A multi-criteria decision-making framework for evaluating corporate governance: An operations research approach
DOI:
https://doi.org/10.25299/kiat.2025.25230Keywords:
Corporate governance, AHP, TOPSIS, DEA, MCDM, board effectiveness, governance efficiency, transparencyAbstract
Purpose: This study aims to develop a systematic, evidence-based framework to evaluate corporate governance across global sectors, overcoming the limitations of traditional, one-dimensional assessment methods.
Design/methodology/approach: A hybrid Multi-Criteria Decision-Making (MCDM) framework integrating the Analytic Hierarchy Process (AHP), Technique for Order Preference by Similarity to Ideal Solution (TOPSIS), and Data Envelopment Analysis (DEA) was developed. Data from ten anonymised publicly listed firms operating globally were used to assess corporate governance across five core dimensions Board Effectiveness, Transparency and Disclosure, Stakeholder Engagement, Ethical Conduct, and Risk Management via AHP with a Consistency Ratio of 0.06
Findings: The results indicate that firms prioritising transparency, ethical conduct, and stakeholder engagement achieve higher governance performance and resource efficiency. TOPSIS scores ranged from 0.88 to 0.39, while DEA efficiency scores ranged from 0.72 to 1.00, highlighting variation in governance effectiveness among firms.
Limitations and Research implications: The study is based on a relatively small sample of ten firms, and the anonymisation of data may limit sector-specific insights. Further research could extend the framework to larger datasets and additional industries for broader generalisation.
Practical Implications: The hybrid MCDM framework provides boards, regulators, and researchers with a quantitative, replicable, and globally adaptable tool for benchmarking corporate governance, enabling evidence-based decision-making and improved accountability.
Originality/value: H This research offers a novel integration of AHP, TOPSIS, and DEA for corporate governance assessment, delivering a structured, multidimensional, and internationally applicable approach to evaluating governance performance and resource efficiency.
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