Determining relative efficiency of slightly non-homogeneous decision making units by data envelopment analysis: a case study in IROST

2005 ◽  
Vol 165 (2) ◽  
pp. 313-328 ◽  
Author(s):  
Reza Farzipoor Saen ◽  
Azizollah Memariani ◽  
Farhad Hosseinzadeh Lotfi
Keyword(s):  
Decision Making ◽  
Data Envelopment Analysis ◽  
Relative Efficiency ◽  
Data Envelopment ◽  
Decision Making Units

Evaluation of Supplier Performance and Efficiency

2017 ◽  
pp. 184-216
Author(s):  
Chandra Sekhar Patro
Keyword(s):  
Decision Making ◽  
Data Envelopment Analysis ◽  
Relative Efficiency ◽  
Efficient Frontier ◽  
Business Environment ◽  
Vital Role ◽  
Data Envelopment ◽  
Supplier Performance ◽  
Decision Making Units

In the present competitive business environment, it is essential for the management of any organisation to take wise decisions regarding supplier evaluation. It plays a vital role in establishing an effective supply chain for any organisation. Most of the experts agreed that there is no one best way to evaluate the suppliers and different organizations use different approaches for evaluating supplier efficiency. The overall objective of any approach is to reduce purchase risk and maximize overall value to the purchaser. In this paper Data Envelopment Analysis (DEA) technique is developed to evaluate the supplier efficiency for an organisation. DEA is a multifactor productivity technique to measure the relative efficiency of the decision making units. The super efficiency method of DEA provides a way, which indicates the extent to which the efficient suppliers exceed the efficient frontier formed by other efficient suppliers. A case study is undertaken to evaluate the supplier performance and efficiency using DEA approach.

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

A Robust Data Envelopment Analysis Method with Bounded Data for Ranking Operations Strategies

2015 ◽  
Vol 6 (3) ◽  
pp. 49-64 ◽  
Author(s):  
Mohamad Amin Kaviani ◽  
Mehdi Abbasi
Keyword(s):  
Decision Making ◽  
Data Envelopment Analysis ◽  
Cement Industry ◽  
Data Envelopment ◽  
Analysis Method ◽  
Interval Numbers ◽  
Complete Ranking ◽  
Bounded Data ◽  
Decision Making Units

This paper introduces a new robust data envelopment analysis (RDEA) approach for analyzing and ranking the organizations' operations strategies. In the proposed RDEA method, pessimistic and optimistic efficiencies of decision making units (DMUs) obtained from the robust counterpart of the envelopment form and the optimistic counterpart of the multiplier form of DEA are introduced. The inputs and outputs data are assumed to be bounded data (interval numbers) in the proposed models. A case study in the cement industry is presented to demonstrate the applicability of the proposed RDEA approach. The results obtained from the authors' proposed RDEA approach is more robust and their method provides a more complete ranking of the DMUs compared to conventional Likert-based DEA model.

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.

scholarly journals Identification and Prioritization of Hazardous Road Locations by Segmentation and Data Envelopment Analysis Approach

1970 ◽  
Vol 25 (2) ◽  
pp. 127-136 ◽  
Author(s):  
Aliasghar Sadeghi ◽  
Esmaeel Ayati ◽  
Mohammadali Pirayesh Neghab
Keyword(s):  
Decision Making ◽  
Data Envelopment Analysis ◽  
Regression Models ◽  
Data Envelopment ◽  
The Road ◽  
Black Spots ◽  
Main Factors ◽  
Dea Method ◽  
Decision Making Units

The aim of the present study is the representation of a method to identify and prioritize accident-prone sections (APSs) based upon efficiency concept to emphasize accidents with regard to traffic, geometric and environmental circumstances of road which can consider the interaction of accidents as well as their casual factors. This study incorporates the segmentation procedure into data envelopment analysis (DEA) technique which has no requirement of distribution function and special assumptions, unlike the regression models. A case study has been done on 144.4km length of Iran roads to describe the approach. Eleven accident-prone sections were identified among 154 sections obtained from the segmentation process and their prioritization was made based on the inefficiency values coming from DEA method. The comparisons demonstrated that the frequency and severity of accidents would not be only considered as the main factors for black-spots identification but proper rating can be possible by obtaining inefficiency values from this method for the road sections. This approach could applicably offer decision-making units for identifying accident-prone sections and their prioritizations. Also, it can be used to prioritize intersections, roundabouts or the total roads of the safety organization domain.

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 A Survey and Analysis of Scholarly Literature in DEA Published by Croatian Researchers: 1978 – 2018

2019 ◽  
Vol 22 (1) ◽  
pp. 93-106
Author(s):  
Luka Neralić ◽  
Margareta Gardijan Kedžo
Keyword(s):  
Decision Making ◽  
Data Envelopment Analysis ◽  
Performance Measurement ◽  
Relative Efficiency ◽  
Data Envelopment ◽  
Scholarly Literature ◽  
Empirical Results ◽  
Research Areas ◽  
Shed Light ◽  
Decision Making Units

Abstract After its introduction in 1978, Data Envelopment Analysis (DEA) has instantly been recognized as a useful methodology for measuring the relative efficiency of different entities, called Decision Making Units (DMUs), given multiple criteria. Up until nowadays, the popularity of DEA has been growing and a significant number of bibliographical items was published, reporting on both theoretical and empirical results. However, the main applicative area of DEA remained the performance measurement in economics and business. On the 40th anniversary of DEA, the aim of this paper is to present the DEA bibliography of Croatian scientists (up until June 2018). We consider six main categories of DEA-related publications, followed with key statistics and an overview of keywords and research areas. The whole list of DEA-related publications used in this analysis is published online. We believe this research will shed light on the state of DEA in Croatian science and motivate future researches.

scholarly journals Measuring the Productivity of Energy Consumption of Major Industries in China: A DEA-Based Method

2014 ◽  
Vol 2014 ◽  
pp. 1-12 ◽  
Author(s):  
Xishuang Han ◽  
Xiaolong Xue ◽  
Jiaoju Ge ◽  
Hengqin Wu ◽  
Chang Su
Keyword(s):  
Decision Making ◽  
Energy Consumption ◽  
Data Envelopment Analysis ◽  
Malmquist Productivity Index ◽  
Productivity Index ◽  
Productivity Change ◽  
Data Envelopment ◽  
Policy Makers ◽  
Time Periods ◽  
Decision Making Units

Data envelopment analysis can be applied to measure the productivity of multiple input and output decision-making units. In addition, the data envelopment analysis-based Malmquist productivity index can be used as a tool for measuring the productivity change during different time periods. In this paper, we use an input-oriented model to measure the energy consumption productivity change from 1999 to 2008 of fourteen industry sectors in China as decision-making units. The results show that there are only four sectors that experienced effective energy consumption throughout the whole reference period. It also shows that these sectors always lie on the efficiency frontier of energy consumption as benchmarks. The other ten sectors experienced inefficiency in some two-year time periods and the productivity changes were not steady. The data envelopment analysis-based Malmquist productivity index provides a good way to measure the energy consumption and can give China's policy makers the information to promote their strategy of sustainable development.

Sign in / Sign up

Export Citation Format

Share Document