The role of trust and e-WOM in the crowdfunding participation: the case of equity crowdfunding platforms in financial services in Iran
Why this work is in the frame
A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.
Bibliographic record
Abstract
Purpose The aim of this research is to examine the roles of trust and electronic word-of-mouth (e-WOM) in crowdfunding (CF) participation for equity CF by taking into account the following antecedents of trust and e-WOM: intrinsic motivation (IM), extrinsic motivation (EM), deterrents, venture quality (VQ), third-party seal (TPS), value congruence (VC) and perceived accreditation (PA). Design/methodology/approach In this research, a survey among 408 active and potential funders in Iran was conducted. The statistical analysis used partial least squares structural equation modeling (PLS-SEM). Findings The results of this research revealed a significant influence of trust and e-WOM on participation in CF for equity CF. Extrinsic motivation had the greatest impact on trust and VC had the greatest impact on e-WOM. Originality/value This research extends the equity CF research area to CF success and considers the effects of some parameters on CF participation. This research provides many theoretical and practical implications.
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Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.003 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 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 it