Consumer Resistance to Chatbot Adoption

Artificial intelligence has impacted the online customer experience by creating numerous opportunities for e-commerce players. With chatbots, these players can now offer their customers instant and personalized responses. However, despite these advantages, some consumers still show reluctance towards using this technology. Our study, based on the model of Ram and Sheth (1989), aims to provide a better understanding of the barriers that hinder the adoption of chatbots in the online shopping environment. It proposes an integrative model that combines functional, psychological, and individual barriers to explain consumers' resistance to using this technology. Structural equation modeling was used to test our theoretical framework. The results show that perceived complexity, functional risk, image barriers, and technological anxiety can lead to resistance towards chatbot usage. Thus, our work enriches the existing literature by testing the Ram and Sheth model (1989) for the first time in the context of chatbot adoption and expanding it with new variables. It also provides valuable recommendations to businesses offering online services.