Analyzing drivers of organic food sales-A pooled spatial data analysis for Hamburg (Germany).

Shifting the food system to a more sustainable one requires changes on both sides of the supply chain, with the consumer playing a key role. Therefore, understanding the factors that positively correlate with increased organic food sales over time for an entire population can help guide policymakers, industry, and research to increase this transition further. Using a statistical approach, we developed a spatial pooled cross-sectional model to analyze factors that positively correlate with an increased demand for organic food sales over 20 years (1999-2019) for an entire region (the city-state of Hamburg, Germany), accounting for spatial effects through the spatial error model, spatially lagged X model, and spatial Durbin error model.

Global shipping network dynamics during the COVID-19 pandemic's initial phases.

Catastrophic incidents can significantly disrupt supply chains, but most of these disruptions remain localized. It was not until the onset of COVID-19 that a disruption in our lifetimes achieved a global magnitude. In order to contain the pandemic, governments around the world resorted to closing borders, shutting down manufacturing plants, and imposing lockdowns, which resulted in disrupted production capabilities and weakened consumer spending.

Potential and limiting factors in the use of alternative fuels in the European maritime sector.

The maritime sector is a key asset for the world economy, but its environmental impact represents a major concern. The sector is primarily supplied with Heavy Fuel Oil, which results in high pollutant emissions. The sector has set targets for deacrbonisation, and alternative fuels have been identified as a short-to medium-term option.