When transparency backfires: how AI identity disclosure fuels consumer information distortion in service recovery

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Authors: Jiaxuan Li, Mingxing Han, Qinjian Yuan
Cited by: 1
References: 75

Abstract

With the rapid adoption of artificial intelligence (AI) in the hotel and tourism industry, AI agents are increasingly involved in online service recovery. This study examines how disclosing an AI agent’s identity influences consumers’ information distortion in online service recovery. Building on mind perception theory and psychological distance theory, we propose that AI agent identity disclosure reduces consumers’ mind perception of service agents, which subsequently shapes cognitive trust and increases their tendency to distort information during service recovery interactions. Across two experimental studies using realistic hotel service recovery scenarios, we find consistent evidence for this serial mediation effect. Furthermore, the level of anthropomorphism moderates the relationship. This research advances the literature on AI transparency in hospitality and tourism by uncovering a previously overlooked psychological mechanism that drives consumer information distortion. The findings also provide practical guidance for hotel and tourism service providers to improve service recovery effectiveness.

Fields of Study & Subjects

AI in Service Interactions Ethics and Social Impacts of AI Privacy Security and Data Protection

Publication details

Journal / source
Journal of Hospitality Marketing & Management
Publisher
Informa UK Limited
Volume
35
Issue
5
Pages
751–777
Publication date
8 February 2026
Language
EN