Why businesses Ssucceed: financial and non-financial determinants
Autor(a) principal: | |
---|---|
Data de Publicação: | 2023 |
Tipo de documento: | Dissertação |
Idioma: | eng |
Título da fonte: | Repositório Científico de Acesso Aberto de Portugal (Repositórios Cientìficos) |
Texto Completo: | http://hdl.handle.net/10362/162776 |
Resumo: | Micro, small and medium enterprises correspond to 99.9% of non-financial firms in Portugal. These ventures suffer severely from internal and external factors that difficult their maintenance in the market. Matching data from Orbis and Quadros de Pessoal, the current paper studies how financial and non-financial dimensions contribute to the success of a business. Following a logistic regression approach, the designed prediction model precisely forecasts 95.65% and 77.61% of companies failing within one and five years after inception, respectively. It is also able to describe 72.14% of successful firms. The results uncover important insights for different stakeholders in the economy. |
id |
RCAP_12ca223cf51555d05c8f579842d9230f |
---|---|
oai_identifier_str |
oai:run.unl.pt:10362/162776 |
network_acronym_str |
RCAP |
network_name_str |
Repositório Científico de Acesso Aberto de Portugal (Repositórios Cientìficos) |
repository_id_str |
7160 |
spelling |
Why businesses Ssucceed: financial and non-financial determinantsSmesPrediction modelNon-financial determinantsLogistic regressionDomínio/Área Científica::Ciências Sociais::Economia e GestãoMicro, small and medium enterprises correspond to 99.9% of non-financial firms in Portugal. These ventures suffer severely from internal and external factors that difficult their maintenance in the market. Matching data from Orbis and Quadros de Pessoal, the current paper studies how financial and non-financial dimensions contribute to the success of a business. Following a logistic regression approach, the designed prediction model precisely forecasts 95.65% and 77.61% of companies failing within one and five years after inception, respectively. It is also able to describe 72.14% of successful firms. The results uncover important insights for different stakeholders in the economy.Brinca, PedroRUNJoão Mário De Almeida Caetano2024-01-26T15:48:50Z2023-01-192023-01-192023-01-19T00:00:00Zinfo:eu-repo/semantics/publishedVersioninfo:eu-repo/semantics/masterThesisapplication/pdfhttp://hdl.handle.net/10362/162776TID:203314689enginfo:eu-repo/semantics/openAccessreponame:Repositório Científico de Acesso Aberto de Portugal (Repositórios Cientìficos)instname:Agência para a Sociedade do Conhecimento (UMIC) - FCT - Sociedade da Informaçãoinstacron:RCAAP2024-03-11T05:45:48Zoai:run.unl.pt:10362/162776Portal AgregadorONGhttps://www.rcaap.pt/oai/openaireopendoar:71602024-03-20T03:59:05.366608Repositório Científico de Acesso Aberto de Portugal (Repositórios Cientìficos) - Agência para a Sociedade do Conhecimento (UMIC) - FCT - Sociedade da Informaçãofalse |
dc.title.none.fl_str_mv |
Why businesses Ssucceed: financial and non-financial determinants |
title |
Why businesses Ssucceed: financial and non-financial determinants |
spellingShingle |
Why businesses Ssucceed: financial and non-financial determinants João Mário De Almeida Caetano Smes Prediction model Non-financial determinants Logistic regression Domínio/Área Científica::Ciências Sociais::Economia e Gestão |
title_short |
Why businesses Ssucceed: financial and non-financial determinants |
title_full |
Why businesses Ssucceed: financial and non-financial determinants |
title_fullStr |
Why businesses Ssucceed: financial and non-financial determinants |
title_full_unstemmed |
Why businesses Ssucceed: financial and non-financial determinants |
title_sort |
Why businesses Ssucceed: financial and non-financial determinants |
author |
João Mário De Almeida Caetano |
author_facet |
João Mário De Almeida Caetano |
author_role |
author |
dc.contributor.none.fl_str_mv |
Brinca, Pedro RUN |
dc.contributor.author.fl_str_mv |
João Mário De Almeida Caetano |
dc.subject.por.fl_str_mv |
Smes Prediction model Non-financial determinants Logistic regression Domínio/Área Científica::Ciências Sociais::Economia e Gestão |
topic |
Smes Prediction model Non-financial determinants Logistic regression Domínio/Área Científica::Ciências Sociais::Economia e Gestão |
description |
Micro, small and medium enterprises correspond to 99.9% of non-financial firms in Portugal. These ventures suffer severely from internal and external factors that difficult their maintenance in the market. Matching data from Orbis and Quadros de Pessoal, the current paper studies how financial and non-financial dimensions contribute to the success of a business. Following a logistic regression approach, the designed prediction model precisely forecasts 95.65% and 77.61% of companies failing within one and five years after inception, respectively. It is also able to describe 72.14% of successful firms. The results uncover important insights for different stakeholders in the economy. |
publishDate |
2023 |
dc.date.none.fl_str_mv |
2023-01-19 2023-01-19 2023-01-19T00:00:00Z 2024-01-26T15:48:50Z |
dc.type.status.fl_str_mv |
info:eu-repo/semantics/publishedVersion |
dc.type.driver.fl_str_mv |
info:eu-repo/semantics/masterThesis |
format |
masterThesis |
status_str |
publishedVersion |
dc.identifier.uri.fl_str_mv |
http://hdl.handle.net/10362/162776 TID:203314689 |
url |
http://hdl.handle.net/10362/162776 |
identifier_str_mv |
TID:203314689 |
dc.language.iso.fl_str_mv |
eng |
language |
eng |
dc.rights.driver.fl_str_mv |
info:eu-repo/semantics/openAccess |
eu_rights_str_mv |
openAccess |
dc.format.none.fl_str_mv |
application/pdf |
dc.source.none.fl_str_mv |
reponame:Repositório Científico de Acesso Aberto de Portugal (Repositórios Cientìficos) instname:Agência para a Sociedade do Conhecimento (UMIC) - FCT - Sociedade da Informação instacron:RCAAP |
instname_str |
Agência para a Sociedade do Conhecimento (UMIC) - FCT - Sociedade da Informação |
instacron_str |
RCAAP |
institution |
RCAAP |
reponame_str |
Repositório Científico de Acesso Aberto de Portugal (Repositórios Cientìficos) |
collection |
Repositório Científico de Acesso Aberto de Portugal (Repositórios Cientìficos) |
repository.name.fl_str_mv |
Repositório Científico de Acesso Aberto de Portugal (Repositórios Cientìficos) - Agência para a Sociedade do Conhecimento (UMIC) - FCT - Sociedade da Informação |
repository.mail.fl_str_mv |
|
_version_ |
1799138171002290176 |