Advertisement

Competitive bidding for health insurance contracts: lessons from the online HMO auctions

  • Alok Gupta
  • Stephen T. Parente
  • Pallab Sanyal
Article

Abstract

Healthcare is an important social and economic component of modern society, and the effective use of information technology in this industry is critical to its success. As health insurance premiums continue to rise, competitive bidding may be useful in generating stronger price competition and lower premium costs for employers and possibly, government agencies. In this paper, we assess an endeavor by several Fortune 500 companies to reduce healthcare procurement costs for their employees by having HMOs compete in open electronic auctions. Although the auctions were successful in generating significant cost savings for the companies in the first year, i.e., 1999, they failed to replicate the success and were eventually discontinued after two more years. Over the past decade since the failed auction experiment, effective utilization of information technologies have led to significant advances in the design of complex electronic markets. Using this knowledge, and data from the auctions, we point out several shortcomings of the auction design that, we believe, led to the discontinuation of the market after three years. Based on our analysis, we propose several actionable recommendations that policy makers can use to design a sustainable electronic market for procuring health insurance.

Keywords

Electronic market design Auctions Health insurance procurement HMO 

JEL Classification

I1 D44 G22 

References

  1. Adomavicius, G., Curley, S. P., Gupta, A., & Sanyal, P. (2012a). Effect of information feedback on bidder behavior in continuous combinatorial auctions. Management Science (forthcoming).Google Scholar
  2. Adomavicius, G., Gupta, A., & Sanyal, P. (2012b). Effect of information feedback on the outcomes and dynamics of multisourcing multiattribute procurement auctions. Journal of Management Information Systems (forthcoming).Google Scholar
  3. Arora, A., Greenwald, A., Kannan, K., & Krishnan, R. (2007). Effects of information–revelation policies under market-structure uncertainty. Management Science, 53(8), 1234–1248.CrossRefGoogle Scholar
  4. Athey, S., & Levin, J. (2001). Information and competition in US Forest Service timber auctions. Journal of Political Economy, 109(2), 375–417.CrossRefGoogle Scholar
  5. Bajari, P., & Summers, G. (2002). Detecting collusion in procurement auctions. Antitrust Law Journal, 70(1), 143–170.Google Scholar
  6. Bajari, P., & Ye, L. (2003). Deciding between competition and collusion. The Review of Economics and Statistics, 85(4), 971–989.CrossRefGoogle Scholar
  7. Baldwin, L. H., Marshall, R. C., & Richard, J. (1997). Collusion at forest service timber sales. The Journal of Political Economy, 105(4), 657–699.CrossRefGoogle Scholar
  8. Bapna, R., Das, S., Garfinkel, R., & Stallert, J. (2008). A market design for grid computing. INFORMS Journal on Computing, 20(1), 100–111.CrossRefGoogle Scholar
  9. Bapna, R., Goes, P., & Gupta, A. (2003a). Analysis and design of business-to-consumer online auctions. Management Science, 49(1), 85–101.CrossRefGoogle Scholar
  10. Bapna, R., Goes, P., & Gupta, A. (2003b). Replicating online yankee auctions to analyze auctioneers’ and bidders’ strategies. Information Systems Research, 14(3), 244–268.CrossRefGoogle Scholar
  11. Bichler, M. (2000). An experimental analysis of multi-attribute auctions. Decision Support Systems, 29(3), 249–268.CrossRefGoogle Scholar
  12. Brown, J., & Morgan, J. (2009). How much is a dollar worth? Tipping versus equilibrium coexistence on competing online auction sites. Journal of Political Economy, 117(4), 668–700.CrossRefGoogle Scholar
  13. Carbone, J. (2003, December 11). Debate rages over use of e-auctions for components. Purchasing Magazine Online.Google Scholar
  14. Carter, C. R., Kauffman, L., Beall, S., Carter, P. L., Hendrick, T. E., & Peterson, K. J. (2004). Reverse auctions–grounded theory from the buyer and supplier perspective. Transportation Research, 40, 229–254.CrossRefGoogle Scholar
