Efficiency Analysis and Improvement Method of Domestic R&D Business Performance : Through Data Analysis - 오규환; 류기환 (International Journal of Advanced Culture Technology(IJACT), 2025)
Currently, the central government establishes its own management system, including the contents of support tasks, selection criteria, and performance management standards, according to the R&D area under the jurisdiction of each department, so even if a complete transfer is carried out, there is a possibility that the characteristics of the project will be changed or the sustainability will be slightly reduced depending on the management system, and furthermore, the R&D business performance can be affected. This study compares and analyzes the difference in efficiency of R&D project performance according to the dualization of the project supervision department. It was intended to measure the efficiency of various R&D performances (scientific, technical, economic, and social). In particular, to verify more multifacetedly, internal and external influencing factors were verified along with differences in efficiency by business week ministries and research regions. As an analysis method, data statistical analysis, data envelope analysis (DEA), average difference between group analysis, and correlation analysis were used. As a result of the analysis, there were statistically significant differences between the Ministry of Trade, Industry and Energy and the Ministry of Small and Medium Venture Business in both quantitative and qualitative efficiency in R&D projects. In conclusion, it can be seen as a result of reflecting differences in management capabilities, such as setting management systems and performance indicators.. Since this study was analyzed based on a specific R&D project, it is somewhat insufficient to generalize the results. There is a possibility that not all of the R&D characteristics that generate performance over a long period of input have been reflected, and there are some areas that are somewhat insufficient to explain precise causal relationships, so it is expected that causality verification between variables will be necessary through the application of various analysis methodologies in the future.