A Study on the Second-hand Sailboat Price Prediction Model Based on Principal Component Analysis and Multiple Linear Regression

This paper proposes a second-hand sailboat price prediction model based on Principal Component Analysis (PCA) and Multiple Linear Regression (MLR) to address issues of non-transparent transactions and information asymmetry in the market. By analyzing four key indicators year, condition, appearance, and performance and categorizing national economic development levels using the Regional Economic Development Index (REDI), we transform these levels into dummy variables. Separate regression analyses were conducted for monohull and catamaran sailboats. The study shows that the year, appearance, and performance of sailboats are highly positively correlated with their prices, and regional economic development levels significantly affect prices. The model demonstrates excellent performance in predicting second-hand sailboat prices, aiding sellers in pricing accurately and promoting market transparency and development.