An improved LINMAP for multicriteria decision: designing customized incentive portfolios in an organization

This study proposes three new versions of the well-known linear programming technique for multidimensional preference analysis (LINMAP). LINMAP addresses the multi-criteria decision problem by analyzing individual diferences in preferences in relation to a set of prespecifed incentives in multidimen...

Full description

Autores:
Rubiano, Jessica
Nucamendi-Guillén, Samuel
Cordero Franco, Alvaro Eduardo
Rodríguez-Magaña, Alejandro
Tipo de recurso:
Article of investigation
Fecha de publicación:
2022
Institución:
Universidad de Ciencias Aplicadas y Ambientales U.D.C.A
Repositorio:
Repositorio Institucional UDCA
Idioma:
eng
OAI Identifier:
oai:repository.udca.edu.co:11158/4605
Acceso en línea:
https://repository.udca.edu.co/handle/11158/4605
https://repository.udca.edu.co
Palabra clave:
Análisis de datos
Toma de decisiones
Rights
openAccess
License
https://creativecommons.org/licenses/by-nc-sa/4.0/legalcode.es
id RepoUDCA2_18a224ef6cdf5d77775468f0e5361de5
oai_identifier_str oai:repository.udca.edu.co:11158/4605
network_acronym_str RepoUDCA2
network_name_str Repositorio Institucional UDCA
repository_id_str
dc.title.eng.fl_str_mv An improved LINMAP for multicriteria decision: designing customized incentive portfolios in an organization
title An improved LINMAP for multicriteria decision: designing customized incentive portfolios in an organization
spellingShingle An improved LINMAP for multicriteria decision: designing customized incentive portfolios in an organization
Análisis de datos
Toma de decisiones
title_short An improved LINMAP for multicriteria decision: designing customized incentive portfolios in an organization
title_full An improved LINMAP for multicriteria decision: designing customized incentive portfolios in an organization
title_fullStr An improved LINMAP for multicriteria decision: designing customized incentive portfolios in an organization
title_full_unstemmed An improved LINMAP for multicriteria decision: designing customized incentive portfolios in an organization
title_sort An improved LINMAP for multicriteria decision: designing customized incentive portfolios in an organization
dc.creator.fl_str_mv Rubiano, Jessica
Nucamendi-Guillén, Samuel
Cordero Franco, Alvaro Eduardo
Rodríguez-Magaña, Alejandro
dc.contributor.author.none.fl_str_mv Rubiano, Jessica
Nucamendi-Guillén, Samuel
Cordero Franco, Alvaro Eduardo
Rodríguez-Magaña, Alejandro
dc.subject.unesco.none.fl_str_mv Análisis de datos
Toma de decisiones
topic Análisis de datos
Toma de decisiones
description This study proposes three new versions of the well-known linear programming technique for multidimensional preference analysis (LINMAP). LINMAP addresses the multi-criteria decision problem by analyzing individual diferences in preferences in relation to a set of prespecifed incentives in multidimensional attribute space. The proposed models satisfy the decision-maker’s specifc needs, such as determining a fxed number of incentives to be active or assigning a minimum/maximum weight for the active incentives. The performance of the developed models is assessed using information from a case study in which a decision-maker desires to determine an optimal portfolio of incentives based on the preferences of individuals surveyed. Experimental results confrm that the proposed models could obtain solutions according to the decision-maker’s needs, yielding a better selection of incentives to activate and their corresponding distribution of the weights than those of the original LINMAP model. Moreover, the consistency of the proposed models is evaluated by performing a sensitivity analysis over database variations of the case study and comparing the outcomes with the results provided in the original case study. Overall, this work is promising when creating a design portfolio, considering individuals’ diferent preferences.
