Crossing Human Factors Research and Business Intelligence
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/10400.26/35111 |
Resumo: | Starting from business intelligence (BI) reference models, this work proposes to extend the multi-dimensional data modelling approach to integrate human factors (HF)-related dimensions. The overall goal is to promote a fine grain understanding of the derived key performance indicators (KPIs) through an enhanced characterization of the operational level of work context. HF research has traditionally approached critical domains and complex socio-technical systems with a chief consideration of human situated action. Grounded on a review of the body of knowledge of the HF field, this work proposes the business intelligence for human factors (BI4HF) framework. It intends to provide guidance on pertinent data identification, collection methods, modelling, and integration within a BI project endeavour. BI4HF foundations are introduced, and a use case on a manufacturing industry organization is presented. The outcome of the enacted BI project referred in the use case allowed new analytical capabilities regarding newly derived and existing KPIs related to operational performance, providing insight into the value of the BI4HF framework. |
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Crossing Human Factors Research and Business IntelligenceStarting from business intelligence (BI) reference models, this work proposes to extend the multi-dimensional data modelling approach to integrate human factors (HF)-related dimensions. The overall goal is to promote a fine grain understanding of the derived key performance indicators (KPIs) through an enhanced characterization of the operational level of work context. HF research has traditionally approached critical domains and complex socio-technical systems with a chief consideration of human situated action. Grounded on a review of the body of knowledge of the HF field, this work proposes the business intelligence for human factors (BI4HF) framework. It intends to provide guidance on pertinent data identification, collection methods, modelling, and integration within a BI project endeavour. BI4HF foundations are introduced, and a use case on a manufacturing industry organization is presented. The outcome of the enacted BI project referred in the use case allowed new analytical capabilities regarding newly derived and existing KPIs related to operational performance, providing insight into the value of the BI4HF framework.Repositório ComumSapateiro, CláudioBernardo, Rui2021-02-01T16:06:55Z20202020-01-01T00:00:00Zinfo:eu-repo/semantics/publishedVersioninfo:eu-repo/semantics/articleapplication/pdfhttp://hdl.handle.net/10400.26/35111engSapateiro, C. M., & Bernardo, R. M. (2020). Crossing Human Factors Research and Business Intelligence. International Journal of Enterprise Information Systems (IJEIS), 16(3), 78-92.1548-111510.4018/IJEIS.2020070106metadata only accessinfo: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:RCAAP2023-11-21T09:55:57Zoai:comum.rcaap.pt:10400.26/35111Portal AgregadorONGhttps://www.rcaap.pt/oai/openaireopendoar:71602024-03-19T23:11:36.697489Repositório 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 |
Crossing Human Factors Research and Business Intelligence |
title |
Crossing Human Factors Research and Business Intelligence |
spellingShingle |
Crossing Human Factors Research and Business Intelligence Sapateiro, Cláudio |
title_short |
Crossing Human Factors Research and Business Intelligence |
title_full |
Crossing Human Factors Research and Business Intelligence |
title_fullStr |
Crossing Human Factors Research and Business Intelligence |
title_full_unstemmed |
Crossing Human Factors Research and Business Intelligence |
title_sort |
Crossing Human Factors Research and Business Intelligence |
author |
Sapateiro, Cláudio |
author_facet |
Sapateiro, Cláudio Bernardo, Rui |
author_role |
author |
author2 |
Bernardo, Rui |
author2_role |
author |
dc.contributor.none.fl_str_mv |
Repositório Comum |
dc.contributor.author.fl_str_mv |
Sapateiro, Cláudio Bernardo, Rui |
description |
Starting from business intelligence (BI) reference models, this work proposes to extend the multi-dimensional data modelling approach to integrate human factors (HF)-related dimensions. The overall goal is to promote a fine grain understanding of the derived key performance indicators (KPIs) through an enhanced characterization of the operational level of work context. HF research has traditionally approached critical domains and complex socio-technical systems with a chief consideration of human situated action. Grounded on a review of the body of knowledge of the HF field, this work proposes the business intelligence for human factors (BI4HF) framework. It intends to provide guidance on pertinent data identification, collection methods, modelling, and integration within a BI project endeavour. BI4HF foundations are introduced, and a use case on a manufacturing industry organization is presented. The outcome of the enacted BI project referred in the use case allowed new analytical capabilities regarding newly derived and existing KPIs related to operational performance, providing insight into the value of the BI4HF framework. |
publishDate |
2020 |
dc.date.none.fl_str_mv |
2020 2020-01-01T00:00:00Z 2021-02-01T16:06:55Z |
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/10400.26/35111 |
url |
http://hdl.handle.net/10400.26/35111 |
dc.language.iso.fl_str_mv |
eng |
language |
eng |
dc.relation.none.fl_str_mv |
Sapateiro, C. M., & Bernardo, R. M. (2020). Crossing Human Factors Research and Business Intelligence. International Journal of Enterprise Information Systems (IJEIS), 16(3), 78-92. 1548-1115 10.4018/IJEIS.2020070106 |
dc.rights.driver.fl_str_mv |
metadata only access info:eu-repo/semantics/openAccess |
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metadata only access |
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openAccess |
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application/pdf |
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Agência para a Sociedade do Conhecimento (UMIC) - FCT - Sociedade da Informação |
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RCAAP |
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RCAAP |
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Repositório Científico de Acesso Aberto de Portugal (Repositórios Cientìficos) |
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Repositório Científico de Acesso Aberto de Portugal (Repositórios Cientìficos) - Agência para a Sociedade do Conhecimento (UMIC) - FCT - Sociedade da Informação |
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