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Open Access Article
1 - Providing a model for evaluate the efficiency of supply chain based on information flow using fuzzy network data envelopment analysis
tahmineh Noohi tehrani maryam shoar saber saati mohtadiRapid development toward globalization, a competitive market, significant technological advances, and high customer expectations have encouraged companies to reduce costs and increase their competitive advantage. One of the things that can help companies achieve a compe MoreRapid development toward globalization, a competitive market, significant technological advances, and high customer expectations have encouraged companies to reduce costs and increase their competitive advantage. One of the things that can help companies achieve a competitive advantage is supply chain management. Information acts as an intermediary between all activities and operations within the supply chain. The innovation of this research can be shown in two aspects of application and modeling. In terms of application, with a review of the literature and investigating the application of multi-stage and network data development analysis in the supply chain, it was revealed that so far, the efficiency of financial and physical flows in the literature has been evaluated more and the indicators are mostly related to two financial and physical flows in the supply chain, therefore there is more research opportunity to evaluate the efficiency of information flow within the supply chain. Measuring the efficiency of information flow should be an integral part of supply chain management. Therefore, this research aimed to present a model to evaluate the efficiency of information flow in the supply chain. In terms of mathematical modeling, research innovation is considering the model of the network and reversible relationship in the supply chain. With a review of the literature, the indicators are investigated to evaluate the efficiency of information flow in the supply chain, and the validity of indicators is examined by the fuzzy Delphi method. Then the decision making unit and inputs and outputs of the model are introduced. In this research, the fuzzy network data envelopment analysis is used. In order to implement the models, we used the GAMS software. Manuscript profile -
Open Access Article
2 - Determining the Russell Technical Efficiency of measure in the Presence of Flexible Factors based on slack variables
Majid Sedighi Hassan Kiyadeh Saber Saati Mohtadi Sohrab KordrostamiThe role of some factors is not completely clear as an input or an output in many real applications of Data Envelopment Analysis (DEA). In other words, some Decision Making Units (DMUs) can use a factor as an input while it may play an output role in other DMUs. This ty MoreThe role of some factors is not completely clear as an input or an output in many real applications of Data Envelopment Analysis (DEA). In other words, some Decision Making Units (DMUs) can use a factor as an input while it may play an output role in other DMUs. This type of factors is called flexible factors. In this paper, a model is proposed to develop models of flexible factors type in the DEA model. This model, at the same time, minimizes the inputs contraction factor and maximizes the outputs expansion factor in the Russell efficiency measure, in presence of flexible factors. The proposed measure in objective function is linear. In the other words, the relation between the factors is suggested as an additive function. In fact, the proposed model, in contrast the Russell measure is not nonlinear. By an illustrated example, the proposed model is compared with the existing models. Manuscript profile -
Open Access Article
3 - Bootstrap Method and Common Set of Weights in Data Envelopment Analysis to Differentiate Efficient Units
Akbar Amiri saber saati mahtadi alireza amirteimooriData Envelopment Analysis (DEA) is a broad range of mathematical models for measuring the relative efficiency of a set of homogeneous decision units with similar inputs and outputs. Multiple models of data envelopment analysis render a set of weights for input and outpu MoreData Envelopment Analysis (DEA) is a broad range of mathematical models for measuring the relative efficiency of a set of homogeneous decision units with similar inputs and outputs. Multiple models of data envelopment analysis render a set of weights for input and output variables of each decision unit to calculate the relative efficiency of those units based on them. The calculation of different weights for the same indices in a set of homogeneous decision units is not realistic. Therefore, the Common Set of Weights (CSW) method was used to solve this problem and the Bootstrap method was used to determine which common set of weights would minimize the number of efficient units. The rank of a unit can provide useful information to decision-makers on the optimal activities of decision units. The priority order of units defines the superiority of a unit in terms of efficiency and effectiveness over others. Calculating unit efficiency for data envelopment analysis models can be a good criterion for ranking one unit. However, the main problem arises when several efficient units all rank first. This study aimed at proposing a model for ranking efficient units using the Bootstrap method to determine the common set of weights in data envelopment analysis by finding a possible confidence interval for the weights using the Bootstrap method. This led to the estimation of a set of possible common weights for the data envelopment analysis. Efficient units were then identified and ranked based on these weights.. Manuscript profile
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