Post-pandemic performance of micro, small and medium-sized enterprises: A Self-organizing Maps application

Autores
Martinez, Lisana Belén; Scherger, Valeria Paola; Orazi, Sofia
Año de publicación
2023
Idioma
inglés
Tipo de recurso
artículo
Estado
versión publicada
Descripción
This paper examines the post-pandemic performance of micro, small, and medium-sized firms using Self-Organizing Maps (SOMs), a type of Artificial Neural Network that groups patterns based on their similarities. The goal is to identify the key characteristics that enable firms to face market changes and overcome the effects of the global COVID-19 pandemic crisis. Considering business failure theory, a set of critical factors (including internal production processes, firm age, number of employees, resilience, financial resources, commercial strategies, management, and the impact of external factors) is used to assess the performance of Argentinian firms. The study categorizes these firms into four clusters based on their patterns. The results reveal a trade-off between a firm’s age and its number of employees, confirming that younger firms with fewer employees, limited financial resources, relatively weaker management, internal production process issues, and lower resilience tend to perform poorly, despite facing fewer impact of external factors. Consequently, the findings emphasize the significance of internal fundamentals and resilience in achieving success or avoiding failure. This highlights the effectiveness of SOM as a tool to visualize the characteristics that lead to successful paths and the survival of firms.
Fil: Martinez, Lisana Belén. Consejo Nacional de Investigaciones Científicas y Técnicas. Centro Científico Tecnológico Conicet - Bahía Blanca. Instituto de Investigaciones Económicas y Sociales del Sur. Universidad Nacional del Sur. Departamento de Economía. Instituto de Investigaciones Económicas y Sociales del Sur; Argentina. Provincia de Buenos Aires. Dirección General de Cultura y Educación. Universidad Provincial del Sudoeste; Argentina
Fil: Scherger, Valeria Paola. Consejo Nacional de Investigaciones Científicas y Técnicas. Centro Científico Tecnológico Conicet - Bahía Blanca. Instituto de Investigaciones Económicas y Sociales del Sur. Universidad Nacional del Sur. Departamento de Economía. Instituto de Investigaciones Económicas y Sociales del Sur; Argentina
Fil: Orazi, Sofia. Consejo Nacional de Investigaciones Científicas y Técnicas. Centro Científico Tecnológico Conicet - Bahía Blanca. Instituto de Investigaciones Económicas y Sociales del Sur. Universidad Nacional del Sur. Departamento de Economía. Instituto de Investigaciones Económicas y Sociales del Sur; Argentina
Materia
BUSINESS FAILURE
BUSINESS PERFORMANCE
COVID-19
SMES
SOM
Nivel de accesibilidad
acceso abierto
Condiciones de uso
https://creativecommons.org/licenses/by/2.5/ar/
Repositorio
CONICET Digital (CONICET)
Institución
Consejo Nacional de Investigaciones Científicas y Técnicas
OAI Identificador
oai:ri.conicet.gov.ar:11336/250304
Acceder
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network_name_str CONICET Digital (CONICET)
spelling Post-pandemic performance of micro, small and medium-sized enterprises: A Self-organizing Maps applicationMartinez, Lisana BelénScherger, Valeria PaolaOrazi, SofiaBUSINESS FAILUREBUSINESS PERFORMANCECOVID-19SMESSOMhttps://purl.org/becyt/ford/5.2https://purl.org/becyt/ford/5This paper examines the post-pandemic performance of micro, small, and medium-sized firms using Self-Organizing Maps (SOMs), a type of Artificial Neural Network that groups patterns based on their similarities. The goal is to identify the key characteristics that enable firms to face market changes and overcome the effects of the global COVID-19 pandemic crisis. Considering business failure theory, a set of critical factors (including internal production processes, firm age, number of employees, resilience, financial resources, commercial strategies, management, and the impact of external factors) is used to assess the performance of Argentinian firms. The study categorizes these firms into four clusters based on their patterns. The results reveal a trade-off between a firm’s age and its number of employees, confirming that younger firms with fewer employees, limited financial resources, relatively weaker management, internal production process issues, and lower resilience tend to perform poorly, despite facing fewer impact of external factors. Consequently, the findings emphasize the significance of internal fundamentals and resilience in achieving success or avoiding failure. This highlights the effectiveness of SOM as a tool to visualize the characteristics that lead to successful paths and the survival of firms.Fil: Martinez, Lisana Belén. Consejo Nacional de Investigaciones Científicas y Técnicas. Centro Científico Tecnológico Conicet - Bahía Blanca. Instituto de Investigaciones Económicas y Sociales del Sur. Universidad Nacional del Sur. Departamento de Economía. Instituto de Investigaciones