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A person‐centred view of citizen participation in civic crowdfunding platforms: A mixed‐methods study of civic backers.
- Source :
- Information Systems Journal; Sep2024, Vol. 34 Issue 5, p1626-1663, 38p
- Publication Year :
- 2024
-
Abstract
- Crowdfunding platforms have emerged as a promising contemporary means for mobilising collective civic actions to address local or social issues, improve community cohesion and develop the public good. This empirical study taps into the understudied civic crowdfunding platforms (CCP) developed to facilitate such actions, proposing, supporting and funding public‐interest projects through crowdsourcing and microfinancing. Previous studies have shown that individuals' characteristics affect their level of civic engagement with social issues. Considering the diversity of contributor motivations, we aim to shed light on the dynamics of emergent subpopulations of citizens who participate in CCPs. To this end, we use a sequential mixed‐methods approach to integrate our fuzzy set Qualitative Comparative Analysis (fsQCA) findings with the results of an in‐depth qualitative study, to gain rich and robust inferences and meta‐inferences. In Study 1 (n = 316), we used fsQCA to explore five distinctive configural profiles that display the heterogeneity of civic backers' motivations, including civic champions, prosocial advocates, normative supporters, reward seekers and regret‐averse contributors. In Study 2, we corroborated and complemented our fsQCA inferences through an extreme‐case study and identified four boundary conditions. Taken together, our inferences and meta‐inferences address the heterogeneity of motivations for participating in CCPs, by understanding and theorising about diverse profiles of citizen backers. Finally, we offer practical implications for successful civic crowdfunding initiatives. [ABSTRACT FROM AUTHOR]
- Subjects :
- POLITICAL participation
FUZZY sets
COLLECTIVE action
LOCAL government
CROWD funding
Subjects
Details
- Language :
- English
- ISSN :
- 13501917
- Volume :
- 34
- Issue :
- 5
- Database :
- Complementary Index
- Journal :
- Information Systems Journal
- Publication Type :
- Academic Journal
- Accession number :
- 178910518
- Full Text :
- https://doi.org/10.1111/isj.12503