Data Envelopment Analyses
Mohammad Alimoradi; Seyed Mohammad Ali Khatami Firouzabadi,; Maghsoud Amiri; Iman Raeesi Vanani
Abstract
Evaluation of performance and productivity and the process of its changes over time is considered essential in the process of improvement in organizations, production, industrial and service units. Regarding the estimation of productivity and productivity changes over time, different models, methods, ...
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Evaluation of performance and productivity and the process of its changes over time is considered essential in the process of improvement in organizations, production, industrial and service units. Regarding the estimation of productivity and productivity changes over time, different models, methods, approaches and indicators have been extracted and presented in various studies, one of the most important, common and widely used of them is the Malmquist Productivity Index. On the other hand, during production processes, undesirable products and outputs are produced simultaneously with desirable products. Therefore, with the development and expansion of the Malmquist Productivity Index, an index called the Malmquist Luenberger was introduced, which took into account the undesirable outputs while seeking to reduce them, and at the same time aimed at expanding the desirable outputs. Therefore, the current research and review paper, based on the PRISMA methodology, with the aim of a structured and systematic analysis of articles and researches on this subject. This research is of a review type that is conducted through searching in domestic and foreign databases such as Academic Jihad Scientific Information, Scopus, Science Direct, Elsevier and Google Scholar in the period from 1980 to 2022 with the approach of selecting the most important, most valid and prominent papers and Internal and external scientific and applied research has been carried out. The results of the current research show the existing scientific gaps and future suggestions regarding productivity evaluation using the Malmquist/Malmquist Luenberger Productivity Index.
Data Envelopment Analyses
Somayye Karimi Omshi; Sohrab Kordrostami; Alireza Amirteimoori; Armin Ghane Kanafi
Abstract
Purpose: In the most investigations of sustainability, including environmental, social and economic issues, in addition to the desirable outputs, undesirable outputs are also presented, which is an obstacle to sustainable development. In this regard, the purpose of this paper is providing an approach ...
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Purpose: In the most investigations of sustainability, including environmental, social and economic issues, in addition to the desirable outputs, undesirable outputs are also presented, which is an obstacle to sustainable development. In this regard, the purpose of this paper is providing an approach based on Data Envelopment Analysis (DEA) with different forms of weak disposability of undesirable outputs to move towards sustainability.Methodology: Presenting a DEA-based model, the sustainability and performance of each dimension of sustainability are calculated simultaneously, while undesirable outputs are present with different forms of weak disposability. The sustainability performance of provincial gas companies is examined using the proposed technique.Findings: The results show that the proposed method in the performance analysis of sustainability and its dimensions is efficient when undesirable outputs are presented.Originality/Value: DEA provides a variety of disposability to minimize undesirable outputs and moves to optimize. In this study, an integrated approach with different forms of weak disposability is presented to analyze sustainability.
Data Envelopment Analyses
Mostafa Radsar; Aliyeh Kazemi; Mohammadreza Mehregan
Abstract
Purpose: It is important to consider the uncertainty in the data, and know how to deal with it when evaluating efficiency by using data envelopment analysis; since the presence of small deviations in the data can lead to significant changes in efficiency results. However, in the real world in many cases, ...
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Purpose: It is important to consider the uncertainty in the data, and know how to deal with it when evaluating efficiency by using data envelopment analysis; since the presence of small deviations in the data can lead to significant changes in efficiency results. However, in the real world in many cases, the data is uncertain. The purpose of this paper is to present a robust model of network data envelopment analysis in order to measure efficiency in the presence of uncertainty.Methodology: A new approach to evaluate efficiency for network data envelopment analysis is first proposed. The definitive method presented in this paper involves undesirable output and can be used for different structures in network data envelopment analysis. Next by extending, the proposed model for uncertain data a new robust network data envelopment analysis model is presented for three-stage networks with undesirable outputs.Findings: The proposed model is used to evaluate the electricity regions of Iran. These regions involve a three-step process with undesirable outputs in some stages. The results show that the proposed model achieves the efficiency of the steps and the total efficiency simultaneously. In addition, the overall network efficiency score can be a basis to rank the areas.Originality/Value: The proposed model is a new model in the field of efficiency evaluation in conditions of uncertainty and having an undesirable output.