• Journal of Navigation and Port Research
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• v.42 no.2
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• pp.107-116
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• 2018

Planning strategies to achieve higher competitiveness of ports are becoming increasingly important in business environment. Therefore, strategic competitive position and efficiency analysis needs to be performed to increase ports' effectiveness and competitiveness. This matches with one of targets of new concept e-Navigation to increase the agility and efficiency of ports. The purpose of this study was to apply Boston Consulting Group matrix to analyze competitive positioning of major ports in Korea and China in term of several main cargo types and then use a combination of Data Envelopment Analysis and Principal Component Analysis model to calculate efficiencies. Results show that, at the moment, Chinese ports are still on the top with high position and efficiency score for the representative-Shanghai port. However, result also points out that except container type, Korean ports have chance to compete in other cargo types. Moreover, Gwangyang port is regarded as efficient. It has better position time. It is believed that Gwangyang port together with Busan port can compete with Chinese port in the near future.

• Proceedings of the Korean Institute of Intelligent Systems Conference
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• 1998.06a
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• pp.517-521
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• 1998

DEA(data envelopment analysis) is a non-parametric technique for measuring and evaluating the relative efficiencies of a set of entities with common crisp inputs and outputs. In fact, in a real evaluation problem input and output data of entities often flucturate. These fluctuating data can be represented as linguistic variables characterized by fuzzy numbers. Based on a fundamental CCR model, a fuzzy DEA model is proposed to deal with fuzzy input and output data, Furthermore, a model that extends a fuzzy DEA to a more general case is also proposed with considering the relation between DEA and RA (regression analysis) . the crisp efficiency in CCR modelis extended to an L-R fuzzy number in fuzzy DEA problems to reflect some uncertainty in real evaluation problems.

• Journal of the Korean Statistical Society
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• v.33 no.4
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• pp.449-458
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• 2004

Data envelopment analysis (DEA) estimators have been widely used in productivity analysis. The asymptotic distribution of DEA estimator derived by Kneip et al. (2003) is too complicated and abstract for analysts to use in practice, though it should be appreciated in its own right. This paper provides another way to express the limit distribution of the DEA estimator in a tractable way.

• Proceedings of the Korean Institute of Navigation and Port Research Conference
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• v.1
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• pp.163-170
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• 2006

This paper presents a approach to the measurement of efficiency. Data envelopment analysis(DEA), as it is called, has particular applicability in the service sector. Applying mathematical programming techniques, DEA enables relative efficiency ratings to be derived within a set of analysed units. This paper investigates the efficiency employing DAE-CCR Model and DEA-BCC Model on data for 15 container terminals covering 1998$^{\sim}$2005 in Korea Results of this paper, suggests to some plan for operation strategy in Container terminals.

• Proceedings of the KIEE Conference
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• 2007.07a
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• pp.854-855
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• 2007

Analyzing the productivity has been widely applied in economic analysis and of the key concept of utility regulation. In this paper we use benchmarking technique known as Data Envelopment Analysis (DEA) model to analyze the productivity. And we show that from the result it is possible to evaluate the performance of inefficient firms by reducing their input levels.

• 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.

• Industrial Engineering and Management Systems
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• v.15 no.1
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• pp.49-62
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• 2016

In this paper, we propose an integrated data envelopment analysis (DEA) and analytic hierarchy process (AHP) methodology in which the information about the hierarchical structures of input-output data can be reflected in the performance assessment of decision making units (DMUs). Firstly, this can be implemented by extending a traditional DEA model to a three-level DEA model. Secondly, weight bounds, using AHP, can be incorporated in the three-level DEA model. Finally, the effects of incorporating weight bounds can be analyzed by developing a parametric distance model. Increasing the value of a parameter in a domain of efficiency loss, we explore the various systems of weights. This may lead to various ranking positions for each DMU in comparison to the other DMUs. An illustrative example of road safety performance for a set of 19 European countries highlights the usefulness of the proposed approach.

• Journal of the Korea Safety Management & Science
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• v.16 no.4
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• pp.359-369
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• 2014

Due to the severe market conditions, pre-entrepreneur seeks to start their business through franchise company. This paper, using the data envelopment analysis(DEA) method, examines efficiency of a group of franchise company in order to provide efficiency information with pre-entrepreneur. Output-oriented DEA model is applied in the investigation of efficiency, and the overall efficiency score is decomposed into pure technical efficiency and scale efficiency. The input variables selected to evaluate the efficiency are franchise deposit, franchise contribution cost and the output variables are sales and number of franchises, and length of business. The results of this paper show franchise industry have the low level of overall efficiency and the main sources of inefficiency is found technical rather than scale. As a result, this paper provides not only the current status of efficiency information of a franchise with pre-entrepreneur but also give warning when they sign-up with franchise business.

• Journal of Navigation and Port Research
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• v.29 no.3 s.99
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• pp.195-201
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• 2005

This paper presents the measurement of efficiency for container ports. Data envelopment analysis(DEA), as it is called, has particular applicability in the service sector. Applying mathematical programming techniques, DEA enables relative efficiency ratings to be derived within a set of analysed units. This paper investigates the efficiency employing DEA Model on data for 53 container ports covering 1995-2001 in the world and the change in efficiency for 7 years. As a results, port of Busan was evaluated as inefficiency port compare with major ports of the world except 1995year and 1996year. But After 1997year, efficiency of Busan port is increasing somewhat better every year.

• Health Policy and Management
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• v.30 no.2
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• pp.199-210
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• 2020

Background: Based on the importance of ceasing smoking programs to control the regional disparity of smoking behavior in Korea, this study aims to reveal the variation of smoke rate and determinants of it for 229 provinces. An evaluation of the relative efficiency of the cease smoking program under the consideration of regional characteristics was followed. Methods: The main sources of data are the Korean Statistical Information Service and a national survey on the expenditure of public health centers. Multivariate regression is performed to figure the determinants of regional variation of smoking rate. Based on the result of the regression model, clustering analysis was conducted to group 229 regions by their characteristics. Three clusters were generated. Using data envelopment analysis (DEA), relative efficiency scores are calculated. Results from the pooled model which put 229 provinces in one model to score relative efficiency were compared with the cluster-separated model of each cluster. Results: First, the maximum variation of the smoking rate was 16.9%p. Second, sex ration, the proportion of the elder, and high risk drinking alcohol behavior have a significant role in the regional variation of smoking. Third, the population and proportion of the elder are the main variables for clustering. Fourth, dissimilarity on the results of relative efficiency was found between the pooled model and cluster-separated model, especially for cluster 2. Conclusion: This study figured regional variation of smoking rate and its determinants on the regional level. Unconformity of the DEA results between different models implies the issues on regional features when the regional evaluation performed especially on the programs of public health centers.