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State- and Control-Dependent Incentives in a Closed-Loop Supply Chain with Dynamic Returns

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  • Pietro De Giovanni

    (ESSEC Business School)

Abstract

This paper analyzes two incentive schemes available for a closed-loop supply chain (CLSC) in which a manufacturer and a retailer contribute to the return rate dynamics through their investments in green activity programs. Both firms have economic motivations to perform the return rate because customers who return end-of-use goods also repurchase new ones. In addition, the manufacturer exploits the returns’ residual value in operations to increase profits. Because the manufacturer has both operational and marketing motivations to close the loop, he can provide an incentive to the retailer to boost her investments in green activity programs. The incentive can be either state dependent or control dependent. The former assumes that the incentive depends on the fraction of customers who are willing to return end-of-use products; the latter is proportional to the retailer’s green activity programs efforts. Our results show that a state-dependent incentive is profit-Pareto-improving only when the retailer’s environmental effectiveness is large. In contrast, a control-dependent incentive mechanism is profit-Pareto-improving for low incentive values, high retailer’s environmental effectiveness, and customers’ repurchasing intention. In all other cases, players have divergent preferences and neither mechanism coordinates the CLSC.

Suggested Citation

  • Pietro De Giovanni, 2016. "State- and Control-Dependent Incentives in a Closed-Loop Supply Chain with Dynamic Returns," Dynamic Games and Applications, Springer, vol. 6(1), pages 20-54, March.
  • Handle: RePEc:spr:dyngam:v:6:y:2016:i:1:d:10.1007_s13235-015-0142-6
    DOI: 10.1007/s13235-015-0142-6
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    Cited by:

    1. Cristina Maranesi & Pietro De Giovanni, 2020. "Modern Circular Economy: Corporate Strategy, Supply Chain, and Industrial Symbiosis," Sustainability, MDPI, vol. 12(22), pages 1-25, November.
    2. Sacco, Armando & De Giovanni, Pietro, 2019. "Channel coordination with a manufacturer controlling the price and the effect of competition," Journal of Business Research, Elsevier, vol. 96(C), pages 97-114.
    3. Jun Wang & Qian Zhang & Xinman Lu & Rui Ma & Baoqin Yu & Huming Gao, 2022. "Emission reduction and coordination of a dynamic supply chain with green reputation," Operational Research, Springer, vol. 22(4), pages 3945-3988, September.
    4. Lang Liu & Lulu Wang & Taisheng Huang & Jinhui Pang, 2022. "The Differential Game of a Closed-Loop Supply Chain with Manufacturer Competition Considering Goodwill," Mathematics, MDPI, vol. 10(11), pages 1-18, May.
    5. De Giovanni, Pietro, 2018. "A joint maximization incentive in closed-loop supply chains with competing retailers: The case of spent-battery recycling," European Journal of Operational Research, Elsevier, vol. 268(1), pages 128-147.
    6. Ehsan Shekarian & Simme Douwe Flapper, 2021. "Analyzing the Structure of Closed-Loop Supply Chains: A Game Theory Perspective," Sustainability, MDPI, vol. 13(3), pages 1-32, January.
    7. Pietro De Giovanni & Georges Zaccour, 2022. "A selective survey of game-theoretic models of closed-loop supply chains," Annals of Operations Research, Springer, vol. 314(1), pages 77-116, July.
    8. Zhi-Hua Hu & Shu-Wen Wang, 2022. "An Evolutionary Game Model Between Governments and Manufacturers Considering Carbon Taxes, Subsidies, and Consumers’ Low-Carbon Preference," Dynamic Games and Applications, Springer, vol. 12(2), pages 513-551, June.
    9. Preeker, Tim & De Giovanni, Pietro, 2018. "Coordinating innovation projects with high tech suppliers through contracts," Research Policy, Elsevier, vol. 47(6), pages 1161-1172.
    10. Pietro Giovanni & Georges Zaccour, 2019. "A selective survey of game-theoretic models of closed-loop supply chains," 4OR, Springer, vol. 17(1), pages 1-44, March.

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