Advancing Marine-Bearing Capacity and Economic Growth: A Comprehensive Analysis of Blue Economy Resilience, Network Evolution, and Technological Influences in China’s Coastal Areas
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1. Introduction
With China’s strategic emphasis on becoming a maritime power, the marine economy has emerged as a crucial driver of global economic expansion. This strategy advocates for a sustainable blue economy, highlighting the importance of marine ecological preservation alongside economic advancement. Yet, the evolution of globalization presents dual challenges. On one side, reliance on expansive development and the adverse effects of climate change-induced marine disasters have significantly compromised marine ecological integrity, hindering sustainable progress. On the other hand, mounting global uncertainties, including economic trade tensions and geopolitical disputes, have markedly decelerated marine economic growth. Within this global scenario, bolstering the blue economy’s resilience and enhancing its network cohesion to effectively navigate and thrive amid crises and volatility are paramount. Achieving this goal necessitates comprehensive policy coordination, innovation in science and technology, and market integration on a global scale. Moreover, it entails a delicate balancing act between marine ecological conservation and economic expansion, aiming to elevate the global marine economy’s quality of development and stimulate new momentum and pathways for worldwide economic growth.
The advancements in these research endeavors underscore that the exploration of marine economic resilience has emerged as a pivotal intersection of environmental transformation, economic progression, and societal welfare. Through the development and application of varied resilience assessment metrics, scholars have been able to pinpoint critical factors influencing marine economic resilience. This includes evaluating the marine economy’s resistance, recuperation, and adaptability to external disturbances, thereby offering both theoretical insights and practical guidance to foster the sustainable advancement of the marine economy. Moreover, as global marine economic activities escalate and the exploitation of marine resources intensifies, the study of marine economic resilience is poised to make a significant contribution. It aims to enhance our comprehension and fortification of the marine economic system’s stability and sustainability, marking a crucial step towards a balanced integration of ecological conservation and economic development.
The existing scholars on this subject has predominantly concentrated on delineating the conceptual framework and gauging the extent of the blue economy or its resilience, seldom intertwining the two to delve into the determinants impacting the blue economy’s resilience. Notably absent are cross-sectional analyses exploring developmental variances within the blue economy across coastal areas, alongside a marked scarcity in discourse adopting a network-centric viewpoint. Thus, the unique contributions of this article are illuminated through three primary dimensions. Firstly, by amalgamating the principles of the blue economy with those of resilience, this investigation meticulously charts the interaction between maritime and land-based dynamics, crafting a layered evaluative framework for the blue economy’s resilience which spans systemic, dimensional, and indicator levels. This elaborate framework captures the core elements of the blue economy while thoroughly addressing the complex essence of resilience, thereby enriching the marine economy’s appraisal with a more comprehensive and insightful exploration. Secondly, leveraging social network analysis, this study probes the structural nuances of China’s blue economy resilience network, conducting both longitudinal and latitudinal assessments of resilience within diverse marine economic zones. This methodological progression furnishes a novel perspective and analytical toolset for unraveling the evolving dynamics within the blue economy’s resilience network, enhancing our comprehension and strategic augmentation of sustainable marine economic frameworks. Thirdly, by employing the time-varying effect random graph model (TERGM), this research reveals the structural evolution and driving forces behind China’s blue economy resilience network, offering a solid foundation of empirical evidence for subsequent inquiries, grounded in data integrity.
The distinctive value of this study is rooted in its novel research perspective and methodological approach. It introduces a fresh theoretical framework and analytical instruments for assessing and dissecting the resilience of the blue economy, extending beyond theoretical contributions to offer empirically grounded policy recommendations. These insights are aimed at aiding policymakers in fostering the sustainable progression and holistic management of the marine economy. By delving into the structure and dynamics of the blue economy’s resilience network, this paper significantly augments the corpus of marine economics and resilience economics. Its contributions bear substantial theoretical and practical relevance, providing a robust foundation for guiding the high-quality advancement of the global marine economy. This blend of innovative analysis and practical application underscores this study’s pivotal role in navigating the complexities of marine economic sustainability and resilience, marking a significant stride toward informed and effective economic policy and management in the marine sector.
