Abstract
Online customer reviews have become a significant information source for scholars and practitioners to understand customer experience and its association with their satisfaction to maintain the sustainable development of relative industries. Thus, this study attempted to find the underlying dimensionality in online customer reviews reflecting customers experience in the Hong Kong Disneyland hotel and identified its relationship with customer satisfaction. Semantic network analysis by Netdraw and factor analysis and linear regression analysis by SPSS 26.0 (IBM, New York, NY, USA) were applied for data analysis. As a result, 70 keywords with high frequency were extracted, and their connection to each other was calculated based on their centralities. Consequently, seven factors were explored by exploratory factor analysis, and moreover, three factors, “Family Empathy”, “Value”, and “Food Quality”, were testified to be negatively related to customer satisfaction. The findings of this study, to a great extent, could be utilized as a research scheme for future research to investigate theme hotels with big data analytics of online customer reviews. More importantly, some new insights and practical implications for the future research and industry development were provided and discussed as well.
Highlights
A great number of studies and real applications in the industry have demonstrated the huge potential of big data and relative analytics to promote the industry development and procure business intelligence to maintain the economic sustainability of the industry [2,3,4]
The methodology used in this study is online customer reviews with big data analytics
The data collection period set in this research was four years, which is from 1 January 2017 to 4 May 2021, and “Disneyland Hotel” + “Hong Kong” were used as keywords for data collection since
Summary
Academic Editors: Dimitrios Buhalis and Hyo Sun Jung. The tremendous growth of social media and consumer-generated content on the Internet, such as their online reviews for specific products or services, photos or videos customers posted, etc., has inspired the development of so-called big data and big data analytics to understand and solve real-life problems [1]. There is no doubt that these social media platforms and consumer-generated content on the Internet continue to grow and impact the tourism and hospitality industry. A great number of studies and real applications in the industry have demonstrated the huge potential of big data and relative analytics to promote the industry development and procure business intelligence to maintain the economic sustainability of the industry [2,3,4]
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