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Big Data Analytics in turbulent contexts: towards organizational change for enhanced agility
| hal.structure.identifier | Montpellier Research in Management [MRM] | |
| dc.contributor.author | BARLETTE, Yves | |
| hal.structure.identifier | Institut de Recherche en Gestion des Organisations [IRGO] | |
| dc.contributor.author | BAILLETTE, Paméla | |
| dc.date.accessioned | 2023-04-05T12:38:58Z | |
| dc.date.available | 2023-04-05T12:38:58Z | |
| dc.date.issued | 2021 | |
| dc.identifier.issn | 0953-7287 | |
| dc.identifier.uri | https://oskar-bordeaux.fr/handle/20.500.12278/172797 | |
| dc.description.abstractEn | This conceptual paper addresses the capabilities offered by big data analytics (BDA), critical in turbulentenvironments, in the context of the Industry 4.0 revolution. BDA enhances organizational agility,as it is highly valuable for the identification of opportunities and threats (i.e. the sensing process ofagility); however, with the exception of aiding decision-making tools, seizing its benefits for reacting(i.e. responding) is more difficult without organizational adaptation. Hence, the changes required toexploit the full capabilities offered by BDA, particularly at the organizational level, are considerable.From a theoretical perspective, through a narrative literature review, this paper highlights several possibilitiesof organizational changes for enhancing a company’s agility and leveraging BDA to achieveenhanced performance in turbulent contexts. The findings are then related to three organizational theories.This work ends in a conceptual model and several research paths for future studies. From amanagerial perspective, this paper highlights, through several examples, the importance of top management’srole in achieving the necessary organizational changes to enhance the companies’ respondingcapabilities. | |
| dc.language.iso | en | |
| dc.publisher | Taylor & Francis | |
| dc.subject.en | Big data analytics | |
| dc.subject.en | agility | |
| dc.subject.en | Industry 4.0 | |
| dc.subject.en | organization | |
| dc.subject.en | turbulence | |
| dc.title.en | Big Data Analytics in turbulent contexts: towards organizational change for enhanced agility | |
| dc.type | Article de revue | en_US |
| dc.identifier.doi | 10.1080/09537287.2020.1810755 | |
| dc.subject.hal | Sciences de l'Homme et Société/Gestion et management | |
| bordeaux.journal | Production Planning and Control | en_US |
| bordeaux.page | 105-122 | |
| bordeaux.volume | 33 | |
| bordeaux.hal.laboratories | IRGO (Institut de Recherche en Gestion des Organisations) - EA 4190 | en_US |
| bordeaux.issue | 2-3 | |
| bordeaux.institution | Université de Bordeaux | |
| bordeaux.peerReviewed | oui | |
| bordeaux.import.source | hal | |
| hal.identifier | hal-03037251 | |
| hal.version | 1 | |
| hal.export | false | |
| workflow.import.source | hal | |
| dc.rights.cc | Pas de Licence CC | en_US |
| bordeaux.COinS | ctx_ver=Z39.88-2004&rft_val_fmt=info:ofi/fmt:kev:mtx:journal&rft.jtitle=Production%20Planning%20and%20Control&rft.date=2021&rft.volume=33&rft.issue=2-3&rft.spage=105-122&rft.epage=105-122&rft.eissn=0953-7287&rft.issn=0953-7287&rft.au=BARLETTE,%20Yves&BAILLETTE,%20Pam%C3%A9la&rft.genre=article |
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