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Competition between auctions

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Abstract

Even though auctions are capturing an increasing share of commerce, they are typically treated in the theoretical economics literature as isolated. That is, an auction is typically treated as a single seller facing multiple buyers or as a single buyer facing multiple sellers. In this paper, we review the state of the art of competition between auctions. We consider three different types of competition: competition between auctions, competition between formats, and competition between auctioneers vying for auction traffic. We highlight the newest experimental, statistical, and analytical methods in the analysis of competition between auctions.

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Notes

  1. Milgrom (2004) contends that the defining event that changed the auction landscape towards consideration of multiple auction events was the rise of FCC spectrum auctions in the 1990s. We devote some space to package auctions in this review, but Internet auctions receive more attention here. These two events took place at precisely the same time—so the historical argument remains.

  2. The factors that led to eBay dominating the electronic auction market in the United States over its much bigger rivals are numerous and complex. They cannot and should not be reduced to the closing rule decision and we do not wish to do so here. Nevertheless, it is clear that every single format decision (and other strategic decisions) made by eBay had to take into consideration the actions of its competitors, and in this case the format choice served to both differentiate eBay and to create a buzz about sniping. We would also like to emphasize that the implied omission of competition does not affect or detract from the results of Roth and Ockenfels. It only sheds a different light on the interpretation of their findings.

  3. Many of these attributes may be difficult to express quantitatively, making it difficult to utilize multi-attribute auction mechanisms.

References

  • Anwar, S., McMillan, R., & Zheng, M. (2006). Bidding behavior at competing auctions: evidence from eBay. European Economic Review, 50(2), 307–322 February.

    Article  Google Scholar 

  • Bajari, P., & Hortaçsu, A. (2004). Economic insights from internet auctions. Journal of Economic Literature, 42, 457–486.

    Article  Google Scholar 

  • Bapna, R., Jank, W., & Shmueli, G. (2006). Price formation and its dynamics in online auctions. Decision Support Systems, 44, 641–656.

    Article  Google Scholar 

  • Bradlow, E. T., & Park, Y.-H. (2007). Bayesian estimation of bid sequences in internet auctions using a generalized record breaking model. Marketing Science, 26(2), 218–229.

    Article  Google Scholar 

  • Carare, O. (2007). Reserve prices in repeated auctions. Mimeo, University of Texas at Dallas.

  • Chan, T. Y., Kadiyali, V., & Park, Y.-H. (2006). The exercise of buy-it-now pricing in auctions: seller revenue implications. Working Paper, Cornell University.

  • Chan, T. Y., Kadiyali, V., & Park, Y.-H. (2007). Willingness to pay and competition in online auctions. Journal of Marketing Research, 44(2), 324–333.

    Article  Google Scholar 

  • Che, Y.-K. (1993). Design competition through multi-dimensional auctions. RAND Journal of Economics, 24(4), 668–680.

    Article  Google Scholar 

  • Chen, X., Makio, J., & Weinhardt C. (2005). Agent-based simulation on competition of e-auction marketplaces, Proceedings of the 2005 International Conference on Computational Intelligence for Modeling Control and Automation (CIMCA 2005), volume 2, pp. 910-915.

  • Cox, J. C., Dinkin, S., & Swarthout, J. T. (2001). Endogenous entry and exit in common value auctions. Experimental Economics, 4(2), 163–181.

    Google Scholar 

  • Cox, J. C., Offerman, T., Olson, M. A., & Schram, A. J. H. C. (2002). Competition for versus on the rails: a laboratory experiment. International Economic Review, 43(3), 709–736.

    Article  Google Scholar 

  • Cramton, P., Shoham, Y., & Steinberg, R. (2006). Introduction to combinatorial auctions. In P. Cramton, Y. Shoham, & R. Steinberg (Eds.), Combinatorial auctions pp. 1–13. Cambridge, MA: MIT.

    Google Scholar 

  • Dogan, K., Haruvy, E., & Li, S. (2007). Social identity in matching markets with price. Working paper, University of Texas at Dallas.

