Measuring and Modelling the Adaptive Capacity of Universities: A Composite Indicators Methodology

Abstract

Initiating, implementing, and sustaining reforms are the most daunting and challenging aspects of change in higher education institutions. This research argues that to survive and thrive in a changing environment, adaptive capacity is fundamental. Thus, this study aims to serve two purposes. While the leading purpose was measuring the adaptive capacity of universities using a conceptual model developed based on literature review, introducing the critical components that determine adaptive capacity was secondary. Therefore, guided by a pragmatic approach this study has tried to maintain both subjective reflections and objective data during data collection and analysis. Accordingly, to attain the purpose of the study mixed research design particularly, a sequential explanatory approach was used. To gather relevant data from the target population, the questionnaire was distributed and 594 completed and useful questionnaires were returned from 133 leaders at different position, 268 academic staffs and 193 support staffs, which was a 62.06% response rate. Besides, 15 interviews and documents were reviewed. Finally, among the composite indicators approach, structural equation modeling (SEM) mainly principal least square path modeling (PLS-PM) was used to measure and analyze adaptive capacity using XLSTAT software. As a result, the adaptive capacity of universities was found unsatisfactory i.e. lower than moderate. This indicates universities might not fully implement the change ideas they wish to introduce into their system. Consequently, the identified gaps and challenges in the studied universities strengthen the argument for the need to assess universities adaptive capacity using a model and make appropriate intervention before struggling to introduce any change initiative without a fertile ground.