Conjoint Analysis in Marketing: New Developments with Implications for Research and Practice 
Paul E. Green & V. Srinivasan
Conjoint Analysis in Marketing: New Developments With Implications for Research and Practice
The authors update and extend their 1978 review of conjoint analysis. In addition to discussing several new developments, they consider alternative approaches for measuring preference structures in the presence of a large number of attributes. They also discuss other topics such as reliability, validity, and choice simulators.
S
INCE the early 1970s, conjoint analysis has received considerable academic and industry attention as a major set of techniques for measuring buyers ' tradeoffs among multiattributed products and services (Green and Rao 1971; Johnson 1974; Srinivasan and Shocker 1973b). We presented a state-ofthe-art review of conjoint analysis in 1978 (Green and Srinivasan 1978). Since that time many new developments in conjoint analysis and related methods have been reported. The purpose of this article is to review those developments (with comments on their rationale, advantages, and limitations) and propose potentially useful avenues for new research. We assume the reader is familiar with our previous review as background for a detailed study of this article. ' In subsequent sections we describe a variety of de-
velopments that have been achieved since the 1978 review. Topics include:
• choosing conjoint models to minimize prediction error, • collecting conjoint data via the telephone-mail-telephone method, • experimental designs that incorporate environmental correlations across the attributes, • methods for improving part-worth estimation accuracy, • new techniques for coping with large numbers of attributes and levels within attribute, • issues in measuring conjoint reliability, • recent findings in conjoint validation, • coping with the problem of "unacceptable" attribute levels, • extending conjoint to multivariate preference responses, • trends in conjoint simulators, and • new kinds of industry applications of
Conjoint Analysis in Marketing: New Developments With Implications for Research and Practice
The authors update and extend their 1978 review of conjoint analysis. In addition to discussing several new developments, they consider alternative approaches for measuring preference structures in the presence of a large number of attributes. They also discuss other topics such as reliability, validity, and choice simulators.
S
INCE the early 1970s, conjoint analysis has received considerable academic and industry attention as a major set of techniques for measuring buyers ' tradeoffs among multiattributed products and services (Green and Rao 1971; Johnson 1974; Srinivasan and Shocker 1973b). We presented a state-ofthe-art review of conjoint analysis in 1978 (Green and Srinivasan 1978). Since that time many new developments in conjoint analysis and related methods have been reported. The purpose of this article is to review those developments (with comments on their rationale, advantages, and limitations) and propose potentially useful avenues for new research. We assume the reader is familiar with our previous review as background for a detailed study of this article. ' In subsequent sections we describe a variety of de-
velopments that have been achieved since the 1978 review. Topics include:
• choosing conjoint models to minimize prediction error, • collecting conjoint data via the telephone-mail-telephone method, • experimental designs that incorporate environmental correlations across the attributes, • methods for improving part-worth estimation accuracy, • new techniques for coping with large numbers of attributes and levels within attribute, • issues in measuring conjoint reliability, • recent findings in conjoint validation, • coping with the problem of "unacceptable" attribute levels, • extending conjoint to multivariate preference responses, • trends in conjoint simulators, and • new kinds of industry applications of
References: Conjoint Analysis in Marketing / 1 7 Krishnamurthi, Lakshman (1988), 'Conjoint Models of Family Decision Making," International Journal of Research in Marketing, 5, 185-98