Efficient Structures for Innovative Social Networks

Authors:
William S. Lovejoy;Amitabh Sinha
Affiliations:
Ross School of Business, University of Michigan, Ann Arbor, Michigan 48109;Ross School of Business, University of Michigan, Ann Arbor, Michigan 48109
Venue:
Management Science
Year:
2010

Citing 7
Cited 1

A survey of algorithmic methods for partially observed Markov decision processes

Annals of Operations Research
Networks, Diversity, and Productivity: The Social Capital of Corporate R&D Teams

Organization Science
Statistical mechanics of complex networks

Statistical mechanics of complex networks
Recombinant Uncertainty in Technological Search

Management Science
Evolution of R&D Capabilities: The Role of Knowledge Networks Within a Firm

Management Science
The Structure and Dynamics of Networks: (Princeton Studies in Complexity)

The Structure and Dynamics of Networks: (Princeton Studies in Complexity)
Interfirm Collaboration Networks: The Impact of Large-Scale Network Structure on Firm Innovation

Management Science

Can knowledge be more accessible in a virtual network?: Collective dynamics of knowledge transfer in a virtual knowledge organization network

Decision Support Systems

Quantified Score

Hi-index	0.01

Visualization

Abstract

What lines of communication among members of an organization are most productive in the early, ideation phase of innovation? We investigate this question with a recombination and selection model of knowledge transfer operating through a social network. We find that ideation is accelerated when people in the organization dynamically churn through a large (ideally the entire population) set of conversational partners over time, which naturally begets short path lengths and eliminates information bottlenecks. Group meetings, in which the content of conversations is available to all for consideration, are another way to learn in parallel and accelerate the ideation process, although for complex problems they may not offer significant advantages over the best decentralized networks. The idealized core-periphery graphs emerge as an important family on the time--cost efficient frontier. New sociometrics for the analyses of innovation processes emerge from this investigation.