Elements Needed to Create High-Ridership Transit Systems: Interim Guidebook (2005)

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TCRP H-32: Interim Guidebook 3-1 3. Identification of Service Needs and Opportunities Introduction In addition to understanding the relative impacts of external and internal factors, selecting appropriate strategies aimed at attracting and/or retaining riders requires: • Identifying service needs and opportunities; this includes determining gaps/deficiencies in existing services, as well as assessing the nature of unmet needs and potential markets for transit service. • Identifying strategies that efficiently and effectively address the needs of one or more market segments, address gaps in existing service and are appropriate to particular service environments. The first of these steps is discussed below; the second step is addressed in the next chapter. Evaluation of Existing Services The basic elements in identifying the nature of service needs and opportunities in a region are (1) evaluation of the existing service network – as well as the supporting marketing program, information system and fare system -- to identify gaps/deficiencies/opportunities; and (2) development of an understanding of the characteristics and service needs of different market segments. Changes in a region’s development patterns, population characteristics and economic conditions can often result in significant gaps or inefficiencies in the existing transit network – and can also create new service opportunities. The increasing dispersion of population and employment centers in particular has produced new travel patterns in most regions that are typically not well-served by CBD-oriented transit routes. An agency’s marketing, information, and/or fare systems may similarly be insufficient to effectively support the region’s needs. The first step in seeking to boost ridership should therefore be to evaluate the current service design and route performance; the agency should then assess the effectiveness of the existing marketing, information and/or fare collection programs. Service Evaluation An agency can follow one of several approaches to evaluating its service, including:

TCRP H-32: Interim Guidebook 3-2 • Ongoing or periodic monitoring of route performance, with detailed evaluation of individual routes deemed to fall below defined service standards • Evaluation of all routes (e.g., a comprehensive operational analysis or service restructuring study) • Evaluation of a particular type of service (e.g., express routes) or routes within a particular corridor (i.e., as part of an alternatives analysis or corridor study aimed at considering the need/potential for a higher capacity service such as rail or BRT) A detailed service evaluation process typically includes the following steps: Ridership Data Collection -- There are several different methods and tools for collecting ridership data; the basic methods/tools are as follows: • Manual boarding/alighting counts or ridechecks – Agency “checkers” (or outside contractors) observe and count riders on individual routes. Counts can either be done at stops (as riders get on or off vehicles), on-board (which more easily allows load counts as well as boarding and alighting counts), or even in a trailing automobile. Ridership information may be recorded manually or via specially-programmed handheld units. Counts are most often done on a sample of trips for each route, although in some cases an agency may opt for collecting data on all trips for a particular day(s). • Automated passenger counts – Agencies are increasingly using automated passenger counters (APCs) installed on buses to collect ridership data. APCs can be integrated with automated vehicle location (AVL) systems to link counts to the location of the vehicle. • Farebox data – Agencies that have electronic registering fareboxes can also use fare payment data for ridership information separated by type of fare payment (including incidence of transfers). However, this data tends to be less reliable than that collected by other means, as the quality of the data tends to vary somewhat depending on the conscientiousness of individual drivers. Automated fare collection can improve the reliability of the data, especially if no driver action is required to record each fare category. The particular method an agency uses will depend on the resources available (i.e., the existence of APCs and/or registering fareboxes, and the number of checkers or the budget available for hiring data collection contractors). The method chosen may also depend on the intended usage of the data (e.g., for

TCRP H-32: Interim Guidebook 3-3 evaluating route-level performance or for reporting systemwide ridership to the National Transit Database). Classification of Routes – Because individual routes perform different functions and serve different geographic areas, it is generally inappropriate to apply one set of standards to all routes. Thus, the first step in developing a series of route evaluation measures is to create a system of route classification – recognizing that many routes will not fall neatly into one class because they serve dual or multiple functions. An example of a route classification scheme is as follows:1 • Radial line haul • Express • Commuter • Urban circulator • Urban crosstown • Urban feeder/distributor • Suburban local • Suburban circumferential • Suburban feeder/distributor Development of Route Evaluation Measures – Route evaluation measures are often placed into two basic categories: • Design measures – These measures concern where bus routes ought to be operated and what the service characteristics of those routes should be. Typical examples include: o Coverage – This measure applies to the whole system, rather than to individual routes, and serves to set the recommended spacing between routes for varying densities. For example, for high density residential areas with at least 3 households per acre, an agency could decide that 90% of households should be within one quarter mile of a bus route, while, for medium-density suburban areas (e.g., 2-3 households per acre), 80% of households should be within one quarter mile of a bus route. o Span of service – This measure addresses how many days per week, and how long on each day, service should be provided. An example of proposed span of service guidelines for a transit system with the above route classification scheme is as follows (Table 3-1). 1 TranSystems Corp. et al., WMATA Regional Bus Study – Comprehensive Operational Analysis Summary Report (February 2001), prepared for Washington Metropolitan Area Transit Authority, p. 3.

