IDEAS home Printed from https://ideas.repec.org/a/gam/jsusta/v13y2021i13p7394-d586987.html
   My bibliography  Save this article

How Social Networks Affect the Spatiotemporal Planning of Smart Tourism: Evidence from Shanghai

Author

Listed:
  • Song Liu

    (College of Agriculture and Urban Planning, Tongji University, Shanghai 200092, China
    Key Laboratory of Ecology and Energy-Saving Study of Dense Habitat, Ministry of Education, Tongji University, Shanghai 200092, China)

  • Xiaoyan Ma

    (College of Agriculture and Urban Planning, Tongji University, Shanghai 200092, China
    Key Laboratory of Ecology and Energy-Saving Study of Dense Habitat, Ministry of Education, Tongji University, Shanghai 200092, China)

Abstract

Scenic tourism route plans are usually generated by combining scenic Points of Interest (PoIs) and the scenic road network. Traditional algorithms map the road networks linking the PoIs into a route collection and build a corresponding graph model. However, a single PoI description mechanism for scenic spots with multiple entrances and exits is significantly different from the actual tour route, which has multiple entrances and exits. Furthermore, the preferences and needs of tourists are not considered in attraction selection in existing algorithms. In this study, we propose a double-weighted graph model that considers the multiple entrances and exits of the PoI and identifies the tourists’ preferences using social network data. According to tourists’ different preferences and demands, different optimized tourist routes closer to the actual optimal paths were generated through an ant colony algorithm based on the proposed double-weighted graph model. To address the efficiency of the proposed model, we applied it in Shanghai and compared it with the traditional model through the 2bulu app, which can record three-dimensional (3D) trajectories of tourists. The comparison results show that the proposed model using social network data is closer to the actual 3D trajectory than the traditional model.

Suggested Citation

  • Song Liu & Xiaoyan Ma, 2021. "How Social Networks Affect the Spatiotemporal Planning of Smart Tourism: Evidence from Shanghai," Sustainability, MDPI, vol. 13(13), pages 1-18, July.
    • Handle: RePEc:gam:jsusta:v:13:y:2021:i:13:p:7394-:d:586987
    as

    Download full text from publisher

    File URL: https://www.mdpi.com/2071-1050/13/13/7394/pdf
    Download Restriction: no
    File URL: https://www.mdpi.com/2071-1050/13/13/7394/
    Download Restriction: no
    ---><---

    References listed on IDEAS

    as
    1. Du, Jiaoman & Zhou, Jiandong & Li, Xiang & Li, Lei & Guo, Ao, 2021. "Integrated self-driving travel scheme planning," International Journal of Production Economics, Elsevier, vol. 232(C).
    2. Lin Zhang, 2021. "Research on case reasoning method based on TF-IDF," International Journal of System Assurance Engineering and Management, Springer;The Society for Reliability, Engineering Quality and Operations Management (SREQOM),India, and Division of Operation and Maintenance, Lulea University of Technology, Sweden, vol. 12(3), pages 608-615, June.
    3. Ghermandi, Andrea, 2018. "Integrating social media analysis and revealed preference methods to value the recreation services of ecologically engineered wetlands," Ecosystem Services, Elsevier, vol. 31(PC), pages 351-357.
    4. Cuomo, Maria Teresa & Tortora, Debora & Foroudi, Pantea & Giordano, Alex & Festa, Giuseppe & Metallo, Gerardino, 2021. "Digital transformation and tourist experience co-design: Big social data for planning cultural tourism," Technological Forecasting and Social Change, Elsevier, vol. 162(C).
    Full references (including those not matched with items on IDEAS)