  • Donald, S. G., Paarsch, H. J., & Robert, J. (2006). An empirical model of the multi-unit, sequential, clock auction. Journal of Applied Econometrics, 21, 1221–1247.

    Article  Google Scholar 

  • Ellison, G., Fudenberg, D., & Mobius, M. (2004). Competing auctions. Journal of the European Economic Association, 2(1), 30–66.

    Article  Google Scholar 

  • Engelbrecht-Wiggans, R., Haruvy, E., & Katok, E. (2007). A comparison of buyer-determined and price-based multi-attribute mechanisms. Marketing Science, 26(5), 629–641.

    Article  Google Scholar 

  • Engelbrecht-Wiggans, R., & Katok, E. (2006). e-sourcing in procurement: theory and behavior in reverse auctions with non-competitive contracts. Management Science, 52(4), 581–596.

    Article  Google Scholar 

  • Goeree, J. K., & Holt, C. A. (2007). A simple combinatorial auction. Working paper.

  • Greenleaf, E. A., Ma, J., Qiu, W., Rao, A. G., & Sinha, A. R. (2002). Note on guarantees in auctions: the auction house as negotiator and managerial decision maker. Management Science, 48(12), 1640–1644.

    Article  Google Scholar 

  • Greenleaf, E. A., Rao, A. G., & Sinha, A. R. (1993). Guarantees in auctions: the auction house as negotiator and managerial decision maker. Management Science, 39(9), 1130–1145.

    Google Scholar 

  • Greenleaf, E. A., & Sinha, A. R. (1996). Combining buy-in penalties with commissions at auction houses. Management Science, 42(4), 529–540.

    Google Scholar 

  • Harris, M., & Raviv, A. (1981). Allocation mechanisms and the design of auctions. Econometrica, 49, 1477–1499.

    Article  Google Scholar 

  • Harstad, R. M. (1990). Alternative common-value procedures: revenue comparisons with free entry. Journal of Political Economy, 98, 421–429.

    Article  Google Scholar 

  • Haruvy, E., & Katok, E. (2007). An experimental investigation of buyer determined procurement auctions. Working paper.

  • Haruvy, E., & Popkowski Leszczyc, P. T. L. (2007). Individual choice among charity auctions. Working paper.

  • Haruvy, E., & Popkowski Leszczyc, P. T. L. (2008). When zero search cost is too high: What does it take to make consumers search? Working paper.

  • Haruvy, E., & Unver, U. (2007). Equilibrium selection in repeated B2B matching markets. Economic Letters, 94, 284–289.

    Article  Google Scholar 

  • Hernando-Veciana, Á. (2005). Competition among auctioneers in large markets. Journal of Economic Theory, 121(1), 107–127.

    Article  Google Scholar 

  • Hyde, V., Jank, W., & Shmueli, G. (2006). Investigating concurrency in online auctions through visualization. The American Statistician, 60(3), 241–250.

    Article  Google Scholar 

  • Ivanova-Stenzel, R., & Salmon, T. (2004). Bidder preferences among auction institutions. Economic Inquiry, 42, 223–236.

    Article  Google Scholar 

  • Jank, W., & Shmueli, G. (2006). Functional data analysis in electronic commerce research. Statistical Science, 21(2), 155–166.

    Article  Google Scholar 

  • Jank, W., & Shmueli, G. (2007). Modeling concurrency of events in online auctions via spatio–temporal semiparametric models. Journal of the Royal Statistical Society, Series C, 56(1), 1–27.

    Article  Google Scholar 

  • Jank, W., & Zhang, S. (2007). A comparison of concurrency models for price in online auctions. Working paper, Smith School, University of Maryland.

  • Jap, S. D. (2002). Online, reverse auctions: issues, themes, and prospects for the future. Journal of the Academy of Marketing Science, 30(4), 506–525.

    Article  Google Scholar 

  • Jap, S. D. (2003). An exploratory study of the introduction of online reverse auctions. Journal of Marketing, 67(3), 96–107.

    Article  Google Scholar 

  • Jap, S. D. (2007). The impact of online reverse auction design on buyer–supplier relationships. Journal of Marketing, 71(1), 146–159.

