scholarly journals Uncertain Random Data Envelopment Analysis: Efficiency Estimation of Returns to Scale

2021 ◽  
Vol 2021 ◽  
pp. 1-8
Author(s):  
Bao Jiang ◽  
Shuang Feng ◽  
Jinwu Gao ◽  
Jian Li
Keyword(s):  
Data Envelopment Analysis ◽  
Returns To Scale ◽  
Random Variables ◽  
Data Envelopment ◽  
Random Data ◽  
Chance Theory ◽  
Random Models ◽  
Efficiency Estimation ◽  
Scientific Decision ◽  
Decision Making Units

Evaluating efficiency according to the different states of returns to scale (RTS) is crucial to resource allocation and scientific decision for decision-making units (DMUs), but this kind of evaluation will become very difficult when the DMUs are in an uncertain random environment. In this paper, we attempt to explore the uncertain random data envelopment analysis approach so as to solve the problem that the inputs and outputs of DMUs are uncertain random variables. Chance theory is applied to handling the uncertain random variables, and hence, two evaluating models, one for increasing returns to scale (IRS) and the other for decreasing returns to scale (DRS), are proposed, respectively. Along with converting the two uncertain random models into corresponding equivalent forms, we also provide a numerical example to illustrate the evaluation results of these models.

USING THE MINIMUM DISTANCE OF DMUs FROM THE FRONTIER OF THE PPS FOR EVALUATING GROUP PERFORMANCE OF DMUs IN DEA

2012 ◽  
Vol 29 (02) ◽  
pp. 1250010 ◽  
Author(s):  
G. R. JAHANSHAHLOO ◽  
J. VAKILI ◽  
S. M. MIRDEHGHAN
Keyword(s):  
Decision Making ◽  
Data Envelopment Analysis ◽  
Minimum Distance ◽  
Group Performance ◽  
Returns To Scale ◽  
Data Envelopment ◽  
Production Possibility ◽  
Variable Returns To Scale ◽  
Decision Making Units

Evaluating group performance of decision-making units (DMUs) is an application of data envelopment analysis (DEA) and usually provides a measure to compare the frontiers of the production possibility sets (PPSs) corresponding to different groups and the internal inefficiencies of DMUs associated with their group. In this paper, first, a method is presented for obtaining the minimum distance of DMUs from the frontier of the PPS by ‖⋅‖1, which itself can be a very important subject in DEA, and then, for stating an application of these distances, an approach is provided for evaluating group performance of DMUs based on the production ability of the PPSs such that both constant and variable returns to scale assumptions can be used in this method in contrast with some other methods. Therefore, providing the methods for both obtaining the minimum distance of DMUs from the frontier of the PPS and evaluating group performance of DMUs is the most important contribution of this paper.

Technical Efficiency of State Road Transport Undertakings in India - Data Envelopment Analysis

2012 ◽  
Vol 1 (2) ◽  
pp. 31-42 ◽  
Author(s):  
V. Prakash ◽  
J. Rajesh ◽  
M. Thilagam
Keyword(s):  
Decision Making ◽  
Data Envelopment Analysis ◽  
Technical Efficiency ◽  
Relative Efficiency ◽  
Fuel Efficiency ◽  
Returns To Scale ◽  
Road Transport ◽  
Data Envelopment ◽  
Variable Returns To Scale ◽  
Decision Making Units

Data envelopment analysis (DEA) is a method of analyzing the relative efficiency of similar types of organizations known as decision making units (DMU’s). In this paper, DEA model is applied to evaluate the relative technical efficiency of state road transport undertakings (SRTU’s) in India during the period 2011-2012. The authors have considered thirty-four SRTU’s functioning in India. The variables chosen to characteristic production units are the number of fleet held, staff strength and fuel efficiency as inputs and Passengers carried as output. The BCC model is input- oriented allowing for variable returns to scale (VRS), units are ranked and the projection analyses are given.

