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Article
Publication date: 1 February 2003

Abba Krieger, Paul Green, Leonard Lodish, Jim D’Arcangelo, Chris Rothey and Paul Thirty

Conjoint analysis is a class of techniques for analyzing consumers’ preferences and trade‐offs regarding their selection of products and services. Typically, conjoint analysis has…

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Abstract

Conjoint analysis is a class of techniques for analyzing consumers’ preferences and trade‐offs regarding their selection of products and services. Typically, conjoint analysis has been applied to established markets such as frequently purchased packaged goods, consumer durables, communication services, and business‐to‐business products. Recently, marketing researchers have extended conjoint methodology to cope with the measurement of buyer trade‐offs associated with “really new” products and services, for which there is little or no prior buyer knowledge or experience. The researcher’s task is twofold: to educate the potential buyer regarding the pros and cons of the new product/service while, at the same time, obtaining the respondent’s evaluation of the new product/service itself. This article describes the application of conjoint techniques to a new service, TrafficPulse, that enables subscribers to obtain continuous 24/7 updates on traffic conditions, travel times, and alternative routes, should congestion occur. In particular, describes how traditional conjoint analysis can be embellished to obtain relevant information about consumer evaluations of new goods and services prior to their actual use by prospective consumers. In short, the prospective consumer can be “educated” about the new product/service before obtaining evaluation of its potential worth. The paper also shows how conjoint analysis can be modified to accommodate restrictions on various attribute levels, how the use of BASES‐like norms can be incorporated, and how optimization algorithms can be used at either the single product or multiple product (i.e. product line) level.

Details

Journal of Services Marketing, vol. 17 no. 1
Type: Research Article
ISSN: 0887-6045

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