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CHOICE‐CONSTRAINED CONJOINT ANALYSIS
Author(s) -
DeSarbo Wayne S.,
Green Paul E.
Publication year - 1984
Publication title -
decision sciences
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 1.238
H-Index - 108
eISSN - 1540-5915
pISSN - 0011-7315
DOI - 10.1111/j.1540-5915.1984.tb01221.x
Subject(s) - conjoint analysis , respondent , preference , computer science , function (biology) , set (abstract data type) , revealed preference , metric (unit) , preference elicitation , mathematical optimization , operations research , choice set , econometrics , economics , mathematics , microeconomics , operations management , programming language , evolutionary biology , political science , law , biology
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.