• The Journal of Fisheries Business Administration
• /
• v.47 no.1
• /
• pp.63-86
• /
• 2016

The purpose of this study is to investigate production efficiency of Oceans and Fisheries Human Resources Development Programs Efficiency using Bootstrap-DEA. The study extracts 33 officials curriculum, 11 fisheries managers curriculum for its analytical. First, the study estimates technical, pure technical, and scale efficiency of each curriculums based on traditional DEA under the assumption of CRS and VRS. 8(official 7, managers 1) curriculums are identified as efficient DMUs under the CCR-model, and 13(official 10, managers 3) under the BCC-model. We provide inputs that allow inefficient curriculum to be efficient DMUs on a production frontier, and a reference set for their bench-marking. Second, rank test, Wilcoxon-Mann-Whitney test to find a statistical significance of heterogeneity existing in efficiences between Bootstrap-DEA tenical vs Bootstrap-DEA pure technical was no significant difference. We have identified that G10, 11, 12 13, 25, 31, 33, 39 curriculums are the most efficiently produced in the technical and pure technical efficiency. Also we managed to measure the inefficiency which exists in efficiently produced curriculums when estimating the bias corrected efficiency scores. In Technical efficiency, Operation and facility was significant at the 10%. In Pure technical efficiency, facility was significant at the 10%.

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

• Proceedings of the Korean Institute of Information and Commucation Sciences Conference
• /
• 2018.05a
• /
• pp.298-299
• /
• 2018

In this study, the discriminant power of the DEA models which do not require the prior information of decision makers was evaluated. Entropy model, Bootstrap model, Benevolent Cross Efficiency model, Aggressive Cross Efficiency model and Game Cross Efficiency model were selected as the DEA model for discriminant power evaluation. The discriminant power of five DEA models was evaluated using coefficient of variation and degree of importance. According to the evaluation results, the rank of discrimination power was evaluated in the order of Entropy model, Aggressive CE model, Benevolent CE model, Game CE model, and Bootstrap model in both evaluation indexes.

• The Journal of the Korea Contents Association
• /
• v.17 no.1
• /
• pp.201-212
• /
• 2017

This study presented the new evaluation index which can evaluate the discrimination of DEA models. To evaluate the discrimination of DEA models, data were analyzed using importance index as suggested in previous study and the coefficient of variation as suggested in this study for the discrimination evaluation. This study selected the CCR-DEA, BCC-DEA, entropy, bootstrap, super efficiency, and cross efficiency DEA model for the discrimination evaluation and accomplished empirical analysis. In order to grasp the rank correlation of the models, this study implemented the rank correlation analysis between the efficiency of CCR model and BCC model and entropy, bootstrap, super efficiency, and efficiency of the cross efficiency model. The obtained results of this study are as follows. First, the discrimination rank of models using the importance index and the coefficient of variation was shown to be identical. Therefore, the coefficient of variation can be used the discrimination evaluation index of DEA model. Second, the discrimination of the super efficiency model was found to be the highest rank among 4 models according to the analysis of this present study. Third, the highest rank correlation with CCR model was the super efficiency model. In addition, the super efficiency model was found to be the highest rank correlation with BCC model.

• The Journal of Fisheries Business Administration
• /
• v.52 no.1
• /
• pp.23-46
• /
• 2021

The purpose of this study is to understand the production efficiency of individual fishing communities and provide directions for improvement. The subject of the study is aquaculture type Ochon-Gye in Goheung-gun. The analysis method used bootstrap-DEA to overcome the statistical reliability problem of the traditional DEA analysis technique. In addition, data mining-GIS was applied to identify the spatial productivity of fishing communities. The values of technology efficiency, pure technology efficiency, and scale efficiency were estimated for 32 aquaculture-type fishing villages. Then, using the benchmarking reference set and weights, the projection was presented through adjustment of the input factor excess, and furthermore, the confidence interval of the efficiency values considering statistical significance was estimated using bootstrap.

• Journal of Distribution Science
• /
• v.15 no.11
• /
• pp.49-57
• /
• 2017

Purpose - In Korea, general super markets have a great impact on the market performance of traditional markets. We propose a modified two stage DEA model for evaluating the performance of traditional markets in Incheon, Korea by identifying the influence of external environmental factors including the presence of general super markets as non-discretionary variables in DEA. Research design, data, and methodology - After obtaining bias-corrected estimates of original DEA efficiency scores using the input and output data of 49 traditional markets, we regress them on several external environmental factors by bootstrap-truncated regression. Results - We obtain bias-corrected efficiency scores from the original DEA efficiency scores by bootstrap and among the five environmental factors, the residential population and the presence of general super markets or SSMs can be considered as the driving forces influencing bias-corrected efficiency scores, positively and negatively, respectively. Conclusions - When DEA efficiency scores tend to be overestimated, we need to use a biased-corrected efficiency score by bootstrap. It is important to note that the efficiency of traditional markets can be largely influenced by external environmental factors such as the presence of general super markets or SSMs that traditional markets can not control. Therefore, it is desirable to consider such environmental factors appropriately for a reasonable performance evaluation.

• Journal of the Korean Operations Research and Management Science Society
• /
• v.35 no.2
• /
• pp.19-35
• /
• 2010

Many papers have used a two-stage approach of first calculating DEA efficiency scores and then seeking to correlate these scores with various environmental variables. Most of the studies have not checked whether such a two-stage approach is statistically valid for identifying significant environmental variables. Recently Simar and Wilson (2007) (SW) introduce a sensible data generating process and bootstrap procedure based on truncated regression for the two-stage approach. Banker and Natarajan (2008) (BN) provide a statistical foundation for the two-stage approach comprising a DEA followed by an ordinary least squares or maximum likelihood estimation. Researchers have to identify an approach suitable for their research circumstances in terms of properties, merits, demerits, and robustness to plausible departures from its chosen data generating process. We summarize the foundations and properties of the two-stage procedures suggested by SW and BN. And we discuss merits and demerits of those procedures. Also using Monte Carlo simulation we assess their relative performance under several misspecified settings.

• Journal of Korean Society of Industrial and Systems Engineering
• /
• v.41 no.3
• /
• pp.61-71
• /
• 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
• /
• v.33 no.8
• /
• pp.573-581
• /
• 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.

• Journal of Korean Society for Quality Management
• /
• v.42 no.4
• /
• pp.647-664
• /
• 2014

Purpose: The purpose of this study was to evaluate administrative efficiency of the Korean university and to identify the factors which may affect on the efficiency of universities. In addition, last purpose of this study was to compare correlation among administrative, research and education model. Methods: The collected data through Higher Education in Korea were analysed using DEA (Data Envelopment Analysis). Furthermore, in order to provide the better accurate results by removing the bias of the results, this paper implements Bootstrap DEA. It also analyzed the causes of efficiency by Tobit Regression after setting the dependent variable as a proposed efficiency score and compared correlation analysis results between other models. Results: The results of this study are as follows; First, the Korean universities showed low administrative efficiencies. Second, efficiency of national universities are higher than it of private universities. Finally, the administrative and research education model have statistically significant correlation. However, usually many Korean universities focus their resources on education performance such as employment and rates to attract new students than research performances. Conclusion: This study shows that the administrative efficiency positively affects both research and educational efficiency. Approximately 70% of the Korean universities needs to improve their administrative efficiencies and to pay attention to enhance their poor services, low-level performances.