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dc.contributor.authorDaowd, Ahmad
dc.contributor.authorHasan, Ruaa
dc.contributor.authorKamal, Muhammad Mustafa
dc.contributor.authorEldabi, Tillal
dc.contributor.authorKoliousis, Ioannis
dc.contributor.authorPapadopoulos, Thanos
dc.date.accessioned2022-02-21T10:07:21Z
dc.date.available2023-02-21T00:00:00Z
dc.date.available2022-02-21T10:07:21Z
dc.date.issued2022-05-16
dc.identifier.citationHasan R, Kamal M M, Daowd A, Eldabi T, Koliousis I, Papadopoulos T (2022) 'Critical analysis of the impact of Big Data analytics on supply chain operations', Production Planning and Control, (), pp.-.en_US
dc.identifier.issn0953-7287
dc.identifier.doi10.1080/09537287.2022.2047237
dc.identifier.urihttp://hdl.handle.net/10547/625326
dc.description.abstractUndoubtedly, due to the increasingly competitive pressures and the stride of varying demands, volatility and disturbance have become the standard in today’s global markets. The spread of Covid-19 is a prime example for that. Supply chain managers are urged to rethink their competitive strategies to make use of Big Data Analytics (BDA), due to the increasing uncertainty in both demand and supply side, the competition among the supply chain partners and the need to identify ways to offer personalised products and services. With many supply chain executives recognising the need of “improving with data”, supply chain businesses need to equip themselves with sophisticated BDA methods/techniques to create valuable insights from big data, thus, enhancing the decision-making process and optimising the efficiency of Supply Chain Operations (SCO). This paper proposes the building blocks of a theoretical framework for understanding the impact of BDA on SCO. The framework is based on a Systematic Literature Review (SLR) on BDA and SCO, underpinned by Task-Technology-Fit theory and Institutional Theory. The paper contributes to the literature by building a platform for future work on investigating factors driving and inhibiting BDA impact on SCO.en_US
dc.language.isoenen_US
dc.publisherTaylor and Francisen_US
dc.relation.urlhttps://www.tandfonline.com/doi/full/10.1080/09537287.2022.2047237
dc.rightsGreen - can archive pre-print and post-print or publisher's version/PDF
dc.rightsAttribution-NonCommercial-NoDerivatives 4.0 International*
dc.rights.urihttp://creativecommons.org/licenses/by-nc-nd/4.0/*
dc.subjectBig Dataen_US
dc.subjectbusiness analyticsen_US
dc.subjectBig Data analyticsen_US
dc.subjectsupply chain operationsen_US
dc.subjectoptimisationen_US
dc.subjectdecision-makingen_US
dc.subjectTask-Technology-Fit theoryen_US
dc.subjectinstitutional theoryen_US
dc.subjectSubject Categories::N290 Management studies not elsewhere classifieden_US
dc.titleCritical analysis of the impact of Big Data analytics on supply chain operationsen_US
dc.typeArticleen_US
dc.identifier.journalProduction Planning and Controlen_US
dc.date.updated2022-02-21T10:01:39Z
dc.description.note12m embargo from pub date when known
refterms.dateFOA2022-07-22T09:07:01Z


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