• 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.

• Proceedings of the Korean Operations and Management Science Society Conference
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• 2007.11a
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• pp.141-144
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• 2007

This research aims to propose model for measuring the efficiency of R&D organizations by using Data Envelopment Analysis. In existing research about using Data Envelopment Analysis, the types of R&D organizations have not been clarified and the difference between analysis time from measurement time is usually $4{\sim}5$ years. This research divides R&D organizations into three types and provides proper methods for measuring the efficiency of each R&D organizations.

• Journal of Technology Innovation
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• v.22 no.2
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• pp.77-104
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• 2014

Government R&D support for SMEs is very important and the R&D budget is also increasing. This study suggests a new method for analyzing a performance of R&D programs and analyzes the performance of R&D programs funded by small & medium business administration using the method. We discuss new measures "efficiency" that means short-term performance and "effectiveness" that means long-term performance. Weights based on the R&D programs' characteristics among the various sub-indicators of two measures were derived, and then the final scores were calculated by combining the weights with the responses on the indicators. Finally, this study tests the mean differences between R&D programs statistically. As a results, efficiency of R&D programs shows a significant difference between the R&D programs, while effectiveness does not. Most of the efficiency scores are low, whereas the effectiveness scores are high. The results explain that the R&D programs are managed inefficiently. However, most SMEs predict a positive impact of government R&D supports on effectiveness in the long term. Government needs to try to improve the efficiency of R&D supports because SMEs cannot expect sustainable performance with no improvement in efficiency.

• Journal of Korea Technology Innovation Society
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• v.14 no.2
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• pp.205-222
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• 2011

The Korean government continuously increases the R&D investment in order to pursue an economic growth through technological innovation. Hence, the intensity of governmental R&D has increased rapidly. However, the whole amount of the R&D investment is still small compared to developed countries. And the type of R&D policies is more and more changing from the catch-up model to the technology-driven model. Therefore, there is a growing interest in the efficiency of public R&D investment. Hence, many studies on the efficiency of R&D investment have been researched. This study estimated the efficiency of governmental R&D programs considering the technological outcomes, e.g. theses, patents and so on, using DEA(Data Envelopment Analysis) with data of S&T investment and outcomes from NTIS(National S&D Information Service). In addition, we used the Mann-Whitney Test to investigate the characteristics of governmental R&D investment.

• Journal of Technology Innovation
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• v.11 no.2
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• pp.151-173
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• 2003

This paper analyses the efficiency and productivity of R&D system across time (1991${\sim}$2000) and 16 OECD countries using multi-output and multi-input non-parametric frontier methods such as DEA (data envelopement analysis) and Malmquist productivity indexes. Malmquist productivity indexes are decomposed into two components measures, namely technical change and efficiency change. To calculate R&D efficiency and productivity, we used R&D stock and the number or researchers as R&D input proxies and the number of adjusted SCI papers and U.S. patent applications as R&D output proxies. Empirical result shows that Switzerland, Canada, U.S., Australia's R&D efficiencies are the highest and Korea's R&D productivity growth is the highest in the sample for the period. Technical efficiency growth was a more important source of productivity growth than technological innovation.

• Journal of Energy Engineering
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• v.23 no.3
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• pp.42-50
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• 2014

Korean government has been investing more than 400 billion KRW in R&D on renewable energy. This paper aims to measure the R&D efficiency of national R&D program in the field of renewable energy, and to identify the sources of inefficiency. 4,213 R&D projects supported by Korean government during 2009-2011 are analyzed by using Data Envelopment Analysis and statistical tests. Results implies as follows. First, hydrogen, bio, fuel cell, photovoltaic have higher R&D efficiency than other renewable energies. Second, universities conducted national R&D program more efficiently than firms did, and small and medium sized enterprises are more efficient than large sized enterprises. Third, R&D inefficiency is mainly caused by the lacks of patent performance rather than excessive R&D investment or academic paper performance.

