• 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.

• Proceedings of the Korea Contents Association Conference
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• 2017.05a
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• pp.71-72
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• 2017

최근 빅데이터 분석력 강화와 과학기술정보 콘텐츠 기반의 R&D 전략 수립의 중요성이 강조됨에 따라 국내외 주요 과학기술 통계와 정보를 수집, 범주화하여 DB를 구축하고 국가 기초연구지원을 위한 정책을 수립하는데 활용하고자 하였다. 과학기술 통계 정보 콘텐츠 DB를 기반으로 빅데이터 심층분석을 실시하여 우리나라 R&D 경쟁력과 효과성을 보여주고 본 DB 활용성의 확장에 대해 고찰하였다.

• Journal of Information Technology Services
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• v.7 no.3
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• pp.31-45
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• 2008

The number of national research and development(R&D) projects have been continually increased, and it is necessary that the efficiency of investment of R&D projects have been improved during the last two decades. also the government has improved national R&D process and supporting tools for the projects. However, it is not enough to develop a quality model to evaluate the projects systematically. Therefore, a quality model for national R&D projects need to be revised. The quality model for the projects should be based on the global standard(ISO/IEC 9126). In this paper, the authors proposed a quality model for national R&D projects and took a case study for verification of the quality model. The quality model is defined in terms of functionality, reliability, usability, efficiency, portability and maintainability. Also, the authors suggest metrics for measuring the quality of products or services. finally, The productivity and quality of national R&D projects will be improved by the quality model.

• Journal of Internet Computing and Services
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• v.21 no.3
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• pp.61-70
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• 2020

The 4th Industrial Revolution is a revolutionary change through intelligence, big fusion and personalization, and the importance of sensor technology that is the basis of core technology is emerging. This study empirically analyzes the derivation of national strategy for R&D of sensor technology, and draws out the effect of technology internalization effort through strategic R&D activities on technical performance and further on national economy. The research and development results are calculated for each type of technology internalization, and the results of the research and development are verified to establish a structure that contributes to the national economic performance. As a national technology internalization strategy, considering its own R&D investment and joint research and development, we examine the impact of each factor on patents and GDP, focusing on causality and ripple effects. For causality analysis, Grandeur causality analysis shows that R&D investment and joint research and development in all countries have mutual causal relationship with GDP. The implications are as follows. First, it is necessary to establish the policy of national economic development through the internalization of technology and knowledge. Second, it is necessary to establish policies according to the type of knowledge internalization. Third, it will be necessary to create an ecosystem environment based on a virtuous relationship between knowledge internalization and national technology and economic development.

• Knowledge Management Research
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• v.22 no.3
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• pp.91-106
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• 2021

With the recent rapid development of deep learning technology, the demand for analyzing huge text documents in the national R&D field from various perspectives is rapidly increasing. In particular, interest in the application of a BERT(Bidirectional Encoder Representations from Transformers) language model that has pre-trained a large corpus is growing. However, the terminology used frequently in highly specialized fields such as national R&D are often not sufficiently learned in basic BERT. This is pointed out as a limitation of understanding documents in specialized fields through BERT. Therefore, this study proposes a method to build an R&D KoBERT language model that transfers national R&D field knowledge to basic BERT using further pre-training. In addition, in order to evaluate the performance of the proposed model, we performed classification analysis on about 116,000 R&D reports in the health care and information and communication fields. Experimental results showed that our proposed model showed higher performance in terms of accuracy compared to the pure KoBERT model.

• Journal of the Korean Society of Industry Convergence
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• v.25 no.2_2
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• pp.219-232
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• 2022

The aim of this study is to provide the dynamic convergence index that reflected the inherent characteristics of the convergence phenomenon and utilized the nationally-funded R&D projects data, thereby suggesting useful information about the direction of the national convergence R&D strategy. The dynamic convergence index that we suggested was made of two indicators: persistency and diversity. From a time-series perspective, the persistency index, which measures the degree of continuous convergence of multidisciplinary nationally-funded R&D projects, and the diversity index, which measures the degree of binding with heterogeneous research areas. We conducted the empirical experiment with 151,248 convergence R&D projects during the 2015~2021 time period. The results showed that convergence R&D projects in both public health and life sciences appeared the highest degree of persistency. It was presumed that the degree of persistency has increased again due to the COVID-19 pandemic. Meanwhile, the degree of diversity has risen with combining with disciplinary such as materials, chemical engineering, and brain science areas to solve social problems including mental health, depression, and aging. This study not only provides implications for improving the concept and definition of dynamic convergence in terms of persistency and diversity for national convergence R&D strategy but also presented dynamic convergence index and analysis methods that can be practically applied for directing public R&D programs.

