Research Article
Reputation Signaling and Investor Trust: Implications for UMKM Funding Success on Securities Crowdfunding Platforms
@INPROCEEDINGS{10.4108/eai.16-9-2025.2361117, author={Khairunnisa Harahap and Nurul Wardhani Lubis and Dina Sarah Syahreza}, title={Reputation Signaling and Investor Trust: Implications for UMKM Funding Success on Securities Crowdfunding Platforms}, proceedings={Proceedings of the 7th International Conference on Innovation in Education, Science, and Culture, ICIESC 2025, 16 September 2025, Medan, Indonesia}, publisher={EAI}, proceedings_a={ICIESC}, year={2026}, month={3}, keywords={securities crowdfunding investor trust ipr funding succes signaling theory}, doi={10.4108/eai.16-9-2025.2361117} }- Khairunnisa Harahap
Nurul Wardhani Lubis
Dina Sarah Syahreza
Year: 2026
Reputation Signaling and Investor Trust: Implications for UMKM Funding Success on Securities Crowdfunding Platforms
ICIESC
EAI
DOI: 10.4108/eai.16-9-2025.2361117
Abstract
The emergence of securities crowdfunding (SCF) represents a crucial alternative funding channel for Micro, Small, and Medium Enterprises (MSMEs) in Indonesia. However, this market is characterized by the fundamental challenge of substantial information asymmetry, which makes it difficult for investors to accurately evaluate the quality and prospects of MSMEs. To overcome this, MSMEs need to project credible signals to foster investor trust, which is a determining factor for fundraising success. This study is designed to empirically investigate the impact of several quality signals—including Business Reputation, ownership of Intellectual Property Rights (IPR), Percentage of Shares Offered, Business Age, and the Number of Directors—on the final funding outcomes of MSMEs on SCF platforms. This research adopts a quantitative methodology, using binary logistic regression analysis on a dataset consisting of 65 MSMEs listed on Indonesian SCF platforms. The dependent variable, funding success, is dichotomously codified (1 for Success, 0 for Failure). Statistical analysis reveals that the regression model collectively has significant predictive power (Chi-square = 13.476; p = 0.019) and shows a good fit with the data (Hosmer and Lemeshow test p = 0.096). In the partial analysis, IPR ownership was identified as the sole predictor that positively and significantly increases the probability of funding success (p = 0.019), with an odds ratio reaching 8.681.
