The interplay between dockless bikeshare and bus for small-size cities in the US: A case study of Ithaca

As another mode of shared transportation, bikeshare can substitute or complement public transit. Prior studies mainly relied on self-reported survey data or aggregated station-level data from docked bikeshare systems, and their conclusions and implications were focused on large cities. It is largely unknown how and to what extent a dockless bikeshare system complements or substitutes public transit, especially in small cities. This study was set to measure the interplay between Lime dockless bikeshare and bus service in Ithaca, NY – a typical small-size college town – and its environs. By joining about 3.42 million records of bus stop data and 102 thousand Lime bikeshare trip data from 2019, two types of Bikeshare-Bus-Linkage (BBL) trips were identified, namely (1) the first-mile trip where a user rides a Lime to board a bus, and (2) the last-mile trip where a user bikes to their destination after alighting a bus. BBL trips were identified using a spatiotemporal proximity framework based on two important parameters: the catchment radius and the time window between a bus stop event and a Lime trip. Different values were tested with a sensitivity analysis, and the parameters were finally set at 100 ft. and 5 min. As such, 3026 BBL trips were identified, which was 3% of total Lime ridership or 0.1% of total bus ridership. Our findings indicated that Lime provided useful first- and last-mile transfers to bus service for commuters. The complementary effect was particularly strong in the urban core and with transit development and employment land use areas. Moreover, in the morning peak, there were more first-mile trips from residential areas to bus stops in the urban core, while in the evening peak more last-mile trips started from bus stops in the urban core to residential areas. Based on the unique first-mile and last-mile trip patterns identified, policy implications and recommendations for bikeshare operators, local government, transit agencies, and transportation policymakers were discussed to better integrate bikeshare and public transit.     

Factors associated with disability paratransit's travel time reliability

This paper identifies some of the characteristics of trips and pick-up and drop-off locations that are associated with paratransit's travel time reliability. Following convention, reliability has been defined as the inverse of variability. Four measures of travel time variability have been used to examine reliability: Standard Deviation, Percent Variation, Misery Index, and Buffer Index. Regression models have been used to estimate these four variables with trip data from Access Link, the paratransit service provided by NJ TRANSIT pursuant to the Americans with Disabilities Act (ADA). A number of characteristics of the pick-up and drop-off locations as well as selected characteristics of the trips were used as independent variables of the models. The statistical significance of the independent variables varied depending on which measure of reliability was estimated, but a few variables were consistently associated with reliability in all four models. These variables were trip distance, booking type, winter season, density of motor vehicle crashes in pick-up and drop-off locations, and whether pick-ups occurred in suburban bus corridors or urban core areas. Because of the significance of the variables on motor vehicle crash density in pick-up and drop-off locations, an additional regression model was used to examine the effect of crash incidents on trip duration by considering drop-offs that occurred in locations immediately after a crash. The model showed that trips take 4 to 5% longer when crashes occur in locations prior to a drop off. Planning implications of the findings are discussed.     

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     

Who takes part in film tourism? The analysis of determinants of visiting film locations

Film tourism is one of the fastest developing sub-segments of creative tourism in the 21st century. Many studies investigated tourists' motivation and behavior towards film tourism in the context of psychological and emotional motives and their involvement and experience. However, we still know very little about the structure of visitors of film sites. Utilizing primary data collected in Slovakia and adopting the econometric approach, the aim of this empirical study is to estimate the relationship between preferred trip parameters and the decision to include a visit to a film location in the travel plan. The results suggest that visits to film sites occur to a significant extent by chance, film tourism is additional, mainly to other segments of tourism, characterized as adventurous and explorative experiences. Visits to film locations occur mainly as trips by younger age groups and longer stays, mostly as self-organized trips, regardless of budget, frequency of travel, or gender.     

Spatial variation in shared ride-hail trip demand and factors contributing to sharing: Lessons from Chicago

As ride-hailing becomes more common in cities, public agencies increasingly seek transportation network company (TNC) service data to understand (and potentially regulate) demand and service response. Despite the increase in ride-hailing or TNC demand and subsequent research into its determinants, there remains little research on shared TNC trips and the spatial distribution of trip demand across demographic and land use variables. Using Chicago as a case study, shared TNC trip data from 2019 was used to estimate the count and ratio of shared ride services, based on built environment, demographic, location, time of day, and trip details. Findings reveal that trip length, day of week designation, density of pedestrian and multi-modal infrastructure, and underlying socioeconomic characteristics of the origin zones influence the proportion and count of shared ride-hail trips. Of concern is that those using transit or active modes may be taking more ride-hailing trips, but these Chicago-region results indicate that the provision of pedestrian infrastructure and remoteness to transit stops result in fewer shared trips.     

Do rural older adults take fewer trips than their urban counterparts for lack of a ride?

