Incentivizing persistent efforts

Last registered on September 02, 2022

Pre-Trial

Trial Information

General Information

Title
Incentivizing persistent efforts
RCT ID
AEARCTR-0009995
Initial registration date
August 30, 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
September 02, 2022, 4:04 PM EDT

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

Locations

Region

Primary Investigator

Affiliation
Monash University

Other Primary Investigator(s)

PI Affiliation
Monash University
PI Affiliation
University of Technology Sydney

Additional Trial Information

Status
In development
Start date
2022-09-05
End date
2023-06-30
Secondary IDs
Prior work
This trial is based on or builds upon one or more prior RCTs.
Abstract
Many tasks in organizations are boring and involve repetitive work without internal reward. This project examines whether we can design external mechanisms to incentivize persistent efforts in completing these tasks.
External Link(s)

Registration Citation

Citation
Incekara-Hafalir, Elif , Grace Lee and Erte Xiao. 2022. "Incentivizing persistent efforts." AEA RCT Registry. September 02. https://doi.org/10.1257/rct.9995-1.0
Sponsors & Partners

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Experimental Details

Interventions

Intervention(s)
We design incentive mechanisms to promote perseverant effort to complete tasks with low internal rewards.
Intervention Start Date
2022-09-05
Intervention End Date
2022-12-31

Primary Outcomes

Primary Outcomes (end points)
Full completion rate of the tasks; zero completion rate; completion rate after one failure; when do subjects start to work on the task each week; the quality of the completed work; whether subjects continue to complete the optional task in the more lenient ‘all-or-nothing’ incentive mechanism.
Primary Outcomes (explanation)

Secondary Outcomes

Secondary Outcomes (end points)
Secondary Outcomes (explanation)

Experimental Design

Experimental Design
Participants will be invited to work on an online survey over five weeks (one each week). Depending on the treatment, the subject would either receive the payment based on the number of surveys they complete (piece rate treatment) or would have to complete all surveys to receive the payment (exogenously imposed all-or-nothing treatment). We also allow the subjects to choose between the piece rate or the all-or-nothing option (the self-select treatment). In addition, we introduce a more lenient ‘all-or-nothing’ mechanism (exogenously imposed and self-select) by allowing them to miss one task and yet still receive the full reward (e.g., they received full rewards by completing at least 80% of the given tasks). Finally, we include additional treatments with reminders - reminding those who have completed 80% of tasks that they are qualified for full payment and that their next task is optional.
Experimental Design Details
The participants are undergraduate students, and we randomly assign them to one of the following treatments:
1: Baseline (Piece-rate)
2: All-or-nothing (complete all)
3: All-or-nothing (allow missing one) – No reminder
4: All-or-nothing (allow missing one) – Reminder
5: Self-select (complete all)
6: Self-select (allow missing one) – No reminder
7: Self-select (allow missing one) – Reminder
* Reminder - Reminding those who have completed 80% of tasks that they are qualified for full payment and that their next task is optional.
Randomization Method
Block randomization in Qualtrics
Randomization Unit
Individual
Was the treatment clustered?
No

Experiment Characteristics

Sample size: planned number of clusters
Approximately 1000 students
Sample size: planned number of observations
Approximately 1000 students
Sample size (or number of clusters) by treatment arms
100 Baseline (Piece-rate)
100 All-or-nothing (complete all)
100 All-or-nothing (allow missing one) – No reminder
100 All-or-nothing (allow missing one) – Reminder*
200 Self-select (complete all)
200 Self-select (allow missing one) – No reminder
200 Self-select (allow missing one) – Reminder*
Minimum detectable effect size for main outcomes (accounting for sample design and clustering)
IRB

Institutional Review Boards (IRBs)

IRB Name
Monash University Human Research Ethics Committee
IRB Approval Date
2022-08-30
IRB Approval Number
35285

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