To prevent the outbreak of the Coronavirus disease (COVID-19), many countries around the world went into lockdown and imposed unprecedented containment measures. These restrictions progressively produced changes to social behavior and global mobility patterns, evidently disrupting social and economic activities. Here, using maritime traffic data collected via a global network of Automatic Identification System (AIS) receivers, we analyze the effects that the COVID-19 pandemic and containment measures had on the shipping industry, which accounts alone for more than 80% of the world trade. We rely on multiple data-driven maritime mobility indexes to quantitatively assess ship mobility in a given unit of time. The mobility analysis here presented has a worldwide extent and is based on the computation of: Cumulative Navigated Miles (CNM) of all ships reporting their position and navigational status via AIS, number of active and idle ships, and fleet average speed. To highlight significant changes in shipping routes and operational patterns, we also compute and compare global and local vessel density maps. We compare 2020 mobility levels to those of previous years assuming that an unchanged growth rate would have been achieved, if not for COVID-19. Following the outbreak, we find an unprecedented drop in maritime mobility, across all categories of commercial shipping. With few exceptions, a generally reduced activity is observable from March to June 2020, when the most severe restrictions were in force. We quantify a variation of mobility between −5.62 and −13.77% for container ships, between +2.28 and −3.32% for dry bulk, between −0.22 and −9.27% for wet bulk, and between −19.57 and −42.77% for passenger traffic. The presented study is unprecedented for the uniqueness and completeness of the employed AIS dataset, which comprises a trillion AIS messages broadcast worldwide by 50,000 ships, a figure that closely parallels the documented size of the world merchant fleet.

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Purpose Population growth, urbanisation and the increased use of online shopping are some of the key challenges affecting the traditional logistics model. The purpose of this paper is to focus on the distribution of grocery products ordered online and the subsequent home delivery and click and collect services offered by online retailers to fulfil these orders. These services are unsustainable due to increased operational costs, carbon emissions, traffic and noise. The main objective of the research is to propose sustainable logistics models to reduce economic, environmental and social costs whilst maintaining service levels. Design/methodology/approach The authors have a mixed methodology based on simulation and mathematical modelling to evaluate the proposed shared logistics model using: primary data from a major UK retailer, secondary data from online retailers and primary data from a consumer survey on preferences for receiving groceries purchased online. Integration of these three data sets serves as input to vehicle routing models that reveal the benefits from collaboration by solving individual distribution problems of two retailers first, followed by the joint distribution problem under single decision maker assumption. Findings The benefits from collaboration could be more than 10 per cent in the distance travelled and 16 per cent in the time required to deliver the orders when two online grocery retailers collaborate in distribution activities. Originality/value The collaborative model developed for the online grocery market incentivises retailers to switch from current unsustainable logistics models to the proposed collaborative models.