Ranking strategic objectives in a strategy map based on logarithmic fuzzy preference programming and similarity method
Autor(a) principal: | |
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Data de Publicação: | 2019 |
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/10362/99128 |
Resumo: | This paper aims to rank strategic objectives in a strategy map to improve the efficiency of strategy implementation. Objectives are ranked based on strategic destinations using the combination of Logarithmic Fuzzy Preference Programming (LFPP) and similarity method. In the first step, the weight of strategic destinations is obtained using LFPP technique; then objectives are ranked by similarity method. Similarity method uses the concept of alternative gradient and magnitude for effectively solving the general multi-criteria analysis problem. Finally, objectives are ranked in an actual strategy map. As a practical and efficient tool, the proposed approach can assist managers and decision-makers in drawing more efficient output from strategy maps. |
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Ranking strategic objectives in a strategy map based on logarithmic fuzzy preference programming and similarity methodBalanced Scorecard (BSC)Logarithmic Fuzzy Preference Programming (LFPP)similarity methodStrategy mapManagement Information SystemsIndustrial and Manufacturing EngineeringManagement of Technology and InnovationSDG 9 - Industry, Innovation, and InfrastructureThis paper aims to rank strategic objectives in a strategy map to improve the efficiency of strategy implementation. Objectives are ranked based on strategic destinations using the combination of Logarithmic Fuzzy Preference Programming (LFPP) and similarity method. In the first step, the weight of strategic destinations is obtained using LFPP technique; then objectives are ranked by similarity method. Similarity method uses the concept of alternative gradient and magnitude for effectively solving the general multi-criteria analysis problem. Finally, objectives are ranked in an actual strategy map. As a practical and efficient tool, the proposed approach can assist managers and decision-makers in drawing more efficient output from strategy maps.DEMI - Departamento de Engenharia Mecânica e IndustrialUNIDEMI - Unidade de Investigação e Desenvolvimento em Engenharia Mecânica e IndustrialRUNSafari, HosseinKhanmohammadi, EhsanMaleki, MeysamCruz-Machado, VirgilioShevtshenko, Eduard2020-06-10T00:39:13Z2019-09-012019-09-01T00:00:00Zinfo:eu-repo/semantics/publishedVersioninfo:eu-repo/semantics/article9application/pdfhttp://hdl.handle.net/10362/99128eng2299-0461PURE: 16168416https://doi.org/10.1515/mspe-2019-0025info: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:RCAAP2024-03-11T04:46:10Zoai:run.unl.pt:10362/99128Portal AgregadorONGhttps://www.rcaap.pt/oai/openaireopendoar:71602024-03-20T03:39:07.811008Repositório 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 |
Ranking strategic objectives in a strategy map based on logarithmic fuzzy preference programming and similarity method |
title |
Ranking strategic objectives in a strategy map based on logarithmic fuzzy preference programming and similarity method |
spellingShingle |
Ranking strategic objectives in a strategy map based on logarithmic fuzzy preference programming and similarity method Safari, Hossein Balanced Scorecard (BSC) Logarithmic Fuzzy Preference Programming (LFPP) similarity method Strategy map Management Information Systems Industrial and Manufacturing Engineering Management of Technology and Innovation SDG 9 - Industry, Innovation, and Infrastructure |
title_short |
Ranking strategic objectives in a strategy map based on logarithmic fuzzy preference programming and similarity method |
title_full |
Ranking strategic objectives in a strategy map based on logarithmic fuzzy preference programming and similarity method |
title_fullStr |
Ranking strategic objectives in a strategy map based on logarithmic fuzzy preference programming and similarity method |
title_full_unstemmed |
Ranking strategic objectives in a strategy map based on logarithmic fuzzy preference programming and similarity method |
title_sort |
Ranking strategic objectives in a strategy map based on logarithmic fuzzy preference programming and similarity method |
author |
Safari, Hossein |
author_facet |
Safari, Hossein Khanmohammadi, Ehsan Maleki, Meysam Cruz-Machado, Virgilio Shevtshenko, Eduard |
author_role |
author |
author2 |
Khanmohammadi, Ehsan Maleki, Meysam Cruz-Machado, Virgilio Shevtshenko, Eduard |
author2_role |
author author author author |
dc.contributor.none.fl_str_mv |
DEMI - Departamento de Engenharia Mecânica e Industrial UNIDEMI - Unidade de Investigação e Desenvolvimento em Engenharia Mecânica e Industrial RUN |
dc.contributor.author.fl_str_mv |
Safari, Hossein Khanmohammadi, Ehsan Maleki, Meysam Cruz-Machado, Virgilio Shevtshenko, Eduard |
dc.subject.por.fl_str_mv |
Balanced Scorecard (BSC) Logarithmic Fuzzy Preference Programming (LFPP) similarity method Strategy map Management Information Systems Industrial and Manufacturing Engineering Management of Technology and Innovation SDG 9 - Industry, Innovation, and Infrastructure |
topic |
Balanced Scorecard (BSC) Logarithmic Fuzzy Preference Programming (LFPP) similarity method Strategy map Management Information Systems Industrial and Manufacturing Engineering Management of Technology and Innovation SDG 9 - Industry, Innovation, and Infrastructure |
description |
This paper aims to rank strategic objectives in a strategy map to improve the efficiency of strategy implementation. Objectives are ranked based on strategic destinations using the combination of Logarithmic Fuzzy Preference Programming (LFPP) and similarity method. In the first step, the weight of strategic destinations is obtained using LFPP technique; then objectives are ranked by similarity method. Similarity method uses the concept of alternative gradient and magnitude for effectively solving the general multi-criteria analysis problem. Finally, objectives are ranked in an actual strategy map. As a practical and efficient tool, the proposed approach can assist managers and decision-makers in drawing more efficient output from strategy maps. |
publishDate |
2019 |
dc.date.none.fl_str_mv |
2019-09-01 2019-09-01T00:00:00Z 2020-06-10T00:39:13Z |
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/10362/99128 |
url |
http://hdl.handle.net/10362/99128 |
dc.language.iso.fl_str_mv |
eng |
language |
eng |
dc.relation.none.fl_str_mv |
2299-0461 PURE: 16168416 https://doi.org/10.1515/mspe-2019-0025 |
dc.rights.driver.fl_str_mv |
info:eu-repo/semantics/openAccess |
eu_rights_str_mv |
openAccess |
dc.format.none.fl_str_mv |
9 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 |
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1799138007534534656 |