• Korean Management Science Review
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• v.19 no.1
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• pp.117-128
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• 2002

In this Paper we investigate the performance of the five efficiency estimation methods which include the stochastic frontier model estimated by maximum likelihood (SFML), the stochastic frontier model estimated by corrected ordinary least squares (SFCOLS), the data envelopment analysis (DIA) model, the combined estimation of SFML and DEA (SFML + DEA), and the combined estimation of SFCOLS arid DIA (SFCOLS+ DEA) using Monte Carlo analysis. The results include: 1) SFML provides most accurate efficiency estimates for the sample sloe 150 or over,2) SFML+DEAor SFCOLS + DIA Perform better for the cases with sample sloe 25, 50, and low random errors, 3) SFCOLS performs better for the close with sample sloe 25, 50, and very high random errors.

• Journal of Korea Port Economic Association
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• v.36 no.1
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• pp.183-196
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• 2020

Until now, there have been few studies analyzing the efficiency of the Port of Mokpo and comparing it with other seaports in the country to identify the future direction of development for the port. In this paper, we use the data envelopment analysis (DEA) model in combination with the Malmquist Productivity Index (MPI) to measure the efficiency and productivity of major ports in Korea, focusing on the Port of Mokpo. First, the study identifies which ports are efficient or inefficient based on technical or operational scale. Second, by using the MPI to overcome the shortfalls of the DEA model, the study can compare a port's performance across the years and evaluate the productivity of a port during the research period. Moreover, this study also applies fuzzy C-means (FCM) clustering to classify port groups based on the size of their infrastructure and their efficiency scores. Finally, it is possible to find ways to enhance the efficiency and future direction of development of the Port of Mokpo.

• Journal of KIISE:Software and Applications
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• v.41 no.8
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• pp.598-604
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• 2014

In this paper, we develop stepwise regression data envelopment model to select important variables. We formulate null hypothesis to understand the importance of each variable and use Kruskal-Wallis test for this purpose. If the Kruskal-Wallis test does reject the null hypothesis this will imply there is significant fluctuation in the efficiency score relative to base model. And therefore we have to further check the pair of variables that causes the fluctuation in order to determine its importance using Conover-Inman test. The proposed models helps understand the extent of misclassification decision making units as efficient/inefficient when variables are retained or discarded alongside provides useful managerial prescription to make improvement strategies.

• Journal of Korean Institute of Industrial Engineers
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• v.39 no.4
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• pp.298-312
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• 2013

This paper compares efficiency results and performance targets for academic departments in a local private college using DEA (Data Envelopment Analysis). Because of an aging society, a smaller school-age population entering colleges, and enhanced accreditation standards by the government, colleges and universities are not recruiting and retaining sufficient students and therefore are struggling for survival. In contrast to popular four-year undergraduate universities concentrated in Seoul and its satellite cities, retaining students is critical for the survival of local private colleges in poor or remote regions. Therefore, it is very important to identify the factors involved in the retention of students in the various departments of a college. However, given the different characteristics of the departments, it is difficult to identify one unique or robust set of standards to evaluate their performance. The purpose of this paper is to maximize student retention capabilities by ensuring that additional resources are assigned to efficient DMUs, while, inefficient DMUs are given benchmarked targets. Based on previous studies and college accreditation standards, this paper presents indices to be used in evaluating the efficiency of academic departments in a college. In evaluating relative efficiency, this paper uses the output-oriented BCC model. To define target levels to be achieved for efficient DMU, a multi-stage DEA procedure is used.

• Journal of Korea Technology Innovation Society
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• v.2 no.2
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• pp.249-265
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• 1999

This study examines the efficiency of engineering education using DEA(data envelopment analysis) which is often used in the efficiency evaluation of public services. We evaluate 27 mechanical engineering departments according to academy-basis, general basis, and employment-basis considering students' academic level and input costs as input factors. Our empirical results suggest that an evaluation method using DEA can give us useful informations such as benchmarks to improve education specialization where it is desirable, decisions about whether a department should expand its gross input or not, and proper directions about which input factors should be controlled and how much control is needed.

