Analyzing New Energy Vehicle Sales Influencing Factors Based on Statistical Learning
DOI:
https://doi.org/10.54097/ema0xe58Keywords:
Quantify, Grey Correlation Analysis, Ridge Regression, TOPSIS.Abstract
Amid global environmental concerns and the push for sustainable development, the electric vehicle (EV) market is expanding swiftly, recognized as pivotal in curbing greenhouse gas emissions and advancing energy diversification. This thesis investigates factors shaping the EV market and assesses the impact of new energy vehicle development on conventional vehicles. Drawing on industry reports, market data, and relevant literature, it delves into key factors influencing China's new energy vehicle market, such as patent counts, public charging infrastructure, and government subsidies. Based on this analysis, recommendations are proposed to foster the sustainable growth of the new energy vehicle market, including subsidies for related industries, fostering technological innovation, and enhancing charging infrastructure. The study offers insights into the current and future trajectory of the electric vehicle market, revealing rapid expansion at the expense of traditional energy vehicles. By quantifying and visualizing the impact of new energy vehicles on traditional counterparts, this research furnishes valuable insights for policymaking in the new energy vehicle sector.
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