• Journal of Korean Society of Industrial and Systems Engineering
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• v.45 no.2
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• pp.30-36
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• 2022

This study analyzed the relationship between efficient pitchers and teams advancing to the postseason in Korean professional baseball through DEA. A total of 1,133 pitchers who threw more than one inning from the 2014 season to the 2018 season were selected for this study. For DEA analysis, input variables were selected as annual salary and inning output variables as Wins, Saves, and Holds and the number of efficient pitchers for each season was classified using the input-oriented BCC model. After that, it was divided into two groups based on joining the postseason or not, and the number of efficient pitchers was compared through a prop test. As a result of the analysis, the groups that advanced to the postseason in the rest of the season except for the 2014 and 2017 seasons had more efficient pitchers. Considering that the 2014 season recorded the highest WAR (Wins Above Replacement) at 183.56 compared to other seasons, most pitchers threw well, and in the 2017 season, they made more mistakes in pitching than in other seasons, but they performed well in batters. The results of this study have expanded the research field using efficiency analysis in professional baseball and can be used as useful data for practical research.

• Journal of Korean Society of Forest Science
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• v.105 no.2
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• pp.247-252
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• 2016

This study was conducted to evaluate the technical efficiency of Annual Chestnut production in South Korea. In this study, technical efficiency is the maximum possible production for which a certain amount of costs is inputted. For analysis on the technical efficiency we used output-oriented BCC Model, and then we analyzed correlation among input costs, production, gross income, net income, and market price per unit in order to determine the cause of variation in the technical efficiency. As study materials, we used statistics for the forestry production costs for 7 years from 2008 to 2014. The study results showed that the maximum possible production and actual production in 2008, 2009, and 2010 were 1,568 kg, 1,745 kg, and 1,534 kg by hectares in the order which were the same values. Consequently, the technical efficiency of those was all evaluated as 1.00. On the other hand, actual production from 2011 to 2014 was 1,270 kg 1,047 kg, 1,258 kg, and 1,488 kg by hectares in the order and the maximum possible production was 1,524 kg, 1,467 kg, 1,635 kg, and 1,637 kg by hectares in the analysis. From those values, the technical efficiency was evaluated in the following order:0.83, 0.71, 0.75, 0.91. The lowest value of the technical efficiency was 0.71 in 2012, and the values of this increased gradually since 2013. It is indicated that the cause of variation in the technical efficiency was related to the relationship between production and market price, and there was a negative correlation with r = -0.821 (p<0.05). The level of maximum available production per unit area was between 1,488kg in lower limit and 1,745 kg in upper limit, and the average was turned out as 1,548 kg.

• Journal of Korea Water Resources Association
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• v.51 no.12
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• pp.1195-1205
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• 2018

In the study, the water shortage of Boryeong Dam watershed ($163.6km^2$) was evaluated under future climate change scenario. The Soil and Water Assessment Tool (SWAT) was used considering future dam release derived from multiple linear regression (MLR) analysis. The SWAT was calibrated and verified by using daily observed dam inflow and storage for 12 years (2005 to 2016) with average Nash-Sutcliffe efficiency of 0.59 and 0.91 respectively. The monthly dam release by 12 years MLR showed coefficient of determination ($R^2$) of above 0.57. Among the 27 RCP 4.5 scenarios and 26 RCP 8.5 scenarios of GCM (General Circulation Model), the RCP 8.5 BCC-CSM1-1-M scenario was selected as future extreme drought scenario by analyzing SPI severity, duration, and the longest dry period. The scenario showed -23.6% change of yearly dam storage, and big changes of -34.0% and -24.1% for spring and winter dam storage during 2037~2047 period comparing with 2007~2016 period. Based on Runs theory of analyzing severity and magnitude, the future frequency of 5 to 10 years increased from 3 in 2007~2016 to 5 in 2037~2046 period. When considering the future shortened water shortage return period and the big decreases of winter and spring dam storage, a new dam operation rule from autumn is necessary for future possible water shortage condition.

• Atmosphere
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• v.25 no.2
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• pp.295-308
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• 2015

