• The Journal of shipping and logistics
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• v.27 no.3
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• pp.457-474
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• 2011

The aim of this study is to analyze the efficiency of major ports in Northeast Asia such as Korea, China and Japan. For the empirical analysis, we tried to apply the data envelopment analysis (DEA), which is an efficiency evaluation model based on mathematical programming theory, and we also established a model to Northeast Asian ports. In our opinion, DEA analysis which involves multiple inputs as well as multiple outputs in its efficiency valuation makes analysis more suitable for port efficiency measurement because ports produce a number of different outputs. In this paper, we attempted to analyze the relative efficiency of 27 ports (5 Korean ports, 13 Chinese ports, 9 Japanese ports) through DEA-CCR, DEA-BCC models. According to the result, Chinese ports are relatively efficient than Korean and Japanese ports. The result of the analysis shows that 7 Chinese ports are efficient in DEA-CCR model in 2009, but in DEA-BCC model 8 Chinese ports and 1 Koran port are efficient. Most of inefficient ports have a value closed to 1 in efficiency for scale, it means that the reason of inefficiency is caused from the technical aspect. Furthermore, we also verified that there exists excess of input in Korean and Japanese ports than Chinese ports.

• Journal of Digital Convergence
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• v.16 no.6
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• pp.75-84
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• 2018

Although many logistics companies are interested in project logistics, the existing research has been limited to the growth potential of project logistics market and the high barrier and importance of project logistics. This study analyzes using DEA the operational efficiency of forwarding companies registered in major overseas construction EPC companies and performing logistics services for overseas plant construction projects. For efficiency analysis, Super-SBM analysis and Malmquist analysis are used among DEA analysis techniques. As a result of the Super-SBM analysis, DMU 5 ranked first at 1.807. DMU 5 is more efficient than the other large corporations because it has the stable supply of its parent company H and the smallest input and output variables among the large corporations. As a result of Malmquist analysis, TCI, which is a technological development, showed a fluctuation while TECI showed a relatively stable variation. In addition, there is a difference in scale between major companies and small and medium sized companies. So, it is necessary to identify the efficiency improvement strategy for each group and apply it to the practical work.

• Journal of Navigation and Port Research
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• v.30 no.10 s.116
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• pp.793-800
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• 2006

The purpose of this paper is to show a way for extracting the core input and output variable in Korean seaports by using principal component analysis and DEA(data envelopment analysis). Two inputs(birthing capacity, and cargo handling capacity) and three outputs(export cargo handling amount, import cargo handling amount, and number of ship calls), and three cross sectional data(1995, 2000, and 2004) for 26 Korean seaports are considered for measuring the efficiencies of 21 DEA models. 21 models can be treated as variables and efficiencies as observations for extracting the core inputs and outputs variables by using principal component analysis. An empirical main result indicates that core input variable is cargo handling capacity, and core output is the number of ship calls. The Korean seaport authority can adopt the DEA and principal component analysis for deciding the development and investment to each seaport.

• Journal of Intelligence and Information Systems
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• v.7 no.1
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• pp.63-79
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• 2001

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 and merits, some features of DEA remain bothersome. DEA offers no guideline about to which direction relatively inefficient DMUs improve since a reference set of an inefficient DMU, several efficient DMUs, hardly provides a stepwise path for improving the efficiency of the inefficient DMU. In this paper, we aim to show that DEA can be used to evaluate the efficiency of life insurance companies while overcoming its limitation with the aids of machine learning methods.

• Journal of Korean Library and Information Science Society
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• v.40 no.2
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• pp.491-514
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• 2009

The supply of public libraries in Korea has been rapidly improving because of the recent increase for cultural demands and revitalization of the local culture. This paper aims to analyze the efficiency about 565 public libraries using Clustering DEA/AHP(CDA) model. This model is employed the efficiency analysis in order to incorporate project irreversibility and division due to the limit of resources spending. The results shows that the public libraries are divided into three groups which are large size libraries(Group 1), middle size libraries(Group 2) and small size libraries(Group 3). Their average efficiency was found as 0.89, 0.72 and 0.60 each.

• The Journal of the Korea Contents Association
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• v.8 no.8
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• pp.147-157
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• 2008

ERP is the general trend of industrial information system and many companies are introducing strategically to strengthen the competitive power. This paper analyzes the efficiency of introducing companies of ERP system using DEA model. We also suggest the introducing of ERP system which can be benchmarked based on analyzed information. We evaluate the CCR, BCC efficiency and RTS of 38 introducing companies of ERP system. The result shows that three enterprises whose values of CCR efficiency are 1, and seven enterprises whose values of BCC efficiency are 1. RTS indicates IRS of 22 companies. DRS of 2 companies and CRS of 4 companies.

