Open innovation represents an emergent paradigm by which organizations make use of internal andexternal resources to drive their innovation processes. The growth of information and communicationtechnologies has facilitated a direct contact with customers and users, which can be organized as openinnovation communities through Internet. The main drawback of this scheme is the huge amount ofinformation generated by users, which can negatively affect the correct identification of potentially applicableideas. This paper proposes the use of evolutionary computation techniques for the identification ofinnovators, that is, those users with the ability of generating attractive and applicable ideas for the organization.For this purpose, several characteristics related to the participation activity of users thoughopen innovation communities have been collected and combined in the form of discriminant functionsto maximize their correct classification. The right classification of innovators can be used to improvethe ideas evaluation process carried out by the organization innovation team. Besides, obtained resultscan also be used to test lead user theory and to measure to what extent lead users are aligned withthe organization strategic innovation policies
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