IMPACTS OF ACCESSIBILITY, CONNECTIVITY AND MODE CAPTIVITY ON TRANSIT CHOICE

Transcription

1 U. S. Department Federal Transit of Transportation Administration IMPACTS OF ACCESSIBILITY, CONNECTIVITY AND MODE CAPTIVITY ON TRANSIT CHOICE March 2005 Final Report Percent age of Tra nsit U se 100% 80% 60% 40% 20% 0% Transit Captives Auto Captives (auto better) disutility difference (transit better) with captives without captives

2 IMPACTS OF ACCESSIBILITY, CONNECTIVITY AND MODE CAPTIVITY ON TRANSIT CHOICE Final Report March 2005 Prepared by Xia Jin with Edward Beimborn and Michael Greenwald Center for Urban Transportation Studies University of Wisconsin Milwaukee Milwaukee, Wisconsin Prepared for U.S. Department of Transportation Federal Transit Administration Through The Great Cities University Transportation Consortium ii

3 EXHIBIT IX REPORT DOCUMENTATION PAGE REPORT DOCUMENTATION PAGE Form Approved OMB No Public reporting burden for this collection of information is estimated to average 1 hour per response, including the time for reviewing instructions, searching existing data sources, gathering and maintaining the data needed, and completing and reviewing the collection of information. Send comments regarding this burden estimate or any other aspect of this collection of information, including suggestions for reducing this burden, to Washington Headquarters Services, Directorate for Information Operations and Reports, 1215 Jefferson Davis Highway, Suite 1204, Arlington, VA , and to the Office of Management and Budget, Paperwork Reduction Project ( ), Washington, DC AGENCY USE ONLY (Leave blank) 2. REPORT DATE March, TITLE AND SUBTITLE IMPACTS OF ACCESSIBILITY, CONNECTIVITY AND MODE CAPTIVITY ON TRANSIT CHOICE 6. AUTHOR(S) Xia Jin, Edward Beimborn, and Michael Greenwald 7. PERFORMING ORGANIZATION NAME(S) AND ADDRESS(ES) Center for Urban Transportation Studies University of Wisconsin-Milwaukee Milwaukee, Wisconsin, REPORT TYPE AND DATES COVERED Draft Report 5. FUNDING NUMBERS 8. PERFORMING ORGANIZATION REPORT NUMBER 9. SPONSORING/MONITORING AGENCY NAME(S) AND ADDRESS(ES) Midwest Universities Transportation Consortium University of Alabama-Birmingham 10. SPONSORING/MONITORING AGENCY REPORT NUMBER 11. SUPPLEMENTARY NOTES 12a. DISTRIBUTION/AVAILABILITY STATEMENT 12b. DISTRIBUTION CODE 13. ABSTRACT (Maximum 200 words) It is the objective of this report to examine the way that transit service factors such as accessibility and connectivity can be used to define mode captivity, and seek to incorporate these factors in mode split models to see whether segmentation between the captivity groups can lead to better methods of forecasting. Individual trip data were segmented into transit captive, auto captive and choice users based on information about private vehicle availability, transit connectivity and distance from a transit stop. Traditional transit mode split models are compared to models that segment users into choice and captive groups. The results suggest that traditional models underestimate the variation in mode choice for captive users, while overestimating the attractiveness of transit for choice users. Incorporating mode captivity factors can improve the accuracy of the logit model, either by segmenting the market or by employing the factors as independent variables. The explanatory power of the models will largely increase when captivity conditions are used in the equation to predict transit use. Additionally, among choice transit users, differences in travel times between automobile and transit modes does little to influence mode selection; while automobile ownership, and out-of-vehicle time are the most important factors in terms of influencing mode choice. 14. SUBJECT TERMS Transit Service Market, Mode Captivity, Transit Accessibility, Transit Connectivity, Mode Split Models, Travel Mode Choice, Captive users, Choice riders, Transit Market Segmentation 15. NUMBER OF PAGES PRICE CODE 17. SECURITY CLASSIFICATION OF REPORT Unclassified 18. SECURITY CLASSIFICATION OF THIS PAGE Unclassified 19. SECURITY CLASSIFICATION OF ABSTRACT Unclassified 20. LIMITATION OF ABSTRACT

4 DISCLAIMER This document is disseminated under the sponsorship of the United States Department of Transportation, Federal Transit Administration, in the interest of information exchange. The United States Government assumes no liability for the contents or use thereof. The United States Government does not endorse products or manufactures. Trade or manufacturers names appear herein solely because they are considered essential to the contents of the report. iv

5 ACKNOWLEDGEMENT We would like to thank Jon Ausman of Florida DOT and Marc Cooper at URS Grenier for their technical assistance in the early stages of this project. We would also like to express our gratitude to Bill Stein at the Portland Metropolitan Services District for his assistance in retrieving archived data needed for this analysis. We would also like to thank Profs Alan Horowitz and Zhong-Ren Peng of the University of Wisconsin-Milwaukee and the draft report reviewers for their input and helpful comments on this project This paper was developed as part of work being conducted by the Great Cities University consortium under the lead of the University of Alabama at Birmingham using funds provide by the Federal Transit Administration of the U.S. Department of Transportation. Additional support for the project was also provided through the Midwest Regional University Transportation Center and the University of Wisconsin-Milwaukee. The opinions expressed are the product of independent university work and not necessarily those of the sponsoring agencies or of the agencies supplying data for the project. Impacts of Accessibility, Connectivity and Mode Captivity on Transit Choice v

