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Commuting alternatives in the United States

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Title:
Commuting alternatives in the United States recent trends and a look to the future
Physical Description:
viii, 108 p. : ; 28 cm.
Language:
English
Creator:
Ball, William L
University of South Florida -- Center for Urban Transportation Research
National Urban Transit Institute (U.S.)
Publisher:
University of South Florida, Center for Urban Transportation Research
Available through the National Technical Information Service
Place of Publication:
Tampa, Fla
Springfield, VA
Publication Date:

Subjects

Subjects / Keywords:
Ridesharing -- United States   ( lcsh )
Telecommuting -- United States   ( lcsh )
Commuting -- United States   ( lcsh )
Genre:
bibliography   ( marcgt )
technical report   ( marcgt )
non-fiction   ( marcgt )

Notes

Bibliography:
Includes bibliographical references (p. 107-108).
Additional Physical Form:
Also available online.
Funding:
Performed by the National Urban Transit Insitute in cooperation with the U.S. Dept. of Transportation under contract no.
Statement of Responsibility:
William L. Ball.
General Note:
F95-61 (Local FSEC accession no.)
General Note:
"December 1994."
General Note:
Publication No. DOT-T-95-11
General Note:
Final report.

Record Information

Source Institution:
University of South Florida Library
Holding Location:
University of South Florida
Rights Management:
All applicable rights reserved by the source institution and holding location.
Resource Identifier:
aleph - 020342266
oclc - 31898722
usfldc doi - C01-00007
usfldc handle - c1.7
System ID:
SFS0032130:00001


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..IL National .. .,QL Urban .. .JOQL T ranslt .... ,. '"ir Institute at the CENTER FOR URBAN TRANSPORTATION RESEARCH University of South florida Florida State University Florida A&M University Florida International University CoMMUTING ALTERNATIVES IN THE UNITED STATES: REcENT TRENDS AND A looK TO THE fUTURE William L. Ball Center for Urban Transportation Research December1994 CUTR Center for Urban Transportation Research College of Engineering, University of South Florida 4202 E. Fowler Avenue, ENB 118 Tampa, Florida 33620-5350 ph (813) 974-3120, fax (813) 974-5168

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, ... 1. Aceel-.on No. 1 C:ulog No. NUTI93USF4 1 ._ T ... --Dece mber 1994 COMMUTIN G ALTERNATIVES I N lliE UNITED STATES: RECENT S, O:l!lllllltMortC:... TRENDS A ND A LOOK TO lliE FUTURE 1 I. Pd:lmllnQ R .... NO, William L. Ball Research Associate t Ol'9111iUIIOn N..-.ll'let 10. Wbr11. Unt No. National Urban Transit Institute Center for Urban Transportation Research, University of South F lorida 1 $. CON:raei or Gt81lt No 4202 E. F owler Avenue ENB 118, Tampa, Florida 33620-5350 DTRS 93-G-0019 12. SIIO'ItoMQ AotMY """' lnd Mlnn tJ, l)pe of Rtl'Oit ar'ld P tl"iid COYtr.d Office of Research and Special Programs Administration July 1993 through December 1994 U.S. Department of Transportation Final Report Washington, D C 20690 tS HiiiM1 S upport ed by a grant from the U S Department of Transportation University Resear ch Institute P rogram Cha nging demographic and travel behavior characteristics have resutted in s i gnificant challenges for transportation decisio nmakers, planners and practitioners throughout the U S Efforts to meet these challenges have had vary ing degrees of s uccess and/or failure and, as we look to the future, It appears that dealing with existing and evolving transportation needs will only become more difficult. Commuting i n the U .S. has evolved substantially over the past several decades, from the more traditional commute with a majority of destinations in the central business district to new travel patterns where commuting from suburb to s uburb has grown to be the dominant commuting pattern This report was prepared to assist i n developing a thorough understanding of recent trends in commuting alternatives i n the U S Using data from the Census. American Housing Survey (AHS), and the Nationwide Personal Transportation Study (NPTS), ge n eral trends In commuting are presented. i nclud ing those r e l ated to mode choi ce vehicle occupa ncy. departur e t i me travel time and travel distance This is followed by a discuss i on of commuting a l ternatives including pubfoc transportation ridesharing, and working at home. Recent trends in the use of each commuting a ltern a tiv e are presented includ ing the commute share for a series of commuter subgr oups characterized by a variety of geographic demographic and housing charact eristics A discussion of the future outlook for each of the commuting attematives a lso Is present ed and includ es some basic reco mmenda tio ns as to what can be done to maint ain, and perhaps incr ease the commute mode share of each of the commuting alternatives. I 1 Ktr VlllfOl t 8. Olwtbullon &ttl ttl'ltnl Journey t o Work Commuting. Public Ava i lable to the public through the National Techn ical Inform ation Service Transportat ion, Ridesharing, Wor1
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--------

