Selecting Start-up Businesses in a Public Venture Capital with Intuitionistic Fuzzy TOPSIS

Government-run public venture capital (GPVC), especially in developing countries is often beset with challenges compared to private venture capital initiatives. In particular, selection of early stage but high-potential start-ups in GPVCs often fail rigorous scrutiny because decisions are sometimes influenced by peripheral considerations of political and social affiliations. This phenomenon results in low capital recovery rate and a mischance in choosing deserving start-ups. With a numerical example, this paper adopts an intuitionistic fuzzy TOPSIS framework to demonstrate the selection of start-up businesses in a government high priority area such as in Information and Communications Technology. The Intuitionistic Fuzzy Weighted Averaging (IFWA) Operator is used to aggregate individual ratings into composite group decisions. The framework could serve as a useful tool for decision makers to scrutinize selection of start-ups in other government priority areas.