6 EXECUTIVE SUMMARY The objective of this report to examine the way that transit service factors such as accessibility and connectivity can be used to define mode captivity, and seek to incorporate these factors in mode split models to see whether segmentation between the captivity groups can lead to better methods of forecasting. The data for this study comes from the Portland, Oregon 1994 Household Activity and Travel Diary Survey, the Regional Land Information System for the Portland Area, the U.S. EPA Fuel Economy Database, and the U.S. Dept. of Energy. Individual trip data were segmented into transit captive, auto captive and choice users based on information about private vehicle availability, transit connectivity and distance from a transit stop. Traditional transit mode split models are compared to models that segment users into choice and captive groups. The results suggest that traditional models underestimate the variation in mode choice for captive users, while overestimate the attractiveness of transit for choice users. Incorporating mode captivity factors can improve the accuracy of the logit model, either by segmenting the market or by employing the factors as independent variables. The explanatory power of the models will increase when captivity conditions are used in the equation to predict transit use. A multinomial regression model was developed to predict transit and auto captivity. The result was disappointing. The model widely overestimate choice users while severely underestimate captive users. At this point, auto captivity is still hard to predict. Auto captivity is affected by many other factors besides personal characteristics incorporated in the model. Additionally, among choice transit users, differences in travel times between automobile and transit modes does little to influence mode selection; while automobile ownership, and out-of-vehicle time are the most important factors in terms of influencing mode choice. Impacts of Accessibility, Connectivity and Mode Captivity on Transit Choice vi

7 TABLE OF CONTENTS DISCLAIMER...iii ACKNOWLEDGEMENT...iv EXECUTIVE SUMMARY...v TABLE OF CONTENTS...vi LIST OF FIGURES...viii LIST OF TABLES...ix CHAPTER 1: INTRODUCTION THE NEED OF TRANSIT MARKET ANALYSIS TRANSIT SERVICE MARKET OBJECTIVES AND SCOPE REPORT ORGANIZATION...7 CHAPTER 2: LITERATURE REVIEW TRANSIT S CURRENT MARKET SHARE FACTORS INFLUENCING MODE CHOICE CAPTIVE USERS VS. CHOICE RIDERS MODELS IN ESTIMATING TRANSIT RIDERSHIP SUMMARY...38 Impacts of Accessibility, Connectivity and Mode Captivity on Transit Choice vii

8 TABLE OF CONTENTS CHAPTER 3: PROJECT APPROACH AND DATA SOURCES FACTORS RELATED TO MODE CAPTIVITY DATA SOURCES SEGMENTATION OF THE MARKET BY ACCESSIBILITY AND CONNECTIVITY LOGIT MODE SPLIT MODEL...49 CHAPTER 4: ANALYSIS AND RESULTS DATA SUMMARY MARKET SEGMENTATION TRAVELER CHARACTERISTICS AND CAPTIVITY LOGIT MODEL FOR WORK TRIPS LOGIT MODEL FOR NON-WORK NON-SCHOOL TRIPS MODE CAPTIVITY MODELS...83 CHAPTER 5 CONCLUSIONS...87 REFERENCES...92 APPENDIX...97 A SAMPLE OF THE TRAVEL DIARY SURVEY...97 B DATA ITEMS COLLECTED IN THE SURVEY C REGRESSION RESULTS FOR WORK TRIPS D REGRESSION RESULTS FOR NON-WORK NON-SCHOOL TRIPS E REGRESSION MODEL FOR MODE CAPTIVITY Impacts of Accessibility, Connectivity and Mode Captivity on Transit Choice viii

9 LIST OF FIGURES Figure 1.1. Logit mode split with and without captivity (1)...3 Figure 2.1. Estimation of the Decay Function (13)...16 Figure 3.1. Trip decision process (1)...42 Figure 4.1. Mode captivity by gender...60 Figure 4.2. Mode captivity by race...61 Figure 4.3. Mode captivity by age group...62 Figure 4.4. Mode captivity by licensed...63 Figure 4.5. Mode captivity by pay to park...65 Figure 4.6. Captivity by number of household vehicles...64 Figure 4.7. R-square values for work trip models...70 Figure 4.8. Exp (B) for Variable Vehicle Cost...72 Figure 4.9. Exp (B) for number of vehicles in household...73 Figure Exp (B) for out-of-vehicle time...74 Figure Exp (B) for number of vehicles in household...80 Figure Exp (B) for number of vehicles in household...81 Figure Exp (B) for vehicle network time...82 Impacts of Accessibility, Connectivity and Mode Captivity on Transit Choice ix

