• Journal of Information Technology Services
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• v.22 no.1
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• pp.57-74
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• 2023

It has been pointed out as a limitation that the rank of some efficient DMUs(decision making units) cannot be discriminated due to the relativity nature of efficiency measured by DEA(data envelopment analysis), comparing the production structure. Recently, to solve this problem, a DEA-SNA(social network analysis) model that combines SNA techniques with data envelopment analysis has been studied intensively. Several models have been proposed using techniques such as eigenvector centrality, pagerank centrality, and hypertext induced topic selection(HITS) algorithm, but DMUs that cannot be ranked still remain. Moreover, in the process of extracting latent information within the DMU group to build effective network, a problem that violates the basic assumptions of the DEA also arises. This study is meaningful in finding the cause of the limitations by comparing and analyzing the characteristics of the DEA-SNA model proposed so far, and based on this, suggesting the direction and possibility to develop more advanced model. Through the results of this study, it will be enable to further expand the field of research related to DEA.

• Journal of Korea Technology Innovation Society
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• v.3 no.3
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• pp.36-52
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• 2000

This study takes an issue of efficiency analysis in the presence of network effect utilizing the DEA (Data Envelopment Analysis) framework. Network effect has important policy implication for the regulation of local monopolies which undertake their business through physical network, such as electricity, natural gas, local telephony, etc. If the difference in spatial condition between companies is not controlled properly, the performance comparison and associated incentive regulation bear significant bias. In this study, we propose a methodology to measure the true managerial or technical efficiency apart from efficiency difference accruing from the difference in spatial condition. A series of modified DEA efficiency models are combined to investigate the extent of exogenous and endogenous efficiency component in the Korean natural gas distribution companies. Empirical results show that the network effect plays significant role in determining superficial performance difference.

• Proceedings of the KOR-KST Conference
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• 2007.02a
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• pp.97-105
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• 2007

• Journal of Environmental Policy
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• v.14 no.2
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• pp.27-47
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• 2015

In this paper, we present a new empirical method to estimate the environmental efficiency of decision making units. We propose a model with a new approach that describes a network process consisting of two stages, production and wastewater abatement based on the data extracted from 51 Korean industrial complexes. Taking into account the inter-dependency of two stages, we show a process how to decompose the environmental efficiency into production efficiency and abatement efficiency. Moreover, our new proposed method can be used to explain the information on network relationship between economic growth and environmental protection.

• Journal of Korea Port Economic Association
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• v.31 no.3
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• pp.155-166
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• 2015

This study selected container terminals of Gwangyang and Busan Ports to evaluate the influence of efficient container terminals. For the study, after data envelopment analysis (DEA) using the CCR and BCC models, the decision-making unit (DMU) system was used to define nodes; and with the use of a reference group in DEA (BCC model) and a lambda value, this study created a social network and analyzed the influences of efficient DMUs through a centrality analysis of eigenvectors. The results are presented as follows: First, as a result of the DEA, CCR efficiencies in PNC, HJNC, and HPNT container terminals of Busan Port were 1 and BCC efficiencies at Singamman Terminal, Wooam Terminal, PNC, HJNC, HPNT, and BNCT container terminals of Busan Port were 1. Second, as a result of undertaking social network analysis (SNA), according to an eigenvector centrality analysis, HJNC Terminal was referred to the most (influence score of 0.515), which indicates that it is the most influential as a container terminal. The influence of PNC Terminal was 0.512, while that of Wooam Terminal was 0.379. CJ Korea Express in Gwangyang Port was ranked fourth in influence, but its influence score of 0.256 indicates that it was the most influential of the container terminals at Gwangyang Port.

