Transit Pass Research Articles

Using Behavioral Nudges and Incentives to Increase Affordability of Transit Systems through Donations

This study relies on an experimental design framework to identify the behavioral nudges and incentives that can facilitate altruism for a transportation-related cause of the members of a university community. Our findings reveal the overall willingness to support transportation options for low-income community members either through financial contributions or, in the case of some of the students, donating their infrequently used student transit passes. We also found the positive effect of recognition on donating for students and male car commuters, as well as higher chances for a sunk cost of a contribution to increase the likelihood of a donation.

Post-pandemic transit commute: Lessons from focus group discussions on the experience of essential workers during COVID-19

Public transit services, which provide a critical lifeline for many essential workers, were severely interrupted during the COVID-19 pandemic. As institutions gradually return to normal in-person operations, it is critical to understand how the pandemic affected essential workers' commute and what it will take to ensure the effective recovery of transit ridership and enhance the long-term resiliency and equity of public transportation systems for those who need it the most. This study used focus group discussions with essential workers who were pre-pandemic transit riders to understand how the COVID-19 pandemic has impacted their commute perceptions, experiences, motives, and challenges and explore the potential changes in their travel behavior post-pandemic. We used NVivo 12 Pro to conduct a thematic analysis of the transcripted discussion data and examined patterns of commute mode change with respect to participants' attributes, including job type, home location, and gender. The results show that public transit had multiple reliability and frequency challenges during the pandemic, which resulted in most participants switching away from public transportation. With the increased availability of hybrid remote work and pandemic-related parking policies, driving emerged as a safer and more affordable commute mode for many pre-pandemic transit riders, rendering transit services less efficient for those who continued to rely on it. Planning for post-COVID resilient and reliable mobility requires a major rethinking of providing an efficient and effective transport system and a more fundamental approach to long-term public transport policy. To recover transit ridership, transit agencies need to ensure transit service availability and provide reliable transit information through smartphone apps. Similarly, transit agencies need to coordinate with other employers to provide free or heavily subsidized transit passes, to facilitate the recovery of transit demand effectively.

A collective incentive strategy to manage ridership rebound and consumer surplus in mass transit systems

This paper models and analyzes a collective incentive strategy with passenger departure time equilibrium to maximize the total passenger surplus, which could further enhance the sustainability of transit systems in the post-pandemic era. In the proposed collective incentive strategy, passengers with transit passes have dynamic discounts where the discount value depends on the total number of passengers enrolled in the incentive program. A bi-level optimization model is established by considering passengers' demand elasticity and responses to the strategy, which eventually determines the starting time and duration of the collective incentive strategy during the time of the day. We further analyze the properties of the proposed collective incentive model to identify the analytical solutions and performance. Analytical results indicate that there exists a threshold demand elasticity below which the total surplus of commuters with and without transit passes can be improved simultaneously. Properties also show that there could exist multiple local optimal solutions of incentive strategy duration for a given starting time. A case study is conducted with the metro system in Toronto: the results show that the proposed collective incentive strategy could improve both the fare revenues and ridership by 33.31 % and 83.56 %, respectively.

Missing Typical Weekdays in Travel Surveys: A Pseudo-Panel Approach to Explore Weekly Travel Patterns

Travel surveys generally rely on single-day travel diaries where respondents report their travel information for a typical weekday. However, the concept of a typical weekday does not represent the current reality, as travel behavior has been largely altered in the post-pandemic period. Besides, the conclusions based on analyzing single-day travel diaries lack the ability to capture daily variations in travel behavior. In response to these concerns, this research proposed a framework to expand single-day travel diaries into longitudinal multi-day travel data using a pseudo-panel approach. Leveraging the constructed longitudinal data, the study evaluated the determinants of people’s daily participation in work–school, routine, and discretionary activities. Fixed and random effects panel data estimation models were used for this purpose. Results showed that activity participation is largely attributed to vehicle ownership, income, education, driving license, and household structure. Noticeable daily trends were observed in work–school and discretionary activities. A negative association between transit pass ownership and activity participation was noticed, suggesting social exclusion faced by transit users. In addition, teleworkers were found to be relatively more engaged in discretionary activities. Suburban residents were found to travel longer to participate in activities compared to urban dwellers. The proposed research framework can support future activity-based modeling aspects, such as activity participation, scheduling, mode choice, shared travel, and destination choice models, specifically addressing the “typical weekday” barrier.

