TTB or not TTB, that is the question: a review and analysis of the empirical literature on travel time (and money) budgets

This paper summarizes and analyses findings from more than two dozen aggregate and disaggregate studies of travel time (and sometimes money) expenditures, exploring the question of the existence of a constant travel time budget. We conclude (with prior researchers) that travel time expenditures are not constant except, perhaps, at the most aggregate level. Nevertheless, individuals’ travel time expenditures do show patterns that can be partly explained by measurable characteristics. Travel time expenditure is strongly related to individual and household characteristics (e.g., income level, gender, employment status, and car ownership), attributes of activities at the destination (e.g., activity group and activity duration), and characteristics of residential areas (e.g., density, spatial structure, and level of service). To the extent that travel time expenditures are constant at the aggregate level, the underlying mechanisms explaining that regularity are not well understood. Consequently, further research into explaining travel time and money expenditure patterns is justified.     

Explaining “peak car” with economic variables

Many western countries have seen a plateau and subsequent decrease of car travel during the 21st century. What has generated particular interest and debate is the statement that the development cannot be explained by changes in traditional explanatory factors such as GDP and fuel prices. Instead, it has been argued, the observed trends are indications of substantial changes in lifestyles, preferences and attitudes to car travel; what we are experiencing is not just a temporary plateau, but a true “peak car”. However, this study shows that the traditional variables GDP and fuel price are in fact sufficient to explain the observed trends in car traffic in all the countries included in our study: the United States, France, the United Kingdom, Sweden and (to a large extent) Australia and Germany. We argue that the importance of the fuel price increases in the early 2000s has been underappreciated in the studies that shaped the later debate. Results also indicate that GDP elasticities tend to decrease with rising GDP, and that fuel price elasticities tend to increase at high price levels and during periods of rapid price increases.     

A test of the two-mode UMOT in the Netherlands

The UMOT model, presented as an alternative to conventional travel demand models, is critically examined for its feasibility to predict vehicle distance travelled and average daily traffic in The Netherlands. Using data from the National Travel Survey (OVG) 1978 a Dutch version of UMOT is developed, and an attempt is made to validate it on historical data from the period 1960 to 1980. Some comparisons are made with results of similar work using 1976 survey data in the UK by the Transport and Road Research Laboratory.     

Understanding Travel Time Expenditures Around the World: Exploring the Notion of a Travel Time Frontier

Travel behavior researchers have been intrigued by the amount of time that people allocate to travel in a day, i.e., the daily travel time expenditure, commonly referred to as a “travel time budget”. Explorations into the notion of a travel time budget have once again resurfaced in the context of activity-based and time use research in travel behavior modeling. This paper revisits the issue by developing the notion of a travel time frontier (TTF) that is distinct from the actual travel time expenditure or budget of an individual. The TTF is defined in this paper as an intrinsic maximum amount of time that people are willing to allocate for travel. It is treated as an unobserved frontier that influences the actual travel time expenditure measured in travel surveys. Using travel survey datasets from around the world (i.e., US, Switzerland and India), this paper sheds new light on daily travel time expenditures by modeling the unobserved TTF and comparing these frontiers across international contexts. The stochastic frontier modeling methodology is employed to model the unobserved TTF as a production frontier. Separate models are estimated for commuter and non-commuter samples to recognize the differing constraints between these market segments. Comparisons across the international contexts show considerable differences in average unobserved TTF values.     

Virtual reality simulation game approach to investigate transport adaptive capacity for peak oil planning

The peak and decline of world oil production is an emerging issue for transportation and urban planners. Peak oil from an energy perspective means that there will be progressively less fuel. Our work treats changes in oil supply as a risk to transport activity systems. A virtual reality survey method, based on the sim game concept, has been developed to audit the participant’s normal weekly travel activity, and to explore participant’s travel adaptive capacity. The travel adaptive capacity assessment (TACA) Sim survey uses avatars, Google Map™, 2D scenes, interactive screens and feedback scores. Travel adaptive capacity is proposed as a measure of long-range resilience of activity systems to fuel supply decline. Mode adaptive potential is proposed as an indicator of the future demand growth for less energy intensive travel. Both adaptation indicators can be used for peak oil vulnerability assessment. A case study was conducted involving 90 participants in Christchurch New Zealand. All of the participants were students, general staff or academics at the University of Canterbury. The adaptive capacity was assessed by both simulated extreme fuel price shock and by asking, “do you have an alternative mode?” without price pressure. The travel adaptive capacity in number of kilometers was 75% under a 5-fold fuel price increase. The mode adaptive potential was 33% cycling, 21% walking and 22% bus. Academics had adaptive capacity of only 1-5% of trips by canceling or carrying out their activity from home compared to 10-18% for students.     

