IDEAS home Printed from https://ideas.repec.org/a/gam/jsusta/v17y2025i2p659-d1568147.html
   My bibliography  Save this article

The Impact of Intelligent Logistics on Logistics Performance Improvement

Author

Listed:
  • Aishan Ye

    (Faculty of Humanities and Social Sciences, Macao Polytechnic University, Macao 999078, China
    College of Yonyou Digital & Intelligence, Nantong Institute of Technology, Nantong 226000, China)

  • Jiayi Cai

    (College of Yonyou Digital & Intelligence, Nantong Institute of Technology, Nantong 226000, China)

  • Zhenjie Yang

    (Faculty of Humanities and Social Sciences, Macao Polytechnic University, Macao 999078, China)

  • Yangyang Deng

    (College of Yonyou Digital & Intelligence, Nantong Institute of Technology, Nantong 226000, China)

  • Xiaohua Li

    (College of Yonyou Digital & Intelligence, Nantong Institute of Technology, Nantong 226000, China)

Abstract

The logistics industry is essential to global economic development but continues to grapple with challenges related to quality improvement, cost reduction, and efficiency enhancement. Addressing these issues is crucial for promoting high-quality growth within the sector. The emergence of intelligent logistics—leveraging automation, data analytics, and Internet of Things (IoT) technologies—offers a promising approach to transforming traditional logistics operations. This study develops a theoretical framework that integrates these intelligent logistics components to investigate their mechanisms and limitations in influencing logistics performance. Using an empirical analysis of Chinese provincial panel data, we identify significant disparities in logistics industry performance across the provinces, with most regions exhibiting an initial improvement followed by a subsequent decline. Our findings reveal a notable spatial interaction effect between intelligent logistics and logistics performance, indicating that intelligent logistics substantially enhance performance. However, the impact varies by region: it significantly promotes performance in the eastern and western regions but has a limited effect in the central and northeastern regions, potentially due to distortions in production factors and other regional specificities. Additionally, the degree of openness to the outside world positively influences logistics performance in the western region. The proposed mechanisms are validated in all regions except the eastern region. This study provides valuable insights for policymakers on leveraging intelligent logistics to improve logistics industry performance, highlighting the need for region-specific strategies to maximize the benefits of intelligent logistics technologies.

Suggested Citation

  • Aishan Ye & Jiayi Cai & Zhenjie Yang & Yangyang Deng & Xiaohua Li, 2025. "The Impact of Intelligent Logistics on Logistics Performance Improvement," Sustainability, MDPI, vol. 17(2), pages 1-19, January.
    • Handle: RePEc:gam:jsusta:v:17:y:2025:i:2:p:659-:d:1568147
    as

    Download full text from publisher

    File URL: https://www.mdpi.com/2071-1050/17/2/659/pdf
    Download Restriction: no
    File URL: https://www.mdpi.com/2071-1050/17/2/659/
    Download Restriction: no
    ---><---

    References listed on IDEAS

    as
    1. Weidong Jiang & Naiwen Li, 2024. "The Intelligent Upgrading of Logistics between an Internet Enterprise and a Logistics Enterprise Based on Differential Game Theory," Sustainability, MDPI, vol. 16(19), pages 1-22, October.
    2. Daron Acemoglu & Pascual Restrepo, 2019. "Automation and New Tasks: How Technology Displaces and Reinstates Labor," Journal of Economic Perspectives, American Economic Association, vol. 33(2), pages 3-30, Spring.
    3. Cui, Huixia & Chen, Xiangyong & Guo, Ming & Jiao, Yang & Cao, Jinde & Qiu, Jianlong, 2023. "A distribution center location optimization model based on minimizing operating costs under uncertain demand with logistics node capacity scalability," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 610(C).
    4. Su, Liangjun & Wang, Wuyi & Xu, Xingbai, 2023. "Identifying latent group structures in spatial dynamic panels," Journal of Econometrics, Elsevier, vol. 235(2), pages 1955-1980.
    Full references (including those not matched with items on IDEAS)

    Citations

    Citations are extracted by the CitEc Project, subscribe to its RSS feed for this item.
    as


    Cited by:

    1. Meng Li & Yang Xu, 2025. "The Impact of Computing Infrastructure Construction on Innovation in Manufacturing Enterprises: Evidence from a Quasi-Natural Experiment Based on the Establishment of China’s National Supercomputing C," Sustainability, MDPI, vol. 17(19), pages 1-23, October.

