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Research on coordinated development between metropolitan economy and gistics using big data and Haken model
Univ Hong Kong, Dept Ind & Mfg Syst Engn, HKU ZIRI Lab Phys Internet, Hong Kong, Peoples R China. an, Shulin.
KTH, School of Industrial Engineering and Management (ITM), Production Engineering, Production Systems.ORCID iD: 0000-0001-8679-8049
2019 (English)In: International Journal of Production Research, ISSN 0020-7543, E-ISSN 1366-588X, Vol. 57, no 4, p. 1176-1189Article in journal (Refereed) Published
Abstract [en]

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

Place, publisher, year, edition, pages
Taylor & Francis, 2019. Vol. 57, no 4, p. 1176-1189
Keywords [en]
big data, city logistics, metropolitan economic and logistics development, coordinated development, relation analysis
National Category
Economic Geography
Identifiers
URN: urn:nbn:se:kth:diva-248359DOI: 10.1080/00207543.2018.1503427ISI: 000461395200013Scopus ID: 2-s2.0-85052289382OAI: oai:DiVA.org:kth-248359DiVA, id: diva2:1302656
Note

QC 20190405

Available from: 2019-04-05 Created: 2019-04-05 Last updated: 2019-04-05Bibliographically approved

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Wang, Lihui

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  • apa
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