Behind the learning curve: a sketch of the learning process
Management Science
Adaptation on rugged landscapes
Management Science
Simulation of Learning in Supply Partnerships
Computational & Mathematical Organization Theory
Organizations and Complexity: Searching for the Edge of Chaos
Computational & Mathematical Organization Theory
Deliberate Learning and the Evolution of Dynamic Capabilities
Organization Science
Imitation of Complex Strategies
Management Science
Dynamics of Team Member Replacements from Complex Systems Theory
Computational & Mathematical Organization Theory
Speed and Search: Designing Organizations for Turbulence and Complexity
Organization Science
Mathematical Models for Studying the Value of Motivational Leadership in Teams
Computational & Mathematical Organization Theory
Interdependency, Competition, and Industry Dynamics
Management Science
Modularity and incremental innovation: the roles of design rules and organizational communication
Computational & Mathematical Organization Theory
Agency and structure: a social simulation of knowledge-intensive industries
Computational & Mathematical Organization Theory
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We explore the proposition that parametric interdependence makes learning-by-doing a nondeterministic, path-dependent process. The implications of our model challenge two conventional beliefs about the relationships between industrial structure, spillovers, and learning-by-doing. First, we challenge the belief that the monopolistic industrial structure always maximizes learning-by-doing gains when there are no spillovers. Second, we challenge the belief that increasing spillovers unambiguously increases welfare when learning-by-doing drives innovation.