Inverse DEA Model with Considering Returns to Scale and Elasticity

2013 ◽  
Author(s):  
Xiaoya Li ◽  
Jinchuan Cui
Keyword(s):  
Returns To Scale ◽  
Dea Model

scholarly journals MEASURING BANK EFFICIENCY: DEA APPLICATION

2014 ◽  
Vol 20 (4) ◽  
pp. 739-757 ◽  
Author(s):  
Jelena Titko ◽  
Jelena Stankevičienė ◽  
Nataļja Lāce
Keyword(s):  
Banking Sector ◽  
Linear Regression Analysis ◽  
Analytical Data ◽  
Returns To Scale ◽  
Mean Values ◽  
Dea Model ◽  
Two Samples ◽  
Variables Selection ◽  
Measuring Efficiency ◽  
Selection For

The paper aims to improve the methodology of measuring efficiency of Latvian banks. Efficiency scores were calculated with application of non-parametric frontier technique Data Envelopment Analysis (DEA). Input-oriented DEA model under Variable Returns to Scale (VRS) assumption was used. Potential model variables were selected based on the intermediation and profitability approach. Fourteen alternative models with different inputs-outputs combinations were developed for the research purposes. To substantiate the variables selection for DEA model the received data was processed, using such methods, as correlation analysis, linear regression analysis, analysis of mean values, and two-samples Kolmogorov-Smirnov test. The research results assisted the authors in providing general recommendations about the variables selection for DEA application in the Latvian banking sector. The present research contributes to the existing analytical data on bank performance in Latvia. The empirical findings provide a background for further studies, in particular, the efficiency of Latvian banks could be analysed in the extended time period.

Measurement of returns to scale using a non-radial DEA model

2012 ◽  
Vol 85 (1) ◽  
pp. 144-148 ◽  
Author(s):  
V. E. Krivonozhko ◽  
F. R. Førsund ◽  
A. V. Rozhnov ◽  
A. V. Lychev
Keyword(s):  
Returns To Scale ◽  
Dea Model

Developing a new super-efficiency DEA model in the presence of both zero data and stochastic data: a case study in the Iranian airline industry

2020 ◽  
Vol ahead-of-print (ahead-of-print) ◽  
Author(s):  
Mohammad Tavassoli ◽  
Amirali Fathi ◽  
Reza Farzipoor Saen
Keyword(s):  
Airline Industry ◽  
Returns To Scale ◽  
Content Type ◽  
Super Efficiency ◽  
Dea Model ◽  
Proposed Model ◽  
Stochastic Dea ◽  
Stochastic Data ◽  
Constant Returns To Scale

PurposeThe purpose of this study is to propose a novel super-efficiency DEA model to appraise the relative efficiency of DMUs with zero data and stochastic data. Our model can work with both variable returns to scale (VRS) and constant returns to scale (CRS).Design/methodology/approachThis study proposes a new stochastic super-efficiency DEA (SSDEA) model to assess the performance of airlines with stochastic and zero inputs and outputs.FindingsThis paper proposes a new analysis and contribution to the knowledge of efficiency assessment with stochastic super-efficiency DEA model by (1) using input saving and output surplus index for efficient DMUs to get the optimal solution; (2) obtaining efficiency scores from the proposed model that are equivalent to original stochastic super-efficiency model when feasible solutions exist. A case study is given to illustrate the applicability of our proposed model. Also, poor performance reasons are identified to improve the performance of inefficient airlines.Originality/valueFor the first time, a new SSDEA model for ranking DMUs is proposed. The introduced model produces a feasible solution when dealing with zero input or output. This paper applies the input saving and output surplus concept to rectify the infeasibility problem in the stochastic DEA model.

Estimating the efficiency of Greek banking system during the last decade of world economic crisis

2018 ◽  
Vol 25 (6) ◽  
pp. 1762-1794 ◽  
Author(s):  
Zois Sompolos ◽  
Maria Mavri
Keyword(s):  
Economic Crisis ◽  
Banking Sector ◽  
Returns To Scale ◽  
Banking System ◽  
Operational Efficiency ◽  
Operating Efficiency ◽  
Content Type ◽  
Dea Model ◽  
The Impact ◽  
Constant Returns To Scale

Purpose The purpose of this paper is to examine the efficiency of the four largest Greek banking organizations for the period 2004–2014, including both a period of strong economic growth and a period of economic crisis and recession, which is still plaguing the Greek economy and more specifically the Greek banking sector. Design/methodology/approach The study incorporates the application of financial ratio analysis and the data envelopment analysis (DEA) in order to calculate the technical efficiency of Greek financial institutions. More specifically, a two-stage output-oriented DEA model is developed in order to estimate the global efficiency of banks. The banking function is considered as consisting of two stages in series, a service/operational efficiency and a profitability efficiency. In both output-oriented models, methods of constant returns to scale and variable returns to scale were applied. Findings The results show that in terms of operational efficiency, banks started from a low rate of return in 2004, which improved until 2008, which marked the peak of operational efficiency. By 2010, the operating efficiency varied with downward trend until 2012–2013. In terms of profitability efficiency, the image is clearer, since the impact the financial crisis had on bank’s profit efficiency led, by 2012, to a plunge in the average efficiency by 30–40 percent. Originality/value A multi-stage DEA process, input oriented, was used in order to estimate changes in the performance and efficiency of banking system. The period 2004–2014 has not been examined until recently and all previous studies used the output-oriented DEA model.

