Research on Enterprise Innovation Behavior Based on the Regression Analysis Under Big Data Technology
- DOI
- 10.2991/978-94-6463-064-0_68How to use a DOI?
- Keywords
- Career experience of senior management; Innovation investment; Big date technology
- Abstract
This paper uses the 2016–2018 SME Board listed companies as sample, takes the senior executives’ professional experience as an explanatory variable, and divides them into two dimensions: academic, overseas, to empirically test the impact of different professional experiences on corporate innovation investment. In the regression, the application level of big data technology is used as the moderating variable. The study found that: the professional experience of executives has a significant positive effect on the innovation investment of enterprises; the application of big data technology promotes the relationship between the professional experience and innovation investment of enterprises. The research has certain reference value for China’s SME Board listed companies to improve the structure of the senior management team and enhance the innovation capabilities of enterprises.
- Copyright
- © 2023 The Author(s)
- Open Access
- Open Access This chapter is licensed under the terms of the Creative Commons Attribution-NonCommercial 4.0 International License (http://creativecommons.org/licenses/by-nc/4.0/), which permits any noncommercial use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons license and indicate if changes were made.
Cite this article
TY - CONF AU - Siqi Chen AU - Zhaohua Li PY - 2022 DA - 2022/12/27 TI - Research on Enterprise Innovation Behavior Based on the Regression Analysis Under Big Data Technology BT - Proceedings of the 2022 3rd International Conference on Big Data and Social Sciences (ICBDSS 2022) PB - Atlantis Press SP - 665 EP - 673 SN - 2589-4900 UR - https://doi.org/10.2991/978-94-6463-064-0_68 DO - 10.2991/978-94-6463-064-0_68 ID - Chen2022 ER -