Maximilian Heumann , Tobias Kraschewski , Philipp Otto , Lukas Tilch , Tim Brauner , Michael H. Breitner
{"title":"Factors influencing the usage of shared micromobility: Implications from Berlin","authors":"Maximilian Heumann , Tobias Kraschewski , Philipp Otto , Lukas Tilch , Tim Brauner , Michael H. Breitner","doi":"10.1016/j.jcmr.2025.100063","DOIUrl":null,"url":null,"abstract":"<div><div>The popularity of urban micromobility has steadily grown in cities worldwide. There is a lack of comparative studies investigating factors influencing the travel behavior of shared micromobility in Europe. From this, we investigate shared bicycle, e-scooter, and e-moped usage in Berlin based on trip data from September 2019 to March 2022. We incorporate a comprehensive set of spatial, temporal, weather-, fleet size-, and COVID-19-lockdown-related factors. To account for significant over-dispersion in our hourly resolved panel dataset for 542 traffic analysis zones, we employ a functional spatiotemporal regression model to estimate variables of trip counts for the three micromobility modes. Our descriptive results reveal spatiotemporal characteristics of shared bicycle, e-scooter, and e-moped usage and significant growth of operating fleet sizes in Berlin in recent years. We provide evidence that fleet expansion does not lead to a proportional increase in trips, implying competitive effects among operators limit potential growth. As urban space is scarce and regulations on fleet sizes are lacking, urban planners and service providers use these findings and complementary studies to plan fleets and their allocation optimally. Impacts associated with land use vary between modes and allow for demand-based planning. Precipitation is the most impactful factor among the weather variables and shows a pronounced adverse effect on all three modes. COVID-19-lockdown phases had no significant effect on e-mopeds. While bicycles were moderately affected, e-scooter trips decreased significantly. The findings can help policymakers and micromobility operators further optimize sharing mobility services and facilitate evidence-based strategies for the spatial and temporal design of micromobility.</div></div>","PeriodicalId":100771,"journal":{"name":"Journal of Cycling and Micromobility Research","volume":"4 ","pages":"Article 100063"},"PeriodicalIF":0.0000,"publicationDate":"2025-03-21","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"Journal of Cycling and Micromobility Research","FirstCategoryId":"1085","ListUrlMain":"https://www.sciencedirect.com/science/article/pii/S2950105925000075","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 0
Abstract
The popularity of urban micromobility has steadily grown in cities worldwide. There is a lack of comparative studies investigating factors influencing the travel behavior of shared micromobility in Europe. From this, we investigate shared bicycle, e-scooter, and e-moped usage in Berlin based on trip data from September 2019 to March 2022. We incorporate a comprehensive set of spatial, temporal, weather-, fleet size-, and COVID-19-lockdown-related factors. To account for significant over-dispersion in our hourly resolved panel dataset for 542 traffic analysis zones, we employ a functional spatiotemporal regression model to estimate variables of trip counts for the three micromobility modes. Our descriptive results reveal spatiotemporal characteristics of shared bicycle, e-scooter, and e-moped usage and significant growth of operating fleet sizes in Berlin in recent years. We provide evidence that fleet expansion does not lead to a proportional increase in trips, implying competitive effects among operators limit potential growth. As urban space is scarce and regulations on fleet sizes are lacking, urban planners and service providers use these findings and complementary studies to plan fleets and their allocation optimally. Impacts associated with land use vary between modes and allow for demand-based planning. Precipitation is the most impactful factor among the weather variables and shows a pronounced adverse effect on all three modes. COVID-19-lockdown phases had no significant effect on e-mopeds. While bicycles were moderately affected, e-scooter trips decreased significantly. The findings can help policymakers and micromobility operators further optimize sharing mobility services and facilitate evidence-based strategies for the spatial and temporal design of micromobility.