Non-work Travel Research Articles

The gender gap in non-work travel: The relative roles of income earning potential and land use

We empirically test two hypotheses: (1) that gender differences in income earning potential play a role in the within-household division of non-work travel and (2) that compact land use development can reduce the within-household gender gap in non-work travel. Using the 2001 Southern California Household Travel Survey, we find that non-work travel patterns for men and women do not vary much by gender unless children are in the household. Households with children display a striking difference in chauffeuring trips and women bear most of the chauffeuring burden. Adjusting for sociodemographics, women in households with children take over 300% more chauffeuring trips than do men living alone. The difference in chauffeuring trips among females and males within the household, the “within-household, female–male chauffeuring gap”, is larger for households with employed males and smaller in households with employed females. The chauffeuring gap is smaller when the woman’s earning power is larger compared to the man in the same household. The chauffeuring gap is larger for households that have higher amounts of single family residential land use in the quarter-mile area around their residence, and the chauffeuring gap is larger for households that live farther than a half mile from the nearest bus stop. The magnitude of the effect of those two land use variables on the chauffeuring gap is similar to the magnitude of variables that measure within-household differences in income-earning potential or female and male employment status, suggesting that more dense land use and better transit service can help reduce disproportionate chauffeuring burdens of women.

On the effect of the built environment and preferences on non-work travel: Evidence from Japan

This study uses data from the 4th Nationwide Person Trip Survey to analyse the relation between the built environment, modal access preference at residential location and travel behaviour in Japan. By estimating random parameter count models, significant statistical associations were found between the built environment and preferences with non-work trip frequency by mode. Furthermore the effect of population density, car ownership and some access preference traits were found to be heterogeneous for some modes. Since most of the recent literature has focused largely on North-American and European cities, this study contributes to the existing body of literature by examining the role of the built environment and individual preferences on travel behaviour in the context of Japanese cities, and sheds some light on existing heterogeneity in the effects of some factors related to travel behaviour.

Re-estimating UK Appraisal Values for Non-work Travel time Savings Using Random Coefficient Logit Model

The official appraisal values of travel time savings (VTTS) for non-work trips in UK were estimated by basic discrete choice model on stated choice data collected over 20 years ago. This choice model developed by Bates and Whalen (2001) was specified to address some long-standing issues in the field of VTTS valuation including the sign and size of VTTS while allowing continuous interactions between VTTS and journey covariates. With respect to the size issue, it was found that a “tapering” function, whereby time changes are increasingly discounted, could best explain the lower unit utility observed for small time savings (STS). While this set of non-work VTTS is still being used for transport appraisal in UK, the field of discrete choice modelling has evolved significantly brought by a leap of computing power and improved simulation techniques. Notably, advanced model such as mixed multinomial logit (MMNL) has been widely used to facilitate more realistic travel behavioural modelling by explaining random taste heterogeneity across respondents, which cannot be achieved in a deterministic manner. Also, techniques in specifying such model for VTTS valuation are well established by researchers nowadays. The key objective of this research was then to apply the MMNL model and re-estimate the current UK VTTS within a random coefficient logit framework. Alongside the theoretical discussions, this paper presents a synthesis of empirical evidence to support an updated appraisal value for non-work travel time savings in UK. Some key findings from this paper include a much higher mean value for the VTTS and the significantly reduced “perception effect” for the STS. In particular, this research found that MMNL model substantially reduces the “tapering” parameter of the discounting function for STS such that the “perception effect” of the VTTS becomes minimal. This finding suggests that travel benefits due to STS should be included for transport appraisal and it challenges some appraisal frameworks for countries like Germany where VTTS are discounted or even completely ignored for STS.

Toward sustainable urban mobility: Investigating nonwork travel behavior in a sprawled Canadian city

