Advancing entrepreneurship as a design science: developing additional design principles for effectuation
提出创业研究可从人工智能的遗传算法中借鉴设计知识，为效果逻辑理论补充设计原则，从而推动创业作为一门设计科学的发展。
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.