• Journal of Korean Society of Industrial and Systems Engineering
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• v.33 no.1
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• pp.10-16
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• 2010

Mail centers are essential postal facilities that sort and dispatch postal items, and should be operated efficiently to provide customers high quality postal services. So the efficiency analysis of mail centers should be performed in order to induce better operation. But current performance evaluation system has 95 percent of predetermined and weighted non-quantitative indices. There is need to introduce objective efficiency measurement methodology. The main objectives of this study was to analyze the efficiency of 24 mail centers empirically using cone-ratio DEA and suggest the appropriate cone-ratio method. Consequently, this paper suggests that the cone-ratio DEA model integrating decision-maker's preferences is more desirable for efficiency analysis than that of using transformed data.

• Korean Journal of Organic Agriculture
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• v.26 no.1
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• pp.33-41
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• 2018

The paper aims to estimate efficiency of watermelon by using a bootstrapping approach to generating efficiency estimates through Monte Carlo simulation resampling process. We use the input-output data for watermelon 107 farmers. The main results are as follows. The estimates of efficiency depends on the methodology. The estimates of general DEA is greater than the bootstrapping method. The technical efficiency and pure technical efficiency measure of watermelon is 0.72, 0.82 respectively. However the bias-corrected estimates are less than those of DEA. We know that the DEA estimator is an upward biased estimator. According to these results, the DEA bootstrapping model used here provides bias-corrected and confidence intervals for the point estimates, it is more preferable.

• Asia-Pacific Journal of Business
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• v.6 no.2
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• pp.1-17
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• 2015

This study compares the most widely used parametric and non-parametric techniques to measure cost and profit efficiency of banks, namely the Stochastic Frontier Analysis (SFA) and Data Envelopment Analysis (DEA). We formulate the specification form of both stochastic cost and profit frontier models and constant return to scale Cost DEA and Profit DEA models and provide an empirical assessment of the cost and profit frontiers based on a panel dataset of National Commercial Banks (NCBs) and Private Banks (PBs) in Bangladesh over the 2001-2010 period. The cost inefficiency and profit efficiency are slightly higher for PBs than NCBs in case of both SFA and DEA. The coefficients of advance and off-balance sheet items are significant that positively influence the banks in stochastic cost frontier model while the advance, other earning assets, price of borrowed fund are significant and negative effects on the banks in stochastic profit frontier model. The average cost inefficiency and average profit efficiency are recorded with 16.3% and 91% respectively. The highest and lowest cost inefficiency are observed for Janata Bank and United Commercial Bank Limited whilst the highest and lowest profit efficiency are recorded for Eastern Bank Limited and Janata Bank respectively. The average technical and allocative efficiency are 68.8% and 35.9%, respectively in case of CRS cost-DEA model whereas they are 70.3% and 31.8% in case of CRS profit-DEA model. The average cost inefficiency is recorded 6.3% by SFA whereas it is 24.5% by DEA. The average profit efficiency is found 91% by SFA while it is 22.1% by DEA, and SFA method shows better bank efficiency than DEA.

• Journal of Korean Society of Industrial and Systems Engineering
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• v.32 no.2
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• pp.29-37
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• 2009

National R&D programs play an important role in the development of a country in this age of the knowledge economy. Since many numbers of R&D programs compete for limited resources such as national R&D budget, the R&D program evaluation problem is a challenging decision-making problem faced by decision makers that deal with R&D management. In this sense, DEA(Data Envelopment Analysis) has been regarded as one of the most widely accepted methods to measure the relative efficiency of productivity of R&D programs. DEA is a methodology to measure and to evaluate the relative efficiency of a homogeneous set of decision-making units(DMUs) in a process which uses multiple inputs to produce multiple outputs. However, the sample of the R&D programs could consist of two or more naturally occurring subsets, thus exhibiting clear signs of heterogeneity such as different objectives. In such situations, the fairness of DEA is limited, for the nature of the relative efficiency of a DMU is likely to be influenced by its membership in a particular subset of the sample. In this study, we propose a methodology AI-DEA(attainment index DEA) allowing for reflecting decision maker's subjective judgement on difference among different subsets of R&D programs which have heterogeneous objectives. This methodology combines AHP and Delphi in order to decide the attainmnet index of each DMU for each outputs, and apply them to DEA model. We illustrate the proposed approach with a pilot evaluation of 13 programs involving 6 different subsets of Korean National R&D programs and compares the results of the original DEA model and AI-DEA model.

