Abstract
This paper explores the spatial spillover effect of shared mobility on urban traffic congestion by constructing spatial econometric models. Based on panel data of 94 Chinese cities from 2016 to 2019, this study analyses the spatial correlation of shared mobility enterprise layout and geographical correlation of urban transport infrastructure and examines their influence mechanism. From the perspective of geographic spatial distribution, congestion has positive spatial correlation among Chinese cities, and it has different directions and centripetal forces across regions. The shared mobility enterprises in a region have same direction distribution with traffic congestion, but the centripetal forces of the aggregation effect are different. The econometric results include the fact that bike-sharing has reduced congestion significantly, but the overall impact of car-sharing is not clear. Neither bike-sharing nor car-sharing can offset the traffic congestion caused by economic activities and income growth. From the perspective of spillover effects, congestion has been influenced by bike-sharing, economic development, population, and public passengers in surrounding areas. In terms of spatial heterogeneity, bike-sharing relieves congestion in the Pearl River Delta region while having no significant effect in other regions. Meanwhile, car-sharing has aggravated congestion in the Yangtze River Delta but eased traffic jams in the Pearl River Delta.
Highlights
The development of intelligent urban transportation, the use of information technology and the application of artificial intelligence are transforming traffic use
Comparing the results of our study and the literature, we have found that some control variables have consistent influence on traffic congestion, such as gross regional domestic product (GDP), regional resident population (RRP), and length of the road (LEN)
Based on the spatial linkage of shared mobility and transportation, this paper aims to examine the relationship between shared mobility and traffic congestion, expanding the scope of previous studies from a single city or a single service to 94 cities in China
Summary
The development of intelligent urban transportation, the use of information technology and the application of artificial intelligence are transforming traffic use. Shared mobility is the intelligent tool most extensively used by commuters and travelers. Various forms of shared mobility have flooded the urban roads and streets to cater to the demand for public mobility [1]. With the rapid growth of shared mobility, a series of undesirable problems has emerged, for example, the excessive allocation of shared bikes has caused resources to be wasted and has seriously harmed the sustainability of public transportation. The reliance on shared mobility to solve traffic problems has faced challenges in large cities [2]. Whether the development of shared mobility in China can reduce urban traffic congestion and improve the sustainability of transportation is a topic worthy of discussion
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