Decision-Making in Virtual Team Leadership: The Impact of Timing on Reward Distribution – An Online RCT Study

The intervention consists of assigning participants to one of four scenarios that simulate the decision-making process of virtual team leaders allocating rewards. The scenarios are: Pre-Project Decision, where leaders decide on the reward distribution before the project starts; Post-Project Uncertainty, where leaders decide after the project concludes without knowledge of the outcomes; Positive Outcome, where leaders are informed of high earnings before deciding; and Negative Outcome, where leaders are informed of low earnings before making their decisions.

Participants will be randomly assigned to one of four groups, each facing different scenarios for deciding how to distribute rewards within their teams:

1. Pre-Project Decision group: Leaders determine the percentage of earnings they and their team members receive before the project starts.
2. Post-Project Uncertainty group: Leaders make allocation decisions after the project concludes but before knowing the earnings.
3. Positive Outcome group: Leaders make decisions after being informed of high earnings.
4. Negative Outcome group: Leaders make decisions after being informed of low earnings.

Participants will provide responses based on their imagined decisions as team leaders, determining what percentage of the total team earnings goes to themselves and team members. Additionally, participants will provide the reasoning behind their choices. Personal Traits of participants will also be collected as control variables or interaction terms. For detailed questionnaires and scenario descriptions, please refer to the Supporting documents.

2023-12-07

2023-12-11

The primary outcome measures the percentage of total team earnings that participants, acting as virtual team leaders, allocate to themselves versus their team members in various scenarios. This assesses the leaders' decision-making patterns in reward distribution within virtual teams.

This study examines how different scenarios influence virtual team leaders' decisions on reward allocation. It aims to understand the distribution strategies reflecting potential generosity and responsibility in leadership roles. Specifically:

H1 (Leaders Show Generosity): Leaders who can decide on the reward distribution before the project starts are hypothesized to allocate a smaller percentage of rewards to themselves, hence a larger share to their team members, compared to those making the decision post-project completion.

H2 (Leaders Show Responsibility): Leaders informed of poor project outcomes are hypothesized to allocate a smaller percentage of rewards to themselves, thus a larger share to their team members, relative to those informed of better outcomes.

Secondary outcomes include the reasoning behind the reward allocation decisions made by participants and the examination of how individual characteristics, such as personality traits and gender, may interact with the decision-making process.

The secondary outcomes aim to delve into the psychological and personal factors influencing the reward allocation process. This includes analyzing participants’ explanations for their decisions to uncover motivations such as fairness, generosity, or self-interest, and investigating the role of personality traits and gender in explaining variability in decision-making behavior.

The study employs a 4-arm randomized controlled trial (RCT) to investigate reward allocation decisions among virtual team leaders. Participants are randomly assigned to one of four scenario-based interventions, exploring different contexts of reward distribution: Pre-Project Decision, Post-Project Uncertainty, Positive Outcome, and Negative Outcome. Responses on reward allocation percentages and underlying rationales will be collected and analyzed, with personal characteristics considered as control and interaction variables.
Please refer to the supporting documents provided in the 'Supporting Documents' section for detailed information on the experimental design and methodology.

Please refer to the supporting documents provided in the 'Supporting Documents' section for detailed information on the experimental design and methodology.

The survey company will employ a computer-generated randomization sequence to allocate registered users across Japan to one of the four different intervention sites. The experiment will be conducted under a double-blind condition, ensuring that both the participants and the researchers administering the experiment are unaware of the group assignments.

Individual participant

No

N/A (individual participants will be randomized across four distinct survey sites without the use of clusters).

For each of the four distinct scenario interventions, we will randomly assign 130 participants to each arm, ensuring an equal gender distribution. This allocation strategy applies to all treatment arms, resulting in a total of 520 participants across the four arms.

130 individuals per arm, totaling 520 participants randomized equally across four intervention groups.

This study incorporates two separate experiments: the first comparing Pre-Project Decision with Post-Project Uncertainty groups, and the second assessing Positive Outcome versus Negative Outcome groups. Each experiment independently employs a two-tailed t-test to compare outcome variables between the groups. The sample size calculation, based on a medium effect size (Cohen's d of 0.5), an alpha error (significance level) of 0.05, and a desired power of 0.95, estimates the need for approximately 105 participants per group. This leads to a total of about 210 participants for each experiment, and 420 participants for both experiments combined. However, beyond the primary comparison using t-tests, the study also intends to examine the interactions of individual characteristics with the treatment effects. This additional analysis necessitates a larger sample size to maintain statistical power and precision. The calculation for this aspect of the study, which considers the complexity and variability introduced by examining interactions, results in a total sample size of 520 participants. This increased sample size ensures that the study is adequately powered not only for the main effects analysis but also for the exploration of these interaction effects, thereby enhancing the comprehensiveness and depth of the research findings.