2022
DOI: 10.3390/su142215454
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Node Centrality Comparison between Bus Line and Passenger Flow Networks in Beijing

Abstract: In recent decades, complex network theory has become one of the most important approaches for exploring the structure and dynamics of traffic networks. Most studies mainly focus on the static topology features of the traffic networks, and there are also increasing literature focusing on passenger flow networks. However, not much work has been completed on comparing the static networks with dynamic flow networks from the perspective of supply and demand. Therefore, this study aimed to apply the complex network … Show more

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Cited by 8 publications
(4 citation statements)
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“…Tokyo discovered a strong relationship between railway network centrality and ridership [26]. In Beijing, bus networks exhibited a high correlation with passenger flow based on centrality measures [27]. Moreover, railway network centrality has been associated with subcenter formation in polycentric cities [28].…”
Section: Influence Of Network Centrality On Property Valuementioning
confidence: 98%
“…Tokyo discovered a strong relationship between railway network centrality and ridership [26]. In Beijing, bus networks exhibited a high correlation with passenger flow based on centrality measures [27]. Moreover, railway network centrality has been associated with subcenter formation in polycentric cities [28].…”
Section: Influence Of Network Centrality On Property Valuementioning
confidence: 98%
“…Conversely, the negative impact range of betweenness centrality in bus network nodes is broader. This is because areas with higher betweenness centrality in bus network nodes often offer more convenient, economical, and environmentally friendly public transportation options [88]. This scenario can reduce the demand for ride-hailing services, subsequently decreasing emissions generated by ride-hailing travel.…”
Section: Analysis Of Spatio-temporally Heterogeneous Effectsmentioning
confidence: 99%
“…Network theory is valuable for analyzing public transport networks and a topic of growing attention. In this sense, centrality measures have been associated with ridership at stations of urban rail transit, with degree, betweenness and closeness as the most common ones (He, Zhao, and Tsui 2019;Dai et al 2022). For instance, passenger flows are related to centralities of both physical and service-level networks in tram systems (Luo, Cats, and van Lint 2020), while in metro systems, centralities of the physical network and the network of public transport alternatives demonstrate linear correlations with passenger flows at stations (Kopsidas, Douvaras, and Kepaptsoglou 2023a).…”
Section: Questionsmentioning
confidence: 99%