Efficiency achievement measure for Taiwanese Semiconductor companies using rough set theory and multiple objectives programming.

• Main Authors: Fang-hung, Chu, 朱芳宏
• Other Authors: Hung-Yi, Wu
• Format: Others
• Language: zh-TW
• Published: 2010
• Online Access: http://ndltd.ncl.edu.tw/handle/73517905145553419697

碩士 === 開南大學 === 企業與創業管理學系 === 98 === There were many empirical researches concerning about the influences of the intellectual capital on company's value and business’s performances in the past; however, they were mostly restricted to the test analysis of traditional statistical. The intellectual capital is an intangible asset which measures the characteristics of many attributes, quality and quantity. Therefore, the mining of core attributes and important characteristics has become the key problems of business performance’s analysis. The purpose of this study is to explore the core attributes of intellectual capital affecting the company’s value for measuring the efficiency of business’s performances. We summarized important indicators measuring the efficiency of business including 11 intellectual capitals (4 human capitals, 3 innovation capitals, and 4 process capitals), and 3 company's values (return on assets, return on equity, and value of Tobin’s Q). 100 data of publicly traded company in the semiconducting manufacturing industries from 2004 to 2008 were also collected. This research first utilized Rough Set Theory (RST) taking 11 indicators of intellectual capital as conditional attributes and using 3 indicators of company’s value as decision-making attributes to capture core attributes and conclude the decision-making rules. Then, we applied multiple objectives programming (MOP) getting core attributes of intellectual capital as input and letting company’s value being output to analyze efficiency achievement measure (EAM). By RST, this study captured 8 efficient measuring indicators of core companies including ratio of staff number, productivity of employees, profit Margin, expense of R&D, productivity of R&D, inventory turnover, fixed asset turnover, and total asset turnover. By MOP, this research revealed that there were 4 factories of Decision Making Unit (DMU); as a whole, the achieving ratio of efficiency was good, and the average was 0.85.