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Process Mining for IS Project Success Factors Management: A proposal

2021-12Comunicação em conferência Acesso aberto
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datacite.subject.fosCiências Naturais::Ciências da Computação e da Informação
datacite.subject.sdg07:Energias Renováveis e Acessíveis
datacite.subject.sdg09:Indústria, Inovação e Infraestruturas
datacite.subject.sdg11:Cidades e Comunidades Sustentáveis
dc.contributor.authorPedrosa, Joana
dc.contributor.authorVarajão, João
dc.contributor.authorMagalhaes, Luis Gonzaga
dc.contributor.authorMartinho, Ricardo
dc.date.accessioned2026-04-10T15:11:46Z
dc.date.available2026-04-10T15:11:46Z
dc.date.issued2021-12
dc.description32nd Australasian Conference on Information Systems: Information Systems for a Sustainable Future, Connectedness, and Social Good, ACIS 2021; Conference date - 6 December 2021 - 10 December 2021; Conference code - 192482
dc.description.abstractResearch on Success Factors (SF) of Information Systems (IS) projects carried out over the last decades has resulted in a vast literature. However, extant studies typically aim to identify and list generic SF for projects, denoting a static perspective, with few concerns of practical nature regarding their use as management tools to support decisions throughout the projects’ lifecycle. On the other hand, process mining has been used to discover, analyze, and improve project management processes. In this paper, we propose a new approach that involves relating the performance of those processes with SF in IS projects. By using process mining, the aim is to automatically extract and manage SF in projects, measure processes performance, and provide project managers with information on how SF correlate with performance. This will provide managers with enhanced information regarding status and improvement opportunities for current and future projects. The main purpose is to contribute to the project management theory and practice by providing a decision support system that can associate performance with IS projects’ SF automatically obtained from internal and external data sources.eng
dc.description.sponsorshipThis work has been supported by FCT – Fundação para a Ciência e Tecnologia within the R&D Units Project Scope: UIDB/00319/2020.
dc.identifier.citationPedrosa, Joana; Varajão, João; Magalhaes, Luis Gonzaga; and Martinho, Ricardo, "Process Mining for IS Project Success Factors Management: A proposal" (2021). ACIS 2021 Proceedings. 58. https://aisel.aisnet.org/acis2021/58.
dc.identifier.urihttp://hdl.handle.net/10400.8/16098
dc.language.isoeng
dc.peerreviewedyes
dc.publisherAssociation for Information Systems
dc.relationALGORITMI Research Center
dc.relation.hasversionhttps://aisel.aisnet.org/acis2021/58/
dc.rights.urihttp://creativecommons.org/licenses/by-nc/4.0/
dc.subjectInformation System
dc.subjectProcess Decision Support System
dc.subjectProcess Mining
dc.subjectProject Success
dc.subjectSuccess Factors
dc.titleProcess Mining for IS Project Success Factors Management: A proposaleng
dc.typeconference paper
dspace.entity.typePublication
oaire.awardNumberUIDB/00319/2020
oaire.awardTitleALGORITMI Research Center
oaire.awardURIhttp://hdl.handle.net/10400.8/14247
oaire.citation.conferenceDate2021-12
oaire.citation.conferencePlaceSydney, Australia
oaire.citation.endPage8
oaire.citation.startPage1
oaire.citation.titleACIS 2021 - Australasian Conference on Information Systems, Proceedings
oaire.fundingStreamConcurso de avaliação no âmbito do Programa Plurianual de Financiamento de Unidades de I&D (2017/2018) - Financiamento Base
oaire.versionhttp://purl.org/coar/version/c_970fb48d4fbd8a85
person.familyNameMartinho
person.givenNameRicardo
person.identifier.ciencia-idF51E-9BB5-EF92
person.identifier.orcid0000-0003-1157-7510
person.identifier.ridK-8277-2013
person.identifier.scopus-author-id25823103700
relation.isAuthorOfPublicationb2a74e46-f06c-4dcd-8c64-8f78f1d55440
relation.isAuthorOfPublication.latestForDiscoveryb2a74e46-f06c-4dcd-8c64-8f78f1d55440
relation.isProjectOfPublication69ebc407-cbd1-4057-9da5-59997a73bcb9
relation.isProjectOfPublication.latestForDiscovery69ebc407-cbd1-4057-9da5-59997a73bcb9

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Research on Success Factors (SF) of Information Systems (IS) projects carried out over the last decades has resulted in a vast literature. However, extant studies typically aim to identify and list generic SF for projects, denoting a static perspective, with few concerns of practical nature regarding their use as management tools to support decisions throughout the projects’ lifecycle. On the other hand, process mining has been used to discover, analyze, and improve project management processes. In this paper, we propose a new approach that involves relating the performance of those processes with SF in IS projects. By using process mining, the aim is to automatically extract and manage SF in projects, measure processes performance, and provide project managers with information on how SF correlate with performance. This will provide managers with enhanced information regarding status and improvement opportunities for current and future projects. The main purpose is to contribute to the project management theory and practice by providing a decision support system that can associate performance with IS projects’ SF automatically obtained from internal and external data sources.
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