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dc.contributor.authorVincent, Charles
dc.contributor.authorTsolas, I.E.
dc.contributor.authorGherman, T.
dc.date.accessioned2019-12-15T12:20:42Z
dc.date.accessioned2019-12-16T14:33:18Z
dc.date.available2019-12-15T12:20:42Z
dc.date.available2019-12-16T14:33:18Z
dc.date.issued2018-10
dc.identifier.citationVincent C, Tsolas IE and Gherman T (2018) Satisficing data envelopment analysis: a Bayesian approach for peer mining in the banking sector. Annals of Operations Research. 269(1-2): 81-102.en_US
dc.identifier.urihttp://hdl.handle.net/10454/17537
dc.descriptionYes
dc.description.abstractOver the past few decades, the banking sectors in Latin America have undergone rapid structural changes to improve the efficiency and resilience of their financial systems. The up-to-date literature shows that all the research studies conducted to analyze the above-mentioned efficiency are based on a deterministic data envelopment analysis (DEA) model or econometric frontier approach. Nevertheless, the deterministic DEA model suffers from a possible lack of statistical power, especially in a small sample. As such, the current research paper develops the technique of satisficing DEA to examine the still less explored case of Peru. We propose a Satisficing DEA model applied to 14 banks operating in Peru to evaluate the bank-level efficiency under a stochastic environment, which is free from any theoretical distributional assumption. The proposed model does not only report the bank efficiency, but also proposes a new framework for peer mining based on the Bayesian analysis and potential improvements with the bias-corrected and accelerated confidence interval. Our study is the first of its kind in the literature to perform a peer analysis based on a probabilistic approach.en_US
dc.language.isoenen_US
dc.rights© Springer Science+Business Media New York 2017. Reproduced in accordance with the publisher's self-archiving policy. The final publication is available at Springer via http://dx.doi.org/10.1007/s10479-017-2552-xen_US
dc.subjectData envelopment analysis
dc.subjectSatisficing DEA
dc.subjectMathematical programming
dc.subjectBanking
dc.subjectPeer mining
dc.subjectBayesian predictive analytics
dc.titleSatisficing data envelopment analysis: a Bayesian approach for peer mining in the banking sectoren_US
dc.status.refereedYes
dc.date.application17/06/2017
dc.typeArticle
dc.type.versionAccepted manuscript
dc.identifier.doihttps://doi.org/10.1007/s10479-017-2552-x
dc.date.updated2019-12-15T12:20:58Z
refterms.dateFOA2019-12-16T14:33:48Z
dc.openaccess.statusopenAccess
dc.date.accepted2017


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