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Exploring the Salient Attributes of Short-Term Rental Experience: An Analysis of Online Reviews from Chinese Guests

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  • Yuanyuan Guo

    (School of Maritime Economics and Management, Dalian Maritime University, Dalian 116026, China
    Collaborative Innovation Center for Transport Studies, Dalian Maritime University, Dalian 116026, China)

  • Yanqing Wang

    (School of Maritime Economics and Management, Dalian Maritime University, Dalian 116026, China)

  • Chaoyou Wang

    (School of Management Science and Engineering, Dongbei University of Finance and Economics, Dalian 116025, China)

Abstract

Although China has become an emerging market in the peer-to-peer (P2P) accommodation industry, no research has been conducted to examine Chinese guests’ experience with short-term rentals. This study aims to investigate major service attributes that influence Chinese guests’ experiences and satisfaction with P2P accommodations by analyzing online reviews on the Xiaozhu sharing economy platform in China. Using text mining and content analysis method, the study found that Chinese guests who stayed in entire houses/apartments and private rooms frequently mentioned “host service,” “cleanliness,” “location and transportation,” and “living environment.” In addition, the guests who stayed in private rooms cared more about “security and privacy” and “value for money.” Those who stayed in entire houses cared more about the facilities, with a particular focus on the aspects of the kitchen. Finally, the guests who stayed in private rooms valued social interaction with the host more and left a lower proportion of negative reviews related to “host service” than those who stayed in entire houses. This study provides a comprehensive understanding of the Chinese guests’ experience.

Suggested Citation

  • Yuanyuan Guo & Yanqing Wang & Chaoyou Wang, 2019. "Exploring the Salient Attributes of Short-Term Rental Experience: An Analysis of Online Reviews from Chinese Guests," Sustainability, MDPI, vol. 11(16), pages 1-19, August.
    • Handle: RePEc:gam:jsusta:v:11:y:2019:i:16:p:4290-:d:255849
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    References listed on IDEAS

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    Cited by:

    1. Susan (Sixue) Jia, 2021. "Analyzing Restaurant Customers’ Evolution of Dining Patterns and Satisfaction during COVID-19 for Sustainable Business Insights," Sustainability, MDPI, vol. 13(9), pages 1-15, April.
    2. Irene Rubino & Cristina Coscia & Rocco Curto, 2020. "Identifying Spatial Relationships between Built Heritage Resources and Short-Term Rentals before the Covid-19 Pandemic: Exploratory Perspectives on Sustainability Issues," Sustainability, MDPI, vol. 12(11), pages 1-22, June.
    3. Yi Luo & Xiaowei Xu, 2019. "Predicting the Helpfulness of Online Restaurant Reviews Using Different Machine Learning Algorithms: A Case Study of Yelp," Sustainability, MDPI, vol. 11(19), pages 1-17, September.

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