• Management & Information Systems Review
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• v.5
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• pp.81-101
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• 2000

The purpose of this comparative study is to compare and evaluate venture business of electronic and communication industry by Data Envelopment Analysis(DEA). DEA is a linear programming-based technique that converts multiple input and output measures into a single comprehensive measures of productive efficiency. In this paper, the CCR model and trend analysis model are used to examine the efficiency of 18 venture business. Input variables are number of employees. raw-material costs and production capability and output variables are real production, sales revenues and net income after taxes. DEA approach broad information like as efficiency level of each Decision Making Unit(DMU), reference group of efficiency improvement and trends of efficiency shift. Finally, the correlation of input and output variables are examined to examine the relationship among variables.

• The Journal of Fisheries Business Administration
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• v.52 no.1
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• pp.23-46
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• 2021

The purpose of this study is to understand the production efficiency of individual fishing communities and provide directions for improvement. The subject of the study is aquaculture type Ochon-Gye in Goheung-gun. The analysis method used bootstrap-DEA to overcome the statistical reliability problem of the traditional DEA analysis technique. In addition, data mining-GIS was applied to identify the spatial productivity of fishing communities. The values of technology efficiency, pure technology efficiency, and scale efficiency were estimated for 32 aquaculture-type fishing villages. Then, using the benchmarking reference set and weights, the projection was presented through adjustment of the input factor excess, and furthermore, the confidence interval of the efficiency values considering statistical significance was estimated using bootstrap.

• Proceedings of the Korean Institute of Navigation and Port Research Conference
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• 2022.06a
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• pp.198-200
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• 2022

With the expansion of the global supply chain, the efficiency of maritime logistics is considered a crucial factor for countries' trade and competitiveness. Nevertheless, prior research has not thoroughly evaluated the efficiency of maritime logistics, including countries' ports and shipping capacities. Accordingly, this study examines integrated maritime logistics efficiency at the national level using DEA-CCR, BCC, and super-efficiency DEA. Furthermore, this study identifies a difference between the selected countries' maritime logistics efficiency and LPI (Logistics Performance Index) through Spearman's correlation test as an ad-hoc analysis. From this, Asian countries showed higher efficiency and European countries showed higher LPI scores. These results might be derived from this difference in port-city development patterns. Additionally, the main cause of inefficiency in Europe and Japan might be attributed to high fleet capacity of control. Consequently, this study can provide valuable implications for coastal countries to set more efficient directions for maritime logistics investment and policy.

• Journal of the Korea Academia-Industrial cooperation Society
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• v.21 no.7
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• pp.517-524
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• 2020

In line with the recent wave of the 4th Industrial Revolution, the environment for defense R&D is transforming into a center of high-tech military technology. In particular, developed countries are strengthening control of technology exports and technology transfer to protect advanced defense science and technology. For this reason, the budget demand for securing the ability to develop independently high-tech weapons and core technologies suitable for the future battlefield environment is increasing, and increasing efficiency in R&D investment has been highlighted for efficient distribution of limited budgets. This study examined the efficiency of the defense basic R&D project using the non-parametric approach, DEA. The R&D budget, R&D researcher, and R&D period were selected as the input variables, and the number of papers and patents were used as output variables. The efficiency of basic R&D projects was analyzed through CCR, BCC models, and SE. Lastly, based on the efficiency measurements, the cause of the inefficiency of R&D projects was suggested, and ways to improve efficiency were suggested. This study is expected to be used as useful information that can be applied to project performance management through efficiency analysis of basic defense R&D projects and be reflected in the project planning stage through feedback.

• Journal of the Korean Society of Marine Environment & Safety
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• v.27 no.6
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• pp.763-774
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• 2021

The COVID-19 virus has generated major shockwaves in all spheres of human life since its outbreak. Maritime transport (both cargo and passenger) is one of the industries most heavily affected, yet over 80% of the world cargo is transported by sea. This study analyzes maritime port operational efficiencies before and after the start of the COVID-19 pandemic to determine whether the pandemic has caused major differences in the operational efficiencies of many leading Asian maritime container ports via data envelopment analysis (DEA). The results of both the CCR and BCC models reveal that overall, efficiency during the COVID-19 pandemic has been higher than before the pandemic despite a few inefficiencies. This implies that the pandemic has so far not has major consequences for the operational efficiency of maritime ports. However, two ports (Busan and Guangzhou) should adjust the scale sizes and technical capacities of their operations to improve performance.

• The Journal of the Korea Contents Association
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• v.19 no.7
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• pp.99-109
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• 2019

Data Envelopment Analysis (DEA), a non-parametric productivity analysis tool, has become an accepted approach for assessing efficiency in a wide range of fields. Despite of its extensive applications, some features of DEA remain bothersome. For example DEA is good at estimating "relative" efficiency of a DMU(Decision Making Unit), it only tells us how well we are doing compared with our peers but not compared with a "theoretical maximum." Thus, in order to measure efficiency of a new DMU, we have to develop entirely new DEA with the data of previously used DMUs. Also we cannot predict the efficiency level of the new DMU without another DEA analysis. We aim to show that DEA can be used to evaluate the efficiency of ports and suggest the methodology which overcomes the limitation of DEA through hybrid analysis utilizing DEA along with C5.0. We can generate classification rules C5.0 in order to classify any new Port without perturbing previously existing evaluation structures by proposed methodology.

