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AI is better when I'm sure: The influence of certainty of needs on consumers' acceptance of AI chatbots

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  • Zhu, Yimin
  • Zhang, Jiemin
  • Wu, Jifei
  • Liu, Yingyue

Abstract

This study examines how the certainty of consumer needs affects consumers' acceptance of artificial intelligence (AI) chatbots in the online pre-purchase stage. Three experiments are conducted to demonstrate that consumers are more likely to choose AI chatbots when their needs are more certain. This effect is mediated by consumers' perceived effectiveness of AI chatbots and moderated by product type. Specifically, when the certainty of needs is higher, consumers perceive AI chatbots to be more effective, ultimately promoting consumers' acceptance of AI chatbots. For search products, higher (vs. lower) certainty of needs increases consumers' acceptance of AI chatbots, while for experience products the certainty of needs does not significantly affect consumers' acceptance of AI chatbots. These findings make important theoretical contributions to the existing literature on AI chatbots and also provide some practical implications for electronic commerce companies to implement AI chatbot strategies more effectively.

Suggested Citation

  • Zhu, Yimin & Zhang, Jiemin & Wu, Jifei & Liu, Yingyue, 2022. "AI is better when I'm sure: The influence of certainty of needs on consumers' acceptance of AI chatbots," Journal of Business Research, Elsevier, vol. 150(C), pages 642-652.
    • Handle: RePEc:eee:jbrese:v:150:y:2022:i:c:p:642-652
    DOI: 10.1016/j.jbusres.2022.06.044
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    as
    1. Chiara Longoni & Andrea Bonezzi & Carey K Morewedge, 2019. "Resistance to Medical Artificial Intelligence," Journal of Consumer Research, Journal of Consumer Research Inc., vol. 46(4), pages 629-650.
    2. Karimi, Sahar & Holland, Christopher P. & Papamichail, K. Nadia, 2018. "The impact of consumer archetypes on online purchase decision-making processes and outcomes: A behavioural process perspective," Journal of Business Research, Elsevier, vol. 91(C), pages 71-82.
    3. Berkeley J. Dietvorst & Joseph P. Simmons & Cade Massey, 2018. "Overcoming Algorithm Aversion: People Will Use Imperfect Algorithms If They Can (Even Slightly) Modify Them," Management Science, INFORMS, vol. 64(3), pages 1155-1170, March.
    4. Nelson, Phillip, 1970. "Information and Consumer Behavior," Journal of Political Economy, University of Chicago Press, vol. 78(2), pages 311-329, March-Apr.
    5. Bernd Schmitt, 2020. "Speciesism: an obstacle to AI and robot adoption," Marketing Letters, Springer, vol. 31(1), pages 3-6, March.
    6. Ronan de Kervenoael & Rajibul Hasan & Alexandre Schwob & Edwin Goh, 2020. "Leveraging human-robot interaction in hospitality services: Incorporating the role of perceived value, empathy, and information sharing into visitors’ intentions to use social robots," Post-Print hal-02782265, HAL.
    7. Urbany, Joel E & Dickson, Peter R & Wilkie, William L, 1989. "Buyer Uncertainty and Information Search," Journal of Consumer Research, Journal of Consumer Research Inc., vol. 16(2), pages 208-215, September.
    8. Fernandes, Teresa & Oliveira, Elisabete, 2021. "Understanding consumers’ acceptance of automated technologies in service encounters: Drivers of digital voice assistants adoption," Journal of Business Research, Elsevier, vol. 122(C), pages 180-191.
    9. Xu, Yingzi & Shieh, Chih-Hui & van Esch, Patrick & Ling, I-Ling, 2020. "AI customer service: Task complexity, problem-solving ability, and usage intention," Australasian marketing journal, Elsevier, vol. 28(4), pages 189-199.
    10. Daniel Belanche & Luis V. Casaló & Carlos Flavián & Jeroen Schepers, 2020. "Service robot implementation: a theoretical framework and research agenda," The Service Industries Journal, Taylor & Francis Journals, vol. 40(3-4), pages 203-225, March.
    11. Chung, Minjee & Ko, Eunju & Joung, Heerim & Kim, Sang Jin, 2020. "Chatbot e-service and customer satisfaction regarding luxury brands," Journal of Business Research, Elsevier, vol. 117(C), pages 587-595.
    12. Logg, Jennifer M. & Minson, Julia A. & Moore, Don A., 2019. "Algorithm appreciation: People prefer algorithmic to human judgment," Organizational Behavior and Human Decision Processes, Elsevier, vol. 151(C), pages 90-103.
    13. Roy, Rajat & Naidoo, Vik, 2021. "Enhancing chatbot effectiveness: The role of anthropomorphic conversational styles and time orientation," Journal of Business Research, Elsevier, vol. 126(C), pages 23-34.
    14. Jacoby, Jacob, et al, 1994. "Tracing the Impact of Item-by-Item Information Accessing on Uncertainty Reduction," Journal of Consumer Research, Journal of Consumer Research Inc., vol. 21(2), pages 291-303, September.
    15. Sheehan, Ben & Jin, Hyun Seung & Gottlieb, Udo, 2020. "Customer service chatbots: Anthropomorphism and adoption," Journal of Business Research, Elsevier, vol. 115(C), pages 14-24.
    16. Moorthy, Sridhar & Ratchford, Brian T & Talukdar, Debabrata, 1997. "Consumer Information Search Revisited: Theory and Empirical Analysis," Journal of Consumer Research, Journal of Consumer Research Inc., vol. 23(4), pages 263-277, March.
    17. Wien, Anders Hauge & Peluso, Alessandro M., 2021. "Influence of human versus AI recommenders: The roles of product type and cognitive processes," Journal of Business Research, Elsevier, vol. 137(C), pages 13-27.
    18. Xueming Luo & Siliang Tong & Zheng Fang & Zhe Qu, 2019. "Frontiers: Machines vs. Humans: The Impact of Artificial Intelligence Chatbot Disclosure on Customer Purchases," Marketing Science, INFORMS, vol. 38(6), pages 937-947, November.
    19. Holbrook, Morris B & Hirschman, Elizabeth C, 1982. "The Experiential Aspects of Consumption: Consumer Fantasies, Feelings, and Fun," Journal of Consumer Research, Journal of Consumer Research Inc., vol. 9(2), pages 132-140, September.
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