Telecommuting and other trips: an English case study

This paper investigates the importance of non-work travel to the growing population of telecommuters and the implications of this for sustainable travel patterns. Previous research has identified a link between increased online access to work and reduced proximity between residential and workplace locations. These studies raise concerns that as more people split their work activities between home and external workplace, whilst living in more dispersed locations, more unsustainable transport impacts will be generated, including higher vehicle mileage, car dependency, and less physical activity. This paper counters that the implications of telecommuting and other flexible working practices for sustainable travel behaviours may be more dependent upon the number and type of non-work journeys and the accessibility of amenities for these purposes rather than on the distance to the workplace for less frequent commuting journeys. Using the National Travel Survey for England, the travel behaviours of those who identify themselves not as home workers but as working from home at least once a week are compared to other working adults by measuring and modelling the number and purpose of trips within a week's travel diary, independent of distance or mode. Telecommuters record fewer commute trips, more trips for other purposes, and the marginal utility of additional non-work trips to telecommuters is greater than for many other socio-economic characteristics. Thus, addressing the accessibility of non-work destinations proactively through local planning has the potential to optimise the sustainability benefits of telecommuting.     

The indirect effect of the built environment on travel mode choice: A focus on recent movers

Many studies have demonstrated that the built environment has a strong impact on people's travel mode choice. However, the built environment also influences elements such as travel distance and car ownership, which might be the true predictors of which travel modes are chosen. In this study, we analyse the effects of changes in residential neighbourhood on changes in travel mode (for commute trips and leisure trips), both directly and indirectly through changes in car ownership, travel distances and travel attitudes. This study applies a structural equation modelling approach using quasi-longitudinal data from 1650 recently relocated residents in the city of Ghent, Belgium. Results indicate that the built environment has strong direct effects on active leisure trips and car use. However, distance (for car use) and attitudes (for active travel) were found to be important mediating variables. In sum, the effect of the built environment on travel mode choice might be more complex than commonly assumed as it partly seems mediated by travel distance and travel attitudes.     

The structure of joint leisure trips: analyzing two-person leisure trips of Dutch students

This paper investigates the spatial structure of students’ leisure trips and to what extent locational characteristics of social network partners influence decisions about their joint leisure activities and travel. To this end a survey was held among university students asking them about details of their last leisure trip made with a friend. Cluster analysis suggests that four typical leisure trip patterns can be derived. Three clusters seem to be determined by the residential locations of ego and alter. Depending on the residential distance between ego and alter, leisure trip distances are either short for ego and alter (if residential distance is very short), somewhat longer for both (if residential distance is slightly longer) or long for at least one partner (if residential distance is large). A fourth cluster includes cases with long leisure trips for both partners, independent of residential distance, representing cases where specific destinations are visited. A more detailed analysis of travel distance suggests that travel distance depends on size of the residential municipality, residential distance and objective and perceived quality of leisure facilities such as cafés, bars and restaurants. Overall, our study provides support for the idea that leisure trip decisions should be understood on the level of social network ties (i.e. ego and alter) rather than based on individual characteristics only. Also, it provides support for the idea that a focus on single ties, rather than on the structure of social networks as a whole, increases our insight in leisure trip decision making.Keywords: Social network links, Social-recreational travel, Spatial context, Students     

Linking expected mobility production to sustainable residential location planning: some evidence from Flanders

Based on a set of spatial proximity characteristics this paper develops a model that estimates for every neighbourhood in Flanders (Belgium) the amount of traffic that would be generated by an additional residential unit when socio-economic variables are held constant. The results show that residential density, land use diversity and proximity of facilities influence daily travelled distances when these variables are measured in the immediate vicinity of the residential location of the respondent (within a radius of 1 km). When aggregating these variables at a larger geographical scale, in most cases the impact proves no longer significant. Variables based on the spatial distribution of jobs, or on the global accessibility of the entire population in the study area, do not show any significant effects on the travel distance.Despite the statistical significance only a fraction of the observed variance in reported distances is explained by characteristics of spatial proximity. However, we can assume that the importance of spatial structure in the genesis of mobility patterns will increase in case the cost of transport would rise (cf. peak oil). For this reason, the application of the mapped results of the proposed model could contribute to the practice of sustainable spatial planning.     

