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Network data envelopment analysis: A review

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TLDR
This paper reviews studies on network DEA by examining the models used and the structures of the network system of the problem being studied, and highlights some directions for future studies from the methodological point of view.
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This article is published in European Journal of Operational Research.The article was published on 2014-11-16. It has received 446 citations till now. The article focuses on the topics: Data envelopment analysis.

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Measuring China’s regional energy and carbon emission efficiency with DEA models: A survey

TL;DR: A comprehensive survey of empirical studies published in 2006-2015 on China's regional energy efficiency and carbon emission efficiency assessment using DEA-type models was conducted in this paper, where the main features used in previous studies were identified, and then the methodological framework for deriving the EE&CE indicators as well as six widely used DEA models were introduced.
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Research fronts in data envelopment analysis

TL;DR: This study applies a network clustering method to group the literature through a citation network established from the DEA literature over the period 2000 to 2014, and presents the research fronts, a coherent topic or issue addressed by a group of research articles in recent years.
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Evaluating the eco-efficiency of China's industrial sectors: A two-stage network data envelopment analysis.

TL;DR: Evaluating the eco-efficiency of China's industrial sectors between 2007 and 2015 by using the directional distance function (DDF) of network data envelopment analysis (DEA), which contains a two-stage structure that divides industrial processes into three linked subprocesses, indicates that China's industries have already achieved a win-win situation in the development of environmental protection and economic growth over the past few years.
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Two-stage DEA models with undesirable input-intermediate-outputs $

TL;DR: In this paper, the authors examined two-stage DEA models with undesirable inputs-intermediate-outputs and used the free-disposal axioms to construct the production possibility sets.
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Reprint of "Performance evaluation of China's high-tech innovation process :Analysis based on the innovation value chain"

TL;DR: Wang et al. as discussed by the authors presented a conceptual model extended from the innovation value chain model to simultaneously estimate the R&D and commercialization efficiencies for the high-tech industries of 29 provincial-level regions in China.
References
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Journal ArticleDOI

Measuring the efficiency of decision making units

TL;DR: A nonlinear (nonconvex) programming model provides a new definition of efficiency for use in evaluating activities of not-for-profit entities participating in public programs and methods for objectively determining weights by reference to the observational data for the multiple outputs and multiple inputs that characterize such programs.
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Some Models for Estimating Technical and Scale Inefficiencies in Data Envelopment Analysis

TL;DR: The CCR ratio form introduced by Charnes, Cooper and Rhodes, as part of their Data Envelopment Analysis approach, comprehends both technical and scale inefficiencies via the optimal value of the ratio form, as obtained directly from the data without requiring a priori specification of weights and/or explicit delineation of assumed functional forms of relations between inputs and outputs as mentioned in this paper.
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A procedure for ranking efficient units in data envelopment analysis

TL;DR: In this paper, a modified version of DEA based upon comparison of efficient DMUs relative to a reference technology spanned by all other units is developed, which provides a framework for ranking efficient units and facilitates comparison with rankings based on parametric methods.
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Data envelopment analysis (DEA) - Thirty years on

TL;DR: A sketch of some of the major research thrusts in data envelopment analysis (DEA) over the three decades since the appearance of the seminal work of Charnes et al. is provided.
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Efficiency decomposition in two-stage data envelopment analysis: an application to non-life insurance companies in taiwan

TL;DR: The relational model developed in this paper is more reliable in measuring the efficiencies and consequently is capable of identifying the causes of inefficiency more accurately.
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