• Journal of Korea Port Economic Association
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• v.25 no.3
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• pp.229-250
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• 2009

This paper aims to implement an empirical research about the efficiency of America and Northeast Asia pots, and to suggest an effective strategy which can operate these ports more well. This study tries to apply the Data Envelopment Analysis(DEA) model to America and Northeast Asia ports. DEA is a methodology of comparing the relative efficiency of each decision making unit(DMU) by comparing it with other DMUs having similar input and output structure, and is specially very useful when a form of production function of each DMU such as a port is not known. DEA provides the extent of inefficiency of DMUs, which is practically useful information (like the efficiency score and reference sets) required to improve efficiency. This paper analyzed the relative efficiency of 35 ports in America and Northeast Asia for 3 years from 2005 to 2007 through DEA-CCR, DEA-BCC model and scale efficiency. Accordingly, this paper evaluates the efficiency of America and Northeast Asia ports, grasps the position at the present time, and suggests an advanced direction in future.

• Asia-Pacific Journal of Business Venturing and Entrepreneurship
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• v.8 no.2
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• pp.161-174
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• 2013

The purpose of this study was to examine the efficiency of senior welfare centers and the cause of differences among senior welfare centers in that regard, and to investigate influential factors for the differences in efficiency and the size of the influence of the factors. What methods would be effective at assessing the efficiency of senior welfare centers by taking into account their circumstances was reviewed, and post-hoc analyses were made by using data envelopment analysis(DEA) and Tobit analysis, which were useful tools to evaluate relative efficiency. After 24 senior welfare centers located in Seoul were selected, their yearly operating data of 2011 were utilized. In this study, we set limits to the medical welfare of the elderly welfare services business, and divided into model 2 including the elderly population in the region and model 1, input factors for only internal factors, such as full-time workers. We calculated a valid result by proceeding a BCC analysis and analysis of CCR respectively. As this study has some limitations, follow-up research should be implemented. Yet this study is of significance in that it attempted to present general norms for the efficiency analysis of senior welfare centers by using a DEA model and made various post-hoc analyses based on the efficiency data to give significant suggestions on the service of senior welfare centers.

• Journal of Korea Port Economic Association
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• v.40 no.1
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• pp.87-118
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• 2024

Coastal ports play an essential role in developing a country and a city. Port efficiency is an important factor affecting port trade, and the importance of port efficiency for port performance has been recognized in previous literature. DEA (Data Envelopment Analysis) and SFA (Stochastic Frontier Analysis) are widely used in this field of research. However, these two methods are limited in selecting input and output variables. In addition, the literature studies on Chinese coastal ports mainly focus on the study of port clusters in local areas, which lacks a holistic approach and generally lacks up-to-date data. Therefore, to fill the gap in this area of research, this paper introduces a model combining principal component analysis and data envelopment analysis to analyze the operational efficiency of the top 17 coastal ports in China in terms of throughput based on the most recent data available in 2021. This paper identifies container throughput as the output variable, and 13 second indicators are selected as input variables from four primary indicators: land, capital, labor, and infrastructure. Four principal components were selected from 13 second indicators using PCA.After that, DEA (BBC) and DEA (CCR) were used to analyze the 17 ports, among which five were Shanghai, Ningbo-Zhoushan, Guangzhou, Xiamen, and Dongguan, respectively, DEA efficient, and the remaining 12 ports were non-DEA efficient. Finally, improvement directions for each port are derived, and brief suggestions are made. This paper provides some reference value for developing and constructing coastal ports in China.

• Journal of the Korean Society for Railway
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• v.12 no.6
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• pp.1030-1036
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• 2009

In 1990's, in Europe and some advanced nations, the structural reform of the railroad industry for improving the productive efficiency of the railroad industry and competitive power had been progressed. This paper empirically explores the relationship between railway restructuring and productive efficiency in the railway industry. We use Data Envelopment Analysis (DEA) to construct efficiency scores, and explain these scores, using Tobit regression analysis by using variables reflecting institutional factors and organizational type. Our results suggest that vertical separation, infrastructure and services are separated, and horizontal separation, passenger service and freight service are separated, improve productive efficiency. We also find that market competition has positive effect on the efficiency, but independent management from the government has negative effect, which is in line with economic intuition as well as with expectations on the railway restructuring. As a consequence, increased independence without sufficient competition and adequate regulation may deteriorate incentives for productive efficiency.