Elasticities of fuel and traffic demand and the direct rebound effects: An econometric estimation in the case of Norway

We estimate the elasticities of fuel and travel demand with respect to fuel prices and income in the case of Norway. Furthermore, we derive the direct rebound effects that explain the degree to which a fuel price increase is “offset” in the form of greater fuel use and/or travel due to improvements in vehicle fuel efficiency. For this purpose, we use and compare two alternative econometric approaches: the error correction model (ECM) and the dynamic model. Our initial assumption is that one should not be indifferent with respect to the approach used to derive elasticities. The data used are for the period 1980–2011. Our results indicate the following: (1) the dynamic model fits the data better than the ECM model does; (2) the estimated elasticities of fuel demand with respect to price and income are −0.26 and 0.06 in the short run and −0.36 and 0.09 in the long run. For travel demand, the respective elasticities are −0.11 and 0.06 in the short run and −0.24 and 0.13 in the long run, implying inelastic demands for fuel and travel demand; and (3) rebound effects indicate that 0.26% and 0.06% of fuel savings as a result of fuel price increase will be offset in the form of more fuel use in the short run and in the long run, respectively, if fuel efficiency increases by 1%. Our policy recommendations are that policies should not be indifferent to the methods used to derive elasticities. We contend that it is crucial to seriously consider rebound effects in policy making because basic elasticity estimates exaggerate the impact of fuel price increases.     

A utility-theory travel demand model incorporating travel budgets

A model of traveler behavior is proposed which is consistent with the possibility that travelers expend average daily amounts of time and money on travel with stable regularities both among urban areas and over time in the same area. The model is founded on economic utility theory. It is designed to forecast: (1) the amount of total travel generated by types of households, (2) the division of travel among available modes, and (3) the relationship between the amounts of time and money allocated to travel expenditures. The qualitative properties of the model are shown to be consistent with economic principles. Specific theoretical results reveal that, in the simultaneous presence of constraints on both time and money, travel budgets are not strictly constant proportions of income and time available as they are in the cases of single constraints relevant to classes of travelers to whom time is scarce compared to money, or conversely. Constant expenditure proportions are shown to be linear approximations which are subject to empirical validation. The relevant economic principle is that expenditures can be considered fixed in the short run but become flexible in the long run when utility maximization is applied to the expenditures themselves and not just to their allocation. Empirical tests of the model using data from three urban areas are positive, but additional tests are called for. The most important output of the research is deemed to be the establishment of theoretical hypotheses which can be used in continuing tests of travel budgets.     

Time use,mobility and expenditure: an innovative survey design for understanding individuals’ trade-off processes

A large amount of information is required to model the complex trade-off processes between travel activities, non-travel activities and budget assignment at the individual level. This paper describes the development of a new survey design, which incorporates components of travel surveys, time use surveys and consumer expenditure surveys in an integrated format, which is expected to deliver a richer data set allowing deeper insights into individuals’ activity and consumption patterns. The survey procedure and the incentives paid, which were necessary to obtain acceptable response rates, are also described. Results from two pilot studies using a trip-based and an activity-based diary format are presented. The paper examines to which extent the diaries have been capable of collecting the required data with high quality and response rates. The innovative “Mobility–Activity–Expenditure-Diary” is introduced and results of the main survey using this design are presented. Travel behaviour and non-travel activities were reported at high quality. Expenditures would require longer observation periods (and preferably not only telephone but also personal support in the survey process) to reduce unsystematic variations and to better capture individuals’ long term equilibrium.

     

Impact of fuel price on vehicle miles traveled (VMT): do the poor respond in the same way as the rich?

