Analyzing changes in hotel customers' expectations by trip mode

Liu, S; Law, R; Rong, J; Li, G; Hall, J

Analyzing changes in hotel customers' expectations by trip mode

Liu, S

Law, R Rong, J Li, G Hall, J

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Publication Type:: Journal Article
Citation:: International Journal of Hospitality Management, 2013, 34 (1), pp. 359 - 371
Issue Date:: 2013-09-01

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Field	Value	Language
dc.contributor.author	Liu, S https://orcid.org/0000-0001-6062-6580	en_US
dc.contributor.author	Law, R	en_US
dc.contributor.author	Rong, J	en_US
dc.contributor.author	Li, G	en_US
dc.contributor.author	Hall, J	en_US
dc.date.issued	2013-09-01	en_US
dc.identifier.citation	International Journal of Hospitality Management, 2013, 34 (1), pp. 359 - 371	en_US
dc.identifier.issn	0278-4319	en_US
dc.identifier.uri	http://hdl.handle.net/10453/123230
dc.description.abstract	With the emergence of Web 2.0, electronic word-of-mouth (eWOM) shared through social networking sites has become the primary information source for many travelers. An enormous quantity of reviews has been posted by customers, and has become a valuable means by which hoteliers can better understand customer satisfaction and expectations. Efforts have been made to analyze these parameters in terms of customers' backgrounds. Although customer expectations vary according to background, whether or not this is still the case across different trip modes remains unknown. In this study, an eWOM dataset was obtained from an online source and sentiment mining used to improve its quality by imputing missing values. A complete analysis of customer profiles and their contrast by trip mode was then conducted using association rule mining. The empirical results demonstrate differences in both customer expectation and satisfaction when the same traveler engages in different trip modes. © 2012 Elsevier Ltd.	en_US
dc.relation.ispartof	International Journal of Hospitality Management	en_US
dc.relation.isbasedon	10.1016/j.ijhm.2012.11.011	en_US
dc.subject.classification	Sport, Leisure & Tourism	en_US
dc.title	Analyzing changes in hotel customers' expectations by trip mode	en_US
dc.type	Journal Article
utslib.citation.volume	1	en_US
utslib.citation.volume	34	en_US
utslib.for	1506 Tourism	en_US
utslib.for	1504 Commercial Services	en_US
utslib.for	1505 Marketing	en_US
pubs.embargo.period	Not known	en_US
pubs.organisational-group	/University of Technology Sydney
pubs.organisational-group	/University of Technology Sydney/Faculty of Engineering and Information Technology
pubs.organisational-group	/University of Technology Sydney/Faculty of Engineering and Information Technology/School of Computer Science
pubs.organisational-group	/University of Technology Sydney/Strength - AAI - Advanced Analytics Institute Research Centre
utslib.copyright.status	open_access
pubs.issue	1	en_US
pubs.publication-status	Published	en_US
pubs.volume	34	en_US

Abstract:

With the emergence of Web 2.0, electronic word-of-mouth (eWOM) shared through social networking sites has become the primary information source for many travelers. An enormous quantity of reviews has been posted by customers, and has become a valuable means by which hoteliers can better understand customer satisfaction and expectations. Efforts have been made to analyze these parameters in terms of customers' backgrounds. Although customer expectations vary according to background, whether or not this is still the case across different trip modes remains unknown. In this study, an eWOM dataset was obtained from an online source and sentiment mining used to improve its quality by imputing missing values. A complete analysis of customer profiles and their contrast by trip mode was then conducted using association rule mining. The empirical results demonstrate differences in both customer expectation and satisfaction when the same traveler engages in different trip modes. © 2012 Elsevier Ltd.

Please use this identifier to cite or link to this item:

http://hdl.handle.net/10453/117416