Please use this identifier to cite or link to this item:
Corporate Governance and the Prediction of Litigation Presence- A Neuro-Fuzzy Approach
|關鍵字:||Corporate governance;公司治理;Litigation warning;knowledge;Logistic regression;Neuro-fuzzy;訴訟預警;羅吉斯迴歸;類神經模糊||出版社:||會計學研究所||摘要:||
This study examines if corporate governance mechanisms of publicly listed companies may play the role of self-supervision, hence provide auditors with judgmental assistances for decision-making. A sample including 62 sued cases selected from Securities and Futures Bureau as well as Investors Protcetion Center and 124 non-sued companies chosen as matched-pair samples having equivalently demographic characteristics of size and industry is used to analyze the characteristics and weaknesses of contemporary corporate governance. The study applies a logistic regression and a neuro-fuzzy technique to construct litigation-presence warning models, subsequently to capture the relationship between corporate governance and litigation presence. Empirical results show that litigation presence significantly has negative relation with both the shareholding and the number of directors and supervisors. However, the relationship between institutional/secondary shareholders and litigation presence remains unclear. Further, concerning the prediction ability, the logistic regression can provide the earliest warnings in comparison with neuro-fuzzy, but such an ability would be violated if structural changes occur, for instance, law regulations become rigorous. On the contrary, the neuro-fuzzy with its unique ability of learning offers better warning while the time is getting closed to litigation occurrence. Hence benefits to the related parties could be derived from avoiding economic losses and resource wastes. In addition, the knowledge base rules and 3D plots among the variables obtained from the neuro-fuzzy also offer a promotion of auditing effectiveness and efficiency, and a guidance for regulation establishments.
|Appears in Collections:||會計學系所|
Show full item record
TAIR Related Article
Items in DSpace are protected by copyright, with all rights reserved, unless otherwise indicated.