IDEAS home Printed from https://ideas.repec.org/h/wsi/wschap/9789811270277_0047.html
   My bibliography  Save this book chapter

Research on Evaluating the Digital Transformation Capability of Logistics Based on Structure Entropy Weight Method

In: Economic Management and Big Data Application Proceedings of the 3rd International Conference

Author

Listed:
  • Ruinan Wang
  • Qinglie Wu

Abstract

In the era of Industrial Revolution 4.0, digital transformation has become an important strategic choice for the development of logistics. In order to comprehensively evaluate the digital transformation capability of logistics, this paper analyzes the influencing factors and constructs an evaluation index system from five aspects. Then, the index weight is calculated by the structure entropy weight method, the evaluation score is obtained by the Delphi method, and the evaluation results are divided into five categories. Finally, an example is given to illustrate how the proposed evaluation method can effectively support digital transformation logistics decisions.

Suggested Citation

  • Ruinan Wang & Qinglie Wu, 2024. "Research on Evaluating the Digital Transformation Capability of Logistics Based on Structure Entropy Weight Method," World Scientific Book Chapters, in: Sikandar Ali Qalati (ed.), Economic Management and Big Data Application Proceedings of the 3rd International Conference, chapter 47, pages 529-547, World Scientific Publishing Co. Pte. Ltd..
    • Handle: RePEc:wsi:wschap:9789811270277_0047
    as

    Download full text from publisher

    File URL: https://www.worldscientific.com/doi/pdf/10.1142/9789811270277_0047
    Download Restriction: Ebook Access is available upon purchase.
    File URL: https://www.worldscientific.com/doi/abs/10.1142/9789811270277_0047
    Download Restriction: Ebook Access is available upon purchase.
    ---><---

    As the access to this document is restricted, you may want to search for a different version of it.

    More about this item

    Keywords

    Big Data; Information Management; Economic; Data Applications; Blockchain; E-commerce;
    All these keywords.

    JEL classification:

    • C63 - Mathematical and Quantitative Methods - - Mathematical Methods; Programming Models; Mathematical and Simulation Modeling - - - Computational Techniques
    • C8 - Mathematical and Quantitative Methods - - Data Collection and Data Estimation Methodology; Computer Programs
    • O14 - Economic Development, Innovation, Technological Change, and Growth - - Economic Development - - - Industrialization; Manufacturing and Service Industries; Choice of Technology

    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:wsi:wschap:9789811270277_0047. 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: Tai Tone Lim (email available below). General contact details of provider: http://www.worldscientific.com/page/worldscibooks .

    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.