Modelización de la autosuficiencia de las instituciones microfinancieras mediante regresión logística basada en análisis de componentes principales

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The analysis of the factors that influence sustainability is the key to achieving it. Based on the Theory of Resources and Capabilities (Grant, 1991), a management model that determines the explanatory factors of the sustainability of microfinance institutions (MFI) is developed. The empirical model...

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Detalles Bibliográficos
Autores: Irimia Diéguez, Ana, Blanco Oliver, Antonio, Oliver Alfonso, María Dolores
Formato: artículo
Fecha de Publicación:2016
Institución:Universidad ESAN
Repositorio:Revistas - Universidad ESAN
Lenguaje:español
OAI Identifier:oai:ojs.pkp.sfu.ca:article/151
Enlace del recurso:https://revistas.esan.edu.pe/index.php/jefas/article/view/151
Nivel de acceso:acceso abierto
Materia:Microfinance
Operational sustainability
Theory of organisational change
Self-sufficiency
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spelling Modelización de la autosuficiencia de las instituciones microfinancieras mediante regresión logística basada en análisis de componentes principalesIrimia Diéguez, Ana Blanco Oliver, Antonio Oliver Alfonso, María Dolores MicrofinanceOperational sustainabilityTheory of organisational changeSelf-sufficiencyThe analysis of the factors that influence sustainability is the key to achieving it. Based on the Theory of Resources and Capabilities (Grant, 1991), a management model that determines the explanatory factors of the sustainability of microfinance institutions (MFI) is developed. The empirical model is constructed by applying a principal component and logistic regression analysis using a sample of 313 MFI, with 31 finance variables, grouped into 6 components/factors that are theoretically associated with self-sufficiency. The results obtained showed a significant and positive relationship between size and the efficiency-productivity of the MFI and their sustainability, with the credit risk factor having an inverse relationship as regards that sustainability. Thus, it may be suggested that the MFI that wish to continue developing their activity using a self-sufficiency approach must promote a management strategy oriented towards: (1) an increase in efficiency-productivity, (2) the exhaustive control of credit risk and, (3) the increase in size in order to achieve economies of scale. The predictive capacity of the model is high, with an area under the ROC curve of 89.7%. Doi: https://doi.org/10.1016/j.jefas.2015.12.​002Universidad ESAN2016-06-01info:eu-repo/semantics/articleinfo:eu-repo/semantics/publishedVersionPeer-reviewed Articleapplication/pdfhttps://revistas.esan.edu.pe/index.php/jefas/article/view/151Journal of Economics, Finance and Administrative Science; Vol. 21 No. 40 (2016): January - June; 30-38Journal of Economics, Finance and Administrative Science; Vol. 21 Núm. 40 (2016): January - June; 30-382218-06482077-1886reponame:Revistas - Universidad ESANinstname:Universidad ESANinstacron:ESANspahttps://revistas.esan.edu.pe/index.php/jefas/article/view/151/118Copyright (c) 2021 Journal of Economics, Finance and Administrative Sciencehttps://creativecommons.org/licenses/by/4.0/info:eu-repo/semantics/openAccessoai:ojs.pkp.sfu.ca:article/1512021-11-04T00:32:44Z
dc.title.none.fl_str_mv Modelización de la autosuficiencia de las instituciones microfinancieras mediante regresión logística basada en análisis de componentes principales
title Modelización de la autosuficiencia de las instituciones microfinancieras mediante regresión logística basada en análisis de componentes principales
spellingShingle Modelización de la autosuficiencia de las instituciones microfinancieras mediante regresión logística basada en análisis de componentes principales
Irimia Diéguez, Ana
Microfinance
Operational sustainability
Theory of organisational change
Self-sufficiency
