Accelerating Entrepreneurial Decision- Making with Hybrid Intelligence

Previous studies revealed that around 75 percent of all start-ups fail at an early stage. One main reason for this tremendous failure rate is that entrepreneurs are typically confronted with high levels of uncertainty about the viability of their proposed business idea. Following this argumentation, entrepreneurial decision-making can be defined as complex decision-making problem under both risk and uncertainty. While risk includes quantifiable probabilities, uncertainty describes situations where neither outcomes nor their probability distribution can be assessed a priori. Consequently, the entrepreneurial decision-making context is highly complex and contains lots of “black swan events” that seems to be unpredictable. As previous research does not provide any IT-based and scalable solutions for decisional guidance in such contexts, the purpose of this study is to explore the entrepreneurial decision- making context and then suggest novel and innovative design paradigms and design principles for decisional guidance in the context of entrepreneurial decision-making.