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Assessing regional and global environmental footprints and value added of the largest food producers in the world

Kucukvar, Murat, Onat, Nuri C., Abdella, Galal M., Tatari, Omer
Resources, conservation, and recycling 2019 v.144 pp. 187-197
algorithms, carbon, carbon footprint, databases, employment, energy, food industry, food supply chain, human resources, socioeconomic factors, statistical analysis, supply chain, value added, China, United States
This research aims to provide important insights regarding the environmental and socioeconomic impacts of the world’s largest food producing countries based on four sustainability metrics: energy use, carbon footprint, value-added and compensation of employees by low, medium and high-skill groups. World Input-Output Database is used as a detailed and intercountry and sector economic database. To compare the results between global databases, Eora and EXIOBASE are also used for comparative analysis. Three statistical analysis techniques such as Mann-Kendal trend test, matching index and k-means clustering algorithm are applied to provide a further insight from the analysis. The results are presented for three categories: regional on-site, regional supply chain, and global supply chain. The agriculture industry has the largest environmental footprints in food supply chains. Based on the Mann-Kendall trend test, there is a statistically significant trend in carbon, energy, and employment indicators. The maximum value of the matching–index of the overall impact (0.92) is achieved between the EXIOBASE and WIOD databases. China and USA are positioned in different clusters based on total sustainability performance when using different MRIO databases.