A Comprehensive Framework for Evaluating Corporate Sustainability Performance: Evidence from the Automotive Manufacturing Sector

This study proposes a comprehensive framework for evaluating the sustainability performance of an international automotive manufacturer between 2018 and 2023 using real corporate data. The framework integrates expert judgments analyzed through the Spherical Fuzzy Step-wise Weight Assessment Ratio Analysis (SF-SWARA) method to determine the relative importance of 51 sustainability criteria. Spherical fuzzy sets were adopted to model uncertainty and hesitation in expert judgments by simultaneously capturing membership, non-membership, and hesitancy degrees, thereby providing a more flexible representation of uncertain information compared to classical fuzzy extensions. Annual sustainability performance was evaluated using three multi-criteria decision-making (MCDM) methods, namely Measurement of Alternatives and Ranking according to Compromise Solution (MARCOS), Combinative Distance-based Assessment (CODAS), and Axiomatic Design (AD). MARCOS and CODAS were employed to capture complementary utility-based and distance-based performance perspectives, while the AD method was used to evaluate the consistency of annual performance with predefined sustainability objectives, enabling a comprehensive assessment of trade-offs among sustainability criteria. The resulting rankings were subsequently aggregated using the Copeland Score technique to obtain a balanced and reliable final ranking. An extensive sensitivity analysis confirmed the robustness and consistency of the framework, demonstrating high correlation among MCDM results and stability against variations in expert and criterion weights. The findings indicate that the proposed framework provides a reliable and practically applicable approach for sustainability performance evaluation in the automotive industry.