The effects of fuel price on travel demand for different income groups reveal the choices and constraints they are faced with. The first purpose of this study is to understand these underlying choices and constraints by examining the variation of fuel price elasticity of vehicle miles travelled (VMT) across income groups. On the other hand, the rebound effect—increase in VMT as a result of improvement in fuel efficiency may offset the negative effect of fuel price on VMT. The second purpose of this study is to compare the relative magnitudes of the fuel price elasticity of VMT and the rebound effect. A system of structural equations with VMT and fuel efficiency (MPG, miles per gallon) as endogenous variables is estimated for households at different income levels from 2009 National Household Travel Survey. Higher income households show greater fuel price elasticity than lower income households. Fuel price elasticities are found to be ?0.41 and ?0.35 for the two highest income groups, while an elasticity of ?0.24 for the lowest income group is identified. The rebound effect is found to be only significant for the lowest income households as 0.7. These findings suggest the potential ability of using fuel price as a tool to affect VMT. The study results also suggest possible negative consequences faced by lower income households given an increase in fuel price and call for more studies in this area.     

The impact of “free” public transport: The case of Brussels

Public transport subsidies play an important role in the present Belgian mobility policy. The introduction of “free” bus transport in Hasselt in 1997 was an important event. Later, the Flemish government in cooperation with the regional public transport company elaborated the so-called “third-payer system” for target groups. The price of public transport is not paid by the user or the provider, but partly or completely by a “third party”. In how far these measures contribute to a more sustainable mobility system has caused much debate.In the academic year 2003–2004, a “free public transport” initiative was introduced for the students of Flemish colleges and universities in Brussels. These students had the opportunity to obtain a refunded annual season ticket on Brussels public transport. Brussels was selected for the case study, because in the same city there is a group of students that benefits from the measure, and another group (students from French speaking universities and colleges) that does not. In order to examine the effects of this measure, we conducted a survey among the students to examine their present travel behaviour (number of trips, motives, modal choice …) and the changes with the travel behaviour of the previous year. In addition we compare the current travel behaviour between the students benefiting from the measure, and those who do not.     

I can’t believe your attitude: a joint estimation of best worst attitudes and electric vehicle choice

The number of conventionally fuelled motor vehicles in use is increasing worldwide despite warnings about finite fossil fuel and the detrimental impacts of burning such fuels. While electric vehicles, the subject of much research, generate far less emissions and offer the potential for power from renewable sources, they are yet to significantly penetrate the market. Tangible barriers such as price and vehicle range still exist, but consumer attitudes also drive behaviour. This paper examines attributes in a framework relatively new to transportation and energy policy; best–worst scaling. This method is widely considered an improvement over traditional methods of eliciting attitudes and beliefs, where respondents select attitudes they find best or worst from a set of attitudinal statements. To avoid potential endogeneity bias, we jointly model attitudes and choice for the first time with best–worst data. It is found that energy crisis, air quality and climate change concerns influence behaviour with respect to vehicle range and that travel behaviour change and forms of government incentives are needed influences on behaviour with respect to vehicle emissions. It is argued that correctly modelling attitudes reduces the error term of the vehicle choice model and provides policy makers with an improved lens for assessing behaviour. Additionally, the methods described within can easily be adapted to other policy scenarios.     

Auto travel fuel elasticity in a rapidly developing urban area

This paper presents results of a study conducted to quantify the effect of fuel cost increases on household auto travel in Riyadh, the rapidly developing capital of Saudi Arabia. Responses of a stratified random sample of 1648 individual households provided the data base for the analysis. The auto trip measures of shrinkage ratio, arc and log-arc elasticities were calculated for households categorized by income and family size. The elasticity measures suggested the existence of significant relationship among the factors of fuel cost, the number of daily auto trips, and family size. It was found that as fuel prices increased, the number of daily trips decreased, and that this decrease in daily trips was greater with larger family size. A step-wise multiple regression analysis with three independent variables of car ownership, family size, and daily fuel expenditures was developed. The model was fairly accurate in predicting variations in daily household travel. The regression parameter of the variable fuel cost was also used to derive demand elasticity to fuel expenditures. Elasticity measures ranged between -0.30 and -0.37.     

Uncertain socioeconomic projections used in travel demand and emissions models: could plausible errors result in air quality nonconformity?

