Despite the increase of government spending on R&D in South Korea, there have been limits in enhancing the challenging trait and creativity of research outcomes. A new approach to the current mode of R&D is considered necessary to tackle this problem. In 2015, South Korea operated fifteen programs, namely "High-risk Highreturn R&D," from seven government ministries. The purpose of this study is to examine the actual conditions for adoption and to further promote early establishment and wide implementation of the new "High-risk High-return policy" in National R&D, and to suggest ways to improve it. In this study, we have approached the case with a life-cycle perspective of planmanagement-evaluation of R&D by carrying out a survey and unstandardized interviews with key staff from R&D management agencies. Based on the results of the analysis, we suggest improvements in three aspects: 1) flexible system operation, 2) government ministries' autonomy and accountability, 3) effective incentives. Finally, we discuss possible improvements, future directions, and the limits of this study.

Abstract:The purpose of this study is to suggest efficiency improvement using the analysis of the efficiency of the royalty system for government-funded research institutes (GRIs) belonging to the National Research Council of Science & Technology (NST). Twenty three GRIs' royalty incomes and expenses (2013)(2014)(2015) were analyzed using the data envelopment analysis (DEA) model. First, Research Model 1 was used to find out if the obligated expense category's distribution ratio were efficient. Five Charnes, Cooper and Rhodes (CCR) model organizations and 14 Banker, Charnes and Cooper (BCC) model organizations demonstrated 100% efficiency. With the exception of the obligated expense category, Research Model 2 was used. Seventeen CCR model organizations and 18 BCC model organizations demonstrated 100% efficiency. GRIs were divided into efficient and inefficient organizations using each model, and potential improvements and benchmarking decision-making units (DMUs) were found for inefficient organizations. Second, multiple regression analysis in Research Model 2 was used to analyze the cause of the efficiency to find factors that influenced the transfer of technology and license improvement. Third, there were efficiency differences among research organizations as a result of the efficiency analysis considering the research organization type with respect to the constant returns to scale (CRS) efficiency of Research Models 1 and 2. Thus, different policies should be applied to improve the efficiency. Finally, the possible improvements, future directions and limits of this study are discussed.