Shopping intention at AI-powered automated retail stores (AIPARS)
By Rajasshrie Pillai, Brijesh Sivathanu, Yogesh Kumar Dwivedi. 2020
367 citations recorded by the source corpus.
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.
Subfields: Information Systems, Information Systems and Management, Marketing
View Paper: https://www.semanticscholar.org/paper/8df615f3870e0bae5d5ec42c4ccd8731b56577ef
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In Information Systems
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Citations in the corpus
- An integrated artificial intelligence framework for knowledge creation and B2B marketing rational decision making for improving firm performance (2021, background): “However, there are limited research studies in this domain (Pandey et al., 2020; Pillai, Sivathanu, & Dwivedi, 2020).”