The Effects of Big Data Regulations on Industrial Modernization in Resource-Based Cities: A Semi-Natural Study Using a State-Level Big Data Coordination Zone

As a core component of the digital economy, big data provides resource-based cities with a new impetus for upgrading their industrial structures. This paper employs a double difference method with panel data from 86 resource cities in China from 2009 to 2020 in order to investigate the effects of big data policies on resource cities' upgrading of their industrial structures objectively. Quasi-control groups are the quasi-natural trials of two batches of 19 resource cities in national big data comprehensive experimental zones. The empirical results demonstrate that the nationwide comprehensive experimental zone for big data exerts a considerable influence on the industrial upgrading of resource-based cities. This conclusion remains robust even after putting it through a series of tests, including the consolidation test and the stability test. Ultimately, this study offers a novel approach to catalyzing industrial upgrading in a big data context, shedding light on crucial issues such as economic instability in resource-based cities.

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Publication Details

Journal
Journal of Education Humanities and Social Sciences
Published
2024-11-07
DOI
https://doi.org/10.54097/0yg35k78
Primary Topic
Big Data Technologies and Applications
Type
article
Field-Weighted Citation Impact
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article

The Effects of Big Data Regulations on Industrial Modernization in Resource-Based Cities: A Semi-Natural Study Using a State-Level Big Data Coordination Zone

Ying Wang
Journal of Education Humanities and Social Sciences
Big Data Technologies and Applications
article

The Effects of Big Data Regulations on Industrial Modernization in Resource-Based Cities: A Semi-Natural Study Using a State-Level Big Data Coordination Zone

Ying Wang
article en

Abstract

As a core component of the digital economy, big data provides resource-based cities with a new impetus for upgrading their industrial structures. This paper employs a double difference method with panel data from 86 resource cities in China from 2009 to 2020 in order to investigate the effects of big data policies on resource cities' upgrading of their industrial structures objectively. Quasi-control groups are the quasi-natural trials of two batches of 19 resource cities in national big data comprehensive experimental zones. The empirical results demonstrate that the nationwide comprehensive experimental zone for big data exerts a considerable influence on the industrial upgrading of resource-based cities. This conclusion remains robust even after putting it through a series of tests, including the consolidation test and the stability test. Ultimately, this study offers a novel approach to catalyzing industrial upgrading in a big data context, shedding light on crucial issues such as economic instability in resource-based cities.

Journal of Education Humanities and Social SciencesVol. 39
Openalex Percentile: Top 76%
Big Data Technologies and Applications
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The Effects of Big Data Regulations on Industrial Modernization in Resource-Based Cities: A Semi-Natural Study Using a State-Level Big Data Coordination Zone — Ying Wang · Journal of Education Humanities and Social Sciences (2024) | TGRS Research Map | TGRS