Aging and the presence of one or more illnesses result in limited travel for many adults age 65 and over. Yet, the need to get to essential, social, and non-emergency medical destinations endures. At some point in their life, older adults become dependent on family/friends, or rely on for-profit/not-for-profit transportation services for their mobility needs, while some do not go on certain trips. Researchers have studied out-of-home activity and mobility of older adults using data on trips taken. There is a gap, however, in understanding trips not taken in the older adult population in rural versus urban locations. Our objectives in this paper are: (i) to investigate unmet travel needs of older adults by relying on responses for trips not taken; (ii) to examine how personal abilities, living situation, and socio-demographic factors are associated with trips not taken to various destinations; and (iii) to compare the likelihood of trips not taken due to lack of a ride in urban versus rural locations across the age and income spectrum. Our data come from a phone survey conducted across the province of Alberta, Canada, in 2017–18 (n = 1390). We specify ordinal logistic models where the dependent variable is how often a respondent did not undertake a trip due to not having a ride to various trip destinations. We find that rural seniors are more likely to not take trips compared to older adults in cities, holding all else equal including driving cessation, worsening health, and disability. Rural seniors who live alone or in low-density housing are also more likely to not take trips compared to urban older adults. Household income, however, tempers these location preferences. Our findings suggest that rural older adults can be supported through income transfers, community-based low-cost travel, and moving to higher-density residential locations.     

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 location and daily travel distances: the influence of trip purpose

This paper investigates the extent to which residential location influences daily distance travelled if travel purposes are differentiated. Statistical multilevel models are applied to Swedish National Travel Survey data from 2005–2006. Travel purposes are categorized by considering time–spatial constraints and hypothesized factors of personal freedom of choice. Results indicate that the influence of residential location on daily distance travelled is highly conditional on trip purpose in a nationwide Swedish context. Although statistically significant proportions of the variation in daily distance travelled to work, on service errands, and on weekdays were dependent on residential location, daily travel distances for leisure activities and on weekends varied greatly among people living in the same neighbourhood. From a policy perspective, these results suggest that measures intended to alter the built environment to reduce the volume of travel will be most efficient as regards work trips, while trips taken during free time are unlikely to be much affected. In addition, the multilevel models applied reveal several important interactions between the variation in travel distances across residential locations and individual characteristics of which researchers should be aware, especially when examining service trips.     

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 effect of travel cost on frequencies of shopping and recreational trips in Sweden

This article focus on how the cost of travel affects travel behavior. A trip frequency model for recreational and shopping trips is suggested and used to investigate this. The data that is used comes from a Swedish travel habit survey where the respondents’ trip frequencies of both types of trips on a certain day are recorded. This is likely to introduce a correlation structure, which is incorporated in the model. Special attention is paid to the effect of travel cost on trip frequencies for different regions and income groups. As a measure of the sensitivity of cost changes, elasticity of demand is calculated. The precision of the elasticities are evaluated with simulated p-values.     

Characteristics and Behaviour of Tourists Who Use Trails

This article documents the popularity of five types of trail-based recreation relative to other forms of recreation that tourists frequently participate in on their trips; identifies these trail users’ cross-participation in other outdoor recreation activities; and profiles the travel behaviour, media habits, trip planning behaviour, and demographic and socioeconomic characteristics of day hikers and snowmobilers as two particularly large trail user segments. Findings are based on data from a household telephone survey conducted in Michigan, surrounding states, and Ontario, Canada. Hiking/backpacking was found to be the most popular natural resource-based recreation activity that respondents participated in on pleasure trips taken during the past 12 months; other forms of trail-based recreation were significantly less popular; mountain bikers participated in nature-oriented recreation activities in Michigan at levels that were similar to those of hikers/backpackers; and snowmobiling appeared to be the focus of most pleasure trips on which this activity occurred, in contrast to day hiking, which appeared to be more of an ancillary pursuit.     

The role of airport proximity on warehouse location and associated truck trips: Evidence from Toronto,Ontario

This paper examines the two-way relationship between land use and transportation from the perspective of warehouses in the Toronto Census Metropolitan Area. A location choice model is first developed to reproduce the decision process of firms selecting suitable locations to operate warehousing facilities. The results highlight that transportation plays a prominent role in the location of warehouses with proximity to airport, highway infrastructure, and rail to a lesser extent. However, the proportion of industrial land use provides the largest role in the model suggesting that available land and zoning is the most important factor. This paper also studies the impact of warehouse location on freight transportation trips. The resulting analysis highlights that GPS derived trips arising from warehouses near a major airport in Toronto tend to travel 1.8 times further than trips pertaining to other warehouses in the region. This suggests that trips related to the airport are more likely to be connected to a larger supply chain process.     

