• The Journal of Fisheries Business Administration
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• v.43 no.2
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• pp.79-94
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• 2012

The purpose of this study is to investigate the production efficiencies of the Korean aquaculture fishery with respect to species and methods using a Data Envelopment Analysis. The study extracted the 8 fishes in each of the sea cage culture, aquarium basin, and enclosed aquaculture for the analytical purposes. First, the study estimated the technical, pure technical, and scale efficiencies of the total of 24 aquaculture fishes based on the traditional DEA under the assumptions of both CRS and VRS. 2 fishes were identified as the efficient DMUs under the CCR-model, and 6 fishes under the BCC-model. Second, we tested to see if there was any difference in production efficiencies regarding those three different methods of aquaculture. we could not find any evidence of the differences in efficiency using a rank sum test based on the traditional DEA. However, we could do find that the pure technical efficiency in the sea cage culture was lower than others at 1% level of significance and the pure technical efficiency in enclosed aquaculture was also lower than others at 5% level of significance using Bilateral-DEA, which could explicitly consider the heterogeneity in the 3 production methods of aquaculture. Finally, the study obtained the 95% confidence intervals of the efficiency scores for the 24 fishes under our study using the smoothed bootstraping method in the process of the re-sampling in cooperation with both a kernel density estimation and a reflection method. At the same time, we could estimate the bias-corrected efficiency scores while the traditionally estimated efficiency scores suffered from the biases in the process of solving a linear programming with the deterministic nature of a production frontier. And hence, we could distinguish the differences in production efficiencies of the 8 fishes with respect to those 3 methods of aquaculture.

• Journal of Korean Society of Industrial and Systems Engineering
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• v.38 no.4
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• pp.117-131
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• 2015

Conventional data envelopment analysis (DEA) models require that inputs and outputs are given as crisp values. Very often, however, some of inputs and outputs are given as imprecise data where they are only known to lie within bounded intervals. While a typical approach to addressing this situation for optimization models such as DEA is to conduct sensitivity analysis, it provides only a limited ex-post measure against the data imprecision. Robust optimization provides a more effective ex-ante measure where the data imprecision is directly incorporated into the model. This study aims to apply robust optimization approach to DEA models with imprecise data. Based upon a recently developed robust optimization framework which allows a flexible adjustment of the level of conservatism, we propose two robust optimization DEA model formulations with imprecise data; multiplier and envelopment models. We demonstrate that the two models consider different risks regarding imprecise efficiency scores, and that the existing DEA models with imprecise data are special cases of the proposed models. We show that the robust optimization for the multiplier DEA model considers the risk that estimated efficiency scores exceed true values, while the one for the envelopment DEA model deals with the risk that estimated efficiency scores fall short of true values. We also show that efficiency scores stratified in terms of probabilistic bounds of constraint violations can be obtained from the proposed models. We finally illustrate the proposed approach using a sample data set and show how the results can be used for ranking DMUs.

• Journal of Korean Society for Quality Management
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• v.43 no.4
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• pp.533-544
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• 2015

Purpose: The purpose of this study is to analyze the cost efficiency of food industry in JeollaNamdo. And this study is focused on the correlation between the economic efficiency of food industry and its cost efficiency, based on the analysis of 372 food companies' data in JeollaNamdo in 2012. Methods: DEA cost minimization is the measurement of the cost efficiency of JeollaNamdo food industry in 2012. In this study, the CCR and BBC models have been employed to analyze the decomposing cost efficiency-technical efficiency, allocative efficiency, and scale efficiency respectively. And the Spearman rank correlation and Wilcoxon signed rank test also have been employed to check the correlation and difference between the ranking orders based on the efficiency scores respectively. Results: For the CCR model, mean cost efficiency was found to be 0.084(0.54 for allocative efficiency and 0.19 for technical efficiency). For the BCC model, mean cost efficiency was found to be 0.252(0.453 for allocative efficiency and 0.564 for technical efficiency). Average scale efficiency was found to be 0.38. In analyzing the results, this study argues that the optimal way to improve cost efficiency is by reducing inputs proportionally and changing their combination. Conclusion: The efficiency scores of the two models show high correlation, whereas, the differences between them are also found to be significant. Hence, it should be cautious to select a suitable model when we do the research.

• Journal of the Korean Operations Research and Management Science Society
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• v.35 no.2
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• pp.19-35
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• 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 Digital Convergence
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• v.12 no.6
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• pp.181-192
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• 2014

This study suggests consulting directions for non-profit private organizations which were found to be inefficient in the efficiency analysis for the public activities support projects on those organizations performed by the Korean government. An ANOVA analysis on seven types of public activities support projects showed that there were differences among those types. By applying CCB-I, BCC-I, Super efficiency models among DEA, performance efficiencies were analyzed. Four input elements (age of the organization, supported amount, number of members, and the number of workers) and three output elements (project scores, financial scores, and comprehensive scores) were analyzed, and high efficient organizations were found as benchmarking objects, and, through super efficiency analysis, those objects were classified into short, mid, and long-term objects. Through such methods, this research provided organizations with the best information on other organizations to learn from and improve themselves.

