This paper aims to systematically review and analyze the literature on green shipping, focusing on research trends, key areas, and future directions. A bibliometric analysis is conducted on 1339 articles published between 2000 and 2023, using data from the SCI-EXPANDED and SSCI core collections on the Web of Science platform. Co-occurrence analyses are performed for authors, countries, institutions, and keywords. The analysis reveals exponential growth in green shipping research over the past decade, with a significant increase since 2019. China leads in publication output and international collaboration. Key research areas identified include sustainable development, green energy, green ports, and green supply chain management. Green shipping research is rapidly expanding, emphasizing sustainable practices and technological advancements. Future research is expected to integrate artificial intelligence, big data analytics, and other advanced technologies to further promote sustainability. Strengthening international cooperation and interdisciplinary integration will be crucial for advancing the global green shipping agenda.

Ship navigation technical data contains a lot of information. In this paper, we explore a relationship between the crude oil price and tankers’ port-call features by mining the information recorded in Automatic Identification System (AIS), which extends the application field of ship navigation technical data and aims to help oil shipping enterprises and port enterprises to arrange operation plans in advance. We generate a monthly panel data over the period from 2010 to 2020 of major global ports located in main crude oil exporting countries from AIS data. By using the panel fixed-effect model and binary logit model, our empirical results innovatively present the tanker’s monthly port-call features are influenced by crude oil price fluctuation through four dimensions, that is the tankers’ port-call numbers, the average docking time, total gross tonnage of the docking tankers and the number of different docking tankers. With these variables, we attempt to analyze the relationship between crude oil price fluctuation on tankers’ port-call features. The results of the study are helpful to comprehensively understand the impact mechanism of the crude oil price on the tankers’ port-call features.

We investigate the recovery of domestic industries following the effective control of the COVID-19 pandemic in China, which has implications for future trends in global economic recovery. We employ online firm recruitment data from a major Chinese online job listing website to reflect the recovery in employment and a regression discontinuity design. The results show that after the COVID-19 pandemic was effectively controlled in China from March 2020, the Chinese economy in terms of employment experienced an overall V-shaped recovery. From an industry perspective, some industries underwent the same rapid recovery, whereas others exhibited a U-shaped recovery path. In addition, we found that industries in the information technology industry were not negatively affected by COVID-19 and continued to perform well during the domestic epidemic.