Innovation requires a balanced amount of openness and structure, especially in its early phases. Ontologies as logical representations of knowledge bear the potential of bridging this obvious dilemma and provide a promising approach to significantly improve management during the early stages of the innovation process.

Angelika C. Bullinger examines ontologies as an approach to modeling, analyzing and comparing the fuzzy front end of innovation management, in particular idea assessment and selection. She uses an extensive array of theories and methods, combining the knowledge bases of business administration and information systems. Starting from theoretical informatics, she elaborates, applies and tests a methodology for ontology development for use in business management. Based on empirical data, she models ontologically the moment of idea assessment and selection on a company-specific, industry-typical and generic level. Included are action-oriented implications for the implementation of the methodology in business reality.

Autorentext
Dr. Angelika C. Bullinger promovierte bei Prof. Dr. Prof. h.c. Dr. h.c. Ralf Reichwald am Institut für Information, Organisation und Management der Technischen Universität München. Sie ist wissenschaftliche Mitarbeiterin bei Prof. Dr. Kathrin Möslein am Lehrstuhl für Information der Universität Nürnberg-Erlangen.

Zusammenfassung
Foreword Innovation equally requires rational problem solving and interpretive space (Lester & Piore, 2004). It is a key challenge for innovation management to overcome this obvious dilemma, especially in the early stages of the innovation process. Ontologies as logical representations of knowledge bear the potential to enable the required balance between structure and flexibility. They provide a promising, yet largely unexplored approach for significantly improving corporate innovation processes. During the early stages of the innovation process, the so-called Fuzzy Front End of innovation management, decision-making in corporate practice is often uncertain fumbling at minimal sight (Hauschildt & Salomo, 2007), i.e. the existing idea selection processes tend to be ad hoc and somewhat intuitive. Due to this unsatisfying situation, in which new ideas are difficult to compare, inadequate risks are taken and projects are stopped too late, a generic framework for the early stages of innovation management is necessary. Ontologies, used to represent knowledge, provide powerful modeling potential. Developed by researchers from the field of Artificial Intelligence, ontologically based applications recently been widely applied in online business to business solutions. The so-called semantic web is also based on ontologies. Its high flexibility and easy adaptability recommend ontological modeling for broader use and application in a business context. The few existing examples in the field of HR management as well as in the field of knowledge management indicate the potential of corporate ontologies.

Inhalt
Roadmap for the Fuzzy Front End.- Innovation.- Roadmap for the Fuzzy Front End.- Summary of FFE Roadmap.- Ontology.- Concept Formation.- Deployment in Business.- Potential of Ontologies.- Elements of Ontologies.- Classification The OntoCube.- Design Science Ontology Lifecycle.- Multimethodological Background.- Empirical Approach.- Results: The OntoGate.- Results of Prepare.- Results of Develop/ Build.- Results of Justify/ Evaluate.