Evaluation Method For Project Efficiency Based On DEA And System Dynamic

The construction of large-scale scientific facilities not only enhances the comprehensive national strength of China, but also plays a great role in promoting the development and progress of science and technology, which has a great significance of social impact. It is very important to improve the management capacity of national large-scale scientific facilities construction project. For Chinese enterprise technology innovation project, compared with other western countries, still there is a significant gap. Therefore, the research on project efficiency is very important.In this study, the management model of national large-scale scientific facilities construction project and enterprise technology innovation project are analyzed. Based on technology evolution rules of TRIZ theory, the project management model of research institution and enterprise are summarized.Technology innovation project has the properties of multi-factor. From the perspective of process management, to achieve the goal of evaluating innovation project efficiency effective and weight optimization, an indicator system that synthesizes the requirements of subsystem, system and super system of innovation project and an evaluation model integrates objective weight with subjective weight are established by using TRIZ and DEA. Then, a four-quadrant decision diagram is given for enterprise analysis.Synthesizes performance indexes on project schedule and cost,an evaluation method of national scientific construction project efficiency is presented. Firstly, effectiveness factors on both project and product level are analyzed. Then, a two-hierarchy system dynamic simulation model including seven indicators such as project management performance, research capacity and reliability is established and project efficiency is evaluated based on DEA.A case study of three leading enterprises from three different industries and a nation large-scale scientific project using the proposed evaluation and decision method is shown to verify the correctness of the model.The modeling approach and evaluation method of this research, including multiple influence factors, which can solve variable quantification problems in project efficiency evaluation for data envelopment analysis where these nonobservable variables are assigned simulated result. The research provides a new way for efficiency evaluation of project management and the results would contribute to improving management capacity of both national Large-scale scientific construction project and enterprise innovation.