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Orchestrating Resources for Big Data Analytics Implementation in Manufacturing SMEs: Insights Into Managerial Role and Engagement

aut.relation.endpage33
aut.relation.issueahead-of-print
aut.relation.journalProduction Planning and Control
aut.relation.startpage1
aut.relation.volumeahead-of-print
dc.contributor.authorDehe, Benjamin
dc.contributor.authorSubasinghage, Maduka
dc.contributor.authorMirzaei, Maryam
dc.date.accessioned2026-04-17T03:00:46Z
dc.date.available2026-04-17T03:00:46Z
dc.date.issued2025-09-24
dc.description.abstractBig Data Analytics (BDA) offers transformative potential for Small and Medium Enterprises (SMEs), enabling enhanced performance, improved decision-making, innovation and business growth. Yet, manufacturing SMEs often face considerable constraints that hinder effective BDA implementation. This study adopts Resource Orchestration Theory (ROT) to explore how managers in manufacturing SMEs structure, bundle, and leverage resources to overcome these challenges and deploy BDA effectively. Using semi-structured interviews with 17 SMEs managers, we examine BDA deployment across supply chain operations guided by the SCOR model. The findings reveal key managerial roles and strategies, including approaches to selecting, configuring, and operationalising BDA solutions. This study contributes to theory by applying ROT to the underexplored context of BDA implementation in SMEs, highlighting the dynamic capabilities managers must develop to succeed. Practically, it provides actionable insights for SMEs managers navigating digital transformation in resource-constrained settings. The study proposes a roadmap to guide BDA adoption in manufacturing SMEs.
dc.identifier.citationProduction Planning and Control, ISSN: 0953-7287 (Print); 1366-5871 (Online), Taylor and Francis Group, ahead-of-print(ahead-of-print), 1-33. doi: 10.1080/09537287.2025.2561966
dc.identifier.doi10.1080/09537287.2025.2561966
dc.identifier.issn0953-7287
dc.identifier.issn1366-5871
dc.identifier.urihttp://hdl.handle.net/10292/20939
dc.languageen
dc.publisherTaylor and Francis Group
dc.relation.urihttps://www.tandfonline.com/doi/full/10.1080/09537287.2025.2561966
dc.rights© 2025 The Author(s). Published by Informa UK Limited, trading as Taylor & Francis Group. This is an Open Access article distributed under the terms of the Creative Commons Attribution-NonCommercial-NoDerivatives License (http://creativecommons.org/licenses/by-nc-nd/4.0/), which permits non-commercial re-use, distribution, and reproduction in any medium, provided the original work is properly cited, and is not altered, transformed, or built upon in any way. The terms on which this article has been published allow the posting of the Accepted Manuscript in a repository by the author(s) or with their consent.
dc.rights.accessrightsOpenAccess
dc.subject35 Commerce, Management, Tourism and Services
dc.subject3503 Business Systems In Context
dc.subject3507 Strategy, Management and Organisational Behaviour
dc.subject3509 Transportation, Logistics and Supply Chains
dc.subject46 Information and Computing Sciences
dc.subject4609 Information Systems
dc.subjectData Science
dc.subjectGeneric health relevance
dc.subject9 Industry, Innovation and Infrastructure
dc.subjectOperations Research
dc.subjectBig data analytics
dc.subjectSMEs
dc.subjectresource orchestration theory
dc.subjectmanagers’ role
dc.titleOrchestrating Resources for Big Data Analytics Implementation in Manufacturing SMEs: Insights Into Managerial Role and Engagement
dc.typeJournal Article
pubs.elements-id630597

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