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TRUVACE RECORD VERSION
record: TRV-2026-2651
version: 1
kind: certified
reason: Certified into the record
timestamp: 2026-11-12T16:56:45.183241Z
status: published
lens: trace
sector: business
headline: Mitigating Chatbot Service Failures: The Roles of Anthropomorphism, Acknowledgment, and Apology
dek: ABSTRACT This study examines how chatbot anthropomorphism shapes consumer responses to service failure by distinguishing between process failure and outcome failure and by testing alternative recovery responses. Across three pretests ( N = 30, 120 and 240) and two scenario‐based experiments (Study 1: N = 346; Study 2: N = 778), consumers evaluated interactions with high‐ versus low‐anthropomorphic chatbots in service settings. The findings show that chatbot anthropomorphism intensifies customer aggression under…
gain_title: In two scenario experiments (346 and 778 consumers), an apology after a process failure reduced customer aggression more than acknowledging the chatbot's AI nature, especially for highly humanlike chatbots.
problem_title: In two scenario-based experiments (346 and 778 consumers), highly humanlike chatbots intensified customer aggression after a process failure because they violated stronger expectations of polite, competent interaction.
trace_subject: Humanlike chatbot design and recovery after service failure
gain_reading: In two scenario experiments (346 and 778 consumers), an apology after a process failure reduced customer aggression more than acknowledging the chatbot's AI nature, especially for highly humanlike chatbots.
gain_evidence: an apology is more effective than acknowledgment of the chatbot's AI nature in mitigating customer aggression, particularly for highly anthropomorphic chatbots
problem_reading: In two scenario-based experiments (346 and 778 consumers), highly humanlike chatbots intensified customer aggression after a process failure because they violated stronger expectations of polite, competent interaction.
problem_evidence: chatbot anthropomorphism intensifies customer aggression under process failure
quick_read: Researchers ran three pretests (30, 120 and 240 participants) and two scenario-based experiments (346 and 778 consumers) in which people evaluated service interactions with chatbots designed to seem more or less humanlike. The experiments found that humanlike design made customers more aggressive when the failure concerned the interaction process itself.

The effect worked through broken expectations. Highly humanlike chatbots led consumers to expect socially appropriate and competent conversation, and a process failure violated those expectations more sharply.

After a process failure, an apology reduced customer aggression more than telling customers they were dealing with an AI, and the gap was larger for highly humanlike chatbots. The authors present this as guidance for firms designing chatbot recovery strategies.
limitation: The findings come from scenario-based experiments in which consumers evaluated described or simulated interactions, not from observed real-world customer behaviour.
tag: Dual reading
key_points: The studies combined three pretests (N = 30, 120 and 240) with two scenario experiments (N = 346 and N = 778). | Consumers compared high- and low-anthropomorphic chatbots in service settings. | Humanlike chatbots intensified customer aggression under process failure, where the failure concerned the interaction itself. | The effect was mediated by disconfirmation of anticipated expectations of socially appropriate, competent interaction. | After process failure, an apology worked better than acknowledging the chatbot's AI nature, particularly for highly humanlike chatbots.
rundown: The research separated process failure, where the interaction itself goes wrong, from outcome failure. Humanlike design raised customer aggression in the process case, which the authors tie to expectations being violated.

Two recovery responses were tested: an apology and an acknowledgment that the chatbot is an AI. The apology reduced aggression more after process failure, with the largest benefit for highly humanlike chatbots.

The authors say the work clarifies when humanlike chatbots help or harm consumers in service encounters and offers firms practical guidance on designing recovery strategies.
sources:
- peer_reviewed | Journal of Consumer Behaviour | https://doi.org/10.1002/cb.70240 | 2026-09-04
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