Inverted VEA for worst-practice benchmarking: with an application to distress prediction of European banks
Author:
Publisher
Springer Science and Business Media LLC
Subject
Management Science and Operations Research,General Decision Sciences
Link
https://link.springer.com/content/pdf/10.1007/s10479-023-05764-x.pdf
Reference74 articles.
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2. Amin, G. R., & Boamah, M. I. (2020). A new inverse DEA cost efficiency model for estimating potential merger gains: A case of Canadian banks. Annals of Operations Research, 295, 21–36. https://doi.org/10.1007/s10479-020-03667-9
3. Andersen, P., & Petersen, N. C. (1993). A procedure for ranking efficient units in data envelopment analysis. Management Science, 39, 1261–1264. https://doi.org/10.1287/mnsc.39.10.1261
4. Avkiran, N. K., & Cai, L. (2014). Identifying distress among banks prior to a major crisis using non-oriented super-SBM. Annals of Operations Research, 217, 31–53. https://doi.org/10.1007/s10479-014-1568-8
5. Banco BPM (2018a). Consolidated 2018 annual report. Available at: https://gruppo.bancobpm.it/media/dlm_uploads/Consolidated-annual-report-2018-1-1.pdf.
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