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CONTENTS Acknowledgements ... .. .... .. .... .... .. .... .. ... .. ... .... ... .. .. ........ . ..... ..... .... ................ .... ...... .. .... .. .... v ii Abstract .. .. ............. .... .. .... .. .... .. .... .............. ...... .... ............ .... .... .... .. .... ...... ..... .. ..... .... .. ..... ... . 1 Exe c utive Summary ........ ......... .... . ...... .. ... ... .... .... ...... .... .. .. .......... ...... ..... ........... ..... .......... 3 Sect i on 1: I ntroduction .......... .. ......... . .. ..... .... .... .... ......... .. .... .... .. . ... .... .. ...... ... ... .. ...... . 11 Section 2 : National Commuting Trends .............................................................. ........... ....... 1 3 Section 3: Public Transportation ................................ ... .......................................... ............... 3 3 Section 4 : Rldesharing .......... ............ ..... ..... ................. ........... .... .. ....................... .. ..... ........ . 43 Section 5: Working at Home ............... ......................... .... .. ... .. .... .. ..... ................ . .............. ... . 5 1 Section 6: The Future of Commuting Alternatives .. ... ... .. .. ......... .... .. .... .. ... .. ..... .. ..... .. . ..... ... 59 Appendix A : Urban Area Comparisons ..... ... .... .. .. .... ........... .... ................ .. .... .. ..... .. ..... ......... 77 Notes . ............ .. . .. ... . .. ........... .... .. .......... .... .................. ....... .......... ..... .......... ... . .. .... .. ........... 103 References .. ..... ..... . ..... .... ... . .... .. . .. ......... .... .............. ............. .............. ..... .. ... ......... ..... .... 1 07

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AcKNoWLEDGEMENTS This project i s made possib l e through a grantfromthe U.S. Department of Transportation, University Research Institute Program. Their support is gratefully knowledged. A National Urban Transit I nstitute was estab l ished as part of the lnterrnodal Surface Transportation Effic i ency Act (ISTEA) of 1991. Headquartered altha U niversity of South F l orida's (USF) Centerfor Urban T r ansportation Research (CUTR). the Institute is a consortium of USF, Florida Agricuttural and Mechanical University F l orida International University. and Florida State Un i versity. This documen t Is designed to provide a comprehensive look at the recent t r ends in the use of commuting alternatives in t h e United States. as well as to provide an assessment of the future of each alternative. After reviewing nationa l c ommuting trends in general, an assessment of commuting alternatives is provided, including public transportation, ridesharing and working at home. The report draws primarily from the 1 990 decennial census (and previous) and the American Housi ng Surveys conducted in 1985, 1 989, and 1991 In addition. some data are used as comp il ed from the 1990 Nationw i de Persona l Transportation Study (NPTS) a national survey sponsored by the Federal Highway Administ r at i on (FHWA). Nat i ona l U rban Tra nsit I nstitute Cen t e r for Urban Transportation Resea rch College of Engineering Univers ity of Sou t h Florida 4202 E. Fowler Avenue ENB 118 Tampa, Florida 33620-5350 (813) 974 3120 fax (813) 974-5168 Gary L. Bros c h Director CUT R Proj ect T e am: William L Ball Principal Investigator Joel R. Rey, Research A s sociate Victoria A. P erk, Research Associate Robert Nevins Student Research Assistant Review and comments from the following individuals are gratefully knowledged : Patricia Henderson, Steven E. Polzin Daniel Rudge. Ronald C. Sheck, Philip L. Winters