TCRP H-32: Interim Guidebook 3-4 Table 3-1: Example, Span of Service Measures Type of Service First AM arrival not later than Last AM arrival not earlier than First PM departure not later than Last PM departure not earlier than Radial line haul—Urban 7:00 N/A N/A 22:00 Radial line haul—Suburban 7:00 N/A N/A 20:00 Commuter 7:00 9:00 16:00 18:30 Express 7:00 9:00 16:00 18:30 Urban circulator No specific threshold Urban crosstown 7:00 N/A N/A 22:00 Urban feeder/distributor 7:00 N/A N/A 19:00 Suburban circumferential 7:00 N/A N/A 18:30 Suburban feeder/distributor 7:00 N/A N/A 19:00 Suburban local 7:00 N/A N/A 19:00 o Frequency of service – Frequency of service thresholds are set to ensure a basic level of service for the area served by a route. For dense areas, for instance, an agency could specify that service should be provided at least every 15 minutes in peak periods and at least every 30 minutes in off-peak periods. For less dense areas, the thresholds might be 30 minutes for peak periods and 60 minutes for off-peak periods. An example of proposed frequency of service guidelines for a transit system with the above route classification scheme is as follows (Table 3-2). Table 3-2: Example, Frequency of Service Measures Type of Service Weekday Peak Period Weekday Off-Peak and Weekend Urban Classes: Headway not greater than 15 minutes 30 minutes Suburban Classes: Headway not greater than 30 minutes 60 minutes Express Routes: Peak period trips not fewer than 4 trips 0 trips o Travel time -- This measure encompasses both route directness and travel speed, since it compares the in-vehicle travel time on a bus from point A to point B to the driving time from point A to point B. Bus routes that are indirect or that have an excessive number of stops would have more difficulty attaining the established threshold (e.g., of having a travel time not more than twice the driving time). An example of proposed travel time guidelines for a transit system with the above route classification scheme is as follows (Table 3-3).

TCRP H-32: Interim Guidebook 3-5 Table 3-3: Example, Travel Time Measures Type of Service Ratio of Scheduled End-to-End AM Peak Bus Running Time to Zone-to-Zone Auto Travel Time All types other than Express 2.0 Express 1.5 • Performance measures – These measures, which are more directly applicable to an operational analysis, quantify how well existing bus routes are used and whether service is comfortable and reliable for the passengers. Typical examples include: o Productivity – Productivity measures the level of demand for the route. The demand can be quantified, for instance, in terms of the number of boardings per vehicle revenue hour, or boardings per trip for express routes. The measure may have separate thresholds for peak period and off-peak period service, and may also have a full- day threshold in case ridership and operational data are not available for peak and off-peak service separately. An example of proposed productivity measures for a transit system with the above route classification scheme is as follows (Table 3-4). Table 3-4: Example, Productivity Measures Type of Service Weekday Peak Period Weekday Whole Day Weekday Off- Peak and Weekend Radial Line Haul Routes: Boardings per VRH 30 24 18 Urban Classes (buses >=30 ft.): Boardings per VRH 30 24 18 Suburban Classes (buses >=30 ft.): Boardings per VRH 15 12.5 10 Express Routes: Boardings per trip 23 23 23 All Classes (buses <30 ft.): Boardings per VRH 12 11 10 o Crowding -- A passenger’s perception of the crowding on a bus is most easily quantified by the load factor -- the number of passengers on board at the peak load point divided by the number of seats. A load factor above 1.0 indicates that some people were forced to stand for a portion of the trip. Except for infrequent services (headway greater than 30 minutes) the load factor on one individual trip is typically not critical; thus, this measure may instead consider, for example, the average load over two consecutive trips for medium frequency services, and over all trips within the peak 30 minutes for frequent services. An example of proposed crowding measures for a transit system with the above route classification scheme is as follows (Table 3-5).

