Trust in humanoid robots in footwear stores: A large-N crisp-set qualitative comparative analysis (csQCA) model

Abstract

Based upon Computers-Are-Social-Actors and Social Exchange theories, this study investigated causal configurations of Human-Robot Trust (HRT), social intelligence, and retail assistance performance of humanoid robots that may increase consumers’ intention to visit a footwear store. A pretest and main study (n = 455) were conducted with a video-based stimulus. Using Crist-Set Qualitative Comparative Analysis (csQCA), the study took a holistic approach to the emerging topic of humanoid robots, and proposed a QCA-based conceptual framework. The results revealed that consumers will always demonstrate a strong intention to visit a robot-operated store when the configurations of HRT and retail assistance performance or HRT and social intelligence are present (sufficient conditions). Most importantly, consumers will never demonstrate a strong intention to visit the store in the absence of HRT (necessary condition). This study serves as an example of new alternative analytical methods, such as large-N csQCA applications, to traditional multivariate analyses.