2. Theoretical Foundations
2.1. Adaptive Theory
2.2. Vulnerability Theory
2.3. Theory of Creative Destruction
2.4. Regional Economic Resilience Theory
2.5. Integrated Theoretical Analysis of the Blue Economy
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Adaptive Theory and the Blue Economy
Adaptive theory highlights the cyclical nature of economic and environmental systems, emphasizing the necessity for the blue economy to continually adapt to changing marine conditions, regulatory frameworks, and technological advancements. This theory underscores the importance of adaptability in ensuring the sustainability of marine economic activities, suggesting that the blue economy’s resilience can be enhanced through adaptive management practices which anticipate and respond to environmental and economic shocks. By fostering an environment conducive to innovation and flexibility, the blue economy can evolve in harmony with marine ecosystems, ensuring long-term sustainability.
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Vulnerability Theory’s Implications for the Blue Economy
Vulnerability theory brings to light the inherent susceptibilities within the blue economy, urging stakeholders to recognize and address these vulnerabilities to prevent systemic collapses in the face of external shocks. It suggests that a deep understanding of these vulnerabilities, combined with proactive resilience-building measures, can transform potential weaknesses into strengths. For the blue economy, this means not only safeguarding against environmental degradation and market fluctuations but also building a robust framework that supports economic stability, environmental conservation, and community well-being.
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The Role of Creative Destruction in the Blue Economy
The theory of creative destruction offers an optimistic perspective on the role of innovation and structural transformation within the blue economy. It posits that disruptions, whether from technological breakthroughs, policy shifts, or environmental crises, can serve as catalysts for renewing and strengthening marine economic systems. By embracing innovation and the restructuring of marine industries, the blue economy can generate new growth opportunities that align with sustainable practices, thus fostering a resilient economic structure which is better equipped to handle future challenges.
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Regional Economic Resilience and the Blue Economy
Regional economic resilience theory emphasizes the importance of localized strategies in enhancing the overall resilience of the blue economy. It recognizes that regions have unique economic structures, resource endowments, and environmental challenges that require tailored approaches to resilience building. By leveraging regional strengths and fostering inter-regional collaboration, the blue economy can enhance its capacity to withstand and recover from shocks, ensuring equitable growth and sustainability across different marine economic zones. This approach calls for integrated policies that consider the diverse needs and potentials of regions within the blue economy, encouraging innovation and investment in areas most likely to drive sustainable growth.
The integration of these theoretical perspectives offers a comprehensive understanding of the complexities and dynamics of the blue economy. It highlights the importance of adaptability, vulnerability mitigation, innovation, and regionalized strategies in building a resilient and sustainable blue economy. By drawing on insights from these theories, policymakers, researchers, and practitioners can develop more effective frameworks for managing marine resources, fostering economic growth, and ensuring environmental sustainability within the context of global and regional challenges.
4. Evaluation Results of the Resilience of the Blue Economy
Overall, the resilience of the blue economy in China’s coastal regions has grown amidst fluctuations. The continuously expanding scale of the marine economy, the increasingly optimized marine industrial structure, the steadily enhanced marine scientific and technological strength, and more proactive marine environmental responses have strengthened the growth and recovery capabilities, control and transformation capabilities, and adaptability and adjustment abilities of the blue economy. However, due to the imbalance in the development foundation and differences in the development positioning of the marine economy, there is a significant gap in the blue economy’s resilience among provinces, with issues of uneven and insufficient growth still present.
