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.

为了减轻众筹项目的订阅失败，募捐人必须了解影响众筹项目采用的各种因素和动态行为。这项研究旨在通过了解单个客户的基本偏好来预测采用率，这些偏好会根据客户的感知风险和影响其采用的社会力量进行调整。为了评估可能增加众筹采用率的策略，该研究说明了拟议的基于数据驱动的基于代理的模型的详细实现，该模型使用AnyLogic 8.2设计并使用SPSS 17中实施的联合分析进行参数化。拟议的模型适用于众筹市场以印度为背景，并封装了各种情况下的输出统计信息。结果表明，公开有关众筹项目的风险信息是使活动成功的最重要因素。敏感性分析表明，投资者对众筹的风险规避会加快其对众筹的采用率。该研究为众筹者进行发布前的准备工作提供了见解，以进行能够影响目标受众网络的众筹活动。这项研究提出了一种独特的，基于直观的基于模拟的方法，从基于代理的角度出发，将扩展的Bass扩散模型和联合模型的概念整合在一起。敏感性分析表明，投资者对众筹的风险规避会加快其对众筹的采用率。该研究为众筹者在启动前的准备工作以建立一个影响目标受众网络的众筹运动提供了见识。这项研究提出了一种独特的，直观的，基于模拟的方法，从基于代理的角度出发，集成了扩展的Bass扩散模型和联合模型的概念。敏感性分析表明，投资者对众筹的风险规避会加快其对众筹的采用率。该研究为众筹者进行发布前的准备工作提供了见解，以进行能够影响目标受众网络的众筹活动。这项研究提出了一种独特的，基于直观的基于模拟的方法，从基于代理的角度出发，将扩展的Bass扩散模型和联合模型的概念整合在一起。