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Unpacking Generative Artificial Intelligence‐Powered Crisis Communication From a Moral Angle: The Role of Moral Outrage, Authenticity, and Forgiveness

Kim, Sungsu, Chon, Myoung‐Gi·2025·Journal of Contingencies and Crisis Management
DOI 10.1111/1468-5973.70066
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Abstract

This study aims to advance crisis communication by incorporating morality in understanding crisis communication and explicating effective strategies for using artificial intelligence (AI) technology (e.g., ChatGPT) in the context of the ‘preventable’ cluster of crisis types. To this end, we conducted an online experiment, adopting a 3 (crisis type) × 2 (crisis response source label) between‐subjects design. The results indicate that scansis elicited greater moral outrage than other crisis types and that a crisis response from ChatGPT led to lower authenticity than a crisis response from a PR representative. Indirect effects analyses demonstrated that moral outrage, authenticity and forgiveness mediated the effects of crisis type and message source label on behavioural outcomes. Theoretical and practical implications are discussed.

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Metadata

Authors
Kim, S., & Chon, M.
Venue
Journal of Contingencies and Crisis Management
Publisher
Wiley
Published
2025-07-31
Volume
33
Issue
3
ISSN
  • 0966-0879
  • 1468-5973
DOI
10.1111/1468-5973.70066
Cited by
3
References
1
Language
en
Licence
creativecommons.org/licenses/by-nc-nd/4.0/ (vor)

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CoChat. (2026). Citation check: Unpacking Generative Artificial Intelligence‐Powered Crisis Communication From a Moral Angle: The Role of Moral Outrage, Authenticity, and Forgiveness. https://app.cochat.ai/papers/10.1111/1468-5973.70066
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Kim, S., & Chon, M. (2025). Unpacking Generative Artificial Intelligence‐Powered Crisis Communication From a Moral Angle: The Role of Moral Outrage, Authenticity, and Forgiveness. Journal of Contingencies and Crisis Management. https://doi.org/10.1111/1468-5973.70066

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Semantic Scholar’s data is described in: Kinney, R., et al. (2023). The Semantic Scholar Open Data Platform. arXiv:2301.10140.