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This work is licensed under a Creative Commons Attribution 4.0 International License (CC BY 4.0).
© 2026 Informa UK Limited, trading as Taylor & Francis Group.The intelligent coordination level of platform-based logistics service supply chains exhibits dynamic evolutionary characteristics. However, existing evaluation methods are predominantly static and fail to fully capture the distinctive structural features and temporal evolution patterns of such supply chains. To address this gap, this paper develops a tailored evaluation index system for assessing the intelligent coordination level of platform-based logistics service supply chains. It further proposes an improved entropy-weighted Technique for Order Preference by Similarity to Ideal Solution (TOPSIS) method for dynamic evaluation. This approach effectively accommodates the mixed nature of the index system, which includes qualitative and quantitative indicators as well as interval and fixed-value indicators. By incorporating a growth coefficient and applying quadratic weighting, the method enables dynamic tracking and comprehensive assessment of coordination evolution over time, overcoming the limitations of traditional static analysis. Empirical applications involving three platform enterprises validate the feasibility of the proposed method, demonstrating its effectiveness in identifying governance deficiencies and revealing dynamic trends in coordination performance. This study offers a comprehensive framework for enterprises to assess supply chain coordination under the influence of intelligent technologies. It thereby facilitates digital transformation, promotes inter-enterprise cooperation, and enhances the competitive advantage of logistics enterprises.
Author(s): Liu W, Wang Q, Tang O, Dong J
Publication type: Article
Publication status: Published
Journal: International Journal of Production Research
Year: 2026
Pages: Epub ahead of print
Online publication date: 10/03/2026
Acceptance date: 01/03/2026
Date deposited: 02/03/2026
ISSN (print): 0020-7543
ISSN (electronic): 1366-588X
Publisher: Taylor and Francis Ltd
URL: https://doi.org/10.1080/00207543.2026.2642414
DOI: 10.1080/00207543.2026.2642414
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