Developing a model for factors affecting customers’ behavioral intentions using structural equations and Fuzzy Inference System (FIS)

this study aimed to develop a model for factors affecting customers' switching intention and their behavioral intentions in the insurance industry using with structural equations and fuzzy inference system.

This study was descriptive-analytical. The statistical population consisted of customers of insurance companies in Alborz province (18 companies).  About 386 customers (by stratified random sampling method) participated in this study using the Cochran sample size formula. Standard questionnaires (with verified validity and reliability) were used for data collection. The structural equation modeling and fuzzy inference system were used for data analysis.

The results in structural equation modeling showed that the set of contextual factors in the theoretical model of this research can explain 91.8% and 77.2% of changes in customers’ behavioral intentions and customers' switching intention (R-Square = 0.918 - 0.772).  In addition, the results from the fuzzy inference system showed that the effects of customer’s satisfaction and perceived risks on each other were in opposite direction.

in perceived risks with upward average amount (from a numerical value of 0.5 to 1), changes of customer satisfaction scores served from a numerical amount of 0.1 to 1, with a decreasing form on customers' switching intention. Also, switching costs had less impact on achieving the positive behavioral intentions of customers than the brand image. Thus, it can be seen that by realizing the high switching costs, i.e., scores higher than 0.8, it is only enough that the brand image is higher than 0.2, so it can be expected that the positive behavioral intentions to be realized in a very acceptable level in the customers.