TRANSIT MARKETS IN OHIO - Ohio Department of Transportation€¦ · The Ohio Department of...

Statewide Market Analysis DRAFTOhio Department of Transportation

Nelson\Nygaard Consulting Associates, Inc. | 1

The Ohio Department of Transportation (ODOT) is conducting a Statewide Transit Needs Study. The goal of this study is to determine if the public transportation services available today meet the needs of Ohio residents. If there are unmet needs, the study will develop a strategy that will improve transit services in a way that is efficient and appropriate. The Statewide Transit Need Study is a year-long effort that is being managed by ODOT and guided by a Steering Committee comprised of transit agencies, human service representatives, business representatives, and members of the state legislature.

As part of the Transit Needs Study, the study team prepared a market analysis. The team designed the market analysis to consider existing conditions in each of Ohio’s 88 counties and use qualitative data, such as site visits with each transit agency (see Appendix A), and quantitative data, such as development patterns and demographics, to broadly assess the need for transit services.1 It is always difficult to quantify the need for public transportation services absolutely. There are always exceptions to every rule and sometimes transit services succeed where you might not expect to them to and fail when they should work. However, national experience suggests that two factors have more influence over the need for transit service than any other:

• Density – places where there are high concentrations of workers and/or residents – is the most important factor in determining transit ridership. Densely developed areas – like downtowns in large cities, university campuses, and hospitals – have many people traveling to them, so there are more people who could use transit. In addition, densely developed areas are also more likely to have safe walking environments with sidewalks and crosswalks, so people can safely get to and from transit routes.

• Demographics suggest that people in a community may rely on public transportation to meet their travel needs. Households with only one vehicle or people with low incomes, for example, indicate that people may be looking for public transportation to supplement their transportation options. Likewise, teenagers who may not have access to a car, or older adults who may be driving less also suggest a reliance on public transportation.

1 County-by-county analyses published under a separate cover.

Density – places where there are high concentrations of workers and/or residents – is the most important factor determining

transit ridership.

Community demographics, such as income, access to a vehicle,

disability status, and age, are also important factors in determining

transit ridership.

TRANSIT MARKETS IN OHIO



National experience tells us that density and demographics also help determine the type of transit service that will work best in a particular region. There are a wide variety of transit services, ranging from high capacity modes such as rail and bus rapid transit to lower capacity modes such as dial-a-ride and community shuttles.2 Each of these different services has different strengths and weaknesses and is designed to serve different types of communities and riders. Rail systems, for example, are very expensive to build but can carry high volumes of passengers efficiently when operating through densely populated corridors and safe, well developed walking environments. Dial-a-ride service, on the other hand, carries fewer riders but work well in areas with lower populations and offer a higher level of service for people unable to walk long distances or who need more assistance traveling. Ultimately, transportation connects people to jobs, activities, and basic services like medical appointments and shopping. Every community has people who cannot reach jobs and basic services on their own. For the most part, these individuals use transportation services provided by other federal and state human and medical service programs, like Medicaid (see bottom two levels of Figure 1). These services are typically mandated by the federal government, and are available statewide, but they are limited trips to and from specific appointments and activities. Public transportation, on the other hand, includes transportation services available to members of the general public traveling for any purpose (see the top three levels of Figure 1). In Ohio, local communities typically counties, decide if they want to provide general public transportation and how to provide that service. The objective of this market analysis, therefore, is to broadly assess the need for public transportation throughout Ohio, including from both a statewide and county perspective. Needs, as discussed, are estimated using a combination of population and employment density and demographic characteristics. The analysis of each of Ohio’s 88 counties is available in separate documents. The following analysis considers historic trends and current patterns that affect the need for transit in Ohio from a statewide perspective.

2 Bus rapid transit is similar to rail but uses buses. An example in Ohio is the Health Line operated by the Greater Cleveland Regional Transit Authority.

