Investigating Factors Influencing the Success of Initial Coin Offerings Using Logistic Regression

Financing remains one of the most critical aspects of business growth and sustainability. The Initial Coin Offering (ICO) method, a novel approach to financing leveraging blockchain technology, has garnered attention due to its ability to attract significant capital globally within a short period and without requiring intermediaries. Understanding and analyzing the factors that influence the success or failure of ICOs is thus valuable for businesses and investors alike. This paper examines the factors impacting ICO success using logistic regression analysis, focusing on 307 completed ICO projects from 2016 to 2018. We consider two target success variables: "Total funds collected" and "Hard cap achievement percentage." Factors related to the project, campaign, social networks, and team characteristics were analyzed in separate models. Through model selection based on performance and feature prioritization using the Permutation Importance (PI) technique, the findings highlight that having a well-defined "Business model available" significantly contributes to ICO success across both models. Additionally, the top features in the first selected model under the categories of project, campaign, and social network are "White paper pages," "Token share for presale investors," and "GitHub account," respectively. In the second model, the most impactful factors are "Use of proceeds mentioned" and "Length of crowdsale" under the project and campaign categories.