Económicas y Sociales del Sur; Argentina. Provincia de Buenos Aires. Dirección General de Cultura y Educación. Universidad Provincial del Sudoeste; ArgentinaFil: Scherger, Valeria Paola. Consejo Nacional de Investigaciones Científicas y Técnicas. Centro Científico Tecnológico Conicet - Bahía Blanca. Instituto de Investigaciones Económicas y Sociales del Sur. Universidad Nacional del Sur. Departamento de Economía. Instituto de Investigaciones Económicas y Sociales del Sur; ArgentinaFil: Orazi, Sofia. Consejo Nacional de Investigaciones Científicas y Técnicas. Centro Científico Tecnológico Conicet - Bahía Blanca. Instituto de Investigaciones Económicas y Sociales del Sur. Universidad Nacional del Sur. Departamento de Economía. Instituto de Investigaciones Económicas y Sociales del Sur; ArgentinaTaylor & Francis2023-11-05info:eu-repo/semantics/articleinfo:eu-repo/semantics/publishedVersionhttp://purl.org/coar/resource_type/c_6501info:ar-repo/semantics/articuloapplication/pdfapplication/pdfapplication/pdfapplication/pdfapplication/pdfhttp://hdl.handle.net/11336/250304Martinez, Lisana Belén; Scherger, Valeria Paola; Orazi, Sofia; Post-pandemic performance of micro, small and medium-sized enterprises: A Self-organizing Maps application; Taylor & Francis; Cogent Business & Management; 10; 3; 5-11-2023; 1-132331-1975CONICET DigitalCONICETenginfo:eu-repo/semantics/altIdentifier/url/https://www.tandfonline.com/doi/full/10.1080/23311975.2023.2276944info:eu-repo/semantics/altIdentifier/doi/10.1080/23311975.2023.2276944info:eu-repo/semantics/openAccesshttps://creativecommons.org/licenses/by/2.5/ar/reponame:CONICET Digital (CONICET)instname:Consejo Nacional de Investigaciones Científicas y Técnicas2025-09-03T09:55:20Zoai:ri.conicet.gov.ar:11336/250304instacron:CONICETInstitucionalhttp://ri.conicet.gov.ar/Organismo científico-tecnológicoNo correspondehttp://ri.conicet.gov.ar/oai/requestdasensio@conicet.gov.ar; lcarlino@conicet.gov.arArgentinaNo correspondeNo correspondeNo correspondeopendoar:34982025-09-03 09:55:20.368CONICET Digital (CONICET) - Consejo Nacional de Investigaciones Científicas y Técnicasfalse
dc.title.none.fl_str_mv Post-pandemic performance of micro, small and medium-sized enterprises: A Self-organizing Maps application
title Post-pandemic performance of micro, small and medium-sized enterprises: A Self-organizing Maps application
spellingShingle Post-pandemic performance of micro, small and medium-sized enterprises: A Self-organizing Maps application
Martinez, Lisana Belén
BUSINESS FAILURE
BUSINESS PERFORMANCE
COVID-19
SMES
SOM
title_short Post-pandemic performance of micro, small and medium-sized enterprises: A Self-organizing Maps application
title_full Post-pandemic performance of micro, small and medium-sized enterprises: A Self-organizing Maps application
title_fullStr Post-pandemic performance of micro, small and medium-sized enterprises: A Self-organizing Maps application
title_full_unstemmed Post-pandemic performance of micro, small and medium-sized enterprises: A Self-organizing Maps application
title_sort Post-pandemic performance of micro, small and medium-sized enterprises: A Self-organizing Maps application
dc.creator.none.fl_str_mv Martinez, Lisana Belén
Scherger, Valeria Paola
Orazi, Sofia
author Martinez, Lisana Belén
author_facet Martinez, Lisana Belén
Scherger, Valeria Paola
Orazi, Sofia
author_role author
author2 Scherger, Valeria Paola
Orazi, Sofia
author2_role author
author
dc.subject.none.fl_str_mv BUSINESS FAILURE
BUSINESS PERFORMANCE
COVID-19
SMES
SOM
topic BUSINESS FAILURE
BUSINESS PERFORMANCE
COVID-19
SMES
SOM
purl_subject.fl_str_mv https://purl.org/becyt/ford/5.2
https://purl.org/becyt/ford/5
dc.description.none.fl_txt_mv This paper examines the post-pandemic performance of micro, small, and medium-sized firms using Self-Organizing Maps (SOMs), a type of Artificial Neural Network that groups patterns based on their similarities. The goal is to identify the key characteristics that enable firms to face market changes and overcome the effects of the global COVID-19 pandemic crisis. Considering business failure theory, a set of critical factors (including internal production processes, firm age, number of employees, resilience, financial resources, commercial strategies, management, and the impact of external factors) is used to assess the performance of Argentinian firms. The study categorizes these firms into four clusters based on their patterns. The results reveal a trade-off between a firm’s age and its number of employees, confirming that younger firms with fewer employees, limited financial resources, relatively weaker management, internal production process issues, and lower resilience tend to perform poorly, despite facing fewer impact of external factors. Consequently, the findings emphasize the significance of internal fundamentals and resilience in achieving success or avoiding failure. This highlights the effectiveness of SOM as a tool to visualize the characteristics that lead to successful paths and the survival of firms.
