EURO 2024 Copenhagen
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326. Comparing two MCDM Approaches to Evaluating Corporate Governance

Contributed abstract in session TC-44: Pairwise comparisons and preference relations 1, stream Multiple Criteria Decision Analysis.

Tuesday, 12:30-14:00
Room: 20 (building: 324)

Authors (first author is the speaker)

1. Kao-Yi Shen
Department of Banking & Finance (SCE), Chinese Culture University

Abstract

This study aims to analyze corporate governance using Rough Set Theory (RST), highlighting its significance in both academic discourse and industrial practices. Corporate governance plays a pivotal role in ensuring trust and protection for investors, effective risk management, enhanced corporate performance, fulfillment of social responsibility, and adherence to legal and regulatory compliance. This study compares a bipolar model based on RST with a traditional multi-attribute decision model. The objective is to evaluate the effectiveness and distinguishing characteristics of the RST-based bipolar model compared to conventional multi-attribute decision models. The RST-based model introduces a unique perspective that deviates from the traditional approaches of multi-attribute decision-making. Through this comparative analysis, the study aims to provide valuable insights into the application of RST in decision-making frameworks, contributing to a deeper understanding of its practical implications in decision science. Through rigorous analysis, the research identified distinct characteristics and performance metrics of the RST-based bipolar model. It assessed its efficacy in decision-making contexts—key findings shedding light on the model's strengths and potential areas for improvement. The comparative analysis enhances our understanding of the practical implications of employing RST in decision science, providing valuable implications for academia and industry.

Keywords

Status: accepted

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