Research on the Evaluation of Technological Innovation Efficiency of Different Industrial Enterprises in China
Qian Zhang, Liangcan Liu
Available Online 2 November 2020.
- https://doi.org/10.2991/assehr.k.201030.057How to use a DOI?
- efficiency of technological innovation, DEA, industrial enterprises above designated size
- This paper takes 21 kinds of industrial enterprises above designated size with different property rights in China from 2015 to 2017 as the research object. The construction input indicators are the full-time equivalent of R&D personnel, R&D expenditure, new product development expenditure while output indicators are the number of patent applications and new product sales. Revenue is used as an indicator system to measure the efficiency of technological innovation. Based on the investment perspective, the BC2-DEA model and the Malmquist-DEA model are used to calculate. The results show that the overall technological innovation efficiency of industrial enterprises above designated size in China has not reached the DEA efficiency. The reason is related to the disadvantages of the nature of the enterprise. For example, a wholly state-owned enterprise has no residual recourse and lacks of fundamental interest drive, which leads to its low efficiency in technological innovation. Finally, in view of the status quo of technological innovation efficiency of industrial enterprises above designated size in my country, appropriate suggestions for improving technological innovation efficiency are put forward.
- Open Access
- This is an open access article distributed under the CC BY-NC license.
Cite this article
TY - CONF AU - Qian Zhang AU - Liangcan Liu PY - 2020 DA - 2020/11/02 TI - Research on the Evaluation of Technological Innovation Efficiency of Different Industrial Enterprises in China BT - 2020 International Conference on Social Sciences and Big Data Application (ICSSBDA 2020) PB - Atlantis Press SP - 277 EP - 283 SN - 2352-5398 UR - https://doi.org/10.2991/assehr.k.201030.057 DO - https://doi.org/10.2991/assehr.k.201030.057 ID - Zhang2020 ER -