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Analyzing behavioral intentions toward Generative Artificial Intelligence: the case of ChatGPT

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Abstract

Generative artificial intelligence (AI) is an innovative AI technology that has garnered considerable attention worldwide. This study aimed to facilitate the development of such technologies by examining the factors affecting individuals’ intentions toward generative AI (e.g., ChatGPT). Concretely, we developed a causal model by extending the expectation confirmation model with information system success theory, privacy concerns, and perceived innovativeness. Then, we tested the model by analyzing survey-based data from 252 Korean ChatGPT users. As a result, we found that antecedent variables -information quality, system quality, privacy concerns, and perceived innovativeness- play notable roles in affecting users’ intentions to continually use and recommend generative AI ChatGPT. Overall, the current research is one of the first attempts to track the variables influencing individuals’ intentions to continually use and recommend in the context of generative AI ChatGPT.

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Funding

This work was supported by a National Research Foundation of Korea (NRF) grant funded by the Korean government (RS-2023-00208278).

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Authors and Affiliations

  1. Department of Human-Artificial Intelligence Interaction, Sungkyunkwan University, Seoul, Korea

    Dongyan Nan, Shunan Zhang, Xiangying Zhao & Jang Hyun Kim

  2. Department of Interaction Science, Sungkyunkwan University, Seoul, Korea

    Dongyan Nan, Shunan Zhang, Xiangying Zhao & Jang Hyun Kim

  3. Department of Applied Artificial Intelligence, Sungkyunkwan University, Seoul, Korea

    Seungjong Sun & Jang Hyun Kim

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  1. Dongyan Nan
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Contributions

Dongyan Nan: Conceptualization, Methodology, Formal analysis, Writing – original draft, Writing – review & editingSeungjong Sun: Methodology, Formal analysisShunan Zhang: Writing – original draftXiangying Zhao: Writing – review & editing Jang Hyun Kim: Conceptualization, Methodology, Supervision, Project administration, Writing – original draft.

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Correspondence to Jang Hyun Kim.

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This study was reviewed and approved by the Internal Review Board (IRB) of Sungkyunkwan University. Informed consent was obtained from all human participants included in the study before they participated in the survey.

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Nan, D., Sun, S., Zhang, S. et al. Analyzing behavioral intentions toward Generative Artificial Intelligence: the case of ChatGPT. Univ Access Inf Soc 24, 885–895 (2025). https://doi.org/10.1007/s10209-024-01116-z

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