Article ID: | iaor20171879 |
Volume: | 253 |
Issue: | 1 |
Start Page Number: | 453 |
End Page Number: | 476 |
Publication Date: | Jun 2017 |
Journal: | Annals of Operations Research |
Authors: | Liang Liang, Li Yongjun, Yang Min, Shi Xiao |
Keywords: | statistics: data envelopment analysis, information, decision theory |
The decision makers always suffer from predicament in choosing appropriate variable set to evaluate/improve production efficiencies in many applications of data envelopment analysis (DEA). The selected data set may exist information redundancy. On that account, this study proposes an alternative approach to screen out proper input and output variables set for evaluation via Akaike’s information criteria (