    Article  Google Scholar 

  • Jap, S. D. & Haruvy, E. (2007). Inter-organizational relationships and bidding behavior in industrial online reverse auctions, Working paper.

  • Jap, S. D. & Naik, P. (2007). BidAnalyzer: a method for estimation and selection of dynamic bidding models. Marketing Science (in press).

  • Jofre-Bonet, M., & Pesendorfer, M. (2003). Estimation of a dynamic auction game. Econometrica, 71, 1443–1489.

    Article  Google Scholar 

  • Katkar, R., & Reiley, D. H. (2006). Public versus secret reserve prices in eBay auctions: results from a pokémon field experiment. Advances in Economic Analysis and Policy, 6(2), Article 7.

  • Klemperer, P. (2004). Auctions: theory and practice. Princeton: Princeton University Press.

    Google Scholar 

  • Levin, D., & Smith, J. L. (1994). Equilibrium in auctions with entry. American Economic Review, 84(3), 585–599.

    Google Scholar 

  • Lin, M., & Jank, W. (2007). Bidder migration in online auctions. In Proceedings of the third symposium on statistical challenges in eCommerce Research (SCECR 07), May 19–20, University of Connecticut.

  • Maskin, E., & Riley, J. (1984). Optimal auctions with risk averse buyers. Econometrica, 52, 1473–1518.

    Article  Google Scholar 

  • Matthews, T., & Katzman, B. (2006). The role of varying risk attitudes in an auction with a buyout option. Economic Theory, 27(3), 597–613.

    Article  Google Scholar 

  • McAfee, R. P. (1993). Mechanism design by competing sellers. Econometrica, 61, 1281–1312.

    Article  Google Scholar 

  • McAfee, R. P., & Vincent, D. (1997). Sequentially optimal auctions. Games and Economic Behavior, 18(2), 246–276.

    Article  Google Scholar 

  • Milgrom, P. (2004). Putting auction theory to work. Cambridge: Cambridge University Press.

    Google Scholar 

  • Milgrom, P. (2007). Comment on market design, Stony Brook Conference, July 15, Stony Brook.

  • Milgrom, P., & Weber, R. (1982). A theory of auctions and competitive bidding. Econometrica, 50, 1089–1122.

    Article  Google Scholar 

  • Millet, I., Parente, D. H., Fizel, J. L., & Venkataraman, R. R. (2004). Metrics for managing online procurement auctions. Interfaces, 34(3), 171–179.

    Article  Google Scholar 

  • Morwitz, V. G., Greenleaf, E. A., & Johnson, E. J. (1998). Divide and prosper: consumers’ reactions to partitioned prices. Journal of Marketing Research, 35(4), 453–463.

    Article  Google Scholar 

  • Overby, E. M., & Jap, S. D. (2007). Electronic vs. physical market mechanisms: evaluating multiple theories in the wholesale automotive market. Working paper.

  • Park, Y.-H., & Bradlow, E. T. (2005). An integrated model for bidding behavior in internet auctions: whether, who, when, and how much. Journal of Marketing Research, 42(4), 470–482.

    Article  Google Scholar 

  • Pekec, A., & Rothkopf, M. H. (2003). Combinatorial auction design. Management Science, 49(11), 1485–1503.

    Article  Google Scholar 

  • Pekec, A., & Rothkopf, M. H. (2004). Noncomputational approaches to mitigating computational problems in combinatorial auctions. In P. Cramton, Y. Shoham, & R. Steinberg (Eds.), Combinatorial auctions. Cambridge, MA: MIT.

    Google Scholar 

  • Peters, M. A. (1997). Competitive distribution of auctions. Review Economic Studies, 64, 97–123.

    Article  Google Scholar 

  • Popkowski Leszczyc, P. T. L., Pracejus, J. W., & Shen, M. (2008). Why more can be less: an inference-based explanation for hyper-subadditivity in product bundles. Organizational Behavior and Human Decision Processes, 105(2), 233–246.

