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Business Models for Mobile Fare Apps (2020)

Chapter: Chapter 2 - Literature Review

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Suggested Citation:"Chapter 2 - Literature Review." National Academies of Sciences, Engineering, and Medicine. 2020. Business Models for Mobile Fare Apps. Washington, DC: The National Academies Press. doi: 10.17226/25798.
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Suggested Citation:"Chapter 2 - Literature Review." National Academies of Sciences, Engineering, and Medicine. 2020. Business Models for Mobile Fare Apps. Washington, DC: The National Academies Press. doi: 10.17226/25798.
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Suggested Citation:"Chapter 2 - Literature Review." National Academies of Sciences, Engineering, and Medicine. 2020. Business Models for Mobile Fare Apps. Washington, DC: The National Academies Press. doi: 10.17226/25798.
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Suggested Citation:"Chapter 2 - Literature Review." National Academies of Sciences, Engineering, and Medicine. 2020. Business Models for Mobile Fare Apps. Washington, DC: The National Academies Press. doi: 10.17226/25798.
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Suggested Citation:"Chapter 2 - Literature Review." National Academies of Sciences, Engineering, and Medicine. 2020. Business Models for Mobile Fare Apps. Washington, DC: The National Academies Press. doi: 10.17226/25798.
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Suggested Citation:"Chapter 2 - Literature Review." National Academies of Sciences, Engineering, and Medicine. 2020. Business Models for Mobile Fare Apps. Washington, DC: The National Academies Press. doi: 10.17226/25798.
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Suggested Citation:"Chapter 2 - Literature Review." National Academies of Sciences, Engineering, and Medicine. 2020. Business Models for Mobile Fare Apps. Washington, DC: The National Academies Press. doi: 10.17226/25798.
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Suggested Citation:"Chapter 2 - Literature Review." National Academies of Sciences, Engineering, and Medicine. 2020. Business Models for Mobile Fare Apps. Washington, DC: The National Academies Press. doi: 10.17226/25798.
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8 Literature Review This chapter presents a review of relevant literature pertaining to transit fare pay- ment technology, particularly mobile fare payment apps and is organized in two sections. The first section reviews prior studies from TCRP. This section briefly summarizes older TCRP reports that provided important background information on transit fare policy and technology and presents more detailed summaries of two recent TCRP studies that focused on new fare payment technologies. The second section summarizes academic papers, conference proceedings, and university reports specifically pertaining to mobile fare payment apps. Prior Research from the Transit Cooperative Research Program This section summarizes relevant prior research on fare policy and fare payment technologies from TCRP. Over the last 25 years, numer- ous TCRP studies have explored fare system trends and technologies. Related TCRP studies are shown in the List of Related TCRP Studies textbox chronologically. The first three studies provided important background information on fare policy and widely used fare tech- nologies, and each is briefly summarized in this section. The fourth and fifth studies shown in the textbox (TCRP Report 177 and TCRP Synthesis 125) are particularly relevant to this report because they included significant discussion of mobile technologies that can be used for fare payment. These two studies are summarized in more detail because of their relevance. The sixth study on multimodal fare pay- ments was conducted in parallel to this study and, because of the con- current time frame, it is not summarized. TCRP Report 10: Fare Policies, Structures, and Technologies reviewed fare policy, fare structure, and fare technology options used by transit agencies (Fleishman et al., 1996). A framework with three key compo- nents was set forth. 1. Fare Policy: This is the principles, goals, and constraints on setting and collecting fares. 2. Fare Strategy: This is the general fare collection and payment structure approach, such as flat fares or differential pricing. 3. Fare Structure: This is the combination of one or more fare strategies with specific fare levels. C H A P T E R 2 List of Related TCRP Studies • 1996 TCRP Report 10: Fare Policies, Structures, and Technologies • 1998 TCRP Report 32: Multipurpose Transit Payment Media • 2003 TCRP Report 94: Fare Policies, Structures, and Technologies: Update • 2015 TCRP Report 177: Preliminary Strategic Analysis of Next Generation Fare Payment Systems for Public Transportation • 2017 TCRP Synthesis 125: Multiagency Electronic Fare Payment Systems • 2020 TCRP Synthesis 144: Multimodal Fare Payment Integration

