CHOICE‐CONSTRAINED CONJOINT ANALYSIS

Wayne S. DeSarbo, Paul E. Green

Research output: Contribution to journalArticle

4 Scopus citations

Abstract

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.

Original languageEnglish (US)
Pages (from-to)297-323
Number of pages27
JournalDecision Sciences
Volume15
Issue number3
DOIs
StatePublished - Jul 1984

All Science Journal Classification (ASJC) codes

  • Business, Management and Accounting(all)
  • Strategy and Management
  • Information Systems and Management
  • Management of Technology and Innovation

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