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The Impact of Information Diffusion on Bidding Behavior in Secret Reserve Price Auctions

Author

Listed:
  • Oliver Hinz

    () (Johann Wolfgang Goethe-University, 60054 Frankfurt am Main, Germany)

  • Martin Spann

    () (University of Passau, 94032 Passau, Germany)

Abstract

The interactive nature of the Internet promotes collaborative business models (e.g., auctions) and facilitates information-sharing via social networks. In Internet auctions, an important design option for sellers is the setting of a secret reserve price that has to be met by a buyer's bid for a successful purchase. Bidders have strong incentives to learn more about the secret reserve price in these auctions, thereby relying on their own network of friends or digital networks of users with similar interests and information needs. Information-sharing and flow in digital networks, both person-to-person and via communities, can change bidding behavior and thus can have important implications for buyers and sellers in secret reserve price auctions. This paper uses a multiparadigm approach to analyze the impact of information diffusion in social networks on bidding behavior in secret reserve price auctions. We first develop an analytical model for the effect of shared information on individual bidding behavior in a secret reserve price auction with a single buyer facing a single seller similar to eBay's Best Offer and some variants of NYOP. Next, we combine the implications from our analytical model with relational data that describe the individual's position in social networks. We empirically test the implications of our analytical model in a laboratory experiment, and examine the impact of information diffusion in social networks on bidding behavior in a field study with real purchases where we use a virtual world as proxy for the real world. We find that the amount and dispersion of information in the individualized context, and betweenness centrality in the social network context, have a significant impact on bidding behavior. Finally, we discuss the implications of our results for buyers and sellers.

Suggested Citation

  • Oliver Hinz & Martin Spann, 2008. "The Impact of Information Diffusion on Bidding Behavior in Secret Reserve Price Auctions," Information Systems Research, INFORMS, vol. 19(3), pages 351-368, September.
  • Handle: RePEc:inm:orisre:v:19:y:2008:i:3:p:351-368
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    File URL: http://dx.doi.org/10.1287/isre.1080.0190
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    Cited by:

    1. repec:eee:jouret:v:91:y:2015:i:1:p:68-88 is not listed on IDEAS
    2. Krämer, Florentin & Schmidt, Klaus M. & Spann, Martin & Stich, Lucas, 2017. "Delegating pricing power to customers: Pay What You Want or Name Your Own Price?," Journal of Economic Behavior & Organization, Elsevier, vol. 136(C), pages 125-140.
    3. Yadav, Manjit S. & de Valck, Kristine & Hennig-Thurau, Thorsten & Hoffman, Donna L. & Spann, Martin, 2013. "Social Commerce: A Contingency Framework for Assessing Marketing Potential," Journal of Interactive Marketing, Elsevier, vol. 27(4), pages 311-323.
    4. Sebastian Voigt & Oliver Hinz, 2017. "Assessing the economic effects of server launches in free-to-play MMO games," Journal of Business Economics, Springer, vol. 87(4), pages 421-464, May.
    5. repec:spr:jbecon:v:87:y:2017:i:6:d:10.1007_s11573-016-0839-z is not listed on IDEAS
    6. repec:eee:jouret:v:90:y:2014:i:4:p:445-462 is not listed on IDEAS
    7. repec:spr:infosf:v:19:y:2017:i:4:d:10.1007_s10796-016-9638-x is not listed on IDEAS
    8. Michaela Sprenger & Tobias Mettler & Robert Winter, 0. "A viability theory for digital businesses: Exploring the evolutionary changes of revenue mechanisms to support managerial decisions," Information Systems Frontiers, Springer, vol. 0, pages 1-24.
    9. Krämer, Florentin & Schmidt, Klaus M. & Spann, Martin & Stich, Lucas, 2017. "Delegating pricing power to customers: Pay What You Want or Name Your Own Price?," Journal of Economic Behavior & Organization, Elsevier, vol. 136(C), pages 125-140.
    10. repec:eee:joinma:v:24:y:2010:i:4:p:283-296 is not listed on IDEAS
    11. Martin Spann & Robert Zeithammer & Gerald Häubl, 2010. "Optimal Reverse-Pricing Mechanisms," Marketing Science, INFORMS, vol. 29(6), pages 1058-1070, 11-12.
    12. repec:eee:jouret:v:88:y:2012:i:1:p:131-144 is not listed on IDEAS
    13. repec:eee:jouret:v:88:y:2012:i:1:p:180-188 is not listed on IDEAS
    14. Florian Probst & Laura Grosswiele & Regina Pfleger, 2013. "Who will lead and who will follow: Identifying Influential Users in Online Social Networks," Business & Information Systems Engineering: The International Journal of WIRTSCHAFTSINFORMATIK, Springer;Gesellschaft für Informatik e.V. (GI), vol. 5(3), pages 179-193, June.
    15. repec:eee:joinma:v:28:y:2014:i:1:p:68-85 is not listed on IDEAS
    16. Jiao, Feng, 2011. "Bidding behaviors in eBay auctions: secret reservation price and endogenous entry," MPRA Paper 35081, University Library of Munich, Germany.
    17. repec:eee:ijrema:v:31:y:2014:i:4:p:368-379 is not listed on IDEAS
    18. Chen, Yahong & Li, Jinlin & Huang, He & Ran, Lun & Hu, Yusheng, 2017. "Encouraging information sharing to boost the name-your-own-price auction," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 479(C), pages 108-117.
    19. Martin Spann & Oliver Hinz & Vandana Ramachandran, 2013. "Business and Information Systems Engineering and Marketing," Business & Information Systems Engineering: The International Journal of WIRTSCHAFTSINFORMATIK, Springer;Gesellschaft für Informatik e.V. (GI), vol. 5(3), pages 127-128, June.
    20. Michael Nofer & Oliver Hinz, 2015. "Using Twitter to Predict the Stock Market," Business & Information Systems Engineering: The International Journal of WIRTSCHAFTSINFORMATIK, Springer;Gesellschaft für Informatik e.V. (GI), vol. 57(4), pages 229-242, August.

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