Abstract
PurposeIn 2020, mechanisms to limit the chain of transmission of coronavirus disease 2019 (COVID-19) in Australia led to widespread restrictions on population mobility and business operations. Such conditions provide a natural experiment that may help to provide insights into consumer behaviour and future trends in food consumption. The overall objective of this study is to explore the possible impacts of COVID-19 on meat consumption patterns in Australia, both in the short and medium term, and to explore whether there have been impacts on the underlying drivers for consumption.Design/methodology/approachThe research reported in this paper analyses the impacts of COVID-19 on meat and seafood consumption in Australia, drawing on a national random survey of 1,200 participants in June 2020. Survey data on past and current consumption rates are compared to respondent estimates of their future consumption behaviour, and ordered probit models are used to identify whether consumption changes can be explained by socio-demographic, attitudinal or economic factors.FindingsTwo potential scenarios were evaluated to explore future consumption trends. The first “acceleration” scenario is that the restrictions would encourage people to speed up existing declines in meat consumption, perhaps taking more account of credence factors such as health, animal welfare and environmental issues. The second “transformation” scenario is that people will change consumption patterns, perhaps moving more towards home-cooked meals and increased consumption. Slightly stronger support was found for the transformation scenario, indicating that consumption rates for most meats and seafood will be stable or increase over the next five years.Originality/valueThis study capitalises on changed social and economic settings generated by COVID-19 to test the effects on consumption of meat (chicken, beef, pork, lamb) and seafood at a national level. Ordered probit models are applied to evaluate participant data on their future intentions for meat consumption to test two scenarios, finding stronger support for the “transformative” scenario than the “accelerate” scenario.
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