How big data drives green economic development: Evidence from China

Li Wang, Yuhan Wu, Zeyu Huang, Yanan Wang

Research output: Contribution to journalArticlepeer-review

25 Scopus citations

Abstract

Big data can improve production efficiency and optimize resource allocation, which is conductive to achieve sustainable development. This paper explores the impact of big data on green economic development. The global MINDW-MML model is used to measure green economic development and text analysis method is used to quantify the development of big data. An empirical study is conducted based on the panel data from 30 provinces in China from 2011 to 2018. Results show that, big data promotes the development of green economy and plays a greater role in facilitating technological progress than improving efficiency. As for sub-indicators of big data, cloud computing, Internet of things, artificial intelligence, and Hadoop positively affect technological progress, while blockchain can improve efficiency. In addition, the positive role of big data in promoting green technological progress and green efficiency will vary according to geographical location, the intensity of environmental governance and the development of digital financial inclusion. As moving into the good phase of the economy, big data is more inclined to enhance green technological progress, while in a sluggish phase, it improves green efficiency more. These findings point the way forward for sustainable development. The Chinese government can actively build information infrastructure and improve the technical level and application capacity of big data.

Original languageEnglish
Article number1055162
JournalFrontiers in Environmental Science
Volume10
DOIs
StatePublished - 22 Nov 2022

Keywords

  • big data
  • efficiency improvement
  • global MINDW-MML model
  • green economic development
  • technological progress

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