A sensitivity analysis of plausible errors in population, employment, fuel price, and income projections is conducted using the travel demand and emissions models of the Sacramento, CA, USA, region for their transportation plan. The results of the analyses indicate that plausible error ranges for household income and fuel prices are not a significant source of uncertainty with respect to the region's travel demand and emissions projections. However, plausible errors in population and employment projections (within approximately one standard deviation) may result in the region's transportation plan not meeting the conformity test for nitrogens of oxides (NO_x) in the year 2005 (i.e., an approximately 16% probability). This outcome is also possible in the year 2015 but less likely (within approximately two standard deviations or a 2.5% probability). Errors in socioeconomic projections are only one of many sources of error in travel demand and emissions models. These results have several policy implications. First, regions like Sacramento that meet their conformity tests by a very small margin should rethink new highway investment and consider contingency transportation plans that incorporate more aggressive emissions reduction policies. Second, regional transportation planning agencies should conduct sensitivity analyses as part of their conformity analysis to make explicit significant uncertainties in the methods and to identify the probability of their transportation plan not conforming. Third, the US Environmental Protection Agency (EPA) should clarify the interpretation of “demonstrate” conformity of transportation plans; that is, specify the level of certainty that it considers a sufficient demonstration of conformity.     

Asymmetric responses of highway travel demand to changes in fuel price: An explanation via fuel price uncertainty

Previous research has examined asymmetric effects of fuel price uncertainty on energy demand. If we consider that energy demand is related to travel demand, the changes in fuel prices may have asymmetric effects on highway travel demand via fuel price uncertainty. In other words, when in general fuel price is steadily rising, the highway traffic volume decreases by a small percentage. On the other hand, the highway traffic volume increases by a large percentage when fuel prices are falling. We hypothesize that the uncertainty in fuel prices generates this kind of asymmetric effect on highway traffic volume in Korea. We use the Korean monthly fuel price and highway traffic volume data from 2001 to 2009, and define the intra-month (weekly) fuel price changes as monthly fuel price volatility which is a proxy for monthly fuel price uncertainty. We found that the direction of the change in fuel prices had asymmetric effects on highway travel demand and that the fuel price uncertainty led drivers to respond asymmetrically to the changes in fuel prices.     

Travel mental budgeting under road toll: An investigation based on user equilibrium

With the approach of introducing the conceptions of mental account and mental budgeting into the process of travelers’ route choice, we try to identify why the usages of tolled roads are often overestimated. Assuming that every traveler sets a mental account for his/her travel to keep track of their expense and keep out-of-pocket spending under control, it addresses these questions such that “How much money can I spend on the travel?” and “What if I spend too much?”. Route tolls that exceed the budget are much more unacceptable compared to those within budget due to the non-fungibility of money between different accounts. A simple network with two nodes and two routes is analyzed firstly, the analytical solutions are obtained and the optimal road tolls supporting the user equilibrium as a system optimum are also derived. The proposed model is then extended to a generalized network. The multiclass user equilibrium conditions with travel mental budgeting are formulated into an equivalent variational inequality (VI) problem and an equivalent minimization problem. Through analyses with numerical examples, it is found that the main reason that the usages of high tolled roads are often overestimated is due to the fact that travelers with low and moderate out-of-pocket travel budget perceive a much higher travel cost than their actual cost on the high tolled roads.     

Time use in travel surveys and time use surveys – Two sides of the same coin?

An in-depth understanding of travel behaviour determinants, including the relationship to non-travel activities, is the foundation for modelling and policy making. National Travel Surveys (NTS) and time use surveys (TUS) are two major data sources for travel behaviour and activity participation. The aim of this paper is to systematically compare both survey types regarding travel activities and non-travel activities. The analyses are based on the German National Travel Survey and the German National Time Use Survey from 2002.The number of trips and daily travel time for mobile respondents were computed as the main travel estimates. The number of trips per person is higher in the German TUS when changes in location without a trip are included. Location changes without a trip are consecutive non-trip activities with different locations but without a trip in-between. The daily travel time is consistently higher in the German TUS. The main reason for this difference is the 10-min interval used. Differences in travel estimates between the German TUS and NTS result from several interaction effects. Activity time in NTS is comparable with TUS for subsistence activities.Our analyses confirm that both survey types have advantages and disadvantages. TUS provide reliable travel estimates. The number of trips even seems preferable to NTS if missed trips are properly identified and considered. Daily travel times are somewhat exaggerated due to the 10-min interval. The fixed time interval is the most important limitation of TUS data. The result is that trip times in TUS do not represent actual trip times very well and should be treated with caution.We can use NTS activity data for subsistence activities between the first trip and the last trip. This can potentially benefit activity-based approaches since most activities before the first trip and after the last trip are typical home-based activities which are rarely substituted by out-of-home activities.     

