The impact of social media on university students' revisit intention in sports tourism: A hybrid method based on SEM and ANN.

The primary aim of this study is to explore the influence of social media on university students' revisit intention in sports tourism, using Expectation-Confirmation Model and the Uses and Gratifications Theory. A structured questionnaire was distributed to a random sample of 435 students from three universities in Hubei Province to measure their self-reported responses across six constructs: perceived usefulness, information quality, perceived enjoyment, electronic word-of-mouth (eWOM), satisfaction, and revisit intention. Employing a hybrid approach of Structural Equation Modeling (SEM) and Artificial Neural Networks (ANN), the study explains the non-compensatory and non-linear relationships between predictive factors and university students' revisit intention in sports tourism. The results indicate that information quality, perceived enjoyment, satisfaction, and eWOM are significant direct predictors of revisit intention in sports tourism. In contrast, the direct influence of perceived usefulness on revisit intention is insignificant. ANN analysis revealed the normalized importance ranking of the predictors as follows: eWOM, information quality, satisfaction, perceived enjoyment, and perceived usefulness. This study not only provides new insights into the existing literature on the impact of social media on students' tourism behavior but also serves as a valuable reference for future research on tourism behavior.