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

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  • Stephen X. Zhang

    (The University of Sydney)

  • Elco Burg

    (Vrije Universiteit Amsterdam)

Abstract

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.

Suggested Citation

  • Stephen X. Zhang & Elco Burg, 2020. "Advancing entrepreneurship as a design science: developing additional design principles for effectuation," Small Business Economics, Springer, vol. 55(3), pages 607-626, October.
    • Handle: RePEc:kap:sbusec:v:55:y:2020:i:3:d:10.1007_s11187-019-00217-x
    DOI: 10.1007/s11187-019-00217-x
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    2. Faiez Ghorbel & Wafik Hachicha & Younes Boujelbene & Awad M. Aljuaid, 2021. "Linking Entrepreneurial Innovation to Effectual Logic," Sustainability, MDPI, vol. 13(5), pages 1-13, March.
    3. Lupp, Daniel, 2023. "Effectuation, causation, and machine learning in co-creating entrepreneurial opportunities," Journal of Business Venturing Insights, Elsevier, vol. 19(C).
    4. Baoshan Ge & Qi Wang & Meifang Yao, 2022. "From ideas to entrepreneurial opportunity: A study on AI," Systems Research and Behavioral Science, Wiley Blackwell, vol. 39(3), pages 618-632, May.

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