Back to History Current Version

When Social Identity Matters: Low Self-Esteem in Highly Esteemed Groups Predicts “We-thinking”

Last registered on September 03, 2019

Pre-Trial

Trial Information

General Information

Title
An Empirical Study of "We-thinking" and Status
RCT ID
AEARCTR-0004655
Initial registration date
September 01, 2019

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
September 03, 2019, 4:55 PM EDT

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

Locations

Primary Investigator

Affiliation
University of Michigan

Other Primary Investigator(s)

Additional Trial Information

Status
In development
Start date
2019-09-03
End date
2019-12-22
Secondary IDs
Abstract
Social motivations, such as one’s status, enjoy wide recognition as critical determinants of human behavior. A key reason for studying individual and group status is to shed light on the conditions that facilitate—or deter—actions that enhance group payoffs at the cost of individual payoffs. In this paper, I focus on two types of status: the status that is conferred on an individual and the status conferred on the group to which an individual belongs. I extend a model based on R. Akerlof (2016) where individuals face a tradeoff between maximizing the group’s payoffs and their individual payoffs, and their willingness to maximize the group’s payoffs is positively related to the extent to which their group status is higher than their individual status. The model predicts that subjects with high (low) group status and low (high) individual status are most (least) engaged in maximizing the group’s payoffs. To test this prediction, I conduct a laboratory experiment in which individual status is assigned based on individual performance in a calculation task, and group status is determined by the overall performance of the individual group members. In the information treatment, subjects learn about both their individual and group ranks (but do not have this information in the baseline). Subjects allocate tokens such that either their own or the group’s payoff is maximized. This study can help us predict what types of people are intrinsically motivated to work for the group and what types of people are not and might need extra motivations.
External Link(s)

Registration Citation

Citation
Song, Zhewei. 2019. "An Empirical Study of "We-thinking" and Status." AEA RCT Registry. September 03. https://doi.org/10.1257/rct.4655-1.0
Sponsors & Partners

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

Request Information
Experimental Details

Interventions

Intervention(s)
Intervention Start Date
2019-09-03
Intervention End Date
2019-12-22

Primary Outcomes

Primary Outcomes (end points)
The number of tokens subjects' allocate to their personal account and the number of tokens they allocate to their group's account.
Primary Outcomes (explanation)

Secondary Outcomes

Secondary Outcomes (end points)
Subjects' self-reported group attachment level
Secondary Outcomes (explanation)

