Using Online Customer Reviews to Understand Customers’ Experience and Satisfaction with Integrated Resorts

Jun Yu, Xiaobin Zhang and Hak-Seon Kim ()
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Jun Yu: School of Hospitality & Tourism Management, Kyungsung Universtiy, Busan 48434, Republic of Korea
Xiaobin Zhang: Department of Tourism Management, Jinzhong University, Jinzhong 030600, China
Hak-Seon Kim: School of Hospitality & Tourism Management, Kyungsung Universtiy, Busan 48434, Republic of Korea

Sustainability, 2023, vol. 15, issue 17, 1-14

Abstract: With the diverse demands of customers for their accommodation experiences, integrated resorts have emerged and have been popular among tourists. Meanwhile, in the context of Tourism and Hospitality 4.0, online information collection and marketing has been one of the most effective strategies for industry operators and investors. Thus, the present study adopted online reviews generated by customers themselves to explore their experience and satisfaction with integrated resorts. With the qualitative and quantitative analyses of online customer reviews, firstly, 70 prominent keywords were extracted from the reviews, and some general understanding was obtained from the top frequent words. After conducting a semantic network analysis of the top frequent words, significant and central words in the network were identified, which were utilized as basic variables for the specific exploration of factors reflecting customers’ experience. In the meantime, four dimensions, “Amenities”, “Entertainment”, “Tourist”, and “Atmosphere”, were garnered via CONCOR analysis to illustrate the key dimensions of customers’ cognition and awareness towards resorts. At last, a quantitative analysis with an exploration factor analysis and a linear regression analysis were conducted to testify the correlation between customer experience and satisfaction. Three factors, “environment”, “staff service”, and “food service”, have a significant effect on customer satisfaction. Analytics of online customer reviews with a big volume, which differ from traditional research methods by designed structure or content, could generate more comprehensive understanding and cognition of research subjects. The findings obtained from analytics could provide baseline information for future research and industry development and promotion.

Keywords: integrated resort; online customer reviews; customer experience; satisfaction; text analytics (search for similar items in EconPapers)
JEL-codes: O13 Q Q0 Q2 Q3 Q5 Q56 (search for similar items in EconPapers)
Date: 2023
References: View references in EconPapers View complete reference list from CitEc
Citations: View citations in EconPapers (1)

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