Research On Measurement And Evaluation Of R&D Performance Of Enterprise High-tech Projects

Research and Development (R&D) is not only the core tach of technology innovation, but also the headspring of enterprises' competitive advantage and drive of continuous development. Enterprise high-tech innovative project R&D plays an important role in enterprise development, which is also a high-risk and high-profit activity. In recent years, government and enterprises themselves have paid more attention to the investment of enterprise high-tech innovative project R&D, which is of greater risk and lower success rate, and that results in that enterprise high-tech innovative project R&D investment performance has naturally highlighted the attention, and that how to measure and evaluate enterprise high-tech innovative project R&D performance effectively becomes an urgent problem to solve.How to accurately measure and evaluate enterprise high-tech innovative project R&D performance is the key issue of post-implementation of high-tech innovation projects. Accurate measurement and evaluation R&D performance is of great value for reducing the risk of enterprise high-tech innovative project R&D and increasing economic benefits. This dissertation has deeply studied these aspects purposefully:This dissertation systematically summarizes the theory and method of R&D performance measurement and evaluation. Then, this dissertation defines R&D performance content of enterprise high-tech innovative project, and based on this establishes enterprise high-tech innovative project R&D performance index system, which includes two aspects, namely R&D effectiveness and R&D efficiency. And then, this dissertation establishes the coupling mechanism of enterprise high-tech innovative project R&D effectiveness and R&D efficiency using the method of Interpretative Structural Modeling (ISM), which provided a scientific basis of theory and practice to improve the performance of R&D strategy from inside. Next, this dissertation adopts Data Envelopment Analysis (DEA) method to establish a two-stage DEA enterprise high-tech innovative project R&D efficiency evaluation model, which include two aspects, namely R&D process efficiency and R&D result traslation, to ensure the comprehensiveness of R&D efficiency evaluation. Taking into account the time factor, this dissertation introduces Malmquist index into enterprise high-tech innovative project R&D efficiency change evaluation, and establishes a R&D technical movement prediction model based on eqo-quanlity line. Aiming at the problems of objeveness and uncertainty of R&D performance measurement and evaluation of enterprise high-tech innovative project, this dissertation uses the principle of unascertained mathmatics and builds a synthetic model combined uncertain number. On the other hand, this dissertation combines blind data, which ensures the results of unascertained model more scientific, and is contributed to the accuracy and precision of enterprise high-tech innovative project R&D effectiveness. Using the data and method, this dissertation makes a comprehensive experiential analysis. Finaly, this dissertation puts forward the countermeasures to improve the level of enterprise high-tech innovative project R&D performance from three aspects, namely internal R&D, enterprise and government, which provides some new thought for enhancing R&D performance level and enterprise core competitiveness.In this dissertation, the study has important theoretical and practical value, which not only enriches and consummates the content of R&D performance evaluation, and develops the methods and models of R&D performance evaluation, which are redounds to the scientificalness and standardization, but also helps govement, enterprises and R&D departments to know the main condition and recognize the dis- and advantages of enterprise high-tech innovative project R&D, which contributes to make the development policies of enterprise high-tech innovative project R&D, and helps to increase R&D capability and competitiveness of enterprises.