Peak-avoidance Experiment

Last registered on November 15, 2022

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Pre-Trial

Trial Information

General Information

Title

Peak-avoidance Experiment

RCT ID

AEARCTR-0006857

Initial registration date

July 12, 2021

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

July 13, 2021, 9:35 AM EDT

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

Last updated

November 15, 2022, 4:50 PM EST

Last updated is the most recent time when changes to the trial's registration were published.

Locations

Country

China

Region

Beijing

Primary Investigator

Name

Duan Su

Affiliation

Beijing Jiaotong University

Contact Primary Investigator

Other Primary Investigator(s)

PI Name

Kexin Geng

PI Affiliation

Beijing Jiaotong University

Contact Investigator

PI Name

Yacan Wang

PI Affiliation

Beijing Jiaotong University

Contact Investigator

PI Name

Duan Su

PI Affiliation

Beijing Jiaotong University

Contact Investigator

Additional Trial Information

Status

Completed

Start date

2021-03-31

End date

2021-10-17

Keywords

Behavior, Environment & Energy

Additional Keywords

Traffic congestion, Tradble permits, Congestion Pricing, Health information

JEL code(s)

C93, D12, H23, L9, R41

Secondary IDs

National Natural Science Foundation of China and the Joint Programming Initiative Urban Europe, National Natural Science Foundation of China

Prior work

This trial does not extend or rely on any prior RCTs.

Abstract

Traffic congestion is a difficult problem faced by urban management all over the world. This experiment investigates how to encourage commuters to drive cars in non-peak hours. We organize a randomized field experiment to explore the effectiveness of different treatments: tradable permits, congestion charges, and health information. We define the time window of 7:00 a.m. to 8:00 a.m. as the big peak hours. and before 6:30 a.m. or after 8:30 a.m. as the small peak hours. Under the tradable permits, drivers' app accounts will be deducted for some tickets if they depart during peak hours. Under congestion charges, drivers' app accounts will be deducted some money if they depart during peak hours. The drivers in health information group will receive reminder messages every week. In the last group, drivers will be influenced by health information and congestion charges.

External Link(s)

Registration Citation

Citation

Geng, Kexin et al. 2022. "Peak-avoidance Experiment." AEA RCT Registry. November 15. https://doi.org/10.1257/rct.6857-1.1

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Experimental Details

Interventions

Intervention(s)

Tradable permits: Drivers need to pay some permit tickets for morning driving during peak hours.
Congestion charges: Drivers need to pay some money from initially allocated money for morning driving during peak hours.
Health information: Drivers receive health information every week to tell how improper commuting modes affect individual health.

Intervention Start Date

2021-06-14

Intervention End Date

2021-07-16

Primary Outcomes

Primary Outcomes (end points)

Whether subjects drive.
Whether subjects depart before 6:30 a.m..
Whether subjects depart between 6:30 a.m. and 7:00 a.m..
Whether subjects depart between 7:00 a.m. and 8:00 a.m..
Whether subjects depart between 8:00 a.m. and 8:30 a.m..
Whether subjects depart after 8:30 a.m..

Primary Outcomes (explanation)

The driver i will experience Ti days (=0,1,…) in the experimental period. Each day t the driver will decide when to drive or not drive in the morning. Generate six main observed variables: whether to drive (Xit=1 or 0), whether to start driving before 6:30 a,m. (Xit=1 or 0), whether to start driving between 6:30 a.m. and 7:00 a.m., (Xit=1 or 0), whether to start driving between 7:00 a.m. and 8:00 a.m., (Xit=1 or 0), whether to start driving during 8:00 a.m. and 8:030 a.m., (Xit=1 or 0), and whether to start driving after 8:30 a.m., (Xit=1 or 0). Per driver with Ti >0 , we compute the average value (x_i ) ̅= 1/T_i ∑_(t=1)^(T_i)▒x_it.

Secondary Outcomes

Secondary Outcomes (end points)

None

Secondary Outcomes (explanation)

None

Experimental Design

During the treatment period, drivers will be incentivized by tradable permits, congestion charges, or health information

Experimental Design Details

Drivers are assigned to the tradable permits group, congestion charge group, health information group, interaction group, or control. The drivers in the tradable permits group will receive some permits each week and need to consume them when driving during peak hours. The drivers of the congestion charge group received a sum of money in the app before the treatment and need to pay a part if they start driving during peak hours. After the treatment ended, they can get all payments. The drivers of the health information group received messages conveying the adverse effect of a long time driving on the body and psychological health. The drivers of the interaction group will meet the two treatments meanwhile.

Randomization Method

Stratified randomization by Excel

Randomization Unit

Individuals

Was the treatment clustered?

Experiment Characteristics

Sample size: planned number of clusters

1 company

Sample size: planned number of observations

500 drivers

Sample size (or number of clusters) by treatment arms

100 subjects control, 100 subjects assigned to reward group, 100 subjects assigned to permit group, 100 subjects assigned to information group, 100 subjects both the reward and information treatment.

Minimum detectable effect size for main outcomes (accounting for sample design and clustering)

Specify the unit: times standard deviation: 20% percentage: 30% behavioral shift Minimum effect size: 70 of each experimental group, a total of 420 subjects are needed

Supporting Documents and Materials

IRB