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Bag, S, Rahman, MS, Srivastra, G, Chan, H-L and Bryde, DJ (2022) The role of big data and predictive analytics in developing a resilient supply chain network in the South African mining industry against extreme weather events. International Journal of Production Economics, 251. ISSN 0925-5273
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Abstract
Most parts of the world have suffered the negative impacts from extreme weather events, in whatever form they may take. To mitigate such impacts, attention in the operations management literature has focused on how firms build resilience in their supply chains, in order to quickly respond to such events and also to return, as soon as possible, to a business-as-usual state. Prior studies have examined the process of building a supply chain (SC) in different countries, industries and in response to various disruptions, such as the COVID-19 pandemic, whilst, at the same time, calling for further research in different contexts. We respond to these calls by exploring SC resilience ability in the South African mining industry under extreme weather events. We situated our study in the dynamic capability view (DCV) view of the firm. We examined the direct effect of big data and predictive analytics (BDPA) capabilities on SC visibility and the final effects on community and rresource resilience. We adopted a sequential mixed methods research design, collecting data from interviews with 10 industry practitioners and from 219 respondents to an online survey. We built and tested our theoretical model using partial least squares structured equation modelling (PLS-SEM). Notable theoretical contributions of our study are that big data enables a more efficient supply chain monitoring system, which, in turn, improves SC visibility. BDPA capability improves a company's ability to make the best use of its available resources. It improves the South African mining industry's dynamic capability, allowing them to adjust their strategies in response to diverse adverse weather conditions. Furthermore, BDPA capability’s ability to improve SC visibility is enhanced when there is strong alignment between BDPA strategy and initiatives. Finally, having a high level of SC visibility helps develop community and resource resilience, which are necessary to ensure that firms in the industry fulfil their responsibilities in relation to social sustainability.
| Item Type: | Article |
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| Uncontrolled Keywords: | big data and predictive analytics; supply chain visibility; resilience; mining operations; South Africa; extreme weather events; Operations Research |
| Subjects: | H Social Sciences > HF Commerce > HF5001 Business H Social Sciences > HD Industries. Land use. Labor > HD28 Management. Industrial Management H Social Sciences > HF Commerce > HF5001 Business > HF5410 Marketing. Distribution of Products |
| Divisions: | Doctoral Management Studies (from Sep 19) |
| Publisher: | Elsevier |
| SWORD Depositor: | A Symplectic |
| Date Deposited: | 07 Jun 2022 12:40 |
| Last Modified: | 20 Dec 2023 00:50 |
| DOI or ID number: | 10.1016/j.ijpe.2022.108541 |
| URI: | https://researchonline.ljmu.ac.uk/id/eprint/17010 |
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