• The Journal of Fisheries Business Administration
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• v.34 no.2
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• pp.109-129
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• 2003

The purpose of this study is to evaluate the managerial efficiency of fisheries cooperatives in Korea by using data envelopment Analysis(DEA). The DEA method is a relative evaluation method on the basis of linear programming. Also, it is known as a useful method for the evaluation of not-for-profit organizations which cannnot be measured by mere monetray units for their performances. The 50 units have been taken for the purpose of analysis. All of the units are homogeneous groups, and the produce multiple services with multiple inputs. Input variables are a number of employee, fixed assets, and business managerial costs. Output variables include a number of deposits, a number of loans, a total deposits, a total loans, and operational income for one year. The empirical results of this study are as follows. First, the average technical efficiency showed 82.35% which revealed about 17.65% of non-efficiency in 2001. Second, in 15 DMUs, the overall inefficiency is mainly attributed to their efficient operations or management. To be opposed, in 18 DMUs, the overall inefficiency is mainly attributed to their scale efficiency. Third, efficiency ranking results by DEA do not agree with the ratio analysis by fisheries cooperatives. Fourth, average efficiency level by year was improving gradually by 0.7408 in 1999, 0.8023 in 2000, and 0.8235 in 2001 at significant 10% level.

• Proceedings of the Korean Operations and Management Science Society Conference
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• 2005.10a
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• pp.441-456
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• 2005

The purpose of this paper is to introduce the concept of negative DEA, which aims at identifying worst performers by placing them on the efficient frontier, This paper also proposes to use a layering technique instead of the traditional cut-off point approach, since this enables incorporation of risk attitudes and risk-based pricing. The results of the empirical application on credit risk evaluation validate the method which is proposed in this paper.

• Journal of Venture Innovation
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• v.1 no.2
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• pp.35-46
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• 2018

The research on the efficiency analysis of domestic auto parts companies is mostly based on the calculation of the magnitude of the performance creation such as the sales amount compared to the input assets. However, the performance indicators such as sales, operating profit, and net profit are directly related to the cost structure and This cost structure is affected by changes in the firm's asset and capital structure. As a result, it is considered that efficient capital procurement needs to be done at the same time to create efficient management performance through proper investment. This study focuses on this point and attempts to measure the efficiency of procurement capital relative to the sales and other performance indicators generated by the first 33 suppliers who supply parts to Hyundai Kia Motors. Among the methods of evaluating efficiency, the DEA model based on the linear programming method is most widely used as a nonparametric method but The efficient frontier-based DEA model has the limitation that it can not use the variables that have a downward influence on the efficiency. This is inadequate to directly consider variables such as borrowings and total liabilities related to capital procurement. In this study, the efficiency of capital procurement was measured using Worst Practice DEA and the improvement direction of the capital procurement aspect of domestic auto parts companies was suggested

• Industrial Engineering and Management Systems
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• v.1 no.1
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• pp.93-98
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• 2002

It is important to evaluate the performance of candidates mathematically from various aspects, and reflect it on decision making. In decision making, we judge the candidates through two steps, classification of objects and comparison of objects or candidates with plural elements. In the former step, Analytic Hierarchy Process (AHP) is useful method to evaluate candidates from plural viewpoints, and in the later step, Data Envelopment Analysis (DEA) is also useful method to evaluate candidates with plural categorized data. In fact, each candidate has plural elements, nevertheless it has been more important to evaluate from various aspects in IT society. So, we propose a new procedure complementing AHP with DEA.

• Journal of Korean Institute of Industrial Engineers
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• v.32 no.1
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• pp.18-28
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• 2006

Some issues which should be considered in an R&D project selection problem are as follows: First, quantitative analysis on the efficiencies of R&D projects is required to guarantee objective validity in the evaluation of the projects. For this reason, the methodology for selecting R&D projects should be based on mathematical models that perform quantitative analysis. Second, in general there are ordinal factors like Likert-scale in the data for evaluating R&D projects. Previous researches, however, couldn't suggest explicit methods incorporating these ordinal factors into models. Third, for the R&D project selection problems with limited resources like budget, it is necessary to decide the perfect ranking of the all projects. This paper develops a mathematical model that can be applicable to the problems of selecting R&D projects with the previous features. In this paper, we improve the original DEA model for evaluating efficiency to incorporate ordinal factors and suggest a new model which can decide the perfect ranking of all projects by merging the improved DEA model and AHP method. Furthermore a web-based R&D project selection system using the DEA/AHP model suggested in this paper is developed and illustrated.

• Proceedings of the Korean Institute of Navigation and Port Research Conference
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• 2004.04a
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• pp.351-356
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• 2004

This study aims to implement an empirical research about the efficiency of container Ports, and to suggest an effective strategy which can operate container Ports more well. This paper presents a new approach to the measurement of efficiency. Data envelopment analysis(DEA), as it is called, has particular applicability in the service sector. This study applies DEA to provide an efficiency measurement for fifty three container ports including Pusan Port. As a result, we suggest several ideas that can improve the efficiency of container terminals. They are as follows. Firstly, we discriminate between efficient and inefficient container ports and then present a method that can move to efficiency container terminal and a benchmarking port. Secondly, we evaluate the efficiency of Pusan port, and grasp the position at the present time, suggest an advanced direction in future.