Research on the Impact of Big Data Development on Green Economy—An Empirical Study Based on Panel Data from Beijing-Tianjin-Hebei Region
- DOI
- 10.2991/978-94-6463-270-5_21How to use a DOI?
- Keywords
- big data; green economy; Beijing-Tianjin-Hebei; R software
- Abstract
This study utilizes panel data from large-scale enterprises in the Beijing-Tianjin-Hebei region from 2013 to 2021. R software is used to perform Winsorize processing on the data. By constructing a index system for the development of big data, the relationship between big data development and the green economy in the region is analyzed. The research findings indicate that the development of big data plays a positive role in promoting the green economy. Firstly, big data technologies provide abundant data resources for enterprises and decision-makers, driving green innovation and technological development. Secondly, big data technologies help optimize resource utilization efficiency, achieving sustainable development in the green economy. This study provides references and insights for the development of the green economy in the Beijing-Tianjin-Hebei region and other areas, emphasizing the significant role of big data in driving the transformation of the green economy.
- 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 - GuanHui Wang AU - XiaoYu Zhou AU - XiaoDi Fan PY - 2023 DA - 2023/10/29 TI - Research on the Impact of Big Data Development on Green Economy—An Empirical Study Based on Panel Data from Beijing-Tianjin-Hebei Region BT - Proceedings of the 3rd International Conference on Internet Finance and Digital Economy (ICIFDE 2023) PB - Atlantis Press SP - 201 EP - 207 SN - 2667-1271 UR - https://doi.org/10.2991/978-94-6463-270-5_21 DO - 10.2991/978-94-6463-270-5_21 ID - Wang2023 ER -