The Benefits of Applying Social Network Analysis to Identify Collaborative Risks

Marco Nunes, António Abreu

Research output: Chapter in Book/Report/Conference proceedingConference contributionpeer-review

4 Citations (Scopus)

Abstract

It is often argued that efficient collaboration is the key for successful organizations. However, achieving efficient collaboration still represents a challenge for most organizations. Often, hidden involuntary behaviors (also known as behavioral risks), threat efficient collaboration in a blink of an eye. Either by the lack of supportive models to manage sscollaboration or due to misunderstandings of what the different dimensions of collaboration are and represent, most organizations fear the engagement in collaborative approaches due the high chances of failure. In this work is proposed a heuristic model to identify organizational collaborative risks by applying social network analysis. This work aims to illustrate how organizations can benefit from the application of social network analysis in the efficient identification and management of collaborative risks. A case study illustrates the application of the proposed model in this work.

Original languageEnglish
Title of host publicationTechnological Innovation for Applied AI Systems - 12th IFIP WG 5.5/SOCOLNET Advanced Doctoral Conference on Computing, Electrical and Industrial Systems, DoCEIS 2021, Proceedings
EditorsLuis M. Camarinha-Matos, Pedro Ferreira, Guilherme Brito
PublisherSpringer Science and Business Media Deutschland GmbH
Pages16-23
Number of pages8
ISBN (Print)9783030782870
DOIs
Publication statusPublished - 2021
Event12th IFIP WG 5.5/SOCOLNET Advanced Doctoral Conference on Computing, Electrical and Industrial Systems, DoCEIS 2021 - Costa de Caparica and Online, Portugal
Duration: 7 Jul 20219 Jul 2021

Publication series

NameIFIP Advances in Information and Communication Technology
Volume626
ISSN (Print)1868-4238
ISSN (Electronic)1868-422X

Conference

Conference12th IFIP WG 5.5/SOCOLNET Advanced Doctoral Conference on Computing, Electrical and Industrial Systems, DoCEIS 2021
Country/TerritoryPortugal
CityCosta de Caparica and Online
Period7/07/219/07/21

Keywords

  • Case study
  • Collaborative risks
  • Organizational business intelligence architecture
  • Organizational performance
  • Social network analysis

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