• The Journal of the Korea Contents Association
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• v.15 no.5
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• pp.475-487
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• 2015

This study measures the managerial efficiency of Korea's 14 public enterprises using bootstrap DEA in 2013. In addition, it examines the factors that affect on the bootstrap bias-corrected efficiency using truncated regression analysis. The results and implications of this study are as follows. First, using bootstrap DEA model analysis, the results showed that the mean technical efficiency was 0.3182, the mean pure technical efficiency was 0.4994 and the mean scale efficiency was 0.6585. The main cause of technical inefficiency was due to pure technical inefficiency. Second, rank test between technical efficiency of general DEA model and bootstrap DEA model was no significant difference under CRS and VRS assumption. Third, the main cause of the inefficiency in 11 DMUs among 14 DMUs were mainly due to the pure technology and three DMUs were because of the scale efficiency. Finally, in the truncated regression analysis, cost of labor, profit, sales, return of equity, and the number of employees appeared as factors affecting the scale efficiency at the 10% significance level.

• Journal of Korea Port Economic Association
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• v.32 no.1
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• pp.29-58
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• 2016

The purpose of this paper is to show the clustering trend and the comparison of empirical results and is to choose the clustering ports for 3 Korean ports(Busan, Incheon and Gwangyang Ports) by using the bootstrapped DEA(Data Envelopment Analysis) and game Cross-efficiency models for 38 Asian ports during the period 2003-2013 with 4 input variables(birth length, depth, total area, and number of cranes) and 1 output variable(container TEU). The main empirical results of this paper are as follows. First, bootstrapped DEA efficiency of SW and LT is 0.7660, 0.7341 respectively. Clustering results of the bootstrapped DEA analysis show that 3 Korean ports [ Busan (6.46%), Incheon (3.92%), and Gwangyang (2.78%)] can increase the efficiency in the SW model, but the LT model shows clustering values of -1.86%, -0.124%, and 2.11% for Busan, Gwangyang, and Incheon respectively. Second, the game cross-efficiency model suggests that Korean ports should be clustered with Hong Kong, Shanghi, Guangzhou, Ningbo, Port Klang, Singapore, Kaosiung, Keelong, and Bangkok ports. This clustering enhances the efficiency of Gwangyang by 0.131%, and decreases that of Busan by-1.08%, and that of Incheon by -0.009%. Third, the efficiency ranking comparison between the two models using the Wilcoxon Signed-rank Test was matched with the average level of SW (72.83 %) and LT (68.91%). The policy implication of this paper is that Korean port policy planners should introduce the bootstrapped DEA, and game cross-efficiency models when clustering is needed among Asian ports for enhancing the efficiency of inputs and outputs. Also, the results of SWOT(Strength, Weakness, Opportunity, and Threat) analysis among the clustering ports should be considered.

• Journal of the Korean Operations Research and Management Science Society
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• v.24 no.2
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• pp.53-68
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• 1999

This paper presents a nonparametric method to test if the mean difference of DEA efficiency estimates between two groups statistically exists. A proposed method employs a bootstrapping approach to generation BCC efficiency estimates through Monte Carlo simulation resampling process. For the purpose of demonstration, we empirically apply the proposed method to the korean bank industry and compare its result with the result by the traditional deterministic DEA method. The nonparametric statistical hypothesis testing procedure in this study, which considers not only stochastic variability of the DEA data, but also random radial deviations off the efficient frontier, serves as a useful tool for dbjectively evaluating whether the mean difference of DEA efficiency estimates between groups is statistically significant.

• Journal of Korea Port Economic Association
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• v.37 no.3
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• pp.75-91
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• 2021

Due to increased competition in supply side to reduce operational costs, port professionals have experienced extreme pressure, which demanded academicians to develop the model for efficient port operations from the industry perspective. Among many ports in the world, U.S. ports are our primary interest to analyze in our study for its high volume of cargoes transacted in the U.S. ports. We primarily employed DEA (Data Envelopment Analysis) technique to research the productivity of U.S. ports and applied the algorithm of double bootstrapped DEA proposed by Simar & Wilson (2007) to further investigate the driving forces of the performance of U.S. port operations. The external variables employed in our study comprise onDock Rail, Channel Depth, Location, Area, Acres, ForeignCargoRatio, and TEUChange, out of which onDock Rail, Acres, ForeignCargoRatio, and TEUChange were significant. In order to evaluate the effects of methodology selection, we conducted the same analysis applying the Censored model (Tobit) and contrasted the outcomes drawn from the two different techniques. Based on the findings from this work we proposed managerial implications and concluded.