10 LIST OF TABLES Table 2-1 Demographic and Socioeconomic Variables...18 Table 2-2 Auto Dependency and Balanced Transportation Compared...29 Table 3-1 Conditions for Acceptable Transit and Automobile Service...43 Table 3-2 Variables and Criteria for Segmentation...48 Table 4-1 Transportation Activity Estimates...53 Table 4-2 Trip Summary by Travel Mode...53 Table 4-3 Trip Summary by Trip Purpose...54 Table 4-4 Number of Trips by Mode Captivity (work trips)...56 Table 4-5 Table 4-6 Number of Trips by Mode Captivity (non-work non-school trips)...56 Model Summary for Work Trips...68 Table 4-7 Model Summary for Non-Work Non-School Trips...77 Table 4-8 Parameter Estimates...85 Table 4-9 Model Goodness-of-fit Statistics... Error! Bookmark not defined. Impacts of Accessibility, Connectivity and Mode Captivity on Transit Choice x

11 INTRODUCTION CHAPTER 1: INTRODUCTION 1.1 THE NEED OF TRANSIT MARKET ANALYSIS Knowing the market is the key to success with any product, including transit services. As a result of the nation s growing population, increased levels of traffic congestion and environmental and energy concerns in many urban and suburban areas, more attention has been paid to public transit systems. In the past two decades, many studies have been conducted to explore the competitive environment for public transit. Today transit competes with the automobile in an environment of low densities, dispersed trip patterns, abundant free parking, cheap fuel prices, and inhospitable walking environments. Rapid decentralization of population and employment over the past several decades has chipped away the U.S. transit industry s market share. Transit organizations are faced with the challenge of attracting people back to public transit using a variety of ridership-building strategies such as improving transit services, implementing transit signal priority policy, encouraging transit-friendly land use development, etc. This report presents a study of transit market identification, as a means to develop more accurate transit forecasting and better service design. Knowing the market is the key to success with any product, including transit services. As is the case with many other products, transit services can improve consumer s day-to-day quality of life, by providing additional travel choices. Understanding transit availability and desirability is critical.in order to know how the transit services should be designed. Given that perception, market analysis plays an important role in transit planning and decision-making. A critical component to successful market analysis is to find accurate evaluation techniques to assess market availability and demand. By applying these, it becomes much easier to determine which routes are under-performing, to find where latent demand exists, and to design effective, targeted services and promotions. Impacts of Accessibility, Connectivity and Mode Captivity on Transit Choice 1

12 INTRODUCTION 1.2 TRANSIT SERVICE MARKET Customers to the transit service market can be classified into two groups: captive riders and choice users. Customers for transit services can be classified into two groups: captive riders and choice users. Captive riders are those who have no choice other than public transportation as a means of travel. They do so because of a variety of possible constraints, including age, disability, income or family circumstances, etc. In contrast, choice users use transit because they have a realistic transit options available that connects their origin and destination at times that meet their needs. Choice of transit occurs when travelers feel that the transit option is superior to other choices in terms of time, cost, convenience and comfort. Similarly, those who do not use transit can be classified into two groups, those who are captive to automobile or some other mode, and those who have options and choose automobiles. Auto dependents are people who feel they must use their cars for a variety of reasons, such as lack of service connecting origins or destinations, or scheduling limitations. Traditionally, transit market share is defined as the number of transit trips made divided by the number of trips that could have been made by transit as a viable option. However, the true population that has a feasible transit choice is often poorly represented. Transit does not connect all locations at all times; it generally only provides acceptable services to a small part of a region s population. For many trips, transit service is not an acceptable choice because of routing, scheduling or lack of access. On the other hand, some trips are made with no private vehicle available, so the travelers must use transit no matter how poorly transit performs. In both situations, it is meaningless to include those trips in mode choice models, since these users have no choice and to do so could decrease the explanatory ability of the models. Impacts of Accessibility, Connectivity and Mode Captivity on Transit Choice 2

13 INTRODUCTION Logit mode choice models use an S-shaped curve to represent mode split by relative disutility of the modes (Figure 1-1). Usually the curve is done on a continuous scale without recognition of captivity. In that case the mode share for transit could be very close to 100% if transit service is overwhelming better than auto service. Because of the existence of auto captives and transit captives, the variation for transit market share is much smaller. 100% Mode split models can be modified to include a captivity factor that represents the portion of persons in a zone that are transit captives or automobile captives. Percent age of T ransit Use 80% Auto Captives 60% 40% 20% Transit Captives 0% (auto better) disutility dif ference (transit better) with captives without captives Figure 1-1 Logit mode split with and without captivity. (1) Impacts of Accessibility, Connectivity and Mode Captivity on Transit Choice 3