TCRP H-32: Interim Guidebook 3-6 Table 3-5: Example, Crowding Measures Type of Service Weekday Peak Period Load Factor Weekday Off-Peak and Weekend Load Factor All Classes other than Urban Crosstown and Express 1.2 1.0 Urban Crosstown 1.1 1.0 Express Routes with premium fare 1.0 1.0 o Reliability – Measures of reliability/schedule adherence apply to the whole system, rather than to individual routes. An example of an assessment of reliability for a transit system is shown in Table 3-6. Table 3-6: Example, Weekday Schedule Adherence Results Allowances Percent On Time Percent Early Percent Late Departures 0 min. early/5 min. late 90.5% 3.9% 5.7% 1 min. early/5 min. late 92.7% 1.6% 5.7% Arrivals 0 min. early/5 min. late 57.4% 25.2% 17.3% 1 min. early/5 min. late 66.5% 16.2% 17.3% 2 min. early/5 min. late 72.3% 10.4% 17.3% 2 min. early/6 min. late 75.9% 10.4% 13.7% Departures and Arrivals 0/5 Departure and 0/5 Arrival 55.1% -1/5 Departure and -2/6 Arrival 73.3% Number of trips in sample 14,617 Route-level Performance Assessment – Once evaluation measures have been established, each route is then evaluated, in terms of how it compares to agency goals or thresholds for that class of routes. The overall system’s performance may also be assessed for certain measures (e.g., coverage). Examples of the application of two of the above measures (span of service, by route class, and productivity, by area) are shown in Tables 3-7 and 3-8.2 2 In Tables 3-7 and 3-8, the percentage of passing routes is calculated in two ways: at the route level unweighted, and by route weighted by vehicle revenue hours (VRH) of service. The unweighted method treats each route in the region equally, while the weighted method counts routes in proportion to the vehicle revenue hours of service on that route. The second method gives a more accurate picture of the span of service or productivity in the region, since if a minor route with only a few trips a day is unable to meet the service span or productivity threshold, it would have only a minimal impact on regional mobility, but if a major route with many trips is unable to meet the threshold, more people would be affected.

TCRP H-32: Interim Guidebook 3-7 Table 3-7: Example, Weekday Span of Service Evaluation Route Classification Number of Routes % Meet Threshold, Routes Total VRH % Meet Threshold, VRH Radial Line Haul 25 92% 3,477 96% Express 32 19% 741 31% Commuter 63 35% 969 53% Urban Circulator 6 100% 192 100% Urban Crosstown 10 100% 1,354 100% Urban Feeder/Distributor 44 93% 2,443 94% Suburban Local 25 64% 813 82% Suburban Circumferential 6 83% 550 94% Suburban Feeder/Distributor 83 77% 4,519 88% TOTAL 294 66% 15,058 87% Table 3-8: Example, Weekday Productivity Evaluation Area Period Number of Routes % Meet Threshold, Routes Total VRH % Meet Threshold, VRH Urban Peak 97 88% 7,176 94% Off-Peak 94 90% 7,135 96% Suburban Peak 167 74% 6,677 85% Off-Peak 171 70% 7,493 85% TOTAL Peak 264 79% 13,854 90% Off-Peak 265 77% 14,628 91% Identification of problem routes – Based on the route-level assessment, “problem routes” (i.e., those with design and/or performance measures that fall below specified thresholds) can be identified. An example of a summary of an agency’s route-level assessments for the above measures is shown in Table 3-9. Identification of Actions to Address Problems -- Based on the route-level assessment, the agency can then identify potential actions for improving the design and performance of problem routes. The types of service adjustments that might be considered are described in Chapter 5. A route-level evaluation is thus an important element of an overall assessment of a transit system. When combined with market research and an assessment of unmet needs/latent demand, an agency can identify opportunities for attracting new riders or expanding usage by current riders. A comprehensive system evaluation may also include a peer analysis that compares the agency’s services and systemwide performance to those of a set of comparable agencies. The next section briefly discusses the evaluation of an agency’s marketing, information and fare systems.

