Traceability Technology Adoption in Supply Chain Networks

Accepted for publication in Management Science

51 Pages Posted: 17 Mar 2021 Last revised: 31 Aug 2023

See all articles by Philippe Blaettchen

Philippe Blaettchen

Bayes Business School (formerly Cass)

Andre Calmon

Georgia Institute of Technology - Operations Management Area; INSEAD - Technology and Operations Management

Georgina Hall

INSEAD - Decision Sciences

Date Written: August 27, 2023

Abstract

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.

Keywords: supply chain traceability, sustainability, technology adoption, network diffusion, computational complexity, fixed-parameter tractability, treewidth

Suggested Citation

Blaettchen, Philippe and Calmon, Andre and Hall, Georgina, Traceability Technology Adoption in Supply Chain Networks (August 27, 2023). Accepted for publication in Management Science, Available at SSRN: https://ssrn.com/abstract=3805040 or http://dx.doi.org/10.2139/ssrn.3805040

Philippe Blaettchen (Contact Author)

Bayes Business School (formerly Cass) ( email )

United Kingdom

Andre Calmon

Georgia Institute of Technology - Operations Management Area ( email )

800 West Peachtree St.
Atlanta, GA 30308
United States

INSEAD - Technology and Operations Management ( email )

Boulevard de Constance
77 305 Fontainebleau Cedex
France

Georgina Hall

INSEAD - Decision Sciences ( email )

United States

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