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Drivers of generative AI adoption in higher education through the lens of the Theory of Planned Behaviour
Open accessAbstract
Drawing on the Theory of Planned Behaviour (TPB), this study investigates the relationship between the perceived benefits, strengths, weaknesses, and risks of generative AI (GenAI) tools and the fundamental factors of the TPB model (i.e., attitude, subjective norms, and perceived behavioural control). The study also investigates the structural association between the TPB variables and intention to use GenAI tools, and how the latter might affect the actual usage of GenAI tools in higher education. The paper adopts a quantitative approach, relying on an anonymous self-administered online questionnaire to gather primary data from 130 lecturers and 168 students in higher education institutions (HEIs) in several countries, and PLS-SEM for data analysis. The results indicate that although lecturers' and students' perceptions of the risks and weaknesses of GenAI tools differ, the perceived strengths and advantages of GenAI technologies have a significant and positive impact on their attitudes, subjective norms, and perceived behavioural control. The TPB core variables positively and significantly impact lecturers' and students’ intentions to use GenAI tools, which in turn significantly and positively impact their adoption of such tools. This paper advances theory by outlining the factors shaping the adoption of GenAI technologies in HEIs. It provides stakeholders with a variety of managerial and policy implications for how to formulate suitable rules and regulations to utilise the…
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In the citing paper
“However, the challenges introduced by generative AI require further exploration within this framework (Ivanov et al. 2024).”
From Addressing student non-compliance in AI use declarations: implications for academic integrity and assessment in higher education (2025) · cites this paper as Ivanov et al. 2024
In the citing paper
“In line with prior research, findings of this study reveal that the influence of subjective norms, particularly the pressure to conform to peer behaviours and group norms, influences academic integrity behaviours (Asch 1951; McCabe and Trevino 1993; Ivanov et al. 2024).”
From Addressing student non-compliance in AI use declarations: implications for academic integrity and assessment in higher education (2025) · cites this paper as Ivanov et al. 2024
In the citing paper
“Similarly, Ivanov et al. (2024) showed that when non-declaration of AI use is common within a peer group, students are less likely to comply with declaration requirements, reflecting how subjective norms influence academic dishonesty (Stone, Jawahar, and Kisamore 2009).”
From Addressing student non-compliance in AI use declarations: implications for academic integrity and assessment in higher education (2025) · cites this paper as Ivanov et al. 2024
In the citing paper
“Perceived behavioral control is a construct of the Theory of Planned Behavior and has been found to be statistically significant in the intention to use AI among program designers and higher educators (Ivanov et al., 2024;Jiao & Cao, 2024).”
From Into the Unknown: AI Adoption and Job Satisfaction of Christian Faculty (2026) · cites this paper as Ivanov et al., 2024
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Metadata
- Authors
- Ivanov, S., Soliman, M., Tuomi, A., Alkathiri, N. A., & Al-Alawi, A. N.
- Affiliations
- Varna University of Management (BG)
- University of Technology and Applied Sciences-Salalah (OM)
- Haaga-Helia University of Applied Sciences (FI)
- University of Technology and Applied Sciences — Ibri (OM)
- Corresponding author
- Ivanov, Stanislav
- Venue
- Technology in Society
- Publisher
- Elsevier BV
- Published
- 2024-06
- Volume
- 77
- Pages
- 102521
- ISSN
- 0160-791X (ISSN-L)
- OpenAlex
- W4393149408
- Cited by
- 397
- References
- 59
- Citations by year
- 2026: 168 · 2025: 186 · 2024: 43
- FWCI
- 148.15
- Type
- journal article
- Language
- en
- Open access
- hybrid
- doi.org
- Licence
- Locations
- Technology in Society (publishedVersion, cc-by)
- Theseus (Ammattikorkeakoulujen) (submittedVersion, cc-by)
- RePEc: Research Papers in Economics (submittedVersion)
- Topics
- Social Sciences › Decision Sciences › Information Systems and Management › Technology Adoption and User Behaviour
- Social Sciences › Education › Artificial Intelligence in Education
- Health Sciences › Medicine › Health Informatics › Artificial Intelligence in Healthcare and Education
- Keywords
- generative AI adoption, higher education, theory of planned behavior, perceived benefits, risk perception, attitudes, subjective norms, perceived behavioral control, intention to use, lecturers, students, AI regulation
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