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Trade-In and Trade-Old-for-Remanufactured in Closed-Loop Supply Chain Under Different Power Structures and Government Subsidy

Author

Listed:
  • Kailing Liu
  • Quanxi Li
  • Jinda Liu
  • Yi Li

Abstract

Trade-in (TON) and trade-old-for-remanufactured (TOR) programs are commonly used to boost consumer demand and recycle old products, and can generate significant economic benefits from disassembling or reusing old products. However, the influence of channel structures on the TON and TOR optimal decisions of closed-loop supply chains (CLSCs) is rarely discussed. To explore the impact of the implementation of the TOR program on the optimal pricing and demand strategy, enterprise profit, environment, and social welfare when the enterprise has applied the TON program, we develop four models with different power structures and market decisions to maximize enterprise profits based on consumer utility and the Stackelberg game: (1) manufacturer-led model with TON (Model M); (2) retailer-led model with TON (Model R); (3) manufacturer-led model with TON and TOR (Model TM); (4) retailer-led model with TON and TOR (Model TR). The manufacturer-led models may benefit consumers more and stimulate the replacement consumers’ demand for TON and TOR programs. Both TON and TOR demand for the Model TM are considerable. However, when the retailer is in the driver’s seat, the retailer can profit more due to government subsidies for the TOR programs. Our analysis provides insights into the choice of corporate power structures, reducing environmental impacts and improving social welfare. This paper studies for the first time the influence of different power structures and government subsidies on TON and TOR programs in CLSCs. Future research could consider the impact of old products quality or multi-period models on TON and TOR programs.

Suggested Citation

  • Kailing Liu & Quanxi Li & Jinda Liu & Yi Li, 2024. "Trade-In and Trade-Old-for-Remanufactured in Closed-Loop Supply Chain Under Different Power Structures and Government Subsidy," SAGE Open, , vol. 14(2), pages 21582440241, May.
    • Handle: RePEc:sae:sagope:v:14:y:2024:i:2:p:21582440241251474
    DOI: 10.1177/21582440241251474
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