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...

Full description

Saved in:
Bibliographic Details
Main Authors: Rawan N. Abulail, Omar N. Badran, Mohammad A. Shkoukani, Fandi Omeish
Format: Article
Language:English
Published: MDPI AG 2025-06-01
Series:Computers
Subjects:
Online Access:https://www.mdpi.com/2073-431X/14/6/230
Tags: Add Tag
No Tags, Be the first to tag this record!
_version_ 1849432678232752128
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
work_keys_str_mv AT rawannabulail exploringthefactorsinfluencingaiadoptionintentionsinhighereducationanintegratedmodelofdoitoeandtam
AT omarnbadran exploringthefactorsinfluencingaiadoptionintentionsinhighereducationanintegratedmodelofdoitoeandtam
AT mohammadashkoukani exploringthefactorsinfluencingaiadoptionintentionsinhighereducationanintegratedmodelofdoitoeandtam
AT fandiomeish exploringthefactorsinfluencingaiadoptionintentionsinhighereducationanintegratedmodelofdoitoeandtam