Abstract
Fare capping, a policy in which a transit agency caps the maximum amount a rider pays over a given period, has emerged as a relatively new innovation in public transit fare policy. This research aims to synthesize fare capping policies and to explore the benefits that riders could receive from fare capping. This study applied a multiple case study method to explore fare capping policies at the 101 largest transit agencies in the U.S.A. At least 21 of those 101 agencies were found to have fare capping policies. Of those 21 agencies, 20 used daily fare caps, four used weekly fare caps, and 14 used monthly fare caps. The number of one-way regular fare trips needed to reach the daily, weekly, and/or monthly cap was determined for each agency. Rider discounts for each fare capping period were then calculated. This study also discussed some innovative fare capping policies like “nested” fare capping, which refers to fare caps within fare caps, as well as capping for reduced fare policies. These unique policies could help to address some of the most pressing challenges that face the transit industry in promoting equity for vulnerable groups such as low-income, elderly, and disabled riders, and incentivizing riders to return to transit post-COVID. The findings of this study could inform transit agencies that are planning or considering the implementation of fare capping policies, a trend which has grown rapidly in the transit industry.
Fare capping, also known as earning a pass or pay as you go, can be defined as a policy in which a “transit agency caps the maximum amount a rider can pay in a given period,” typically using a contactless card or mobile application ( 1 ). This fare policy ensures that for the same set of trip patterns during the same time period, a rider who purchases many smaller-value tickets does not pay more than the cost of an equivalent period pass. For example, if an agency has a daily cap value of $4 and the price of a single fare is $2, a rider who purchases two single fares in a day would not be charged for additional trips made during that day because the fare cap has been met. Fare capping may also be applied to longer periods, such as a week or a month. Monthly fare capping may be particularly beneficial for frequent or transit-dependent riders for its ability to remove the requirement to pay a large upfront cost for a monthly pass.
Fare capping was first introduced in 2005 by Transport for London, but, as of 2021, adoption of this concept was relatively new in the U.S.A. (United States/U.S.) ( 2 ). To the best of the authors’ knowledge, some of the early adopters of daily fare capping in the United States include the Metropolitan Transit Authority of Harris County, Texas (Houston Metro), Alameda-Contra Costa Transit District (AC Transit), and Santa Clara Valley Transportation Authority while Portland’s Tri-County Metropolitan Transportation District of Oregon (TriMet) was the first to introduce monthly fare capping in 2017 (3, 4). Fare capping policies have continued to be introduced by a rapidly increasing number of transit agencies in the United States. At the time of this study, the implementation of fare capping appeared to be driven by three major motivating factors. The first was the recent maturation of technology to support fare capping; for example, contactless cards or mobile fare payment applications were increasingly used in account-based fare systems that could easily support fare capping. A second motivating factor was promoting equity for vulnerable groups such as low-income riders, the elderly, or riders with disabilities. These groups could be given the opportunity to obtain the benefits of a period pass without the burden of paying the large upfront cost for a weekly or a monthly pass. A third factor was potentially simplifying fares for riders; with fare capping, riders could be guaranteed the best fare based on their trip patterns without having to decide upfront to buy a pass or pay as they go (5, 6).
Since fare capping emerged as a trend in the United States, limited prior studies examining this topic have been completed. Therefore, this study aims to fill a gap in the literature by comparing examples of fare capping policies, estimating the potential rider discount of each fare capping policy, and identifying some innovative fare capping policies that promote equity and have the potential to help increase ridership during the country’s recovery from the COVID-19 pandemic.
The rest of this paper is organized as follows: first, a review of the prior studies about fare capping is discussed. Next, the research questions of this study are presented, and the multiple case study method used to conduct this analysis is described. Then, the results of this analysis are discussed. Finally, conclusions are presented in the last section of this paper.
