Effect of Climate Change on Food Industry Supply Chain Resilience in China on the Basis of Double Machine Learning Models
Shengtian Jin, Dongxian Liu, Luchen Huang

TL;DR
This study examines how climate change affects the resilience of China's food industry supply chain using data from 30 provinces between 2011 and 2022.
Contribution
The paper introduces a novel application of double machine learning models to analyze climate impacts on food supply chain resilience in China.
Findings
Climate change significantly reduces food supply chain resilience, with temperature having a stronger negative effect than rainfall.
The impact of climate change varies between major and non-major food-producing regions and across levels of mechanization.
Crop diversification helps reduce the negative effects of temperature fluctuations on supply chain resilience.
Abstract
In recent years, global climate fluctuation has been obvious and has had a significant impact on the food industry system, which makes the impact of climate change on the resilience of the food industry supply chain of great concern. Based on this, this paper selects the panel data of 30 provinces in China from 2011 to 2022; it takes the relationship between climate change and the toughness of the food industry supply chain as the entry point, and probes deeply into the intrinsic mechanism of the impact of climate change on the toughness of the food industry supply chain. The study found the following: First, climate change has a significant negative impact on the food industry supply chain resilience, and in climate change, the impact of temperature on the food industry supply chain resilience is significantly higher than the impact of rainfall on the food industry supply chain…
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Taxonomy
TopicsAgricultural risk and resilience · Supply Chain Resilience and Risk Management
