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An Investigation of the Key Attributes of Korean Wellness Tourism Customers Based on Online Reviews

Author

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  • Aura Lydia Riswanto

    (Department of Global Business, Kyungsung University, Busan 48434, Republic of Korea)

  • Hak-Seon Kim

    (School of Hospitality & Tourism Management, Kyungsung University, Busan 48434, Republic of Korea
    Wellness & Tourism Big Data Research Institute, Kyungsung University, Busan 48434, Republic of Korea)

Abstract

With its fast-growing trend, wellness tourism is transforming the client base and service and product offerings, and it is attracting new suppliers. The purpose of understanding the customer experience as portrayed in online reviews is to sustainably maintain customer loyalty and satisfaction. The objective of this research is to identify the critical attributes and their structural relationships to Korean wellness tourism. The study analyzed 24,060 Google-based customer reviews on 11 wellness tourism destinations in South Korea. Following the calculation of word frequencies in a matrix, UCINET 6.0 was utilized to analyze the centrality of the network and perform a CONCOR analysis. Based on the findings of the CONCOR analysis, the review data were sorted into four distinct categories. Following the quantitative analysis led to the identification of six variables that were grouped together through exploratory factor analysis.: wellness, tangible, value, F&B, purpose, and service. Whereas value, F&B, and service negatively affected the satisfaction of guests, the study also revealed that wellness, tangible, and purpose all had positive impacts and contributed to increased trust among wellness tourism customers. In terms of managerial implication, the results will enable wellness tourism destination managers to focus more on improving the factors of value, food, and service.

Suggested Citation

  • Aura Lydia Riswanto & Hak-Seon Kim, 2023. "An Investigation of the Key Attributes of Korean Wellness Tourism Customers Based on Online Reviews," Sustainability, MDPI, vol. 15(8), pages 1-18, April.
  • Handle: RePEc:gam:jsusta:v:15:y:2023:i:8:p:6702-:d:1124278
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    References listed on IDEAS

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    1. Park, Cheol & Lee, Thae Min, 2009. "Information direction, website reputation and eWOM effect: A moderating role of product type," Journal of Business Research, Elsevier, vol. 62(1), pages 61-67, January.
    2. Klein, Lisa R., 1998. "Evaluating the Potential of Interactive Media through a New Lens: Search versus Experience Goods," Journal of Business Research, Elsevier, vol. 41(3), pages 195-203, March.
    3. Nadine Angelita Valentine, 2016. "Wellness Tourism: Using Tourists’ Preferences to Evaluate the Wellness Tourism Market in Jamaica," Review of Social Sciences, LAR Center Press, vol. 1(3), pages 25-44, March.
    4. Aralbayeva Shadiyar & Hyun-Jeong Ban & Hak-Seon Kim, 2020. "Extracting Key Drivers of Air Passenger’s Experience and Satisfaction through Online Review Analysis," Sustainability, MDPI, vol. 12(21), pages 1-20, November.
    5. Xiaobin Zhang & Hak-Seon Kim, 2021. "Customer Experience and Satisfaction of Disneyland Hotel through Big Data Analysis of Online Customer Reviews," Sustainability, MDPI, vol. 13(22), pages 1-17, November.
    6. Gabriela Cecilia Stanciulescu & Gabriela Nicoleta Diaconescu & Dan Mihnea Diaconescu, 2015. "Health, Spa, Wellness Tourism. What is the Difference?," Knowledge Horizons - Economics, Faculty of Finance, Banking and Accountancy Bucharest,"Dimitrie Cantemir" Christian University Bucharest, vol. 7(3), pages 158-161, September.
    Full references (including those not matched with items on IDEAS)

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