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Innovation and efficiency in financial institutions

This paper proposes a new methodology that combines standard production theory with Multiple-Criteria Decision Analysis (MCDA) methods to rank banks based on their capability of using investment in new technologies to reduce the other inputs' usage, for a given level of output. Banks are first...

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Autores principales: Sena, Vania, Kenjegaliev, Amangeldi, Kenjegalieva, Aliya
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Frontiers Media S.A. 2022
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9399391/
https://www.ncbi.nlm.nih.gov/pubmed/36035069
http://dx.doi.org/10.3389/frma.2022.805116
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author Sena, Vania
Kenjegaliev, Amangeldi
Kenjegalieva, Aliya
author_facet Sena, Vania
Kenjegaliev, Amangeldi
Kenjegalieva, Aliya
author_sort Sena, Vania
collection PubMed
description This paper proposes a new methodology that combines standard production theory with Multiple-Criteria Decision Analysis (MCDA) methods to rank banks based on their capability of using investment in new technologies to reduce the other inputs' usage, for a given level of output. Banks are first ranked based on their investment in innovation (innovation rank); afterwards, we calculate the overall rank by combining two factors of production, viz. labor and assets, using the PROMETHEE II approach that belongs to the family of the outranking methods. We then use directional efficiency measures to measure the banks' efficiency by means of relation between two ranks, for a given level of the outputs. We apply the methodology to a sample of US and EU banks sourced from Orbis BankFocus. The key findings suggest there are four types of banks in our sample: (a) banks whose innovation rank is positively correlated with the overall rank; (b) banks exhibiting a negative correlation between two ranks: their overall ranks are low while still exhibiting high innovation ranks; (c) banks with high overall rank but low innovation rank and (d) banks with the worst ranks both for the innovation rank and the overall rank. The least efficient banks belong to this group.
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spelling pubmed-93993912022-08-25 Innovation and efficiency in financial institutions Sena, Vania Kenjegaliev, Amangeldi Kenjegalieva, Aliya Front Res Metr Anal Research Metrics and Analytics This paper proposes a new methodology that combines standard production theory with Multiple-Criteria Decision Analysis (MCDA) methods to rank banks based on their capability of using investment in new technologies to reduce the other inputs' usage, for a given level of output. Banks are first ranked based on their investment in innovation (innovation rank); afterwards, we calculate the overall rank by combining two factors of production, viz. labor and assets, using the PROMETHEE II approach that belongs to the family of the outranking methods. We then use directional efficiency measures to measure the banks' efficiency by means of relation between two ranks, for a given level of the outputs. We apply the methodology to a sample of US and EU banks sourced from Orbis BankFocus. The key findings suggest there are four types of banks in our sample: (a) banks whose innovation rank is positively correlated with the overall rank; (b) banks exhibiting a negative correlation between two ranks: their overall ranks are low while still exhibiting high innovation ranks; (c) banks with high overall rank but low innovation rank and (d) banks with the worst ranks both for the innovation rank and the overall rank. The least efficient banks belong to this group. Frontiers Media S.A. 2022-08-10 /pmc/articles/PMC9399391/ /pubmed/36035069 http://dx.doi.org/10.3389/frma.2022.805116 Text en Copyright © 2022 Sena, Kenjegaliev and Kenjegalieva. https://creativecommons.org/licenses/by/4.0/This is an open-access article distributed under the terms of the Creative Commons Attribution License (CC BY). The use, distribution or reproduction in other forums is permitted, provided the original author(s) and the copyright owner(s) are credited and that the original publication in this journal is cited, in accordance with accepted academic practice. No use, distribution or reproduction is permitted which does not comply with these terms.
spellingShingle Research Metrics and Analytics
Sena, Vania
Kenjegaliev, Amangeldi
Kenjegalieva, Aliya
Innovation and efficiency in financial institutions
title Innovation and efficiency in financial institutions
title_full Innovation and efficiency in financial institutions
title_fullStr Innovation and efficiency in financial institutions
title_full_unstemmed Innovation and efficiency in financial institutions
title_short Innovation and efficiency in financial institutions
title_sort innovation and efficiency in financial institutions
topic Research Metrics and Analytics
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9399391/
https://www.ncbi.nlm.nih.gov/pubmed/36035069
http://dx.doi.org/10.3389/frma.2022.805116
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