IDEAS home Printed from https://ideas.repec.org/a/gam/jijerp/v19y2022i24p16892-d1005028.html
   My bibliography  Save this article

Risk Assessment of Import Cold Chain Logistics Based on Entropy Weight Matter Element Extension Model: A Case Study of Shanghai, China

Author

Listed:
  • Qiang Fu

    (College of Transport and Communications, Shanghai Maritime University, Shanghai 201306, China)

  • Yurou Sun

    (College of Transport and Communications, Shanghai Maritime University, Shanghai 201306, China)

  • Lei Wang

    (College of Transport and Communications, Shanghai Maritime University, Shanghai 201306, China)

Abstract

The development of world trade and fresh-keeping technology has led to the rapid development of international cold chain logistics. However, the novel coronavirus epidemic continues to spread around the world at the present stage, which challenges disease transmission control and safety supervision of international cold chain logistics. Constructing an Import Cold Chain Logistics Safety Supervision System (ICCL-SSS) is helpful for detecting and controlling disease import risk. This paper constructs an evaluation index system of ICCL safety that comprehensively considers the potential risk factors of three ICCL processes: the logistics process in port, the customs clearance process, and the logistics process from port to door. The risk level of ICCL-SSS is evaluated by combining the Extension Decision-making Model and the Entropy Weight Method. The case study of Shanghai, China, the world’s largest city of ICCL, shows that the overall risk level of ICCL-SSS in Shanghai is at a moderate level. However, the processes of loading and unloading, inspection and quarantine, disinfection and sterilization, and cargo storage are at high risk specifically. The construction and risk assessment of ICCL-SSS can provide theoretical support and practical guidance for improving the safety supervision ability of ICCL regulation in the post-epidemic era, and helps the local government to scientifically formulate ICCL safety administration policies and accelerate the development of world cold chain trade.

Suggested Citation

  • Qiang Fu & Yurou Sun & Lei Wang, 2022. "Risk Assessment of Import Cold Chain Logistics Based on Entropy Weight Matter Element Extension Model: A Case Study of Shanghai, China," IJERPH, MDPI, vol. 19(24), pages 1-16, December.
    • Handle: RePEc:gam:jijerp:v:19:y:2022:i:24:p:16892-:d:1005028
    as

    Download full text from publisher

    File URL: https://www.mdpi.com/1660-4601/19/24/16892/pdf
    Download Restriction: no
    File URL: https://www.mdpi.com/1660-4601/19/24/16892/
    Download Restriction: no
    ---><---

