IDEAS home Printed from https://ideas.repec.org/a/jas/jasssj/2020-188-2.html
   My bibliography  Save this article

Comparing Mechanisms of Food Choice in an Agent-Based Model of Milk Consumption and Substitution in the UK

Author

Abstract

Substitution of food products will be key to realising widespread adoption of sustainable diets. We present an agent-based model of decision-making and influences on food choice, and apply it to historically observed trends of British whole and skimmed (including semi) milk consumption from 1974 to 2005. We aim to give a plausible representation of milk choice substitution, and test different mechanisms of choice consideration. Agents are consumers that perceive information regarding the two milk choices, and hold values that inform their position on the health and environmental impact of those choices. Habit, social influence and post-decision evaluation are modelled. Representative survey data on human values and long-running public concerns empirically inform the model. An experiment was run to compare two model variants by how they perform in reproducing these trends. This was measured by recording mean weekly milk consumption per person. The variants differed in how agents became disposed to consider alternative milk choices. One followed a threshold approach, the other was probability based. All other model aspects remained unchanged. An optimisation exercise via an evolutionary algorithm was used to calibrate the model variants independently to observed data. Following calibration, uncertainty and global variance-based temporal sensitivity analysis were conducted. Both model variants were able to reproduce the general pattern of historical milk consumption, however, the probability-based approach gave a closer fit to the observed data, but over a wider range of uncertainty. This responds to, and further highlights, the need for research that looks at, and compares, different models of human decision-making in agent-based and simulation models. This study is the first to present an agent-based modelling of food choice substitution in the context of British milk consumption. It can serve as a valuable pre-curser to the modelling of dietary shift and sustainable product substitution to plant-based alternatives in Britain.

Suggested Citation

  • Matthew Gibson & Raphael Slade & Joana Portugal Pereira & Joeri Rogelj, 2021. "Comparing Mechanisms of Food Choice in an Agent-Based Model of Milk Consumption and Substitution in the UK," Journal of Artificial Societies and Social Simulation, Journal of Artificial Societies and Social Simulation, vol. 24(3), pages 1-9.
  • Handle: RePEc:jas:jasssj:2020-188-2
    as

    Download full text from publisher

    File URL: https://www.jasss.org/24/3/9/9.pdf
    Download Restriction: no
    ---><---

    References listed on IDEAS

    as
    1. William Rand & Jeffrey Herrmann & Brandon Schein & Neža Vodopivec, 2015. "An Agent-Based Model of Urgent Diffusion in Social Media," Journal of Artificial Societies and Social Simulation, Journal of Artificial Societies and Social Simulation, vol. 18(2), pages 1-1.
    2. Pachucki, M.A. & Jacques, P.F. & Christakis, N.A., 2011. "Social network concordance in food choice among spouses, friends, and siblings," American Journal of Public Health, American Public Health Association, vol. 101(11), pages 2170-2177.
    Full references (including those not matched with items on IDEAS)