TCRP H-32: Interim Guidebook 3-8 Table 3-9: Example, Summary of Routes Meeting Design Thresholds Route/Line Classification Span Freq. Travel Time Produc- tivity Crowding # Not Met # Border- line 22A-F Urban feeder/distributor No No No No Yes 4 0 AT7 Urban feeder/distributor No No No No Yes 4 0 24M,P Urban feeder/distributor No No Yes~ No Yes 3 1 11P Commuter No No Yes No Yes 3 0 13A-G Radial line haul Yes No No No Yes 3 0 21A-F Express No Yes Yes No No 3 0 25A-R Urban feeder/distributor No No Yes No Yes 3 0 28C Urban feeder/distributor No No Yes No Yes 3 0 AT2 Radial line haul No No No Yes Yes 3 0 AT3 Urban feeder/distributor No No Yes No Yes 3 0 AT4 Urban feeder/distributor No No Yes No Yes 3 0 AT5 Urban circulator Yes No No No Yes 3 0 10B,C,D Urban crosstown No No No~ Yes Yes 2 1 23A-T Urban crosstown No No No~ Yes Yes 2 1 28A,B Urban crosstown Yes No No~ Yes No 2 1 38B Radial line haul No No Yes~ Yes Yes 2 1 25B Urban feeder/distributor No No Yes Yes Yes 2 0 3A-F Radial line haul Yes Yes No No Yes 2 0 AT8 Radial line haul Yes No No Yes Yes 2 0 10A,E Urban feeder/distributor Yes No Yes Yes Yes 1 0 16A-J Radial line haul Yes Yes Yes Yes No 1 0 16L Commuter No Yes Yes Yes Yes 1 0 28F,G Express Yes Yes Yes No Yes 1 0 7A-X Urban feeder/distributor Yes Yes Yes~ Yes Yes 0 1 16S, U, W, X Commuter Yes Yes Yes Yes Yes 0 0 4A-S Urban feeder/distributor Yes Yes Yes Yes Yes 0 0 8S-Z Commuter Yes Yes Yes Yes Yes 0 0 ART Urban circulator Yes Yes N/A Yes Yes 0 0 Shoppers Shuttle Urban circulator Yes Yes N/A Yes Yes 0 0 % of routes not meeting threshold 52% 62% 24% 45% 10% Needs Assessment of Marketing/Information and Fare Systems In addition to identifying service gaps or deficiencies, an agency seeking to maximize ridership should review its marketing and information programs, as well as its fare structure/system. With regard to marketing/information strategies, how effective are the existing programs/systems at informing riders about the transit service and how to use it? With regard to the fare structure and fare collection system, are there problem areas or opportunities for improvement? For both categories, are there new strategies that might improve the agency’s ability to attract and retain riders? Considerations related to these areas are discussed in Chapters 7 (Marketing/Promotion and Information Initiatives) and 8 (Fare Collection and Structure Initiatives).

TCRP H-32: Interim Guidebook 3-9 Identification of Needs & Potential Markets Traditionally, budgetary and other constraints (e.g., land use/roadway network limitations) have by and large forced transit agencies to focus their services on specific trip purposes (notably the work trip). In other words, the focus has been on serving the greatest number of people in the most cost-effective manner possible. However, the market for transit services is clearly not monolithic, but rather consists of a broad mix of types of users, with differing socioeconomic characteristics and trip purposes. Efforts to produce significant increases in overall ridership – or greater market share among particular user groups – may therefore require agencies to target specific market segments or niches. In any event, developing an understanding of the characteristics and travel needs of different groups is a key element in identifying the most appropriate ridership growth strategies/initiatives. This section presents guidance on identifying unmet needs and potential markets for transit service. The key elements in identifying needs/markets include the following: • Conducting analysis of demographics and travel patterns within the area or region; this analysis is used to o identify gaps in transit service coverage, focusing on areas with the potential to support transit services (e.g., based on development density, activity centers, and concentrations of transit-dependent residents) o identify the size of the current and projected travel markets (e.g., based on travel volumes to major regional employment centers) • Conducting market research, identifying (1) key market segments and (2) both current riders’ and non-riders’ service preferences and propensity to ride improved transit service. These elements are discussed below. Conducting Demographic and Travel Pattern Analysis Several different types of analyses can be carried out in an effort to understand both the availability of transit services in a city or region and how well that transit service meets current and future travel needs. For example, transit coverage can be compared with current and future development patterns to contrast service availability with evidence of demand. In addition, travel patterns to major regional activity centers can be analyzed to identify potential transit markets. Then, within these potential markets, transit travel times can be compared with auto access times in order to examine the effectiveness of transit accessibility.

TCRP H-32: Interim Guidebook 3-10 One approach that has been found to be invaluable in such analyses is to use geographic information systems (GIS) tools to map key indicators of potential demand (i.e., demographic characteristics, land use patterns, key travel generators) as well as the existing transit services and ridership levels. Graphical displays of this information (see Exhibit 3-1 below for an example) can be quite helpful in identifying the nature of the existing market for transit service as well as areas of potential demand. The GIS data can be used, for instance, to conduct a route coverage analysis. Service areas representing typical walking distance (¼ mile, or 1,300 feet) from the agency’s route network as a whole, and from each individual route, can be produced and incorporated into the GIS database for display and analysis. These areas can then be used to calculate the total population, and the concentration of various transit dependent segments, within walking distance of each route, and of the whole system. Unserved areas of moderate population density, or with a significant concentration of transit dependent residents, can then be identified. Exhibit 3-1: Example of GIS Graphic Based on the evaluation of the existing service, coupled with the assessment of travel, development and demographic patterns – including anticipated future growth patterns – the agency can then identify (1) gaps in the existing service network and (2) specific travel markets in the service area which appear to be underserved. The results of this analysis should ultimately be combined with the findings of the market research (discussed in the next section) to identify the appropriate types of service changes to best address these unmet needs and future opportunities. 0 31 2 Miles Prepared By Multisystems, Inc. Transit Need Indicators Lower Medium Higher Essex Union Bergen Bergen Conducting Market Research Purpose/Goals of Market Research Although demographic analyses are critical to making general assumptions about probable service gaps and the size of underserved market segments, these analyses can be enhanced significantly through the conduct of targeted market research. The purpose of this research is to specifically identify potential markets for increased transit ridership, and to confirm the reasons for current mode choice decisions.