    References listed on IDEAS

    as
    1. Songyi Wang & Fengming Tao & Yuhe Shi, 2018. "Optimization of Location–Routing Problem for Cold Chain Logistics Considering Carbon Footprint," IJERPH, MDPI, vol. 15(1), pages 1-17, January.
    2. Yuangang Li & Maohua Sun & Guanghui Yuan & Yujing Liu, 2019. "Evaluation Methods of Water Environment Safety and Their Application to the Three Northeast Provinces of China," Sustainability, MDPI, vol. 11(18), pages 1-16, September.
    3. Jie Chang & Xiaojun Zuo & Botao Hou & Lipeng Shi & Guanghua Zhang & Zhihan Lv, 2021. "Internet of Things Security Detection Technology Based on Grey Association Decision Algorithm," Complexity, Hindawi, vol. 2021, pages 1-12, June.
    4. Adarsh Kumar Singh & Nachiappan Subramanian & Kulwant Singh Pawar & Ruibin Bai, 2018. "Cold chain configuration design: location-allocation decision-making using coordination, value deterioration, and big data approximation," Annals of Operations Research, Springer, vol. 270(1), pages 433-457, November.
    5. Gaoyuan Qin & Fengming Tao & Lixia Li, 2019. "A Vehicle Routing Optimization Problem for Cold Chain Logistics Considering Customer Satisfaction and Carbon Emissions," IJERPH, MDPI, vol. 16(4), pages 1-17, February.
    6. Yuexiang Yang & Xiaoyu Zheng & Zhen Sun, 2020. "Coal Resource Security Assessment in China: A Study Using Entropy-Weight-Based TOPSIS and BP Neural Network," Sustainability, MDPI, vol. 12(6), pages 1-15, March.
    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. Wenzhu Liao & Lin Liu & Jiazhuo Fu, 2019. "A Comparative Study on the Routing Problem of Electric and Fuel Vehicles Considering Carbon Trading," IJERPH, MDPI, vol. 16(17), pages 1-25, August.
    2. Qi Yao & Shenjun Zhu & Yanhui Li, 2022. "Green Vehicle-Routing Problem of Fresh Agricultural Products Considering Carbon Emission," IJERPH, MDPI, vol. 19(14), pages 1-17, July.
    3. Hongli Zhu & Congcong Liu & Guanghua Wu & Yanjun Gao, 2023. "Cold Chain Logistics Network Design for Fresh Agricultural Products with Government Subsidy," Sustainability, MDPI, vol. 15(13), pages 1-13, June.
    4. Ling Shen & Fengming Tao & Yuhe Shi & Ruiru Qin, 2019. "Optimization of Location-Routing Problem in Emergency Logistics Considering Carbon Emissions," IJERPH, MDPI, vol. 16(16), pages 1-18, August.
    5. Hang Thi Thanh Vu & Jeonghan Ko, 2023. "Inventory Transshipment Considering Greenhouse Gas Emissions for Sustainable Cross-Filling in Cold Supply Chains," Sustainability, MDPI, vol. 15(9), pages 1-22, April.
    6. Longlong Leng & Yanwei Zhao & Jingling Zhang & Chunmiao Zhang, 2019. "An Effective Approach for the Multiobjective Regional Low-Carbon Location-Routing Problem," IJERPH, MDPI, vol. 16(11), pages 1-28, June.
    7. Ghazale Kordi & Parsa Hasanzadeh-Moghimi & Mohammad Mahdi Paydar & Ebrahim Asadi-Gangraj, 2023. "A multi-objective location-routing model for dental waste considering environmental factors," Annals of Operations Research, Springer, vol. 328(1), pages 755-792, September.
    8. Felipe Arenas-Torres & Miguel Bustamante-Ubilla & Roberto Campos-Troncoso, 2021. "The Incidence of Social Responsibility in the Adoption of Business Practices," Sustainability, MDPI, vol. 13(5), pages 1-14, March.
    9. Yuhe Shi & Zhenggang He, 2018. "Decision Analysis of Disturbance Management in the Process of Medical Supplies Transportation after Natural Disasters," IJERPH, MDPI, vol. 15(8), pages 1-18, August.
    10. Sina Abbasi & Maryam Moosivand & Ilias Vlachos & Mohammad Talooni, 2023. "Designing the Location–Routing Problem for a Cold Supply Chain Considering the COVID-19 Disaster," Sustainability, MDPI, vol. 15(21), pages 1-24, October.
    11. Ling Shen & Fengming Tao & Songyi Wang, 2018. "Multi-Depot Open Vehicle Routing Problem with Time Windows Based on Carbon Trading," IJERPH, MDPI, vol. 15(9), pages 1-20, September.
    12. Ao Lv & Baofeng Sun, 2022. "Multi-Objective Robust Optimization for the Sustainable Location-Inventory-Routing Problem of Auto Parts Supply Logistics," Mathematics, MDPI, vol. 10(16), pages 1-22, August.
    13. Zhichao Ma & Jie Zhang & Huanhuan Wang & Shaochan Gao, 2023. "Optimization of Sustainable Bi-Objective Cold-Chain Logistics Route Considering Carbon Emissions and Customers’ Immediate Demands in China," Sustainability, MDPI, vol. 15(7), pages 1-23, March.
    14. Xuya Zhang & Yue Wang & Dongqing Zhang, 2024. "Location-Routing Optimization for Two-Echelon Cold Chain Logistics of Front Warehouses Based on a Hybrid Ant Colony Algorithm," Mathematics, MDPI, vol. 12(12), pages 1-22, June.
    15. Raut, Rakesh D. & Gardas, Bhaskar B. & Narwane, Vaibhav S. & Narkhede, Balkrishna E., 2019. "Improvement in the food losses in fruits and vegetable supply chain - a perspective of cold third-party logistics approach," Operations Research Perspectives, Elsevier, vol. 6(C).
    16. Rodrigo de Almeida Silva & Marina Paula Secco & Jean Carlo Salomé dos Santos Menezes & Ivo André Homrich Schneider & Richard Thomas Lermen, 2022. "Reduction of High-Chromium-Containing Wastewater in the Leaching of Pyritic Waste Rocks from Coal Mines," Sustainability, MDPI, vol. 14(19), pages 1-15, September.
    17. Zhitao Xu & Adel Elomri & Roberto Baldacci & Laoucine Kerbache & Zhenyong Wu, 2024. "Frontiers and trends of supply chain optimization in the age of industry 4.0: an operations research perspective," Annals of Operations Research, Springer, vol. 338(2), pages 1359-1401, July.
    18. Ziyu Shan & Jianming Yao, 2024. "Resource Scheduling Optimization of Fresh Food Delivery Porters Considering Ambient Temperature Variations," Sustainability, MDPI, vol. 16(9), pages 1-25, April.
    19. Ning Zhang & Zaiwu Gong & Kedong Yin & Yuhong Wang, 2018. "Special Issue “Decision Models in Green Growth and Sustainable Development”," IJERPH, MDPI, vol. 15(6), pages 1-8, May.
    20. Hailin Wu & Fengming Tao & Qingqing Qiao & Mengjun Zhang, 2020. "A Chance-Constrained Vehicle Routing Problem for Wet Waste Collection and Transportation Considering Carbon Emissions," IJERPH, MDPI, vol. 17(2), pages 1-21, January.

    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:jijerp:v:19:y:2022:i:24:p:16892-:d:1005028. 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.