Purpose: Spain decided to implement NutriScore with the objective of helping consumers to choose healthier foods. NutriScore is a summary indicator interpretative nutritional labelling. This study aims to verify whether the coexistence with other interpretative labelling may influence NutriScore effectiveness.Design/methodology/approach: A questionnaire was used to analyse two different brands in the same category; one of them ranked with a “B” NutriScore rating and the other with a “D” NutriScore rating. The product packaging was shown in four different ways: without indications, with nutrient-specific labels, with summary indicators (NutriScore) and with both interpretative indicators. Having positive and negative evaluations of NutriScore allowed us to assess its impact. Structural equation modelling (SEM), Student t-test and F-test were employed with a sample of 301 questionnaires.Findings: The different formats of the interpretative labels did not moderate the relationship between perceived healthiness and purchase intention. When a food product is given positive evaluation from NutriScore, nutrient-specific interpretative labelling reinforces the effect of NutriScore. When a food product is given negative evaluation from NutriScore, nutrient specific interpretative labelling cancels the effect of NutriScore on perceived healthiness and purchase intention.Originality/value: Previous studies have analysed the interaction between NutriScore and nutrient-specific interpretative labels, but they attribute a negative message to the product (warning labels). This study was aimed at analysing the interaction between NutriScore and summary indicators nutrient specific with positive message about the nutritional quality of the food item.

The growing concentration of the population in urban areas presents great challenges for sustainability. Within this process, mobility emerges as one of the main generators of externalities that hinder the achievement of the Sustainable Development Goals. The transition of cities towards innovations in sustainable mobility requires progress in different dimensions, whose interaction requires research. Likewise, it is necessary to establish whether the experiences developed between cities with different contexts can be extrapolated. Therefore, the purpose of this study was to identify how the conditions that determine a city’s readiness to implement urban mobility innovations could be combined. For this, qualitative comparative analysis was applied to a model developed using the multi-level perspective, analyzing 60 cities from different geographical areas and with a different gross domestic product per capita. The R package Set Methods was used. The explanation of the readiness of cities to implement mobility innovations is different to the explanation of the readiness negation. While readiness is explained by two solutions, in which only regime elements appear, the negation of readiness is explained by five possible solutions, showing the interaction between the landscape and regimen elements and enacting the negation of innovations as a necessary condition. The cluster analysis shows us that the results can be extrapolated between cities with different contexts.