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A review of Dynamic Data Envelopment Analysis: state of the art and applications.

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Title: A review of Dynamic Data Envelopment Analysis: state of the art and applications.
Authors: Mariz, Fernanda B. A. R.1 rocha_fernanda@outlook.com, Almeida, Mariana R.2 almeidamariana@yahoo.com, Aloise, Daniel3 daniel.aloise@polymtl.ca
Source: International Transactions in Operational Research. Mar2018, Vol. 25 Issue 2, p469-505. 37p. 7 Diagrams, 7 Charts, 1 Graph.
Subjects: Data envelopment analysis, Dynamic data exchange, Group decision making, Linear programming, Dynamic models
Abstract: This article reports the evolution of the literature on Dynamic Data Envelopment Analysis (DDEA) models from 1996 to 2016. Systematic searches in the databases Scopus and Web of Science were performed to outline the state of the art. The results enabled the establishment of DDEA studies as the scope of this article, analyzing the transition elements to represent temporal interdependence. The categorization of these studies enabled the mapping of the evolution of the DDEA literature and identification of the relationships between models. The three most widely adopted studies to conduct DDEA research were classified as structuring models. Mapping elucidated the literature behavior through three phases and showed an increase in publications with applications in recent years. The analysis of applications indicated that most studies address evaluations in the agriculture and farming, banking and energy sectors and consider the facilities as transition elements between analysis periods. [ABSTRACT FROM AUTHOR]
Copyright of International Transactions in Operational Research is the property of Wiley-Blackwell and its content may not be copied or emailed to multiple sites without the copyright holder's express written permission. Additionally, content may not be used with any artificial intelligence tools or machine learning technologies. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)
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  Data: <searchLink fieldCode="JN" term="%22International+Transactions+in+Operational+Research%22">International Transactions in Operational Research</searchLink>. Mar2018, Vol. 25 Issue 2, p469-505. 37p. 7 Diagrams, 7 Charts, 1 Graph.
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  Data: <searchLink fieldCode="DE" term="%22Data+envelopment+analysis%22">Data envelopment analysis</searchLink><br /><searchLink fieldCode="DE" term="%22Dynamic+data+exchange%22">Dynamic data exchange</searchLink><br /><searchLink fieldCode="DE" term="%22Group+decision+making%22">Group decision making</searchLink><br /><searchLink fieldCode="DE" term="%22Linear+programming%22">Linear programming</searchLink><br /><searchLink fieldCode="DE" term="%22Dynamic+models%22">Dynamic models</searchLink>
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  Data: This article reports the evolution of the literature on Dynamic Data Envelopment Analysis (DDEA) models from 1996 to 2016. Systematic searches in the databases Scopus and Web of Science were performed to outline the state of the art. The results enabled the establishment of DDEA studies as the scope of this article, analyzing the transition elements to represent temporal interdependence. The categorization of these studies enabled the mapping of the evolution of the DDEA literature and identification of the relationships between models. The three most widely adopted studies to conduct DDEA research were classified as structuring models. Mapping elucidated the literature behavior through three phases and showed an increase in publications with applications in recent years. The analysis of applications indicated that most studies address evaluations in the agriculture and farming, banking and energy sectors and consider the facilities as transition elements between analysis periods. [ABSTRACT FROM AUTHOR]
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  Data: <i>Copyright of International Transactions in Operational Research is the property of Wiley-Blackwell and its content may not be copied or emailed to multiple sites without the copyright holder's express written permission. Additionally, content may not be used with any artificial intelligence tools or machine learning technologies. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract.</i> (Copyright applies to all Abstracts.)
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              Text: Mar2018
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