Publication Type

Journal Article

Version

publishedVersion

Publication Date

3-2024

Abstract

Modern traceability technologies promise to improve supply chain management by simplifying recalls, increasing visibility, and 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. We leverage our toolbox 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.

Keywords

Supply chain traceability, Sustainability, Technology adoption, Network diffusion, Computational complexity, Fixed-parameter tractability, Treewidth, Linear programming

Discipline

Entrepreneurial and Small Business Operations | Operations and Supply Chain Management | Strategic Management Policy

Research Areas

Operations Management

Publication

Management Science

Volume

71

Issue

1

First Page

83

Last Page

102

ISSN

0025-1909

Identifier

10.1287/mnsc.2022.01759

Publisher

Institute for Operations Research and Management Sciences

Additional URL

https://doi.org/10.1287/mnsc.2022.01759

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