Based on the CMIP5 historical simulation datasets, we assessed the performance of state-of-the-art climate models in respect to the relationship between interannual variabilities of the North Pacific synoptic eddy (NPSE) and East Asian winter monsoon (EAWM). Observation (ERA-Interim) shows a high negative correlation (-0.73) between the interannual variabilities of East Asian winter monsoon (EAWM) intensity and North Pacific synoptic eddy (NPSE) activity during the period of 1979~2005. Namely, a stronger (weaker) EAWM is related to a weaker (stronger) synoptic eddy activities over the North Pacific. This strong reverse relationship can be well explained by latitudinal distributions of the surface temperature anomalies over East Asian continent, which leads the variation of local baroclinicity and significantly weakens the baroclinic wave activities over the northern latitudes of $40^{\circ}N$. This feature is supported by the distribution of the meridional heat flux (${\overline{{\nu}^{\prime}{\theta}^{\prime}}}$) anomalies, which have negative (positive) values along the latitudes $40{\sim}50^{\circ}N$ for strong(weak) EAWM years. In this study, the historical simulations by 11 CMIP5 climate models (BCC-CSM1.1, CanESM2, GFDL-ESM2G, GFDL-ESM2M, HadGEM2-AO, HadGEM2-CC, IPSL-CM5A-LR, MPI-ESM-LR, MPI-ESM-MR, MRI-CGCM3, and NorESM1-M) are analyzed for DJF of 1979~2005. Correlation coefficient between the two phenomena is -0.59, which is comparable to that of observation. Model-to-model variation in this relationship is relatively large as the range of correlation coefficient is between -0.76 (HadGEM2-CC and HadGEM2-AO) and -0.33 (MRI-CGCM3). But, these reverse relationships are shown in all models without any exception. We found that the multi-model ensemble is qualitatively similar to the observation in reasoning (that is, latitudinal distribution of surface temperature anomalies, variation of local baroclinicity and meridional heat flux by synoptic eddies) of the reverse relationship. However, the uncertainty for weak EAWM is much larger than strong EAWM. In conclusion, we suggest that CMIP5 models as an ensemble have a good performance in the simulation of EAWM, NPSE, and their relationship.

• Korea Journal of Hospital Management
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• v.16 no.4
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• pp.35-66
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• 2011

This study analyzed efficiency by utilizing DEA analytical technique centering on materials for 2009 of 20 major university hospitals in capital area. Input variables were utilized professor & full-time doctor, resident, nurse & number of bed hospitals. Output variables were analyzed by dividing number of annual outpatients & number of annual inpatients, and annually total outpatient profit & inpatient profit into a model of the standard for number of patients and the standard for medical profit. DEA analysis was elicited efficiency score by applying CCR, BCC, BFG, scale profit, and SE model. Through t-test after eliciting efficiency score, the implications were suggested by comparing efficiency between DMU in Seoul and DMU in capital area, by comparing between high-class general hospitals and general hospitals, and by comparing between high-class general hospitals in Seoul and 5 big hospitals. As a result of analysis, the major university hospitals in capital area showed high efficiency as a whole close to "1," but indicated low efficiency relatively in CCR field. Thus, the expansion in scale within capital area was indicated to reach the limit. Second, in a model of analyzing the standard for number of patients, the medical institutions, which are being operated efficiently, were indicated to be 10 DMUs. In the standard for medical profit, 12 DMUs were analyzed to be operated efficiently. Third, the efficiency in general hospital was higher than high-class general hospital. Thus, the efficiency of operation was indicated to be more important than scale. Also, large high-class hospitals(big 5) where are located in downtown Seoul showed the higher efficiency than other general high-class general hospitals, but were indicating very low efficiency in some DMUs. Fourth, as a result of generalizing and evaluating the number of patients and the medical profit, the efficient DMU was indicated to be more when analyzing on the basis of medical profit than the standard for number of patients. Thus, major university hospitals in capital area were indicated to make more effort for section in medical profit. Based on the analytical results of efficiency, a strategy for reinforcing efficiency in inefficient DMU was indicated to be needed a strategy of creating customers for promoting number of patients and a strategy for making operation efficient for increasing profitability.

• Journal of Distribution Science
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• v.11 no.8
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• pp.5-14
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• 2013

Purpose - We live in a world of constant change and competition. Many airports have specific competitiveness goals and strategies for achieving and maintaining them. The global economic recession, financial crises, and rising oil prices have resulted in an increasingly important role for facility investment and renewal and the implementation of appropriate policies in ensuring the competitive advantage for airports. It is thus important to analyze the factors that enhance efficiency and productivity for an airport. This study aims to determine the efficiency levels of 20 major airports in East Asia, Europe, and North America. Further, this study also suggests suitable policies and strategies for their development. Research design, data, and methodology - This paper employs the DEA-CCR, DEA-BCC, and DEA-Malmquist production index analysis models to determine airport efficiency. The study uses data on the efficiency and productivity of the world's leading airports between 2006 and 2010. The input variables include the airport size, the number of runways, the size of passenger terminals, and the size of cargo terminals. The output variables include the annual number of passengers and the annual cargo volume. The study uses basic data from the 2010 World Airport Traffic Report (ACI). The world's top 20 airports (as rated by the ACI report) are investigated. The study uses the expanded DEA Model and the Super Efficiency Model to identify the most effective airports among the top 20. The Malmquist productivity index analysis is used to measure airport effectiveness. Results - This study analyzes longitudinal and cross-sectional data on the world's top 20 airports covering 2006 to 2010. A CCR analysis shows that the most efficient airports in 2010 were Gatwick Airport (LGW), Zurich Airport (ZRH), Vienna Airport (VIE), Leonardo da Vinci Fiumicino Airport (FCO), Los Angeles International Airport (LAX), Seattle-Tacoma Airport (SEA), San Francisco Airport (SFO), HongKong Airport (HKG), Beijing Capital International Airport (PEK), and Shanghai Pudong Airport (PVG). We find that changes in airport productivity are affected more by technical factors than by airport efficiency. Conclusions - Based on the study results, we offer four airport development proposals. First, a benchmark airport needs to be identified. Second, inefficiency must be reduced and high-cost factors need to be managed. Third, airport operations should be enhanced through technical innovation. Finally, scientific demand forecasting and facility preparation must become the focus of attention. This paper has some limitations. Because the Malmquist productivity index is based on the hypothesis of the, the identified production change could be over- or under-estimated. Further, as DEA estimates the relative efficiency. It also cannot generalize to include all airport conditions because the variables are limited. To measure airport productivity more accurately, other input variables and environmental variables such as financial and policy factors should be included.