Literature Review
Changes to fare policy in response to innovations in electronic payment methods and the need for equitable fare structures have been explored in numerous prior studies, with perhaps the most extensive references being those from the Transit Cooperative Research Program (TCRP) (1, 7–12). Despite this, there has been a limited discussion of fare capping as an emerging trend in fare policy in previous TCRP reports. However, at the time of this study, fare capping is the subject of an ongoing TCRP synthesis which aims to understand the motivations of transit agencies to implement fare capping, to assess its effects on revenue and ridership, and to identify the methods by which fare capping policies are assessed by transit agencies ( 13 ). Although this ongoing synthesis is very relevant, the focus is on the implementation, planning, and assessment of fare capping from the perspective of a transit agency.
While there have been limited studies of fare capping in the United States, several prior studies of fare capping policies outside of the United States have been conducted. One previous study proposed a fare engine for Transport for London that could simplify a rider’s experience by using fare capping to ensure the guaranteed best fare. The proposed fare engine model could track parallel fare scenarios for an unfolding trip pattern to eliminate instances where a rider might otherwise have been overcharged ( 5 ).
In another prior study presented at the Transit Data Conference in Paris in 2019, the change in revenue resulting from different fare capping periods was explored in three simulated scenarios using automated fare collection data for Montreal, Canada. The first simulated scenario was to implement only daily fare capping. The second was to implement both daily and weekly fare capping. The last scenario was to implement daily, weekly, and monthly fare capping. The results suggested that an increase in fare revenue could be expected (i.e., some riders would pay more with fare capping) in the first two scenarios with only daily or daily and weekly fare capping. The reason behind this unexpected result was the simulated scenarios replaced old fare passes (e.g., two-trip pass and 10-trip pass) that previously had large discounts; riders who made exactly two or 10 trips would not have benefited from fare capping because they would actually have paid more with fare capping. On the other hand, in the last scenario with daily, weekly, and monthly fare capping, the results suggested that the fare revenue would decrease because instances where riders may be overcharged would be eliminated. The study also concluded that a rider may be less incentivized to make additional trips before reaching the cap and more incentivized to make trips after reaching the cap ( 14 ).
In a particularly relevant study, an analysis of rider incentives in response to fare capping was conducted by researchers in Australia. First, the fare capping products offered in Australia and New Zealand were summarized. Out of 27 transit agencies, six agencies offered a daily cap, four agencies offered a weekly cap, and only one agency offered a monthly cap. Two types of fare capping were defined. The first was a trip-based cap, where a rider reached a fare cap based solely on the number of trips taken in a given time period. The second was a value-based cap, where a rider reached a fare cap based on the cumulative monetary value of trips taken in a given time period ( 6 ). Additionally, the study noted that in differentiated fare systems (e.g., time-variant and zonal fare systems), a rider’s discount for the same trip could vary based on the time of day and the order in which zones were traveled across (e.g., when a longer trip across zones was broken into many shorter trips). The type of fare capping offered also affected a rider’s discount; for example, when value-based fare capping was offered to riders in a distance-based fare system, riders who took longer trips could receive a higher discount than riders who took shorter trips. Therefore, different types of fare capping were found to result in different levels of discounts across rider groups. The findings suggest that when fare capping policies are in place, more trips may be taken by riders to reach the cap and benefit from “free” trips. It was also suggested that rider incentives to travel might be greater when fare caps are applied over shorter time periods because a smaller number of trips are required to reach a cap. The study concluded that there was a lack of documentation on the basic mechanism behind fare capping, but that fare capping could be useful to simplify fare structures from the perspective of a rider ( 6 ).
This summary of prior studies shows that although some documentation on fare capping exists, a systematic review of fare capping policies in the United States does not exist at the time of this study. Additionally, where the focus of prior studies has primarily been from the perspective of the transit agency, the focus of this study is on the potential benefits for a rider. Therefore, this research aims to fill gaps in the literature on fare capping policies in the United States, and the potential for fare capping to address some of the current ridership and equity challenges facing transit agencies.
