Why Tourists Avoid Peer‐to‐Peer Accommodations? Insights Into Risk, Trust, and Service Dynamics
Bibliographic record
Abstract
ABSTRACT This study examines the factors influencing tourist avoidance of peer‐to‐peer (P2P) accommodation, defined as the deliberate exclusion of such options from tourists' lodging choices. Psychological risk emerged as the strongest predictor of overall perceived risk, followed by performance and physical risks, highlighting the importance of emotional and practical concerns in shaping avoidance behavior. The overall perceived risk and the lack of cost‐saving features directly influenced tourists' decisions to avoid P2P accommodation, underscoring the significant role of economic considerations. Additionally, the lack of trust, whether directed at individual hosts or the P2P platform itself, was a key driver of avoidance. Trust in the platform indirectly affected avoidance behavior through its influence on perceived risk, illustrating its critical mediating role. These findings underscore the importance of P2P platforms in addressing safety, trust, and economic concerns, thereby reducing perceived risks and promoting the broader adoption of their services, particularly among risk‐averse travelers.
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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 | 0.005 |
| 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 | 0.003 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.003 | 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".