• Journal of Digital Convergence
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• v.14 no.8
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• pp.47-56
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• 2016

This study is on the actual analysis of R&D investment effect through DEA in terms of efficiency resulted from forestry sector climate change response R&D project. Namely, it is clarifying the mechanism of the scientific, technological, social performance result and output, depending on research development cost, employment size as same input. Also, it is in-depth analysis on which performance operates more efficiently in any detailed business. With the study result, we seek political implications to enhance investment effect and core element to consider R&D business project in the future.

• Journal of Korean Society of Industrial and Systems Engineering
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• v.42 no.4
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• pp.8-15
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• 2019

Korea's R&D investment has significantly increased in recent years and the quantitative outputs such as number of papers and patents have also increased with the investment. However, the quality of R&D outputs has not been fully addressed. In particular, quality of technical performance, such as the quality of patents, has attracted little attention. In this paper, a Data Envelopment Analysis (DEA) method was used to construct models for efficiency analysis of R&D investment, focused on quality of technical performance. Indices were proposed to analyze the quantitative and qualitative efficiencies of R&D investment. In order to effectively analyze R&D efficiencies, the measurement units of the input and output variables were standardized. Based on cases of livestock quarantine R&D projects of Korea, the quantitative and qualitative efficiencies of national R&D projects were analyzed and factors that would influence R&D efficiencies were identified. This paper suggests that both quantitative and qualitative efficiencies should be considered when measuring R&D efficiency. Also, it is recommended to carefully consider the characteristics of R&D projects during project selection stage.

• Proceedings of the Polymer Society of Korea Conference
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• 2006.10a
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• pp.60-61
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• 2006

New Energy and Industrial Technology Development Organization (NEDO) promotes R&D that individual private sector enterprises can not undertake by themselves. To do this, it utilizes an extensive network that supports cooperation between industries, universities, and public research organizations. NEDO's government-funded R&D budget for FY2005 totals approximately 148.8 billion yen. Fuel cells and hydrogen technology development project is one of NEDO's emphasizing projects. The budget size was ${\yen}$20.8 billion, corresponding to about 60% of annual expenditure of Japanese government for fuel cells in FY2005. These projects consist of 8 programs as follows.

• Knowledge Management Research
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• v.22 no.4
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• pp.237-260
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• 2021

This study aims to make suggestions for more effective budget utilization and R&D project investment through verification of the efficiency of research results for the government's R&D projects. Efficiency was analyzed using Data Envelope Analysis(DEA) and 'Malmquist Index analysis' for the research results of convergence research projects organized by the National Science and Technology Research Association. The analysis targets were convergence research projects organized by the National Science and Technology Research Association and general entrusted research projects by government-funded research institutes, and dynamic analysis was conducted using DEA and Malmquist Index analysis. As a result of the analysis, the convergence research project showed high efficiency from the static perspective of DEA. On the other hand, from a dynamic perspective through the Malmquist Index analysis method, the efficiency of the general consignment project gradually declined, while the efficiency of the convergence research project improved every year. This suggests that convergence studies have higher results than general studies. Through the results of this study, we intend to present objective standards for performance evaluation of government R&D investment and provide objective implications for rational investment policies and research project planning of research personnel and research funds to improve efficiency for government-funded research institutes.

• Journal of the Korean Society of Industry Convergence
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• v.22 no.5
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• pp.583-589
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• 2019

One of the core pillars of the Fourth Industrial Revolution is the innovation of the manufacturing industry. From the beginning, the 4th Industrial Revolution appeared in Germany under the concept of 'Industrial 4.0', which means a radical change in the manufacturing industry that can provide super intelligent product production and services based on artificial intelligence and big data. Since manufacturing innovation is a change in the industrial character of the entire nation, the initial role of government is important. Korea also has various policies related to the 4th Industrial Revolution, but there are still various problems to be solved. Therefore, this paper monitors and analyzes the public R&D projects of the advanced countries on manufacturing innovations in the background mentioned above, and through this, the policy implications are drawn.

• Journal of Korea Technology Innovation Society
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• v.16 no.1
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• pp.176-198
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• 2013

Preliminary feasibility study(PFS) was introduced in 1999 by financial authority to encourage a cautious approach to new large-scale public investment project. As it applied cost-benefit analysis as prime measure for decision-making, various issues have been arisen concerning feasibility analysis on R&D programs. This work is intended to suggest standard approaches to be established in PFS on R&D program as follows: 1. The issue questions can be induced in a standard way by 15 representative questions and their correlation with evaluation criteria. 2. The analyzing strategy can be standardized by establishing standards for classification of R&D effects and R&D logic analysis.

