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Research on coordinated development between metropolitan economy and logistics using big data and Haken model

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  • Chen Yang
  • Shulin Lan
  • Lihui Wang

Abstract

To quantitatively study the relationship and mutual effects between metropolitan economy and logistics is an important, yet pending issue, which can scientifically guide the urban planning and investment. Through the identified evaluation indexes of metropolitan logistics and economic development, this paper first builds up an evaluation process model of metropolitan economic and logistics development, based on big data analytics (BDA), the entropy evaluation method, and the maximum deviation method. BDA can help extract the exact data about the indicators of metropolitan economy and logistics. Then a Haken model is adopted to ravel out the dynamic co-evolutionary law of economy and logistics in five Chinese cities, which complements the above static evaluation. The results show that the economic development is an order parameter and plays a key role in the coordinated development of metropolitan logistics and economy. However, from 2013 to 2014, these five cities had not established an orderly evolved positive-feedback mechanism through which economic development promotes the coordinated development of metropolitan logistics and economic development.

Suggested Citation

  • Chen Yang & Shulin Lan & Lihui Wang, 2019. "Research on coordinated development between metropolitan economy and logistics using big data and Haken model," International Journal of Production Research, Taylor & Francis Journals, vol. 57(4), pages 1176-1189, February.
    • Handle: RePEc:taf:tprsxx:v:57:y:2019:i:4:p:1176-1189
    DOI: 10.1080/00207543.2018.1503427
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    Citations

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    Cited by:

    1. Büyüközkan, Gülçin & Ilıcak, Öykü, 2022. "Smart urban logistics: Literature review and future directions," Socio-Economic Planning Sciences, Elsevier, vol. 81(C).
    2. Wen Qin & Xiaolie Qi, 2022. "Evaluation of Green Logistics Efficiency in Northwest China," Sustainability, MDPI, vol. 14(11), pages 1-14, June.
    3. Claudio Vitari & Elisabetta Raguseo, 2019. "Big data analytics business value and firm performance: Linking with environmental context," Post-Print hal-02293765, HAL.
    4. Andrea Ferrari & Giulio Mangano & Anna Corinna Cagliano & Alberto De Marco, 2023. "4.0 technologies in city logistics: an empirical investigation of contextual factors," Operations Management Research, Springer, vol. 16(1), pages 345-362, March.
    5. Wei Zhang & Xinxin Zhang & Mingyang Zhang & Woyuan Li, 2020. "How to Coordinate Economic, Logistics and Ecological Environment? Evidences from 30 Provinces and Cities in China," Sustainability, MDPI, vol. 12(3), pages 1-23, February.
    6. Xinbao Tian & Peiran Chen & Jie Li, 2022. "Spatial Econometric Analysis of the Level and Influencing Factors of Coupling and Coordination between Regional Logistics and the Ecological Environment in China," IJERPH, MDPI, vol. 19(22), pages 1-20, November.
    7. Guangmei Cao & Yuesen Wang & Honghu Gao & Hao Liu & Haibin Liu & Zhigang Song & Yuqing Fan, 2023. "Coordination Decision-Making for Intelligent Transformation of Logistics Services under Capital Constraint," Sustainability, MDPI, vol. 15(6), pages 1-25, March.
    8. Pan, Xiongfeng & Li, Mengna & Wang, Mengyang & Zong, Tianjiao & Song, Malin, 2020. "The effects of a Smart Logistics policy on carbon emissions in China: A difference-in-differences analysis," Transportation Research Part E: Logistics and Transportation Review, Elsevier, vol. 137(C).

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