Artificial Intelligence Systems in Retail: Examining Customer Behavior and Adoption

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Abstract
Artificial Intelligence (AI) is a disruptive innovation that has driven digital transformation in the retail industry. Technologies such as robots, chatbots, conversational agents, and generative AI are reshaping customer interactions. Although AI origins date back to the 1950s, when Alan Turing posed the question, “Can machines think?”, the use of this technology has exponentially evolved in recent years across various contexts and functions. These advancements increasingly simulate the capabilities of the human mind, enabling companies to achieve what once was considered impossible. This dissertation explores the antecedents and possible outcomes of AI technology within the retail industry, focusing specifically on AI acceptance and customers’ behavior regarding AI usage. The research undertakes an exploration of the role that AI systems could play in configuring and enhancing customer experiences through three interrelated articles, each offering unique insights into the role of AI in retail strategies. The first study provides a comprehensive analysis of insights on the impact of AI on omnichannel customer experience (OCE), incorporating perspectives from top-retail managers, consultants, and customers. The second study presents a conceptualization and validation of a measurement model for customers’ acceptance of artificial intelligence (CAAI), providing a robust framework for measuring AI acceptance among customers. The third, and final study, investigates and analyze the influence of CAAI on word-of-mouth (WOM), reuse intention, and the moderating effect of trust in technology. Together, these studies present a comprehensive exploration of how AI can be utilized to transform customer acceptance and optimize retail strategies. This dissertation aims to contribute to a deeper understanding of how AI technologies can be leveraged to enhance retail strategies and customer interactions, offering insights for both academic researchers and industry practitioners.
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