Article: AI in sustainable higher education: an interpretive structural model and MICMAC approach Journal: International Journal of Business and Globalisation (IJBG) 2026 Vol.42 No.1 pp.1 - 22 Abstract: Integrating artificial intelligence (AI) in sustainable higher education practices prove to be beneficial in the teaching and learning process of institutions. With the many probable practices which promote sustainability in higher education, stakeholders must be able to proactively prioritise practices given the lack of resources for the full-blown implementation of sustainable higher education practices. Along this line, this paper employs interpretive structural modelling (ISM) with MICMAC analysis to generate a framework for stakeholders to use in prioritising such practices. A real-life case study in a state university in the Philippines is conducted to understand how AI is integrated in sustainable higher education. Interestingly, the framework points out data collection monitoring systems as the core practice to be tackled by educational institutions. Inderscience Publishers - linking academia, business and industry through research

Title: AI in sustainable higher education: an interpretive structural model and MICMAC approach

Authors: Irene O. Mamites; Jose Maria S. Garcia II; Gibe S. Tirol; Nelson F. Nolon; Joy M. Olarte; Ulysis D. Malait; Melanie M. Himang

Addresses: College of Education, Cebu Technological University, Main Campus, Cebu, Philippines ' College of Computer, Information and Communications Technology, Cebu Technological University, Main Campus, Cebu, Philippines ' College of Computer, Information and Communications Technology, Cebu Technological University, Main Campus, Cebu, Philippines ' College of Technology, Cebu Technological University, Dumanjug Extension Campus, Philippines ' Department of Education, Leyte Division, Region VIII, Leyte, Philippines ' College of Education, Cebu Technological University, Cebu City Mountain Satellite Campus, Cebu, Philippines ' College of Computer, Information and Communications Technology, Cebu Technological University, Main Campus, Cebu, Philippines

Abstract: Integrating artificial intelligence (AI) in sustainable higher education practices prove to be beneficial in the teaching and learning process of institutions. With the many probable practices which promote sustainability in higher education, stakeholders must be able to proactively prioritise practices given the lack of resources for the full-blown implementation of sustainable higher education practices. Along this line, this paper employs interpretive structural modelling (ISM) with MICMAC analysis to generate a framework for stakeholders to use in prioritising such practices. A real-life case study in a state university in the Philippines is conducted to understand how AI is integrated in sustainable higher education. Interestingly, the framework points out data collection monitoring systems as the core practice to be tackled by educational institutions.

Keywords: artificial intelligence; sustainable higher education; interpretive structural modelling; ISM; MICMAC analysis; state university.

DOI: 10.1504/IJBG.2026.151997

International Journal of Business and Globalisation, 2026 Vol.42 No.1, pp.1 - 22

Received: 14 Dec 2024
Accepted: 06 Sep 2025
Published online: 02 Mar 2026 *

Title: AI in sustainable higher education: an interpretive structural model and MICMAC approach

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