Technology innovation companies are focusing on contributing to business performance by R&D project as a strategic tool. Successful R&D leads to corporate competitiveness enhancement, national industrial development, but there are high uncertainty and risks in R&D. Public and private R&D projects are carried out to achieve various purposes. It was verified how the risk management and benefit management of the R&D project affect the detailed R&D project performance between the Public and private domain. The impact of Project Leadership on R&D performance was also analyzed. Those who have participated in the Public and Private R&D projects at companies or research institutes were surveyed. First, it was found that project risk and benefit management have partially an effect on R&D project performance. Second, Public and private R&D Project Leadership showed partially a interaction effect between project management and project performance.

The successful implementation of green supply chain management(GSCM) practices requires a level of cooperation that can be difficult to conduct. Despite this challenge, limited scholarly attention has been paid to exploring how the implementation of GSCM practices can be effectively facilitated and enhanced through accumulated social capital with suppliers. Based on social capital theory, this study postulates that supplier network characteristics derived from social capital with key suppliers can be critical antecedents of GSCM, which in turn enhances the firm’s environmental performance. To test hypotheses, data were collected from 330 firms in 15 countries, and structural equation modeling was employed. Results show that GSCM improves environmental performance, and structural and cognitive social capitals of the supplier network act as antecedents and lead to GSCM implementation.

In this study, we have defined measurement and verification methods and procedures to assess the energy use on the utility system of building. Time series data conversion methods and algorithms have been proposed in performance evaluation options. To verify the feasibility of the method, the energy consumption of the refrigerator, which was an energy utility, was measured and analyzed. we present an algorithm based on the annual base conversion and analyze it based on actual data. As a result, a k-means clustering moving average method was defined for the performance calculation option A, and the use time correction coefficient method was proposed. The validity of this method was verified through the verification.

The use of Project Management Information System (PMIS) is increasing in project management industries such as construction, defense, manufacturing, software development, telecommunication, etc. It is generally known that PMIS helps to improve the quality of decision making in project management, and consequently improves the project performance. However, how much and which parts of project management performance are affected by PMIS still need to be studied further. The purpose of this study is to investigate the impact of PMIS quality on project management performance. We collected data from various project based industries such as construction, defense, manufacturing, software development and telecommunication by using survey questionnaire. PMIS quality was measured in three dimensions. They are system quality, information quality and service quality. Project management performance was measured in nine variables such as time reduction, work accuracy, cost management, etc. Statistical analyses such as multiple regression were used to analyze the data. The results showed that PMIS quality had significant impacts on the project management performance and user satisfaction. It was notable that only two dimensions out of the three PMIS quality dimensions, system quality and information quality, affected the project management performance. Also, it was found that PM performance played a mediating role between PMIS and user satisfaction, and between PMIS and reuse intention. The contribution of this research is that it helps to clarify what aspects of PMIS affect the project management performance and user satisfaction.

This study analyzes the business performance of research and development(R&D) and especially studies the effect of technology management activity and technology innovation competency on commercialization performance. According to previous studies, the technology management activity can be composed of technological innovativeness, analysis of market, R&D method, and appropriateness for commercialization plan. Also, the technology innovation can be divided into patent, R&D manpower, R&D investment ratio, production capability, and marketing capability. On the result of the analysis, all the components of technology management activity are positively related with commercialization performance. In case of technology innovation competency, however, only production and marketing capabilities have influence on the business performance. Especially, marketing capability controls the effect of technology management activities on the commercialization performance. Consequently, technology management is very important activity for SMEs to succeed commercialization and SMEs should collaborate with production and marketing departments from the early stage of R&D.

This study verified for the necessity for the comprehensive analysis of outcomes resulting from the local industry promotion project in many respects. To analyze the operation planning for performance management of local industry promotion project, this study redesigns the so-called PDCA(Plan→Do→Check→Act) model which is also known as Deming Cycle and verifies some hypotheses. To accomplish study purposes, 169 response samples from 85 project groups which drive the local industry promotion project were verified using SPSS 12.0. The findings are as follows: First, there was a positive relationship between the planing phase and the implementation phase. Second, there was also a positive relationship between the implementation phase and completion of the project phase. Third, there was a positive relationship between the planing phase and completion of the project phase. Finally, the implementation phase was a partial mediator on the relationship between the planing phase and completion of the project phase. Based on these findings, the implications and the limitations of the research findings were discussed, and recommendations for future research were provided.