Hierarchical modeling of cooling system failure drivers in Saudi Arabian schools using an integrated RII-ISM method

This study examines the principal drivers of cooling system failures in Saudi Arabian schools and their interrelationships over the project life cycle. A literature review identified 26 drivers, which were categorized into five phases: programming, design, construction and installation, commissioning, and operation and maintenance. A questionnaire survey targeting 90 stakeholders, including HVAC designers, facilities managers, and HVAC contractors, was conducted to assess the importance of these drivers using the Relative Importance Index (RII). Stakeholder agreement was examined using Spearman’s rank correlation. The study adopts an integrated mixed-methods framework that combines the RII with Interpretive Structural Modelling (ISM). RII is first used to determine the ranks of the identified drivers upon their relative importance. The highest-ranked drivers are then analysed using ISM to develop a hierarchical model. The RII–ISM integration provides a structured pathway from importance ranking to causal modelling, enabling the identification of fundamental driving drivers and their cascading effects across the system. The findings indicate that “Insufficient budget for design, supply, and installation” is the most influential driver affecting cooling system failures, followed by “Insufficient expertise within the design team” and “Inappropriate equipment specifications”. The results demonstrate that cooling system failures arise not from isolated issues but from interconnected technical, financial, and managerial drivers spanning multiple project phases. The study contributes methodologically by demonstrating the value of integrating RII with ISM as a hierarchical mixed-methods framework for analysing complex infrastructure failures. It also offers practical mitigation strategies to support improved design, installation, and maintenance practices. These insights can assist HVAC professionals, facilities managers, and policymakers in optimizing resource allocation, improving system reliability, and enhancing indoor learning environments in regions with extreme climatic conditions.