• Journal of Korea Port Economic Association
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• v.26 no.1
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• pp.1-19
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• 2010

This paper focuses measuring the efficiency of container yards on container terminals in Busan (Gasungdae, Shinsundae, Gamman, New Gamman, Uam, Gamchon, PNC) and Gwangyang(GICT, KEC, Dongbu, KIT) using Data Envelopment Analysis(DEA) approach. Container terminals in Busan and Gwangyang play an important role in the region's economic development. The results show that Shinsundae was an efficient DMU during the period of 2007 to 2009, while Gamman, New Gamman and PNC were efficient terminals in 2009. The very inefficient terminals were shown to be GICT, KEC, Dongbu and KIT. GICT(2009), KEC(2009), Dongbu(2008-2009), KIT(2009) on Gwangyang Port were found to be relatively the inefficient terminals in terms of the returns to scale. This study also finds that the efficiency of Shinsundae terminal was so high as to be abel to keep its efficiency in spite of the additional increase of the inputs from 2007 to 2009. Gamman terminal was in the decreasing returns to scale in 2009, while the other terminals were in the increasing returns to scale. It means that we are able to improve the efficiency of the Gamman terminal with increasing returns to scale through enlarging the scale.

• Journal of Navigation and Port Research
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• v.36 no.6
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• pp.527-534
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• 2012

In order to achieve sustainable growth and gain competitive advantages business performance should be monitored regularly by a company. In the port industry container terminal operators are facing growing competition. A large scale of new container terminals are constructed and the number of new container terminal operators are increasing. Container shipping lines are gaining bargaining power against terminal operators in terms of negotiating terminal usage. The competitive environments result in reduced cargo handling charges and poor financial performance of container terminal operators. It becomes very important to examine how efficiently container terminal operators are operating their terminals and how to improve their performance. This paper investigates the measurement efficiency for container terminal operators in Korea using Data envelopment analysis(DEA) of DEA-CCR and DEA-BCC Model. This paper finds out which container terminal operators are inefficient and how to improve their management efficiency.

• Journal of Information Technology Services
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• v.16 no.4
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• pp.15-31
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• 2017

This study analyzes 45 Korea IT service companies from 2012 to 2016 using DEA analysis. Large enterprises, medium enterprises and small and medium enterprises (SMEs). CCR model and BCC model were used for efficiency analysis. Among the various analytical objects, the decision objects which yield the maximum output with minimum input are compared with other analysis objects. The relative inefficiency was measured through this, and Technical Efficiency (TE), Pure Technology Efficiency (PTE), Scale Efficiency (SE), scale profit, reference frequency were analyzed. Also, we analyzed the Technology Gap Ratio (TGR), which is the distance between production function and Meta-Frontier for each firm, using Meta-Frontier analysis. Finally, the Tobit model is used to analyze the sources of efficiency and inefficiency. The inputs are assets, capital, and employees, and the output factor is sales. The analysis shows that large firms are achieving technological achievements more efficiently than small and medium enterprises. As a result, medium-sized enterprises and SMEs can improve efficiency overall through efficient operation of workforce and appropriate combination of inputs such as assets and capital. Also, as a result of the influence factor analysis, it was found that the ratio of the managed asset ratio and the management cost ratio were significant factors influencing the efficiency of the IT service companies. This study suggests the efficiency analysis using DEA for many Korea IT service companies. Inefficient parts of each company are classified according to size and technology. Also, we identify the most efficient companies and analyze the causes of those companies whose profits are lower than their size.

