Development Level, Spatiotemporal Evolution, and Barrier Analysis of China's Marine Economic Competitiveness: From the Perspective of the Driving Factors of New Quality Productive Forces
- 1Key Research Base of Humanities and Social Sciences of the Ministry of Education, Institute of Marine Sustainable Development, Liaoning Normal University, Dalian 116029, China
Abstract
Guided by the theoretical perspective of new quality productive forces, this study develops a three-dimensional “technology-factor-industry” framework and constructs a corresponding evaluation system for assessing marine economic competitiveness. Employing a comprehensive methodology, including the entropy-weighted TOPSIS method, kernel density estimation, exploratory spatiotemporal data analysis(ESTDA), and the obstacle degree model, this study examines the development level, spatiotemporal evolution, and barrier factors of marine economic competitiveness across 11 coastal provinces(autonomous regions and centrally administered municipalities) in China from 2013 to 2021.The results indicate that: (1) Marine economic competitiveness has improved significantly overall, although pronounced gradient disparities persist among regions, forming a spatial pattern characterized by “the eastern region leading and the northern and southern regions diverging”.(2) Local indicators spatial autocorrelation(LISA) temporal paths indicate that the overall spatial correlation pattern remains relatively stable, whereas local path evolution is complex and exhibits strong path dependence; spatiotemporal transition analysis further shows that both medium-low and high competitiveness regions exhibit low probabilities of transition and decline, reflecting a “bipolar lock-in” phenomenon.(3) At the system level, barriers are ranked in descending order as industry, factors, and technology, with the effects of the main barrier factors remaining stable. This paper offers an analytical framework from the perspective of new quality productive forces for understanding the formation mechanism of marine economic competitiveness, aiming to provide policy implications for promoting the high-quality development of China's marine economy and coordinated regional development.
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BibTeX
@article{tong2026development,
title = {{Development Level, Spatiotemporal Evolution, and Barrier Analysis of China's Marine Economic Competitiveness: From the Perspective of the Driving Factors of New Quality Productive Forces}},
author = {XIE Tong and LIU Kai},
journal = {Haiyang Kaifa yu guanli},
year = {2026},
month = jul,
doi = {10.20016/j.cnki.hykfygl.2026.07.011},
url = {https://doi.org/10.20016/j.cnki.hykfygl.2026.07.011},
note = {CC BY-NC-ND},
}
RIS
TY - JOUR
TI - Development Level, Spatiotemporal Evolution, and Barrier Analysis of China's Marine Economic Competitiveness: From the Perspective of the Driving Factors of New Quality Productive Forces
AU - XIE Tong
AU - LIU Kai
PY - 2026
DA - 2026/07/01
JO - Haiyang Kaifa yu guanli
DO - 10.20016/j.cnki.hykfygl.2026.07.011
UR - https://doi.org/10.20016/j.cnki.hykfygl.2026.07.011
AB - Guided by the theoretical perspective of new quality productive forces, this study develops a three-dimensional “technology-factor-industry” framework and constructs a corresponding evaluation system for assessing marine economic competitiveness. Employing a comprehensive methodology, including the entropy-weighted TOPSIS method, kernel density estimation, exploratory spatiotemporal data analysis(ESTDA), and the obstacle degree model, this study examines the development level, spatiotemporal evolution, and barrier factors of marine economic competitiveness across 11 coastal provinces(autonomous regions and centrally administered municipalities) in China from 2013 to 2021.The results indicate that: (1) Marine economic competitiveness has improved significantly overall, although pronounced gradient disparities persist among regions, forming a spatial pattern characterized by “the eastern region leading and the northern and southern regions diverging”.(2) Local indicators spatial autocorrelation(LISA) temporal paths indicate that the overall spatial correlation pattern remains relatively stable, whereas local path evolution is complex and exhibits strong path dependence; spatiotemporal transition analysis further shows that both medium-low and high competitiveness regions exhibit low probabilities of transition and decline, reflecting a “bipolar lock-in” phenomenon.(3) At the system level, barriers are ranked in descending order as industry, factors, and technology, with the effects of the main barrier factors remaining stable. This paper offers an analytical framework from the perspective of new quality productive forces for understanding the formation mechanism of marine economic competitiveness, aiming to provide policy implications for promoting the high-quality development of China's marine economy and coordinated regional development.
SN - 1005-9857
ER -