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Tourism, smart specialisation, growth, and resilience

This work analyses the implications of tourism dynamics and smart specialisation strategies on growth and socioeconomic resilience of European regions where tourism is a regional priority. By using a panel data model for 2006–2017, phases of growth, recession, and recovery are scrutinised. A converg...

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Detalles Bibliográficos
Autor principal: Romão, João
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Elsevier Ltd. 2020
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7348604/
https://www.ncbi.nlm.nih.gov/pubmed/32834229
http://dx.doi.org/10.1016/j.annals.2020.102995
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author Romão, João
author_facet Romão, João
author_sort Romão, João
collection PubMed
description This work analyses the implications of tourism dynamics and smart specialisation strategies on growth and socioeconomic resilience of European regions where tourism is a regional priority. By using a panel data model for 2006–2017, phases of growth, recession, and recovery are scrutinised. A convergence process is identified, with higher growth rates for less-developed regions; however, the most developed regions are more resilient. Tourism demand is positively correlated with growth and resilience but a high share of tourism within regional employment has negative impacts on both. Specialisation patterns combining tourism with agriculture have positive effects in both cases. Diversification strategies including unrelated sectors contribute to increased resilience in these regions, and a prioritisation of construction reduces regional resilience.
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spelling pubmed-73486042020-07-10 Tourism, smart specialisation, growth, and resilience Romão, João Ann Tour Res Research Article This work analyses the implications of tourism dynamics and smart specialisation strategies on growth and socioeconomic resilience of European regions where tourism is a regional priority. By using a panel data model for 2006–2017, phases of growth, recession, and recovery are scrutinised. A convergence process is identified, with higher growth rates for less-developed regions; however, the most developed regions are more resilient. Tourism demand is positively correlated with growth and resilience but a high share of tourism within regional employment has negative impacts on both. Specialisation patterns combining tourism with agriculture have positive effects in both cases. Diversification strategies including unrelated sectors contribute to increased resilience in these regions, and a prioritisation of construction reduces regional resilience. Elsevier Ltd. 2020-09 2020-07-10 /pmc/articles/PMC7348604/ /pubmed/32834229 http://dx.doi.org/10.1016/j.annals.2020.102995 Text en © 2020 Elsevier Ltd. All rights reserved. Since January 2020 Elsevier has created a COVID-19 resource centre with free information in English and Mandarin on the novel coronavirus COVID-19. The COVID-19 resource centre is hosted on Elsevier Connect, the company's public news and information website. Elsevier hereby grants permission to make all its COVID-19-related research that is available on the COVID-19 resource centre - including this research content - immediately available in PubMed Central and other publicly funded repositories, such as the WHO COVID database with rights for unrestricted research re-use and analyses in any form or by any means with acknowledgement of the original source. These permissions are granted for free by Elsevier for as long as the COVID-19 resource centre remains active.
spellingShingle Research Article
Romão, João
Tourism, smart specialisation, growth, and resilience
title Tourism, smart specialisation, growth, and resilience
title_full Tourism, smart specialisation, growth, and resilience
title_fullStr Tourism, smart specialisation, growth, and resilience
title_full_unstemmed Tourism, smart specialisation, growth, and resilience
title_short Tourism, smart specialisation, growth, and resilience
title_sort tourism, smart specialisation, growth, and resilience
topic Research Article
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7348604/
https://www.ncbi.nlm.nih.gov/pubmed/32834229
http://dx.doi.org/10.1016/j.annals.2020.102995
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