Comprehensive Risk Analysis for the Self-Evaluation Process of Higher Education Institutions in Ecuador

Abstract

Institutional self-evaluation in Ecuadorian Higher Education Institutions (HEIs) is a key process for continuous improvement and accreditation. However, it is exposed to operational risks that may compromise the validity and reliability of its results. To address this issue, a hybrid methodology is proposed, combining Fuzzy Cognitive Maps (FCM), the Analytic Hierarchy Process (AHP), and the TOPSIS technique to conduct a comprehensive risk analysis and prioritize mitigation strategies. Through FCM, seven critical factors were identified: governance, data quality, staff training, process documentation, student participation, technological infrastructure, and external auditing. The influence matrix revealed that governance plays a central role, significantly impacting auditing, institutional processes, and infrastructure. Simulations showed high organizational stability, even under specific interventions, indicating a mature structure within the analyzed HEIs. Using AHP, four key evaluation criteria were weighted, with governance emerging as the most relevant (0.5424). Subsequently, TOPSIS was applied to rank three mitigation strategies, with the political-organizational approach being the closest to the ideal solution (0.6794), outperforming technological and training-based alternatives.

The results suggest that strengthening institutional structures and internal policies has a greater impact than investing solely in technology. The proposed framework offers a replicable and practical tool to enhance risk management in self-evaluation processes within Ecuadorian HEIs.