The Evaluation Prediction System for Urban Advanced Manufacturing Development

Systems, Год журнала: 2023, Номер 11(8), С. 392 - 392

Опубликована: Авг. 1, 2023

With the rapid development of economy, it is important to reasonably evaluate status regional manufacturing industry. Given this, this article expands evaluation indicators urban advanced (UAM) from perspective push–pull-mooring (PPM). Then, uses a machine learning (ML) method predict results other cities through small amount sample data. The show that: (1) From current UAM in Guangdong Province (GD), Pearl River Delta region occupy dominant position. However, eastern, western, and mountainous regions have strong potential lead cities. Therefore, each has with high levels demonstrative role. (2) By comparison, was found that overall level GD not significantly different Yangtze Economic Belt. due significant differences their extreme values, proportion above average population relatively small. This indirectly proves GD’s only phased nature, but also (3) prediction effect perceptron model better than methods. Although neural network models performance models, they should overly rely on complex structure comparing results, reliability verified. Finally, according life cycle theory, we propose targeted path for UAM.

Язык: Английский

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Can digitalization alleviate China's energy poverty? Empirical investigation and mechanism analysis

Environmental Impact Assessment Review, Год журнала: 2024, Номер 109, С. 107634 - 107634

Опубликована: Авг. 23, 2024

Язык: Английский

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Smart Cities and Greener Futures: Evidence from a Quasi-Natural Experiment in China’s Smart City Construction

Sustainability, Год журнала: 2024, Номер 16(2), С. 929 - 929

Опубликована: Янв. 22, 2024

As the digital economy becomes new engine of economic growth, China has introduced a series smart city policies aimed at promoting high-quality and sustainable urban development. This paper aims to evaluate green development effects China’s “Smart City Pilot” policy explore heterogeneity across different types cities. Using panel data from 283 prefecture-level cities in 2006 2020, this study examines relationship between construction efficiency using total factor productivity (GTFP). We employ Causal Forest mediation effect models estimate impact pilot on GTFP underlying mechanisms. The main results are: (1) significantly enhances GTFP, finding consistent diverse evaluation approaches. (2) influence varies among cities, such is effectively captured by Forest. (3) varied primarily stems location factors inherent characteristics. Notably, Eastern outpaces that other regions. yields greater benefits with financial medical capital rises, but excessive government public expenditure curtails its positive influence. (4) mechanisms through which promotes exhibit certain differences “high-effect group” “low-effect group”. former predominantly leverages innovation-driven agglomeration effects, while latter chiefly relies industrial structural advancement rationalization.

Язык: Английский

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The impact of green credit policy on total factor productivity of enterprises

International Review of Economics & Finance, Год журнала: 2024, Номер 95, С. 103480 - 103480

Опубликована: Авг. 5, 2024

Язык: Английский

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Driving effect of digital government policy on synergy in corporate pollution reduction, carbon reduction, and green expansion

Journal of Environmental Management, Год журнала: 2024, Номер 369, С. 122301 - 122301

Опубликована: Авг. 30, 2024

Язык: Английский

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