Measuring Heterogeneous Reservation Prices for Product Bundles

Kamel Jedidi (), Sharan Jagpal () and Puneet Manchanda ()
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Kamel Jedidi: Graduate School of Business, Columbia University, New York, New York 10027
Sharan Jagpal: Rutgers Business School, Rutgers University, 180 University Avenue, Newark, New Jersey 07102
Puneet Manchanda: Graduate School of Business, University of Chicago, 1101 East 58th Street, Chicago, Illinois 60637

Marketing Science, 2003, vol. 22, issue 1, 107-130

Abstract: This paper develops a model for capturing continuous heterogeneity in the joint distribution of reservation prices for products and bundles. Our model is derived from utility theory and captures both within-and among-subject variability. Furthermore, it provides dollarmetric reservation prices and individual-level estimates that allow the firm to target customers and develop customized and nonlinear pricing policies. Our experiments show that, regardless of whether the products are durables or nondurables, the model captures heterogeneity and predicts well. Models that assume homogeneity perform poorly, especially in predicting choice of the bundle. Furthermore, the methodology is robust even when respondents evaluate few profiles. Self-stated reservation prices do not have any informational content beyond that contained in the basic model. The direct elicitation method appears to understate (overstate) the variation in reservation prices across consumers for low-priced (high-priced) products and bundles. Hence this method yields biased demand estimates and leads to suboptimal product-line pricing policy. The optimization results show that the product-line pricing policy depends on the degree of heterogeneity in the reservation prices of the individual products and the bundle. A uniformly high-price strategy for all products and bundles is optimal when heterogeneity is high. Otherwise, a hybrid strategy is optimal.

Keywords: bundling; reservation prices; optimal pricing; consumer heterogeneity; multinomial probit models; conjoint analysis; bayesian models (search for similar items in EconPapers)
Date: 2003
References: View references in EconPapers View complete reference list from CitEc
Citations: View citations in EconPapers (50)

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Persistent link: https://EconPapers.repec.org/RePEc:inm:ormksc:v:22:y:2003:i:1:p:107-130

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