The Moderating Effect of Value Cognition and Market Competition: A Study of the Relationship between R&D Intensity and Performance of AI Enterprise

Litian Chen, Yufeng Wang

2022

Abstract

From the perspective of value cognition and innovation theory, using panel data of 75 listed companies in China’s AI concept stocks from 2011 to 2019 as samples, this paper analyzes and examines the influence of R&D intensity of AI enterprises on enterprise performance and the regulatory effect of value cognition and market competition in this process. Studies have shown that the R&D intensity of AI enterprises is positively correlated with their performance. In addition, the complexity of value cognition and the pressure of market competition have a negative regulatory effect on the relationship between the R&D intensity and performance of AI enterprises.

Paper Citation

in Harvard Style

Chen L. and Wang Y. (2022). The Moderating Effect of Value Cognition and Market Competition: A Study of the Relationship between R&D Intensity and Performance of AI Enterprise. In Proceedings of the International Conference on Big Data Economy and Digital Management - Volume 1: BDEDM, ISBN 978-989-758-593-7, pages 762-768. DOI: 10.5220/0011290300003440

in Bibtex Style

@conference{bdedm22,
author={Litian Chen and Yufeng Wang},
title={The Moderating Effect of Value Cognition and Market Competition: A Study of the Relationship between R&D Intensity and Performance of AI Enterprise},
booktitle={Proceedings of the International Conference on Big Data Economy and Digital Management - Volume 1: BDEDM,},
year={2022},
pages={762-768},
publisher={SciTePress},
organization={INSTICC},
doi={10.5220/0011290300003440},
isbn={978-989-758-593-7},
}

in EndNote Style

TY - CONF

JO - Proceedings of the International Conference on Big Data Economy and Digital Management - Volume 1: BDEDM,
TI - The Moderating Effect of Value Cognition and Market Competition: A Study of the Relationship between R&D Intensity and Performance of AI Enterprise
SN - 978-989-758-593-7
AU - Chen L.
AU - Wang Y.
PY - 2022
SP - 762
EP - 768
DO - 10.5220/0011290300003440