Abstract
The importance of Big Data Analytics (BDA) has drawn much attention as the need for sustainability in manufacturing supply chains grows. However, a systematic understanding of the evolving landscape at the intersection of BDA, manufacturing supply chains and the Triple Bottom Line of sustainability is still missing. In response, the study aims to synthesise the existing literature to unearth the potential benefits of BDA to enhance sustainability and to clarify barriers constraining its widespread adoption. A systematic review of 64 peer-reviewed articles reveals a growing trend in BDA research related to sustainable manufacturing supply chains. The findings are thematically analysed and categorised according to how BDA influences ecological, social, and economic sustainability within these supply chains. Moreover, to comprehensively elucidate the landscape, the research leverages the Technology-Organisation-Environment framework to effectively frame organisations’ multifaceted challenges on their journey to embrace BDA. An integrated framework is proposed to elaborate holistically on BDA applications for sustainability. This review presents a vital reference for researchers, practitioners, and policymakers alike, facilitating a deeper understanding of how BDA can be harnessed to unlock sustainability in manufacturing supply chains and pave the way for more informed decisions in a rapidly changing environment.
| Original language | English |
|---|---|
| Article number | 100256 |
| Number of pages | 13 |
| Journal | Cleaner Logistics and Supply Chain |
| Volume | 16 |
| Early online date | 14 Aug 2025 |
| DOIs | |
| Publication status | Published - Sept 2025 |
Bibliographical note
Copyright © 2025 The Author(s). Published by Elsevier Ltd. This is an open access article under the CC BY license ( https://creativecommons.org/licenses/by/4.0/ ).Keywords
- Big data analytics
- Sustainable supply chain management
- ManufacturingTriple bottom line
- Technology-organisation-environment framework
- Adoption barriers
- TOE Framework