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Published on: February 3, 2023
Shared micromobility, perceived accessibility, and social capital
Zihao An1,2,3,4, Caroline Mullen1, Xiaodong Guan5
1Institute for Transport Studies, University of Leeds, Leeds, UK.
Abstract:
While the impacts of shared micromobility (SMM) on the environment and transport systems are being extensively researched, its societal implications and the influence of the social environment on the use of SMM remain largely unexplored. In this research, we investigate the interrelationships between the use of SMM, perceived overall accessibility, and social capital. We focus on two types of SMM - shared bikes and shared e-scooters - in three European countries: the Netherlands, England, and Sweden. We measure perceived overall accessibility through a multicriteria subjective evaluation of individuals' ability to reach regular destinations, services, and activities. We consider multidimensional social capital measures: social trust, cooperativeness, reciprocity, network bonding, and network bridging. We use multivariate models to investigate the associations between perceived overall accessibility, SMM use, and social capital, and examine the dominant direction of these associations using the direct linear non-Gaussian acyclic model (DirectLiNGAM) and direction dependence analysis (DDA). We find that lower levels of perceived overall accessibility may contribute to lower levels of social trust, reciprocity, and cooperativeness. However, individuals with a lower level of perceived overall accessibility tend to use shared bikes more frequently, which in turn, may increase their social trust and cooperativeness. We also find that increased shared e-scooter use may contribute to increased network bonding, yet the frequency of use has no relation with perceived overall accessibility. Our research suggests that the introduction of shared bikes alone, independent of other measures aimed at encouraging their use, may help mitigate individual differences in social capital. We argue that the applied DirectLiNGAM and DDA help gain deeper insights into the likely causal relationship between transport and social capital in non-intervention studies.
Supplementary Information:
The online version contains supplementary material available at 10.1007/s11116-024-10521-5.
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