Understanding repurchase intention of Airbnb consumers: perceived authenticity, electronic word-of-mouth, and price sensitivity
Bibliographic record
Abstract
The purpose of this paper is to extend the research on consumer repurchase intention, perceived value, and perceived risk into the realm of the peer-to-peer economy, specifically in the context of Airbnb. A total of 395 surveys were collected in Canada and the United States. The results showed that perceived risk negatively impacts Airbnb consumers’ perceived value and repurchase intention while perceived value positively enhances their repurchase intention. Interestingly, price sensitivity was found not to reduce customers’ perceived risk but can improve their perceived value and positively influences them to repurchase the Airbnb products. Perceived authenticity was found to have a significant effect in reducing Airbnb consumers’ perceived risk and positively influencing their perceived value. Electronic word-of-mouth has a positive effect on repurchase intention as well as perceived value whereas it negatively affects perceived risk. Theoretical and managerial implications are discussed and future study directions are offered.
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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 | 0.009 |
| 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 | 0.001 |
| Scholarly communication | 0.002 | 0.002 |
| 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".