Green Technology Collaboration Network Analysis of China's Transportation Sector: A Patent-Based Analysis

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Abstract

The development of green transportation technologies in China has grown rapidly due to increasing concerns about climate change and environmental pollution. Collaboration innovations covering kinds of participating entities and various linked relationships have become one of the critical drivers for the transportation sector. Some researchers have analysed the collaborative innovation of scientific literature in this field. However, fewer studies have investigated the current performance of collaborative technology innovation represented by patents in the transportation sector. In this context, a research framework based on the social network analysis approach is proposed for collaboration green transportation technologies. The purpose of the research is to establish an analytical framework for the green transportation innovation network and seek the key collaboration activities and strategies. Subsequently, a collaborative innovation network based on the patent data of green transportation technologies was built and analysed. Especially, the innovation entities in the collaboration network are divided into four groups: business enterprises, individuals, universities, and research institutions, so that more detailed information in the network could be obtained. The results show that the proposed research framework based on patent data and social network analysis method helps examine the critical nodes and links in the network, as well as their types and characteristics of the collaboration network. The increasing number of green transportation technologies shows active cooperation in this field. The study also found that business enterprises node gradually plays a major role in cooperative innovation. The corresponding policy recommendations are also provided.

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Huang, L., Xu, Y., Pan, X., & Zhang, T. (2021). Green Technology Collaboration Network Analysis of China’s Transportation Sector: A Patent-Based Analysis. Scientific Programming, 2021. https://doi.org/10.1155/2021/9961071

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