Bright, K.J., Kiewell, D. and Kincheloe, A.H. (2006) ‘Pricing in a Proliferating

168

Notes

World’. McKinsey Quarterly, August, web-edition, URL http://www.mckinseyquarterly.com/article_page.aspx?ar=1841&L2=16&L3=0 accessed 2 January 2007. 5 Jonason, A. and Holma, B. (2004) ‘Innovative Pricing: A Case of Pricing for Profits on the Mobile Internet’. International Journal of Information Technology and Management, 3 (1), pp. 105–115.

Index

acquisition risk 42, 46–8, 61, 77, 79, 104, 110, 117, 121, 123, 129–31; high 47, 119–20, 130; perception of 131 advanced: buyers 93, 116, 119–20, 122, 145–6; demand i, 105, 109, 116, 118, 120–3, 129–32; pricing 16, 42; purchase 41, 43, 45–7, 49, 51, 53, 55, 57, 59, 61, 63, 65, 67 agents 53, 125, 142 aid firms 5, 114 airline industry 17, 107, 114–15, 128, 145 airlines 2, 8, 15–18, 33, 47, 99, 100, 104, 108, 111–12, 114–15, 126–7, 130–1, 133, 145–6, 150–1 airport 46, 82, 85, 150–1 applications 124, 135–6 assets 6, 17, 59, 60, 150 assurance 14, 37–8, 78, 116, 147 attributes 2, 24, 27–30, 46, 51, 64, 66, 68–9, 78, 80–1, 97, 111, 133–4, 142–4; credence 29–31; intangible 27, 29, 30 attributes benefits 28, 134 augmentation 68–9 availability 2, 78–9, 93, 127, 147–8 average revenue 97–8 Baidu 71–2 Becker 95–6 beliefs 29–31, 51, 118 Belobaba 114–15 benefits 24–31, 48, 54–6, 61, 66–9, 71–3, 75, 77–81, 127–8, 133–4; buyers 133; core 28; perception of 38, 81 Berry 14 bidders 3, 102 bids 3, 101–2 Bitner 30, 62, 84, 138 Boyd 123 branding 30

brands 30–1, 55, 68 bundling 99, 100 business 31, 37, 73, 75, 101, 123, 127; performance 99, 101 buyer: attributes 123; behaviour 14, 60, 117, 122; choice 23, 147; decision process 35; expectations 25–6; purchases 138; risk aversion 117; segments 106, 129, 133, 139 buyer-seller exchange 42 buyer-state dependency 44 buyer values 36, 147 buyers: airline ticket 126; benefit 14; heterogeneous market of 47, 80; high valuation risk 146; highest price 107; influence 29, 30; low time-cost 33; price-insensitive 117; price-sensitive 117; price-taking 124; purchase 62, 121, 147; risk-averse 14, 37, 145; value 146 cancellations 112, 115, 119, 121 capabilities 1, 100, 135, 137, 148 capacity 1, 2, 6, 9, 16, 18–19, 46, 96–101, 107–14, 119–20, 129–37, 146–51; allocations 7, 114–16, 124–5, 129; constraints 46, 97–8, 125, 131; firms 145; fixed 99, 108, 121; idle 99, 100, 108; insufficient 16, 108; large 140, 146; limitation 46, 135; no-show 122; re-selling 119, 122; role of 133; of service firms 99 capacity-based dynamic pricing models 107 carbon footprint 76 cards, credit 80, 126, 145 channel intermediaries 52–3, 100 channels 2, 4, 51–2, 69, 76, 80, 105, 113, 118–19, 151