ABSTRACTThe prevalence of urban sprawl, amplified levels of auto dependency, and nonwork travel during the afternoon peak hours have resulted in a steady increase in unsustainable patterns of travel in Canadian cities. Active and green modes of transportation along with smart growth have been promoted as a panacea. This article investigates the efficacy of such sustainable urban mobility strategies in Windsor, Ontario, using data records from a Household Travel Survey. Multinomial and mixed-logit models are developed to identify the factors influencing nonwork mode choice travel behavior. Next, the models are used in a scenario-building and simulation exercise to illustrate the benefits attained from jointly improving public transit, encouraging smart growth development, and lowering vehicle ownership. Based on the obtained results, embracing single-policy instruments is not an effective approach for reducing auto dependency in the study area. However, adopting a multidimensional policy approach that integrates land use and transportation policy instruments is proven more effective for achieving sustainable outcomes. It is recommended that the service and facilities for transit and nonmotorized modes be improved, and easier access to commercial and recreational activities be enhanced through progressive improvements to the built environment. Adoption of smart-growth strategies should be also pursued by planners and decision makers to create an environment conducive to reducing the levels of auto ownership. Such a goal is of paramount importance for sustainability because the level of auto ownership emerged as the most important policy instrument for reducing auto dependency in the study area.

Measuring Community Completeness: Jobs—Housing Balance, Accessibility, and Convenient Local Access to Nonwork Destinations

Using 2007 travel-diary data from metropolitan Chicago, I investigate what aspects of urban form contribute most to community completeness, as defined by internal tour capture for nonwork tours. I examine two distinct geographic scales: census-defined ‘places’, and synthetically constructed ‘centered communities’. Centered communities are defined as nonwork travel sheds centered upon well-defined concentrations of activity. Higher accessibility share (a new urban form measure defined in the paper) and higher mixed use both significantly predict greater community completeness, as do higher levels of residential or employment density. Furthermore, I find that mixed-use measures describe something other than simple proximity to job-based attractions; these measures also address the appropriate balance of activities necessary for a complete community. To build more-complete communities, planners need to ensure that local accessibility to a variety of destinations of interest is high relative to the regional accessibility to these same types of destinations outside the community.

WHY ARE URBAN TRAVEL TIMES SO STABLE?

ABSTRACTPersonal travel time in U.S. urban areas has been stable, clashing with the assertion that urban sprawl greatly lengthens travel. Average commute time rises by 7.7 percent with each cross‐sectional doubling of Metropolitan Statistical Area (MSA) jobs. Using the RELU‐TRAN structural computable general equilibrium model of the Chicago MSA, we simulate the equilibrium effects of a 24 percent population increase projected from 2000 to 2030 by the Chicago Metropolitan Agency for Planning. If no new road capacity is added, then congestion per mile increases. Although the urbanized land area increases by 19 percent, indicating sprawl, the vehicle miles traveled (VMT) per car‐trip decreases by 1.31 percent and the VMT per car‐trip to work decreases by 2.78 percent. Car travel time increases by only 6.25 percent and commuting time by only 4.54 percent, from 30.3 minutes in 2000 to 31.7 in 2030 or 3.4 seconds per year. We further explore the effects of new road capacity, gasoline prices, public transit speed, fuel economy gains, limits on suburban construction, and importantly, the cross‐elasticity of public transit use with respect to car times. The availability of public transportation, economizing on nonwork travel, and land use adjustments that increase job‐residence proximity keep times stable.

Activity fragmentation, ICT and travel: An exploratory Path Analysis of spatiotemporal interrelationships

This paper focuses on the interrelationships between ICT, activity fragmentation and travel behaviour. The concept of fragmentation relates to how activities are spatiotemporally reorganized, by subdividing activities into smaller components that are then performed at different times and/or locations, in connection with ICT use. The association between ICT, activity fragmentation and travel relationships remains uncharted. Based on a two-day Dutch communication-activity-travel diary different associations between ICT use, paid work spatiotemporal fragmentation indicators and frequency of travel are specified and tested with Path Analysis Modelling accounting for sociodemographic and land use factors. The results demonstrate that the interrelationships between fragmentation, ICT and travel are quite complex. ICT and fragmentation apparently have a reciprocal relationship with mobile ICT use influencing the degree of spatial fragmentation whereas the usages of sedentary ICT are influenced by the degree of temporal fragmentation. Person-ICT attributes and ICT use mediate the participation in non-work activities, and can replace work and non-work travel. Fragmentation reduces work trips but at the same time restricts non-work personal travel possibilities and can reallocate time for leisure activity and travel.

