perfomance management
Esmaeil Keshavarz; abbas shoul; Ali Fallah Tafti
Abstract
Data Envelopment Analysis (DEA) is an approach based on mathematical programming for the relative evaluation of decision-making units treated as similar yet distinct production systems. In this approach, the performance of each unit is characterized by describing the transformation of specific inputs ...
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Data Envelopment Analysis (DEA) is an approach based on mathematical programming for the relative evaluation of decision-making units treated as similar yet distinct production systems. In this approach, the performance of each unit is characterized by describing the transformation of specific inputs into specific outputs. Traditional DEA models assume that the role of each performance factor is clearly defined. However, in some real-world problems, certain factors might be identified as dual-role factors depending on the evaluation nature or the decision-makers' perspective. These factors can play the role of both input and output, or even be considered neutral in assessing the units' performance. In the current paper, to determine the status of dual-role factors and calculate the efficiency of DMUs, two new linear programming models, based on the concept of deviation in the efficiency constraint and a common set of weights, are suggested. The main advantages of the proposed models are significantly reducing the computations and iterations required to solve the model, and involving all DMUs to determine the role of factors. To assess the performance of the proposed models, a data set for the evaluation of eighteen suppliers in the presence of two inputs, three outputs, and two dual-role factors has been employed. The obtained results showed that, compared to other models, the proposed models are computationally more efficient, and the role determination and evaluation of the units, based on the obtained weights from these models, are better aligned with the expectations of decision-makers
Mojhgan PourAlizadeh; Alireza Amirteimoori; mohsen vaez-ghasemi
Abstract
Data envelopment analysis is auseful method to measurement unified rational and operational and environmental efficiency a supply chain. Supply chain management divisions produce two types outputs based on economic activities and inputs separate into two categories under natural and managerial disposability. ...
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Data envelopment analysis is auseful method to measurement unified rational and operational and environmental efficiency a supply chain. Supply chain management divisions produce two types outputs based on economic activities and inputs separate into two categories under natural and managerial disposability. The current paper propose a new Data Envelopment Analysis based model to efficiency assessment a supply chain under investment on certain types of inputs to new technologic innovation. In hence, dual-role factors controls cleanup costs of flaring gas and the amount electricity consumptions of power plants also dual-role indices improve expertise in transmission entities. A real case study on Iran power industry is presented to demonstrate the applicability of the proposed model. To demonstrate the capability of the proposed approach this framework is implemented for the performance evaluation of a supply chain identified by oil and gas companies, power plants, transmissions companies, dispatching companies and final consumers in Iran.
hossein mohebbi; adel azar; Abasali Heidari; Ameneh Khadivar
Abstract
Nowadays, most supply chains are starting to go green in their business with pay more attention to environmental protection as competitive advantage. Therefore, Designing a two-stage green supply chain for optimum assignment a green supplier to a green producer based on maximum efficiency and attention ...
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Nowadays, most supply chains are starting to go green in their business with pay more attention to environmental protection as competitive advantage. Therefore, Designing a two-stage green supply chain for optimum assignment a green supplier to a green producer based on maximum efficiency and attention to intermediate products and processes is essential. Because, economic performance and environmental performance of the supply chain will increases. One of the methods used to evaluating efficiency in the green supply chain management, is data envelopment analysis (DEA). The traditional DEA methods for evaluating efficiency of supply chain processes and multi-stage systems not working properly, Because, each decision making units is assumed as a black box and ignore its internal processes. In order to overcome this deficiency, a novel two-stage network DEA will be presented based on the concepts of Electrical Engineering that ability to consider all inputs, Intermediate products, desirable and undesirable outputs between supplier and producer in the green supply chain for optimum assignment a supplier to producer based on maximum efficiency. The proposed model has been described by an application example and Its reliability has been confirmed.
