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Identifying food insecurity in food sharing networks via machine learning

Author

Listed:
  • Nica-Avram, Georgiana
  • Harvey, John
  • Smith, Gavin
  • Smith, Andrew
  • Goulding, James

Abstract

Food insecurity in the UK has captured public attention. However, estimates of its prevalence are deeply contentious. The lack of precision on the volume of emergency food assistance currently provided to those in need is made even more ambiguous due to increasing use of peer-to-peer food sharing systems (e.g. OLIO). While these initiatives exist as a solution to food waste rather than food poverty, they are nonetheless carrying a hidden share of the food insecurity burden, with the socio-economic status of technology-assisted food sharing donors, volunteers, and recipients remaining obscure. In this article we examine the relationship between food sharing and deprivation generally, before applying machine learning techniques to develop a predictive model of food insecurity based upon aggregated food sharing behaviours by OLIO users in the UK. We demonstrate that data from food sharing systems can help quantify a previously hidden aspect of deprivation and we make the case for a reformed approach to modelling food insecurity.

Suggested Citation

  • Nica-Avram, Georgiana & Harvey, John & Smith, Gavin & Smith, Andrew & Goulding, James, 2021. "Identifying food insecurity in food sharing networks via machine learning," Journal of Business Research, Elsevier, vol. 131(C), pages 469-484.
    • Handle: RePEc:eee:jbrese:v:131:y:2021:i:c:p:469-484
    DOI: 10.1016/j.jbusres.2020.09.028
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    1. Daniel D. Lee & H. Sebastian Seung, 1999. "Learning the parts of objects by non-negative matrix factorization," Nature, Nature, vol. 401(6755), pages 788-791, October.
    2. Michelini, Laura & Principato, Ludovica & Iasevoli, Gennaro, 2018. "Understanding Food Sharing Models to Tackle Sustainability Challenges," Ecological Economics, Elsevier, vol. 145(C), pages 205-217.
    3. Sivarajah, Uthayasankar & Kamal, Muhammad Mustafa & Irani, Zahir & Weerakkody, Vishanth, 2017. "Critical analysis of Big Data challenges and analytical methods," Journal of Business Research, Elsevier, vol. 70(C), pages 263-286.
    4. César Ducruet & Laurent Beauguitte, 2014. "Spatial Science and Network Science: Review and Outcomes of a Complex Relationship," Networks and Spatial Economics, Springer, vol. 14(3), pages 297-316, December.
    5. Li, Qingyuan & Li, Si & Xu, Li, 2018. "National elections and tail risk: International evidence," Journal of Banking & Finance, Elsevier, vol. 88(C), pages 113-128.
    6. Francesca Galli & Alessio Cavicchi & Gianluca Brunori, 2019. "Food waste reduction and food poverty alleviation: a system dynamics conceptual model," Agriculture and Human Values, Springer;The Agriculture, Food, & Human Values Society (AFHVS), vol. 36(2), pages 289-300, June.
    7. César Ducruet & Laurent Beauguitte, 2014. "Network science and spatial science : Review and outcomes of a complex relationship," Post-Print hal-03246947, HAL.
    8. Loopstra, Rachel & Reeves, Aaron & Tarasuk, Valerie, 2019. "The rise of hunger among low-income households: an analysis of the risks of food insecurity between 2004 and 2016 in a population-based study of UK adults," LSE Research Online Documents on Economics 100880, London School of Economics and Political Science, LSE Library.
    9. Hruschka, Harald, 2014. "Linking Multi-Category Purchases to Latent Activities of Shoppers: Analysing Market Baskets by Topic Models," University of Regensburg Working Papers in Business, Economics and Management Information Systems 482, University of Regensburg, Department of Economics.
    10. Iijima, Ryota & Kamada, Yuichiro, 2017. "Social distance and network structures," Theoretical Economics, Econometric Society, vol. 12(2), May.
    11. repec:mpr:mprres:5077 is not listed on IDEAS
    12. Andrius Vabalas & Emma Gowen & Ellen Poliakoff & Alexander J Casson, 2019. "Machine learning algorithm validation with a limited sample size," PLOS ONE, Public Library of Science, vol. 14(11), pages 1-20, November.
    13. Takaya Saito & Marc Rehmsmeier, 2015. "The Precision-Recall Plot Is More Informative than the ROC Plot When Evaluating Binary Classifiers on Imbalanced Datasets," PLOS ONE, Public Library of Science, vol. 10(3), pages 1-21, March.
    14. Oecd, 2018. "National Legislative And Regulatory Activities," Nuclear Law Bulletin, OECD Publishing, vol. 2016(2), pages 65-84.
    15. Oecd, 2018. "National legislative and regulatory activities," Nuclear Law Bulletin, OECD Publishing, vol. 2017(1), pages 75-95.
    16. Daiane Scaraboto, 2015. "Selling, Sharing, and Everything In Between: The Hybrid Economies of Collaborative Networks," Journal of Consumer Research, Journal of Consumer Research Inc., vol. 42(1), pages 152-176.
    17. Thompson, C. & Smith, D. & Cummins, S., 2018. "Understanding the health and wellbeing challenges of the food banking system: A qualitative study of food bank users, providers and referrers in London," Social Science & Medicine, Elsevier, vol. 211(C), pages 95-101.
    18. repec:elg:eechap:15612_26 is not listed on IDEAS
    19. Oecd, 2018. "National legislative and regulatory activities," Nuclear Law Bulletin, OECD Publishing, vol. 2018(1), pages 93-106.
    20. Stephen P. Borgatti, 2006. "Identifying sets of key players in a social network," Computational and Mathematical Organization Theory, Springer, vol. 12(1), pages 21-34, April.
    Full references (including those not matched with items on IDEAS)

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