Comparison of Discrete Choice and Machine Learning Models for Simultaneous Modeling of Mobility Tool Ownership in Agent-Based Travel Demand Models

Individual travel behavior, such as mode choice, is determined to a distinct degree by the respective portfolio of available mobility tools, such as the number of cars, public transit pass ownership, or a carsharing membership. However, the choice of different mobility tools is interdependent, and individuals weigh alternatives against each other. This process of parallel trade-offs is currently not reflected in typically used sequential logit models of agent-based travel demand models. This study fills this research gap by applying discrete choice and neural network models on a synthetic population to model multiple mobility tool ownership simultaneously. Using data from a national household travel survey, both model types approximated the given target distributions of mobility tools more accurately than the sequence of three corresponding logit models. Owing to its greater flexibility, the tested shallow and deep neural network exhibited higher predictive accuracy than simultaneous discrete choice models. The results indicated that neural networks with only one hidden layer were more robust and easier to formulate and interpret than deep networks with three hidden layers. Finally, the flat neural network was applied to a different synthetic population resulting in equally accurate results.

Support for Active Transport Policy Initiatives Among Canadian Adults: The Canadian National Active Transportation Survey

Objectives: To examine public support for active transportation (AT) policies and to identify demographic and behavioural predictors of support for each policy approach.Methods: Canadian adults aged 18 years and older (N = 2,868) provided information on demographic factors (e.g., age, income), place of residence (e.g., region, size of community), and the frequency with which they walked/wheeled or cycled to work or school in a typical week. In addition, they rated their support for AT-related policies (e.g., spending government money on more dedicated bicycle paths, offering tax credits for public transit passes, charging higher rates for parking to subsidize costs for AT infrastructure, changing the design of neighbourhoods and communities to encourage informal physical activity). Multinomial regressions examined demographics and AT behaviour as predictors of support for each policy approach, yielding a total of eight models.Results: Although most policy actions to promote AT were supported by Canadians, the level of support varied by the type of policy actions and by demographics and AT behaviour. A majority of Canadians supported policy approaches targeting environmental planning and fiscal measures that incentivized AT. A minority of Canadians supported policies aimed at regulation or coercive fiscal measures. The level of support for AT policies was higher among women, those with more education, younger respondents, those residing in central and eastern Canada, and individuals who engaged in AT.Conclusion: Canadians are supportive of policy actions to facilitate AT. This public support might be important for their future development and implementation.  

Moving on income as a social determinant of health: free transit for social assistance recipients in Kingston, Ontario.

The public health intervention setting is the City of Kingston, Ontario, Canada. The authors were involved in various stages of development of the intervention, including advocacy, design, implementation, and evaluation. In early 2017, the City of Kingston launched a pilot program to offer all recipients of social assistance a pass that would provide unlimited access to transit. The 1-year pilot program showed promise in terms of the objectives of the two departments involved, Housing and Social Services and Kingston Transit, as it reduced barriers to transportation and increased ridership in the city. The pilot was adopted as an ongoing program, The Ontario Works Universal Transit Pass, upon completion of the pilot. The program was funded by redirecting provincial means-tested and discretionary employment benefits from the Housing and Social Services budget to the Kingston Transit budget in order to purchase transit in bulk for Ontario Works (OW) recipients. The program provided greater access to essential services, increased household budgets, reduced stigma, and increased ridership. The improved social and economic opportunities that the program facilitated demonstrate the potential of addressing social determinants of health through transportation. The program illustrates an effective model for addressing income as a social determinant of health through transportation policy. Moreover, it demonstrates the potential for creative, cooperative approaches to inter/intra-government operations-like the transfer of funds from Housing and Social Services to Kingston Transit-which simultaneously promotes both greater efficacy of public services and health equity.