TCRP H-32: Interim Guidebook 3-11 The most fertile markets for potential transit ridership increases are those where the actual rate of transit use falls below that group’s expected level (e.g., based on Journey to Work Census statistics. Reasons for lower-than-expected transit usage include the lack of information availability, a mismatch between services provided and those desired (span of service, routing, etc), pricing, and other operating environment issues (such as safety). Trip characteristics, traveler characteristics, and travel needs and wants represent the primary pieces of information targeted by transit market research. Compiling responses to these travel characteristics-related questions with more precision than that afforded by a broad demographic analysis allows for a better understanding of why a transit provider is not reaching its full potential in market penetration. In deciding on a market research methodology, a key initial question must be answered: is the agency attempting to learn more about riders or non-riders? Riders are easier to reach and their interaction with the system presents opportunities for a variety of market research methods, as well as providing for easier management of the research program. Non-riders present a host of challenges, not least of which is the large number of them (several times the number of transit riders in even the highest ridership metropolitan areas), and the costs inherent in reaching out to them. Market Research Techniques The next decisions are (1) whether to use quantitative or qualitative market research techniques and (2) which specific technique(s) to employ. These decisions are primarily governed by the nature of the desired information, as well as the resources – and amount of time -- available. There is a wide variety of market research techniques, and each is suited to specific research needs and budgets. The basic market research approaches are as follows: • Surveys and interviews • Travel Diaries • Focus groups • Customer panels and advisory committees The advantages and disadvantages of these are discussed below. Although the above techniques vary in their applicability, all should strive to meet certain standard characteristics:3 3 NCHRP Report 487, Using Customer Needs to Drive Transportation Decisions (2003).

TCRP H-32: Interim Guidebook 3-12 • Sufficient detail to form the basis for agency decision-making • Statistically reliable • Fully inclusive and representative of target group • Justify the costs of research • Replicable and understandable • Usable in context with other techniques Surveys/interviews take many forms, including telephone, on-board, household/mailback, online and intercept (e.g., in a station or at a bus stop). Some of these are suitable only for one target group (customer or non-customer) while others can be used for both. Telephone surveys targeting the broad population (both customers and non-customers) represent one of the more expensive market research techniques. However, this generally represents the best way of reaching non-riders, and is particularly useful (for riders and non- riders) if the survey instrument is complex (e.g., a “stated preference” survey involving a series of trade-off questions). Other strategies for conducting a complex rider survey are to do in-person interviews, or to hand out the questionnaires on-board or at stops/stations and provide a mailback option. Some of the key differences between telephone and on-board survey methods are compared in Table 3-10. Table 3-10: Comparison of Telephone and On-Board Surveys Telephone interviews On-board surveys/personal interviews On-board surveys with mailback Data collection costs Moderate to high High Low to moderate Time for data collection Short to moderate Moderate to long Moderate Control over respondent selection High High Low Response rates Moderate to high High Low to moderate Ability to access hidden populations Moderate High Low Complexity of questions Simple to moderate Moderate to complex Simple Completion of boring/tedious questions Moderate High Low Completion of sensitive questions Moderate to high Low Moderate Interviewer bias and error Low to moderate Moderate to high None Ability to ask open-ended questions Low to moderate High Moderate Perceived respondent anonymity Moderate to high Low Moderate to high Source: TCRP Report 37, A Handbook: Integrating Market Research into Transit Management (1998), p. 94

