| Summary: | 碩士 === 中國文化大學 === 會計研究所 === 96 === In these few years, the rapid change of information globalization has increased the occurrence possibility of corporate governance. Business performance forecasting in the perspective of corporate governance is a significant problem for economic development. Therefore, to build up an advantageous business performance model has become a very important task for this situation. The purpose of this research is to provide a complete data analysis process, and there are two main stages included. In the first, we used data envelopment analysis to identify an appropriate number of clusters for the corporate operating efficiency. After then, we integrated stepwise regression、support vector machine and back-propagation neural network to solve the classification problems. To demonstrate the efficiency of the proposal approaches, classification tasks are performed on two data sets both of the corporate efficiency data and board independence data. As the results reveal, the proposed integrated approach provides a better initial solution than the conventional support vector machine and back-propagation neural network and the classification accuracies increase for both cases in the proposed methodology
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