A spatial agent-based model for assessing strategies of adaptation to climate and tourism demand changes in an alpine tourism destination

Journal Article


Abstract


  • A vast body of literature suggests that the European Alpine Region is amongst the most sensitive socioecosystems

    to climate change impacts. Our model represents the winter tourism socio-ecosystem of

    Auronzo di Cadore, located in the Dolomites (Italy), which economic and environmental conditions are

    highly vulnerable to climate variations. This agent-based model includes eight types of agents corresponding

    to different winter tourist profiles based on their socio-economic background and activity

    targets. The model is calibrated with empirical data while results are authenticated through direct

    interaction of local stakeholders with the model. The model is then used for assessing three hypothetical

    and contrasted infrastructure-oriented adaptation strategies for the winter tourism industry, that have

    been previously discussed with local stakeholders, as possible alternatives to the “business-as-usual”

    situation. These strategies are tested against multiple future scenarios that include: (a) future weather

    conditions in terms of snow cover and temperature, (b) the future composition and total number of

    tourists and (c) the type of market competition. A set of socio-economic indicators, which are strongly

    coupled with relevant environmental consequences, are considered in order to draw conclusions on the

    robustness of the selected strategies.

Authors


  •   Balbi, Stefano (external author)
  •   Giupponi, Carlo (external author)
  •   Perez, Pascal
  •   Alberti, Marco (external author)

Publication Date


  • 2013

Citation


  • Balbi, S., Giupponi, C., Perez, P. & Alberti, M. (2013). A spatial agent-based model for assessing strategies of adaptation to climate and tourism demand changes in an alpine tourism destination. Environmental Modelling and Software, 45 29-51.

Ro Metadata Url


  • http://ro.uow.edu.au/smartpapers/104

Number Of Pages


  • 22

Start Page


  • 29

End Page


  • 51

Volume


  • 45

Abstract


  • A vast body of literature suggests that the European Alpine Region is amongst the most sensitive socioecosystems

    to climate change impacts. Our model represents the winter tourism socio-ecosystem of

    Auronzo di Cadore, located in the Dolomites (Italy), which economic and environmental conditions are

    highly vulnerable to climate variations. This agent-based model includes eight types of agents corresponding

    to different winter tourist profiles based on their socio-economic background and activity

    targets. The model is calibrated with empirical data while results are authenticated through direct

    interaction of local stakeholders with the model. The model is then used for assessing three hypothetical

    and contrasted infrastructure-oriented adaptation strategies for the winter tourism industry, that have

    been previously discussed with local stakeholders, as possible alternatives to the “business-as-usual”

    situation. These strategies are tested against multiple future scenarios that include: (a) future weather

    conditions in terms of snow cover and temperature, (b) the future composition and total number of

    tourists and (c) the type of market competition. A set of socio-economic indicators, which are strongly

    coupled with relevant environmental consequences, are considered in order to draw conclusions on the

    robustness of the selected strategies.

Authors


  •   Balbi, Stefano (external author)
  •   Giupponi, Carlo (external author)
  •   Perez, Pascal
  •   Alberti, Marco (external author)

Publication Date


  • 2013

Citation


  • Balbi, S., Giupponi, C., Perez, P. & Alberti, M. (2013). A spatial agent-based model for assessing strategies of adaptation to climate and tourism demand changes in an alpine tourism destination. Environmental Modelling and Software, 45 29-51.

Ro Metadata Url


  • http://ro.uow.edu.au/smartpapers/104

Number Of Pages


  • 22

Start Page


  • 29

End Page


  • 51

Volume


  • 45