I am particularly interested in interdisciplinary research where one or both areas are leveraged to help organizations. For example, AI offers knowledge about methods and techniques to generate insights from machine-readable data, while digital innovation researchers and practitioners are increasingly looking at new ways of finding and assimilating new knowledge sources to inform their ideas and develop new services.
With the increasing availability of such data, data-driven innovation is one of my key research interests. I am also curious about understanding data-driven decision making (and automated decisions) and their impact on individuals, organizations and society.
In addition to studying data as an element of phenomena I study, I use it as an indispensable tool in informing my research results and turn to data science techniques in my analyses. Techniques such as clustering, association rules and topic modeling are examples of those in my toolbox towards theory development and validation.
