Amid the dual imperatives of global trade expansion and low-carbon transition, intelligent maritime shipping has emerged as a central driver for the innovation of international logistics systems, now entering a critical window period for the deep integration of Internet technologies and automated port infrastructure. While existing research predominantly focuses on isolated applications of intelligent technologies, systematic evaluations of the synergistic effects of technological integration on maritime ecosystems, policy compatibility, and contributions to global carbon emission governance remain under-explored. Leveraging bibliometric analysis, this study systematically examines 488 publications from the Web of Science (WoS) Core Collection (2000–2024), yielding three pivotal findings: firstly, China dominates the research landscape, with a 38.5% contribution share, where Artificial Intelligence (AI), the Internet of Things (IoT), and port automation constitute the technological pillars. However, critical gaps persist in cross-system protocol standardization and climate-adaptive modeling, accounting for only 2.7% and 4.2% of the literature, respectively. Secondly, international collaboration networks exhibit pronounced “Islamization”, characterized by an inter-team collaboration rate of 17.3%, while the misalignment between rapid technological iteration and existing maritime regulations exacerbates industry risks. Thirdly, a dual-track pathway integrating Cyber–Physical System (CPS)-based digital twin ports and open-source vertical domain-specific large language models is proposed. Empirical evidence demonstrates its efficacy in reducing cargo-handling energy consumption by 15% and decision-making latency by 40%. This research proposes a novel tripartite framework, encompassing technological, institutional, and data sovereignty dimensions, to resolve critical challenges in integrating multi-source maritime data and managing cross-border governance. The model provides academically validated and industry-compatible strategies for advancing sustainable maritime intelligence. Subsequent investigations should expand data sources to include regional repositories and integrate interdisciplinary approaches, ensuring the adaptability of both technical systems and international policy coordination mechanisms across diverse maritime ecosystems.

The 21st Century Maritime Silk Road (MSR) is a key component of China’s Belt and Road Initiative (BRI), launched in 2013 to enhance global connectivity and foster economic cooperation. By promoting infrastructure development, trade facilitation, and cultural exchange, the MSR seeks to strengthen maritime connectivity, boost regional economic integration, and create new growth opportunities for participating countries. The MSR policy has a positive promoting effect on the economic construction and port development of China’s coastal ports. This study established a difference-in-difference model (DID) to explore the impact of MSR policies on SO₂ emissions from coastal and inland ports in China. We searched for panel data from 34 coastal and inland ports in China from 2008 to 2023, and based on this panel data, established a DID model for regression analysis. The regression analysis results indicate that the implementation of MSR policy has a significant positive impact on SO₂ emissions from coastal and inland ports in China. Some control variables, such as the total amount of imported goods and domestic emission control area (DECA) policies, also have a significant negative impact on SO₂ emissions, while the number of berths, population, and total amount of exported goods have a significant positive impact on SO₂ emissions. Based on the regression results of the model, we have proposed some suggestions for port operators and relevant governments to better adapt to MSR policies, promote economic development and environmental protection of ports.

This paper aims to analyze how the digital economy affects industrial restructuring and examine the mediating role of the relevant factors. Based on the analysis of the effect mechanism of the digital economy development on industrial restructuring, this paper constructs an improved measuring index system of digital economy covering digital infrastructure, digital industrialization, and industrial digitalization, and measures regional digital economic growth based on provincial panel data in China from 2013 to 2020 by using the entropy TOPSIS method, empirical analyses on the impact of the digital economy on industrial restructuring, and verifies the mediating effect of human capital, technological innovation, and financial development in this process. Research findings are as follows: (i) Digital economic growth demonstrates a considerable positive effect of the speed, efficiency of industrial restructuring, and industrial structure rationalization. (ii) Digital economy indirectly boosts industrial restructuring by affecting human capital, technological innovation, and financial development. The findings in this study are of theoretical significance to interpret the effect of digital economic growth on industrial restructuring, facilitating relevant economies in the decision-making of industrial restructuring and upgrading.

Port cargo throughput plays a pivotal role in driving national economic growth, facilitating trade activities, and promoting urban development. This study employs a Multi-scale Geographically Weighted Regression (MGWR) model to analyse the influencing factors of port cargo throughput, with regional Gross Domestic Product (GDP), highway construction investment, waterway construction investment, total import and export volume of goods, total retail sales of consumer goods, number of port berths, and urban residents’ consumption expenditure as independent variables. Based on data collected from 43 ports across China, the research reveals the magnitude and spatial distribution characteristics of these variables’ impacts on port cargo throughput. By comparing the fitting results of the global regression model with those of local regression models, the study demonstrates that the MGWR model achieves superior local regression fitting compared to the fixed-bandwidth Geographically Weighted Regression (GWR) model. This research provides theoretical support for understanding the spatial heterogeneity of factors influencing port cargo throughput and offers actionable insights for policy formulation and port planning.

With the accelerated growth of global trade, the shipping industry has experienced substantial expansion due to its reliability and cost-effectiveness in facilitating globalization. However, the environmental consequences of this rapid development, particularly pollution emissions, have garnered increasing attention. Sulfur dioxide has drawn more attention than other shipping pollutants due to its serious negative effects on health. America has three delimited emission control areas to limit sulfur emissions from ships and to enhance the quality of air in America’s coastal areas. This paper uses the difference in difference (DID) model to assess the sulfur emissions in the five busiest ports in America and check whether the emission control area (ECA) policy has a positive significant effect in decreasing the sulfur dioxide emission in the five busiest ports in America. The variables used for this study are sulfur emissions, gross domestic products, imports, exports, inflation rate as well as throughput for each of the five ports. The research results indicate that sulfur emission policies have no significant positive impact on ports other than the Port of Los Angeles, as many regulations have been developed to reduce the adverse effects of ship pollution emissions before the implementation of sulfur regulations.

With the rapid advancement of digitization, the duty of the digital economic climate in advertising regional economic growth is ending up being progressively noticeable. Nonetheless, there is relatively little research study on how the digital economic situation specifically impacts regional environment-friendly and high-quality financial growth (RGED). This study utilizes provincial panel data from 2013 to 2020 in China to empirically assess the effect of the digital economic environment and validates its effect with a fixed impacts model. The study has produced four unique and important findings for: firstly, the effect of the digital economic climate on RGED exhibits nonlinear qualities; Second of all, RGED is significantly influenced by the “∩ - formed” effect of the advancement of the digital economic situation and the degree of industrial digitization; Finally, the influence of digital framework and digital industrialization on RGED exhibits a considerable “U-shaped” pattern; Fourth, the digital economic situation indirectly advertises the growth of RGED by enhancing human funding and updating commercial structure. These conclusions offer beneficial plan support for relevant financial entities to achieve RGED. First published online 05 June 2025