IDEAS home Printed from https://ideas.repec.org/a/gam/jsusta/v10y2017i1p43-d124420.html
   My bibliography  Save this article

A Model to Measure Tourist Preference toward Scenic Spots Based on Social Media Data: A Case of Dapeng in China

Author

Listed:
  • Yao Sun

    (School of Architecture and Urban Planning, Shenzhen Graduate School, Harbin Institute of Technology, Shenzhen 518055, China
    Department of Building and Real Estate, The Hong Kong Polytechnic University, Hong Kong, China)

  • Hang Ma

    (School of Architecture and Urban Planning, Shenzhen Graduate School, Harbin Institute of Technology, Shenzhen 518055, China)

  • Edwin H. W. Chan

    (Department of Building and Real Estate, The Hong Kong Polytechnic University, Hong Kong, China)

Abstract

Research on tourist preference toward different tourism destinations has been a hot topic for decades in the field of tourism development. Tourist preference is mostly measured with small group opinion-based methods through introducing indicator systems in previous studies. In the digital age, e-tourism makes it possible to collect huge volumes of social data produced by tourists from the internet, to establish a new way of measuring tourist preference toward a close group of tourism destinations. This paper introduces a new model using social media data to quantitatively measure the market trend of a group of scenic spots from the angle of tourists’ demand, using three attributes: tourist sentiment orientation, present tourist market shares, and potential tourist awareness. Through data mining, cleaning, and analyzing with the framework of Machine Learning, the relative tourist preference toward 34 scenic spots closely located in the Dapeng Peninsula is calculated. The results not only provide a reliable “A-rating” system to gauge the popularity of different scenic spots, but also contribute an innovative measuring model to support scenic spots planning and policy making in the regional context.

Suggested Citation

  • Yao Sun & Hang Ma & Edwin H. W. Chan, 2017. "A Model to Measure Tourist Preference toward Scenic Spots Based on Social Media Data: A Case of Dapeng in China," Sustainability, MDPI, vol. 10(1), pages 1-13, December.
    • Handle: RePEc:gam:jsusta:v:10:y:2017:i:1:p:43-:d:124420
    as

    Download full text from publisher

    File URL: https://www.mdpi.com/2071-1050/10/1/43/pdf
    Download Restriction: no
    File URL: https://www.mdpi.com/2071-1050/10/1/43/
    Download Restriction: no
    ---><---

    References listed on IDEAS

    as
    1. Wang, Xia & Li, Xiang (Robert) & Zhen, Feng & Zhang, JinHe, 2016. "How smart is your tourist attraction?: Measuring tourist preferences of smart tourism attractions via a FCEM-AHP and IPA approach," Tourism Management, Elsevier, vol. 54(C), pages 309-320.
    Full references (including those not matched with items on IDEAS)

    Citations

    Citations are extracted by the CitEc Project, subscribe to its RSS feed for this item.
    as


    Cited by:

    1. Alecxandrina Deaconu & Elena Mădălina Dedu & Ramona Ștefania Igreț & Cătălina Radu, 2018. "The Use of Information and Communications Technology in Vocational Education and Training—Premise of Sustainability," Sustainability, MDPI, vol. 10(5), pages 1-18, May.
    2. Weiwei Zhang & Lingling Jiang, 2021. "Effects of High-Speed Rail on Sustainable Development of Urban Tourism: Evidence from Discrete Choice Model of Chinese Tourists’ Preference for City Destinations," Sustainability, MDPI, vol. 13(19), pages 1-19, September.
    3. Chenghao Yang & Tongtong Liu, 2022. "Social Media Data in Urban Design and Landscape Research: A Comprehensive Literature Review," Land, MDPI, vol. 11(10), pages 1-22, October.

