Investigating the Influence of ESG Information on Funding Success in Online Crowdfunding Platform by Using Text Mining Technique and Logistic Regression
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In this paper, we examine the influence of Environmental, Social, and Governance (ESG)-related content on the success of online crowdfunding proposals. Along with the increasing significance of ESG standards in business, investment proposals incorporating ESG concepts are now commonplace. Due to the ESG trend, conventional wisdom holds that the majority of proposals with ESG concepts will have a higher rate of success. We investigate by analyzing over 9000 online business presentations found in a Kickstarter dataset to determine which characteristics of these proposals led to increased investment. We first utilized lexicon-based measurement and Feature Engineering to determine the relationship between environment and society scores and financial indicators. Next, Logistic Regression is utilized to determine the effect of including environmental and social terms in a project's description on its ability to obtain funding. Contrary to popular belief, our research found that microentrepreneurs were less likely to succeed with proposals that focused on ESG issues. Our research will generate new opportunities for research in the disciplines of information science and crowdfunding by shedding new light on the environment of online micro-entrepreneurship.
Abstract
In this paper, we examine the influence of Environmental, Social, and Governance (ESG)-related content on the success of online crowdfunding proposals. Along with the increasing significance of ESG standards in business, investment proposals incorporating ESG concepts are now commonplace. Due to the ESG trend, conventional wisdom holds that the majority of proposals with ESG concepts will have a higher rate of success. We investigate by analyzing over 9000 online business presentations found in a Kickstarter dataset to determine which characteristics of these proposals led to increased investment. We first utilized lexicon-based measurement and Feature Engineering to determine the relationship between environment and society scores and financial indicators. Next, Logistic Regression is utilized to determine the effect of including environmental and social terms in a project's description on its ability to obtain funding. Contrary to popular belief, our research found that microentrepreneurs were less likely to succeed with proposals that focused on ESG issues. Our research will generate new opportunities for research in the disciplines of information science and crowdfunding by shedding new light on the environment of online micro-entrepreneurship.
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