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Although entrepreneurship scholars increasingly embrace the design science approach (DS), many struggle with the perception that existing DS methodologies lack guidance for exploration projects. Exploration projects deviate from more traditional improvement projects, which typically commence with a clear goal or problem in mind. Instead, they aim to explore fundamentally novel means-end relationships. This article introduces a DS methodology guiding researchers in executing high-quality exploration DS projects. The proposed Design Science Methodology for Exploration Projects (in short: DS:X) offers procedural guidance for exploring and exploiting novel means-end relationships. DS:X is designed to be a modular methodology that emphasizes formative evaluation and allows to engage in design pivots as part of the DS process. Taken together, DS:X broadens the methodological repertoire of DS scholars, providing a shared framework for planning, conducting, and publishing exploration projects in entrepreneurship and beyond.

Extensive efforts have been made by both academics and practitioners to understand the inter-firm competitive relationship owing to its profound impacts on multiple key business goals, e.g., company benchmarking, marketing strategy planning, and talent acquisition. However, it has never been an easy task to fully characterize firms and assess the competitive relationship among them, mainly due to the challenge of information heterogeneity. In this regard, we propose a novel IT artifact for firm profiling and inter-firm competition assessment guided by Information System Design Theory (ISDT). We start by constructing a Heterogeneous Occupation Network (HON) using employees’ occupation details and educational attainments. Then we adopt a Metapath2vec-based heterogeneous network embedding model to learn firms latent profiles (embeddings). Using the firm features and embeddings as input, we train multiple supervised classifiers to assess the competitive relationship among the firms. Following the principles of design as a search process, we demonstrate the effectiveness of our IT artifact through extensive experimental studies and detailed discussions. Our research has also discovered that the occupation and education specifics of employees are key factors in identifying potential competitors of a focal firm.

Design science research (DSR) aims to generate knowledge about innovative solutions to real-world problems. Consequently, DSR needs to deal with the complexity related to problem and solution spaces involving socio-technical phenomena that people perceive differently and are subject to constant change. This complexity poses challenges to sequential, process-based approaches—specifically, the existing DSR methodology. We designed a DSR methodology that extends existing approaches by adding a complementary organizing logic to address complexity. Based on the theory of hierarchical, multilevel systems, we suggest organizing DSR based on the concept of “echelon”—meaning to decompose DSR projects into smaller logically coherent self-contained parts—and suggest a set of five design echelons that imply a hierarchical organizing logic for DSR projects. The echeloned DSR (eDSR) methodology was developed in five iterations, involving seven design and evaluation episodes.

Descriptive and prescriptive theorizing are two sides of the same coin and fundamentally complementary, if not reciprocal in their relationship. Both have a place in management theorizing, yet this Point-Counterpoint debate takes issue with how they are currently performed in research. The Point makes the case for prescriptive theorizing to help tackle societal grand challenges and meaningfully impact practice, and it offers a recipe for doing this on a solid normative foundation. The Counterpoint cautions against the impact that such prescriptions may have and calls for more contextualized approaches. In this introduction to the debate, I intend to take the conversation that both the Point and Counterpoint have provoked even further by highlighting some under-emphasized but important theoretical avenues to examine the (un)intended consequences of both prescriptive and descriptive theorizing; namely by mobilizing research on performativity and counter-performativity.

Although management research has a rich tradition of both descriptive and prescriptive theorizing, the latter is often (and erroneously) viewed as unscientific, purely practice-oriented, or simply a corollary of descriptive analysis. Prescriptive theorizing concerns how things should be and how they can be achieved, as opposed to descriptive theorizing, which focuses on why or how things are (interrelated). Accordingly, prescriptive theorizing has strong normative and instrumental properties, which are especially relevant when addressing pressing societal, ecological, and ethical concerns, also referred to as grand challenges, that demand a re-evaluation of established norms and behavioural patterns. However, this opportunity is currently underutilized in the management literature, and there is a lack of guidance on how to leverage the principles of prescriptive theorizing. Therefore, I clarify its main characteristics, outline how scholars can construct rigorous prescriptive arguments, and show how normative and instrumental reasoning can promote positive social change. Embracing prescriptive theorizing as a vital complement to descriptive theorizing in management research provides scholars with an intellectual toolkit to actively engage in the urgent discourse on grand challenges and develop compelling new and impactful theories.

The food production sector is one of the largest industries globally, yet it is confronted with significant challenges. While food tech startups are viewed as a promising means of addressing some of these obstacles, they frequently encounter the issue of being highly research-intensive and risky investments. In this project, we pose the following question: How can we effectively design investment vehicles and strategies to support food tech startups? To address this question, we undertook an exploration design science research project. In collaboration with a corporate venture fund, we initially explored opportunities and subsequently developed a solution design for one of the most promising prospects. This study contributes to the body of design knowledge in three primary ways. Firstly, it contributes by providing a situated artifact that outlines the design of a closed-ended deep science food tech fund engaged in production and input supply. Secondly, it contributes by establishing design principles for investment vehicles and strategies in ventures that are highly research-intensive and risky. Lastly, this study makes a methodological contribution by showcasing how a methodology for addressing exploration design science projects could look like.

Entrepreneurship scholars increasingly embrace the design science approach. While established design science methodologies from other fields have distinct strengths, they provide little guidance for a particularly relevant type of design science project for entrepreneurship scholars, namely exploration projects. In this article, we propose a methodology for exploration projects which we refer to as the infinity methodology. The infinity methodology builds on scientific knowledge of the entrepreneurial process, design science activities, and principles. More specifically, the infinity methodology guides scholars through two interrelated entrepreneurial cycles (i.e., opportunity exploration and exploitation), each of which involves three key design science activities (i.e., analysis, design, and evaluation). The infinity methodology makes a unique contribution to the methodological repertoire of design science scholars and provides a common framework for publishing design science in entrepreneurship.

While many recognize the relevance of creativity in design science, there is a lack of guidance in the field on how to use creativity methods effectively. In this article, we draw on the creativity literature to provide guidance on choosing effective creativity methodsin the DSR process. A Creativity-MethodsFit Framework suggests that the fit of creativity methods depends on the structuredness of the problem and the solution space. Furthermore, it outlines which divergent and convergent creativity methods should be used. This paper contributes in two main ways. First, the framework provides guidance on the use of creativity methods in DSR. Second, the paper complements previous frameworks discussing fitting evaluation methods, by introducing the notion of fitting creativity methods to the DSR discourse.

Design science research (DSR) produces knowledge via the design and evaluation of innovative solutions to real-world problems. DSR provides an improved understanding of how and why the solutions work. While DSR is being widely embraced in many research disciplines, its educational pedagogy so far remains immature with little guidance on how best to inform and train various audiences on relevant and rigorous DSR skillsets. Grounded on the authors’ wide experience in designing and delivering DSR courses over the past decades, we develop a “DSR Proficiency Model” to highlight key skills required to succeed in planning, applying, and communicating DSR. We recognize the different educational environments and student backgrounds that DSR courses must accommodate and provide actionable guidance for mapping the proficiency model to academic, training, and executive audiences. Informative examples demonstrate how we have structured DSR curricula for different academic and executive education programs.

A key capability to work in multidisciplinary teams is smart collaboration. While previous research has elaborated on starting smart collaboration in firms, less is known about how to move smart collaboration from initial starting projects towards excellent implementation. In this design science project, we address this question and develop design knowledge on how to move smart collaboration from good to great in a firm working with multidisciplinary teams. We outline a situated artifact for the collaborating firm (i.e., The Firm) and infer more general design principles based on this study. This study contributes in three ways. First, it develops a situated artifact for improving smart collaboration in a firm relying on multidisciplinary teams. Second, it develops more general design principles on improving smart collaboration in professional service firms. Third, it provides initial empirical evidence for the quality of the proposed design object.

We examine how machine learning (ML) predictions of high-growth enterprises (HGEs) help a budget-constrained venture capitalist source investments for a fixed size portfolio. Applying a design science approach, we predict HGEs 3 years ahead and focus on decision (not statistical) errors, using an accuracy measure relevant to the decision-making context. We find that when the ML procedure adheres to the budget constraint and maximizes the accuracy measure, nearly 40% of the HGE predictions are correct. Moreover, ML performs particularly well where it matters in practice—in the upper tail of the distribution of the predicted HGE probabilities.

The goal of strategy is not only to address a given environment, but also to change it to a firm’s advantage. In this article, we maintain that design science provides a useful theoretical foundation for understanding the development of novel strategies by shifting strategists’ perspective from what is to what could be, from the past and present to the future, and from choosing among existing alternatives to discovering new problems and solutions. We propose a structured process based on design mechanisms, which enables strategists to overcome the impediments to generating novel strategies that have been identified in prior research. The process we theorize integrates (a) strategists’ shaping intentions to transform an existing situation into a preferred one, (b) discovery-oriented exploration of problems and solutions based on designing without final goals, and (c) stakeholder dialogue to validate and extend novelty and value. Our ideas extend the micro-foundations of strategy with respect to the generation of strategic foresight and shaping intentions, as well as the work at the intersection of stakeholder strategies and complex societal problems.

If we have two bodies that interact gravitationally, and we know their positions and velocities at a given point in time, it is possible to predict all their future positions. However, the introduction of a third body surprisingly leads to a problem that is analytically unsolvable. This suggests that if we have a system of two bodies that are unsettled with respect to one another, there may be a hidden third body lurking around that, if identified and understood, could help us make better sense of the system as a whole. While metaphors should be used with care, the three-body problem can help illuminate a pressing epistemological issue within our own discipline.

This paper explores the challenges impact investors face in assessing the social and environmental impact of startups, as traditional venture investing tools cannot fully capture their unique characteristics. Following a design science approach, we identify three startup-specific design requirements in the literature and propose five design principles. Building on this, we present a conceptual impact due diligence that takes into account the specific criteria for evaluating impact-driven startups. We conduct alpha tests with expert interviews that confirm the overall practical relevance and applicability of the framework. The study makes a theoretical and practical contribution to research in sustainable entrepreneurship and sustainability accounting by identifying solutions to the specific challenges of valuing such startups. Practitioners can use the resulting conceptual artifact to adapt their impact evaluation practices.

Today's Information Systems (IS) design research projects pursue digital innovation to conquer complex societal challenges. Many of these projects reach out beyond disciplinary and organisational boundaries, as evident in interdisciplinary consortia and academia-industry collaboration. The design activities in each project differ based on contextual requirements and the team's underlying design logic. As diversity increases, shared understanding is essential for project success. Established design research methodologies need complementary tools to support design researchers in configuring their design activities and representing them faithfully, dimensions that contribute to a shared understanding. This article presents Baustein as an instance of such design tools. Baustein is tailorable to the contextual requirements of each design research project, comprising an ensemble of card-deck, ready-made configurations, and a manual. To ensure theoretical and practical relevance, the design of Baustein is based on primary empirical data (workshop and interviews with 16 IS design researchers) and a literature analysis of 99 published IS design research projects. We demonstrate its proof-of-value through three main evaluation episodes, altogether involving over 110 IS design researchers. With Baustein, design research teams can balance the trade-off between creative messiness and standardised configurations of design activities.

Designing requires skills that are different from making and is an integral part of venture creation. To encourage considerations of design in entrepreneurship education, this paper elaborates how designing can be embedded in entrepreneurship education as a distinct composite capability to be developed. It outlines a perspective of entrepreneurial action as design, whereby activities of framing, modeling, and performing give a concrete action its entrepreneurial meaning of concerning a future venture. We discuss how the underpinning capabilities can be developed in educational settings, using principles, methods, and examples as distinct types of instructions to be deployed by entrepreneurship educators in different combinations and for different purposes. We develop the implications of our work by offering a set of design principles tailored for entrepreneurship education.

In this paper we provide a counterpoint to the view that prescriptive theorizing reflects a viable means for enhancing the practical impact of management theorizing towards addressing some of the most pressing societal concerns and grand challenges of our times. To do so, we first contextualize the roots of prescriptive theorizing in management research, argu- ing that the approach developed by Hanisch is reflective of the wider ‘positive’ prescriptive turn in social science theorizing. Second, we problematize the presumptive basis upon which much prescriptive theorizing as well as related ideas around utopian thinking are based. In doing so, our broader aim is to draw attention to the bases upon which prescriptive claims are made and we specifically highlight the dangers of implementing decontextualized, overly simple and styl- ized prescriptions in the face of complex grand challenges. In contrast to prescriptive theorizing, we propose that the practical impact of management theory may rather be enhanced through a tempering of instrumental rationality with a deep(er) concern for phenomena and experience. We conclude the paper by offering a number of ways in which this can be done.

For entrepreneurship research to be relevant and impactful, entrepreneurship scholars must start by understanding the problems faced by entrepreneurs.However, problems are different from research questions.As scholars, where do we start, and how do find these problems? And how do we ensure that we do user-inspired research that advances both understanding and practical relevance? Based on my experience and learnings as an ex-practitioner in training to be an entrepreneurship scholar, who took on the Me-search approach in my research to solve a problem in digital entrepreneurship, this essay presents my humble experiences in framing a real-world problem in solution-oriented entrepreneurship research.Given that I have taken a path less traveled, unintentionally, starting with a problem rather than from a theory orientation, I present my informal reflections on why entrepreneurship scholars need to develop both descriptive and prescriptive knowledge.

Design science in the entrepreneurship field holds the promise of developing relevant knowledge with scientific rigor. Yet despite the promise of this approach, the entrepreneurship field still lacks guidance on how to plan, conduct, and assess design science work. In order to develop theoretically grounded principles, we first make our perspective on design science explicit. We characterize design science in entrepreneurship as a specific scientific approach that shares the values of practice (i.e., usefulness) and uses the methods of science (i.e., scientific method plus more specific, scrutable methods). We conceptualize design knowledge as a body of scientific knowledge that comprises both design object knowledge (e.g., situated artifact, and design principles), and design evaluation knowledge (e.g., usefulness, and social worth). Drawing on these foundations, we provide guidance on (1) how to make design knowledge contributions explicit, (2) how to position design science work, (3) how to effectively utilize prior knowledge, and (4) how to use fitting methods in design science work. The article contributes by further developing the conceptual foundations of design science in entrepreneurship and providing guidance on how to conduct and assess design science work in the entrepreneurship field.

The debate about the relevance of management scholarship is not new (Nicolai & Seidl, 2010). Many would attest to our societal impact through our manifold activities: teaching, consulting, outreach—and our research on topics such as grand challenges. Yet, when we look at, say, economists, they have more visibility and impact. Clearly, there is room for improvement. How then can we as management scholars organize ourselves better to collectively achieve more relevance with our research?

Recognizing the importance of various types of artifacts for entrepreneurship, design science (DS) has been proposed as an inclusive approach that combines relevance and rigor. By enabling researchers to go beyond their traditional roles as observers and analysts of established artifacts to help design new artifacts, DS can improve the relevance of entrepreneurship research. However, there is a paucity of knowledge on how this type of research can be published in leading entrepreneurship journals. In this editorial, we seek to provide practical guidance on how to craft and assess DS studies that target Entrepreneurship Theory & Practice (ETP) and other top-tier journals.

