Social Norms, Incentives, and Congestion at Electric Vehicle Charging Stations

Last registered on October 07, 2026
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Pre-Trial

Trial Information

General Information

Title
Social Norms, Incentives, and Congestion at Electric Vehicle Charging Stations
RCT ID
AEARCTR-0019881
Initial registration date
October 05, 2026

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
October 07, 2026, 11:05 AM EDT

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

Locations

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Primary Investigator

Name
Jan Domagalski
Affiliation
Paris School of Economics
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Other Primary Investigator(s)

PI Name
Nicolas Astier
PI Affiliation
Paris School of Economics; École nationale des ponts et chaussées
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Additional Trial Information

Status
On going
Start date
2026-09-25
End date
2026-11-06
Keywords
Behavior, Environment & Energy
Additional Keywords
electric vehicles, charging, nudges, congestion
JEL code(s)
D12, Q41, R41
Secondary IDs
Prior work
This trial does not extend or rely on any prior RCTs.
Abstract
The increasing adoption of electric vehicles is creating congestion at public charging stations, where available spots are more and more often all occupied at the same time. Previous research has shown that drivers are strongly responsive to financial incentives such as peak vs off-peak electricity prices. However, electricity prices are not well suited to managing congestion because electricity consumption falls to zero once a vehicle's battery is full. An overstay fee addresses this problem by charging, when the station is busy, a per-minute fee to cars that stay at the station despite being almost fully charged. This project studies whether the informational content of the notification sent shortly before the overstay fee is triggered affects drivers' behaviour. We compare a control message with three messages appealing to prosocial behaviour, social norms, and information about decreasing charging speed.
External Link(s)

Registration Citation

Citation
Astier, Nicolas and Jan Domagalski. 2026. "Social Norms, Incentives, and Congestion at Electric Vehicle Charging Stations." AEA RCT Registry. October 07. https://doi.org/10.1257/rct.19881-1.0
Sponsors & Partners

Partner

Name
Electra
Type
private_company
URL
https://www.go-electra.com/en/
Experimental Details

Interventions

Intervention(s)
The intervention varies the informational content of a push notification sent to electric-vehicle drivers shortly before an overstay fee becomes applicable at a congested charging station. Eligible charging sessions are randomly assigned to one of four notification messages: a control message providing only information about the impending fee, a prosocial message encouraging drivers to leave the charging spot for others, a social-norm message emphasizing stopping charging around 80% state of charge, and an informational message explaining that charging slows after 80%.
Intervention Start Date
2026-09-25
Intervention End Date
2026-11-06

Primary Outcomes

Primary Outcomes (end points)
(1) Compliance within the grace period (i.e. whether or not the charging session ended with paying an overstay fee); (2) Time from notification to the end of the charging session.
Primary Outcomes (explanation)
Compliance within the grace period is an indicator equal to one if the charging session ends within five minutes of the notification and zero otherwise (in this case, there is an overstay fee charge). Time to end of session is the number of minutes between the notification and the end of the charging session. The five-minute threshold corresponds to the grace period before the overstay fee applies. Pasted text

Secondary Outcomes

Secondary Outcomes (end points)
Session rating; total session payment; time until the user's next charging session in the operator's network; average charging speed; final battery state of charge.
Secondary Outcomes (explanation)
Acceptability is measured using the driver's five-star session rating. Revenue is the total payment associated with the charging session. Retention is measured as the time until the driver's next charging session in the operator's network. Efficiency is measured using average charging speed during the session. Final state of charge is the vehicle's battery state of charge at the end of the session.

Experimental Design

Experimental Design
We conduct a four-arm randomized controlled trial among eligible charging sessions at public electric-vehicle charging stations. Treatment is randomized at the charging-session level with equal probability across the four notification conditions. The experiment is planned to run for six weeks. The primary analysis compares each treatment group separately with the control group.
Experimental Design Details
Not available
Randomization Method
Randomization is implemented automatically by the company's software when an eligible notification is triggered. Each eligible charging session is independently assigned with equal probability to one of the four notification conditions.
Randomization Unit
Charging session. A user may contribute more than one charging session and may therefore receive different treatment assignments across sessions. Treatment is randomized at the individual charging-session level. Inference will nevertheless account for repeated observations by clustering standard errors at the user level.
Was the treatment clustered?
No

Experiment Characteristics

Sample size: planned number of clusters
Not applicable: treatment is not cluster-randomized. The unit of randomization is the charging session.
Sample size: planned number of observations
Approximately 14,700 eligible notification events, corresponding to approximately 14,004 usable charging-session observations under the main conservative planning scenario of 350 notifications per day over 42 days.
Sample size (or number of clusters) by treatment arms
Equal allocation across four arms. Under the main conservative scenario, approximately 3,501 usable charging sessions per arm: Control ≈ 3,501; Prosocial ≈ 3,501; Social norm ≈ 3,501; Information ≈ 3,501.
Minimum detectable effect size for main outcomes (accounting for sample design and clustering)
Power calculations assume 80% power, equal allocation across four treatment arms, and a Bonferroni-adjusted significance level of α = 0.00833 for six primary hypothesis tests. Under the main conservative scenario of approximately 3,501 usable observations per arm, the minimum detectable effect is approximately 0.81 minutes for time to session end and 4.24 percentage points for compliance within five minutes. The baseline mean time to session end is 7.85 minutes (SD 10.13) and the baseline five-minute compliance rate is 54.0%. The MDE calculations account for repeated observations at the user level where applicable.
Supporting Documents and Materials

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IRB

Institutional Review Boards (IRBs)

IRB Name
IRB Approval Date
IRB Approval Number
Analysis Plan

Analysis Plan Documents

Analysis Plan

MD5: 14e9fa73582c3124759077f952ad4555

SHA1: 0da9bf493680219011b81c28a02494c57748e7b7

Uploaded At: October 05, 2026