Blockchain and AI in Reverse Logistics: A Qualitative Synthesis of Strategic Applications and Challenges

Abstract

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).