Maximizing Learning Through Cohesion: Contributions From a Nonlinear Approach
Autor(a) principal: | |
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Data de Publicação: | 2020 |
Outros Autores: | , , |
Tipo de documento: | Artigo |
Idioma: | eng |
Título da fonte: | Repositório Científico de Acesso Aberto de Portugal (Repositórios Cientìficos) |
Texto Completo: | http://hdl.handle.net/10316/91186 https://doi.org/10.1177/1046496420944488 |
Resumo: | This study explores the relationship between team cohesion and team learning by adopting a nonlinear approach. A quantitative study with a sample composed of 82 organizational teams was conducted. Radial Basis Function (RBF) interpolation models were used and results showed that the best predicting ability was obtained by the Thin Plate RBF model, which revealed that an increase in both dimensions of cohesion leads to an increase in team learning up to a certain threshold. Moreover, our results showed that the maximum value of team learning is obtained at higher values of task cohesion and moderate values of social cohesion. |
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Repositório Científico de Acesso Aberto de Portugal (Repositórios Cientìficos) |
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7160 |
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Maximizing Learning Through Cohesion: Contributions From a Nonlinear ApproachTeam cohesionTeam learningNonlinear approachRadial basis functionsThis study explores the relationship between team cohesion and team learning by adopting a nonlinear approach. A quantitative study with a sample composed of 82 organizational teams was conducted. Radial Basis Function (RBF) interpolation models were used and results showed that the best predicting ability was obtained by the Thin Plate RBF model, which revealed that an increase in both dimensions of cohesion leads to an increase in team learning up to a certain threshold. Moreover, our results showed that the maximum value of team learning is obtained at higher values of task cohesion and moderate values of social cohesion.Sage2020info:eu-repo/semantics/publishedVersioninfo:eu-repo/semantics/articlehttp://hdl.handle.net/10316/91186http://hdl.handle.net/10316/91186https://doi.org/10.1177/1046496420944488eng1046-49641552-8278https://journals.sagepub.com/doi/10.1177/1046496420944488Dimas, Isabel DórdioLourenço, Paulo Renato Martins Ribeiro da SilvaRebelo, TeresaRocha, Humbertoinfo: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:RCAAP2022-05-25T06:13:54Zoai:estudogeral.uc.pt:10316/91186Portal AgregadorONGhttps://www.rcaap.pt/oai/openaireopendoar:71602024-03-19T21:11:07.330768Repositório 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 |
Maximizing Learning Through Cohesion: Contributions From a Nonlinear Approach |
title |
Maximizing Learning Through Cohesion: Contributions From a Nonlinear Approach |
spellingShingle |
Maximizing Learning Through Cohesion: Contributions From a Nonlinear Approach Dimas, Isabel Dórdio Team cohesion Team learning Nonlinear approach Radial basis functions |
title_short |
Maximizing Learning Through Cohesion: Contributions From a Nonlinear Approach |
title_full |
Maximizing Learning Through Cohesion: Contributions From a Nonlinear Approach |
title_fullStr |
Maximizing Learning Through Cohesion: Contributions From a Nonlinear Approach |
title_full_unstemmed |
Maximizing Learning Through Cohesion: Contributions From a Nonlinear Approach |
title_sort |
Maximizing Learning Through Cohesion: Contributions From a Nonlinear Approach |
author |
Dimas, Isabel Dórdio |
author_facet |
Dimas, Isabel Dórdio Lourenço, Paulo Renato Martins Ribeiro da Silva Rebelo, Teresa Rocha, Humberto |
author_role |
author |
author2 |
Lourenço, Paulo Renato Martins Ribeiro da Silva Rebelo, Teresa Rocha, Humberto |
author2_role |
author author author |
dc.contributor.author.fl_str_mv |
Dimas, Isabel Dórdio Lourenço, Paulo Renato Martins Ribeiro da Silva Rebelo, Teresa Rocha, Humberto |
dc.subject.por.fl_str_mv |
Team cohesion Team learning Nonlinear approach Radial basis functions |
topic |
Team cohesion Team learning Nonlinear approach Radial basis functions |
description |
This study explores the relationship between team cohesion and team learning by adopting a nonlinear approach. A quantitative study with a sample composed of 82 organizational teams was conducted. Radial Basis Function (RBF) interpolation models were used and results showed that the best predicting ability was obtained by the Thin Plate RBF model, which revealed that an increase in both dimensions of cohesion leads to an increase in team learning up to a certain threshold. Moreover, our results showed that the maximum value of team learning is obtained at higher values of task cohesion and moderate values of social cohesion. |
publishDate |
2020 |
dc.date.none.fl_str_mv |
2020 |
dc.type.status.fl_str_mv |
info:eu-repo/semantics/publishedVersion |
dc.type.driver.fl_str_mv |
info:eu-repo/semantics/article |
format |
article |
status_str |
publishedVersion |
dc.identifier.uri.fl_str_mv |
http://hdl.handle.net/10316/91186 http://hdl.handle.net/10316/91186 https://doi.org/10.1177/1046496420944488 |
url |
http://hdl.handle.net/10316/91186 https://doi.org/10.1177/1046496420944488 |
dc.language.iso.fl_str_mv |
eng |
language |
eng |
dc.relation.none.fl_str_mv |
1046-4964 1552-8278 https://journals.sagepub.com/doi/10.1177/1046496420944488 |
dc.rights.driver.fl_str_mv |
info:eu-repo/semantics/openAccess |
eu_rights_str_mv |
openAccess |
dc.publisher.none.fl_str_mv |
Sage |
publisher.none.fl_str_mv |
Sage |
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 |
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1799134008235261952 |