Evaluating Smart City Using the Fuzzy-Bwm Decision-Making Framework

Smart city initiatives have become pivotal in guiding local governments toward sustainable and technology-driven urban development. Many small cities in developing countries struggle to assess their smart city initiatives systematically, making it urgent to adopt robust evaluation frameworks. This paper evaluates and ranks the smart city pillars and indicators of Mojokerto Regency, Indonesia, using the Fuzzy Best-Worst Method (Fuzzy-BWM). The primary objective is to identify which pillars-namely Smart Governance, Smart Economy, Smart Society, Smart Living, Smart Environment, and Smart Branding-require the most immediate policy attention, and to determine the contribution of each specific indicator within those pillars. A dataset of nine indicators spanning six key smart city pillars is analyzed by integrating expert judgment with fuzzy logic to model uncertainty in comparative weights. The proposed fuzzy-BWM extends the classic BWM by allowing experts to use linguistic terms (modeled as triangular fuzzy numbers) in pairwise comparisons. This approach explicitly captures uncertainty and reduces cognitive bias in expert judgments. This approach yields robust criteria weights and performance insights, highlighting relative strengths and weaknesses across the pillars. The results highlight pivotal strengths and deficiencies in Mojokerto's smart city framework, pinpointing areas such as digital governance services, SME contributions to regional income, and environmental initiatives as high-priority interventions. This systematic approach ensures that city planners and policymakers can allocate resources more efficiently and develop policies aligned with local development goals.