  One of the most critical tasks for startups is to validate their business
model. Therefore, entrepreneurs try to collect information such as feedback
from other actors to assess the validity of their assumptions and make
decisions. However, previous work on decisional guidance for business model
validation provides no solution for the highly uncertain and complex context of
earlystage startups. The purpose of this paper is, thus, to develop design
principles for a Hybrid Intelligence decision support system (HI-DSS) that
combines the complementary capabilities of human and machine intelligence. We
follow a design science research approach to design a prototype artifact and a
set of design principles. Our study provides prescriptive knowledge for HI-DSS
and contributes to previous work on decision support for business models, the
applications of complementary strengths of humans and machines for making
decisions, and support systems for extremely uncertain decision-making
problems.
