Analysis of means-end chain data in marketing research

Abstract

Means-End Chain Theory has been developed in order to understand how consumers link attributes (A) of products with particular consequences (C), and how these consequences satisfy their personal values (V). The associations in the mind of the consumer between A's, C's and V's are labelled means-end chains (MEC). These chains are often seen as a representation of the basic drive that motivates consumer behaviour. Numerous studies have shown that techniques using MEC are suitable for a wide range of marketing applications. But there is no agreement among researchers as to the way MEC observations should be analysed. In this paper, we review methods of analysis of such observations and suggest the most appropriate procedures. Data from a study of smokers’ perceptions of cigarettes in a European city are used for illustration purposes.Journal of Targeting, Measurement and Analysis for Marketing (2006) 15, 12–20. doi:10.1057/palgrave.jt.5750028 ABSTRACT FROM AUTHOR Copyright of Journal of Targeting, Measurement & Analysis for Marketing is the property of Palgrave Macmillan Ltd. and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts)