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08-06-2019 | Issue 3/2020 Open Access

Small Business Economics 3/2020

Advancing entrepreneurship as a design science: developing additional design principles for effectuation

Small Business Economics > Issue 3/2020
Stephen X. Zhang, Elco Van Burg
Important notes
The authors are indebted to David Goldberg, the pioneer of genetic algorithms. David inspired this paper and helped the R&R process invaluably. Next to that, we thank special issue editor Martin Obschonka, the anonymous reviewers, as well as Joep Cornelissen, Dimo Dimov and seminar partipants at the 2016 Effectuation Conference in Bodø for their comments on earlier versions of this study.

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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.

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