Evidence map›Paper›PMID 38818355›Full record

ArticleISPRS international journal of geo-information2020

Understanding the Shared E-scooter Travels in Austin, TX.

Junfeng Jiao, Shunhua Bai

Abstract read
In one paragraph

Article in ISPRS international journal of geo-information, 2020. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 11 papers, 1 of them a synthesis that pooled it.

0numbers the graph read from it
0cells of the map it votes in
11citing papers in PubMed, 1 pooled it
–field-weighted citation impact
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

11 citing papers in PubMed, 1 synthesis or guideline pooled it.

  1. Pooled it
  2. Article
  3. Article
  4. Article
  5. Article
  6. Article
  7. Article
  8. Article
  9. Article
  10. Modeling the Demand for Shared E-Scooter Services.Transportation research record · 2022
    Article
  11. Spatial associations of dockless shared e-scooter usage.Transportation research. Part D, Transport and environment · 2020
    Article
4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

2 authors.

Junfeng JiaoUrban Information Lab, The University of Texas at Austin, Austin, TX 78712, USA.ORCID 0000-0002-7272-8805
Shunhua BaiUrban Information Lab, The University of Texas at Austin, Austin, TX 78712, USA.ORCID 0000-0002-8774-5368

Funding

Scientific & Technical CoreP2CHD042849 · NICHD · UNIVERSITY OF TEXAS AT AUSTIN · PI MARK D. HAYWARD · 2017 to 2026
$5.2M
NICHD NIH HHS P2C HD042849
6 · The paper itself

Abstract

This paper investigated the travel patterns of 1.7 million shared E-scooter trips from April 2018 to February 2019 in Austin, TX. There were more than 6000 active E-scooters in operation each month, generating over 150,000 trips and covered approximately 117,000 miles. During this period, the average travel distance and operation time of E-scooter trips were 0.77 miles and 7.55 min, respectively. We further identified two E-scooter usage hotspots in the city (Downtown Austin and the University of Texas campus). The spatial analysis showed that more trips originated from Downtown Austin than were completed, while the opposite was true for the UT campus. We also investigated the relationship between the number of E-scooter trips and the surrounding environments. The results show that areas with higher population density and more residents with higher education were correlated with more E-scooter trips. A shorter distance to the city center, the presence of transit stations, better street connectivity, and more compact land use were also associated with increased E scooter usage in Austin, TX. Surprisingly, the proportion of young residents within a neighbourhood was negatively correlated with E-scooter usage.

Indexed as

e-scootershared micro-mobilitytravel patternurban environment

Identifiers

PMID38818355
PMCPMC11139225

What OpenQuestion holds

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LicenceCC BY
Read underepoch 390

Registered trials

None linked

Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.