Modelling the Dynamics of Influence on Individual Thinking during Idea Generation in Co-design Teams

Abstract

Social influence is not evenly distributed in teams. Some individuals, referredto here as influencers, become more influential than others. Consequentially,these influencers play a significant role in shaping project performance.The current work simulates the presence of influencers duringidea generation in co-design teams to better understand emergent socio-cognitivephenomena. Besides providing, a novel approach for modelling learningin concept generation the model highlights the results related to individualcognition during idea generation. Idea quality and exploration of designspace are affected by the presence of influencers in design teams. Teamswith no well-defined influencers produce solutions with high general explorationbut less quality. In contrast, the agents in the teams with only oneinfluencer produce solutions high quality than those teams with no influencers.

How Familiarity Impacts Influence in Collaborative Teams?

“…Although the study dealt with only 5 teams, it could be seen that a high amount of perceived influence in them results in the lesser spread of their solutions. Similar results were predicted by Singh et al (2020a), where having high influence from well-defined influencers in teams resulted in the lesser spread of the solutions in the design space. Usually, it is seen that a team with a lower quality tends to search divergently in an attempt to improve that representation and a team with a high-quality has no need to refine their representation through broad search, hence lower exploration.…”

“…The interaction between the team members gives rise to social influence (Myers, 1982) that is not evenly distributed in teams. Some individuals might be perceived as more influential than others and this perceived degree of influence impacts individual thinking thus, the design outcome (Singh et al, 2020a). As working in teams is gaining momentum in many fields, understanding how the design output is impacted with respect to the amount of influence perceived by its members in a design team, could aid in explaining team performance.…”

Comparing Design Outcomes Achieved by Teams of Expert and Novice Designers Through Agent-Based Simulation

“…The design task/problem as shown as an example in Figure 2, is computationally represented as a 2-dimensional function where each dimension denotes a design aspect (in this case 2 aspects were considered). Any point on the design space is the potential solution and can have a value between 0-1 (solution value =1 in lightest hue and worst solution value =0 in darkest hue) (Singh et al, 2020a). The results of the design outcome presented in the paper are related to the design space with 1 and 5 peaks where peaks denote the best alternative options.…”

“…The agents generate solutions during the idea generation based on the given set of rules as described in (Singh et al, 2020a). Each agent has its way to explore solution space based on its energy which decreases with the length of an idea generation session.…”

“…This is because there is a huge overlap in the two terms as one can become an expert simply by working on a task for a lot of time. Since studying interactions and social factors is difficult to control in laboratory experiments due to their dynamic nature, the paper uses the MILANO (Model of Influence, Learning, and Norms in Organizations) framework, originally presented by Singh et al (2020aSingh et al ( , 2020b to study this phenomenon. MILANO models collaborative design teams, thus providing a platform to simulate various team compositions and see their effect on design outcome.…”