• Journal of Korean Society of Industrial and Systems Engineering
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• v.40 no.2
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• pp.31-40
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• 2017

In this paper, we compared the efficiencies of national R&D investments between NT (Nanotechnology) areas in terms of papers, patents, and commercializations, and found ways to improve the efficiencies of national R&D investments for each NT area. This is in response to huge R&D investments government has made recently in NT areas. Here, we collected data on investments, papers, patents, and commercializations for the R&D projects in NT areas through National Science & Technology Information Service. Based on the data, we analyzed the investment and performances (papers, patents, and commercializations) for each NT area, calculated the efficiency for each NT area, and compared the efficiencies between NT areas. Next, using cluster analysis, we identified several NT areas with similar characteristics in terms of paper efficiency, patent efficiency and commercialization efficiency. Finally, we derived implications for the efficiency enhancement for each grouping. The cluster analysis showed that there could be two groups, one being low in terms of technological outcome (papers and patents) efficiencies and high in terms of commercialization efficiencies, while the other being high in terms of technological outcome (papers and patents) efficiencies and low in terms of commercialization efficiencies. Therefore, the strategy for one group calls for support for technology transfer or technology introduction from other R&D performers and grant of guidance for improving R&D performers' commercialization ability to other R&D performers while the strategy for the other group calls for R&D support for transfer of technology to other R&D performers, activation of technology transfer and support for commercialization of R&D performers.

• Journal of Korea Multimedia Society
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• v.23 no.2
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• pp.317-327
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• 2020

R&D(Research and Development) efficiency analysis is a very important issue in academia and industry. Although many studies have been conducted to analyze R&D(Research and Development) efficiency since the past, studies that analyzed R&D(Research and Development) efficiency considering both patentability and patent quality efficiency according to the financial performance of a company do not seem to have been actively conducted. In this study, measuring the patent application and patent quality efficiency according to financial performance, patent quality efficiency according to patent application were applied to corporate groups related to artificial intelligence hardware technology defined as GPU(Graphics Processing Unit), FPGA(Field Programmable Gate Array), ASIC(Application Specific Integrated Circuit) and Neuromorphic. We analyze the efficiency empirically and use Data Envelopment Analysis as a measure of efficiency. This study examines which companies group has high R&D(Research and Development) efficiency about artificial intelligence hardware technology.

• 한국정보디스플레이학회:학술대회논문집
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• 2009.10a
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• pp.486-488
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• 2009

High efficiency deep blue and pure white phosphorescent organic light emitting diodes were developed using a new deep blue phosphorescent dopant, tris((3,5-difluoro-4-cyanophenyl)pyridine) iridium (FCNIr). A high quantum efficiency of 9.1 % with a color coordinate of (0.15, 0.16) at 1,000 cd/$m^2$ was obtained in the deep blue device and a high quantum efficiency of 15.2 % with a color coordinate (0.30, 0.32) was obtained in the pure white organic light-emitting diodes. The quantum efficiency of the pure white device is the best quantum efficiency value reported in the pure white device up to now.

• Korean Management Science Review
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• v.34 no.2
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• pp.67-83
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• 2017

This paper proposes a R&D project performance measurement model for private firms combining balanced scorecard (BSC) and data envelopment analysis (DEA). The efficiency of R&D projects is measured in terms of each of the three perspectives of BSC by using DEA : the internal process perspective (DEA-P), the customer perspective (DEA-C), and the financial perspective (DEA-F). The performance indicators of the three perspectives of BSC are considered as outputs of the corresponding DEA models. To provide strategic implications for R&D planning, we also propose the R&D project performance matrices composed of two different types of efficiency dimensions. The proposed model is expected to be fruitfully utilized for R&D performance measurement of private firms.

• Journal of Technology Innovation
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• v.20 no.3
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• pp.29-55
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• 2012

In order to successfully adopt and implement the Balanced Scorecard(BSC), firms need to respond adequately to the rapid changes of today's business environment and consider the growing importance of non financial factors in the business activities such as intangible assets(R&D expenditure, patent, goodwill, etc.). Our primary focus throughout this paper is on developing Key Performance Index(KPI) of BSC for R&D expenditure activities. In this study, we have developed and named PEI(Patent Efficiency Index),which is the KPI for R&D expenditure by focusing on the efficiency of a patent that is the output from the R&D expenditures. Secondarily, we have attempted to address the solution for the current problems of the traditional R&D performance measurement by using our developed PEI and examine the usefulness and effectiveness of the newly developed our PEI. According to the empirical test results, we find that the PEI is positively associated with ROA and Tobin's Q, respectively and show that our developed PEI is more effective and accurate than the traditional R&D performance measurement as a business performance measurement. Furthermore, these findings proves that we can measure and evaluate how efficiently the firms perform the R&D activities and shows that the PEI can be a critical index for evaluating firm's business performance related to the R&D expenditures.