  15. Carter, C. R., & Stevens, C. K. (2007). Electronic reverse auction configuration and its impact on buyer price and supplier perceptions of opportunism: A laboratory experiment. Journal of Operations Management, 25, 1035–1054.CrossRefGoogle Scholar
  16. Che, Y. K. (1993). Design competition through multidimensional auctions. The RAND Journal of Economics, 24(4), 668–680.CrossRefGoogle Scholar
  17. Chen-Ritzo, C. H., Harrison, T. P., Kwasnica, A. M., & Thomas, D. J. (2005). Better, faster, cheaper: An experimental analysis of a multi-attribute reverse auction mechanism with restricted information feedback. Management Science, 51(12), 1753–1762.CrossRefGoogle Scholar
  18. Cramton, P. (1998). Ascending auctions. European Economic Review, 42(3–5), 745–756.CrossRefGoogle Scholar
  19. Cramton, P., & Katzman B. E. (2008). Reducing healthcare costs requires good market design. The Economists’ Voice, 1–4.Google Scholar
  20. Dellarocas, C., & Wood, C. A. (2008). The sound of silence in online feedback: Estimating trading risks in the presence of reporting bias. Management Science, 54(3), 460–476.CrossRefGoogle Scholar
  21. Easley, R. F., & Tenerio, R. (2004). Jump bidding strategies in internet auctions. Management Science, 50(10), 1407–1419.CrossRefGoogle Scholar
  22. Easley, R. F., Wood, C. A., & Barkataki, S. (2010–11). Bidding patterns, experience, and avoiding the winner’s curse in online auctions. Journal of Management Information Systems, 27(3), 241–268.Google Scholar
  23. Elmaghraby, W. J. (2007). Auctions within e-sourcing events. Production Operations Management, 16(4), 409–422.CrossRefGoogle Scholar
  24. Elmaghraby, W. J., Katok, E., & Santamaria, N. (2012). A laboratory investigation of rank feedback in procurement auctions. Working paper. University Park, PA: Penn State University.Google Scholar
  25. 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.CrossRefGoogle Scholar
  26. Engelbrecht-Wiggans, R., & Katok, E. (2006). E-sourcing in procurement: Theory and behavior in reverse auctions with noncompetitive contracts. Management Science, 52(4), 581–596.CrossRefGoogle Scholar
  27. Graham, D., & Marshall, R. (1987). Collusive bidder behavior at single-object second-price and english auctions. Journal of Political Economy, 95, 1217–1239.CrossRefGoogle Scholar
  28. Greenwald, A., Kannan, K., & Krishnan, R. (2010). On evaluating information revelation policies in procurement auctions: A Markov decision process approach. Information Systems Research, 21(1), 15–36.CrossRefGoogle Scholar
  29. Haruvy, E., & Katok, E. (2012). An experimental investigation of buyer determined procurement auctions. Working paper. University Park, PA: Penn State University.Google Scholar
  30. Haruvy, E., Leszczyc, P. T. L. P., Carare, O., Cox, J. C., Greenleaf, E. A., Jap, S. D., et al. (2008). Competition between auctions. Marketing Letters, 19(5), 431–448.CrossRefGoogle Scholar
  31. Herbsman, Z. J., Chen, W. T., & Epstein, W. C. (1995). Time is money: Innovative contracting methods in highway construction. Journal of Construction Engineering Management, 121(3), 273–281.CrossRefGoogle Scholar
  32. Hossain, T., & Morgan, J. (2006). Plus shipping and handling: Revenue (non) equivalence in field experiments on eBay. Advances in Economic Analysis & Policy, 6(2), 1–26.Google Scholar
  33. 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.CrossRefGoogle Scholar
  34. Jap, S. D. (2003). An exploratory study of the introduction of online reverse auctions. Journal of Marketing, 67(3), 96–107.CrossRefGoogle Scholar
  35. Jap, S. D. (2007). The impact of online reverse auction design on buyer–supplier relationships. Journal of Marketing, 71(1), 146–159.CrossRefGoogle Scholar
  36. Katok, E., & Wambach, A. (2012). Collusion in dynamic buyer-determined reverse auctions. Working paper. University Park, PA: Penn State University.Google Scholar
