Customer satisfaction scores: New models to estimate the number of fake reviews
Tourism Management, ISSN: 0261-5177, Vol: 106, Page: 105030
2025
- 1Citations
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Example: if you select the 1-year option for an article published in 2019 and a metric category shows 90%, that means that the article or review is performing better than 90% of the other articles/reviews published in that journal in 2019. If you select the 3-year option for the same article published in 2019 and the metric category shows 90%, that means that the article or review is performing better than 90% of the other articles/reviews published in that journal in 2019, 2018 and 2017.
Citation Benchmarking is provided by Scopus and SciVal and is different from the metrics context provided by PlumX Metrics.
Article Description
In this paper we develop new models for the distribution of customer satisfaction scores. This leads to new approaches for estimating the number of fake reviews in empirical data. Modifications of the basic model are presented that account for the propensity of extreme positive and negative reviews, and a potential lack of engagement on the part of reviewers. Further work to incorporate price and cultural effects is proposed.
Bibliographic Details
Elsevier BV
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