The digital economy development promotes green transformation in China’s economy. Based on provincial-level data from 2011–2019, an ArcGIS spatial analysis is used to explore the spatial and temporal evolution patterns of the digital economy development and green economic efficiency. The digital economy development’s impact on the green economic efficiency is tested through fixed effect, mediation effect, and spatial Durbin models. The digital economy development and green economic efficiency increased during the study period. Spatial patterns of high-level areas spread to form “clusters” with surrounding areas. The digital economy development’s catalytic effect on the green economic efficiency holds after robustness and endogeneity tests. A heterogeneity analysis shows that the digital economy development promotes the green economic efficiency in the eastern and central regions; the impact on the western region is non-significant. Compared with industry digitalization, digital industrialization has a stronger promoting effect on the green economic efficiency. The digital economy development better facilitates the green economic efficiency in regions with high digital economy development levels and Big Data experimental areas. The digital economy development promotes green economic efficiency through human capital, industrial structure upgrading, and technological innovation; industrial structure upgrading has a stronger mediating effect, reaching 40%. The digital economy development facilitates the regional green economic efficiency and significantly promotes green economic efficiency in neighboring regions through spatial spillover effects.

Based on the POI data of logistics enterprises in Xinjiang in 2012, 2016, and 2020, the ArcGIS spatial analysis technique, geographic detector, and other methods were used for the quantitative analysis of the spatial and temporal distributions of logistics enterprises in Xinjiang during 2012–2020 and the influencing factors. The following findings were obtained in the present study: (1) there was a significant difference in the distributions of logistics enterprises in Xinjiang at different development stages, with unbalance among areas; further, there was a higher number of logistics enterprises in Northern Xinjiang compared with Southern Xinjiang; (2) the spatial distribution of logistics enterprises in Xinjiang was generally characterized by a “northeast–southwest” trend; there was a periodic shift in the distribution center from northeast to southwest; the distribution center remained in Bayingolin Mongol Autonomous Prefecture in 2012 and 2020, and shifted to Changji Hui Autonomous Prefecture in 2016, close to the junction of the two areas; (3) the agglomeration of logistics enterprises in Xinjiang was positively correlated with the scale; the kernel density analysis results revealed that there was obvious spatial differentiation characterized by “multi-center development with core agglomeration and patch distribution at the edge”, and the hotspot areas of logistics enterprises were distributed in major cities, with small variations; the Tianshan Mountain North Slope Economic Belt was the main agglomeration area of logistics enterprises; (4) the results from the geographic detector show that the regional GDP, regional total retail sales of consumer goods, regional utilization of foreign direct investment, and regional fixed assets investment were factors that influenced the spatial distribution of logistics enterprises in Xinjiang, thereby significantly promoting the stable and rapid development of logistics enterprises.