Modeling dynamics in household car ownership over life courses: a latent class competing risks model

Transportation - This study presents a latent class competing risks model to examine the influence of socio-demographics and life course events on car transaction behaviour. The types of car...     

Representing and estimating interactions between activities in a need-based model of activity generation

Although several activity-based models made the transition to practice in recent years, modeling dynamic activity generation and especially, the mechanisms underlying activity generation are not well incorporated in the current activity-based models. For instance, current models assume that activities are independent, but to the extent that different activities fulfill the same underlying needs and act as partial substitutes, their interactions/dependencies should be taken into account. For example, recreational, leisure, and social activities tend to be partly substitutable since they satisfy a common need of relaxation, and when undertaken together with others, social needs will be satisfied as well. This paper describes the parameter estimation of a need-based activity generation model, which includes the representation of possible interaction effects between activities. A survey was carried out to collect activity data for a typical week and a specific day among a sample of individuals. The diary data contain detailed information on activity history and future planning. Estimation of the model involves a range of shopping, social, leisure, and sports activities, as dependent variables, and socioeconomic, day preference, and interaction variables, as explanatory variables. The results show that several person, household, and dwelling attributes influence activity-episode timing decisions in a longitudinal time frame and, thus, the frequency and day choice of conducting the social, leisure, and sports activities. Furthermore, interactions were found in the sense that several activities influence the need for other activities and some activities affect the utility of conducting another activity on the same day.     

The effect of location,mobility and socio-demographic factors on task and time allocation of households

This paper investigates the role of location factors in task and time allocation at the household level. It is hypothesized that, if time constraints are less binding as a result of living in an urban area or owning more cars, spouses engage more often and longer in out-of-home activities and schedule their activities more independently. The hypotheses are tested with logistic and Cox regression models of activity participation and time allocation on a data set collected in the Amsterdam–Utrecht region in the Netherlands. Results suggest that the hypotheses are supported with respect to specific household activity scheduling decisions.     

More gray hair—but for whom? Scenario-based simulations of elderly activity travel patterns in 2020

This paper reports the results of a scenario-based simulation study to explore mobility effects of an aging society in the Netherlands. Four accumulative behavioral scenario variants, embedded in an economic and demographic scenario are used to simulate possible future activity-travel patterns, using the Albatross system as the simulator. The variants account for likely differences in activity-travel behavior between elderly today and elderly in the future. Trends ongoing over the last decade in the Netherlands suggest that future elderly need to work longer, change their activity pattern with most growth occurring in the social/leisure activity category, will try to avoid morning peak hours by rescheduling their activities and may introduce more spatial diversity in terms of their residence location. Results show that these behavioral and spatial changes lead to a significant increase in travel demands as well as temporal, spatial and modal shifts in mobility patterns. We discuss possible policy implications of these predictions and evaluate the specific strength of activity-based models for studies of this kind.

Social networks,social influence and activity-travel behaviour: a review of models and empirical evidence

ABSTRACT

The study of social networks in activity-travel research has recently gained momentum because social activities and social influence were relatively poorly explained in activity-based models of travel demand. Over the last decade, many scholars have shown interest in identifying personal social networks that constitute an important source of explanation of activity-travel behaviour. This paper seeks to review two research streams: social networks and activity-travel behaviour, and social influence and travel decisions. We classify models, summarise empirical findings and discuss important issues that require further research.     

A stated choice approach to developing multi-faceted models of activity behavior

Most existing activity-based models have been developed from revealed preference data. This paper introduces an approach to developing activity-based models from stated preference data. We focus on activity behavior as a multi-facet choice process to decide where and in what sequence to conduct activities, i.e., choice of destination and choice of stop pattern. A design strategy is developed to generate choice experiments that allow the estimation of multi-facet models of activity behavior. The results of an empirical application are reported. The experience and results obtained indicate that the proposed approach does provide a stated preference alternative to the revealed preference approach in developing multi-facet models of activity behavior.     

Carsharing: the impact of system characteristics on its potential to replace private car trips and reduce car ownership

Transportation - This paper aims to explore the potential of carsharing in replacing private car trips and reducing car ownership and how this is affected by its attributes. To that affect, a...     

Modelling Complex Activity‐Travel Scheduling Decisions: Procedure for the Simultaneous Estimation of Activity Generation and Duration Functions

Abstract

Activity generation is a key factor in individual's choices of trip frequency and trip purpose. This paper describes the results of an experiment conducted to estimate functions of several temporal factors on individuals' propensity to schedule a given activity on a given day. The theory on which the experimental design is based states that the probability of scheduling an activity is a complex and continuous function of how long ago the activity was lastly performed, the duration constraints for the activity and the amount of available time in the activity schedule of the day considered. Aurora, an existing model of activity scheduling, assumes S‐shaped utility functions for the history as well as the duration functions, whereas most time‐use studies assume monotonically decreasing marginal utilities. The stated‐choice experiment involves a range of flexible activities and a large sample of individuals to measure the utility effects of a set of carefully chosen levels for the factors and tests these specific assumptions. The results suggest that the amount of discretionary time on a day has no significant impact on the scheduling decisions provided that enough time is available for the activity. The effects of other factors are as expected and show diminishing marginal utilities. We find mixed evidence for an initial phase of increasing marginal returns as assumed in an S‐shaped function.     

Changing household car ownership level and life cycle events: an action in anticipation or an action on occurrence

This paper analyzes households’ decision to change their car ownership level in response to actions/decisions regarding mobility issues and other household events. Following recent literature on the importance of critical events for mobility decisions, it focuses on the relationship between specific events (e.g. childbirth and buying an extra car), rather than trying to explain the status of car ownership from a set of stationary explanatory variables. In particular, it is hypothesized that changes in household car ownership level take place in response to stressors, resulting from changed household needs or aspirations. The study includes a broad range of events. Apart from changes in work status, employer and residential location, it analyzes demographic events such as household formation and childbirth. Also, it scrutinizes the temporal sequence in which chains of related events are most likely to occur. To this end, data from a retrospective survey that records respondents’ car ownership status, as well as residential and household situation over the past 20 years are used. A panel analysis has been carried out to disentangle typical relationships. The results suggest that strong and simultaneous relationships exist between car ownership changes and household formation and dissolution processes. Childbirth and residential relocation invoke car ownership changes. Changes are also made in anticipation of future events such as employer change and childbirth. Childbirth is associated with increasing the number of cars, whereas the effect of employer change goes the opposite way. Job change increases the probability of car ownership change in the following year.     

The effects of social networks on choice set dynamics: Results of numerical simulations using an agent-based approach

Activity-based analysis has slowly shifted gear from the analysis of daily activity patterns to the analysis and modeling of dynamic activity-travel patterns. In this paper, we address one type of dynamics: the formation and adaptation of location choice sets under influence of dyad relationships within social networks. It extends the dynamic model developed in earlier work, which simulates habitual behavior versus exploitation and exploration as a function of discrepancies between dynamic, context-dependent aspiration levels and expected outcomes. Principles of social comparison and knowledge transfer are used in modeling the impact of social networks through information exchange, adaptations of spatial choice sets and formation of common aspiration levels. We demonstrate model properties using numerical simulation with a case study of shopping activities.