170

Index

choice 1, 16, 23–4, 29, 38, 41, 47, 54–7, 67, 75, 143–4, 152; service-attribute 144 clients 4, 29, 56, 64, 110, 118–19, 151 co-creation 83–5 companies 31, 44, 62, 66, 76, 82–3, 118, 126, 135–7, 139, 149, 151 competition 5, 17, 26, 53–5, 69, 71, 94, 106, 124, 145 competitors 6, 17, 26, 30, 38, 54, 57, 71, 80, 94–5, 106, 113, 115, 123–5 complexity of service pricing 18 components 10–11, 26, 40, 43–4, 133 conditions 9, 38, 46, 49, 106, 121; fencing 128 congestion 110 consequences 11, 16, 36, 44–5, 68, 78, 145 consumer: demands 95–6; surplus 24, 67, 92–3, 101, 103 consumers 4, 11, 15, 43–4, 52, 55, 58, 61–2, 64, 85, 93, 95–6, 103 consumption 10–11, 14–15, 25, 32, 34–6, 40–3, 46, 52–3, 62–3, 70–1, 109–10, 116–19, 130–2, 139; experience 14; prices 117; process 61, 139; of services 36, 68, 104; time of 15, 43–4, 46–7, 86, 105, 117, 130, 132, 146–7, 150; value 71 contracts 53, 59, 142, 147 costs 16–18, 23–4, 28, 32–3, 35–6, 54–5, 65–6, 70–1, 74–6, 80–1, 96–7, 125–6, 134–5, 139–40; high 17, 121, 147; opportunity 32–3, 59, 61, 76; sunk 18 coupons 112, 142 criticality of consumption 131–2 current capacity-based dynamic pricing practices 107 customer: delight 68–9; effort, role of 82, 85; gap 62–3, 65–6; perception 64; segments 53, 112–13, 138; service 9, (frontline 64); value 24, 41, 64, (extracting 106; unlocking 14) customers 6, 9, 24, 27–8, 41, 43–4, 62–7, 69–76, 78–9, 81–3, 85, 94, 99–101, 110–13, 134–40; high price 140; lower price 140; potential 63, 66, 99; right 113, 115 de-marketing 110 decision sets 133–4 decisions 4, 9, 26, 30, 32, 38, 48–9, 58, 66, 86, 91–2, 96, 111; market-penetrating price 151 definition of service 9 delivery 9, 10, 28, 31, 41–2, 51–2, 64, 68, 110, 134, 139, 148

demand: data 105, 107, 114; forecasting 17, 108, 115, 117, 121–3; function 91–3, 95–8, 104–5, 117, 120, 124 demand-based pricing 2, 18, 126 design 9, 27, 66, 83, 129, 134 Desiraju 116 differentiation 30, 76, 78–81, 93, 100, 129 disciplines 7, 9, 11, 13–14, 18, 56, 115–16 discounted prices benefit 127 discounts 33, 40, 44–5, 48–9, 59, 61, 68, 79, 87, 99, 100, 103, 112, 120, 127–8 dry cleaners 12, 37, 63–4 Dutch auction 101–2 dynamic pricing 105–7, 115; capacity-based 107; demand-based 106; models 2, 105 eBay 71–2, 101 economy 4, 5, 7, 11, 74; class passengers 133 effect, endowment 58–9 effort 1, 11, 40, 47, 53, 57, 66, 68, 81–2, 85, 102, 111, 117, 130, 143; costs 81 elasticity 93–4, 103–4 Elmaghraby 107, 160–2 employees 10, 108, 110, 139, 152 encounter 14, 138–9 entitlement 78 ENV 23, 25–7, 29, 31, 33, 36–7, 39, 40, 48–9, 53–6, 62–7, 72, 78; framework 26, 48, 53, 56, 61, 66, 68, 70 environment 38, 44, 76, 137, 139, 149 equipment 41–2, 108, 118–19 evaluation of net value 26 expectations 14, 25–6, 29, 33, 45, 49, 51, 62–5, 82, 84, 138; of service customers 62 expected: benefits 24, 26–7, 48–9, 51, 54, 56, 61, 66–7, 72–3, (of service 26–7, 61); net value 23, 25–7, 29, 31, 33, 37, 39, 48, 61–5, 67; outlays 26, 31–2, 34, 37, 41, 48, 51, 55, 67, 72–3, (of service 26, 32, 61); service 25, 62–3, 65, 68 experience 14–15, 24, 29, 31, 37, 39, 49, 63, 65–6, 77, 94, 99, 122, 138; attributes 29, 30 factors, random 54, 61 fairness 58, 125–7 fairness perceptions 125–8 financial services 7, 8, 31, 55 firms 2, 4, 5, 16–18, 28–31, 37–8, 56–9, 61–4, 66, 68–74, 76–82, 99–102, 119–21, 124–5, 137–9, 144–9

