• The Journal of Asian Finance, Economics and Business
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• 제8권1호
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• pp.751-758
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• 2021

This research is conducted to measure the efficiency level of Islamic banking in Indonesia and also to analyze the factors that can affect its efficiency level. This research used a purposive sampling technique to determine the sample size that will be used, with criteria that the bank has been operating since 2010 and consistently published its financial reports during the research period from 2011 until 2019; therefore, the total sample obtained was 11 samples. Analysis for efficiency level is done by using linear programming Stochastic Frontier Analysis (SFA), with test tool in the form of Frontier 4.1 and Eviews9 to find out what factors that affect efficiency. Efficiency test is done by involving input and output, while influence test used bank-specific variables comprising bank size, bank financial ratio, and macro-economy variable. Research result shows that there are only two banks that are almost close to being fully efficient firms, but the result still does not indicate that Islamic bank works efficiently. Results of the influence test show that factors affecting Islamic banking efficiency in Indonesia are bank size, Capital Adequacy Ratio (CAR), Non-Performing Finance (NPF), and Financing to Deposit Ratio (FDR), while other factors are not influential over the study period.

• 무역학회지
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• 제47권4호
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• pp.271-292
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• 2022

In Korea, the road transport industry is pointed out as a major cause of air pollutants, so management control is needed. Existing studies used only positive input and output variables to measure regional efficiency. However, it is necessary to consider the environmental pollution problem in efficiency analysis. In this study, an undesirable SBM analysis using CO₂ was conducted to measure efficiency of domestic regions. In addition, SDM was conducted to examine the ripple effect between domestic regions. As a result of the analysis, the efficiency of the capital area such as Seoul, Gyeonggi, and Incheon was high in the road transport industry. However, the efficiency of the road transportation industry in Daegu and Gangwon was low. In the SDM analysis, it was found that the regional equipment capabilities had a great influence on efficiency. In order to improve efficiency, it is necessary to increase and improve the equipment capacity of the road transport industry.

• International Journal of Advanced Culture Technology
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• 제6권4호
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• pp.292-302
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• 2018

This study proposes a Bayesian stochastic frontier model that is well-suited to productivity/efficiency analysis particularly using panel data. A unique feature of our proposal is that both production frontier and efficiency are estimable for each individual firm and their linkage to various firm characteristics enriches our understanding of the source of productivity/efficiency. Empirical application of the proposed analysis to Human Capital Corporate Panel data enables identification and quantification of the effects of Human Resource factors on firm efficiency in tandem with those of firm types on production frontier. A comprehensive description of the Markov Chain Monte Carlo estimation procedure is forwarded to facilitate the use of our proposed stochastic frontier analysis.

• 보건행정학회지
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• 제10권4호
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• pp.75-98
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• 2000

This study applied Data Envelopment Analysis(DEA) and Ratio Analysis and Regression Analysis to a set of Korean Public Corporation Medical Centers to evaluate their relative human resource efficiencies. The output measure used in this study was based on health insurance system which was used in both in-patient departments and out-patient departments. Inputs included working time of the doctors, nurses, technicians, and managerial department staff. Based on the data provided on the inputs and outputs, the analysis showed 23 of the 34 hospitals to be relatively inefficient. Each hospital with an efficiency rating of less than 1 was considered relatively inefficient. In addition, managerial strategies based on dual variables were constructed to indicate the manner In which inefficient hospitals may be made efficient. A subsequent analysis of t-test revealed that the bed occupancy rate, medical revenue per 100beds, value added revenue per staff, medical revenue per staff were statistically significant. The results of this study suggest the DEA is a promising tool for evaluating relative human resource efficiency in hospitals which have multiple inputs and outputs and where the efficient production function is not specifiable with any precision. But it is considered that efficiency evaluations may be most effective]y accomplished by Incorporating a combination of methodologies such as ratio analysis and regression analysis.

• 한국유기농업학회지
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• 제21권4호
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• pp.487-500
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• 2013

The purpose of this study is to estimate efficiency of environmental-friendly agricultural product by using Data Envelopment Analysis. A proposed method employs a bootstrapping approach to generating efficiency estimates through Monte Carlo simulation resampling process. The technical efficiency, pure technical efficiency, and scale efficiency measure of strawberry by pesticide-free certification is 0.967, 0.995, 0.968 respectively. However those of bias-corrected estimates are 0.918, 0.983, 0.934. We know that the DEA estimator is an upward biased estimator. In technical efficiency, average lower and upper confidence bounds of 0.807 and 0.960. According to these results, the DEA bootstrapping model used here provides bias-corrected and confidence intervals for the point estimates, it is more preferable.