Social inequalities in travel behaviour: trip distances in the context of residential self-selection and lifestyles

In recent years, the framework of ‘classical’ objective determinants of travel behaviour – such as transport systems, generalised travel costs, life situation and the built environment – has begun to make way for the introduction of subjective elements including attitudes, lifestyles, and location preferences. This paper presents findings from an empirical study of trip distances travelled for three purposes (work, maintenance, leisure). The study was conducted in the region of Cologne, and the analysis is based on structural equation modelling. The results indicate that, in general, neither lifestyles nor location preferences have a strong impact on trip distances, except for leisure activities: here lifestyle has the strongest impact of all variables studied. Maintenance trip distances are significantly affected by the spatial setting in which people live, indicating the relevance of the built environment for this travel segment.     

Exploring residential relocation behavior for families with workers and students; a study from Beijing,China

The effects of residential relocation on changes in travel behaviors have been studied worldwide; however, little is known about factors that influence relocation behavior in households with workers and students. This study explores the relationship between residential relocation behavior and its factors, such as the built environment, the housing price, the work commute distance, the school commute distance, and households' sociodemographic attributes, by building a structural equation model using the data collected in the Fifth Travel Survey of Beijing Inhabitants. The results show that the built environment and sociodemographic attributes have direct effects on residential relocation behavior and the housing price, work commute distance, and school commute distance have indirect effects on it. Besides, trade-offs between the housing price and the built environment and between the housing price and the home-work and home-school commute distances are found. Based on the results, a number of suggestions for the balanced development of public transportation and city land-use plans are proposed.     

The path and time efficiency of residents' trips of different purposes with different travel modes: An empirical study in Guangzhou,China

Improving residents' travel efficiency and reducing carbon emissions from travel are the key issues for sustainable development of urban transportation. This study first employed a circuity index to measure the path efficiency of residents' trips based on 2015 survey data in Guangzhou and developed a generalized additive model (GAM) to investigate the relationship between the path efficiency and travel distance for different purposes of trip and different travel modes. On this basis, it further evaluated the time efficiency of different travel modes for each trip. The results showed that there is a complex and nonlinear relationship between the path efficiency and travel distance, which differs between different purposes of trips and different travel modes. In general, trips by non-motorized transport have a lower circuity index and higher path efficiency than those by cars or public transport. Moreover, non-motorized transport is the time-efficiency optimal mode for almost half of the trips, especially for daily shopping trips. However, people prefer to choose public transport on their trips even though public transport is not the time-efficiency optimal mode for these trips. Generally, only about half of the residents chose the time-efficiency optimal mode for their trips. Those who did not choose the time-efficiency optimal mode tended to choose the modes with higher carbon-intensity. The conclusions of this study indicate that for improving travel efficiency and reducing carbon emissions from transport, more efforts should be focused on the non-motorized travel environment and developing relevant policies to encourage more walking and cycling.     

Expanding the positive utility of travel through weeklong tracking: Within-person and multi-environment variability of ideal travel time

Travel has been found to have a positive utility—often measured as a desire for non-zero travel time. Although past studies have found that desired travel time varies by trip attributes, they often focused on a single trip purpose (e.g., commute) or single time point (e.g., peak period of one day) and rarely captured variation within individuals and across multiple travel environments. To address these limitations, we employed a smartphone-based travel behavior survey of 186 users making 4397 trips in the Washington, DC, and Blacksburg, VA metropolitan areas. For each user, multiple trips were recorded and the user was asked to repeatedly report on the ideal travel time for each trip. We found that desired travel time varied across different trip environmental characteristics and purposes. Ideal travel time was longer for active travel trips, leisure trips, weekend trips, and when the user conducted activities during trips (e.g., talking, using the phone, looking at the landscape) and traveled with companions. Our study suggests the need for more realistic estimation of the value of travel time savings and the need for quantifying the effect of multitasking during travel on people's willingness to reduce travel time. Practitioners should also consider providing better urban infrastructure for pedestrians and bicyclists to fulfill their trips, as their ideal travel times closely match actual travel times.     

Residential dissonance and walking for transport

The concept of residential dissonance contextualizes the combined impact of built environment and individual travel and land-use preferences on travel behavior. A limited number of studies have explored the effect of residential dissonance specifically on walking. However, evidence from the active travel literature suggests that the environmental characteristics associated with diverse active travel modes differ to some extent. This study addresses residential dissonance in a framework specific for walking outcomes, as the applied neighborhood boundaries, residential preferences and the observed built environment were operationalized with measures related to walking for transport. SoftGIS, a public participatory GIS method allowing the mapping of frequently visited destinations was used to survey the daily walking behavior of 772 respondents aged 25–40 years living in the Helsinki metropolitan area, Finland. Ordinal logistic regression analyses were used to assess the adjusted odds of walking a high share of estimated monthly trips and travel distance. The identified residential dissonance groups were found to have significant associations with the walking outcomes. Associations between the observed neighborhood walkability and the walking outcomes varied by trip purpose, being more consistent with walking to utilitarian than to recreational destinations. Overall, the results support views on the interconnectedness of individual attitudes and the built environment in facilitating walking for transport.     