Uncovering the spatiotemporal patterns of CO2 emissions by taxis based on Individuals' daily travel

Traffic-related carbon dioxide (CO₂) emissions have become a major problem in cities. Especially, the CO₂ emissions induced by taxis account for a high proportion in total CO₂ emissions. The availability of taxi trajectory data presents new opportunities for addressing CO₂ emissions induced by taxis. Few previous studies have analyzed the impact of human trips on CO₂ emissions. This paper investigates trip-related CO₂ emission patterns based on individuals' travel behavior using taxi trajectory data. First, we propose a trip purpose inference method that takes into account the spatiotemporal attractiveness of POIs to divide human trips into different types. Further, we reveal the spatiotemporal patterns of CO₂ emissions from various types of trips, including temporal regularity and periodicity as well as spatial distribution of “black areas”. Finally, comparative analysis of CO₂ emissions for different kinds of trips based on trip behavior is conducted using three variables, namely trip distance, trip duration and trip speed. This study is helpful for us to understand how to make travel and cities more sustainable through modifying people's trip behaviors or taxi trips.     

Journey quality as the focus of future transport policy

While personal travel seems to be growing inexorably, along with car ownership, other transport parameters are invariant: average travel time, trip rate, and the proportion of household income spent on travel. Past growth in personal travel may, therefore, be attributed to longer trips carried out at higher speeds and made possible by higher expenditure. For the future, the need to limit environmental detriments associated with the transport system requires the diversion of growing personal expenditure, from further increasing the quantity of travel to enhancing the quality of the journey. Policies and technologies to achieve this objective are discussed, including discriminatory road pricing.     

Built environment diversities and activity–travel behaviour variations in Beijing, China

The association between built environment and travel behaviour has received considerable research attention in recent years. In an attempt to contribute to this growing literature, this paper investigates the connections between urban built environments and activity–travel patterns in Beijing, the capital city of China. We characterize the built environment in Beijing and establish associations between built environment and activity–travel behaviour in terms of car ownership, time spent for out-of-home activities, and daily trip frequencies and travel time. Activity diaries from 1119 respondents living in ten different neighbourhoods were collected by face-to-face interviews. A household-level structure equations model incorporating intra-household interactions is developed to analyse this data. The empirical results show that residents of different types of neighbourhoods in Beijing demonstrate significant differences in car ownership, time spent for out-of-home activities, trip rate, and travel time. Further, the characteristics of the built environment are found to have more significant impacts on the activity–travel behaviour of the male head than that of the female head.     

Walking to transit: An unexpected source of physical activity

Using data from a regional survey carried out in Montreal, this paper shows empirical evidence that modal shift from car to transit contributes to the volume of daily physical activity. First, the paper presents a method to calculate the walking distance related to transit trips, and a totally disaggregate trip assignment model. The walking distance involved in every transit trip is then associated to the individuals' characteristics to estimate the number of steps made by the population in the whole transit system.Results show that, in average, a transit trip involves 1250 steps, required to access and egress the network as well as to transfer between routes or modes. Thus, a round trip represents 2500 steps, which account for 25% of the recommended volume of physical activity per day. Hence, analysis shows that the volume of walking varies according to attributes of the traveler (general decrease with age, higher for men) and of the trip (study and work trip involve more steps, the use of train generates more steps). A regression model confirms that these variables significantly affect the number of steps involved in transit trips. Such positive outcome, for the traveler himself, is an innovative argument to promote the use of transit that is also aligned with current sustainable transportation goals.     

Logistics facilities for intra and inter-regional shipping: Spatial distributions,location choice factors,and externality

Existing studies of urban logistics facility locations and their impacts on negative externality tend to focus on the movements of freight that start and end within a metropolitan area and overlook the role of the shipments with origin or destination outside of the urban area – external shipments – in characterizing logistics facilities. This research aims to fill such gap. Focusing on the Tokyo Metropolitan Area, we analyze locations and goods vehicle trips associated with four logistics facility groups that have different splits between intra and inter-regional trips for inbound and outbound shipments. The spatial density analysis and the location choice modeling highlight the differences in the distribution and location choice factors among those groups. The importance of trip distance minimization is more evident for the facilities that serve intra-regional shipments. Furthermore, we show that the traffic impacts of goods vehicle traffic associated with logistics facilities also differ in many ways among the above-mentioned groups. Finally, we discuss the policy insights to address their heterogeneity in the contribution to externality.     

Distributional effects of public transport subsidies

We analyze the distribution of transit subsidies across population groups in Stockholm. We develop a novel methodology that takes into account that the subsidy per passenger varies across transit links, since production costs and load factors vary. With this, we calculate the subsidy per trip in the transit network and analyze the distribution of subsidies across population groups. The average subsidy rate in Stockholm is 44%, but the variation across trips turns out to be large: while 34% of the trips are not subsidized at all but generates a profit, 16% of the trips have a subsidy rate higher than 2/3. We calculate the concentration index to explore the distribution of subsidies across income groups. The average subsidy per person is similar for all income groups, except for the top income quintile. This holds not only for the current flat-fare system, but also for distance-based fares and fares with a constant subsidy rate. Transit subsidies is hence not effective as a redistribution policy in Stockholm. The largest systematic variation we find is across residential areas: the average subsidy per person is five times higher in the peripheral areas of the region compared to the regional core, and the subsidy per trip is ten times higher.     

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.