Teams and attitudes: are there gender differences?

There is no direct intervention. Indirect intervention comes through random assignment of individuals to a team of 3 giving us a varied degree of gender heterogeneity.

2025-04-07

2025-04-19

1. Gender of the team leader
2. Winning Team and its gender composition
3. Team performance
4. Consensus in decision making
5. Teamwork related outcomes like satisfaction, experience
6. Choice of objects

1. Self explanatory
2. Self explanatory
3. Team performance = points scored by the team in the assigned task
4. Consensus in decision making= self reported individual level post survey questionnaire
5. Team work related outcomes like satisfaction, experience= self reported individual level post survey questionnaire
6. Self explanatory

1. Individual performance

1. Individual performance = measured by points scored in the individual level task

Field experiment stages are listed below:
1. Round 1 = Individual level task
2. Round 2 = Individuals work as a Team and replicate task from Round 1
2.a. Assigning individuals randomly to a Team of 3 where we would vary gender composition of the team, for example, teams with no females, one female, and two females. Benchmark/control group are teams with no females (i.e., all males teams).
3. After team task, everyone fills a post task questionnaire
4. Subjects paid participation honorarium after filling up questionnaires
5. After studying outputs, we will announce individual and team winners at a later date (within 45 days of the study).

Individual come for participation in the study.
Individuals are provided information about the study, task, incentives, based on which they consent to be part of the study or not.

A. Task design
Round 1 = Individual level task
We show digital images of non-branded common daily use objects/consumables like wooden stick, mosquito kill racket, tissue roll, purse, tin can, broom, hanger, apple, apron, sugar cubes, pen etc., to name a few.

In Round 1, individuals have to select 4 items from 12 items displayed and write the maximum number of feasible uses. They get 10 minutes to do it.

In Round 2, we assign students randomly to a team of 3 students and ask them to do the same task as a team. Objective is to see changes in outcomes with variation in gender composition of teams.

To give an example, suppose a session-class size is 30 students. We show them 12 non-branded common daily use objects/consumables objects. Everyone independently selects k=4 objects and writes their maximum possible uses.

At team level, they reproduce the task, i.e., now as a team they pick 3 objects and write their maximum possible uses. This task is in line with students’ curriculum as they routinely do team exercises. 5% of top scoring students in per class would win (e.g. From a class of 30 consenting students, two winners would be selected)

Winners will be decided by the weighted average of 1.) number of uses conditional on feasibility, and 2) uniqueness of the object (calculated as 1/n where n is the number of individuals/teams choosing that object within a session). Winning criteria will be described in the information sheet provided at the start of the task. As a tie breaker, we will look at the uniqueness of uses within top scoring teams.

B. Key methodology/treatment/instrument
Randomization of participants into a team of 3 gives us variation in the degree of gender heterogeneity. Our objective is to understand how individual behavior and team output varies with variation in team homogeneity in terms of gender.

Teams would be required to (i) choose a leader, (ii) complete the task within stipulated time. They will get 20 minutes to discuss and complete the tasks. The leader's responsibility is to ensure that the task is completed and submitted within time.

The task will be followed by a post treatment questionnaire to capture team player attitudes. Additionally, post treatment questionnaire’s responses will help us understand team dynamics in terms of leadership, attitudes, consensus building, satisfaction, etc.

Randomization done in real time (as consented students participate in Round I) using a computerized randomization algorithm.

Individual level

No

NA

Upper limit if everyone consents to participate = 1240 students mapping into 413 teams

Since only 18-20% of students are females, our power to create mixed gender team is limited.
In the best case scenario, all 1240 students would turn up and consent to take part leading to 413 teams in total. In this scenario, our team composition will be the following: All males teams = 305; Female Majority Teams = 54; Female Minority Teams = 54

In expected scenario, we will see 70% participation rate, leading to the following composition: All males teams= 214; Female Majority Teams = 38; Female Minority Teams = 38

For a MDE 0.25 with level of significance 0.05, power 0.8, 0.26 proportion of teams in treatment, assuming SD 0.2 in the main outcome of the team performance, we need at least 32 teams of each type.