Investigating Factors Affecting the Success of the Initial Coin Offering method with the Random Forest Algorithm

At the current time, the aggravation of the problem of stagflation in the country has caused more emphasis on all policies of the supply-side, and on top of that, the financing of entrepreneurs with an emphasis on reducing inflation. The initial coin offering method is a new method for financing businesses based on blockchain technology, which realizes the possibility of attracting high capital in a short time compared to other methods. In the meantime, small and medium-sized enterprises that, despite the need for small levels of resources, have an undeniable role in production of Countries, can be good candidates for applying this method. The explanation of this method and the identification of factors affecting its success to solve the existing information gaps can provide the process of perfect use and benefiting from its potentials. Therefore, in this article, by collecting 307 ICO in 2016 to the end of 2018, the factors influencing their success-include the characteristics of the team, project, campaign and social networks- in a cumulative process by Random Forest algorithm has been investigated. In the recent article, the total raised capital and Percentage of hard cap raised has been considered as a criterion of success in two series of separate models. By dividing the level of priority of the features into three levels, the findings show that three features of the total number of project tokens, the number of white paper pages, the clarity of the team's share of the token have the priority of level one and have the highest role in the success of an ICOs campaign.