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

Rameshwar Dubey, Angappa Gunasekaran, Stephen J. Childe, Constantin Blome, Thanos Papadopoulos

Research output: Contribution to journalArticlepeer-review

133 Scopus citations


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.

Original languageEnglish (US)
Pages (from-to)341-361
Number of pages21
JournalBritish Journal of Management
Issue number2
StatePublished - Apr 2019

All Science Journal Classification (ASJC) codes

  • Business, Management and Accounting(all)
  • Strategy and Management
  • Management of Technology and Innovation

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