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Pricing Strategies in Online & Offline Retailing Pricing Strategies in Online & Offline Retailing Gottfried Gruber Institute for Management Information Systems Vienna University of Economics and Business Administration Augasse 2–6, 1090 Wien [email protected] Supervisor Hans Robert Hansen Institute for Management Information Systems Vienna University of Economics and Business Administration Augasse 2–6, 1090 Wien [email protected] Fall 2008 Abstract The thesis deals with pricing strategies for multichannel retailers, espe- cially traditional stores which additionally manage an online shop. The problem of integrating two sales channels and applying a well-suited pricing strategy is still an emergent question. This work develops a stochastic model to represent consumer behavior on pricing. On the one hand the model contains two probability functions which render consumers’ reservation prices for each individual channel. On the other hand the stochastic model is based on numerous distributions which rep- resent switching probabilities from and to each separate channel. The various distribution functions will be estimated from the results of a sur- vey. To highlight differences of pricing strategies due to several product categories a cross comparisons of books, clothes and digital cameras will be presented. The results show that there are differences in multichannel pricing of the various products. These inequalities stem from consumers’ perceptions of the sales channels. For each product a separate sales channel is pre- ferred by consumers. Therefore, one channel exhibits some advantage versus the alternative channels. This advantage is reflected in different pricing strategies. Further appropriate marketing strategies could help a firm to counter discounting by its competitors. So firms should keep an eye on the reservation price structure of its consumers as well as their demanded marketing activities. Zusammenfassung Diese Arbeit beschaftigt¨ sich mit der Preispolitik im Mehrkanalvertrieb, im Speziellen werden traditionelle Ladengeschafte¨ die auch einen Onli- neshop betreiben untersucht. Die Integration mehrerer Vertriebskanale¨ und die Realisierung einer entsprechenden Preisstrategie stellt noch im- mer eine kritische Frage dar. In dieser Arbeit wird ein stochastis- ches Modell entwickelt, dass das Einkaufsverhalten der Konsumenten darstellt. Das Modell besteht aus zwei Wahrscheinlichkeitsfunktionen, die die Reservationspreise der Konsumenten in jedem Vertriebskanal reprasentieren.¨ Ferner basiert das Modell auf mehreren Wahrschein- lichkeitsfunktionen, die die Wechselwahrscheinlichkeiten zwischen den verschiedenen Kanalen¨ darstellen. Die unterschiedlichen Wahrschein- lichkeiten werden mithilfe einer Umfrage geschatzt.¨ Differenzen in der Preispolitik werden anhand von Buchern,¨ Kleidung und Digitalkameras erschlossen. Die Unterschiede in der Preispolitik stammen von unterschiedlichen Wahrnehmungen der Vertriebskanale¨ durch die Konsumenten. Fur¨ jedes Produkt wird ein anderer Kanal von den Konsumenten bevorzugt. Diese Vorliebe ermoglicht¨ unterschiedlichen Preisstrategien. Des Weit- eren kann durch eine angepasste Marketingstrategie besser auf Preisat- tacken von Mitbewerbern reagiert werden. Daher sollten Unternehmen sowohl die Reservationspreise ihrer Kunden beobachten als auch deren geforderten Marketinghandlungen anbieten. Acknowledgements Firstly, I like to take this opportunity to thank the people who provided scientific support to make this work possible. I would like to express profound gratitude to my advisors Prof. Hans Robert Hansen and Prof. Kurt Hornik for their invaluable support, en- couragement, supervision and useful suggestions throughout this re- search work. I am grateful for the cooperation of two companies by allowing me to publish my survey on their web presence. I really appreciate the kindness of Mag. Anja Sickinger (thalia.at) and Mag. Evelyn Thumb (geizhals.at) for their support in advertising my survey. Moreover, I would like to acknowledge all of my respondents who answered my survey. My sincere thanks go to many friends and colleagues from the Institute for Management Information Systems, Vienna University of Business Administration, for scientific discussion, advice and continuous support always so greatly appreciated. Finally, I want to thank my family for their love and support. My parents raised me to believe that I could achieve anything I set my mind to. Gottfried Gruber, Fall 2008 Its not that I am so smart. Its just that I stay with problems longer. (Albert Einstein) CONTENTS i Contents 1 Introduction 1 2 Literature Review 7 2.1 PriceLevels............................. 9 2.2 PriceElasticity ........................... 10 2.3 PriceDispersion........................... 11 2.4 SearchCosts............................. 