Effort Transparency and Fairness

Last registered on July 17, 2023
View Trial History

Pre-Trial

Trial Information

General Information

Title
Effort Transparency and Fairness
RCT ID
AEARCTR-0009291
Initial registration date
April 21, 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
April 28, 2022, 5:52 PM EDT

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

Last updated
July 17, 2023, 11:12 AM EDT

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

Locations

Country
United States of America
Region

Primary Investigator

Name
Elif Demiral
Affiliation
Austin Peay State University
Contact Primary Investigator

Other Primary Investigator(s)

PI Name
Joy Buchanan
PI Affiliation
Samford University
PI Name
Umit Saglam
PI Affiliation
East Tennessee State University

Additional Trial Information

Status
Completed
Start date
2022-04-22
End date
2022-05-31
Keywords
Behavior, Labor
Additional Keywords
Transparency, Experiment, Effort, Fairness, Gender
JEL code(s)
C90, J01, D90
Secondary IDs
Prior work
This trial does not extend or rely on any prior RCTs.
Abstract
In many situations, information asymmetries arise and influence human behavior. Such cases are widespread in hierarchical work settings. For example, a manager can have more precise knowledge of the value of worker output than the workers themselves do. This information asymmetry may then be carried over to the decisions executed by the manager involving the allocation of resources. If individual contributions are imperfectly known, the allocation of resources, such as compensation, career promotions, and bonus distributions, may be enacted unfairly. For example, in a teamwork setting, with imperfect information on individual performance, one party would have an incentive to take advantage of others' hard work (Chaw et al., 1988). Further underscoring this from an organizational standpoint, such secrecy and unfair behavior can result in a decline in work effort (Nai et al., 2020). If workers know that the reward can be less than their marginal value of effort, this will result in the effort level being inferior. In this project, we aim to address how information asymmetry affects fairness behavior in endowment allocation and worker performance. We plan to test this with an online experiment using a dictator game with joint endowments.
External Link(s)

Registration Citation

Citation
Buchanan, Joy, Elif Demiral and Umit Saglam. 2023. "Effort Transparency and Fairness." AEA RCT Registry. July 17. https://doi.org/10.1257/rct.9291-1.1
Sponsors & Partners
Experimental Details

Interventions

Intervention(s)
Intervention Start Date
2022-04-22
Intervention End Date
2022-05-31

Primary Outcomes

Primary Outcomes (end points)
Giving (taking) behavior in the dictator game by Player A.
Effort level in the first part by Player B.
Primary Outcomes (explanation)
We test two main hypotheses. First, we believe player A will adhere to meritocratic rules while distributing the endowment (recognizing and honoring player B's effort) more in the transparent than in the nontransparent situation. We expect that player A will take some of player B's contribution (will give As less than they performed) when player B does not know their exact contribution (i.e., comparing nontransparent vs. transparent treatment). Next, we believe the effort of player Bs (recipients) will be lower in the nontransparent case compared to the transparent treatment. In the first stage, we expect that player B will exert less effort when they cannot learn about their actual performance (nontransparent treatment) than in the case where they have perfect information (transparent treatment).

Secondary Outcomes

Secondary Outcomes (end points)
Gender's role in effort level for Player B.
Gender's role in giving (taking) behavior for Player A.
Secondary Outcomes (explanation)

Experimental Design

Experimental Design
Our experimental design involves two players: A, the dictator, and B, the recipient. Participants are randomly assigned one of these roles at the start of the experiment. The experiment involves two stages. The first stage is a real-effort stage where the participants perform a simple counting task. Each correct answer in this part contributes to a joint endowment to be shared in the second stage (where each correct answer adds $0.10 to the joint endowment). The second stage of the experiment involves a dictator game with taking.

The design embodies two treatments. In our control (transparent) treatment, both players' contributions to the joint endowment are common knowledge in the second stage. Both the dictator (player A) and the recipient (player B) have perfect information about their own and the opponent's performance. The next treatment involves imperfect information (nontransparent), and only player A (dictator) knows the performance and contribution of each player to the joint endowment. Player B receives no information regarding their performance. In the second stage, the dictator (player A) distributes the joint endowment between themself and player B. The experiment then concludes with a questionnaire collecting participants' beliefs (such as beliefs about their own and the opponent's performance) and demographics.
The experiment will be an online experiment using Prolific.
Experimental Design Details
Randomization Method
Experimental software (Qualtrics) conducts randomization of treatments.
Randomization Unit
Randomization will happen for each experimental data collection session.
Was the treatment clustered?
Yes

Experiment Characteristics

Sample size: planned number of clusters
Two clusters, one for each role.
Sample size: planned number of observations
We aim to recruit about 200-300 subjects for each role. This corresponds to a total of 400-600 observations.
Sample size (or number of clusters) by treatment arms
We aim to have about 200-300 observations for each treatment.
Minimum detectable effect size for main outcomes (accounting for sample design and clustering)
Supporting Documents and Materials
IRB

Institutional Review Boards (IRBs)

IRB Name
Austin Peay State University IRB
IRB Approval Date
2022-02-25
IRB Approval Number
APSU IRB 22-012
Analysis Plan

Post-Trial

Post Trial Information

Study Withdrawal

There is information in this trial unavailable to the public. Use the button below to request access.

Request Information

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