Root Cause of Cost Overrun Risks in Public Sector Social Housing Programs in SIDS: Fuzzy Synthetic Evaluation

AbstractCost overruns (COs) in public sector social housing programs (PSSHPs) will continue unabated without immediate intervention to resolve the ad hoc amalgamation of root cause ontologies. This study applied a fuzzy synthetic evaluation (FSE) multicriteria decision support model to evaluate and prioritize the overall cost overrun risk in PSSHPs. In a Caribbean Small Island Developing State (SIDS) context, a questionnaire survey measuring 41 perceived critical risk factors (CRFs) was used to derive the risk impact and normalized impact values from 150 professional participants. Twenty-two normalized CRFs and four principal risk groups’ (PRGs) membership functions were determined using fuzzy synthetic knowledge-based inference procedures. Politically linked contractors and intentionally inferior building contracts caused most PSSHP cost overruns. The FSE risk model reveals that political PRG is the major root cause of COs, followed by socioeconomic, technical, and psychological PRGs. The study found that the overall risk level (ORL) of PSSHPs is high, meaning that government investment in public housing is a high-risk endeavor and ill-informed choices could lead to “wicked” social problems. Defuzzifying cost risks provided deeper insights into the nature and scope of the risk and related management implications that lead to unsustainable decision-making practices and provide opportunities for adequate control strategies to maintain economic viability. This research evidenced the fusion of different CO ontologies and raises awareness of the hidden political risk factors that should be prioritized to achieve sustainable PSSHP decision-making practices. Practical ApplicationsThis study adds to the PSSHP’s cost overrun knowledge by merging known root causes and criticalities into a practical risk model that gives empirical risk values at several tiers, from individual critical factors to root causes and the overall risk assessment. Many theories and ontologies explain CO causes (e.g., political root causes grounded on agency theory and relativism ontology, psychological root causes based on prospect theory and relativism ontology, and economic root causes based on transaction cost theory and realism ontology). Subjectivity and a growing divide between top researchers and practitioners result from the ad hoc amalgamation of these ontologies. The study expands the theoretical foundations of CO research by tackling the ontological issues through a structured, m