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Touristic travel behaviour in a spatio-temporal context: Statistical analyses for the identification and development of tourists’ behavioural patterns

Subject Area Human Geography
Term from 2019 to 2023
Project identifier Deutsche Forschungsgemeinschaft (DFG) - Project number 417192137
 
The research project „Touristic travel behaviour in a spatio-temporal context: Statistical analyses for the identification and development of tourists’ behavioural patterns“ investigates how tourists’ behaviour and touristic travel decision-making changes over time and between different spaces. The temporal component focuses in particular on age, cohort and period effects while the spatial component includes destination choice changes as well as tourists’ source market characteristics. Another core element of this project is to detect influencing factors of travel behaviour and triggers of such changes in travel behaviour in order to better estimate and predict future developments of tourism demand. In contrast to past research, travel behaviour patterns of German tourists will be analysed using a comprehensive, representative, yearly dataset that will be extended with secondary data on potential influencing factors. So far, this dataset has mainly been used for cross-sectional univariate analyses. The integrative research cooperation between tourism geographies and statistics, however, enables the application of modern statistical techniques to further inspect this dataset to detect dynamic patterns of travel decision-making and travel behaviour. This will allow the identification and systematisation of changes of tourism demand in a spatio-temporal context as well as the interpretation of these changes from a tourism research perspective. The integration of additional information from secondary data sources into the original dataset makes it possible to specifically investigate external influencing factors (e g. social, political and economic environment), besides internal influencing factors of travel behaviour (e. g. sociodemography, geographical origin) already included in the dataset. Hence, conclusions on determinants of tourism demand can both be drawn from a micro and macro level perspective. Advanced statistical methods are currently only rarely used in tourism research. Especially the application and development of more sophisticated techniques to analyse cross-sectional data for long-term studies is particularly innovative, both for statistics and tourism research. This project aims to enhance the understanding of travel behaviour and travel decision-making going beyond the knowledge from one-time survey studies and to develop refined methods of applied statistics as well as novel ways to publish and impart scientific research results in form of an interactive web portal.
DFG Programme Research Grants
 
 

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