Abstract
Sniping agents are increasingly being deployed to assist bidders in acquiring items in online auctions. This paper reviews the extant auction literature and proposes an overarching sniping agent design framework that could potentially increase the commercial viability of snipping agents. For better alignment between the functions of sniping agents and the needs of human bidders, we review existing literature based on three fundamentals: (1) knowledge about human bidder behavior, (2) awareness of the product(s) desired by a bidder, and (3) an understanding of the research on bidding agents and auction design. The output of this review is the explicit consideration of iterative combinatorial auction agent design, fuzzy set representation of the bidder’s preferences and dynamic derivation of bidding strategies according to the progress of ongoing auctions.
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References
Anthony, P., & Jennings, N. R. (2003). Developing a bidding agent for multiple heterogeneous auctions. ACM Transactions on Internet Technology, 3(3), 185–217.
Ariely, D., & Simonson, I. (2003). Buying, bidding, playing, or competing? Value assessment and decision dynamics in online auctions. Journal of Consumer Psychology, 13(1–2), 113–123.
Bajari, P., & Hortacsu, A. (2003). The winner’s curse, reserve prices and endogenous entry: Empirical insights from eBay auctions. RAND Journal of Economics, 33(2), 329–355.
Bapna, R. (2003). When snipers become predators: Can mechanism design save online auctions? Communications of the ACM, 46(12), 152–158.
Bapna, R., Goes, P., & Gupta, A. (2003). Replicating online Yankee auctions to analyze auctioneers’ and bidders’ strategies. Information Systems Research, 14(3), 244–268.
Bapna, R., Jank, W., & Shmueli, G. (2004). Price formation and its dynamics in online auctions (Working paper). Department of Operations and Information Management, University of Maryland. Available online: http://www.rhsmith.umd.edu/ceme/statistics/auctionDynamics.pdf.
de Carvalho, R. A., & Costa, H. G. (2007). Application of an integrated decision support process for supplier selection. Enterprise Information Systems, 1(2), 197–216.
Easley, R. F., & Tenorio, R. (2004). Jump bidding strategies in internet auctions. Management Science, 50(10), 1407–1419.
Greenwald, A. (2003). The 2002 trading agent competition: An overview of agent strategies. AI Magazine, 24(1), 83–91.
Gregg, D. G., & Walczak, S. (2006). Auction advisor: Online auction recommendation and bidding decision support system. Decision Support Systems, 41(2), 449–471.
Gregg, D. G., & Walczak, S. (2003). E-commerce auction agents and online-auction dynamics. Electronic Markets, 13(2), 242–250.
He, M. H., Jennings, N. R., & Prgel-Bennett, A. (2004). An adaptive bidding agent for multiple English auctions: A neuro-fuzzy approach. In: Proceedings of IEEE conference on fuzzy systems, Budapest, Hungary (pp. 1519–1524).
Ito, T., Fukuta, N., Shintani, T., & Sycara, K. (2000). Biddingbot: A multiagent support system for cooperative bidding in multiple auctions. In Proceedings of the 4th international conference on multi-agent systems, Boston, MA (pp. 399–400). Los Alamitos: IEEE Comput. Soc.
Kauffman, R. J., & Wood, C. (2006). Doing their bidding: An empirical examination of factors that affect a buyer’s utility in internet auctions. Information Technology and Management, 7(3), 171–190.
Kwang, M. S., & Wong, E. (2001). Toward market-driven agents for electronic auction. IEEE Transactions on Systems, Man, and Cybernetics, Part A: Systems and Humans, 31(6), 474–484.
Kwon, R. H., Anandalingam, G., & Ungar, L. H. (2005). Iterative combinatorial auctions with bidder-determined combinations. Management Science, 51(3), 407–418.
LeBaron, B. (2000). Agent based computational finance: Suggested readings and early research. Journal of Economic Dynamics and Control, 24(5–7), 679–702.
Liu, Y. X., Goodwin, R., & Koenig, S. (2003). Risk-averse auction agents. In Proceedings of the 2nd international joint conference on autonomous agents and multiagent systems (AAMAS), Melbourne, Australia (pp. 353–360).
Luo, J., Xu, L., Jamont, J.-P., Zeng, L., & Shi, Z. (2007). Flood decision support system on agent grid: Method and implementation. Enterprise Information Systems, 1(1), 49–68.
Lucking-Reiley, D. (2000). Auctions on the internet: What’s being auctioned and how? Journal of Industrial Economics, 48(3), 227–252.
Matsubara, S. (2000). Accelerating information revelation in ascending-bid auctions: Avoiding last minute bidding. In Proceedings of the 3rd ACM conference on electronic commerce, Tampa, Florida, USA (pp. 29–37).
Matsumoto, Y., & Fujita, S. (2001). An auction agent for bidding on combinations of items. In Proceedings of the fifth international conference on autonomous agents, Montreal, Quebec, Canada (pp. 552–559).
Nwana, H. S., Rosenschein, J., Sandholm, T., Sierra, C., Maes, P., & Guttmann, R. (1998). Agent-mediated electronic commerce: Issues, challenges and some viewpoints. In Proceedings of the 2nd international conference on autonomous agents, Minneapolis (pp. 189–196).
Ockenfels, A., & Roth, A. E. (2002). The timing of bids in internet auctions: Market design, bidder behavior, and artificial agents. AI Magazine, 23(3), 79–88.
Ogston, E., & Vassiliadis, S. (2002). A peer-to-peer agent auction. In First international joint conference on autonomous agents and multi-agent systems (AAMAS), Bologna, Italy (pp. 151–159).
Parkes, D. C. (1999). iBundle: An efficient ascending price bundle auction. In Proceedings of the 1st ACM conference on electronic commerce, Denver, Colorado, USA (pp. 148–157).
Pekeč, A., & Rothkopf, M. H. (2003). Combinatorial auction design. Management Science, 49(11), 1485–1503.
Pinker, E. J., Seidmann, A., & Vakrat, Y. (2003). Managing online auctions: Current business and research issues. Management Science, 49(11), 1457–1484.
Rasmusson, L., & Jason, S. (1999). Agents, self-interest and electronic markets. The Knowledge Engineering Review, 14(2), 143–150.
Roth, A. E., & Ockenfels, A. (2002). Last minute bidding and the rules for ending second-price auctions: Theory and evidence from a natural experiment on the internet. American Economic Review, 92, 1093–1103.
Sandholm, T. (1999). Approaches to winner determination in combinatorial auctions. Decision Support Systems, 28(1–2), 165–176.
Sloman, S. A. (1996). The empirical case for two systems of reasoning. Psychological Bulletin, 119, 3–22.
Vakrat, Y., & Seidmann, A. (2000). Implications of the bidders’ arrival process on the design of online auctions. In Proceedings of the 33rd Hawaii international conference on systems science, USA (p. 6015).
Vulkan, N. (1999). Economic implications of agent technology and e-commerce. The Economic Journal, 109(453), F67–F90.
Wilcox, R. T. (2000). Experts and amateurs: The role of experience in internet auctions. Marketing Letters, 11(4), 363–374.
Zhang, Y., & Bhattacharyya, S. (2007). Effective of Q-learning as a tool for calibrating agent-based supply network models. Enterprise Information Systems, 1(2), 217–233.
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Tan, CH., Teo, HH., Xie, E. et al. Designing sniping agents. Ann Oper Res 168, 291–305 (2009). https://doi.org/10.1007/s10479-008-0366-6
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DOI: https://doi.org/10.1007/s10479-008-0366-6