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Big Data and Predictive Analytics and Manufacturing Performance: Integrating Institutional Theory, Resource‐Based View and Big Data Culture

Rameshwar DubeyMontpellier Business School Montpellier Research in Management 2300 Avenue des Moulins 34185 Montpellier FranceAngappa GunasekaranSchool of Business and Public Administration California State University Bakersfield 9001 Stockdale Highway Bakersfield CA 93311‐1022 USAStephen J. ChildePlymouth Business School Plymouth University Plymouth PL4 8AA UKConstantin BlomeSchool of Business Management and Economics University of Sussex Sussex House Falmer Brighton BN1 9RH UKΘάνος ΠαπαδόπουλοςKent Business School University of Kent Sail and Colour Loft, The Historic Dockyard Chatham Kent ME4 4TE UK
2019en
ABI

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Abstract The importance of big data and predictive analytics has been at the forefront of research for operations and manufacturing management. The literature has reported the influence of big data and predictive analytics for improved supply chain and operational performance, but there has been a paucity of literature regarding the role of external institutional pressures on the resources of the organization to build big data capability. To address this gap, this paper draws on the resource‐based view of the firm, institutional theory and organizational culture to develop and test a model that describes the importance of resources for building capabilities, skills and big data culture and subsequently improving cost and operational performance. We test our research hypotheses using 195 surveys, gathered using a pre‐tested questionnaire. Our contribution lies in providing insights regarding the role of external pressures on the selection of resources under the moderating effect of big data culture and their utilization for capability building, and how this capability affects cost and operational performance.

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