Research Questions
This study seeks to answer the following research questions about fare capping policies:
How many transit agencies have implemented fare capping in the United States, and what types of fare capping (e.g., trip versus value, time period, etc.) have been implemented?
What is the estimated discount a rider receives from fare capping? How does this vary from agency to agency?
How could fare capping be used to incentivize riders to return to transit post-COVID? Can fare capping incentivize ridership for non-traditional commuters who work from home full- or part-time?
How could fare capping be used to provide savings to vulnerable groups such as those with low incomes, the elderly, and people with disabilies?
Method
A multiple case study was used to explore fare capping in the United States. The top 101 U.S. transit agencies, based on unlinked passenger trips in 2019 were considered. The 2019 unlinked passenger trip dataset was obtained from the National Transit Database (NTD), which has ridership data for all federally funded transit agencies in the United States ( 15 ). Fare capping policies at the largest 101 U.S. transit agencies were considered since these agencies are more likely to have implemented fare capping. The 101st agency, Greater Dayton Regional Transit Authority, was included because it had a fare capping policy.
To compile a list of fare capping policies at transit agencies in the United States, publicly available information sources were used, such as transit agency websites, press releases, public press, and agency reports. Existing fare capping policies were then categorized by the fare capping period, for example, daily, weekly, and monthly. Next, the potential savings of each fare capping program were estimated. Last, agencies with more innovative fare capping policies were further investigated to assess potential solutions for some of the ridership and equity challenges facing transit agencies.
Results and Discussion
The results of this analysis are presented in four parts. First, a preliminary synthesis and comparison of the current state of fare capping in the United States is presented. Second, the number of trips to reach a cap and the potential discounts for riders are explored. Third, agencies with multiple periods of fare capping are examined in more detail to estimate the number of trips to reach a cap and the potential rider discount more accurately. Last, two agencies with capping for reduced fare riders are discussed in detail.
Results Part 1: Synthesis and Comparison of Fare Capping in the United States
A synthesis and comparison of fare capping in the United States is presented in this section. As of September 2021, fare capping policies have been implemented by at least 21 of the 101 largest transit agencies. It is important to note that while this study was ongoing, additional agencies beyond the 21 discussed in this paper announced plans to pilot or implement fare capping policies in the near future, such as New York’s Metropolitan Transportation Authority and Nashville’s WeGo (16, 17).
A list of the 21 agencies and the types of fare capping policies implemented by each agency is summarized in Table 1. As shown in Table 1, daily fare capping was used by 20 of the 21 agencies (95%), monthly fare capping was used by 14 (67%), and weekly fare capping was used by only four (19%). Three of the 21 transit agencies had rolling fare capping periods, where the time period begins once the first purchase has been made. All other agencies had calendar-based fare capping periods, where the period starts over for all customers at a given time and on a given day, such as on the first day of each month.
Fare Capping Types in the United States
Note: A = mobile application, B = contactless bank card, C = transit agency card, W = mobile wallet, NA = not applicable.
Available only to seniors/people with a disability.
Available only to those with registered cards, that is, a card that is not anonymous and is linked to a personal account.
The type of fare media that facilitates fare capping is also described in Table 1. Of the 21 agencies, 20 offered transit agency (contactless) cards with fare capping, 15 offered mobile applications with fare capping, three agencies offered fare capping for riders who pay using a contactless bank card, and two offered fare capping for riders who pay using a mobile wallet.
It should be noted that all fare capping policies implemented by these 21 agencies were value-based caps. In general, the value of the fare caps was set equal to the equivalent period pass by most agencies. To the best of the authors’ knowledge, there were no trip-based fare capping policies in the United States as of September 2021. For a flat-fare system with only one fare capping period, there is no functional difference between a trip- and value-based cap; however, this is not the case for a distance-based system. For example, a long-distance commuter in a distance-based fare system may experience a greater discount than short-distance commuters when a value-based fare cap is in place because the distance traveled would no longer be a factor. Therefore, the level of discount from fare capping may be a function of the fare structure and type of fare capping used.
