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IECE Transactions on Social Statistics and Computing, 2024, Volume 1, Issue 1: 15-18

Free Access | Research Article | 8 January 2024
1 School of Management, Guangzhou University, Guangzhou 510006, China
* Corresponding author: Jebbouri Abdelhamid, email: [email protected]
Received: 30 December 2024, Accepted: 7 January 2024, Published: 8 January 2024  

Abstract
Traveling to diverse locations for leisure purposes is known as tourism, and it offers a variety of vacation experiences, including activities, healthcare, education, and religious, beachside, or rural getaways. People can escape their everyday life, learn new things, and enjoy the arts thanks to it. Both personal growth and cross-cultural exchange are facilitated by tourism. Nonetheless, diverse traveler tastes drive individuals to particular cities, nations, or areas. The goal of this study is to present a current typology of Chinese visitors based on experience and centrality, pinpointing their preferences and building a thorough profile. Prior research conducted in China has investigated the factors that influence this typology, including socio-demographic factors and tourism characteristics such as prior knowledge and on-site activities. It's interesting to note that this study found little difference in preferences between multi-day tourists from rural areas of China and local day-trippers.

Graphical Abstract
Visitors' Preferences at Chinese Historical Sites

Keywords
Visitors’ preferences
Chinese cultural tourists
Heritage sites
Tourism

References

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[12] Nguyen, T. H. H., & Cheung, C. (2014). The classification of heritage tourists: A case of Hue city, Vietnam. Journal of Heritage Tourism, 9(1), 35-50.

[13] Nyaupane, G. P., White, D. D., & Budruk, M. (2006). Motive-based tourist market segmentation: An application to native American cultural heritage sites in Arizona, USA. Journal of Heritage Tourism, 1(2), 81-99.


Cite This Article
APA Style
Niu, R., Zhang, H., & Abdelhamid, J. (2024). Visitors’ preferences at Chinese historical sites. IECE Transactions on Social Statisticsand Computing, 1(1), 15–18. https://doi.org/10.62762/TSSC.2024.808485

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