Abstract

Artificial Intelligence (AI) has revolutionized the online customer experience, creating numerous opportunities for e-commerce businesses. AI chatbots now enable these businesses to provide customers with instant and personalized responses. However, despite these benefits, some consumers remain hesitant to use this technology. Our study, building on the model of Ram and Sheth (1989), seeks to understand the barriers that prevent the adoption of chatbots in online shopping. We propose an integrative model that includes functional, psychological, and individual barriers to explain consumer resistance. Using structural equation modeling, we tested our theoretical framework and found that perceived complexity, functional risk, image barrier, and technological anxiety contribute to resistance towards chatbot usage. This study enhances the existing literature by applying the Ram and Sheth model (1989) to chatbot adoption for the first time and expanding it with new variables, providing new insights into customer behavior. Its offers valuable recommendations to businesses, including designing user-friendly, intuitive, easy-to-use interfaces to alleviate technology anxiety and perceived complexity, while ensuring that conversations with bots are concise and easy to understand. Highlighting the benefits of the bot, such as providing personalized solutions/instant, reliable, 24/7 responses, through demonstrations and advertising for example, can further reduce resistance and encourage its adoption.

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