Conjoint Analysis : Methods and Applications

Conjoint analysis is one of many techniques for dealiing with situations in which a decision maker has to choose among options that simultaneously vary among two or more variables. The problem facing the decision maker is how to trade off the possibility that option X is better than option Y on attribute A but worse than option Y on attribute B, and so on. For 40 years researchers from a variety of disciplines--economics, operations research, psychology, statistics, marketing, and business--have studied aspects of the multiattribute choice problem. Conjoint analysis is concerned with the day-to-day decisions of consumers--what brand of toothpaste, automobile, or photocopying machine to buy (or lease)? The marketing researcher may collect trade-off information for hundreds or even thousands of respondents. Data collection and processing techniques must be relatively simple and routinized to handle problems of this scope. Following the theoretical work of Luce and Tukey (1964), conjoint analysis was introduced to the marketing research community in the early 1970s [Green and Rao, 1971]. Since that time, two extensive reviews of the field [Green and Srinivasan, 1978, 1990] have appeared. Conjoint has been one of the most documented methods in marketing research. Judging by the thousands of conjoint applications that have been conducted since 1970, it has become the most popular multiattribute choice model in marketing [Wittink and Cattin, 1989]. Conjoint analysis is both a trade-off measurement technique for analyzing preferences and intentions-to-buy responses and a method for simulating how consumers might react to changes in current product/services or the introduction of new products into an existing competitive array. Conjoint analysis has been applied to products and services (consumer and industrial) and to not-for-profit offerings as well.