Literature Review 9 TCRP Report 32: Multipurpose Transit Payment Media studied advances in payment technology, particularly smart cards, that enabled fare media to be used on multiple transit systems or for nontransit functions (Fleishman et al., 1998). Two different environments for multipurpose fare media were identified, which are open or closed (see textbox). Five important issues to consider when establishing a multipurpose program were identified (1) institutional and financial, (2) legal and regulatory, (3) operational and administrative, (4) tech- nological, and (5) customer related. As the name implies, TCRP Report 94: Fare Policies, Structures, and Technologies: Update updated TCRP Report 10 (Multisystems, Inc. et al., 2003). In this report, the key parameters of a fare system (policy, structure, and technology) were discussed in detail, and their inter- relationships were identified. These three key parameters can be summarized as follows: 1. Fare Policy: In a similar manner to TCRP Report 10, the fare policy was said to establish principles and goals underlying and guiding a transit agency’s pricing-related decisions. 2. Fare Structure: This was divided into three components, as follows: a. Fare Strategy: This included the general approach for the base fare (e.g., flat fare versus differentiated fare) and the transfer policy. b. Payment Options: These were the different forms of payment, such as period passes or multiride tickets. Payment options will be referred to as fare products in the following report. c. Pricing Levels: These were the actual pricing levels that transit riders pay. 3. Technology: This was divided into two components, as follows: a. Type of Fare Collection: This referred to the manner in which fares were validated or inspected (e.g., barriers, conductor validated, etc.). b. Fare Media: This was the instrument used for payment, such as tokens, magnetic stripe cards, or smart cards. TCRP Report 177: Preliminary Strategic Analysis of Next Generation Fare Payment Systems for Public Transportation included a detailed summary of new and emerging technologies that were being used in transit fare payment systems (Wallischeck et al., 2015). The authors presented a framework for transit fare payment design at the system level and identified the following four key design attributes. They are (1) single versus multiple transit agency operating environ- ment, (2) proprietary fare payment systems versus standards-based systems complying with data and technology specification used by the financial payments industry, (3) closed payment systems versus open payment systems, and (4) card-based versus account-based systems. The last two attributes are particularly relevant to this report, and more details are provided in the textbox to the right. In TCRP Report 177, the authors also identified four types of mobile technologies that can be used for fare payment and validation, which are described below. • Type 1: Flash Pass and QR Barcodes Flash pass systems use smartphone apps to emulate paper tickets. When a passenger boards a transit vehicle, the smartphone screen displaying the ticket is presented to the operator or conductor for Closed Environment: A “transit-only” payment program, which could be one or more transit agencies that issue and/or accept the fare media. Open Environment: A broader program in which the transit agency accepts media issued by one or more nontransit entities, such as a bank or a university. Open Payment System: A fare payment system that can accept third-party payment media, such as bankcards. Open industry interface standards and specifications are often used. Account-based System: Transit fare payment system in which the fare medium associates the transit rider with information held in an account. Fare value is not carried on the fare medium, which is typical of card-based systems, but rather, it is saved in a separate account. Fare processing is typically performed in the transit system’s back office.

10 Business Models for Mobile Fare Apps visual validation, as is typical of “flash pass” fare collection systems. The ticket screen typically contains dynamic security features such as a moving animation, a countdown, or a changing “color of the day” to prevent users from creating fraudulent electronic tickets through screen- shots or other means. It may also be accompanied by a machine-readable two-dimensional QR barcode, which can be scanned by a handheld validator or smartphone. This type of mobile fare payment technology is now widely used in the United States (Ali et al., 2017; Sion et al., 2016). • Type 2: Near Field Communication Near field communication (NFC) utilizes radio frequency communication to exchange data over short distances. When used for transit fare collection, an NFC chip in a phone can be “tapped” by transit users at fare gates or other readers. One method of using NFC payments on transit systems is with products such as Apple Pay, Google Pay, and Samsung Pay. • Type 3: Short Message Service Short message service (SMS) can be used to deliver transit tickets to cell phones via text message. In this model, transit users send a text message to the transit agency that replies with a code for a particular fare type. The SMS ticket can then be presented to inspectors or conductors for visual validation. While this model is used in numerous European cities (Apanasevic and Markendahl, 2017; Apanasevic and Markendahl, 2018), it is not common in the United States. • Type 4: Passive Mobile Technology The last type of mobile payment uses technologies such as Bluetooth Smart or Bluetooth Low Energy to enable passive interaction between a transit user’s smartphone and a fare reader. It is referred to as passive technology because users do not have to physically interact with their phones to make a payment. This type of mobile technology has not yet been widely deployed in the United States; there are some limited deployments in Europe. The authors of TCRP Report 177 also presented a detailed comparison of these four mobile fare payment technologies, which is shown in Table 1. The second recent related TCRP publication is TCRP Synthesis 125: Multiagency Electronic Fare Payment Systems (Okunieff, 2017). This study focused on new electronic fare payment systems for multimodal and multiagency environments. When presenting an overview of the industry, the author found that mobile fare payment apps (i.e., mobile ticketing apps) were being deployed by many transit agencies, and at the time of writing, at least 21 agencies in the United States had deployed a mobile fare payment app. TCRP Synthesis 125 also built on the new fare payment system framework developed in TCRP Report 177 and identified three different types of account-based fare payment systems. These three models are described in detail below, and the first two are particularly relevant to this report because they include forms of mobile technology used for fare payment. • Model 1: Open Design and Open Payment Architecture— Open and Mobile Payments The first model is described as being open design or technology because it uses the same types of readers as retail locations. The payment system uses banking standards and requires connectivity to a bank network for authentication and authorization of payments. Typically, open payment systems accept contactless bankcards, such as MasterCard PayPass or Visa PayWave. Fare payment can also be done using mobile devices in a similar manner, except that the card message format is emulated using NFC. Typically, this will use Apple Pay, Android Pay, Samsung Pay, or another form of a mobile wallet (Okunieff, 2017). Mobile Wallet: An application that stores payment card information on a mobile device and can be used to make purchases. Examples include Apple Pay, Google Pay, and Samsung Pay.