Development of a Visualization Tool for the Integrated Transport and Land Use Model: Insights from a COVID-19 scenario analysis

This paper develops a scenario analysis and visualization tool for an Integrated Transport, Land-Use and Energy (iTLE) model to spatially analyze and predict changes in transport and land-use environment. The decision support tool operates by taking the iTLE model output data as input which includes residential location of households, individuals’ characteristics, and vehicle fleet information. Use of the tool is showcased through a scenario analysis of a ‘business as usual (BAU)’ projection versus a ‘COVID-19 pandemic scenario’ for Halifax, Canada. Agent-based microsimulation explores the possible future changes in households’ socio-demographic characteristics and travel behaviour in the post-pandemic time. Forecasting up to the year 2025 and comparing between BAU and pandemic scenario shows that, many of the lower median income areas in the BAU projection are estimated to have a much lower median income under the COVID-19 scenario. Furthermore, the COVID-19 scenario only slightly decreases the proportion of the overall population with a transit pass. Under the pandemic scenario, the percentage of households with three or more cars experiences significant growth in urban and suburban areas. Outcomes of this study will offer policymakers a greater understanding of the transformation pattern of urban and suburban neighborhoods in the post-pandemic period. The developed iTLE VIZ tool will allow planners to formulate complex transport and land-use scenarios and simulate them for examining urban systems transformation.

Estimating suburban preferences for integrated public transit and ridesourcing services through a revealed-preference/stated-preference survey

Low-density areas like suburbs can be challenging to serve with fixed-route transit. Demand responsive transit has been used to service these areas with mixed results, but suburban travellers may respond to ridesourcing integrated with transit more positively because of the improved booking and dispatching interface offered by ridesourcing. This paper explores how suburban residents perceive transit-integrated ridesourcing, both for cost and time attributes of the system and in comparison to other travel modes in the area (cycling, auto, taxi or Uber, and transit). A Hierarchical Bayes mixed logit model was estimated using the results of a revealed-preference/stated-preference survey, revealing that transit-integrated ridesourcing had similar preferences to fixed-route transit. Across time and cost variables, respondents were more sensitive to walk time, transfer time, the number of transfers, parking cost, and taxi or Uber fare, and were minimally impacted by changes in the IVTT deviation of their trip times. The change in utility for the length of transit or transit-integrated ridesourcing in-vehicle travel time versus auto in-vehicle travel time was found to have a strongly linear relationship, while other attributes exhibited non-linearity to different degrees, particularly walk time, transfer time, transit-integrated ridesourcing fare, and taxi or Uber fare. Respondents who were female, younger, taking home-based school trips, or had lower household incomes were more open to transit-integrated ridesourcing and transit than other demographic groups. The likelihood of taking each of the five travel modes was assessed after COVID-19, finding generally minimal to negative impact for transit-integrated ridesourcing. Insights into vehicle and transit pass ownership, existing travel alternatives, and a prior transit-integrated ridesourcing pilot in the area are presented.

Revisit employer-based travel demand management: A longitudinal analysis

Employer-based travel demand management (TDM) programs have been implemented worldwide for decades, but rarely are longitudinal analyses implemented. This study utilizes a longitudinal dataset to assess the effectiveness of TDM measures on vehicle trip rates (VTRs) over time. The results suggest: (1) VTR grows over time, and TDM measures may decelerate the growth but cannot reverse the trend; (2) for organizational tools, collective bargaining is negatively associated with VTR; (3) distributing transit passes is negatively associated with VTR; (4) ride match is positively correlated with VTR; (5) guaranteed ride home measures, including emergency rides and employer-provided vehicles, are positively associated with VTR; (6) subsidies promoting multimodal transportation (transit, walking, biking) incentivize vehicle trip reduction; the more subsidies, the lower VTR, and such effects are reinforced over time; (7) in contrast, subsidies promoting carsharing are associated with more vehicle trips; (8) larger companies and areas with higher job densities have a lower VTR. To inform practice, when rewarding employees, distributing transit passes is a preferred strategy. Collective bargaining builds agreements between employers and employees and helps promote trip reduction. Carpooling-related and guaranteed ride-home measures should be applied with caution.

Office Development, Rail Transit, and Commuting Choices

Decentralized employment growth has cut into transit ridership across the United States. In California, about 20 percent of those working in office buildings near rail stations regularly commute by transit, nearly three times transit’s modal share among those working away from rail stations. Mode choice models reveal that office workers are most likely to rail-commute if frequent feeder bus services are available, their employers help cover the cost of taking transit, and parking is in short supply. Factors like trip-chaining and the absence of restaurants and retail shops near suburban offices, however, deter transit-commuting. Policy-makers can promote transit-commuting to offices near rail stops by flexing parking standards, introducing high-quality feeder buses, and initiating workplace incentives such as deeply discounted transit passes. While housing has generally been the focus of transit-oriented development, unless the other end of the commute trip—the workplace—is also convenient to transit, transit will continue to struggle in winning over commuters in an environment of increasingly decentralized employment growth.

