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The coordination between maritime economies and marine carrying capacity and their spatiotemporal evolution in the cities of the bohai rim in china

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  • Yu, Zhe
  • Di, Qianbin

Abstract

This study investigated the coordination between maritime economies and marine carrying capacity, a prerequisite for high-quality sustainable development, in 17 cities of the Bohai Rim in China. Metric systems were constructed to evaluate the capacity and efficiency of the coordinated development of the maritime economy and the marine carrying capacity of these cities. Spatiotemporal weighting matrices, the coupling-coordination-relative development (CCRD) model, and the slacks-based measure (SBM) model were used to evaluate each city in terms of its degree of coordination and development efficiency. Additionally, the spatiotemporal evolution of the cities’ coordination capacities was assessed using a grey forecasting model, GM(1,1) estimated in MATLAB based on a spatial gravity model. The results indicate that: (1) The capacity of the 17 cities in the Bohai Rim to coordinate their maritime economy and marine carrying capacity generally increased throughout the 2007–2016 period. However, their coordination capacities varied significantly as the spatial distribution of coordination capacity was dispersed over a wide area but concentrated in a few small zones. (2) The efficiency of coordinated development in the Bohai Rim generally increased over time, although small fluctuations were observed. The maximum increase in average coordination capacity was observed in the central cities, followed by the southern cities, and finally the northern cities. (3) The lines of maximum gravitation between these cities form a gravity circle that wraps around the Bohai Rim, thus generating a multi-region development network around it. The connections between the northern, central, and southern cities strengthened over time, thus causing these cities to become more integrated. The coordination-capacity prediction curve for 2017–2026 indicates that all the cities will improve their coordination capacities over time, albeit with significant intercity differences, since the development of the Bohai Rim is still in a ‘run-in’ period.

Suggested Citation

  • Yu, Zhe & Di, Qianbin, 2020. "The coordination between maritime economies and marine carrying capacity and their spatiotemporal evolution in the cities of the bohai rim in china," Ecological Modelling, Elsevier, vol. 438(C).
  • Handle: RePEc:eee:ecomod:v:438:y:2020:i:c:s0304380020302635
    DOI: 10.1016/j.ecolmodel.2020.109192
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    References listed on IDEAS

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    1. Luigi Pascali, 2017. "The Wind of Change: Maritime Technology, Trade, and Economic Development," American Economic Review, American Economic Association, vol. 107(9), pages 2821-2854, September.
    2. Xianwen Gong, 2019. "Coupling Coordinated Development Model of Urban-Rural Logistics and Empirical Study," Mathematical Problems in Engineering, Hindawi, vol. 2019, pages 1-12, September.
    3. Saad Ahmed Javed & Sifeng Liu, 2019. "Correction to: Predicting the research output/growth of selected countries: application of Even GM (1, 1) and NDGM models," Scientometrics, Springer;Akadémiai Kiadó, vol. 120(3), pages 1505-1505, September.
    4. Bentley, Jacob W. & Serpetti, Natalia & Heymans, Johanna Jacomina, 2017. "Investigating the potential impacts of ocean warming on the Norwegian and Barents Seas ecosystem using a time-dynamic food-web model," Ecological Modelling, Elsevier, vol. 360(C), pages 94-107.
    5. Tone, Kaoru, 2001. "A slacks-based measure of efficiency in data envelopment analysis," European Journal of Operational Research, Elsevier, vol. 130(3), pages 498-509, May.
    6. Charnes, A. & Cooper, W. W. & Rhodes, E., 1979. "Measuring the efficiency of decision-making units," European Journal of Operational Research, Elsevier, vol. 3(4), pages 339-338, July.
    7. Kiyong Keum, 2010. "Tourism flows and trade theory: a panel data analysis with the gravity model," The Annals of Regional Science, Springer;Western Regional Science Association, vol. 44(3), pages 541-557, June.
    8. Zhao, Yunxia & Zhang, Jihong & Lin, Fan & Ren, Jeffrey S. & Sun, Ke & Liu, Yi & Wu, Wenguang & Wang, Wei, 2019. "An ecosystem model for estimating shellfish production carrying capacity in bottom culture systems," Ecological Modelling, Elsevier, vol. 393(C), pages 1-11.
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    Cited by:

    1. Xiaowei Ni & Yongbo Quan, 2023. "Measuring the Sustainable Development of Marine Economy Based on the Entropy Value Method: A Case Study in the Yangtze River Delta, China," Sustainability, MDPI, vol. 15(8), pages 1-16, April.
    2. Yifan Zhang & Bingjun Li, 2023. "Coupling coordination analysis of grain production and economic development in Huang-Huai-Hai region," Environment, Development and Sustainability: A Multidisciplinary Approach to the Theory and Practice of Sustainable Development, Springer, vol. 25(11), pages 13099-13124, November.
    3. Liu, S. & Xiao, Q., 2021. "An empirical analysis on spatial correlation investigation of industrial carbon emissions using SNA-ICE model," Energy, Elsevier, vol. 224(C).

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