PREDICTIVE MODEL OF INTERNATIONAL TOURIST EXPENDITURE IN BALI FOR THE DEVELOPMENT OF DATA-DRIVEN TOURISM MARKETING STRATEGIES - Kadek Aglena Parisesa; Luh Putu Mahyuni (RADJA PUBLIKA, 2026)
This study aims to analyze international tourist spending patterns in Bali and identify factors influencing these spending levels to support the development of data-driven tourism marketing strategies. The research focuses on comparing tourists from Australia and China, two key tourism markets in Bali. The approach used is quantitative, using multiple regression analysis, the Mann-Whitney test, and the development of a data-driven predictive model. Data was obtained from 200 respondents through online and offline surveys, as well as secondary data from relevant agencies. The results indicate that most tourists fall into the mid-range spending category. Chinese tourists have higher average spending than Australian tourists, despite shorter visit durations, with shopping activities predominating. In contrast, Australian tourists tend to allocate spending on accommodation and food and beverage consumption during longer stays. Furthermore, statistical tests show significant differences in spending by gender, with male tourists spending more than female tourists. Factors such as country of origin, length of stay, accommodation type, and tourist characteristics have been shown to influence spending. This study concludes that a data-driven predictive analytics approach can provide a more comprehensive understanding of tourist behavior and serve as a basis for formulating more effective, segmented tourism marketing strategies oriented toward improving the quality and value of tourist spending.