IDEAS home Printed from https://ideas.repec.org/a/kap/mktlet/v35y2024i3d10.1007_s11002-024-09725-7.html
   My bibliography  Save this article

Not a good judge of talent: the influence of subjective socioeconomic status on AI aversion

Author

Listed:
  • Chunya Xie

    (University of Electronic Science and Technology of China)

  • Tianhui Fu

    (Renmin University of China)

  • Chen Yang

    (Jimei University)

  • En-Chung Chang

    (Renmin University of China)

  • Mengying Zhao

    (Beijing National Accounting Institute)

Abstract

The current research constructs a framework to understand how subjective socioeconomic status (SES) affects consumers’ AI aversion in the evaluation context. Three experiments show that subjective SES has a negative impact on consumers’ willingness to accept AI evaluation. Consumers with higher subjective SES are more likely to resist AI evaluation because they perceive that AI agents are not as capable as human agents of identifying their talents. This effect is moderated by the agent type–the impact of subjective SES on resistance to the AI agent is attenuated when the AI agent is non-evaluative. This research is of great significance in enriching research on improving AI services efficiency across various social classes.

Suggested Citation

  • Chunya Xie & Tianhui Fu & Chen Yang & En-Chung Chang & Mengying Zhao, 2024. "Not a good judge of talent: the influence of subjective socioeconomic status on AI aversion," Marketing Letters, Springer, vol. 35(3), pages 381-393, September.
  • Handle: RePEc:kap:mktlet:v:35:y:2024:i:3:d:10.1007_s11002-024-09725-7
    DOI: 10.1007/s11002-024-09725-7
    as

    Download full text from publisher

    File URL: http://link.springer.com/10.1007/s11002-024-09725-7
    File Function: Abstract
    Download Restriction: Access to full text is restricted to subscribers.

    File URL: https://libkey.io/10.1007/s11002-024-09725-7?utm_source=ideas
    LibKey link: if access is restricted and if your library uses this service, LibKey will redirect you to where you can use your library subscription to access this item
    ---><---

    As the access to this document is restricted, you may want to search for a different version of it.

    References listed on IDEAS

    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. Montero Guerra, José Manuel & Danvila-del-Valle, Ignacio & Méndez Suárez, Mariano, 2023. "The impact of digital transformation on talent management," Technological Forecasting and Social Change, Elsevier, vol. 188(C).
    3. Edmond Awad & Sohan Dsouza & Richard Kim & Jonathan Schulz & Joseph Henrich & Azim Shariff & Jean-François Bonnefon & Iyad Rahwan, 2018. "The Moral Machine experiment," Nature, Nature, vol. 563(7729), pages 59-64, November.
    4. 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.
    Full references (including those not matched with items on IDEAS)

