Country-Specific Effects of Reputation: A Cross-Country Comparison of Online Auction Markets

214 Pages·2011·1.225 MB·English

by  Christopher Schlägel (auth.)

Christopher Schlägel
Country-Specifi c Effects of Reputation
GABLER RESEARCH
International Management Studies
Herausgegeben von
Professorin Dr. Birgitta Wolff
Die Schriftenreihe trägt dazu bei, Erkenntnisse aus der internationalen Unter-
nehmensforschung zu verbreiten. Die meisten Beiträge zeichnen sich durch eine
Fundierung auf die theoretische Basis der Neuen Institutionenökonomik sowie
eine empirische Analyse aus. Die Reihe ist offen für Arbeiten in deutscher und
englischer Sprache.
The series aims at circulating insights from research projects on international
corporations. Most of its contributions are characterized both by a foundation on
a theoretical basis of the New Institutional Economics and an empirical analysis.
The series is open to works in German and in English.
Christopher Schlägel

Country-Specifi c Effects
of Reputation
A Cross-Country Comparison
of Online Auction Markets
With a foreword by Prof. Dr. Birgitta Wolff
RESEARCH
Bibliographic information published by the Deutsche Nationalbibliothek
The Deutsche Nationalbibliothek lists this publication in the Deutsche Nationalbibliografi e;
detailed bibliographic data are available in the Internet at http://dnb.d-nb.de.
Dissertation University of Magdeburg, 2010
Date of Disputation: 4 March 2010

1st Edition 2011
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ISBN 978-3-8349-2520-6
Foreword
Electronic market platforms such as eBay or the Amazon marketplace enable sellers to offer
products and services to national as well as to international buyers. They provide consumers
with the opportunity to search and compare products and services basically worldwide. While
transactions in electronic markets reduce market entry barriers for sellers and the search costs
for potential buyers, the temporal and spatial separation of anonymous transaction partners
gives rise to opportunistic behavior. Sellers might end up not delivering correctly; customers
might end up not paying. Such behavior would absolutely undermine the effectiveness of
electronic markets. In order to reduce the likelyhood of such behavior, platform providers
have installed certain “anti-opportunism” devices. For instance, payment can be secured
through third parties such as PayPal, or a seller’s reliability can be judged based on
information on his previous record. International electronic market platforms, however, use
the same reputation mechanisms and systems to address these challenges in different countries
in spite of those countries’ different institutional environments. The focus of Christopher
Schlägel’s book is to investigate the influence of different institutional environments on the
relation between the sellers’ reputation and the economic outcomes in electronic markets. He
uses different methods and various data sets to investigate the challenges that arise in
transactions in electronic markets. The results of the four studies included in the book show
that both formal as well as informal institutional environments influence the relation between
reputation and economic outcomes of online transactions. Sellers’ reputations become more
important in countries with lower levels of trust and higher levels of uncertainty avoidance.
Moreover, the results show that the attributes that determine a negative reputation vary across
countries and have country-specific effects on the economic outcomes. Finally, the results also
show that third parties have no influence on the trust building function of reputation. These
insights have various implications for theory and prac-tice. They can help the providers of
electronic market platforms to customize their reputation mechanisms with respect to the
revealed needs and preferences of the respective users. The book is mostly identical with
Christopher Schlägel’s Ph.D. thesis. It contributes to the growing stream of research that
investigates the influence of cross-country differences on transaction partners’ economic
behavior in electronic markets. The results of his work have widely been presented at
international conferences and were received with great interest. The thesis was impressive
with respect to the results but also with respect to Christopher’s craftsmanship in the areas of
data collection and analysis. Everybody involved in the creation of these studies has greatly
benefited from this experience. Using its results in practice can contribute to further improve
the effectiveness and efficiency of electronic markets and, thus, to make the earth a still flatter
place.

