Investigating the temporal changes in the relationships between time spent on the internet and non-mandatory activity-travel time use

The amount of time we spend online has been increasing dramatically, influencing our daily travel and activity patterns. However, empirical studies on changes in the extent to which the amount of time spent online are related to changes in our activity and travel patterns are scarce, mainly due to a lack of available longitudinal or quasi-longitudinal data. This paper explores how the relationships between the time spent using the Internet, and the time spent on non-mandatory maintenance and leisure activities, have evolved over a decade. Maintenance activities include out-of-home activities such as shopping, banking, and doctor visits, while leisure activities include entertainment activities, visiting friends, sporting activities, and so forth. Our approach uses two datasets from two major cross-sectional surveys in Scotland, i.e. the 2005/06 Scottish Household Survey (SHS) and the 2015 Integrated Multimedia City Data (iMCD) Survey, which were similarly structured and formed. The multiple discrete–continuous extreme value (MDCEV) model and difference-in-differences (DD) estimation are applied and integrated to examine how the relationships between the time spent on the Internet and travel have changed over time and the direction and magnitude of the changes. Our findings suggest that the complementary associations between Internet use and individuals’ non-mandatory activity-travel time use are diminishing over time, whereas their substitutive associations are increasing. We additionally find that such temporal changes are significant in the case of those who spent moderate to high levels of time on the Internet (5 h or more online) per week.

     

An examination of factors affecting propensities to use bicycle and pedestrian facilities in suburban locations

The US federal Congestion Mitigation and Air Quality program was created to fund transportation projects that have the potential to contribute to the attainment or maintenance of the National Ambient Air Quality Standards. This study evaluates a random sample of eight suburban bicycle and pedestrian facilities funded by the Congestion Mitigation and Air Quality Program in the Chicago metro area. Users of these facilities were randomly sampled using a “time-based” user sampling approach and surveyed in intercept mode to implement a recall-based evaluation design. A random intercept logit model was used to explain variations in the propensity to switch from single occupant vehicle use to bicycling or walking, using attributes of users and sites. The analysis shows relatively low usage levels but that substitution of motorized modes have resulted, potentially leading to improved air quality outcomes.