Which Factors Can Contribute to the Success of Environmental and Animal Protection Projects in Donation-based Crowdfunding? A Neural Network Model

Abstract

The crowdfunding industry has developed rapidly in recent years, the existing research shows that crowdfunding can help in many fields such as entrepreneurship, creative products, or donations. Due to global meteorological issues, more and more people are paying attention to the environment and animal protection. However, fundraising in these areas has been the biggest problem, the emergence of donation crowdfunding (DCF) can alleviate this dilemma. Currently, in academia, there is still less research focused on crowdfunding for environmental and animal protection. This paper aims to study the factors influencing the successful financing of environmental and animal protection projects in the DCF.

This paper analyses 700 DCF environmental and animal protection projects in China as samples, and creatively introduces financial transparency scoring indicators. Through binary logistic regression, financial transparency was found to be the most critical positive factor affecting project success. At the same time, donors receive NPO-initiated projects well, and the number of donors can also positively impact the results. However, the excessive description of the projects can have the opposite effect. This study also introduced a neural network model, and found that the neural network model can optimize the discriminant accuracy of the traditional binary logistic regression model.