    Article  Google Scholar 

  • Popkowski Leszczyc, P. T. L., Qiu, C., & He, Y. (2007). Empirical testing of the reference price effect of buy-now prices in internet auctions. SSRN working paper Nr. 689121.

  • Popkowski Leszczyc, P. T. L., & Rothkopf, M. H. (2007). Charitable intent and bidding in charity auctions. SSRN working paper nr. 899296.

  • Rangan, V. K. (1998). Freemarkets online pp. 1–20. Boston, MA: Harvard Business School Case #598109.

    Google Scholar 

  • Reynolds, S., & Wooders, J. (2007). Auctions with a buy price. Economic Theory (in press).

  • Riley, J., & Samuelson, W. (1981). Optimal auctions. American Economic Review, 71, 381–392.

    Google Scholar 

  • Roth, A. E., & Ockenfels, A. (2002). Last-minute bidding and the rules for ending second-price auctions: evidence from eBay and Amazon auctions on the internet. American Economic Review, 92(4), 1093–1103 September.

    Article  Google Scholar 

  • Rothkopf, M. H., & Harstad, R. M. (1994). On the role of discrete bid levels in oral auctions. European Journal of Operations Research, 74, 572–581.

    Article  Google Scholar 

  • Rothkopf, M. H., Pekec, A., & Harstad, R. M. (1998). Computationally manageable combinational auctions. Management Science, 44(8), 1131–1147.

    Article  Google Scholar 

  • Sinha, A. R., & Greenleaf, E. A. (2000). The impact of discrete bidding and bidder aggressiveness on sellers’ strategies in open English auctions: reserves and covert shilling. Marketing Science, 19(Summer), 244–265.

    Article  Google Scholar 

  • Sinha, A., & Greenleaf, E. A. (2001). Valuing and Attracting Auction Bidders as Customers: Traditional Auctions and the Internet, working paper.

  • Sun, E. (2005). The effects of auctions parameters on price dispersion and bidder entry on eBay: a conditional logit analysis. Working paper, Stanford University.

  • Wang, R. (1993). Auctions versus posted-price selling. The American Economic Review, 83(4), 838–851.

    Google Scholar 

  • Wang, S., Jank, W., Shmueli, G., & Smith, P. (2006). Modeling price dynamics in eBay auctions using principal differential analysis. Journal of the American Statistical Association (in press).

  • Wang, S., Jank, W., & Shmueli, G. (2008). Explaining and forecasting online auction prices and their dynamics using functional data analysis. Journal of Business and Economic Statistics, 26(2), 144–160.

    Article  Google Scholar 

  • Wilcox, R. (2000). Experts and amateurs: the role of experience in internet auctions. Marketing Letters, 11(4), 363–374.

    Article  Google Scholar 

  • Xie, J., Elrod, T., & Popkowski Leszczyc, P. (2007). The influence of competition on the effectiveness of seller strategy in online auctions. Mimeo.

  • Yao, S., & Mela, C. F. (2007). Online auction demand. Mimeo.

  • Zeithammer, R. (2006). Forward-looking bidding in internet auctions. Journal of Marketing Research, 43(3), 462–476.

    Article  Google Scholar 

  • Zeng, D., Cox, J. C., & Dror, M. (2007). Coordination of purchasing and bidding activities across posted offer and auction markets. Journal of Information Systems and e-Business Management, 5, 25–46.

    Article  Google Scholar 

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Acknowledgement

Sadly, after the completion of this paper, our friend and co-author Michael Rothkopf suddenly passed away. Mike was a great scholar and one of the big experts in the areas of auctions. It has been a privilege to have Mike participate in this choice symposium and to co-author with him on this paper. We will miss his love and passion for research.

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Correspondence to Peter T. L. Popkowski Leszczyc.

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This paper is based on the special session at the 7th Triennial Invitational Choice Symposium, at the Wharton School of Business, University of Pennsylvania, June 2007 (co-chaired by the first two authors).

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Haruvy, E., Popkowski Leszczyc, P.T.L., Carare, O. et al. Competition between auctions. Mark Lett 19, 431–448 (2008). https://doi.org/10.1007/s11002-008-9037-2

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