(untitled) (London Journal of Research In Management & Business, 2025)
Since the rapid growth of e-commerce, product returns volume has soared, creating pressure on reverse logistics systems to be more efficient, transparent and cost-effective. Nonetheless, the traditional reverse logistics processes are encountered with operational challenges such as high costs, return fraud, ineffective tracking systems, and environmental concerns. Mature AI and Blockchain Technologies allow businesses to automate various processes, make more informed decisions, and ensure that supply chain operations are transparent. Based on case studies from leading global companies including Amazon, Walmart, and Alibaba, this study sheds light on the integration of AI and Blockchain in reverse logistics as an avenue for reverse logistics integration in overall supply chain strategy. Employing a qualitative methodology and secondary data sources, including industry reports, academic literature, and company publications, this study explores how these modern technologies are positively impacting return management processing, fraud detection, operational efficiency, and sustainability. AI-powered automation greatly helps the companies in returns forecasting, inventory optimization, and customer service, unveiling the time and costs relating to reverse logistics operations as per the findings. Simultaneously, the implementation of blockchain technology allows for real-time tracking, fraud mitigation, and generation of trusted data for sharing, thereby enhancing return transactional transparency. Specifically, companies which combine both AI and blockchain, directly creates use cases leading to superior decision-making capabilities, more efficient logistics and support processes, as well as superior management of product returns. While these technologies offer potential advantages, the study reveals critical hurdles in implementing these technologies, such as high deployment costs, regulatory obstacles, data privacy issues, and interoperability challenges among various blockchain systems. Moreover, it can also be quite challenging for companies to find the technical expertise needed to implement AI or blockchain in their logistics infrastructure. To the best of our knowledge, this research effort contributes to the literature on supply chain management and technology adoption by providing tested instruments and best practice options for businesses that seek to enhance their reverse logistics operations through the application of technologies. The study also aids theory and practice by illustrating some policies for adoption challenges and offering managerial recommendations for firms. These insights need to be validated and refined through empirical research and industry application of AI and blockchain in the context of reverse logistics (Wang et al., 2018; Kafeel et al., 2023).