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

Suny At Binghamton, Binghamton NY

Investigators

Abstract

This project will investigate how the diverse knowledge, expertise and behaviors of people and their social networks can make large-scale collaborative design processes more effective and innovative. This has become a very important issue in modern society where developing successful solutions for complex problems requires collaboration among many individuals with diverse knowledge, expertise and behaviors, and where the interactions of those individuals are often complex and dynamic. The project will use multiple research methods to address this issue, combining computer simulations for idea and hypothesis generation and online experiments with human participants for idea and hypothesis testing. The project will expand knowledge about the linkage between individuals' interactions in various organizational configurations and their performance in innovation, which will be applicable to product, service, concept, policy, and/or aesthetic design tasks in a wide variety of domains. 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.