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COMPARING DESIGN OUTCOMES ACHIEVED BY TEAMS OF EXPERT AND NOVICE DESIGNERS THROUGH AGENT-BASED SIMULATION

Published online by Cambridge University Press:  27 July 2021

Harshika Singh ,
Gaetano Cascini  and
Christopher McComb
Harshika Singh*
Affiliation:
Politecnico di Milano
Gaetano Cascini
Affiliation:
Politecnico di Milano
Christopher McComb
Affiliation:
The Pennsylvania State University
*
Singh, Harshika, Politecnico di Milano, Department of Mechanical Engineering, Italy, [email protected]

Abstract

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Previous research has shown that experienced and novice individuals behave and think differently. Although experienced individuals are better at solving problems, organisations are constantly forming teams of experienced and novice designers to work together on their projects. It is crucial to understand how these teams affect the design outcomes. Therefore, the aim of the study is to investigate how collaborative design teams perform when composed of varying numbers of experienced and novice agents. Specifically in this paper, teams work on a routine task and design outcomes are measured in terms of quality, variety, and exploration of the design space. Since the parameters in the empirical laboratory experiments are difficult to control, an agent-based model was used to simulate these teams. In general, the results show that a team of novice agents with a small number of experienced agents produces solutions of higher quality than an all novice team of agents. However, an all novice team of agents does provide a higher variety of solutions. These results have important implications when teams of experienced and novice designers are formed to work together in practice.

Keywords

Collaborative designTeamworkComputational design methodsHuman behaviour in designDesign process
Type
Article
Information
Proceedings of the Design Society , Volume 1: ICED21 , August 2021 , pp. 661 - 670
Creative Commons
Creative Common License - CCCreative Common License - BYCreative Common License - NCCreative Common License - ND
This is an Open Access article, distributed under the terms of the Creative Commons Attribution-NonCommercial-NoDerivatives licence (http://creativecommons.org/licenses/by-nc-nd/4.0/), which permits non-commercial re-use, distribution, and reproduction in any medium, provided the original work is unaltered and is properly cited. The written permission of Cambridge University Press must be obtained for commercial re-use or in order to create a derivative work.
Copyright
The Author(s), 2021. Published by Cambridge University Press

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