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Joint optimisation of tracking capability and price in a supply chain with endogenous pricing

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  • James B. Dai
  • Lei Fan
  • Neville K.S. Lee
  • Jianbin Li

Abstract

Tracking systems have been widely used to resolve the issues of product recall and food safety. Thus far, few researches have been done on designing the tracking capability from the perspective of supply chain. In this paper, using the traceable unit size at the manufacturer level to measure the tracking capability, we propose a non-convex non-linear programming to jointly optimise the tracking capability and price considering the tracking cost and recall cost in a supply chain with endogenous pricing. Results show that, in both centralised and decentralised supply chains, there is a unique tracking capability and retailing/wholesale price with closed-form solutions to optimise the supply chain profit. When the cost ratio (unit tracking cost/unit recall cost) is sufficiently large and small, the optimal tracking strategy is barcode tracking and unit tracking, respectively, and otherwise, the optimal tracking strategy is batch tracking with an economic traceable unit size which depends on the cost ratio, quality inspection threshold, supply defection rate and the supplier’s tracking capability. Furthermore, in the context of large and small cost ratio, we find that improving tracking capability will enlarge and mitigate the effect of double marginalisation, respectively. In particular, we find that the strict tracking regulation policy is more robust than the subsidy policy to improve the supply chain tracking capability.

Suggested Citation

  • James B. Dai & Lei Fan & Neville K.S. Lee & Jianbin Li, 2017. "Joint optimisation of tracking capability and price in a supply chain with endogenous pricing," International Journal of Production Research, Taylor & Francis Journals, vol. 55(18), pages 5465-5484, September.
  • Handle: RePEc:taf:tprsxx:v:55:y:2017:i:18:p:5465-5484
    DOI: 10.1080/00207543.2017.1321800
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    References listed on IDEAS

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    1. Lindley, Bryan, 2007. "Trade-off between cost of traceability within a small and large commercial meat plant and economic benefits of reducing the number of recalls and size of recalls," ISU General Staff Papers 2007010108000015882, Iowa State University, Department of Economics.
    2. Fritz, Melanie & Schiefer, Gerhard, 2009. "Tracking, tracing, and business process interests in food commodities: A multi-level decision complexity," International Journal of Production Economics, Elsevier, vol. 117(2), pages 317-329, February.
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    Cited by:

    1. Hall, David C. & Johnson-Hall, Tracy D., 2021. "Recall effectiveness, strategy, and task complexity in the U.S. meat and poultry industry," International Journal of Production Economics, Elsevier, vol. 234(C).
    2. Dai, Bin & Nu, Yu & Xie, Xia & Li, Jianbin, 2021. "Interactions of traceability and reliability optimization in a competitive supply chain with product recall," European Journal of Operational Research, Elsevier, vol. 290(1), pages 116-131.
    3. Zhou, Xiongyong & Zhu, Qinghua & Xu, Zhiduan, 2023. "The role of contractual and relational governance for the success of digital traceability: Evidence from Chinese food producers," International Journal of Production Economics, Elsevier, vol. 255(C).
    4. Junhai Ma & Jiecai Chen & Yuxin Liu, 2022. "Research on optimization of food supply chain considering product traceability recall and safety investment," Managerial and Decision Economics, John Wiley & Sons, Ltd., vol. 43(8), pages 3953-3972, December.
    5. Montecchi, Matteo & Plangger, Kirk & West, Douglas C., 2021. "Supply chain transparency: A bibliometric review and research agenda," International Journal of Production Economics, Elsevier, vol. 238(C).

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