Figure 1 Transit Services Hierarchy Pyramid



HISTORIC TRENDS – OHIO’S DEVELOPMENT PATTERNS AND DEMOGRAPHIC CHARACTERISTICSPopulation and economic activity in Ohio boomed in the early 19th century, as part of the industrial revolution when access to transport such as waterways and railways, natural resources (coal and iron ore), and a stable workforce was critical. Ohio grew rapidly until the mid-1960s, when it reached a population of 10 million. The U.S. economy has changed dramatically since the mid-1960s, and is less dependent on transportation and natural resources and more on services. Although Ohio is adjusting to these changes, for a complex set of reasons, Ohio’s transition has been slower as compared to other parts of the country. Partially in response to changes in the national economy, Ohio’s population grew slowly between 1970 and the current day, to its current level of about 11.5 people, making it the seventh most populous state in the U.S.

Unlike most U.S. states, which typically have just one or two major cities, Ohio has three fairly large urban areas plus an additional five well established small- to medium-sized urban areas. To a large extent this pattern of urbanization reflects the economic development in Ohio during the 20th century. By 2010, nearly 78 percent of Ohio’s population lived in urban areas, and about 60 percent of the population lives in one of the state’s eight largest cities – Akron, Canton, Cincinnati, Cleveland, Columbus, Dayton, Toledo, and Youngstown.3 This urban population lives almost entirely along the diagonal corridor cutting across northeast and southwest Ohio, anchored by Cleveland, Columbus, and Cincinnati. The remaining 40 percent of the state’s population lives in small towns or rural areas. Undoubtedly, a percentage of the population in any urban area also lives in areas of lower suburban density. This pattern of urbanization with means that Ohio faces a continuous challenge associated with providing public transportation appropriately.

3 2010 U.S. Census



Key Trends in Ohio’s Development Patterns: Key Trends in Ohio’s Demographic & Socio-Economic Characteristics:• Declines in manufacturing and the widespread construction of limited-

access highways in Ohio (among other causes) hurt cities, especially downtown areas, which lost residents, jobs, and retail.

• Recent data suggests this trend may be reversing (see the Demographic Trend Analysis), but population growth and development in Ohio has largely occurred outside of Ohio’s downtowns over the past decades. Many cities, including the largest, lost population.

– To date, only the largest cities have experienced some reversal of this trend.

• Overall, Ohio is becoming less dense. In Ohio’s urban areas, population density decreased from 3.4 persons per acre in 2000 to 3.1 in 2012.

• Ohio cities are also less dense than urban areas nationally (see Figure 2).

• In the past decade, Ohio grew more slowly than the rest of the nation. Between 2000 and 2012, Ohio grew by 1.7 percent, while the nation grew by nearly 11 percent.

• The United States overall is becoming both younger and older. Ohio, however, is adding older people without the same growth in the younger population (see Figure 3).

– The loss of youth population in Ohio slowed somewhat in 2007-2012 while the growth rate of the older adult population increased.

• Ohio also has more low-income individuals than it did a decade ago. In 2000, roughly 18 percent of the population was characterized as low income; by 2012, this percentage was just under 25 percent.

– The number of low-income individuals has been growing since before the 2009 recession, though the growth rate increased slightly in the past five years.

Figure 2 Persons per Acre in U.S. and Ohio Urban Areas, 2000-2010 Figure 3 Percent Change in Population Characteristics in Ohio, 2000-2012



Employment

Ohio has about 5.3 million jobs and, despite growth in many sectors, is not yet back to pre-recession employment levels.4 Recent employment growth has been unsteady but slowly improving since the large decline in 2009. As part of determining transit service needs, this study examines how – at a macro level – people traveled to work. Employment statistics show:

• In 2011, just about half (about 53 percent) of Ohio’s workforce lived and worked in the same Ohio county.

• The other half (about 47 percent) worked outside of the county in which they resided.

• Counties that import the most workers from surrounding counties include Cuyahoga (Cleveland), Franklin (Columbus), and Hamilton (Cincinnati), as expected (see Figure 4).

