The Role of Project Description in the Success of Sustainable Crowdfunding Projects
Bibliographic record
Abstract
Crowdfunding nowadays has become a significant source of financing for all those entrepreneurs who require funds to start their operations, specifically for social ventures. Furthermore, determining what factors decide whether a project will successfully raise funds is a very relevant question. Past literature has examined various factors that influence fundraising success. Of these factors, information efficiency is the determinant of successful fundraising due to precise project descriptions and effective message delivery. Despite this fact, few studies have investigated how such project descriptions affect the success of crowdfunding campaigns, specifically sustainable projects. The present study tries to fill this gap by examining the relation between the length and readability of the crowdfunding project descriptions and the success rate for sustainable projects in a reward-based model. For the analysis, data were obtained from Kickstarter, the largest crowdfunding platform in the world, with a sample of 12,613 projects, employing a multiple logistic regression model. The results show that the word count and readability of the project descriptions are positively related to crowdfunding success. Furthermore, the analysis shows that using more words related to SDG keywords results in positive fundraising. Such insights reflect that good project descriptions are important for crowdfunding success and, on the theoretical level, provide practical value for project owners.
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How this classification was reachedexpand
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 | 0.002 | 0.000 |
| 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 | 0.000 | 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 itClassification
machine, unvalidatedMachine predicted; a candidate call from one teacher head, 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".