The Effects of AI Anthropomorphism and Service Recovery on Perceived Fairness, Post Recovery Trust, and Recovery Satisfaction in Chinese E-Commerce
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Abstract
Artificial Intelligence (AI) has become a key component of customer service in e-commerce, particularly in handling service failures and recovery processes. However, the mechanisms through which AI-assisted service recovery influences consumers' perceptions and post-recovery outcomes remain insufficiently understood. This study examines the effects of AI anthropomorphism and service recovery on perceived fairness, and investigates how perceived fairness subsequently influences post-recovery trust and recovery satisfaction in Chinese e-commerce. Data were collected from 400 users of major Chinese e-commerce platforms using a structured questionnaire and analyzed through descriptive statistics, Pearson correlation, and multiple regression analysis. Results indicate that both AI anthropomorphism and service recovery significantly influence perceived fairness, together explaining 44.7% of its variance. Perceived fairness significantly affects post-recovery trust (Adjusted R² = 0.461) and recovery satisfaction (Adjusted R² = 0.504), with interactional fairness emerging as the most influential dimension. In AI-mediated service encounters, interactional fairness, which reflects consumers' perceptions of respectful, sincere, and empathetic treatment, proves more influential than distributive or procedural fairness. This occurs because human-like interaction quality is particularly salient when consumers evaluate whether an AI system genuinely cares rather than merely processes complaints. This study extends the Stimulus-Organism-Response (S-O-R) framework and offers practical implications for e-commerce platforms. Findings suggest that AI customer service systems should incorporate calibrated empathy through emotionally responsive language, sincere acknowledgment of concerns, and personalized interactional cues to strengthen interactional fairness perceptions and enhance post-recovery trust and satisfaction.
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References
Boshoff, C. (1999). RECOVSAT: An instrument to measure satisfaction with transaction-specific service recovery. Journal of Service Research, 1(3), 236–249.
Colquitt, J. A. (2001). On the dimensionality of organizational justice: A construct validation of a measure. Journal of Applied Psychology, 86(3), 386–400.
Crolic, C., Thomaz, F., Hadi, R., & Stephen, A. T. (2022). Blame the bot: Anthropomorphism and anger in customer–chatbot interactions. Journal of Marketing, 86(1), 132–148.
Cronbach, L. J. (1951). Coefficient alpha and the internal structure of tests. Psychometrika, 16(3), 297–334. https://doi.org/10.1007/BF02310555.
Epley, N., Waytz, A., & Cacioppo, J. T. (2007). On seeing human: A three-factor theory of anthropomorphism. Psychological Review, 114(4), 864–886.
Fürst, A., Trißler, L., Friedrich, R., & Wirtz, J. (2025). Service recovery by AI or human agents: Do failure and strategy context matter? Journal of Service Management, 36(3), 390–418.
Gidaković, P., & Čater, B. (2021). Perceived justice and service recovery satisfaction in a posttransition economy. Journal of East European Management Studies, 26(1), 10–43.
Gronroos, C. (1990). Service management and marketing: Managing the service profit logic. John Wiley & Sons.
Huang, Y. S. S., & Dootson, P. (2022). Chatbots and service failure: When does it lead to customer aggression? Journal of Retailing and Consumer Services, 68, Article 103044.
Ilhamalimy, R. R., & Ali, H. (2021). Model perceived risk and trust: e-WOM and purchase intention. Dinasti International Journal of Digital Business Management, 2(2), 204–221.
Koh, L. Y., Cheh, Y. G., Yuen, K. F., & Wang, X. (2025). Satisfaction with AI chatbots in crowdsourcing services: Anthropomorphic and fairness perspectives. Behaviour & Information Technology, 1–22. Advance online publication.
Kuo, Y. R., Lin, H. H., Duong, N. T., Wang, Y. M., Lin, S. J., Huang, Y. T., & Wang, Y. S. (2025). Investigating the effect of service recovery on consumer responses in the context of food delivery platforms: An experimental study. British Food Journal. Advance online publication.
Liao, Y. K., Wu, C. Y., Truong, G. N. T., & Do, Y. T. (2022). The roles of service recovery and perceived justice on post-recovery satisfaction in M-commerce. Sustainability, 14(22), Article 14838.
Mayer, R. C., Davis, J. H., & Schoorman, F. D. (1995). An integrative model of organizational trust. Academy of Management Review, 20(3), 709–734.
McKnight, D. H., Choudhury, V., & Kacmar, C. (2002). The impact of initial consumer trust on intentions to transact with a web site: A trust building model. Journal of Strategic Information Systems, 11(3), 297–323.
Nass, C., & Moon, Y. (2000). Machines and mindlessness: Social responses to computers. Journal of Social Issues, 56(1), 81–103.
Rovinelli, R. J., & Hambleton, R. K. (1977, April). On the use of content specialists in the assessment of criterion-referenced test item validity [Paper presentation]. Annual Meeting of the American Educational Research Association, New York, NY, United States.
Russo, I., Masorgo, N., & Gligor, D. M. (2022). Examining the impact of service recovery resilience in the context of product replacement: The roles of perceived procedural and interactional justice. International Journal of Physical Distribution & Logistics Management, 52(8), 638–672.
Shen, P., Zhang, F., Fan, X., & Liu, F. (2024). Artificial intelligence psychological anthropomorphism: Scale development and validation. The Service Industries Journal, 44(15–16), 1061–1092.
Song, S., Liu, R., & Dong, D. (2017). An empirical study on the interpersonal relationship between customers and staff in professional services in China. In Proceedings of the 2017 3rd International Conference on Humanities and Social Science Research (pp. 116–124). Atlantis Press.
Tax, S. S., Brown, S. W., & Chandrashekaran, M. (1998). Customer evaluations of service complaint experiences: Implications for relationship marketing. Journal of Marketing, 62(2), 60–76.
Tomlinson, E. C., Nelson, C. A., & Langlinais, L. A. (2021). A cognitive process model of trust repair. International Journal of Conflict Management, 32(2), 340–360.
