Harnessing Big Data for Reverse Logistics and Waste Management

This chapter investigates the transformative potential of Big Data Analytics (BDA) in promoting sustainable practices within reverse logistics and waste management, highlighting its contribution to the development of circular supply chains. It delves into the basic concepts of reverse logistics, explores perspectives that guide sustainable operations, and examines the capabilities of BDA in predictive analytics, AI-supported decision-making, and real-time monitoring. Practical implementations, including product returns management, recycling process optimization, and integration of waste management in urban and industrial contexts, are discussed, along with challenges such as data privacy, interoperability, and organizational preparedness. Additionally, the chapter illustrates how BDA aligns with circular economy principles, supporting product life extension, secondary market development, and material recirculation, while future directions point to blockchain traceability, ethical AI, and alignment with ESG and SDG frameworks.