Research of the Construction Industry Efficiency in China — Based on DEA Panel Data Approach

2013 ◽  
Vol 689 ◽  
pp. 105-109 ◽  
Author(s):  
Wei Zhong Zhou ◽  
Chun Lu Liu
Keyword(s):  
Data Envelopment Analysis ◽  
Panel Data ◽  
Construction Industry ◽  
Returns To Scale ◽  
Increasing Returns ◽  
Data Envelopment ◽  
Increasing Returns To Scale ◽  
Dea Model ◽  
Net Profit ◽  
The Mean

The efficiency of the construction industry is analyzed based on provinces panel data in China in this paper. The Mean Number of Employee and the Mean Completed Investment are used as inputs. The Mean Actual Sales of Commercial Houses and the Mean Net Profit are used as outputs. Data Envelopment Analysis (DEA) model is used to measure the efficiency of the construction industry. Shanghai and Zhejiang are found technically efficient. Shandong is scale efficient but technology efficiency is lower. There are two provinces are decreasing returns to scale and other provinces are increasing returns to scale. On the whole, the technology efficiency of the construction industry of China is lower. Based on the conclusions, the paper proposes some suggestions to improve the efficiency of the construction industry in China.

scholarly journals Technical Efficiency Of Social Foundations In A Multidimensional Context

2010 ◽  
Vol 9 (11) ◽  
Author(s):  
Imelda S. Dorado ◽  
Emilyn Cabanda
Keyword(s):  
Data Envelopment Analysis ◽  
Technical Efficiency ◽  
Returns To Scale ◽  
The Philippines ◽  
Data Envelopment ◽  
Non Profit ◽  
Dea Model ◽  
Social Foundations ◽  
Efficiency Assessment ◽  
Constant Returns To Scale

The paper is the first attempt at examining the technical efficiency and benchmarking the performance of 15 social foundations in the Philippines for the period 2000-2005 using the data envelopment analysis (DEA) model. The 65.55% of social foundations are operating at increased returns to scale, 4.45% at decreased returns to scale and 30% at constant returns to scale. Forty percent of firms are efficiently utilizing their expenses and the majority shows resource excesses (capital and labor). All firms show output deterioration for donations and total awards to beneficiaries. With the aid of the DEA tool, measurement of the efficiency of social foundations has been verified and proven as manageable and quantifiable from a multidimensional assessment. Results reveal the importance of technical efficiency assessment for the non-profit sector.

An inverse semi-oriented radial data envelopment analysis measure for dealing with negative data

2020 ◽  
Vol 31 (4) ◽  
pp. 505-516
Author(s):  
Mojtaba Ghiyasi ◽  
Ning Zhu
Keyword(s):  
Data Envelopment Analysis ◽  
Global Financial Crisis ◽  
Returns To Scale ◽  
Data Envelopment ◽  
Negative Data ◽  
Dea Model ◽  
Proposed Model ◽  
Scale Properties ◽  
The Global Financial Crisis ◽  
Special Case

Abstract The conventional inverse data envelopment analysis (DEA) model is only applicable to positive data, while negative data are commonly present in most real-world applications. This paper proposes a novel inverse DEA model that can handle negative data. The conventional inverse DEA model is a special case of our model as our model is more general in terms of returns-to-scale properties. The proposed model is used to evaluate the efficiency of the Chinese commercial banks after the global financial crisis, where negative outputs existed. We show that our model is feasible in the presence of negative data and generates empirical findings that are consistent with reality.

Evaluation of Ground Thermal Infrared Camouflage Using Pure Technical and Pure Scale Dynamic DEA Model

2014 ◽  
Vol 989-994 ◽  
pp. 2323-2327 ◽  
Author(s):  
Ling Li ◽  
Xu Liang Lü ◽  
Bing Zhen Li ◽  
Xiao Peng Li ◽  
Huai Xiao Wang
Keyword(s):  
Returns To Scale ◽  
Thermal Infrared ◽  
Time Parameter ◽  
Scale Efficiency ◽  
Dea Model ◽  
New Models ◽  
Set Up ◽  
The Relationship ◽  
Variable Returns To Scale ◽  
Infrared Camouflage

For coping with modern thermal infrared reconnaissance, thermal infrared camouflage is becoming the hotspot of camouflage pattern research. Concerning the traditional methods on evaluating ground thermal infrared camouflage can’t solve the “dynamic” problem and the pure technical as well as pure scale efficiency. This article established new models to figure it out. The new measure introduced time parameter to construct dynamic model, then it set up pure technical dynamic DEA model which supposed it had variable returns to scale. Through the relationship among technical, pure technical and pure scale DEA model, we can get the pure scale dynamic DEA model. Finally, an example was calculated which shows the application of the new models.

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