University Students' ChatGPT Adoption Driven More by the People Around Them Than by Performance
An analysis of 233 university students finds that accessibility, responsiveness, and network quality raise satisfaction, while social influence has the largest effect on adoption intention — published in the international journal Scientific Reports
A study analyzing why university students adopt ChatGPT has been published in Scientific Reports (SCIE), an international journal from Nature Portfolio. The research was conducted jointly by researchers at the HJ Institute of Technology and Management (HJITM) and Professor Youngsok Bang of the Yonsei University School of Business, with Professor Bang serving as corresponding author.
The researchers proposed the TOEK model, which adds 'knowledge application' to the technology–organization–environment (TOE) framework used to explain corporate technology adoption, and analyzed responses from 233 Korean university students using structural equation modeling. They examined how technological factors such as network quality, accessibility, and system responsiveness, along with the school's organizational culture, social influence from peers, and the degree to which students actually apply knowledge gained from ChatGPT, affect satisfaction and adoption intention.
The analysis showed that accessibility (β=0.399) had the greatest effect on satisfaction, with system responsiveness (β=0.226) and network quality (β=0.159) also significant. In other words, being easy to use anytime, anywhere matters as much as performance in shaping satisfaction.
The factor with the greatest influence on adoption intention was social influence from friends, colleagues, and others nearby (β=0.511). Knowledge application (β=0.160), satisfaction (β=0.157), and organizational culture (β=0.156) also significantly raised adoption intention. Demographic variables such as gender, age, education, and income had no significant effect.
The study is notable for extending a firm-level technology adoption theory to university students' adoption of generative AI. It suggests that universities seeking to spread the use of generative AI can do so effectively by ensuring a stable access environment while building a culture that shares on-campus use cases and encourages knowledge application in class.
HJITM continues to conduct joint research with scholars in Korea and abroad on the use of generative AI in education.
Key findings
- Accessibility (β=0.399), system responsiveness (β=0.226), network quality (β=0.159) → satisfaction
- Social influence (β=0.511) → largest effect on adoption intention
- Knowledge application (β=0.160), satisfaction (β=0.157), organizational culture (β=0.156) → adoption intention
- Demographic variables have no effect · N=233
- Paper
- Analyzing ChatGPT adoption drivers with the TOEK framework
- Authors
- Hyeon Jo, Youngsok Bang
- Journal
- Scientific Reports (Springer Nature, SCIE), Vol. 13, 22606, 2023
- DOI
- 10.1038/s41598-023-49710-0
- Cite
- Hyeon Jo, Youngsok Bang (2023). Analyzing ChatGPT adoption drivers with the TOEK framework. Scientific Reports, 13, 22606.
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