Abstract
China, who owns the largest automobile consuming market, is becoming the largest automobile manufacturing country. However, a gap still lies between China and other traditional automobile manufacturing countries in terms of design capability and production efficiency. Standardization can effectively promote technological innovation and industrial upgradation, which enhances the overall performance of the automobile industry. This paper aims at identifying the structural problem in the automobile standard citation network in China, since the citation relationship reflects the transmission and development of knowledge or technologies. To this end, a dynamic standard citation network model is developed for ease of extraction of standard data at any time points. A set of complex network metrics at both node and network level are chosen with rational explanations in the context of automobile industry. With the data collected from publicized Web sites, the topological evolution of this network is analyzed as well. We significantly show that the standard citation networks at different time periods are generally loosely connected and contain too many isolated nodes. Meanwhile, the critical nodes in the standard citation network also change dynamically. We suggest that these isolated standards should be integrated into the citation network through revision activities.
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Acknowledgements
This work was supported by the National Natural Science Foundation of China [Grant Numbers 71401181, 71701213] and the MOE (Ministry of Education in China) Project of Humanities and Social Sciences [Grant Numbers 14YJC630136 and 15YJC630008].
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Wei, Y., Chen, F., Xue, H. et al. Research on structural dynamics in Chinese automobile standard citation network. Neural Comput & Applic 32, 31–39 (2020). https://doi.org/10.1007/s00521-018-3740-6
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DOI: https://doi.org/10.1007/s00521-018-3740-6