TCRP H-32: Interim Guidebook 3-13 Travel diaries are another useful market research tool that is applicable to both customer and non-customer target groups. With this technique, participants log information on all aspects of their travel behavior (time of day, mode choice, origin/destination) over a pre-determined period. Once collected, this information provides a more comprehensive snapshot of participant travel needs and habits than could be obtained through surveys and other techniques. Travel diaries also provide the transit agency with enough information to determine the suitability of serving non-transit trips with existing or enhanced transit service. Focus groups cost considerably less to administer than surveys or travel diaries, but have the drawback of being the least representative of the approaches.4 Focus groups generally cannot be used to produce statistically-significant information – or any quantitative information, for that matter. However, focus groups are useful for gauging levels of interest in new initiatives, or getting input from different market groups on key issues or concepts. Agencies also sometimes use focus groups as a means of establishing or testing out questions to be used in a survey. Customer panels and advisory boards are typically more appropriate to monitoring an ongoing agency program than to identify means for increasing ridership. NCHRP Report 487 distinguishes between data-gathering techniques designed to solicit customer or public input and those that are aimed more at receiving feedback on a program that has already been implemented. While market research with the goal of increasing ridership falls into the first category of data gathering, customer panels and advisory boards are more suited to the second. As suggested above, the availability of resources at an agency often governs the technique(s) utilized. The availability of resources – and the size of the agency -- also affects an agency’s organizational approach to market research. For example, large agencies that conduct ongoing market research programs may find it cost-effective to maintain a full-time, dedicated market research staff. However, this may mean that most of the agency’s market research is limited to what can be directly undertaken by that staff. In such a case, for instance, an on- board survey is often the least expensive technique, as it can be carried out by agency staff. That same agency may find techniques such as focus groups prohibitively costly, given a limited budget for hiring outside contractors to do market research. Alternatively, for a smaller agency that conducts market research on more of an as-needed basis, contracting all survey efforts out to private firms may be the most cost-effective way to carry out the research. In such cases, the agency often assigns the responsibility for the research to the specific department in search of market information at that time. Even for 4 As discussed below, the relative cost of the different techniques to an agency ultimately depends on the nature of the resources available (e.g., whether there is any in-house market research staff, and the specific capabilities of that staff).

TCRP H-32: Interim Guidebook 3-14 agencies with in-house staff, though, contracting out large or particularly complex survey efforts to private firms is often necessary. Examples of Agency Market Research Approaches A number of agencies maintain regular comprehensive transit market research programs. In the San Francisco Bay Area, for instance, BART conducts bi- annual passenger surveys that gauge rider satisfaction with 44 BART service characteristics. BART compares the results with previous surveys to identify trends and measure improvement resulting from new service enhancements. This survey is augmented by follow-up telephone surveys conducted in the off year with a subset of the passenger survey respondents. BART also makes the results of this research available to the public through its website. Depending on the desired information sought by the transit agency, a more focused research program targeting one submarket may be preferred. For instance, the City of Lowell (MA) was interested in attracting more city youths (a submarket with the potential for high ridership given the cost of auto ownership and the minimum age requirements for a drivers license) to local transit service. The Lowell Regional Transportation Authority (LRTA) and the city’s campus of the University of Massachusetts jointly conducted a survey of city high school and middle school students. The survey asked youths to identify gaps in service to popular recreational and employment destinations. The result of the research effort was a “Youth Loop” bus service serving 18 popular destinations and residential areas with high concentrations of young people. Another approach is to conduct a survey focused on a particular aspect of the transit service. For example, agencies often conduct surveys related to fare payment preferences and concerns as part of fare system or policy studies. Similarly, an agency introducing a new type of service (e.g., BRT or LRT) may find it useful to survey area residents on desired attributes and potential usage of the new service. Survey Analysis Methods There is a broad range of survey analysis methods. The appropriate method depends on the nature of the questions and the intended use of the results (e.g., what type of market segmentation will be developed?). For straightforward questions (e.g., related to frequency of travel or demographic characteristics), simple frequencies are useful. Cross-tabulation is the simplest and most common method for analyzing the relationships between pairs of variables. Another useful technique for depicting the relationship between two variables is quadrant analysis; the relative ratings or performance of the two variables are plotted on a graph that clearly shows their relative importance. For analyzing the relationships among several variables or analyzing more complex questions (e.g., trade-off questions related to how respondents value alternative service or fare attributes), more sophisticated multivariate analysis techniques must be used; examples of such techniques include correlation analysis, multiple regression analysis,

TCRP H-32: Interim Guidebook 3-15 discriminant analysis, factor analysis, correspondence analysis and conjoint analysis.5 Regardless of the specific analysis methods employed, the ultimate goal of the market research should be to provide the agency with a better understanding of the attitudes, preferences, characteristics and/or unmet needs of different service area market segments. These findings should then be combined with the service evaluation and the analysis of demographic data and trends to identify mobility needs and growth markets and opportunities for transit in the region. An important aspect of this process is the identification of the needs of key market segments; market segmentation is discussed in the next sections. Identifying Market Segments Market Segmentation Approaches TCRP Report 36, A Handbook: Using Market Segmentation to Increase Transit Ridership, notes the following: • “Everyone is not a prospect for every product or service offered. It is evident to everyone in the transit industry that not everyone rides or will ride the bus, participate in a carpool or vanpool, ride a bike to work, or otherwise leave their car at home – even for a day. • An agency’s product or service mix must be controlled for maximum efficiency. Recent cutbacks in funding make it increasingly important to understand customers’ needs and wants in order to use these increasingly scarce resources most effectively. • Since the product/service mix and customer pool are limited, it is most efficient to match your products and services to customer needs and wants.” (p. 2) Of course, there are a number of different ways to segment the market for transit (or any product or service). TCRP Report 36 explains that there are two basic approaches: • “Pre-determined (a priori) segmentation – selecting certain groups from a population based on known characteristics and declaring them ‘segments.’ 5 For a description of these techniques, as well as other details related to market research, the reader is directed to the following reports: TCRP Report 37, A Handbook: Integrating Market Research into Transit Management (1998); D. Aaker et. al., Marketing Research (1995); P. Alreck and R. Settle, Survey Research Handbook (1995); G. Churchill, Marketing Research: Methodological Foundations (1995).