Literature Review 11 • Model 2: Open Design and Closed Payment Architecture— Mobile Ticketing The second model includes account-based systems that are open in design or technology, closed in payment architecture, and are used for mobile fare payment apps. A mobile fare payment app system is account based and requires a user to register a device and payment method to purchase fare products (Okunieff, 2017). • Model 3: Open Design and Closed Payment Architecture— Use of Other Credentials The third model includes account-based systems that are open in design or technology, closed in payment architecture, and use some other form of credentials. This could include student cards, Scope Efficiency Penetration Technical Maturity Flash Pass and Barcode •Flash pass cannot be used at fare gates or barriers; this hinders integration in a fully gated system. •Barcodes allow use at fare gates or barriers, but require readers. •Customers can buy tickets online or print tickets at home. •Minimal productivity improvements in systems with 100% visual inspection, since the same level of staffing is required. •Can be used by any passenger with a smartphone. •Mature, with many operational systems in the United States and internationally. Near Field Communication (NFC) Enabled Devices •Can be used in gated and ungated systems. •Enables integration across transit modes and operators. •Can support visual inspection when paired with a mobile fare payment app. •Supports validators and self-service devices at ungated stations. •May increase efficiency by reducing inspection labor. •Market penetration not yet sufficient to be the primary mobile payment technology, but NFC-enabled devices are increasing in adoption. •Not all carriers may offer NFC-enabled phones at this time. •Secure element technologies (device, cloud, etc.) are mature. SMS/Text Message (Visual) •Cannot be used at fare gates or barriers, which limits integration in gated systems. •Same as flash pass (see above). •Can be used by any passenger with a cell phone, including nonsmartphones. •Technically mature, with several operational systems, primarily internationally. Passive Ticketing (Bluetooth) •Can be used in gated and ungated systems. •Enables integration across transit modes and operators. •Can support visual inspection as needed. •Supports validators and self-service devices at ungated stations. •May increase efficiency by reducing inspection labor. •Requires prior set up and configuration by rider to allow passive (Source: Adapted from Wallischeck et al., 2015) interaction. •Not sufficient to be the primarily mobile payment technology. •Only some riders may elect to allow passive interaction. •Not technically mature, with limited number of systems under development. Table 1. Comparison of mobile fare payment technologies. Mobile Fare Payment App (or Mobile Ticketing App) is a software application on a smartphone or other similar elec- tronic device that allows transit riders to pay for and access public transit services. Mobile fare payment apps are typically downloaded from Google Play for Android devices or the Apple App Store for iOS devices.

