Abstract:
Evidence shows that only a small number of entrepreneurial endeavors - high-impact
companies - create most of the new employment in the US. This research is looking for the
causes of emergence and uses computational methods to analyze speci c aspects of these
companies. First, this research proves or disproves some "popular conjectures" regarding the
age, location, industry and entrepreneurial character of high-impact companies. Secondly,
the agent-based model shows how a company grows in employment and revenue based on
two layers of organization: 1) one is the heterogeneous team formation and interaction
at the mezzo level of a company organization and 2) another one is the heterogeneous
employees skills and interaction at the individual level of a company organization. The
model advances and tests the hypothesis that companies that learn the "fastest" from failed
projects while retaining access to capital are more likely to become high-impact companies.
The experiments replicate the high-impact rate given by the real life data and show that
the high-impact phase of a company growth is achieved for speci c learning parameters
and failed projects. The purpose is to provide a coherent theory-model-evidence analysis
on high-impact entrepreneurship, that adds new insights for researchers, policy makers and
business practitioners, in addition to the qualitative information, informal knowledge or
hands-on experience that they currently posses.
