Keywords
robot industry, total factor productivity, DEA model, technical efficiency
Abstract
The robot industry can effectively improve development of high-level manufacture industry in China.In this paper,we respectively utilized DEA Malmquist method,the BCC model and the other econometric models to measure and analyze the total factor productivity and its influence factors of the robot industry from the aspects of time sequence and region by using the panel data of the listed 33 Chinese robot companies from the CNRDS database in 2015-2019.The results show that:The current TFP was slowly improved by the different expression of technical efficiency,pure technical efficiency,and scale efficiency;It can quickly improve the TFP to optimize the capital composition,the profit ability,the capital flow operation,the operation scale and the management ability, but their roles are different.We proposed some suggestions based on results above:the enterprises should formulate appropriate development strategies and improve their own management mode in order to improve their scale efficiency and pure technical efficiency;The industries must formulate the industrial strategies according to the local conditions;The governments need to launch more targeted policies that fit for their industrial development.
DOI
10.16315/j.stm.2020.05.002
Recommended Citation
DU, Ke and LI, Qiao-Xing
(2020)
"Research on total factor productivity and influencing factors of China's robot industry,"
Journal of Science and Technology Management: Vol. 22:
Iss.
5, Article 2.
DOI: 10.16315/j.stm.2020.05.002
Available at:
https://jstm.researchcommons.org/journal/vol22/iss5/2
Creative Commons License
This work is licensed under a Creative Commons Attribution-NonCommercial-No Derivative Works 4.0 International License.
