Agent-based modeling demonstrates reduced emissions in a zero-emission cold chain for beef logistics, suggesting a path to sustainability.
The growing demand for sustainable food logistics underscores the need for a zero-emission cold chain model that integrates energy-efficient technologies, renewable energy sources, and digital innovations. This study develops an Agent-Based Modeling (ABM) simulation framework aimed at establishing a Zero-Emission Cold Chain (ZECC) for perishable food logistics, in line with the 2050 net-zero carbon target. The model includes electric vehicles (EVs), renewable energy, and digital logistics tools. The model evaluates decarbonization strategies through scenario analysis, including comparisons between traditional and electronic logistics auctions, as well as the deployment of electric vehicles and renewable energy. Results indicate that in the beef cold chain (BCC), adopting EVs, renewable energy, and digital auction systems can significantly reduce emissions and energy consumption. These findings offer practical insights for policymakers, industry stakeholders, and researchers to support a sustainable transition in cold chain logistics while enhancing food security, affordability, and environmental outcomes.
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Badiee et al. (2026) studied this question.
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