• Journal of Korea Port Economic Association
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• v.26 no.3
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• pp.165-174
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• 2010

DEA converts multiple inputs and outputs of a decision unit into a single measure of performance, generally mentioned as relative efficiency. DEA has been applied successfully as a performance evaluation tool in many fields including manufacturing, banks, pharmacies, and hospitals to name a few. This paper applies the input-oriented DEA model, DEA/Window analysis, and Malmquist indices to the 9 regions in Korea to measure the efficiency and productivity. The empirical results show the following findings. First, the super efficiency indicate that efficiency of Group 2 is greater than Group 1. Second, Malmquist indices show that productivity of Group 2 is less than Group 1. Third, DEA/Window of Group2 show that Chungnam is most stable, while Jeonnam is most unstable.

• The Journal of Asian Finance, Economics and Business
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• v.7 no.12
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• pp.555-564
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• 2020

The purpose of this study is to analyze the efficiency of research institutes of futures companies, and to promote the development of futures market and real economy. This study employs DEA-solver software to conduct super-efficiency data envelopment analysis (SE-DEA), and also selects 40 representative futures research institutes in China as decision-making units (DMUs). For data of input and output indicators, we collect from the China Futures Association, Futures Daily, Hexun.com and Webstock.com respectively, and the time duration is the 103 trading days between from October 2019 to February 2020. Then the indicator for the strategy accuracy rate is calculated separately by analyzing the strategies published by each DMUs in public media. In conclusions, most institutes have excessive investment in human resources, and also have insufficient strategy accuracy rate and insufficient published research reports. The findings of this study suggest that Chinese futures companies need to improve the efficiency of research institutes, and better meet the demand of the financial market. In fact, the analysis of the efficiency of the futures company research institute has not been found in the literature worldwide, Application of DEA model in efficiency analysis of securities and futures research institutions and establishment of indicators are the innovations of this paper.

• Journal of Distribution Science
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• v.12 no.4
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• pp.23-30
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• 2014

Purpose - The purpose of this study is to analyze the efficiency of retail businesses by dividing domestic retailers into discount stores, super supermarkets (SSMs), and department stores. It suggests retail-business investment strategies by using data environment analysis (DEA) to analyze how input elements such as store area, parking lot area, number of employees, and sales management expenses for the convenience of customers positively affect business performance measurements such as sales and visiting customers per day. Research Design, Data, and Methodology - The DEA model calculates a ratio of the weighted mean of various inputs to the weighted mean of various outputs and measures the efficiency of a specific decision making unit (DMU). The study included 19 companies (five discount store DMUs, ten SSM DMUs, and four department store DMUs). Because the business elements and sizes of retail store DMUs used in this analysis are different, average per-store input and output variables were used. Data were collected from "The Yearbook of Retail Industry in Korea (2012)." DEA analysis was used to determine differences in efficiency among discount stores, SSMs, and department stores in terms of the business elements of each retail business. It was also used to determine what business elements were excessively invested in by comparing and analyzing efficiency by business elements using SPSS software's ANOVA (Analysis of Variance). Results - The CCR and BCC efficiency analysis found that the efficiency of discount stores is low. We believe that the saturation state of discount stores is a major factor. The ANOVA analysis confirms the VRS hypothesis with a statistically significant difference among the three groups, based on an analysis confidence interval of 95%. CRS and SE were not found to be significantly different among the three groups. As for the post hoc test, which concretely shows differences by group, the Scheffe's multiple comparison analysis test found the average differences between group 1 (discount stores) and group 2 (SSM) to be statistically significant. Conclusions - The DEA efficiency analysis implies that investment in input elements, including store area, parking lot area, and sales management expenses, were excessive in the case of discount stores, while SSMs need to invest more in promotion activities such as gifts, events, and coupons for customer management. Department stores have found that small companies invest excessively in input elements. Department stores need to invest in differentiated shopping mall complexes. This study was limited in acquiring statistical data; various input variables which might have shown more secure customer management and promotional expenses could not be applied. As the study was limited in various aspects of the efficiency analyses because financial analyses of the companies and of causal relationships, including satisfaction and loyalty of visiting customers, were not done, these aspects will be examined in the next study.

• Korean Journal of Organic Agriculture
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• v.23 no.2
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• pp.207-231
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• 2015

This study evaluate examines the efficiency and the improvement measurement of Oilseed crops (Sesame and Perilla). For this purpose, In the first stage, this study analyzes the current conditions of oilseed industry. In the second stage, this study evaluates the efficiency and super-efficiency of environmentally-friendly agricultural product producers. The result of this study show that: (1) Changes in annual wholesale price of Sesame and Perilla; (2) An efficiency and ranking of environmentally-friendly product producers; (3) The solutions and improvement measurements for inefficient producers.

