NDLI: An integrated approach of data envelopment analysis and boosted generalized linear mixed models for efficiency assessment

Content Provider	Springer Nature Link
Author	Bou Hamad, Imad Auze, Abdel Latef Larocque, Denis
Copyright Year	2016
Abstract	Performance evaluation is an important part in the management of any decision-making unit (DMU) as it identifies sources of managerial inefficiencies and provides a policy for inefficient DMUs to improve their efficiency. The latter is generally affected by environmental variables that are beyond managerial control. Modeling the impact of these environmental variables is a critical issue for both researchers and practitioners. Researchers developed and proposed several methods to deal with this issue in general and in the data envelopment analysis (DEA) literature in particular. However, the available two-stage DEA methods do not account for interdependence between observations and they are of limited use when the number of variables is fairly large. This paper proposes an integrated framework combining DEA, and boosted generalized linear mixed models (GLMMs) that accounts for the interdependence problem when studying the impact of environmental variables on performance. Additionally, the framework carries out variable selection. The framework is illustrated with a sample of 151 commercial banks from Middle East and North African countries.
Starting Page	77
Ending Page	95
Page Count	19
File Format	PDF
ISSN	02545330
Journal	Annals of Operations Research
Volume Number	253
Issue Number	1
e-ISSN	15729338
Language	English
Publisher	Springer US
Publisher Date	2016-10-15
Publisher Place	New York
Access Restriction	One Nation One Subscription (ONOS)
Subject Keyword	Data envelopment analysis Generalized linear mixed models Boosting Environmental variables Middle East and North African countries Banking efficiency Operation Research/Decision Theory Combinatorics Theory of Computation
Content Type	Text
Resource Type	Article
Subject	Management Science and Operations Research

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