Impacts of Better Information on Driving Habits and Willingness to Pay

Last registered on December 18, 2019

Pre-Trial

Trial Information

General Information

Title
Impacts of Better Information on Driving Habits and Willingness to Pay
RCT ID
AEARCTR-0003343
Initial registration date
September 27, 2018

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
September 27, 2018, 3:33 PM EDT

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

Last updated
December 18, 2019, 9:58 AM EST

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

Locations

Region

Primary Investigator

Affiliation
MIT

Other Primary Investigator(s)

Additional Trial Information

Status
In development
Start date
2018-11-01
End date
2021-06-01
Secondary IDs
Abstract
In 2017, the transportation sector was the second largest consumer of energy in the U.S., representing approximately 29 percent of total energy consumption. Energy consumption in the transportation sector closely tracks greenhouse gas (GHG) emissions: transportation contributed about 28 percent of total U.S. GHG emissions in 2016, and cars, motorcycles, and trucks contributed 83 percent of those emissions. Despite significant fuel economy increases for passenger cars and light trucks, overall fuel consumption for the sector has increased over the past several decades because of an increase in the number of vehicles and the number of miles traveled per vehicle.
Since the transportation sector is such a large contributor to U.S. GHG emissions, reducing transportation-related emissions is a necessary step to achieve our emissions reduction goals. Policies have primarily sought to address this by promoting increases in fuel economy (e.g., fuel economy standards) and the use of alternative fuels (e.g., renewable fuel standards).

We implement a field experiment to test for the persistence and magnitude of information-based interventions on driver behavior and its impact on the fuel economy. In addition, we elicit drivers willingness to pay for this technology at varying levels of information and driver feedback.


External Link(s)

Registration Citation

Citation
Knittel, Christopher. 2019. "Impacts of Better Information on Driving Habits and Willingness to Pay." AEA RCT Registry. December 18. https://doi.org/10.1257/rct.3343-1.1
Former Citation
Knittel, Christopher. 2019. "Impacts of Better Information on Driving Habits and Willingness to Pay." AEA RCT Registry. December 18. https://www.socialscienceregistry.org/trials/3343/history/59138
Experimental Details

Interventions

Intervention(s)
Depending on the treatment group, treated individuals will receive feedback on their driving in the form of driving scores, driving metrics as well as driving achievement badges, tips for driving improvement, and will be included in a leaderboard ranking them against other participants.

Intervention Start Date
2018-12-01
Intervention End Date
2021-06-01

Primary Outcomes

Primary Outcomes (end points)
Changes in driving metrics
Willingness-to-pay

Primary Outcomes (explanation)

Secondary Outcomes

Secondary Outcomes (end points)
Secondary Outcomes (explanation)

Experimental Design

Experimental Design
Participants will be randomly assigned to the control group or to one of three treatment groups, which will receive information about their driving habits at a varying frequency. The first treatment group, known as the “partial-treatment” group, will receive access to the app which will provide them a drive score and additional metrics for six months. The second treatment group, the "split" group, will receive the same treatment program as the partial-treatment group. However, the split group will only receive access to these resources for the first three months. The final treatment group, the "full treatment" group, will receive drive scores, tips for improvement, badges for driving achievements and inclusion in a leaderboard which ranks participants against other drivers participating in the study. The participant will be able to see their rank amongst the list of drivers, all of whom appear in the list under a username the participant will choose upon registration.
Experimental Design Details
Randomization Method
Randomization done by computer
Randomization Unit
Individuals (drivers)
Was the treatment clustered?
No

Experiment Characteristics

Sample size: planned number of clusters
2000 drivers in two waves.
Sample size: planned number of observations
2000 across 7 months, panel of 14000.
Sample size (or number of clusters) by treatment arms
-Treatment 1 (Partial-treatment): 400 participants (200 per wave)
-Treatment 2 (Split-treatment): 300 participants (150 per wave)
-Treatment 3 (Full-treatment): 300 participants (150 per wave)
-Control: 1000 participants (500 per wave)
Minimum detectable effect size for main outcomes (accounting for sample design and clustering)
IRB

Institutional Review Boards (IRBs)

IRB Name
MIT COUHES
IRB Approval Date
2017-03-13
IRB Approval Number
1702830025

Post-Trial

Post Trial Information

Study Withdrawal

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Intervention

Is the intervention completed?
No
Data Collection Complete
Data Publication

Data Publication

Is public data available?
No

Program Files

Program Files
Reports, Papers & Other Materials

Relevant Paper(s)

Reports & Other Materials