Specifically, within the northern marine economic circle, Shandong’s blue economy resilience median is higher than 0.3, significantly above other regions, and its violin plot length is longer, with the black box positioned higher up. This indicates that the region has a high level of blue economy resilience and a fast improvement rate. The kernel density curves for Liaoning, Tianjin, and Shandong are all “single-peaked”, whereas Hebei’s blue economy resilience level is far below that of other regions, with a “double-peaked” kernel density curve, indicating low and unstable resilience levels. The possible reason for this is Hebei’s smaller marine economy scale, its marine industry still being in a more extensive development stage, and its insufficient marine innovation capabilities, resulting in lower scores for Hebei in terms of growth and recovery, control, and transformation capabilities. In the eastern marine economic circle, Shanghai’s blue economy resilience median ranges between 0.25 and 0.3, slightly higher than in the area of Jiangsu–Zhejiang. Although the outer violin shell length is long, the inner black box is positioned lower, indicating a general downward trend in Shanghai’s blue economy resilience. High-intensity socio-economic activities have increased marine ecological pressure, coupled with frequent marine disasters in recent years, leading to reduced scores in terms of resistance and resilience capabilities for regions like Shanghai. In the southern marine economic circle, Guangdong’s blue economy resilience median is close to 0.4, significantly higher than Fujian, Guangxi, and Hainan. The latter three have their medians and black boxes positioned very low, with “single-peaked” kernel density distributions. Although the southern marine economic circle is known for its rich marine resources, there is still a significant development space. Apart from Guangdong, the scale of marine economic development in these areas is far lower than that of other regions in the same period, indicating a heavy task in developing the blue economy in the southern marine economic circle.
5. Social Network Analysis
5.1. Characteristics of Individual Network Structure
The analysis of nodal centrality reveals that Shandong, Shanghai, and Guangdong occupy pivotal roles within their respective marine economic circles, demonstrating significant influence and leadership. This suggests that these regions are central to the network of blue economy resilience, exerting a substantial radiating effect and holding commanding positions. Notably, Shanghai’s nodal centrality has seen a decline in recent years, indicating a shift towards a more comparable standing with Zhejiang within the central marine economic circle. This change points to evolving dynamics of competition and collaboration within the network, highlighting the fluid nature of leadership and influence in the blue economy resilience framework.
From the viewpoint of betweenness centrality, there was a noticeable decline from 2007 to 2013 and 2019, suggesting a reduction in the network’s polarizing tendencies and a more balanced distribution of influence among its nodes. Specifically, Shandong, Guangdong, and Shanghai maintained high levels of betweenness centrality across these periods, underscoring their significant control and pivotal roles as connecting hubs within the network. Conversely, regions such as Tianjin, Hebei, Guangxi, and Hainan consistently exhibit a betweenness centrality of zero, placing them in comparatively peripheral positions within the network. This dynamic highlights a shift towards a more equitable connectivity and interaction among regions, albeit with certain areas remaining less central in the overall structure.
The analysis of closeness centrality further reveals that, while regions like Liaoning, Zhejiang, Guangdong, Guangxi, and Hainan may not occupy leading positions within the network, they have consistently demonstrated an upward trajectory in this measure. This trend signifies an acceleration in the flow and exchange of blue economy resources across these areas. Notably, in 2019, the closeness centrality across coastal areas saw a general improvement, highlighting a significant enhancement in the mobility and interconnectivity of the entire blue economy resilience network. This advancement indicates a strengthened interaction among the nodes, thereby facilitating a more dynamic and responsive network structure. These insights not only shed light on the structural features and evolving patterns of the blue economy resilience network in coastal regions but also offer critical policy insights and strategic recommendations for further enhancing the network’s architecture and elevating the resilience level of the blue economy in these areas.
5.2. Overall Network Structure Characteristics
This research meticulously investigates the evolution of the blue economy resilience network within China’s coastal regions from 2007 to 2019, crafting a detailed map of structural changes based on pivotal metrics such as network density, clustering coefficient, and average path length. The observed yearly variations and overall growth in network density underscore an intensification of connections within the blue economy’s resilience across these coastal areas, particularly between 2013 and 2019. Despite a trend towards stabilization in the network’s structure, the average network density remains at a modest 0.397, highlighting significant potential for enhancing collaborative efficiency within the blue economy resilience network.
The network clustering coefficient exhibits an inverted “W”-shaped trend, consistently remaining below that of a similarly scaled random network. This pattern underscores a low degree of clustering within the blue economy resilience network across coastal areas, indicating that the connections between the nodes are relatively sparse. This dispersion suggests that, while certain regions may engage in robust interactions within the blue economy sphere, overall, blue economic activities are predominantly focused around a few central nodes. This concentration prevents the emergence of a broad-based regional synergy, highlighting an area for potential enhancement to foster a more interconnected and collaborative blue economy network.
