RESEARCH WITH IMPACT

dTS | Data-driven Tourism for Sustainability




The Mission

The current developments around COVID-19, but also regarding other influencing variables, e.g., in the area of climate change, have demonstrated how sensitively the tourism ecosystem reacts to disruptive influences and events. It is therefore essential for future development to achieve the highest possible level of resilience through a combination of sustainable concepts, as well as digitalization and the use of technology. While new digital solutions might provide new challenges, the same technologies might provide solutions to the challenge of creating sustainable and resilient tourism for the future, which strengthens and supports regional, national, and European strategies. With the practical application of these technologies, Austria and its regions have the potential to position themselves on a national and international level as an innovative and sustainable destination. In addition, via the use of data-driven innovation, the tourism sector can increase resilience concerning the before-mentioned disruptive forces, as these innovations and underlying technologies increase flexibility and adaptive capacity to mitigate and conquer impacts on business models and the overall ecosystem. Equally important is the accompanying and steering development of destination management concepts, as well as concepts for the scaling of project results for a strategic, sustainable development of regions. A particular focus here is on avoiding the disadvantaging of vulnerable or disadvantaged groups using technology.

The Focus

The dTS project approaches the challenge of intelligent data use for future-oriented development of tourism regions from a digital sustainability perspective, leveraging digitalization and data-driven technologies to address a) ecological, b) economical, c) and societal challenges from a transdisciplinary perspective in the domain of regional tourism. The main goal for the dTS project is to use the combination of AI and agent-based modelling/simulation to contribute to resilient and sustainable regional tourism in Austria on the example of visitor flow control. The active control and management of visitor flows based on the intelligent use of data can help to sustainably alter the behavior of tourists and lead to a better balance of capacities in the long run. Two use cases in the Land Salzburg have been selected with the aim of strengthening the entire region, exhaust mobility resources, and work towards carbon-neutrality. Therefore, the technical developments within the project need to be accompanied by a sustainable point of view to ensure its effectiveness and optimal integration within the regional tourist ecosystem. At the same time, all technical solutions will be following privacy-by-design patterns and strategies concerning the overall architecture, algorithms, data handling, as well as interaction with the system as a whole.

The Goal

To answer the question: “How can the combination of AI and agent-based modelling/simulation contribute to resilient and sustainable regional tourism in Austria on the example of visitor flow control?”, dTS proposes a scalable and portable model for resilient and sustainable tourism. To achieve the development of such a framework, two use cases with different technological maturity levels are being examined. The result will be the design of a scalable data exchange and simulation platform that is also capable to serve as a data circle for visitor flows. Using artificial intelligence and agent-based simulations, the authentic movement and behavior patterns of the target groups are to be learned and understood to then incorporate these findings in the sense of a sustainable and gentle mobility concept. This also enables the modelling of „what-if“ scenarios in the sense of decision support for the respective administrations. They main elements of this investigation will be the development of models for fair AI-based predictions and agent-based simulations as well as the application of a federated data management platform approach. These solutions will be contextualized by an extensive framework for governance, sustainability, and up-scaling.

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