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Data Science and Digital Business pp 157–171Cite as

Furthering Big Data Utilization in Tourism

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Abstract

In recent years, so-called “big data” have been attracting the attention of companies and researchers. This chapter aims to identify the number of visitors of each period and their characteristics based on the location data of mobile phone users collected by the mobile phone company. The study sites of this survey are tourist destinations in Ishikawa Prefecture and Toyama city, including Kanazawa city, which became nationally popular after the Hokuriku Shinkansen opened in 2015.

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References

  1. Dolnicar, S., & Ring, A. (2014). Tourism marketing research: Past, present, and future. Annals of Tourism Research, 47, 31.

    Article  Google Scholar 

  2. Bello-Orgaz, G., Jung, J. J., & Camacho, D. (2016). Social big data: Recent achievements and new challenges. Information Fusion, 28, 45–59.

    Article  Google Scholar 

  3. Fuchs, M., Höpken, W., & Lexhagen, M. (2014). Big data analytics for knowledge generation in tourism destinations—A case from Sweden. Journal of Destination Marketing & Management, 3(4), 198–208.

    Article  Google Scholar 

  4. Xiang, Z., Schwartz, Z., Gerdes, J. H., Jr., & Uysal, M. (2015). What can big data and text analytics tell us about hotel guest experience and satisfaction? International Journal of Hospitality Management, 44, 120–129.

    Article  Google Scholar 

  5. Ahas, R., Aasa, A., Roose, A., Mark, Ü., & Silm, S. (2008). Evaluating passive mobile positioning data for tourism surveys: An Estonian case study. Tourism Management, 29(3), 469–485.

    Article  Google Scholar 

  6. Japan Tourism Agency, Keitaidenwa kara erareru ichijouhou tou wo katuyousita hounichi gaikokujin doutaichousa houkokusho [Foreign visitors’ dynamics research report utilizing mobile phone location information]. Retrieved from http://www.mlit.go.jp/common/001080545.pdf (2014).

  7. Liu, F., Janssens, D., Wets, G., & Cools, M. (2013). Annotating mobile phone location data with activity purposes using machine learning algorithms. Expert Systems with Applications, 40(8), 3299–3311.

    Article  Google Scholar 

  8. Gao, H., & Liu, F. (2013). Estimating freeway traffic measures from mobile phone location data. European Journal of Operational Research, 229(1), 252–260.

    Article  Google Scholar 

  9. Steenbruggen, J., Tranos, E., & Nijkamp, P. (2015). Data from mobile phone operators: a tool for smarter cities? Telecommunications Policy, 39(3–4), 335–346.

    Article  Google Scholar 

  10. Okinawa Prefecture Culture, Sports, and Tourism Department, Senryakuteki repeater souzou jigyou houkokusho [Report on strategic creation of repeaters]. Retrieved from http://www.pref.okinawa.jp/site/bunka-sports/kankoseisaku/kikaku/report/houkokusixyo/documents/07dairokusiyou.pdf (2013).

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Acknowledgements

This work was supported by JSPS KAKENHI Grant Number JP15K01970.

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Authors and Affiliations

  1. Faculty of Foreign Studies, Nagoya Gakuin University, Nagoya, Japan

    Masahide Yamamoto

Authors
  1. Masahide Yamamoto
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Correspondence to Masahide Yamamoto .

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Editors and Affiliations

  1. ETSI Industriales de Ciudad Real, University of Castilla-La Mancha, Ciudad Real, Spain

    Fausto Pedro García Márquez

  2. LeBow College of Business, Drexel University, Philadelphia, PA, USA

    Benjamin Lev

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Yamamoto, M. (2019). Furthering Big Data Utilization in Tourism. In: García Márquez, F., Lev, B. (eds) Data Science and Digital Business. Springer, Cham. https://doi.org/10.1007/978-3-319-95651-0_9

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