• The Journal of the Korea Contents Association
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• v.20 no.4
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• pp.14-24
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• 2020

This paper aims to establish an efficient national R&D Application Programming Interface (API) management system for national R&D data-driven management and explore the possibility of using operational data according to the recent global data openness and sharing policy. In accordance with the trend of opening and sharing of national R&D data, we plan to improve management efficiency by analyzing operational data of the national R&D API service. For this purpose, we standardized the parameters for the national R&D APIs that were distributed separately by integrating the individual APIs to build a national R&D API management system. The results of this study revealed that the service call traffic of the national R&D API has shown 554.5% growth in the year as compared to the year 2015 when the measurement started. In addition, this paper also evaluations the possibility of using operational data through data preparation, analysis, and prediction based on service operations management data in the actual operation of national R&D integrated API management system.

• Journal of Korea Technology Innovation Society
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• v.21 no.2
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• pp.663-683
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• 2018

This study aims to analyze the effectiveness of R&D tax credit for SMEs. We surveyed to collect the information on firm's financial statements and R&D tax credit during 2014-2016, and implemented fixed effect model, random effect model and panel negative binomial model. The results show that the effect of R&D tax credit is 5.3 times larger in terms of R&D expenditure and 4.3 times bigger in terms of number of researchers than that of R&D subsidy. In addition, the effect of tax credit on non-metropolitan area companies is higher than that in the metropolitan area. Based on these results, we suggests three ways to improve the R&D tax incentive system for SMEs; To convert unused R&D tax credit of the start-ups to tax points, to exempt the minimum tax rate on R&D expenditure in equipment, and to unify the operation of various R&D tax credit institution.

• Journal of Korea Technology Innovation Society
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• v.21 no.4
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• pp.1268-1295
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• 2018

This study examines the effects of policy mix on R&D efficiency in by using data from 2014 and 2016 Korean Innovation Survey. The DEA-Tobit analysis is used to estimate the impact of policy mix on relative R&D efficiency. As a result of the DEA analysis, the R&D efficiency of the Korean manufacturing industry firms is low, because the R&D investment has not been used effectively. According to the Tobit model, policy mix have a positive effect on R&D efficiency. In particular, the combination of market-oriented, market supply-oriented, and supply demand-oriented policy mix showed a positive relationship with R&D efficiency. R&D portfolio is necessary to improve R&D efficiencies and government has to facilitate a policy mix in view of the nature of firms and Consistency of policy tools.

• Journal of Technology Innovation
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• v.18 no.1
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• pp.75-98
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• 2010

The purpose of this paper is to give policy implications for relevant policy-makers by analyzing factors affecting performance of industrial R&D programs of the Ministry of Knowledge Economy. The independent variables are type of project leader organization(Big Enterprises, SMEs, Ventures Businesses, Public Research Institutions, Universities), cooperative or noncooperative R&D among industry-university-research institution, total number of project participant organization, total R&D investment, and the ratio of private investment to total R&D investment. The dependent variables are domestic or foreign patents granted and domestic or foreign papers accepted. The method of analysis is Poisson Regression analysis operated by STATA. The results of this research are follows ; Universities show higher R&D performance compared to enterprises or public research institutions in terms of patents and papers as well. Venture businesses show higher patent performance compared to SMEs. Inverted U-shaped relationship between total number of project participant organization and R&D performance is not supported. The higher total R&D investment, the higher R&D performance. The higher the ratio of private investment to total R&D investment, the higher R&D performance.

• Proceedings of the Korea Technology Innovation Society Conference
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• 2005.05a
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• pp.18-32
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• 2005

본 연구는 IT 기업의 R&D활동의 성과를 파악하는 것을 목적으로 한다. 공공 R&D의 성과에 대한 연구는 상당부분 진척이 이루어졌으나, 경제의 주체인 민간기업의 R&D 활동에 대한 연구는 부족한 실정이다. 이 연구목적을 위하여, 기업의 재무자료를 이용하여 R&D투자액을 집계하였으며, IT기업의 경영성과도 분석하였다. 분석한 결과를 간단하게 요약하면, 다음과 같다. 첫째, IT기업은 대기업의 R&D투자 비중이 $93.6\%$에 달한다. IT R&D 투자 상위 10개 기업이 IT 산업에서 매출액의 $71\%$, 종업원의 $61\%,$ R&D 투자의 $87\%$를 차지한다. 둘째, 기업의 투자활동은 선택과 집중의 원칙에 따라 R&D 투자에 주력하는 경향이 강해졌다. 유형자산투자는 급격한 감소를 보이는 반면, R&D투자는 증가하고 있다. 셋째, IT 중소기업의 R&D투자는 한계가 있을 수밖에 없다. 본 연구에서 나타난 분석결과의 시사점을 보면, IT 중소기업의 R&D 투자는 한계가 있을 수밖에 없다. 따라서 중소기업의 R&D투자의 효율성을 높여주는 한편, 미래성장의 seed에 대한 준비와 단기 개발연구를 통해 기업의 수익에 기여할 수 있도록 해야 할 것이다. 또한 IT 대기업과 중소기업의 R&D에 대한 효율적인 네트워크를 구축하는 것도 IT기업의 활성화를 위해 요구된다.

