Between Radical and Market-based Innovation
The dilemma between radical and market innovations is unlighted here by a simulation. Following evolutionist theory and innovation management, an agent-based model issued from genetic algorithm is built. In a perfect world, transformation and selection create dynamics and emergence in an agent population. Examining that population evolution which consists in a stylized representation of upcoming projects in the organization appears full of lessons. Results put into relief Lamarckian and Darwinian adaptation mechanisms, their relations with the environment and their interactions. Simulations show the existence of an optimum level of experimentation and experimentation of projects upstream the innovation process, demonstrates that the efficiency of evolutionist processes is contingent to environment complexity and allows exploring interdependencies and coexistence between two paths of evolution. The model validity is approach through similarity to admitted theory and through a study of the innovation process of Renault, a French carmaker. Innovation process of this organization appears as a wonderful field to confront our results.
Project Management, Selection, Transformation, Agent-based Model, Genetic Algorithm