  37. Katzman, B., & McGeary, K. A. (2008). Will competitive bidding decrease medicare prices? Southern Economics Journal, 74(3), 839–856.Google Scholar
  38. Klemperer, P. (1999). Auction theory: A guide to the literature. Journal of Economic Surveys, 13(3), 227–286.CrossRefGoogle Scholar
  39. Koppius, O. R., & van Heck, E. (2003). Information architecture and electronic market performance in multidimensional auctions. Working paper. Rotterdam, The Netherlands: Erasmus University.Google Scholar
  40. Kwasnica, A., & Katok, E. (2007). The effect of timing on bid increments in ascending auctions. Production and Operations Management, 16(4), 483–494.CrossRefGoogle Scholar
  41. Lucking-Reiley, D. (2000). Auctions on the internet: What’s being auctioned, and how? The Journal of Industrial Economics, 48(3), 227–252.Google Scholar
  42. Maxwell, J., & Temin, P. (2002). Managed competition versus industrial purchasing of health care among the Fortune 500. Journal of Health Politics, Policy and Law, 27(1), 5–30.PubMedCrossRefGoogle Scholar
  43. Maxwell, J., Temin, P., & Watts, C. (2001). Corporate health care purchasing among Fortune 500 firms. Health Affairs (Project Hope), 20(3), 181–188.CrossRefGoogle Scholar
  44. Mayhew-Smith, A. (2004). Under the hammer. Electronics Weekly, (2138), 26.Google Scholar
  45. Milgrom, P. (2008). Putting auction theory to work. New York: Cambridge University Press.Google Scholar
  46. Milgrom, P. R., & Weber, R. J. (1982). A theory of auctions and competitive bidding. Econometrica, 50, 1089–1122.CrossRefGoogle Scholar
  47. Millet, I., Parente, D. H., Fizel, J. L., & Venkatraman, R. R. (2004). Metrics for managing online procurement auctions. Interfaces, 34(3), 171–179.CrossRefGoogle Scholar
  48. Mithas, S., & Jones, J. L. (2007). Do auction parameters affect buyer surplus in e-auctions for procurement? Production and Operations Management, 16(4), 455–470.CrossRefGoogle Scholar
  49. Narasimhan, R., Talluri, S., & Mahapatra, S. K. (2008). Effective response to RFQs and supplier development: A supplier’s perspective. International Journal of Production Economics, 115(2), 461–470.CrossRefGoogle Scholar
  50. Pesendorfer, M. (2000). A study of collusion in first-price auctions. The Review of Economic Studies, 67(3), 381–411.CrossRefGoogle Scholar
  51. Porter, R. H., & Zona, J. D. (1993). Detection of bid rigging in procurement auctions. Journal of Political Economy, 101(3), 518–538.CrossRefGoogle Scholar
  52. Rice, S. (2012). Reputation and uncertainty in on-line markets: An experimental study. Information Systems Research, 23(4), 436–452.Google Scholar
  53. 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.CrossRefGoogle Scholar
  54. Rothkopf, M. H., & Harstad, R. M. (1994). Modeling competitive bidding: A critical essay. Management Science, 40(3), 364–384.CrossRefGoogle Scholar
  55. Shugan, S. M. (2005). Marketing and designing transaction games. Marketing Science, 24(4), 525–530.CrossRefGoogle Scholar
  56. Strecker, S. (2010). Information revelation in multi-attribute english auctions: A laboratory study. Decision Support Systems, 49(3), 272–280.CrossRefGoogle Scholar
  57. Tunca, T. I., & Wu, Q. (2009). Multiple sourcing and procurement process selection with bidding events. Management Science, 55(5), 763–780.CrossRefGoogle Scholar
  58. Wilson, R. (2002). The architecture of power markets. Econometrica, 70(4), 1299–1340.CrossRefGoogle Scholar
  59. Wolfstetter, E. (1996). Auctions: An introduction. Journal of Economic Surveys, 10(4), 367–420.Google Scholar

Copyright information

© Springer Science+Business Media New York 2012

Authors and Affiliations

  • Alok Gupta
    • 1
  • Stephen T. Parente
    • 2
  • Pallab Sanyal
    • 3
  1. 1.Department of Information and Decision SciencesCarlson School of Management, University of Minnesota MinneapolisUSA
  2. 2.Department of FinanceCarlson School of Management, University of MinnesotaMinneapolisUSA
  3. 3.Department of Information Systems and Operations Management, School of Management George Mason UniversityFairfaxUSA

Personalised recommendations