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- All Subjects: Supply Chain Management
- Creators: Department of Information Systems
The Russian invasion of Ukraine began in February 2022, and has caused a ripple effect of global supply disruptions. The United States, Canada, EU and other allies have responded to the Russian invasion of Ukraine by sanctioning imports from Russia in an attempt to isolate their economy. However, some countries that have not placed trade sanctions on Russia are taking advantage of the opportunity to import from Russia. By integrating import data from Panjiva into a geospatial mapping tool, ArcGIS, global trade patterns can be visualized to understand how global trade is impacted, the effectiveness of Western sanctions on Russia, and potential substitution effects on trade flows from one country to another. First, six key commodities and three countries were identified based on preliminary data analysis. After further analysis, it can be concluded that the Russian sanctions were not effective at isolating their economy for two reasons: certain commodities are critical to our modern lifestyles and some countries took advantage of Western trade sanctions on Russia and increased global trade. In an attempt to diversify their supply, many firms sourced from countries other than Russia, but oftentimes commodities are still sourced from Russia. Lack of supply chain visibility prevents business leaders from making the most efficient supply networks that are in alignment with government regulations.
The COVID-19 pandemic’s unprecedented nature caused significant disruptions in the global supply chain industry, resulting in setbacks for supply chain operations. The repercussions of the supply chain challenges impacted various industries. This thesis seeks to investigate the impact of the COVID-19 pandemic on the supply chain industry, with a focus on how disruptions have affected the efficiency and resilience of companies within this sector. Data analytics will be leveraged to analyze these disruptions and improve supply chain operations.
My recommendations to the company will be based on the findings of the analyses’ used. There may be multiple conclusions in the recommendations for demand forecasting based on each individual forecast used. However, I will give my insight on which forecast I think is more accurate and why this one would be the best to implement in terms of accuracy. Going forward, the company will be capable of implement these models and fine tune them as necessary to help streamline their inventory needs.
Keywords. Supply Chain Management, Social Responsibility, Sustainability, Economics, Supply Management, Blockchain, Intelligent Technology
Paper Type. Conceptual Paper