A signalling paradigm incorporating an Agent-Based Model for simulating the adoption of crowd funding technology

In order to mitigate the unsuccessful subscription of crowdfunding projects, it is critical for the fundraisers to understand various factors and dynamic behaviours affecting the adoption of crowdfunding projects. This study aims to forecast the adoption rate by understanding the underlying preferences of individual customers which is adjusted to their perceived risk and social forces influencing their adoption. To evaluate strategies that could potentially increase crowdfunding adoption, the study illustrates a detailed implementation of the proposed data-driven agent-based model, designed using AnyLogic 8.2 and parameterised using Conjoint Analysis implemented in SPSS 17. The proposed model is applied to a crowdfunding market in an Indian context and encapsulates the output statistics under various scenarios. The results indicate that disclosing the risk information about the crowdfunding project is the most important factor in making the campaign successful. Sensitivity analysis shows that investor's risk aversion towards crowdfunding accelerates their adoption rate of crowdfunding. The study provides an insight for the crowdfunders in making pre-launch preparations to build a crowdfunding campaign that influences a network of target audience. This study presents a unique, intuitive simulation-based approach, integrating the concepts of an extended Bass Diffusion Model and the Conjoint Model from an agent-based perspective.