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A Comparative Study of Customer Perceptions of Urban and Rural Bed and Breakfasts in Beijing: An Analysis of Online Reviews

Author

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  • Xin Zhang

    (Key Laboratory of Regional Sustainable Development Modeling, Institute of Geographic Sciences and Natural Resources Research, Chinese Academy of Sciences, Beijing 100101, China
    College of Resources and Environment, University of Chinese Academy of Sciences, Beijing 100049, China)

  • Jiaming Liu

    (Key Laboratory of Regional Sustainable Development Modeling, Institute of Geographic Sciences and Natural Resources Research, Chinese Academy of Sciences, Beijing 100101, China
    College of Resources and Environment, University of Chinese Academy of Sciences, Beijing 100049, China)

  • He Zhu

    (Key Laboratory of Regional Sustainable Development Modeling, Institute of Geographic Sciences and Natural Resources Research, Chinese Academy of Sciences, Beijing 100101, China
    College of Resources and Environment, University of Chinese Academy of Sciences, Beijing 100049, China)

  • Zongcai Huang

    (State Key Laboratory of Resources and Environment Information System, Institute of Geographic Sciences and Natural Resources Research, Chinese Academy of Sciences, Beijing 100101, China)

  • Shuying Zhang

    (State Key Laboratory of Resources and Environment Information System, Institute of Geographic Sciences and Natural Resources Research, Chinese Academy of Sciences, Beijing 100101, China)

  • Ping Li

    (College of Recreation and Tourism, Beijing Sport University, Beijing 100084, China)

Abstract

The differences between urban and rural B&Bs should be emphasized, which is critical for the sustainable development of the B&B industry. This study identified and compared the topics that customers were concerned about for urban and rural B&Bs in Beijing by analyzing 13,241 online reviews obtained from the website Ctrip. The results showed that customers focused on 10 common topics: “room”, “location”, “host”, “experience”, “surroundings”, “facilities”, “service”, “design/style”, “value”, and “entertainment”. However, the importance of each topic varied between urban and rural B&Bs. Customers paid more attention to the room. Urban B&B customers were more concerned about location. The convenience of urban B&Bs was more prominent than that of rural B&Bs, especially in terms of public transportation and commercial services. While rural B&B customers were more concerned about experience, service, design/style, and entertainment. In addition, the “host” is the most crucial and influential factor in the development of B&Bs. This study made contributions to customer perceptions of B&Bs from a comparative perspective and enriched the understanding of the characteristics of urban and rural B&Bs. In the part of practice, this study might provide enlightenment for B&B operators and local governments to take measures for B&Bs sustainable development.

Suggested Citation

  • Xin Zhang & Jiaming Liu & He Zhu & Zongcai Huang & Shuying Zhang & Ping Li, 2021. "A Comparative Study of Customer Perceptions of Urban and Rural Bed and Breakfasts in Beijing: An Analysis of Online Reviews," Sustainability, MDPI, vol. 13(20), pages 1-15, October.
  • Handle: RePEc:gam:jsusta:v:13:y:2021:i:20:p:11303-:d:655246
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    References listed on IDEAS

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    1. Nawhath Thanvisitthpon, 2021. "Statistically Validated Component- and Indicator-Level Requirements for Sustainable Thai Homestay Businesses," Sustainability, MDPI, vol. 13(2), pages 1-17, January.
    2. Gutiérrez, Javier & García-Palomares, Juan Carlos & Romanillos, Gustavo & Salas-Olmedo, María Henar, 2017. "The eruption of Airbnb in tourist cities: Comparing spatial patterns of hotels and peer-to-peer accommodation in Barcelona," Tourism Management, Elsevier, vol. 62(C), pages 278-291.
    3. Xi Zhang & Juan Tang, 2021. "A Study of Emotional Solidarity in the Homestay Industry between Hosts and Tourists in the Post-Pandemic Era," Sustainability, MDPI, vol. 13(13), pages 1-17, July.
    4. Leo Huang, 2008. "Bed and breakfast industry adopting e-commerce strategies in e-service," The Service Industries Journal, Taylor & Francis Journals, vol. 28(5), pages 633-648, June.
    5. Paul A. Lynch, 2000. "Networking in the Homestay Sector," The Service Industries Journal, Taylor & Francis Journals, vol. 20(3), pages 95-116, July.
    6. Ian Sutherland & Youngseok Sim & Seul Ki Lee & Jaemun Byun & Kiattipoom Kiatkawsin, 2020. "Topic Modeling of Online Accommodation Reviews via Latent Dirichlet Allocation," Sustainability, MDPI, vol. 12(5), pages 1-15, February.
    7. Ye, Shun & Xiao, Honggen & Zhou, Lingqiang, 2018. "Commodification and perceived authenticity in commercial homes," Annals of Tourism Research, Elsevier, vol. 71(C), pages 39-53.
    8. Yi-Chung Hu & Jen-Hung Wang & Ru-Yu Wang, 2012. "Evaluating the Performance of Taiwan Homestay Using Analytic Network Process," Mathematical Problems in Engineering, Hindawi, vol. 2012, pages 1-24, August.
    9. Xiang, Zheng & Du, Qianzhou & Ma, Yufeng & Fan, Weiguo, 2017. "A comparative analysis of major online review platforms: Implications for social media analytics in hospitality and tourism," Tourism Management, Elsevier, vol. 58(C), pages 51-65.
    10. Fei Long & Jiaming Liu & Shuying Zhang & Hu Yu & Hou Jiang, 2018. "Development Characteristics and Evolution Mechanism of Homestay Agglomeration in Mogan Mountain, China," Sustainability, MDPI, vol. 10(9), pages 1-18, August.
    11. Yuguo Tao & Feng Zhang & Chunyun Shi & Yun Chen, 2019. "Social Media Data-Based Sentiment Analysis of Tourists’ Air Quality Perceptions," Sustainability, MDPI, vol. 11(18), pages 1-23, September.
    12. Zhihua Zhang & Rachel J. C. Fu, 2020. "Accommodation Experience in the Sharing Economy: A Comparative Study of Airbnb Online Reviews," Sustainability, MDPI, vol. 12(24), pages 1-11, December.
    13. Zain ul Abedin Janjua & Gengeswari Krishnapillai & Mobashar Rahman, 2021. "A Systematic Literature Review of Rural Homestays and Sustainability in Tourism," SAGE Open, , vol. 11(2), pages 21582440211, April.
    14. Mura, Paolo, 2015. "Perceptions of authenticity in a Malaysian homestay – A narrative analysis," Tourism Management, Elsevier, vol. 51(C), pages 225-233.
    15. Guo, Yue & Barnes, Stuart J. & Jia, Qiong, 2017. "Mining meaning from online ratings and reviews: Tourist satisfaction analysis using latent dirichlet allocation," Tourism Management, Elsevier, vol. 59(C), pages 467-483.
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