• Journal of Korea Port Economic Association
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• v.33 no.4
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• pp.1-16
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• 2017

The total container throughput of ASEAN is expected to increase continuously with economic development. However, ASEAN port infrastructure is insufficient to handle the increasing trade volume. According to the World Economic Forum, ASEAN ports except Singapore and Malaysia are ranked in low. Participation in ASEAN port development projects can lead an increase in trade efficiency with S. Korea by improving the port infrastructure of ASEAN countries. In addition, the S. Korean port-related industry can be energized through entering ASEAN port development projects. This study, which measures the efficiency of ASEAN ports, can be used as a basic guideline for the development and the planning of the ports. This study used Data Envelopment Analysis(DEA) and Shannon's Entropy model together to measure ASEAN ports' efficiency. After measuring each DEA (CCR, I-BCC, O-BCC, SBM) weight, the efficiency of ASEAN ports is measured as reflecting each DEA weight. As a result, the ports of Singapore and Malaysia, the major ports in the world, have the highest efficiency. Further, Vietnamese ports need to raise efficiency along with increasing container throughput. Leam Chabang (Thailand), Ho Chi Minh City (Vietnam), and Tanjung Priok (Indonesia) exhibit a negative correlation between container throughput and efficiency; therefore, the ports need to improve so as to maintain competitiveness. Lastly, Cambodia, Myanmar, and Brunei, which do not have active economic development, need to improve their ports for economic development.

• Asia-Pacific Journal of Business Venturing and Entrepreneurship
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• v.12 no.2
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• pp.125-136
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• 2017

This study focuses on a relative efficiency of 109 operating food companies out of 22 regions in Jeollanam-do. The relative efficiency has been analyzed by 5 input factors(capital, number of employees, annual labor costs, raw material purchase, and site area) and 2 output factors(annual exports and annual production of the companies in Jeollanam-do). This study suggests efficient companies which inefficient companies can benchmark to improve their system in short-mid-long term in phases. The main result of empirical analysis are as follows: Firstly, according to the Traditioanl DEA analysis, 7 companies out of 109 DMU indicate the optimal production scale in score 1 of CCR efficiency value, BCC efficiency value, and scale efficiency value. Secondly, a result from the Tier 1 step of inefficient companies by Post-DEA suggests that it would be better to apply each Tier step to the proper stage of the worst 5 inefficient companies such as Tier 3 step(short-term benchmark)${\rightarrow}$Tier 2 step(mid-term benchmark)${\rightarrow}$Tier 1 step(long-term benchmark) in step. This study expects that the result of the study can reduce the trial and error in inefficient part, lead to improvement, and have a big help in food exporting industry in the end.

• Journal of Korea Port Economic Association
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• v.27 no.4
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• pp.51-71
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• 2011

The purpose of this study is to use DEA modeling to make an analysis on 12 ODCYs in the hinterland of Busan North Port, so that it may propose possible ways to efficiently operate them. For analysis, this study adopted 3 input factors such as CY area, number of employees and number of cargo work equipments and also adopted 1 output factor, i.e. container throughput. According to the analysis DEA-CCR model, it was found that Chunil(YongDang CY) was the most efficient one among companies engaged in the operation of ODCY. And it was found that KCTC(YongDang CY), Kukbo(U-Am CY), KORAIL(BusanJin CY) and Hanjin (JaeSong CY) would need to boost the container throughput 5 or more times higher than current throughput with a view to improving cargo handling efficiency, while Sebang(U-Am CY), KCTC(U-Am CY), KCTC(YongDang CY), Hyopsung(YongDang CY) and Kukbo(U-Am CY) need to work on personnel restructuring targeted to current employees. Based on the analysis DEA-BCC model, it was found that Chunil(YongDang CY), Dongbu(ShinYoung GamMan CY), Intergis(GamMan CY) and Sebang(U-Am CY) were efficient companies, but KCTC(YongDang CY), Kukbo(U-Am CY), KORAIL(BusanJin CY) and Hanjin(JaeSong CY) were inefficient companies. Particularly, it was found that both KCTC(U-Am CY) and Kukbo(U-Am CY) would need to try harder to carry out personnel reshuffle than other comparable companies.

• Journal of the Korea Convergence Society
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• v.12 no.7
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• pp.273-282
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• 2021

Nursing home plays a role in providing elderly care in the context of China's rapid population aging, but little understanding of the efficiency of the nursing homes. In this paper, we investigated the efficiency in nursing homes using Data Envelopment Analysis (DEA) and Malmquist index (MPI) for the modeling of the number of nursing home beds, fixed assets, and medical personnel as input variables, and the number of elderly people of self-care, the number of elderly people of partial self-care, the number of bed-ridden elderly people and the income of nursing homes as output variables. Stratification analysis showed that the top two provinces in the DEA-CCR yield were Beijing and Shanghai in the five-year survey period. Four provinces (Beijing, Jiangsu, Shandong, and Shanghai) scored 1.00 in terms of DEA-BCC yield. The MPI analysis showed that Hainan ranked the highest five-year average in the included provinces. In terms of resource utilization, internal management, operation scale, and other aspects, the nursing homes in the provinces with high-efficiency evaluation results show high efficiency and technological progress, whereas the areas with low-efficiency evaluation showed a feature of the improving technical efficiency.