What can big data and text analytics tell us about hotel guest experience and satisfaction?
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Insight generated through a strong BDAC allows better understanding of consumer behavior, interactions, and experiences with a product or service.
“allow for a better understanding of consumer behavior, interactions, and experiences with a product or service [77,78]”
From Exploring the relationship between big data analytics capability and competitive performance: The mediating roles of dynamic and operational capabilities (2020) · cites this paper as [78]
Big data provides a huge amount of detail that contains deep-structure information on experiences, feelings, interests and opinions.
“Studies, such as those of Marine-Roig and Clavé [47] and Xiang et al. [74], suggested that big data provides a huge amount of detail that contains deep-structure information on experiences, feelings, interests and opinions.”
From A Big Data Analytics Method for Tourist Behaviour Analysis (2017) · cites this paper as [74]
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- Authors
- Xiang, Z., Schwartz, Z., Gerdes, J. H., & Uysal, M.
- Affiliations
- Virginia Tech (US)
- University of Delaware (US)
- University of South Carolina (US)
- Corresponding author
- Xiang, Zheng
- Venue
- International Journal of Hospitality Management
- Publisher
- Elsevier BV
- Published
- 2015-01
- Volume
- 44
- Pages
- 120-130
- ISSN
- 0278-4319 (ISSN-L)
- OpenAlex
- W1992777957
- Cited by
- 953
- References
- 64
- Citations by year
- 2026: 62 · 2025: 80 · 2024: 66 · 2023: 92 · 2022: 117 · 2021: 120 · 2020: 107 · 2019: 111 · 2018: 66 · 2017: 73 · 2016: 41 · 2015: 16 · 2014: 2
- FWCI
- 96.77
- Type
- journal article
- Language
- en
- Open access
- closed
- Locations
- International Journal of Hospitality Management (publishedVersion)
- eSpace (Curtin University) (submittedVersion)
- Topics
- Social Sciences › Business, Management and Accounting › Organizational Behavior and Human Resource Management › Customer Service Quality and Loyalty
- Social Sciences › Sociology and Political Science › Digital Marketing and Social Media
- Social Sciences › Sociology and Political Science › Diverse Aspects of Tourism Research
- Keywords
- hotel guest experience, guest satisfaction, big data analytics, text analysis, consumer reviews, Expedia, user-generated content, social media, semantic composition, hospitality
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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.
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