A GEV model with scale heterogeneity for investigating the role of mobility tool ownership in peak period non-work travel mode choices

The paper presents results of investigation on mode choice behaviour for peak period non-work trips (trips that are made during the peak period and are not linked to any other trips). Pure non-work trips within the peak period represent a significant portion of peak period traffic. In the case of the Greater Toronto and Hamilton Area (GTHA), the study area of this investigation, around 11 percent of peak period trips are pure non-work trips and auto driving is the dominant mode. Also more peak period non-work trips are made using the auto passenger mode than all transit modes combined. This heavy auto dependency for pure non-work trips in the peak period, when transit service is at its highest throughout the day, requires an improved understanding of such mode choice behaviour. This paper uses data from a household travel survey collected in the GTHA to investigate peak period pure non-work trip mode choice in the context of household mobility tool ownership (auto and transit pass ownership). The paper also proposes an advanced econometric modelling approach for capturing preference heterogeneity as well as scale heterogeneity (heteroskedasticity). The model involves systematic parameterization of the scale parameter of a GEV model. Empirical models highlight the superiority of the proposed model over a homoskedastic model. Empirical model also explains the influence of household mobility tool ownership on peak period pure non-work trip mode choices in terms of explaining both preference heterogeneity and scale heterogeneity.

Using a GPS Data Set to Examine the Effects of the Built Environment along Commuting Routes on Travel Outcomes

Although extensive research has investigated how the built environment near people’s homes and work places influence automobile travel behavior, little is known about how commuting routes affect travel outcomes. This article presents a methodology that addresses this question by examining the correlation between built environment along commuting routes and vehicle miles traveled (VMT) and fuel consumption for nonwork automobile travel. Using a global positioning systems (GPS) data set collected from automobile trips of 46 drivers from the southeast Michigan area over a 30-day time frame, this study identifies the actual commuting routes for all drivers and derives their fuel consumption for nonwork travel. Although statistically significant relationships are not found between route environments and nonwork VMT and fuel consumption, this study is unique in its focus on the commuting routes and in establishing a methodology for using GPS data in transportation and land-use research, and it offers suggestions for refining the modeling of travel behavior along commuting routes.

Explaining the “immigrant effect” on auto use: the influences of neighborhoods and preferences

Since immigrants will account for most urban growth in the United States for the foreseeable future, better understanding their travel patterns is a critical task for transportation and land use planners. Immigrants initially travel in personal vehicles far less than the US-born, even when controlling for demographics, but their reliance on autos increases the longer they live in the US. Cultural or habitual differences, followed by assimilation to auto use, could partly explain this pattern; and it may also be partly due to changes in locations and characteristics of home and work neighborhoods. Previous studies have rarely investigated non-work travel, and have not tested workplace land use measures, compared the relative influences of enclave and home neighborhood measures, or looked at the role of culturally-bound residential preferences or motivations for migration. This study relies on a unique and rich dataset consisting of a survey of US residents born in South Asia, Latin America, and the US, joined to spatial information in a GIS. I find that the home built environment is the most consistently influential factor in explaining the lower auto use of both recent and settled Latin American immigrants. Indian immigrants use autos less than would be expected given their home and work neighborhoods. There is little evidence that either ethnic enclaves, or cultural differences, play a role in lower auto use by immigrants. These results suggest there may be a role for neighborhood built environment policies in delaying immigrant assimilation to auto use in the US.

The impact of urban design features and qualities on walkability and health in under-construction environments: The case of Hashtgerd New Town in Iran

A number of recent studies have examined the relationship between the built environment and the health of the residents. However, to our knowledge, no studies have focused on neighborhoods that are under construction. The new town of Hashtgerd near Tehran was selected for this study because individuals have been residing in the town during the construction phase while a high percentage of the area remains vacant and undeveloped. The purpose of the study is to investigate the impact of the formal–spatial factors of such an environment on walkability and health. Because different impacts were expected for men and women, the study also included gender differences to understand how such an environment affects the walkability and health outcomes for each group. First, a cross-sectional study enabled us to collect data on the physical activity and Body-Mass Index BMI of the residents in selected clusters. In the following phase, the residents were surveyed regarding the environmental barriers to walking. These barriers were then regarded as potential urban design features, which later, were classified as the three main urban design qualities. A regression analysis was performed to reveal the impact of each barrier (urban design quality) on walkability and health. Our results demonstrated that, in this environment, continuity has the largest effect on walkability, complexity has an important effect on non-work travel, and scale attributes play a significant role in work travel. Additionally, it was concluded that this environment has a stronger influence on female residents than on male residents. Safety was the most important factor for women, whereas distance to destinations was the most important factor for men.

Does TOD Need the T?