• Counties that export the most workers to surrounding counties include Lorain (west of Cleveland), Clermont (east of Cincinnati), Medina (south of Cleveland), Butler (north of Cincinnati), and Fairfield (east of Columbus).

• A small number of employed Ohio residents (< 1 percent) worked outside of the state.

4 Based on Bureau of Labor Statistics, 2014

Figure 4 Job Flow in Ohio Counties, 2011 LEHD



Ohio has 61 transit agencies in as many counties, with 26 systems classified as urban and 35 classified as rural. Urban and rural classifications are based on Federal Transit Administration (FTA) classifications and generally reflect the area where they operate, or proximity to a large urbanized area. In general, urban areas tend to operate scheduled, fixed route services, while rural areas are more likely to operate demand response, or dial-a-ride type services (see Figure 5 and Figure 6). There are also twenty-seven counties that have no transit service at all (see Figure 7). Nine of these are located in northwest Ohio along the northern Indiana border, seven are located in the southern tip of the state in the Ohio River Valley, and another four are located south-southwest of Cleveland-Akron-Canton.

EXISTING TRANSIT SERVICES

Figure 5 Existing Fixed Route Service in Ohio Figure 6 Existing Demand Response Only Service in Ohio

Figure 7 Counties in Ohio without Transit Service



TRANSIT SUPPORTIVE DEVELOPMENT PATTERNSDevelopment Patterns (Population and Employment Density) Influencing Transit Service Design

Figure 8As discussed, density and land use patterns are the single most important factor in determining transit ridership. Regardless of demographic and socio-economic characteristics, people who live or work in areas where there are a lot of other people are more likely to use transit. The market analysis linked density to transit demand by creating an index that combines population and employment density, treating each with equal weight, and then broadly relating these densities to the most appropriate types of transit service.

Generally speaking, there are no density requirements for demand response, or dial-a-ride, service. Demand response services can work in any environment but remain less efficient in areas with low density.

Fixed-route service, however, does generally require some level of density to be effective. The transit density index (see Figure 8) mapped local densities to one of two general categories of transit service: deviated fixed route, which is a hybrid between fixed route and demand response, and fixed route. The index does not make suggestions about the specific frequency of service needed or the days of the week service should be provided; instead, it suggests the type of service that would likely be productive based on density.5

Figure 8 shows the results of matching service levels/types to population and employment density by 2010 Census block. The analysis highlights the following patterns (see map):

• Ohio’s largest cities have the largest markets for transit service and are the most likely to support fixed route transit service. These areas include:

– Akron – Columbus

– Canton – Dayton

– Cincinnati – Toledo

– Cleveland – Youngstown

• Ohio’s development pattern of small towns is also visible in the transit index map; nearly every county has at least one town with sufficient density to support deviated fixed route service.

• The remainder of the state has lower densities such that demand response service is likely the most appropriate, though difficulties in providing this base level of service may still exist.

5 For a detailed methodology, see Appendix A.



Figure 9 Transit Supportive Development Patterns and Fixed-Route Service in Toledo, OH

Urban Example: Lucas and Wood County (Toledo Urbanized Area)

The Toledo Area Regional Transit Authority, TARTA, serves Metro Toledo in parts of Lucas and Wood County. Figure 9 shows TARTA’s transit routes together with the transit density index. Areas with the highest density (shown in red) include Toledo’s downtown core on both sides of the Maumee River, as well as Monroe Street, the primary corridor running northwest from downtown. Outside of these two areas, development quickly transitions to a mix of densities (orange and red) that likely

supports a mix of standard and deviated fixed route services. Overlaying TARTA’s existing fixed route structure on the map indicates that TARTA already knows what the map demonstrates: fixed routes succeed where the highest densities occur.

TARTA offers a variety of transit services, including demand response service such as ADA paratransit as well as curb-to-curb Call-A-Ride service. In this way, TARTA is able to match the type of transit services with the local development patterns. There is no county-wide service in Lucas or Wood County, however.

This statewide analysis is not intended to do detailed, local route planning but rather provides an overview of where and what general type of transit service is likely appropriate.