title_short Modelización de la autosuficiencia de las instituciones microfinancieras mediante regresión logística basada en análisis de componentes principales
title_full Modelización de la autosuficiencia de las instituciones microfinancieras mediante regresión logística basada en análisis de componentes principales
title_fullStr Modelización de la autosuficiencia de las instituciones microfinancieras mediante regresión logística basada en análisis de componentes principales
title_full_unstemmed Modelización de la autosuficiencia de las instituciones microfinancieras mediante regresión logística basada en análisis de componentes principales
title_sort Modelización de la autosuficiencia de las instituciones microfinancieras mediante regresión logística basada en análisis de componentes principales
dc.creator.none.fl_str_mv Irimia Diéguez, Ana
Blanco Oliver, Antonio
Oliver Alfonso, María Dolores
author Irimia Diéguez, Ana
author_facet Irimia Diéguez, Ana
Blanco Oliver, Antonio
Oliver Alfonso, María Dolores
author_role author
author2 Blanco Oliver, Antonio
Oliver Alfonso, María Dolores
author2_role author
author
dc.subject.none.fl_str_mv Microfinance
Operational sustainability
Theory of organisational change
Self-sufficiency
topic Microfinance
Operational sustainability
Theory of organisational change
Self-sufficiency
description The analysis of the factors that influence sustainability is the key to achieving it. Based on the Theory of Resources and Capabilities (Grant, 1991), a management model that determines the explanatory factors of the sustainability of microfinance institutions (MFI) is developed. The empirical model is constructed by applying a principal component and logistic regression analysis using a sample of 313 MFI, with 31 finance variables, grouped into 6 components/factors that are theoretically associated with self-sufficiency. The results obtained showed a significant and positive relationship between size and the efficiency-productivity of the MFI and their sustainability, with the credit risk factor having an inverse relationship as regards that sustainability. Thus, it may be suggested that the MFI that wish to continue developing their activity using a self-sufficiency approach must promote a management strategy oriented towards: (1) an increase in efficiency-productivity, (2) the exhaustive control of credit risk and, (3) the increase in size in order to achieve economies of scale. The predictive capacity of the model is high, with an area under the ROC curve of 89.7%. Doi: https://doi.org/10.1016/j.jefas.2015.12.​002
publishDate 2016
dc.date.none.fl_str_mv 2016-06-01
dc.type.none.fl_str_mv info:eu-repo/semantics/article
info:eu-repo/semantics/publishedVersion
Peer-reviewed Article
format article
status_str publishedVersion
dc.identifier.none.fl_str_mv https://revistas.esan.edu.pe/index.php/jefas/article/view/151
url https://revistas.esan.edu.pe/index.php/jefas/article/view/151
dc.language.none.fl_str_mv spa
language spa
dc.relation.none.fl_str_mv https://revistas.esan.edu.pe/index.php/jefas/article/view/151/118
dc.rights.none.fl_str_mv Copyright (c) 2021 Journal of Economics, Finance and Administrative Science
https://creativecommons.org/licenses/by/4.0/
info:eu-repo/semantics/openAccess
rights_invalid_str_mv Copyright (c) 2021 Journal of Economics, Finance and Administrative Science
https://creativecommons.org/licenses/by/4.0/
eu_rights_str_mv openAccess
dc.format.none.fl_str_mv application/pdf
dc.publisher.none.fl_str_mv Universidad ESAN
publisher.none.fl_str_mv Universidad ESAN
dc.source.none.fl_str_mv Journal of Economics, Finance and Administrative Science; Vol. 21 No. 40 (2016): January - June; 30-38
Journal of Economics, Finance and Administrative Science; Vol. 21 Núm. 40 (2016): January - June; 30-38
2218-0648
2077-1886
reponame:Revistas - Universidad ESAN
instname:Universidad ESAN
instacron:ESAN
instname_str Universidad ESAN
instacron_str ESAN
institution ESAN
reponame_str Revistas - Universidad ESAN
collection Revistas - Universidad ESAN
repository.name.fl_str_mv
repository.mail.fl_str_mv
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