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AuthorBou-Hamad, Imad
AuthorAnouze, Abdel Latef
AuthorOsman, Ibrahim H.
Available date2023-04-10T06:42:12Z
Publication Date2021-05-06
Publication NameAnnals of Operations Research
Identifierhttp://dx.doi.org/10.1007/s10479-021-04024-0
CitationBou-Hamad, I., Anouze, A. L., & Osman, I. H. (2022). A cognitive analytics management framework to select input and output variables for data envelopment analysis modeling of performance efficiency of banks using random forest and entropy of information. Annals of Operations Research, 308(1-2), 63-92.
ISSN0254-5330
URIhttps://www.scopus.com/inward/record.uri?partnerID=HzOxMe3b&scp=85105727223&origin=inward
URIhttp://hdl.handle.net/10576/41778
AbstractThe efficiency of banks has a critical role in development of sound financial systems of countries. Data Envelopment Analysis (DEA) has witnessed an increase in popularity for modeling the performance efficiency of banks. Such efficiency depends on the appropriate selection of input and output variables. In literature, no agreement exists on the selection of relevant variables. The disagreement has been an on-going debate among academic experts, and no diagnostic tools exist to identify variable misspecifications. A cognitive analytics management framework is proposed using three processes to address misspecifications. The cognitive process conducts an extensive review to identify the most common set of variables. The analytics process integrates a random forest method; a simulation method with a DEA measurement feedback; and Shannon Entropy to select the best DEA model and its relevant variables. Finally, a management process discusses the managerial insights to manage performance and impacts. A sample of data is collected on 303 top-world banks for the periods 2013 to 2015 from 49 countries. The experimental simulation results identified the best DEA model along with its associated variables, and addressed the misclassification of the total deposits. The paper concludes with the limitations and future research directions.
Sponsor- The National Research Center of Lebanon. - The University Research Board of the American University of Beirut
Languageen
PublisherSpringer Nature
SubjectData envelopment analysis
Input/output variable selection
Performance efficiency of banks
Random forests
Shannon entropy of information
TitleA cognitive analytics management framework to select input and output variables for data envelopment analysis modeling of performance efficiency of banks using random forest and entropy of information
TypeArticle
Pagination63-92
Issue Number1-2
Volume Number308
ESSN1572-9338
dc.accessType Full Text


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