Revolutionizing Food Ordering: Predicting the Dynamics of Chatbot Adoption in a Tech-Driven Era

Aslam, Wajeeha, Ham, Marija, Mirza, Farhan, Ding, Ting Hooi and Hussain, Dr Ali (2025) Revolutionizing Food Ordering: Predicting the Dynamics of Chatbot Adoption in a Tech-Driven Era. Journal of Foodservice Business Research: 2468035. pp. 1-25. ISSN 1537-8020
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In today's technology-driven world, businesses have recognized the crucial role of real-time customer interaction. Many companies have enthusiastically adopted self-service technologies (SSTs) such as chatbots to fulfill these needs effectively. Our study examines the intention behind utilizing chatbots for food ordering. The proposed model was tested with the PLS-SEM technique on 296 respondents who had experience using a chatbot for food ordering. Given that chatbots are currently in the early stages of adoption, the present study focuses on several key factors directly relevant to the context of AI-based services, such as inconvenience, technological anxiety, anthropomorphism, automation, perceived innovativeness, and perceived intelligence. We seek to explain technology usage using the Unified Theory of Acceptance and Use of Technology (UTAUT) and the Technology Acceptance Model (TAM). The study's findings indicate a positive relationship between anthropomorphism, perceived intelligence, and negative association of inconvenience with the intention to adopt. In addition, the intention to adopt significantly predicted the subsequent actual usage. Our study will enrich the existing knowledge landscape and guide future endeavors in AI-driven customer interactions and engagement strategies, leading to a better understanding, fulfilling their needs, and impacting how society perceives and interacts with AI technologies.

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