Factors influencing consumer use of social supermarkets in the UK: A redistribution model providing low-cost surplus food

Aiden Berri*, L Toma

*Corresponding author for this work

Research output: Contribution to journalArticlepeer-review

3 Citations (Scopus)
159 Downloads (Pure)


Food poverty and food waste are prominent societal challenges in the UK. To mitigate their effects, social supermarkets (SSMs) provide high quality surplus food, usually not considered sellable in the mainstream market, to low-income consumers for substantially discounted prices. SSMs aim to supply high quality surplus food in a more dignified shopping experience and thus help lift people from food poverty while allowing customers to exercise personal choice in a supermarket setting; in many cases, they also provide ongoing support and access to additional resources. The aim of this study is to test and estimate relationships between factors that influence consumer intention to use a SSM. A conceptual model was built based on the theory of planned behaviour (TPB) and tested using cross section survey data (N = 486) and structural equation modelling (SEM). The model explained 64% of the variance in intention to use a SSM, with attitudes towards them as the strongest influence. Other influences were price consciousness; knowledge of SSMs, foodbanks or other forms of food assistance programmes (FAP); past experience of food insecurity; perceived risks associated with SSM use; perceptions of consumer normalcy, and perceptions of food quality and safety. This study is, to the best of our knowledge, the first to analyse consumers’ perceptions of SSMs. The findings are relevant for food waste reduction policies as they indicate factors potentially influencing the use of an emerging avenue for food surplus.
Original languageEnglish
Article number100133
JournalCleaner and Responsible Consumption
Early online date27 Jul 2023
Publication statusPrint publication - Sept 2023


  • Consumer behaviour
  • Food waste
  • Social supermarkets
  • Structural equation modelling


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