Big data analytics based enablers of supply chain capabilities and firm competitiveness: a fuzzy-TISM approach
Journal of Enterprise Information Management
ISSN: 1741-0398
Article publication date: 4 December 2020
Issue publication date: 28 January 2021
Abstract
Purpose
This paper aims to identify the big data analytics (BDAs) based enablers of supply chain capabilities (SCCs) and competitiveness of firms. This paper also models the interaction among identified enablers and thus projects the relationship strength of these enablers with SCC and a firm's competitiveness.
Design/methodology/approach
In order to achieve the research objectives of this paper, we employed fuzzy total interpretive structural modeling (TISM), an integrated approach of an interpretive structural model and TISM.
Findings
Results suggest that BDA-based enablers namely, IT infrastructure for BDA; leadership commitment; people skills for use of BDA and financial support for BDA significantly enable SCC and enhance firm competitiveness.
Practical implications
Results of the present study have implications for researchers and practitioners; the results will enable them to design policies around identified enablers of BDA initiatives.
Originality/value
The present paper is one of a few early efforts that address the role of BDA in augmenting SCC and subsequently a firm's competitiveness from a resource-dynamic capability perspective.
Keywords
Acknowledgements
The authors thank Dr. Malin Song and anonymous reviewers for their valuable feedback. This has helped the authors in improving the paper.
Citation
Bamel, N. and Bamel, U. (2021), "Big data analytics based enablers of supply chain capabilities and firm competitiveness: a fuzzy-TISM approach", Journal of Enterprise Information Management, Vol. 34 No. 1, pp. 559-577. https://doi.org/10.1108/JEIM-02-2020-0080
Publisher
:Emerald Publishing Limited
Copyright © 2020, Emerald Publishing Limited