Index 171 first-time purchase 63, 65 fixed costs 16–18, 134, 150 Fleischmann 116 flexibility 3, 78, 81, 122, 134–5, 144, 147 flights 10, 28–9, 33–4, 47, 65, 69, 80, 85, 93, 96, 100, 147, 150 fly 123, 136, 150 forecasts 17, 107, 114–15, 118, 120, 133 framework 23, 25–7, 29, 31, 33, 37, 39, 56, 66 framing 58–9, 127–8 gains 55, 58–60, 67, 72, 127–8; multiple 59; potential 59 gap 11, 23, 62, 64, 96; provider 62, 64–5 gaps model of service quality xii, 62 goods 2, 4, 7, 8, 10–11, 14–6, 27, 29–31, 37, 41, 43, 52, 56, 87, 94–6, 105–6; firms 7, 48, 119; pricing 149 Google 71–2, 101 Goose, Julie 38–9 gross value minus outlays 24 Gummesson 10–1 healthcare 12, 149, 151 heterogeneity 10–11, 14, 53, 96 high time-cost buyers 33 highest end-value 85 hospitals 43–4, 138, 149 hotels 1, 17–18, 46, 57, 80, 99, 100, 108, 112, 114, 119, 127–31, 150 hygiene factors 69 IBM Research on Services Sciences 9 Ikea 139 implications 48, 57–8, 61, 68, 136 improved revenue 73 incentives 13, 102, 129, 143, 145 industries 5, 7–9, 12–13, 55, 100, 111–14, 124, 133, 149, 152 influence demand 80–1 information 32, 34, 36, 48, 50–1, 53, 72, 74, 80, 82, 86–7, 93, 126–7, 142 insurance 1, 7, 8, 31, 46, 51, 59, 60, 86, 119, 130, 135, 146, 148–9, 151 intangibility 11, 14, 52–3 integrating customer focus 30, 62, 138 interdependence 133–4 Interdisciplinary Review of Pricing Services 12 interest 5–7, 56, 64, 93–4, 105, 114, 124, 143–4 intermediating services 85–7 internet 2–4, 17, 32, 64, 71–2, 74, 81,

86–7, 101, 105–6, 112, 114–15, 126; service providers 85, 114 investment 5, 6, 18, 30, 66 Journal of Service Research 7 Kahneman 55, 58 Keskinocak 107 key definitions of value xiv, 25 Kimes 12, 107, 116, 121, 127–8 knowledge xvi, xvii, xxi, 8, 9, 11, 13, 70, 86, 115 Ladany 12 lawyers 8, 29, 43, 129 learning experience 83–5 Lee 46, 99, 101, 117 level 25, 36, 66, 69, 80, 85, 91–3, 100–2, 116–7, 122, 125, 127, 145 Lieberman 121 limited capacity 106, 108, 117, 119, 129; perception of 46, 131 links, attribute-benefit 27–8 list, waiting 120 literature 11, 46, 106, 113–14, 116, 122; service research 41 loans 1, 47, 58, 108, 135–6 losses 16–7, 33–4, 55, 58–60, 67, 128; pareto 67–8 Lovelock 10, 80 management 9, 11–13, 53, 100, 108, 111, 115–17, 124, 129 managers 4, 14, 18, 96 marginal: costs 5, 16, 18, 24, 37, 81, 97, 100, 105, 134; revenue 5, 18, 24, 96–8 market 2, 4–6, 47, 72–3, 76, 94–5, 100–1, 103, 125–6, 133–5, 142–4, 146, 151; demand 19, 23; segmentable 121; segmentation 68, 108; segments 28, 33, 100, 127, 134, 138–9, 142–3; system 5 marketers 1, 28–9, 52, 68, 137, 143, 151 marketing 4, 11, 13, 56, 116, 130, 137, 142–3; mix 49, 53, 61 maximize revenue 109, 115–16 meals 28–9, 38, 47, 62, 94, 110 models 107, 110–11, 116–17, 124–5, 135, 143; mathematical 124 monetary costs 31–2, 61 money 23, 25–6, 38–9, 55, 58, 63, 71, 79, 86, 110, 126, 133, 137, 146 Monroe 24 multi-attribute 80 multi-service firms 100

