Analysis and Forecast of Monthly Tourist Arrivals and Revenue using the ARIMA Model: A Case of Thailand

Abstract

Thailand is one of the world's most popular tourist destinations, known for its rich cultural heritage, diverse landscapes, and vibrant cities. Tourism plays a crucial role in the country's economy, contributing significantly to GDP and employment. Among the numerous tourist destinations in Thailand, Phuket stands out as a premier location, attracting millions of international tourists each year due to its pristine beaches, luxury resorts, and vibrant nightlife. Phuket's tourism industry is a major economic driver, generating substantial revenue and influencing the overall growth of the national tourism sector. This research comprises two primary components aimed at enhancing the understanding and management of tourism in Thailand. The first component involves the creation of data visualizations depicting the number of tourists and the revenue generated from tourism in each province of Thailand from 2020 to 2023. The focus is primarily on Phuket, a globally renowned tourist destination, to compare its tourism statistics with those of other provinces. Phuket is highlighted due to its significant annual tourist influx and substantial contribution to national revenue. These visualizations are crucial for identifying trends, making comparisons, and informing strategic decisions for stakeholders. The second component utilizes the ARIMA Model, a widely-used statistical model for time series data forecasting, to predict the daily number of tourists and the associated revenue for each province in Thailand. These forecasts extend to the year 2028, offering insights into the future growth of Thailand's tourism sector. The emphasis remains on Phuket, with comparative analyses involving other provinces. Overall, this paper provides a comprehensive dataset highlighting trends in tourist statistics and revenue generation, including projected forecasts. The forecasted data is very important for decision-making, providing both government and private sectors with valuable information to optimize tourism management, enhance competitiveness, and promote sustainable tourism development. This data-driven approach ensures that strategies are based on robust evidence, facilitating more effective and efficient tourism planning and operations.