Corporate Governance-Based Financial Performance Analysis: A Decision Support System for Identification of Top-Performing Industry Benchmarks

Abstract

This study aims to evaluate corporate governance-based financial performance by integrating governance mechanisms with financial metrics, moving beyond analyses that rely solely on financial indicators. A decision support system (DSS) is developed using a hybrid Continuous Pythagorean Fuzzy (CPF)-Criteria Importance through Intercriteria Correlation (CRITIC)-Weighted Euclidean Distance-Based Approach (WEDBA). The method simultaneously incorporates quantitative and qualitative parameters and assigns expert influence based on experience and risk-taking propensity. Subjective and objective weighting approaches are combined: CPF sets are employed for subjective weighting, while the CRITIC method is used to determine objective criterion weights. The WEDBA method calculates companies' corporate governance-based financial performance levels. The approach is applied to ten food and beverage companies operating in Turkey. Among sixteen corporate governance-based financial performance criteria, "Return on Equity" emerges as the most influential, with independent board members, board size, and female board representation also demonstrating significant importance. Within the sample, Türk Tuborg is identified as the top-performing company. The reliability and robustness of the results are confirmed through sensitivity and comparative analyses. The study presents a novel hybrid MCDM framework that integrates expert judgment and quantitative data within a Continuous Pythagorean fuzzy context, offering a practical DSS for assessing corporate governance-driven financial performance. The findings provide actionable insights for corporate managers and policymakers seeking to enhance governance practices and financial outcomes in sector-specific contexts.