• Journal of Korea Port Economic Association
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• v.18 no.1
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• pp.3-26
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• 2002

The purpose of this paper is to Investigate the productive efficiency and competitive strength of world container ports using the DEA, Super-efficiency, and FDH methods with the raw data from previous research by Jun et al.(1993). The super-efficiency measure examines the maximal radial change In input, outputs for an observation to remain efficient. Therefore, it provides a means of distinguishing between efficient observations, which would otherwise seem identical. FDH provides a good test mechanism for examining the practical implications of the choice available among alternative efficiency measures and orientations, because of the lack of convexity of its production possibility set. Both methods are complementary to DEA. This paper follows the traditional productivity analysis method overcoming the limitation of previous studies by using the DEA, FDH and Super-efficiency methods, and proposing in measure the relative competitive strength of worldwide container ports. The main empirical results of this paper are as follows: Firstly the ports of Singapore, Hongkong, Kilrung, Busan, Tokyo. and Longbeach were found to be efficient In the CCR model. The ports of Felixstowe, Bangkok, Singapore, Hongkong, Kilung, Busan, Tokyo, and Longbeach were found to be efficient in the BCC model. Secondly, super. efficiency rankings under CRS and input-oriented model are as follows: Longbeach, Keelung, Singapore, Busan, Tokyo, and Honkong. However, it was difficult In differenciate the rankings under the VRS and input-oriented model. due to major difficulties posed by the ports of Singapore, Hongkong, and Longbeach. Thirdly, the FDH method shows that the inefficient ports are Bremerhaven, Antwerp, Le Havre, Kobe, Seattle, New York The policy Implications of this study are as follows: Firstly, when port authorities want to measure the international competitive strength of container ports and enhance their productive efficiency, they should consider the traditional method as well as introducing the Super-efficiency and FDH methods. Secondly, according to the analysis results of the super-efficiency and FDH methods, poll authorities should recommend benchmarks ports and dominated ports as reference ports in order to enhance the productive efficiency of their container ports that have an efficiency rating of less than 1. Efficient ports whose efficiency ratings are over 1 in the Input-oriented Super-efficiency model should also consider the usage of input and output elements used by more efficient ports.

• Korean Journal of Agricultural Science
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• v.39 no.2
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• pp.279-289
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• 2012

This study was conducted to survey and diagnose operation status of the agricultural machinery rental service, analyse and compare operational efficiency among 82 city and county ATDEC (agricultural technology development and extension center) using the DEA (Data Envelopment Analysis) method, and recommend future direction, for improvement of the business. Input variables were invested budget and labor, and output variable was rental return. Percentages of return to investment on the rental service were calculated as 68.3% and 63.9% when analyzed with CCR (Charnes, Cooper and Rhodes) and BCC (Banker, Charnes and Cooper) models, respectively, indicating inefficiency of the service operation. Increase of rental charge would increase efficiency by 63.9~68.3% depending on models, and decrease of financial and labor investment would improve the efficiency by about 11.3%. Technical efficiency would be more important than scale efficiency, therefore adjustment of over-invested budget and labor needed to be made together with increase of rental charge to improve the operation. Among the ATDECs providing the rental service, 6 (7.3%), 43 (52.4%), and 33 (40.2%) were in state of CRS (constant return to scale), IRS (increasing return to scale), and DRS (decreasing return to scale), respectively. These indicated public aspects of the rental system, over-investment, lack of output component for input component, meaning that scale income would be increased by qualitative expand of rental charge. Efficiency analysis of the rental system by region showed that efficient ATDECs to be benchmarked by others were in the order of DMU-70, DMU-54, DMU-29, DMU-5, DMU-22, DMU-2, and DMU-61. More comprehensive and extensive survey and analyses would be necessary in the future.

• Journal of Digital Convergence
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• v.17 no.12
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• pp.147-157
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• 2019

The purpose of this study is to analyze the efficiency of urbanization in 31 provinces and cities in China, including both desirable and non-expected outputs produced during the urbanization process. Efficiency was analyzed by applying the SBM-DEA model using the urbanization calculation data of 2017 in 31 provinces and cities in China. The results show that the urbanization efficiency of eastern region is the highest, followed by central region and northeast region, and the urbanization efficiency of western region is the lowest. This study is meaningful in that it analyzes the efficiency of urbanization in 31 provinces and cities in China and suggests the direction of continuous urbanization policy. This study is limited in that it does not reflect the past trend only by conducting cross-sectional analysis for one year in 2017, and it is necessary to comprehensively evaluate urbanization efficiency by conducting additional longitudinal area analysis in the future.