publishDate 2022
dc.date.accessioned.none.fl_str_mv 2022-04-26T17:12:20Z
dc.date.available.none.fl_str_mv 2022-04-26T17:12:20Z
dc.date.issued.none.fl_str_mv 2022
dc.type.spa.fl_str_mv Artículo de revista
dc.type.coar.spa.fl_str_mv http://purl.org/coar/resource_type/c_2df8fbb1
dc.type.driver.spa.fl_str_mv info:eu-repo/semantics/article
dc.type.version.spa.fl_str_mv info:eu-repo/semantics/publishedVersion
dc.type.content.spa.fl_str_mv Text
dc.type.redcol.spa.fl_str_mv http://purl.org/redcol/resource_type/ART
dc.type.coarversion.spa.fl_str_mv http://purl.org/coar/version/c_970fb48d4fbd8a85
format http://purl.org/coar/resource_type/c_2df8fbb1
status_str publishedVersion
dc.identifier.citation.spa.fl_str_mv Rubiano-Moreno, J., Nucamendi-Guillén, S., Cordero-Franco, A., & Rodríguez-Magaña, A. (2022). An improved LINMAP for multicriteria decision: Designing customized incentive portfolios in an organization. Operational Research, doi:10.1007/s12351-022-00698-x
dc.identifier.issn.spa.fl_str_mv 11092858
dc.identifier.uri.none.fl_str_mv https://repository.udca.edu.co/handle/11158/4605
dc.identifier.doi.none.fl_str_mv 10.1007/s12351-022-00698-x
dc.identifier.instname.spa.fl_str_mv Universidad de Ciencias Aplicadas y Ambientales
dc.identifier.reponame.spa.fl_str_mv UDCA
dc.identifier.repourl.spa.fl_str_mv https://repository.udca.edu.co
identifier_str_mv Rubiano-Moreno, J., Nucamendi-Guillén, S., Cordero-Franco, A., & Rodríguez-Magaña, A. (2022). An improved LINMAP for multicriteria decision: Designing customized incentive portfolios in an organization. Operational Research, doi:10.1007/s12351-022-00698-x
11092858
10.1007/s12351-022-00698-x
Universidad de Ciencias Aplicadas y Ambientales
UDCA
url https://repository.udca.edu.co/handle/11158/4605
https://repository.udca.edu.co
dc.language.iso.spa.fl_str_mv eng
language eng
dc.relation.indexed.spa.fl_str_mv N/A
dc.relation.citationedition.spa.fl_str_mv (Feb., 2022)
dc.relation.citationendpage.spa.fl_str_mv 32
dc.relation.citationstartpage.spa.fl_str_mv 1
dc.relation.ispartofjournal.spa.fl_str_mv Operational Research
dc.rights.eng.fl_str_mv https://creativecommons.org/licenses/by-nc-sa/4.0/legalcode.es
dc.rights.coar.fl_str_mv http://purl.org/coar/access_right/c_abf2
dc.rights.uri.spa.fl_str_mv https://creativecommons.org/licenses/by-nc-sa/4.0/
dc.rights.accessrights.spa.fl_str_mv info:eu-repo/semantics/openAccess
dc.rights.license.spa.fl_str_mv Atribución-NoComercial-CompartirIgual 4.0 Internacional (CC BY-NC-SA 4.0)
rights_invalid_str_mv https://creativecommons.org/licenses/by-nc-sa/4.0/legalcode.es
https://creativecommons.org/licenses/by-nc-sa/4.0/
Atribución-NoComercial-CompartirIgual 4.0 Internacional (CC BY-NC-SA 4.0)
http://purl.org/coar/access_right/c_abf2
eu_rights_str_mv openAccess
dc.format.mimetype.spa.fl_str_mv application/pdf
dc.source.spa.fl_str_mv https://udca.elogim.com:2074/article/10.1007/s12351-022-00698-x
institution Universidad de Ciencias Aplicadas y Ambientales U.D.C.A
bitstream.url.fl_str_mv https://repository.udca.edu.co/bitstreams/a75afebd-1f1f-43f0-b9e5-7c1de6267798/download
https://repository.udca.edu.co/bitstreams/05abe6da-d2f5-4253-9fc4-a762069b5b4a/download
https://repository.udca.edu.co/bitstreams/f6d8ff29-a866-4bda-8173-b45dc7828e02/download
https://repository.udca.edu.co/bitstreams/544f84cd-cde6-4a17-964f-840d52376a01/download
bitstream.checksum.fl_str_mv d16b5dedf5a56105716c6ceb0af7d5d8
f661acf14bedbf9f5d13897a0387e751
d9804854cf3f26f38f74b90cc3846126
09e224eecde9449a8bfd1744ae14663b
bitstream.checksumAlgorithm.fl_str_mv MD5
MD5
MD5
MD5
repository.name.fl_str_mv Repositorio - Universidad de Ciencias Aplicadas y Ambientales UDCA.