PAGE 9

ABSTRACT Changing demographic and tmvel behavior characteristics have resulled in significanl challenges for tJansportation decisionmakers planners. and practitioners throughout the U.S. Efforts to meet these challenges have had varying degrees of success and/or failure and, as we look to the Mure, it appears that dealing with existing and evolving tmnsportation needs will only become more Commuting In the U.S has evolved substantially over the past several decades, from the more traditional commute with a majority of destinations in the centJal business distlict to new travel. patterns where commuting from subUrb to suburb has grown to be the dominant commuting pattern. This report was prepared to assist in developing a thorough understanding of re cent trends in commuting alternatives in the U .S. Using data from the Census, American Housing Survey (AHS), and the Natio nwide Personal Transportation Study (NPTS) general tl'ends in commuting are presented, including those related to mode choice vehicle occupancy, departure time travel time, and travel distance This is followed by a discussion of commuting alternatives, including public tJansportation, ridesharing, and worl
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ExECUTIVE SUMMARY Changing demographic and travel behavior characteris tics have resulted in significant challenges for t ransporta tion decisionmakers. planners, and through out the u.s. Efforts to meet these challenges have had varying degrees of success and/or failure and, as we look to the fut ure it appears that dealing existing and evolving transportation needs will only become more difflcutt. This report was prepared to assist in developing a thor ough understanding of recent trends in commuting alter natives i n the U.S Using data from the Decennial Census. the American Housing Survey (AHS), and the Na t ionwide Personal Transportation Study (NPTS), gen eral trends in comm ut ing are presented, includ i ng those related to mode choice, vehicle occupancy departure t ime travel time and travel distance. This is followed by a discussion of commuting attematives. includ ing public transportation, ridesharing, and wor1
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All attemalives experienced declines in mode share in each of the past three decades the exception of working at home in the 1990s Distinguished as a separate mode starting i n 1980 ,the number ofwor1
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Travel distance to work appears to be Increasing as the proportion of shorter work trips has de clined, while the proportion of longer work trips has increased : Given that travel times remained stable and travel distance appears to have increased, the result clearly suggests an increase in average speed. Travel time to work was shortest in the midwest and longest in the northeast while the south and west had similar travel times In between Travel distance was shorter in the south and west relative to the northeast and midwest, as ind;. cated by t he proport i on of work trips in the "less than 1 mile" and 1 to 4 mile categories. Travel time to work for the Black population appeared to be generally longe r than for t h e population as a whole, w hile the Hispanic and elder ly populations were close to the national distribut ion Desptte the longer travel t imes to work. the data suggest t ha t the Black population have shorter distances to travel to work than the national average Travel d i s tance to work also appeared to be shorter t han the national average for both the Hispanic and elder ly populations. The travel time and travel distance to work for commuters below the poverty leve l were both lower than for the u.s. population as a whole. The data suggest t hat travel time and travel d i stance to work tot suburban residents were generally lo nger than for t he U S as a whole. In contrast, trave l time and travel distance for workers living outside the metropolttan area were much shorter than the national average. The travel distance for central ctty residents appears to be shorter t han the U.S. total, while travel time appears to be similar to t he U .S. as a whole (perhaps slightly shorter). COMMUTING ALTERNATIVE TRENDS AND MARKETS Recenttrends and potential markets for commuting alter natives are compiled and assessed tor public transporta tion, ridesharing, and working at home. Commuting through the use of these ahematives is reported for a variety of geographic demographic, and housing charac teristics Although much of the data confirms expecta tions regarding the tradttional characteristics of the users of commuting alternatives the infonna t i on is use ful since tt provides recent trends over a shorter period oftlme than is typically available in national databases. The American Housing Survey (AHS) is used to define potential mar kets which provides journey-to-work data in 1985 1989. and 1991. A summary of trends and !Tlarkets for these commuting ahematives is provided in Table 1. THE FUTURE OF COMMUTING AIJERNATIVES A discussion of t he future of each of these commuting' alternatives is also presented. These discussions are based primarily on t he ltterature a nd natio nal stu<1ies that have been conducted to assess the future outlook of each of t he respective alternatives. Recommendations are provided for each commuting alternative that may contrib ute to a greater probabiltty of maintaining. and pe rhaps increasing commute mode share. These recommenda tions are s u mmarized below. Public Transportation Four major recommenda tions are identified as being importan t tor the future success of public transportation based on review of several nationa l policy studies, along wrth other lite rature discussing the fut ure of public t rans portation. These recomme ndation s are iden t ified and discussed below. 1. Incorporate New Management Strategies The transtt system of lhe future cannot continue to operate based on the tradrt ional view of the t rans it orga niza tion In order to achieve success, transrt systems

