Impact of FinTech intelligent recommendation systems on crowdfunding success in China: a trust and system quality perspective

Purpose This study aims to investigate the influence of intelligent recommendation systems on crowdfunding success within China’s crowdfunding platforms. By developing a comprehensive theoretical framework that integrates the Information Systems Success Model, Dynamic Capabilities Theory, Signaling Theory, and Trust Theory, the research explores how these systems enhance project-investor matching, foster user trust, and ultimately enhance project financing success rates. Design/methodology/approach Adopting a positivist philosophy and quantitative methodology, the study collected data through a structured survey questionnaire distributed to users of Chinese crowdfunding platforms that utilize intelligent recommendation systems. A total of 302 valid responses were analyzed using structural equation modeling to test the hypothesized constructs and relationships in the proposed research model. Findings The findings have shown that intelligent recommendation systems significantly enhance crowdfunding success by enhancing system quality, information quality, signaling effectiveness, trust, and user engagement. Social influence was found to moderate the relationships between these factors and crowdfunding success, amplifying their positive effects. Practical implications The research provides empirical evidence and strategies for crowdfunding platforms to optimize their intelligent recommendation systems. By improving system and information quality and strengthening trust mechanisms, platforms can enhance user engagement and increase project success rates. These insights are valuable for platform developers and policymakers aiming to leverage technology to overcome market-specific challenges in China’s crowdfunding industry. Originality/value This study constructs an integrated theoretical model that elucidates how intelligent recommendation systems influence crowdfunding success, addressing a gap in the existing literature. By synthesizing multiple theories, the research offers novel academic perspectives and practical insights, advancing theoretical understanding and practical application of FinTech in crowdfunding, and providing actionable recommendations for practitioners and policymakers.

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Publication Details

Journal
International Journal of Bank Marketing
Published
2025-09-08
DOI
https://doi.org/10.1108/ijbm-12-2024-0733
Primary Topic
FinTech, Crowdfunding, Digital Finance
Type
article
Field-Weighted Citation Impact
0.00
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article

Impact of FinTech intelligent recommendation systems on crowdfunding success in China: a trust and system quality perspective

Ibrahim Othman, Yunfeng Wang
International Journal of Bank Marketing
FinTech, Crowdfunding, Digital Finance
article

Impact of FinTech intelligent recommendation systems on crowdfunding success in China: a trust and system quality perspective

Ibrahim Othman, Yunfeng Wang
article en

Abstract

Purpose This study aims to investigate the influence of intelligent recommendation systems on crowdfunding success within China’s crowdfunding platforms. By developing a comprehensive theoretical framework that integrates the Information Systems Success Model, Dynamic Capabilities Theory, Signaling Theory, and Trust Theory, the research explores how these systems enhance project-investor matching, foster user trust, and ultimately enhance project financing success rates. Design/methodology/approach Adopting a positivist philosophy and quantitative methodology, the study collected data through a structured survey questionnaire distributed to users of Chinese crowdfunding platforms that utilize intelligent recommendation systems. A total of 302 valid responses were analyzed using structural equation modeling to test the hypothesized constructs and relationships in the proposed research model. Findings The findings have shown that intelligent recommendation systems significantly enhance crowdfunding success by enhancing system quality, information quality, signaling effectiveness, trust, and user engagement. Social influence was found to moderate the relationships between these factors and crowdfunding success, amplifying their positive effects. Practical implications The research provides empirical evidence and strategies for crowdfunding platforms to optimize their intelligent recommendation systems. By improving system and information quality and strengthening trust mechanisms, platforms can enhance user engagement and increase project success rates. These insights are valuable for platform developers and policymakers aiming to leverage technology to overcome market-specific challenges in China’s crowdfunding industry. Originality/value This study constructs an integrated theoretical model that elucidates how intelligent recommendation systems influence crowdfunding success, addressing a gap in the existing literature. By synthesizing multiple theories, the research offers novel academic perspectives and practical insights, advancing theoretical understanding and practical application of FinTech in crowdfunding, and providing actionable recommendations for practitioners and policymakers.

International Journal of Bank MarketingVol. 44(2)
University of Technology Malaysia (MY), Universiti Teknologi MARA (MY)
Openalex Percentile: Top 49%
FinTech, Crowdfunding, Digital Finance
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