IDEAS home Printed from https://ideas.repec.org/a/gam/jsusta/v16y2024i15p6294-d1441088.html
   My bibliography  Save this article

The Optimal Logistics Distribution Service Strategy of the E-commerce Closed-Loop Supply Chain Network under Blockchain Technology and the Government Blockchain Subsidy

Author

Listed:
  • Yan Zhou

    (Business School, Qingdao University, Qingdao 266071, China)

  • Cong Liang

    (Business School, Qingdao University, Qingdao 266071, China)

  • Kar-Hung Wong

    (School of Computer Science and Applied Mathematics, University of the Witwatersrand, Johannesburg 2000, South Africa)

Abstract

The booming development of e-commerce has promoted the diversified development of logistics distribution services (LDS). For LDS, e-commerce retailers (e-retailers) often choose either the outsourced logistics distribution services strategy (OLDSS) or the self-built logistics distribution services strategy (SBLDSS). Although there are problems such as products getting lost and damaged during the logistics distribution process, the high transparency and traceability characteristics of blockchain technology (BT) can help solve the problem of products being lost and damaged in the logistics distribution process. However, due to the high cost of BT, e-retailers may encounter reduced sales, which causes the supply chain corporate profits to decrease. To encourage the BT investment enthusiasm of the e-retailers and regulate corporate profits, the government implements subsidies for e-retailers’ BT, namely, the government blockchain subsidy (GBS). In addition, in recent years, environmental degradation has become increasingly severe, causing negative impacts on people’s lives. To promote sustainable development, we use variational inequality to establish an e-commerce closed-loop supply chain (E-CLSC) network equilibrium model in which the network equilibrium decisions of e-retailers choosing the OLDSS and those choosing the SBLDSS are obtained. Then, we analyze the impact of the BT input cost and the GBS quota on equilibrium decisions by studying their properties and verifying the theoretical results by performing numerical examples. Finally, we analyze the profits of the e-retailers to obtain the impact of the BT input cost and the GBS quota on e-retailers’ choice of the optimal LDS strategy; in this way, we provide a scientific basis for e-retailers to choose the optimal LDS strategy. The results show that increasing the BT input costs reduces e-retailers’ product sales under the two LDS strategies, which decreases the production rate and the recovery rate of the products. When the BT input cost is low, SBLDSS is the best choice for e-retailers. When the BT input cost is high, OLDSS is the best choice for e-retailers. Moreover, there is a positive correlation between GBS and e-retailers’ product sales; thus, GBS is conducive to expanding market demand, regulating the profits of manufacturers, increasing the e-retailers’ profits, improving the enthusiasm of the e-retailers for BT investment, and promoting the overall development of supply chain enterprises. For e-retailers, choosing the OLDSS can lead to a better development of the E-CLSC.

Suggested Citation

  • Yan Zhou & Cong Liang & Kar-Hung Wong, 2024. "The Optimal Logistics Distribution Service Strategy of the E-commerce Closed-Loop Supply Chain Network under Blockchain Technology and the Government Blockchain Subsidy," Sustainability, MDPI, vol. 16(15), pages 1-29, July.
  • Handle: RePEc:gam:jsusta:v:16:y:2024:i:15:p:6294-:d:1441088
    as

    Download full text from publisher

    File URL: https://www.mdpi.com/2071-1050/16/15/6294/pdf
    Download Restriction: no

    File URL: https://www.mdpi.com/2071-1050/16/15/6294/
    Download Restriction: no
    ---><---

