• Knowledge Management Research
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• v.22 no.3
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• pp.151-172
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• 2021

The government's implementation of customer-friendly financial policies, such as lowering commission fees for credit card merchants and lowering the maximum interest rate, put the specialized credit finance companies in a crisis of lowering profitability. In this unfavorable situation, the efficiency study of specialized credit finance companies is meaningful. Accordingly, this study measured the efficiency of 34 specialized credit finance companies through Data Envelopment Analysis (DEA) and meta-frontier analysis. For meta-frontier analysis, specialized credit finance companies were divided into two groups (card companies and non-card companies) by industry or three groups (AA0 and above, AA-, and A+ or below) by credit rating. The results of the analysis will provide general insight into the efficiency of specialized credit finance companies. The results of this study are as follows. First, the average meta-efficiency of card companies was analyzed higher than that of non-card companies. Second, 80% of non-card's decision-making units (DMUs) were inefficient by pure technology rather than by scale. Third, decision-making units (DMUs), which account for 62.5% of the credit card company group and 80% of the 'AA-' credit rating group, are in non-economic areas of scale. Fourth, there was no statistically significant difference in meta-efficiency values (TE and PTE) by industry (card companies, non-card companies) and credit rating (AA0 or higher, AA-, A+ or lower). The contribution of this study will provide strategic initiatives for establishing management strategies to improve inefficiency by measuring the efficiency level of companies under an unfriendly business environment for specialized credit finance companies.

• Proceedings of the Korean Institute of Navigation and Port Research Conference
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• 2004.11a
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• pp.331-336
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• 2004

In order to strengthen the competitiveness of port against calling for the huge vessel and reducing the shipping service time, the productivity of container terminal must be improved. This productivity variously results according to the kinds of productivity evaluation model, input elements like yard, equipment, employee, facility, etc,. But, it is discussed that the productivity is measured by partial productivity evaluation model or general input elements. Therefore, we measured for the productivity of the container terminal using the Developed the data Envelopment Analysis (DEA), which is developed in order to evaluate the relative efficiency of decision making units - it's difficult to clear cause and effect between input and output. We measured the whole productivity of container terminal in Busan according to decision of the correct input elements. And we investigated the change of the productivity measurement result according to input elements, presents more accurate productivity evaluation model in container terminal.

• Journal of Korea Port Economic Association
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• v.27 no.1
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• pp.213-234
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• 2011

The literature on efficiency of the maritime and shipping industry has typically focused on container ports and terminals. The study presented in this paper uses data envelopment analysis to evaluate ocean carriers based on financial and operational data from 2004 to 2007. A comparison is made up of the efficiency of global ocean carriers in efficiency of financial and operational performance respectively. A positive correlation is shown between the input and output data. In the static-efficiency analysis, we describe CCR, BCC and scale efficiency of Global Ocean Carriers in 2007. And we also provide about the stability and trend of their efficiency for four years (2004-2007) in the dynamic-efficiency analysis. The empirical results validate the necessity of restoring freight rates to facilitate the efficiency of the global ocean carriers supported by adjust of the supply of containership space. The study provides a basis for estimating the competitiveness of international shipping companies, for benchmarking best practice and for identifying the specific factors and causes of inefficiency.

• Korean Journal of Construction Engineering and Management
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• v.15 no.5
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• pp.103-114
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• 2014

Data envelopment analysis (DEA) measures the relative efficiency of decision making units (DMUs) with multiple performance factors that are grouped into outputs and inputs. DEA has proven to be superior to simple aggregation of performance measures, and is also useful for evaluating the performance of construction companies for comparison with competitor performance. The purpose of this study was to survey literatures on the application of DEA methodology and to propose a methodological scheme to measure the performance of construction organizations. Articles on previous studies were surveyed and examined as part of a comprehensive review. The survey revealed that the application of DEA in the construction industry was li mited. Further, the survey indicated that there is a need for the development of a methodological framework on the special goals and subjects of performance measurement, methods of data structure and collection, selection of appropriate DEA models, analysis of results, and post-test. Based on the survey, this study identified and discussed the types of major issues and topics for future studies from a methodological perspective, which could be helpful to researchers interested in using DEA to study performance issues in construction organizations.

• KSCE Journal of Civil and Environmental Engineering Research
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• v.33 no.6
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• pp.2455-2464
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• 2013

This study is focused on the effect of reformation of public transportation system on the efficiency of bus route system as a result of change of government subsidy scheme. Two types of government subsidy scheme has been considered and before and after analysis by Data Envelopment Analysis technique has been carried out for bus routes in Ulsan Metropolitan City. The analysis output has shown that there is no clear evidence to clarify the relationship between the change of government subsidy scheme and the efficiency of bus route system. There are two types of backgrounds may be suggested for this situation such as more longer period necessary to identify the policy effect and limitation to increase the number of passenger in a provincial city. Tobit regression analysis has also been conducted to discover the most effective variables for maximum efficiency and three variables including route length, frequency per vehicle per day, and headway are found to be influential. It is also seen that strategy to minimising input factors and service upgrade plan such as shortened route length and headway, increasing frequency per vehicle are necessary to develop the efficiency of bus routes operated in Ulsan city.

