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EM Algorithm-Based Enterprise Digital Transformation: Green Innovation Efficiency of Enterprise Investment.

Authors :
Cao, Xinyu
Xu, Li
Duan, Qian
Source :
Mathematical Problems in Engineering; 9/16/2022, p1-12, 12p
Publication Year :
2022

Abstract

The digital transformation of manufacturing industry refers to the integration and application of the new generation of information technology in the field of manufacturing in the context of the current digital economy development. Architecture is the foundation of the real economy, which is closely related to digital chemistry and industrial digitalization. On the one hand, high-tech manufacturing of digital information products such as terminal equipment, smart equipment, electronic components, and integrated circuits is the material basis of digital chemical industry. It is a product of traditional manufacturing, blockchain, and artificial intelligence. On the other hand, digital technologies such as simulation technology are the core of the development of manufacturing, the key to achieving precise market positioning, expanding product functions, and improving product quality and added value. Digital technology is an intellectual industry. From the perspective of investment returns, the investment behavior of enterprises is manifested as effective investment and invalid investment. If the capital cost during the investment process is lower than the company's income, the company will not increase the investment amount for any reason, so it will not receive enough investment. Due to the low threshold of investment income, investment growth exceeding a certain threshold will actually reduce investment income and lead to excessive investment. In this context, this article studies the digital transformation of corporate enterprises based on algorithms: green innovation in investment efficiency organizations. This article deeply studies the status quo and the advantages of green innovation investment in digital technology and puts forward corresponding suggestions. [ABSTRACT FROM AUTHOR]

Details

Language :
English
ISSN :
1024123X
Database :
Complementary Index
Journal :
Mathematical Problems in Engineering
Publication Type :
Academic Journal
Accession number :
159173133
Full Text :
https://doi.org/10.1155/2022/8782652