Results Part 2: Fare Capping Discounts for Riders
In this section, an analysis of the potential fare capping discounts for riders is presented, which is important to understand for two reasons. First, the trips to reach a cap may reveal which group of passengers would benefit most from each fare capping period and corresponding price. Second, the timing and value of the discount are helpful to determine the effectiveness of a fare capping policy to incentivize riders to use transit. For example, a rider may estimate their expected number of trips over a period of time to determine if they should buy a period pass. A commuter may be reluctant to buy a period pass if they have plans to take an out-of-town trip during that period of time. A city hosting a convention or sports event could have an influx of tourists who may be unfamiliar with and reluctant to use that city’s public transit. When fare capping policies are implemented, a rider may be drawn to the simplicity of guaranteed best fare and may choose public transit over other modes of transportation. Additionally, a rider may be incentivized to make more discretionary trips such as social trips or shopping just to reach a cap and receive “free trips,” especially when a shorter period fare cap is available. In the following section, the number of trips needed to reach a cap and the potential rider discount are estimated.
The number of trips needed to reach the daily, weekly, or monthly cap at each transit agency was calculated by dividing the period cap by the single fare and then rounding up to the nearest whole number, as shown in Table 2. For all but one agency, St. Louis Metro Transit, the number of trips needed to reach a daily cap ranged from two to three. These results suggested that a typical commuter who purchases only two one-way, regular fare tickets to get to and from work may not benefit from daily fare capping. However, for riders who take three or more trips in a day, especially transit-dependent riders who often use transit for frequent travel, daily fare capping policies may offer immediate and frequent discounts.
Summary of Daily, Weekly, and Monthly Fare Capping
This fare was the base fare for Metro bus. However, it should be noted that Metro was operating at reduced fare because of COVID-19 restrictions ( 39 ).
Greater Dayton Regional Transit Authority was offering promotional rates for fare capping. These rates are likely to change in the future ( 43 ).
Number of trips was rounded up.
Note: na = not applicable.
Table 2 also shows that the number of trips to reach the fare cap ranged from nine to 13 for weekly caps and from 20 to 56 for monthly caps. Because weekly fare capping existed at only four of the 21 agencies discussed in this study, few overarching patterns could be identified; therefore, weekly caps are not discussed in more detail in this paper. Of the 14 transit agencies that offered a monthly cap, riders at 13 agencies could reach a monthly cap by their 40th trip, assuming they had not reached any smaller period caps during that time period. Only the Regional Transit Service of Monroe County (Rochester, NY) fell outside of this range with a cap at the 56th trip. These findings suggested that, at most agencies with monthly fare caps, frequent riders who take at least 40 trips in a month (e.g., commuters who make one round trip every day for at least 20 days in a month) may benefit from monthly fare capping.
Next, the discount that a rider could have experienced based on a range of trips for each period was calculated using Equation 1, below. The discount was calculated by multiplying the cost of a single fare by the number of trips, subtracting the value of the fare cap, and dividing this difference by the cost of a single fare multiplied by the number of trips. The ratio was put into percent form, and the lower limit for this number was set at zero.
where
D = percent discount
N = number of trips
F = single fare ($)
C = fare cap ($).
The results for the percent discount from daily and monthly fare capping are visualized in Figures 1 and 2, respectively. Graphs for weekly fare capping were not included because of the limited use of such fares cap at the transit agencies in this study. In Figure 1, the daily fare cap is shown as a horizontal line, and the cumulative single fare intersects that line on the trip at which a rider reaches a daily cap. For 15 of the 20 agencies (75%) with daily fare capping, a rider reached a discount by their third trip. These results suggest that, for a transit-dependent rider, a tourist, or any rider who takes three or more trips in a single day, daily fare capping typically provided immediate discounts and an incentive to choose transit over other modes for subsequent trips. Therefore, daily fare capping policies could offer benefits for transit-dependent riders, tourists, and other frequent riders.
