The measurement of social and psychological phenomena has been advanced by recent progress in the fields of behavioural economics and hedonic psychology. In addition, the increased interest in understanding how individuals perceive their own quality of life, has led to investigating the relations between various macro and individual level variables, generically subsumed as happiness. For many “happiness is considered to be an ultimate goal in life” and it plays an important role in the way people perceive the overall society they live in. Therefore, social scientists and behavioural economists are now stressing the importance of well-being measures, related to people’s evaluations of their quality of life in addition to economic indicators. In the transport sector, project evaluation is mainly based on cost–benefit analyses using economic indicators. However, any provided transportation project/service impacts the quality of the travel experience, the well-being of travellers and their travel behaviour. Competitiveness of modes may be also affected by the promotion of derived or experienced travellers’ well-being. Thus, existing behavioural travel choice models should be enhanced with regards to their behavioural validity incorporating the impacts of travelling happiness/ satisfaction. This study aims to understand and model the impact of stated (anticipated) happiness in the decision choice between a private transport mode—car, and a public transport mode—metro.

Access to food products is essential to sustain life. In this paper, we discuss the differences concerning accessibility levels to food retailers among potential consumers in Belo Horizonte, Brazil. The goal was to characterize spatial mismatches regarding opportunities to access food and identify suitable areas for sustainable last food mile solutions, such as non-motorized home delivery and purchase trips. For this, we have spatially related: (i) the population concentration; (ii) the income of households and (iii) accessibility measures considering both the spatial structure of food retailers and the distance between households and stores, considering the food last mile. We have then used spatial statistics (Global Moran’s I index, average nearest neighborhood analysis) and spatial analyses (overlay and processing) to determine the spatial pattern and the relation of the variables population, income, and accessibility to food retailers. We have considered the cumulative-opportunity measure, which is an indicator of the number of opportunities that can be reached within a time threshold. There is great spatial differentiation regarding the accessibility levels of food retailers and the results can be considered to support the development of policy and land use regulation that can stimulate non-motorized and collaborative delivery as an effective last-mile solution.