Making the World a Better Place: How Crowdfunding Increases Consumer Demand for Social-Good Products
Bibliographic record
Abstract
Crowdfunding has emerged as an alternative means of financing new ventures wherein a large number of individuals collectively back a project. This research specifically examines reward-based crowdfunding, in which those who take part in the crowdfunding process receive the new product for which funding is sought in return for their financial support. This work illustrates that consumers make fundamentally different decisions when considering whether to contribute their money to crowdfund versus purchase a product. Six studies demonstrate that compared with a traditional purchase, crowdfunding more strongly activates an interdependent mindset and, as a result, increases consumer demand for social-good products (i.e., products with positive social and/or environmental impact). The research further highlights that an active involvement in the crowdfunding process is necessary to increase demand for social-good products: when a previously crowdfunded product is already to market, the effect is eliminated. Finally, it is demonstrated that crowdfunding participants exhibit an increased demand for social-good products only when collective efficacy (i.e., one’s belief in the collective’s ability to bring about change) is high.
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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 | 0.001 | 0.006 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 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) | 0.007 | 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".