Selection and the Role of Personality

Last registered on November 17, 2023

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Pre-Trial

Trial Information

General Information

Title

Selection and the Role of Personality

RCT ID

AEARCTR-0012473

Initial registration date

November 09, 2023

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

November 17, 2023, 7:58 AM EST

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

Locations

Country

Germany

Region

Primary Investigator

Name

Raphael Moritz

Affiliation

University of Tuebingen

Contact Primary Investigator

Other Primary Investigator(s)

PI Name

Kerstin Pull

PI Affiliation

University of Tuebingen

Contact Investigator

PI Name

Sonja Utz

PI Affiliation

Leibniz-Institut für Wissensmedien (IWM), Tuebingen

Contact Investigator

Additional Trial Information

Status

In development

Start date

2020-07-01

End date

2024-12-31

Keywords

Behavior

Additional Keywords

Selection, Personality, Social Media, Field Experiment, Shared Housing, Information Systems

JEL code(s)

R23, J15, J16, C93

Secondary IDs

Prior work

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

Abstract

We conduct a correspondence test in the shared housing market to determine the role of personality signaling images posted on fictitious social media profiles on selection decisions. Approximately 3,000 fictitious applications with a randomly assigned social media profile are sent to vacant room ads to determine the effect of personality information on callback rates. The profiles were created over the course of three years to credibly signal high (low) conscientiousness and high (low) agreeableness/low (high) neuroticism, respectively – reflecting the Big Five personality traits most pertinent to selection decisions in both shared housing markets and organizational settings. We conducted several randomized online pilot experiments to verify that the selected images posted on the profiles accurately represent the intended personality dimensions, while also ensuring the realism of the profiles. In addition, we can approximate whether landlords or roommates visit these profiles and exploit this information using statistics on profile visits and page impressions.

External Link(s)

Registration Citation

Citation

Moritz, Raphael, Kerstin Pull and Sonja Utz. 2023. "Selection and the Role of Personality." AEA RCT Registry. November 17. https://doi.org/10.1257/rct.12473-1.0

Sponsors & Partners

Experimental Details

Interventions

Intervention(s)

Intervention (Hidden)

Intervention Start Date

2024-02-01

Intervention End Date

2024-06-30

Primary Outcomes

Primary Outcomes (end points)

Callbacks rates

Primary Outcomes (explanation)

Callbacks rates conditional on variation in social media information signaling personality traits. A response is classified as a callback, if the applicant is invited to a viewing, or to a (video) call.

Secondary Outcomes

Secondary Outcomes (end points)

- Other types of responses
- Time between sending the application and receiving a response
- Other information in response
- Social media variables

Secondary Outcomes (explanation)

Other types of responses may include advertisers requesting a phone/online call, asking for additional information about the applicant, or rejections. Other information regarding the response itself could include length, friendliness, number of smileys or other emojis, time between callback and viewing date, etc. Social media variables include weekly visits, reach, and impressions of profiles and/or posts.

Experimental Design

We use a non-matched pair randomized controlled trial (between-subjects design) to test for callback differences across different personality traits signaled by social media profiles in the shared housing market in Germany. To do so, we use a 2x2 design (conscientiousness vs. agreeableness/neuroticism x high vs. low), additional to a baseline condition without social media information. Therefore, we randomly vary the information that a potential roommate or landlord receives as a source of additional information about an applicant’s personality in an application for a vacant room (correspondence test design). The submitted applications are similar in all aspects except for the parts that signal an applicant's personality through the corresponding social media profile.

Experimental Design Details: The informational variation of our study is provided by social media profiles that signal different personality traits. Therefore, we create four social media profiles on the photo-sharing platform “Instagram” showing images of a female student who agreed to provide us with her personal photos for the purpose of this experiment. Using a selection of these photos and additional photos, e.g., from PsychoFlickr (Segalin et al. 2016), we compile a set of photos and description texts indicating high (low) conscientiousness and high (low) agreeableness/low (high) neuroticism. These photos and description texts were uploaded to the profiles over the course of three years. The name of each profile owner is held constant across all conditions and represents one of the most common German female names in the respective birth cohort. In addition, all other characteristics of the profile owner are held constant, i.e., age, study program, etc. The number of followers and the number of other profiles subscribed to by the fictitious profile are very similar for the conditions high (low) conscientiousness and differ for high (low) agreeableness/low (high) neuroticism, in line with the personality traits. Real students are recruited as followers in order to make the profiles as realistic as possible. To test whether the treatment conditions (fictitious social media profiles) successfully manipulate the relevant personality traits, we conducted a randomized online experiment prior to this RCT in which one of the four social media profiles signaling the respective personality traits was randomly assigned.

Experimental Design Details

Randomization Method

Computer generated (pseudo) randomization using Python

Randomization Unit

Individual level

Was the treatment clustered?

Experiment Characteristics

Sample size: planned number of clusters

n/a

Sample size: planned number of observations

3,000

Sample size (or number of clusters) by treatment arms

Assuming a 42.2% percent overall callback rate (average from previous studies) we will send out approximately 600 inquiries (roughly estimated) for each of the five conditions (conscientiousness vs. agreeableness/neuroticism x high vs. low + without social media information), resulting in about 3,000 applications in total.

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

Supporting Documents and Materials

IRB