Three-stage performance modeling using DEA-BPNN for better practice benchmarking

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• 作者：He-Boong Kwon^a ; ^{heboong.kwon@csupueblo.edu}Author Vitae ; Jon H. Marvel^b ; ^{jhmarvel@wcu.edu}Author Vitae ; James Jungbae Roh^c ; ^{roh@rowan.edu}Author Vitae
• 关键词：Backpropagation neural network ; Better practice benchmarking ; Data envelopment analysis ; Three-stage model
• 刊名：Expert Systems with Applications
• 出版年：2017
• 出版时间：1 April 2017
• 年：2017
• 卷：71
• 期：Complete
• 页码：429-441
• 全文大小：982 K
• 卷排序：71

文摘

DEA stratification and grouping of DMUs to form hierarchical frontiers. BPNN learning of efficiency patterns and classification of frontiers. BPNN prediction of incremental improvement outputs. The three-stage model for innovative ‘better practice benchmarking’. Empirically validated by using healthcare data.