Problem, research strategy, and findings: Transit-oriented developments (TODs) often consist of new housing near rail stations. Channeling urban growth into such developments is intended in part to reduce the climate change, pollution, and congestion caused by driving. But new housing might be expected to attract more affluent households that drive more, and rail access might have smaller effects on auto ownership and use than housing tenure and size, parking availability, and the neighborhood and subregional built environments. I surveyed households in northern New Jersey living within two miles of 10 rail stations about their housing age and type, access to off-street parking, work and non-work travel patterns, demographics, and reasons for choosing their neighborhoods. The survey data were geocoded and joined to on-street parking data from a field survey, along with neighborhood and subregional built environment measures. I analyzed how these factors were correlated with automobile ownership and use as reported in the survey. Auto ownership, commuting, and grocery trip frequency were substantially lower among households living in new housing near rail stations compared to those in new households farther away. But rail access does little to explain this fact. Housing type and tenure, local and subregional density, bus service, and particularly off- and on-street parking availability, play a much more important role. Takeaway for practice: Transportation and land use planners should broaden their efforts to develop dense, mixed-use, low-parking housing beyond rail station areas. This could be both more influential and less expensive than a development policy oriented around rail. Research support: Data collection and initial research were funded under contract with the New Jersey Department of Transportation.

Do Residents of Smart Growth Neighborhoods in Los Angeles, California, Travel “Smarter”?

With the individual trip diary from the recent 2009 National Household Travel Survey, a study was done on the effect of neighborhood-level smart growth patterns and socioeconomic diversity on commute mode choice, daily work travel mode choice, and nonwork travel mode choice for individuals living in neighborhoods in the Los Angeles, California, metropolitan statistical area. Model results consistently showed that nonauto transportation infrastructure diversity and quality were the most important aspects of smart growth patterns that affected the choice of nonauto travel modes. Moreover, housing mix in a neighborhood increased the likelihood of choosing walking and cycling for daily work trips and daily nonwork trips. The socioeconomic diversity of a neighborhood reduced the likelihood of choosing walking and cycling for daily nonwork trips. The remaining two factors—residential density and mixed use—insignificantly affected travel mode choice. Overall, people living in smart growth neighborhoods in Los Angeles do travel smarter, in that they use environmentally more sustainable (bus and train) and healthier (walking and cycling) travel modes.

Time Use Patterns, Lifestyles, and Sustainability of Nonwork Travel Behavior

ABSTRACT This article adds to the limited literature on lifestyles and travel behavior by examining the relationship between nonwork travel and five lifestyle orientations: passive leisure, socializing, family, recreation, and community. Using data from the 2003 American Time Use Survey, we estimate negative binomial models of trip frequency and Tobit models of travel time. Family-oriented lifestyle is found to have the strongest auto dependence while recreation-oriented lifestyle has the weakest. The results indicate that the uphill battle for sustainability may benefit from research that targets travel related to family activities and from policies that promote recreation-oriented lifestyle.

Nonwork Travel Behavior Changes during Temporary Freeway Closure

A 1-mi stretch of Interstate 5 in downtown Sacramento, California, was intermittently closed for reconstruction in the summer of 2008. Nonwork travel behavior changes during the reconstruction were investigated with the use of data from two contemporaneous Internet surveys. More than half of the sample of 6,362 respondents made at least one studied change during the study period, including changes of route, activity location, time of day, day of an activity, and cancellation of an activity. First, the choice to make any nonwork travel change was modeled with binary probit (the any change model). Respondents were more likely to make nonwork travel changes when traffic conditions were worse than usual and less likely to do so when conditions were much better than usual. Women were more likely to make changes than men were. Those travelers who were not aware of any of the travel demand management measures designed to mitigate the impacts of the reconstruction were less likely to make nonwork changes. Next, the five individual nonwork changes were simultaneously modeled with multivariate probit. Again, women were more likely to make the individual changes studied (except route changes). The impacts of traffic conditions and commute characteristics were consistent with those in the any change model. Unobserved characteristics associated with the two temporal changes (day and time) were highly correlated, as were those associated with the two spatial changes (location and route). Unobserved influences on location, day, and time changes were highly correlated with those affecting activity cancellation.

