Assessing Label Frames and Emotional Primes in the Context of Animal Rearing—Response of an Explorative fNIRS Study

Abstract

Against the background of rising societal interest for sustainable food and nutrition choices, food labels have gained importance in providing important information to consumers. However, little is known about how the differences between quality frames in labels are evaluated and how priming might serve as an anchor for label perception. This study aims to observe the neural reaction of this in the context of differently framed food labels for products of animal origin, claiming the presence or absence of an additional quality aspect and under the impulse of emotional priming. In an explorative setup, we measured the neural prefrontal cortex activity of 26 participants with the neuroimaging technology fNIRS. An idyllic prime and a prime related to a label claiming an additional product quality led to increased neural activity in the OFC and dlPFC. Shedding light on what elements are of importance to identify products that meet consumers’ requirements in terms of quality aspects, this could indicate that the prime stressed the meaning of the label. This strengthens the argument to positively phrase and anchor frames regarding quality attributions as opposed to negative declarations. It further demonstrates the ability of fNIRS to capture processing through labels and primes in the context of consumer behavior.

A Bibliometric Analysis of Consumer Neuroscience towards Sustainable Consumption

“…Looking at green branding with the use of EEG technology, it was found that theta activation was significantly higher in pro-environmental consumers than in those who were not [ 75 ]. Using fNIRS technology, Mehlhose and Risius revealed that products with organic labels attached caused increased activity in the PFC compared to products without these labels [ 76 ]. Herbes et al found that the pricing of green electricity was predicted by neural activation metrics such as ERPs, and that WTP for green electricity was found to be approximately 15% higher than for non-green electricity [ 77 ].…”

“…In summary, this review provides the following insights into neuroscience application towards sustainable consumption: First, fNIRS technology, in addition to traditional EEG and fMRI technologies, has strong potential in discriminating whether consumer may prefer eco-labeled products, due to its advantages in allowing trials to immerse participants in a real consumption scenario as well as it also being less costly and more portable than fMRI [ 76 ]. Second, data analysis to neural signals through machine learning or deep learning techniques may be valuable to predict sales for eco-labeled products [ 86 ].…”