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The Impact of the COVID-19 Pandemic on the Tourism Sector in the Autonomous Region of Madeira

Author

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  • Paulo Rita

    (NOVA Information Management School (NOVA IMS), Universidade NOVA de Lisboa, 1070-312 Lisbon, Portugal)

  • Nuno António

    (NOVA Information Management School (NOVA IMS), Universidade NOVA de Lisboa, 1070-312 Lisbon, Portugal)

  • João Neves

    (NOVA Information Management School (NOVA IMS), Universidade NOVA de Lisboa, 1070-312 Lisbon, Portugal)

Abstract

The highly regarded and award-winning tourism destination that is the autonomous region of Madeira (ARM), in the Madeira and Porto Santo islands, has suffered the consequences that the COVID-19 pandemic has brought to tourism through the mobility limitations as well as the fear faced by travelers. From data collected on tourism, COVID-19, and demography in ARM from the years 2019 to 2020, this study makes use of data science techniques, including statistics, data mining, and data visualization, to analyze the direct and indirect effects of the coronavirus outbreak as well as the weight of population density in the propagation of the virus. The results validate a direct effect and show evidence of dense regions having aggravated virus propagation, but they do not corroborate the idea that an indirect effect was significant.

Suggested Citation

  • Paulo Rita & Nuno António & João Neves, 2023. "The Impact of the COVID-19 Pandemic on the Tourism Sector in the Autonomous Region of Madeira," Sustainability, MDPI, vol. 15(16), pages 1-17, August.
    • Handle: RePEc:gam:jsusta:v:15:y:2023:i:16:p:12298-:d:1215682
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    References listed on IDEAS

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    1. Scott R. Baker & Nicholas Bloom & Steven J. Davis & Stephen J. Terry, 2020. "COVID-Induced Economic Uncertainty," NBER Working Papers 26983, National Bureau of Economic Research, Inc.
    2. Baser, Onur, 2021. "Population density index and its use for distribution of Covid-19: A case study using Turkish data," Health Policy, Elsevier, vol. 125(2), pages 148-154.
    3. Zhang, Hanyuan & Song, Haiyan & Wen, Long & Liu, Chang, 2021. "Forecasting tourism recovery amid COVID-19," Annals of Tourism Research, Elsevier, vol. 87(C).
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