• International Area Studies Review
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• v.22 no.2
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• pp.61-91
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• 2018

Credit Guarantee scheme is one of the most effective tools for the small business policy. The performance analysis on domestic institution level is relevant in terms of various factors of assisting tools factor. This study measured comparative global efficiency by DEA model and Super-efficiency model among 70 credit guarantee institutions in Japan, Taiwan, and Korea who are operating the schemes. At the result of the analysis, Korean credit guarantee institutions are comparatively efficient than Japanese institutions, and the DMU shows moderate in operation efficiency. The Super-efficiency ranked by Hiroshima, Taiwan SMEG, Pusan, Chiba, Shizuoka, Ulsan, and KOTEC. Most of the Credit Guarantee Institutions showed increasing returns to scale, and it indicates increasing input strategy. The statistical difference of efficiency level in Japan and Korea shows very meaning numbers. This research suggest that (1)Periodical Analysis are needed on Japanese Schemes, (2)The analysis on the impact of credit guarantee scale to the national economy and SME policy, (3) Analysis on the conclusive factors of the efficiency, (4)The policy direction has to be made by inefficient factor analysis, (5) The measurement tools of efficiency of the schemes in various aspects.

• Korea Journal of Hospital Management
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• v.28 no.2
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• pp.44-65
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• 2023

Purposes: As super-aging population and low fertility rates are threatening the sustainability of the National Health Insurance funds, enhancing the efficiency of hospital management is paramount. In the past, studies analyzing the efficiencies of hospitals primarily made inter-hospital comparisons, but it is important to assess hospitals' internal efficiency and develop improvement measures in order to attain practical improvements in hospital efficiencies. The purpose of this study is to analyze the efficiencies of specialists by medical specialty in a hospital in order to provide foundational data for efficient hospital management. Methodology/Approach: We used the activity-based costing (ABC) data and hospital statistical data from one tertiary hospital in Seoul to analyze the efficiency of specialists by medical specialty. Efficiency was analyzed and compared among specialists using the data envelopment analysis developed by Charnes, Cooper, and Rhodes (DEA-CCR) model and the slacks-based measure (SBM) models. The input variables were labor cost, material cost, and operational expenses, and the output variables were the number of outpatients, number of inpatients, outpatient revenue, and inpatient revenue. Findings: First, there was a marked deviation in efficiency across specialists. Second, there was a marked deviation in efficiency across medical specialties. Third, there was little difference in efficiency according to the specialist's sex, age, and job position. Fourth, the SBM model produced more conservative results and better explained efficiency parameters than the CCR model. Practical Implications: The efficiency of a specialist was more influenced by their medical specialty than their personal characteristics, namely sex, age, and job position. Therefore, Further research is needed to analyze the efficiencies of each subspecialty and identify factors that contribute to the variations in efficiencies across medical specialties, such as clinical practices and fee structures.

• The Journal of Fisheries Business Administration
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• v.51 no.1
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• pp.37-52
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• 2020

The production of abalone seed has grown and been specialized since the 2000s with the growth of the abalone farming industry. Despite the increase in the production of abalone seeds, the sales volume of abalone seeds remained flat and competition among producers increased. This paper will analyze the management efficiency of abalone seed production fishery to diagnose the management status and improve the abalone seed production efficiency. In addition, this study is the result of the basic research on the abalone seed industry and it is meaningful to prepare a platform for further research since the management status survey and the management efficiency survey of abalone seed production fishery have not been conducted until now. The data on the farmed fish prices of abalone seeds were collected from surveys of sample fish as part of the fish seed observation project conducted by the Fisheries Outlook Center (FOC) of Korea Maritime and Fisheries Development Institute (KMI). Management efficiency analysis utilizes DEA (Data Envelopment Analysis) model. The DEA model was analyzed by classifying into CCR (Super-CCR), BCC, and SBM (Super-SBM) models according to the assumptions taking into account the characteristics of the industry. The slack considered in the SBM model was judged as possible decreases in input variables and increase in output variables. The average efficiency from the CCR model was analyzed to be 69%. The BCC model was classified into input and output orientations, and the average efficiency was 79% and 75%, respectively. There were seven production fisheries with an SE value of 1 or more, which remained unchanged in terms of size and could be benchmarked. The average efficiency of the SBM model was 59% for CRS and 66% for VRS. Under the VRS assumptions, the variable increase/decrease efficiency analysis shows that labor costs can be reduced by 37.3%, facility capacity by 18.8%, and operating costs by 8.5%. In order to improve management efficiency, Wando needs to reduce labor and management costs. In Jindo region, sales increase as well as labor cost reduction is urgent. In other regions, reduced facilities and increased sales are recommended.

