Research on the structural characteristics and influencing factors of global environmental services trade networks.

The development of the environmental services trade is crucial to achieving climate goals and a green economic transition. Based on environmental services trade data from 2001 to 2019, this work uses the social network analysis (SNA) method to depict the structural features of global environmental services trade networks, empirically testing the influencing mechanism of network evolution based on the quadratic assignment procedure (QAP) model. The results indicate that the global environmental services trade is now in a rebound stable period.

Spatial-temporal variation characteristics and evolution of the global industrial robot trade: A complex network analysis.

Industrial robots are a strategic future technology and an important part of the development of artificial intelligence, and they are a necessary means for the intelligent transformation of manufacturing industry. Based on global industrial robot trade data from 1998 to 2017, this paper applies the dynamic complex network analysis method to reveal the spatial and temporal variation characteristics and trade status evolution of the global industrial robot trade network. The results show that the global industrial robot network density has steadily increased, and the industrial robot trade has been characterized by 'diversification'.