Evaluation of China's marine economic growth quality based on set pair analysis

Liu, Baiqiong; Xu, Min; Wang, Jing; Wang, Zaifeng; Zhao, Lin

doi:10.1016/j.marpol.2021.104405

Cited by 23 publications

(13 citation statements)

References 54 publications

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“…Since the study area has not yet been involved in the marine oil and gas industry, the development of marine fisheries (including marine aquaculture, product processing, etc.) should be focused on the actual development of the marine industry in the study area [ 16 ]. On the other hand, the use, dismantling and construction of marine vessels and coastal tourism, marine engineering construction, and maritime navigation will establish a typical economic environment model based on marine fishing, comprehensive utilization of seawater, dismantling, and reconstruction.…”

Section: Discussionmentioning

confidence: 99%

Water Resources Carrying Capacity and Circular Economy Based on Fuzzy Multilayer Algorithm

2022

Computational Intelligence and Neuroscience

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By combining the relevant theoretical foundations such as fuzzy algorithm and water resources environmental management, and selecting the actual water resources integration data, this paper establishes an index system to investigate the carrying capacity of the water environment in this area. Through the study and application of the comprehensive multilevel fuzzy evaluation model, based on scenario analysis, the current situation of water resources environmental management and the temporal and spatial variation characteristics of water resources in the study area in recent years were evaluated. In order to observe the differences more accurately in the spatial structure of water use in the study area through information entropy, ArcGIS IS images were drawn according to the calculation results of the urban degree balance in the study area. In the development of circular economy, the information center plays an important role in the industrial ecosystem, which is the basis for the recycling of materials, energy, and water. By building a unique data platform, it can help companies understand the latest status of logistics, energy, and waste recycling in the park and can make adaptive adjustments to the above conditions, to achieve the sustainable development of the overall industrial chain.

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Section: Discussionmentioning

confidence: 99%

Water Resources Carrying Capacity and Circular Economy Based on Fuzzy Multilayer Algorithm

2022

Computational Intelligence and Neuroscience

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“…Erumban et al (2019) showed that upgrading of industrial structure can increase labor productivity and has a positive effect on economic growth. In the field of marine research, many scholars have conducted studies and obtained similar results using methods such as principal component analysis, panel regression models, vector autoregressive (VAR) models and grey correlations, and concluded that the upgrading of marine industry structure has a significant contribution to marine economic growth (Di et al, 2014;Zhai, 2020;Liu et al, 2021a). Specifically, the upgrading of MAEM 6,1 marine industry structure will affect the spatial and temporal evolution of the marine economy by influencing production factor inputs and improving the effect of financial support (Wang and Han, 2017;Fei, 2020), and there is a significant spatial dependence between the upgrading of marine industry structure and coastal economic growth, showing nonuniform distribution characteristics (Wang and Zhai, 2020).…”

Section: Literature Reviewmentioning

confidence: 99%

“…In the field of marine research, many scholars have conducted studies and obtained similar results using methods such as principal component analysis, panel regression models, vector autoregressive (VAR) models and grey correlations, and concluded that the upgrading of marine industry structure has a significant contribution to marine economic growth (Di et al. , 2014; Zhai, 2020; Liu et al. , 2021a).…”

Section: Introductionmentioning

confidence: 99%

Forecasting China’s marine scientific research and education, marine industrial structure upgrading and marine economy growth based on the AWBO-MGM(1,m) model

Xu¹,

Li²

2023

MAEM

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PurposeThe purpose of this paper is to explore the internal interaction mechanism of marine scientific research and education, industrial structure upgrading and marine economic growth from a systematic perspective, based on which this work forecasts their future development trends.Design/methodology/approachIn this study, a multivariate grey model is applied to the prediction of marine scientific research and education, industrial structure upgrading and marine economic growth. Considering the impact of the COVID-19 on marine development, this paper introduces the weakening buffer operator into MGM(1,m) and constructs the AWBO-MGM(1,m) model. To verify the validity and accuracy of the new model, this paper uses AWBO-MGM(1,m), MGM(1,m), GM(1,N), GM(1,1), back propagation neural network and linear regression models for simulation and prediction based on the data from 2010 to 2021, respectively.FindingsFrom the theoretical perspective, the development of marine scientific research and education can accelerate industrial upgrading and promote marine economic growth by providing high-quality talents, promoting marine science and technology progress and reducing transaction costs; while the upgrading of marine industrial structure and marine economic growth can promote the development of marine scientific research and education by guiding social capital, enhancing talent demand and stimulating market vitality. From the empirical analysis, the AWBO-MGM(1,m) model can effectively deal with epidemic shocks and has higher fitting and prediction accuracy than the other five comparative models.Practical implicationsThe government should pay attention to the construction of marine scientific research and education, so as to provide high-quality talents and advanced scientific research results for the high-quality development of marine economy. On the basis of using science and technology to firmly build the primary and secondary marine industries, the government should actively guide the labor, capital and other factors of production to the tertiary industry, thereby promoting the optimization and upgrading of marine industrial structure.Originality/valueOn the one hand, the interplay mechanism of marine scientific research and education, industrial structure upgrading and marine economic growth is analyzed from a systematic perspective; on the other hand, the enhanced AWBO-MGM(1,m) possesses higher forecasting performance and is applicable to the systemic multivariate forecasting problem in the presence of outstanding external shocks.

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“…Scholars have recently explored various avenues to achieve HQMED, including technological innovation (Liu et al, 2021a(Liu et al, , 2021b, financial advancement (Wang et al, 2021), and the digital economy (Jian et al, 2021). As a spatial economic activity, industrial agglomeration (IA) is considered a key factor influencing the realization of environmentally sustainable, green, and highquality development (Guo & Ma, 2021;Han et al, 2018;Zheng & He, 2022).…”

Section: Introductionmentioning

confidence: 99%

Impact of marine industrial agglomeration on high-quality marine economic development: the mediating effect of knowledge spillover

Wang,

Ru,

Cheng

2024

Mar Dev

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Industrial agglomeration significantly influences economic development; however, its impact on high-quality economic growth within the marine industry remains understudied. We conducted a study using panel data from 11 coastal provinces in China (2008–2020) and used the entropy method to quantify high-quality marine economic development (HQMED). Our study meticulously examines the direct, mediating, and nonlinear effects of marine industrial agglomeration (MIA) on HQMED. The key findings include the following: (1) There is a steady HQMED growth and reduced interprovincial gaps. (2) MIA significantly enhances local HQMED and leads to positive spatial spillover to adjacent regions. (3) The analysis of the mediating effect highlights the pivotal role of knowledge spillover in MIA’s influence on HQMED. (4) Threshold analysis shows significant MIA effects on local and neighboring HQMED using knowledge spillover as a threshold variable. The study’s findings hold theoretical and practical significance and guide MIA’s role in fostering sustainable marine economic development in China.

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Evaluation of China's marine economic growth quality based on set pair analysis

Cited by 23 publications

References 54 publications

Water Resources Carrying Capacity and Circular Economy Based on Fuzzy Multilayer Algorithm

Water Resources Carrying Capacity and Circular Economy Based on Fuzzy Multilayer Algorithm

Forecasting China’s marine scientific research and education, marine industrial structure upgrading and marine economy growth based on the AWBO-MGM(1,m) model

Impact of marine industrial agglomeration on high-quality marine economic development: the mediating effect of knowledge spillover

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