• Proceedings of the Korean Society for Quality Management Conference
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• 2010.04a
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• pp.33-48
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• 2010

The purpose of this study is to empirically analyze the productivity change of the 10 Single PPM Certification Company in the 3 Industry(Electronics, Motor-Parts, Machines). In this study, Productivity change over the time in Korean small and medium sized firms in the 3 industries by the bootstrapped Malmquist Productivity Index(MPI). The traditional Malmquist Productivity Index(MPI) and Data Envelopment they could lead to wrong evaluations of the efficiency and productivity scores. In this paper, DEA and a MPI are combined with a bootstrap method in order to provide statistical inferences that analyze the performance of the Single PPM Certification Company. The data cover the period between 2004 and 2007. The result of this paper reveals : 1) The electronic industries(Motor-Parts, Machines). 2) average productivity Progress of the 7DMU(Electronics), 1DMU(Motor-Parts) and none(Machines).

• Journal of Korean Society for Quality Management
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• v.38 no.2
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• pp.261-275
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• 2010

The purpose of this study is to empirically analyze the productivity change of the 10 Single PPM Certification Company in the 3 Industry(Electronics, Motor-Parts, Machines). In this study, Productivity change over the time in Korean small and medium sized firms in the 3 industries by the bootstrapped Malmquist Productivity Index(MPI). The traditional Malmquist Productivity Index(MPI) and Data Envelopment Analysis(DEA) Models have not only bias but also lack statistical confidence intervals. they could lead to wrong evaluations of the efficiency and productivity scores. In this paper, DEA and a MPI are combined with a bootstrap method in order to provide statistical inferences that analyze the performance of the Single PPM Certification Company. The data cover the period between 2004 and 2007. The result of this paper reveals : 1) The Electronics Industry had productivity effect of 17%, but there was not direct effect for other Industries(Motor-Parts, Machines). 2) average productivity Progress of the 7DMU(Electronics), 1DMU(Motor-Parts) and none(Machines).

• Journal of Korean Society of Industrial and Systems Engineering
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• v.41 no.3
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• pp.61-71
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• 2018

The purpose of this study is to analyze the efficiencies of project management offices in large information system construction projects using the data envelopment analysis. In addition, we tried to estimate the confidence interval of those efficiencies using bootstrap DEA to give a statistical meaning. The efficiency by the CCR model is analyzed as eight project management offices are fully efficient and 22 project management offices are inefficient. On the other hand, there are 15 project management offices are fully efficient, but 15 project management offices are inefficient in the BCC model. As the result of the scale efficiencies, of the inefficient project management offices, 13 project management offices are inefficient in scale. It is possible to eliminate the inefficiency in the CCR model by improving their project performances. And, the nine project management offices showed that the inefficiency was due to pure technical efficiency, and these companies should look for various improvements such as improvement of project execution system and project management process. In order that the inefficient project management offices be efficient, it is analyzed that more efforts must be made for on-budget and on-time as a result of examining the potential improvement potentials of inefficient project management offices.

• Journal of Navigation and Port Research
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• v.33 no.8
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• pp.573-581
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• 2009

Today, overall industry has been operated on the basis of information technology and has increased the investment on it. In the logistics industry, the integrated material handling information network has become important more and more and the investment on the informatization has been increased to operate efficiently. In the previous literature, most of the measures for the efficiency of container terminals were the variables such as fixed assets of equipments. There has not been any research effort toward examining the effect of informatization level on the efficiency. This work describes the importance on the efficiency evaluation considering the informatization level to in a container terminal and the relative efficiency level is measured using data envelopment analysis and bootstrap.