Choice Overload on Regret Aversion

Last registered on May 05, 2022

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Pre-Trial

Trial Information

General Information

Title

Choice Overload on Regret Aversion

RCT ID

AEARCTR-0009354

Initial registration date

May 04, 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

May 05, 2022, 10:03 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

Hye Joo Jung

Affiliation

Skidmore College

Contact Primary Investigator

Other Primary Investigator(s)

Additional Trial Information

Status

In development

Start date

2022-05-04

End date

2022-05-21

Keywords

Behavior

Additional Keywords

JEL code(s)

Secondary IDs

Prior work

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

Abstract

The study investigates the effect of choice overload on regret aversion. Participants are assigned to one of the two different size of choice sets (6 options and 30 options), then asked to report their regret aversion preference. To test the hypotheses, we used Qualtrics survey and recruited the participants using Amazon Mechanical Turk. This study is conducted as a Senior Thesis experiment at Skidmore in the Spring semester of 2022.

External Link(s)

Registration Citation

Citation

Jung, Hye Joo. 2022. "Choice Overload on Regret Aversion." AEA RCT Registry. May 05. https://doi.org/10.1257/rct.9354-1.0

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Experimental Details

Interventions

Intervention(s)

Participants randomly assigned to a small choice set (6 options) and a large choice set (30 options). After they are asked to report their regret aversion preference.

Intervention Start Date

2022-05-04

Intervention End Date

2022-05-12

Primary Outcomes

Primary Outcomes (end points)

Regret Aversion(pay to avoid regret; not pay but avoid regret; seek Information)

Primary Outcomes (explanation)

Secondary Outcomes

Secondary Outcomes (end points)

Secondary Outcomes (explanation)

Experimental Design

The participants are randomly introduced to two

Experimental Design Details

Randomization Method

Qualtrics's randomization function was used in the process of assigning participants to the conditions. The function was again used in the process of randomly introducing the three rounds of choice sets and selection of the payment round.

Randomization Unit

individual

Was the treatment clustered?

Experiment Characteristics

Sample size: planned number of clusters

120

Sample size: planned number of observations

120

Sample size (or number of clusters) by treatment arms

approximately 60 in large choice set; 60 in small choice set

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 102 participants is necessary to find an effect size of 0.39 at α = 0.05 with a statistical power of 0.80 and approximately 7 predictors. We will recruit a sample size of 120 participants to ensure statistical power of at least 0.80 with exclusions.

Supporting Documents and Materials

IRB