Exploring the Drivers of AI Adoption: A Meta-Analysis of Technological, Organizational and Environmental (TOE) Factors
| dc.contributor.author | Agostinho Sousa Pinto; António Abreu; Manuel Pérez Cota; Jerónimo Paiva | |
| dc.date.accessioned | 2026-08-31T11:01:35Z | |
| dc.date.available | 2026-08-31T11:01:35Z | |
| dc.date.issued | 2024-12-16 | |
| dc.description | Preprint / Systematic Review, 12 empirical studies were reviewed. | |
| dc.description.abstract | Abstract. The Artificial Intelligence (AI) revolution is transforming the corpo rate sector and rapidly accelerating the process of digital transformation. Based on a selection of 12 studies for meta-analysis with 3398 respondents from various industries and countries, this study investigates the factors influencing the adop tion of AI using the Technology-Organization-Environment (TOE) framework. The results show that seven out of eight TOE factors have a statistically signifi cant effect on AI adoption. Technological factors, including Compatibility (CPT) and Relative Advantage (ADV) have a positive impact, while Complexity (CX) was found to be statistically insignificant. Organizational factors, particularly Or ganizational Readiness (RE) and Management Support (MS) have a positive moderate effect. Environmental factors reveal that Government Support (GOV), Competitive Pressure (COP) and Vendor Partnership (VP) have a strong and pos itive impact. The study emphasizes the importance of Vendor Partnership and Organizational Readiness as critical factors in fostering AI adoption. Finally, this research will be advantageous for researchers and practitioners looking to explore the determinants driving significant AI adoption. | |
| dc.description.sponsorship | Agostinho Sousa Pinto; António Abreu; Manuel Pérez Cota; Jerónimo Paiva | |
| dc.identifier.citation | Pinto, A. S., Abreu, A., Cota, M. P., & Paiva, J. (2024). Exploring the drivers of AI adoption: A meta-analysis of technological, organizational and environmental (TOE) factors. Research Square. https://doi.org/10.21203/rs.3.rs-5634577/v1 | |
| dc.identifier.issn | 10.21203/rs.3.rs-5634577/v1 | |
| dc.identifier.uri | https://ir.funaab.edu.ng/handle/123456789/670 | |
| dc.language.iso | en | |
| dc.publisher | Springer Science and Business Media LLC (Springer Nature) | |
| dc.subject | Artificial Intelligence (AI) | |
| dc.subject | Generative AI (GenAI) | |
| dc.subject | Large Lan guage Model (LLM) | |
| dc.subject | TOE Framework | |
| dc.subject | Meta-Analysis | |
| dc.subject | PRISMA | |
| dc.title | Exploring the Drivers of AI Adoption: A Meta-Analysis of Technological, Organizational and Environmental (TOE) Factors | |
| dc.type | Article |
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