Modelling the enablers of sustainability in higher education institutions

Abstract

Purpose

The purpose of this paper is to explore and encapsulate the enablers that can facilitate education for sustainable development in higher education (HE). The study also aims to understand the interdependence between the enablers.

Design/methodology/approach

The study adopts the total interpretive structural modelling approach to comprehend the interaction and transitivity between the enablers. Cross-impact multiplication matrix analysis was applied to rank the enablers and classify them on the basis of the driving and dependence power into dependent, autonomous, independent and linkage enablers.

Findings

An extensive literature review and expert opinion helped in identifying 10 enablers that can promote sustainability in higher education. The structural model revealed government policies, media, accreditation/sustainability audit, sustainability leadership and institutional commitment as the crucial enablers that can drive sustainability and activate the enablers with high dependence and low driving power.

Practical implications

The results of this study will assist the policymakers and management of universities and colleges in understanding important factors that can facilitate sustainability in higher education. Universities and colleges to incorporate sustainability in their system need to transform not only the core higher education activities of learning and teaching, research and engagement, also the way the colleges operate its culture, governance, structure and how it supports the staff and students.

Originality/value

So far, research on sustainability in higher education has looked into each factor in isolation. This research provides a comprehensive view of the factors and has attempted to establish a multidirectional interplay between factors facilitating sustainability in higher education (SHE).

Citation

Menon, S. and Suresh, M. (2022), "Modelling the enablers of sustainability in higher education institutions", Journal of Modelling in Management, Vol. 17 No. 2, pp. 405-439. https://doi.org/10.1108/JM2-07-2019-0169