Systems Research and Behavioral Science · 2017 · 10 citations · 63 references
ManagementInnovation ManagementOrganization StudiesArtificial IntelligenceInnovationOrganizationsCollective IntelligenceEvolutionary ComputationOrganizational InnovationArtificial Bee ColonyBee-inspired OptimizationBio-inspired Swarm AlgorithmsCollective Intelligence PlatformsError ReductionEvolutionary AlgorithmsInnovation ImplementationSwarm Decision-making
Technological innovation is almost certainly the key driver of long‐term economic growth. Yet for many years, not only have discoveries depended on serendipity and happenstance but also selection and development of the innovations has been managed by over‐centralized bureaucracies that are more concerned with stability and error reduction than with adaptation to a changing world. This paper uses bee swarm logic to suggest a different way forward. The novel system proposed would consist of a designed collective intelligence platform co‐ordinating the work of a number of competing, self‐organizing research groups, each using evolutionary algorithms to optimize their potential solution to a given innovation problem. Each research group would compete to recruit supporters in strict proportion to the independently estimated profitability of its solution. The first solution to accumulate a quorum level of support would win the competition, and its supporters would then be able to develop the solution through implementation. Copyright © 2017 John Wiley & Sons, Ltd.
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Exploration and Exploitation in Organizational Learning
James G. March · Organization Science · 1991 · 21.4K citations