At home and abroad: Comparing sustainable behaviour and willingness to pay across contexts
Bibliographic record
Abstract
Does a person’s everyday behavior at home influence their desire to travel sustainably and pay for it? Testing the Holmes, Dodds and Frochot (HDF) model, this research sought to understand the influence that daily behavior – measured by frugality, altruism, and pro-environmental behavior – has on both sustainable travel behavior and a traveler’s propensity to pay. This paper augments the HDF model in that it finds sustainable travel behavior to be not just a single construct, but rather influenced separately by sociocultural, environmental and local consumption behaviors. Second, this study also examines how these differences in sustainable travel influence the traveler’s propensity to pay. The findings of this study explain that day-to-day behavior at home does explain a traveler’s propensity to pay for sustainability efforts when traveling. Those who are more altruistic are more likely to be more environmentally friendly and more likely to look for local experiences when traveling. Those who are more environmentally minded at home are also more likely to seek out cultural, environmentally friendly and local experiences when traveling. In contrast, those who are more frugal are less likely to be environmentally friendly when traveling.
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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 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.002 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 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".