    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. Ruixue Liu & Jing Xiao, 2020. "Factors Affecting Users’ Satisfaction with Urban Parks through Online Comments Data: Evidence from Shenzhen, China," IJERPH, MDPI, vol. 18(1), pages 1-22, December.
    2. Mercado, Waldemar & Vásquez Lavín, Felipe & Ubillus, Karina & Orihuela, Carlos Enrique, 2020. "¿Es relevante la biodiversidad en la decisión de visita a los parques nacionales en el Perú?," Economia Agraria y Recursos Naturales, Spanish Association of Agricultural Economists, vol. 20(02), December.
    3. repec:ags:aaea22:335730 is not listed on IDEAS
    4. Dai, Peichao & Zhang, Shaoliang & Gong, Yunlong & Zhou, Yuan & Hou, Huping, 2022. "A crowd-sourced valuation of recreational ecosystem services using mobile signal data applied to a restored wetland in China," Ecological Economics, Elsevier, vol. 192(C).
    5. Cuesta-Valiño, Pedro & Gutiérrez-Rodríguez, Pablo & García-Henche, Blanca, 2022. "Word of mouth and digitalization in small retailers: Tradition, authenticity, and change," Technological Forecasting and Social Change, Elsevier, vol. 175(C).
    6. Xu, Yong & Yuan, Ling & Khalfaoui, Rabeh & Radulescu, Magdalena & Mallek, Sabrine & Zhao, Xin, 2023. "Making technological innovation greener: Does firm digital transformation work?," Technological Forecasting and Social Change, Elsevier, vol. 197(C).
    7. Thowayeb H. Hassan & Amany E. Salem & Mahmoud I. Saleh, 2022. "Digital-Free Tourism Holiday as a New Approach for Tourism Well-Being: Tourists’ Attributional Approach," IJERPH, MDPI, vol. 19(10), pages 1-14, May.
    8. Sinclair, Michael & Ghermandi, Andrea & Signorello, Giovanni & Giuffrida, Laura & De Salvo, Maria, 2022. "Valuing Recreation in Italy's Protected Areas Using Spatial Big Data," Ecological Economics, Elsevier, vol. 200(C).
    9. Yuzong Zhao & Hui Wang & Zhen Guo & Mingli Huang & Yongtao Pan & Yongrui Guo, 2022. "Online Reservation Intention of Tourist Attractions in the COVID-19 Context: An Extended Technology Acceptance Model," Sustainability, MDPI, vol. 14(16), pages 1-17, August.
    10. Maria Teresa Cuomo & Debora Tortora & Alessandro Danovi & Giuseppe Festa & Gerardino Metallo, 2022. "Toward a ‘New Normal’? Tourist Preferences Impact on Hospitality Industry Competitiveness," Corporate Reputation Review, Palgrave Macmillan, vol. 25(3), pages 212-225, August.
    11. Hannes Thees & Elina Störmann & Franziska Thiele & Natalie Olbrich, 2021. "Shaping digitalization among German tourism service providers: Processes and implications," Post-Print hal-03373971, HAL.
    12. Thees, Hannes & Störmann, Elina & Thiele, Franziska & Olbrich, Natalie, 2021. "Shaping digitalization among German tourism service providers: Processes and implications," EconStor Open Access Articles and Book Chapters, ZBW - Leibniz Information Centre for Economics, vol. 7, pages 3-15.
    13. Lingua, Federico & Coops, Nicholas C. & Griess, Verena C., 2022. "Valuing cultural ecosystem services combining deep learning and benefit transfer approach," Ecosystem Services, Elsevier, vol. 58(C).
    14. Xue, Zhebin & Li, Qing & Zeng, Xianyi, 2023. "Social media user behavior analysis applied to the fashion and apparel industry in the big data era," Journal of Retailing and Consumer Services, Elsevier, vol. 72(C).
    15. Sinclair, Michael & Mayer, Marius & Woltering, Manuel & Ghermandi, Andrea, 2020. "Valuing nature-based recreation using a crowdsourced travel cost method: A comparison to onsite survey data and value transfer," Ecosystem Services, Elsevier, vol. 45(C).
    16. Moein Abdolmohamad Sagha & Nader Seyyedamiri & Pantea Foroudi & Morteza Akbari, 2022. "The One Thing You Need to Change Is Emotions: The Effect of Multi-Sensory Marketing on Consumer Behavior," Sustainability, MDPI, vol. 14(4), pages 1-18, February.
    17. Fernandez-Lores, Susana & Crespo-Tejero, Natividad & Fernández-Hernández, Ruth, 2022. "Driving traffic to the museum: The role of the digital communication tools," Technological Forecasting and Social Change, Elsevier, vol. 174(C).
    18. Cuomo, Maria Teresa & Colosimo, Ivan & Celsi, Lorenzo Ricciardi & Ferulano, Roberto & Festa, Giuseppe & La Rocca, Michele, 2022. "Enhancing Traveller Experience In Integrated Mobility Services Via Big Social Data Analytics," Technological Forecasting and Social Change, Elsevier, vol. 176(C).
    19. Tharaka A. Jayalath & Patrick Lloyd-Smith & Marcus Becker, 2023. "Biodiversity Benefits of Birdwatching Using Citizen Science Data and Individualized Recreational Demand Models," Environmental & Resource Economics, Springer;European Association of Environmental and Resource Economists, vol. 86(1), pages 83-107, October.
    20. Kolstoe, Sonja & Naald, Brian Vander & Cohan, Alison, 2022. "A tale of two samples: Understanding WTP differences in the age of social media," Ecosystem Services, Elsevier, vol. 55(C).
    21. Lapuz, Mark Chris M., 2023. "The role of local community empowerment in the digital transformation of rural tourism development in the Philippines," Technology in Society, Elsevier, vol. 74(C).

    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:13:y:2021:i:13:p:7394-:d:586987. 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.