A Study on Travel Experience Design Based on the Motivation of Chinese Millennials to Travel Alone

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Abstract

This study studies Chinese millennial solo travelers as a unique research object to explore their motivations for solo travel and provide guidance for user experience design. Millennials have become the backbone of the Chinese travel market, with the proportion of millennials traveling alone on the rise. Solo travelers are freer and more immersed in the journey itself, so they demand a more personalized experience. However, China’s products for this group are still in the immature stage, and the real needs of this group have not been explored and met. Therefore, this paper will explore the needs and motivations of solo travelers. According to netnography, ethnography and questionnaire research, Chinese millennials have seven main motivations for solo travel, which can be further grouped into three motivation types, including enjoy oneself, play in group and express oneself. Their travel satisfaction has 9 important influencing factors, including safety, cost-effective, privacy, sociability, familiarity, novelty, uniqueness, richness and quality. Different motivations have different weight of influencing factors. For people who enjoy oneself, familiarity, privacy, quality and novelty are important influencing factors of travel satisfaction. For people play in group, sociability, safety, familiarity and cost-effective are important. For people who express oneself, uniqueness, richness, and social travel satisfaction are important. The study identified the characteristics of solo travelers among China’s millennial generation. Based on the results of the study, a comparative analysis is made based on the existing tourism products in China. This study can help researchers or service providers understand this growing market in China.

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APA

Chen, X., & Dai, L. (2020). A Study on Travel Experience Design Based on the Motivation of Chinese Millennials to Travel Alone. In Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics) (Vol. 12202 LNCS, pp. 581–593). Springer. https://doi.org/10.1007/978-3-030-49757-6_42

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