12 Business Models for Mobile Fare Apps wearables that support Bluetooth Low Energy, chip-based government or work-issued identification cards, or possibly even personal biometrics. Before proceeding, one important clarification should be made: this research focuses specifically on mobile fare payment apps and does not include other forms of mobile payment that could be used for transit fare payment (as discussed in both TCRP Report 177 and TCRP Synthesis 125). As previously defined, a mobile fare payment app is a software application specifically designed for transit riders to pay for and access transit services, and it is down- loaded from the operating system provider (e.g., Apple’s App Store). This document does not focus on forms of mobile payment such as using a mobile wallet to pay the base fare in open payment fare systems, since this can be done without a mobile fare payment app. The remainder of the literature review and the analysis that follows focus specifically on mobile fare payment apps. Chronological Summary of Prior References on Mobile Fare Payment Apps Beyond TCRP, there are numerous journal articles, conference proceedings, and university reports pertaining to mobile fare payment apps. These studies are summarized chrono- logically in the following paragraphs. Before continuing, it should be noted that this report synthesizes trends in the United States and Canada and, therefore, the following literature review focuses on publications from North America. However, there are also numerous international publications on mobile fare payments, particularly from Europe (e.g., Apanasevic and Markendahl, 2017; Apanasevic and Markendahl, 2018; Di Pietro et al., 2015; Ferreira et al., 2017; Fontes et al., 2017). Interested readers can find citation infor mation for these international publications in the References at the end of this report. Studies Published in 2014 One of the early academic studies on mobile fare payment apps in the United States was conducted by Brakewood et al. (2014) to evaluate potential future adoption by riders prior to availability of mobile fare payment apps on the commuter railroad in the Boston metropolitan region. The authors conducted an onboard survey of two commuter railroad lines and found that riders have high levels of technology use, with approximately 76% using smartphones and 50% making mobile purchases at other merchants. Survey partici- pants were also asked a stated preference question about how likely they would be to use their smartphone to purchase a commuter rail ticket, and this was used in a logit model to forecast adoption throughout the commuter rail system. The results revealed that approximately 26% of commuter rail riders in the Boston region were very likely to adopt mobile fare payment apps. Perhaps the most relevant prior reference is a conference paper presented at the 2014 APTA Rail Conference that focused specifically on business models used in mobile fare payment app partnerships (Bernstein, 2014). The author identified three models that differed in terms of app development and hosting: (1) in-house development and hosting, (2) outsourced developing and in-house hosting, and (3) outsourced development and hosting. These models are described in more detail in Figure 2. It is important to note that when this report was written, only a handful of transit agencies had launched mobile fare payment apps within the United States and Canada. Since then, more than 100 transit providers have deployed mobile fare payment apps in either pilot programs or permanent deployments.

Literature Review 13 Studies Published in 2015 The Federal Reserve Bank of Boston (Tavilla, 2015) published an early study summarizing the state of consumer experience with and adoption of transit mobile fare payment apps. The author conducted interviews with 16 executives from transit agencies, system integrators, and companies with mobile platforms. The author considered both transit open payment systems, including those with NFC-enabled mobile payments, and mobile fare payment apps with visual and QR Code validation. The author concluded that broader availability of NFC-enabled phones, mobile wallets, and contactless payments will increase awareness and adoption of mobile fare payments in transit. Additionally, fare payment apps with visual and QR Code validation are a good introduction to mobile payment fare payment apps for transit agencies and their customers. Studies Published in 2016 Another early study was conducted in Nassau County, which is on Long Island outside of New York City (Sion et al., 2016). During the planning stages prior to deployment of a mobile fare payment app, the authors aimed to understand adoption of smartphones and credit and debit cards by riders on the Nassau Inter-County Express bus system, since smartphones and some form of electronic payment are typically needed to utilize a mobile fare payment app. Two rider surveys were conducted, and the authors concluded that younger riders were more likely to have smartphones, whereas older, more affluent riders were more likely to have credit and debit cards. A stated preference survey question asked riders about potential adoption of a mobile fare payment app, and the results revealed that younger riders were likely to be early adopters. A second study published in 2016 analyzed anonymized mobile fare payment app data from the East River Ferry service operated by NY Waterway in the New York City region (Rahman et al., 2016). Similar to automated fare collection systems, such as smart cards, mobile fare payment apps could collect data about passenger travel patterns. The mobile fare payment app evaluated in this study prompted riders to enter their origin and destination during the purchase and activation phases (shown in Figure 3). The mobile fare payment activation data on origin-destination patterns were compared to a recent onboard travel survey, and the results revealed that during peak periods, the mobile fare payment data closely aligned with survey data. However, in the off-peak periods and on weekends, the two data sources had greater differences. The authors concluded that mobile fare payment apps have the potential to Model 1: In-House Development and Hosting •The “do-it-yourself” model in which all costs and risks are borne by the transit providers. •Development of the mobile fare payment app is done by internal IT staff and integrated into the existing back-office system. Model 2: Outsourced Development; In-House Hosting •A hybrid model in which development is done by a third-party company, typically via a fixed fee arrangement. •The transit provider is responsible for hosting the app, but the third- party developer would continue to maintain the app via some contractual arrangement. Model 3: Outsourced Development and Hosting •The app vendor configures or customizes a preexisting mobile fare payment platform, which could include some sort of upfront development costs paid by the transit provider. •The primary means of compensation for the vendor are via a revenue sharing agreement. Figure 2. Mobile fare payment app business models identified by Bernstein (2014).

