Data Envelopment Analyses
Mohammad Kachouei; Ali Ebrahimnejad; Hadi Bagherzadeh Valami
Abstract
Purpose: In classical data envelopment analysis models, a production system for measuring performance is considered as a black box and no attention is paid to the internal structure of decision-making units in the process of evaluation performance. However, it is important to consider the internal structure ...
Read More
Purpose: In classical data envelopment analysis models, a production system for measuring performance is considered as a black box and no attention is paid to the internal structure of decision-making units in the process of evaluation performance. However, it is important to consider the internal structure of the units to identify sources of inefficiency to calculate efficiency. On the other hands, the observed values of input and output data in real world problems are sometimes imprecise and vague. Therefore, in this paper, the network data envelopment analysis model is used in order to evaluate the performance of decision-making units with a two-stage structure in a fuzzy environment in which input and output values are displayed in terms of triangular fuzzy numbers.Methodology: To solve the fuzzy two-stage data envelopment analysis model, the fuzzy arithmetic approach is used and a lexicographic optimization method for calculating the fuzzy efficiency of processes and the fuzzy efficiency of the system is proposed.Findings: The main advantage of the proposed approach over the exsiting approaches is that it solves fewer models for finding fuzzy efficiency.Originality/Value: The application of the proposed model is explained by evaluating the performance of 24 insurance companies.
Data Envelopment Analyses
Naser Amani; Hadi Bagherzadeh valami
Abstract
Data Envelopment Analysis (DEA) is a method based on linear programming to measure the efficiency of Decision-Making Units (DMU). In classic models of DEA, the whole system had been usually considered as a Decision-Making Units to evaluate respective efficiency and it is also ignored the separate processes ...
Read More
Data Envelopment Analysis (DEA) is a method based on linear programming to measure the efficiency of Decision-Making Units (DMU). In classic models of DEA, the whole system had been usually considered as a Decision-Making Units to evaluate respective efficiency and it is also ignored the separate processes inside the system. Whereas, the internal relations of various sectors of a Decision-Making Unit can have had diverse structures which cause complexity in evaluating its efficiency, because, the type of structures and the performance of these components would have different effects on efficiency of the system. Network standpoint is one of the appropriate ways for the internal relations of units’ modelling and the relation among sub-units in a DMU may be communicated in series, parallel or mixed way. In this paper, a new convert called Star Structure was introduced as a comprehensive one. The one that every structure existing between a Decision-Making Units’ sub-units can easily be converted to such structure so that can accurately evaluate a Decision-Making Units’ efficiency and also using star structure, we evaluated the performance of regional electronic companies in Iran.