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Assessing the Use of Regression Analysis in Examining Service Recovery in the Insurance Industry: Relating Service Quality, Customer Satisfaction, and Customer Trust

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  • Steven A. Taylor

Abstract

This study explores customer service quality, satisfaction, and trust judgments within the context of service recovery and relationship marketing practices in an insurance setting. Service recovery most generally deals with complaint management. The study offers three contributions to the body of knowledge specific to the insurance industry. First, the results identify potential interactive and curvilinear influences that possess the ability to bias traditional regression results. Second, the results suggest that models of customer behaviors may vary across target markets and/or respondent pools, and even across organizations and their own agents. Finally, a research framework is presented and discussed that will assist insurance marketers in helping to overcome potential bias in regression coefficients used in competitive insurance settings. The research and managerial implications of the reported study are also presented and discussed.

Suggested Citation

  • Steven A. Taylor, 2001. "Assessing the Use of Regression Analysis in Examining Service Recovery in the Insurance Industry: Relating Service Quality, Customer Satisfaction, and Customer Trust," Journal of Insurance Issues, Western Risk and Insurance Association, vol. 24(1/2), pages 30-57.
    • Handle: RePEc:wri:journl:v:24:y:2001:i:1:p:30-57
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    Cited by:

    1. Pradeep Kautish & Arpita Khare & Rajesh Sharma, 2022. "Health insurance policy renewal: an exploration of reputation, performance, and affect to understand customer inertia," Journal of Marketing Analytics, Palgrave Macmillan, vol. 10(3), pages 261-278, September.
    2. Ruifeng Gong & Jian Xue & Ruli Liu & Jinhua Zhou & Laijun Zhao, 2022. "A closed‐loop supply chain decision model considering corporate social responsibility and value‐added services," Managerial and Decision Economics, John Wiley & Sons, Ltd., vol. 43(6), pages 1704-1720, September.

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