Department of Management

Consumers associative networks of plant-based food product communications

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Food producers respond to the current consumer trend of clean label products and reducing meat consumption by increasingly offering plant-based food products and transparent, understandable ingredient lists. However, consumer interest can be driven by various motives and food producers face the challenge of identifying the most effective motive to address. We analyze concept maps of 90 consumers who received information that positioned plant-based food products as sustainable, healthy, or with a transparent ingredient focus. To assess the applicability of text mining with a view to reducing coder bias and the duration of qualitative data analysis, we compared the results of text mining versus a human coder approach. Our results show that human coder analysis results in more detail, however the advantage of the text mining procedure is that it can run independently and analyze qualitative data more objectively. When a high degree of control and depth of analysis is necessary to satisfy the study objective, human coding might have its rewards. For the current study, both approaches draw a similar picture of the associative networks and are therefore equally suitable to satisfy the study objective. When plant-based diets are communicated solely based on the ingredient used for substituting animal-based ingredients, associative networks are less complex and associations are primarily concerned with taste. A health communication perspective results in more complex networks with a focus on other food product properties such as processing degree and nutrition. A sustainability communication also results in higher complexity, with fewer associations concerning the product properties itself, but rather with the environmental impact and the authenticity of the product. The in-depth understanding of consumers’ associations evoked by communicating different perspectives of plant-based food products can be used by practitioners in tailoring their marketing activities to the characteristics of their product offerings.

Original languageEnglish
JournalFood Quality and Preference
Pages (from-to)145-156
Number of pages12
Publication statusPublished - 2019

    Research areas

  • Concept mapping, Flexitarians, Network analysis, Potato protein, Text mining

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