12 2.5 TransactionsCosts ......................... 13 2.6 PricingStrategies . 14 2.7 TaskDefinitions........................... 18 2.7.1 Physical Surroundings . 19 2.7.2 Social Surroundings . 20 2.7.3 TemporalAspects. 21 2.7.4 TaskDefinitions . 22 2.7.5 AntecedentStates. 22 3 Reservation Prices 25 4 Research Scope 27 4.1 Discussion of Conditions . 28 4.2 Discussion of Strategic Decisions . 30 4.3 MarketModel............................ 31 5 Conceptual Consumer Model 33 5.1 Demographics............................ 34 ii CONTENTS 5.2 Product ............................... 35 5.3 ShoppingGoal ........................... 37 5.4 LatentDemand ........................... 39 5.5 Formation of Reservation Prices . 41 5.6 The Product-Shopping Goal Link . 42 6 Basic Model 45 6.1 ReservationPrices. 47 6.2 Intra-Firm Switching . 51 6.3 Inter-Firm Switching . 54 6.4 AssemblingtheModel . 56 6.5 ExpectedValue ........................... 62 6.6 PriceElasticity ........................... 69 7 Basic Model - Refined 73 7.1 InfluenceofMarketing . 73 7.1.1 StrategicScope . 76 7.1.2 ProductPolicy ....................... 78 7.1.3 Communication Policy . 83 7.1.4 Distribution Policy . 87 8 Simulation Model 89 8.1 TheFirmSide............................ 90 8.2 TheConsumerSide......................... 91 8.3 Scenarios .............................. 92 8.4 The Beta Distribution . 93 8.5 Estimating Beta Distributions with Maximum Likelihood . 94 9 Methodology 97 9.1 Survey................................ 97 9.2 Sample Constitution . 98 10 Results Books 101 10.1 Marketing Strategies . 104 CONTENTS iii 10.2 Elasticity ..............................107 10.3 MeanandVariance . 109 10.4 Consumer Drift Dynamics . 110 10.5Pricing................................116 11 Results Clothes 121 11.1 Marketing Strategies . 123 11.2 Elasticity ..............................127 11.3 MeanandVariance . 128 11.4 Consumer Drift Dynamics . 129 11.5Pricing................................134 12 Results Digital Camera 137 12.1 Marketing Strategies . 140 12.2 Elasticity ..............................143 12.3 MeanandVariance . 145 12.4 Consumer Drift Dynamics . 145 12.5Pricing................................150 13 Cross-Comparison 153 14 Conclusion and Limitations 159 14.1 Conclusion .............................159 14.2 Limitations .............................161 A Detailed Tables 181 A.1 Books ................................181 A.2 Clothes ...............................194 A.3 DigitalCameras...........................207 B Questionnaire 221 B.1 InternetUsage............................221 B.2 Shopping Behaviour . 222 B.3 PersonalityTraits . 223 B.4 PurchaseBehavior .........................225 iv CONTENTS B.5 Demographic ............................232 C Sourcecode 235 LIST OF FIGURES v List of Figures 2.1 InfluencesontheBasicModel . 8 2.2 S-O-R Model (Belk 1975) . 19 2.3 Parameters of Task Definitions . 19 4.1 Elements of the E-Commerce Business Model (Hansen 1998) . 27 4.2 MarketModel............................ 31 5.1 ConceptualConsumerModel. 33 6.1 Probability Density Function of Offline Reservation Prices .... 50 6.2 Probability Density Function of the Switching Probability from the Online Channel to the Offline Channel . 53 6.3 Switching Probabilities of the Online Channel Consumer Base of Firm1................................ 56 7.1 Additional Dimensions of the Refined Model (Hansen 2005) . 76 9.1 AgeStructure ............................ 99 9.2 Educational Structure . 100 10.1 Frequency of Relative Price Statements . 102 10.2 Importance of Marketing Attributes Offline . 105 10.3 Importance of Marketing Attributes Online . 106 10.4 Price Elasticity versus the Offline Price of Firm 1 . 108 10.5 Elasticity ..............................112 11.1 Frequency of Relative Price Statements . 122 vi LIST OF FIGURES 11.2 Importance of Marketing Attributes Offline . 125 11.3 Importance of Marketing Attributes Online . 125 11.4 Price Elasticity versus the Offline Price of Firm 1 . 127 11.5 Elasticity ..............................130 12.1 Frequency of Relative Price Price Statements . 138 12.2 Importance of Marketing Attributes Offline . 140 12.3 Importance of Marketing Attributes Online . 141 12.4 Price Elasticity versus the Offline Price of Firm 1 . 143 12.5 Elasticity ..............................146 LIST OF TABLES vii List of Tables 8.1 SimulationScenarios . 92 10.1 Parameters for the Beta Distributions . 103 10.2 Optimal Marketing Investments . 107 10.3 ResultsSummary . 110 10.4 InitialOffsetValues. 111 10.5 ResultsSummary . 117 11.1 Parameter for the Beta Distribution . 123 11.2 Optimal Marketing Spending . 126 11.3 ResultsSummary . 128 11.4 InitialOffsetValues. 129 11.5 ResultsSummary . 134 12.1 Parameter for the Beta Distribution . 139 12.2 Optimal Marketing Spending
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