Conjoint Analysis in Marketing: New Developments with Implications for Research and Practice

13113 Words May 12th, 2013 53 Pages
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.

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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
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Price typically is included as an attribute; see Srinivasan (1982) for a justification. Because of the substantial amount of among-person variation in consumer preferences, conjoint analysis usually is carried out at the individual level. Significant improvements in predictive validity are obtained by estimating preference models at the individual level rather than at the aggregate or segment level (see Wittink and Montgomery 1979, Table 1, and Moore 1980, Table 2). Consequently, in this review we deemphasize methods that are primarily useful in estimating pref^Conjoint analysis is being used increasingly to develop marketing strategy. For instance, over the past several years the management consulting firm McKinsey and Company has sponsored more than 200 applications of conjoint analysis, the results of which are used in marketing and competitive strategy planning for its clients (Allison 1989). 'Adaptive Conjoint Analysis (ACA), developed by Richard M. Johnson of Sawtooth Software, incorporates data collection in a computer-interactive mode, estimation of part-worths, and choice simulation. Sawtooth Software 's Conjoint Value Analysis is designed expressly for pricing studies. A second set of microcomputer packages has been developed by Steven Herman of Bretton-Clark Software. Conjoint Designer prepares full-profile stimuli (cards) using fractional factorial designs (Green 1974). Conjoint Analyzer and Conjoint LINMAP estimate part-worth functions by metric and
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