Big data for big insights: Investigating language-specific drivers of hotel satisfaction with 412,784 user-generated reviews

Highlights

• Domestic vs. international tourists' preference on hotel are studied using big data.

• Hotel attributes preference of tourists from nine countries are examined.

• Travel types, e.g. business vs. leisure have significant mediating effects.

• Methodological contributions of the study are highlighted.

Abstract

This study leveraged the advantages of user-generated reviews with the aim of offering new insights into the determinants of hotel customer satisfaction by discriminating among customers by language group. From a collection of 412,784 user-generated reviews on TripAdvisor for 10,149 hotels from five Chinese cities, we found that foreign tourists, who speak diverse languages (English, German, French, Italian, Portuguese, Spanish, Japanese, and Russian), differ substantially in terms of their emphasis on the roles of various hotel attributes (“Rooms,” “Location,” “Cleanliness,” “Service,” and “Value”) in forming their overall satisfaction rating for hotels. Chinese tourists domestically exhibit distinct preferences for room-related hotel attributes when compared to foreign tourists. Major interaction effects are revealed between the attributes “Rooms” and “Service” and between “Value” and “Service”.

Introduction

Satisfaction of hotel customers has long been an important topic in tourism research. This is understandable, since travelers’ lodging experience constitutes an important and integral part of their overall travel experience (cf. Kau & Lim, 2005). A high level of customer satisfaction has been found not only to elicit positive perceptions of hotel image among customers (Hu, Kandampully, & Juwaheer, 2009) but also to motivate willingness to make recommendations, to pay more, and to stay at the hotel again (Bowen and Chen, 2001, Velázquez et al., 2015).

Nonetheless, reliably identifying the key determinants of satisfaction is challenging, because of the inherent heterogeneity of demand for lodging across various traveler groups. Hotel customers may speak any of numerous languages and differ in their cultural background and expectations. Dissimilarities among tourists’ profiles and types of travel influence their preference with respect to various hotel attributes, such as value for money, cleanliness, and location (Banerjee and Chua, 2016, Matzler et al., 2006, Poon and Low, 2005). Therefore, hotels favored by a particular group of customers may not be liked by another group, as we will prove later in the paper.

These challenges are highly relevant to both the hospitality and the tourism industry, particularly when heterogeneous groups of inbound and outbound tourists are involved, as in the case of China. According to the China National Tourism Administration (2015a), 26.36 million foreigners visited China in 2014, of whom 20.81 million stayed at least one night. These tourists were from various countries: South Korea, Japan, the United States, Russia, Germany, and many others. How to cater to the needs of tourists with diverse profiles appears to be an important practical challenge. Alongside the issue of foreign tourists, a rapid increase in domestic Chinese tourism presents its own challenge. There were approximately 3.26 billion domestic tourist trips in China in 2013 (China National Tourism Administration, 2014). Clearly, therefore, major hotels in China need to host both domestic and international customers simultaneously. For better satisfying the demands of both categories of guest, a clear understanding of the preferences characteristic of various tourist categories is imperative.

In our research, we sought, to this end, to leverage user-generated reviews of hotels in China. User-generated reviews can be defined as “peer-generated evaluations posted on company or third party websites” (Mudambi & Schuff, 2010, p. 186). Online reviews can be regarded as representing an individual customer's unique lodging experience. Having analyzed 412,784 reviews collected from TripAdvisor, covering 10,149 hotels in five major Chinese cities, we aim to offer new insights into the determinants of customers' overall satisfaction with hotels by discriminating among the languages that customers used to write their review comments.