Model for Studying Commodity Bundling with a Focus on Consumer Preference
AbstractThis 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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Bibliographic InfoPaper provided by Seoul National University; Technology Management, Economics, and Policy Program (TEMEP) in its series TEMEP Discussion Papers with number 200934.
Length: 21 pages
Date of creation: Nov 2009
Date of revision: Nov 2009
Bayesian estimation; Commodity bundling; Consumer heterogeneity; Game theory; Mixed multiple discrete-continuous extreme value model; Oligopoly model;
Find related papers by JEL classification:
- C11 - Mathematical and Quantitative Methods - - Econometric and Statistical Methods and Methodology: General - - - Bayesian Analysis: General
- C35 - Mathematical and Quantitative Methods - - Multiple or Simultaneous Equation Models; Multiple Variables - - - Discrete Regression and Qualitative Choice Models; Discrete Regressors; Proportions
- D11 - Microeconomics - - Household Behavior - - - Consumer Economics: Theory
- D12 - Microeconomics - - Household Behavior - - - Consumer Economics: Empirical Analysis
- L40 - Industrial Organization - - Antitrust Issues and Policies - - - General
This paper has been announced in the following NEP Reports:
- NEP-ALL-2010-01-10 (All new papers)
- NEP-COM-2010-01-10 (Industrial Competition)
- NEP-MKT-2010-01-10 (Marketing)
Please report citation or reference errors to , or , if you are the registered author of the cited work, log in to your RePEc Author Service profile, click on "citations" and make appropriate adjustments.:
- Spector, David, 2007.
"Bundling, tying, and collusion,"
International Journal of Industrial Organization,
Elsevier, vol. 25(3), pages 575-581, June.
- Peitz, Martin, 2008. "Bundling may blockade entry," International Journal of Industrial Organization, Elsevier, vol. 26(1), pages 41-58, January.
- Joel Huber and Kenneth Train., 2000.
"On the Similarity of Classical and Bayesian Estimates of Individual Mean Partworths,"
Economics Working Papers
E00-289, University of California at Berkeley.
- Joel Huber & Kenneth Train, 2001. "On the Similarity of Classical and Bayesian Estimates of Individual Mean Partworths," Econometrics 0012003, EconWPA.
- Huber, Joel & Train, Kenneth, 2000. "On the Similarity of Classical and Bayesian Estimates of Individual Mean Partworths," Department of Economics, Working Paper Series qt7zm4f51b, Department of Economics, Institute for Business and Economic Research, UC Berkeley.
- Allenby, Greg M. & Rossi, Peter E., 1998. "Marketing models of consumer heterogeneity," Journal of Econometrics, Elsevier, vol. 89(1-2), pages 57-78, November.
- 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.
- 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.
- Train,Kenneth E., 2009.
"Discrete Choice Methods with Simulation,"
Cambridge University Press, number 9780521766555, April.
- 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.
- 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.
- Jaehwan Kim & Greg M. Allenby & Peter E. Rossi, 2002. "Modeling Consumer Demand for Variety," Marketing Science, INFORMS, vol. 21(3), pages 229-250, December.
- Castro, Marisol & Bhat, Chandra R. & Pendyala, Ram M. & Jara-Díaz, Sergio R., 2012. "Accommodating multiple constraints in the multiple discrete–continuous extreme value (MDCEV) choice model," Transportation Research Part B: Methodological, Elsevier, vol. 46(6), pages 729-743.
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