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Customized Bundle Pricing for Information Goods: A Nonlinear Mixed-Integer Programming Approach

Listed author(s):
  • Shin-yi Wu

    ()

    (Nanyang Business School, Nanyang Technological University, Singapore 639798, Singapore)

  • Lorin M. Hitt

    ()

    (The Wharton School, University of Pennsylvania, Philadelphia, Pennsylvania 19104)

  • Pei-yu Chen

    ()

    (Tepper School of Business, Carnegie Mellon University, Pittsburgh, Pennsylvania 15213)

  • G. Anandalingam

    ()

    (Robert H. Smith School of Business, University of Maryland, College Park, Maryland 20742)

Registered author(s):

    This paper proposes using nonlinear mixed-integer programming to solve the customized bundle-pricing problem in which consumers are allowed to choose up to N goods out of a larger pool of J goods. Prior work has suggested that this mechanism has attractive features for the pricing of information and other low-marginal cost goods. Although closed-form solutions exist for this problem for certain cases of consumer preferences, many interesting scenarios cannot be easily handled without a numerical solution procedure. In this paper, we investigate the efficiency gains created by customized bundling over the alternatives of pure bundling or individual sale under different assumptions about customer preferences and firm cost structure, as well as the potential loss of efficiency caused by pricing with incomplete information about consumer reservation values. Our analysis suggests that customized bundling enhances sellers' profits and enhances welfare when consumers do not place positive values on all goods, and that this consumer characteristic is much more important than the shape of the valuation distribution in determining the optimal pricing scheme. We also find that customized bundling outperforms both pure bundling and individual sale in the presence of incomplete information, and that customized bundling still outperforms other simpler pricing schemes even when exact consumer valuations are not known ex ante.

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    File URL: http://dx.doi.org/10.1287/mnsc.1070.0812
    Download Restriction: no

    Article provided by INFORMS in its journal Management Science.

    Volume (Year): 54 (2008)
    Issue (Month): 3 (March)
    Pages: 608-622

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    Handle: RePEc:inm:ormnsc:v:54:y:2008:i:3:p:608-622
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    1. Jeffrey K. MacKie-Mason & Juan F. Riveros & Robert S. Gazzale, "undated". "Pricing and Bundling Electronic Information Goods: Field Evidence," Department of Economics Working Papers 2000-01, Department of Economics, Williams College.
    2. Schmalensee, Richard, 1984. "Gaussian Demand and Commodity Bundling," The Journal of Business, University of Chicago Press, vol. 57(1), pages 211-230, January.
    3. R. Venkatesh & Wagner Kamakura, 2003. "Optimal Bundling and Pricing under a Monopoly: Contrasting Complements and Substitutes from Independently Valued Products," The Journal of Business, University of Chicago Press, vol. 76(2), pages 211-232, April.
    4. Marshall L. Fisher, 1981. "The Lagrangian Relaxation Method for Solving Integer Programming Problems," Management Science, INFORMS, vol. 27(1), pages 1-18, January.
    5. David S. Sibley & Padmanabhan Srinagesh, 1997. "Multiproduct Nonlinear Pricing with Multiple Taste Characteristics," RAND Journal of Economics, The RAND Corporation, vol. 28(4), pages 684-707, Winter.
    6. R. Preston McAfee & John McMillan & Michael D. Whinston, 1989. "Multiproduct Monopoly, Commodity Bundling, and Correlation of Values," The Quarterly Journal of Economics, Oxford University Press, vol. 104(2), pages 371-383.
    7. Chuang, John Chung-I & Sirbu, Marvin A., 1999. "Optimal bundling strategy for digital information goods: network delivery of articles and subscriptions," Information Economics and Policy, Elsevier, vol. 11(2), pages 147-176, July.
    8. Salinger, Michael A, 1995. "A Graphical Analysis of Bundling," The Journal of Business, University of Chicago Press, vol. 68(1), pages 85-98, January.
    9. A. Michael Spence, 1980. "Multi-Product Quantity-Dependent Prices and Profitability Constraints," Review of Economic Studies, Oxford University Press, vol. 47(5), pages 821-841.
    10. Kamel Jedidi & Sharan Jagpal & Puneet Manchanda, 2003. "Measuring Heterogeneous Reservation Prices for Product Bundles," Marketing Science, INFORMS, vol. 22(1), pages 107-130, July.
    11. Lorin M. Hitt & Pei-yu Chen, 2005. "Bundling with Customer Self-Selection: A Simple Approach to Bundling Low-Marginal-Cost Goods," Management Science, INFORMS, vol. 51(10), pages 1481-1493, October.
    12. Shugan, Steven M, 1980. " The Cost of Thinking," Journal of Consumer Research, Oxford University Press, vol. 7(2), pages 99-111, Se.
    13. Yannis Bakos & Erik Brynjolfsson, 1999. "Bundling Information Goods: Pricing, Profits, and Efficiency," Management Science, INFORMS, vol. 45(12), pages 1613-1630, December.
    14. William James Adams & Janet L. Yellen, 1976. "Commodity Bundling and the Burden of Monopoly," The Quarterly Journal of Economics, Oxford University Press, vol. 90(3), pages 475-498.
    15. McAfee, R. Preston & McMillan, John, 1988. "Multidimensional incentive compatibility and mechanism design," Journal of Economic Theory, Elsevier, vol. 46(2), pages 335-354, December.
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