New consumer behavior: A review of research on eWOM and hotels
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Each is checked against this paper’s own text: does it say what the citing paper says it does?
As the number of online information increases, searching, manipulating and aggregating data to extract relevant insights about tourists' attitude, behaviour and experience quality becomes tedious and time-consuming for travellers, industry users, and researchers.
“However, as the number of online information is increasing at an extremely fast pace, searching, manipulating and aggregating the data to extract relevant and useful insights about tourists' attitude, behaviour and experience quality becomes a tedious and time-consuming task for both, travellers and industry users as well as professional and academic researchers (Cantallops & Salvi, 2014;Ellion, 2”
From Sentiment Analysis in Tourism: Capitalizing on Big Data (2019) · cites this paper as Cantallops & Salvi, 2014
Social media and blogs nowadays complement opinions attained from relatives, friends, colleagues, and official sources.
“Therefore, social media and blogs nowadays complements opinions attained from relatives, friends, colleagues, and official sources (Cantallops & Salvi, 2014;Chua & Banerjee, 2013;Filieri et al., 2015;Hepburn, 2007;Mack et al., 2008).”
From Sentiment Analysis in Tourism: Capitalizing on Big Data (2019) · cites this paper as Cantallops & Salvi, 2014
Cites
The Discovery of Grounded Theory; Strategies for Qualitative Research
Glaser, B. G., Strauss, A. L., & Strutzel, E. (1968) · Nursing Research · doi:10.1097/00006199-196807000-00014 · Cited by 39,449 · see citing works
The impact of online reviews on hotel booking intentions and perception of trust
Sparks, B. A., & Browning, V. (2011) · Tourism Management · doi:10.1016/j.tourman.2010.12.011 · Cited by 1,688 · see citing works
Harrison-Walker, L. J. (2001) · Journal of Service Research · doi:10.1177/109467050141006 · Cited by 1,583 · see citing works
Flagged first, then by citations
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Sorted by citations
What can big data and text analytics tell us about hotel guest experience and satisfaction?
Xiang, Z., Schwartz, Z., Gerdes, J. H., & Uysal, M. (2015) · International Journal of Hospitality Management · doi:10.1016/j.ijhm.2014.10.013 · Cited by 953 · see citing works
Sentiment Analysis in Tourism: Capitalizing on Big Data
Alaei, A. R., Becken, S., & Stantic, B. (2019) · Journal of Travel Research · doi:10.1177/0047287517747753 · Cited by 622 · see citing works
What makes an online consumer review trustworthy?
Filieri, R. (2016) · Annals of Tourism Research · doi:10.1016/j.annals.2015.12.019 · Cited by 587 · see citing works
Xu, Y., Du, J., Shahzad, F., & Li, X. (2021) · Frontiers in Psychology · doi:10.3389/fpsyg.2021.724452 · Cited by 52 · see citing works
Satisfaction measures with monetary and non-monetary components: hotel’s overall scores
Nicolau, J. L., Mellinas, J. P., & Martín-Fuentes, E. (2020) · International Journal of Hospitality Management · doi:10.1016/j.ijhm.2020.102497 · Cited by 33 · see citing works
- Authors
- Serra Cantallops, A., & Salvi, F.
- Affiliations
- Universitat de les Illes Balears (ES)
- Venue
- International Journal of Hospitality Management
- Publisher
- Elsevier BV
- Published
- 2014-01
- Volume
- 36
- Pages
- 41-51
- ISSN
- 0278-4319 (ISSN-L)
- OpenAlex
- W2010599172
- Cited by
- 884
- References
- 3
- Citations by year
- 2026: 23 · 2025: 46 · 2024: 62 · 2023: 108 · 2022: 80 · 2021: 94 · 2020: 116 · 2019: 103 · 2018: 83 · 2017: 63 · 2016: 61 · 2015: 29 · 2014: 15 · 2013: 1
- FWCI
- 109.45
- Type
- journal article
- Language
- en
- Open access
- closed
- Locations
- International Journal of Hospitality Management (publishedVersion)
- Topics
- Social Sciences › Sociology and Political Science › Digital Marketing and Social Media
- Social Sciences › Sociology and Political Science › Diverse Aspects of Tourism Research
- Social Sciences › Business, Management and Accounting › Marketing › Consumer Behavior and Marketing Influence
- Keywords
- electronic word of mouth, online reviews, hotel industry, consumer behavior, hotel marketing
About these checks
Registry, retraction, Cites and statistics results are computed, not judged, with one exception: a printed reference that no index lists is read once by a model before it counts as a citation error. Claims are extracted by a model and kept only when their quote appears verbatim in the text; each cited source is then checked, with a model’s help, for whether it says what the claim relies on. Those verdicts can be wrong — read the claim’s quote and the cited source before relying on one.
Statistics and arithmetic are recomputed, not judged.
Confidence bands are shown only for fields calibrated on our annotated test set. None is calibrated yet, so no band is shown.
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