Journal of the Operational Research Society

, Volume 57, Issue 9, pp 1126–1133 | Cite as

A decision approach to competitive electronic sealed-bid auctions for land

Theoretical Paper


Electronic markets for land are innovative techniques potentially advantageous to buyers and private sellers, the latter being interested in sealed-bid auctions assuring high levels of competition among many bidders so that coalitions and cooperative games are ruled out. Land electronic tendering requires sufficient online information for bidders such as valuation reports by prestigious surveyors. To help the bidder make his best choice, we propose a decision model for moderately pessimistic players facing tenders where competition among a great number of independent antagonists excludes the use of cooperative games and involves strict uncertainty. A worked example concerning farmland in Spain is presented.


bidding decision analysis investment online sales 


  1. Athey S and Haile PA (2002). Identification of standard auction models. Econometrica 70: 2107–2140.CrossRefGoogle Scholar
  2. Bajari P (1997a). Econometric of sealed bid auctions. Working Paper, Department of Economics, Harvard University.Google Scholar
  3. Bajari P (1997b). The first price auction with asymmetric bidders: Theory and applications. PhD thesis, University of Minnesota.Google Scholar
  4. Ballestero E (2002). Strict uncertainty: a criterion for moderately pessimistic decision makers. Decision Sci 33 (1): 87–107.CrossRefGoogle Scholar
  5. Battigalli P and Siniscalchi M (2000). Rationalizable bidding in general first price auctions. Working Paper, Universita Bocconi.Google Scholar
  6. Bielza C, Gómez M, Ríos-Insua S and Fernández del Pozo JA (2000). Structural, elicitation and computational issues faced when solving complex decision making problems with influence diagrams. Comp Opns Res 27: 725–740.CrossRefGoogle Scholar
  7. Bielza C, Müller P and Ríos Insua D (1999). Decision analysis by augmented probability simulation. Mngt Sci 45: 995–1007.CrossRefGoogle Scholar
  8. Blackwell D and Girshick MA (1954). Theory of Games and Statistical Decisions. Wiley: New York.Google Scholar
  9. Cadman D and Topping R (2001). Property Development. Spon Press: London.Google Scholar
  10. Clemen R and Reilly T (1999). Correlations and copulas for decision and risk analysis. Mngt Sci 45 (2): 208–224.CrossRefGoogle Scholar
  11. Cova B, Salle R and Vincent R (2000). To bid or not to bid: screening the Whorcop project. Eur Mngt J 18 (5): 551–560.Google Scholar
  12. French S (1988). Decision Theory: An Introduction to the Mathematics of Rationality. John Wiley: New York.Google Scholar
  13. Guler K (2002). Equilibrium in copula models. Technical Report 2002–357. Hewlett-Packard Laboratories, Palo Alto, CA.Google Scholar
  14. Guler K and Zhang B (2002). Bidding by empirical Bayesians in sealed bid first price auctions. Technical Report 2002–212, Hewlett-Packard Laboratories, Palo Alto, CA.Google Scholar
  15. Klemperer P (1999). Auction Theory: a Guide to the Literature. J Econ Surv 13 (3): 227–286.CrossRefGoogle Scholar
  16. Krishna V (2002). Auction Theory. Academic Press: San Diego.Google Scholar
  17. Laffont J (1997). Game theory and empirical economics: the case of auction data. Eur Econ Rev 41: 1–35.CrossRefGoogle Scholar
  18. Laffont J and Vuong Q (1996). Structural analysis of auction data. Am Econ Rev 86: 414–420.Google Scholar
  19. LeBrun B (1996). Existence of an equilibrium in first price auctions. Econ Theory 7: 421–430.CrossRefGoogle Scholar
  20. Luce RD and Raiffa H (1957). Games and Decisions. Wiley: New York.Google Scholar
  21. Maskin E and Riley J (1996). Uniqueness in sealed high bid auctions. Technical Report, Harvard and UCLA.Google Scholar
  22. McKelvey R and Palfrey T (1995). Quantal response equilibria for normal form games. Game Econ Behav 10: 6–38.CrossRefGoogle Scholar
  23. Milgrom PR and Weber RJ (1982). A theory of auctions and competitive bidding. Econometrica 50: 1089–1122.CrossRefGoogle Scholar
  24. Milgrom PR and Weber RJ (1985). Distributional strategies for games with incomplete information. Maths Opns Res 10: 619–632.CrossRefGoogle Scholar
  25. Paarsch HJ (1992). Deciding between the common and private value paradigms in empirical models of auctions. J Econometrics 51: 192–215.CrossRefGoogle Scholar
  26. Palomo J (2003). Bayesian methods in bidding processes. PhD thesis, Rey Juan Carlos University, Spain.Google Scholar
  27. Perrigne I and Vuong Q (1999). Structural econometrics of first-price auctions: a survey of methods. Can J Agric Econ 47: 203–223.CrossRefGoogle Scholar
  28. Porter R and Shoham Y (2005). On cheating in sealed-bid auctions. Dec Sup Syst 39: 41–54.CrossRefGoogle Scholar
  29. Rapoport A, Erev I and Zwick R (1995). An experimental study of buyer-seller negotiation with one-sided incomplete information and time discounting. Mngt Sci 41 (3): 377–394.CrossRefGoogle Scholar
  30. Reed R, Robinson J and Williams P (2002). Does an auction represent fair market value? Proceedings of the Queensland Property Conference, Brisbane, 12 June 2002.Google Scholar
  31. Schneller GO and Spicas GP (1983). Decision making under uncertainty: Starr's domain criterion. Theory Dec 15: 321–336.CrossRefGoogle Scholar

Copyright information

© Palgrave Macmillan Ltd 2005

Authors and Affiliations

  1. 1.Technical University of Valencia (Alcoy School)Spain
  2. 2.Technical University of MadridMadridSpain

Personalised recommendations