An assessment model for evaluating asymmetric effects of attribute-level performance on satisfaction

Abstract

The effects of attribute performance on satisfaction have been widely addressed in the discussion on satisfaction. In traditional view, customer satisfaction should be enhanced by improving product or service attribute performance. However, as theoretical and empirical studies have shown, the linkage between attribute performance and overall satisfaction is asymmetric and nonlinear, which means that it is not a definite relationship between high performance of attribute and satisfaction. Regarding the research on delivering asymmetric effects, the Kano model was utilized extensively in the previous studies. But this method suffers from lacking a validity testing and failing to take account of the degree of attribute's importance. To get a more effective access to measuring the asymmetric and nonlinear effects of attributes on customer satisfaction, this study presents an integrated approach which can express asymmetric effects through evaluating the significance of different attributes to satisfaction based on response surface analysis and importance grid analysis methods. In this paper, an empirical study on rural tourists' satisfaction was undertaken using this integrated method. Furthermore, compared with the regression with a dummy variable method, this proposed approach shows more responsive to enhancing attribute performance and makes allowance for improving a certain target attribute in the customer satisfaction improvement process.