Research on the Innovation Efficiency of Artificial Intelligence Enterprise Based on DEA Method
Xia Gao, Zhongkai Yang, Zhaogang Sun
Available Online 6 April 2020.
- https://doi.org/10.2991/aebmr.k.200402.001How to use a DOI?
- artificial intelligence, innovative development, innovation efficiency
- This paper uses DEA method to evaluate innovation efficiency of 40 typical artificial intelligence enterprise in our country, which inputs element as human (research and development personnel accounted for the ratio of the total number of employees) and capital (the ratio of R&D and business revenue), and which output elements as technology (patent number and the sum of the number of software copyright) and economic (operating profit margin). Combining with the evaluation results, the paper analyzed comprehensive efficiency, pure technical efficiency and scale efficiency, return to scale and input redundancy of 40 artificial intelligence enterprise representative in our country. The results show that comprehensive efficiency is low, scale efficiency and pure technical efficiency are not high, and some enterprises have factor redundancy. It is innovative in industry research for selecting 40 enterprises and collecting relevant data of 40 enterprises by using enterprise statements, statistical yearbook, government bulletin and peer, and to conduct research with DEA method.
- Open Access
- This is an open access article distributed under the CC BY-NC license.
Cite this article
TY - CONF AU - Xia Gao AU - Zhongkai Yang AU - Zhaogang Sun PY - 2020 DA - 2020/04/06 TI - Research on the Innovation Efficiency of Artificial Intelligence Enterprise Based on DEA Method BT - Proceedings of the 3rd International Conference on Advances in Management Science and Engineering (IC-AMSE 2020) PB - Atlantis Press SP - 1 EP - 6 SN - 2352-5428 UR - https://doi.org/10.2991/aebmr.k.200402.001 DO - https://doi.org/10.2991/aebmr.k.200402.001 ID - Gao2020 ER -