Based on Seckler, C., Mauer, R., & vom Brocke, J. (2022, in press). Design Science in Entrepreneurship: Conceptual Foundations and Guiding Principles. Journal of Business Venturing Design.

Guiding Principle 1: Be Explicit in Outlining the Contributions to the Body of Design Knowledge in Entrepreneurship

The first guiding principle is to make the contribution to the entrepreneurship field explicit. The aim of design science is to contribute to the body of design knowledge (e.g., Holmström et al., 2009; vom Brocke et al., 2020) and hence the aim of design science in entrepreneurship is to contribute to design knowledge in the entrepreneurship field. Explicitness about the intended contribution is useful in planning, communicating, and assessing design science work. However, the question of how to be explicit is more easily asked than answered (e.g., Corley & Gioia, 2011). In the design knowledge contribution framework, we provide a taxonomy that may help to make the types of contributions explicit (see Figure 3). We outline four distinct types of contributions along two axes, denoting the type of design knowledge and type of contribution. As discussed above, we differentiate two types of design knowledge: design object and design evaluation knowledge. Furthermore, we draw on an often-used differentiation of the type of contribution by distinguishing between theoretical and empirical contributions (e.g., Corley & Gioia, 2011; Whetten, 1989). By theoretical contributions, we refer to the development or extension of ideas – that is, concepts, propositions, classifications, theories, methods and whatever else can be thought of (Bunge, 2003). By empirical contributions, we refer to the characterization of objects of experience (e.g., observing, describing, measuring) as well as the realization of artifacts (e.g., constructing a material artifact or realizing a training design) (Bunge, 1967).

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Guiding Principle 2: Be Specific in Positioning the Design Science Study within the Existing Entrepreneurship Literature

The second guiding principle is to be specific about how the design science study is positioned within the existing design knowledge in the entrepreneurship field. It is important to be explicit about the design problem or design opportunity that motivates the design science project. While being specific about the positioning of the design study is important because it clarifies the purpose of the study (and largely influences the way the design problem/opportunity is addressed), the question of how to position a study is challenging for every design science project. In the design science positioning matrix, we propose four types of design science positionings: evaluation, improvement, exaptation, and exploration (see Figure 4). The matrix builds on Gregor and Hevner (2013) and draws on the conceptualization of design knowledge as a relational concept premised on means-ends relationships and their evaluation. We distinguish between known and unknown means or ends to outline the four resulting positionings, which we outline in more detail in the following.

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Guiding Principle 3: Be Comprehensive in Drawing on the Best Available Scientific Knowledge in Analyzing, Designing, and Evaluating

A third guiding principle for conducting good design science is to draw on the best scientific knowledge available in analyzing, designing, and evaluating. Building on the existing body of scientific knowledge is one of the hallmarks that differentiates design science from practice (Drechsler & Hevner, 2018). However, the question of how to effectively leverage the existing knowledge base is by no means trivial (Drechsler & Hevner, 2018). In the knowledge base utilization framework (see Figure 5), we provide guidance on how to leverage the knowledge base (i.e., explanatory knowledge and design knowledge) for three typical sub-problems of a design science project: analysis, design and evaluation (e.g., Peffers et al., 2007; Sein, Henfridsson, Purao, Rossi, & Lindgren, 2011; Van Aken & Berends, 2018).

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Guiding Principle 4: Be Rigorous in Using Fitting Methods Depending on the State of Prior Knowledge

A fourth guiding principle for conducting design science in entrepreneurship is to use fitting methods and to use them rigorously. The use of scientific methods is what sets design science as a scientific approach apart from practice (Bunge, 1967, 1996). While any methods must be implemented and used rigorously – that is, in adherence to state-of-the-art rules (Bunge, 2003) – the question of how to use fitting methods is conceptually more challenging (e.g., Edmondson & McManus, 2007). In the methodical fit framework (see Figure 6), we suggest that the fit of methods is determined largely by the state of background knowledge (i.e., the body of knowledge used, and taken for granted) on the issue at hand.

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