    Most related items

    These are the items that most often cite the same works as this one and are cited by the same works as this one.
    1. Missinne, Sarah & Colman, Elien & Bracke, Piet, 2013. "Spousal influence on mammography screening: A life course perspective," Social Science & Medicine, Elsevier, vol. 98(C), pages 63-70.
    2. Iljana Schubert & Judith I. M. de Groot & Adrian C. Newton, 2021. "Challenging the Status Quo through Social Influence: Changes in Sustainable Consumption through the Influence of Social Networks," Sustainability, MDPI, vol. 13(10), pages 1-17, May.
    3. Jonas Friege & Georg Holtz & Emile Chappin, 2016. "Exploring Homeowners’ Insulation Activity," Journal of Artificial Societies and Social Simulation, Journal of Artificial Societies and Social Simulation, vol. 19(1), pages 1-4.
    4. Els Weinans & George van Voorn & Patrick Steinmann & Elisa Perrone & Ahmadreza Marandi, 2024. "An Exploration of Drivers of Opinion Dynamics," Journal of Artificial Societies and Social Simulation, Journal of Artificial Societies and Social Simulation, vol. 27(1), pages 1-5.
    5. Linna Luo & Bowen Pang & Jian Chen & Yan Li & Xiaolei Xie, 2019. "Assessing the Impact of Lifestyle Interventions on Diabetes Prevention in China: A Modeling Approach," IJERPH, MDPI, vol. 16(10), pages 1-12, May.
    6. Barsha Saha & Miguel Martínez-García & Sharad Nath Bhattacharya & Rohit Joshi, 2022. "Overcoming Choice Inertia through Social Interaction—An Agent-Based Study of Mobile Subscription Decision," Games, MDPI, vol. 13(3), pages 1-16, June.
    7. Reczek, Corinne, 2012. "The promotion of unhealthy habits in gay, lesbian, and straight intimate partnerships," Social Science & Medicine, Elsevier, vol. 75(6), pages 1114-1121.
    8. Conklin, Annalijn I. & Forouhi, Nita G. & Surtees, Paul & Khaw, Kay-Tee & Wareham, Nicholas J. & Monsivais, Pablo, 2014. "Social relationships and healthful dietary behaviour: Evidence from over-50s in the EPIC cohort, UK," Social Science & Medicine, Elsevier, vol. 100(C), pages 167-175.
    9. Chathika Gunaratne & Nisha Baral & William Rand & Ivan Garibay & Chathura Jayalath & Chathurani Senevirathna, 2020. "The effects of information overload on online conversation dynamics," Computational and Mathematical Organization Theory, Springer, vol. 26(2), pages 255-276, June.
    10. Li, Zhenpeng & Tang, Xijin, 2019. "Robustness of complex networks to cascading failures induced by Poisson fluctuating loads," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 536(C).
    11. William Rand & Christian Stummer, 2021. "Agent‐based modeling of new product market diffusion: an overview of strengths and criticisms," Annals of Operations Research, Springer, vol. 305(1), pages 425-447, October.
    12. Shakya, Holly B. & Fleming, Paul & Saggurti, Niranjan & Donta, Balaiah & Silverman, Jay & Raj, Anita, 2017. "Longitudinal associations of intimate partner violence attitudes and perpetration: Dyadic couples data from a randomized controlled trial in rural India," Social Science & Medicine, Elsevier, vol. 179(C), pages 97-105.
    13. Indrani Saran & Günther Fink & Margaret McConnell, 2018. "How does anonymous online peer communication affect prevention behavior? Evidence from a laboratory experiment," PLOS ONE, Public Library of Science, vol. 13(11), pages 1-16, November.
    14. Perry, Brea L. & Ciciurkaite, Gabriele, 2019. "Contributions of personality to social influence: Contingent associations between social network body size composition and BMI," Social Science & Medicine, Elsevier, vol. 224(C), pages 1-10.
    15. Meena Mahadevan & John Ruzsilla, 2012. "Assessing the Nutritional Health Outcomes of African American Women with HIV and Substance Abuse Disorders Using a Socioecological Approach," SAGE Open, , vol. 2(3), pages 21582440124, September.
    16. Shand, Calum & Crozier, Sarah & Vassilev, Ivaylo & Penn-Newman, Daniel & Dhuria, Preeti & Cooper, Cyrus & Rogers, Anne & Baird, Janis & Vogel, Christina, 2021. "Resources in women's social networks for food shopping are more strongly associated with better dietary quality than people: A cross-sectional study," Social Science & Medicine, Elsevier, vol. 284(C).
    17. Juan Carlos Sánchez Herrera & Carolyn Dimitri, 2019. "The Role of Clustering in the Adoption of Organic Dairy: A Longitudinal Networks Analysis between 2002 and 2015," Sustainability, MDPI, vol. 11(6), pages 1-19, March.

    Corrections

    All material on this site has been provided by the respective publishers and authors. You can help correct errors and omissions. When requesting a correction, please mention this item's handle: RePEc:jas:jasssj:2020-188-2. See general information about how to correct material in RePEc.

    If you have authored this item and are not yet registered with RePEc, we encourage you to do it here. This allows to link your profile to this item. It also allows you to accept potential citations to this item that we are uncertain about.

    If CitEc recognized a bibliographic reference but did not link an item in RePEc to it, you can help with this form .

    If you know of missing items citing this one, you can help us creating those links by adding the relevant references in the same way as above, for each refering item. If you are a registered author of this item, you may also want to check the "citations" tab in your RePEc Author Service profile, as there may be some citations waiting for confirmation.

    For technical questions regarding this item, or to correct its authors, title, abstract, bibliographic or download information, contact: Francesco Renzini (email available below). General contact details of provider: .

    Please note that corrections may take a couple of weeks to filter through the various RePEc services.

    IDEAS is a RePEc service. RePEc uses bibliographic data supplied by the respective publishers.