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Record W2587840773 · doi:10.1080/10548408.2016.1224750

Understanding repurchase intention of Airbnb consumers: perceived authenticity, electronic word-of-mouth, and price sensitivity

2017· article· en· W2587840773 on OpenAlex

Why this work is in the frame

A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.

affAt least one author lists a Canadian institution in the pinned OpenAlex snapshot.
aboutThe title or abstract carries a Canadian signal from the geographic lexicon.

Bibliographic record

VenueJournal of Travel & Tourism Marketing · 2017
Typearticle
Languageen
FieldBusiness, Management and Accounting
TopicSharing Economy and Platforms
Canadian institutionsUniversity of Guelph
Fundersnot available
KeywordsRisk perceptionBusinessContext (archaeology)Value (mathematics)AdvertisingMarketingWord of mouthConsumer behaviourRealmPsychologyPerceptionGeography

Abstract

fetched live from OpenAlex

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.

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.

Full frame distilled prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.

metaresearch head score (Codex)0.004
metaresearch head score (Gemma)0.001
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.207
Threshold uncertainty score0.562

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0040.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.001
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0000.000

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.

Opus teacher head0.055
GPT teacher head0.252
Teacher spread0.197 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it