Exploring the Dynamics in Travel Time Frontiers

Abstract

Understanding people's travel time expenditures and the factors contributing to such expenditures can provide valuable insights into activity travel demand under a range of policy scenarios. The role of time in activity travel behavior is therefore of great interest to researchers. While the travel time expenditure constitutes the actual time spent traveling in a day, the expenditure does not necessarily constitute the upper limit of the amount of time that people are able and willing to dedicate to travel. In this context, it may be feasible to define an unobserved travel time frontier that represents an upper bound (under usual conditions) on the amount of time that people are able to dedicate to travel. A stochastic frontier modeling approach is adopted to estimate the travel time frontier, as this is an unobserved behavioral characteristic. Models are estimated for a sample of households from 3 years of the National Household Travel Survey in the United States to explore the dynamics of the frontier over a 15-year period. The variations in frontier values—as well as trends in the ratio of expenditure to frontier values, which may be interpreted as a metric of time pressure—differ considerably across sociodemographic groups; this finding calls for the formulation of policies that consider the unique mobility needs of different market segments.

Stochastic Production Frontier Models to Explore Constraints on Household Travel Expenditures Considering Household Income Classes

“…have a larger needs of spending minimum travel time and also bigger time constraints. This result is in line with Volosin et al (2013), they found that the highest income group exhibits higher travel time expenditures than other income groups. They also further revealed that the variations in production frontier values as well as trends in the ratio of travel time expenditure to frontier values differ considerably across sociodemographic groups.…”

“…Therefore, a modeling approach is adopted to estimate HTEF based on inequality and non-negative terms. To ensure positive predictions due to the highly skewed nature of the HTE distribution, a log transformation is normally applied (see Banarjee et al, 2007;Volosin et al, 2013).…”

Understanding Household's Travel Costs Budget Frontier in Banda Aceh, Indonesia

“…Another research by [15] investigated unseen stochastic limit and variations of individual travel time using data set from the UK National Travel Survey. Further application of the SFA on the travel time expenditure frontier done by [16], they investigated and showed differences in the frontier values and trends in the ratio of travel time expenditure to frontier values differ considerably across socio-demographic groups in the United States. However, the travel costs expenditures were considered a more crucial issue due to their direct…”

Effect of Traveler’s Nationality on Daily Travel Time Expenditure Using Zero-Inflated Negative Binomial Regression Models: Results from Belgian National Household Travel Survey

“…To enhance the success of such policies, empirical research on the relationship between ethnicity and other factors, which directly and indirectly influence travel behaviour, is critical (5,7). This relationship can be investigated by examining the ethnic variation of people's travel time expenditures and the factors contributing to such expenditures (8). The contribution of ethnic diversity in altering travel behaviour within a population is especially prominent from a social exclusion point of view that calls for the inclusion of time use analyses (9).…”

“…Regarding daily travel time expenditure, Volosin et al (8) underline that it is a key measure of travel demand and that a thorough comprehension of contributing factors can help in increasing the performance of travel demand forecasts, for instance by balancing mode choice preference and travel demand to achieve an acceptable level of service. Moreover, they expanded the notion of a travel time frontier developed by Banerjee et al (16) and concluded that the frontier values, as well as the ratio of the travel time expenditure to these frontier values differ considerably across socio-demographic groups.…”