repository.mail.fl_str_mv bdigital@metabiblioteca.com
_version_ 1837099593534275584
spelling Rubiano, JessicaNucamendi-Guillén, SamuelCordero Franco, Alvaro EduardoRodríguez-Magaña, Alejandro2022-04-26T17:12:20Z2022-04-26T17:12:20Z2022Rubiano-Moreno, J., Nucamendi-Guillén, S., Cordero-Franco, A., & Rodríguez-Magaña, A. (2022). An improved LINMAP for multicriteria decision: Designing customized incentive portfolios in an organization. Operational Research, doi:10.1007/s12351-022-00698-x11092858https://repository.udca.edu.co/handle/11158/460510.1007/s12351-022-00698-xUniversidad de Ciencias Aplicadas y AmbientalesUDCAhttps://repository.udca.edu.coThis study proposes three new versions of the well-known linear programming technique for multidimensional preference analysis (LINMAP). LINMAP addresses the multi-criteria decision problem by analyzing individual diferences in preferences in relation to a set of prespecifed incentives in multidimensional attribute space. The proposed models satisfy the decision-maker’s specifc needs, such as determining a fxed number of incentives to be active or assigning a minimum/maximum weight for the active incentives. The performance of the developed models is assessed using information from a case study in which a decision-maker desires to determine an optimal portfolio of incentives based on the preferences of individuals surveyed. Experimental results confrm that the proposed models could obtain solutions according to the decision-maker’s needs, yielding a better selection of incentives to activate and their corresponding distribution of the weights than those of the original LINMAP model. Moreover, the consistency of the proposed models is evaluated by performing a sensitivity analysis over database variations of the case study and comparing the outcomes with the results provided in the original case study. Overall, this work is promising when creating a design portfolio, considering individuals’ diferent preferences.Incluye referencias bibliográficas.application/pdfenghttps://creativecommons.org/licenses/by-nc-sa/4.0/legalcode.eshttps://creativecommons.org/licenses/by-nc-sa/4.0/info:eu-repo/semantics/openAccessAtribución-NoComercial-CompartirIgual 4.0 Internacional (CC BY-NC-SA 4.0)http://purl.org/coar/access_right/c_abf2https://udca.elogim.com:2074/article/10.1007/s12351-022-00698-xAn improved LINMAP for multicriteria decision: designing customized incentive portfolios in an organizationArtículo de revistahttp://purl.org/coar/resource_type/c_2df8fbb1info:eu-repo/semantics/articleinfo:eu-repo/semantics/publishedVersionTexthttp://purl.org/redcol/resource_type/ARThttp://purl.org/coar/version/c_970fb48d4fbd8a85N/A(Feb., 2022)321Operational ResearchAnálisis de datosToma de decisionesPublicationORIGINALRubiano-Moreno2022_Article_AnImprovedLINMAPForMulticriter.pdfRubiano-Moreno2022_Article_AnImprovedLINMAPForMulticriter.pdfapplication/pdf1865311https://repository.udca.edu.co/bitstreams/a75afebd-1f1f-43f0-b9e5-7c1de6267798/downloadd16b5dedf5a56105716c6ceb0af7d5d8MD51LICENSElicense.txtlicense.txttext/plain; charset=utf-814775https://repository.udca.edu.co/bitstreams/05abe6da-d2f5-4253-9fc4-a762069b5b4a/downloadf661acf14bedbf9f5d13897a0387e751MD52TEXTRubiano-Moreno2022_Article_AnImprovedLINMAPForMulticriter.pdf.txtRubiano-Moreno2022_Article_AnImprovedLINMAPForMulticriter.pdf.txtExtracted texttext/plain81088https://repository.udca.edu.co/bitstreams/f6d8ff29-a866-4bda-8173-b45dc7828e02/downloadd9804854cf3f26f38f74b90cc3846126MD53THUMBNAILRubiano-Moreno2022_Article_AnImprovedLINMAPForMulticriter.pdf.jpgRubiano-Moreno2022_Article_AnImprovedLINMAPForMulticriter.pdf.jpgGenerated Thumbnailimage/jpeg10933https://repository.udca.edu.co/bitstreams/544f84cd-cde6-4a17-964f-840d52376a01/download09e224eecde9449a8bfd1744ae14663bMD5411158/4605oai:repository.udca.edu.co:11158/46052024-05-09 14:32:41.107https://creativecommons.org/licenses/by-nc-sa/4.0/https://creativecommons.org/licenses/by-nc-sa/4.0/legalcode.esopen.accesshttps://repository.udca.edu.coRepositorio - Universidad de Ciencias Aplicadas y Ambientales UDCA.bdigital@metabiblioteca.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