According to the different organizational forms of logistics in manufacturing, the types of linkage development between the logistics and manufacturing industries include two different logistics service modes: logistics outsourcing and logistics self-operation. This study considers two manufacturing clusters for comparison: the northeast region in China, mainly state-owned and self-operated, and the Yangtze River Delta region in China, mainly focusing on logistics outsourcing services. First, we construct a parallel network system considering heterogeneity and an unexpected super-efficiency slacks-based measure: the Grey Relational Analysis model. Second, considering the unexpected output, this study evaluates the environmental performance of the linkage development of the logistics and manufacturing industries and explains the types of linkage development between them. Finally, the spatial and temporal characteristics of linkage efficiency under different linkage modes are studied using an exploratory spatial data analysis method. The research results show that the efficiency of the two-industry linkage in different linkage types that consider the unexpected output presents different development characteristics. Regarding time characteristics and trends, we compare the development efficiency of the two-industry linkage at the overall level of the northeast and the Yangtze River Delta regions from 2009 to 2016. The Yangtze River Delta region showed a higher state of linkage while the northeast region showed a medium linkage state. Regarding spatial pattern evolution, the effect of the technical efficiency of the linkage between the two industries in the three northeastern provinces showed continuous evolution from the medium linkage stage to the weak linkage stage, and the Yangtze River Delta showed continuous evolution from the medium linkage to the strong linkage stage.Implications: Due to data availability, references to the relevant achievements of the research on the linkage between the manufacturing and logistics industries, the transportation industry, warehousing, and postal and telecommunications industry data are generally used as logistics industry data. Manufacturing data are replaced by industrial data. The manufacturing industry is the core industry of industrial systems. Its output value accounts for more than 90% of the industrial output. Thus, it can reflect the development trend of the manufacturing industry in general.