Innovation and Ontologies

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.

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 "e;uncertain fumbling at minimal sight"e; (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.

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.

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.