• The Journal of Society for e-Business Studies
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• v.26 no.2
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• pp.45-59
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• 2021

As software(SW) has been considered as a key driver of the fourth industrial revolution, significant R&D investment has been made by Korean government. Despite the attention and support by the government, systematic analysis on the SW R&D efficiency has not been fully addressed. In this study, the efficiency of SW national research and development projects was analyzed using Data Envelopment Analysis(DEA) techniques. Efficiency was measured from both static and dynamic perspectives based on 1,463 projects conducted by the National IT Industry Promotion Agency(NIPA) from 2008 to 2018. The static efficiency analysis identified the causes of inefficiency as scale and technology problems. As a result of dynamic efficiency analysis, we present a sector-specific response model using an efficiency-stability matrix. This study is meaningful in that efficiency analysis was conducted on the entire SW national R&D project, and static/dynamic efficiency analysis results are expected to be used as a guideline for planning SW national R&D project.

• Journal of Korean Institute of Industrial Engineers
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• v.40 no.2
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• pp.172-183
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• 2014

This paper measures and compares the efficiency of national health technology R&D programs focused on translational research program increasing importance using data envelopment analysis (DEA). Three input variables and three output variables are selected for DEA. Inputs are funds, researchers, and project period and outputs are SCI (E) papers, applied and granted patents, and impact factor. This study uses a three-stage approach. In the first stage, output-based DEA model is applied to evaluate the efficiency of decision making unit (DMU). In the second stage, based on efficiency scores of target diseases high-efficiency group and low-efficiency group are classified. And then strategic portfolio matrix of translational research program is composed of four dimensions combining research types. Mann-Whitney U test is then run to compare average efficiency scores among four groups. In the final stage, Tobit regression model is used to estimate factors likely to influence the efficiency. The results are expected to provide policy implications for effectively establishing investment strategy and managing performance of R&D program.

• Journal of Technology Innovation
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• v.28 no.3
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• pp.1-28
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• 2020

This study examines whether the firm with high innovation efficiency realizes high operating performance. We measured innovation efficiency by the ratio of patent applications for R&D expenditure or R&D stock and measured operating performance by the ratio of operating income or operating cash flow to total assets for the following year. The sample consists of 1,880 manufacturing firm-years, which listed on the Korean Exchange between 2014 and 2017. We analyze the effect of innovation efficiency on operating performance using a model of Hirshleifer et al. (2013) results show that both innovation efficiency variables have a significantly positive relationship with the total asset operating margin. Besides, the following year's performance, measured by the total asset operating cash flow ratio, also shows a positive relationship with the two innovation efficiency variables at the 5% and 1% significance levels, respectively. The results indicate that high innovation efficiency firms that link the outcomes of R&D to more patent applications realize higher operating performance. Also, we divided the R&D-intensive and non-R&D-intensive industries and performed the same analysis. As a result, the innovation efficiency has a significant positive effect on operating margin in both industries. However, the effect of innovation efficiency on the operating cash flow is only significant in R&D-intensive industries. This study suggests that the effects of innovation efficiency are more consistent in the R&D-intensive industry. Additionally, we divided the high patent application and low patent applications industries and performed the same analysis. As a result, the innovation efficiency has a significant positive effect on operating margin in both industries. This study suggests that the effects of innovation efficiency are more consistent in the high patent application industry. We show that a firm's innovation efficiency is a critical factor for a firm's performance, while prior studies on the R&D performance have not considered the innovation efficiency of each firm. The evidence suggests that firms not only consider R&D expenditures but also improve the performance of companies by increasing innovation efficiency. Investors need to consider their innovation efficiency when evaluating the value of firms.

• 한국정보디스플레이학회:학술대회논문집
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• 2007.08b
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• pp.1253-1256
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• 2007

A display device combining plasma display panel (PDP) and field emission display (FED) is proposed to achieve high luminous efficiency. The device can avoid the main energy loss channels of both PDP (ion loss) and FED (low CL efficiency). $2{\sim}6$”-diagonal test panels with carbon nano-tube (CNT) electron emitter and Xenon ambient gas showed the luminous efficiency of 4.14lm/W and brightness of $263cd/m^2$ at 35V (1kHz, 1% duty), indicating that it is a good candidate for the low voltage driven, highly efficient next generation display.

• Journal of Korean Society of Industrial and Systems Engineering
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• v.42 no.2
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• pp.62-68
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• 2019

The growth and employment effects of R&D investment were analyzed according to business size, export value and manufacturing sectors so as to suggest improvement directions for effective industry policies. The effect of R&D investment was considered simultaneously from the two perspectives of growth and employment effect, and the causality analysis was carried out by using a path analysis. The result of the path analysis confirmed significant differences in the growth effect of R&D investment depending on business size. However, the effect of increasing employment was difficult to obtain statistically significant results for any various combinations of business size and export value. This is a mixture of directions for the effects of R&D investment on employment, which could be due to the failure to consider appropriate time lags between investment and effect. Efficiency analysis by industry sectors confirmed significant differences in efficiency depending on business size, but differences depending on export value were difficult to identify. In order to derive improvement policy by industry sector according to business size and export value, the direction of selective support policy and universal support policy was derived for six industry groups by combining the return to scale in the efficiency analysis and R&D concentration. Hirschman-Herfindahl index is used for calculating R&D concentration.