Please use this identifier to cite or link to this item: https://hdl.handle.net/1959.11/57056
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dc.contributor.authorShafiabady, Niushaen
dc.contributor.authorHadjinicolaou, Nicken
dc.contributor.authorUd Din, Fareeden
dc.contributor.authorBhandari, Binayaken
dc.contributor.authorWu, Robert M Xen
dc.contributor.authorVakilian, Jamesen
dc.date.accessioned2023-12-20T05:10:16Z-
dc.date.available2023-12-20T05:10:16Z-
dc.date.issued2023-05-10-
dc.identifier.citationPLOS ONE, 18(5), p. 1-37en
dc.identifier.issn1932-6203en
dc.identifier.urihttps://hdl.handle.net/1959.11/57056-
dc.description.abstract<p>Since the pandemic organizations have been required to build agility to manage risks, stakeholder engagement, improve capabilities and maturity levels to deliver on strategy. Not only is there a requirement to improve performance, a focus on employee engagement and increased use of technology have surfaced as important factors to remain competitive in the new world. Consideration of the strategic horizon, strategic foresight and support structures is required to manage critical factors for the formulation, execution and transformation of strategy. Strategic foresight and Artificial Intelligence modelling are ways to predict an organizations future agility and potential through modelling of attributes, characteristics, practices, support structures, maturity levels and other aspects of future change. The application of this can support the development of required new competencies, skills and capabilities, use of tools and develop a culture of adaptation to improve engagement and performance to successfully deliver on strategy. In this paper we apply an Artificial Intelligence model to predict an organizations level of future agility that can be used to proactively make changes to support improving the level of agility. We also explore the barriers and benefits of improved organizational agility. The research data was collected from 44 respondents in public and private Australian industry sectors. These research findings together with findings from previous studies identify practices and characteristics that contribute to organizational agility for success. This paper contributes to the ongoing discourse of these principles, practices, attributes and characteristics that will help overcome some of the barriers for organizations with limited resources to build a framework and culture of agility to deliver on strategy in a changing world.</p>en
dc.languageenen
dc.publisherPublic Library of Scienceen
dc.relation.ispartofPLOS ONEen
dc.rightsAttribution 4.0 International*
dc.rights.urihttp://creativecommons.org/licenses/by/4.0/*
dc.titleUsing Artificial Intelligence (AI) to predict organizational agilityen
dc.typeJournal Articleen
dc.identifier.doi10.1371/journal.pone.0283066en
dcterms.accessRightsUNE Greenen
local.contributor.firstnameNiushaen
local.contributor.firstnameNicken
local.contributor.firstnameFareeden
local.contributor.firstnameBinayaken
local.contributor.firstnameRobert M Xen
local.contributor.firstnameJamesen
local.profile.schoolSchool of Science and Technologyen
local.profile.emailfuddin@une.edu.auen
local.output.categoryC1en
local.record.placeauen
local.record.institutionUniversity of New Englanden
local.publisher.placeUnited States of Americaen
local.identifier.runningnumbere0283066en
local.format.startpage1en
local.format.endpage37en
local.peerreviewedYesen
local.identifier.volume18en
local.identifier.issue5en
local.access.fulltextYesen
local.contributor.lastnameShafiabadyen
local.contributor.lastnameHadjinicolaouen
local.contributor.lastnameUd Dinen
local.contributor.lastnameBhandarien
local.contributor.lastnameWuen
local.contributor.lastnameVakilianen
dc.identifier.staffune-id:fuddinen
local.profile.orcid0000-0001-6122-2043en
local.profile.roleauthoren
local.profile.roleauthoren
local.profile.roleauthoren
local.profile.roleauthoren
local.profile.roleauthoren
local.profile.roleauthoren
local.identifier.unepublicationidune:1959.11/57056en
dc.identifier.academiclevelAcademicen
dc.identifier.academiclevelAcademicen
dc.identifier.academiclevelAcademicen
dc.identifier.academiclevelAcademicen
dc.identifier.academiclevelAcademicen
dc.identifier.academiclevelAcademicen
local.title.maintitleUsing Artificial Intelligence (AI) to predict organizational agilityen
local.output.categorydescriptionC1 Refereed Article in a Scholarly Journalen
local.search.authorShafiabady, Niushaen
local.search.authorHadjinicolaou, Nicken
local.search.authorUd Din, Fareeden
local.search.authorBhandari, Binayaken
local.search.authorWu, Robert M Xen
local.search.authorVakilian, Jamesen
local.uneassociationYesen
local.atsiresearchNoen
local.sensitive.culturalNoen
local.year.published2023en
local.fileurl.closedpublishedhttps://rune.une.edu.au/web/retrieve/5a48f2cc-b51c-46e2-ab37-932b23d4b876en
local.subject.for2020460199 Applied computing not elsewhere classifieden
local.subject.seo2020220402 Applied computingen
local.profile.affiliationtypeExternal Affiliationen
local.profile.affiliationtypeExternal Affiliationen
local.profile.affiliationtypeUNE Affiliationen
local.profile.affiliationtypeExternal Affiliationen
local.profile.affiliationtypeExternal Affiliationen
local.profile.affiliationtypeExternal Affiliationen
Appears in Collections:Journal Article
School of Science and Technology
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This item is licensed under a Creative Commons License Creative Commons