Investigating the association between neighbourhood characteristics and e-scooter safety
Bibliographic Data
| ID | 21233351 |
|---|---|
| Authors | Shahram Heydari (0000-0001-5497-4909, University of Southampton, corresponding author), Michael Forrest (0000-0002-0648-7468, University of Southampton), John Preston (0000-0003-1219-4108, University of Southampton) |
| Year | 2022 |
| Volume | 83 |
| Pages | 103982 |
| Publication date | 2022-08-01 |
| Open Access | Yes |
| Type | ARTICLE |
| Venue | Sustainable Cities and Society (JOURNAL) |
| Journal identifiers | ISSN: 2210-6707 • E-ISSN: 2210-6715 |
| Publisher | Elsevier BV (PUBLISHER) |
| DOI | 10.1016/j.scs.2022.103982 |
| OpenAlex | W4281830995 |
| Language | EN |
| Citations received | 6 |
| References cited | 49 |
The uptake of e-scooters as an alternative mode of travel has risen sharply in recent years; however, their safety is less-understood compared to other modes of travel. For the first time in the extant literature, we explore the association between neighbourhood characteristics and e-scooter safety in Greater London, UK. We found that, over the study period, the expected e-scooter crash frequency was the highest in the City of London, followed by the West End, and then St. James's―both wards located in the borough of Westminster in central London. We found that e-scooter crash frequencies increase with an increase in area-level walking and cycling activities. Similarly, we found that the number of schools is positively associated with the expected e-scooter crash frequency. In contrast, the results indicated that as the proportion of ward-level greenspace increases, the number of crashes involving e-scooters decreases. The results also highlighted social inequalities in this context, with higher e-scooter crash frequencies in areas with larger Black, Asian and Minority Ethnic population, those with higher crime rates, and those with a higher population of children in out of work households. This research provides practical recommendations to prioritise areas for safety interventions and for selecting suitable safety improvement programmes
Borough · Built environment · Civil engineering · Crash · Environmental health · Extant taxon · Geography · Injury prevention · Occupational safety and health · Poison control · Population · Psychological intervention · Socioeconomics · Sociology · Transport engineering · Computer Science · Demography · Engineering · Human Factors and Ergonomics · Medicine · Noise Effects and Management · Psychology · Traffic and Road Safety · Urban Transport and Accessibility
Understanding willingness to use shared electric scooters for first- and last-mile travel in urban cities
Assessing the economic effects of micromobility sharing using credit card transaction data
Toward safer micromobility
E-scooter dynamics in a tourism-driven city
Unraveling the mode substitution of dockless bike-sharing systems and its determinants
Shared scooter integration in multimodal networks
Understanding predictive information criteria for Bayesian models
A mulTi-noRmalization mUlti-distance aSsessmenT (TRUST) approach for locating a battery swapping station for electric scooters
E-scooters and sustainability
Assessment and mitigation of personal exposure to particulate air pollution in cities
Blurred boundaries
| Citations per year | 2 |
|---|---|
| Citation span | 2023 - 2026 (4) |
| Highly cited | No |