IMproving Sustainable Development Policies and PrActices to assess, diversify and TOURis (Impactour)

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Budget
2 971 250 €
Partners
12
Coordinated by
UNINOVA
The main ambition of IMPACTOUR project is to create an innovative and easy-to-use methodology and tool to measure and assess the impact of Cultural Tourism (CT) on European economic and social development and to improve Europe’s policies and practices on CT, strengthening its role as a sustainable driving force in the growth and economic development of European regions.

The main ambition of IMPACTOUR project is to create an innovative and easy-to-use methodology and tool to measure and assess the impact of Cultural Tourism (CT) on European economic and social development and to improve Europe’s policies and practices on CT, strengthening its role as a sustainable driving force in the growth and economic development of European regions. 

IMPACTOUR proposes to bring together CT-related stakeholders and researchers to achieve new approaches taking advantage of the large amounts of information that confront policy-makers. IMPACTOUR will deliver an innovative methodology and tool (combining data analytics algorithms with artificial intelligence and machine learning strategies) providing CT stakeholders with strategic guidance so that policies and practices on CT can be improved.

Cultural tourism as a factor of Europeanisation

Cultural tourism (CT) is considered a factor of economic growth and a bridge between different cultures in the development of European regions. However, the impacts of the different types of CT are not yet estimated. Another question remains about the adequate cross-border strategies used to reach sustainable development. The EU-funded IMPACTOUR project will connect CT stakeholders and researchers envisaging new approaches and methods that will support European CT, reinforce a feeling of belonging, value minority cultures and promote Europeanisation. The project will elaborate on an advanced and adaptable methodology to estimate the impact of CT on EU regional economic growth. It will combine data analytics algorithms with machine learning and AI approaches to improve policies and actions on CT.