Reviewing the applications of artificial intelligence in sustainable supply chains: Exploring research propositions for future directions

The widespread environmental consequences of manufacturing and transportation operations have created a need for a resilient sustainable supply chain (SSC) network. In this regard, companies are facing governmental, societal and competitive pressures to integrate sustainability dimensions in their operations. Recent advancements in technology have provided multiple optimal solutions to the environmentally unsustainable operations of businesses. 

The integration of artificial intelligence (AI)-based techniques in supply chain (SC) processes has transformed their way of working. This study by Naz et al., has emphasized the importance of a thorough evaluation and review of studies conducted in the field of AI and SSC. A bibliometric analysis and structural topic modelling (STM) were employed to generate a systematic literature review in the selected field of study.

Ten emerging research themes were produced using STM. These are as follows:
  1. carbon emissions in SC,
  2. sustainable transportation,
  3. optimization in SC,
  4. data analytics in SC,
  5. vehicle routing in SC,
  6. reverse logistics,
  7. proposed models in SSC,
  8. sustainable supplier selection,
  9. remanufacturing in SC and
  10. decision-making in SC.
These themes have been thoroughly examined and discussed. This study will deliver a deeper understanding into the SSC through integrating AI and will encourage managers to consider future propositions.

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