Variables and data sources.

Accurately forecasting new energy passenger vehicle sales is essential for developing effective marketing strategies and supporting government policies. Consumers purchase decisions for new energy passenger vehicles are primarily driven by product value, which is shaped by various product attributes that evolve through technological advancements. In this study, we develop a product value function for new energy vehicles based on the theory of value engineering. Then, the product value is integrated into the Bass model, and an Improved Bass Model based on Product Value (IBMPV) is proposed. The experiment results demonstrate that the IBMPV outperforms the Bass, Gompertz, Logistic and ARMAX models in terms of goodness of fit and predictive accuracy, making it more suitable for forecasting new energy passenger vehicle sales. The market potential for new energy passenger vehicles exhibits exponential growth as product value improves. Furthermore, we find that while enhanced product value increases the influence of external factors, it simultaneously reduces the influence of internal factors. This study provides a quantitative assessment of the role of product value on new energy passenger vehicle diffusion and presents a practical framework for sales forecasting.