Research on the Innovation Capability Evaluation of Science and Technology-Based Large and Medium-Sized Enterprises Based on the Artificial Neural Network Under Coupling Weights
- DOI
- 10.2991/aebmr.k.220502.064How to use a DOI?
- Keywords
- AHP; CRITIC; ANN; Technology-based Enterprises; Innovation Capability; Evaluation Study
- Abstract
Science and technology innovation capability is the core competitiveness for the long-term development of science and technology-based enterprises. In this paper, we construct an evaluation system of innovation capability of science and technology-based large and medium-sized enterprises by taking listed science and technology-based enterprises in Jiangsu Province in China’s Shanghai and Shenzhen A-shares. The coupling method of AHP subjective assignment and CRITIC objective assignment is used to assign weights to the indicators, and the data are subjected to ANN training to find the best neural network structure, so as to achieve the evaluation of innovation capability of science and technology-based large and medium-sized enterprises. The results show that the growth rate of R&D expenses and the number of invention patent applications are the most important. R&D investment and innovation output are more important. This study uses quantitative methods to evaluate the innovation ability of large and medium-sized scientific and technological enterprises, providing enterprises with a reality evaluation and decision-making basis, with certain guiding significance.
- Copyright
- © 2022 The Authors. Published by Atlantis Press International B.V.
- Open Access
- This is an open access article distributed under the CC BY-NC 4.0 license.
Cite this article
TY - CONF AU - Ziqing Ye AU - Xiangcheng Qin PY - 2022 DA - 2022/05/16 TI - Research on the Innovation Capability Evaluation of Science and Technology-Based Large and Medium-Sized Enterprises Based on the Artificial Neural Network Under Coupling Weights BT - Proceedings of the 2022 International Conference on Urban Planning and Regional Economy(UPRE 2022) PB - Atlantis Press SP - 356 EP - 363 SN - 2352-5428 UR - https://doi.org/10.2991/aebmr.k.220502.064 DO - 10.2991/aebmr.k.220502.064 ID - Ye2022 ER -