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Learning by migrating: A computational study of diversity and team-level decision-making

Learning by migrating: A computational study of diversity and team-level decision-making

Year: 2017

Section: Human Behaviour in Design

Editor: Anja Maier, Stanko Škec, Harrison Kim, Michael Kokkolaras, Josef Oehmen, Georges Fadel, Filippo Salustri, Mike Van der Loos

Author: Thomas, Russell (1); Gero, John (1,2)

Series: ICED

Institution: 1: George Mason University, United States of America; 2: UNC Charlotte, United States of America

Section: Human Behaviour in Design

Pages: 589-598

ISBN: 978-1-904670-96-4

ISSN: 2220-4342

Abstract

How does previous experience and learning influence a team’s ability to successfully agree on a system architecture, team roles and responsibilities, and design method? Migration of team members leads to diversity in past experiences and beliefs, which might have a positive or negative affect on team decision-making. Using computational modeling of self-managed teams across multiple project life cycles, we perform controlled experiments to evaluate performance and decision-making patterns of migrating vs. non-migrating teams. We find that there is no difference in mean performance, indicating that neither approach is intrinsically better. However, statistical tests of paired trials shows a meaningful an advantage for migrating (diverse) teams. Examining patterns of decision-making over time reveal that migrating (diverse) teams explore a wider range of team-level decisions, which makes them more adaptable in specific circumstances.

Keywords: Design methodology, Human behaviour in design, New product development, Organizational processes, Simulation

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