14 INTRODUCTION 1.3 OBJECTIVES AND SCOPE Mode split models can be modified to include a captivity factor that represents the portion of persons in a zone that are transit captives or automobile captives. This may provide a better representation of transit choice since it only applies the equation to those who actually have a choice rather than to the entire population. If auto and transit dependency are known they can be included as a captivity term in the model as shown in Equation 1-1. Pr (T) = Pr (TCaptive) + Pr (TChoice) * [1- Pr (ACaptive)- Pr (TCaptive )] 1-1 Where Pr (T) = Probability of selecting transit compared to automobile modes of travel, Pr (TCaptive) = Probability of user being a transit captive Pr (TChoice) = Probability of user choosing transit as a choice user Pr (ACaptive) = Probability of user being a auto captive For example in Figure 1-1, it is assumed that there are 10% transit captives and 40% automobile captives. Therefore, there are 50% choice users. The probability of selecting transit varies from 0.1 to 0.6 overall, rather than from 0 to 1 in a traditional logit approach. Given the concerns above, mode captivity needs to be fully understood to predict transit usage with greater accuracy when these factors are incorporated into choice models. Generally, only limited information from census data, such as income and auto ownership, is used in the transit modeling process. Other data that related to mode captivity, such as origin destination patterns, transit accessibility, level of service, and household circumstances are seldom linked in a useful way to define transit markets. Impacts of Accessibility, Connectivity and Mode Captivity on Transit Choice 4

15 INTRODUCTION A system to link these data as well as a more useful definition of market size and characteristics could be very useful for transit operations, transit planning and for policy. Emerging methods such as Geographic Information Systems (GIS) and advanced Public Transportation Systems technologies provide a potentially useful framework for a more improved data system for transit decision-making. Work with the TLOS system has indicated that conventional wisdom about transit service coverage seriously overestimates the number of individuals that have adequate transit service. The Transit Level of Service software (TLOS) developed by the Florida Department of Transportation (2) provides perhaps one of the most advanced techniques for the analysis of transit access and availability of service. TLOS uses GIS tools to do a detailed analysis of local street networks and transit schedules to determine a transit level of service, defined as the number of person (or job) minutes of service provided to users that fit set criteria for walking and waiting time. Actual stree t paths walk buffers, and service schedules are used to determine if transit service is, in fact, available to users. Work with the TLOS system has indicated that conventional wisdom about transit service coverage can seriously overestimate the number of individuals that have adequate transit service. Experience with these methods indicates that far fewer individuals have adequate transit service to meet their travel needs than had been previously thought. This leads to a need to rethink how transit and travel markets are defined and to develop cleared definitions of market segments for use in transit service planning. Impacts of Accessibility, Connectivity and Mode Captivity on Transit Choice 5

16 INTRODUCTION The goal of this project is to develop tools to better represent the true market size for public transit, which leads to more accurate transit ridership forecasting and better service design. The objectives are: 1. To examine the way transit service factors such as accessibility and connectivity relate to mode captivity, and 2. To incorporate the factors in mode split models to see whether segmentation between the captivity groups can lead to better methods of forecasting. A deeper understanding of transit market is essential in order to provide a rational transit service and to plan for future services. The hypothesis tested in this study is that transit usage is highly dependant upon the circumstances of the traveler and availability of acceptable service, and that it is possible to predict transit usage with greater accuracy when these factors are incorporated into choice models. A deeper understanding of transit market is essential in order to provide a rational transit service and to plan for future services. Transit planning and management can be greatly enhanced with better understanding about the elements of the market they serve. The methods developed will have a great potential for service design and operations planning. This may be especially useful for the planning of suburban services or services to provide job access related to welfare reform. In addition, it will help transit agencies explain their role in travel by giving a clear understanding of who actually has transit service. Impacts of Accessibility, Connectivity and Mode Captivity on Transit Choice 6

17 INTRODUCTION 1.4 REPORT ORGANIZATION This report is organized into 5 chapters, including this introduction chapter. Following this chapter, Chapter 2 presents a detailed review of factors underlying individual mode choice behavior, as well as the issue of mode captivity. Similar works on modeling transit ridership are also studied. Chapter 3 describes the methodology and approach for the analysis, including a description of the data set used in this work. The trip information was from the Portland, Oregon 1994 Household Activity and Travel Diary Survey. Chapter 4 presents the mode choice models employed in this study, and explains the calibration results from the Portland case study. Mode captivity is determined by factors of transit accessibility and connectivity. Other factors such as trip costs and time are incorporated in the choice models. Multinomial regression model is developed to predict mode captivity. Finally, Chapter 5 summarizes the findings of the study and provides some thoughts for future work. Impacts of Accessibility, Connectivity and Mode Captivity on Transit Choice 7

18 LITERATURE REVIEW CHAPTER 2: LITERATURE REVIEW 2.1 TRANSIT S CURRENT MARKET SHARE This chapter presents a literature review of existing studies in the field of transit market identification. Transit s current market trends are summarized in the first section followed by a detailed review of the factors underlying individual mode choice behavior. The third section explores transit market in terms of captive users and choice riders, automobile dependency and its effects on transportation market are also included. Some models in estimating transit ridership are presented in the fourth section. The final section is a summary of the review. Decentralization and Transit Market Rapid decentralization of population and employment over the past several decades has chipped away the U.S. transit industry s market share. Cervero examined the nation s largest transit operators; performance statistics are used to compare suburban and urban transit operations (3). He indicated that transit s decline in suburbia is an outcome of many factors. Traditional fixed-route services radically linked to downtown were ill suited for lateral suburb-to-suburb journeys. The densities and built environment of suburbs are generally not conductive to transit riding. Suburbs also produce high rates of off-peak and weekend travel, when bus headways tend to be longest. Statistics from 1980 and 1990 census data from Summary Tape File 3A for the nation s largest metropolitan areas shows that paralleling the rapid suburban growth has been a diminishing role for transit with a sharper decline in transit s share trips of suburbanites than for metropolitan residents. TCRP report 27: Building Transit Ridership: An Exploration of Transit s Market Share and the Public Policies that Influence It, summarized the journey-to-work data from the 1990 Census of Population (4). It showed that ridership levels and market shares are very strongly associated with development densities, and are highest in the Impacts of Accessibility, Connectivity and Mode Captivity on Transit Choice 8