    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. Tao Chen & Shuwen Pi & Qing Sophie Wang, 2025. "Artificial Intelligence and Corporate Investment Efficiency: Evidence from Chinese Listed Companies," Working Papers in Economics 25/05, University of Canterbury, Department of Economics and Finance.
    2. Genz, Sabrina & Schnabel, Claus, 2023. "Digitalization is not gender-neutral," Economics Letters, Elsevier, vol. 230(C).
    3. Qihang Li & Yituan Liu & Wenjie Li & Linman Zheng, 2025. "Will Industrial Robots Terminate Enterprise Innovation?—An Empirical Evidence from China’s Enterprise Robot Penetration," Journal of the Knowledge Economy, Springer;Portland International Center for Management of Engineering and Technology (PICMET), vol. 16(2), pages 10074-10103, June.
    4. Gao, Jie & Li, Zhizhuo & Nguyen, Thithuha & Zhang, Wentao, 2025. "Digital transformation and enterprise employment," International Review of Economics & Finance, Elsevier, vol. 99(C).
    5. Barth, Erling & Davis, James C. & Freeman, Richard B. & McElheran, Kristina, 2023. "Twisting the demand curve: Digitalization and the older workforce," Journal of Econometrics, Elsevier, vol. 233(2), pages 443-467.
    6. Kudoh, Noritaka & Miyamoto, Hiroaki, 2025. "Robots, AI, and unemployment," Journal of Economic Dynamics and Control, Elsevier, vol. 174(C).
    7. Czarnitzki, Dirk & Fernández, Gastón P. & Rammer, Christian, 2023. "Artificial intelligence and firm-level productivity," Journal of Economic Behavior & Organization, Elsevier, vol. 211(C), pages 188-205.
    8. Daniel Jacobi & Elizabeth M. King & Claudio Montenegro & Peter F. Orazem, 2025. "Governance, Risks, and Returns to Human Capital," LIS Working papers 898, LIS Cross-National Data Center in Luxembourg.
    9. Rudnik, Alesia, 2024. "Machinery of dissent: Exploring the techno-social practices of modern protests," Internet Policy Review: Journal on Internet Regulation, Alexander von Humboldt Institute for Internet and Society (HIIG), Berlin, vol. 13(4), pages 1-30.
    10. Bárány, Zsófia L. & Siegel, Christian, 2020. "Biased technological change and employment reallocation," Labour Economics, Elsevier, vol. 67(C).
    11. Caselli, Mauro & Fracasso, Andrea & Scicchitano, Sergio & Traverso, Silvio & Tundis, Enrico, 2025. "What workers and robots do: An activity-based analysis of the impact of robotization on changes in local employment," Research Policy, Elsevier, vol. 54(1).
    12. Cao, Sean & Jiang, Wei & Wang, Junbo & Yang, Baozhong, 2024. "From Man vs. Machine to Man + Machine: The art and AI of stock analyses," Journal of Financial Economics, Elsevier, vol. 160(C).
    13. Hong, Han & Ju, Gaosheng & Li, Qi & Yan, Karen X., 2024. "Varying-coefficient spatial dynamic panel data models with fixed effects: Theory and application," Journal of Econometrics, Elsevier, vol. 245(1).
    14. Sindhwani, Rahul & Pereira, Vijay & Sampat, Brinda & Shankar, Amit & Nigam, Achint & Salwan, Prashant, 2025. "Exploring barriers to social robot adoption: A mixed-method study in the Indian retail sector," Technological Forecasting and Social Change, Elsevier, vol. 212(C).
    15. David Kunst, 2019. "Deskilling among Manufacturing Production Workers," Tinbergen Institute Discussion Papers 19-050/VI, Tinbergen Institute, revised 30 Dec 2020.
    16. Dilip Mookherjee & Debraj Ray, 2022. "Growth, Automation and the Long-Run Share of Labor," Review of Economic Dynamics, Elsevier for the Society for Economic Dynamics, vol. 46, pages 1-26, October.
    17. Montobbio, Fabio & Staccioli, Jacopo & Virgillito, Maria Enrica & Vivarelli, Marco, 2022. "Robots and the origin of their labour-saving impact," Technological Forecasting and Social Change, Elsevier, vol. 174(C).
    18. Fedorets Alexandra & Kirchner Stefan & Adriaans Jule & Giering Oliver, 2022. "Data on Digital Transformation in the German Socio-Economic Panel," Journal of Economics and Statistics (Jahrbuecher fuer Nationaloekonomie und Statistik), De Gruyter, vol. 242(5-6), pages 691-705, December.
    19. Milan Miric & Nan Jia & Kenneth G. Huang, 2023. "Using supervised machine learning for large‐scale classification in management research: The case for identifying artificial intelligence patents," Strategic Management Journal, Wiley Blackwell, vol. 44(2), pages 491-519, February.
    20. Li, Daiyue & Jin, Yanhong & Cheng, Mingwang, 2024. "Unleashing the power of industrial robotics on firm productivity: Evidence from China," Journal of Economic Behavior & Organization, Elsevier, vol. 224(C), pages 500-520.

    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:gam:jsusta:v:17:y:2025:i:2:p:659-:d:1568147. 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.