In recent years, the food industry witnessed a growing interest in meat analogues and plant-based meat (PBM), which aim to mimic traditional meat in terms of taste, texture, andappearance. While it’s clear that these new products target vegetarian and vegan consumers, PBMalso offers an alternative for those concerned with health and ethical considerations, due to itspotentially lower environmental impact in terms of emissions, water and land use compared toconventional meat.Despite the increasing market presence, PBM remains a niche product, with several aspectslimiting its broader adoption. These include higher prices, limited availability in stores, skepticismabout its resemblance to real meat, and a phenomenon known as food neophobia (Barrena andSánchez, 2013). Understanding the factors influencing PBM purchase decisions is thereforeessential for companies willing to develop effective strategies.In this work, we contribute to the literature on PBM consumer behavior conducting an onlinesurvey on a sample of mainly Italian consumers (n=988). We analyzed the data using Bayesiannetworks (BNs), a class of probabilistic graphical models identifying significant relationshipsamong variables representing the system under study. A BN is able to represent a set of variablesand their conditional dependencies via a directed acyclic graph: by utilizing BN, we, hence, aim touncover potential relationships among factors representing the relevant constructs of the literature explaining PBM purchase.
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