The analysis of the network’s average path length indicates that the efficiency of information and resource dissemination within the coastal areas’ blue economy resilience network is generally suboptimal. Notably, a slight upward trend post 2016 suggests a decline in the network’s efficiency regarding the flow of resources and information in recent years. This trend may stem from factors such as the geographic distribution of marine economic activities, adjustments in the industrial structure, and shifts in the marine environment. These factors contribute to increased costs associated with emergency responses and resource allocation within the network. Particularly in the context of marine disasters and other urgent situations, the capability for rapid inter-regional response appears constrained.
In conclusion, while the blue economy resilience network in coastal areas has achieved a degree of structural stability, there remains substantial scope for enhancing its coordination, clustering, and transmission efficiency. Future efforts should aim to bolster inter-regional coordination within the blue economy, refine the network’s architecture, and augment the efficiency of information and resource flows. By doing so, we can forge a more interconnected and efficient blue economy resilience network, thereby advancing the sustainable development of the blue economy in coastal regions.
5.3. Evolution Characteristics of Cyberspace Structure
Firstly, the network’s scale expansion and density increase signify a strengthening of connections within marine economic circles and a notable enhancement of the network’s radiative effect. This evolution from sparse to dense connectivity not only bolsters the network’s cohesion but also fosters inter-circle resilience in the blue economy, thereby reinforcing the coordinated development across the northern, eastern, and southern marine economic circles.
Secondly, the network’s hierarchical structure is manifested through the radial dispersion of core nodes within the spatial layout, transitioning from Shandong–Shanghai–Guangdong to Shandong–Zhejiang–Guangdong. This shift indicates that Shanghai’s marine ecological environment faces challenges due to intense socio-economic activities and frequent marine disasters, and, thus, its pivotal role in the blue economy resilience network is under threat. Meanwhile, Zhejiang has emerged as the new cornerstone of the eastern marine economic circle, attributed to its stable marine economic growth and efficient marine resource management.
Thirdly, the enhancement of network connectivity within distinct marine economic zones is evident in the notable performance of both the northern and southern marine economic sectors. Leveraging its robust marine scientific and technological capabilities, the northern marine economic zone consistently deepens integration, fosters the exchange and coordination of marine economic resources, and bolsters the gravitational pull among internal network nodes. Meanwhile, the southern marine economic zone capitalizes on its abundant marine resources, particularly centered around Guangdong, to significantly bolster its capacity for stability enhancement and industrial recovery within the marine economy. This strengthens its control and driving influence within the network, further accentuating the siphoning effect of its core node.
By employing a spatial framework characterized by multi-faceted leadership and coordination across the three regions, China’s blue economy resilience network not only demonstrates the dynamic evolution of its internal architecture but also presents a fresh perspective and strategy for advancing high-quality development within coastal blue economies. Moving forward, prioritizing the enhancement and synchronization of inter-regional connections within the blue economy resilience network while optimizing its structural layout holds paramount importance for fostering the sustainable growth of China’s marine economy and significantly bolstering the overall resilience of the blue economy.
6. TERGM Analysis
In this study, both estimation methods are employed to conduct a thorough analysis of the factors influencing the formation of the blue economy resilience network. The model’s AIC and BIC values, both below 1000, signify high degrees of fit and explanatory capabilities. This outcome not only validates the chosen model’s efficacy but also provides a scientific foundation for comprehending the pivotal factors shaping the construction of the blue economy resilience network.
Firstly, the variance in the stability enhancement capacity of the marine economy profoundly influences the establishment of the blue economy resilience network. This suggests that, within regions marked by substantial differences in their economic development levels, those experiencing swifter economic growth are notably appealing to regions with slower development rates. This “siphon effect” fosters resource flow between regions, hastening the cross-regional exchange and integration of blue economy resources.
