Publication Date
1-10-2026
Document Type
Contribution to a Book
Publication Title
Emerging Technologies in Supply Chains. International Series in Operations Research & Management Science
Editor
Khojasteh, Y. and Jahan Abadi, S.M.
Volume
373
DOI
10.1007/978-3-032-01218-0_8
First Page
203
Last Page
229
Abstract
Reverse supply chains face various challenges such as incomplete end-of-life data, product untraceability, information asymmetry, and low perceived value of remanufactured products. Blockchain, as a promising new technology, can be used to store accurate and reliable information regarding manufacturers, suppliers, logistics, product life expectancy, reusability, and recycling. Data precision and completeness help manufacturers to reduce or avoid costly testing and time consuming reduces. Despite documented benefits and real-world examples of blockchain, limited research integrates blockchain with recycling strategies, advertising efforts, and information management in reverse supply chains. This chapter reviews these challenges and how blockchain help to address them. It specifically analyzes blockchain adoption under three recycling modes (the manufacturer collecting used products directly from customers, the manufacturer contracting a retailer for collection, and the manufacturer outsourcing the collection activities to a third-party recycler). Additionally, it explores interactions between blockchain adoption and advertising strategies, as well as information strategies.
Keywords
Blockchain, Information strategies, Recycling mode, Reverse supply chain
Department
Global Innovation and Leadership
Recommended Citation
Yanting Huang and Tianqin Shi. "Application of Blockchain in Reverse Supply Chain" Emerging Technologies in Supply Chains. International Series in Operations Research & Management Science (2026): 203-229. https://doi.org/10.1007/978-3-032-01218-0_8
Comments
This is an Accepted Manuscript of a book chapter published by Springer Nature in Emerging Technologies in Supply Chains. International Series in Operations Research & Management Science, vol 373., 2026. The final authenticated version is available online at: https://doi.org/10.1007/978-3-032-01218-0_8