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Big Data-Driven Circularity: Enhancing Sustainability Through Closed-Loop Supply Chain Models
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Author(s): Mohammad Al Refat Reyel (Ulster University, UK), Mehedi Hassan Anik (Unitec Institute of Technology, New Zealand)and Syed Waqar Ul Hassan Shah (Ulster University, UK)
Copyright: 2026
Pages: 42
Source title:
Enhancing Sustainability in Global Supply Chains With Big Data Analytics
Source Author(s)/Editor(s): Mohammad Kamrul Hasan (Tongling University, China), Tahsina Khan (Bangladesh University of Professionals, Bangladesh), Arbia Hlali (Taibah University, Saudi Arabia)and Md Mehedi Hasan Emon (American International University-Bangladesh, Bangladesh)
DOI: 10.4018/979-8-3373-6896-2.ch007
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Abstract
This chapter explores how big data technologies are transforming circular supply chains, enabling firms to manage end-of-life products more efficiently while promoting sustainability. By integrating predictive analytics, IoT, AI, and digital twins, organizations can anticipate product returns, optimize reverse logistics, automate sorting, and make informed decisions on reuse, refurbishment, and recycling. The discussion highlights applications across electronics, automotive, and consumer goods industries, illustrating how data-driven strategies support circular economy practices, improve resource efficiency, and reduce environmental impact. Challenges such as interoperability, data quality, cost, privacy, and ethical considerations are also examined, alongside recommendations for governance, collaboration, and technology adoption. The chapter underscores the strategic potential of data-driven circularity in achieving long-term operational and environmental resilience.
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