172

Index

nannies 75 net value 24–6, 31, 33, 49, 73; perceived 25, 62 Ng 12, 46, 85, 99, 101, 117, 151 no-shows 112, 119–22 non-consumption 77, 119, 145–6 non-monetary: costs 24, 31–2, 34, 37, 61, 67, 69, 72–6, 81, 85, 91–2, 140; outlays 35, 40, 72–3 non-price 62, 67 objectives 4–6, 111, 152 occupied time 141 Operational Research Society 115 operations 9, 134–5, 137, 143; management 130, 137 operations research 7, 130 option 37, 42, 52, 54, 81, 143, 146 organisations 85, 136–7 outlays 5, 25, 31–3, 36, 38–9, 48–9, 54–6, 62–4, 66–9, 75–6, 91, 95, 138; non-price 65, 67–8, 72, 138 overbooking 53, 115, 117, 120–3 oversells 119–20 parents 75, 123, 137 pareto: gains 73; loss amount 67, 72–3, 75, 138 park charges 32, 34 passengers 27, 33, 47, 65, 75, 97, 150 payment 39, 59, 80, 86 perceived service 25, 62–3, 65 perceptions 14, 25, 28, 36, 49, 52, 56–7, 59, 63–4, 80–1, 93, 128, 132, 147 performance 9, 11, 14, 24, 44, 79; of service businesses 9 perishability 11, 16, 42, 108, 110, 150; of services 16, 109 personal concierge 74 PLA 73–5, 138 planes 76, 109, 136–7 Png 117, 146 PNV 25 practise 130–2; revenue management 77, 109, 121, 129–30, 144 practitioners 9 premium 59, 69, 117, 127–8, 136, 142, 146 price: advanced 47, 117, 120; change 105, 112; changes 2, 60, 94, 118, 127; customer-perceived 24; deviations 125; differences 59, 60, 127–8; discounted 99, 145; discrimination 82, 93, 101–4, 111, 126, 129, 138, (second-degree 102,

135; third-degree 103); elasticity 93–4, 103; fair market 126; final 102, 142; given set of 18, 114; high 5, 47, 54, 119, 133, 142, 149–50; higher 14, 27, 37, 40, 45, 47, 57, 59, 62–5, 72, 80–1, 86–7, 91, 109, 146–7; highest 92, 102; hike 94, 126; level 18, 57, 92, 114, 149–50; low 5, 44, 77, 119–20, 142, 151; lower 14, 40, 59, 92, 99, 100, 104, 117, 120, 122, 125, 127–8, 142–3; macroeconomic functions of 4, 5, 149; maximum 102; odd-number 61; optimal 5–7, 96, 105; outlay 73; perception 57–8; points 91, 94, 133, 152; posted 106, 125; predicting buyer reservation 7; premium 14, 117, 142; right 113, 115; service firms charge 118; system 5; takers 91, 96, 124; theory 4, 5, 18, (research 5); ticket 47, 112; wars 17, 30, 54 price quantity capacity 134 price quantity marginal revenue 97 priceline.com 3, 106 pricing: airport services xv, 150; decisions 4, 11–12, 14, 18–19, 53–4, 87, 96, 114, 117, 150–2; experts 5; implications 41, 121; policies 25, 66, 105, 114, 116, 151–2 ‘Pricing Dimensions in Health Care Services’ 12 ‘Pricing Engineering Services’ 12 ‘Pricing and Industrial Services’ 12 ‘Pricing and Location of Physician Services’ 12 ‘Pricing Retail Services’ 12, 154 pricing of services 11–12 probability 26, 43–4, 60, 78 problems 6, 11–13, 16, 23, 36–7, 43, 49, 52, 73, 85, 100, 107–8, 114, 136 processes 9, 11, 14, 28, 32, 51, 53, 64, 66, 83–5, 101, 114–5, 134–6, 138–40, 149 produce-price pair 142 producers 79, 82–3 product 3, 4, 15–17, 23–31, 50–4, 59–61, 66–8, 70–1, 76, 80–1, 94–5, 99, 101, 135–6, 142–4; augmented 28, 68; categories 59; differentiation 80; high-priced 57; lower-priced 57 product-price line 142 product, primary 86 production 10–11, 15–16, 18, 41–2, 52, 83, 109–10, 119, 150 professional services 8, 110, 129 profitability 18, 69, 87, 93, 125, 149–50 profits 5, 6, 16, 23, 65–7, 95, 116–17, 119, 125–6, 145–6

