Modern traceability technologies promise to improve supply chain management by simplifying recalls, increasing visibility, or verifying sustainable supplier practices. Initiatives leading the implementation of traceability technologies must choose the least-costly set of firms - or seed set - to target for early adoption. Choosing this seed set 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 subset of firms in a product's supply chain. We prove that the problem of selecting the least-costly seed set 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 seed set. The algorithm is fixed-parameter tractable in the supply chain network's treewidth, which we show to be low in real-world supply chain networks. The algorithm also enables us to derive easily-computable bounds on the cost of selecting an optimal seed set. Finally, we leverage our algorithms to conduct large-scale numerical experiments that provide insights into how the supply chain network structure influences diffusion. These insights can help managers optimize their technology diffusion strategy.

翻译：现代可追溯技术通过简化召回、提升可见性或验证可持续供应商实践，有望改进供应链管理。推动可追溯技术落地的倡议必须选择成本最低的企业集合（即种子集合）作为早期采纳目标。选择该种子集合面临挑战，因为企业隶属于复杂网络互联的供应链，由此产生固有的供应链效应：可追溯技术带来的收益取决于产品供应链中某个子集企业的技术采纳情况。我们证明，在供应链网络中选择最低成本种子集合的问题难以求解，甚至无法在多项式对数因子内进行近似。尽管如此，我们提出一种基于线性规划的新型算法来识别最低成本种子集合。该算法在供应链网络的树宽（经证实现实供应链网络中的树宽值较低）下具有固定参数可解性。该算法还使我们能够推导出可轻松计算的最优种子集合成本边界。最后，我们利用所提算法开展大规模数值实验，揭示供应链网络结构如何影响技术扩散——这些见解可帮助管理者优化其技术扩散策略。