• Journal of the Korea Society of Computer and Information
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• v.5 no.2
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• pp.158-164
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• 2000

The purpose of this study is concerned with evaluating management performance in electronics and communication companies using DEA(Data Envelopment Analysis) DEA is a linear programming based technique for measuring the relative performance of organizational units where the Presence of multiple inputs and outputs makes comparisons difficult. In this research. input variables are raw-material costs, number of employees, and production capacity Real production, sales revenue and net earning are suggested as output variables. Management performance of most companies are increased or equal during 97 and 98 fiscal year and input & output variables show high correlation.

• Asia-Pacific Journal of Business
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• v.5 no.1
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• pp.1-11
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• 2014

The study provides new empirical evidence on the level of profit efficiency and returns to scale of the Bangladesh banking sector. We employ the Slack-Based Data Envelopment Analysis (SBM-DEA) method to assess the level of profit efficiency of individual banks over the years 2004 to 2011. The empirical findings indicate that the Bangladesh banking sector has exhibited the highest and lowest level of profit efficiency during years 2004 and 2011 respectively. We find that only eight banks have been profit efficient throughout the period under study. The empirical findings seem to suggest that most of the Bangladesh banks have been experiencing economies of scale due to being at less than the optimum size, or diseconomies of scale due to being at more than the optimum size. Thus, decreasing or increasing the scale of production could result in cost savings or efficiencies.

• Journal of Digital Convergence
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• v.11 no.10
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• pp.255-262
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• 2013

Data envelopment analysis(DEA) is a linear programming procedure designed to evaluate the relative efficiency of a set of peer entities called decision making units which use the same inputs to produce the same outputs. It has been widely employed in a variety of disciplines as an efficiency or performance measurement tool for comparing a set of entities such as firms, banks, hospitals, nations and organizations. The method, however, cant's make the priority of their performance when many units have efficiency score of unity or 100 percent. In this paper, we propose a new approach which combine qualitative method(graphical approach using network analysis) and quantitative method(super-efficient analysis using DEA), and present the results of an empirical analysis using the data of the Korean professional baseball players. As a result, there were 12 DMU that priority is hardly realized through DEA. However, this problem could be solved with super-efficiency analyzing. Also, more in-depth interpretation was able through integrating results of dendrogram and super-efficiency analyzing and prospecting it in qualitative, quantitative ways.

• International Journal of Contents
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• v.4 no.3
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• pp.1-9
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• 2008

The Korean life insurance industry has undergone profound changes, such as the beginning of the variable insurance in July 2001 and the bancassurance enforcement in August 2003. However, little empirical research has analyzed data that includes the bancassurance of life insurance companies operating in Korea. In response to this lack of research, this paper applies DEA (data envelopment analysis) models to measure and decompose their efficiency. We discovered that life insurance companies operating in Korea are a little different in their composition ratio of inputs and outputs, due to the increased variety of distribution channels and new products. We provided efficiency scores, return to scale, and reference frequencies. We also decomposed CCR, BCC, and SBM efficiency into scale efficiency and MIX efficiency. So, we try to investigate whether the sources of inefficiency were caused by the inefficient operation of DMU, disadvantageous conditions, the difference of the composition ratio in inputs and outputs with reference sets, or any combination of the above. Most companies in the sample display had either constant or decreasing returns to scale. The efficiency rankings were less consistent among models and efficient DMUs. In response to this problem, we used the super-efficiency model to rank them and then compared the rankings of the DMUs among the various models. It was also concluded that the availability of panel data, rather than cross-sectional data, would greatly improve the validity of the efficiency estimates.

• Journal of the Korea Academia-Industrial cooperation Society
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• v.15 no.1
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• pp.165-172
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• 2014

The purpose of this paper is to identify whether the national baseball squad made up of the best players may get the outstanding results in the international competitions or not. Using Data Envelopment Analysis, the relative efficiency of players in Korean Baseball Organization is estimated as performance measure, and compared with the efficiency scores of national squad members. The paper focuses on the proper choice of DEA model in a baseball setting, thereby selecting the BCC model with non-discretionary variable. Two input variables(plate appearances and stolen bases to enforce) and three output variables(runs, on-base plus slugging and stolen base percentage) are used to evaluate the efficiency of the baseball players. Results showed that 22 players among 97 players were classified as efficient and 8 players among 12 national squad members were as efficient. These findings indicate a potential for DEA to be a major part of the analytical approaches in evaluating the relative efficiency of players.