Modelling food sourcing decisions under climate change: A data-driven approach
Computers and Industrial Engineering
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Srinivasan, R., Giannikas, E., Kumar, M., Guyot, R., & McFarlane, D. (2019). Modelling food sourcing decisions under climate change: A data-driven approach. Computers and Industrial Engineering, 128 911-919. https://doi.org/10.1016/j.cie.2018.10.048
Changes in climate conditions are expected to pose signi cant challenges to the food industry, as it is very likely that they will a ect the production of various crops. As a consequence, decisions associated with the sourcing of food items will need to be reconsidered in the years to come. In this paper, we investigate how environmental changes are likely to a ect the suitability and risk of di erent regions |in terms of growing certain food items| and whether companies should adapt their sourcing decisions due to these changes. In particular, we propose a three-stage approach that guides food sourcing decisions by incorporating climate change data. The methodology utilises environmental data from several publicly available databases and models weather uncertainties to calculate the suitability and risk indices associated with growing a crop in a particular geographical area. The estimated suitability and risk parameters are used in a mean-variance analysis to calculate the optimal sourcing decision. Results from a case example indicate that sourcing decisions of popular food items are likely to require signi cant adaptations due to changes to the suitability of certain regions.
External DOI: https://doi.org/10.1016/j.cie.2018.10.048
This record's URL: https://www.repository.cam.ac.uk/handle/1810/286523