Factors affecting evolution of the interprovincial technology patent trade networks in China based on exponential random graph models.

Abstract Five China's interprovincial patent trade networks over the period 2012–2016 are established on the basis of patent transfer information collection, transfer entity identification, and regional mapping. Based on the analysis of patent trade trends and the characteristics of the network structure, endogenous structural effects and exogenous factors affecting the evolution of the trade networks are proposed, and exponential random graph models (ERGMs) constructed to select the most parsimonious model. Based on the variables in the most parsimonious model, temporal ERGM is used to determine the factors of trade networks evolution among provinces. The results provide six key factors affecting network evolution over the period 2012–2016, i.e., reciprocity, eastern output effect, intensity of technological R&D, proximity to economic center, and technology openness. Moreover, analysis reveals that the concentration of technology in provinces is the key factor inhibiting evolution, while differences among provinces on economic levels, technology trade experience, the technology receiving of western provinces, and the geographical proximity of provinces exhibit a weak effect on the evolution process. Finally, suggestions to promote interprovincial patent trade are proposed. Highlights • Five China's interprovincial patent trade networks over the period 2012–2016 are established. • Temporal exponential random graph model is introduced to explore the factors affecting networks evolution. • 6 of the 10 hypotheses regarding network evolution are supported. • The pivotal driving factors and inhibitory factors for network evolution are revealed. [ABSTRACT FROM AUTHOR]