Choice-Constrained Conjoint Analysis

Decision Science, 15(3), 297-323

27 Pages Posted: 15 May 2016

See all articles by Wayne S. DeSarbo

Wayne S. DeSarbo

Pennsylvania State University

Paul E. Green

University of Pennsylvania, The Wharton School, Marketing Department (Deceased)

Date Written: July 1984


Choice-constrained conjoint analysis (CCCA) is a new method for metric conjoint analysis studies. It computes part-worth utility functions that account for “revealed preference” — those products a respondent actually selects in an independent choice situation. CCCA uses an iterative penalty function estimation procedure that successively modifies initial regressionderived part worths so that respondent choices (either actual or intended) of real brands are predicted as accurately as possible.

The paper first describes the motivation and rationale for CCCA and presents the mathematics of the algorithm. As an illustration, it applies the CCCA model and penalty function estimation procedure to a limited set of synthetic data. A second application of the technique is presented that uses data obtained by a major telecommunications firm that used conjoint analysis to examine the importance of several features of residential communication devices. The paper also discusses potential extensions of the CCCA model and the kinds of marketing applications for which it might be useful.

Keywords: Consumer Behavior, Marketing Research, Statistical Techniques

Suggested Citation

DeSarbo, Wayne S. and Green, Paul E., Choice-Constrained Conjoint Analysis (July 1984). Decision Science, 15(3), 297-323, Available at SSRN:

Wayne S. DeSarbo (Contact Author)

Pennsylvania State University ( email )

University Park
State College, PA 16802
United States

Paul E. Green

University of Pennsylvania, The Wharton School, Marketing Department (Deceased) ( email )

700 Jon M. Huntsman Hall
3730 Walnut Street
Philadelphia, PA 19104-6340
United States

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