Extreme weather is driving surges in food delivery orders and the packaging waste they generate, and this project will measure exactly how much. The problem is straightforward but poorly understood. When heatwaves, cold snaps, or heavy rain hit, more people order food online to avoid going out. That spike in deliveries means more plastic, cardboard, and single-use containers entering the waste stream—at precisely the moments when waste collection systems may already be strained by the weather. Current data on this link is sparse. The project brings together researchers in the UK, Taiwan, Singapore, and Australia to analyse real delivery and weather data using statistical models that can capture complex, non-linear relationships. If successful, the research will produce the first systematic evidence of how specific weather events drive delivery volumes and waste. That evidence can inform practical changes: better packaging design for extreme-weather periods, more resilient logistics planning, and targeted policy recommendations for reducing single-use waste without cutting off access to food. The findings will be relevant to any city where food delivery is common and extreme weather is becoming more frequent.
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With the growth of internet technology, food delivery has become an important part of daily life for many people. Extreme weather events like heatwaves, cold snaps, heavy rainfall, and snowstorms are becoming more frequent, significantly affecting urban life, especially online food consumption and delivery services. During such events, many people rely on food delivery to avoid going out, leading to a surge in orders and increased packaging waste, which poses environmental challenges. This project aims to use advanced data analytics to systematically assess the impacts of extreme weather on online food delivery and its environmental consequences. Our international collaboration connects researchers from UK, Taiwan, Singapore, and Australia to study how these weather events influence food delivery patterns and the associated rise in packaging waste. We will use advanced statistical models, such as spatio-temporal quantile regression and zero-inflated time series models, to capture the complex relationships between extreme weather, online food consumption, and waste generation. This research will foster collaborations between Taiwan (Feng Chia University-FCU, National Tsing Hua University-NTHU, National Central University-NCU) and UK (Brunel University London-BUL) in understanding these impacts. By uncovering the link between extreme weather, food delivery, and environmental impact, we can offer recommendations for more sustainable, low-carbon consumption behaviors to better adapt to future climate changes. The outcomes will benefit not only Taiwan and UK but also extend to Singapore (Nanyang Technological University-NTU) and Australia (The University of Sydney Business School-USBS), providing valuable insights for policy-making to enhance resilience in food delivery systems amid extreme weather challenges.
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