• Journal of Digital Convergence
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• v.19 no.2
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• pp.117-133
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• 2021

This study aimed to identify its research trends using social network analysis(SNA). The results of the analysis showed that, for degree centrality, Busan Port(0.223) was the keyword that had the highest centrality, followed by DEA(0.060), AHP(0.056), and container terminal and port competitiveness(0.049). Busan Port(0.245) also had the highest betweenness centrality, followed by DEA(0.048), container terminal(0.044), AHP(0.039), and Busan New Port(0.032). The trend analysis inferred that efficiency analysis(DEA), strategy selection, and competition analysis(AHP) were the keywords with a high centrality for Busan Port to gain a competitive edge with global ports. However, research on the Fourth Industrial Revolution, which is emerging as a key issue, was insufficient. In the future, research using social data, such as mass media and social networks, is necessary.

• Journal of Korea Port Economic Association
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• v.38 no.3
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• pp.29-51
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• 2022

The International Maritime Organization (IMO) designated the Emission Control Area (ECA) in Northern Europe to reduce the NOx and SOx emissions from ships in the coastal areas. This study used Network slack-based measure (SBM) Data Envelopment Model (DEM) and Bootstrop Truncated Regression (BTR) model to analyze the ECA's impact on ferry companies' financial performances based on the financial data from eight ferry carriers in Northern Europe, the Mediterranean and North America from 2004 to 2017. To alleviate the problem of arbitrary variable selection in DEA, the variable selection criteria proposed by Dyson et al. (2001) were applied; the size of the company was considered through the Network SBM DEA model; and the company's profit-generating process was divided into stages to measure financial performance in more detail. In addition, the BTR model was applied to derive results that minimize the bias of the data. The study found that ECA regulations did not always negatively affect the shipping companies' financial performance. Rather, a steady increase in efficiency was observed for Northern European ferry companies which were subject to the strongest regulations. For North American ferry companies, government subsidies were found to have a significant impact on efficiency, and relatively small impact on efficiency due to the ECA and oil prices. For the Mediterranean ferry companies, efficiency values have decreased since the implementation of ECA regulation despite the lowest level of regulation in the region.

• Proceedings of the Korea Technology Innovation Society Conference
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• 2017.11a
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• pp.131-131
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• 2017

그동안 지역혁신체제론의 관점에서 지역연구개발시스템의 효율성을 분석하는 다양한 연구가 수행되었다. 하지만 (1)지역연구개발시스템의 내부 처리과정 고려 미흡과 (2)연구개발의 특수성을 고려하지 못한 효율성의 분석모형 설정, (3)투입 산출지표 설정의 타당성 부족, (4)산출된 효율성 지수의 민감도 분석 소홀 등의 여러 한계점이 존재한다. 특히 5~10년 이내의 단기간으로 접근함에 따라 지역연구개발시스템의 효율성이 어떻게 변모해왔는지 그 역동성을 상세히 고찰하지 못하였다. 따라서 본 연구에서는 1999년~2014년까지 16개 광역지방자치단체를 대상으로 네트워크 자료포락분석(Network Data Envelope Analysis: DEA)의 2단계 접근법(two-stage approach)을 활용해서 지역연구개발시스템의 효율성을 분석하고 주요 개선방향들을 논의하였다.

• 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.

• Journal of Digital Convergence
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• v.11 no.10
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• pp.255-262
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• 2013

Data envelopment analysis(DEA) is a linear programming procedure designed to evaluate the relative efficiency of a set of peer entities called decision making units which use the same inputs to produce the same outputs. It has been widely employed in a variety of disciplines as an efficiency or performance measurement tool for comparing a set of entities such as firms, banks, hospitals, nations and organizations. The method, however, cant's make the priority of their performance when many units have efficiency score of unity or 100 percent. In this paper, we propose a new approach which combine qualitative method(graphical approach using network analysis) and quantitative method(super-efficient analysis using DEA), and present the results of an empirical analysis using the data of the Korean professional baseball players. As a result, there were 12 DMU that priority is hardly realized through DEA. However, this problem could be solved with super-efficiency analyzing. Also, more in-depth interpretation was able through integrating results of dendrogram and super-efficiency analyzing and prospecting it in qualitative, quantitative ways.