Time pressure in decision making quality

Last registered on March 28, 2022

View Trial History

Pre-Trial

Trial Information

General Information

Title

Time pressure in decision making quality

RCT ID

AEARCTR-0008970

Initial registration date

March 25, 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

March 28, 2022, 7:09 AM EDT

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

Locations

Country

United States of America

Region

Primary Investigator

Name

Ha Linh Nguyen

Affiliation

Skidmore College

Contact Primary Investigator

Other Primary Investigator(s)

PI Name

Sandra Goff

PI Affiliation

Skidmore College

Contact Investigator

Additional Trial Information

Status

Completed

Start date

2022-03-22

End date

2022-03-27

Keywords

Behavior

Additional Keywords

game theory

JEL code(s)

Secondary IDs

Prior work

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

Abstract

This study, conducted as a Senior Thesis experiment at Skidmore College in the Spring semester of 2022, investigates the effect of time pressure in the context of decision-making quality. The study will implement two economic games: ultimatum and beauty contest game to determine whether time pressure impacts the game choices from participants.

External Link(s)

Registration Citation

Citation

Goff, Sandra and Ha Linh Nguyen. 2022. "Time pressure in decision making quality ." AEA RCT Registry. March 28. https://doi.org/10.1257/rct.8970-1.0

Sponsors & Partners

Experimental Details

Interventions

Intervention(s)

Participants are randomized to receive either the time pressure or no time pressure condition. All participants play two games: a beauty contest and an ultimatum game

Intervention Start Date

2022-03-25

Intervention End Date

2022-03-26

Primary Outcomes

Primary Outcomes (end points)

Participant's choices in each game

Primary Outcomes (explanation)

Secondary Outcomes

Secondary Outcomes (end points)

Secondary Outcomes (explanation)

Experimental Design

Participants recruited on Amazon Mechanical Turk engage in an online economic experiment in which they are randomly assigned to either a control (no time pressure) or treatment (time pressure) condition before playing two economic games: the beauty contest game and the ultimatum game

Experimental Design Details

This study is conducted on Amazon Mechanical Turk with approximately 174 participants from across the United States. Participants are randomly assigned to a time condition (with time pressure and without time pressure).
In the beauty contest game, the participants will be instructed to pick a number between 0 and 100, and given the information that anyone whose number is closest to the pre-defined values (two-third of average) would win the game. In the offer game, participants will be put into 2 scenarios: provider and receiver. The provider will offer some money of their choice between 0 and 5$. If the receiver rejects it, both sides will receive 0, if the receiver accepts it, then they will separate the money as decided. In the time treatment of the experiment, the participants will have 15 seconds to make their decisions, while there is no time limit for the participants under without time pressure treatment.
Finally, participants are asked a set of risk preferences and demographic questions and a question to determine what they think the study is about.

Randomization Method

Qualtrics' randomization capabilities are used to assign participants to conditions.

Randomization Unit

individual

Was the treatment clustered?

Experiment Characteristics

Sample size: planned number of clusters

174 participants

Sample size: planned number of observations

174 observations (1 observation per participant)

Sample size (or number of clusters) by treatment arms

approximately 87 in time pressure/87 in no time pressure

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

Using an online a priori calculator for multiple regression analysis, a minimum sample size of 157 participants is necessary to find an effect size of 0.2 at α = 0.01 with a statistical power of 0.95 and approximately 8 predictors. We will recruit a sample size 174 participants to ensure statistical power.

Supporting Documents and Materials

IRB