Is ChatGPT a Responsible Communication: A Study on the Credibility and Adoption of Conversational Artificial Intelligence
Abstract
In the realm of generative artificial intelligence (AI), ChatGPT has garnered widespread acclaim for its remarkably realistic chatbot interactions. Despite its popularity, recent challenges in reliability have emerged. This research uniquely combines the Stimulus-Organism-Response (S-O-R) framework with dual-process theory to dissect the factors influencing ChatGPT’s credibility and popularity. Employing cross-sectional data from select social media platforms, the study identifies quality, accuracy, timeliness, audience familiarity, and congruence with other sources as pivotal elements shaping ChatGPT’s credibility. Significantly, this research reveals how users evaluate the reliability of generative AI-generated search results by comparing them to conventional methods. The study’s novel contribution lies in its exploration of ChatGPT as a medium of communication, offering valuable insights into understanding and enhancing the reliability of generative AI applications in the information landscape.
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Ethical concerns have been raised with the use of ChatGPT, such as potential negative impacts on genuine human connections and interactions, privacy, and human ingenuity.
“Ethical concerns have been raised with the use of ChatGPT, such as the potential negative impacts of AI chatbots on genuine human connections and interactions, privacy, and human ingenuity [30,35,37].”
From Consumer Responses to Generative AI Chatbots Versus Search Engines for Product Evaluation (2025) · cites this paper as [30]
Quality, accuracy, timeliness, audience familiarity, and congruence with other sources play important roles in affecting AI chatbot credibility.
“Other researchers have examined the factors that influence the consumer perception and adoption of AI chatbots, specifically ChatGPT [30][31][32] and found that quality, accuracy, timeliness, audience familiarity, and congruence with other sources play important roles in affecting its credibility [30].”
From Consumer Responses to Generative AI Chatbots Versus Search Engines for Product Evaluation (2025) · cites this paper as [30]
AI chatbots may lack the ability to comprehend human speech nuances and contextually deeper meanings.
“For example, AI chatbots may lack the ability to comprehend human speech nuances and contextually deeper meanings [30,34].”
From Consumer Responses to Generative AI Chatbots Versus Search Engines for Product Evaluation (2025) · cites this paper as [30]
Cites
Ray, P. P. (2023) · Internet of Things and Cyber-Physical Systems · doi:10.1016/j.iotcps.2023.04.003 · Cited by 2,463 · cited 1× · see citing works
“This study aims to deliver valuable understandings into maximizing the utility of ChatGPT while navigating its limitations in diverse applications, ultimately contributing to the ethical and effective integration of conversational AI in various domains (Radford et al., 2018; Ray, 2023).”
ChatGPT: five priorities for research
van Dis, E. A. M., Bollen, J., Zuidema, W., van Rooij, R., & Bockting, C. L. (2023) · Nature · doi:10.1038/d41586-023-00288-7 · Cited by 1,842 · cited 1× · see citing works
“In an era where users face information overload, the ability of ChatGPT to deliver up-to-date content contributes significantly to its perceived credibility (van Dis et al., 2023).”
Generative AI and ChatGPT: applications, challenges, and AI-human collaboration
Fui-Hoon Nah, F., Zheng, R., Cai, J., Siau, K., & Chen, L. (2023) · Journal of Information Technology Case and Application Research · doi:10.1080/15228053.2023.2233814 · Cited by 1,363 · see citing works
Lecler, A., Duron, L., & Soyer, P. (2023) · Diagnostic and Interventional Imaging · doi:10.1016/j.diii.2023.02.003 · Cited by 385 · cited 1× · see citing works
“This is particularly relevant in scientific fields, where the lack of nuance and context in texts generated by ChatGPT may be insufficient compared to texts produced by human experts (Lecler et al., 2023).”
Kim, J.-H., Kim, M., Park, M., & Yoo, J. (2023) · Telematics and Informatics · doi:10.1016/j.tele.2022.101936 · Cited by 188 · see citing works
Sison, A. J. G., Daza, M. T., Gozalo-Brizuela, R., & Garrido-Merchán, E. C. (2024) · International Journal of Human–Computer Interaction · doi:10.1080/10447318.2023.2225931 · Cited by 169 · see citing works
Khan, R., Gupta, N., Sinhababu, A., & Chakravarty, R. (2024) · Science & Technology Libraries · doi:10.1080/0194262x.2023.2254814 · Cited by 65 · see citing works
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Consumer Responses to Generative AI Chatbots Versus Search Engines for Product Evaluation
Kim, S., & Priluck, R. (2025) · Journal of Theoretical and Applied Electronic Commerce Research · doi:10.3390/jtaer20020093 · Cited by 20 · see citing works
“Ethical concerns have been raised with the use of ChatGPT, such as the potential negative impacts of AI chatbots on genuine human connections and interactions, privacy, and human ingenuity [30,35,37].”
- Authors
- Chakraborty, U., & Biswal, S. K.
- Affiliations
- Presidency University (IN)
- Rama Devi Women's University (IN)
- Corresponding author
- Chakraborty, Uttam
- Venue
- Journal of Promotion Management
- Publisher
- Informa UK Limited
- Published
- 2024-03-24
- Volume
- 30
- Issue
- 6
- Pages
- 929-958
- ISSN
- 1049-6491 (ISSN-L)
- 1540-7594
- OpenAlex
- W4393154444
- Cited by
- 24
- References
- 7
- Citations by year
- 2026: 12 · 2025: 11 · 2024: 1
- FWCI
- 3.54
- Type
- journal article
- Language
- en
- Open access
- closed
- Locations
- Journal of Promotion Management (publishedVersion)
- Topics
- Physical Sciences › Computer Science › Artificial Intelligence › AI in Service Interactions
- Social Sciences › Sociology and Political Science › Digital Marketing and Social Media
- Physical Sciences › Computer Science › Information Systems › Information Retrieval and Search Behavior
- Keywords
- ChatGPT, generative AI, AI chatbots, credibility, technology adoption, stimulus-organism-response model, dual-process theory, information quality, audience familiarity, social media
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