Abstract: In order to scientifically grasp the spatial network structure of carbon emission efficiency in urban transportation and achieve sustainable development in the transportation industry, based on the data of nine national central cities in China from 2011 to 2020, a global super efficiency SBM model (GB-US-Super-SBM model) considering unexpected output was constructed to assess the transportation carbon emission efficiency; the revised spatial gravity model was used to construct the spatial correlation network and, based on this, the social network analysis method was applied to reveal the spatial network structure of transportation carbon emission efficiency and the influencing factors. The results showed that: (1) During the entire study duration, the overall transportation carbon emission efficiency of nine national central cities was relatively low, and there were considerable gaps among the cities. (2) The spatial correlation of transportation carbon emission efficiency in national central cities presented a network structure, gradually forming multiple network centers such as Tianjin, Xi'an and Zhengzhou; the spatial network of transportation carbon emission efficiency shows a trend of first strengthening and then weakening with 2017 as the node; cities such as Tianjin, Xi'an and Zhengzhou served as "bridges" and "intermediaries", playing a crucial role in the shaping of the spatial network. (3) Variations in economic development, urbanization, energy-saving technology and spatial proximity significantly influenced the spatial configuration of carbon emission efficiency in transportation. Among these factors, spatial proximity and differences in the level of economic development exerted the most substantial impact.