Based on the panel data of the 11 provinces along the Yangtze River Economic Belt from 1997 to 2015, the super slack-based model (Super-SBM) model is adopted to calculate the provincial-level eco-efficiency of industrial energy. While bringing in time series analysis and spatial differentiation feature analysis, the traditional and spatial Markov probability transition matrix is established. This study delves into the spatial-temporal dynamic evolution traits of the eco-efficiency of industrial energy along the Yangtze River Economic Belt. According to the results: the eco-efficiency of industrial energy of the Yangtze River Economic Belt manifests "single crest" evolution and distribution traits from left to right and top to bottom, indicating that the eco-efficiency of industrial energy of the Yangtze River Economic Belt is steadily improving gradually. However, the overall level is still low and there is still ample room for the improvement of the eco-efficiency of industrial energy. Furthermore, the eco-efficiency of industrial energy along the Yangtze River Economic Belt is elevating. The geographical spatial pattern plays a pivotal role in the spatial and temporal evolution of eco-efficiency of industrial energy, and the spatial agglomeration traits are noticeable.
Keywords: Yangtze River Economic Belt; industrial energy eco-efficiency; spatial Markov chain.