Figure 10 Transit Supportive Development Patterns in Lancaster, OHRural Example: Fairfield County and the City of Lancaster

The City of Lancaster in Fairfield County, by contrast, has significantly less density as compared to Toledo (see Figure 10). Although there is a clear cluster of higher density development within the City of Lancaster, the area immediately around the city has very low density.

This data suggests that while some standard fixed route service may be needed within the city limits, the small geographic area would make it difficult to offer more than one or two routes. In addition, the data suggests it would be difficult to operate fixed route service into Lancaster because none of the surrounding areas have sufficient densities. Development patterns suggest that demand response service is the most likely to succeed outside of Lancaster.

Lancaster currently offers county-wide demand response service and, since 2013, one four-mile deviated fixed route along Memorial Drive headed northwest from downtown (parallel to the railroad tracks).

In addition, Fairfield County shares a border with southeast Franklin County and Metro Columbus. Many Fairfield County residents commute outside of the county for jobs (Figure 4), so existing density may be more residential and demand more focused around serving commuters.6

6 County- or system-level route files were not available for this study outside of these examples.



TRANSIT RELIANCEDemographic and socio-economic characteristics, or an analysis of transit reliance, also help explain the need for transit service.

Transit reliance combines four demographic and socio-economic characteristics into a single measure that estimates who might have a greater tendency to use transit as their primary method of transport.7 The four characteristics were chosen based on national experience and research, and include older adults, persons with disabilities, low-income individuals, and zero-vehicle households. The reliance analysis purposefully excluded density as a factor but does consider where populations more likely to rely on transit service are concentrated.8

General patterns emerge when looking at the individual characteristics that went into creating the transit reliance measure, discussed in the boxes to the right and shown in Figure 11 through Figure 14. As expected, most of the population for each characteristic is concentrated in Ohio’s largest urban areas. Outside of these areas, minor concentrations exist within the small city or town in each county. Similar concentrations occur along the Ohio River. Each of the four characteristics also shows sprawl throughout the state, though to varying degrees.

7 Data is from the 2012 American Community Survey (5-Year Estimates).

8 Completed for the entire state by Census block group, one can directly compare an area to other areas in the state. No comparisons can be made to areas outside of Ohio. This methodology used the population within each characteristic rather than normalizing over total population (percentage of the total population) or area (density). This helps to understand the absolute reliance without favoring areas of higher density, which we already considered, or areas with few people but a high percentage that fall into one or more of the characteristics analyzed. For a detailed methodology, see Appendix A.



Figure 11 Older Adults in Ohio, 2012 5-Year American Community Survey Figure 12 Persons with Disabilities in Ohio, 2012 5-Year American Community Survey



Figure 13 Low Income Individuals in Ohio, 2012 5-Year American Community Survey Figure 14 Zero-Vehicle Households in Ohio, 2012 5-Year American Community Survey



Urban and Rural Transit Reliance Example As part of understanding transit reliance across the state, the study team combined the four transit reliance factors into a single scale and mapped them for individual counties. Differences in census block group size across the state of Ohio make interpreting this analysis from a statewide perspective challenging; consequently, a statewide map is not shown.9 Instead, the transit reliance index shows the distribution of high reliance areas within a single county and suggests locations where transit service may be needed (see Figure 15). As a comparison, the same two areas examined in the density analysis – Toledo and Lancaster – are reexamined from a transit reliance perspective.

In Toledo (Lucas County), the downtown core, major corridors, and areas on the outer edges of the city show the highest transit reliance. TARTA, the transit agency in Toledo, serves many of these corridors and areas already but may be able to identify gaps. Recommendations for the appropriate type of service are only possible, however, when the measure of transit reliance and the index of transit-supportive development patterns are considered together. In Lancaster, two small areas show high transit reliance. Lancaster’s county-wide demand response service provides transit to these areas.10

In both cases, areas on the edges of urbanized areas (Toledo and Columbus (northwest of Lancaster)) show higher reliance than some areas closer to downtown, which can be counter-intuitive. With development patterns over the past half-century, populations that tend to rely on transit have become more dispersed along with housing and employment. Challenges exist in serving these areas with transit, and some areas may be impractical to serve, but the analysis provides a necessary understanding of where high transit reliance exists.

