Exploring the Factors Influencing AI Adoption Intentions in Higher Education: An Integrated Model of DOI, TOE, and TAM
This study investigates the primary technological and socio-environmental factors influencing the adoption intentions of AI-powered technology at the corporate level within higher education institutions. A conceptual model based on the Diffusion of Innovation Theory (DOI), the Technology–Organizatio...
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| Format: | Article |
| Language: | English |
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MDPI AG
2025-06-01
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| Series: | Computers |
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| Online Access: | https://www.mdpi.com/2073-431X/14/6/230 |
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| author | Rawan N. Abulail Omar N. Badran Mohammad A. Shkoukani Fandi Omeish |
| author_facet | Rawan N. Abulail Omar N. Badran Mohammad A. Shkoukani Fandi Omeish |
| author_sort | Rawan N. Abulail |
| collection | DOAJ |
| description | This study investigates the primary technological and socio-environmental factors influencing the adoption intentions of AI-powered technology at the corporate level within higher education institutions. A conceptual model based on the Diffusion of Innovation Theory (DOI), the Technology–Organization–Environment (TOE), and the Technology Acceptance Model (TAM) combined framework were proposed and tested using data collected from 367 higher education students, faculty members, and employees. SPSS Amos 24 was used for CB-SEM to choose the best-fitting model, which proved more efficient than traditional multiple regression analysis to examine the relationships among the proposed constructs, ensuring model fit and statistical robustness. The findings reveal that Compatibility “C”, Complexity “CX”, User Interface “UX”, Perceived Ease of Use “PEOU”, User Satisfaction “US”, Performance Expectation “PE”, Artificial intelligence “AI” introducing new tools “AINT”, AI Strategic Alignment “AIS”, Availability of Resources “AVR”, Technological Support “TS”, and Facilitating Conditions “FC” significantly impact AI adoption intentions. At the same time, Competitive Pressure “COP” and Government Regulations “GOR” do not. Demographic factors, including major and years of experience, moderated these associations, and there were large differences across educational backgrounds and experience. |
| format | Article |
| id | doaj-art-a9ee2a72ecb14061965d92e7f392dfa4 |
| institution | Kabale University |
| issn | 2073-431X |
| language | English |
| publishDate | 2025-06-01 |
| publisher | MDPI AG |
| record_format | Article |
| series | Computers |
| spelling | doaj-art-a9ee2a72ecb14061965d92e7f392dfa42025-08-20T03:27:18ZengMDPI AGComputers2073-431X2025-06-0114623010.3390/computers14060230Exploring the Factors Influencing AI Adoption Intentions in Higher Education: An Integrated Model of DOI, TOE, and TAMRawan N. Abulail0Omar N. Badran1Mohammad A. Shkoukani2Fandi Omeish3Department of Computer Science, Philadelphia University, Amman 19392, JordanDepartment of Business Management, Istanbul Aydin University, Istanbul 34295, TürkiyeDepartment of Computer Science, Applied Science Private University, Amman 11931, JordanDepartment of E-Marketing and Social Media, Princess Sumaya University for Technology, Amman 11941, JordanThis study investigates the primary technological and socio-environmental factors influencing the adoption intentions of AI-powered technology at the corporate level within higher education institutions. A conceptual model based on the Diffusion of Innovation Theory (DOI), the Technology–Organization–Environment (TOE), and the Technology Acceptance Model (TAM) combined framework were proposed and tested using data collected from 367 higher education students, faculty members, and employees. SPSS Amos 24 was used for CB-SEM to choose the best-fitting model, which proved more efficient than traditional multiple regression analysis to examine the relationships among the proposed constructs, ensuring model fit and statistical robustness. The findings reveal that Compatibility “C”, Complexity “CX”, User Interface “UX”, Perceived Ease of Use “PEOU”, User Satisfaction “US”, Performance Expectation “PE”, Artificial intelligence “AI” introducing new tools “AINT”, AI Strategic Alignment “AIS”, Availability of Resources “AVR”, Technological Support “TS”, and Facilitating Conditions “FC” significantly impact AI adoption intentions. At the same time, Competitive Pressure “COP” and Government Regulations “GOR” do not. Demographic factors, including major and years of experience, moderated these associations, and there were large differences across educational backgrounds and experience.https://www.mdpi.com/2073-431X/14/6/230AI adoptiondiffusion of innovation theory (DOI)higher educationstructural equation modeling (SEM)technology–organization–environment (TOE) frameworktechnology acceptance model (TAM) |
| spellingShingle | Rawan N. Abulail Omar N. Badran Mohammad A. Shkoukani Fandi Omeish Exploring the Factors Influencing AI Adoption Intentions in Higher Education: An Integrated Model of DOI, TOE, and TAM Computers AI adoption diffusion of innovation theory (DOI) higher education structural equation modeling (SEM) technology–organization–environment (TOE) framework technology acceptance model (TAM) |
| title | Exploring the Factors Influencing AI Adoption Intentions in Higher Education: An Integrated Model of DOI, TOE, and TAM |
| title_full | Exploring the Factors Influencing AI Adoption Intentions in Higher Education: An Integrated Model of DOI, TOE, and TAM |
| title_fullStr | Exploring the Factors Influencing AI Adoption Intentions in Higher Education: An Integrated Model of DOI, TOE, and TAM |
| title_full_unstemmed | Exploring the Factors Influencing AI Adoption Intentions in Higher Education: An Integrated Model of DOI, TOE, and TAM |
| title_short | Exploring the Factors Influencing AI Adoption Intentions in Higher Education: An Integrated Model of DOI, TOE, and TAM |
| title_sort | exploring the factors influencing ai adoption intentions in higher education an integrated model of doi toe and tam |
| topic | AI adoption diffusion of innovation theory (DOI) higher education structural equation modeling (SEM) technology–organization–environment (TOE) framework technology acceptance model (TAM) |
| url | https://www.mdpi.com/2073-431X/14/6/230 |
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