Modeling and solving used sailboat market strategy and pricing method

Abstract

The value of a sailboat changes with age and market conditions, and the price of a sailboat is also affected by many factors such as manufacturer, variant, length, etc. Based on this, the purpose of this article modeling is to study the pricing of used sailboats so that brokers can sell them better. This paper explains the market situation and appropriate pricing of sailboats through the following methods. Firstly, data cleaning and processing are performed to construct an influence factor map for the value of second-hand sailboats, establish an influence factor matrix and network, and utilize a decision tree model to explain the pricing. Additionally, other data resources are incorporated to enhance the accuracy of the model, and statistical software is used for modeling and validation. A multiple regression model is established to convert geographic area variables into dummy variables, assess the impact of geographic regions on prices through multiple linear regression, and explain the practical and statistical significance. The regression model is then employed to predict prices in the Hong Kong market, with comparisons to actual market data to demonstrate practical and statistical significance. Lastly, a cluster analysis algorithm is implemented to classify second-hand sailboats and improve sales effectiveness. In summary, the team prepared a report through modeling and solving, which explained the market for sailing boats and reasonable quotations for second-hand sailboats.