9 Census block groups are sized to contain between 600 and 3,000 people. As a result, urban areas are typically comprised of many geographically small blocks, while rural areas tend to have fewer but geographically larger blocks. While this design is useful for data analysis, mapping the data on a large scale can distort the readers’ perception of the data; our eye tends to focus on large census block groups and has a harder time seeing the relative importance of a cluster of small census block groups.

10 We do not know what form of transportation residents of block groups with high reliance actually use, only that the transportation tendency within each of those areas is oriented towards transit.

Figure 15 Transit Reliance in Toledo (top) and Lancaster (bottom), OH



KEY FINDINGSTogether, development patterns and transit reliance tell a compelling story about transit in Ohio. The state is a somewhat unique network of large urban areas, various well established small- to medium-sized urban areas, and a small town or city in nearly all of the 88 counties. Yet, Ohio’s population remains heavily oriented towards small urban and rural areas, with about 40 percent of the population living outside of major urbanized areas. Additionally, the urban areas have lost density since at least 2000. These development patterns over the past half century mean that a key indicator of transit use, density, is below that of even the U.S. overall. Conversely, an aging population that is becoming less well off suggests that more transit is needed now more than ever. Thus, the challenge to serve these dispersed, high need communities is very real. Cities remain the primary areas where providing public transportation would benefit the most people and potentially attract even greater density and development. To meet more of the needs of more Ohio residents, however, strategies for providing some level of service to those who do not live in dense areas are necessary. Future trends and patterns will change the transit story to an unknown degree and in unknown areas, but transit agencies can play an integral role in shaping the story. Each county has its own challenges, opportunities, and needs (see county-by-county analyses published under a separate cover), but the previous discussion suggests some overarching statewide findings:

PEOPLE IN OHIO COMMUTE ACROSS COUNTY BORDERS TO GET TO JOBS. Ohio’s economy is starting to recover with the number of jobs in the state increasing slowly but steadily since 2009. About half of workers have jobs in the same county where they live. The other half commute to jobs outside of their home county. More people commute into counties with the largest cities – Cleveland, Columbus, Cincinnati, Dayton, Toledo, and to a lesser extent, Akron. However, the data shows workers throughout the state travel across county lines to get to work. The vast majority of Ohio’s transit services operate within county borders, thus the existing transit network is not equipped to support nearly half of the work trips.

TWENTY-SEVEN COUNTIES IN OHIO CURRENTLY DO NOT HAVE ACCESS TO PUBLIC TRANSPORTATION. There are no public transportation services in 27 of Ohio’s 88 counties; this represents about 9 percent of the state’s total population. Without public transportation, only people participating in specific programs for the highest need individuals are able to reach essential services without a personal vehicle.

THE DEVELOPMENT PATTERNS AND DEMOGRAPHICS OF COUNTIES WITHOUT PUBLIC TRANSPORTATION VARY. The 27 counties without transit services tend to be very rural and most have no or only very small population centers. Several of the counties, however, have pockets of high need especially with regards to individuals with low incomes. In addition, several counties are located close to one or more of Ohio’s largest cities (see Figure 16 and Figure 17). There may be opportunities to support transportation to regional medical centers, jobs, and other services.



Figure 16 Development Patterns and Ohio Counties with No Transit Service Figure 17 Low Income Individuals and Ohio Counties with No Transit Service



OHIO’S LOW DENSITY DEVELOPMENT CHALLENGES THE DELIVERY OF COST EFFECTIVE TRANSIT SERVICES. All parts of Ohio struggle with sprawl, even the largest cities. Therefore, although the overall need for transit service is growing, transit service is becoming more difficult to provide and sustain. Transit agencies are serving areas with low density development in some areas. Serving these areas efficiently requires careful consideration of appropriate service type, span, and frequency to meet need and demand.

