IDEAS home Printed from https://ideas.repec.org/h/spr/advbcp/978-94-6463-734-2_89.html

Green Supply Chain Finance Risk Assessment Model Based on TOPSIS Method

In: Proceedings of the 2025 10th International Conference on Social Sciences and Economic Development (ICSSED 2025)

Author

Listed:
  • Ying Zhou

    (XianDa College of Economics & Humanities Shanghai International Studies University, School of Digital Culture and Tourism)

  • Haobo Dong

    (China Road and Bridge Corporation)

Abstract

This study constructs a green supply chain finance risk assessment model based on the TOPSIS method and conducts an empirical analysis using Company H as a case study. First, an assessment indicator system covering exogenous risks, endogenous risks, and subject risks is developed, with the entropy weight method employed to determine indicator weights and reduce subjective influence. Subsequently, the TOPSIS method is used to calculate the green supply chain finance risk assessment values for Company H from 2016 to 2023. The results show an overall downward trend in risk levels, decreasing from 0.7959 in 2016 to 0.2427 in 2023, indicating significant achievements in the company’s green supply chain finance risk management. However, a slight increase (0.0001) in the risk assessment value was observed between 2021 and 2022, suggesting that the company should remain vigilant to potential new risks and continuously optimize its management system. This study enriches the theoretical framework of green supply chain finance risk assessment and provides a scientific decision-making basis for enterprises and financial institutions, contributing to the sustainable development of green supply chain finance.

Suggested Citation

  • Ying Zhou & Haobo Dong, 2025. "Green Supply Chain Finance Risk Assessment Model Based on TOPSIS Method," Advances in Economics, Business and Management Research, in: Huaping Sun & Hang Luo & Vilas Gaikar & Natālija Cudečka-Puriņa (ed.), Proceedings of the 2025 10th International Conference on Social Sciences and Economic Development (ICSSED 2025), pages 810-816, Springer.
    • Handle: RePEc:spr:advbcp:978-94-6463-734-2_89
    DOI: 10.2991/978-94-6463-734-2_89
    as

    Download full text from publisher

    To our knowledge, this item is not available for download. To find whether it is available, there are three options:
    1. Check below whether another version of this item is available online.
    2. Check on the provider's web page whether it is in fact available.
    3. Perform a
    for a similarly titled item that would be available.

    More about this item

    Keywords

    ;
    ;
    ;
    ;
    ;

    Statistics

    Access and download statistics

    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:spr:advbcp:978-94-6463-734-2_89. 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.

    We have no bibliographic references for this item. You can help adding them by using 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: Sonal Shukla or Springer Nature Abstracting and Indexing (email available below). General contact details of provider: http://www.springer.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.