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Intentions to engage in a meat-reduced diet: an application of the integrative model of behavioural prediction

The consumption of meat and meat products has been cited as the most critical area to be addressed if we are to meet a sustainable future diet, regarding the impact on climate change and health. The numerous sustainability concerns that have been raised have stimulated calls to reduce the quantity of meat people in general eat, and have created an on-going global debate among policymakers, academics and practitioners. This research makes use of the Integrative Model of Behavioural Prediction (IMBP) in order to isolate the key determinants of what drives the intentions of middle to upper-income South Africans to engage in a meat-reduced diet (MRD). A two-phase methodology was utilised, by firstly conducting an elicitation study to identify the salient beliefs present in the population, and secondly by conducting a population survey to quantify the cognitive foundation of this behaviour. The empirical results showed that the areas of cognition which most strongly predict whether one intends to engage in an MRD were instrumental attitude, experiential attitude and injunctive norms. This study makes three primary contributions. Firstly, a theoretical contribution, through providing insight into how behavioural themes and beliefs materialise into changes in meat-consumption. Secondly, marketing practitioners can benefit from the insight offered by IMBP, which is valuable as it helps to identify what behavioural shift is required to promote MRDs. Lastly, this study contributes to the methodology utilised when applying the IMBP by applying the model to dietary behaviour, which has received comparatively less attention in the past.

Identiferoai:union.ndltd.org:netd.ac.za/oai:union.ndltd.org:uct/oai:localhost:11427/31014
Date29 January 2020
CreatorsRansome, Kristin
ContributorsLappeman, James
PublisherFaculty of Commerce, School of Management Studies
Source SetsSouth African National ETD Portal
LanguageEnglish
Detected LanguageEnglish
TypeMaster Thesis, Masters, MBusSci
Formatapplication/pdf

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