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Abstract

Online reviews left by guests have business value in terms of understanding customers' perceptions of hotels' product and service attributes. By focusing on customers' textual reviews through a text-mining approach (specifically, latent semantic analysis) and statistical tests, this study examined...

Author(s)
Xu Xun
Publisher
Sage Publications Ltd, London, UK
Citation
Journal of Hospitality & Tourism Research, 2019, 43, 1, pp 141-163
Abstract

Customer online reviews of hotels have significant business value in the e-commerce and big data era. Online textual reviews have an open-structured form, and the technical side, namely the linguistic attributes of online textual reviews, is still largely under-explored. Using a sample of 127,629...

Author(s)
Zhao YaBing; Xu Xun; Wang MingShu
Publisher
Elsevier Ltd, Amsterdam, Netherlands
Citation
International Journal of Hospitality Management, 2019, 76, Part A, pp 111-121
Abstract

Purpose: This study aims to investigate the online customer review behavior and determinants of overall satisfaction with hotels of travelers in various travel group compositions. Design/methodology/approach: The author collected data from online reviews of travelers in various travel group...

Author(s)
Xu Xun
Publisher
Emerald Publishing, Bingley, UK
Citation
International Journal of Contemporary Hospitality Management, 2018, 30, 3, pp 1663-1685
Abstract

Customers' online reviews play an important role in generating electronic word of mouth; these reviews serve as an online communication tool that highly influences consumers' demand for hotels. Using latent semantic analysis, which is a text mining approach, we analyze online customer reviews of...

Author(s)
Xu Xun; Li YiBai
Publisher
Elsevier Ltd, Amsterdam, Netherlands
Citation
International Journal of Hospitality Management, 2016, 55, pp 57-69