Household Excess Travel and Neighbourhood Characteristics

This study proposes an alternative approach to estimate excess travel using activity diaries, extending it to non-work travel and capturing interhousehold variation. Central to this approach is a residential relocation exercise that helps to decompose the amount of travel by a household into two types of travel: required and excess travel. An empirical demonstration of the approach in North Carolina shows that on average 30 per cent of households’ travel in the study area is in excess. Furthermore, lower levels of required and excess travel are found among households living in neighbourhoods with more compact development patterns, suggesting that households in such neighbourhoods are able to concentrate daily destinations in relatively smaller geographical areas and achieve better spatial co-ordination between residential and activity locations. Results also indicate that households make trade-offs between travel efficiency and neighbourhood amenities such as security and school quality, suggesting the importance of social dimensions in addressing transport problems.

Residential Choice, the Built Environment, and Nonwork Travel: Evidence Using New Data and Methods

Residents of dense, mixed-use, transit-accessible neighborhoods use autos less. Recent studies have suggested that this relationship is partly because transit-preferring and walk-preferring households seek and find such neighborhoods. If this is so, and if the number of such households is small, policies to alter the built environment may not influence auto use very much. I argue that many of these studies are inconclusive on methodological grounds, and that more research is needed. A purpose-designed survey of households in two urban regions in California is investigated, with the aid of a new methodological approach. I find that most surveyed households explicitly consider travel access of some kind when choosing a neighborhood, but that this process of residential self-selection does not bias estimates of the effects of the built environment very much. To the extent that it does exert an influence, the bias results both in underestimates and overestimates of the effects of the built environment, contrary to previous research. The analysis not only implies a need for deregulatory approaches to land-use and transportation planning, but also suggests that there may be value in market interventions such as subsidies and new prescriptive regulations.

The relationship between the built environment and nonwork travel: A case study of Northern California

Many studies have found that residents living in suburban neighborhoods drive more and walk less than their counterparts in traditional neighborhoods. This evidence supports the advocacy of smart growth strategies to alter individuals’ travel behavior. However, the observed differences in travel behavior may be more of a residential choice than a travel choice. Applying the seemingly unrelated regression approach to a sample from Northern California, we explored the relationship between the residential environment and nonwork travel frequencies by auto, transit, and walk/bicycle modes, controlling for residential self-selection. We found that residential preferences and travel attitudes (self-selection) significantly influenced tripmaking by all three modes, and also that neighborhood characteristics (the built environment and its perception) retained a separate influence on behavior after controlling for self-selection. Both preferences/attitudes and the built environment itself played a more prominent role in explaining the variation in non-motorized travel than for auto and transit travel. Taken together, our results suggest that if cities use land use policies to offer options to drive less and use transit and non-motorized modes more, many residents will tend to do so.

Deconstructing development density: Quality, quantity and price effects on household non-work travel

Smart growth and transit-oriented development proponents advocate increasing the density of new land development and infill redevelopment. This is partly in order to reduce auto use, by reducing distances between trip origins and destinations, creating a more enjoyable walking environment, slowing down road travel, and increasing the market for transit. But research investigating how development density influences household travel has typically been inadequate to account for this complex set of hypotheses: it has used theoretically unjustified measures, has not accounted for spatial scale very well, and has not investigated potentially important combinations of measures. Using data from a survey of metropolitan households in California, measures of development density corresponding to the main hypotheses about how density affects travel—activity density affecting distance traveled, network load density affecting the speed of auto travel, and built form density affecting the quality of walking—are tested as independent variables in models of auto trip speed and individual non-work travel. Residential network load density is highly negatively correlated with the speed of driving, and is also highly correlated with non-work travel, both singly and in combination with other measures. Activity density and built form density are not as significantly related, on their own. These results suggest that denser development will not influence travel very much unless road level-of-service standards and parking requirements are reduced or eliminated.

Is non-work travel excessive?

This paper examines the potential and limitations of extending the excess commuting framework and its associated methods to the analysis of non-work travel. We identify several substantive considerations that differentiate work from non-work travel and point out how these issues impact the broader applicability of the excess commuting framework. The idea that people might optimize their behavior has had a long standing prominence as an applied and operational assumption, in that the classical central place models began with a “nearest” center assumption, though subsequent refinements in spatial interaction theory have allowed a much richer set of analyses. This paper touches on these concepts with reference to activity analysis, optimal multi-purpose tours, school bus travel and district design, and the notion of quasi-constrained behavior in Alonso’s theory of movement.