Daily fare capping rider savings and discount.
Monthly fare capping savings and discount.
In Figure 2, the cumulative uncapped single fare paid is shown along with the cumulative fare paid with a monthly fare cap. The point at which the two lines diverge is the number of trips to reach a monthly fare cap. The uncapped fare, capped fare, and percent discount are called out for the 42nd trip, which represents two trips per day for 21 days, or a typical commuter trip pattern for those who commute to a workplace. In this study, the average number of commuter trips in a month was assumed to be 42, or two daily trips over 21 days. However, this could range from 38 to 46 trips depending on the number of weekdays in a given month. Additionally, it should be noted that the graphs in Figure 2 require the assumption that no intermediate period caps are reached, for example, daily or weekly caps. It was found that when a rider could reach smaller period fare caps within larger period fare caps, the number of trips at which a rider reached a fare cap, as well as the percent discount a rider could receive, changed. This concept is discussed in the next section. Considering only monthly fare capping, riders at 13 of the 14 agencies received a monthly discount ranging from 4.8% to 52.4% on their 42nd trip. The exception to this trend was the Regional Transit Service of Monroe County in Rochester, NY; a rider at this agency did not receive a monthly discount from fare capping until they made their 56th single fare trip, assuming no more than three trips were taken in a single day.
Results Part 3: “Nested” Fare Capping or Fare Caps Within Fare Caps
In this section, transit agencies with more than one fare capping period are discussed. First, a summary of how fare capping affects a rider’s discount is presented. A policy having fare caps within fare caps, which is referred to as “nested” fare capping in this study, is the basis of this discussion. Next, a special case of nested fare capping at CTtransit, which may be particularly well-suited to incentivize ridership among the widest range of passenger groups, is examined.
Synthesis of “Nested” Fare Capping
Several of the transit agencies discussed in this study had more than one fare capping period; 15 out of 21 transit agencies had at least two fare capping periods, and four agencies had more than two fare capping periods. It was found that when multiple fare caps can apply within a given period of time, the number of trips a rider takes to reach the longest period fare cap can increase. For example, if a rider takes three trips per day for a week, and there is a daily cap equivalent to the value of two single fares and a weekly cap equivalent to the value of 10 single fares, it is not accurate to say that this rider will reach the weekly cap on their 10th trip. Because the rider earns one “free” trip per day, the actual number of trips taken before reaching the weekly fare cap would be 14 (10 paid trips plus four “free” trips). Although the rider took three trips on the first day, the rider still needs to pay for eight more trips. Every “free” trip taken does not count toward reaching the next cap, but the rider earns a discount after only a short period. Once the shorter period has concluded (e.g., the day is over), the discount is discontinued until another cap is reached; in this manner, a rider’s discount will increase and decrease according to the frequency of daily trips over a continuous period of time.
The concept of multiple fare caps that can apply within the same period of time is referred to as “nested” fare capping in this study. An overview of the agencies that have nested fare capping is provided in Table 3. The number of daily caps needed to reach a weekly and monthly cap and the number of weekly caps needed to reach a monthly cap was calculated by dividing the value of the longer period cap by the value of the shorter period cap. For agencies with more than two fare capping periods, the number of days of continuous travel required for each period cap was most precisely determined by dividing the value of the longest period cap by the value of the next-longest period cap. This was because at some transit agencies, it was not possible for a rider to reach a longer period cap without first reaching the shorter period caps. For example, at CTtransit, the value of 18 daily caps was equivalent to the value of a monthly cap, but a rider on CTtransit was not able to reach the monthly cap after only 18 days of at least twice daily, continuous travel. Because CTtransit also had other fare capping periods, the actual number of continuous days of travel required to reach the monthly fare cap was closer to the number of weekly fare caps multiplied by seven days (3.3 weekly caps × 7 days = 22.9 daily trips). By using a spreadsheet to model the exact fare paid over the course of a month for a given trip pattern (in this case, at least two daily trips every day for 31 days) the trip and day on which the monthly cap was reached was found to be the first trip of the 23rd day. A more detailed look at CTtransit’s nested fare capping policy is provided next.
