IDEAS home Printed from https://ideas.repec.org/a/eee/ecomod/v438y2020ics0304380020302635.html
   My bibliography  Save this article

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

Author

Listed:
  • 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
    as

    Download full text from publisher

    File URL: http://www.sciencedirect.com/science/article/pii/S0304380020302635
    Download Restriction: Full text for ScienceDirect subscribers only

    File URL: https://libkey.io/10.1016/j.ecolmodel.2020.109192?utm_source=ideas
    LibKey link: if access is restricted and if your library uses this service, LibKey will redirect you to where you can use your library subscription to access this item
    ---><---

    As the access to this document is restricted, you may want to search for a different version of it.

    References listed on IDEAS

    as
    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.
    Full references (including those not matched with items on IDEAS)

    Citations

    Citations are extracted by the CitEc Project, subscribe to its RSS feed for this item.
    as


    Cited by:

    1. 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).
    2. 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.
    3. 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.

    Most related items

    These are the items that most often cite the same works as this one and are cited by the same works as this one.
    1. Bao Jiang & Enxin Chi & Jian Li, 2022. "Uncertain Data Envelopment Analysis for Cross Efficiency Evaluation with Imprecise Data," Mathematics, MDPI, vol. 10(13), pages 1-9, June.
    2. Zhang, Weike & Meng, Jia & Tian, Xiaoli, 2020. "Does de-capacity policy enhance the total factor productivity of China's coal companies? A Regression Discontinuity design," Resources Policy, Elsevier, vol. 68(C).
    3. Kao, Chiang, 2022. "Measuring efficiency in a general production possibility set allowing for negative data: An extension and a focus on returns to scale," European Journal of Operational Research, Elsevier, vol. 296(1), pages 267-276.
    4. Carla Henriques & Clara Viseu, 2022. "Are ERDFs Devoted to Boosting ICTs in SMEs Inefficient? A Three-Stage SBM Approach," Sustainability, MDPI, vol. 14(17), pages 1-20, August.
    5. Kao, Chiang, 2022. "A maximum slacks-based measure of efficiency for closed series production systems," Omega, Elsevier, vol. 106(C).
    6. Kao, Chiang, 2022. "Closest targets in the slacks-based measure of efficiency for production units with multi-period data," European Journal of Operational Research, Elsevier, vol. 297(3), pages 1042-1054.
    7. Zhu, Xinhua & Li, Yan & Zhang, Peifeng & Wei, Yigang & Zheng, Xuyang & Xie, Lingling, 2019. "Temporal–spatial characteristics of urban land use efficiency of China’s 35mega cities based on DEA: Decomposing technology and scale efficiency," Land Use Policy, Elsevier, vol. 88(C).
    8. Usman Akbar & József Popp & Hameed Khan & Muhammad Asif Khan & Judit Oláh, 2020. "Energy Efficiency in Transportation along with the Belt and Road Countries," Energies, MDPI, vol. 13(10), pages 1-20, May.
    9. Chia-Nan Wang & Anh Luyen Le & Chu-Chieh Hou, 2019. "Applying Undesirable Output Model to Security Evaluation of Taiwan," Mathematics, MDPI, vol. 7(11), pages 1-15, October.
    10. Vladimír Baláž & Eduard Nežinský & Tomáš Jeck & Richard Filčák, 2020. "Energy and Emission Efficiency of the Slovak Regions," Sustainability, MDPI, vol. 12(7), pages 1-18, March.
    11. Suvvari Anandarao & S. Raja Sethu Durai & Phanindra Goyari, 2019. "Efficiency Decomposition in two-stage Data Envelopment Analysis: An application to Life Insurance companies in India," Journal of Quantitative Economics, Springer;The Indian Econometric Society (TIES), vol. 17(2), pages 271-285, June.
    12. Wanping Yang & Bingyu Zhao & Jinkai Zhao & Zhengda Li, 2019. "An Empirical Study on the Impact of Foreign Strategic Investment on Banking Sustainability in China," Sustainability, MDPI, vol. 11(1), pages 1-15, January.
    13. Can Zhang & Jixia Li & Tengfei Liu & Mengzhi Xu & Huachun Wang & Xu Li, 2022. "The Spatiotemporal Evolution and Influencing Factors of the Chinese Cities’ Ecological Welfare Performance," IJERPH, MDPI, vol. 19(19), pages 1-27, October.
    14. Mehdiloozad, Mahmood & Sahoo, Biresh K. & Roshdi, Israfil, 2014. "A generalized multiplicative directional distance function for efficiency measurement in DEA," European Journal of Operational Research, Elsevier, vol. 232(3), pages 679-688.
    15. Kao, Chiang & Liu, Shiang-Tai, 2022. "Group decision making in data envelopment analysis: A robot selection application," European Journal of Operational Research, Elsevier, vol. 297(2), pages 592-599.
    16. Subhash C. Ray, 2018. "Data Envelopment Analysis with Alternative Returns to Scale," Working papers 2018-20, University of Connecticut, Department of Economics.
    17. Maohui Ren & Tao Zhou & Di Wang & Chenxi Wang, 2023. "Does Environmental Regulation Promote the Infrastructure Investment Efficiency? Analysis Based on the Spatial Effects," IJERPH, MDPI, vol. 20(4), pages 1-24, February.
    18. Mei Tao & Shanshan Lv & Shiqian Feng, 2023. "Study on the Evaluation of the Development Efficiency of Smart Mine Construction and the Influencing Factors Based on the US-SBM Model," Sustainability, MDPI, vol. 15(6), pages 1-17, March.
    19. Wang, Qiang & Jiang, Feng & Li, Rongrong, 2022. "Assessing supply chain greenness from the perspective of embodied renewable energy – A data envelopment analysis using multi-regional input-output analysis," Renewable Energy, Elsevier, vol. 189(C), pages 1292-1305.
    20. Liu, Runxi & Huang, Runyao & Shen, Ziheng & Wang, Hongtao & Xu, Jin, 2021. "Optimizing the recovery pathway of a net-zero energy wastewater treatment model by balancing energy recovery and eco-efficiency," Applied Energy, Elsevier, vol. 298(C).

    Corrections

    All material on this site has been provided by the respective publishers and authors. You can help correct errors and omissions. When requesting a correction, please mention this item's handle: RePEc:eee:ecomod:v:438:y:2020:i:c:s0304380020302635. See general information about how to correct material in RePEc.

    If you have authored this item and are not yet registered with RePEc, we encourage you to do it here. This allows to link your profile to this item. It also allows you to accept potential citations to this item that we are uncertain about.

    If CitEc recognized a bibliographic reference but did not link an item in RePEc to it, you can help with this form .

    If you know of missing items citing this one, you can help us creating those links by adding the relevant references in the same way as above, for each refering item. If you are a registered author of this item, you may also want to check the "citations" tab in your RePEc Author Service profile, as there may be some citations waiting for confirmation.

    For technical questions regarding this item, or to correct its authors, title, abstract, bibliographic or download information, contact: Catherine Liu (email available below). General contact details of provider: http://www.journals.elsevier.com/ecological-modelling .

    Please note that corrections may take a couple of weeks to filter through the various RePEc services.

    IDEAS is a RePEc service. RePEc uses bibliographic data supplied by the respective publishers.