Research on the Innovation Efficiency of Artificial Intelligence Enterprise Based on DEA Method

DOI

10.2991/aebmr.k.200402.001How to use a DOI?

Keywords

artificial intelligence, innovative development, innovation efficiency

Abstract

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.

Copyright

© 2020, 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/).

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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  - 10.2991/aebmr.k.200402.001
ID  - Gao2020
ER  -