Shopping intention at AI-powered automated retail stores (AIPARS) |
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| Institution: | 1. Babson College, United States;2. University of Arkansas, United States;3. Indian Institute of Management Bangalore, India;4. University of Calgary, Canada;5. Bond University, Australia;1. University of Hull/ University of Texas, El Paso, United States;2. University of Hull, UK;3. De Montfort University, UK;4. Department of Marketing & International Business, Turku School of Economics, University of Turku, Turun Yliopisto, FI-20014 Turku, Finland;1. UWA Business School, The University of Western Australia, 35 Stirling Highway, Crawley, Perth 6009, Australia;2. Marketing, Nottingham University Business School China, University of Nottingham Ningbo China, 199, Taikang East Road, Ningbo 315100, China;3. School of Management, Faculty of Business, Government and Law, University of Canberra, ACT 2601, Australia;4. School of Marketing, Curtin Business School, Curtin University, Bentley Campus, Perth, Western Australia;1. Montana State University, Jake Jabs College of Business & Entrepreneurship, Bozeman, MT 59717, USA;2. KyungHee University, School of Management, Seoul, South Korea;3. Breda University of Applied Sciences, Mgr. Hopmansstraat 2, 4817 JS Breda, the Netherlands;4. ZUYD University of Applied Sciences, Bethlehemweg 2, 6222 BM Maastricht, the Netherlands |
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| Abstract: | Artificial Intelligence (AI) is transforming the way retail stores operate. AI-Powered Automated Retail Stores are the next revolution in physical retail. Consumers are facing fully automated technology in these retail stores. Therefore, it is necessary to scrutinize the antecedents of consumers' intention to shop at AI-Powered Automated Retail Stores. This study delves into this area to find the predictors of consumers’ intention to shop at AI-Powered Automated Retail Stores. It extends the technology readiness and acceptance model by the addition of AI context-specific constructs such as Perceived Enjoyment, Customization and Interactivity from the present literature. The proposed model is tested by surveying 1250 consumers & the data is analyzed using the PLS-SEM technique and empirically validated. The outcome of the study reveals that Innovativeness and Optimism of consumers affect the perceived ease and perceived usefulness. Insecurity negatively affects the perceived usefulness of AI-powered automated retail stores. Perceived ease of use, perceived usefulness, perceived enjoyment, customization and interactivity are significant predictors of shopping intention of consumers in AI-powered automated stores. This research presents insightful academic and managerial implications in the domain of retailing and technology in retail. |
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| Keywords: | TRAM PLS-SEM Perceived enjoyment Customization Interactivity Artificial intelligence-powered automated retail stores |
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