The DOI matches its Crossref record; 84 of the 87 references it cites were found in a registry or an index, and 3 are not checked yet.
Generating Credibility in Crisis: Will an AI-Scripted Response Be Accepted?
Abstract
Increasingly, practitioners are using artificial intelligence (AI) to strategically monitor and respond to crises. However, there is little evidence indicating whether a crisis response, disclosed as AI-scripted, will be accepted by stakeholders and what effects the disclosure may have on message credibility, attribution of responsibility, message acceptance, and organizational reputation. Using Situational Crisis Communication Theory (SCCT), this 2 (type of crisis) x 2 (presence or absence of AI label) online experiment explored how the disclosure of AI-generated content affects post-crisis organizational outcomes. Participants (n = 238) were randomly assigned to a vignette featuring a victim (e.g. shooting) or accidental (e.g. data breach) cluster crisis and a detailed response that either disclosed or did not disclose that the content was AI-generated. Results revealed no effect of disclosure on message credibility or attribution of responsibility. However, message acceptance served as a mediator between message credibility and attribution of responsibility on organizational reputation. This study contributes to SCCT and provides contextual evidence for practitioners who are considering AI for crisis responses. Ethical implications and future directions are discussed.
Overview
Integrity signals
Registry
Cites
Statistics
Verification
Claims the paper makes
Claims other papers make about this one
Each is checked against this paper’s own text: does it say what the citing paper says it does?
In the citing paper
“Extending SCCT to AI-mediated responses, Ray et al. (2025) conducted a 2 (victim vs. accidental crisis) x 2 (AI disclosure) experiment and found no main effects of disclosing AI-scripted content on message credibility or responsibility attribution; however, message acceptance mediated the path from credibility through responsibility to reputation, suggesting indirect risks even when direct effects”
From Artificial Intelligence in Crisis Communication: Investigating Source Effects and Matched Crisis Responses on Stakeholder Perceptions (2026) · cites this paper as Ray et al. 2025
In the citing paper
“Their results showed that transparency about AI use did not necessarily damage reputation but suggested the need to consider contextual factors such as message purpose and audience sensitivity.”
From Artificial Intelligence in Crisis Communication: Investigating Source Effects and Matched Crisis Responses on Stakeholder Perceptions (2026) · cites this paper as Ray et al. 2025
Citations
Cites
An attributional theory of achievement motivation and emotion
Weiner, B. (1985) · Psychological Review · doi:10.1037/0033-295x.92.4.548 · Cited by 7,846
Coombs, W. T. (2007) · Corporate Reputation Review · doi:10.1057/palgrave.crr.1550049 · Cited by 2,790
Ongoing Crisis Communication: Planning, Managing, and Responding
Coombs, W. T. (1999) · Cited by 2,445
Proceedings for the Annual Meeting of the Cognitive Science Society
Dziemianko, M., Clarke, A. D. F., & Keller, F. (2013) · Cited by 1,726
Persuasion theory and research
O’Keefe, D. J. (1990) · Cited by 1,555
Coombs, W. T., & Holladay, S. J. (2002) · Management Communication Quarterly · doi:10.1177/089331802237233 · Cited by 1,144
Accounts, excuses, and apologies: a theory of image restoration strategies
(1995) · Choice Reviews Online · doi:10.5860/choice.33-1337 · Cited by 872
Communication and Attributions in a Crisis: An Experimental Study in Crisis Communication
Coombs, W. T., & Holladay, S. J. (1996) · Journal of Public Relations Research · doi:10.1207/s1532754xjprr0804_04 · Cited by 706
AI-Mediated Communication: Definition, Research Agenda, and Ethical Considerations
Hancock, J. T., Naaman, M., & Levy, K. (2020) · Journal of Computer-Mediated Communication · doi:10.1093/jcmc/zmz022 · Cited by 658
Measuring Message Credibility: Construction and Validation of an Exclusive Scale
Appelman, A., & Sundar, S. S. (2016) · Journalism & Mass Communication Quarterly · doi:10.1177/1077699015606057 · Cited by 625
Research works printed but not linked: 7
- Dahlhoff D. (2023 August 2). AI in marketing & communications: Boosting productivity- and creativity too?. The Conference Board. https://www.conference-board.org/research/CMO-CCO-Meter/AI-Marketing-Communications-survey
