GFS Modelling Organisational Behaviour and Change Management Effects on MIS Implementation Success

DOI

https://www.doi.org/10.59256/ijire.20250606006

Published In

Volume 6, Issue 6 (2025)

Published Online

November-December 2025

Pages

28-42

Article Type

Original Article

Check for updates

This study investigates the role of organisational behaviour and change management in the successful implementation of Management Information Systems (MIS) for Outcome-Based Education (OBE) evaluation in higher education institutions. A structured survey was administered across 56 colleges that had adopted MIS for OBE evaluation, with a focus on key organisational and behavioural determinants influencing system effectiveness. To model the complex and interdependent relationships among these factors, a Genetic Fuzzy System (GFS) was developed by embedding expert knowledge within fuzzy logic rules and optimising them using a genetic algorithm. The proposed GFS consisted of six Single Input Multiple Output (SIMO) fuzzy models and was rigorously tested and validated, achieving a Root Mean Square Error of 0.1182 after 150 generations. The findings reveal that Leadership and Management Support (LMS) is the most influential factor, contributing 79% to successful MIS adoption and user satisfaction. Communication and Cultural Norms (CCN) were found to account for 70% of effective MIS utilisation, while Utilisation of Change Management (UCM) had a significant impact on the Time Taken for Adoption (TTA), influencing outcomes by 47%. While the study is limited to higher education institutions within a specific regional context, potentially affecting the generalisability of the results, it offers valuable insights for future cross-regional or sectoral validation. Practically, the study provides actionable guidance for academic institutions aiming to enhance MIS-based OBE evaluation by emphasising strong leadership commitment, transparent communication, and systematic change management practices. The originality of this work lies in its integration of organisational behaviour and change management variables into MIS adoption research using a genetic fuzzy modelling approach, thereby presenting a novel decision-support framework that effectively bridges behavioural dynamics with technological implementation.