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Tablel SummGrf of Mode Share Trends and Markets (AHS). percent Transit Ridesharing Wor1dng at Home 1985 1989 199 1 1985 1989 1991 1985 1989 1991 UNITED STATES 5.1 4.6 4.8 14.1 1 1 .8 12.0 3.0 2.6 2.6 REGION Northeast 12.4 10.7 11.4 12 .6 10.4 10.4 2.8 2.3 2.2 Midwest 3.4 3 3 3 4 12.8 10.5 10 7 4.1 2.9 3.2 South 2.6 2.2 2.4 16.5 13.1 12 8 2.4 2.2 2.0 West 3.8 3.9 3.7 13 .2 12 .7 13.7 2.6 2.9 3.2 DEMOGRAPHIC SUBGROUPS Black 15.3 14.7 13.8 18 .9 15.4 15.7 0.7 0 7 0.8 Hispanic 10.3 9.2 10 3 19.3 19.0 20.3 1.4 1 .5 1.4 (65+) 7 1 5 3 5.3 12.9 10.7 10.4 6 8 4.9 5.9 Poverty Level 8 5 6.8 7.5 17.7 17.0 16.3 6 7 5.4 5 3 RESIDEN11AL LOCA noN central Cly 11.5 10.7 10.7 13.0 12.1 12.5 2 0 1 7 1 .9 Subwb 3.1 26 3.0 13.9 11.3 11.1 25 2.4 2 4 Outs ideMSA 0 5 0.4 0.5 16.1 127 13.4 5.5 4.2 4.1 Urban 6.7 6.1 6.3 1 3.3 11.5 11.8 2.1 2.0 21 Rural 0.5 0.5 0.6 16.3 127 12.5 5.5 4 .2 4.0 HOUSEHOLD CHARACTERISncs Otmer 3.2 2.7 2.8 13.7 11.0 10.8 3.3 2.9 3.0 Renter 9.2 8.6 8.9 14.9 13.6 14 6 2.2 1.9 1.7 New Construction (4 years) 1.3 2.1 2.0 1 5.0 10.0 11.5 2.1 2.4 2.5 Moved in Last Year 5.3 5.3 5.8 15.7 13.9 14 7 1 .7 1.7 1.5 Mobile Home 0.6 0.3 0.6 19.4 16 .0 16.4 1 9 2.2 1.8 Severe Housing Problem 15.9 7 7 8.6 22.2 13.0 12.7 27 2.5 4.2 Moderate HOusing Problem 8.6 7 5 6.1 19.7 19.7 17.2 2.3 2.6 2.8

