The Spatial Effect of Shared Mobility on Urban Traffic Congestion: Evidence from Chinese Cities

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.

Bibliometric analysis of carsharing and car rental research in the field of urban transportation and tourism transportation

“…The third cluster (in red) consists of automobiles, public transportation, smart city, urban mobility, electric The fourth cluster (in blue) consists of carsharing types, including shared mobility, bike sharing, free floating, oneway carsharing, carpooling and simulation. Most of the articles focus on shared mobility as a driving force, factors affecting shared mobility, the welfare impact of shared mobility, the sustainability of shared mobility and shared mobility on urban traffic congestion to solve urban mobility and traffic problems (Akyelken et al, 2018;Becker et al, 2020;Giovanni et al, 2019;Jiachen et al, 2021;Jie et al, 2021;Li & Kamargianni, 2020).…”

Impact-Asymmetric Analysis of Bike-Sharing Residents’ Satisfaction: A Case Study of Harbin, China

“…In 2021, Harbin ranked eighth in China regarding traffic congestion during commuting peak, with a congestion index of 1.741, and the congestion index increased by 5.69% year-on-year in 2020 [3]. As traffic congestion intensifies, the environmental pollution and energy consumption problems it brings also severely constrain socioeconomic development, and urban traffic congestion needs urgent improvement [4]. In recent years, major cities have promoted bike sharing as a green mode of travel, which is essential in easing traffic congestion in Chinese cities, in addition to providing convenience and reducing travel costs for urban residents [5].…”

“…As traffic congestion intensifies, the environmental pollution and energy consumption problems it brings also severely constrain socioeconomic development, and urban traffic congestion needs urgent improvement [4]. In recent years, major cities have promoted bike sharing as a green mode of travel, which is essential in easing traffic congestion in Chinese cities, in addition to providing convenience and reducing travel costs for urban residents [5]. In 2017, approximately 8000 shared bikes were launched in Harbin; however, by 2021, the total number of shared bikes in Harbin reached 100,000.…”