• 한국정보디스플레이학회:학술대회논문집
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• 2004.08a
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• pp.1049-1052
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• 2004

In general, contrary to the CRTs with impulsive emission, liquid crystal displays have motion artifacts such as blurring. ghost image, decrease of dynamic CR(contrast ratio), and stroboscopic motion due to hold type driving method. In this paper, to improve motion picture quality of LCDs. impulsive driving method of black data insertion was applied to the OCB mode which is well known for its fast LC response time and wide viewing angle properties. Subject evaluation was carried out with CRT, TN, SIPS(Super IPS). and impulsive driving OCB. Moving picture image quality near CRT was obtained in impulsive OCB driving mode

• Asian Journal of Innovation and Policy
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• v.5 no.3
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• pp.315-329
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• 2016

Public R&D investment information has diverse implications for researching R&D trends. Also, as it is important for the establishment of R&D policy to grasp the current situation and trends of R&D to improve science and technology level, science and technology information service system, such as NTIS (National Science & Technology Information Service), is operated at a national level in most countries. However, since the data forms provided by current NTIS are raw data, it is necessary to develop the R&D performance indicator or to use additional scientometric methods by analyzing scientific papers or scientific R&D project information for grasping R&D trends or analyzing R&D task results. Thus, this study applied public R&D investment information to investigate and monitor R&D trends in the field of information & communication technology (ICT) of meteorology and climatology by using NTIS data of Korea and NSF (National Science Foundation) data of USA.

• Journal of Technology Innovation
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• v.11 no.2
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• pp.123-149
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• 2003

The paper examines the effects of tax incentives on corporate R&D expenditures. We regress tax incentives and financial variables on the increase or the level of corporate R&D expenditures. Tax incentive variables are the magnitude of R&D tax credit and the level of reserve for R&D, while financial variables are the amount or increase of R&D expenditures in prior years, profitability, cash flows and Tobin Q. Sample firms are selected among the listed companies which reported R&D expenditures in the financial statements from 1995 to 2000. The results indicate that increase and level of R&D expenditures is positively influenced by the magnitude of R&D tax credit and the level of reserve for R&D. The amount of R&D expenditures has positive relationship with prior one-year R&D expenditures, while the increase of R&D expenditures has negative relationship with prior year increase and recent three year's average of R&D expenditures. The evidence is consistent to the hypothesis and results of other studies, which suggest that tax incentives for R&D encourage the corporate R&D expenditures.

• Journal of Korean Institute of Industrial Engineers
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• v.43 no.2
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• pp.90-99
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• 2017

As the importance of R&D has increased, there have been various efforts to apply the quality management principles and tools to R&D activities in order to manage them effectively. The R&D sector differs from other value chains, so it may be difficult to apply quality management without proper considerations of R&D characteristics. This study describes the characteristics of R&D as high uncertainty and risk, diversity of R&D types, project-based activities, importance of strategic goals and business models, and importance of intangible assets. Three well accepted R&D quality management models are reviewed and implications for quality management and R&D characteristics are summarized. Based on these findings, the management targets of R&D quality management are classified into management level (organization, project) and management focus (process, output), and the contexts of R&D quality management are classified into R&D type (research, development) and market/customer requirement clarity (fluid, specific), and appropriate R&D quality management activities in each situations have been suggested.

• Journal of Korean Society of Industrial and Systems Engineering
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• v.41 no.4
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• pp.101-110
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• 2018

This study aims to objectively measure the efficiency of nanotechnology R&D programs by systematically evaluating the inputs and outputs of nanotechnology R&D activities and to find implications for improving the efficiency of nanotechnology R&D programs. Data on input factors such as R&D investment, R&D manpower, R&D period, and output factors such as paper, patent, and commercialization for R&D projects which started from 2008 or afterwards and ended by 2011 are gathered through National Science and Technology Knowledge Information Service, which are used for efficiency evaluation. In this study, we analyzed R&D efficiency in detailed technology units in depth. The process taken in this study is as follows. First, the basic statistics of input and output factors to compare and analyze R&D investment, R&D manpower, R&D period, paper, patent, and commercialization status by technology unit are analyzed. Next, DEA models are utilized to derive the overall efficiency, pure technology efficiency, and scale efficiency by conducting the efficiency evaluation for each technology unit, from which implications for strategic budget allocation are derived. In addition, partial efficiency evaluation is conducted to identify advantages and disadvantages of each technology unit. In turn, cluster analysis is performed to identify similar technology units, from which implications for efficiency improvement are derived.