Employer Perceptions and Implementation of Commute Alternatives Strategies

Employer-based trip reduction (EBTR) strategies are the transportation demand management elements of commute options programs that target commute travel. This article reports the results of two surveys conducted in the Atlanta metropolitan area of implementation of EBTR strategies and employer perceptions of associated costs and benefits. On average, less than a quarter of the employers surveyed utilized EBTR strategies. Survey results indicate that employers commonly perceive that EBTR strategies provide minimal benefits for the company, that employers believe their employees lack interest in such measures, and that upper management does not provide support. Employers regard the distance between work location and transit as a significant barrier to implementing EBTR programs, and onsite sale of transit passes is associated with cost, equity, and operational concerns. However, members of transportation management associations and Atlanta’s Clean Air Campaign report higher levels of implementation.

Providing discounted transit passes to younger university students: Are there effects on public transit, car and active transportation trips to university?

Until 2017, only University students below 26 years old benefited from discounted transit passes in Montreal, Quebec. Some student transit discounts have previously been shown to reduce car trips and increase public transit use. However, their effects on active transportation (cycling and walking) are rarely assessed, nor is the use of an age restriction on transit pass discounts. Relationships between University students’ frequent commuting modes to campus and access to an age-based discounted transit pass are assessed using four logistic regressions. Estimated probabilities serve to plot age-based regression discontinuities. Overall, younger students with access to discounted transit passes used transit at higher rates and drove or used active modes at lower rates. However, relationships were not significant near the age threshold for pass access. The student discounted transit passes did not generate ridership benefits, partly because of students’ characteristics. On average, the youngest students lived more frequently at their parents and farther from campus, but had similar situations to older ones near the age threshold. This program had a very modest to null effect on transit use, partly due to its flexibility. The dominant policy objective of discount programs and fit with potential users should be closely examined when developing programs.

Food access, mobility, and transportation: a survey and key informant interviews of users of non-profit food hubs in the City of Vancouver before and during the COVID-19 crisis

BackgroundIn the City of Vancouver, Canada, non-profit food hubs such as food banks, neighbourhood houses, community centres, and soup kitchens serve communities that face food insecurity. Food that is available yet inaccessible cannot ensure urban food security. This study seeks to highlight food access challenges, especially in terms of mobility and transportation, faced by users of non-profit food hubs in the City of Vancouver before and during the COVID-19 crisis.MethodsThis study involved an online survey (n = 84) and semi-structured follow-up key informant interviews (n = 10) with individuals at least 19 years old who accessed food at a non-profit food hub located in the City of Vancouver more than once before and during the COVID-19 crisis.Results88.5% of survey respondents found food obtained from non-profit food hubs to be either very or somewhat important to their household’s overall diet. In their journey to access food at non-profit food hubs in the City of Vancouver, many survey respondents face barriers such as transportation distance/time, transportation inconveniences/reliability/accessibility, transportation costs, line-ups at non-profit food hubs, and schedules of non-profit food hubs. Comments from interview participants corroborate these barriers.ConclusionsDrawing from the findings, this study recommends that non-profit food hubs maintain a food delivery option and that the local transportation authority provides convenient and reliable paratransit service. Furthermore, this study recommends that the provincial government considers subsidizing transit passes for low-income households, that the provincial and/or federal governments consider bolstering existing government assistance programs, and that the federal government considers implementing a universal basic income. This study emphasizes how the current two-tier food system perpetuates stigma and harms the well-being of marginalized populations in the City of Vancouver in their journey to obtain food.

