What you are is what you like – similarity biases in venture capitalists’ evaluations of start-up teams

The evaluation process of venture capitalists (VCs) has received much attention in the fields of entrepreneurship and finance, as it gives valuable insights into the criteria that distinguish successful from unsuccessful new firms. The underlying premise of these studies is that VC evaluations are objective, i.e. they predict actual start-up success without systematic distortions. Only recently, research has pointed out that VC evaluations are likely to be biased. In this paper, we analyze biases previously not discussed in the venture capital literature, namely, systematic distortions of VC evaluations that derive from the similarity between VCs and start-up team. Our study employs a conjoint design to obtain preference rankings from 51 VCs regarding venture teams with particular characteristics. We analyze these rankings using ordered probability models. Our independent variables include team characteristics and observed similarity measures. We find that similarity along two dimensions significantly affects the ranking of teams. Discrepancies between individual evaluation results are therefore not purely random, but vary systematically with the rater’s personal profile. Our results indicate that subjective evaluations of VCs should not be treated as objective measures of potential start-up success. Our research results also carry important implications for the decision making processes of VCs. (199 words)