Skip to main content

Promoting Sustainable Travel Through a Web-Based Tourism Support System

  • Conference paper
  • First Online:
Intelligence for Future Cities (CUPUM 2023)

Part of the book series: The Urban Book Series ((UBS))

  • 500 Accesses

Abstract

In Japan, distributed travel is recently promoted in order to prevent both the problems associated with overtourism and the spread of the COVID-19 pandemic in urban tourist destinations. The present study developed a tourism support system by integrating web-geographic information system (Web-GIS), recommendation system and social network services (SNS). The system has two unique key functions (the functions of tourism congestion display and tourist attraction recommendation) in order to promote distributed travel during the sightseeing planning stage. The system was operated for six weeks targeting Kamakura City in Kanagawa Prefecture, Japan. The evaluation results for the system performance revealed that the function of tourism congestion display can promote tourism that takes congestion periods and areas into consideration. It also showed that the function of tourist attraction recommendation can provide users with novel tourist attraction recommendations and achieve high levels of intent to visit recommended tourist attractions.

This is a preview of subscription content, log in via an institution to check access.

Access this chapter

Chapter
USD 29.95
Price excludes VAT (USA)
  • Available as PDF
  • Read on any device
  • Instant download
  • Own it forever
eBook
USD 219.00
Price excludes VAT (USA)
  • Available as EPUB and PDF
  • Read on any device
  • Instant download
  • Own it forever
Softcover Book
USD 279.99
Price excludes VAT (USA)
  • Compact, lightweight edition
  • Dispatched in 3 to 5 business days
  • Free shipping worldwide - see info
Hardcover Book
USD 279.99
Price excludes VAT (USA)
  • Durable hardcover edition
  • Dispatched in 3 to 5 business days
  • Free shipping worldwide - see info

Tax calculation will be finalised at checkout

Purchases are for personal use only

Institutional subscriptions

Similar content being viewed by others

References

  • Abe S, Sasaki R, Yamamoto K (2021) Sightseeing support system with augmented reality and no language barriers. In: Geertman S, Pettit C, Goodspeed R, Kauppi A (eds) Lecture notes in urban informatics for future cities. Springer, pp 591–611

    Google Scholar 

  • An HW, Moon N (2019) Design of recommendation system for tourist spot using sentiment analysis based on CNN-LSTM. J Ambient Intell Humaniz Comput 13:1653–1663

    Article  Google Scholar 

  • Bali A, Monavari SM, Riazi B, Khorasani M, Zarkeh MMK (2016) A spatial decision support system for ecotourism development in caspian hyrcanian mixed forests ecoregion. Boletim De Ciencias Geodesicas 21(2):340–353

    Article  Google Scholar 

  • Bongki K (2018) Global tourism promotion and overtourism. J Hiroshima Bunka Gakuen Univ Center Netw Soc 14(1):45–54

    Google Scholar 

  • Choi K (2020) The occurrence of overtourism and the struggle for sustainable tourism development. KIU J Econ Int Studies 5:193–206

    Google Scholar 

  • Esmaeili L, Mardani S, Alireza S, Golpayegani H, Madar ZZ (2020) A novel tourism recommender system in the context of social commerce. Expert Syst Appl 149:1–11

    Article  Google Scholar 

  • García-Palomares JC, Gutiérrez J, Mínguez C (2015) Identification of tourist hot spots based on social networks: a comparative analysis of European metropolises using photo-sharing services and GIS. Appl Geogr 63:408–417

    Article  Google Scholar 

  • Hida M, Kanaya Y, Kawanaka S, Matsuda Y, Nakamura Y, Suwa H, Fujimoto M, Arakawa Y, Yasumoto K (2020) On-site trip planning support system based on dynamic information on tourism spots. Smart Cities 3(2):212–231

    Google Scholar 

  • Himono D, Ieiri Y, Hishiyama R (2020) Analysis of guided person’s behavior history at the time of guidance using AR-POI. Proceeding of the 82th national convention of IPSJ 2020(1):227–228

    Google Scholar 

  • Hirota M, Endo M, Kato D, Ishikawa H (2019) Discovering hotspots using photographic orientation and angle of view from social media site. Int J Inf Soc 10(3):109–117

    Google Scholar 

  • Ikeda T, Yamamoto K (2014) Development of social recommendation GIS for tourist spots. Int J Adv Comput Sci Appl 5(12):8–21

    Google Scholar 

  • Itou J, Mori T, Munemori J, Babguchi N (2018) Development of a stroll support system using Route display on a map and image sharing service. In: Egi H, Yuizono T, Baloian N, Yoshino T, Ichimura S, Rodrigues A (eds) Collaboration technologies and social computing. Springer, pp 48–55

    Google Scholar 

  • Japan Tourism Agency, Ministry of Land, Infrastructure, Transport and Tourism (2019) Toward a sustainable advanced country of tourism. 46 p

    Google Scholar 

  • Jannach D, Zanker M, Felferning A, Friedrich G (2010) Recommender systems: An introduction. Cambridge University Press, 352 p

    Google Scholar 

  • Kamakura City (2016) The third stage Kamakura City tourism basic plan. 78 p

    Google Scholar 

  • Kamishima T (2008) Algorithms for recommender systems (2). J Japanese Soc Artif Intell 23(1):89–103

    MathSciNet  Google Scholar 

  • Kato Y, Yamamoto K (2020) Sightseeing spot recommendation system that takes into account the visiting frequency of users. Geo-Information 9(7):411.https://doi.org/10.3390/ijgi9070411

