A
Ali Emrouznejad
Researcher at Aston University
Publications - 245
Citations - 9386
Ali Emrouznejad is an academic researcher from Aston University. The author has contributed to research in topics: Data envelopment analysis & Computer science. The author has an hindex of 43, co-authored 213 publications receiving 7289 citations. Previous affiliations of Ali Emrouznejad include National Research University – Higher School of Economics & University of Warwick.
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Evaluation of research in efficiency and productivity:a survey and analysis of the first 30 years of scholarly literature in DEA
TL;DR: An extensive, if not nearly complete, listing of DEA research covering theoretical developments as well as "real-world" applications from inception to the year 2007 is presented.
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A survey and analysis of the first 40 years of scholarly literature in DEA: 1978–2016
Ali Emrouznejad,Guo-liang Yang +1 more
TL;DR: This paper aims to report an extensive listing of DEA-related articles including theory and methodology developments and "real" applications in diversified scenarios from 1978 to end of 2016.
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A taxonomy and review of the fuzzy data envelopment analysis literature: two decades in the making
TL;DR: Fuzzy Data Envelopment Analysis (DEA) is a methodology for measuring the relative efficiencies of a set of decision making units (DMUs) that use multiple inputs to produce multiple outputs as discussed by the authors.
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The state of the art development of AHP (1979–2017): a literature review with a social network analysis
Ali Emrouznejad,Marianna Marra +1 more
TL;DR: The pattern of development of the AHP research field is examined using social network analysis and scientometrics, and its intellectual structure is identified, and two types of networks are analysed: social networks and cognitive mapping or the network of disciplines affected by AHP.
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A semi-oriented radial measure for measuring the efficiency of decision making units with negative data, using DEA
TL;DR: A semi-oriented radial measure is proposed, which permits the presence of variables which can take both negative and positive values in DEA and is applied to data on a notional effluent processing system to compare the results with those yielded by two alternative methods for dealing with negative data in DEA.