Digital innovations have become imperative for organizational survival as they enable businesses to be more competitive. The development of novel artefacts and the systematic gathering of design knowledge are important, both from a researcher and practitioner perspective. The main goal of the dissertation proposal is to synthesize design knowledge of a digital advertisement optimization system in the form of an information system design theory, a prescriptive theory, that describes a digital advertisement optimization system class at several interrelated levels. To build the system class, a proposed system is conceptualized and constructed at the premise of the industry partner. The system is conceptualized to provide improved advertisements in collaboration with human actors. To improve advertisements the system applies reinforcement learning to learn what advertisement content provides better results by manipulating an advertisement construction tool and investigating consumer segment properties. Beyond only improving the advertisements, the system has a goal of delivering more individualized advertisements in regards to attractiveness. The project applies a design science methodology for constructing the information system design theory and the actual artefact in an iterative and incremental approach.
Thesis Project Team
Presented at Thesis Proposal Seminar, 1 October, 2021.