China’s Provincial Vehicle Ownership Forecast and Analysis of the Causes Influencing the Trend

Abstract

The growth of vehicle ownership not only brings opportunity for the economy, but also brings environment and transport problems, which is not good for sustainable transportation. It is of great significance to build supporting infrastructure and other services based on accurate forecasts of vehicle ownership in various provinces because of the variance of economic development stages, the carrying capacity of resources, and different degrees of transport planning in each province. We used the Gompertz model in order to predict China’s provincial vehicle ownership from 2018 to 2050. Considering the impact of the population structure, we summed up the growth rate of GDP per labor, the growth rate of population and the growth rate of employment rate to get the growth rate of GDP and then the GDP per capita of each province. We found that the vehicle ownership in each province will grow rapidly in the next 30 years; however, the change in the ranking of vehicle ownership among provinces varies. The ranking of some provinces with high or middle ranking now will decline in the following years, especially Beijing, Tianjin, Shanghai and Xinjiang. While the ranking of some provinces that locates in the middle and low ranking now will increase, such as Chongqing, Hubei, Anhui, Sichuan, Heilongjiang, Jiangxi, Hunan and Guangxi. We also investigate the reasons that affect the trend in each province and we find that the suitable vehicle growth pattern of each province, the stage of economic development and government policy, which are related to the growth rate of GDP per labor, employment rate, and GDP per capita, can affect vehicle ownership in the future.

The Markets of Green Cars of Three Countries: Analysis Using Lotka–Volterra and Bertalanffy–Pütter Models

“…The best outcome was achieved by BP(1.19, 1.2), with R 2 > 99.8% for seven data. Furthermore, for different technologies, certain named trend models provided fits that were close to the best achievable fits (Table 5): the Brody model was suitable for gas cars, the Gompertz model (logistic growth was suitable, too) for electric and hybrid cars (this confirms the finding of [36]), and the West model (the Bertalanffy model and logistic growth were suitable, too) for conventional cars (diesel, gasoline). For these models, R-squared was close to the largest R-squared that could be achieved by a single model for all datasets of these classes.…”

“…We decided to use the BP model as it is known to be flexible [33] and as it includes as special cases several simple three-parameter models which have been used previously in the analysis and forecasting of technology diffusion and business trends [34,35]. Specifically, the modeling of the automotive market has often used logistic growth [5,23] or the Gompertz model [36][37][38].…”

The Efficiency of the Sustainable Development Policy for Energy Consumption under Environmental Law in Thailand: Adapting the SEM-VARIMAX Model

“…Wang et al [82] predicted air temperature by introducing a new integrated model, the Variational Mode Decomposition-Autoregressive Integrated Moving Average (VMD-ARIMA), which was found to be effective in providing accurate temperature forecasting. Ma et al [83] [86] explored the connection between household energy use and residential building costs by using time series methods, the exponential smoothing method, the autoregressive integrated moving average (ARIMA) model and the artificial neutral networks (ANNs) model. In the study, the ANNs model was proven to be the most accurate for cost forecasting.…”

Government Intervention and Automobile Industry Structure: Theory and Evidence from China

“…The economic development process of various countries in the world shows that vehicle ownership gradually increases with the development of economy, especially GDP per capita [1]. Although the automobile manufacturing industry increased rapidly in China, automobile maintenance industry less developed compared with developed countries and has not received enough attention [2].…”

“…Although some researchers focus on sustainable district development [46], balanced development of industry structure is also important. Finally, the research about China's automobile industry mainly focus on the manufacturing industry currently, such as the prediction of vehicle ownership [1,47,48], study on life cycle cost of electric vehicle [49][50][51][52], the bottleneck in the development of electric vehicles [53][54][55], and research on the development and market scale of ride-hailing [56,57]. There is little literature on automobile maintenance industry; however, we need to fully understand the development of the automobile industry, including the maintenance industry to promote sustainable development.…”