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Competitive Pricing and Remanufacturing Problem in an Uncertain Closed-Loop Supply Chain with Risk-Sensitive Retailers

Author

Listed:
  • Hua Ke

    (School of Economics and Management, Tongji University, Shanghai 200092, P. R. China)

  • Yong Wu

    (School of Economics and Management, Tongji University, Shanghai 200092, P. R. China)

  • Hu Huang

    (School of Economics and Management, Tongji University, Shanghai 200092, P. R. China)

Abstract

Nowadays, pricing and remanufacturing problems under uncertain markets have gained increasing attention from both industrial and academic fields. In the literature, it is generally assumed that all the channel members are risk-neutral, ignoring the influences of channel members’ risk attitudes in the face of dynamic market. This paper focuses on a pricing problem in a closed-loop supply chain (CLSC) with two competitive risk-sensitive retailers under uncertain environment. The uncertainty is associated with the recycling costs, consumer demands and remanufacturing costs. Due to the dynamic market, supply chain managers may be unable to collect enough historical data to estimate these demands and costs when making pricing and remanufacturing decisions. In such cases, experts’ estimations are usually employed to describe these uncertain parameters. To deal with these human estimations, an uncertainty theory-based model is proposed. Based on the equilibrium results, how the retailers’ risk sensitivity and human estimations (uncertain degrees) affect the prices and profits is analyzed. It is found that both the retailers will get lower profits while the manufacturer will gain more profit when either of the two retailers becomes more risk-averse. We also find that a higher level of uncertainty in the supply chain will induce a higher collecting rate.

Suggested Citation

  • Hua Ke & Yong Wu & Hu Huang, 2018. "Competitive Pricing and Remanufacturing Problem in an Uncertain Closed-Loop Supply Chain with Risk-Sensitive Retailers," Asia-Pacific Journal of Operational Research (APJOR), World Scientific Publishing Co. Pte. Ltd., vol. 35(01), pages 1-21, February.
  • Handle: RePEc:wsi:apjorx:v:35:y:2018:i:01:n:s0217595918500033
    DOI: 10.1142/S0217595918500033
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    References listed on IDEAS

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    Cited by:

    1. Weisheng Deng, 2020. "Sustainable development: Impacts of consumers' risk aversion on remanufacturing model selection and environmental performance," Sustainable Development, John Wiley & Sons, Ltd., vol. 28(6), pages 1564-1574, November.
    2. 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.
    3. Muhammad Omair & Mohammed Alkahtani & Kashif Ayaz & Ghulam Hussain & Johannes Buhl, 2022. "Supply Chain Modelling of the Automobile Multi-Stage Production Considering Circular Economy by Waste Management Using Recycling and Reworking Operations," Sustainability, MDPI, vol. 14(22), pages 1-26, November.
    4. Zheng, Xiao-Xue & Li, Deng-Feng & Liu, Zhi & Jia, Fu & Sheu, Jiuh-Biing, 2019. "Coordinating a closed-loop supply chain with fairness concerns through variable-weighted Shapley values," Transportation Research Part E: Logistics and Transportation Review, Elsevier, vol. 126(C), pages 227-253.
    5. Lingli Shu & Xuedong Liang & Jingyuan Yao & Peng Luo, 2023. "Price Optimization of Closed-loop Supply Chain With Uncertain Demand Under Multi-channel Cross Influence," SAGE Open, , vol. 13(4), pages 21582440231, December.
    6. Lin Chen & Ting Dong & Jin Peng & Dan Ralescu, 2023. "Uncertainty Analysis and Optimization Modeling with Application to Supply Chain Management: A Systematic Review," Mathematics, MDPI, vol. 11(11), pages 1-45, May.
    7. Maojun Zhang & Jiaqi Li & Feifei Liu & Jiangxia Nan & Jiawen Jiang, 2024. "Pricing and Financing Strategies of Dual-Channel Green Supply Chain with Risk Aversion and Consumer Preferences," Sustainability, MDPI, vol. 16(13), pages 1-26, June.
    8. Shen, Jiayu, 2020. "An uncertain sustainable supply chain network," Applied Mathematics and Computation, Elsevier, vol. 378(C).

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