Qualitative decision–making model of investment into start–up companies

Abstract

The investments into start–up companies are often unique. The results are difficult to forecast. These investments are based on sparse and vague information, which is why statistical modelling methods are not applicable. Therefore, this paper applies qualitative modelling and qualitative decision tree to support investment decision–making into start–up companies. A team of experts was asked to describe start–up investment and 12 characteristics (variables) were chosen, e.g., profitability, market potential, etc. These variables were divided to two sets, variables that are under the management control - decision variables - and variables that are not under managerial control - lottery variables. The 12–dimensional models were developed; a common–sense analysis identifies 18 qualitative equationless relations and the model generated 20 scenarios. A subset of scenarios was transferred into a qualitative decision tree. The tree was evaluated to identify the best possible sequence of decisions using heuristics based on common–sense reasoning.