Combining text mining of social media data and conjoint approach to investigate consumer choices on organic food

Abstract

The growing interest in organic food is driven by consumer concerns about the impact of conventional agricultural practices on human health, and environment. It is crucial to understand the factors that influence consumer preference of organic food. Consumer preferences for organic food has been largely investigated using traditional methods which have limitations in terms of data validity, reliability, time, and cost. This study used social media data to investigate main factors influencing consumer perceptions and preferences of organic food using X’s API. The data were analysed by text mining, and topic modelling.The results reveal that organic production, sustainability, origin, shelf-life, and price are the five most important factors that influence consumers’ choices for organic food. Organic milk was used as the representative organic food product with attributes and levels established from the social media data analysis. A conjoint analysis was used with a sample of Vietnamese consumers. Sustainability is the most important attribute affecting organic consumer food choices followed by organic production, price, shelf-life, and origin. Segmentation analysis identified two clusters of consumers: in cluster 1 sustainability is the most importance attribute while in cluster 2 organic production is the most importance one.In conclusion, this study underscored the potential of social media data as a valuable source for understanding consumer behaviour and preferences in the context of organic food consumption. In addition, this study emphasized the significance of sustainability as a critical attribute in consumer decision-making with lower environmental impact influencing consumers’ likelihood to purchase organic food products.