Journal of Entrepreneurship Education (Print ISSN: 1098-8394; Online ISSN: 1528-2651)

Abstract

Corporate Venture Capital Strategy for Selecting Start-Up Investments in Indonesia using an Agent-Based Model: Cases of a Mobile Application Start-Up, Payment Solution Start-Up and Digital Advertising Start-Up

Author(s): G.N. Sandhy Widyasthana, Dermawan Wibisono, Mustika Sufiati Purwanegara, Manahan Siallagan, Pratiwi Sukmawati

Digital-related businesses are growing significantly globally, and an average increase of 20% from 2014 to 2020 is expected. These businesses are dominated by rising start-ups based in Silicon Valley. The financing model implemented by many of these start-ups is the venture capital (VC) model. In addition to providing funding, VC offers mentorship and networking with investors and other market opportunities that can help start-ups grow into successful companies. Venture capitalists should practice caution when deciding to invest in a start-up. They must find a good start-up to reap the benefits of start-up valuation growth. Venture capitalists have long used subjective methods to make investments, and these methods involve high risk. To better predict start-up valuation and minimize risk, investors must understand the key parameters, i.e., the management team, the nature of the product, intellectual capital, geographic location and coherence, and they should track the changes in these parameters based on the start-up activity. Start-up activity is defined as the interactions within the ecosystem with stakeholders, such as venture capitalists, government agencies/bodies, other start-ups and customers, to improve business performance, networks and product capabilities, which may be factors in venture capitalists’ investment decision making.

This study attempts to model start-up interactions with other stakeholders within the start-up ecosystem and measure the effects of those interactions on start-up performance over a certain period of time. The agent-based model of start-up interaction simulates start-up improvement progress using three scenarios. The purpose of the model and the simulation is to aid investors in predicting future start-up performance based on stakeholder interaction effectiveness.

The results of the simulation demonstrate that start-up performance progress is determined by the effectiveness of interactions between stakeholders. The more effective the interaction, the better the start-up performance. The simulation results can also be used as a template for the interaction of start-ups with their stakeholders to achieve strong performance that provides value for investors.