Assessment of spatial transferability of an activity-based model, TASHA
Spatial transferability has been recognized as a useful validation test for travel demand models. To date, however, transferability of activity-based models has not been frequently assessed. This paper assesses the spatial transferability of an activity-based model, TASHA (Travel Activity Scheduler for Household Agents), which has been developed for the Greater Toronto Area (GTA), Canada. TASHA has been transferred to the context of the Island of Montreal, Canada using the 2003 Origin–Destination (O–D) travel survey and the 2001 Canadian Census. It generates daily schedules of activities (individual and joint) for each individual in this region. The modelled activity attributes (frequency, start time, duration and distance) from TASHA and observed attributes from the 2003 O–D travel survey are compared for five different activities (i.e. work, school, shopping, other, and return to home). At the aggregate level, TASHA provides quite reasonable outcomes (in some cases – better results than for the Toronto Area) for all four attributes for work, school and return to home activities with few exceptions (for instance, school start time). The model outcomes are also promising for shopping frequency and start times; however, TASHA provides larger differences for average shopping durations and distances. Only the forecasts for all four attributes for the ‘other’ activity type differ greatly with the observed attributes for the Montreal Island. These large differences most likely indicate the differences in behaviour between the Montreal Island and the Toronto Area. In general, we conclude that re-estimation of model parameters and the use of local activity attribute distributions (frequency, start time and duration) is a desirable step in the transfer of the TASHA model from one context to another.
The temporal effects of life events on mobility choices in the Netherlands : an analysis of the anticipation- and lagged -effects of life events on car ownership and most used mode using four waves of the Dutch Mobility Panel
The deliberation of the past and the future is an important factor in individual decision making but is generally overlooked in most behavioral models. Many studies have focused on anticipation or apprehension involved with the attributes of alternatives, but paid less attention to anticipation and lagged effects involving life events on car ownership and most frequent used mode. This thesis therefore made an attempt to narrow this research gap in terms of capturing the effects of anticipation and lagged effects of life events on car ownership and most used mode in the choice modelling framework, especially in the dynamic context. Car ownership and mode most used mode are selected in this study as dependents variables, because these two mobility choices are still underestimated in the analysis of life events. In addition, car ownership can be considered as mediating the relationship between the built environment and travel behavior and can affect trip frequency choice, and mode choice. Four waves of data (2013 - 2016) from the world’s largest ongoing mobility panel, ‘The Netherlands Mobility Panel’ (in Dutch: MobiliteitsPanel Nederland) (MPN) is used. The MPN is a state-of -the-art web based travel survey that contain panel data. Panel data was very important in this study, because it allowed the researcher to analyze the travel behavior over time of the same households/individuals and therefore measure the effects of life events. Additional built environment variables (e.g. destination accessibility and population density) were collected on postcode four level. Job accessibility by public transport, bicycle and car were also included. The MPN mobility panel contains approximately 6000 respondents in around 2500 complete households. 1273 stayer respondents (i.e. respondents who participated in all four years) with a total of 58035 trips are included in the analysis. In this thesis, joint mixed logit models of life events and car ownership, and life events and most used mode were developed and estimated to determine the temporal effects (i.e. anticipation and lagged effects of life events) on these two mobility choices. The model results showed that work-related life events, spatial family-related life event (move house), non-spatial family related life event (child birth) and a combination of a work-related life event and having a baby or move house, have anticipation and or lagged effects on car ownership and most used mode. Overall, the anticipation effects are found to be stronger and more important than the lagged effects considering the model results and the elasticities of job accessibility in the analysis. Furthermore, the variables that were influential in determining the temporal effects of the life events in this study are: distance to daycare, urbanity, job accessibility by car and by public transport, employment, number of persons in the household, travel time and mode preferences for the purpose of work and leisure activities. Lastly, the results of the models and the estimated elasticities and probabilities were able to reveal the presence of the temporal effects of the life events and mobility choices. The use of the joint estimation of the life events and mobility choices have proven to be useful in this study, and the output of the research can provide insight to the field of analysing behavioural impacts of life events on mobility.
The Use of Qualitative Information in Macro-Economic Policy Analysis
The majority of macro-economic policy models takes for granted that conflicts among objectives can be assessed by means of a tradeoff analysis. Such tradeoffs imply that sacrifices and benefits of various impacts of decisions can be measured on a cardinal scale, so that a conventional macro-economic utility or welfare analysis can be applied.