Title of Paper

Understanding Hotel Guest Experience: A Text-Mining Approach

Author Bios (50 Words)

Ms. Lena Liang is a PhD candidate at the University of Guelph in Canada. Her research interests include consumer behaviour in tourism and hospitality, tourism economic impact analysis, smart tourism and research methods in tourism and hospitality.

Abstract (150 Words)

The objective of this study is to explore the group differences of consumers in handling service failures in the hotel industry via a text-mining approach. Distinguishing from previous studies which used data either from third parties like tripadvisor.com or surveys from random customers, this study obtained a nine-year longitudinal dataset directly from an internationally recognized hotel chain. A total of 1,224 observations were analyzed with the text mining and Natural Language Processing (NLP) technique. A series of analyses were conducted to explore the hidden information from the massive amount of unstructured text data. The results revealed that gender demonstrated group difference in reporting service failure. Female travelers are more sensitive to affective feelings in a hotel stay while males concern more about facilities/amenities experience. Purpose of stay also affects how consumers deal with service failure. Leisure travelers are found to be more price sensitive and likely to have issues with the usage of coupons. Theoretical and practical implications are also discussed.

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Understanding Hotel Guest Experience: A Text-Mining Approach

The objective of this study is to explore the group differences of consumers in handling service failures in the hotel industry via a text-mining approach. Distinguishing from previous studies which used data either from third parties like tripadvisor.com or surveys from random customers, this study obtained a nine-year longitudinal dataset directly from an internationally recognized hotel chain. A total of 1,224 observations were analyzed with the text mining and Natural Language Processing (NLP) technique. A series of analyses were conducted to explore the hidden information from the massive amount of unstructured text data. The results revealed that gender demonstrated group difference in reporting service failure. Female travelers are more sensitive to affective feelings in a hotel stay while males concern more about facilities/amenities experience. Purpose of stay also affects how consumers deal with service failure. Leisure travelers are found to be more price sensitive and likely to have issues with the usage of coupons. Theoretical and practical implications are also discussed.