Geo-visualisation of the community structure of intercity express delivery network in China based on waybill big data

IF 2.6 3区 经济学 Q2 ENVIRONMENTAL STUDIES Environment and Planning B: Urban Analytics and City Science Pub Date : 2024-03-26 DOI:10.1177/23998083241241842
Jiacheng Chang, Guoqi Li, Wenjie Sun, Nannan He, Guopeng Du
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Abstract

Waybill data can reflect the transport process of express delivery in different cities, providing an important basis for revealing intercity logistics connectivity. However, current research neglects the critical function of routing information in waybill data, making it difficult to realistically represent intercity connectivity in the express delivery network. This study uses waybill big data with routing information to map the spatial distribution and network structures of intercity express delivery networks in China, and identifies three main types of network communities: interprovincial communities, regional hub communities, and corridor pattern communities, so that a more accurate and realistic representation of intercity connectivity can be presented.
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基于运单大数据的中国城际快递网络社群结构地理可视化
运单数据可以反映快递在不同城市的运输过程,为揭示城际物流的连通性提供了重要依据。然而,目前的研究忽视了运单数据中路由信息的关键作用,导致难以真实呈现快递网络的城际连通性。本研究利用带有路由信息的运单大数据,绘制了中国城际快递网络的空间分布和网络结构,并识别出省际群落、区域枢纽群落和走廊模式群落三大类型的网络群落,从而更准确、更真实地呈现城际连通性。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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来源期刊
CiteScore
6.10
自引率
11.40%
发文量
159
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