Identifying Principal Investors in Crowdfunding Initiatives for E-Commerce Entrepreneurship: An Integrated BTS Framework

The phenomenon of followership is widely observed in the e-commerce industry. Crowdfunding, as a model of e-commerce entrepreneurship, has attracted many investors. Principal investors function as “leaders” who exert influence on follow-on (subsequent) investors. Accurately identifying principal investors in online entrepreneurial ventures and analyzing their preferences could enhance the success rate of fundraising. Grounded in the BTS (Behavior–Text–Social) framework, this study constructs a multi-dimensional model comprising 15 sub-indicators across three domains: user behavior, textual data, and social connections. A neural network is employed for training and prediction. By integrating the central and peripheral routes elicited from the Elaboration Likelihood Model (ELM), which ranks influence, principal investors are identified. The experiment results indicate that ELM-derived ranking demonstrates the highest consistency (error = 0.15), followed by user behavior (error = 0.30), social metrics (error = 0.71), and textual features (error = 0.95). Weight analysis using SHAP highlights the relative importance of structural holes, out-degree centrality, investment times, and investment moments. Furthermore, principal investors exhibit a preference for local projects and occupy dual roles. This study provides a theoretical foundation and practical guidance for identifying principal investors, thereby improving financing performance and mitigating investment risks for follow-on investors.