Graph theory approach to quantify uncertainty of performance measures
Autor(a) principal: | |
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Data de Publicação: | 2015 |
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/1822/35253 |
Resumo: | In this work, the performance measurement process is studied to quantify the uncertainty induced in the resulting performance measure (PM). To that end, the causes of uncertainty are identified, analysing the activities undertaken in the three following stages of the performance measurement process: design and implementation, data collection and record, and determination and analysis. A quantitative methodology based on graph theory and on the sources of uncertainty of the performance measurement process is used to calculate an uncertainty index to evaluate the level of uncertainty of a given PM or (key) performance indicator. An application example is presented. The quantification of PM uncertainty could contribute to better represent the risk associated with a given decision and also to improve the PM to increase its precision and reliability. |
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Repositório Científico de Acesso Aberto de Portugal (Repositórios Cientìficos) |
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Graph theory approach to quantify uncertainty of performance measuresData QualityUncertaintyGraph theoryPerformance MeasuresRisk determinationScience & TechnologyIn this work, the performance measurement process is studied to quantify the uncertainty induced in the resulting performance measure (PM). To that end, the causes of uncertainty are identified, analysing the activities undertaken in the three following stages of the performance measurement process: design and implementation, data collection and record, and determination and analysis. A quantitative methodology based on graph theory and on the sources of uncertainty of the performance measurement process is used to calculate an uncertainty index to evaluate the level of uncertainty of a given PM or (key) performance indicator. An application example is presented. The quantification of PM uncertainty could contribute to better represent the risk associated with a given decision and also to improve the PM to increase its precision and reliability.FCT – Fundação para a Ciência e Tecnologia within the Project Scope: PEst- OE/EEI/UI0319/2014.University of Montenegro. Center for QualityUniversidade do MinhoSousa, SérgioLopes, Isabel da SilvaNunes, Eusébio P.20152015-01-01T00:00:00Zinfo:eu-repo/semantics/publishedVersioninfo:eu-repo/semantics/articleapplication/pdfhttp://hdl.handle.net/1822/35253engSousa, S. D; Lopes, I.S. and Nunes, E. P., (2015), Graph theory approach to quantify uncertainty of performance measures, International Journal for Quality Research, Vol. 9 Iss1 pp37-50, ISSN 1800-6450.1800 - 6450http://www.ijqr.net/journal/v9-n1/3.pdfinfo: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:RCAAP2023-07-21T12:16:10Zoai:repositorium.sdum.uminho.pt:1822/35253Portal AgregadorONGhttps://www.rcaap.pt/oai/openaireopendoar:71602024-03-19T19:08:41.042915Repositório 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 |
Graph theory approach to quantify uncertainty of performance measures |
title |
Graph theory approach to quantify uncertainty of performance measures |
spellingShingle |
Graph theory approach to quantify uncertainty of performance measures Sousa, Sérgio Data Quality Uncertainty Graph theory Performance Measures Risk determination Science & Technology |
title_short |
Graph theory approach to quantify uncertainty of performance measures |
title_full |
Graph theory approach to quantify uncertainty of performance measures |
title_fullStr |
Graph theory approach to quantify uncertainty of performance measures |
title_full_unstemmed |
Graph theory approach to quantify uncertainty of performance measures |
title_sort |
Graph theory approach to quantify uncertainty of performance measures |
author |
Sousa, Sérgio |
author_facet |
Sousa, Sérgio Lopes, Isabel da Silva Nunes, Eusébio P. |
author_role |
author |
author2 |
Lopes, Isabel da Silva Nunes, Eusébio P. |
author2_role |
author author |
dc.contributor.none.fl_str_mv |
Universidade do Minho |
dc.contributor.author.fl_str_mv |
Sousa, Sérgio Lopes, Isabel da Silva Nunes, Eusébio P. |
dc.subject.por.fl_str_mv |
Data Quality Uncertainty Graph theory Performance Measures Risk determination Science & Technology |
topic |
Data Quality Uncertainty Graph theory Performance Measures Risk determination Science & Technology |
description |
In this work, the performance measurement process is studied to quantify the uncertainty induced in the resulting performance measure (PM). To that end, the causes of uncertainty are identified, analysing the activities undertaken in the three following stages of the performance measurement process: design and implementation, data collection and record, and determination and analysis. A quantitative methodology based on graph theory and on the sources of uncertainty of the performance measurement process is used to calculate an uncertainty index to evaluate the level of uncertainty of a given PM or (key) performance indicator. An application example is presented. The quantification of PM uncertainty could contribute to better represent the risk associated with a given decision and also to improve the PM to increase its precision and reliability. |
publishDate |
2015 |
dc.date.none.fl_str_mv |
2015 2015-01-01T00:00:00Z |
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/1822/35253 |
url |
http://hdl.handle.net/1822/35253 |
dc.language.iso.fl_str_mv |
eng |
language |
eng |
dc.relation.none.fl_str_mv |
Sousa, S. D; Lopes, I.S. and Nunes, E. P., (2015), Graph theory approach to quantify uncertainty of performance measures, International Journal for Quality Research, Vol. 9 Iss1 pp37-50, ISSN 1800-6450. 1800 - 6450 http://www.ijqr.net/journal/v9-n1/3.pdf |
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.publisher.none.fl_str_mv |
University of Montenegro. Center for Quality |
publisher.none.fl_str_mv |
University of Montenegro. Center for Quality |
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 |
|
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1799132509249732608 |