E-Biking in Switzerland (EBIS)

Last registered on November 18, 2022

Pre-Trial

Trial Information

General Information

Title
E-Biking in Switzerland (EBIS)
RCT ID
AEARCTR-0010266
Initial registration date
November 15, 2022

Initial registration date is when the trial was registered.

It corresponds to when the registration was submitted to the Registry to be reviewed for publication.

First published
November 18, 2022, 12:17 PM EST

First published corresponds to when the trial was first made public on the Registry after being reviewed.

Locations

Primary Investigator

Affiliation
ETH Zürich

Other Primary Investigator(s)

PI Affiliation
University of Basel
PI Affiliation
University of Basel
PI Affiliation
ETH Zurich
PI Affiliation
ETH Zurich
PI Affiliation
University of Basel
PI Affiliation
University of Oregon

Additional Trial Information

Status
On going
Start date
2022-09-01
End date
2023-03-03
Secondary IDs
SI/502348-01
Prior work
This trial does not extend or rely on any prior RCTs.
Abstract
We investigate the potential for reducing carbon emissions in the
transport sector due to e-biking based on a large sample of e-bikers in
Switzerland and using a combination of GPS tracking and surveys. The
first part of the project assesses the current situation and improves on
the present state of knowledge about mode shift due to e-biking and the
transport choices of e-bikers. The second part consists in a randomized
controlled trial, in which mobility pricing based on the external costs of
transport is implemented for a subset of the participants. We measure
the resulting causal effects on carbon emissions and the other external
costs of transport (health, congestion) and investigate mode substitution,
with a special focus on e-biking. Last, the potential for carbon reductions
due to e-biking in the population as a whole is computed, including un-
der different scenarios, i.e., future mobility pricing and transport policies.
External Link(s)

Registration Citation

Citation
Axhausen, Kay et al. 2022. "E-Biking in Switzerland (EBIS)." AEA RCT Registry. November 18. https://doi.org/10.1257/rct.10266-1.0
Sponsors & Partners

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Experimental Details

Interventions

Intervention(s)


Intervention Start Date
2022-10-05
Intervention End Date
2023-03-03

Primary Outcomes

Primary Outcomes (end points)
Change in distances traveled, modes, and departure time in response to Pigovian transport pricing.
Primary Outcomes (explanation)

Secondary Outcomes

Secondary Outcomes (end points)
Reduction in CO2 emissions, health effects, accidents and congestion if this pricing were used countrywide.
Secondary Outcomes (explanation)

Experimental Design

Experimental Design
After a baseline survey to gather basic information related to travel and demographics, participants will be tracked for a purely observational baseline period of 4 weeks, followed by a retrospective survey and another period of 5 weeks of observation. We will make use of a GPS-based technology that tracks the movement of participants through an app on their phone and automatically determines travel modes based on map matching, speeds and departure time tables. The app has been extensively tested in an earlier study during which we successfully tracked over 3,600 participants. This approach will allow us to investigate mode choice and travel behaviour in much more detail than was previously possible in studies solely relying on self-reported travel data. All participants receive CHF 50 to complete the study.

Experimental Design Details
Not available
Randomization Method
Randomization done in office by a computer
Randomization Unit
Individuals. For people that live in the same household as someone else in the study, the group assignment is the same as that of the first household member.
Was the treatment clustered?
No

Experiment Characteristics

Sample size: planned number of clusters
1000 participants
Sample size: planned number of observations
1000 participants
Sample size (or number of clusters) by treatment arms
500 individuals control, 500 individuals treatment
Minimum detectable effect size for main outcomes (accounting for sample design and clustering)
This sample size will allow us to detect a reduction of the external costs of transport by 5% with a probability of 80%.
IRB

Institutional Review Boards (IRBs)

IRB Name
ETH Zurich Ethics comission
IRB Approval Date
2022-09-22
IRB Approval Number
EK 2022-N-54
Analysis Plan

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