- Davies, N. (2023). 8 ways PR pros can leverage generative AI for crisis communication. Agility PR Solutions. https://www.agilitypr.com/pr-news/public-relations/8-ways-pr-pros-can-leverage-generative-ai-for-crisis-communication/
- Elasser, J. (2021). Thoughts on the AI Wave for communicators. Public Relations Society of America. https://prsay.prsa.org/2021/05/10/thoughts-on-the-ai-wave-for-communicators/
- Myers, C. (2024). To disclose or not to disclose? That is the AI question. Institute for Public Relations. https://instituteforpr.org/to-disclose-or-not-to-disclose-that-is-the-ai-question/
- Public Relations Society of America. (2024). PRSA releases guidance on artificial intelligence [Press release]. https://www.prsa.org/news/2023/11/20/prsa-releases-guidance-on-artificial-intelligence
- 10.4324/9780429330650 · DOI
- 10.48550/arxiv.2111.04230 · arXiv · doi:10.48550/arxiv.2111.04230
Cited by
AI State of Play: The Technology, Strategic Communication Practice and Academia
Gregory, A., & Smith, B. K. (2025) · International Journal of Strategic Communication · doi:10.1080/1553118x.2025.2474875 · Cited by 15
Ge, H., & Jae-Wook, S. (2025) · Acta Psychologica · doi:10.1016/j.actpsy.2025.106041 · Cited by 10
Schneider, E., Kyriakopoulos, V., Seo, Y., Hong, N., Lee, M., & Lim, J. S. (2026) · Corporate Reputation Review · doi:10.1057/s41299-026-00254-9 · Cited by 4
Anani-Bossman, A., Abeka-Daniels, M., Tandoh, I., & Tella, F. (2026) · Corporate Communications An International Journal · doi:10.1108/ccij-08-2025-0252 · Cited by 1
Tracking Public Sentiment on Poverty in Indonesia through AI-Based Social Media Analysis
Santoso, R. B., Wulandari, M. P., & Saleh, A. M. (2026) · Komunikator · doi:10.18196/jkm.v18i1.30582 · Cited by 1
Metadata
- Authors
- Ray, E. C., Merle, P. F., & Lane, K.
- Affiliations
- Florida State University (US)
- Corresponding author
- Ray, Elizabeth C.
- Venue
- International Journal of Strategic Communication
- Publisher
- Informa UK Limited
- Published
- 2024-12-17
- Volume
- 19
- Issue
- 2
- Pages
- 158-175
- ISSN
- 1553-118X (ISSN-L)
- 1553-1198
- OpenAlex
- W4405493401
- Cited by
- 16
- References
- 85
- Citations by year
- 2026: 11 · 2025: 5
- FWCI
- 8.42
- Type
- journal article
- Language
- en
- Open access
- closed
- Locations
- International Journal of Strategic Communication (publishedVersion)
- Topics
- Social Sciences › Communication › Public Relations and Crisis Communication
- Social Sciences › Business, Management and Accounting › Strategy and Management › Corporate Identity and Reputation
- Social Sciences › Business, Management and Accounting › Marketing › AI in Service Interactions
- Keywords
- message credibility, attribution of responsibility, message acceptance, organizational reputation, Situational Crisis Communication Theory, crisis response, AI ethics
About these checks
Registry, retraction, Cites and statistics results are computed, not judged, with one exception: a printed reference that no index lists is read once by a model before it counts as a citation error. Claims are extracted by a model and kept only when their quote appears verbatim in the text; each cited source is then checked, with a model’s help, for whether it says what the claim relies on. Those verdicts can be wrong — read the claim’s quote and the cited source before relying on one.
Statistics and arithmetic are recomputed, not judged.
Confidence bands are shown only for fields calibrated on our annotated test set. None is calibrated yet, so no band is shown.
What counts as a claim ›How we measure confidence ›How we check this ›
Are you an author, or do you see a problem with this page? Request a review
How to cite
Cite CoChat for the checks on this page, and the paper for its own findings.
- This page
- CoChat. (2026). Citation check: Generating Credibility in Crisis: Will an AI-Scripted Response Be Accepted? https://app.cochat.ai/papers/10.1080/1553118x.2024.2435494
- The paper
- Ray, E. C., Merle, P. F., & Lane, K. (2025). Generating Credibility in Crisis: Will an AI-Scripted Response Be Accepted? International Journal of Strategic Communication. https://doi.org/10.1080/1553118x.2024.2435494
Data sources
Bibliographic data: Semantic Scholar, OpenAlex, Crossref.
Contains information from the Semantic Scholar Academic Graph Datasets, made available under the ODC Attribution License (ODC-BY 1.0).
Semantic Scholar’s data is described in: Kinney, R., et al. (2023). The Semantic Scholar Open Data Platform. arXiv:2301.10140.