Li Jingdong, Song Zhouying
Institute of Geographic Sciences and Natural Resources Research, Chinese Academy of Sciences, Beijing 100101, China.
Key Laboratory of Regional Sustainable Development Modeling, Chinese Academy of Sciences, Beijing 100101, China.
Foods. 2022 Aug 23;11(17):2552. doi: 10.3390/foods11172552.
The food supply chain operates in a complex and dynamic external environment, and the external uncertainties from natural and socio-economic environment pose great challenges to the development of the food industry. In particular, the COVID-19 pandemic and Russia-Ukraine conflict have further exacerbated the vulnerability of the global food supply chain. Analyzing the dynamic impacts of external uncertainties on the stability of food supply chain is central to guaranteeing the sustainable security of food supply. Based on the division of food supply chain and the classification of external uncertainties, the TVP-FAVAR-SV model was constructed to explore the dynamic impacts of external uncertainties on food supply chain. It was found that the impacts of external uncertainty elements were significantly different, the combination of different external uncertainty elements aggravated or reduced the risks of food supply chain. And some uncertainty elements had both positive and negative impacts in the whole sample period, as the magnitude and direction of the impacts of various uncertainties in different periods had time-varying characteristics.
食品供应链在复杂多变的外部环境中运行,自然和社会经济环境带来的外部不确定性给食品行业发展带来巨大挑战。特别是,新冠疫情和俄乌冲突进一步加剧了全球食品供应链的脆弱性。分析外部不确定性对食品供应链稳定性的动态影响是保障食品供应可持续安全的核心。基于食品供应链的划分和外部不确定性的分类,构建了时变参数因子增强向量自回归带随机波动(TVP-FAVAR-SV)模型,以探究外部不确定性对食品供应链的动态影响。研究发现,外部不确定性因素的影响存在显著差异,不同外部不确定性因素的组合加剧或降低了食品供应链风险。并且一些不确定性因素在整个样本期内既有正向影响又有负向影响,因为不同时期各种不确定性影响的大小和方向具有时变特征。