Please use this identifier to cite or link to this item: http://hdl.handle.net/1893/36073
Appears in Collections:Faculty of Social Sciences Journal Articles
Peer Review Status: Refereed
Title: How can agent-based modelling provide new insights into the impact of minimum unit pricing in Scotland?
Author(s): Boyd, Jennifer
Holmes, John
Gibbs, | Naomi
Buckley, Charlotte
Purshouse, Robin
Meier, Petra
Contact Email: jennifer.boyd1@stir.ac.uk
Keywords: agent-based modelling, alcohol consumption, alcohol harm, minimum unit pricing
Issue Date: 5-Jun-2024
Date Deposited: 6-Jun-2024
Abstract: In recent years we have gained insight into the impact of minimum unit pricing (MUP)-a legal floor price below which a given volume of alcohol cannot be sold-on population-level reductions in alcohol sales, consumption and harm. However, several questions remain unanswered including how individual-level purchasing changes impact the local economy (e.g., balance between on-licence and off-licence outlets), lead to long-term population-level trends (e.g., youth drinking) and social harms (e.g., violence). Agent-based modelling captures heterogeneity, emergence, feedback loops and adaptive and dynamic features, which provides an opportunity to understand the nuanced effects of MUP. Agent-based models (ABM) simulate heterogeneous agents (e.g., individuals, organisations) often situated in space and time that interact with other agents and/or with their environment, allowing us to identify the mechanisms underlying social phenomena. ABMs are particularly useful for theory development, and testing and simulating the impacts of policies and interventions. We illustrate how ABMs could be applied to generate novel insights and provide best estimates of social network effects, and changes in purchasing behaviour and social harms, due to the implementation of MUP. ABMs like other modelling approaches can simulate alternative implementations of MUP (e.g., policy intensity [£0.50, £0.60] or spatial scales [local, national]) but can also provide an understanding of the potential impact of MUP on different population groups (e.g., alcohol exposure of young people who are not yet drinking). Using ABMs to understand the impact of MUP would provide new insights to complement those from traditional epidemiological and other modelling methods.
DOI Link: 10.1111/dar.13880
Rights: This is an open access article under the terms of the Creative Commons Attribution License, which permits use, distribution and reproduction in any medium, provided the original work is properly cited.© 2024 The Author(s).
Notes: Funding information Chief Scientist Office, Grant/Award Number: SPHSU20; Medical Research Council, Grant/Award Number: MC_UU_00022/5.
Licence URL(s): https://creativecommons.org/licenses/publicdomain

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