Nested Fare Capping Results
Because this agency had weekly fare capping, this number may not be perfectly accurate.
This transit agency had monthly and annual fare capping periods. Note: na = not applicable.
CTtransit, a Special Case of Nested Fare Capping
In addition to daily, weekly, and monthly fare capping, CTtransit offered fare capping over three- and five-day periods. In summary, CTtransit’s Go CT Card had the option for fare caps over the periods of one, three, five, seven, and 31 consecutive days. The value of the fare caps was the same as the equivalent period pass as follows: one-day pass, $3.50; three-day pass, $8.75; five-day pass, $14; seven-day pass, $19.25; and 31-day pass, $63. CTtransit’s flexible fare capping policy was considered a nested fare capping policy because the longest period cap may have allowed for the application of shorter period caps simultaneously. For example, over the course of a week, a CTtransit rider who took at least two trips per day every day would have reached a daily fare cap on their second trip of days one, two, four, and six. Simultaneously, the same rider would have reached a three-day cap on their first trip of day three, a five-day cap on the first trip of day five, and a seven-day cap on their first trip of day seven. The more daily trips a rider took, the more their discount grew; however, when travel was not continuous, a rider started over with the shortest period fare cap and a lower “tier” of discount. Therefore, the discount on off-period days was lower than on period days, and a rider received the best discount when a fare cap was most tailored to their travel pattern. This phenomenon is visualized in three dimensions in Figure 3. The x-axis (horizontal) shows the number of daily trips, the y-axis (into the page) identifies the number of days of continuous travel, and the z-axis (vertical) shows the cumulative fare paid or cumulative percent discount.
Three-dimensional visualization of CTtransit’s “nested” fare capping mechanism over the period of a week: (a) cumulative uncapped fare, (b) cumulative capped fare, (c) cumulative discount (%).
This type of flexible time period in fare capping policies could be particularly relevant, since the COVID-19 pandemic has changed how some people commute. A recent Pew Research survey showed that, as of December 2020, 71% of workers with remote-capable jobs worked from home part- or full-time, and over half of those workers would like to continue working remotely after COVID-19 ( 53 ). Another recent study showed that transit ridership has decreased, particularly among middle-income households, as a result of the increased opportunity to work from home during the COVID-19 pandemic ( 54 ). It could be that many commuters’ travel patterns have been permanently altered because of the popularity of remote work. For those commuters who are able to work remotely only partially and may have irregular travel patterns, a nested fare cap with many shorter-duration fare capping periods could incentivize some riders to return to public transit. Additionally, nested fare capping could lead to the “gamification” of fares, wherein a rider may take additional trips just to reach the next fare capping period and therefore receive “free” trips. This incentive might not be achieved with daily or monthly fare capping periods alone. Nested fare capping can also be considered an equitable fare policy; a transit-dependent rider who cannot afford to buy a monthly period pass would not receive the same benefits of a monthly period pass from daily caps alone. By implementing both short-term and long-term periods of fare capping, a transit agency may incentivize ridership across a wider range of rider groups.