Estimating social travel demand of senior citizens in the Netherlands

Like many other countries, the Netherlands is experiencing a sharp rise in the ageing population. As age increases, people’s mobility may decrease. However, older people have more leisure time compared to their younger (working) counterparts, and potentially spend more time on social activities. Therefore, this group can possibly increase social travel demand. However, to date, the travel demand for social activities of senior citizens has received only little attention. This paper studies trip-making for social purposes, with a special focus on the demographic ageing factors. Using social activity diary data, models are estimated to predict the number of social trips, the travel distance and mode of transport for social trips. The results indicate that the elderly of today seem to be as mobile as their younger counterparts with respect to the number of social trips. High education and involvement in clubs on average result in more social trips and full time work is found to result in fewer social trips. With regard to trip distance the results show that the average travel distance does not decrease as people get older. Full time work is found to result in longer social trips. Shorter trips were found for people in urban as well as rural areas. Trips for the purpose of visiting or joint activities tend to be longer than average. With regard to transport mode choice the results indicate that older seniors (75+) are less likely to choose the bicycle, relative to driving. No other significant age effects were found. Significant effects were found for gender, household structure, education level, car ownership, having a disability, urban density, distance and the purpose of the social activity.     

Micromobility evolution and expansion: Understanding how docked and dockless bikesharing models complement and compete – A case study of San Francisco

Shared micromobility – the shared use of bicycles, scooters, or other low-speed modes – is an innovative transportation strategy growing across the United States that includes various service models such as docked, dockless, and e-bike service models. This research focuses on understanding how docked bikesharing and dockless e-bikesharing models complement and compete with respect to user travel behaviors. To inform our analysis, we used two datasets from February 2018 of Ford GoBike (docked) and JUMP (dockless electric) bikesharing trips in San Francisco. We employed three methodological approaches: 1) travel behavior analysis, 2) discrete choice analysis with a destination choice model, and 3) geospatial suitability analysis based on the Spatial Temporal Economic Physiological Social (STEPS) to Transportation Equity framework. We found that dockless e-bikesharing trips were longer in distance and duration than docked trips. The average JUMP trip was about a third longer in distance and about twice as long in duration than the average GoBike trip. JUMP users were far less sensitive to estimated total elevation gain than were GoBike users, making trips with total elevation gain about three times larger than those of GoBike users, on average. The JUMP system achieved greater usage rates than GoBike, with 0.8 more daily trips per bike and 2.3 more miles traveled on each bike per day, on average. The destination choice model results suggest that JUMP users traveled to lower-density destinations, and GoBike users were largely traveling to dense employment areas. Bike rack density was a significant positive factor for JUMP users. The location of GoBike docking stations may attract users and/or be well-placed to the destination preferences of users. The STEPS-based bikeability analysis revealed opportunities for the expansion of both bikesharing systems in areas of the city where high-job density and bike facility availability converge with older resident populations.     

The multiplicity of self-selection: What do travel attitudes influence first,residential location or work place?

Residential self-selection has been widely considered as an important issue in quantifying the impacts of the residential built environment on travel behavior and much empirical evidence regarding the nature and magnitude of the self-selection effect has been reported. Nevertheless, people may be based on travel attitudes/needs to self-select not only residential location, but also work place, car ownership, etc. In other words, the impacts of long-term decisions other than residential location choices (e.g., decisions on work place, car ownership, etc.) on travel behavior may also be biased by the self-selection effect. However, self-selection concerning these long-term decisions has not been explored much in the travel behavior literature. The role of residential self-selection would not be properly evaluated if self-selections concerning other long-term decisions were not considered because they are often related. This paper addresses this research gap in the travel behavior literature by exploring the multiplicity of travel-based self-selection. We jointly examine the possible self-selections concerning residential location, workplace, commuting distance and car ownership in an integrated framework, taking into consideration the interrelationships among these decisions. Data are derived from an activity-travel diary survey conducted in 2016 in Beijing, China. We classify the respondents into two groups based on the choice order of their current residential and work locations and conduct a comparative analysis using structural equation models. It is found that self-selection exists in all long-term choices examined in the study. The choices of residential location and work place are found to be mutually dependent. Consequently, both choices have indirect impacts on travel behavior through the other choice.     

