Dynamic conceptual framework to investigate adoption of healthy diet through agent-based modelling

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Date
2021-02-17
Authors
Rahmani, Jamal
MirzayRazaz, Jalaledin
Kalantari, Naser
Garcia, Leandro M. T.
Shariatpanahi, Seyed Peyman
Bawadi, Hiba
Thompson, Jacqueline Y.
Ryan, Paul M.
Santos, Heitor O.
Haghighian Roudsari, Arezoo
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Emerald Publishing Ltd.
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Abstract
Purpose: The purpose of this research is to develop a dynamic conceptual framework depicting factors related to the adoption of a healthy diet, which will underpin the development of an agent-based model (ABM) to uncover the dynamic interplay between these factors. Design/methodology/approach: The conceptual framework was developed in three steps using available empirical data from a semi-structured in-depth interview qualitative study, comprehensive systematic literature searches, existing theories and models and expert opinions from across the world. Findings: The conceptual framework explicitly presents intention as the key determinant of the tendency to adopt a healthy diet. Intention is determined by demographic, psychological and behavioural factors and individual dietary mindset factors and dynamically affected by social environment and the person's past behaviour. The relationship between intention and behaviour is dynamically moderated by perceived control factors (price and accessibility of healthy food and time). Originality/value: The conceptual framework developed in this study is well supported by evidence and experts' opinions. This conceptual framework will be used to design the ABM of this study, and it can be used in future investigations on the tendency to adopt healthy diet and food choices.
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Keywords
Agent-based model , Conceptual framework , Food choices , Healthy diet
Citation
Rahmani, J., Mirzay Razaz, J., Kalantari, N., Garcia, L. M. T., Shariatpanahi, S. P., Bawadi, H., Thompson, J. Y., Ryan, P. M., Santos, H. O. and Haghighian Roudsari, A. (2021) 'Dynamic conceptual framework to investigate adoption of healthy diet through agent-based modelling', British Food Journal, 123(8), pp. 2743-2755. doi: 10.1108/BFJ-09-2020-0828
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