Research Article
Production Enterprise Operation Information Decision Analysis Based on Data Feature Analysis
@INPROCEEDINGS{10.4108/eai.19-5-2023.2334220, author={Aixin Hou and Jiao Han and Huan Du and Ying Li and Yujie Hu}, title={Production Enterprise Operation Information Decision Analysis Based on Data Feature Analysis}, proceedings={Proceedings of the 2nd International Conference on Bigdata Blockchain and Economy Management, ICBBEM 2023, May 19--21, 2023, Hangzhou, China}, publisher={EAI}, proceedings_a={ICBBEM}, year={2023}, month={7}, keywords={production enterprise operation index digital model characteristic index}, doi={10.4108/eai.19-5-2023.2334220} }
- Aixin Hou
Jiao Han
Huan Du
Ying Li
Yujie Hu
Year: 2023
Production Enterprise Operation Information Decision Analysis Based on Data Feature Analysis
ICBBEM
EAI
DOI: 10.4108/eai.19-5-2023.2334220
Abstract
With the advent of the era of big data, digital technologies such as the industrial Internet, big data, artificial intelligence, and cloud computing have been popularized. Digitalization and technological innovation have injected new impetus into economic and social development, have greatly improved information processing capacity and efficiency of information use, and have become a new engine driven by innovation. Manufacturing enterprises need to make operational information decisions to eliminate externalities and uncertainties when carrying out technological innovation activities. It needs to constantly increase financial support, and establish and improve R & D support system to improve the ability of independent innovation of enterprises. However, the low conversion rate and low efficiency of resource utilization are still the problems faced in the process of technological innovation. By analyzing the characteristics of data information in the operation of manufacturing enterprises, this paper matches the characteristics of operation indicators with the characteristics of enterprise products and completes the decision-making and positioning prediction of products.