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' must foster a working env i ronment that can quickly and easily adapttothe changing needs ofijs users. Perkinson referred to ft as a service organ izatio n i n contrast to the more tradijionallnfrastructure organization Barker em phasizes the importance of involvi ng employees at all l evels i n the decisionmaking process Meyer's recom mendations included the need for a sales-oriented orga nizational structure. This approach to manag e ment i n the transportation i ndustry i s often referred to as management where t ransij systems find ways to trans port patrons by whatever means is most convenient and cost effective. 2. Focus on Traditional Transit Markets The transh industry should focus the majority of efforts on markets and services t h at they have tradaionally served well. Service for the suburb-to -cen tral c it y journey to work and circulation within the central has been the bread and butter" for most t ransa syste(lls in the past severa l decades Despije suburb-to-suburb travel becoming the predominant commute flow pattern growth i n ihe traditiona l suburb-to-central commute flow has been substantial. Efforts to serve suburb-to suburb travel wah fixed-route public transportation ser vice are extremely expens ive and have proven to be large ly unproductive. 3. Anticipate Future Market Opportunities for Specialized Services AHhough the focus shou l d be on tradftio n al transit mar kets transij systems should antic i pate future market opportunaies for specialized services. Niche markets will be the key to the industry's future beyond tradijional service. Examp l es of service concepts and markets that may be appropriate in the future for many transa systems include: ne i ghborhood trans i t serv i ces j itney services expanded paratransa fare strategies and payment methods targeted toward specific markets employer partnerships privatization and brokerage smaller vehicles transportation demand management strategies reverse commute services intermodal feeder/distributor services time transfer/pulse services An important research project for the transij i ndustry is about to begin as part of the Transtt Cooperative Re search Program. Enti tled Transit Marl
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implementation? New technology does not necessarily result in better se!Vice. The emp l oyees who contro l the t echnology must ensure that is used property so that potential benefits can be achieved Ridesharing Based on recent trends and a review of literature on ridesharing, four major recommendations are offered. These recommendations s te m from the need for carpool programs and Travel Demand Management (TOM) orga nizations in general to more effectively adapt to evolving demographic and geographic trends in the U.S. 1. Identify and Learn From Areas of Success TOM efforts need to be evaluated objectively so re sources can be focused on proven actions. In the process of evaluating carpoo l ing trends in loca l ized areas some geographic areas can be identified where carpooling has remained re l atively stable or even increased from 1 980 to 1990 both in absolute tenms and in commute share. These areas can be identified at any geographic l evel using Census data i.e .. county, place, census tract block group Addijional research should then be conducted on these successful areas to seNe as case stud i es to identify the reasons for success and what specific actions could be appl ied i n other areas. For example, a carpool program that selVes a county could review the trends in ca r pool share for each census t r act within that county. The characteristics of commuters residing In tracts i n which the carpool share remained stable or increased could be identified and analyzed along with the character istics of the commute (travel lime. origin/destination. etc.). Significant potential exists for learning from tracts exhibiting a greater propensity to carpool For guidance on the implementation of TOM measures, see Mak ing TOM Work in Your Community by CUTR and Implementing Effective Travel Demand Manage men/ Measures: A Series on TOM by Coms is, et al. 2. Reconsider Focus of Program The t raditional focus of carpoo l p r ograms has been on urban travel with the primary objective being to ma rket the program to employees of large businesses and com panies within major activijy centers Programs should consider focusing efforts on rural residents who commute long d i stances to cities Longer commutes, both in distance and time, have traditionally been an important element In the carpool decision. Based on an evaluation of carpooling trends at the county level i n North Carolina Hartgen suggests that serious consideration shou l d be given to replacing employer-focused programs. in urban areas with residence-based programs in rural areas. Agencies i nterested i n pursuing this type of program shou l d be aware that efforts such as these can resutt in some institutional conflicts between residential and employer-focused programs that seNe many of the same trips. Conflict usually a rises when trying to determine which program should receive credij for these trips 3. Use Target Ma(keting I n Section 4 of the fina l report the carpool share for the journey to work was presented for worker subgroups according to a series of demographic. geographic and housing characteristics. The purpose ofthis effort was to ident ify market segments that appear to have a greater probabi l tty of carpooling based on t h e resutts of AHS surveys. There is some disagreement in the literat ure regarding whether this type of infonmation is useful in pred i cting carpool fonmation. However a review of de script i ve statistics compiled from the AHS clearly ind i cates that certain market segments have a significantly greater carpool share than the national average Tradttionally, organizations charged w ith encouraging and facll"ating travel demand m anageme n t i nitiati ves. including rides haling have focused on the work des tina lion side of the commute and especially during peak travel periods, i .e., 6 a.m. to 9 a m This makes sense s i nce it Is logical to assume that workers wijh commute destina tions t h at are i n close proximity would be good candidates for carpoo l ing. I n addrtion nearly 62 percent of all vehicle trips made during the morning peak are home-based work trips The focus on this major market should continue However, marketing efforts should be considered In an effort to penetrate other more specifiC market segments Efforts t o penetrate specific market segments could be inrtiated with two distinctly different approaches. including

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emphasis on the residential end or emphasis on the employmen t end. Narrowing the focus through target marketing should reduce not only the cost of undertaking some marketing but also be more effective In reaching individualS who are more likely to pai11Cipate In a carpool. The two approaches are discussed below. Residential EndAs indicated previously, recenttrends in the use of carpools can be used to identify existing and evolving market segments that appear to have a greater probab il ity of becoming involved i n a carpool. Once these market segments have been ldentlfied,the specific char acteristics of these segments must be loca ted geographi cally within the region i n which a given TOM organization serves Fo r many characteristics, this can be accom plishe d using Census data, which provide demographic and housing i nfomnation at geographic leve ls down to the census tract and block group. Once certain tracts or block gro ups have been i dentified thai include concentrations of these market segments marketing efforts can be focused within t hese more geographic areas. Employment End-One of the primary objectives of most TOM organizations is the development of a database of potent ial carpool applicants and the preparation of matchlists for these applicants in order to assist in carpool fomnation The information collected from potential cants usually includes characteristics such as those used to distinguish market segments using the AHS. Individu als characteristics thai suggest a greater for carpool formation could be specifically targe ted for more aggressive marl
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Top-down support Is vital The organization must consider telecommuting as a reasonable and desirable anemative. Senior management must provide support. . Senior management support is necessary All managers and decisionmakers the or ganization must accept the idea and practice of te l ecommuting. Te lecommuters and their supervisors must be willing participants Both employees and managers must feet comfortable with telecommuting in tenns of its surtabilrty to per sonal work habits rts effects on social interaction and career advancement, and its impacts on management style and the organization. Training Is key Significantly higher perfor mance results a re noted when both the te l ecommuters and their direct supervisors par t icipated in telecommuting-specific training prior t o i nrtiating a program. Availability of adequate, cost-effective technology-It is essential that telecommuters have sufficient technological equipment to work at home. However, most of the lrterature finds that major investments are not necessary. It is clear that a better understanding of telecommuting and potential market will be necessary to property incorporate this technique into today's travel demand management arsenal. Knowledge on which jobs and individuals are amenable to the prospect oftelecommuting is important torts Mure success. as is understanding why people will or will not choose to participate in or support telecommuting. The success of subsequent telecommuting programs will depend on proper imple mehtation, the support of all parties involved and the avoidance of the that predecessors may have encountered. Since many benefits will be realized no matter if the level of implementation is national regional, or merely local, it is imperative that planners and decisionmakers concentrate on starting telecommuting programs, and not on factors or projec tions of Mure participation.