19 LITERATURE REVIEW core areas of the nation s most densely developed cities. Between 1980 and 1990, transit s traditional markets commute trips within core area, and trips from suburbs to the central area have been growing at a much slower rate than have intra-suburban, reverse commute, and exurban trips. Comparison of Trends in the United States and Canada Canadian experience shows that much higher public transit use coexists with slightly lower automobile use. Schimek described differences in automobile and public transportation use in Canada compared with that in the United States (5). The higher levels of gasoline taxation in Canada seems to have reduced gasoline consumption by controlling growth in the distance traveled, improving fuel efficiency and even slowing growth in the rates of car ownership. Transit use in Canada was always higher than that in the United States. Canada has about 40% more transit service and has 100% more rides. Schimek explains this as a consequence of the higher urban density in Canada rather than better transit service. Canadian experience shows that much higher public transit use coexists with slightly lower automobile use. There is no one-to-one substitution of transit trips for automobile trips. The increased public transit trips are much more likely to come from past public transit users than from past automobile users. Impacts of Accessibility, Connectivity and Mode Captivity on Transit Choice 9

20 LITERATURE REVIEW Rail Transit Long transit lines with high speeds and wide station spacing are desirable in the future to serve large, decentralized areas. Levinson provided a global overview of existing rail transit systems, their locations, extent, configuration, and ridership (6). The study focused on grade-separated metro and light rail systems. Levinson suggested that rail transit would become more important than it is today since urban areas will increase in number, size, and importance. Rail transit can provide needed transport capacity in heavily traveled corridors; relieve the overloading of existing surface transport services; ensure reliable, safe transport service and mobility with diverse mean, physical abilities, and choices; and enable high employment densities in central cities. In North America, rail transit ridership will continue to be hampered by cheap gasoline, low automobile travel costs, high car ownership, and continued decentralization of people and jobs. Long transit lines with high speeds and wide station spacing are desirable in the future to serve large, decentralized areas. Bus and park & ride access to stations will be essential. Bus rapid transit may provide faster, more effective and less expensive service than LRT system. Impacts of Accessibility, Connectivity and Mode Captivity on Transit Choice 10

21 LITERATURE REVIEW New Transit Ridership Infrequent riders might be a critical transit market and perhaps the key to build transit ridership and revenues. Infrequent riders might be a critical transit market and perhaps the key to build transit ridership and revenues. Oram and Stark found infrequent users (those riding twice a week or less) possessed a far larger share of the total market of transit users than had been previously thought, and they also generate a large share of total trips taken (7). The observations sustained even when seniors or other naturally infrequent users are excluded. It is also found that new riders are disproportionate as infrequent riders. New riders tend to be younger and have higher incomes; they are also very likely to stop riding. They are most often drawn to use transit for an occasional work trip, their riding rate grows with riding duration and they may diversify into off-peak use. They are insensitive to price and willing to pay more without riding less. Similarly, studies made by Polzin, Chu, and Rey showed the same trends of market shift from transit captive to choice users (8). They studied trends in dependency and transit-trip numbers from 1965 to Despite the decline in the size of the transit-dependent population, the number of transit trips has not declined. This finding indicates that the transit industry has, to some extent, been able to replace lost captive trips with new choice-traveler trips. Research about the Chicago Transit Authority s (CTA s) new Orange Line showed that, by the end of the first operating year, over 25% of the daily users were new to transit, representing former automobile commuters or new trips for which automobile was a candidate (9). Comparing new riders from other survey respondents, work and school were less significant as trip purposes, and Park & Ride was more important as a mode of access. New riders were more likely to be male, whites, own more automobiles, and have higher household incomes. Impacts of Accessibility, Connectivity and Mode Captivity on Transit Choice 11

22 LITERATURE REVIEW 2.2 FACTORS INFLUENCING MODE CHOICE Mode choice decisions are micro behaviors that, in aggregate, determine transit s market share. Among the many factors that affect individuals mode choice, cost and travel time might be the most understood and well incorporated factors. The purpose of this section is to explore the issues beyond cost and time. Factors underlying mode choice behavior are examined from four aspects: origin-destination patterns, level of service, transit accessibility and traveler characteristics. Urban Design and Land Use Patterns Urban design and land use patterns have long been considered fundamental to transit use. It may include variables of population density, employment density, land use balance, land use development policy, etc. Although many research has indicated the effects of land use patterns on transit use, its significance is not fully quantified because of the difficulty of properly defining and measuring the effects. A comprehensive analysis of the 1995 Nationwide Personal Transportation Study (NPTS) was conducted to explore transit use rates across various levels of MSA population scale and area density (8). Two types of geographic units were employed: metropolitan statistical area and urbanization classification. Findings showed that transit-market share increases as the MSA scale increases, and as the density increases. The effects of area scale on transit-market share are much larger for areas with higher density than for areas with lower density, and similarly the effect of area density is much larger for larger areas than for smaller areas. The authors cite a few observations as the logical basis for the importance of urban size in transit use. Urban size, regardless of density, may result in a level of transit service that provides more trip destinations being served by transit in absolute terms. Also, longer trips, which would be more likely in larger urban areas, are more conductive to transit use. Impacts of Accessibility, Connectivity and Mode Captivity on Transit Choice 12

