1 General 

Design Science is a problem‑centred research approach with roots in the engineering disciplines that has become a core paradigm in Information Systems research. Its primary focus is the development and evaluation of innovative artefacts that support the analysis, design, implementation, management, and use of information systems. Such artifacts may take the form of constructs, models, methods, or instantiated systems and are intended to improve the effectiveness and efficiency of socio‑technical settings. (Hevner et al. 2004)

Artefacts are not created in a theoretical vacuum. Design‑science studies are grounded in existing theories and bodies of knowledge, which are applied to concrete problem contexts, used to inform design decisions, and refined based on empirical evaluation. In this sense, Design Science seeks to combine rigorous scientific grounding with a strong orientation towards practically relevant problem solving (see Research Methods and Theoretischer Rahmen und Argumentation).

Hevner (2007, p. 87) conceptualises design‑science research using a three‑cycle view that distinguishes three interrelated cycles:

• the Relevance Cycle ("The Relevance Cycle inputs requirements from the contextual environment into the research and introduces the research artifacts into environmental field testing."),
• the Rigor Cycle ("The Rigor Cycle provides grounding theories and methods along with domain experience and expertise from the foundations knowledge base into the research and adds the new knowledge generated by the research to the growing knowledge base."), and
• the Design Cycle ("The central Design Cycle supports a tighter loop of research activity for the construction and evaluation of design artifacts and processes.").

The Relevance Cycle channels requirements and problem statements from the application environment into the research project and feeds the resulting artefacts back into the environment, for example through field tests or pilot deployments. The Rigor Cycle connects the project to the existing knowledge base by providing theoretical foundations, methods, and domain expertise, and by adding newly generated insights back into that knowledge base. At the core, the Design Cycle comprises the iterative build‑and‑evaluate loop, in which design artifacts and processes are constructed, tested, and gradually refined.

Taken together, Design Science can be seen as a research strategy that enables the development of purposeful artifacts based on both scientific and practical criteria, and the systematic investigation of their effects (see also Research Methods – Qualitative Methods).

2 Goal

The primary purpose of design‑science research is to create and evaluate artifacts that address relevant organisational and information‑system‑related problems. These artefacts may be genuinely novel or represent substantial improvements of existing solutions.

A widely used classification distinguishes four core categories of artifacts:

• Constructs (e. g. core concepts, variables, and terminologies),
• Models (e. g. conceptual or formal representations of relationships),
• Methods (e. g. procedures for analysis, design, or decision support), and
• Instantiations (e. g. prototypes, software systems, workflows).

Design Science thus pursues a dual ambition. On the one hand, artefacts are expected to deliver tangible value to practitioners (e.g. improved efficiency, better decision quality, enhanced transparency). On the other hand, the design and evaluation of these artefacts should contribute to the scientific knowledge base, for example through design principles, design theories, or refined conceptual models (see Research Question and Research Gap in Information Systems).

3 Execution

The design‑science process is often characterised by the two core activities “build” and “evaluate”. The build phase encompasses the activities required to construct the artefact, such as requirements elicitation, conceptual design, and implementation of prototypes. The evaluate phase subjects the artefact to systematic assessment using appropriate methods, and the resulting feedback informs subsequent design iterations.

In practice, this build‑and‑evaluate cycle is typically executed multiple times, enabling progressive refinement of the artefact and a deeper understanding of the underlying problem domain. Hevner et al. (2004) articulate several guidelines for conducting design‑science research:

• Design as an artifact
  The research must produce a viable artefact in the form of a construct, a model, a method, or an instantiation that addresses a clearly defined problem.
• Problem relevance
  The study targets a relevant organisational or business problem for which a technology‑based solution is developed.
• Design evaluation
  Appropriate evaluation methods (e. g. experiments, case studies, simulations, expert reviews) are used to demonstrate the utility, quality, and impact of the artifact.
• Research contributions
  The research provides verifiable contributions in at least one of the following areas: artifact design, design foundations, or design methodologies (e. g. novel design principles or extended conceptual models).
• Research rigor
  Rigorous research methods are applied to both the construction and the evaluation of the artifact. This includes systematic derivation of the design from theory and requirements, as well as transparent reporting of the evaluation procedure.
• Design as a search process
  The development of artifacts is understood as a search process within a solution space constrained by available resources, environmental conditions, and problem boundaries. The aim is to identify a solution that is satisfactory under these constraints.
• Communication of research
  Findings from design‑science projects are communicated in a way that addresses both technically oriented and management‑oriented audiences (e. g. the IS research community, industry partners).

Design‑science projects therefore require a close integration of theoretical grounding, practically relevant problem settings, and carefully planned evaluation. Additional guidance on embedding design‑science approaches in thesis work is provided in the sections Theses and Research Methods.

Anyone planning to use design‑science approaches in a thesis or research project should ensure that the theoretical framework, the research question, and the methodological design are carefully aligned. In addition to this overview, the pages Research Methods, Research Question and Research Gap in Information Systems, and Theoretischer Rahmen und Argumentation provide further guidance for conceptually framing and structuring the project.

Core literature

• Hevner, A.R.; March, S.T.; Park, J.; Ram, S. (2004): Design Science in Information Systems Research. In: MIS Quarterly, Vol. 28 (2004) No. 1, pp. 75-105.
• Hevner, A.R. (2007): A Three Cycle View of Design Science Research. In: Scandinavian Journal of Information Systems, Vol. 19 (2007) No. 2, pp. 87-92.

Further literature

• Gregor, S.; Hevner, A.R. (2013): Positioning and Presenting Design Science Research for Maximum Impact. In: MIS Quarterly, Vol. 37 (2013) No. 2, pp. 337-356.
• Peffers, K.; Tuunanen, T.; Rothenberger, M.A.; Chatterjee, S. (2007): A Design Science Research Methodology for Information Systems Research. In: Journal of Management Information Systems, Vol. 24 (2007) No. 3, pp. 45-77.