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

Dubey, Rameshwar and Gunasekaran, Angappa and Childe, Stephen J. and Blome, Constantin and Papadopoulos, Thanos (2019) Big Data and Predictive Analytics and Manufacturing Performance : Integrating Institutional Theory, Resource-Based View and Big Data Culture. British Journal of Management, 30 (2). pp. 341-361. ISSN 1045-3172

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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.

Item Type:
Journal Article
Journal or Publication Title:
British Journal of Management
Additional Information:
Publisher Copyright: © 2019 British Academy of Management
Uncontrolled Keywords:
/dk/atira/pure/subjectarea/asjc/1400
Subjects:
?? business, management and accounting(all)strategy and managementmanagement of technology and innovation ??
ID Code:
176046
Deposited By:
Deposited On:
04 Oct 2022 08:20
Refereed?:
Yes
Published?:
Published
Last Modified:
28 Nov 2023 10:36