TCRP H-32: Interim Guidebook 3-16 • Market-defined (post hoc) segmentation – identifies segments based on actual market investigations, notably analysis of answers to survey questions intended to predict marketplace responses.” (p. 75) The authors of Report 36 suggest that “Bases used for pre-determined (a priori) segmentation vary widely depending on goals.” (p. 13). They provide a number of examples, including: • “Riders versus nonriders, frequent riders versus infrequent riders versus occasional riders, or former riders versus current riders. • Loyal riders versus vulnerable or nonloyal riders. • Transit dependent riders versus choice riders. • Residents of high-density areas versus suburban residents. • Commuters to downtown CBDs versus suburb-to-suburb commuters. • Student commuters versus work commuters. • ‘High’ versus ‘mid’ versus ‘low’ income groups. • Geographic location as defined by zip code, census tract. or transit analysis zone.” (p. 13) While a priori segmentation uses existing group definitions, post hoc segmentation requires new market research. A list of some of the types of classifications and variables often deployed in market-defined segmentation analyses is presented in Table 3-11. (TCRP Report 36 describes and presents examples of various types of market segmentation that have been used by transit agencies.) Key Market Segments With regard to identifying specific market segments, a report recently prepared for APTA (B. Hemily, Trends Affecting Public Transit’s Effectiveness: A Review and Proposed Actions, November 2004) identifies four key segments for transit, based on an analysis of demographic, socioeconomic and land use trends; these segments are: (p. 27) • Commuters • Immigrants (particularly in older inner suburbs) • Serving the mobility needs of an aging population

TCRP H-32: Interim Guidebook 3-17 Table 3-11: Some Common Bases for Post Hoc Segmentation Product Selection Behaviors Usage rates and occasions (e.g., frequency of riding or trip purpose) Knowledge of and experience with product Substitutability of related categories (e.g., availability of alternative modes) Mode Selection Behaviors Favorite travel mode Acceptable modes Disliked modes Mode loyalty versus mode switching Product Class-Related Attitudes Benefits sought Problems encountered using product/service Attribute utilities of mode Mode-Related Attitudes Awareness and perceptions Mode user imagery Perceived appropriateness for use occasions Person-Related Attitudes Self-perceptions Values Life styles Other “psychographics” Other Bases Stage in life cycle Socioeconomic status Ethnicity Other demographics Source: TCRP Report 36, A Handbook: Using Market Segmentation to Increase Transit Ridership, 1998 (p. 20) • Access for customers with special needs (persons with disabilities and economically disadvantaged). Hemily argues that transit agencies must recognize and understand the different needs of these markets if they hope to address the challenges facing the transit industry. In a broader study of transit market segments, TCRP Report 28 (Transit Markets for the Future – The Challenge of Change) analyzed current and future transit market groups, based on use of transit as reported in the 1990 U.S. Census and 1990 Nationwide Personal Transportation Study (NPTS). Table 3-12 shows “transit use by various market niches indexed to average metropolitan transit use.” In this table, groups with an “MSA Transit Index” higher than 1 were “more likely than average to commute using transit;” the higher the index, the higher the group’s reliance on transit. Based on this analysis, the authors identified the following groups of transit users as “. . . being more likely than average to use transit as their principal mode for commuting to work in U.S. metropolitan areas in 1990:

TCRP H-32: Interim Guidebook 3-18 Table 3-12: Transit Use by Various Market Niches Indexed to Average Metropolitan Transit Use Market Niches MSA Transit Index Market Niches MSA Transit Index Sex Men Women Race & Ethnicity White Black Hispanic Asian Vehicle Ownership No car One or more car Age of Worker 17 – 29 30 – 39 40 – 49 50 – 59 60 – 64 65 – 69 Education No school Elementary Junior High Some High School High School Some College College Graduate School 0.85 1.18 0.68 2.72 1.73 1.74 5.76 0.68 1.14 0.96 0.87 0.92 1.07 1.10 2.59 2.08 1.69 1.25 0.91 0.82 1.05 1.06 Household Income <$5k $5 – 10k $10 – 15k $15 – 20k $20 – 25k $25 – 30k $30 – 40k $40 – 50k $50 – 60k $60 – 70k $70k plus Immigration Status Non-immigrant Immigrant Years in US <5 5 – 10 10 – 15 15 – 20 20 – 25 25 – 30 30 – 40 40 plus Limitations Work limitation Mobility limitation 1.23 1.24 1.08 1.04 0.97 0.90 0.78 0.77 0.84 0.91 0.95 0.84 2.08 3.01 2.25 1.74 1.89 1.88 1.49 1.48 1.80 1.25 2.41 Source: TCRP Report 28, Transit Markets for the Future – The Challenge of Change, 1998 (p. 8) – data from 1990 U.S. Census • Women • Blacks • Hispanics • Asians