• The Journal of Society for e-Business Studies
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• v.19 no.3
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• pp.91-105
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• 2014

This study purposed to benchmark the number of patients who visited an oriental medicine hospital from its surrounding regions using data envelopment analysis (DEA) model, and to analyze the relationships between regional characteristics and efficiency scores from DEA. Study data was collected from one oriental medicine hospital operated in a metropolitan city in Korea. Patient locations were identified at the smallest administrative district, Dong, and number of patients was calculated at the Dong level based on the address of patients in hospital information system. Socio-demographic variables of each Dong were identified from the Statistics of Korea web-sites. DEA was used to benchmark the number of patients between Dongs and to compute the efficiency scores. Tobit regression analysis model was applied to analyze the relationship between efficiency scores and regional variables. 6 Dongs were identified as efficient after DEA. In Tobit analysis, number of medical aid recipients and number of total population in each Dong was significant in explaining the differences of efficiency scores. The study model introduced the application of DEA model in benchmarking the patients between regions. It can be applied to identify the number of patients in each region which a hospital needs to improve their performances.

• The Journal of the Korea Contents Association
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• v.20 no.4
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• pp.159-168
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• 2020

This study aims to utilize DEA, analyze the efficiency of Korean coffee franchises, look into the factors that affect efficiency, and improve the efficiency of Korean coffee franchises. The main results of this study are as follows. First, according to CCR model standards, there are a total of 9 efficient coffee franchises and according to BCC model standards, there are a total of 12 efficient coffee franchises. A total of three of the inefficient DMUs were found to have a value of 1 for BCC, while the other 25 were found to be inefficient for both technology and scale. Second, of 28 franchises, 11 were analyzed to be decreasing return to scale and through future increased investments of optimum levels, business performance can be improved and efficiency can be enhanced. Analysis showed that 9 franchises appeared as CRS and it is most ideal to maintain the yield of future output elements at current levels and the work efficiency of 8 franchises in increasing returns to scale states expands as production scales increase according to specialization and role division and yield can relatively improve a lot. Third, the analysis of factors affecting the efficiency of franchises through the Tobit regression analysis showed that the number of franchises and operating periods had a positive (+) effect on efficiency. Based on this study, the efficiency of coffee franchises should be analyzed to establish strategies to maximize efficiency. Based on this study, the efficiency of coffee franchises should be analyzed to establish strategies to maximize efficiency.

• Journal of Korea Port Economic Association
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• v.24 no.4
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• pp.25-46
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• 2008

By using data envelopment analysis(DEA) this research measures the efficiency of Korea's five seaports and their Malmquist productivity from 1997 to 2006. Under the assumption of CRS(constant returns to scale) and VRS(various returns to scale), seaports' rankings of efficiency are measured. Busan port is confirmed as a best-performed port in the various measurements. Important finding facts are as follows. 1)Busan, lncheon and Ulsan seaports are efficient ports under the assumption of CRS and VRS. 2)Gwangyang port shows 4.3% lower efficiency level compared with efficient ports. 3)Pohang port shows 27.3% lower efficiency level compared with efficient ports. 4)Average total factor productivity of Korea's five ports has been lower at the rate of 3.1% during the period from 1997 to 2006. Main policy implications are 1)Busan port is more efficient than Gwangyang port, which reflects the difference of economic activities between two regional econmies. 2)During the period 1997-2006, Korea's five largest ports has experienced lower efficiency levels in the first half period because of the 1997 Korean Financial Crisis, but higher efficiency levels in the second half period because of economic recovery. In future research the more and better data will be expected to improve the understanding of Korean seaports' efficiency characteristics.

• International Commerce and Information Review
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• v.14 no.3
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• pp.323-350
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• 2012

This study analyzes the efficiency of 25 shipping companies in Korea over the period 2005-2009, using Data Envelopment Analysis (DEA). Among 31 companies that listed in order of decreasing sales volume for the period 2006-2010, the sample companies has been selected on the ground of data availability. This study computes the companies' efficiency, estimates their year-on-year Malmquist productivity index, and analyzes the cause leads to the changes in the productivity, In particular, this study attempts, by dividing the companies into two group, listed or not, to compare the changes in the productivity and analyze the reasons. The results from static analysis based on CCR and BCC model indicate that listed companies are higher efficient than unquoted companies. The results from tests on the productivity changes based on the Malmquist productivity index show that 19 unquoted companies increase their average productivity by 16.2 percent year after year during the period but 6 listed companies increase by 0.5% during the same period.

• Asia-Pacific Journal of Business Venturing and Entrepreneurship
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• v.6 no.4
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• pp.137-152
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• 2011

The purpose of this study is to estimate efficiency of agricultural business corporations using Data Envelopment Analysis. A proposed method employs a bootstrapping approach to generate efficiency estimates through Monte Carlo simulation re-sampling process. The technical efficiency, pure technical efficiency, and scale efficiency measure of the corporations is 0.749 0.790, 0.948 respectively. Among the 692 agricultural business corporations, the number of Increasing Returns to Scale (IRS)-type corporations was analyzed to be 539(77.9%). The number of Constant Returns to Scale (CRS)-type corporations was 108(15.6%), and that of Decreasing Returns to Scale (DRS)-type corporations was 45(6.5%). Since an increase in input is lower than an increase in output in IRS, an increase in input factors such as new investments is required. The Tobit model suggests that the type of corporation, capital level, and period of operation affect the efficiency score more than others. The positive coefficient of capital level and period of operation variable indicates that efficiency score increases as capital level and period of operation increases.