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Tourism demand, low cost carriers and European institutions: The case of Brussels

Author

Listed:
  • Anabela Marques Santos
  • Michele Cincera

Abstract

The flow of tourism to a region is highly dependent on its accessibility and the cost of travel represents the main economic factor explaining tourism demand. The arrival of low cost carriers (LCC), with cheaper air fares, greatly leveraged the tourist flow around the world. However, as argued by some authors, if the destination is unique the importance of accessibility could be less relevant. Using quarterly data from 2000 to 2015, the paper assesses the effect of LCC on tourism demand focusing on Brussels. The peculiarity of Brussels comes from the high concentration of European and International institutions located in the city, which makes it a very interesting and singular case of research. Results reveal that LCC per se have a smaller positive effect on tourism demand for business purpose than the specific characteristic of Brussels. Indeed, the presence of European institutions complements the higher availability of low air fares, especially for business travellers.

Suggested Citation

  • Anabela Marques Santos & Michele Cincera, 2018. "Tourism demand, low cost carriers and European institutions: The case of Brussels," ULB Institutional Repository 2013/290326, ULB -- Universite Libre de Bruxelles.
    • Handle: RePEc:ulb:ulbeco:2013/290326
    Note: SCOPUS: re.j
    as

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    Cited by:

    1. Ashmi Banerjee & Tunar Mahmudov & Emil Adler & Fitri Nur Aisyah & Wolfgang Wörndl, 2025. "Modeling sustainable city trips: integrating $$\text {CO}_{2}\text {e}$$ CO 2 e emissions, popularity, and seasonality into tourism recommender systems," Information Technology & Tourism, Springer, vol. 27(1), pages 189-226, March.
    2. MARQUES SANTOS Anabela & MADRID Carmen & HAEGEMAN Karel & RAINOLDI Alessandro, 2020. "Behavioural changes in tourism in times of Covid-19: Employment scenarios and policy options," JRC Research Reports JRC121262, Joint Research Centre.
    3. Recep Ulucak & Ali Gökhan Yücel & Salih Çağrı İlkay, 2020. "Dynamics of tourism demand in Turkey: Panel data analysis using gravity model," Tourism Economics, , vol. 26(8), pages 1394-1414, December.
    4. Michał Roman & Monika Roman & Monika Wojcieszak-Zbierska, 2022. "Health Tourism—Subject of Scientific Research: A Literature Review and Cluster Analysis," IJERPH, MDPI, vol. 20(1), pages 1-17, December.
    5. Patrycjusz Zarębski & Grzegorz Kwiatkowski & Ewa Malchrowicz-Mośko & Ove Oklevik, 2019. "Tourism Investment Gaps in Poland," Sustainability, MDPI, vol. 11(22), pages 1-19, November.
    6. Gour Gobinda Goswami & Meshbaul Hassan Chowdhury & Mostafizur Rahman & Mahnaz Aftabi Atique, 2024. "Australian Tourist Flow: A Gravity Model Approach," Sustainability, MDPI, vol. 16(13), pages 1-14, July.
    7. Michał Żemła, 2020. "Reasons and Consequences of Overtourism in Contemporary Cities—Knowledge Gaps and Future Research," Sustainability, MDPI, vol. 12(5), pages 1-20, February.
    8. Vergori, Anna Serena & Arima, Serena, 2022. "Low-cost carriers and tourism in the Italian regions: A segmented regression model," Annals of Tourism Research, Elsevier, vol. 97(C).
    9. Tianzhi Liu & Fen Luo & Jiawen He, 2023. "Evolution of Spatial Structure of Tourist Flows for a Domestic Destination: A Case Study of Zhangjiajie, China," Sustainability, MDPI, vol. 15(4), pages 1-19, February.
    10. Wang, Huan & Tsui, Kan Wai Hong & Wu, Hanjun & Fu, Xiaowen & Wang, Xuecheng, 2025. "External environments and the growth of low-cost carriers in the Asia-Pacific region: A systematic review and future research agendas," Research in Transportation Economics, Elsevier, vol. 109(C).
    11. Michał Roman & Monika Roman & Arkadiusz Niedziółka, 2020. "Spatial Diversity of Tourism in the Countries of the European Union," Sustainability, MDPI, vol. 12(7), pages 1-16, March.
    12. Abdelghany, Ahmed & Guzhva, Vitaly S., 2022. "Exploratory analysis of air travel demand stimulation in first-time served markets," Journal of Air Transport Management, Elsevier, vol. 98(C).

    More about this item

    Keywords

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    JEL classification:

    • C22 - Mathematical and Quantitative Methods - - Single Equation Models; Single Variables - - - Time-Series Models; Dynamic Quantile Regressions; Dynamic Treatment Effect Models; Diffusion Processes
    • L93 - Industrial Organization - - Industry Studies: Transportation and Utilities - - - Air Transportation
    • L83 - Industrial Organization - - Industry Studies: Services - - - Sports; Gambling; Restaurants; Recreation; Tourism

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