This study investigates the role of machine learning (ML) and artificial intelligence (AI) in reverse logistics (RL) within the scope of e-commerce and e-waste. RL is a process to plan and manage the flow of products from consumer to provider with the purpose to generate value. From the bottom line of sustainability, it is important to manage and improve the product return and end-of-life product. Past research studies have presented several techniques to optimize the cost, schedule, and route. However, the integration of ML and AI tools in information technology systems is limited and insufficient. The purpose is to present the research gap for further study. The article is organized as follows: Section 1 provides an introduction to reverse logistics, ML, AI, e-commerce, and e-waste. Section 2 presents a comprehensive review of the current research, and Section 3 concludes the article.
TopIntroduction
Logistics has a long and illustrious history. The phrase “logistics management” was initially used by the United States to control the transit and supply of munitions during WWII (Zhang et al., 2020). Following WWII, the term “logistics” expanded and gained a foothold in fields such as business, procurement, distribution, reverse supply chain, green logistics, domestic logistics, humanitarian logistics, and so on. The physical distribution of commodities is the emphasis, which includes order fulfilment, product distribution, storage, production planning, and customer support. Logistics, as described by the Council of Logistics Management, is the process of planning, implementing, and regulating the efficient, effective movement and storage of products, services, and associated information from point of origin to point of consumption in order to meet customer expectations (Swamidass, 2000).
The closed-loop supply chain (CLSC) is an emerging topic of research in terms of sustainability in different dimensions of environmental, economic, and social, in connection with the circular economy (Islam & Huda, 2018). “A circular economy is a regenerative system in which resource input and waste, emission, and energy leakage are minimized by slowing, closing, and narrowing the material and energy loops,” (Geissdoerfer et al., 2017). This can be accomplished by long-term planning, maintenance, repair, reuse, remanufacturing, refurbishment, and recycling (Geissdoerfer et al., 2017). CLSC management, according to Guide and Van Wassenhove (2009), is the design, control, and operation of a system to optimize value creation across a product's complete life cycle with the dynamic recovery of value from various types and volumes of returns over time (Guide et al., 2009). CLSC's research includes a wide range of topics, including the return of products, product maintenance, product refurbishing, component reuse, prefabrication, and waste (Jaehn., 2016).
Stock (1992) defines RL as the term typically used for the function of logistics in recycling, waste disposal, and hazardous material management; a broader view covers all concerns pertaining to logistical actions carried out in source reduction, recycling, substitution, reuse, and disposal (Stock., 1992).
“Reverse logistics is the process of planning, implementing, and controlling the efficient, cost-effective flow of raw materials, in-process inventory, finished goods, and related information from the point of consumption to the point of origin for the purpose of recapturing or creating value or proper disposal,” according to Rogers and Tibben-Lembke (1999).
Due to a growth in e-commerce firms that allow quick and free product returns and businesses that manage end-of-life/reusable products, RL has lately gained increased interest and relevance among scholars and practitioners. Firms are using it as a strategic strategy for gaining economic advantages and improving their company’s social image (Kannan et al., 2012). Wang et al. (2017) describe the content of reverse logistics, which includes transportation, storage, product recovery, recycling, remanufacture, redistribution, and discarding. The concept of RL or CLSC as a component of the Circular Economy has long piqued the interest of supply chain researchers. However, the present decade's technological development has made it difficult to integrate its tools with supply chain operations.