Utilizing Machine Learning for Analysing Digital Marketing's Influence on Gen-Z Travellers’ Destination Selection

Abstract

Digital marketing significantly influences travellers’ decision-making processes. This research aims to analyze the specific digital marketing strategies affecting Gen-Z travellers’ decisions. Machine learning techniques were employed to uncover key insights. Data were collected through a survey using a convenience random sampling of 346 university students in Thailand. Correlation analysis and machine learning approaches, such as logistic regression and neural network analysis, were used to explore the relationships between various digital marketing strategies and their impact on Gen-Z travellers’ destination choices. The findings indicate that Online Travel Agency (OTA) websites exert the most significant influence on Gen-Z travellers’ decision-making processes, with an odds ratio of 1.6879. This is followed by the use of social media marketing strategies and businesses having their own websites. To validate these results, an Artificial Neural Network (ANN) technique was also employed, confirming the importance of rankings derived from the logistic regression analysis. This research provides valuable insights into which digital marketing strategies most influence Gen-Z travellers’ decision-making processes. These insights can help tourism businesses make informed investments in digital marketing strategies, prioritizing those that align with the preferences of Gen-Z travellers.