Short-term impact analysis of fuel price policy change on travel demand in Malaysian cities

Abstract

Malaysia is one of the few countries in the world that provides a fuel subsidy to consumers. Due to the recent economic crisis, the Malaysian Government decided to revise its fuel subsidization policy from a fixed price subsidy to a floating price subsidy dependent on global oil demand. Recognizing that the change in fuel subsidization policy can have an impact on travel behavior, this article investigates the short-term impact of the policy change on private and public transportation in the Klang Valley region of Malaysia. Spectral analyses are performed to investigate if the policy change has an impact on private vehicle travel demand, measured in terms of road traffic, and short-term travel demand elasticity with respect to fuel price is estimated. To measure the impact on the public transportation system, the demand cross-elasticity values of rail transit and buses are also estimated. It was found that traffic flow reduces with an increase in fuel price, although elasticity and cross-elasticity values obtained are low. The article finds that there is a potential mode shift from private vehicles to rail transit with increasing fuel price. It is demonstrated that reducing fuel price subsidy can be an effective travel demand management strategy to alleviate congestion.     

A model of complex travel behavior: Part I—Theoretical development

This paper presents a policy sensitive approach to modeling travel behavior based on activity pattern analysis. A theoretical model of complex travel behavior is formulated on a recognition of a wide range of interdependencies associated with an individual's travel decisions in a constrained environment. Travel is viewed as input to a more basic process involving activity decisions. A fundamental tenet of this approach is that travel decisions are driven by the collection of activities that form an agenda for participation; the utility of any specific travel decision can be determined only within the context of the entire agenda. Based on the theoretical model of complex travel behavior, an operational system of models, STARCHILD (Simulation of Travel/Activity Responses to Complex Household Interactive Logistic Decisions), has been developed to examine the formation of household travel/activity patterns, and is presented in a companion paper (Recker et al., 1986).     

Demand management as an element of transportation policy: using carrots and sticks to influence travel behavior

This paper describes the characteristics of transportation demand management. The origin of transportation demand management (TDM) as it has evolved in the US is related to federal policy initiatives that first focused on improving the efficiency of the urban transportation system through operational improvements, and then incorporated concerns such as air quality and energy conservation into the transportation planning process. The paper then examines the effectiveness of TDM actions, and concludes that those actions most likely to increase the “price” of travel for single occupant vehicle use will be most effective. The paper identifies several strategies for improving the effectiveness of TDM actions in the context of regional transportation planning, including: incorporating TDM as part of the solutions for regional transportation planning, linking TDM to land use decisions, making the costs of travel more apparent to the user, and making TDM implementation more palatable to the general public.     

Using a stages of change approach to explore opportunities for increasing bicycle commuting

Given the potential benefits of bicycling to the environment, the economy, and public health, many U.S. cities have set ambitious goals for increasing the bicycle share of commute trips. The Transtheoretical Model of Behavior Change, which seeks to describe how positive and permanent change can be fostered in individuals, may shed light on how cities can most effectively increase bicycle commuting. We use the model’s “stages of change” framework to explore the potential for increased bicycle commuting to the UC Davis campus in Davis, California. Our analysis uses data from the 2012 to 2013 UC Davis Campus Travel Survey, an annual online survey that is randomly administered to students and employees at UC Davis. Based on their responses to questions about current commute mode and contemplation of bicycle commuting, respondents are divided into five stages of change: Pre-contemplation, Contemplation, Preparation, Action, and Maintenance. We construct a Bayesian multilevel ordinal logistic regression model to understand how differences in socio-demographic characteristics, travel attributes, and travel attitudes between individuals explain their membership in different stages of change. In addition, we use this model to explore the potential of various intervention strategies to move individuals through the stages of change toward becoming regular bicycle commuters. Our results indicate that travel attitudes matter more to progression toward regular commute bicycling than travel attributes, tentatively supporting the efficacy of “soft” policies focused on changing travel attitudes.