Birgitta Wolff
V
Ackowledgments
Having spent the past few years working on this dissertation, I must thank many people. I
could never have finished it without the support and inspiration of my supervisors Birgitta
Wolff and Abdolkarim Sadrieh. Both trained me to think about relevant details and see
opportunities to extend and improve existing literature, which resulted in the papers that lay
the foundation for this dissertation. Without their input, this thesis would never have been
finished in the way it is. I also want to thank all my colleagues at the Otto-von-Guericke-
University Magdeburg. Special words of thanks apply to Marjaana Gunkel, Franziska Krüger,
Fan Wu, Karina Rückert, and Tim Hoppe, who provided ideas, inspiration and support.
Furthermore, I would like to thank Ina Bader, Wencke Petersen, and Anita Wilke – their
thorough comments and suggestions helped to improve my thesis in the final stages. Marco
Rothaufe, Sandra Liebner, Alexander Schardt, Thiemo Fetzer, Pascal Stock, and Benjamin
Hanstein provided extensive and extremely competent assistance in the data collection, for
which I am very grateful. Other researchers with whom I had a chance to interact along these
years also deserve special thanks, especially Robert Engle because of his advice in some of
the research endeavors that I explored. I have learned a lot from him. I benefited from many
discussions with other researchers during my research stays in Tucson and Hamden as well as
during seminars, workshops, and conferences at various stages of the research process. For the
financial support I would like to thank the VHB, DAAD, DFG, and the Schmalenbach-
Gesellschaft für Betriebswirtschaftslehre. Their support was an enormous help in presenting
the studies at international conferences and made it possible for me to spend a research period
at the University of Arizona. Of course, I have also been inspired by lots of people outside of
the academic world. I would specifically like to thank Stefan Henze, Kay Milde, and Marco
Kiel for being great friends during the past, the present, as well as in the future. To conclude, I
would like to thank the most important people in my life. My dear family, you have always
motivated me to do whatever I wanted to do. You raised me to the person I am today, by
being there whenever I needed you. Finally, Esther, thank you for the wonderful person you
are. During the latest years, you spent too much time by yourself, because I had to work.
Without your love, friendship, moral support, encouragement, understanding, and patience
along all these years, I could not have written this dissertation.

Christopher Schlägel

VII
Table of Contents
List of Tables ............................................................................................................................ X(cid:44)(cid:3)
List of Figures ......................................................................................................................... XV(cid:3)
List of Abbreviations ............................................................................................................ XVII(cid:3)
List of Variables .................................................................................................................... XIX(cid:3)
1 Country-Specific Effects of Reputation in Online Auctions – An Introduction .................. 1(cid:3)
2 Online Auction Markets, Reputation Effects, and Institutional Frameworks – A
Literature Review and Conceptual Development ................................................................. 7(cid:3)
2.1 The Relations between Uncertainty, Trust, and Reputation in Online Auctions ............. 8(cid:3)
2.1.1 Online Auction Markets – The Example of eBay ..................................................... 8(cid:3)
2.1.2 Uncertainty in Online Auction Markets .................................................................. 10(cid:3)
2.1.3 Trust and Reputation in Online Auction Markets ................................................... 13(cid:3)
2.1.4 The Effects of Reputation on Online Auction Outcomes – A Meta-Analysis ........ 23(cid:3)
2.1.5 Reputation Effects in Online Auctions – Summary and Hypotheses ..................... 38(cid:3)
2.2 The Influence of Institutional Frameworks on Reputation Effects in Online Auctions . 38(cid:3)
2.2.1 The Formal Institutional Framework ...................................................................... 40(cid:3)
2.2.2 The Informal Institutional Framework ................................................................... 46(cid:3)
2.2.3 The Influence of Institutional Frameworks on Online Auction Transactions ........ 50(cid:3)
2.2.4 Reputation Effects in Different Institutional Frameworks – A Literature Review . 53(cid:3)
2.2.5 Institutional Frameworks and Reputation Effects – Summary and Hypotheses .... 56(cid:3)
2.3 Country-Specific Reasons for Negative Feedback Ratings ............................................ 57(cid:3)
2.3.1 Categories of Negative Feedback Ratings – A Literature Review ......................... 57(cid:3)
2.3.2 The Influence of Institutional Frameworks on Negative Feedback Categories ...... 60(cid:3)
2.3.3 Institutional Frameworks and Negative Feedback Categories – Summary and
Exploratory Research Questions ............................................................................. 62(cid:3)
2.4 Summary of Hypotheses and Exploratory Research Questions ..................................... 63(cid:3)
3 Comparing Reputation Effects between Countries – The Research Method ...................... 65(cid:3)
3.1 Samples and Data Collection .......................................................................................... 65(cid:3)
3.1.1 Samples and Data Collection – Study 1: Product Types ........................................ 65(cid:3)
3.1.2 Samples and Data Collection – Study 2: Negative Feedback Categories ............... 68(cid:3)
3.1.3 Samples and Data Collection – Study 3: Country Clusters .................................... 69(cid:3)
3.2 Variables and Measures in the Quantitative Analysis .................................................... 71(cid:3)
3.2.1 Variables and Measures – Study 1 .......................................................................... 72(cid:3)
3.2.2 Variables and Measures – Study 2 .......................................................................... 73(cid:3)
3.2.3 Variables and Measures – Study 3 .......................................................................... 74(cid:3)
3.3 The Quantitative Data Analysis ...................................................................................... 75(cid:3)
3.4 The Qualitative Data Analysis ........................................................................................ 78(cid:3)
IX
4 Country-Specific Effects of Reputation – Analysis and Results of Study 1 ....................... 83(cid:3)
4.1 Product Characteristics and Country-Specific Reputation Effects ................................. 83(cid:3)
4.2 Discussion and Consequences – Study 1 ...................................................................... 109(cid:3)
5 The Effects of Buyer Complaint Categories on Auction Outcomes – Analysis and
Results of Study 2.............................................................................................................. 115(cid:3)
5.1 The Effect of Reputation on Auction Outcomes .......................................................... 115(cid:3)
5.2 Negative Feedback Categories and their Effect on Auction Outcomes ....................... 125(cid:3)
5.3 Discussion and Consequences – Study 2 ...................................................................... 134(cid:3)
6 Uncertainty Avoidance, Third Party Insurance, and Reputation Effects – Analysis and
Results of Study 3.............................................................................................................. 137(cid:3)
6.1 The Effects of Reputation and Third Party Insurance on Online Auction Outcomes .. 137(cid:3)
6.2 Discussion and Consequences – Study 3 ...................................................................... 153(cid:3)
7 Discussion, Limitations, and Directions for Further Research ......................................... 157(cid:3)
Bibliography ........................................................................................................................... 161(cid:3)
Appendices ............................................................................................................................. 177(cid:3)

