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• Novel Integration of Cloud Model Theory and DEMATEL in the field of Public Procurement The study pioneers the combined use of Cloud Model Theory (to handle fuzzy human judgments) and DEMATEL (to analyze causal relationships) in public procurement. This hybrid approach addresses subjectivity in expert evaluations and quantifies interdependencies among efficiency factors, offering a robust methodological framework for decision-making. • Identification and Ranking of 28 Critical Efficiency Factors The research identifies 28 key factors (e.g., Weak Procedures, award mechanism) specific to "Goods" procurement, categorizing them into cause-effect groups (e.g., "Rigid Policies" as a cause vs. "Missing Objectives" as an effect). This granular analysis helps prioritize interventions. • D ata-Driven Policy and DSS Design The results provide actionable insights for policymakers to streamline procurement processes (e.g., reducing delays and improving transparency) and for practitioners to design Decision Support Systems (DSS) that incorporate top-ranked factors (e.g., award mechanisms and bureaucratic inefficiencies) for optimal efficiency. • Empirical Validation with Expert Input The methodology is grounded in real-world expert judgments (from government procurement agencies), ensuring practical relevance. Participant weights are assigned based on seniority and experience, enhancing the reliability of the causal analysis. Also reliability and validity tests are done with comparative analysis to prove that method is highly efficient and effective • Strategic Implications for SDGs and Public Governance By linking procurement efficiency to broader goals like the UN Sustainable Development Goals (SDGs) and socio-economic growth, the study underscores how optimized procurement can mitigate risks (e.g., cost overruns, inferior quality) and align with national policy agendas. The public goods procurement is an essential but intricate process, hindered by inefficiencies like cost overruns, delays, and mismanagement. Although previous studies have investigated procurement issues, a notable deficiency exists in the causal analysis of efficiency factors—especially in goods procurement—where interdependencies are insufficiently considered. This work addresses this gap by integrating Cloud Model Theory with DEMATEL, representing the first application of this hybrid methodology in procurement research. The Cloud Model encapsulates linguistic ambiguity in expert assessments, whereas DEMATEL quantifies causal interrelations among 28 identified variables. Key findings indicate that "Award Mechanism" (F22) and "Weak Procedure" (F3) are the most significant causal factors, leading to substantial effects such as "Missing Objectives" (F10) and "Cost Increase" (F1). The comparative analysis across several perturbed rankings shows remarkable consistency with more than 96% stability, 0.9 Spearman’s rank correlation, and a coefficient of Variation well below 2%. The study’s methodological innovation and empirical findings provide a robust foundation for dynamic decision-support systems in public procurement. The results indicated a very high level of agreement among the experts, exhibiting Kendall’s coefficient (W = 0.911), and Cronbach’s Alpha (α = 0.993), which demonstrates excellent reliability, well above the 0.9 threshold. The study’s methodological innovation, reliability, and validity provide a robust foundation for dynamic decision-support systems in public procurement. The empirical findings will aid policymakers and public procurement managers in addressing critical gaps in the public goods procurement process.
Khan et al. (Wed,) studied this question.