Revealing intra-urban travel patterns and service ranges from taxi trajectories

As an important transport tool, taxi plays a significant role to meet travel demand in urban city. Understanding the travel patterns of taxis is important for addressing many urban sustainability challenges. Previous research has primarily focused on examining the statistical properties of taxi trips to characterize travel patterns, while it may be more appropriate to explore taxi service strategies on seasonal, weekly or daily time scale. Therefore, intra-urban taxi mobility is investigated by examining taxi trajectory data that were collected in Harbin, China, while 12-week corresponding to 12-month is chosen as the sampling period in our study. The multivariate spatial point pattern analysis is firstly adopted to characterize and model the spatial dependence, and infer significant positive spatial relationships between the picked up points (PUPs) and the dropped off points (DOPs). Secondly, the points of interest (POIs) are identified from DOPs using the emerging hot spot detection technique, then the taxi services and movement patterns surrounding POIs are further examined in details. Moreover, our study builds on and extends the existing work to examine the statistical regularities of trip distances, and we also validate and quantify the impacts posed by airport trips on the distance distributions. Finally, the movement-based kernel density estimation (MKDE) method is proposed to estimate taxis' service ranges within three isopleth levels (50, 75 and 95%) between summer/weekday and winter/weekend from taxi driver's perspective, and season as well as temperature factors are identified as the significant effect within certain service range levels. These results are expected to enhance current urban mobility research and suggest some interesting avenues for future research.     

The spatial externalities of car-based worktravel emissions in greater London, 1981 and 1991

This research considers vehicle emissions from travel to work trips by car within and through the localities of London. Specific focus is placed on the residential origins of the trips and the analysis is based on 1981 and 1991 Census travel to work data. London is divided into some 24 one kilometre concentric ring bands and the number of vehicle kilometres travelled within each of these is calculated from ward to ward origin-destination worktravel movements by car. The spatial distribution of vehicle emissions from the perspective of the source origin of this type of urban environmental external disbenefit is derived. The research points to the highest concentrations of emissions located firmly in the centre of the city and this confirms scientific survey evidence of air quality. The results also confirm that in Central and Inner London the largest proportionate contribution to total emissions arises from vehicles originating from residences in Outer London.     

The influence of socioeconomic characteristics,land use and travel time considerations on mode choice for medium- and longer-distance trips

This paper contributes to the limited number of investigations into the influence of the spatial configuration of land use and transport systems on mode choice for medium- and longer-distance travel (defined here as home-based trips of 50 km and over) in the Netherlands. We have employed data from the 1998 Netherlands National Travel Survey to address the question as to how socioeconomic factors, land use attributes, and travel time affect mode choice for medium- and longer-distance travel, and how their role varies across trip purposes: commuting, business, and leisure. The empirical analysis indicates that land use attributes and travel time considerations are important in explaining the variation in mode choice for medium- and longer-distance travel when controlling for the socioeconomic characteristics of travellers.     

Structures of commitment in mode use: a comparison of Switzerland, Germany and Great Britain

Travellers commit themselves to particular behaviours through the ownership of cars and season tickets. They trade a large one-off payment for low or zero marginal cost at the point of use. It can be assumed that these commitments influence travel behaviour. To the knowledge of the authors there is no literature which addresses the choice between the commitment to the one or the other mode and its impacts on travel behaviour.The paper presents models using structural equation modelling to test a-priori hypotheses on the paths linking car-availability, season-ticket-ownership and modal usage. Modal usage is operationalised as the number of trips by car, public transport, or as the distances travelled by car or public transport. The models are based on three different surveys: Switzerland, Germany and Great Britain. The results confirm the dominance of car-availability, which drives the other variables, but the relationships are more complicated than generally assumed.     

Errors in variables in multinomial choice modeling: A simulation study applied to a multinomial logit model of travel mode choice

Modeling travel demand is a vital part of transportation planning and management. Level of service (LOS) attributes representing the performance of transportation system and characteristics of travelers including their households are major factors determining the travel demand. Information on actual choice and characteristics of travelers is obtained from a travel survey at an individual level. Since accurate measurement of LOS attributes such as travel time and cost components for different travel modes at an individual level is critical, they are normally obtained from network models. The network-based LOS attributes introduce measurement errors to individual trips thereby causing errors in variables problem in a disaggregate model of travel demand. This paper investigates the possible structure and magnitude of biases introduced to the coefficients of a multinomial logit model of travel mode choice due to random measurement errors in two variables, namely, access/egress time for public transport and walking and cycling distance to work. A model was set up that satisfies the standard assumptions of a multinomial logit model. This model was estimated on a data set from a travel survey on the assumption of correctly measured variables. Subsequently random measurement errors were introduced and the mean values of the parameters from 200 estimations were presented and compared with the original estimates. The key finding in this paper is that errors in variables result in biased parameter estimates of a multinomial logit model and consequently leading to poor policy decisions if the models having biased parameters are applied in policy and planning purposes. In addition, the paper discusses some potential remedial measures and identifies research topics that deserve a detailed investigation to overcome the problem. The paper therefore significantly contributes to bridge the gap between theory and practice in transport.     

