Go Fund Yourselves! Predicting the Likelihood of Obtaining Capital Through Online Crowdfunding
Year: 2021
Type: article
Abstract: This study explores the various endogenous factors that affect the likelihood of obtaining required capital (LORC) for online crowdfunding platform projects in Kickstarter and The Spark Project.These factors include amount of capital required, campaign length, currency, Facebook length, currency, Facebook connectivity, month of launch, number of FAQs, number of images, number of reward levels, number of updates, number of videos, and product market category.Using linear discriminant analysis, the researchers found that currency has a discriminating power towards global platforms, while number of FAQs and month of launch have a discriminating power towards local platforms.Likewise, using logistic regression, the researchers found that amount of capital required, number of FAQs, number of updates, and product market category are highly significant (α = 0.01) under global platforms (i.e.represented by Kickstarter).In local platforms (i.e.represented by The Spark Project), none of the variables were highly significant, but amount of capital required was very significant (α = 0.05).The study also takes into account the insights of three key stakeholders who had firsthand experience with online crowdfunding, particularly in Kickstarter and/or The Spark Project.All three respondents gave insights on each of the variables, identifying some with significant impact on LORC.For Kickstarter, all three agreed that amount of capital required, campaign length, number of images, and number of videos are significant.For The Spark Project, all three concurred that amount of capital required, Facebook connectivity, number of videos, and product market category have significant impact.They also identified three new variables: story, crowd, and product.With such insights, this study may help aspiring entrepreneurs in the Philippines launch projects successfully through online crowdfunding.The researchers developed a machine learning program based on the results of the statistical analysis of this study, which will be turned into an application that determines the likelihood of a project's success at obtaining LORC and its suitability in local or global platforms based on project features inputted by the user.This will be released as a product for entrepreneurs as a means of helping them plan their project campaigns for success should they set out to access online crowdfunding.
Language: English
Subfield: Management Information Systems
Domain: Social Sciences
Open Access status: bronze
OpenAlex ID: W3192906522