Data envelopment analysis and big data
type: Item
instance of: scholarly article
title: Data envelopment analysis and big data
zbMATH Open document ID: 1430.90407
author: Dariush Khezrimotlagh
author: Joe Zhu
author: Wade D. Cook
author: Mehdi Toloo
published in: European Journal of Operational Research
publication date: 2019-01-09T00:00:00Z
Mathematics Subject Classification ID: 90C08
Mathematics Subject Classification ID: 90B50
Mathematics Subject Classification ID: 62P20
Mathematics Subject Classification ID: 62H30
zbMATH DE Number: 6999099
zbMATH Keywords: data envelopment analysis (DEA)
zbMATH Keywords: big data
zbMATH Keywords: performance evaluation
zbMATH Keywords: simulation
MaRDI profile type: Publication
full work available at URL: j.ejor.2018.10.044
OpenAlex ID: W2899304741
cites work: Streamlined computation for data envelopment analysis
cites work: Some Models for Estimating Technical and Scale Inefficiencies in Data Envelopment Analysis
cites work: Parallel and hierarchical decomposition approaches for solving large-scale data envelopment analysis models
cites work: Measuring the efficiency of decision making units
cites work: A procedure for large-scale DEA computations
cites work: Determining radial efficiency with a large data set by solving small-size linear programs
cites work: Q3412530
cites work: A new procedure for identifying the frame of the convex hull of a finite collection of points in multidimensional space
cites work: An Algorithm for Identifying the Frame of a Pointed Finite Conical Hull
cites work: A computational study of DEA with massive data sets
cites work: Preprocessing DEA
cites work: An algorithm for data envelopment analysis
cites work: A dimensional decomposition approach to identifying efficient units in large-scale DEA models
cites work: A response to comments on `Modeling undesirable factors in efficiency evaluation'.
cites work: Efficient algorithm for additive and multiplicative models in data envelopment analysis
cites work: Efficiency evaluation based on data envelopment analysis in the big data context
DOI: 10.1016/J.EJOR.2018.10.044
description: scientific article; zbMATH DE number 6999099