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DEA Models for Extended Two-Stage Network Structures

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TLDR
Two models are proposed to evaluate the performance of this type general two-stage network structures where all outputs of the first stage are the only inputs to the second stage, and a non-cooperative model, in which one of the stages is regarded as the leader and the other is the follower.
Abstract
This chapter discusses DEA modeling technique for a two-stage network process where the inputs of the second stage include both the outputs from the first stage and additional inputs to the second stage. Two models are proposed to evaluate the performance of this type two-stage network structures. One is a non-linear centralized model whose global optimal solutions can be estimated using a heuristic search procedure. The other is a non-cooperative model, in which one of the stages is regarded as the leader and the other is the follower. The newly developed models are illustrated with a case of regional R&D of China.

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Citations
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A survey of DEA applications

TL;DR: This study is the first literature survey that focuses on DEA applications, covering DEA papers published in journals indexed by the Web of Science database from 1978 through August 2010, and suggests that the two-step contextual analysis and network DEA are the recent trends across applications.
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Dynamic DEA with network structure: A slacks-based measure approach

TL;DR: In this paper, the authors proposed a dynamic DEA model involving network structure in each period within the framework of a slacks-based measure approach, and applied this model to a dataset of US electric utilities and compared the result with that of DSBM.
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Network data envelopment analysis: A review

TL;DR: 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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Data envelopment analysis application in sustainability: The origins, development and future directions

TL;DR: This study reviews the literature on data envelopment analysis (DEA) applications in sustainability using citation-based approaches and constructs a directional network based on citation relationships among DEA papers published in journals indexed by the Web of Science database from 1996 to March 2016.
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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.
References
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Journal ArticleDOI

Slacks and congestion: a comment

TL;DR: In this paper, the authors focus on clarifying the distinction between their approach to modeling technology and measuring congestion, differentiating between weak disposability and the law of variable proportions, and show that whereas their congestion measure identifies congestion only if associated strongly disposable technology solution has nonzero slacks, the converse is not true.
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DEA as a tool for predicting corporate failure and success: A case of bankruptcy assessment

TL;DR: In this article, the authors used an additive super-efficiency data envelopment analysis (DEA) model to predict corporate failure and success, and developed a new assessment index based on two frontiers for predicting corporate failures and success.
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DEA-based production planning

TL;DR: Two DEA-based production planning approaches are developed to find the most preferred production plans for all individual units in the next production season when demand changes can be forecasted.
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A modified DEA model to estimate the importance of objectives with an application to agricultural economics

TL;DR: In this article, a connection between data envelopment analysis (DEA) and a non-interactive elicitation method to estimate the weights of objectives for decision-makers in a multiple attribute approach is demonstrated.
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