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Tourism is measured by the statistics of visitor movements, expenditure and estimates of the number of visitor facilities. In the world there are many current tools, methodologies and innovative technologies used to measure the economic impact of tourism. Tourism statistics have been on the frontline of Big Data-related innovations of statistical sources and methods. Data from mobile phones (as part of Big Data set) are increasingly used as new indices for social science research. Therefore, this paper looks for an answer to the question – what is the specifics of a theoretical model for automation tourism economic impact assessment in specific regions via the use of ICT and mobile positioning data (MPD)? Using qualitative research methods authors propose theoretical model based on two interlinked parts. First of which – ‘Data storage’ – can be built upon the most popular BD platform ‘Apache Hadoop Ecosystem’, where the data precision of the online surveys can be increased by implementing mobile positioning solutions. Meanwhile the other part – ‘Data analysis’ – can be based on the locally created assessment methodology, which has been derived from the Finnish standardized economic impact estimation approach. The research results show the findings and propose a theoretical model. Its strength and novelty lies in the ability to use traditional tourism statistics, the economic impact analysis and passive mobile positioning data for spatial characteristics of tourism flow. Its construction is a distinctive combination of typically used technological approaches.

The model of automation and extension of tourism economic impact assessment in specific regions