Leadership and Team Productivity

Last registered on February 21, 2023

Pre-Trial

Trial Information

General Information

Title
Leadership and Team Productivity
RCT ID
AEARCTR-0010956
Initial registration date
February 15, 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
February 21, 2023, 6:53 AM EST

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

Locations

Region

Primary Investigator

Affiliation
University of Stavanger Business School

Other Primary Investigator(s)

PI Affiliation
University of Stavanger Business School

Additional Trial Information

Status
In development
Start date
2023-02-13
End date
2023-07-31
Secondary IDs
Prior work
This trial does not extend or rely on any prior RCTs.
Abstract
Economic output in most industries is the result of many individuals working together in a team. The team environment shares features present in a public good in that the team members are working towards a common goal and are sharing the rewards that result from the finalized output. Such an environment can promote incentives for free-riding, resulting in inefficient allocation of effort across team members,
diminishing the teams productivity. This paper examines the effects of having a leader in increasing the teams’ productivity. To do so, we first gather data on business school students who are randomly assigned into groups and work in high-stakes team projects as a part of their course work. We randomly encourage half of the teams to select a team leader that will be responsible for managing the team project. We then evaluate the effects of having a team leader on various outcomes such as the teams’ project grade and the self-reported quality of team meetings.
External Link(s)

Registration Citation

Citation
Haeckl, Simone and Hammad Shaikh. 2023. "Leadership and Team Productivity." AEA RCT Registry. February 21. https://doi.org/10.1257/rct.10956-1.0
Experimental Details

Interventions

Intervention(s)
We provide students in the treatment group with a Microsoft Excel sheet planner to organize their meeting. It prompts students to select a team leader who will help guide the meetings for the remainder of the course. Additionally, the Excel planner also prompts students to enter the meeting attendees, purpose of meeting, list of items completed since last meeting, list of next steps, and write a brief summary of the meeting. The control group is also given such a Microsoft excel sheet planner, but the ``Team Leader" row is omitted. We randomly assign half of the students into treatment group. Additionally, the leaders within the treatment group will also be prompted by email to participate in an online activity which will help teach them leadership skills, if take-up of the excel sheets is sufficiently high. The online activity will present the leader with information relating to division of tasks across team members, managing meetings, and setting effective goals.
Intervention Start Date
2023-02-15
Intervention End Date
2023-06-05

Primary Outcomes

Primary Outcomes (end points)
The primary outcomes are the teams' performance on the research paper, and the quality of teamwork as measured by a survey index.
Primary Outcomes (explanation)
The quality of teamwork will be constructed by aggregating 6 Likert scale questions measured on a 4-point scale (1 = Strongly Disagree, 2 = Disagree, 3 = Agree, and 4 = Strongly Agree).

Respondents are asked "To what extent do you agree with the following statements?" The 6 statements included are:
a) Tasks were divided up amongst team members in an effective manner
b) All team members did a similar amount of work
c) The team members cooperated well together
d) One team member did most of the work (R)
e) The team meetings were well organized
f) I felt like I belonged in the team

We generate the team quality index by aggregating the responses to the questions listed above with equal weighting. In particular, the responses will be aggregated as follows: a + b + c - d + e + f. Such an equally weighted index is interpreted to be increasing in team quality with respect to the agreement scale.

Secondary Outcomes

Secondary Outcomes (end points)
Secondary outcome is a binary variable for whether a team member feels that all team members worked sufficiently hard towards the project.

We also plan to follow the students over time and collect data on whether they complete their degree, years spent until completion, and grades in subsequent courses.
Secondary Outcomes (explanation)
The secondary outcome is constructed using the following binary (Yes/No) survey question: "Do you feel that all your teams' members worked sufficiently hard towards completing the group project?". Answering no to this question is indicative of potential free-riding occurring within the team.

Experimental Design

Experimental Design
The study takes place in a master's level research methods course for business students. The business students have one of the following specializations: Economics, Leadership, Innovation, Finance, or Marketing. The main assessment in this course is a research paper, weighted as 100% of their course grade. After receiving a few lectures on relevant research methods (e.g., multiple regression), students are randomly assigned into teams with 4 students each within their specializations. Then for each specialization, we randomize half of the teams to the treatment group. The treated teams receive an Microsoft Excel planner to manager their meeting which prompts them to set a team leader. The control group also receives the Microsoft Excel planner, but are not prompted to select a team leader. If there is sufficiently high utilizing of the Microsoft Excel sheets, we also plan to follow-up with the team leaders in the treated group and request them to participate in online modules designed to improve their leadership competency.
Experimental Design Details
Randomization Method
We carry out a randomization in Stata to assign teams to either the treatment or control group in a way so that we have balance in the number of treated and control teams within each field of study (Economics, Leadership, Innovation, Finance, and Marketing). That is we use field of study as a block and perform a complete randomization within each block.
Randomization Unit
The unit of randomization is a team of students
Was the treatment clustered?
Yes

Experiment Characteristics

Sample size: planned number of clusters
We are carrying out a pilot study without around 20 student teams.
Sample size: planned number of observations
Each team has around 4 students, so 20*4 = around 80 students.
Sample size (or number of clusters) by treatment arms
We are planning to have 10 student teams in control (40 students) and 10 student teams in treatment (40 students).
Minimum detectable effect size for main outcomes (accounting for sample design and clustering)
Given this is a pilot study, we understand that it will be severely under powered and that only very large effect sizes will be detectable. We will use the results from the pilot study and form hypothesis on the likely effect size for the main outcomes, and do a detailed power analysis for the full scale study.
Supporting Documents and Materials

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IRB

Institutional Review Boards (IRBs)

IRB Name
Norwegian Social Sciences Data Services (NSD)
IRB Approval Date
2023-01-24
IRB Approval Number
310913
Analysis Plan

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Post-Trial

Post Trial Information

Study Withdrawal

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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