Willingness-To-Pay vs Actual Behavior: Sustainable Procurement at Festivals
Bibliographic record
Abstract
Sales and purchases of socially and environmentally responsible festival clothing are a way for festival attendees to engage in ethical consumption and for event organizers to undertake sustainable procurement. Although there have been a number of studies examining willingness-to-pay (WTP), few of them examine this in a festival setting, and there is a gap in existing research regarding the determination of actual behavior. The goal of this study is therefore to explore participants’ willingness-to-pay for apparel based on more external motivations (visible environmental messages) and then ascertain whether this behavior was actually replicated in a natural field setting. This study first collected surveys from 427 festival-goers in 2015, then used a natural field experiment in 2016 to investigate whether attendees at the Mariposa Folk Festival in Ontario, Canada, would actually be prepared to pay a premium for ethical festival T-shirts over a conventional alternative. The findings reveal that attendees not only showed a willingness-to-pay but they also did actually pay a premium for such T-shirts.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.004 | 0.012 |
| 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) | 0.006 | 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".