Fil: Martinez, Lisana Belén. Consejo Nacional de Investigaciones Científicas y Técnicas. Centro Científico Tecnológico Conicet - Bahía Blanca. Instituto de Investigaciones Económicas y Sociales del Sur. Universidad Nacional del Sur. Departamento de Economía. Instituto de Investigaciones Económicas y Sociales del Sur; Argentina. Provincia de Buenos Aires. Dirección General de Cultura y Educación. Universidad Provincial del Sudoeste; Argentina
Fil: Scherger, Valeria Paola. Consejo Nacional de Investigaciones Científicas y Técnicas. Centro Científico Tecnológico Conicet - Bahía Blanca. Instituto de Investigaciones Económicas y Sociales del Sur. Universidad Nacional del Sur. Departamento de Economía. Instituto de Investigaciones Económicas y Sociales del Sur; Argentina
Fil: Orazi, Sofia. Consejo Nacional de Investigaciones Científicas y Técnicas. Centro Científico Tecnológico Conicet - Bahía Blanca. Instituto de Investigaciones Económicas y Sociales del Sur. Universidad Nacional del Sur. Departamento de Economía. Instituto de Investigaciones Económicas y Sociales del Sur; Argentina
description This paper examines the post-pandemic performance of micro, small, and medium-sized firms using Self-Organizing Maps (SOMs), a type of Artificial Neural Network that groups patterns based on their similarities. The goal is to identify the key characteristics that enable firms to face market changes and overcome the effects of the global COVID-19 pandemic crisis. Considering business failure theory, a set of critical factors (including internal production processes, firm age, number of employees, resilience, financial resources, commercial strategies, management, and the impact of external factors) is used to assess the performance of Argentinian firms. The study categorizes these firms into four clusters based on their patterns. The results reveal a trade-off between a firm’s age and its number of employees, confirming that younger firms with fewer employees, limited financial resources, relatively weaker management, internal production process issues, and lower resilience tend to perform poorly, despite facing fewer impact of external factors. Consequently, the findings emphasize the significance of internal fundamentals and resilience in achieving success or avoiding failure. This highlights the effectiveness of SOM as a tool to visualize the characteristics that lead to successful paths and the survival of firms.
publishDate 2023
dc.date.none.fl_str_mv 2023-11-05
dc.type.none.fl_str_mv info:eu-repo/semantics/article
info:eu-repo/semantics/publishedVersion
http://purl.org/coar/resource_type/c_6501
info:ar-repo/semantics/articulo
format article
status_str publishedVersion
dc.identifier.none.fl_str_mv http://hdl.handle.net/11336/250304
Martinez, Lisana Belén; Scherger, Valeria Paola; Orazi, Sofia; Post-pandemic performance of micro, small and medium-sized enterprises: A Self-organizing Maps application; Taylor & Francis; Cogent Business & Management; 10; 3; 5-11-2023; 1-13
2331-1975
CONICET Digital
CONICET
url http://hdl.handle.net/11336/250304
identifier_str_mv Martinez, Lisana Belén; Scherger, Valeria Paola; Orazi, Sofia; Post-pandemic performance of micro, small and medium-sized enterprises: A Self-organizing Maps application; Taylor & Francis; Cogent Business & Management; 10; 3; 5-11-2023; 1-13
2331-1975
CONICET Digital
CONICET
dc.language.none.fl_str_mv eng
language eng
dc.relation.none.fl_str_mv info:eu-repo/semantics/altIdentifier/url/https://www.tandfonline.com/doi/full/10.1080/23311975.2023.2276944
info:eu-repo/semantics/altIdentifier/doi/10.1080/23311975.2023.2276944
dc.rights.none.fl_str_mv info:eu-repo/semantics/openAccess
https://creativecommons.org/licenses/by/2.5/ar/
eu_rights_str_mv openAccess
rights_invalid_str_mv https://creativecommons.org/licenses/by/2.5/ar/
dc.format.none.fl_str_mv application/pdf
application/pdf
application/pdf
application/pdf
application/pdf
dc.publisher.none.fl_str_mv Taylor & Francis
publisher.none.fl_str_mv Taylor & Francis
dc.source.none.fl_str_mv reponame:CONICET Digital (CONICET)
instname:Consejo Nacional de Investigaciones Científicas y Técnicas
reponame_str CONICET Digital (CONICET)
collection CONICET Digital (CONICET)
instname_str Consejo Nacional de Investigaciones Científicas y Técnicas
repository.name.fl_str_mv CONICET Digital (CONICET) - Consejo Nacional de Investigaciones Científicas y Técnicas
repository.mail.fl_str_mv dasensio@conicet.gov.ar; lcarlino@conicet.gov.ar
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score 13.13397

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