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Exploring the mechanism of sustained consumer trust in AI chatbots after service failures: a perspective based on attribution and CASA theories

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Listed:
  • Chenyu Gu

    (Minjiang University
    Fujian Social Science Research Base)

  • Yu Zhang

    (Minjiang University)

  • Linhao Zeng

    (Renmin University of China)

Abstract

In recent years, artificial intelligence (AI) technology has been widely employed in brand customer service. However, the inherent limitations of computer-generated natural language content occasionally lead to failures in human-computer interactions, potentially damaging a company’s brand image. Therefore, it is crucial to explore how to maintain consumer trust after AI chatbots fail to provide successful service. This study constructs a model to examine the impact of social interaction cues and anthropomorphic factors on users’ sustained trust by integrating the Computers As Social Actors (CASA) theory with attribution theory. An empirical analysis of 462 survey responses reveals that CASA factors (perceived anthropomorphic characteristics, perceived empathic abilities, and perceived interaction quality) can effectively enhance user trust in AI customer service following interaction failures. This process of sustaining trust is mediated through different attributions of failure. Furthermore, AI anxiety, as a cognitive characteristic of users, not only negatively impacts sustained trust but also significantly moderates the effect of internal attributions on sustained trust. These findings expand the research domain of human-computer interaction and provide insights for the practical development of AI chatbots in communication and customer service fields.

Suggested Citation

  • Chenyu Gu & Yu Zhang & Linhao Zeng, 2024. "Exploring the mechanism of sustained consumer trust in AI chatbots after service failures: a perspective based on attribution and CASA theories," Palgrave Communications, Palgrave Macmillan, vol. 11(1), pages 1-12, December.
    • Handle: RePEc:pal:palcom:v:11:y:2024:i:1:d:10.1057_s41599-024-03879-5
    DOI: 10.1057/s41599-024-03879-5
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    1. Iglesias, Oriol & Markovic, Stefan & Rialp, Josep, 2019. "How does sensory brand experience influence brand equity? Considering the roles of customer satisfaction, customer affective commitment, and employee empathy," Journal of Business Research, Elsevier, vol. 96(C), pages 343-354.
    2. McLean, Graeme & Osei-Frimpong, Kofi & Barhorst, Jennifer, 2021. "Alexa, do voice assistants influence consumer brand engagement? – Examining the role of AI powered voice assistants in influencing consumer brand engagement," Journal of Business Research, Elsevier, vol. 124(C), pages 312-328.
    3. Canhoto, Ana Isabel & Clear, Fintan, 2020. "Artificial intelligence and machine learning as business tools: A framework for diagnosing value destruction potential," Business Horizons, Elsevier, vol. 63(2), pages 183-193.
    4. Li, Hao & Jiang, Jinhu & Wu, Mingjie, 2014. "The effects of trust assurances on consumers’ initial online trust: A two-stage decision-making process perspective," International Journal of Information Management, Elsevier, vol. 34(3), pages 395-405.
    5. Golossenko, Artyom & Pillai, Kishore Gopalakrishna & Aroean, Lukman, 2020. "Seeing brands as humans: Development and validation of a brand anthropomorphism scale," International Journal of Research in Marketing, Elsevier, vol. 37(4), pages 737-755.
    6. Shahzad, Muhammad Farrukh & Xu, Shuo & An, Xin & Javed, Iqra, 2024. "Assessing the impact of AI-chatbot service quality on user e-brand loyalty through chatbot user trust, experience and electronic word of mouth," Journal of Retailing and Consumer Services, Elsevier, vol. 79(C).
    7. 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.
    8. Song, Christina Soyoung & Kim, Youn-Kyung, 2022. "The role of the human-robot interaction in consumers’ acceptance of humanoid retail service robots," Journal of Business Research, Elsevier, vol. 146(C), pages 489-503.
    9. 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.
    10. Daniel Belanche & Luis V. Casaló & Carlos Flavián, 2021. "Frontline robots in tourism and hospitality: service enhancement or cost reduction?," Electronic Markets, Springer;IIM University of St. Gallen, vol. 31(3), pages 477-492, September.
    11. 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.
    12. Joseph F. Hair & Christian M. Ringle & Siegfried P. Gudergan & Andreas Fischer & Christian Nitzl & Con Menictas, 2019. "Partial least squares structural equation modeling-based discrete choice modeling: an illustration in modeling retailer choice," Business Research, Springer;German Academic Association for Business Research, vol. 12(1), pages 115-142, April.
    13. Simon, Françoise, 2013. "The influence of empathy in complaint handling: Evidence of gratitudinal and transactional routes to loyalty," Journal of Retailing and Consumer Services, Elsevier, vol. 20(6), pages 599-608.
    14. Lastner, Matthew M. & Folse, Judith Anne Garretson & Mangus, Stephanie M. & Fennell, Patrick, 2016. "The road to recovery: Overcoming service failures through positive emotions," Journal of Business Research, Elsevier, vol. 69(10), pages 4278-4286.
    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. Chuah, Stephanie Hui-Wen & Yu, Joanne, 2021. "The future of service: The power of emotion in human-robot interaction," Journal of Retailing and Consumer Services, Elsevier, vol. 61(C).
    17. Kull, Alexander J. & Romero, Marisabel & Monahan, Lisa, 2021. "How may I help you? Driving brand engagement through the warmth of an initial chatbot message," Journal of Business Research, Elsevier, vol. 135(C), pages 840-850.
    18. Corina Pelau & Irina Ene & Mihai-Ionut Pop, 2021. "The Impact of Artificial Intelligence on Consumers’ Identity and Human Skills," The AMFITEATRU ECONOMIC journal, Academy of Economic Studies - Bucharest, Romania, vol. 23(56), pages 1-33, February.
    19. Pankaj Aggarwal & Ann L. Mcgill, 2012. "When Brands Seem Human, Do Humans Act Like Brands? Automatic Behavioral Priming Effects of Brand Anthropomorphism," Journal of Consumer Research, Journal of Consumer Research Inc., vol. 39(2), pages 307-323.
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