Estimating Consumers' Willingness to Pay for the Individual Quality Attributes with DEA

In a highly competitive environment, a product's commercial success depends increasingly more upon the ability to satisfy consumers' preferences that are highly diversified. Since a product typically comprises a host of technological attributes, its market value incorporates all of the individual values of technological attributes. If the willingness-to-pay (WTP) for individual quality attributes of a product is known, one can conjecture the overall WTP or the imputed market price for the product. The market price listed by the producer has to be equal to or lower than this WTP for the commercial survival of the product. In this paper, we propose a methodology for estimating the value of individual product characteristics and thus the overall WTP of the product with DEA. Our methodology is based on a model derived from consumer demand theory on the one hand, and the recent developments in DEA on the other hand. The paper also presents a real case study for the mobile phone market, which is characterized by its high speed of innovation. On the theoretical side, we expect our framework to provide a possibility of combining DEA and consumer demand theory. We also expect that the empirical application will shed some light on the nature of the process of product differentiation based on consumers' valuation.

[1]  W. Cooper,et al.  RAM: A Range Adjusted Measure of Inefficiency for Use with Additive Models, and Relations to Other Models and Measures in DEA , 1999 .

[2]  Peter C. Smith,et al.  Lancaster's characteristics approach revisited: product selection using non-parametric methods , 2002 .

[3]  Kenneth E. Train,et al.  Discrete Choice Methods with Simulation , 2016 .

[4]  W. Cooper,et al.  Data Envelopment Analysis: A Comprehensive Text with Models, Applications, References and DEA-Solver Software , 1999 .

[5]  B. Skiera,et al.  Measuring Consumers' Willingness to Pay at the Point of Purchase , 2002 .

[6]  John A. Weymark,et al.  Money-Metric Utility Functions , 1985 .

[7]  H. Varian A Model of Sales , 1980 .

[8]  Roger H. von Haefen,et al.  Welfare Measurement and Representative Consumer Theory , 1997 .

[9]  K. Train Discrete Choice Methods with Simulation , 2003 .

[10]  C. Lovell,et al.  Stochastic Frontier Analysis: Frontmatter , 2000 .

[11]  K. Lancaster A New Approach to Consumer Theory , 1966, Journal of Political Economy.

[12]  Ralph L. Keeney,et al.  Value-Focused Thinking: A Path to Creative Decisionmaking , 1992 .

[13]  Kenneth C. Land,et al.  Chance‐constrained data envelopment analysis , 1993 .

[14]  L. Schrage Optimization Modeling With LINDO , 1997 .

[15]  Daniel Kahneman,et al.  Fairness and the Assumptions of Economics , 1986 .

[16]  M Johannesson,et al.  Hypothetical versus real willingness to pay in the health care sector: results from a field experiment. , 2001, Journal of health economics.

[17]  K. Mayumi,et al.  Reformulating the foundations of consumer choice theory and environmental valuation , 2001 .

[18]  Craig W. Kirkwood,et al.  Strategic decision making : multiobjective decision analysis with spreadsheets : instructor's manual , 1996 .

[19]  Tai-Yoo Kim,et al.  The Measurement of Consumption Efficiency Considering the Discrete Choice of Consumers , 2005 .

[20]  Rakesh K. Sarin,et al.  Preference Conditions for Multiattribute Value Functions , 1980, Oper. Res..

[21]  Wagner A. Kamakura,et al.  Measuring Market Efficiency and Welfare Loss , 1988 .

[22]  Mandy Ryan,et al.  Testing for consistency in willingness to pay experiments , 2000 .

[23]  S. Rosen Hedonic Prices and Implicit Markets: Product Differentiation in Pure Competition , 1974, Journal of Political Economy.

[24]  Theodor J. Stewart,et al.  Trends in Multicriteria Decision Making , 1998 .

[25]  José Carlos Rodriguez Alcantud,et al.  Continuous representation by a money-metric function , 2001, Math. Soc. Sci..