Results Part 4: Reduced Fare Policies With Fare Capping
This section briefly discusses two agencies with particularly equitable fare capping policies designed to provide extra benefits to vulnerable riders. Fare capping policies could provide the benefits of a period pass to riders who cannot afford a large upfront payment. When combined with a reduced fare program, fare capping could be leveraged to provide additional benefits to some vulnerable groups of riders such as low-income families, the elderly, and people with disabilities. Of the 14 transit agencies that offered monthly fare capping, 10 also offered reduced monthly fare capping. Many of these transit agencies provided proportionally reduced single fares and fare caps. For example, the Hillsborough Area Regional Transit Authority of Tampa, FL offered a reduced single fare ($1) and reduced monthly fare cap ($32.50) that were set to be half that of the regular single fare ($2) and regular monthly fare cap ($65). Because the reduction in the single fare and the value of the monthly cap was proportional, a reduced-fare rider would reach the monthly cap after the same number of trips as a regular-fare rider, and both regular-fare riders and reduced-fare riders would experience similar percent discounts for any number of trips. However, two transit agencies, the Tri-County Metropolitan Transportation District of Oregon (TriMet) and the City and County of Honolulu, had disproportionally reduced fare capping policies designed to offer deeper discounts to some groups of riders (55, 56). These disproportionally reduced fare capping policies are further discussed in this section.
TriMet offered a disproportionally reduced monthly fare cap for low-income riders, seniors over the age of 65, and those on Medicare or who have a disability ( 55 ). TriMet had a reduced single fare of $1.25 (half of the regular fare price of $2.50) and a reduced monthly cap of $28 (28% of the regular monthly fare cap of $100). The percent discount for TriMet’s reduced monthly fare cap was calculated using Equation 1 from Results Part 2 and is shown in Figure 4. Figure 4 shows that a reduced-fare rider could reach a monthly cap on their 23rd trip, whereas a regular-fare rider could reach a monthly cap on their 40th trip. Moreover, a typical TriMet commuter eligible for reduced fares could experience an approximately 47% discount on their 42nd monthly trip, which was substantially higher than a typical TriMet commuter paying regular fare who could save just about 5%.
Reduced monthly fare capping savings and discount, TriMet (top) and City and County of Honolulu (bottom).
Similarly, the City and County of Honolulu had a reduced single fare of $1 (about 36% of a regular fare price of $2.75) and a reduced monthly cap of $6 (less than 9% of the regular monthly fare cap of $70). The reduced fare was available to seniors over the age of 65 and people with disabilities ( 56 ). A reduced-fare rider could reach a monthly cap on their sixth trip, whereas a regular-fare rider could reach a monthly cap on their 26th trip. The percent discount was calculated using Equation 1. While a regular-fare rider could save 39.4% on their 42nd monthly trip, a reduced fare rider could save 85.7%, as shown in Figure 4.
The disproportionally reduced fare capping approach at these two agencies may be a particularly innovative way of ensuring equity in transit fares for vulnerable groups while also minimizing revenue loss for a transit agency. By offering a relatively higher discount to reduced-fare riders, these transit agencies may have protected the affordability of their services to vulnerable groups by allowing a reduced-fare rider to reach the fare cap with fewer trips. This disproportionally reduced fare capping approach could reduce the relatively higher fare burden felt by vulnerable groups with low incomes.
Conclusion and Areas for Future Research
This study explored fare capping policies implemented in the United States using a multiple case study method. The findings of this study showed that as of September 2021, fare capping policies had been adopted by at least 21 transit agencies out of the largest 101 transit agencies in the United States. Twenty of those 21 agencies offered daily fare capping. The findings of this study suggested that daily fare capping practices may not offer much, if any, discount for a typical commuter assumed to make only two transit trips per day. However, daily fare capping likely provides important discounts to transit-dependent riders, tourists, and other frequent riders. Another key finding was that 14 of the 21 agencies offered monthly fare capping, which typically resulted in a discount for regular commuters who made two trips on at least 20 weekdays per month. Additionally, more frequent riders received higher discounts, meaning fare capping may potentially incentivize additional trips.