Data Envelopment Analysis with Output-Bounded Data

2016 ◽  
Vol 33 (06) ◽  
pp. 1650050 ◽  
Author(s):  
Juan Du ◽  
Jiazhen Huo ◽  
Joe Zhu
Keyword(s):  
Data Envelopment Analysis ◽  
Returns To Scale ◽  
Data Envelopment ◽  
Practical Applications ◽  
Efficiency Measures ◽  
Output Side ◽  
Bounded Data ◽  
Constant Returns To Scale ◽  
Percentage Data ◽  
Decision Making Units

In conventional data envelopment analysis (DEA), data are usually assumed to be non-negative with no specific bounds. However, many practical applications require some data, and thus their projections, to fall within certain limits. For example, percentage data such as the satisfactory rate cannot exceed 100% to make sense. This data characteristic is very likely to be violated under the assumption of constant returns to scale (CRS), due to its ray expansion property. In order to tackle this issue under CRS, a series of radial models are developed to constrain DEA projections within imposed bounds from the output side. Then efficient decision making units (DMUs) can be further discriminated simply by eliminating it from the reference set, avoiding the infeasibility problem existing in the VRS super-efficiency measures. The methodology is demonstrated with data consisting of 119 general acute care hospitals located in Pennsylvania, USA.

scholarly journals Energy Requirement Optimization of Greenhouse Vegetable Production Using Data Envelopment Analysis (DEA) Method in Algeria

2020 ◽  
Vol 23 (2) ◽  
pp. 60-66
Author(s):  
Ahmed Nourani ◽  
Abdelaali Bencheikh
Keyword(s):  
Decision Making ◽  
Data Envelopment Analysis ◽  
Returns To Scale ◽  
Scale Model ◽  
Energy Requirements ◽  
Data Envelopment ◽  
Greenhouse Vegetable ◽  
Constant Returns To Scale ◽  
Variable Returns To Scale ◽  
Decision Making Units

AbstractAlgeria has recently experienced an important agricultural development in terms of gardening in plastic greenhouses thanks to the favourable factors (climatic conditions, etc.). In order to optimize the energy requirements, data from 29 farmers were collected, who qualitatively represent the greenhouse vegetable producers from the most productive sub-provinces of Biskra region (south of Algeria). Considering the various parametric and non-parametric methods for energy consumption optimization, data envelopment analysis is the most common non-parametric method applied. Results showed that the mean radial technical efficiency assumptions of the samples under constant returns to scale and variable returns to scale models were 0.88 and 0.98, respectively. The 51.72% of decision-making units were efficient on the basis of the constant returns to scale model; 79.31% decision-making units were observed efficient on the basis of variable returns to scale model. Calculation of optimal energy requirements for vegetable greenhouse indicated that 108.50 GJ·ha−1 can be saved on machinery (1.38 GJ·ha-1); diesel fuel (4.68 GJ·ha−1); infrastructure (9.35 GJ·ha−1); fertilizers (17.08 GJ·ha−1); farmyard manure (12.05 GJ·ha−1); pesticides (3.93 GJ·ha−1); and electricity (60.03 GJ·ha−1).

scholarly journals Assessment of cooperative sugar factories in tamilnadu - a dea approach

2017 ◽  
Vol 7 (1) ◽  
pp. 16-26
Author(s):  
RAJESH J ◽  
PRAKASH V
Keyword(s):  
Decision Making ◽  
Data Envelopment Analysis ◽  
Relative Efficiency ◽  
Tamil Nadu ◽  
Returns To Scale ◽  
Similar Type ◽  
Data Envelopment ◽  
Sugar Production ◽  
Variable Returns To Scale ◽  
Decision Making Units

Data Envelopment Analysis (DEA) is a method of analyzing the relative efficiency of similar type of organizations known as Decision Making Units (DMUs). In this paper, DEA model is applied to evaluate the relative technical efficiency of Cooperative Sugar Factories in Tamil nadu during the period 2012-2013. We have considered 15 sugar factories functioning in the state. The variables chosen here to characterize production units are,Sugar cane crushed, Share capital as inputs and Sugar production as output. The BCC model is Output- oriented allowing for variable returns to scale (VRS), units are ranked based on peer count summary.

scholarly journals Sampling size and efficiency bias in data envelopment analysis

1998 ◽  
Vol 2 (1) ◽  
pp. 51-64 ◽  
Author(s):  
Mohammad R. Alirezaee ◽  
Murray Howland ◽  
Cornelis van de Panne
Keyword(s):  
Decision Making ◽  
Data Envelopment Analysis ◽  
Large Scale ◽  
Returns To Scale ◽  
Data Envelopment ◽  
Bank Branch ◽  
Decision Making Units ◽  
Inputs And Outputs