THERE ARE SMALL TOWNS SCATTERED THROUGHOUT OHIO, SOME OF WHICH HAVE SUFFICIENT DENSITY TO SUPPORT FIXED ROUTE TRANSIT SERVICE. In many cases these small town communities with relatively high densities are too small geographically to support more than one or two fixed route services. There may be opportunities for transit services that connect to or from small towns, especially if they are located fairly close to other larger urbanized areas.

OHIO’S POPULATION INCLUDES INDIVIDUALS WHO LIKELY RELY ON PUBLIC TRANSPORTATION TO MEET PART OF THEIR TRANSPORTATION NEEDS. For purposes of this study, demographic and socio-economic characteristics associated with a greater reliance on public transportation include older adults, persons with disabilities, individuals with low incomes, and households with no vehicles. Consistent with having larger populations overall, Ohio’s urban areas have more people who rely on public transportation. The data also shows, however, that there are people who rely on public transportation in every county in Ohio, especially low-income individuals and older adults. Developing transportation infrastructure that supports these individuals in their need to travel to work, school, and basic services is needed.



APPENDIX A



METHODOLOGYThe purpose of this market analysis is to identify geographical areas within the State of Ohio that show demand for transit services. Two separate calculations were made in this analysis. First, a measure of transit reliance was determined for each block group in the State of Ohio that considers populations with a tendency to rely on transit as their primary mode of transport. Geographic concentrations of members of these groups are mapped to indicate where a high number of potential transit users live within Ohio. Second, demand related to development patterns is based on overall population and employment densities by county. Higher density areas, by definition, will have more people living within walking distance of a given transit stop than in lower density areas, thereby increasing the potential for transit ridership. Density was then used to calculate the level of transit service that is most appropriate for an area.

Transit RelianceThe American Community Survey 2008-2012 5-Year Estimates dataset was the primary source for each of the variables used to analyze the level of transit reliance. Data at the block group level provided detailed information on the distribution of each demographic and socioeconomic variable within the State of Ohio. Based on discussions with the study team, the four characteristics associated with strong transit use chosen for this study were: seniors 65 years or older, low income (150% of poverty level) individuals, households without private vehicles, and persons with disabilities. To create the transit reliance index, we used absolute population rather than proportion of the population, i.e. 1,500 people with low-income rather than 20% of the population. This approach helps to balance the interest in showing both relative and absolute reliance. Using the proportion of the population, or percentages, does a good job highlighting relative reliance by showing areas with relatively high concentrations of reliance. However, that approach does not take into consideration the fact that some areas with high relative reliance may represent a small group of individuals. Using data for the entire state, each of the four variables were then broken into five groups using natural breaks1, and each block group was given a score, one being the lowest and five being the highest. Figure A-1 shows the break points for each characteristic.

Figure A-1 Transit Reliance Score Breakpoints

ScoreDemographic and Socioeconomic Characteristics (absolute population)

Seniors (65 or older) Low-Income Individuals Persons with Disabilities Zero-Vehicle Households1 0 - 98 0 - 157 0 - 55 0 - 342 99 - 179 158 - 312 56 - 106 35 - 903 180 - 275 313 - 500 107 - 170 91 - 1874 276 - 406 501 - 766 171 - 273 188 - 3685 407 or more 767 or more 274 or more 369 or more

After assigning each block group a score, we summed the score for each characteristic, resulting in a number from 4 to 20, called the “Transit Reliance Index.” Block groups with higher index values have a greater number of seniors, people with disabilities, low-income individuals, and/or zero-vehicle households. Residents living in block groups scoring a “Very High” mark are most likely to rely on transit. As shown in Figure A-2, a block group within Hancock County has been assessed a score of 11 relative to all other block groups within Ohio.

1 “Natural breaks” is a data classification method that partitions data into classes based on natural groups in the data distribution. Natural breaks occur in the low points of valleys of a histogram.



