teamDiversity, Network Structure, and the Effectiveness of Collective Design and Innovation

Project Website

This project is currently supported by the NSF Science of Organizations (SoO) and Systems Science (SYS) Programs (Award #: NSF SES-1734147).
Any opinions, findings, and conclusions or recommendations expressed in this material are those of the authors and do not necessarily reflect the views of the National Science Foundation.


About the Project

As the complexity of products and services has skyrocketed over the last several decades, collective design and innovation processes have become a necessity for the development of successful solutions for real-world problems. Such large-scale design processes typically involve individuals with diverse knowledge, expertise and behaviors, and the organizational structures under which the collective design takes place are often complex and dynamic with temporally changing non-trivial network properties.

This project aims to investigate, both theoretically and experimentally, how the diversity of knowledge, expertise, and behaviors of individual members and the topological properties of organizational network structures will affect the effectiveness of design and innovation processes at collective levels. This will be accomplished through (a) theoretical agent-based network modeling and simulation, and (b) model evaluation through online laboratory experiments involving student participants with diverse majors. Modeling and simulation will investigate potential interactions between task-related diversity and large-scale organizational network structures. The predictions produced by the simulations will be evaluated through online laboratory experiments, in which participants will collaborate on several open-ended collective design tasks through a computer-mediated collaboration platform. In these experiments, the participants' task-related diversity will be measured and its distribution in the organizational network will be manipulated. The topologies of the network will also be monitored and manipulated dynamically.

The successful outcome of the project will be a new "guiding principle" for configuring and manipulating task-related diversity and organizational network structures to promote effective collective design and innovation. This will bear multidisciplinary impacts on organizational science, management science, systems science, systems engineering, operations research, and network science.


Research Team

Principal investigators

Graduate Students


Publications

Journal Articles

Conference Presentations


Online Resources


Contact Us

Please address any inquiries about this project to:

Hiroki Sayama, D.Sc.
Director, Center for Collective Dynamics of Complex Systems
Professor, Department of Systems Science and Industrial Engineering
Binghamton University, State University of New York
P.O. Box 6000, Binghamton, NY 13902-6000
Email: sayama@binghamton.edu
Tel: (607) 777-3566


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