Exploring barriers to social robot adoption: A mixed-method study in the Indian retail sector

Abstract

The global market for social robots, AI-based devices designed to take over different job functions at the workplace, is projected to grow to $13.3 billion by 2027. This article explores the use of social robots in the retail sector in India. The current study proposes a comprehensive two-stage methodology that follows a mixed-method approach. Stage 1 of the study captured the qualitative features of the barriers associated with using social robots using the Fuzzy Interpretive Structural Model (F-ISM). In Stage 2 of the study, researchers took a statistical approach to test the association between the proposed barriers, namely perceived sacrifice, loss of privacy, human identity threat, and robot-induced unemployment, to understand the reasons for reduced intention to use social robots. 201 retailers that used social robots participated in the study. The study's findings suggest that loss of privacy and human identity threats directly impact the reduced intention to use social robots. The authors further discuss the study's research and managerial implications. The research adds to the corpus of knowledge on social robots by empirically testing the barriers and the mediating role of loss of privacy in reduced intention to use social robots.