IDEAS home Printed from https://ideas.repec.org/a/gam/jsusta/v15y2023i4p3294-d1064891.html
   My bibliography  Save this article

The Impact of AI’s Response Method on Service Recovery Satisfaction in the Context of Service Failure

Author

Listed:
  • Zengmao Yang

    (School of Economics and Management, Beijing University of Posts and Telecommunications, Beijing 100876, China)

  • Jinlai Zhou

    (School of Economics and Management, Beijing University of Posts and Telecommunications, Beijing 100876, China)

  • Hongjun Yang

    (School of Economics and Management, Beijing University of Posts and Telecommunications, Beijing 100876, China)

Abstract

In order to perpetuate service sustainability and promote sustainable growth in the service sector, it is important to resolve service failures. AI technology is being applied to service jobs in more and more industries, but AI will inevitably fail while providing service. How to carry out service recovery and obtain the understanding and forgiveness of customers is a problem that urgently needs solving in the practice and research of AI services. The purpose of this study was to explore the artificial intelligence remediation mechanism in the context of service failure and to explore the remedial utility of AI’s self-deprecating humor responses. The study conducted data collection through three experiments to test our hypotheses: study 1 verified the main effect of self-deprecating humor responses and the mediating effect of perceived sincerity and perceived intelligence; study 2 verified the moderated effect of the sense of power; and study 3 verified the moderated effect of failure experience. The experimental results show that, in the context of AI for service recovery, self-deprecating humor responses can improve customers’ willingness to tolerate failure, with perceived intelligence and perceived sincerity found to play a mediating role in this. The sense of power also plays a moderating role by affecting perceived sincerity, and failure experience has a moderate effect by affecting perceived intelligence. The theoretical contribution of the article is to introduce the perspective of AI’s self-deprecating humor service recovery, which complements theoretical research in the field of AI services. The management significance of the article is to provide new AI communication strategies and practical suggestions for enterprises and technical personnel.

Suggested Citation

  • Zengmao Yang & Jinlai Zhou & Hongjun Yang, 2023. "The Impact of AI’s Response Method on Service Recovery Satisfaction in the Context of Service Failure," Sustainability, MDPI, vol. 15(4), pages 1-18, February.
    • Handle: RePEc:gam:jsusta:v:15:y:2023:i:4:p:3294-:d:1064891
    as

    Download full text from publisher

    File URL: https://www.mdpi.com/2071-1050/15/4/3294/pdf
    Download Restriction: no
    File URL: https://www.mdpi.com/2071-1050/15/4/3294/
    Download Restriction: no
    ---><---

