Demand Forecasting for Ensuring Safety and Boosting Operational Efficiency in Hotel Hospitality Using ARIMA Model

The Hotel Demand Forecasting Model leverages the ARIMA model to enhance safety and operational efficiency in the hospitality industry. By integrating historical data, market trends, and safety parameters, the model accurately forecasts guest demand amidst unpredictable factors like fluctuating travel trends and evolving safety regulations. Traditional models often fail to account for these variables, leading to inefficiencies and safety concerns. This model aims to establish a robust system that considers the interconnectedness of Property Management System (PMS) data, staff productivity, and procurement efficiency, optimizing hotel operations. The research employs Exploratory Data Analysis (EDA) with Multivariate Graphical techniques to uncover patterns and trends impacting demand. Implemented in MATLAB, the proposed model achieves 91% accuracy, offering a strategy that balances automation, efficiency, and safety. By automating demand prediction, hotels can optimize resource allocation, proactively respond to demand fluctuations, and prioritize guest satisfaction while maintaining safety protocols.