Classifying Innovation: An Ontological Framework and Data-Driven Approach for Measuring Radicalness in the Front End of Innovation Management

Abstract

Idea evaluation has emerged as a pivotal aspect of creative thought and innovation processes, drawing increasedattention from researchers and managers. Despite the lack of consensus on a precise definition of innovation, there is a clear understanding that radical innovation significantly differs from incremental innovation. However, techniques for evaluating and selecting radical ideas have often been adapted from methods designed for incremental innovation or creative thought processes. This thesis establishes a framework to differentiate between radical and incremental innovations. Starting with foundational definitions, we examine traditional methods for evaluating innovative ideas. The core of our research introduces a novel Innovation Ontology and we demonstrate the capability to distinctly classify incremental and radical innovations, presenting a predictive model that generates a ‘radicalness’ score, thereby enhancing the precision and effectiveness of innovation management.