23 LITERATURE REVIEW Transit Level of Service Transit quality of service is referred to comfort, headway, hours of service, service coverage, service information, parking facilities, pedestrian environment, amenities, safety and security, reliability, convenience, and cost, etc. It is generally accepted that a high level of transit service attracts more users. However, transit service is provided only in fixed schedule and routes to a certain area; and some of the LOS factors are difficult to measure, which may not be transferable from area to area. Contradictory results may be found from different urban areas. Syed used a factor analysis approach to identify the key factors that serve as determinants of public transit ridership from attitude survey responses in 1995 (10). The 8 key factors that determine transit use were bus information, on-street service, station safety, customer service, safety in route, reduced fares, cleanliness, and general attitude, in order of importance. Hamberger and Chatterjee identified the effects of fare and other factors on transit usage in a medium-sized urban area (11). A multiple regression model was developed for estimating ridership. Three variables were selected as significant and complemented factors. Bus fare has significant adverse effects on bus ridership. Express miles and employment have positive relationship with ridership. Then the author analyzed changes in ridership through elasticity measures. He indicated that: 1) small cities have higher fare elasticity because of less congested central business districts and lower parking costs; 2) peak-hour travel is less responsive to fare changes; and 3) choice riders and higher income groups may have larger fare elasticity. Impacts of Accessibility, Connectivity and Mode Captivity on Transit Choice 13

24 LITERATURE REVIEW The results indicated a promising effect of transit information systems in encouraging transit ridership. Abdel-aty, Kitamura, and Jovanis studied the effects of transit information on commuter propensity to use transit (12). A computer-aided telephone interview was designed and conducted, targeting a random sample in two areas in Northern California (Sacramento and San Jose). The results indicated a promising effect of transit information systems in encouraging transit ridership. Among the transit users, over 72% were either satisfied or very satisfied with the information they had about transit. Transit route map, waiting time, fare, walking time to transit stops and seat availability were the items that indicated by the transit users as factors that influence transit use, in an order of importance. As for non-transit users, the frequency of transit service was indicated as one of the most important information items. Also, waiting time, transit route maps, and hours of operation were among the most important items of transit information. An ordered probit model of likelihood that respondents will use transit at least 1 day per week if transit information is available illustrated several significant factors that influence transit use. Those factors were carpool, commute travel time, gender, age, and car ownership. About 38% of non-transit users indicated that they might consider transit use if appropriate transit information were available to them. Non-transit users who are currently driving and receiving traffic information would be more likely to use transit when transit information was available. Impacts of Accessibility, Connectivity and Mode Captivity on Transit Choice 14

25 LITERATURE REVIEW Transit Accessibility Transit accessibility refers to the ability of travelers to reach transit facilities, including bus stops and/or rail stations. Accessibility has been recognized as one of the most important factors that affect transit use. Transit accessibility refers to the ability of travelers to reach transit facilities, including bus stops and/or rail stations (13). Many factors contribute to transit accessibility, including reasonable proximity from the origin and the destination to the service; safe, pleasant, and comfortable walking pathways to transit facilities; and acceptable parking facilities for cars or bicycles, etc. Of the many factors, walking distance to transit facilities is recognized as an important determinant of transit use. A quarter mile (1320 feet) is the commonly accepted distance for a people willing to walk to use transit. Levinson and Brown-West indicated in their study that transit use sharply drop after the first 0.06 mile (316.8 feet), and diminish beyond 0.36 mile ( feet) (14). Cervero s research showed that there were high levels of rail travel if both the origins and destinations were in reasonably close proximity to a station (15). He suggested that within walking distance of a rail station, the physical characteristics of the surrounding environment matter little in shaping commuting choices, with the exception of density. Zhao conducted a transit onboard survey to determine the effect of walking distance on transit use (13). The results showed that transit use deteriorates exponentially with walking distance to transit stops. A decay function was developed to reflect the deteriorating trend, as shown in Figure 2-1. Transit walk accessibility was measured by the percentage of the population, weighted by the decay function, in a zone that within 0.5 mile from transit stops. It is indicated that increasing the limit of walking distance beyond 0.5 mile doesn t produce noticeable increase in accessibility. Impacts of Accessibility, Connectivity and Mode Captivity on Transit Choice 15