• Journal of Distribution Science
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• v.11 no.8
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• pp.5-14
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• 2013

Purpose - We live in a world of constant change and competition. Many airports have specific competitiveness goals and strategies for achieving and maintaining them. The global economic recession, financial crises, and rising oil prices have resulted in an increasingly important role for facility investment and renewal and the implementation of appropriate policies in ensuring the competitive advantage for airports. It is thus important to analyze the factors that enhance efficiency and productivity for an airport. This study aims to determine the efficiency levels of 20 major airports in East Asia, Europe, and North America. Further, this study also suggests suitable policies and strategies for their development. Research design, data, and methodology - This paper employs the DEA-CCR, DEA-BCC, and DEA-Malmquist production index analysis models to determine airport efficiency. The study uses data on the efficiency and productivity of the world's leading airports between 2006 and 2010. The input variables include the airport size, the number of runways, the size of passenger terminals, and the size of cargo terminals. The output variables include the annual number of passengers and the annual cargo volume. The study uses basic data from the 2010 World Airport Traffic Report (ACI). The world's top 20 airports (as rated by the ACI report) are investigated. The study uses the expanded DEA Model and the Super Efficiency Model to identify the most effective airports among the top 20. The Malmquist productivity index analysis is used to measure airport effectiveness. Results - This study analyzes longitudinal and cross-sectional data on the world's top 20 airports covering 2006 to 2010. A CCR analysis shows that the most efficient airports in 2010 were Gatwick Airport (LGW), Zurich Airport (ZRH), Vienna Airport (VIE), Leonardo da Vinci Fiumicino Airport (FCO), Los Angeles International Airport (LAX), Seattle-Tacoma Airport (SEA), San Francisco Airport (SFO), HongKong Airport (HKG), Beijing Capital International Airport (PEK), and Shanghai Pudong Airport (PVG). We find that changes in airport productivity are affected more by technical factors than by airport efficiency. Conclusions - Based on the study results, we offer four airport development proposals. First, a benchmark airport needs to be identified. Second, inefficiency must be reduced and high-cost factors need to be managed. Third, airport operations should be enhanced through technical innovation. Finally, scientific demand forecasting and facility preparation must become the focus of attention. This paper has some limitations. Because the Malmquist productivity index is based on the hypothesis of the, the identified production change could be over- or under-estimated. Further, as DEA estimates the relative efficiency. It also cannot generalize to include all airport conditions because the variables are limited. To measure airport productivity more accurately, other input variables and environmental variables such as financial and policy factors should be included.

• Journal of Korea Port Economic Association
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• v.29 no.2
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• pp.159-171
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• 2013

This paper aims to analyse the relative efficiency of logistics facilities and suggest the policy alternatives for exploring and activating them. This study also divides the logistics facilities into airport terminals, logistics complexes, container terminals, and trucking freight terminals. For this purpose, the CCR-DEA as well as the BCC-DEA techniques are employed to show which part explains the primary cause of inefficiencies of each DMU(Decision Making Unit). The empirical results indicate that the efficiency of logistics complex is the lowest of all, while freight trucking terminal has the highest efficiency. This study also reveals that operation inefficiency is greater than scale inefficiency in most of DMUs, showing that much more effort be done for alleviating the cost resulting from irrational management.

• Journal of Korean Society of Transportation
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• v.32 no.2
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• pp.93-105
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• 2014

This study evaluated the relative efficiency of mobile emission reduction countermeasures through a Data Envelopment Analysis (DEA) approach and determined the priority of countermeasures based on the efficiency. Ten countermeasures currently applied for reducing greenhouse gases and air pollution materials were selected to make a scenario for evaluation. The reduction volumes of four air pollution materials(CO, HC, NOX, PM) and three greenhouse gases($CO_2$, $CH_4$, $N_2O$) for the year 2027, which is the last target year, were calculated by utilizing both a travel demand forecasting model and variable composite emission factors with respect to future travel patterns. To estimate the relative effectiveness of reduction countermeasures, this study performed a super-efficiency analysis among the Data Envelopment Analysis models. It was found that expanding the participation in self car-free day program was the most superior reduction measurement with 1.879 efficiency points, followed by expansion of exclusive bus lanes and promotion of CNG hybrid bus diffusion. The results of this study do not represent the absolute data for prioritizing reduction countermeasures for mobile greenhouse gases and air pollution materials. However, in terms of presenting the direction for establishing reduction countermeasures, this study may contribute to policy selection for mobile emission reduction measures and the establishment of systematic mid- and long-term reduction measures.