Will coolness factors predict user satisfaction and loyalty? Evidence from an artificial neural network–structural equation model approach

Our research attempts to track the role of coolness factors (i.e., attractiveness, subculture, and uniqueness) on user satisfaction and loyalty with respect to technological products. For this purpose, we construct a model for a particular technological product on the basis of coolness and satisfaction–loyalty theories. We then gather survey-based data from 454 Koreans for measuring the coolness factors, satisfaction, and loyalty variables. Subsequently, we employ an artificial neural network–structural equation model for testing the proposed model. Based on the outcomes, (1) we find that attractiveness and uniqueness have notable and positive effects on satisfaction, (2) whereas, subculture does not have a considerable impact on satisfaction. (3) In addition, a positive association between satisfaction and loyalty is identified. (4) Interestingly, there are no significant moderating influences of age and gender on the associations of coolness elements. Overall, the outcomes of our research contribute to the expansion of the literature regarding coolness theory and user experience of technologies.