Novice digital service designers’ decision-making with decision aids — A comparison of taxonomy and tags

Digital services are a key driver of contemporary businesses. In order to scale the implementation of design-centric development processes, companies increasingly assign design work to design novices. As design novices have limited design knowledge and experience, they are challenged to select adequate design techniques throughout the entire lifecycle of digital services. Thus, providing decision aids to design novices is becoming increasingly important. In this research, we investigate taxonomy-based and tags-based decision aids. We draw on cognitive fit theory to construct a research model explaining the relationship between different decision aids and selection accuracy while considering the cognitive effort and the decision styles of novice designers. To test our hypotheses, we conducted a between-subject laboratory experiment with 195 subjects. Our experimental results provide extensive support to our hypotheses. Taxonomy-based decision aids outperform tags-based decision aids concerning selection accuracy mediated by cognitive effort. Furthermore, the results suggest rational decision style as a moderator in the relationship between taxonomy-based decision aids and selection accuracy. Our results have practical implications: First, taxonomy-based decision aids should be primarily leveraged on decision support platforms supporting design processes. Second, design novices' decision style and cognitive effort are influential factors when developing decision aids to support digital service design processes.