Abstract:

The coupling and coordination between expressway transportation and regional economy can effectively facilitate the sustainable development of regional economies. However, existing research lacks quantitative studies and the indexes evaluating transportation have not been systematically established, particularly lacking analyses of vehicle type differentiation, energy type classification, and industrial heterogeneity. This paper constructed a multi-dimensional expressway transportation indicator system based on 9 metrics and acquires quarterly data via a cloud platform. The study employs Spearman correlation to analyze the correlation between transportation and economic indicators, applies the entropy method to measure the developmental level of systems, and utilizes vector autoregression and coupling coordination degree models to investigate the dynamic interactions and coupling evolution, thereby testing for small-sample robustness and regional variations. Taking Guangdong Province as a case study, the findings are as follows: (1) The correlation between transportation and the economy exhibits distinct vehicle type-specific characteristics. The correlation of small-vehicle indicators is significantly higher than that of large-vehicle indicators. The average transport distance of large buses shows a strong negative correlation with the secondary industry, while the proportion of new energy vehicles makes a prominent contribution to the correlation with the tertiary industry. (2) There exists a bidirectional causal relationship between expressway transportation and regional economy with notable time lag effects. The demand release of the tertiary industry demonstrates greater elasticity in driving transportation. (3) Since the second half of 2022, the coupling of Guangdong Province has consistently exceeded 0.85. Lagging regions have shown faster improvement, are more sensitive to transportation disturbances, and the contribution of green indicators accounts for approximately 40%. The advantageous indicators mainly include the passenger volume of small buses, the proportion of new energy vehicles, and the turnover volume of large trucks, while the restrictive indicators primarily consist of the turnover volume of small buses, the proportion of new energy in small trucks, and the average transport distance of large trucks. This study reveals that expressway transportation has a stronger impact on economically underdeveloped regions and provides differentiated policy recommendations for promoting balanced regional development.

Key words: transportation economy, system of indicators, coupling coordination degree model, expressway, vector autoregression model