Breaking ground in ESG assessment: Integrated DEA and MCDM framework with spherical fuzzy sets for Vietnam's wire and cable sector

Abstract

In corporate sustainability reporting, the credibility of environmental, social, and governance (ESG) information is paramount, especially for socially responsible investors relying on ESG metrics. This study proposes an integrated method combining Data Envelopment Analysis (DEA), Analytic Hierarchy Process (SF-AHP), and Weighted Aggregated Sum Product Assessment (SF-WASPAS) under the Spherical fuzzy environment to assess the ESG performance of Vietnam's wire and cable companies by integrating quantitative indicators from financial statements and qualitative factors from literature reviews and expert interviews. Firstly, the DEA-Malmquist model gauges the efficiency performance of the ten wire and cable enterprises through five critical financial indicators. Secondly, using expert opinions, the SF-AHP method determines the weights of 16 selected ESG criteria, offering a qualitative dimension to the evaluation. Subsequently, the SF-WASPAS approach ranks the ten businesses based on aggregated scores derived from the criteria, forming a robust foundation for ranking. Furthermore, a comparative analysis demonstrates the practicality and reliability of our proposed framework against the Technique for Order of Preference by Similarity to Ideal Solution (SF-TOPSIS) and Fermatean fuzzy WASPAS. While the Malmquist results highlight SAM Holding Corporation (A6) with the highest average efficiency score, a holistic assessment across all three ranking methods places Vietnam Electric Cable Corporation (A1) at the forefront, closely followed by Hai Phong Electronic Mechanical JSC (A2). By harmoniously blending quantitative and qualitative perspectives and employing robust evaluation techniques, this study extends to effective resource management, targeted investor attraction, and heightened stakeholder engagement, offering substantial benefits to the wire and cable industry's ESG endeavours.

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