    References listed on IDEAS

    as
    1. Wang, Lisha & Chen, Jing & Lu, Yali, 2022. "Manufacturer's channel and logistics strategy in a supply chain," International Journal of Production Economics, Elsevier, vol. 246(C).
    2. Yan Zhou & Miao Hou & Kar-Hung Wong, 2023. "The Optimal Remanufacturing Strategy of the Closed-Loop Supply Chain Network under Government Regulation and the Manufacturer’s Design for the Environment," Sustainability, MDPI, vol. 15(9), pages 1-34, April.
    3. Chan, Chi Kin & Zhou, Yan & Wong, Kar Hung, 2018. "A dynamic equilibrium model of the oligopolistic closed-loop supply chain network under uncertain and time-dependent demands," Transportation Research Part E: Logistics and Transportation Review, Elsevier, vol. 118(C), pages 325-354.
    4. Zhang, Qian & Li, Yongjian & Hou, Pengwen & Wang, Jun, 2024. "Price signal or blockchain technology? Quality information disclosure in dual-channel supply chains," European Journal of Operational Research, Elsevier, vol. 316(1), pages 126-137.
    5. Hammond, David & Beullens, Patrick, 2007. "Closed-loop supply chain network equilibrium under legislation," European Journal of Operational Research, Elsevier, vol. 183(2), pages 895-908, December.
    6. Wu, Qing & Mu, Yinping & Feng, Yi, 2015. "Coordinating contracts for fresh product outsourcing logistics channels with power structures," International Journal of Production Economics, Elsevier, vol. 160(C), pages 94-105.
    7. Yang, Guang-fen & Wang, Zhi-ping & Li, Xiao-qiang, 2009. "The optimization of the closed-loop supply chain network," Transportation Research Part E: Logistics and Transportation Review, Elsevier, vol. 45(1), pages 16-28, January.
    8. Morkunas, Vida J. & Paschen, Jeannette & Boon, Edward, 2019. "How blockchain technologies impact your business model," Business Horizons, Elsevier, vol. 62(3), pages 295-306.
    9. R. Canan Savaskan & Shantanu Bhattacharya & Luk N. Van Wassenhove, 2004. "Closed-Loop Supply Chain Models with Product Remanufacturing," Management Science, INFORMS, vol. 50(2), pages 239-252, February.
    10. Saberi, Sara & Cruz, Jose M. & Sarkis, Joseph & Nagurney, Anna, 2018. "A competitive multiperiod supply chain network model with freight carriers and green technology investment option," European Journal of Operational Research, Elsevier, vol. 266(3), pages 934-949.
    11. Cao, Kaiying & Xu, Yuqiu & Hua, Ye & Choi, Tsan-Ming, 2023. "Supplier or co-optor: Optimal channel and logistics selection problems on retail platforms," European Journal of Operational Research, Elsevier, vol. 311(3), pages 971-988.
    12. I-Hsuan Hong & Pin-Chun Chen & Hsien-Ting Yu, 2016. "The effects of government subsidies on decentralised reverse supply chains," International Journal of Production Research, Taylor & Francis Journals, vol. 54(13), pages 3962-3977, July.
    13. Niu, Baozhuang & Dong, Jian & Liu, Yaoqi, 2021. "Incentive alignment for blockchain adoption in medicine supply chains," Transportation Research Part E: Logistics and Transportation Review, Elsevier, vol. 152(C).
    14. Baozhuang Niu & Jianhua Zhang & Zihao Mu, 2023. "IoT-enabled delivery time guarantee in logistics outsourcing and efficiency improvement," International Journal of Production Research, Taylor & Francis Journals, vol. 61(12), pages 4135-4156, June.
    Full references (including those not matched with items on IDEAS)

