Modelling food sourcing decisions under climate change: A data-driven approach

Rengarajan Srinivasan, Vaggelis Giannikas, Mukesh Kumar, Renaud Guyot, Duncan McFarlane

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3 Citations (Scopus)
5 Downloads (Pure)

Abstract

Changes in climate conditions are expected to pose significant challenges to the food industry, as it is very likely that they will affect 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 affect the suitability and risk of different 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 significant adaptations due to changes to the suitability of certain regions.

Original languageEnglish
Pages (from-to)911-919
Number of pages9
JournalComputers and Industrial Engineering
Volume128
Early online date26 Oct 2018
DOIs
Publication statusPublished - 28 Feb 2019

Keywords

  • Climate change
  • Food supply chain
  • Open data
  • Sourcing decision
  • Sourcing risk

ASJC Scopus subject areas

  • Computer Science(all)
  • Engineering(all)

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