Cited by 78Transportation and Mobility InnovationsUrban Transport and AccessibilityInnovation Diffusion and Forecasting

The effect of social influence and social interactions on the adoption of a new technology: The use of bike sharing in a student population

Open access
Manca, Francesco, Sivakumar, Aruna, Polak, John W.·2019·Transportation Research Part C Emerging Technologies

Integrity signals

Registry

Crossref · 10.1016/j.trc.2019.02.010

Cites

55 of 55 references verified0 citation errors · 0 not checkable

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Authors
Manca, F., Sivakumar, A., & Polak, J. W.
Affiliations
Imperial College London (GB)
Corresponding author
Manca, Francesco
Venue
Transportation Research Part C Emerging Technologies
Publisher
Elsevier BV
Published
2019-08
Volume
105
Pages
611-625
ISSN
0968-090X (ISSN-L)
OpenAlex
W2917269934
Cited by
78
References
56
Citations by year
2026: 6 · 2025: 10 · 2024: 15 · 2023: 7 · 2022: 16 · 2021: 16 · 2020: 6 · 2019: 2
FWCI
4.57
Type
journal article
Language
en
Open access
Locations
  • Transportation Research Part C Emerging Technologies (publishedVersion)
  • Spiral (Imperial College London) (submittedVersion, cc-by-nc-nd)
Funders
Engineering and Physical Sciences Research Council
Topics
  • Physical Sciences › Engineering › Automotive Engineering › Transportation and Mobility Innovations
  • Social Sciences › Transportation › Urban Transport and Accessibility
  • Social Sciences › Decision Sciences › Management Science and Operations Research › Innovation Diffusion and Forecasting
Keywords
social influence, social interaction, technology adoption, bike sharing, mode choice, social norms, conformity, public transport strikes, mixed logit model, students, cycling, behavioral inertia

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Registry, retraction, Cites and statistics results are computed, not judged, with one exception: a printed reference that no index lists is read once by a model before it counts as a citation error. Claims are extracted by a model and kept only when their quote appears verbatim in the text; each cited source is then checked, with a model’s help, for whether it says what the claim relies on. Those verdicts can be wrong — read the claim’s quote and the cited source before relying on one.

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