Abstract
Purpose: This study aims to compare the rating dynamics of the same hotels in two online review platforms (Booking.com and Trip Advisor), which mainly differ in requiring or not requiring proof of prior reservation before posting a review (respectively, a verified vs a non-verified platform).
Design/methodology/approach: A verified system, by definition, cannot host fake reviews. Should also the non-verified system be free from “ambiguous” reviews, the structure of ratings (valence, variability, dynamics) for the same items should also be similar. Any detected structural difference, on the contrary, might be linked to a possible review bias.
Findings: Travelers’ scores in the non-verified platform are higher and much more volatile than ratings in the verified platform. Additionally, the verified review system presents a faster convergence of ratings towards the long-term scores of individual hotels, whereas the non-verified system shows much more discordance in the early phases of the review window.
Research limitations/implications: The paper offers insights into how to detect suspicious reviews. Non-verified platforms should add indices of scores’ dispersion to existing information available in websites and mobile apps. Moreover, they can use time windows to delete older (and more likely biased) reviews. Findings also ring a warning bell to tourists about the reliability of ratings, particularly when only a few reviews are posted online.
Originality/value: The across-platform comparison of single items (in terms of ratings’ dynamics and speed of convergence) is a novel contribution that calls for extending the analysis to different destinations and types of platform.
Design/methodology/approach: A verified system, by definition, cannot host fake reviews. Should also the non-verified system be free from “ambiguous” reviews, the structure of ratings (valence, variability, dynamics) for the same items should also be similar. Any detected structural difference, on the contrary, might be linked to a possible review bias.
Findings: Travelers’ scores in the non-verified platform are higher and much more volatile than ratings in the verified platform. Additionally, the verified review system presents a faster convergence of ratings towards the long-term scores of individual hotels, whereas the non-verified system shows much more discordance in the early phases of the review window.
Research limitations/implications: The paper offers insights into how to detect suspicious reviews. Non-verified platforms should add indices of scores’ dispersion to existing information available in websites and mobile apps. Moreover, they can use time windows to delete older (and more likely biased) reviews. Findings also ring a warning bell to tourists about the reliability of ratings, particularly when only a few reviews are posted online.
Originality/value: The across-platform comparison of single items (in terms of ratings’ dynamics and speed of convergence) is a novel contribution that calls for extending the analysis to different destinations and types of platform.
| Original language | English |
|---|---|
| Journal | International Journal of Culture, Tourism and Hospitality Research |
| Early online date | 26 Feb 2020 |
| DOIs | |
| Publication status | Early online - 26 Feb 2020 |
Keywords
- online review
- e-word-of-mouth
- rating convergence
- verified review platforms
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Data availability statement for 'A comparison of hotel ratings between verified and non-verified online review platforms'.
Figini, P. (Creator), Vici, L. (Creator) & Viglia, G. (Creator), University of Portsmouth, 26 Feb 2020
Dataset