Secondly, the coefficient of influence of the variance in marine industrial structure is negative, suggesting that a greater similarity in marine industrial structure between regions correlates with closer ties in the blue economy resilience network. This phenomenon likely stems from the fact that comparable industrial structures foster the convergence of capital, technology, and labor demands, thereby facilitating resource sharing and collaboration among regions.
Thirdly, the positive coefficient of influence regarding the variance in environmental regulation intensity suggests that regional disparities in regulatory stringency may prompt market players to relocate from regions with stricter regulations to those with more lenient ones. This not only affects resource allocation between regions but also influences the formation of the blue economy’s resilience network.
Fourthly, the negative coefficient of influence pertaining to the variance in marine scientific and technological prowess underscores the fact that, when marine economic resources are heavily concentrated in certain developed regions, differences in marine scientific and technological capabilities among regions impede scientific and technological exchanges and cooperation. This scenario is detrimental to the construction and advancement of the blue economy’s resilience network.
Robustness Test
7. Conclusions and Suggestions
7.1. Conclusions
This study systematically measures and deeply analyzes the resilience of the blue economy in China’s coastal regions from 2007 to 2019, employing a comprehensive approach encompassing the entropy weight method, social network analysis, and the time series edge plot regression model (TERGM). Through these methodologies, this paper unveils the dynamic evolutionary process and influencing factors of the blue economy’s resilience network, yielding the following key conclusions:
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Growth Trend and Challenges
Over the study period, the resilience of the blue economy in China’s coastal regions exhibited a fluctuating growth trend, propelled by the expansion of the marine economy scale and advancements in marine scientific and technological capabilities. However, due to the imbalanced foundation of marine economic development and regional disparities in marine economic development strategies, growth within the marine economy remains uneven and insufficient. Particularly, regions such as Hebei and Guangxi display a low resilience, while Shanghai’s blue economy resilience demonstrates a downward trajectory, highlighting challenges in marine economic development across certain regions.
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Analysis of Network Structure Characteristics
The individual structure of the blue economy’s resilience network exhibits prominent core–periphery characteristics, with core regions like Shandong and Guangdong holding high degrees of centrality within the network, while Tianjin and Hebei consistently occupy peripheral positions. In recent years, the strengthening of regional indirect closeness centrality indicates an enhanced regional interconnectedness within the network, signifying a gradual improvement in the integration level of the blue economy’s resilience network.
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Network Performance and Spatial Pattern
The rise in network density and expansion of the network scale signify the development of the blue economy’s resilience network towards a closer and more extensive direction. Nonetheless, network agglomeration and transmission remain lower compared to a random network of a similar scale, indicating the need for enhanced flexibility and adaptability. Furthermore, the increase in network spatial correlation strength contributes to the spatial pattern of “multi-point leading, three-zone coordination”, significantly enhancing interactions among diverse marine economic circles.
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Analysis of Influencing Factors
Variances in the stability enhancement capacity of the marine economy and marine industrial structure positively impact the formation of the blue economy’s resilience network, while disparities in environmental regulation intensity and marine science and technology strength exert negative influences. This finding sheds light on pivotal factors driving the formation and development of the blue economy’s resilience network, providing robust support for the formulation of pertinent policies and strategies.
In summary, this study not only offers insights into understanding and fortifying the resilience of the blue economy in China’s coastal regions but also provides critical guidance for crafting strategies and policies aimed at promoting sustainable development within the marine economy. Moving forward, optimizing the network structure and enhancing the network performance of the blue economy’s resilience network will be pivotal in driving high-quality development within coastal blue economies.
7.2. Suggestions
Moreover, safeguarding the marine ecological environment and enhancing the value of marine ecology are pivotal in constructing a healthy and stable blue economy resilience network. Strengthening marine ecological protection and restoration and enhancing the efficiency and efficacy of marine environmental governance can effectively bolster the resilience of the blue economy in coastal regions, ensuring strong support for its sustainable development.
Through the implementation of these measures, not only can the internal connectivity and external interaction of the blue economy resilience network in coastal areas be strengthened, but also efficient collaboration and high-quality development of the marine economy can be advanced, laying a robust foundation for achieving the strategic objective of maritime prowess.
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