Customer Experience and Satisfaction of Disneyland Hotel through Big Data Analysis of Online Customer Reviews
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 dimensio...
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MDPI AG
2021
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oai:doaj.org-article:270eb909f17b4f938bfea93a1a49151e2021-11-25T19:03:38ZCustomer Experience and Satisfaction of Disneyland Hotel through Big Data Analysis of Online Customer Reviews10.3390/su1322126992071-1050https://doaj.org/article/270eb909f17b4f938bfea93a1a49151e2021-11-01T00:00:00Zhttps://www.mdpi.com/2071-1050/13/22/12699https://doaj.org/toc/2071-1050Online 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.Xiaobin ZhangHak-Seon KimMDPI AGarticletheme hotelDisneyland hotelonline customer reviewssemantic network analysisbig data analyticsEnvironmental effects of industries and plantsTD194-195Renewable energy sourcesTJ807-830Environmental sciencesGE1-350ENSustainability, Vol 13, Iss 12699, p 12699 (2021) |
| institution |
DOAJ |
| collection |
DOAJ |
| language |
EN |
| topic |
theme hotel Disneyland hotel online customer reviews semantic network analysis big data analytics Environmental effects of industries and plants TD194-195 Renewable energy sources TJ807-830 Environmental sciences GE1-350 |
| spellingShingle |
theme hotel Disneyland hotel online customer reviews semantic network analysis big data analytics Environmental effects of industries and plants TD194-195 Renewable energy sources TJ807-830 Environmental sciences GE1-350 Xiaobin Zhang Hak-Seon Kim Customer Experience and Satisfaction of Disneyland Hotel through Big Data Analysis of Online Customer Reviews |
| description |
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. |
| format |
article |
| author |
Xiaobin Zhang Hak-Seon Kim |
| author_facet |
Xiaobin Zhang Hak-Seon Kim |
| author_sort |
Xiaobin Zhang |
| title |
Customer Experience and Satisfaction of Disneyland Hotel through Big Data Analysis of Online Customer Reviews |
| title_short |
Customer Experience and Satisfaction of Disneyland Hotel through Big Data Analysis of Online Customer Reviews |
| title_full |
Customer Experience and Satisfaction of Disneyland Hotel through Big Data Analysis of Online Customer Reviews |
| title_fullStr |
Customer Experience and Satisfaction of Disneyland Hotel through Big Data Analysis of Online Customer Reviews |
| title_full_unstemmed |
Customer Experience and Satisfaction of Disneyland Hotel through Big Data Analysis of Online Customer Reviews |
| title_sort |
customer experience and satisfaction of disneyland hotel through big data analysis of online customer reviews |
| publisher |
MDPI AG |
| publishDate |
2021 |
| url |
https://doaj.org/article/270eb909f17b4f938bfea93a1a49151e |
| work_keys_str_mv |
AT xiaobinzhang customerexperienceandsatisfactionofdisneylandhotelthroughbigdataanalysisofonlinecustomerreviews AT hakseonkim customerexperienceandsatisfactionofdisneylandhotelthroughbigdataanalysisofonlinecustomerreviews |
| _version_ |
1718410328578981888 |