26 LITERATURE REVIEW The results showed that transit use deteriorates exponentially with walking distance to transit stops. Normalized Frequency y = e x R 2 = Walk Distance (ft) Figure 2-1 Estimation of the walk distance decay function. (13) Traditionally, transit accessibility is measured using the GIS air buffer to calculate the proportion of population or employees that are within quarter mile from bus stops or rail stations. This method assumes that the walking distance to a transit facility is equal to the straight line distance (or the air distance). But the real pathways are always longer, and must follow the actual street network. A person may live close to a bus stop but still doesn t have access to transit because there is no streets or walking paths that connect the origin and the stop, or there are some natural or man-made barriers such as canals, community walls, or fences surround a development that block access. Impacts of Accessibility, Connectivity and Mode Captivity on Transit Choice 16

27 LITERATURE REVIEW To improve the estimation of the transit service population, O Neill and Chou developed a network ratio method, in which the proportion of population was calculated as the ratio of total length of streets that are within quarter mile to that of all streets (16). The network-based method yielded lower estimates of accessibility than traditional buffer method. However the method doesn t work well for mixed density land uses. Zhao modified the method that took into consideration of the walking distance, population distribution, and existing barriers (17). TLOS... is based on the fact that transit service coverage is determined not only by the spatial separation between transit facilities to trip origins and destinations, but also by the frequency and hours of service. The Transit Level of Service software (TLOS) developed by the Florida Department of Transportation (3) provides an advanced techniques for the analysis of transit access and availability of service. TLOS employs a concept of percent person-minutes served (PPMS), which is based on the fact that transit service coverage is determined not only by the spatial separation between transit facilities to trip origins and destinations, but also by the frequency and hours of service. Actual street paths walk buffers, and service schedules are used to determine if transit service is available to users that fit set criteria for walking and waiting time. Such techniques allow one to quantify and visualize the mobility provided by a transit system at different times of the day and week at any location within the system's service area. Kittelson & Associates (1999) developed a software package to analyze fixed-route service using TLOS output of PPMS. The mode split value is adjusted by multiplying the number of non-transit trips by the PPMS value before the auto trips being applied to the mode split equation. The adjusted mode split value reflects the mode share for the area and time for which transit service is available (18). The equation is as follows, Adjusted Mode Split = # of # of transit trips transit trips + PPMS # of auto trips 2-1 Impacts of Accessibility, Connectivity and Mode Captivity on Transit Choice 17

28 LITERATURE REVIEW Socioeconomic and Demographic Characteristics Socioeconomic and demographic characteristics are usually mentioned together in transportation planning processes. They both describe traveler s characteristics and both have impacts on transit use. However they represent different categories of variables, as listed in Table 2-1. Table 2-1 Demographic and Socioeconomic Variables Demographics Population Number of Households / Families Household Size / Family Size Age Family Life Cycle Marital Status Race Nationality Religion Socioeconomics Education Occupation Income Home Ownership (owner versus renter, type of dwelling, mobility / stability) Automobile Ownership (number and type of vehicles owned) Social Class Extensive research has been done in evaluating the impacts of socioeconomic and demographic characteristics on travel behavior. However, contradictory findings were observed in different research. Some research found that elderly is more likely to ride transit, but others indicated that they are more dependent on automobiles, either as the driver or as passengers. Also, income is indicated to be significant in affecting Impacts of Accessibility, Connectivity and Mode Captivity on Transit Choice 18

29 LITERATURE REVIEW transit use in some research, while other studies concluded otherwise. In addition, individual s socioeconomic and demographic characteristics are often highly correlated, such as income and vehicle ownership. Rosenbloom and Fielding identified eleven groups as being more likely than average to use transit as their principal mode for commuting to work, independent of their income or the size or density of the metropolitan areas in which they lived (19). These are: workers with low incomes, workers with no household cars, workers with college education, blacks, Hispanics, workers with graduate school, workers age 17 to 29, women, Asians, immigrants (under 10 years in the United States), and workers with mobility or work limitations. The report further summarized the needs of transit services for different groups. Women: Women are more likely to use public transit for both work and non-work and require both new transit services and various non-transportation services to maintain their current ridership patterns. Services which provide more direct access to their work sites or address their domestic needs might maintain ridership. Female workers will require transit services that reflect the suburban or low-density character of their origin or destination, their concerns about personal security, and the nontraditional times at which they may commute. Transit concepts which increase the speed and the ease of their trip will positively affect working women. Impacts of Accessibility, Connectivity and Mode Captivity on Transit Choice 19

30 LITERATURE REVIEW People without cars and those with household income below $15,000: This group needs services with similar attributes as women. But there are also differences. Many low-income and carless workers may live in or near the central core of the city but commute to suburban areas. Feasible services for such workers would be relatively direct reverse-commute services, feeder services, or both from suburban transit stops and stations to their actual employment sites. Such workers might also require additional or targeted service information. Low-income and carless travelers tend to be more responsive to transit fare levels than other travelers. Ethnic and racial minorities: Blacks, Hispanics, and Asians are substantially more likely to use transit, even when controlling for income. Hispanic and Asian populations are becoming concentrated in older suburbs and may present special challenges to transit operators; route restructuring might better meet their transit needs. In addition, Hispanics are substantially more likely to carpool than other ethnic groups; subsidized vanpools may meet more of their needs. Those with a college degree: This group prefers transit concepts which provide a higher level of service, particularly providing direct service to their employers and offering various deviation and flex services. In addition, such riders may be more sensitive to time and speed, as well as the ease of using a system. Route restructuring, park-and-ride, express buses, and high-occupancy vehicle (HOV) lanes may all provide the kind of service that such travelers require. Impacts of Accessibility, Connectivity and Mode Captivity on Transit Choice 20

