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The Impact of Competitiveness on Employability
Last registered on April 08, 2019

Pre-Trial

Trial Information
General Information
Title
The Impact of Competitiveness on Employability
RCT ID
AEARCTR-0004031
Initial registration date
March 20, 2019
Last updated
April 08, 2019 4:09 PM EDT
Location(s)
Region
Primary Investigator
Affiliation
George Mason University
Other Primary Investigator(s)
PI Affiliation
George Mason University
Additional Trial Information
Status
In development
Start date
2019-03-21
End date
2019-07-10
Secondary IDs
Abstract
Hiring an employee is an essential task for decision makers and can significantly affect the future performance of an organization. Even though some research addresses the effect of hiring competitive employees on the organization’s performance, little is known about the impact of different competitive preferences on employee hiring decisions. Would decision makers like to hire agents who compete against other people or the ones who continuously challenge against their own previous performance or the ones who work efficiently without competing against anyone? Using one laboratory and two online experiments this project aims to investigate whether and to what extent competitiveness as a trait/preference impact one's likelihood of being hired. The laboratory study focuses on the performance aspect of competitiveness; i.e., are competitive individuals perceived as better performers than non-competitive individuals? Online studies focus on the social aspect; i.e., would competitive individuals be liked/disliked at different extents than less competitive individuals in the workplace? Would hypothetical cover letters be evaluated differently based on the competitive preferences of the candidate? The study additionally involves a particular focus on gender. We will answer whether being a competitive woman is more likely to be penalized/disliked in a hypothetical job search situation and whether being a self-competitive individual (i.e., being committed to constant self-improvement as opposed to being rivalrous against other people) would increase women's likelihood of being hired.
External Link(s)
Registration Citation
Citation
Demiral, Elif E and Johanna Mollerstrom. 2019. "The Impact of Competitiveness on Employability." AEA RCT Registry. April 08. https://doi.org/10.1257/rct.4031-2.0.
Former Citation
Demiral, Elif E and Johanna Mollerstrom. 2019. "The Impact of Competitiveness on Employability." AEA RCT Registry. April 08. https://www.socialscienceregistry.org/trials/4031/history/44774.
Experimental Details
Interventions
Intervention(s)
We will study our research question using three experiments: a laboratory experiment (Study 1), and two online experiments (Studies 2 and 3). In Study 1, student subjects will be in the role of a Firm and will decide to hire a Worker who performed in a task (math addition task) for several rounds. The hired worker's score in the first round will determine the firm's payoff. Workers will differ in their compensation scheme choices they made in the last round (choices being entering a tournament against another person, entering in a tournament against self, or not entering in a tournament). In Study 2, online participants will give advice to a hypothetical job seeker on what to include in his/her cover letter regarding his/her competitive preferences (options being self-competitive, non-competitive or other-competitive). In Study 3, online participants will read six hypothetical cover letters which will vary in gender (as signaled with names) and the competitive preferences (possibilities being self-competitive, non-competitive and other-competitive) of the candidates and rate them based on their employability prospects.

In Study 1, there will be three treatments. We will randomly assign subjects to one of these treatments (randomized at the individual level).
1. Female treatment where all the workers will be females.
2. Male treatment, where all the workers will be males.
3. Neutral treatment, where the gender of the worker will not be known by the firm.

In Study 2, there will be four (2x2) conditions. The candidates will vary in gender and the work will either involve working independently or working as a team. Each subject will give advice to a male and a female candidate. We will randomly assign subjects in either of the work condition (independent vs. team).

In Study 3, there will be 12 (2x2x3) conditions. The candidates will vary in gender, the work will either involve working independently or working as a team and each candidate will have a different competitive preference (self-competitive, not competitive, other-competitive).​ Each subject will rate six cover letters varying in gender and the competitive preference. ​We will randomly assign subjects in either of the work condition (independent vs. team).
Intervention Start Date
2019-03-21
Intervention End Date
2019-07-10
Primary Outcomes
Primary Outcomes (end points)
Likelihood of being hired based on competition choice (Study 1).
The content of the advice given regarding competitive preferences (Study 2).
The rating (on a Likert scale) that each cover letter receives regarding its employability (Study 3). The ratings include the likelihood of the candidate a) getting an interview, b) being hired, c) getting a promotion.
Primary Outcomes (explanation)
Likelihood of being hired will be a binary variable denoting whether a certain worker is hired.
The content of the advice is the advice (among three alternatives) that the subjects give to the hypothetical candidates to mention in a cover letter.
The rating is a value assigned to each candidate using a Likert scale from 1 to 10.
Secondary Outcomes
Secondary Outcomes (end points)
Firms' belief about the worker's performance. (Study 1)
Firms' belief about their own performance. (Study 1)
Self-reported competitiveness of the firms. (Study 1)
Self-reported causal attributions that the firms report regarding worker performance. (Study 1)
Self-reported risk preferences. (Study 1)
Self-reported competitiveness. (Study 2)
Self-reported risk preferences. (Study 2)
Rating of how enjoyable would it be to work with the candidate. (Study 3)
Rating of easiness to work with the candidate. (Study 3)
Rating of how confident the candidate would be. (Study 3)
Rating of how productive the candidate would be. (Study 3)
Self-reported competitiveness. (Study 3)
Self-reported risk preferences. (Study 3)

