Identifying cognitive aspects to improve business process reengineering

Autores
Martín, Adriana Elba; Cechich, Alejandra
Año de publicación
2004
Idioma
inglés
Tipo de recurso
documento de conferencia
Estado
versión publicada
Descripción
Knowledge-intensive processes are widely used to recover from errors, handle exceptional cases and complaints, and to improve or adapt a process itself. In this context, evolved Business-Process Reengineering (BPR) techniques are changing to give some answers to this reality. In this paper, we identify some cognitive aspects used by traditional and recent reengineering models. We provide a framework highlighting how cognitive aspects might improve reengineering through knowledge and perception modelling.
Eje: I - Workshop de Ingeniería de Software y Base de Datos
Red de Universidades con Carreras en Informática (RedUNCI)
Materia
Ciencias Informáticas
base de datos
SOFTWARE ENGINEERING
Business Process Reengineering
Knowledge-Intensive Processes
Cognitive Science
Nivel de accesibilidad
acceso abierto
Condiciones de uso
http://creativecommons.org/licenses/by-nc-sa/2.5/ar/
Repositorio
SEDICI (UNLP)
Institución
Universidad Nacional de La Plata
OAI Identificador
oai:sedici.unlp.edu.ar:10915/22355
Acceder
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oai_identifier_str oai:sedici.unlp.edu.ar:10915/22355
network_acronym_str SEDICI
repository_id_str 1329
network_name_str SEDICI (UNLP)
spelling Identifying cognitive aspects to improve business process reengineeringMartín, Adriana ElbaCechich, AlejandraCiencias Informáticasbase de datosSOFTWARE ENGINEERINGBusiness Process ReengineeringKnowledge-Intensive ProcessesCognitive ScienceKnowledge-intensive processes are widely used to recover from errors, handle exceptional cases and complaints, and to improve or adapt a process itself. In this context, evolved Business-Process Reengineering (BPR) techniques are changing to give some answers to this reality. In this paper, we identify some cognitive aspects used by traditional and recent reengineering models. We provide a framework highlighting how cognitive aspects might improve reengineering through knowledge and perception modelling.Eje: I - Workshop de Ingeniería de Software y Base de DatosRed de Universidades con Carreras en Informática (RedUNCI)2004info:eu-repo/semantics/conferenceObjectinfo:eu-repo/semantics/publishedVersionObjeto de conferenciahttp://purl.org/coar/resource_type/c_5794info:ar-repo/semantics/documentoDeConferenciaapplication/pdfhttp://sedici.unlp.edu.ar/handle/10915/22355enginfo:eu-repo/semantics/openAccesshttp://creativecommons.org/licenses/by-nc-sa/2.5/ar/Creative Commons Attribution-NonCommercial-ShareAlike 2.5 Argentina (CC BY-NC-SA 2.5)reponame:SEDICI (UNLP)instname:Universidad Nacional de La Platainstacron:UNLP2025-09-03T10:27:48Zoai:sedici.unlp.edu.ar:10915/22355Institucionalhttp://sedici.unlp.edu.ar/Universidad públicaNo correspondehttp://sedici.unlp.edu.ar/oai/snrdalira@sedici.unlp.edu.arArgentinaNo correspondeNo correspondeNo correspondeopendoar:13292025-09-03 10:27:48.948SEDICI (UNLP) - Universidad Nacional de La Platafalse
dc.title.none.fl_str_mv Identifying cognitive aspects to improve business process reengineering
title Identifying cognitive aspects to improve business process reengineering
spellingShingle Identifying cognitive aspects to improve business process reengineering
Martín, Adriana Elba
Ciencias Informáticas
base de datos
SOFTWARE ENGINEERING
Business Process Reengineering
Knowledge-Intensive Processes
Cognitive Science
title_short Identifying cognitive aspects to improve business process reengineering
title_full Identifying cognitive aspects to improve business process reengineering
title_fullStr Identifying cognitive aspects to improve business process reengineering
title_full_unstemmed Identifying cognitive aspects to improve business process reengineering
title_sort Identifying cognitive aspects to improve business process reengineering
dc.creator.none.fl_str_mv Martín, Adriana Elba
Cechich, Alejandra
author Martín, Adriana Elba
author_facet Martín, Adriana Elba
Cechich, Alejandra
author_role author
author2 Cechich, Alejandra
author2_role author
dc.subject.none.fl_str_mv Ciencias Informáticas
base de datos
SOFTWARE ENGINEERING
Business Process Reengineering
Knowledge-Intensive Processes
Cognitive Science
topic Ciencias Informáticas
base de datos
SOFTWARE ENGINEERING
Business Process Reengineering
Knowledge-Intensive Processes
Cognitive Science
dc.description.none.fl_txt_mv Knowledge-intensive processes are widely used to recover from errors, handle exceptional cases and complaints, and to improve or adapt a process itself. In this context, evolved Business-Process Reengineering (BPR) techniques are changing to give some answers to this reality. In this paper, we identify some cognitive aspects used by traditional and recent reengineering models. We provide a framework highlighting how cognitive aspects might improve reengineering through knowledge and perception modelling.
Eje: I - Workshop de Ingeniería de Software y Base de Datos
Red de Universidades con Carreras en Informática (RedUNCI)
description Knowledge-intensive processes are widely used to recover from errors, handle exceptional cases and complaints, and to improve or adapt a process itself. In this context, evolved Business-Process Reengineering (BPR) techniques are changing to give some answers to this reality. In this paper, we identify some cognitive aspects used by traditional and recent reengineering models. We provide a framework highlighting how cognitive aspects might improve reengineering through knowledge and perception modelling.
publishDate 2004
dc.date.none.fl_str_mv 2004
dc.type.none.fl_str_mv info:eu-repo/semantics/conferenceObject
info:eu-repo/semantics/publishedVersion
Objeto de conferencia
http://purl.org/coar/resource_type/c_5794
info:ar-repo/semantics/documentoDeConferencia
format conferenceObject
status_str publishedVersion
dc.identifier.none.fl_str_mv http://sedici.unlp.edu.ar/handle/10915/22355
url http://sedici.unlp.edu.ar/handle/10915/22355
dc.language.none.fl_str_mv eng
language eng
dc.rights.none.fl_str_mv info:eu-repo/semantics/openAccess
http://creativecommons.org/licenses/by-nc-sa/2.5/ar/
Creative Commons Attribution-NonCommercial-ShareAlike 2.5 Argentina (CC BY-NC-SA 2.5)
eu_rights_str_mv openAccess
rights_invalid_str_mv http://creativecommons.org/licenses/by-nc-sa/2.5/ar/
Creative Commons Attribution-NonCommercial-ShareAlike 2.5 Argentina (CC BY-NC-SA 2.5)
dc.format.none.fl_str_mv application/pdf
dc.source.none.fl_str_mv reponame:SEDICI (UNLP)
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reponame_str SEDICI (UNLP)
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instname_str Universidad Nacional de La Plata
instacron_str UNLP
institution UNLP
repository.name.fl_str_mv SEDICI (UNLP) - Universidad Nacional de La Plata
repository.mail.fl_str_mv alira@sedici.unlp.edu.ar
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score 13.13397

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