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Let me transfer you to our AI-based manager: Impact of manager-level job titles assigned to AI-based agents on marketing outcomes

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  • Jeon, Yongwoog Andrew

Abstract

This paper examines to what extent the job titles assigned to AI agents can influence the customer’s perception of these agents and ultimately their marketing outcomes such as customer satisfaction, brand attitude, and intention to buy AI-recommended products. Also, this study explores how customers perceive the AI agent as the manager working with either a human or an AI representative. Across three experiments (using a scenario or a combination of a scenario and the real AI chatbot), the study shows that consumers perceive the AI manager more positively in terms of likeability, knowledgeability, and trustworthiness than the AI representative and the human manager. The customers perceive the AI manager more positively when they are transferred to the AI manager from a representative of the same kind (AI) than from a human representative. Further, the job titles given to the AI agents are found to have favorable downstream effects on customer satisfaction, brand attitude, and the customers’ intentions to buy the products recommended during the chat by the AI manager.

Suggested Citation

  • Jeon, Yongwoog Andrew, 2022. "Let me transfer you to our AI-based manager: Impact of manager-level job titles assigned to AI-based agents on marketing outcomes," Journal of Business Research, Elsevier, vol. 145(C), pages 892-904.
  • Handle: RePEc:eee:jbrese:v:145:y:2022:i:c:p:892-904
    DOI: 10.1016/j.jbusres.2022.03.028
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    1. Mullinix, Kevin J. & Leeper, Thomas J. & Druckman, James N. & Freese, Jeremy, 2015. "The Generalizability of Survey Experiments," Journal of Experimental Political Science, Cambridge University Press, vol. 2(2), pages 109-138, January.
    2. Loureiro, Sandra Maria Correia & Guerreiro, João & Tussyadiah, Iis, 2021. "Artificial intelligence in business: State of the art and future research agenda," Journal of Business Research, Elsevier, vol. 129(C), pages 911-926.
    3. Rampersad, Giselle, 2020. "Robot will take your job: Innovation for an era of artificial intelligence," Journal of Business Research, Elsevier, vol. 116(C), pages 68-74.
    4. Adam, Martin & Wessel, Michael & Benlian, Alexander, 2020. "AI-based chatbots in customer service and their effects on user compliance," Publications of Darmstadt Technical University, Institute for Business Studies (BWL) 119304, Darmstadt Technical University, Department of Business Administration, Economics and Law, Institute for Business Studies (BWL).
    5. Vlačić, Božidar & Corbo, Leonardo & Costa e Silva, Susana & Dabić, Marina, 2021. "The evolving role of artificial intelligence in marketing: A review and research agenda," Journal of Business Research, Elsevier, vol. 128(C), pages 187-203.
    6. Grewal, Dhruv & Guha, Abhijit & Satornino, Cinthia B. & Schweiger, Elisa B., 2021. "Artificial intelligence: The light and the darkness," Journal of Business Research, Elsevier, vol. 136(C), pages 229-236.
    7. Lynch, John G, Jr, 1982. "On the External Validity of Experiments in Consumer Research," Journal of Consumer Research, Journal of Consumer Research Inc., vol. 9(3), pages 225-239, December.
    8. Thomas Davenport & Abhijit Guha & Dhruv Grewal & Timna Bressgott, 2020. "How artificial intelligence will change the future of marketing," Journal of the Academy of Marketing Science, Springer, vol. 48(1), pages 24-42, January.
    9. Lv, Xingyang & Liu, Yue & Luo, Jingjing & Liu, Yuqing & Li, Chunxiao, 2021. "Does a cute artificial intelligence assistant soften the blow? The impact of cuteness on customer tolerance of assistant service failure," Annals of Tourism Research, Elsevier, vol. 87(C).
    10. Kai H. Lim & Izak Benbasat & Lawrence M. Ward, 2000. "The Role of Multimedia in Changing First Impression Bias," Information Systems Research, INFORMS, vol. 11(2), pages 115-136, June.
    11. Ming-Hui Huang & Roland T. Rust, 2021. "A strategic framework for artificial intelligence in marketing," Journal of the Academy of Marketing Science, Springer, vol. 49(1), pages 30-50, January.
    12. Pantano, Eleonora & Pizzi, Gabriele, 2020. "Forecasting artificial intelligence on online customer assistance: Evidence from chatbot patents analysis," Journal of Retailing and Consumer Services, Elsevier, vol. 55(C).
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    Cited by:

    1. Ryoo, Yuhosua & Jeon, Yongwoog Andy & Kim, WooJin, 2024. "The blame shift: Robot service failures hold service firms more accountable," Journal of Business Research, Elsevier, vol. 171(C).

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