Managing Venture Capital Investment Decisions: a Knowledge-based Approach

In this study, we build a causal map of the investment decision using causal mapping techniques by interviewing venture capitalists (VCs). We convert this map into a causal Bayes net using techniques we developed. Causal Bayes nets are especially suited for domains characterized by high degree of uncertainty. Bayes nets have been recently developed in artificial intelligence and used in medical diagnosis, modeling portfolio risk and return, and new product development. They are based on probability theory. The network of cause-effect relations that constitutes a causal map reflects how individuals view the world and make inferences about the values of some variables in these maps when information is received about other variable in the map.