Crowdfunding Participation Model Development and Empirical Analysis: A Two-Sided Membership Platform Framework

Abstract

Crowdfunding is an activity of customer participation in the form of financial support for a target project. Despite its importance in both research and practice, however, the nature of crowdfunding platform and its impact on business and society are not fully understood. Therefore, in this study, we intend to build a conceptual model of the crowdfunding process for understanding its nature and working mechanism and 2) to uncover the dynamics among creators, projects, and sponsors in the crowdfunding platform. Based on reviews of the related literature and the theoretical framework of the two-sided membership platform (TSMP), we developed the Crowdfunding Participation Model (CPM). In the CPM, we modeled how creators and sponsors were linked thorough projects in the crowdfunding platform.

In Study 1, on the basis of the CPM, we proposed a research model linking creator motivations, project characteristics, sponsor motivations, and funding behavior. We empirically validated the relationships by combining survey data from creators and sponsors of the crowdfunding platform and diverse transaction data. And, from the result of analysis, we found the important variables, relationships, and paths in the CPM. Additionally, we found the critical project characteristics in predicting performance of the crowd-funded projects with aggregated data at the project level.

In Study 2, we developed a typology of crowdfunding platform users based on their motivations by conducting a cluster analysis. And we further analyzed the characteristics of each cluster by ANOVA test with user-related variables and project-related variables. The result indicates that creators and sponsors in the CP are categorized into four types, respectively. We showed each cluster displays distinguished characteristics and different behav-iors in the CP. Furthermore, we also identified the significant relationships between creator clusters and sponsor clusters by crosstab analysis.