Beyond conjoint analysis: Advances in preference measurement
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Beyond conjoint analysis: Advances in preference measurement Oded Netzer & Olivier Toubia & Eric T. Bradlow & Ely Dahan & Theodoros Evgeniou & Fred M. Feinberg & Eleanor M. Feit & Sam K. Hui & Joseph Johnson & John C. Liechty & James B. Orlin & Vithala R. Rao
Published online: 30 July 2008 # Springer Science + Business Media, LLC 2008
Abstract 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 O. Netzer (*) : O. Toubia Columbia Business School, Columbia University, 3022 Broadway, New York, NY 10027, USA e-mail: [email protected] O. Toubia e-mail: [email protected] E. T. Bradlow University of Pennsylvania, 700 Jon M. Huntsman Hall, 3730 Walnut Street, Philadelphia, PA 19104-6340, USA e-mail: [email protected] E. Dahan UCLA Anderson School, University of California, Los Angeles, 110 Westwood Plaza, B-514, Los Angeles, CA 90095-1481, USA e-mail: [email protected] T. Evgeniou INSEAD, Boulevard de Constance, 77305 Fontainebleau, France e-mail: [email protected] F. M. Feinberg : E. M. Feit Stephen M. Ross School of Business, University of Michigan, 701 Tappan St., Ann Arbor, MI 48109-1234, USA
e-mail: [email protected] E. M. Feit e-mail: [email protected]
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Market Lett (2008) 19:337–354
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. Keywords Preference measurement . Conjoint analysis . Marketing research
1 Introduction: beyond conjoint analysis Researchers and practitioners often equate preference measurement with conjoint analysis. Indeed, since its introduction (Green and Rao 1971), conjoint analysis (and its variants) has become the method of choice for quantitative preference measurement, and is considered among the major contributions of marketing science to marketing practice. However, conjoint analysis is only a special case of the broader field of preference measurement (Gustafsson et al. 2007). While academic research in conjoint analysis may be viewed by some as mature, the field of preference measurement remains very active, important, and growing. In this paper, we review recent developments in preference measurement that go beyond the “traditional” set of tools that are familiar to many practitioners and academics, and offer directions for future research. We propose viewing preference measurement as comprising three main components (see Fig. 1): (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)
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