Table 2 The summary of key model variables/processes, assumptions and corresponding parameters in ABMS

1.1 A set of individual proposals to 10 problem aspects of a task

Members possess a set of initial proposals to 10 problem aspects and update their proposals according to the temporal outcome of team consensus due to the feedback loop

An initial normal distribution function with the mean of 0.5 and a standard deviation in one of three scenarios (high/medium/low scale, namely a 0.5/0.3/0.1 standard deviation) to represent functional diversity

1.2 A set of expertise perception of “who knows what,” including self- and others-perception

Members possess a set of initial expertise perception of “who knows what” (Wegner 1987) and update their perception according to the temporal outcome of team consensus due to the feedback loop

Random variables between 0 and 1; the higher the value, the higher perception of expertise

The initial accuracy of expertise recognition in one of three scenarios (high/medium/low scale, namely 75%/50%/25%) to represent expertise perception

1.3 A set of job-related knowledge, skills and attitudes (KSAs) to 10 aspects of a task

Member possess a set of fixed job-related KSAs to 10 problem aspects

Random variables between 1 and 100; the higher the value, the higher KSAs to a problem aspect.

The variables used to determine who the absolute experts are for the 10 problem aspects

2.1 Proposal evaluation

Members compare own proposals against the presented one and evoke dyadic task/relationship conflict if there exists a disagreement about the proposals or the perception of expertise

Members (except the proposer) compare the variance between own proposal and the presented one

Members opt to support or reject the presented proposal depending on the proposal discrepancy (<  0.5) and the relative levels of perceived expertise to the specific problem aspect

If members do not support the presented proposal, dyadic task conflict as well as relationship conflict will be evoked

3.1 Problem aspect identification

In each round of discussion, 10 problem aspects of a task are identified one by one

In each round of discussion, a team identifies 10 problem aspects one by one

In total, 10 problem aspects of a task are identified in each round

3.2 Proposal elaboration

For each problem aspect, a team randomly assigns a member to elaborate his/her proposal to the identified problem aspect

A team member is randomly assigned to present his/her proposal to the identified problem aspect for others’ evaluation (as described in 2.1)

3.3 Team consensus

Team decision-making process follows the consensus approach (McGrath 1984) to determine a joint decision whether or not to support the presented proposal to the specific problem aspect

A team will support the presented proposal to the specific problem aspect if more than half of members opt for the proposal (due to dyadic interactions as described in 2.1)

A team will reject the presented proposal to the specific problem aspect if less than half of members opt for the proposal (due to dyadic interactions as described in 2.1)

3.4 Intragroup conflict

Intragroup conflict originates from lower-level processes and manifests across levels to make an impact on team functioning (Korsgaard et al. 2008; Kozlowski and Klein 2000)

In each round of discussion, the magnitude of team-level task conflict is measured by averaging individually accumulated number of task conflicts due to dyadic interactions, and divided by the maximum number of possible task conflicts

The relationship of intragroup task conflict, intragroup trust and intragroup relationship conflict follows the study by Simons and Peterson (2000) and the magnitude of team-level relationship conflict is then computed accordingly

4.1 Decision commitment

Decision commitment is one of key criteria to measure the success of team decision-making

The relationship of intragroup task conflict, relationship conflict, and decision commitment follows the study by Parayitam and Dooley (2009) and the magnitude of decision commitment is then computed accordingly in the final round of discussion (i.e., when time steps = 20)

4.2 Decision quality

Decision quality is one of key criteria to measure the success of team decision-making

Operationalized in terms of the final accuracy of expertise recognition

Measured as the percentage of the number of perceived experts correctly matching to the absolute experts out of 10 problem aspects in the final round

The value in the range of 0% to 100%; the higher the value, the higher decision quality

4.3 Decision consensus

Decision consensus is one of key criteria to measure the success of team decision-making

Measured as the total number of supported proposals (out of 10 problem aspects) in the final round

The value in the range of 0 to 10; the higher the value, the higher decision consensus