• Information Systems Review
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• v.17 no.3
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• pp.113-133
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• 2015

In this paper, DEA analysis is employed to compare and evaluate the relative efficiency of a business intelligence (BI) system among five industrial groups such as IT and financial services, electricity and electronics, energy and chemistry, automotive and heavy machinery, and food and apparel. Especially, this study has analyzed the improving tendency of relative efficiency of the industrial groups since they adopted the BI System using Time-Window Analysis. The research findings show that the energy and chemical industry group tends to be remarkably more efficient than the other groups and the electrical and electronic industry turns out to gradually improve their efficiency since the adoption of the BI system.

• International Area Studies Review
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• v.14 no.3
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• pp.205-219
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• 2010

In general, industrial production involves large amounts of harmful by-product, causing serious pollution and ecological risk. Eco-efficiency, which indicates how efficient the economic activity is by considering both the environmental risks and economic performance, is a new concept for economic sustainability analysis and quantitative ecological risk analysis. Data envelopment analysis (DEA) has been widely used to examine eco-efficiency in recent years. Whereas traditional DEA models such as CCR and BCC model neglect undesirable outputs, this paper adopts a stochastic undesirable-output DEA model to measure the eco-efficiency of each province of China and Korea. The results indicate that whereas the eco-efficiency of the eastern region was the highest, that of the western region was the lowest. The reason may come from the negative external dis-economies of environment. And thus the governmental efforts for outreach on the underdeveloped regions should be promoted.

• The Journal of the Korea Contents Association
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• v.19 no.5
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• pp.64-73
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• 2019

This study analyzed the efficiency by using the DEA model to evaluate the competitiveness of specialty construction firms. The target of the analysis is 300 firms with continuous data from 2010 to 2017 as listed and externally listed firms. Significant analysis results are as follows. First, the efficiency of specialty construction firms is lower than that of general construction industry. Second, efficiency by type was highest in facilities construction and dismantling work. This shows that the relevant industries such as reinforced concrete works and scaffolding and demolition work are relatively efficient in specialty construction industry. Third, the efficiency of specialty construction industry is affected by economic fluctuations. When the construction industry is in the expansion phase, the efficiency value is high and the efficiency value is low in the down phase. Finally, in the scale profitability analysis, specialty construction industry was most analyzed by DRS. This means that it is effective to scale down for the efficiency of the firm.

• Korean Journal of Organic Agriculture
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• v.30 no.3
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• pp.351-374
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• 2022

In recent years, the development of rice industry has been highly valued by the state. In hubei area, due to the development of the modernization and the shortage of labor, traditional way of rice cultivation methods is facing serious challenges, and economic benefits have become the decisive factor for the effective promotion and application of rice cultivation methods. According to the research results, first, in the input-side analysis, in the CCR model, D5, D12, D26, D28, D32, D36 farmers with high efficiency appear. The analysis result shows that among the 60 farmers, the average efficiency is 89%, and there is an inefficiency of 11%. In the BCC model, 14 farmers were identified as high-efficiency farmers, with an average efficiency of 0.9453. Second, in direct seeding cultivation of rice, the average scale efficiency is 0.9227, while the average pure technical efficiency is 0.9644. This shows that the effect of scale efficiency is greater than that of purely technical factors, ignoring the reasons for the low operational efficiency of direct seeding cultivation farmers. It can be predicted that with the further deepening of farmers' understanding of this planting mode, the proportion of rice direct seeding may be further expanded in the future. Relevant agricultural departments should further promote this technology to farmers, study the direct seeding technology using scientific methods, and evaluate the changes of this cultivation mode. The agricultural departments of government should concern about the climate risk assessment of direct seeding rice, the environmental impact assessment caused by the extensive use of herbicides, the application of mechanical technology in the process of direct seeding, the lodging of direct seeding rice, and other related issues.