Index 173 programme 9, 68–9 promise 14, 29–31, 44, 52–3, 71, 76 psychology 56, 60–1, 140 purchase 10, 14–15, 23–6, 28–30, 32–6, 39–49, 55–9, 64–5, 76–8, 81, 86–7, 118–21, 138–9; advanced 46; context 58; decouple 76, 130; separation of 40–1, 48, 70, 145; of services 15, 37, 48, 94, 144; spot 46; time of 42–4, 72, 76–7, 79, 104, 118, 150 quality 24–5, 29, 30, 37, 39, 52, 64, 66, 84–5, 93, 110, 139–40 quantity 3, 4, 16, 91–8, 101–2, 105, 109, 133 queues 32–3, 36, 48, 95–6, 120, 139–40 rate fences 46, 126–8, 144 rates 78, 112, 127; flat 78, 148 re-price 137, 139 re-sell 119–20, 146–7 reduced PLA 73 reference: points 57, 59; prices 57–8, 125–6, 128 refunds 78–9, 117, 145–7, 150; full 79, 145; partial 147 regulators 5, 149, 151 relinquished capacity 119–20 repeat purchase 25, 63, 65; Customer gap 65; time purchase 25 research 6–8, 11, 13–14, 17, 23, 56–8, 60–1, 66, 113–14, 116, 121–2, 124–5, 128 reservations 46, 117, 121 resources 4, 5, 67, 112, 135–6; productive 84–5 restaurant pricing 96 restrictions 46, 115, 127 revenue 5–7, 16, 41–2, 55, 71–5, 80–2, 97–8, 108–11, 129–30, 138–40, 150; functions 96–8; higher 23, 54–5, 70–5, 77, 79, 81, 83, 85–7, 122–3, 133, 139, 146; models 72, 86 revenue management 16–17, 103, 107–9, 111, 113–18, 120–35, 137, 139; definition of 113, 115; practices 111–12, 114, 120–1, 125–6, 128, (perceived fairness of 127–8); pricing 128, 166, (perceived fairness of 125; practices 128); problem 115–16; research 113–17, 124; researchers 117–18, 123; scope of 113–14; of services 19, 108–9, 111, 113, 115, 117, 119, 121, 123, 125, 127; systems 7, 111, 114, 122, (new 128, 130, 133, 137)

risk 14, 32, 36–47, 55, 60–1, 78–9, 109, 120, 146–9, 152; high valuation 45, 122–3; revenue loss 109–10; of unavailability 76, 147; unused capacity 109–10 riskier 36–7 role: of price i, 23, 67; of Pricing 12 rooms 41, 47, 82, 104, 108 Rothstein 114 Ryanair 151 Ryzin, van 124 sacrifices 24–5, 32–3 savings 57–8, 60, 126 seats 27, 33, 46–9, 60, 65, 78–9, 93, 96–7, 108–10, 112, 120, 130, 134, 150 segmentation 4, 82, 109, 129, 142–4 segments 28, 34, 66, 99, 101–3, 108–9, 111–12, 122, 126, 133, 142–4, 151 self-selection 142–4 self-service 82, 102 sellers 3–5, 42, 44, 46, 58, 61, 67, 72, 75, 77, 96, 102, 105–6, 110, 117 selling period 41–2, 105, 109–10, 117–8; advanced 104–5, 120–1 sensitivity 93–4 separation 41, 43, 104 service: attributes 81, 118, 122, 142, (tweaking 144); blueprint 138; brands 31, 55; businesses 9, (revenue-generating 74); buyers 40, 80–1, 93, 137, 146; capacity 97, 135; characteristics 10, 13; choices 143–4; components 7, 10; consumption date 48; context 69, 135; customers 32, 62, 66, 84; delivery 10, 15, 62, 66, 80, 143, (process 14, 53); economy 8, 9, 13, 85, 151; encounter 14, 51, 138–40; experience 8, 28, 38, 66, 80, 85; firms 2, 7, 10, 14, 16–17, 28, 45–6, 53, 65–7, 98–100, 108, 130, 149, (profitable 66); industries 7, 9, 13, 16, 18–19, 43, 46, 111, 128, 150–1; level 25, 64; literature 13, 80; marketing mix strategy 61; outcomes 84, 159; price 17; pricing 1, 7, 11, 13, 16, 18, 149, (customisable 2; research 7, 18; strategies 53, 149); processes 134, 136; quality 62, 66, 85, 101; researchers 14; sector 6, 7, 31, 135; value 99 service business 160 Service Industries Journal 7 service Rrsearch 7, 8, 82, 85 services: augmented 68, 80; co-created