Using GIS to visualise and evaluate student travel behaviour

Using GIS to evaluate travel behaviour is an important technique to increase our understanding of the relationship between accessibility and transport demand. In this paper, the activity space concept was used to identify the nature of participation in activities (or lack of it) amongst a group of students using a 2 day travel-activity diary. Three different indicators such as the number of unique locations visited, average daily distance travelled, and average daily activity duration were used to measure the size of activity spaces. These indicators reflect levels of accessibility, personal mobility, and the extent of participation, respectively. Multiple regression analyses were used to assess the impacts of students socio-economic status and the spatial characteristics of home location. Although no differences were found in the levels of accessibility and the extent of participation measures, home location with respect to a demand responsive transport (DRT) service was found to be the most important determinant of their mobility patterns. Despite being able to travel longer distances, students who live outside of the DRT service area were found to be temporally excluded from some opportunities. Student activity spaces were also visualised within a GIS environment and a spatial analysis was conducted to underpin the evaluation of the performance of the DRT. This approach was also used to identify the activity spaces of individuals that are geographically excluded from the service. Evaluation of these results indicated that although the service currently covers areas of high demand, 90% of the activity spaces remained un-served by the DRT service. Using this data six new routes were designed to meet the coverage goal of public transport based on a measure of network impedance based on inverse activity density. Following assessment of public transport service coverage, the study was extended using a spatial multi criteria evaluation (SMCE) technique to assess the effect of service provision on patronage.     

Segmenting travellers based on day-to-day variability in work-related travel behaviour

Travel needs for commute and business trips are complex and choices are not made based on the characteristics of individual trips, but instead based on the needs over weeks and months. For example, the cost per trip of commuting by bus varies depending upon the frequency of travel, and the cost of a monthly subway pass depends upon the number of zones visited during that period. Intrapersonal variability, namely the variation in an individual's travel behaviour from day to day, therefore shapes our transport choices and should influence service provision. Changes in working patterns such as increases in part time working, self-employment and tele-commuting challenge the traditionally held assumptions that work activities are fixed in time and space, thus making intrapersonal variability increasingly relevant. This research uses a data-driven approach to segment workers based on their work-related travel behaviour, including frequency of travel and both spatial and time of day intrapersonal variability. The analysis uses survey and seven day travel diary data for over 110,000 people collected over a 19 year period in England. Four groups of workers were identified: infrequent, spatially variable, temporally variable and regular travellers. These groups do not align closely with self-reported working arrangements such as self-employment or part time working. The group of regular travellers has decreased in size between 1998 and 2016 but remains the largest group, containing just under 60% of workers in 2016. Both the infrequent and spatially variable groups have grown over the same period. For a small but growing group of workers, a seven day diary is insufficient to understand their work-related transport needs as little or no work travel is recorded. These findings have implications for the design of public transport ticketing, the design of mobility as a service packages and the appraisal of congestion charging schemes.     

Causes and effects between attitudes,the built environment and car kilometres: A longitudinal analysis

Travel-related attitudes are believed to affect the connections between the built environment and travel behaviour. Previous studies found supporting evidence for the residential self-selection hypothesis which suggests that the impact of the built environment on travel behaviour could be overestimated when attitudes are not accounted for. However, this hypothesis is under scrutiny as the reverse causality hypothesis, which implies a reverse direction of influence from the built environment towards attitudes, is receiving increased attention in recent research. This study tests both directions of influence by means of cross-sectional and longitudinal structural equation models. GPS tracking is used to assess changes in travel behaviour in terms of car kilometres travelled. The outcomes show stronger reverse causality effects than residential self-selection effects and that land-use policies significantly reduce car kilometres travelled. Moreover, the longitudinal models show that the built environment characteristics provide a better explanation for changes in car kilometres travelled than the travel-related attitudes. This contradicts the cross-sectional analysis where associations between car kilometres travelled and travel-related attitudes were stronger. This highlights the need for more longitudinal studies in this field.