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AI in E-Commerce: Application of the Use and Gratification Model to The Acceptance of Chatbots

Author

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  • Rob Kim Marjerison

    (Global Business, College of Business and Public Management, Wenzhou-Kean University, Wenzhou 325015, China)

  • Youran Zhang

    (Accounting, College of Business and Public Management, Wenzhou-Kean University, Wenzhou 325015, China)

  • Hanyi Zheng

    (Accounting, College of Business and Public Management, Wenzhou-Kean University, Wenzhou 325015, China)

Abstract

This study applies and builds on the Use and Gratification (U&G) theory to explore consumer acceptance of applied artificial intelligence (AI) in the form of Chatbots in online shopping in China. Data were gathered via an anonymous online survey from 540 respondents who self-identified as frequent online shoppers and are familiar with Chatbots. The results of the data analysis provide empirical evidence indicating that utilitarian factors such as the “authenticity of conversation” and “convenience”, as well as hedonic factors such as “perceived enjoyment”, result in users having a positive attitude towards Chatbots. However, privacy issues and the immaturity of technology have had a negative impact on acceptance. This paper provides both theoretical and practical insights into Chinese attitudes toward Chatbots and may be of interest to e-commerce researchers, practitioners, and U&G theorists.

Suggested Citation

  • Rob Kim Marjerison & Youran Zhang & Hanyi Zheng, 2022. "AI in E-Commerce: Application of the Use and Gratification Model to The Acceptance of Chatbots," Sustainability, MDPI, vol. 14(21), pages 1-16, November.
    • Handle: RePEc:gam:jsusta:v:14:y:2022:i:21:p:14270-:d:960146
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    References listed on IDEAS

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    1. Eliza Nichifor & Adrian Trifan & Elena Mihaela Nechifor, 2021. "Artificial Intelligence in Electronic Commerce: Basic Chatbots and Consumer Journey," The AMFITEATRU ECONOMIC journal, Academy of Economic Studies - Bucharest, Romania, vol. 23(56), pages 1-87, February.
    2. Ha, Sejin & Stoel, Leslie, 2009. "Consumer e-shopping acceptance: Antecedents in a technology acceptance model," Journal of Business Research, Elsevier, vol. 62(5), pages 565-571, May.
    3. Lo, Alex Y., 2014. "Negative income effect on perception of long-term environmental risk," Ecological Economics, Elsevier, vol. 107(C), pages 51-58.
    4. Mónika-Anetta Alt & Vizeli Ibolya, 2021. "Identifying Relevant Segments of Potential Banking Chatbot Users Based on Technology Adoption Behavior," Tržište/Market, Faculty of Economics and Business, University of Zagreb, vol. 33(2), pages 165-183.
    5. Martin Adam & Michael Wessel & Alexander Benlian, 2021. "AI-based chatbots in customer service and their effects on user compliance," Electronic Markets, Springer;IIM University of St. Gallen, vol. 31(2), pages 427-445, June.
    6. Rese, Alexandra & Ganster, Lena & Baier, Daniel, 2020. "Chatbots in retailers’ customer communication: How to measure their acceptance?," Journal of Retailing and Consumer Services, Elsevier, vol. 56(C).
    7. Markus Blut & Cheng Wang & Nancy V. Wünderlich & Christian Brock, 2021. "Understanding anthropomorphism in service provision: a meta-analysis of physical robots, chatbots, and other AI," Journal of the Academy of Marketing Science, Springer, vol. 49(4), pages 632-658, July.
    8. Viswanath Venkatesh & Fred D. Davis, 2000. "A Theoretical Extension of the Technology Acceptance Model: Four Longitudinal Field Studies," Management Science, INFORMS, vol. 46(2), pages 186-204, February.
    9. Lin Li & Kyung Young Lee & Emmanuel Emokpae & Sung-Byung Yang, 2021. "What makes you continuously use chatbot services? Evidence from chinese online travel agencies," Electronic Markets, Springer;IIM University of St. Gallen, vol. 31(3), pages 575-599, September.
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