Research on a forecasting model of tourism traffic volume in theme parks in China

Abstract

Abstract In this study, a model based on multiple regression analysis is developed to forecast the tourism traffic volume of theme parks. First, the macro, meso and micro factors affecting traffic passenger volume are analysed. Second, SPSS software is used for multivariate regression analysis on data for 10 theme parks from 2014. A tourism traffic volume forecasting model is then proposed. Finally, related data for 2015 is used to validate the model, with results showing a prediction error of 14.1%. All results show that the model has a high predictive ability.