X
List of Tables
Table 1: Internet Auction Fraud in the U.S. .............................................................................. 11(cid:3)
Table 2: The Effects of Reputation on the Probability of Sale ................................................. 25(cid:3)
Table 3: Determinants of the Probability of Sale ...................................................................... 27(cid:3)
Table 4: The Effects of Reputation on the Number of Bidders ................................................ 28(cid:3)
Table 5: Determinants of the Number of Bidders ..................................................................... 29(cid:3)
Table 6: The Effects of Reputation on the Number of Bids ...................................................... 29(cid:3)
Table 7: Determinants of the Number of Bids .......................................................................... 30(cid:3)
Table 8: The Effects of Reputation on Auction Prices .............................................................. 31(cid:3)
Table 9: Determinants of Auction Prices .................................................................................. 33(cid:3)
Table 10: Liability Periods in Germany .................................................................................... 42(cid:3)
Table 11: Uncertainty Avoidance and Interpersonal Trust ....................................................... 49(cid:3)
Table 12: Cross-Country Comparisons of the Effect of Reputation on Auction Outcomes ..... 54(cid:3)
Table 13: The Effect of Feedback Comments ........................................................................... 58(cid:3)
Table 14: Hypotheses and Explorative Research Questions ..................................................... 64(cid:3)
Table 15: Item Characteristics – Study 1 .................................................................................. 66(cid:3)
Table 16: Homogeneous and Heterogeneous Item Samples – Study 1 ..................................... 66(cid:3)
Table 17: Overview of the Quantitative Datasets – Study 2 ..................................................... 69(cid:3)
Table 18: Overview of the Main Datasets – Study 3 ................................................................ 70(cid:3)
Table 19: Overview of the Sub-Datasets – Study 3 .................................................................. 71(cid:3)
Table 20: Description of Variables – Study 1 ........................................................................... 73(cid:3)
Table 21: Description of Additional Variables – Study 2 ......................................................... 74(cid:3)
Table 22: Description of Variables – Study 3 ........................................................................... 75(cid:3)
Table 23: Buyer Complaint Categories, Descriptions, and Examples ...................................... 81(cid:3)
Table 24: Descriptive Statistics – Compact Discs Sample ....................................................... 84(cid:3)
Table 25: Descriptive Statistics – Digital Cameras Sample ...................................................... 85(cid:3)
Table 26: Descriptive Statistics – Silver Coin Sample ............................................................. 86(cid:3)
Table 27: Descriptive Statistics – Gold Coin Sample ............................................................... 87(cid:3)
Table 28: Results of Regression Analysis – Number of Bidders (Unused Items) .................... 89(cid:3)
Table 29: Summary of Regression Results – Number of Bidders (Unused Items) ................... 90(cid:3)
Table 30: Results of Regression Analysis – Number of Bidders (Used Items) ........................ 91(cid:3)
Table 31: Summary of Regression Result – Number of Bidders (Used Items) ........................ 92(cid:3)
Table 32: Results of Moderated Regression Analysis – Compact Disc Sample ....................... 94(cid:3)
Table 33: Results of Moderated Regression Analysis – Digital Camera Sample ..................... 95(cid:3)
XI