• 경영과학
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• 제32권3호
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• pp.37-54
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• 2015

This paper suggests energy efficiency which can be the foundation on corporate profit and effective energy management following by change of global climate and of energy-related regulations. Using comparable financial information and information related to energy use, an DEA (Data Envelopment Analysis) model has been used to identify energy efficiency with DMU (Decision Making Unit)s which are companies subjected to reduce greenhouse gas emission in 2009. Through this research, different from existing researches, environmental variables which can influence on energy efficiency are identified. The results show as follows. First, most of companies follow IRS, which means scale of economy exists among units so that they have more opportunity to increase efficiency by increasing scale of inputs. Second, this research identified that depending on the difference of environmental characters such as the emission structure and the size of companies, energy efficiency of the companies turns out differently.

• 한국도서관정보학회지
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• 제41권4호
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• pp.35-50
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• 2010

본 연구는 대전 지역에 소재하고 있는 15개 공공도서관을 대상으로 DEA 모형을 사용하여 2008년도 공공도서관의 상대적 효율성을 분석하고 이어서 최근 3년간의 추세변화를 분석하였다. 투입요소로는 직원수, 면적, 장서수가 사용되었으며 산출요소로는 이용책수와 이용자수가 사용되었다. 연구결과, 기술효율성 값의 추세변화를 분석해 보면 3년간 지속적으로 효율성이 개선되었으며, 기술효율성의 개선은 순수 기술효율성과 규모 효율성 둘 다의 개선에 있었다.

• 수산경영론집
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• 제52권1호
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• pp.23-46
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• 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.

• 아태비즈니스연구
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• 제6권2호
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• pp.1-17
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• 2015

This study compares the most widely used parametric and non-parametric techniques to measure cost and profit efficiency of banks, namely the Stochastic Frontier Analysis (SFA) and Data Envelopment Analysis (DEA). We formulate the specification form of both stochastic cost and profit frontier models and constant return to scale Cost DEA and Profit DEA models and provide an empirical assessment of the cost and profit frontiers based on a panel dataset of National Commercial Banks (NCBs) and Private Banks (PBs) in Bangladesh over the 2001-2010 period. The cost inefficiency and profit efficiency are slightly higher for PBs than NCBs in case of both SFA and DEA. The coefficients of advance and off-balance sheet items are significant that positively influence the banks in stochastic cost frontier model while the advance, other earning assets, price of borrowed fund are significant and negative effects on the banks in stochastic profit frontier model. The average cost inefficiency and average profit efficiency are recorded with 16.3% and 91% respectively. The highest and lowest cost inefficiency are observed for Janata Bank and United Commercial Bank Limited whilst the highest and lowest profit efficiency are recorded for Eastern Bank Limited and Janata Bank respectively. The average technical and allocative efficiency are 68.8% and 35.9%, respectively in case of CRS cost-DEA model whereas they are 70.3% and 31.8% in case of CRS profit-DEA model. The average cost inefficiency is recorded 6.3% by SFA whereas it is 24.5% by DEA. The average profit efficiency is found 91% by SFA while it is 22.1% by DEA, and SFA method shows better bank efficiency than DEA.

• 경영과학
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• 제30권2호
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• pp.97-106
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• 2013

Of the new and renewable energies currently being pursued domestically, wind energy, together with solar photovoltaic energy, is a new core growth driver industry of Korea. As of May 2012, 33 wind farms at a capacity of 347.8MW are in operation domestically. The purpose of this study was to compare and analyze how efficiently each operational wind farm is utilizing its power generation capacity and the weather resource of wind. For this purpose, the study proceeded in 3 phases. In phase 1, ANOVA analysis was performed for each wind farm, thereby categorizing farms according to capacity, region, generator manufacturer, and quantity of weather resources available and comparing and analyzing the differences among their operating efficiency. In phase 2, for comparative analysis of the operating efficiency of each farm, Data Envelopment Analysis (DEA) was used to calculate the efficiency index of individual farms. In the final phase, phase 3, regression analysis was used to analyze the effects of weather resources and the operating efficiency of the wind farm on the power generation per unit equipment. Results shows that for wind power generation, only a few farms had relatively high levels of operating efficiency, with most having low efficiency. Regression analysis showed that for wind farms, a 1 hour increase in wind speeds of at least 3m/s resulted in an average increase of 0.0000045MWh in power generation per 1MW generator equipment capacity, and a unit increase in the efficiency scale was found to result in approximately 0.20MWh power generation improvement per unit equipment.