The optimal allocation model of corporate governance based on computational intelligence: Board composition and ownership structure to maximize the firm value

• Main Authors: KAO, HUI-SUNG, 高惠松
• Other Authors: LEE, JAN-ZAN
• Format: Others
• Language: zh-TW
• Published: 2009
• Online Access: http://ndltd.ncl.edu.tw/handle/17437902053667040709

博士 === 國立臺北大學 === 會計學系 === 97 === The purpose of this study is to discover the optimal allocation model of corporate governance, to resolve non-consistent result of corporate governance and firm value. This study use computational intelligence, Neural network and Genetic algorithm, to improve the disadvantage of traditional econometric method. The findings of this paper indicated genetic algorithm that could resolve the allocation’s problem of corporate governance. The result of this paper is as follows. The optimal size of board of director is 11 to 13 people. The optimal percentage of outside director is around 50%. That is more than request of regulator now. About ownership structure, the optimal shareholdings of director and supervisor are about 32% to 56%. The optimal shareholdings of CEO are 1% to 5%. The optimal shareholdings of block holders are 20% to 23%. The optimal shareholdings of institute investor are about 43% to 79%. The optimal deviation of control right is 4 to 9. The implication of academic is finding the optimal allocation of corporate governance, resolve estimate problem of nonlinear model and combine the technical of computational intelligence. The implication of practice is providing to structure the valuation system of corporate governance and help management to allocate the ownership structure. The value function of this paper is useful for investor to make trade decision. Future research could continue integrate accounting issue and computational intelligence technical, enhance the valuation system of corporate governance and link up fuzzy theory to discuss the optimal situation of corporate governance.