    Most related items

    These are the items that most often cite the same works as this one and are cited by the same works as this one.
    1. Marilyn Giroux & Jungkeun Kim & Jacob C. Lee & Jongwon Park, 2022. "Artificial Intelligence and Declined Guilt: Retailing Morality Comparison Between Human and AI," Journal of Business Ethics, Springer, vol. 178(4), pages 1027-1041, July.
    2. Leah Warfield Smith & Randall Lee Rose & Alex R. Zablah & Heath McCullough & Mohammad “Mike” Saljoughian, 2023. "Examining post-purchase consumer responses to product automation," Journal of the Academy of Marketing Science, Springer, vol. 51(3), pages 530-550, May.
    3. Chen, Nuoya & Mohanty, Smaraki & Jiao, Jinfeng & Fan, Xiucheng, 2021. "To err is human: Tolerate humans instead of machines in service failure," Journal of Retailing and Consumer Services, Elsevier, vol. 59(C).
    4. Peng, Leiqing & Luo, Mengting & Guo, Yulang, 2023. "Deposit AI as the “invisible hand†to make the resale easier: A moderated mediation model," Journal of Retailing and Consumer Services, Elsevier, vol. 75(C).
    5. Poushneh, Atieh & Vasquez-Parraga, Arturo & Gearhart, Richard S., 2024. "The effect of empathetic response and consumers’ narcissism in voice-based artificial intelligence," Journal of Retailing and Consumer Services, Elsevier, vol. 79(C).
    6. David A. Schweidel & Yakov Bart & J. Jeffrey Inman & Andrew T. Stephen & Barak Libai & Michelle Andrews & Ana Babić Rosario & Inyoung Chae & Zoey Chen & Daniella Kupor & Chiara Longoni & Felipe Thomaz, 2022. "How consumer digital signals are reshaping the customer journey," Journal of the Academy of Marketing Science, Springer, vol. 50(6), pages 1257-1276, November.
    7. Zhang, Yaqiong & Wang, Shifu, 2023. "The influence of anthropomorphic appearance of artificial intelligence products on consumer behavior and brand evaluation under different product types," Journal of Retailing and Consumer Services, Elsevier, vol. 74(C).
    8. Manjunath Padigar & Ljubomir Pupovac & Ashish Sinha & Rajendra Srivastava, 2022. "The effect of marketing department power on investor responses to announcements of AI-embedded new product innovations," Journal of the Academy of Marketing Science, Springer, vol. 50(6), pages 1277-1298, November.
    9. Chenfeng Yan & Quan Chen & Xinyue Zhou & Xin Dai & Zhilin Yang, 2024. "When the Automated fire Backfires: The Adoption of Algorithm-based HR Decision-making Could Induce Consumer’s Unfavorable Ethicality Inferences of the Company," Journal of Business Ethics, Springer, vol. 190(4), pages 841-859, April.
    10. Lim, Xin-Jean & Cheah, Jun-Hwa & Ng, Siew Imm & Kamal Basha, Norazlyn & Liu, Yide, 2021. "Are men from Mars, women from Venus? Examining gender differences towards continuous use intention of branded apps," Journal of Retailing and Consumer Services, Elsevier, vol. 60(C).
    11. Jochen Wirtz & Valentina Pitardi, 2023. "How intelligent automation, service robots, and AI will reshape service products and their delivery," Italian Journal of Marketing, Springer, vol. 2023(3), pages 289-300, September.
    12. Alabed, Amani & Javornik, Ana & Gregory-Smith, Diana, 2022. "AI anthropomorphism and its effect on users' self-congruence and self–AI integration: A theoretical framework and research agenda," Technological Forecasting and Social Change, Elsevier, vol. 182(C).
    13. Lidan Xu & Ravi Mehta, 2022. "Technology devalues luxury? Exploring consumer responses to AI-designed luxury products," Journal of the Academy of Marketing Science, Springer, vol. 50(6), pages 1135-1152, November.
    14. 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.
    15. 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.
    16. Uzir, Md Uzir Hossain & Al Halbusi, Hussam & Lim, Rodney & Jerin, Ishraq & Abdul Hamid, Abu Bakar & Ramayah, Thurasamy & Haque, Ahasanul, 2021. "Applied Artificial Intelligence and user satisfaction: Smartwatch usage for healthcare in Bangladesh during COVID-19," Technology in Society, Elsevier, vol. 67(C).
    17. Xiong, Xiling & Wong, IpKin Anthony & Yang, Fiona X., 2021. "Are we behaviorally immune to COVID-19 through robots?," Annals of Tourism Research, Elsevier, vol. 91(C).
    18. Erik Hermann & Gizem Yalcin Williams & Stefano Puntoni, 2024. "Deploying artificial intelligence in services to AID vulnerable consumers," Journal of the Academy of Marketing Science, Springer, vol. 52(5), pages 1431-1451, October.
    19. Stephanie M. Noble & Martin Mende, 2023. "The future of artificial intelligence and robotics in the retail and service sector: Sketching the field of consumer-robot-experiences," Journal of the Academy of Marketing Science, Springer, vol. 51(4), pages 747-756, July.
    20. Huang, Dan & Jin, Xin & Coghlan, Alexandra, 2021. "Advances in consumer innovation resistance research: A review and research agenda," Technological Forecasting and Social Change, Elsevier, vol. 166(C).

    Corrections

    All material on this site has been provided by the respective publishers and authors. You can help correct errors and omissions. When requesting a correction, please mention this item's handle: RePEc:kap:mktlet:v:35:y:2024:i:3:d:10.1007_s11002-024-09725-7. See general information about how to correct material in RePEc.

    If you have authored this item and are not yet registered with RePEc, we encourage you to do it here. This allows to link your profile to this item. It also allows you to accept potential citations to this item that we are uncertain about.

    If CitEc recognized a bibliographic reference but did not link an item in RePEc to it, you can help with this form .

    If you know of missing items citing this one, you can help us creating those links by adding the relevant references in the same way as above, for each refering item. If you are a registered author of this item, you may also want to check the "citations" tab in your RePEc Author Service profile, as there may be some citations waiting for confirmation.

    For technical questions regarding this item, or to correct its authors, title, abstract, bibliographic or download information, contact: Sonal Shukla or Springer Nature Abstracting and Indexing (email available below). General contact details of provider: http://www.springer.com .

    Please note that corrections may take a couple of weeks to filter through the various RePEc services.

    IDEAS is a RePEc service. RePEc uses bibliographic data supplied by the respective publishers.