Investor Intention in Equity Crowdfunding. Does Trust Matter?
Bibliographic record
Abstract
Equity crowdfunding (ECF) is becoming a convenient alternative instrument for investing in entrepreneurs’ projects in many countries. The purpose of this study was to investigate the factors that affect the investor’s intentions toward ECF platforms in Saudi Arabia, where they have not been introduced until very recently. This context offers a unique opportunity to test the role of investors’ perceived trust in the context of ECF. The proposed framework builds on two critical layers: (1) trust in the platform (intermediary) and (2) trust in the fundraiser. Structured equation modelling was applied to examine the factors that affect investors’ trust and intentions. The framework was analysed using survey data from 216 users of Manafa, one of the largest ECF platforms in Saudi Arabia. Our findings showed that both fundraiser and platform trust have a significant effect on the investor’s intentions. In particular, trust in the platform substantially impacts the fundraiser’s trust, showing the importance of the fundraiser’s reliance on trusted institutions. On the other hand, to build investors’ trust, fundraisers must deliver high-quality information for their projects.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.003 | 0.018 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.002 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.003 | 0.000 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".