Measurement and spatiotemporal analysis of high-quality development of China’s industry

Pamucar, Dragan and Yang, Yuexiang and Ren, Lei and Du, Zhihui and Tong, Guanqun (2021) Measurement and spatiotemporal analysis of high-quality development of China’s industry. PLOS ONE, 16 (12). e0259845. ISSN 1932-6203

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Abstract

Background
China’s economy has been transitioning from a phase of rapid growth to high-quality development. The high-quality development of industry is the foundation of a sustainable and healthy growth of national economy, and is of great significance to improve people’s living standards, and to meet people’s needs for a better life.

Methods
We develop an evaluation index system of high-quality development of industry from the perspectives of industrial benefit, innovation ability, coordination ability, green ability, opening ability and sharing ability. Based on a panel data of 30 provinces in China during 1999–2018, we evaluate the level of high-quality development of industry using the entropy-weight method and Technique for Order Preference by Similarity to an Ideal Solution (TOPSIS) method. Meanwhile we select six specific years and adopt the Natural Breaks method to classify the provinces according to their levels. At last, Moran’s I index is used to analyze the spatial correlation among the provinces.

Results
Opening ability and innovation ability are found to have greater impacts on industrial high-quality development than other indices, and their influence has been increasing in recent years. There are large spatial and temporal differences among different provinces. Municipalities and coastal provinces are found to be at constantly high levels. The levels in the central region dropped first and then increased, however it was the opposite in the western region. In the northeast region, the levels fluctuated greatly. Overall, the high-quality development of industry among China’s provinces shows positive spatial correlation. Most provinces in China are in High-High and Low-Low clustering States. The High-High clustering type is mainly distributed in the eastern region and the Low-Low clustering type is mainly distributed in the western and central regions.

Conclusion
(1) Innovation ability and open ability are the most important factors. (2) Green ability has not sufficiently contributed to China’s industrial development. (3) Regional and time evolution differences are significant. (4) There is a significant and stable spatial clustering effect in the high-quality development of industry among China’s provinces.

Item Type: Article
Subjects: Impact Archive > Social Sciences and Humanities
Depositing User: Managing Editor
Date Deposited: 11 Jan 2023 08:03
Last Modified: 25 May 2024 07:31
URI: http://research.sdpublishers.net/id/eprint/316

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