No abstract

Taxonomies are classification systems that help researchers conceptualize phenomena based on their dimensions and characteristics. To address the problem of ‘ad-hoc’ taxonomy building, Nickerson et al. (2013) proposed a rigorous taxonomy development method for information systems researchers. Eight years on, however, the status quo of taxonomy research shows that the application of this method lacks consistency and transparency and that further guidance on taxonomy evaluation is needed. To fill these gaps, this study (1) advances existing methodological guidance and (2) extends this guidance with regards to taxonomy evaluation. Informed by insights gained from an analysis of 164 taxonomy articles published in information systems outlets, this study presents an extended taxonomy design process together with 26 operational taxonomy design recommendations. Representing an update for taxonomy designers, it contributes to the prescriptive knowledge on taxonomy design and seeks to augment both rigorous taxonomy building and evaluation.

Taxonomies are design science artifacts used by researchers and practitioners to describe and classify existing or future objects of a domain. As such, they constitute a necessary foundation for theory building. Yet despite the great interest in taxonomies, there is virtually no guidance on how to rigorously evaluate them. Based on a literature review and a sample of 446 articles, this study explores the criteria currently employed in taxonomy evaluations. Surprisingly, we find that only a minority of taxonomy building projects actually evaluate their taxonomies and that there is no consistency across the multiplicity of criteria used. Our study provides a structured overview of the taxonomy evaluation criteria used by IS researchers and proposes a set of potential guidelines to support future evaluations. The purposeful and rigorous taxonomy evaluation our study advances contributes to DSR by bridging the gap between generic evaluation criteria and concrete taxonomy evaluation criteria.

In creative work such as design thinking projects, teams mostly seek to solve complex (wicked) problems as well as situations of uncertainty and value conflicts. To design solutions that cope with these aspects, teams usually start doing something, reflect on their results, and adjust their process. By actually doing something, tacit knowledge (i.e., knowing-in-action) of individuals is disclosed, which might be beneficial for an entire project team because it allows drawing on information and experiences that go beyond single individuals. Accordingly, the present study aims to investigate how tools can be designed that support collaborative reflection in creativity-driven projects. Drawing on reflection theory and several expert interviews, we derive design requirements as well as present a concrete software-based prototype as an expository instantiation.

Yet despite the great interest in taxonomies, there is virtually no guidance on how to purposefully visualize them. Interestingly, taxonomies are visualized in ways as diverse as morphological boxes, hierarchies and mathematical sets, to name three typical examples. As a result, taxonomy builders face the following question: Which type of taxonomy task is best supported by which type of taxonomy visualization? This short paper raises the awareness of the problem and lays ground for conducting controlled experiments that have the potential to purposefully leverage taxonomy visualizations. We present an experimental design that allows to investigate the cognitive fit between the different types of taxonomy visualizations and taxonomy tasks. Thus, we contribute towards researching whether taxonomy visualizations make a difference when performing certain tasks by using taxonomies.