Abstract
This paper outlines the path towards a method focusing on a process model for the integrated engineering of Digital Innovation (DI) and Design Science Research (DSR). The use of the DSR methodology allows for achieving both scientific rigor and practical relevance, while integrating the concept of innovation strategies into the proposed method enables a conscious approach to classify different Information Systems (IS) artifacts, and provides a way to create, transfer, and generalize their design. The resulting approach allows for the systematic creation of innovative IS artifacts. On top of that, cumulative DSR knowledge can be systematically built up, facilitating description, comparability, and reuse of the artifacts. We evaluate this newly completed approach in a case study for an automated conversational call center interface leveraging the identification of the caller’s age and gender for dialog optimization, based on machine learning models trained on the SpeechDat spoken-language resource database. Moreover, we validate innovation strategies by analyzing additional innovative projects.
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