Research on Technological Innovation of Listed Companies in Pearl River Delta of China
- https://doi.org/10.2991/icemaess-18.2018.112How to use a DOI?
- Pearl River Delta of China, listed company, R&D, Patent, Income, Selective sample, Tobit model
This paper chooses the 519 companies of the Pearl River Delta listed in China's A-share market and establishes a multivariate linear regression model with the financial data of 2017. Considering the problem of selective samples, OLS and ML methods are used to analyse the general model and Truncated Regression model respectively. The results show that gross trading income has a significant and positive impact on R&D investment. The positive influence of R&D in manufacturing and Information Transmission, Software and Information Technology industries are higher than that in other industries. The R&D level of Listed Companies in Shenzhen is higher than that in other cities. The manufacturing industry has the industrial agglomeration effect of patented technology, but the transformation efficiency of R&D into patented technology is not high in the manufacturing industry. Shenzhen has the urban agglomeration effect of patented technology, but the transformation efficiency of Shenzhen R&D into patented technology is not high; the increase of patents helps to increase gross trading income, and the impact of industrial agglomeration of patents is significant, but the urban agglomeration effect of patents is not significant.
- © 2018, the Authors. Published by Atlantis Press.
- Open Access
- This is an open access article distributed under the CC BY-NC license (http://creativecommons.org/licenses/by-nc/4.0/).
Cite this article
TY - CONF AU - Yan Wu PY - 2018/11 DA - 2018/11 TI - Research on Technological Innovation of Listed Companies in Pearl River Delta of China BT - Proceedings of the 2018 5th International Conference on Education, Management, Arts, Economics and Social Science (ICEMAESS 2018) PB - Atlantis Press SP - 548 EP - 554 SN - 2352-5398 UR - https://doi.org/10.2991/icemaess-18.2018.112 DO - https://doi.org/10.2991/icemaess-18.2018.112 ID - Wu2018/11 ER -