    References listed on IDEAS

    as
    1. Tang, Le & Sun, Shiyu, 2021. "How does leader self-deprecating humor affect creative performance? The role of creative self-efficacy and power distance," Finance Research Letters, Elsevier, vol. 42(C).
    2. Sourav Bikash Borah & Srinivas Prakhya & Amalesh Sharma, 2020. "Leveraging service recovery strategies to reduce customer churn in an emerging market," Journal of the Academy of Marketing Science, Springer, vol. 48(5), pages 848-868, September.
    3. 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.
    4. Sara Kim & Ann L. McGill, 2011. "Gaming with Mr. Slot or Gaming the Slot Machine? Power, Anthropomorphism, and Risk Perception," Journal of Consumer Research, Journal of Consumer Research Inc., vol. 38(1), pages 94-107.
    5. Wei, Chuang & Liu, Maggie Wenjing & Keh, Hean Tat, 2020. "The road to consumer forgiveness is paved with money or apology? The roles of empathy and power in service recovery," Journal of Business Research, Elsevier, vol. 118(C), pages 321-334.
    6. Babin, Barry J. & Zhuang, Weiling & Borges, Adilson, 2021. "Managing service recovery experience: Effects of the forgiveness for older consumers," Journal of Retailing and Consumer Services, Elsevier, vol. 58(C).
    7. Bo Huang & Matthew Philp, 2021. "When AI-based services fail: examining the effect of the self-AI connection on willingness to share negative word-of-mouth after service failures," The Service Industries Journal, Taylor & Francis Journals, vol. 41(13-14), pages 877-899, October.
    8. Helena González‐gómez & Sarah Hudson & Aude Rychalski, 2021. "The psychology of frustration: Appraisals, outcomes, and service recovery," Post-Print hal-03329187, HAL.
    9. Huang, Ran & Ha, Sejin, 2020. "The effects of warmth-oriented and competence-oriented service recovery messages on observers on online platforms," Journal of Business Research, Elsevier, vol. 121(C), pages 616-627.
    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. Xu, Xing'an & Liu, Juan & Gursoy, Dogan, 2022. "Emotional intelligence similarity in service recovery," Annals of Tourism Research, Elsevier, vol. 96(C).
    2. Honora, Andreawan & Chih, Wen-Hai & Wang, Kai-Yu, 2022. "Managing social media recovery: The important role of service recovery transparency in retaining customers," Journal of Retailing and Consumer Services, Elsevier, vol. 64(C).
    3. 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.
    4. Teng, Lefa & Sun, Chuluo & Chen, Yifei & Lever, Michael W. & Foti, Lianne, 2024. "Partner or servant? The influence of robot role positioning on consumers’ brand evaluations," Journal of Business Research, Elsevier, vol. 180(C).
    5. Francesc Fusté-Forné & Tazim Jamal, 2021. "Co-Creating New Directions for Service Robots in Hospitality and Tourism," Tourism and Hospitality, MDPI, vol. 2(1), pages 1-19, January.
    6. Liu, Fu & Wei, Haiying & Zhu, Zhenzhong & Chen, Haipeng (Allan), 2022. "Warmth or competence: Brand anthropomorphism, social exclusion, and advertisement effectiveness," Journal of Retailing and Consumer Services, Elsevier, vol. 67(C).
    7. K Akdim & Luis V. Casaló, 2023. "Perceived value of AI-based recommendations service: the case of voice assistants," Service Business, Springer;Pan-Pacific Business Association, vol. 17(1), pages 81-112, March.
    8. Muhammad Mazhar & Muhammad Amir Nadeem & Haider Ali Abbasi & Umaima Tariq & Amin Jan & Rao Abdul Hannan Jaffar, 2022. "Reparation for Service Failure Through Service Recovery: An Assessment of Consumer Behaviour in an Online Shopping Context," Business Management and Strategy, Macrothink Institute, vol. 13(1), pages 64-87, June.
    9. Aubel Martin & Pikturniene Indre & Joye Yannick, 2022. "Risk Perception and Risk Behavior in Response to Service Robot Anthropomorphism in Banking," Journal of Management and Business Administration. Central Europe, Sciendo, vol. 30(2), pages 26-42, June.
    10. Sebastian Molinillo & Francisco Rejón-Guardia & Rafael Anaya-Sánchez, 2023. "Exploring the antecedents of customers’ willingness to use service robots in restaurants," Service Business, Springer;Pan-Pacific Business Association, vol. 17(1), pages 167-193, March.
    11. Malgorzata Karpinska-Krakowiak & Lukasz Skowron & Lachezar Ivanov, 2020. "“I Will Start Saving Natural Resources, Only When You Show Me the Planet as a Person in Danger”: The Effects of Message Framing and Anthropomorphism on Pro-Environmental Behaviors that are Viewed as E," Sustainability, MDPI, vol. 12(14), pages 1-14, July.
    12. Shengliang Zhang & Chaoying Huang & Xiaodong Li & Ai Ren, 2022. "Understanding Impacts of Service Robots with the Revised Gap Model," Sustainability, MDPI, vol. 14(5), pages 1-23, February.
    13. Jacob C. Lee & Sara Kim & Phyllis Xue Wang, 2022. "Anthropomorphizing makes material goods as happiness-inducing as experiences," Marketing Letters, Springer, vol. 33(1), pages 61-73, March.
    14. Zhang, Yicong & Guo, Xiaoling, 2023. "“New and old†: Consumer evaluations of co-branding between new brands and Chinese time-honored brands," Journal of Retailing and Consumer Services, Elsevier, vol. 73(C).
    15. Silvia Biraghi & Rossella Chiara Gambetti & Angela Antonia Beccanulli, 2020. "Achieving cultural relevance in technomediated platforms: instant cultural branding and controversial clicktivism," Italian Journal of Marketing, Springer, vol. 2020(2), pages 163-187, September.
    16. Han, Jie & Wang, Desheng & Yang, Zhihao, 2023. "Acting like an interpersonal relationship: Cobrand anthropomorphism increases product evaluation and purchase intention," Journal of Business Research, Elsevier, vol. 167(C).
    17. Han, Nah Ray & Baek, Tae Hyun & Yoon, Sukki & Kim, Yeonshin, 2019. "Is that coffee mug smiling at me? How anthropomorphism impacts the effectiveness of desirability vs. feasibility appeals in sustainability advertising," Journal of Retailing and Consumer Services, Elsevier, vol. 51(C), pages 352-361.
    18. Huang, Jingya & Wang, Liangyan & Chan, Eugene, 2024. "When does anthropomorphism hurt? How tool anthropomorphism negatively affects consumers' rewards for tool users," Journal of Business Research, Elsevier, vol. 170(C).
    19. Nika Meyer (née Mozafari) & Melanie Schwede & Maik Hammerschmidt & Welf Hermann Weiger, 2022. "Users taking the blame? How service failure, recovery, and robot design affect user attributions and retention," Electronic Markets, Springer;IIM University of St. Gallen, vol. 32(4), pages 2491-2505, December.
    20. 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.

    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:gam:jsusta:v:15:y:2023:i:4:p:3294-:d:1064891. 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: MDPI Indexing Manager (email available below). General contact details of provider: https://www.mdpi.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.