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Model for Studying Commodity Bundling with a Focus on Consumer Preference

  • Jungwoo Shin
  • Chang Seob Kimi
  • Jongsu Lee

    ()

    (Technology Management, Economics and Policy Program(TEMEP), Seoul National University)

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    This research complements demand side analysis of previous commodity bundling studies in which oligopoly models and game theory were used. According to demand side analysis, this study proposes the use of discrete-continuous consumption behavior applied to a commodity bundling model that incorporates consumer heterogeneity to analyze the effect of bundling strategies. Previous researchers have assumed a simple consumer utility model such that the heterogeneity of consumer preference is not reflected. Most analyzed effects of commodity bundling by focusing on firm behavior. However, to measure the results of the competition of bundling strategy, analysis of commodity bundling that is based on consumer preference is useful. Unlike previous research, this study proposes a model that directly analyzes consumer behavior for commodity bundling. This study conducted empirical analysis, obtained from data on information communication technology (hereafter, ICT) service subscription and usage in Korea, to validate the proposed model. The empirical results show that the proposed model is useful to analyze the effects of bundling for various services and products.

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    File URL: ftp://147.46.237.98/DP-34.pdf
    File Function: First version, 2009
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    Paper provided by Seoul National University; Technology Management, Economics, and Policy Program (TEMEP) in its series TEMEP Discussion Papers with number 200934.

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    Length: 21 pages
    Date of creation: Nov 2009
    Date of revision: Nov 2009
    Handle: RePEc:snv:dp2009:200934
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    1. Joel Huber & Kenneth Train, 2001. "On the Similarity of Classical and Bayesian Estimates of Individual Mean Partworths," Econometrics 0012003, EconWPA.
    2. Choi, Jay Pil, 2003. "Bundling new products with old to signal quality, with application to the sequencing of new products," International Journal of Industrial Organization, Elsevier, vol. 21(8), pages 1179-1200, October.
    3. Kenneth Train, 2003. "Discrete Choice Methods with Simulation," Online economics textbooks, SUNY-Oswego, Department of Economics, number emetr2, September.
    4. Bhat, Chandra R. & Sen, Sudeshna, 2006. "Household vehicle type holdings and usage: an application of the multiple discrete-continuous extreme value (MDCEV) model," Transportation Research Part B: Methodological, Elsevier, vol. 40(1), pages 35-53, January.
    5. Peitz, Martin, 2008. "Bundling may blockade entry," International Journal of Industrial Organization, Elsevier, vol. 26(1), pages 41-58, January.
    6. Allenby, Greg M. & Rossi, Peter E., 1998. "Marketing models of consumer heterogeneity," Journal of Econometrics, Elsevier, vol. 89(1-2), pages 57-78, November.
    7. Spector, David, 2007. "Bundling, tying, and collusion," International Journal of Industrial Organization, Elsevier, vol. 25(3), pages 575-581, June.
    8. Greenlee, Patrick & Reitman, David & Sibley, David S., 2008. "An antitrust analysis of bundled loyalty discounts," International Journal of Industrial Organization, Elsevier, vol. 26(5), pages 1132-1152, September.
    9. Adams, William James & Yellen, Janet L, 1976. "Commodity Bundling and the Burden of Monopoly," The Quarterly Journal of Economics, MIT Press, vol. 90(3), pages 475-98, August.
    10. Jaehwan Kim & Greg M. Allenby & Peter E. Rossi, 2002. "Modeling Consumer Demand for Variety," Marketing Science, INFORMS, vol. 21(3), pages 229-250, December.
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