While recent research explores the dark side of entrepreneurship there remains little exploration of what, if any, role entrepreneurship education (EE) plays in producing dark side outcomes. Accordingly, we explore dangers and unintended consequences EE poses to students and universities as well as the role of both student and instructor in mitigating dark side concerns. Specifically, we use a Delphi technique to distill from a panel of experienced educators the dangers EE may pose as well as strategies for mitigating dark side consequences. In sum, this work contributes to EE research by providing a unique mixed-methods view of the dark side of EE and raising awareness of the unintended consequences borne by the students and institutions we serve.

The impact of young companies with purely digital products and services has raised interest in so-called digital entrepreneurs (DEs), all-digital business models, and ecosystems in which DEs thrive. Researchers study this Schumpeterian destruction, policy makers try to replicate digital ecosystems, and investors seek the next “gazelle.” We return to an early research topic: can psychological traits classify entrepreneurs? Are DEs unique digital natives, or are they business as usual? Using the five-factor personality model and psycholinguistic analysis of entrepreneur interviews, we improve start-up performance prediction when distinguishing DEs from traditional entrepreneurs. DEs are less concerned about the future than traditional entrepreneurs and use “neuroticism” to their advantage. Anxiety in DEs correlates with performance, whereas anxiety correlates with risk and negatively with performance among traditional entrepreneurs. We show that DEs are sufficiently different from traditional entrepreneurs to warrant further research on their motivation and on policies and ecosystems that reflect these differences.

A value proposition common among startup incubators and clusters is they provide firms with an environment that is more supportive than the open market, for example a high concentration of startups can be conducive to the building of social capital and tacit knowledge by tenants who, upon graduation from such sites, impact the regional economy. The positive impact of social capital on startup survival has been well described in the literature, but the impact of startup incubators and clusters remains inconclusive, with some researchers reporting that the survival rate of firms graduating from incubators or clusters is worse than that of startups that never participated in such sites. The lackluster performance of graduating firms is all the more striking given the opportunity for social capital diffusion in these high density sites, and the importance of social capital to startup success. Empirical tests using the Kauffman Firm Survey find that being in an environment in which social capital is readily accessible does not imply that the startup will engage it. We also find those startups that collaborate with other agents (universities, industries, and government organizations) outperform startups that do not. This result is moderated by industry, i.e. low-versus high-tech.