Digital economy, binary factor mismatch and sustainable economic development of coastal areas in China

Wu, Shujuan; Tang, Jianhua; Li, Minmin; Xiao, Jianhua

doi:10.1016/j.heliyon.2024.e26453

Cited by 1 publication

(1 citation statement)

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“…Although the overall trend of digital economy development in YEB remains positive, a noticeable regional imbalance still exists in the middle and lower reaches, which underscores the necessity for government intervention through tailored policy support strategies to foster equitable growth across diverse regions within the digital economy landscape. This is in line with the views of Wu et al, who emphasized that the uneven development of the digital economy may be affected by regional resource allocation and policy support [58]. Furthermore, our study also yielded findings that diverged from those of previous research [59], which may have attributed to the variations in data samples or calculation methods.…”

Section: Discussionsupporting

confidence: 83%

Regional Differences and Spatial-Temporal Evolution Characteristics of Digital Economy Development in the Yangtze River Economic Belt

Chen,

Hu,

Luo

2024

Sustainability

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Digital economy has emerged as one of the primary driving forces for economic globalization. However, assessing digital economy development in a robust and scientific manner remains a great challenge. This paper proposes an evaluation system with measurement errors correction to accurately research the regional differences in and the spatial-temporal evolution characteristics of digital economy development in the Yangtze River Economic Belt (YEB), combining the entropy method, the Dagum–Gini coefficient, an σ convergence model and grey correlation analysis. The results present that the digital economy development index in the YEB rose from 2012 to 2021, with the greatest weight being social livelihood benefits. Meanwhile, there were noticeable regional differences in digital economy development in the YEB; in particular, the middle reaches showed obvious convergence. The grey correlation degree between the influence factors and the digital economy development ranged from 0.5286 to 0.9144, demonstrating a robust positive correlation. The theoretical framework of this paper integrates economic development models with advanced statistical analysis techniques, providing a robust analytical perspective for examining the complexities of digital economy evolution. The insights offer a blueprint for policymakers seeking to foster a robust and equitable digital economy, underscoring the potential of data-driven policy formulations in navigating the intricate landscape of economic globalization.

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Section: Discussionsupporting

confidence: 83%