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Social Preferences Under Risk Peer Types and Relationships in Economic Decision Making Social Preferences under Risk Peer Types and Relationships in Economic Decision Making Zur Erlangung des akademischen Grades eines Doktors der Wirtschaftswissenschaften (Dr. rer. pol.) von der Fakultät für Wirtschaftswissenschaften des Karlsruhe Instituts für Technologie (KIT) genehmigte Dissertation von Dipl.-Wi.-Ing. Timm Teubner Referent: Prof. Dr. Christof Weinhardt Korreferent: Prof. Dr. Karl-Martin Ehrhart Tag der mündlichen Prüfung: 5. Dezember 2013 2013 Karlsruhe Acknowledgements This work would not have been possible without the support of many people, towards whom I would like to express my gratitude. It has benefited from their remarks, ideas, challenging questions, proof reading, and from their personal support and encourage- ment. First of all, I would like to thank my advisor Prof. Dr. Christof Weinhardt for enabling and supporting my research over the last 3 years. His enthusiasm and visionary thinking have inspired much of my work and motivated and guided me throughout this time. I would like to thank my co-advisor Prof. Dr. Karl-Martin Ehrhart for his constructive comments. My thanks also go to Prof. Dr. Clemens Puppe and Prof. Dr. Jan Kowalski for serving on the board of examiners. I thank Marc Adam for his terrific support. His hints and comments have constituted a steady backing and wise counselling throughout the last years. I would also like to thank all my colleagues at our Institute for constituting such a pleasant environment. I thank Christoph Flath, Henner Gimpel, Stephan Meyer, and Rico Knapper for their invaluable feedback, thoughts, and for brightening up my time at the Institute and at various sporting activities. Many thanks go to my officemates for countless coffees and many enriching conversations, particularly to Jens Ilg and Philipp Astor. I thank Silard Toth, Deniz Tschammler, David Harbeke, Sebastian Gatzer, Max Fer- dinand Kunz, Stephan Meyer, Christoph Buring, Christoph Flath, Florian Teschner, Marc Adam, Philipp Astor, Sarah Zhang, Henner Gimpel, and Athanasios Mazarakis for reading, commenting on, and improving parts of this work. Lastly, I would like to thank my family and my friends who have supported me through- out the time in Karlsruhe and elsewhere and, when necessary, reminded me that there is also a life besides research. Thank you! Karlsruhe, December 2013 Timm Teubner i Contents 1. Introduction 1 1.1. The “Peer-to-Peer Economy” . .2 1.2. The Market Engineering Approach . .4 1.3. Research Questions . .8 1.4. Structure of the Thesis . 11 2. Foundations 13 2.1. Social Preferences . 13 2.1.1. Foundations . 14 2.1.2. Distributional, Type, and Intention Based Preferences . 15 2.1.3. Reciprocity . 18 2.1.4. Emotional Motives . 19 2.1.5. Models of Social Preferences . 25 2.1.6. Experimental Measurement of Social Preferences . 29 2.1.7. Application Example of Social Preferences . 31 2.2. Risk Preferences . 33 2.2.1. Foundations . 33 2.2.2. Risk Preferences Elicitation . 41 2.3. Social Preferences and Risk . 43 2.3.1. Foundations . 44 2.3.2. Classification Framework . 47 2.3.3. Related Literature . 51 3. Measuring Risk Preferences in Ad-Hoc Experiments 59 3.1. Methodological Issues in Economic Experiments . 59 3.2. Ad-Hoc Risk Preference Elicitation . 62 3.2.1. Considerations and Requirements . 63 3.2.2. A Proposition based on the Holt and Laury Task . 64 3.3. Experimental Design . 67 3.4. Results . 69 3.4.1. General Statistics . 69 3.4.2. Correlation and Regression Analysis . 71 3.5. Discussion and Conclusions . 74 iii Contents 4. Risky Decisions among Humans and Computers 77 4.1. Auctions and Electronic Markets . 78 4.2. Theoretical Background and Hypotheses . 80 4.2.1. Immediate Emotions and Arousal during the Auction . 81 4.2.2. Social Competition and Bidding . 83 4.2.3. Arousal and Bidding Behavior . 85 4.3. Experimental Design . 87 4.3.1. Treatment and Session Structure . 87 4.3.2. Auction Process . 89 4.3.3. Procedure . 90 4.3.4. Physiological Measurements . 93 4.4. Results . 94 4.4.1. Immediate Emotions in Response to Auction Events . 94 4.4.2. Market Environment, Arousal, and Bidding Behavior . 98 4.4.3. Efficiency . 106 4.5. Discussion and Conclusions . 107 4.5.1. Practical Implications . 108 4.5.2. Theoretical Implications . 110 4.5.3. Limitations and Future Work . 112 5. Risky Decisions among Friends and Strangers 115 5.1. The 2-Person Risk Game . 117 5.2. Experimental Design . 120 5.3. Empirical Results . 123 5.3.1. Behavioral Data . 124 5.3.2. Correlation Analysis . 127 5.3.3. Logit Regressions . 129 5.3.4. Intermediate Summary . 134 5.4. Formal and Strategic Analysis . 134 5.4.1. Utility Function and Risk Aggregation . 135 5.4.2. Decision Alternatives . 137 5.4.3. Best Responses . 138 5.4.4. First Mover Perspective . 143 5.4.5. Equilibria . 145 5.5. Model Fit and Benchmark . 149 5.5.1. Parameter Estimation . 150 5.5.2. Sensitivity Analysis . 