(M)eat more plants: How category dimensions and inferences shape consumer acceptance of plant-based proteins

Abstract

A dietary shift to more plant-based and less animal-derived proteins is needed to counter environmental, public health, and animal welfare problems. Although many consumers find this important, consumers do not regularly consume plant-based proteins. Plant-based proteins are often perceived as one overarching category by consumers. We investigate a wider variety of relevant dimensions on which plant-based proteins might differ (e.g., the extent to which plant-based proteins mimic meat and dairy), which in turn might result in different consumer associations. We conducted a representative survey among Dutch consumers (N = 1002). Using structural equation modelling (SEM), we show that consumers categorise plant-based proteins (i.e., non-analogues, semi-analogues, analogues, and hybrids) along several predefined dimensions (analogy, processing, novelty, origin), and these dimensions predict acceptance through inferences (price, sensory appeal, convenience, familiarity, sustainability, health). This study demonstrates that (new) food alternatives are not one group but can be cross-categorised into multiple (sub)categories. Subcategories result in inferences that can sometimes be conflicting or even paradoxical, shaping consumer acceptance of plant-based proteins. By shedding light on how plant-based proteins are categorised and how this subsequently leads to common (mis)perceptions about certain product categories, we give directions for targeted interventions.