Simple pre-post analysis overestimates the impacts of new public transit services on ridership: Evidence from a quasi-experimental study of new bus rapid transit in Columbus, Ohio, USA

This paper empirically demonstrates the value of quasi-experimental study designs to evaluate the direct impacts of new public transit services on ridership within its corridor. Using a new bus rapid transit (BRT) service, CMAX, in Columbus, Ohio, USA, as an example, we compare its impact on ridership based on a pre-post and quasi-experimental analysis framework. We conduct the pre-post analysis using a ridership space-time cube exploring a massive Automatic Passenger Counter (APC) database. Differences in total passenger counts before and after the BRT intervention indicate a 36% increase in ridership within its corridor. However, this patronage increase may not be attributable solely to the new public transit service. Potential confounding effects include systemwide ridership trends and a new unlimited transit pass program for downtown workers. To address these issues, we adopt a quasi-experimental study design with a difference-in-differences (DiD) identification strategy. We use propensity score matching (PSM) to match a counterfactual control group with the treatment group when implementing DiD model. After accounting for confounding effects, we find a less than 5% increase but not statistically significant impacts of CMAX on ridership. Our results support the argument that a simple pre-post analysis ignoring confounding effects can lead to a misleading evaluation of a new public transit service’s direct impact on ridership.

What influences the substitution of ride-sourcing for public transit and taxi services in Toronto? An exploratory structural equation model-based study

The continued growth and utilization of ride-sourcing services have reshaped traditional perceptions of urban mobility. As the popularity of this relatively novel mode of travel has continued to grow, there has been a greater focus on the effect that the adoption and use of ride-sourcing have on the utilization of more traditional modes of transportation. With a few notable exceptions, prior studies on the topic often rely on descriptive statistics to understand the modes that are replaced by ride-sourcing for specific trips. This study utilizes structural equation models to investigate the factors influencing the decision to choose public transit and taxi as their so-called substitute alternative mode for a recent ride-sourcing trip, using data from a web-based survey of Toronto residents. The results indicate that socio-economic and trip-related attributes influence the selection of the substitute alternative mode, and to a lesser extent, attitudes toward ride-sourcing services. In particular, students, persons from lower-income households, and transit pass owners were found to be more likely to substitute ride-sourcing for public transit, while older respondents and persons from wealthier households were more likely to select taxi instead. The study outcomes shed light on the types of transit trips that are more likely to be replaced in favor of ride-sourcing services and the attributes of individuals who are more likely to make this replacement. This information can inform policies that aim to reduce the substitution of ride-sourcing for public transit, which can worsen both congestion and emissions.

Examining the influence of attitudinal factors on the use of ride-hailing services in Toronto

The continued growth of ride-hailing usage creates the need for policymakers to understand the factors that affect the adoption and utilization of ride-hailing services. Attitudinal and perceptual factors are of particular importance, both because ride-hailing services are still evolving, and a relatively small number of studies have examined the role of these factors. This paper utilizes data from a web-based survey to understand the role that latent attitudinal factors play in adopting and using ride-hailing services in Toronto. Specifically, two binary logistic regression models are used to understand the factors that influence the adoption of exclusive and shared ride-hailing services. Besides, a zero-inflated ordered probit (ZIOP) model is estimated to investigate the factors that affect the frequency with which a person uses ride-hailing. The empirical investigation reveals that the perception of ride-hailing services tends to differ between individuals with ride-hailing experience and those without, which is expected given the relative novelty of ride-hailing. The logistic regression models reveal that, although common attributes affect the likelihood that a person has adopted a ride-hailing service, the influence of these factors varies based on the specific type of service. This underscores the value of distinguishing between exclusive and shared ride-hailing services. The ZIOP model shows that attitudinal factors regarding qualitative trip characteristics, the inclination towards using ride-hailing services in certain situations, and the consideration of parking requirements affect the frequency with which a person uses ride-hailing. Also, transit pass ownership was found to influence the frequency with which a person uses ride-hailing positively. The results of this study aim to provide insights into the adoption and utilization of ride-hailing, which can help inform policies that aim to encourage the use of shared ride-hailing as an alternative to exclusive ride-hailing services.

