Idea selection in design teams: a computational framework and insights in the presence of influencers. (23rd August 2022)

• Record Type: Journal Article
• Authors: Singh, Harshika; Cascini, Gaetano; McComb, Christopher
• Is Part Of: Design science. Volume 8(2022)
• Publication Date: 2022-08-23
• Subjects: agent-based approach -- design team collaboration -- idea selection -- influencers; Design -- Research -- Periodicals; New products -- Management -- Periodicals; Design; Design -- Research; Electronic journals; Periodicals; 658.5752
• DOI: 10.1017/dsj.2022.17
• Languages: English
• ISSNs: 2053-4701

Abstract

Abstract: Idea selection is crucial in design as it impacts the outcome of a project. A collaborative design activity could be considered as a social process where the interactions and individual states (such as the importance in the team and self-efficacy level) could affect decision-making. It is often seen in design teams that some individuals, referred to as 'influencers' in the article have more capacity to influence than others, hence they govern the team process for better or worse. Due to the limited work done in the past to study the effect of these influencers on design outcomes, the work aims at increasing the understanding by presenting some insights from its agent-based simulation. The simulation results show how different influencer team compositions affect design outcomes in terms of quality and exploration of the solutions. The idea selection starts with the agents who are ready with their solution in their 'mind'. The work presented in this article describes a framework for simulating decision-making during idea selection by considering the influencer and majority effect. The empirical study presented in the article verifies the model logic, that is, the presence of influencer and the majority during idea selection and supports the assumption that individuals' agreement on solutions proposed by other team members depends on the degree of influence and past agreement. The results of the simulation show that teams with well-defined influencers produced solutions with higher variety and had more uniform contributions from team members, but also produced solutions of lower quality.