Capturing the Production of the Innovative Ideas: An Online Social Network Experiment and "Idea Geography" Visualization

TL;DR

This study investigates how diversity in participants' backgrounds affects collective design and innovation in social networks, introducing 'Idea Geography' visualization and finding that random background distribution yields higher utility ideas.

Contribution

It presents a novel 'Idea Geography' visualization method and experimental evidence on the impact of background diversity on idea quality in collaborative design.

Findings

Random background groups produced higher utility ideas.

Diversity of backgrounds influences idea diversity.

Idea Geography visualizes exploration and exploitation in design processes.

Abstract

Collective design and innovation are crucial in organizations. To investigate how the collective design and innovation processes would be affected by the diversity of knowledge and background of collective individual members, we conducted three collaborative design task experiments which involved nearly 300 participants who worked together anonymously in a social network structure using a custom-made computer-mediated collaboration platform. We compared the idea generation activity among three different background distribution conditions (clustered, random, and dispersed) with the help of the "doc2vec" text representation machine learning algorithm. We also developed a new method called "Idea Geography" to visualize the idea utility terrain on a 2D problem domain. The results showed that groups with random background allocation tended to produce the best design idea with highest utility values. It was also suggested that the diversity of participants' backgrounds distribution on the network might interact with each other to affect the diversity of ideas generated. The proposed idea geography successfully visualized that the collective design processes did find the high utility area through exploration and exploitation in collaborative work.