The rapid development of the logistics industry has made considerable contributions to China’s industrial transformation and economy soaring. However, the improvement of logistics competitiveness often leads to high carbon emissions. Understanding the dynamic relationship between logistics competitiveness, logistics carbon emission efficiency, and industrial structure upgrading is of great significance for promoting the high-quality development of regional logistics under the context of the carbon-neutrality target. This study employed the panel vector autoregression (PVAR) model to analyse the relationship between logistics competitiveness, logistics carbon emission efficiency, and industrial structure upgrading based on the data from 30 provincial – regions in China for the period of 2007–2021. Meanwhile, the impulse response function was used to reflect the dynamic relationship between the variables of the model, and using variance decomposition to display the percentage change of one variable affected by another variable. The results show that there are self-adjustment effects in logistics competitiveness, logistics carbon emission efficiency, and industrial structure upgrading. Besides, a U-shaped effect is observed from the effect of logistics competitiveness on logistics carbon emission efficiency. It shows a negative impact in the short term and a positive impact in the long term. And it is the same as the effect of logistics carbon emission efficiency on logistics competitiveness, indicating the existence of the time-lag effect. Moreover, upgrading industrial structures has a positive promoting effect on both logistics carbon emission efficiency and logistics competitiveness. Thus, this research provides a unique perspective by exploring how to improve the development of the logistics industry by discussing the nexus between logistics competitiveness, logistics carbon emission efficiency, and industrial structure upgrading.