Constructing a Business Model Taxonomy: Using statistical tools to generate a valid and reliable business model taxonomy

Pernille Groth, Christian Nielsen


Business model, Taxonomy, Research design, Cluster analysis, Theory development


Purpose: The paper proposes a research design recipe capable of leading to future business model taxonomies and discusses the potential benefits and implications of achieving this goal.

Design/Methodology/Approach: The paper provides a review of relevant scholarly literature about business models to clarify the subject as well as highlighting the importance of past studies of business model classifications. In addition it reviews the scholarly literature on relevant methodological approaches, such as cluster analysis and latent class analysis, for constructing a business model taxonomy. The two literature streams combined to form the basis for the suggested recipe.

Findings: The paper highlights the need for further large-scale empirical studies leading to a potential business model taxonomy, a topic that is currently under-exposed even though its merits are highlighted continuously in the contemporary literature. However, the research stream in relation to a business model taxonomy also needs a sound starting point in order to ensure valid and reliable outcomes. In this paper a research design for conducting such studies is presented and obstacles, which need to be overcome to ensure the quality of business model taxonomy studies in the future are identified.

Originality/Value: The paper highlights the benefits and potential implications of designing business model taxonomy studies and makes the case for ensuring the quality of future studies relating to e.g. performance. Reviewing the literature on both business models and methodological theories achieves this.