14 Business Models for Mobile Fare Apps generate large quantities of data about where and when passengers are traveling, which can be used for transportation planning. Beginning in 2016, a two-part study was performed to evaluate the efficacy of deploying mobile fare payment apps at a transit agency in Florida. In the first phase of the project, a frame- work for implementation was developed by first conducting an industry scan and then drafting a concept of operations for deploying a mobile fare payment app (Georggi et al., 2016). The second phase of the project evaluated a 7-month public field test of a mobile fare payment app in Tallahassee, Florida (Hendricks et al., 2018). Bus riders were recruited to use the app and were asked to complete online surveys before and after using the app. Bus drivers were also asked to complete a survey evaluating the mobile fare payment app. The results revealed that, overall, satisfaction levels were high with the fare payment app. Studies Published in 2017 Two studies were published in 2017 that focused on the mobile fare payment app from NJ TRANSIT (Bartin et al., 2017; Brakewood and Paaswell, 2017). The first study developed a four-step framework to evaluate mobile fare payment apps to detect and fix usability problems prior to implementation (Bartin et al., 2017). The proposed framework included (1) alpha tests by a small number of participants in a laboratory setting, (2) beta tests by a small number of users in the field, (3) pilot test in the field, and (4) a systemwide evaluation. The first three stages of this framework were then applied to evaluate NJ TRANSIT’s new mobile fare payment application, and the authors concluded that overall, the app performed in satisfactory manner. The second study of NJ TRANSIT’s mobile fare payment app considered potential new features in the app after deployment (Brakewood and Paaswell, 2017). Because most smart- phones are equipped with technology that can determine a user’s location, the study aimed to assess receptiveness to providing customized information to passengers based on their location, Figure 3. Screenshots of NY Waterway app showing origin and destination selection (Source: Rahman et al., 2016).

Literature Review 15 which is referred to as geotargeting. Focus groups and an online survey of app users were conducted, and the results revealed that most app users found it acceptable for NJ TRANSIT’s app to detect their location. The most desired potential feature was targeted transit service alerts. Another study published in 2017 compared mobile fare payment apps and their features in five regions: Portland, Boston, Austin, Chicago, and New Jersey (Ali et al., 2017). The authors downloaded the publicly available apps from the transit agencies in these regions and compared them along various dimensions, including features in the apps and use of location services. The authors concluded that the common features beyond ticketing in the apps are trip planners, real-time vehicle location information, and transit service alerts. The authors also found that most transit payment apps use the location services in the user’s smartphone, which is primarily to assist riders in finding nearby stops or stations for these features. Studies Published in 2018 A paper by Mesoraca and Brakewood (2018) synthesized the state of mobile fare payment apps in the commuter railroad industry by downloading and comparing apps from 14 large commuter rail operators. The authors’ analysis revealed that all of the mobile fare payment apps used visual inspection for validation, and some of them additionally had QR barcodes for validation. The fare policies offered through these apps were also compared, and the findings revealed that most commuter rail operators offered the majority of fare products in their mobile fare payment apps. However, the authors found that only a handful had fully integrated transfer policies between commuter rail and other nearby transit modes using mobile fare payments, which is an area that the authors identified for further study. Chapter Summary and Next Steps In this chapter, relevant literature pertaining to transit fare payment technology—particularly mobile fare payment apps—was reviewed. In the first section, five prior studies from TCRP were summarized to provide background information on transit fare policies and new fare payment technologies. The second section summarized numerous academic papers, conference proceedings, and university reports specifically pertaining to mobile fare payment apps. This prior research sets the stage for the following investigation of business models and approaches to implementing mobile fare payment apps. The following synthesis builds upon this prior research and focuses on the rapid changes that have occurred in the mobile app space in the 5 years prior to this study. Over 100 transit providers in the United States and Canada have deployed mobile fare payment apps in either pilot programs or permanent deployments, and the survey discussed in the following chapter aims to capture new trends in the industry.

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Five different business models for mobile fare payment apps are examined, as the world of apps used by transit agencies in the United States and Canada continues to steadily grow.

The TRB Transit Cooperative Research Program's TCRP Synthesis 148: Business Models for Mobile Fare Apps documents current practices and experiences of transit agencies that offer mobile fare payment applications to transit riders.

The report includes case examples from six cities: Santa Monica, Denver, Austin, Chicago, Dallas, and Ontario, Canada.

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