    Most related items

    These are the items that most often cite the same works as this one and are cited by the same works as this one.
    1. Bahram Zikirya & Chunshan Zhou, 2023. "Spatial Distribution and Influencing Factors of High-Level Tourist Attractions in China: A Case Study of 9296 A-Level Tourist Attractions," Sustainability, MDPI, vol. 15(19), pages 1-18, September.
    2. Hugo Padrón-Ávila & Raúl Hernández-Martín, 2019. "Preventing Overtourism by Identifying the Determinants of Tourists’ Choice of Attractions," Sustainability, MDPI, vol. 11(19), pages 1-17, September.
    3. Assumpció Huertas & Antonio Moreno & Jordi Pascual, 2021. "Place Branding for Smart Cities and Smart Tourism Destinations: Do They Communicate Their Smartness?," Sustainability, MDPI, vol. 13(19), pages 1-18, October.
    4. Inessa Tyan & Mariemma I. Yagüe & Antonio Guevara-Plaza, 2020. "Blockchain Technology for Smart Tourism Destinations," Sustainability, MDPI, vol. 12(22), pages 1-11, November.
    5. Francisco E. Cabrera & Manuel Amaya & Gustavo Fabián Vaccaro Witt & José Ignacio Peláez, 2019. "Pairwise Voting to Rank Touristic Destinations Based on Preference Valuation," Sustainability, MDPI, vol. 11(21), pages 1-13, October.
    6. Chi Yunxian & Li Renjie & Zhao Shuliang & Guo Fenghua, 2020. "Measuring multi-spatiotemporal scale tourist destination popularity based on text granular computing," PLOS ONE, Public Library of Science, vol. 15(4), pages 1-33, April.
    7. Danny Daniel Castillo Vizuete & Alex Vinicio Gavilanes Montoya & Eduardo Antonio Muñoz Jácome & Carlos Renato Chávez Velásquez & Stelian Alexandru Borz, 2021. "An Evaluation of the Importance of Smart Tourism Tools in the Riobamba Canton, Ecuador," Sustainability, MDPI, vol. 13(16), pages 1-22, August.
    8. Tomašević Ivana & Đurović Sandra & Abramović Nikola, 2019. "Analysis of the Use of Digital Technologies in Montenegro’s Tourist offer on the Example of a Hotels in Bar," Economics, Sciendo, vol. 7(1), pages 119-125, June.
    9. Mateusz Naramski, 2020. "The Application of ICT and Smart Technologies in Polish Museums—Towards Smart Tourism," Sustainability, MDPI, vol. 12(21), pages 1-27, November.
    10. Xiaoping Gu & Carter A. Hunt & Xiang Jia & Lijun Niu, 2022. "Evaluating Nature-Based Tourism Destination Attractiveness with a Fuzzy-AHP Approach," Sustainability, MDPI, vol. 14(13), pages 1-23, June.
    11. Chung-Ming Chuang, 2023. "The conceptualization of smart tourism service platforms on tourist value co-creation behaviours: an integrative perspective of smart tourism services," Palgrave Communications, Palgrave Macmillan, vol. 10(1), pages 1-16, December.
    12. Fotiadis, Anestis K. & Stylos, Nikolaos, 2017. "The effects of online social networking on retail consumer dynamics in the attractions industry: The case of ‘E-da’ theme park, Taiwan," Technological Forecasting and Social Change, Elsevier, vol. 124(C), pages 283-294.
    13. Dejan Križaj, 2020. "Integration of Quality, Continuous Improvement, and Innovation in Tourism: The QCII Model," Academica Turistica - Tourism and Innovation Journal, University of Primorska Press, vol. 13(1), pages 97-110.
    14. Pedro Cuesta-Valiño & Fadoua Bolifa & Estela Núñez-Barriopedro, 2020. "Sustainable, Smart and Muslim-Friendly Tourist Destinations," Sustainability, MDPI, vol. 12(5), pages 1-13, February.
    15. Meena Kumari Pradhan & Jungjoo Oh & Hwansoo Lee, 2018. "Understanding Travelers’ Behavior for Sustainable Smart Tourism: A Technology Readiness Perspective," Sustainability, MDPI, vol. 10(11), pages 1-20, November.
    16. Sanjit K. Roy & Gaganpreet Singh & Corey Hatton & Bidit Dey & Nisreen Ameen & Satish Kumar, 2023. "Customers’ motives to co-create in smart services interactions," Electronic Commerce Research, Springer, vol. 23(3), pages 1367-1400, September.
    17. Hannia Gonzalez-Urango & Mónica García-Melón, 2017. "A Multicriteria Model to Evaluate Strategic Plans for the Nautical and Naval Industry in Cartagena de Indias, Colombia," Sustainability, MDPI, vol. 9(4), pages 1-16, April.
    18. Sürme Metin & Ince Ercan, 2023. "Smart Destination Selection Process: Research on Generation Y Tourists," European Journal of Tourism, Hospitality and Recreation, Sciendo, vol. 13(1), pages 26-39, December.
    19. Femenia-Serra , Francisco & Neuhofer, Barbara, 2018. "Smart tourism experiences: conceptualisation, key dimensions and research agenda," INVESTIGACIONES REGIONALES - Journal of REGIONAL RESEARCH, Asociación Española de Ciencia Regional, issue 42, pages 129-150.
    20. Silvia ISTRATE & Valerica NESTIAN & Maria NEAGU, 2018. "A Company Improvement Analysis using the AHP and the ANP Methods," Economics and Applied Informatics, "Dunarea de Jos" University of Galati, Faculty of Economics and Business Administration, issue 2, pages 48-59.

    Corrections

    All material on this site has been provided by the respective publishers and authors. You can help correct errors and omissions. When requesting a correction, please mention this item's handle: RePEc:gam:jsusta:v:10:y:2017:i:1:p:43-:d:124420. See general information about how to correct material in RePEc.

    If you have authored this item and are not yet registered with RePEc, we encourage you to do it here. This allows to link your profile to this item. It also allows you to accept potential citations to this item that we are uncertain about.

    If CitEc recognized a bibliographic reference but did not link an item in RePEc to it, you can help with this form .

    If you know of missing items citing this one, you can help us creating those links by adding the relevant references in the same way as above, for each refering item. If you are a registered author of this item, you may also want to check the "citations" tab in your RePEc Author Service profile, as there may be some citations waiting for confirmation.

    For technical questions regarding this item, or to correct its authors, title, abstract, bibliographic or download information, contact: MDPI Indexing Manager (email available below). General contact details of provider: https://www.mdpi.com .

    Please note that corrections may take a couple of weeks to filter through the various RePEc services.

    IDEAS is a RePEc service. RePEc uses bibliographic data supplied by the respective publishers.