Digital Economy, Employment Quality and Capital Allocation Efficiencies
——Evidence from Intelligent Manufacturing Listed Companies
- DOI
- 10.2991/978-94-6463-326-9_5How to use a DOI?
- Keywords
- Capital Allocation Efficiency; Employment Quality; Digital Economy
- Abstract
Taking intelligent manufacturing listed companies during 2015–2021 as a sample, the paper incordorated capital allocation efficiencies of enterprises, digital economy, and employment quality into a research framework. It was empirically tested the influence of digital economy on capital allocation efficiencies of intelligent manufacturing enterprises and the mediating transmission mechanism of employment quality. The results show that digital economy can promote positively capital allocation efficiencies of intelligent manufacturing enterprises, and improves their capital allocation efficiencies by improving employment quality. After the robustness test, the conclusions are still valid. Through heterogeneity analysis, digital economic has a more significant promoting on capital allocation efficiencies of state-owned enterprises. The improvement effect of the digital economy development on capital allocation efficiencies of intelligent manufacturing enterprises in the eastern region is weaker than that in other regions.
- 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 - Wang Qiong AU - Zhu Hong AU - Ma Ran AU - Zhang Yiwen AU - Zhang Hongru PY - 2023 DA - 2023/12/30 TI - Digital Economy, Employment Quality and Capital Allocation Efficiencies BT - Proceedings of the 2023 3rd International Conference on Business Administration and Data Science (BADS 2023) PB - Atlantis Press SP - 36 EP - 50 SN - 2589-4900 UR - https://doi.org/10.2991/978-94-6463-326-9_5 DO - 10.2991/978-94-6463-326-9_5 ID - Qiong2023 ER -