Publication Details
Issue: Vol 9, No 9 (2026)
Pages: 521-531
ISSN: 2576-5973

Abstract

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 management