Index Transit Need Level4 – 6 Very Low7 – 9 Low10 – 12 Low – Moderate13 – 15 Moderate – High16 – 18 High19 – 20 Very High

Figure A-2 Transit Reliance Index Calculation Sample (Block Group in Hancock County)

Transit Supportive Development PatternsAs mentioned earlier, population density and employment density were used to provide an estimation of potential transit demand based on development patterns. Density is the largest single factor influencing transit demand because the number of people within walking distance of a transit service determines the market size. Transit services can typically attract a portion of the people living within ¼ to ½ mile of the transit line or station. Accordingly, if there are more people living within walking distance, there are more people to use the service. It is also true that high density areas have less parking and are more likely to charge for parking, both of which are factors that make transit relatively attractive.

Transit Mode/ Service Frequencies Population per Acre Jobs per Acre

Flex Bus 0.5Community Circulator 2Local Bus 60 minutes 8 - 16 4 - 8 30 minutes 16 - 31 8 - 16 15 minutes 31 - 47 16 - 24 10 minutes 47 - 92 24 - 48 <= 5minutes > 92 > 48Bus Rapid Transit 26 - 52 > 13Light Rail 31 - 78 > 15

Figure A-3 Population and Employment Density by Transit ModePopulation and employment densities can also be used to provide an indication of the type and frequency of service that would be most appropriate. As shown in Figure A-3, local bus services require eight or more residents per acre or four or more jobs per acre, bus rapid transit (BRT) 26 to 52 persons per acre or more than 13 employees per acre, and light rail 31 to 78 residents per acre or 15 or more jobs per acre. Corridors with high densities, therefore, can support higher frequency, higher capacity transit modes, like light rail or bus rapid transit. Corridors and communities with lower densities are better matched with lower frequency services or service types.

Service frequencies also have a strong impact on the types of riders who will use transit. Infrequent service is inconvenient, and typically serves residents and workers who have few alternate transportation options. Frequent, convenient service, on the other hand, can attract travelers who choose to take transit rather than other alternatives. However, while frequent service is clearly desirable, it is more expensive to operate. As a result, transit service levels must be matched well to demand.



The 2010 U.S. Census and 2011 Longitudinal Employer-Household Dynamics (LEHD) were used in this analysis, which provided total population and number of jobs at a census block level. Population density and employment density were then calculated as persons per acre and jobs per acre, respectively. Similar to the scoring system in the transit reliance index, each census block is assigned a score of 0 to 12 based on its population and employment densities. The index values for population and employment density in every census block were then added together in order to get the score of the composite density value. As shown in Figure A-4, the composite score represents appropriate transit service frequency by census block.

Figure A-4 Composite Transit Service Design Index

Site Visit with Transit Agencies In addition to the quantitative analysis of the transit market, the Nelson\Nygaard team conducted site visits to all 62 transit agencies in the State of Ohio. The purpose of the site visit was to further identify opportunities and challenges associated with transit service. In-person interviews with representatives of the transit agencies allowed us to learn about the services, review and refine existing data on their operations, and discuss key issues and concerns.

Our approach to conducting the site visits were as follows:

• Developed interview guide/data request list. Both the interview guide and requested data varied by transit agency size and type (rural and urban). The meetings were focused around understanding existing operations, future plans, challenges and opportunities, and agency perspective on needs.

• Prepared corresponding fields in database in order for the information and findings to be tracked.

• Scheduled interviews with transit agency staff. Data request list was shared in advance so that staff had time to prepare and collect data, as needed.

• Held interview/meeting with agency staff. Consistent with stakeholder interviews, the interviews with transit agency staff was conducted confidentially to allow participants to speak frankly and openly about opportunities and challenges.

• Incorporate gathered information into market analysis. Once meetings were held, Nelson\Nygaard used the findings from the interviews as qualitative data to support the transit opportunities and challenges for each county.

Index Mode / Frequency< 1 > 60 min1 – 2 60 min2 – 4 30 min4 – 6 15 min6 – 12 10 min≥ 12 <= 5 min

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