Free Transit Passes and School Attendance among High School Students

In multiple U.S. cities, school districts and transit providers collaborate to provide students free public transit access, either replacing or supplementing the yellow school bus service. Although practitioners widely acknowledge these programs as a promising and innovative solution to absenteeism, there is no empirical research evidence to date confirming the benefits of these programs to individual students’ school attendance. We respond to this research gap by investigating the impacts of the Minneapolis Go-To Student Pass Program—a transportation program that began to provide student access to public transit in August 2013—on individual student school attendance. Using Poisson regression, we estimate both the traditional Difference-in-differences models and Two-Way Fixed Effects models to quantify effects of pass use and pass eligibility on student attendance. We find that student-reported pass use and pass eligibility reduce excused absences by 11.5% and 27.5%, respectively. Restricting our sample to students living in the School Walk Zone—the area within 2 mi of one’s school—we find that these effects are even more substantial, with pass use and pass eligibility reducing excused absences by 30.5% and 37.6% respectively. These findings imply that providing free access to public transit is broadly useful to improve student attendance, even for students who live within walking distance of the school and may not use transit passes regularly.

Correlates of active commuting, transport physical activity, and light rail use in a university setting

IntroductionThis study identified correlates of active commute mode, transport physical activity (TPA), and intention to use light rail transit (LRT) at a large university in advance of a new LRT connection to campus. MethodsStaff, faculty and students completed a campus-wide travel survey in 2017. Multivariable logistic and linear regression models assessed associations between individual, organizational and environmental correlates with outcomes of interest in a sample of 6894 respondents to identify factors that may encourage a shift from vehicle to active commute modes and increase TPA. ResultsThose who biked or walked to campus exceeded weekly physical activity recommendations in TPA alone. Commuting by transit was associated with higher levels of TPA, compared to vehicle commuting. Greater commute mode enjoyment was associated with active modes. Staff were least likely to commute via active transport (AT) and had fewer minutes of TPA. Women and Asian racial groups were less likely to report TPA. Rideshare and discounted transit pass use were positively associated with all outcomes. ConclusionsNew LRT presents a critical opportunity to achieve gains in both campus health and environmental sustainability. The factors identified in this study should be further explored as potential intervention or programmatic targets to encourage mode shift.

Ways of nutritional value increasing of distillary grain fiber

In the process of grain processing for ethyl alcohol, practically only carbohydrates are consumed, which are presented mainly in the form of starch. The remaining components (protein, fats, fiber, minerals) in transit pass into the grain fiber remaining after distillation of the alcohol from the mash. Distillery grain fiber surpasses wheat bran in its indicators, since during the processing it is enriched with biomass of alcohol yeast. In addition, there is a technological possibility of its additional enrichment with protein, amino acids, and vitamins due to changes in the modes of alcoholic fermentation. The aim of the work was to assess the influence of the mode and conditions of alcoholic fermentation on the composition of distillery grain fiber. Material and methods. Under laboratory conditions, samples of grain fiber of alcohol production were obtained by the method of fermentation samples from wheat under various fermentation conditions. In the obtained samples, the following parameters were determined: protein according to Barnstein, crude protein, vitamins B1, B2, B6, E, as well as the amino acid composition. The volume fraction of ethyl alcohol, the mass concentration of fermentable carbohydrates, and the concentration of yeast cells were determined in intermediate products of alcohol production. Results and discussion. Studies on the effect of yeast from various manufacturers on fermentation rates, biomass growth and grain fiber composition showed the advantage of race Y-717 in terms of alcohol accumulation (11.5% vol.), Fermentation rate (56 hours) and yeast cell concentration (260 million/cm3), which was 15-30% more than in other options. However, from the point of view of increasing the content of protein according to Barnstein and crude protein in samples of grain fiber with yeast Y-717, an increase of only 3-4% was noted compared with other options. This was associated with a decrease in the concentration of yeast by 72 h of fermentation due to autolysis. Studies on the influence of the initial yeast concentration on the growth of biomass, the fermentation rate and grain fiber indices showed that with an increase in the initial yeast concentration from 15 to 45 million/cm3, the fermentation time reduced to 48 h, the biomass growth at the end of fermentation was 20%, the protein in grain fiber increased by 15%, the content of vitamins B1, B2, B6 and E as well as amino acids increased by 13-17%. Conclusion. According to the results of the studies, the technological possibility of enriching distillery grain fiber with protein, amino acids, and vitamins due to a change in the fermentation process during the processing of grain raw materials to alcohol is shown. In particular, this could be achieved through the use of yeast with a high growth rate, by increasing the concentration of yeast biomass, shortening the fermentation period and preventing yeast autolysis at the maturation stage.