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Does 25 + 25 + 25 = 75?: a natural field experiment on task completion
Last registered on August 21, 2019


Trial Information
General Information
Does 25 + 25 + 25 = 75?: a natural field experiment on task completion
Initial registration date
August 21, 2019
Last updated
August 21, 2019 2:29 PM EDT
Primary Investigator
Other Primary Investigator(s)
PI Affiliation
PI Affiliation
PI Affiliation
Additional Trial Information
In development
Start date
End date
Secondary IDs
There exists rich literature documenting the importance of framing and language in designing incentives for workers in firms. Experimental evidence has shown that framing manipulations that leverage loss aversion can increase worker productivity. Other studies have found that messaging with corporate social responsibility (CSR) also increases productivity while also increasing propensity of cheating. In this paper, we contribute to and synthesize these two strands of literature on worker incentives in a common setting, with experimental data. We intend to run a large-scale experiment that varies the framing and language of monetary incentive offers in messages prompting Lyft driver applicants to complete tasks in the application process. We will use this data to measure the effects on task completion rates, productivity, and work quality for applicants who complete their application.
External Link(s)
Registration Citation
List, John et al. 2019. "Does 25 + 25 + 25 = 75?: a natural field experiment on task completion." AEA RCT Registry. August 21. https://doi.org/10.1257/rct.4606-1.0.
Experimental Details
Individuals who have started but have not completed their application to become a rideshare driver will receive a series of messaging and/or monetary incentive offers that prompt them to complete the various application tasks and give a ride on the rideshare platform.
Intervention Start Date
Intervention End Date
Primary Outcomes
Primary Outcomes (end points)
The primary outcome of interest is the effectiveness of intervention on task completion rates
Primary Outcomes (explanation)
The task completion rate we are primarily interested in is the overall activation rate of applicants, i.e. the proportion of drivers who complete the application and give a ride on the Lyft platform
Secondary Outcomes
Secondary Outcomes (end points)
Secondary outcomes include intermediate task completion rates, time to application completion, and subsequent labor supply outcomes after the applicant becomes a driver.
Secondary Outcomes (explanation)
Intermediate task completion rates will be measured by the proportion of applicants who complete individual intermediate steps of the application. Time to completion will be measured in days (time from messaging to application completion). Subsequent labor supply outcomes after the applicant becomes a driver include hours worked, rides given, hourly wage (total earnings / total hours), tips and ratings received from riders, and attrition (time until driver doesn't give a ride in more than 14 days).
Experimental Design
Experimental Design
Individuals who have have not yet completed their application to become rideshare drivers will be randomized into treatments that vary the monetary incentive offer, corporate social responsibility (CSR) language, and framing of the monetary incentive in messages to the applicant.
Experimental Design Details
Applicants in the experiment will be randomly assigned to one of 6 treatment groups (including a control group). Depending on the treatment, applicants will receive messaging and/or monetary incentive offers to encourage their movement through the application process. We aim to measure the effect of offering monetary incentives for task completion, the effect of varying the framing of these monetary offers, and the effect of including corporate social responsibility (CSR) language on various task completion and engagement measures. The offers and messages will communicated via email and SMS text messages that are sent as the applicant completes tasks in the application process.
Randomization Method
Randomization Unit
Individual applicant
Was the treatment clustered?
Experiment Characteristics
Sample size: planned number of clusters
31,546 applicants
Sample size: planned number of observations
31,546 applicants
Sample size (or number of clusters) by treatment arms
5549 applicants control, 5207 applicants standard incentive offer, 4817 applicants incentive with upfront framing, 5464 applicants incentive with evenly distributed framing, 5267 applicants incentive with CSR language, 5242 no incentive with CSR language
Minimum detectable effect size for main outcomes (accounting for sample design and clustering)
Minimum detectable effect size is 0.96% increase in application completion rate between any two treatment arms under standard assumptions.
IRB Name
University of Chicago
IRB Approval Date
IRB Approval Number
Analysis Plan

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Reports, Papers & Other Materials
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