31 LITERATURE REVIEW People 17 to 29 and people with a high school degree: These two travel groups overlap significantly with the market niches already discussed. Direct services to employers, flexible and route deviation services, and express services are good options. At the same time, these groups will be slightly more responsive to cost attributes and may be very responsive to fare incentives, relaxed transfer policies, and subsidized van and carpools. Immigrants: Immigrants remain more likely to use transit, even after years in the United States and even when their income increases substantially. Most of the service concepts previously discussed will provide the service attributes such travelers seek. However, it may be very important for transit systems to target and market these service concepts to the actual origins and destinations and schedules of immigrant workers, rather than assuming such workers will continue to support the current services offered. People over 65: Although they are more likely to use transit for work and non-work trips, the market share among this market niche is falling in most service environments. On the other hand, elderly people are very responsive to certain service concepts, at least for non-work trips. Those that provide some of the convenience and safety of the car like taxis and demand-responsive services are very attractive to such users. However, elderly travelers have also been drawn to customized but regular transit concepts such as service routes, community buses, and deviation services. Impacts of Accessibility, Connectivity and Mode Captivity on Transit Choice 21

32 LITERATURE REVIEW 2.3 CAPTIVE USERS VS. CHOICE RIDERS The basic idea behind market segmentation is that most markets are not monolithic, but instead consist of submarkets that are relatively homogeneous in terms of certain critical characteristics. Obviously, captive users and choice riders have different mode choice behavior and travel behavior. They represent two groups of customers for transit market, who have different demand and requirement for transit services, and who show different sensitivity to the changes in transit level of service and planning policies. Knowledge of the market is the key to success with any product including transit service. This research will seek to segment the market into several submarkets with some homogenous characteristics, in this case captive users and choice riders, to improve the ability to forecast transit ridership. The basic idea behind market segmentation is that most markets are not monolithic, but instead consist of submarkets that are relatively homogeneous in terms of certain critical characteristics. Transit Cooperative Research Program (TCRP) report 36 provides a guideline to effectively use market segmentation in developing strategies to increase transit ridership. The report gives the definitions of market segments and market segmentation as follows. Market segments refer to groups of people or organizations that are similar in terms of how they respond to a particular marketing mix or in other ways that are meaningful for marketing planning purposes. Market segmentation is the identification of groups of customers or market segments that have similarities in characteristics or similarities in needs who are likely to exhibit similar purchase behavior and/or responses to changes in the marketing mix. (20) Impacts of Accessibility, Connectivity and Mode Captivity on Transit Choice 22

33 LITERATURE REVIEW Market segmentation can improve a transit agency s competitive position and better serve the needs of its customers. Market segmentation can improve a transit agency s competitive position and better serve the needs of its customers. The agency can identify and develop target market segments that represent the greatest potential for increased ridership, and make transit services appeal to these target markets. Research has showed that if transit agencies can identify and differentiate market segments that will remain relatively stable and can be effectively reached; they will achieve increases in ridership by marketing to these segments, beyond ridership increases possible from treating the market as homogeneous. Major benefits of market segmentation strategies include: Design responsive products to meet the needs of the marketplace. Develop effective and cost efficient promotional strategies. Provide insight on present marketing strategies. Provide data on which to base resource allocation decisions. Have available important data on which long-range planning for market growth or product development can be based. Identify and develop target markets that represent the greatest potential for increased ridership. Successfully position transit services to appeal to target markets. The thought above is the genesis of this project. Mode captivity needs to be fully understood to predict transit usage with greater accuracy and to incorporate these factors into choice models. Impacts of Accessibility, Connectivity and Mode Captivity on Transit Choice 23

34 LITERATURE REVIEW Transit Captives Transit captives are usually defined as those people who do not have an automobile available for their travel and therefore have no choice but to use transit. Transit captives are usually defined as those people who do not have an automobile available for their travel and therefore have no choice but to use transit. Examples include persons without an auto in their household as well as persons who cannot use an automobile because of their age, disability, or past driving behavior. These users are usually taken for granted with the assumption that they will always be there no matter how well the transit service does. Litman introduced the concept of transportation disadvantaged, which refers to people who have significant unmet transportation needs. People who cannot drive or do not have access to a motor vehicle, but who must make daily trips to work or school or other places can be deemed as transit captive users (21). A variety of possible reasons contribute to transit captivity. Indicators that may lead to transit captivity are: Households that do not own an automobile; People with significant physical disabilities that limit their ability to drive; Low-income households; Low-income single parents; People who are too young or old to drive; Recent immigrants from developing countries who do not have a license to drive; People who choose not to obtain a driver s license; People who have had their license taken away from them for various reasons. Impacts of Accessibility, Connectivity and Mode Captivity on Transit Choice 24