Traceability Technology Adoption in Supply Chain Networks

Modern traceability technologies promise to improve supply chain management by simplifying recalls, increasing visibility, or verifying sustainable supplier practices. Initiatives developing traceability technologies - and who hope to make their technologies the industry standard - must choose the least-costly set of firms to target as early adopters. This choice is challenging because firms are part of supply chains interlinked in complex networks, yielding an inherent supply chain effect: benefits obtained from traceability are conditional on technology adoption by a (potentially large) subset of firms in a product's supply chain. We prove that the problem of selecting the least-costly set of early adopters in a supply chain network is hard to solve and even approximate within a polylogarithmic factor. Nevertheless, we provide a novel linear programming-based algorithm to identify the least-costly set of early adopters. The algorithm is fixed-parameter tractable in the supply chain network's treewidth, a parameter which we show to be low in real-world supply chain networks. The algorithm also enables us to derive easily-computable bounds on the optimal cost of selecting early adopters as well as key managerial insights about which type of firm to select.