ENHANCING BIG DATA SOLUTIONS IN THE TOURISM INDUSTRY ECONOMIC EFFICIENCY AND FORECASTS INDICATORS
DOI:
https://doi.org/10.5281/zenodo.22688400Abstract
The article examines scientific and methodological approaches to assessing and modeling the efficiency of the tourism industry based on Big Data. It substantiates mechanisms for quantitatively evaluating the impact of Big Data investments on profitability, integrating direct and indirect efficiency indicators, hybrid forecasting of tourism demand, DEA-based destination efficiency analysis, optimal resource allocation, and early risk detection. The KSBI index, KMTM resource allocation model, hybrid ARIMA + ML forecasting model, and IXK risk indicator are proposed as a methodological basis for managing the tourism industry in the digital economy.Keywords
Big Data, tourism economy, efficiency assessment, modeling, KSBI, DEA, hybrid model, ARIMA, machine learning, resource allocation, risk managementReferences
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