    Most related items

    These are the items that most often cite the same works as this one and are cited by the same works as this one.
    1. Yan Zhou & Xin-Tong Lin & Zhi-Ping Fan & Kar-Hung Wong, 2022. "Remanufacturing Strategy Choice of a Closed-Loop Supply Chain Network Considering Carbon Emission Trading, Green Innovation, and Green Consumers," IJERPH, MDPI, vol. 19(11), pages 1-42, June.
    2. Zhang, Abraham & Wang, Jason X. & Farooque, Muhammad & Wang, Yulan & Choi, Tsan-Ming, 2021. "Multi-dimensional circular supply chain management: A comparative review of the state-of-the-art practices and research," Transportation Research Part E: Logistics and Transportation Review, Elsevier, vol. 155(C).
    3. Yan Zhou & Xue-Qi Liu & Kar-Hung Wong, 2021. "Remanufacturing Policies Options for a Closed-Loop Supply Chain Network," Sustainability, MDPI, vol. 13(12), pages 1-26, June.
    4. Chan, Chi Kin & Zhou, Yan & Wong, Kar Hung, 2019. "An equilibrium model of the supply chain network under multi-attribute behaviors analysis," European Journal of Operational Research, Elsevier, vol. 275(2), pages 514-535.
    5. Hamdouch, Younes & Ghoudi, Kilani, 2020. "A Supply Chain Equilibrium Model with General Price-Dependent Demand," Operations Research Perspectives, Elsevier, vol. 7(C).
    6. Yan Zhou & Miao Hou & Kar-Hung Wong, 2023. "The Optimal Remanufacturing Strategy of the Closed-Loop Supply Chain Network under Government Regulation and the Manufacturer’s Design for the Environment," Sustainability, MDPI, vol. 15(9), pages 1-34, April.
    7. Tao, Zhang Gui & Guang, Zhong Yong & Hao, Sun & Song, Hu Jin & Xin, Dai Geng, 2015. "Multi-period closed-loop supply chain network equilibrium with carbon emission constraints," Resources, Conservation & Recycling, Elsevier, vol. 104(PB), pages 354-365.
    8. Zhou, Yan & Chan, Chi Kin & Wong, Kar Hung, 2018. "A multi-period supply chain network equilibrium model considering retailers’ uncertain demands and dynamic loss-averse behaviors," Transportation Research Part E: Logistics and Transportation Review, Elsevier, vol. 118(C), pages 51-76.
    9. Fu, Lingxian & Meng, Fanyong, 2020. "A human disease transmission inspired dynamic model for closed-loop supply chain management," Transportation Research Part E: Logistics and Transportation Review, Elsevier, vol. 134(C).
    10. Chung, Sung H. & Weaver, Robert D. & Friesz, Terry L., 2013. "Strategic response to pollution taxes in supply chain networks: Dynamic, spatial, and organizational dimensions," European Journal of Operational Research, Elsevier, vol. 231(2), pages 314-327.
    11. Guojun Ji & Zhongfeng Sun & Kim Hua Tan, 2021. "Collaborative Rebate Strategy of Business-to-Customer Platforms Considering Recycling and Trade-Ins Simultaneously," Sustainability, MDPI, vol. 13(4), pages 1-19, February.
    12. De Giovanni, Pietro & Zaccour, Georges, 2014. "A two-period game of a closed-loop supply chain," European Journal of Operational Research, Elsevier, vol. 232(1), pages 22-40.
    13. Yang, Yuxiang & Goodarzi, Shadi & Jabbarzadeh, Armin & Fahimnia, Behnam, 2022. "In-house production and outsourcing under different emissions reduction regulations: An equilibrium decision model for global supply chains," Transportation Research Part E: Logistics and Transportation Review, Elsevier, vol. 157(C).
    14. Qiuyun Zhu & Xiaoyang Zhou & Aijun Liu & Chong Gao & Lei Xu & Fan Zhao & Ding Zhang & Benjamin Lev, 2022. "Equilibrium Optimization with Multi-Energy-Efficiency-Grade Products: Government and Market Perspective," Energies, MDPI, vol. 15(19), pages 1-23, October.
    15. Ebrahimi Bajgani, Sahar & Saberi, Sara & Toyasaki, Fuminori, 2023. "Designing a reverse supply chain network with quality control for returned products: Strategies to mitigate free-riding effect and ensure compliance with technology licensing requirements," Technological Forecasting and Social Change, Elsevier, vol. 195(C).
    16. Renbang Shan & Li Luo & Baoli Shi, 2023. "The choice of recycling strategies for decision-makers based on government subsidy and service budget," Environment, Development and Sustainability: A Multidisciplinary Approach to the Theory and Practice of Sustainable Development, Springer, vol. 25(2), pages 1441-1472, February.
    17. Xiong, Yu & Zhou, Yu & Li, Gendao & Chan, Hing-Kai & Xiong, Zhongkai, 2013. "Don’t forget your supplier when remanufacturing," European Journal of Operational Research, Elsevier, vol. 230(1), pages 15-25.
    18. Tatsuya Hirano & Yasushi Narushima, 2019. "Robust Supply Chain Network Equilibrium Model," Transportation Science, INFORMS, vol. 53(4), pages 1196-1212, July.
    19. E. Allevi & A. Gnudi & I. V. Konnov & G. Oggioni, 2018. "Evaluating the effects of environmental regulations on a closed-loop supply chain network: a variational inequality approach," Annals of Operations Research, Springer, vol. 261(1), pages 1-43, February.
    20. Xin Zhang & Gang Zhao & Yingxiu Qi & Botang Li, 2019. "A Robust Fuzzy Optimization Model for Closed-Loop Supply Chain Networks Considering Sustainability," Sustainability, MDPI, vol. 11(20), pages 1-24, October.

    Corrections

    All material on this site has been provided by the respective publishers and authors. You can help correct errors and omissions. When requesting a correction, please mention this item's handle: RePEc:gam:jsusta:v:16:y:2024:i:15:p:6294-:d:1441088. See general information about how to correct material in RePEc.

    If you have authored this item and are not yet registered with RePEc, we encourage you to do it here. This allows to link your profile to this item. It also allows you to accept potential citations to this item that we are uncertain about.

    If CitEc recognized a bibliographic reference but did not link an item in RePEc to it, you can help with this form .

    If you know of missing items citing this one, you can help us creating those links by adding the relevant references in the same way as above, for each refering item. If you are a registered author of this item, you may also want to check the "citations" tab in your RePEc Author Service profile, as there may be some citations waiting for confirmation.

    For technical questions regarding this item, or to correct its authors, title, abstract, bibliographic or download information, contact: MDPI Indexing Manager (email available below). General contact details of provider: https://www.mdpi.com .

    Please note that corrections may take a couple of weeks to filter through the various RePEc services.

    IDEAS is a RePEc service. RePEc uses bibliographic data supplied by the respective publishers.