Bidding Strategy in Simultaneous English Auctions Using Game Theory

Part of the Advances in Intelligent Systems and Computing book series (AISC, volume 174)


With more and more people using the internet for a wide range of purposes, internet use has become an absolute necessity for businesses to survive and grow. Online auction have expanded rapidly over the last decade and have become a fascinating new type of business or commercial transaction in this digital era. The online auction is an important e-commerce application which enables the buying and selling of goods through a dynamic pricing strategy. Users can access the auction system through the Web, WAP-enabled devices and agents. The paper assumes that the auction system supports only English auction. Predicting bidding strategy is not easy, since it is dependent on many factors such as the behavior of each bidder, the number of bidders participating in that auction as well as each bidder’s reservation price. Here, simultaneous English auctions for the same item are considered. This paper uses the concept of Game Theory, to predict the bidding strategy in an auction and helps the user to decide whether to proceed with the auction or to back off from the auction so as to maximize the bidder’s profit. This paper considers the user, bidding for an item simultaneously in more than one auction site.


English auctions bidding and Game Theory 


Unable to display preview. Download preview PDF.

Unable to display preview. Download preview PDF.


  1. 1.
    Bagchi, A., Saroop, A.: Indian Institute of Management Calcutta. Internet Auctions: Some Issues and ProblemsGoogle Scholar
  2. 2.
    ter Hofstede, A., Governatori, G., Dumas, M., Russell, N.: An Architecture for Assembling Agents that Participate in Alternative Heterogeneous Auctions. In: Proceedings of the 12th International Workshop on Research Issues in Data Engineering e-Commerce/e-Business Systems (RIDE 2002). IEEE (2002)Google Scholar
  3. 3.
    Aumann, R.: Backward Induction and Common Knowledge of Rationality. Games and Economic Behavior 8, 6–19 (1995)MathSciNetMATHCrossRefGoogle Scholar
  4. 4.
    Axelrod, R.: Effective choice in the Prisoner’s Dilemma. Journal of Conflict Resolution 24, 3–25 (1980)CrossRefGoogle Scholar
  5. 5.
    Bapna, R., Goes, P., Gupta, A.: Insights and Analyses of Online Auctions. Communications of the ACM 44(11), 43–50 (2001)CrossRefGoogle Scholar
  6. 6.
    Cassady, R.J.R.: Auctions and Auctioneering 58(4), 959–963 (1968)Google Scholar
  7. 7.
    Camerer, C.F.: Behavioral Game Theory: Predicting Human Behavior in Strategic SituationsGoogle Scholar
  8. 8.
    David, E., Rogers, A., Schiff, J., Kraus, S., Jennings, N.R.: Optimal design for English auctions with discrete bid level. In: Proceedings of Sixth ACM Conference on Electronic Commerce (EC 2005), Vancouver, Canada, pp. 98–107 (2005)Google Scholar
  9. 9.
    Fudenberg, D., Tirole, J.: Game TheoryGoogle Scholar
  10. 10.
    He, M., Leung, H., Jennings, N.R.: A fuzzy logic based bidding strategy for autonomous agents in continuous double auctions. IEEE Trans. on Knowledge and Data Engineering 15(6), 1345–11363 (2003)CrossRefGoogle Scholar
  11. 11.
  12. 12.
    Green, K.C.: Forecasting Decision. In: Conflicts: Analogy, Game Theory, Unaided Judgment and Simulation ComparedGoogle Scholar
  13. 13.
    Lee, H.G.: Electronic Brokerage and Electronic Auction: The Impact of IT on Market Structures. In: Proceedings of the 29th HICSS, Los Alamitos, CA. Information Systems – Organizational Systems and Technology, vol. IV, pp. 397–406 (1996)Google Scholar
  14. 14.
    Singh, M., Cassaigne, N., Bussey, P.: Bid Price – Calculating the Possibility of WinningGoogle Scholar
  15. 15.
    Wang, M.-T., Wu, T.-S.: A Bidding Model Combined Game Theory and AI ParadigmsGoogle Scholar
  16. 16.
    Myerson, R.B.: Game Theory: Analysis of Conflict. Harvard University Press (1997)Google Scholar
  17. 17.
    Sidnal, N.S., Manvi, S.S.: Bidding in English Auctions using Cognitive Agents in Mobile e-commerce (June 2011)Google Scholar
  18. 18.
    Vragov, R.: Implicit Consumer Collusion in Auctions on the Internet. In: Proceedings of the 38th Hawaii International Conference on System Sciences (2005)Google Scholar
  19. 19.
    Klein, S., O’Keefe, R.M.: The Impact of the Web on Auctions: Some Empirical Evidence and Theoretical Considerations. International Journal of Electronic Commerce 3(3), 7–20 (1999)Google Scholar
  20. 20.
  21. 21.
  22. 22.

Copyright information

© Springer India 2013

Authors and Affiliations

  1. 1.Dept of PG Studies, JnanasangamaVTUBelgaumIndia

Personalised recommendations