• Journal of Internet Computing and Services
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• v.24 no.6
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• pp.31-39
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• 2023

The purpose of this study is to propose a scientific performance evaluation framework for measuring and managing the overall outcome of complex types of projects that are linked to public demand-based commercialization, such as information system projects and public procurement, in integrated national R&D projects. In the case of integrated national R&D projects that involve multiple research institutes to form a single final product, and in the case of demand-based demonstration and commercialization of the project results, the existing evaluation system that evaluates performance based on the short-term outputs of the detailed tasks comprising the R&D project has limitations in evaluating the mid- and long-term effects and practicality of the integrated research products. (Moreover, as the paradigm of national R&D projects is changing to a mission-oriented one that emphasizes efficiency, there is a need to change the performance evaluation of national R&D projects to focus on the effectiveness and practicality of the results.) In this study, we propose a performance evaluation framework from a structural perspective to evaluate the completeness of each national R&D project from a practical perspective, such as its effectiveness, beyond simple short-term output, by utilizing the Hourglass model. In particular, it presents an integrated performance evaluation framework that links the top-down and bottom-up approaches leading to Tool-System-Service-Effect according to the structure of R&D projects. By applying the proposed detailed evaluation indicators and performance evaluation frame to actual national R&D projects, the validity of the indicators and the effectiveness of the proposed performance evaluation frame were verified, and these results are expected to provide academic, policy, and industrial implications for the performance evaluation system of national R&D projects that emphasize efficiency in the future.

• Journal of Korean Institute of Industrial Engineers
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• v.40 no.1
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• pp.84-99
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• 2014

In this study, determinant input-output variables are identified for calculating Data Envelopment Analysis (DEA) efficiency scores relating to evaluating the efficiency of government-sponsored research and development (R&D) projects. In particular, this study proposes a systematic framework of design and analysis of experiments, called "all possible DEAs", for pinpointing DEA determinant input-output variables. In addition to correlation analyses, two modified measures of time series analysis are developed in order to check the similarities between a DEA complete data structure (CDS) versus the rest of incomplete data structures (IDSs). In this empirical analysis, a few DEA determinant input-output variables are found to be associated with a typical public R&D performance evaluation logic model, especially oriented to a mid- and long-term performance perspective. Among four variables, only two determinants are identified : "R&D manpower" ($x_2$) and "Sales revenue" ($y_1$). However, it should be pointed out that the input variable "R&D funds" ($x_1$) is insignificant for calculating DEA efficiency score even if it is a critical input for measuring efficiency of a government-sonsored R&D project from a practical point of view a priori. In this context, if practitioners' top priority is to see the efficiency between "R&D funds" ($x_1$) and "Sales revenue" ($y_1$), the DEA efficiency score cannot properly meet their expectations. Therefore, meticulous attention is required when using the DEA application for public R&D performance evaluation, considering that discrepancies can occur between practitioners' expectations and DEA efficiency scores.

• Journal of the Korean Society of Industry Convergence
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• v.26 no.1
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• pp.1-14
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• 2023

To secure national future competitiveness, the Korean government announced the 『National Ultra-High Performance Computing (HPC) Innovation Strategy (2021.5.28.)』 and set three innovation strategy goals throughout establishing an innovation ecosystem. This study presented a heterogenous data-based strategic support framework that allowed to understand both the current status of domestic & foreign R&D areas and domestic industrial economy areas in terms of strategic fields related to ultra-high performance computing, and the empirical research was conducted in the life science and public health area. The HPC innovation ecosystem platform based on the connection of heterogeneous data (domestic R&D project-technology-industry-overseas R&D project) presented in this study provided useful and essential information that allowed establishing a specific action plan for the national HPC innovation strategy and contributing to vitalizing the innovation ecosystem. Since the evidence-based policy assumes that a more reasonable consensus is reached through a non-biased decision- making process among stakeholders, the proposed platform may contribute to enhancing policy momentum by increasing legitimacy and trust of planning of the national HPC strategy.

• Journal of Biomedical Engineering Research
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• v.38 no.3
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• pp.89-94
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• 2017

In order to improve national competitiveness through technological research and development, the government puts in R&D budget every year and manages to improve the R&D results. Accordingly, various R&D project management methods have applied for successful advancement of technology and product. TRL is a measurement system developed by NASA to assess the maturity of technology since the 1970s. To apply medical device, the characteristics such as regulation, clinical trials are considered as a significant influence. In this study, we would like to derive PMI(performance measures index) for medical device R&D projects by using TRL and stage-gate model. As a result of this study, it is possible to use the PMI for decision making and evaluation in the R&D projects and believed that the objectivity can be ensured by the approval or certification of regulatory authority.