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The contingent effects of AI transparency in service recovery: a moderated mediation model of perceived warmth and competence
- Truvace record
- TRV-2026-2637raw data (JSON)
- Version
- v1Published
- First published
- Evidence type
- Controlled or validated comparison
- Sources
- 1 sourcePeer-reviewed
- sha256
- 1df3f259aac7…check it
Purpose This research investigates how artificial intelligence (AI) transparency shapes consumer responses in service recovery. By revealing the reasoning process behind AI decisions, transparency functions as an anthropomorphic cue that humanizes the system's communication. Drawing on social cognitive theory, the research develops and tests a generalizable mechanism framework linking AI transparency, consumer cognition and recovery satisfaction, while identifying boundary conditions. Design/methodology/approach…
The gain
In three scenario-based experiments with 98, 230 and 284 participants, AI that revealed its reasoning raised customers' satisfaction with service recovery, partly by making the system seem warmer and more competent.
What this doesn’t fix
The indirect effects through warmth and competence were not significant when service failures were severe, and the evidence comes from scenario-based experiments rather than real customer complaints.
Sources
1 on file- Online Information Reviewdoi:10.1108/oir-08-2025-0646
Cite this record
v1Truvace Impact Record TRV-2026-2637, v1: “The contingent effects of AI transparency in service recovery: a moderated mediation model of perceived warmth and competence.” Truvace, 2026-11-12. /record/TRV-2026-2637 (accessed on the day you copy it). sha256 1df3f259aac72c85…
Change history
1 versionEvery change made to this record since it was first published, and why. Nothing has changed since it went up.
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