• Journal of Korean Society of Forest Science
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• v.102 no.3
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• pp.390-397
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• 2013

The study, utilizing a data envelopment analysis (DEA) which is one of the nonparametric estimation methods, aims to evaluate the management efficiency of chestnut tree cultivators in such provinces in Chungchungnam-do as Cheong-yang, Gong-ju, Bu-yeo and so on. The analysis data of this study is based on inputs and outputs of 20 forestry households surveyed in the 2012 survey titled 'A Study on Current Level and Condition of Chestnut Cultivation and Management', which was conducted from March 2012 to October 2012. The elements of inputs are composed of management cost, harvesting cost, material cost, non-operation expenses and cultivation area, while the element of output is a gross margin only. Then the study analyzes a technical efficiency, a puretechnical efficiency and a scale efficiency using CCR and BCC model among DEA methods. Based on that, it also provides improvement methods for forestry households that turned out to be inefficient. In order to verify the result of DEA analysis, the study additionally compares a result of this efficiency study with that of chestnuts management standard diagnostic table. According to the result, the average value of technical efficiency analyzed was 0.667, proving to be inefficient in general. Given that the average value of pure-technical efficiency was 0.944 and that of scale efficiency was 0.703, it can be inferred that inefficiency exists in the field of scale, not in the field of cultivation techniques. As for forestry households with the efficiency score of 1, it is shown that there were 6 households that recorded 1 in the technical efficiency field and 13 households that recorded 1 in the pure technical efficiency. Meanwhile, there were 6 households that recorded 1 in all of the three aspects. In the comparison with the scores from chestnuts management standard diagnostic table, there were 5 households made a high score of over 80, among which are 3 households with score 1 in the technical efficiency. Also, the results of this study and the chestnuts management standard diagnostic table are proved to have the same result, both of them showing the same households that recorded the highest score and the lowest score. This means the management efficiency evaluation using DEA can be applied to the fieldwork along with the chestnuts management standard diagnostic table.

• Journal of Distribution Science
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• v.12 no.4
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• pp.23-30
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• 2014

Purpose - The purpose of this study is to analyze the efficiency of retail businesses by dividing domestic retailers into discount stores, super supermarkets (SSMs), and department stores. It suggests retail-business investment strategies by using data environment analysis (DEA) to analyze how input elements such as store area, parking lot area, number of employees, and sales management expenses for the convenience of customers positively affect business performance measurements such as sales and visiting customers per day. Research Design, Data, and Methodology - The DEA model calculates a ratio of the weighted mean of various inputs to the weighted mean of various outputs and measures the efficiency of a specific decision making unit (DMU). The study included 19 companies (five discount store DMUs, ten SSM DMUs, and four department store DMUs). Because the business elements and sizes of retail store DMUs used in this analysis are different, average per-store input and output variables were used. Data were collected from "The Yearbook of Retail Industry in Korea (2012)." DEA analysis was used to determine differences in efficiency among discount stores, SSMs, and department stores in terms of the business elements of each retail business. It was also used to determine what business elements were excessively invested in by comparing and analyzing efficiency by business elements using SPSS software's ANOVA (Analysis of Variance). Results - The CCR and BCC efficiency analysis found that the efficiency of discount stores is low. We believe that the saturation state of discount stores is a major factor. The ANOVA analysis confirms the VRS hypothesis with a statistically significant difference among the three groups, based on an analysis confidence interval of 95%. CRS and SE were not found to be significantly different among the three groups. As for the post hoc test, which concretely shows differences by group, the Scheffe's multiple comparison analysis test found the average differences between group 1 (discount stores) and group 2 (SSM) to be statistically significant. Conclusions - The DEA efficiency analysis implies that investment in input elements, including store area, parking lot area, and sales management expenses, were excessive in the case of discount stores, while SSMs need to invest more in promotion activities such as gifts, events, and coupons for customer management. Department stores have found that small companies invest excessively in input elements. Department stores need to invest in differentiated shopping mall complexes. This study was limited in acquiring statistical data; various input variables which might have shown more secure customer management and promotional expenses could not be applied. As the study was limited in various aspects of the efficiency analyses because financial analyses of the companies and of causal relationships, including satisfaction and loyalty of visiting customers, were not done, these aspects will be examined in the next study.