A brief nudge or education intervention delivered online can increase willingness to order a beef-mushroom burger

Increasing the consumption of plant-forward meals, such as beef-mushroom burgers, is a promising avenue for improving environmental sustainability. In the present research, we explored the effectiveness of a brief nudge or education intervention designed to reduce willingness to order an all-beef burger in favor of a beef-mushroom burger. For the nudge intervention the beef-mushroom burger was set as the default menu item, whereas for the education intervention the link between beef consumption and climate change was explained. In the control condition neither were included. Participants (N = 562) completed measures of social dominance orientation (SDO), conservatism, cognitive rationalization of meat-eating, beef consumption, liking beef, and liking mushrooms, in a randomized order. Participants were then randomly assigned to the nudge (n = 189), education (n = 187), or control (n = 186) condition, after which they reported their willingness to order an all-beef (vs. beef-mushroom) burger. Results revealed that, after accounting for liking mushrooms, the nudge (vs. control) condition and the education (vs. control) condition both significantly decreased willingness to order the all-beef (vs. beef-mushroom) burger. SDO, conservatism, cognitive rationalization of meat-eating, beef consumption, or liking beef did not moderate the effectiveness of the interventions. In other words, nudge and education interventions increased willingness to order beef-mushroom burgers regardless of right-wing ideology or meat-eating attitudes or behaviors. Implications and recommendations are discussed.     

Nudging consumers for relevant data using Free JAR profiling: An application to product development

Nudging is nowadays often used in order to influence people’s behaviours. However, we are convinced that nudging can also influence people’s speeches. In a product development context, consumers are more and more integrated in the process: how integrate them in the most efficient way? Whereas formatted measures can be easily analysed but are far from the consumers, measures that seem to be closer to the consumers are often very difficult to analyse. A trade-off has to be found, in order to get data that are, at the same time, as close as possible to consumers’ mind and relevant for the ones who develop new products. In this context, we proposed a new strategy, based on the nudge theory, called “Free JAR Profiling”. Its first step invites consumers to classify products into 3 hedonic categories. This classification impact consumers’ speeches in a soft way as it places consumers in a hedonic state of mind and allows them to easily structure their thoughts toward product improvement keys. The second step invites consumers to assess the products according to their own vocabulary, but with a constraint on how they give their opinion, based on a JAR scale. This strategy allows to have access to oriented and structured data, which mix the consumer spontaneity strength and the R&D approach of JAR scales. The added-value and the relevance of these nudged data can be checked, and a Sentiment Mapping can be performed as a results representation.     

Can Interface Cues Nudge Modeling of Food Consumption? Experiments on a Food‐Ordering Website

Following the nudging perspective, this research investigates how technology interface could cue heuristics that influence decisions. A field study showed that interface cues on a food‐ordering website signaling the amount of food other users consume could trigger an anchoring heuristic and induce individuals to model that amount when deciding their own consumption volume. A laboratory experiment further showed that the anchoring cue tends to induce the modeling behavior of individuals without them being aware of its influence, and such an influence was especially pronounced when resources for cognitive deliberation were limited. Altogether, this research suggests that interface cues could function as nudges and influence decisions at a relatively automatic level. Implications for technology design and intervention are discussed.