An Exploratory Study of Electronic Word-of-Mouth Focused on Casino Hotels in Las Vegas and Macao

Abstract

In order to investigate the key attributes of casino hotel customer eWOM and their structural relationships, this study selects two casino hotels located in Las Vegas and Macao. Through big data analytics, online reviews of two casino hotels from Google Travel were utilized. The frequency and CONCOR analyses showed the top 50 high-frequency words for each hotel and divided them into groups. The results of the factor analysis and linear regression analysis show that four factors, namely “Physical Environment”, “Entertainment”, “Experience”, and “Amenity”, in Las Vegas have a significant impact on customer satisfaction, while two factors, namely “Value” and “Physical Environment”, do in Macao. Through the results, the study points out the general characteristics affecting customer satisfaction of casino hotels, as well as the distinctions in influencing factors of their customer satisfaction in different source markets.

Unlocking Customer Satisfaction of Halal Restaurant in South Korea through Online Review Analysis

“…Qualitative analysis might be said to have taken place at this phase because it focused on the text. In this study, the centrality analysis (Freeman's degree and eigenvector) as well as the CONCOR analysis are carried out in order to identify the significance of the top frequencies in relation to their centrality values and, secondly, to determine the dimensions related to customer perception and cognition of halal-certified restaurants in South Korea [42,44,45] . This research was carried out in order to answer the following questions.…”

Review Evaluation for Hotel Recommendation

“…Nevertheless, regarding intangible products, such as a tour experience, consumers are more likely to be influenced by word-of-mouth [8,9]. The reason is that word-of-mouth has more persuasive power than advertisements, especially for intangible products [10]. Thus, many consumers pursue the opinions of experts or past users before making a purchase.…”

“…In addition, NLP-like methods cannot identify review spam if there are slight similarities among them. Some online travel communities, like Tripadvisor.com (the largest online travel review community [10,18], have announced that they can filter fake reviews by analyzing reviews and comments. However, they do not disclose their criteria for judgment.…”

“…In general, more enthusiastic reviewers contribute reviews with higher reliability. According to several studies [10,[20][21][22], review features can influence the trustworthiness of reviews. For example, if a review contains a specific hotel name many times, we can suspect the review is spam because the review intends to make an impression of the hotel on potential customers.…”

Double or nothing: push and pull factors of casinos in Europe

“…Gambling tourism is important because it is an activity that brings wealth to a city/location and can raise the level of income there, as seen in places like Macau, which before Covid, was set to overtake Qatar as the richest place in the world (Tang & Kim, 2022 ). Investing in gambling tourism will have a multiplier effect on other areas including hotels, shopping, dining, and entertainment, which can in turn bring prosperity to a region and have a positive impact on society (Lehto et al, 2014 ; Leiper, 1989 ; Rosenbaum & Wong, 2015 ).…”