Evaluating Effects Of Travel Demand Management In A Medium Sized Urban Area

"This research examines the use of individualized marketing as a transportation demand management (TDM) strategy, using the City of Portland's SmartTrips program. This research project has two specific aims: (1) to evaluate whether the benefits of these individualized marketing programs continue to at least one year after the project ends; and (2) to examine whether the theory of planned behavior (TPB) can help explain the behavior changes identified. Surveys of residents conducted one or two years after the original program found that the share of daily trips made driving alone, walking, and bicycling were comparable to that found in the previous follow-up surveys, still significantly lower (for driving alone) or higher (for walking and bicycling) than the pre-surveys. This may indicate that the SmartTrips program was effective at changing behavior for a longer time period than previously measured. The theory of planned behavior (TPB) models were effective at explaining travel behavior. The models showed that attitudes, social norms, and perceived behavioral control explain a large share (45-55%) of the variance in travel behavior. The relative influence of each component of the model differed some by mode. The findings support previous research that individualized marketing programs can be effective at changing people's travel behavior. The findings indicate that the benefits of the programs may extend beyond one year and up to at least two years. However, the research also found that the programs may not be as effective in environments that are less conducive to walking, bicycling, and transit. The research also found that attitudes, norms, and perceptions play a large role in travel decisions. To be most effective, individualized marketing programs need to influence these factors, though efforts that focus on social norms to influence travel behavior may be less effective than those that include attitudinal and behavioral control components. Sensitivity to regional characteristics and the specific travel mode that is the target of interest is also warranted"--Technical report documentation page.

This title was first published in 2000: Describes policy innovations in transportation system management, planning and operations in the US that explicitly address interactions between transportation demands and travel behaviour in a mixed economy. The author shows how travel demand and management programmes function in the context of transportation supply and demand, investment, technology, pricing, management and marketing policies and procedures, with examples of voluntary, market-based and regulatory approaches to transportation and activity system management and institutional change. The author describes a variety of evaluation methods and models designed specifically for TDM programmes, and how these can be used to better inform decision-makers and other stockholders in the process of transportation policy formulation. TDM programmes have serious potential to increase the efficiency of a wide variety of transportation systems. Institutional obstacles are likely to prevent full implementation in the near future, but partial efforts are underway and likely to continue and succeed, under proper circumstances.

Research on travel behavior continues to be one of the most prominent areas in the transportation area. Planners and policymakers try to understand and manage travel behavior. Making and implementation of travel demand management (TDM) policies greatly rely on the understanding of the determinants of activity-travel patterns and travel demand. Among the activity-travel patterns, trip chaining and joint travel have received much research interest. Trip chaining is typically viewed as a home-based tour that connects multiple out-of-home activities. Joint travel is commonly defined as traveling with others. Travel demand is generally measured by trip generation and travel distances. Investigating different aspects of travel behavior helps us better understand the links between activity participation and mobility, and improves the evaluation of the transportation infrastructure investments and policies such as high occupancy vehicle (HOV) lanes and vehicle miles traveled (VMT) reduction programs. Several studies have regarded trip chaining, joint travel, trip generation, and travel distances as different dimensions of travel behavior to be examined in terms of various socio-demographics and urban form factors. However, limited work has been done to use activity-travel patterns as mediating variables and analyze how trip chaining and joint travel shape the resulting travel demand. Furthermore, relationships between travel behavior and urban form factors at out-of-home activity locations remain unclear. Based on the 2012 travel survey data from the Cleveland Metropolitan Area, this study first investigates the relationships among trip chaining, joint travel, home-based tour generation, and travel distances at three different levels: tour, individual, and household levels. Second, the influences of socio-demographics and urban form factors at tour origins and destinations on travel behavior are examined simultaneously. Lastly, while using trip chaining and joint travel as mediating variables, this study estimates the mediating effects of socio-demographics and urban form via activity-travel patterns on travel demand. The Structural Equation Modelling (SEM) approach is applied. The study reveals the existence of significant relationships between activity-travel patterns and travel demand. Trip chaining is negatively associated with joint travel. While it increases travel distances, this effects gets weakened through its indirect effect via decreased tour generation. Joint travel appears to increase tour generation but decrease the travel distances. Most socio-demographics have significant effects with expected signs on travel behavior. The analysis suggests that urban form factors at tour origins and destinations play important roles on the resulting travel demand. Some urban form factors may not have direct effects on travel demand but have significant indirect effects on tour generation or travel distances through activity-travel patterns. This research presents how activity-travel patterns shape travel demand and concludes that trip chaining and joint travel should be taken into consideration while analyzing travel demand. The findings on socio-demographics and urban form factors can be used as inputs to improve the future evaluation of transportation projects and help planners integrate land-use strategies as tools to change people’s travel behavior. This will further mitigate the negative externalities associated with our travel patterns.