*2.2. Data Collection*

The data were collected using a softGIS method, in which conventional survey questions, such as multiple choice and scaled questions, were combined with an interactive map [52,56]. The map allowed respondents to mark visited locations and answer questions pertaining to these locations. Thus, it allowed for an accurate way of measuring travel distances, frequencies, and associated emissions using geographical information systems (GIS). The survey is presented in Appendix A, in Table A1. It was targeted to individuals aged 25 to 40 years residing in the HMA municipalities of Helsinki, Vantaa, Kauniainen, and Espoo. This relatively narrow age range was chosen to minimize the effect of life course variables and generational differences. People in this age group are usually employed, are independent from their parents, and have grown up in a globalized world, with good access to information and communication technologies [15]. A random sample of 5000 individuals from the target group was drawn from the Population Register Center of Finland. Two rounds of personal letter invitations were sent to the sampled individuals in August and September 2016. After deducting incomplete responses, the response rate was 16.82% with 841 responses out of the 5000 individuals invited (see [15] for more details). The geographic distribution of the study participants' residences was similar to that of the target population: Pearson's r calculated in a 1 km hexagon grid equals 0.81, which was deemed satisfactory and close to that in other related studies [57]. The sample over-represented people with higher education (70% compared to 46% in the HMA population aged 25 to 40) and women (58% to 50%). However, as the aim of the analysis was not to estimate descriptive statistics of the population, but to estimate correlations, no weights were used in the analyses [58]. The dataset included socio-demographic variables, locations visited every day, behaviors, attitudes, values, consumption

figures and background information, travel distances, estimated GHG emissions from that travel, and residential coordinates categorized into urban zones.
