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Drug recall management and channel coordination under stochastic product defect severity: a game-Theoretic analytical study

Author

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  • Seyyed-Mahdi Hosseini-Motlagh
  • Mohammadreza Nematollahi
  • Nazanin Nami

Abstract

This paper analytically explores drug recall programmes in the pharmaceutical industry by considering the product defect severity as a source of uncertainty. Under the Stackelberg game model, a pharma-manufacturer outsources the drug recall management and pays collecting fees to a third party logistics provider (3PL) for collecting the defective medications. On the other side, the 3PL provides incentives to customers to facilitate product recall. In this research, we first analytically show the negative effect of lack of coordination between the pharma-manufacturer and 3PL. Then, a new coordination model, namely collecting fee agreement is proposed under which the pharma-manufacturer aims to motivate the 3PL to collect more defective medications. This research also analytically explores the effect of orchestrating the collecting fees and incentives under stochastic product defect severity. Finally, a Nash-bargaining game model is proposed to share the profits between the pharma-manufacturer and 3PL under the collecting fee agreement. Both analytical and numerical results reveal that the collecting fee agreement not only increases the collection rate of defective items and protects the patients from unsafe products, but also simultaneously improves the performances of whole pharmaceutical supply chain and its members while reducing the governmental penalties imposed on the pharma-manufacturer.

Suggested Citation

  • Seyyed-Mahdi Hosseini-Motlagh & Mohammadreza Nematollahi & Nazanin Nami, 2021. "Drug recall management and channel coordination under stochastic product defect severity: a game-Theoretic analytical study," International Journal of Production Research, Taylor & Francis Journals, vol. 59(6), pages 1649-1675, March.
  • Handle: RePEc:taf:tprsxx:v:59:y:2021:i:6:p:1649-1675
    DOI: 10.1080/00207543.2020.1723813
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