Quantifying potential tourist behavior in choice of destination using Google Trends

This study uses the Information Processing Approach and the Theory of Planned Behavior of tourists to extract four time-series constructs from 63 relevant and semantically related keywords on “Kerala Tourism” using Google Trends data. Analyzing these data helps in formulating various strategies to boost tourism in a given region and, subsequently, in proposing a structured methodology that applies different econometric models to predict monthly arrivals of both global and domestic tourists to Kerala. The output of these models showed significant improvement in prediction of tourist arrivals when using these constructs in the ARIMAX models. Moreover this study provides a framework for forecasting tourist arrivals to a destination and helps to predict behaviors influencing tourist destination selection using Google Trends data. These analyses are expected to guide policy makers in understanding and making appropriate decisions to deploy resources at potential tourist destination sites to enhance the potential experience of the tourist.