Marketing Letters

, 19:337

First online:

Beyond conjoint analysis: Advances in preference measurement

  • Oded NetzerAffiliated withColumbia Business School, Columbia University Email author 
  • , Olivier ToubiaAffiliated withColumbia Business School, Columbia University
  • , Eric T. BradlowAffiliated withUniversity of Pennsylvania
  • , Ely DahanAffiliated withUCLA Anderson School, University of California, Los Angeles
  • , Theodoros EvgeniouAffiliated withINSEAD, Boulevard de Constance
  • , Fred M. FeinbergAffiliated withStephen M. Ross School of Business, University of Michigan
  • , Eleanor M. FeitAffiliated withStephen M. Ross School of Business, University of Michigan
  • , Sam K. HuiAffiliated withStern School of Business, New York University
  • , Joseph JohnsonAffiliated withSchool of Business Administration, University of Miami
    • , John C. LiechtyAffiliated withSmeal College of Business, The Pennsylvania State University
    • , James B. OrlinAffiliated withSloan School of Management, Massachusetts Institute of Technology
    • , Vithala R. RaoAffiliated withJohnson Graduate School of Management, Cornell University

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We identify gaps and propose several directions for future research in preference measurement. We structure our argument around a framework that views preference measurement as comprising three interrelated components: (1) the problem that the study is ultimately intended to address; (2) the design of the preference measurement task and the data collection approach; (3) the specification and estimation of a preference model, and the conversion into action. Conjoint analysis is only one special case within this framework. We summarize cutting edge research and identify fruitful directions for future investigations pertaining to the framework’s three components and to their integration.


Preference measurement Conjoint analysis Marketing research