174

Index

services continued 84–5; coach 60, 94; core 68, 80, 83–4; distributing 51–2; garage 10, 43, 72; high fixed cost 16, 18; home phone 147; industry 11, 154; legal 29, 30, 108, 131; markets 31; mobile payment 2, 86; motor breakdown 77; personalised 64, 133; postal 52; public 8, 75; quality 14, 25, 63, 66; retail 87; selling 52, 97; shuttle 75; support 11, 118–19; telecommunication 16, 148; tow truck 46, 119; utility 69, 94 services-dominant logic 8 services marketing 14, 30, 62, 138 services sciences 9 shift 8, 55, 60, 94–5 Shugan 116–17, 146 social influences 95–6 society 4, 5, 92 spenders 144–5 spot: buyers 122, 146; demand 118–19, 122, 145–6; prices 77, 120–2, 131–2, 145, (high 77, 121) staff 100, 136–7 state 5, 9, 15, 43–4, 84, 136, 147 step 5, 95, 127, 138, 144, 149 strategic pricing 116, 129, 133, 135, 137, 139, 143, 145, 147 strategic service pricing 116 strategic use of unused service capacity 99 students 69, 83–5 subject 13, 54, 67, 69, 122–3, 138 Subramanian 115 subscription 2, 3, 86, 132, 147 substitutability 54, 130, 136 substitutes 55, 94, 146 sunk 16–18, 97, 134 supermarkets 1, 74, 142, 151 supply 16, 19, 24, 79, 95–6, 99, 106, 113–14, 116, 130, 134, 145 surcharges 127–8 systems 2, 14, 84, 92, 101, 110–11, 122, 135–6 tangible attributes 27, 29–31; examples of 27 technology 1, 9, 14, 36–7, 73–5, 81, 85, 87, 105, 111, 114, 130, 151–2 telecommunication 7, 8, 11, 18, 131 Thaler 58

theatre tickets 24, 48, 96–7, 118 theory 38, 58, 121, 125, 143; prospect 55, 58, 128 third degree price discrimination 104 tickets 34, 43, 45, 47, 52, 74, 78–9, 81, 86, 104, 112, 120, 126, 134, 145 time 15–18, 32–4, 42–4, 46, 48–9, 68–9, 73–4, 76–81, 103–7, 111–12, 116–19, 127–9, 131–2, 138–40, 147; costs 32–3, 73; real 106; spot 43, 46, 109, 118–20, 124, 130 time-based pricing 2, 53 Times Square 49 total revenue 92, 97–8 transaction 8, 24, 125–8 transportation 8, 9, 11, 16–17, 69 Tversky 55 understanding price elasticity 93 unused: capacity 53, 98–100, 109, 151; service capacity 99, 101 utility 16, 26, 42–3, 59, 96, 147 valuation risks 42–8, 61, 77, 79, 104, 110, 117–18, 120, 123, 129, 147 value 10–11, 24–6, 41–4, 48, 50–1, 53, 56–8, 62–6, 68–74, 80–7, 110–2, 125, 129–30, 147–9; best 57, 71, 82, 133; buyers 4; customer-perceived 24; expected 24, 51, 60; gross 24, 26; market segment 133; perceived 24, 59, 86, 127; perceptions 24, 57, 81; positive 41; propositions 68, 135; revised understanding of 67; set 133–4; superior 26, 53, 71 value creation 62, 83 value-oriented pricing 72 variable costs 16–7, 150 willingness 4, 23–4, 26, 39, 41, 44–5, 67–8, 91–2, 95–6, 101, 104, 106, 117, 123 Wirtz 80, 99, 101, 128 world 1, 4, 7, 29, 31, 36, 43, 53, 55, 71–2, 76, 96, 135 Xie 117, 146 Zeithaml 24, 30, 62, 138