  • Kaufmann M, Siegfried P, Huck L, Stettler J (2019) Analysis of tourism hotspot behaviour based on geolocated travel blog data: the case of qyer. Int J Geo-Inf 8(11):493. https://doi.org/10.3390/ijgi8110493

  • Kawai Y, Kumamoto T (2018) A system to visualize regional congestion degree based on the analysis result of swarm tweets. DEIM Forum 2018:3–4

    Google Scholar 

  • Koga Y, Yamamoto K (2021) A sightseeing planning support system with gamification. J Geogr Inf Syst 13(4):485–507

    Google Scholar 

  • Kurashima T, Iwata T, Irie G, Fujimura K (2010) Travel route recommendation using geotags in photo sharing sites. Proceedings of the conference on information and knowledge management (CIKM), 579–588

    Google Scholar 

  • Kurata Y (2012) Potential-of-interest maps for mobile tourist information services. In: Fuchs M, Ricci F, Cantoni L (eds) Information and communication technologies in tourism 2012. Springer, pp 239–248

    Google Scholar 

  • Kurata Y, Ai H, Sanada F (2015) Creation of innovative tourist maps based on the user-posted data of a photo-sharing site. Int J Tourism Sci 8:151–154

    Google Scholar 

  • Ma Q (2019) Utilization and analysis of user generated contents toward personalized and distributed sightseeing. Trans Inst Syst Control Inf Eng 63(1):32–37

    Google Scholar 

  • Majid A, Chen L, Chen G, Mirza HT, Hussain I, Woodward J (2013) A context-aware personalized travel recommendation system based on geotagged social media data mining. Int J Geogr Inf Sci 27(4):662–684

    Article  Google Scholar 

  • Majid A, Chen L, Tura HT, Hussain I, Chen G (2015) A system for mining interesting tourist locations and travel sequences from public geo-tagged photos. Data Knowl Eng 95:66–86

    Article  Google Scholar 

  • Masron T, Mohamaed B, Marzuki A (2015) GIS base tourism decision support system for Langkawi Island, Kedah, Malaysia. Theoret Empirical Res Urban Manag 10(2):21–35

    Google Scholar 

  • Masron T, Ismail N, Marzuki A (2016) The conceptual design and application of web-based tourism decision support systems. Theoret Empirical Res Urban Manag 11(2):64–75

    Google Scholar 

  • Mizutani Y, Yamamoto K (2021) A sightseeing spot recommendation system that takes into account the change in circumstances of users. Int J Geo-Inf 6(10):303. https://doi.org/10.3390/ijgi6100303

  • Noguera JM, Barranco MJ, Segura RJ, Martinez L (2012) A mobile 3D-GIS hybrid recommender system for tourism. Inf Sci 215:37–52

    Article  Google Scholar 

  • Singh SP, Sharma J, Singh P (2011) A geo-referenced information system for tourism (GeoRIST). Int J Geomatics Geosci 2(2):456–464

    Google Scholar 

  • Sugimoto K (2018) Use of GIS-based analysis to explore the characteristics of preferred viewing spots indicated by the visual interest of visitors. Landsc Res 43(3):345–359

    Article  Google Scholar 

  • Sumitomo Y, Ishino T, Kubo K, Yue W (2020) Construction and demonstration experiment of similar spot recommendation system based on emotion word contained in word-of-mouth information. J Japan Personal Comput Appl Technol Soc 14(1):29–35

    Google Scholar 

  • Totsuka K, Murata T (2021) Evaluation of an avoiding method for tourist concentration using agent-based simulation. Proceeding of the 24th subcommittee workshop of social system of the SICE section of system and information, 116–120

    Google Scholar 

  • United Nations World Tourism Organization (UNWTO) (2016) Overtourism?—Understanding and managing urban tourism growth beyond perceptions, 12 p

    Google Scholar 

  • Zhuang C, Ma Q, Liang X, Yoshikawa M (2015) Discovering obscure sightseeing spots by analysis of geo-tagged social images. Proceedings of the 2015 IEEE/ACM international conference on advances in social networks analysis and mining (ASONAM), 590–595

    Google Scholar 

Download references

Acknowledgements

In the operation of the tourism support system to promote distributed travel adopting GIS and recommendation system, and the web questionnaire survey of the present study, enormous cooperation was received from those in Japan. We would like to take this opportunity to gratefully acknowledge them.

Author information

Authors and Affiliations

Authors

Corresponding author

Correspondence to Kayoko Yamamoto .

Editor information

Editors and Affiliations

Rights and permissions

Reprints and permissions

Copyright information

© 2023 The Author(s), under exclusive license to Springer Nature Switzerland AG

About this paper

Check for updates. Verify currency and authenticity via CrossMark

Cite this paper

Kato, Y., Yamamoto, K. (2023). Promoting Sustainable Travel Through a Web-Based Tourism Support System. In: Goodspeed, R., Sengupta, R., Kyttä, M., Pettit, C. (eds) Intelligence for Future Cities. CUPUM 2023. The Urban Book Series. Springer, Cham. https://doi.org/10.1007/978-3-031-31746-0_14

Download citation

  • DOI: https://doi.org/10.1007/978-3-031-31746-0_14

  • Published:

  • Publisher Name: Springer, Cham

  • Print ISBN: 978-3-031-31745-3

  • Online ISBN: 978-3-031-31746-0

  • eBook Packages: EngineeringEngineering (R0)

Publish with us

Policies and ethics