• Journal of Korean Institute of Industrial Engineers
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• v.41 no.2
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• pp.150-161
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• 2015

This paper proposes a new approach to technology valuation, the market-replacement cost approach which integrates the cost-based approach and market-based approach. The proposed approach estimates the market-replacement cost of a target technology using R&D costs of similar R&D projects previously conducted. Similar R&D projects are extracted from project database based on document similarity between project proposals and technology description of the target technology. R&D costs of similar R&D projects are adjusted by mirroring the rate of technological obsolescence and inflation. Market-replacement cost of the technology is then derived by calculating the weighted average of adjusted costs and similarity values of similar R&D projects. A case of "Prevention method and system for the diffusion of mobile malicious code" is presented to illustrate the proposed approach.

• Journal of Information Technology Applications and Management
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• v.22 no.3
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• pp.83-103
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• 2015

The rapid development of internet technologies and social media over the last few years has generated a huge amount of unstructured text data, which contains a great deal of valuable information and issues. Therefore, text mining-extracting meaningful information from unstructured text data-has gained attention from many researchers in various fields. Topic analysis is a text mining application that is used to determine the main issues in a large volume of text documents. However, it is difficult to identify related issues or meaningful insights as the number of issues derived through topic analysis is too large. Furthermore, traditional issue-clustering methods can only be performed based on the co-occurrence frequency of issue keywords in many documents. Therefore, an association between issues that have a low co-occurrence frequency cannot be recognized using traditional issue-clustering methods, even if those issues are strongly related in other perspectives. Therefore, in this research, a methodology to reorganize social issues from a research and development (R&D) perspective using social network analysis is proposed. Using an R&D perspective lexicon, issues that consistently share the same R&D keywords can be further identified through social network analysis. In this study, the R&D keywords that are associated with a particular issue imply the key technology elements that are needed to solve a particular issue. Issue clustering can then be performed based on the analysis results. Furthermore, the relationship between issues that share the same R&D keywords can be reorganized more systematically, by grouping them into clusters according to the R&D perspective lexicon. We expect that our methodology will contribute to establishing efficient R&D investment policies at the national level by enhancing the reusability of R&D knowledge, based on issue clustering using the R&D perspective lexicon. In addition, business companies could also utilize the results by aligning the R&D with their business strategy plans, to help companies develop innovative products and new technologies that sustain innovative business models.

• Journal of the Korean BIBLIA Society for library and Information Science
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• v.16 no.1
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• pp.269-283
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• 2005

Research and Development projects sponsored by the government are one of the main production sectors of academic and research information in domestic area. The access control and information service of R&D outcomes should be considered as a critical factor of nation-wide knowledge-based IS management. This study focused on the practical utilities of three IPR legislations of the government projects and analyzed if they are good enough to support the information service in recent digital network environment. Some suggestions in different perspectives were provided for the improvement of the existed IPR legislation.

• Korean Management Science Review
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• v.16 no.1
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• pp.63-74
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• 1999

This paper presents a R&D investment model for the Information and telecommunications(l&T) technology using multiple objective linear programming(MOLP). The MOLP model involves the simultaneous maximization of three linear objective functions associated with three criteria, which are social, technological, and economic criterion. This model is different from the traditional one which only involves the maximization of economic criterion. It yields a suitable R&D investment ratio to each technology field. Its application to the National R&D Project in l&t Industry is also presented. In this application, the Analytic Hierarchy Process(AHP) is proposed to estimate the weights, which used as the coefficients in each objective function of the MOLP model. Then the problem is solved using the interactive method STEM. It is showed that with the aid of STEM, the MOLP model can be useful decision aid in formulation R&D investment plan in l&t industry. It is expected that the MOLP model works as the basis for planning R&D investment strategy in l&T industry.