Assessing the Sustainability Performance of Fishing Harbors Under Uncertainty: A Gaussian‐Neutrosophic Framework

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Abstract
Fishing harbors are increasingly required to meet sustainability expectations associated with the environmental, social, and economic development goals. Accordingly, assessing their sustainability performance has become an important concern for both policymakers, harbor operating organizations, and harbor managers. This study develops a decision support system (DSS) within a neutrosophic environment to evaluate the sustainability performance of small‐scale fishing harbors. For this purpose, a novel SVN‐Gaussian‐Entropy‐MABAC hybrid method is developed. Expert contribution levels are determined using SVNSs, sustainability performance criteria are weighted through a neutrosophic entropy method, and sustainability performance rankings are obtained using a neutrosophic MABAC approach. In addition, two new aggregation operators, namely Single‐Valued Neutrosophic Gaussian Weighted Averaging (SVNGWA) and Single‐Valued Neutrosophic Gaussian Weighted Geometric (SVNGWG) operators, are introduced. The proposed framework is demonstrated through a real‐world case study conducted in Bursa Province, Türkiye. The results indicate that waste management and recycling capacity is the most important sustainability criterion, while Arnavutköy Fishing Harbor achieved the highest sustainability performance score. Comparative robustness analyses using conventional aggregation operators and alternative neutrosophic ranking methods supported the stability of the proposed framework. Finally, the study provides methodological, theoretical, and practical implications for sustainability assessment, neutrosophic decision‐making, and fisheries infrastructure management.

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