In Data Envelopment Analysis, when the number of decision making units is small, the number of units of the dominant or effcient set is relatively large and the average effciency is generally high. The high average effciency is the result of assuming that the units in the effcient set are 100% effcient. If this assumption is not valid, this results in an overestimation of the efficiencies, which will be larger for a smaller number of units. Samples of various sizes are used to find the related bias in the effciency estimation. The samples are drawn from a large scale application of DEA to bank branch efficiency. The effects of different assumptions as to returns to scale and the number of inputs and outputs are investigated.

Relative Efficiency of Decision Making Units Producing Both Desirable and Undesirable Outputs: A Case of Textile Processing Units in Pakistan.

2011 ◽  
Vol 50 (4II) ◽  
pp. 685-698
Author(s):  
Samina Khalil
Keyword(s):  
Decision Making ◽  
Data Envelopment Analysis ◽  
Relative Efficiency ◽  
Value Added ◽  
Data Envelopment ◽  
Undesirable Outputs ◽  
Textile Processing ◽  
Decision Making Unit ◽  
Desirable And Undesirable Outputs ◽  
Decision Making Units

This paper aims at measuring the relative efficiency of the most polluting industry in terms of water pollution in Pakistan. The textile processing is country‘s leading sub sector in textile manufacturing with regard to value added production, export, employment, and foreign exchange earnings. The data envelopment analysis technique is employed to estimate the relative efficiency of decision making units that uses several inputs to produce desirable and undesirable outputs. The efficiency scores of all manufacturing units exhibit the environmental consciousness of few producers is which may be due to state regulations to control pollution but overall the situation is far from satisfactory. Effective measures and instruments are still needed to check the rising pollution levels in water resources discharged by textile processing industry of the country. JEL classification: L67, Q53 Keywords: Data Envelopment Analysis (DEA), Decision Making Unit (DMU), Relative Efficiency, Undesirable Output

scholarly journals Performance Evaluation of Fishery Enterprises Using Data Envelopment Analysis—A Malmquist Model

Mathematics ◽  
2021 ◽  
Vol 9 (5) ◽  
pp. 469
Author(s):  
Chia-Nan Wang ◽  
Thi-Ly Nguyen ◽  
Thanh-Tuan Dang ◽  
Thi-Hong Bui
Keyword(s):  
Performance Evaluation ◽  
Data Envelopment Analysis ◽  
Technological Progress ◽  
Data Envelopment ◽  
Domestic Economy ◽  
Factor Productivity ◽  
Sales Revenue ◽  
Business Efficiency ◽  
Using Data ◽  
Decision Making Units

In Vietnam, fishing is a crucial source of nutrition and employment, which not only affects the development of the domestic economy but is also closely related to exports, heavily influencing the economy and foreign exchange. However, the Vietnamese fishery sector has been facing many challenges in innovating production technology, improving product quality, and expanding markets. Hence, the fishery enterprises need to find solutions to increase labor productivity and enhance competitiveness while minimizing difficulties. This study implemented a performance evaluation from 2015 to 2018 of 17 fishery businesses, in decision making units (DMUs), in Vietnam by applying data envelopment analysis, namely the Malmquist model. The objective of the paper is to provide a general overview of the fishery sector in Vietnam through technical efficiency, technological progress, and the total factor productivity in the four-year period. The variables used in the model include total assets, equity, total liabilities, cost of sales, revenue, and profit. The results of the paper show that Investment Commerce Fisheries Corporation (DMU10) and Hoang Long Group (DMU8) exhibited the best performances. This paper offers a valuable reference to improve the business efficiency of Vietnamese fishery enterprises and could be a useful reference for related industries.

A model to evaluate the effects of the returns to scale on the inverse data envelopment analysis

2021 ◽  
Author(s):  
M. Ebrahimzade Adimi ◽  
M. Rostamy-Malkhalifeh ◽  
F. Hosseinzadeh Lotfi ◽  
R Mehrjoo
Keyword(s):  
Data Envelopment Analysis ◽  
Returns To Scale ◽  
Data Envelopment
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