Spatial-temporal evolution characteristics and spillover effects of carbon emissions from shipping trade in EU coastal countries

Ocean & Coastal Management, Год журнала: 2024, Номер 250, С. 107029 - 107029

Опубликована: Янв. 31, 2024

Язык: Английский

---

Exploring the factors affecting the performance of shipping companies based on a panel data model: A perspective of antitrust exemption and shipping alliances

Ocean & Coastal Management, Год журнала: 2024, Номер 253, С. 107162 - 107162

Опубликована: Апрель 26, 2024

Язык: Английский

---

Optimizing anti-collision strategy for MASS: A safe reinforcement learning approach to improve maritime traffic safety

Ocean & Coastal Management, Год журнала: 2024, Номер 253, С. 107161 - 107161

Опубликована: Апрель 29, 2024

Язык: Английский

---

Living labs for the resilience of ports against climate change disruptions

Ocean & Coastal Management, Год журнала: 2025, Номер 261, С. 107528 - 107528

Опубликована: Янв. 2, 2025

Язык: Английский

---

Maritime transport resilience: A systematic literature review on the current state of the art, research agenda and future research directions

Ocean & Coastal Management, Год журнала: 2024, Номер 251, С. 107086 - 107086

Опубликована: Март 11, 2024

Язык: Английский

---

Analyzing spatio-temporal variability of aquatic productive components in Northern Bay of Bengal using advanced machine learning models

Ocean & Coastal Management, Год журнала: 2024, Номер 251, С. 107074 - 107074

Опубликована: Март 1, 2024

Язык: Английский

---

A big data analytics method for the evaluation of maritime traffic safety using automatic identification system data

Ocean & Coastal Management, Год журнала: 2024, Номер 251, С. 107077 - 107077

Опубликована: Март 6, 2024

The complex traffic situations are among the factors influencing maritime safety. They can be quantitatively estimated through analysis of data. This paper explores impact on safety, focusing inland waterway traffic. It presents a big data analytics method, utilizing from Automatic Identification System (AIS) and historical accident records. methodology involves AIS preprocessing spatial autocorrelation models, including Moran's index, to extract evaluate dynamic characteristics characteristic includes thorough investigation into spatial-temporal distribution ship average speed trajectory density. then introduces an effective model that evaluates relationship between patterns accidents. study, specifically targeting Nanjing section Yangtze River, reveals variations in density over time. identifies several hotspots with significant local correlation these factors. Moreover, substantial is found locations accidents areas increased speed. These results may provide insights for safety management highlight strategies preventing

Язык: Английский

---

Data-driven approach for port resilience evaluation

Transportation Research Part E Logistics and Transportation Review, Год журнала: 2024, Номер 186, С. 103570 - 103570

Опубликована: Май 8, 2024

Язык: Английский

---

Structural analysis and vulnerability assessment of the European LNG maritime supply chain network (2018–2020)

Ocean & Coastal Management, Год журнала: 2024, Номер 253, С. 107126 - 107126

Опубликована: Апрель 9, 2024

Язык: Английский

---

Sustainable Digital Shifts in Chinese Transport and Logistics: Exploring Green Innovations and Their ESG Implications

Sustainability, Год журнала: 2024, Номер 16(5), С. 1877 - 1877

Опубликована: Фев. 25, 2024

This study, situated in the context of China’s transportation and logistics industry, explores impact digital transformation on corporate environmental, social, governance (ESG) performance, as well role played by green innovation. Analyzing data from 95 A-share listed companies 2011 to 2021, this paper examines relationship between ESG drawing information asymmetry agency theories. The research finds that significantly elevates levels, with more pronounced effects state-owned large enterprises. degree financing constraints modulates relationship, indicating a stronger enhancement performance under lower constraints. Moreover, innovation serves mediator revealing boosts outcomes through fostering contribution study lies providing new insights into specific industry context, expanding field lens mechanisms conditions, underscoring central mediating influence

Язык: Английский

---