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

R Dubey, A Gunasekaran, S Childe, C Blome, T Papadopoulos

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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. 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 moderating effect of big data culture and their utilisation for capability building, and how this capability affects cost and operational performance.
Original languageEnglish
Pages (from-to)341-361
Number of pages0
JournalBritish Journal of Management
Volume30
Issue number2
Early online date8 May 2019
DOIs
Publication statusPublished - 8 May 2019

Keywords

  • Big Data
  • Predictive Analytics
  • Institutional Theory
  • Resource Based View
  • Manufacturing Performance
  • PLS SEM

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