Development of public dynamic spatio-temporal monitoring and analysis tool of supply chain vulnerability, resilience, and sustainability

Supply chains play a pivotal role in driving economic growth and societal
well-being, facilitating the efficient movement of goods from producers to
consumers. However, the increasing frequency of disruptions caused by
geopolitical events, pandemics, natural disasters, and shifts in commerce
poses significant challenges to supply chain resilience. This draft update
report discusses the development of a dynamic spatio-temporal monitoring
and analysis tool to assess supply chain vulnerability, resilience, and
sustainability. Leveraging news data, macroeconomic metrics, inbound cargo
data (for sectors in California), and operational conditions of
California’s highways, the tool employs Natural Language Processing (NLP)
and empirical regression analyses to identify emerging trends and extract
valuable information about disruptions to inform decision-making. Key
features of the tool include sentiment analysis of news articles, topic
classification, visualization of geographic locations, and tracking of
macroeconomic indicators. By integrating diverse and dynamic data sources
(e.g., news articles) and using empirical and analytical techniques, the
tool offers a comprehensive framework to enhance our understanding of
supply chain vulnerabilities and resilience, ultimately contributing to
more effective strategies for decision-making in supply chain management.
The dynamic nature of this tool enables continuous monitoring and
adaptation to evolving conditions, thereby enhancing the analysis of
resilience and sustainability in global supply chains.