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Measuring project performance by applying social network analyses

dc.contributor.authorNunes, Marco
dc.contributor.authorAbreu, António
dc.contributor.authorBagnjuk, Jelena
dc.contributor.authorTiedtke, Jörn
dc.date.accessioned2022-07-11T10:54:28Z
dc.date.available2022-07-11T10:54:28Z
dc.date.issued2021-06
dc.description.abstractIt is often argued that the core of organizational success is efficient collaboration. Some authors even posit that efficient collaboration is more important to organizational innovation and performance than individual skills or expertise. However, the lack of efficient models to manage collaboration properly is a major constraint for organizations to profit from internal and external collaborative initiatives. Currently, much of the collaboration in organizations occurs through virtual network channels, such as e-mail, Yammer, Jabber, Microsoft Teams, Skype, and Zoom. These are even more important in situations where different time zones and even threats of a pandemic constrain face-to-face human interactions. This work introduces a multidisciplinary heuristic model developed based on project risk management and social network analysis centrality metrics graph-theory to quantitatively measure dynamic organizational collaboration in the project environment. A case study illustrates the proposed model's implementation and application in a real virtual project organizational context. The major benefit of applying this proposed model is that it enables organizations to quantitatively measure different collaborative, organizational, and dynamic behavioral patterns, which can later correlate with organizational outcomes. The model analyzes three collaborative project dimensions: network collaboration cohesion evolution, network collaboration degree evolution, and network team set variability evolution. This provides organizations an innovative approach to understand and manage possible collaborative project risks that may emerge as projects are delivered. Organizations can use the proposed model to identify projects' critical success factors by comparing successful and unsuccessful delivered projects' dynamic behaviors if a substantial number of both project types are analyzed. The proposed model also enables organizations to make decisions with more information regarding the support for changes in observed collaborative patterns as demonstrated by statistical models in general, and linear regressions in particular. Further, the proposed model provides organizations with a completely bias-free data-collection process that eliminates organizational downtime. Finally, applying the proposed model in organizations will reduce or eliminate the risks associated with virtual collaborative dynamics, leading to the optimized use of resources; this will transform organizations to become more lean-oriented and significantly contribute to economic, social, and environmental global sustainability.pt_PT
dc.description.versioninfo:eu-repo/semantics/publishedVersionpt_PT
dc.identifier.citationNUNES, Marco; [et al] – Measuring project performance by applying social network analyses. International Journal of Innovation Studies. ISSN 2096-2487. Vol. 5, N.º 2 (2021), pp. 35-55.pt_PT
dc.identifier.doi10.1016/j.ijis.2021.05.001pt_PT
dc.identifier.issn2096-2487
dc.identifier.urihttp://hdl.handle.net/10400.21/14815
dc.language.isoengpt_PT
dc.peerreviewedyespt_PT
dc.publisherElsevierpt_PT
dc.relation.publisherversionhttps://www.sciencedirect.com/science/article/pii/S2096248721000102pt_PT
dc.subjectProject risk managementpt_PT
dc.subjectSocial network analysispt_PT
dc.subjectProject performancept_PT
dc.subjectProject outcomept_PT
dc.subjectProject critical success factorpt_PT
dc.subjectSustainabilitypt_PT
dc.subjectInnovationpt_PT
dc.titleMeasuring project performance by applying social network analysespt_PT
dc.typejournal article
dspace.entity.typePublication
oaire.citation.endPage55pt_PT
oaire.citation.issue2pt_PT
oaire.citation.startPage35pt_PT
oaire.citation.titleInternational Journal of Innovation Studiespt_PT
oaire.citation.volume5pt_PT
person.familyNameNunes
person.familyNameAbreu
person.givenNameMarco
person.givenNameAntónio
person.identifier1829666
person.identifier.ciencia-id3417-C700-7340
person.identifier.ciencia-idF51F-F42E-3D57
person.identifier.orcid0000-0003-3983-1007
person.identifier.orcid0000-0001-8839-5606
person.identifier.ridD-3964-2014
person.identifier.scopus-author-id57218315486
rcaap.rightsclosedAccesspt_PT
rcaap.typearticlept_PT
relation.isAuthorOfPublicationb4e810f0-775f-4098-acdf-c432baf81849
relation.isAuthorOfPublication2e303e99-df37-4381-bf3c-0ab7fc69703c
relation.isAuthorOfPublication.latestForDiscoveryb4e810f0-775f-4098-acdf-c432baf81849

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