• Proceedings of KOSOMES biannual meeting
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• 2006.11a
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• pp.245-251
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• 2006

This is paper aims to evaluate allocation order of SRU using Analytic Network Process. For evaluation, in this paper, assess about person, ship and environment related risk by fuzzy logic and AHP(Analytic hierarchy Process). Also, quantity and quality operation efficiency assess by DEA (Data Envelopment Analysis) and Liquate scale. finally total weight calculate by ANP. At the result, Rescue Units of MP, YS RCC/RSC is order higher. Thus, it needs to have more rescue ships and rescue devices for relieving the risk in the future.

• Journal of the Korean Society of Marine Environment & Safety
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• v.13 no.2 s.29
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• pp.155-160
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• 2007

This paper aims to evaluation of order for allocation of rescue unit using Analytic Network Process. For evaluation, in this paper, assess about person, ship and environment related risk by fuzzy logic and AHP(Analytic hierarchy Process). Also, quantity and quality operation efficiency assess by DEA(Data Envelopment Analysis) and Liquate scale. finally total weight calculate by ANP. At the result, Rescue Units of MP, YS RCC/RSC is order higher. Thus, it needs to have more rescue ships and rescue devices for relieving the risk in the future.

• 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.

• Journal of the Korean Statistical Society
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• v.30 no.2
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• pp.265-280
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• 2001

Estimation of the edge of a distribution has many important applications. It is related to classification, cluster analysis, neural network, and statistical image recovering. The problem also arises in measuring production efficiency in economic systems. Three most promising nonparametric estimators in the existing literature are introduced. Their statistical properties are provided, some of which are new. Themes of future study are also discussed.

• 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.

• International Journal of Advanced Culture Technology
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• v.12 no.2
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• pp.167-179
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• 2024

This study addresses the challenge of objectively evaluating the performance of early-stage startups amidst limited information and uncertainty. Focusing on companies selected by TIPS, a leading private sector-driven startup support policy in Korea, the research develops a new indicator to assess technological efficiency. By analyzing various input and output variables collected from Crunchbase and KIND (Korea Investor's Network for Disclosure System) databases, including technology use metrics, patents, and Crunchbase rankings, the study derives technological efficiency for TIPS-selected startups. A prediction model is then developed utilizing machine learning techniques such as Random Forest and boosting (XGBoost) to classify startups into efficiency percentiles (10th, 30th, and 50th). The results indicate that prediction accuracy improves with higher percentiles based on the technical efficiency index, providing valuable insights for evaluating and predicting startup performance in early markets characterized by information scarcity and uncertainty. Future research directions should focus on assessing growth potential and sustainability using the developed classification and prediction models, aiding investors in making data-driven investment decisions and contributing to the development of the early startup ecosystem.

• Advances in Energy Research
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• v.5 no.2
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• pp.147-177
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• 2017

This study aims to evaluate and prioritize ten different sites in Iran's Khorasan provinces for the construction of wind farm. After studying the geography of the sites, nine criteria; including wind power, topography, wind direction, population, distance from power grid, level of air pollution, land cost per square meter, rate of natural disasters, and distance from road network-are selected for the analysis. Prioritization is performed using data envelopment analysis (DEA). The developed DEA model is validated through value engineering based on the results of brainstorming sessions. The results show that the order of priority of ten assessed candidate sites for installing wind turbines is Khaf, Afriz, Ghadamgah, Fadashk, Sarakhs, Bojnoord, Nehbandan, Esfarayen, Davarzan, and Roudab. Additionally, the outcomes extracted from the value engineering method identify the city of Khaf as the best candidate site. Six different wind turbines (7.5 to 5,000 kW) are considered in this location to generate electricity. Regarding an approach to produce and store hydrogen from wind farm installed in the location, the AREVA M5000 wind turbine can produce approximately $337ton-H_2$ over a year. It is an enormous amount that can be used in transportation and other industries.

• Journal of Korea Technology Innovation Society
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• v.13 no.4
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• pp.794-816
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• 2010

To explore the answer on how the evaluators' network affects efficiency of National R&D Program, this paper analyzes the network of evaluators who attended the peer-review committee for National Nuclear R&D Program from 2007 to 2008. The result derived from network analysis was applied to measure the efficiency of programs by Data Envelopment Analysis. The result shows that the weaker network produces higher efficiency as much as the research result itself. Along with the expertise of evaluators themselves, this paper implies that network should be considered as a main item for evaluation.

• Journal of Technology Innovation
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• v.20 no.3
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• pp.255-285
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• 2012

As the environmental performance is getting important in global automotive industry sector, there is a need to build the intellectual capacity. Hence it is important to measure the performance of the green car patent development of global automotive companies. To do this, we propose to use Data Envelopment Analysis(DEA) Model with Analytic Network Process(ANP), which generates weight coefficients of inputs and outputs for DEA-AR(Assurance Region) model. We considered three inputs: corporate asset, R&D expenditures, number of employees, and three outputs: patent counts, patent citations and patent claims. The results showed that our model could measure the potential of green car technology, and we could see the trend of the green car industry sector.

• Journal of Navigation and Port Research
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• v.36 no.7
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• pp.535-544
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• 2012

In order to improve the overall ASEAN maritime transport network, each port's efficiency is regarded as a crucial factor that should be calculated periodically. This study evaluated the relative efficiency of container port operations of 32 ports belonging to 9 ASEAN nations using Data Envelopment Analysis (DEA). It found that 2 out of 32 ports in 2010 were measured as efficient ports. This study yielded two major findings. Firstly, the ports assessed as inefficient need to benchmark similar ports in size and structure from the ports that are assessed as efficient to improve their efficiency. Secondly, these results could be used to determine potential candidates and country for an international port development co-operation programme with Korea to improve the performance of the entire ASEAN port network by developing the infrastructures of ill-equipped ports.