Towards a framework to predict start-up's business model success potential

Abstract

The present master thesis regards the development a theoretical framework which is an algorithm with the goal of predicting start-ups business model’s success potential. It was designed to support entrepreneurs understanding better what venture capitalists and business angels (VC/BA) take into consideration for predicting start-ups’ success. ISC stands for Idea, Story and Context which are considered the main drivers towards start-ups’ business model success prediction by the model. This study has tested this framework on three real case-study start-ups to compare how the framework rates the three start-ups in comparison with business savvy people, such as VC/BA investors and management students. For doing this study, the framework leveraged an online platform named Business Model Composer®, an online platform for communicating business models using state-of-the-art research on business models’ topics. Finally, it is suggested how such algorithm could be integrated into an online tool to support entrepreneurs swiftly.

Date of Award	18 Oct 2016
Original language	English
Awarding Institution	Universidade Católica Portuguesa
Supervisor	René Bohnsack (Supervisor)