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

By Rameshwar Dubey, Angappa Gunasekaran, Stephen J. Childe, Constantin Blome, Thanos Papadopoulos. British Journal of Management, 2019

744 citations recorded by the source corpus.

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.

Subfields: Management Information Systems, Strategy and Management

View Paper: https://www.semanticscholar.org/paper/247dec05283a1a521f99253a6cca6a5858cac0d2

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Citations in the corpus

Mastering digital transformation: The nexus between leadership, agility, and digital strategy (2022, background): “NIT has commonly been used to understand the organizational change concerning implementing advanced technology by investigating external pressures/factors on organizations ’ practices and cultures (Adebanjo et al., 2018; Dubey et al., 2019).”
Big data analytics capability and decision-making: The role of data-driven insight on circular economy performance (2021, methodology): “Prior research has suggested that the dynamic capabilities perspective matters for performance outcomes (Dubey, Gunasekaran, Childe, Blome, & Papadopoulos, 2019; Mikalef et al., 2019).”
Blockchain-oriented dynamic modelling of smart contract design and execution in the supply chain (2019, background): “…at the near future, the decision-making support in supply chain (SC) management can be considered as good as the digital technology behind it (Dubey, Gunasekaran, Childe, Papadopoulos, et al. 2019; Dubey et al. 2018; Jha et al. 2017; Koh et al. 2017; Ivanov, Dolgui, and Sokolov 2019; Choi,…”
An integrated artificial intelligence framework for knowledge creation and B2B marketing rational decision making for improving firm performance (2021, methodology): “Big data powered AI technology (BDAI) acts as a key technological enabler in this digital age (Dubey et al., 2019), particularly for knowledge creation and decision making (Duan, Edwards, & Dwivedi, 2019).”
Identifying Digital Transformation Paths in the Business Model of SMEs during the COVID-19 Pandemic (2020, background): “Some examples include 5G, artificial intelligence, or 3D printing [7].”