How organizations capture and store knowledge, i.e. knowledge externalization, is a key issue of knowledge management research. Despite various approaches to reduce the required cognitive efforts and time, knowledge externalization remains challenging. However, recent technological advances in automatic speech recognition and natural language processing enable information technology systems to improve knowledge externalization by listening to conversations and processing their content. In this study, we employ a design science approach to examine how speech-based systems should be designed to assist knowledge externalization. Employing the use case of creating meeting protocols, we built a high-fidelity prototype of a speech-based protocol system and demonstrated it in two exploratory online focus groups. Based on this data, we describe the problem space of creating protocols and develop six design principles guiding the design of speech-based protocol systems. Thereby, our research also sheds light on how speech-based systems can enhance knowledge externalization in general.
Koslow, Anton; Berger, Benedikt; Morana, Stefan; and Hess, Thomas, "Enhancing Knowledge Externalization with Speech-Based Protocol Systems: A Design Science Approach" (2021). PACIS 2021 Proceedings. 139.
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