A latent structure factor analytic approach for customer satisfaction measurement

Jianan Wu, Wayne S. DeSarbo, Pu Ju Chen, Yao Yi Fu

Research output: Contribution to journalArticlepeer-review

14 Scopus citations

Abstract

The linkage of customer satisfaction, customer retention, and firm profitability has been well established in the marketing literature, and provides ample justification as to why customer satisfaction measurement (CSM) has been a focal point in marketing decision making. Although aggregate market level research on understanding the determinants of customer satisfaction is abundant, CSM decisions at segment level are possible only if the individual or market segment differences in the formation of overall satisfaction judgments and subsequent heterogeneity in the role these various determinants play are understood. Based on expectancy-disconfirmation theory in customer satisfaction, we propose a maximum likelihood based latent structure factor analytic methodology which visually depicts customer heterogeneity regarding the various major determinants of customer satisfaction judgments involving multiple attributes, and provides directions for segment-specific CSM decisions. We first describe the proposed model framework including the technical aspects of the model structure and subsequent maximum likelihood estimation. In an application to a consumer trade show, we then demonstrate how our proposed methodology can be gainfully employed to uncover the nature of such heterogeneity. We also empirically demonstrate the superiority of the proposed model over a number of different model specifications in this application. Finally, limitations and directions for future research are discussed.

Original languageEnglish (US)
Pages (from-to)221-238
Number of pages18
JournalMarketing Letters
Volume17
Issue number3
DOIs
StatePublished - Jul 2006

All Science Journal Classification (ASJC) codes

  • Business and International Management
  • Economics and Econometrics
  • Marketing

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