This study also discussed how fare capping could be applied to help transit agencies address two of the most pressing challenges that face the industry: promoting equity and recovering ridership after the COVID-19 pandemic. First, reduced fare capping policies that offered higher discounts for specific groups of vulnerable riders like those with low incomes, people with disabilities, and the elderly could be applied by agencies to offer a more equitable transit fare policy while minimizing potential fare revenue loss. These policies have been adopted by TriMet and the City and County of Honolulu. Second, nested fare capping policies with flexible time periods could be adopted by transit agencies as an incentive for part-time commuters to return to transit as agencies explore different ways to increase ridership post-COVID. Nested fare capping with both short-term and long-term fare capping periods may also be implemented to incentivize ridership across the widest range of rider groups, including tourists, those who are transit-dependent, and choice riders who have the option to use transit to commute to work. CTtransit’s nested fare capping policy was further discussed as a special case of nested fare capping, which may be particularly well-suited to incentivize ridership among the widest range of passenger groups.
Finally, some noteworthy areas for future research have emerged from this study and are summarized in the following paragraphs. First, while this research considered only the top 101 largest transit agencies in the United States, smaller agencies have implemented or are planning to implement fare capping policies, particularly via mobile fare payment applications. For example, many smaller agencies using the new Umo mobile app launched fare capping policies in 2021 ( 57 ). As more fare capping policies are implemented, more data may become available to explore the effect of fare capping on rider behavior and the perceived benefits of fare capping. Another area for future research pertains to reduced fare capping and its effectiveness to improve transit equity, as well as potential barriers for vulnerable riders to access fare capping (e.g., the need for a mobile device or credit/debit card). Future studies could also explore whether transit agencies should continue offering period passes alongside fare capping. In cases where a fare cap was set to be equivalent to the price of a pre-existing period pass, some transit agencies have discontinued the equivalent period pass after implementing fare capping.
While many agencies could be motivated to adopt fare capping policies, a major area of concern for transit agencies considering fare capping is the potential to lose revenue. Some transit agencies have estimated the amount of revenue loss they may expect from implementing fare capping policies. TriMet estimated that the introduction of fare capping would result in a 1% to 1.5% reduction in fare revenue. However, it was also believed that there would be a reduction in fare evasion ( 52 ). The Pinellas Suncoast Transit Authority estimated a revenue loss of $305,000 per year, but also expected $175,000 in savings from decreased operational costs ( 48 ). The San Diego Metropolitan Transit System predicted a revenue loss of $2–$5 million and considered increasing the single fare by 25 cents and paratransit fare by 50 cents ( 58 ). Future research should also analyze the revenue impacts after the implementation of fare capping.
One last area for future research is to examine in more detail the potential rider benefits and agency incentives to introduce fare capping in zone-based or distance-based fare systems, which are used mainly on commuter rail and some heavy rail systems in the United States. Monterey-Salinas Transit in California is an example of an agency that has a value-based cap and a distance-based fare system. Agencies with fare capping policies like that at Monterey-Salinas Transit could be explored to provide insights on implementing fare capping in a distance-based fare system and its impacts on revenue ( 59 ). These areas for additional research can help transit agencies considering or planning for the implementation of fare capping policies in the future.
Footnotes
Author Contributions
The authors confirm contribution to the paper as follows: study conception and design: A. Hightower, A. Ziedan, C. Brakewood; data collection: A. Hightower, A. Ziedan; analysis and interpretation of results: A. Hightower, A. Ziedan, C. Brakewood; draft manuscript preparation: A. Hightower, A. Ziedan, C. Crossland, C. Brakewood. All authors reviewed the results and approved the final version of the manuscript.
Declaration of Conflicting Interests
The author(s) declared no potential conflicts of interest with respect to the research, authorship, and/or publication of this article.
Funding
The author(s) disclosed receipt of the following financial support for the research, authorship, and/or publication of this article: This work was supported by the Transit-Serving Communities Optimally, Responsively, and Efficiently (T-SCORE) University Transportation Center Grant No. 69A3552047141 and with matching funds from the University of Tennessee, Knoxville (UTK).
