• 산업경영시스템학회지
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• 제45권2호
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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.

• 한국산림과학회지
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• 제105권2호
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• pp.247-252
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• 2016

본 연구는 우리나라 연도별 밤 생산량에 대하여 기술효율성을 평가하기 위한 목적으로 수행하였고 기술효율성은 일정량의 비용을 투입하여 얻을 수 있는 최대 생산가능량을 의미한다. 기술효율성 분석을 위하여 산출방향 BCC 모형을 이용하였고 기술효율성 증감의 원인을 분석하기 위하여 단위당 투입비용, 생산량, 조수입, 순수입, 시장가격등의 상관관계를 분석하였다. 연구자료는 2008년부터 2014년까지 7년간의 임산물생산비통계를 활용하였다. 연구결과, 2008년, 2009년, 2010년은 최대 생산가능량과 실제생산량이 ha당 1,568 kg, 1,745 kg, 1,534 kg로 동일하게 나타나 기술효율성이 모두 1.00로 평가되었다. 그러나 2011년부터 2014년까지는 실제생산량이 ha당 1,270 kg 1,047 kg, 1,258 kg, 1,488 kg이고 최대 생산가능량은 1,524 kg, 1,467 kg, 1,635 kg, 1,637 kg으로 분석되어 기술효율성이 0.83, 0.71, 0.75, 0.91로 평가되었다. 기술효율성은 2012년이 0.71로 가장 낮은 것으로 평가되었고 2013년부터 기술효율성 값이 점차 증가하는 것으로 나타났다. 기술효율성 증감의 요인은 생산량과 시장가격의 관계성이 있으며 r = -0.821 (p<0.05)로 부(-)의 상관관계를 가지는 것으로 나타났다. 그리고 단위 면적당 최대 생산가능량 수준은 하한 1,488 kg과 상한 1,745 kg사이에 있으며 평균 1,584 kg인 것으로 나타났다.

• 한국수자원학회논문집
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• 제51권12호
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• pp.1195-1205
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• 2018

본 연구에서는 보령댐 유역($163.6km^2$)을 대상으로 SWAT (Soil and Water Assessment Tool) 모델, GCM (General Circulation Model) 기후변화 시나리오와 다중회귀분석으로 산정한 미래 방류량을 활용하여 극한 기후변화 사상이 반영된 보령댐의 물부족을 평가하였다. 유역의 물수지 분석을 위해 보령댐 유역을 대상으로 기상자료, 보령댐 운영자료를 수집하였으며, SWAT 모형의 신뢰성 있는 유출량 보정을 위해 보령댐의 실측 방류량을 이용하여 댐 운영모의를 고려하였고 유입량 및 방류량 자료를 활용하여 모형의 보정(2007~2010)과 검증(2010~2016)을 실시하였다. 기후변화를 반영하기 위해 APCC의 26개 CMIP5 GCM 자료 중 RCP (Representative Concentration Pathway)4.5와 RCP 8.5 시나리오를 SPI와 극한 가뭄지수로 분석하여 RCP 8.5 BCC-CSM1-1-M을 극한 가뭄 시나리오로 선정하였다. 2005년부터 2016년까지의 일별 관측자료로 다중회귀분석하여 월별 방류량 추정식을 만들었고, 1월부터 12월까지 각 식들의 결정계수 $R^2$는 0.57 이상으로 나타났다. 선정된 극한 가뭄 시나리오 기상자료를 방류량 추정식에 대입하여 미래기간 일별 방류량을 구축하였다. SWAT 수문평가 결과, S3 (2037~2046) 기간 봄철 저수량이 34.0% 감소하는 것으로 분석되었다. Runs 이론을 바탕으로 물부족의 심도를 구한 다음 재현기간에 따른 빈도해석을 하였다. 5~10년 빈도의 심도로 발생하는 물부족이 미래기간에 발생하는 빈도로 보령댐의 물부족을 평가하였다. 물부족 평가 결과, S3 (2037~2046) 기간에서 5~10년 빈도의 심도를 가지는 물부족이 기준기간(2007~2016) 보다 2회 더 발생하였으며 S3 (2037~2046)에 물부족 계획 수립이 필요하다고 판단하였다.

• 대기
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• 제25권2호
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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.

• 한국병원경영학회지
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• 제16권4호
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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.

• 유통과학연구
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• 제11권8호
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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.

• 한국산림과학회지
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• 제102권3호
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• pp.390-397
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• 2013

본 연구는 비모수추정 방법인 자료포락 기법을 이용하여 청양, 공주, 부여 등 충남지역의 밤나무 재배임가를 대상으로 경영효율성을 평가하였다. 분석자료는 2012년 3월부터 10월까지 실시한 '|밤나무 경영에 관한 실태조사'결과 중에서 20개 임가의 투입요소(관리비, 수확비, 재료비, 간접비, 재배면적)와 산출요소(조수입액)를 대상으로 하였다. 그리고 DEA 기법중 CCR 모형과 BCC 모형을 이용하여 기술효율성, 순수기술효율성, 규모효율성을 분석하였고 비효율성 임가의 개선방안도 제시하였다. 추가적으로 DEA 분석결과의 검증을 위하여 기술효율성과 표준진단표 결과를 비교하였다. 연구결과, 기술효율성은 평균값이 0.667로 전체적으로 비효율적으로 분석되었고 그 원인은 순수기술효율성이 평균 0.944, 규모효율성이 평균 0.703으로 나타나 재배기술적인 측면에서는 순수기술효율성이 높았지만 규모의 효율성에서는 비효율성이 존재하였다. 효율성이 1인 임가는 기술효율성 6개, 순수기술효율성 13개, 규모효율성이 6개 임가로 나타났고, 3개 모두 1인 임가는 6개로 나타났다. 표준진단표 점수와 비교한 결과 80점이상 고득점을 기록한 임가는 5개로 나타났고 이 중 기술효율성이 1로 분석된 임가는 3개로 나타났다. 또한 기술효율성과 표준진단표의 최저점수와 최고점수를 기록한 임가도 동일하게 나타났다. 이것은 DEA를 이용한 경영 효율성 평가가 표준진단표와 함께 현장에 적용 가능하다는 것을 나타낸다.

• 유통과학연구
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• 제12권4호
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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.