Experimental Design

Experimental Design
This study is intended to test the following predictions: 1) When a person has high group status and low individual status, she puts more weight on her group’s payoff than her own payoff and thus allocates more to her group than herself. 2) When she has low group status and high individual status, she puts more weight on her own payoff than her group’s payoff and thus allocates more to herself than her group.
I conduct a laboratory experiment to test the hypotheses above. The experiment has two treatments: Baseline and TreatStatus. Subjects in the TreatStatus treatment receive information about their group status and individual status before their allocation between their groups and themselves, while subjects in the Baseline do not have the information before their allocation. Both treatments consist of five stages. There are six subjects in each session. I use z-Tree (Fischbacher, 2007) to program this experiment.
In Stage 1, I assign subjects in both treatments to different groups based on their preferences for paintings. The procedure in this stage mainly follows Chen and Li’s design (2006) with a few changes to guarantee that the number of subjects in each group is the same.
Six subjects are assigned to two groups based on their reported preference on five pairs of paintings . In each pair, there is one painting made by Paul Klee and one painting made by Wassily Kandinsky. Each subject independently chooses which painting she prefers in each pair without being told the artist of each painting. After all subjects make their decisions, the computer sorts the six subjects based on how many Klee’s paintings they prefer (if there is a tie among multiple subjects, then these subjects’ orders are determined randomly). The first three subjects, who prefer the most Klee’s paintings, are classified into Group Klee. The second three subjects, who prefer relatively less Klee’s paintings, are classified into Group Kandinsky. Subjects in Group Klee are told that all of their group members relatively prefer Klee’s paintings, compared with other subjects. Subjects in Group Kandinsky are privately told that all of their group members relatively prefer Kandinsky’s paintings . Each subject does not receive information about any other subject’s group membership. Groups remain the same for the entire experiment.
In Stage 2, subjects in both treatments participate in a two-round calculation game. The first round of the game determines their individual status, while the second round determines their group status. In the first round of the game, all subjects are assigned into pairs in which the two subjects are from different groups (i.e. one subject is from the Klee group and the other is from the Kandinsky group). Each pair play a calculation game in which they are asked to solve as many calculation problems as possible within two minutes. Each calculation problem asks subjects to calculate the sum of five two-digit numbers. At the end of the first round, each subject receives $0.25 for each correct answer. Incorrect answers do not decrease each subject’s payoff. In addition, the subject who correctly solved more problems within each pair wins the first round of the game and receives an $1.00 bonus. The winner within each pair is assigned high individual status, while the loser is assigned low individual status.
In the second round, each subject is again given two minutes to solve as many calculation problems (calculating the sum of five two-digit numbers) as possible. At the end of the second round, each subject still receives $0.25 for each correct answer, and incorrect answers do not decrease her payoff either. The computer calculates the total number of correct answers the three members get in each group. The group with more total correct answers wins the second round and each of the three group members receives an additional $1 bonus. Subjects do not receive any information about the results in this game, including the number of correct answers they get in each round, whether they win the first round and whether their groups win the second round until later.
In Stage 3, subjects in the Baseline treatment and the TreatStatus treatment receive different information about their performance in Stage 2. Each subject in the Baseline treatment is only told the number of correct answers she solves in each round of the calculation game and the corresponding payoff, but not whether she wins the first round against her opponent in her pair and whether her group win the second round against the other group. They are told all the information at the end of the experiment. Each subject in the TreatStatus treatment, however, is told all the information, including the number of correct answers she solves in each round, whether she wins the first round and whether her group win the second round. Each subject does not receive any information about any other subject’s game results throughout the whole experiment.
In Stage 4, I elicit subjects’ engagement in “we-thinking” in both treatments. Each subject is asked to play a dictator game in which she decides how to allocate six tokens between her personal account and her group account. Each token allocated to her personal account is worth $1.00, while each token allocated to her group account is worth $1.50. At the end of this stage, the computer randomly selects one subject in each group to determine the payoffs in her group. If a subject’s decision is randomly selected to determine payment, she gets all the money she allocates to her personal account, and the money she allocates to her group account is evenly shared by the 3 members of her group. In other words, this subject’s payoff equals to $1.00 * the number of tokens she allocates to her personal account + $1.50 / 3 * the number of tokens she allocates to her group account. The two other subjects in her group, whose decisions are not selected, receive payoffs of $1.50 / 3 * the number of tokens she (i.e. the subject in their group whose decision is selected) allocates to her group account.
In Stage 5, I ask subjects in both treatments to answer one survey question about to what extent they are attached to their groups.
After subjects in both treatments indicate their levels of group attachment in Stage 5, they are shown the last screen which displays all the game results in Stage 2 (i.e. the number of correct answers they get in each round, whether they win the first round, whether their groups win the second round and their payoffs), Stage 4 (i.e. whether their decisions are randomly selected and their payoffs), and their total earnings in the experiment.
Experimental Design Details
Randomization Method
By a computer
Randomization Unit
individual
Was the treatment clustered?
No

Experiment Characteristics

Sample size: planned number of clusters
280 individuals
Sample size: planned number of observations
280 individuals
Sample size (or number of clusters) by treatment arms
56 individuals in Baseline; 224 individuals in TreatStatus
Minimum detectable effect size for main outcomes (accounting for sample design and clustering)
IRB

Institutional Review Boards (IRBs)

IRB Name
Health Sciences and Behavioral Sciences Institutional Review Board at the University of Michigan
IRB Approval Date
2019-08-26
IRB Approval Number
HUM00168499
Analysis Plan

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

Request Information

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