Forecasting Commercial Vehicle Demand Using a Multiple Linear Regression Model

Abstract

The purpose of this study was to develop predictive equations and explore the elements that are having an effect on the demand for commercial vehicles in Thailand. The Consumer Price Index (CPI), the Business Sentiment Index (BSI), the price of diesel fuel, and the desire for electric cars were all factors that were considered while compiling this information from a database of newly registered automobiles. Multiple regression analysis, consisting of a linear model and a quadratic model, was utilized to investigate how the presence of a variety of influences influenced the demand for commercial cars. Both the Consumer Price Index and the relationship between the CPI and diesel fuel costs were shown to have a considerable impact on the demand for commercial vehicles. This was the case regardless of which factor was considered first. It was determined that there was a connection between these two parameters of 74.96% after doing the necessary calculations.