scholarly journals Presenting a predictive benchmark model of after-sales service agencies for vehicles based on the Data Envelopment Analysis (DEA) Approach

2021 ◽  
Vol 1 (1) ◽  
pp. 1
Author(s):  
Esmael Najafi ◽  
Farhad Hosseinzadeh Lotfi ◽  
Sajjad Kheyri ◽  
Bijan Rahmani
Keyword(s):  
Data Envelopment Analysis ◽  
Data Envelopment ◽  
Benchmark Model ◽  
Dea Approach ◽  
Service Agencies

Decision to bid or not to bid: a data envelopment analysis approach

2010 ◽  
Vol 37 (1) ◽  
pp. 37-44 ◽  
Author(s):  
Mohammad S. El-Mashaleh
Keyword(s):  
Linear Programming ◽  
Data Envelopment Analysis ◽  
Analysis Approach ◽  
Programming Approach ◽  
Data Envelopment ◽  
Parametric Linear Programming ◽  
Linear Programming Approach ◽  
Selection Decisions ◽  
Dea Approach ◽  
Benchmarking Performance

One of the most crucial decisions that is regularly exercised by construction contractors is to determine whether to bid or not to bid on a certain project. The purpose of this paper is to propose a data envelopment analysis (DEA) approach for the bid–no-bid decision. DEA is a robust non-parametric linear programming approach that is used for benchmarking performance and for making selection decisions. Based on a contractor's database of previous considerations of bidding opportunities, DEA creates a “favorable frontier” that consists of favorable bidding opportunities. New bidding opportunities are evaluated in reference to this “favorable frontier” and the bid–no-bid decision is consequently made. The proposed approach incorporates subjective management expertise and deals systematically with bidding situations to guide contractors in their bid–no-bid determination. A major strength of the proposed DEA approach is that it is deployable by organizations facing the bid–no-bid problem regardless of size, country of operation, number and type of factors considered in bidding, or even industry.

Optimization of energy consumption for soybean production using Data Envelopment Analysis (DEA) approach

2011 ◽  
Vol 88 (11) ◽  
pp. 3765-3772 ◽  
Author(s):  
Seyed Hashem Mousavi-Avval ◽  
Shahin Rafiee ◽  
Ali Jafari ◽  
Ali Mohammadi
Keyword(s):  
Energy Consumption ◽  
Data Envelopment Analysis ◽  
Data Envelopment ◽  
Soybean Production ◽  
Dea Approach ◽  
Using Data

DEA by sequential exclusion of alternatives in heterogeneous samples

2016 ◽  
Vol 15 (01) ◽  
pp. 5-22 ◽  
Author(s):  
Fuad Aleskerov ◽  
Vsevolod Petrushchenko
Keyword(s):  
Data Envelopment Analysis ◽  
New Method ◽  
Data Envelopment ◽  
Efficiency Evaluation ◽  
Dea Model ◽  
Economic Applications ◽  
Heterogeneous Samples ◽  
Efficiency Estimation ◽  
Dea Approach ◽  
Russian Universities

Data Envelopment Analysis (DEA) is a well-known nonparametric technique of efficiency evaluation which is actively used in many economic applications. However, DEA is not very well applicable when a sample consists of firms operating under drastically different conditions. We offer a new method of efficiency estimation in heterogeneous samples based on a sequential exclusion of alternatives and standard DEA approach. We show a connection between efficiency scores obtained via standard DEA model and the ones obtained via our algorithm. We also illustrate our model by evaluating 28 Russian universities and compare the results obtained by two techniques.

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