Exploring the influence of circular economy on big data analytics and supply chain resilience nexus: A structural equation modeling approach

The recent pandemic, geopolitical instability, and unforeseen crises have profoundly disrupted global supply chains, igniting a critical need to reevaluate and enhance supply chain resilience strategies. In response, researchers have extensively explored the role of big data analytics in bolstering supply chain resilience during the post-pandemic and war-time recovery phase. Again, to reduce dependency on finite resources, minimize waste, and create adaptive, closed-loop systems, the role of circular economy has also been analyzed widely. However, the interaction between these two, such as how big data analytics impacts supply chain resilience within the framework of circular economy, is still underexplored. Hence, this study aims to explore the mediating role of circular economy in the relationship between big data analytics and supply chain resilience, especially focusing on the readymade garments manufacturing sector of an emerging economy like Bangladesh. A second-order hierarchical component model has been developed and tested using partial least squares structural equation modeling to achieve this. The first-order constructs and measurement items were sourced from an extensive literature review and insights from experts in the Bangladeshi readymade garments sector. The study demonstrates that circular economy significantly plays the role of a partial mediator in the relationship between big data analytics and supply chain resilience. This indicates that while big data analytics directly enhances supply chain resilience, its effectiveness is further amplified when integrated with circular economy practices. The study’s findings offer valuable insights for industry managers and policymakers, enabling them to utilize big data analytics in order to align industrial practices with circular economy principles and bolster supply chain resilience to maintain and improve ecological and socio-economic sustainability. • The study investigates CE’s mediating role in the interaction between BDA and SCR. • A second-order hierarchical component model was built and analyzed using PLS-SEM. • The study suggests that BDA significantly influences SCR. • CE practices play the role of a partial mediator. • The study’s findings offer insights for enhancing SCR and ensuring sustainability.