151 5.5.3. Comparison to Existing Models . 152 5.6. Discussion and Conclusions . 154 5.6.1. Practical Implications . 155 5.6.2. Theoretical Implications . 157 5.6.3. Limitations and Future Work . 159 iv Contents 6. Conclusion 163 6.1. Contributions . 163 6.2. Limitations . 167 6.3. Propositions for Future Work . 170 6.4. Conclusions . 173 A. Experimental Measurement of Social Preferences 177 B. Participant Instructions 179 B.1. Instructions for the Risk Aversion Tasks . 179 B.2. Instructions for the Auction Study . 180 B.3. Instructions for the 2-Person Risk Game . 182 C. Correlation Tables and Logit Regressions 185 D. Sensitivity Analysis 189 E. Formal Representation of Best Response Indifference Curves 193 References 195 List of Abbreviations iv List of Figures vii List of Symbols ix List of Tables xi v Chapter 1. Introduction “Live together like brothers and do business like strangers.” (Arabic proverb) Virtuality has changed the way commerce is conducted, even how economies work, since “the Internet has influenced the economy in every respect” (Choi and Yi, 2009, p. 39). Where ancient market places were built on personal relationships and in-person trans- actions, the consumer culture of the 20th century was rather characterized by mass markets and anonymity. E-Commerce on the Internet now comprises both aspects: On the one hand, many online market places yield anonymity among the transaction part- ners, sometimes even ambiguity about the nature of the other party. On the other hand, however, recent forms of e-commerce are explicitly based on the notion of personal con- nections and relations. Starting from services like eBay early on, peer-to-peer platforms today allow to market and share spare real estate, commodities, skills, or time. In the “global village,” knowledge about identity, history, and accountability potentially decreases economic risk and thus increases potential counterparts’ mutual trustworthi- ness, which is a prerequisite for exchange. Operators of peer-to-peer platforms have recognized this and urge their users to create personal profiles and maintain their online presence, let alone the appearance in online social networks. This puts transactions in e-commerce increasingly into a social context. And it leads to new questions for market engineers, designers and operators of e-commerce platforms, but also with regard to economic decision situations involving social facets in a wider sense. 1 Chapter 1. Introduction In particular, the aspects social context and risk become more explicit in online envi- ronments, since people lack the necessary sensing capabilities when there is no physical presence and direct contact. But the factors social context and risk are neither new nor limited to e-commerce. They do, however, appear in a new light in the context of peer-to-peer economies, in some cases even driving business success. The convergence of “private” and “professional” sphere in many e-commerce applications raises new ques- tions. On the one hand, economic decision making may be distorted when the mere economic outcome is intermingled with personal and relational objectives. The gen- eral presence of peers may, on the other hand, be part of an online- and peer-to-peer provider’s value proposition, be it the thrill of competing, the “warm-glow” of helping others, or the anticipation of complacent interaction. This work thus addresses risky decision making in stylized market situations, which are characterized by the presence of a peer. In two major experimental studies, the peer’s role is investigated by systematically varying i) the nature of the peer (human or computer), and ii) the relationship to the peer (friend or stranger). The interplay of social context and individual risk preferences should be of interest in view of economic and information systems related matters. By taking a theoretical and practical perspective, this work may inform market design as well as operators and users in the e-commerce business. 1.1. The “Peer-to-Peer Economy” The advent of the personal computer and the World Wide Web have caused a shift in the structure of who is able to offer products and services to a global pool of potential customers. E-business and e-commerce have almost become the default form of economic exchange and are ubiquitous in today’s society. “As computers and the Internet pervade almost every corner of life, the impact of IT on economic behavior is definitive” (Riedl et al., 2011, p. 2). Whereas it was long reserved to large corporations with sufficient resources for development, marketing, and logistics, private persons can now make use of different kinds of information systems and online channels in order to develop and offer their products and services to a global clientele, as well as to purchase and consume from it. These private entrepreneurs not only satisfy the demand of an anonymous consumer market, but sell to and interact with other private persons.
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