EL Essawi, Nermine. (2024). The Impact of Barriers and Drivers of AI Technology Utilization on Adoption of AI through Educational Institutions’ Readiness: A Case Study of the Arab Academy for Science, Technology, and Maritime Transport. مجلة جامعة الإسکندرية للعلوم الإدارية, 61(5), 213-253. doi: 10.21608/acj.2024.379188
Nermine EL Essawi. "The Impact of Barriers and Drivers of AI Technology Utilization on Adoption of AI through Educational Institutions’ Readiness: A Case Study of the Arab Academy for Science, Technology, and Maritime Transport". مجلة جامعة الإسکندرية للعلوم الإدارية, 61, 5, 2024, 213-253. doi: 10.21608/acj.2024.379188
EL Essawi, Nermine. (2024). 'The Impact of Barriers and Drivers of AI Technology Utilization on Adoption of AI through Educational Institutions’ Readiness: A Case Study of the Arab Academy for Science, Technology, and Maritime Transport', مجلة جامعة الإسکندرية للعلوم الإدارية, 61(5), pp. 213-253. doi: 10.21608/acj.2024.379188
EL Essawi, Nermine. The Impact of Barriers and Drivers of AI Technology Utilization on Adoption of AI through Educational Institutions’ Readiness: A Case Study of the Arab Academy for Science, Technology, and Maritime Transport. مجلة جامعة الإسکندرية للعلوم الإدارية, 2024; 61(5): 213-253. doi: 10.21608/acj.2024.379188
The Impact of Barriers and Drivers of AI Technology Utilization on Adoption of AI through Educational Institutions’ Readiness: A Case Study of the Arab Academy for Science, Technology, and Maritime Transport
اAssociate Professor Business Information Systems College of Management &Technology
المستخلص
The current study aims to explore how barriers to using AI technologies—such as economic barriers, organizational and managerial barriers, and technological barriers—and drivers of using AI technologies—such as institutional efficiency, R&D sector improvement, and immediate feedback loops—affect the adoption of AI in higher education institutions through the mediating role of educational institutions' readiness, which includes financial, technological, staff, and processes and operations readiness. Utilizing a positivist philosophy with a quantitative analysis approach, the researcher collected primary data via a questionnaire administered to faculty members and students at the Arab Academy for Maritime Transport, Science, and Technology in Alexandria. The findings indicate that both obstacles and motivators significantly impact educational institutions' readiness and the adoption of AI in higher education. Economic, organizational, and technological barriers were found to positively influence readiness, as did motivators such as enhancing institutional efficiency, improving R&D sectors, and establishing immediate feedback loops. Additionally, readiness within educational institutions was shown to positively affect AI adoption. Finally, Staff Readiness partially mediates Economic Barriers, Institutional Efficiency, and AI Adoption, fully mediating R&D Sector Improvement and Immediate Feedback Loop impacts. Processes and Operations Readiness partially mediates Economic and Organizational Barriers, Institutional Efficiency, and AI Adoption, fully mediating R&D Sector Improvement and Immediate Feedback Loop effects. The study suggests that policymakers should address barriers to AI adoption while enhancing readiness through strategic investments, policy development, collaboration promotion, and support for research and development initiatives.
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