Corporate entrepreneurship is a challenge for organizations and their employees, for example because of structural rigidities or inertia. A promising approach of how to spark corporate entrepreneurship lies in effectuation research. Effectuation is a mode of action or decision-making logic that is based on empirical evidence from expert entrepreneurs. Following a Design Science Research (DSR) methodology, we develop and implement an effectuation intervention at a German multinational corporation. The intervention consists of two basic parts: The Market of Makers, an event that leads participants through the effectual process, and the Speedboat Regatta, a 3-months long project development phase. The intervention successfully generated 23 projects that identified opportunities for process innovation. This study contributes to design knowledge, theory and practice. First, we designed a blueprint for similar effectuation interventions and are able to formulate four design principles, which show how voluntariness, playfulness, and constraints enable effectuation and promote corporate entrepreneurship. Second, we contribute to corporate entrepreneurship theory by showing that effectuation is promising for approaching corporate entrepreneurship’s theoretical and empirical problems. Third, we contribute to practice by demonstrating that interventions based on effectuation may shift employees towards leading and engaging with innovative projects.

This paper reports on a design science project developing an innovation accounting system for a professional service firm. Innovation accounting is an approach to track the progress of innovation activities. Although the subject of study has a defined product innovation process, there is a lack of measurable information on the outcomes of innovation activities. This implies a blind spot in the effective allocation of resources in innovation activities. In this paper a design science approach is used to bridge the existing concepts on innovation accounting and the needs of user groups. The output of the paper is a conceptual solution design for an innovation accounting system in the context of the product innovation process for a professional service firm. The learnings from the study are transferred into design propositions by using the CIMO-logic. This paper contributes to the body of design knowledge on innovation accounting in professional service firms.

For many digital ventures, acquiring financial resources in multiple rounds beyond seed funding to grow has become an important part of their entrepreneurial journey. The success rate of raising equity capital beyond their seed investments is, however, very low. Existing entrepreneurship studies on financial resource acquisition have explored separately how entrepreneurs organize their networks, establish venture legitimacy, and decide on funding sources. However, despite being identified as an important subprocess in new venture creation, little is known about why, when, and how entrepreneurs engage potential investors to increase the likelihood of post-seed investments. Hence, this paper synthesizes the literature on financial resource acquisition, theoretical concepts in entrepreneurial financing, and practice knowledge to frame a set of design principles to create a prescriptive process model to increase the likelihood of success in post-seed financial resource acquisition.

Scholars have advocated the development of entrepreneurship as a design science. One foundational challenge in a design science is to identify design principles. We argue that a particular field can draw on a design knowledge from different design sciences to develop design principles. In particular, we show that entrepreneurship research can learn from one branch of artificial intelligence studies called “genetic algorithm,” which is a design field that creates solutions for complex, nonanalytical, and ill-structured problems. We illustrate the analogous transfer process by identifying complementary design principles for one exemplary entrepreneurship theory, namely effectuation. In turn, these additional effectual design principles further effectuation theory as a design science and help advance entrepreneurship as a nascent design science.

Platform as a service (PaaS) has become a strategic option for software vendors who expect to benefit from value co-creation with partners by developing complementary components and applications. In reality, however, established and new software vendors are battling to redefine their offering to embrace PaaS. They face the challenges of transforming, configuring and calibrating their PaaS business models to align them with existing business models, customer expectations and competitive pressures. This motivates our research question: How can software providers design viable business models for PaaS? Our study develops a design theory for PaaS business models. This theory is grounded on a 12-month action design research study at one of the largest global software companies (here called Alpha) with mixed PaaS experiences in the past. Our primary research contribution is a set of design principles that guide software providers to define a viable PaaS business model in order to create a flourishing software eco- system for their cloud platform. By synthesizing prescriptive knowledge related to business model design for emerging cloud platforms, our study advances PaaS research towards the existing body of research on software platforms and business models.