Analyzing the solutions of DEA through information visualization and data mining techniques: SmartDEA framework

Akçay, Alp; Ertek, Gürdal; Büyüközkan, Gülçin

doi:10.1016/j.eswa.2012.01.059

Cited by 36 publications

(11 citation statements)

References 30 publications

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“…DEA as a non-parametric performance evaluation method with diverse aspects of application within various disciplines is a useful tool for assessing efficiency of organizations (Akcay et al, 2012). DEA defined as "a mathematical programming model applied to observational data and a new way of obtaining experimental estimates of relations such as the production functions and/or efficient production possibility surfaces" by Charnes et al (1978).…”

Section: The Dea Methodsmentioning

confidence: 99%

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Data Envelopment Analysis: A knowledge-driven method for mineral prospectivity mapping

Hosseini

Abedi

2015

Computers & Geosciences

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Section: The Dea Methodsmentioning

confidence: 99%

“…The efficiency score of a DMU is basically the distance between a DMU to this efficient frontier. The efficiency scores of the inefficient DMUs are calculated in accordance with such distance presented as a Pareto ratio (Akcay et al, 2012).…”

Section: The Dea Methodsmentioning

confidence: 99%

Data Envelopment Analysis: A knowledge-driven method for mineral prospectivity mapping

Hosseini

Abedi

2015

Computers & Geosciences

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“…The main objective of this research is to develop a general decision support system (DSS) framework to analyze the results of basic DEA models. The research formally shows how the results of DEA models should be structured so that these solutions can be examined and interpreted by analysts through information visualization and data mining techniques effectively (Akçay et al 2012).…”

Section: Data Mining As An Important Component Of Intelligent Decisiomentioning

confidence: 99%

Intelligent Decision Support Systems

Kaklauskas

2014

Intelligent Systems Reference Library

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This chapter presents the latest IDSSs, such as text analytics and mining based DSSs; ambient intelligence and the internet of things-based DSSs; biometrics-based DSSs; recommender, advisory and expert systems; data mining, data analytics, neural networks, remote sensing and their integration with decision support systems and other IDSSs. These other IDSSs include GA-based DSS; fuzzy sets DSS; rough sets-based DSS; intelligent agent-assisted DSS; process mining integration to decision support, adaptive DSS; computer vision based DSS; sensory DSS and robotic DSS. In addition to acquainting these IDSSs, author introduce practical examples where they have been effectively applied. 2

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“…Furthermore, there are plenty of methods which were employed with DEA, for instance, balanced scorecard approach [58], data mining [59] and Principal Component Analysis [60].…”

Section: B Focus and Content Of The Publicationsmentioning

confidence: 99%

A review of Data Development Analysis (DEA) applications in supply chain management research

Chaowarat

Piboonrugnroj

Shi

2013

2013 IEEE International Conference on Industrial Engineering and Engineering Management

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The objective of this paper is to review the application of Data Envelopment Analysis (DEA) in Supply Chain Management (SCM) research including different perspectives and research topics. In this review, academic databases used were ScienceDirect, Scopus and Google Scholar. The latter database was included to identify unpublished studies, conference proceedings and other types of unpublished studies. Practical review criteria are used for the inclusion or exclusion of the pertinent literature. In total 55 publications were found and analyzed in this paper. We found that even though both DEA and SCM were established as a field of study for a long time but there are only a few that applied the DEA to SCM. Most of studies applying DEA in SCM did not consider the whole supply chain, only some parts of the chain were analyzed. Based on the findings of the review, potential research agendas were developed.

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Analyzing the solutions of DEA through information visualization and data mining techniques: SmartDEA framework

Cited by 36 publications

References 30 publications

Data Envelopment Analysis: A knowledge-driven method for mineral prospectivity mapping

Data Envelopment Analysis: A knowledge-driven method for mineral prospectivity mapping

Intelligent Decision Support Systems

A review of Data Development Analysis (DEA) applications in supply chain management research

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