A Spatiotemporal Study and Location-Specific Trip Pattern Categorization of Shared E-Scooter Usage
Maximilian Heumann,
Tobias Kraschewski,
Tim Brauner,
Lukas Tilch and
Michael H. Breitner
Additional contact information
Maximilian Heumann: Information Systems Institute, Leibniz University Hannover, 30167 Hannover, Germany
Tobias Kraschewski: Information Systems Institute, Leibniz University Hannover, 30167 Hannover, Germany
Tim Brauner: Information Systems Institute, Leibniz University Hannover, 30167 Hannover, Germany
Lukas Tilch: Information Systems Institute, Leibniz University Hannover, 30167 Hannover, Germany
Michael H. Breitner: Information Systems Institute, Leibniz University Hannover, 30167 Hannover, Germany
Sustainability, 2021, vol. 13, issue 22, 1-24
Abstract:
This study analyzes the temporally resolved location and trip data of shared e-scooters over nine months in Berlin from one of Europe’s most widespread operators. We apply time, distance, and energy consumption filters on approximately 1.25 million trips for outlier detection and trip categorization. Using temporally and spatially resolved trip pattern analyses, we investigate how the built environment and land use affect e-scooter trips. Further, we apply a density-based clustering algorithm to examine point of interest-specific patterns in trip generation. Our results suggest that e-scooter usage has point of interest related characteristics. Temporal peaks in e-scooter usage differ by point of interest category and indicate work-related trips at public transport stations. We prove these characteristic patterns with the statistical metric of cosine similarity. Considering average cluster velocities, we observe limited time-saving potential of e-scooter trips in congested areas near the city center.
Keywords: e-scooter; micro-mobility; shared-mobility; land use analysis; spatiotemporal analysis; spatial allocation; HDBSCAN; big data (search for similar items in EconPapers)
JEL-codes: O13 Q Q0 Q2 Q3 Q5 Q56 (search for similar items in EconPapers)
Date: 2021
References: View references in EconPapers View complete reference list from CitEc
Citations: View citations in EconPapers (5)
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Persistent link: https://EconPapers.repec.org/RePEc:gam:jsusta:v:13:y:2021:i:22:p:12527-:d:677971
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