Abstract
Key driver analysis (statistically inferred importance analysis) is commonly implemented to understand what customer satisfaction attributes are most important in driving overall customer satisfaction. Building on prior research, this article suggests that dominance analysis and relative weight analysis are the most appropriate statistical techniques for conducting key driver analysis, yet relative weight analysis is the more feasible choice. A process is put forth so that research practitioners can conduct key driver analysis with relative weight analysis implementing a two-step approach. The two-step approach should be used when the key driver analysis contains a large number of attributes, which are theoretically redundant and highly correlated.
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