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.
DOI
10.1111/1467-8551.12355
Publication Date
2019-05-08
Publication Title
British Journal of Management
Volume
30
Issue
2
First Page
341
Last Page
361
ISSN
1045-3172
Embargo Period
2021-05-07
Organisational Unit
Plymouth Business School
Keywords
Big Data, Predictive Analytics, Institutional Theory, Resource Based View, Manufacturing Performance, PLS SEM
Recommended Citation
Dubey, R., Gunasekaran, A., Childe, S., Blome, C., & Papadopoulos, T. (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. Available at: https://doi.org/10.1111/1467-8551.12355