Secondary Outcomes (explanation)
Experimental Design
Experimental Design
Study 1 Design:

The experiment involves two groups of subjects. The first group is the “workers” who perform in a math addition task for four rounds. In the last round, they choose among three different payment schemes: self-tournament, other tournament and piece rate. The workers will be paid based on a randomly picked round.
In a later experiment, we recruit another set of subjects – “firms”. Firms’ first task is to perform in the math task for five minutes for one round – so that they would be familiarized with the nature of the task that the workers finished. We pay them 20 cents per correctly answered problem. Their second task is to choose a person who performed under the three different payment scheme rounds and in a final choice round. The Firms decide who to hire based on their choice in the final round and the worker’s first-round score determines the Firm’s payoff. The lab study involves three treatments: male treatment, female treatment, and neutral treatment.

In gender (male and female) treatments, the Firm first learns the gender of their potential workers. That is, we tell them that among three only male/only female workers, they will hire one. And that each of those males/females has chosen different compensation schemes in their final rounds: one of them competed against herself, one of them competed against another individual, and one of them chose not to compete. We would then ask them who they would like to hire (whose round 1 performance will apply to their own payoff).

In neutral treatment, firms are matched to three individuals whose gender is not known. Rest of the procedures are identical to the gender treatment. In the end, we ask a question of where we learn the believed gender of the worker.

At the end of the experiment, subjects are asked their belief about their own and the hired worker's performance in the task ( in round 1).

Study 2 Design:
In Study 2, online subjects (MTurk workers) are told that a friend of theirs is seeking for advice about what to include his/her cover letter for a job s/he is interested in applying. The advice seeker can have three competitive traits (s/he is sometimes self-competitive, is sometimes other-competitive and sometimes refrains from competitions). The advice giver reads all these traits and what they mean in detail. We will implement four treatments: the work can involve independent decision making or can require teamwork and the gender of the advice seeker varies. We will incentivize the advice by paying subjects extra if their suggestions match with the majority of the participants.

Study 3 Design:
In Study 3, the participants rate different cover letters based on their employability. Keeping everything else constant, we will vary the gender of the applicant and their competitive tendencies (self-competitive, non-competitive, other-competitive). Additionally, we will vary the nature of the work condition: the work can involve independent decision making or can require teamwork. Each subject will rate six cover letters based on their: Likelihood of being invited for an interview; likelihood of being hired; likelihood of getting a promotion for an upper-level position. The way we will incentivize those ratings will involve a comparison of the subjects' ratings to an expert's ratings. The closer their ratings to the expert's, the higher the subjects will earn.


Experimental Design Details
Randomization Method
Treatment conditions will be randomized at the individual level. All randomizations will be done by the computer programs (zTree for Study 1 and Qualtrics for Studies 2 and 3).
Randomization Unit
Treatments will be randomized at the individual level. In the online studies, the order which the subjects rate/give advice to different candidates will also be randomized at the individual level.
Was the treatment clustered?
No
Experiment Characteristics
Sample size: planned number of clusters
No clusters. The lab study will be run at GMU ICES Lab in Fairfax Campus and online studies will be run using Amazon Mechanical Turk.
Sample size: planned number of observations
Around 120 subjects. (Study 1) Around 800 subjects. (Study 2) Around 1000 subjects. (Study 3)
Sample size (or number of clusters) by treatment arms
Study 1: 40 observations for female treatment, 40 observations for male treatment, 40 observations for neutral treatment.
Study 2: 400 observations for independent work condition, 400 for teamwork condition. Gender condition will be implemented as within subject design (subjects will see both a male and a female candidate in random order).
Study 3: 500 observations for independent work condition, 500 for teamwork condition. Gender and competitive preference conditions will be implemented as within subject design (subjects will rate three male and three female cover letters based with varying competitive preferences).
Minimum detectable effect size for main outcomes (accounting for sample design and clustering)
IRB
INSTITUTIONAL REVIEW BOARDS (IRBs)
IRB Name
GMU Office of Research Development, Integrity, and Assurance
IRB Approval Date
2019-03-06
IRB Approval Number
1395227-1
Post-Trial
Post Trial Information
Study Withdrawal
Intervention
Is the intervention completed?
No
Is data collection complete?
Data Publication
Data Publication
Is public data available?
No
Program Files
Program Files
Reports and Papers
Preliminary Reports
Relevant Papers