Abstract
Data envelopment analysis (DEA) is an objective method for rating the efficiency of a group of decision making units by using linear programming, input and output information. Research and development (R&D) is one of the most import activities in high-tech industries. DEA has been applied to evaluate operations efficiency of high-tech firms from various perspectives. The major issue in DEA applications is dealing with how to relate intellectual capital to performance ranking. Inadequate measure may lead to unreasonable result that poor ranking goes to the company with extensive R&D activity. Therefore, a study on the effect of measuring methods in DEA is conducted. Three approaches, MV/BV, Tobin’s Q, and accounting based valuation of corporate R&D, for measuring intellectual capital are applied to the calculation of the intangible asset indicators. In this study the models of DEA are constructed by using the four perspectives of balanced scorecard (BSC) and the three intangible asset indicators. Two major findings are presented. First, we take three years data of IC assembly & testing firms in Taiwan to measure the performance for each year under the three different intangible asset indicators. Results show that the MV / BV and Tobin's Q methods to measure the performance is favorable to high-tech industries in ranking. Second, by adopting MPI (Malmquist Productivity Index), Total Factor Productivity Change, TFPC) and TE (technical efficiency), 12 companies can be classified by operations performance, and suggestions for business improvement can be easily made based on the classification.
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