TCRP H-32: Interim Guidebook 3-19 • Workers with no household cars • Workers age 17 to 29 • Workers age 60 and over • Workers with less than high school education • Workers with some high school but no degree • Workers with college degree • Workers with graduate school education • Workers with household income below $20,000 • Immigrants • Workers with mobility or work limitations.” (p. 8) The report notes that “The data show that there are distinctly different markets among those riding transit -- it is unlikely that they all could or would be well- served by the same services, routes, schedules, and marketing approaches.” (p. 3) There may also be distinct differences in the types of strategies an agency should consider in targeting existing riders vs. new riders. For instance, surveys from the recent regional bus study in the Washington, DC region identified the types of transit improvements desired by both existing riders and non-riders. The results of these survey efforts are shown in Exhibits 3-2 and 3-3. As indicated, there are significant differences between the most desired improvements for the two groups: riders rated service-related improvements most important, while non- riders considered better information and improved amenities (i.e., “better shelters”) most important. Thus, targeting new riders would argue for a different set of actions/initiatives than would an attempt to influence the usage patterns of existing riders. Along these same lines, a report prepared by the California Department of Transportation (An Analysis of Public Transportation to Attract Non- Traditional Transit Riders in California, April 2003) presents the results of market research conducted by a number of California transit agencies of rider and non-rider attitudes toward transit. The report notes that “Surveys across the state reveal that approximately one-half to two-thirds of current riders find the existing service in their area ‘good’ or ‘excellent.’ Their suggestions for improvement are overwhelmingly concentrated as follows:

TCRP H-32: Interim Guidebook 3-20 Figure 2-1: Improvements Desired by Bus Riders 49% 31% 25% 22% 13% 12% 10% 10% 9% 8% 8% 7% 0% 10% 20% 30% 40% 50% 60% On -tim e A rri va l Mo re Fr eq ue nt Se rvi ce Lo ng er Ho ur s Le ss C ro wd ing Cl os er Bu s S top s Go M or e P lac es Fa ste r S erv ice Be tte r S he lte rs Sc he du le Inf o/S ign ag e Be tte r V eh icl e C on dit ion Lo we r F are s Be tte r C us tom er Se rvi ce Exhibit 3-2: Results of Rider Survey (source: TranSystems et al., WMATA Regional Bus Study, 2003) Figure 2-2: Improvements Desired by Non-Riders Improvements Desired by Non-Riders 30% 21% 18% 16% 16% 13% 13% 9% 6% 0% 5% 10% 15% 20% 25% 30% 35% Be tte r In for ma tio n Be tte r S he lte rs Mo re Co nv en ien t S top s Fa ste r S erv ice Mo re Fre qu en t S erv ice Se rvi ce to De sti na tio n Co mf ort ab le Bu se s Se rvi ce to M etr ora il Be tte r R eli ab ilit y Exhibit 3-3: Results of Non-Rider Survey (source: TranSystems et al., WMATA Regional Bus Study, 2003)

TCRP H-32: Interim Guidebook 3-21 • More frequent service (crosses all demographics) • More ‘on-time’ service • Better timed transfers • Extended service (nights and weekends) • Additional routes (to a lesser extent).” (p. 14) As for non-riders, the California DOT reports on two aspects of the market research: “why non-riders don’t use the system now” and “what would entice non-riders to use the system.” Regarding reasons for not using transit now, the most common reason cited was simply ownership of a car; many survey respondents claimed that they would only use transit if they had no alternative (e.g., if their car were broken). Regarding what could lure non-riders to transit, a survey from the Los Angeles area revealed that “To be attracted to transit, (these) non-riders would need the perceived value of transit to equal their current mode.” (p. 20) These respondents considered “travel time compared to the auto“ to be “of high importance,” and also rated the local transit service as “unsafe.” Thus, given the different types of concerns and travel needs associated with different rider and non-rider groups, market segmentation can clearly be a useful component of any effort aimed at increasing ridership or market share; designing marketing plans – as well as types of service – that target specific market segments will often represent the best use of an agency’s limited resources. The remaining chapters provide guidelines on identification of appropriate strategies to address the service needs and potential markets identified through the above method.