• Journal of Korean Society for Quality Management
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• v.44 no.4
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• pp.785-798
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• 2016

Purpose: This paper developed the framework for extracting strategies of research and business development (R&BD) based on the data envelopment analysis(DEA). Methods: DEA has been widely utilized in evaluating R&D efficiency. Even though, technology transfer and commercialization has been regarded as the important factors for practical R&D efficiency evaluation, most research have evaluated R&D efficiency by just using the DEA outputs such as the number of patents and papers. The technology transfer, commercialization and relations among costs and generated technology and commercialization are needed to be considered for more practical R&D efficiency evaluation. Thus, this research addressed a method on how to incorporate the commercialization factors into the R&DB efficiency evaluation, and improve the efficiency strategically in terms of R&D and B&D. To achieve this, this research utilized a two-stage network DEA model for R&BD efficiency evaluation. Results: The proposed framework was applied to the 15 public research institutes and the 34 universities for validation. R&BD efficiency for the 15 public research institutes and the 34 universities was evaluated, and the differentiated improvement strategies for the inefficient DMUs to improve their efficient were proposed. Conclusion: The R&BD efficiency would be effectively analyzed based on two-stage network DEA. It would be utilized for the effective strategy planning for cultivating R&BD.

• 한국태양에너지학회:학술대회논문집
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• 2011.11a
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• pp.56-59
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• 2011

The process conditions for high efficiency industrial crystalline Si solar cells with selective emitter were optimized. In the screen printed solar cells, the sheet resistance must be 50-60V/sq. because of metal contact resistance. But the low sheet resistance causes the increase of the recombination and blue response at the short wavelength. Therefore, the screen printed solar cells with homogeneous emitter have limitations of efficiency, and this means that the selective emitter must be used to improve cell efficiency. This work demonstrates the feasibility of a commercially available selective emitter process, based on screen printing and conventional diffusion process. Now, we improved cell efficiency from 18.29% to18.45% by transition of heavy emitter pattern and shallow emitter doping condition.

• Journal of the Korea Institute of Military Science and Technology
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• v.22 no.1
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• pp.106-123
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• 2019

Demand for performance analysis is increasing for efficient use of limited budgets such as improving investment efficiency and strategic budget allocation in accordance with the continuous increase demand of R&D budget for developing advanced weapon systems in the future battlefields. In accordance with the Act on the Performance Evaluation and Performance Management of the National R&D Projects established in March 2006, the performance analysis has been conducted for the systematic management and utilization of the R&D project performance. It was recognized as a project to achieve self-defense through strengthening the weapons system development capability, however, efficiency evaluation of Defense R&D projects was not much emphasized. Research on the efficiency analysis of defense R&D projects has been conducted in recent years, but most studies focused on corporate efficiency and productivity of defense companies. In this study, we analyzed the three-stage performance of defence R&D projects based on the logical model using the data envelope analysis(DEA) model. We also analyzed performance analysis from various perspectives through R&D type, technology classification and performance model. This study is expected to help defense department improve defense R&D projects and make decision.

• Journal of Information Technology Services
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• v.15 no.2
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• pp.51-63
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• 2016

In this study, we conducted a comparative analysis of R&D investment efficiency and operational efficiency of IT firms using Data Envelopment Analysis (DEA). We categorized thirteen sample firms into two groups-IT manufacturing and IT service-after an extensive literature review on IT industry classification. We adopted an output-oriented two-stage DEA model suggested by Banker et al. (1984) with total asset and R&D investment as input variables. Then, we constructed investment efficiency and operational efficiency by using Return on Equity (ROE) and Return on Asset (ROA) as intervening variables and operating income and Earnings Per Share (EPS) as output variables. The outcome of the analysis is summarized as follows. First of all, IT manufacturing firms were more efficient (57% on average) than IT service firms. To be specific, IT service firms showed decreasing returns to scale (DRS) with diseconomy of scale. In contrast, IT service firms showed higher operational efficiency (81.5% on average) than IT manufacturing firms. Also, we conducted a Mann-Whitney U test to compare the output of IT service firms and IT manufacturing firms. Lastly, we found a negative correlation ($R^2$ = -.754) between R&D investment efficiency and operational efficiency which infers the trade-off between two constructs