Analyzing ChatGPT adoption drivers with the TOEK framework
Abstract With the rapid advancements in AI technology and its growing impact on various aspects of daily life, understanding the factors that influence users' adoption intention becomes essential. This study focuses on the determinants affecting the adoption intention of ChatGPT, an AI-driven l...
| Main Authors: | , |
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| Format: | Article |
| Language: | English |
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Nature Portfolio
2023-12-01
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| Series: | Scientific Reports |
| Online Access: | https://doi.org/10.1038/s41598-023-49710-0 |
| _version_ | 1797376957646635008 |
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| author | Hyeon Jo Youngsok Bang |
| author_facet | Hyeon Jo Youngsok Bang |
| author_sort | Hyeon Jo |
| collection | DOAJ |
| description | Abstract With the rapid advancements in AI technology and its growing impact on various aspects of daily life, understanding the factors that influence users' adoption intention becomes essential. This study focuses on the determinants affecting the adoption intention of ChatGPT, an AI-driven language model, among university students. The research extends the Technology-Organization-Environment (TOE) framework by integrating the concept of knowledge application. A cross-sectional research design was employed, gathering data through a survey conducted to university students. Structural equation modeling was used to analyze the data, aimed at examining the relationships between key determinants influencing adoption intention. The findings of this research indicate that factors such as network quality, accessibility, and system responsiveness contribute to satisfaction. Furthermore, satisfaction, organizational culture, social influence, and knowledge application significantly affect adoption intention. These findings offer both theoretical and practical implications. |
| first_indexed | 2024-03-08T19:47:03Z |
| format | Article |
| id | doaj.art-15f3fc4825e145178f686ce4efbbaaa7 |
| institution | Directory Open Access Journal |
| issn | 2045-2322 |
| language | English |
| last_indexed | 2024-03-08T19:47:03Z |
| publishDate | 2023-12-01 |
| publisher | Nature Portfolio |
| record_format | Article |
| series | Scientific Reports |
| spelling | doaj.art-15f3fc4825e145178f686ce4efbbaaa72023-12-24T12:18:12ZengNature PortfolioScientific Reports2045-23222023-12-0113111710.1038/s41598-023-49710-0Analyzing ChatGPT adoption drivers with the TOEK frameworkHyeon Jo0Youngsok Bang1Headquarters, HJ Institute of Technology and ManagementSchool of Business, Yonsei UniversityAbstract With the rapid advancements in AI technology and its growing impact on various aspects of daily life, understanding the factors that influence users' adoption intention becomes essential. This study focuses on the determinants affecting the adoption intention of ChatGPT, an AI-driven language model, among university students. The research extends the Technology-Organization-Environment (TOE) framework by integrating the concept of knowledge application. A cross-sectional research design was employed, gathering data through a survey conducted to university students. Structural equation modeling was used to analyze the data, aimed at examining the relationships between key determinants influencing adoption intention. The findings of this research indicate that factors such as network quality, accessibility, and system responsiveness contribute to satisfaction. Furthermore, satisfaction, organizational culture, social influence, and knowledge application significantly affect adoption intention. These findings offer both theoretical and practical implications.https://doi.org/10.1038/s41598-023-49710-0 |
| spellingShingle | Hyeon Jo Youngsok Bang Analyzing ChatGPT adoption drivers with the TOEK framework Scientific Reports |
| title | Analyzing ChatGPT adoption drivers with the TOEK framework |
| title_full | Analyzing ChatGPT adoption drivers with the TOEK framework |
| title_fullStr | Analyzing ChatGPT adoption drivers with the TOEK framework |
| title_full_unstemmed | Analyzing ChatGPT adoption drivers with the TOEK framework |
| title_short | Analyzing ChatGPT adoption drivers with the TOEK framework |
| title_sort | analyzing chatgpt adoption drivers with the toek framework |
| url | https://doi.org/10.1038/s41598-023-49710-0 |
| work_keys_str_mv | AT hyeonjo analyzingchatgptadoptiondriverswiththetoekframework AT youngsokbang analyzingchatgptadoptiondriverswiththetoekframework |