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Spatial Influence of Digital Economy on Carbon Emission Efficiency of the Logistics Industry across 30 Provinces in China

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Listed:
  • Yuxia Guo

    (School of Economics and Management, China University of Mining and Technology, Xuzhou 221116, China
    Business School, Suzhou University, Suzhou 234000, China)

  • Xue Wu

    (Business School, Suzhou University, Suzhou 234000, China)

  • Heping Ding

    (Business School, Suzhou University, Suzhou 234000, China)

  • Zhouyu Tian

    (Business School, Suzhou University, Suzhou 234000, China)

Abstract

The logistics industry (LI) is a key pillar of the global economy, and its carbon emission efficiency (CEE) is crucial for achieving carbon neutrality. The rapid development of the digital economy (DE) has had a profound impact on the LI, but the spatial impact on its CEE is currently unclear and requires further research. Firstly, based on the collection of relevant data, we use the entropy weight method and linear weighted sum method to measure the level of development of the DE. Secondly, the SBM model is used to measure the CEE level of the LI. Using Moran’s I index model and OLS and GWR models, we analyze the impact and spatial distribution characteristics of the DE on the CEE of the LI and propose development strategies. The article uses statistical data from 30 provinces in China from 2013 to 2022 as an example to demonstrate the implementation process of the method. The results show that the DE has a positive impact on the CEE of the LI, and there are spatial differences. Based on this, this article proposes policy recommendations for the development of green and low-carbon logistics and digital logistics that are tailored to local conditions, providing theoretical and methodological support for low-carbon research in the LI, and providing reference for other countries and regions to explore the path of green and low-carbon transformation.

Suggested Citation

  • Yuxia Guo & Xue Wu & Heping Ding & Zhouyu Tian, 2024. "Spatial Influence of Digital Economy on Carbon Emission Efficiency of the Logistics Industry across 30 Provinces in China," Sustainability, MDPI, vol. 16(18), pages 1-20, September.
    • Handle: RePEc:gam:jsusta:v:16:y:2024:i:18:p:8086-:d:1479042
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    References listed on IDEAS

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    1. Kleiber, Christian, 2001. "Finite sample efficiency of OLS in linear regression models with long-memory disturbances," Economics Letters, Elsevier, vol. 72(2), pages 131-136, August.
    2. Ran, Qiying & Yang, Xiaodong & Yan, Hongchuan & Xu, Yang & Cao, Jianhong, 2023. "Natural resource consumption and industrial green transformation: Does the digital economy matter?," Resources Policy, Elsevier, vol. 81(C).
    3. Popkova, Elena G. & Sergi, Bruno S., 2020. "A Digital Economy to Develop Policy Related to Transport and Logistics. Predictive Lessons from Russia," Land Use Policy, Elsevier, vol. 99(C).
    4. Kristoffersen, Eivind & Blomsma, Fenna & Mikalef, Patrick & Li, Jingyue, 2020. "The smart circular economy: A digital-enabled circular strategies framework for manufacturing companies," Journal of Business Research, Elsevier, vol. 120(C), pages 241-261.
    5. Sainan Cheng & Guohua Qu, 2023. "Research on the Effect of Digital Economy on Carbon Emissions under the Background of “Double Carbon”," IJERPH, MDPI, vol. 20(6), pages 1-27, March.
    6. Cai, Bofeng & Guo, Huanxiu & Ma, Zipeng & Wang, Zhixuan & Dhakal, Shobhakar & Cao, Libin, 2019. "Benchmarking carbon emissions efficiency in Chinese cities: A comparative study based on high-resolution gridded data," Applied Energy, Elsevier, vol. 242(C), pages 994-1009.
    7. Tone, Kaoru, 2001. "A slacks-based measure of efficiency in data envelopment analysis," European Journal of Operational Research, Elsevier, vol. 130(3), pages 498-509, May.
    Full references (including those not matched with items on IDEAS)

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