• Journal of Korean society of Dental Hygiene
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• v.13 no.4
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• pp.639-644
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• 2013

Objectives : The aim of this study is to investigate the influencing factors of oral health behaviors according to oral health education experiences in middle school students. Methods : The subjects were 301 middle school students who lived in Gimhae and Jinhae. All statistical analyses were performed using SPSS. Results : The group with oral health education experience had higher scores in oral health knowledge(p<.01) than the group without oral health education. The group with oral health education experience has higher scores in oral health behavior (p<.01) than the group without oral health education. The group with oral health education experience has higher scores in self-efficiency (p<.01) than the group without oral health education. The experience of oral health education shows positive correlation with oral health knowledge(r=0.184), oral health behavior(r=0.199) and self-efficiency(r=0.199). There existed a positive correlation between oral health knowledge and self-efficiency(r=0.351). Conclusions : It is necessary to provide oral health promotion program in middle school students. The importance of oral health care is closely related to oral health knowledge.

• Journal of Korean Society for Quality Management
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• v.32 no.4
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• pp.92-102
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• 2004

In this era of intense competition, TQM has become the key program in organizations as they strive for a competitive advantage. It has been applied to manufacturing and service sector since BNQA model was established in 1987. TQM literature for manufacturing sector abounds with empirical studies on the critical dimensions of TQM, but there is few empirical studies on the TQM evaluation for service sector. In this paper, two methodologies are applied to evaluate the TQM activities of service companies comparatively One of them is the traditional scoring system(TSS) by analytic hierarchy process(AHP). The other is the efficiency measuring system(EMS) by data envelopment analysis(DEA). DEA outperformed other alternative methods to measure the efficiency and it can be applied to evaluate the TQM activities. The objective of this paper is to evaluate TQM activities of domestic service companies by applying TAE(Total quality management Activities Evaluation) model to them. The result of this study is that TSS scores are not significantly correlated with EMS scores. It means that service organizations must not only make efforts to get the higher scores in terms of TSS but also take necessary steps to enhance their efficiencies.

• The Journal of Fisheries Business Administration
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• v.46 no.2
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• pp.111-125
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• 2015

This study is to analyze the efficiency of Korean sea food manufacturing using Data Envelopment Analysis. Firstly, based on an output oriented traditional CCR, BCC model, the study estimated the efficiency scores. The average estimates of technical, pure technical, and scale efficiency turned out 0.6517, 0.7184, 0.9074 respectively, which are separated for 50 marine corporations. The 10 DMUs were efficient under CCR model while the 17 DMUs under BCC model. Also, the study suggested that the operating profit of the two output factors should be more increased relatively and averagely from the viewpoint of efficiency improvement. Secondly, super efficiency scores are estimated under super efficiency and SBM model. As a result, it came to be possible to distinguish and rank the efficiency of the efficient DMUs. The highest score was 4.2975 under Super-CCR, was 2.4947 under Super-BCC, was 2.7160 under SBM-Super-CCR, and was 1.5319 under SBM-Super-BCC model. The average estimates of super efficiency were 0.76 and 0.82 under Super-CCR and Super-BCC model respectively, and were 0.61 and 0.67 under SBM-Super-CCR and SBM-Super-BCC model. Finally, the study conducted a rank-sum test, Wilcoxon-Mann-Whitney test, to find a statistical significance of heterogeneity existing in efficiencies among the sample corporations. The result showed that there was a significant difference in average efficiency between Dried, Salted product manufacturing and Frozen product manufacturing under BCC-Super efficiency model at 10% level of significance. Furthermore, TOBIT model was applied to find out the potential factors that might influence the efficiency, Wilcoxonand the results showed debt and sales cost influenced all of the technical, pure technical, and scale efficiency, while net profit influenced only the technical efficiency.

• IE interfaces
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• v.24 no.4
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• pp.314-322
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• 2011

This study analyzes a relationship between Data Envelopment Analysis(DEA) efficiency scores and a normalization index in order to examine the validity of DEA models. A normalization index concerned in this study is 'sales per R&D project fund' which is regarded as a crucial R&D project performance evaluation index in practice. For this correlation analysis, three distinct DEA models are selected such as DEA basic model, DEA/AR-I revised model(i.e. DEA basic model with Acceptance Region Type I constraints) and Super-Efficiency(SE) model. Especially, SE model is adopted where efficient R&D projects(i.e. Decision Making Units, DMU's) with DEA efficiency score of unity from DEA basic model can be further differentiated in ranks. Considering the non-normality and outliers, two rank correlation coefficients such as Spearman's ${\rho}_s$ and Kendall's ${\tau}_B$ are investigated in addition to Pearson's ${\gamma}$. With an up-to-date empirical massive dataset of n = 482 R&D projects associated with R&D Loan Program of Korea Information Communication Promotion Fund in the year of 2011, statistically significant (+) correlations are verified between the normalization index and every model's DEA efficiency scores with all three correlation coefficients. Especially, the congruence verified in this empirical analysis can be a useful reference for enhancing the practitioner's acceptability onto DEA efficiency scores as a real-world R&D project performance evaluation index.

• Journal of the Korea Academia-Industrial cooperation Society
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• v.11 no.7
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• pp.2406-2419
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• 2010

This study aims to elevate the usefulness of the current annual Accreditation of Hospitals. To achieve this purpose, A modeling of an efficiency analysis based on DEA and AHP to the Accreditation of Hospitals Data from 2004 to 2008. By applying to AHP and DEA_AR to the scores derived from the various domains in data, An adequate prediction model about conversion factor in fee contract is made. By summarizing information derived from DEA, factor analysis and Generalized Linear Model, The linear functions combining conversion factor and efficiency index is successfully established. The factor analysis with AHP was used to merge diverse scores from the domains of evaluation. Not only the input and output initially introduced, AHP scores, dummy variables of hospital classification, geographical location are effective variables to forecast a conversion factor. If a predicted conversion factors from efficiency is used, It will be a great contributions to the annul doctor's fee contract.