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INTRODUCTION Changing demographic and b'ave l behavior characteris tic s have resutted in significant chall e nges for transporta tion decision ma k ers planners. and practitioners through ou t the States Efforts to meet these challenges have had varying degrees of success and/or failure an d as we look to the future, it appears that deal i ng with existing and evolv in g transp ortatio n problems will only more difficun. The factors infl uencing transportati o n problems are sill'VIa r lrr growing metropo l itan areas througho ut th e nation. T he in creasing participation of women In the labo r force, the baby boom gene ratio n entering the labo r market. and suburbanlzationofdeve l opmen thaveallc ontributedgreaUy to p r ob l ems related to congestion, air qua lity, e n ergy safety, and the o v erall qua5ty of l ife. Commuti n g in the Un it ed States has evolved substantially over the past severa l decades, from th e more traditio nal commute wi th a majority of destinations in the central busi ness district to new travel patterns where commuting fro m s ub urb to subur b has gro w n to be the dominant commuting pattern These n ew patterns have be e n most effectively characterize d by Pisarski i n Commuting in Ame rica: A National Report on Commuting Patterns and Trends. p erh aps the most widely-referenced document on modern commuting in the United States. Th e purpose of thi s report is to provi de a foundation for the deve l opment of a thorough under standing of recent corn muting trends in the Un ite d States. Based on these trends and a rev iew of the l iterature the future of commuting and, specifically, comm ut ing atte rn atives i s discuss e d. The p rimary objective is to develop a complete understanding of recent trends in commuting anernatives and to offer opinions on the future of each alternative In this report. commuting alternatives include public trans po rtation, ridesharing, a nd working at home. OveMew of Report The report i s organized into s eve n major sections including this introduction and an append ix. Each ofthe subse quent sections is summarized bel ow Section 2 presents nati ona l commuting trends including data on commuting rel ative to all person al travel. mode choice. vehicle occupa ncy departure time to worl<, travel time to work and travel distance to work Section 3 reviews rec en t trends in the use of pubWc transportation for the journey t o work. The transit share of the journey to worl
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NATIONAL COMMUTING TRENDS Commuting in the U S. has evolved substantially over the past several decades. fl'om the more traditional commute w i th a majority of desfinations in the central business d i strict to new travel patterns where commuting from suburb t o suburb has evolved to be the dominant com mute fl o w pattern. Familiarity with the general character i stics and trends in commu ti ng in general is an important e l ement in the development of a thorough understanding of the commuting alternatives discussed in the remainder of this report. This section l ooks at national commuting trends using data from the Decennial Census, AHS, and NPTS. Trends are p resented for the follow ing travel beh avior areas: National Travel Summary -The national travel s um mary presents trends in all personal travel, including annual person trips, annual person miles of travel, person \rips per capita person miles of travel per and average person trip l ength. In addifi on,lhe distribution of person trips by trip purpose also is presented. Commute Mode Choice. Mode choice for the jour ney to work is summarized in terms of th e abso l ute changes in numbers of workers. as.weii as the change in mode share over time. V ehicle Occupancy-Data are presented regardi n g recent trends in vehicle occupancies includin g a summary of changes in t he absolute and percent share change in the use of the single occu pant vehicle and 2-, 3 and 4-person carpoo l s Departure Time to Work Departure time to work is summariz e d for the U.S and i ts regions. The data i nclude a look at the proportion of commuters depart i ng fo r work duri ng the morning peak hours (6 to 9 a.m.). Travel Time and Distance to Work In addition to presenting trends in travel time and distance to work for all U.S. commuters, this informatior:-also is pre sented by region for demograph i c subgroups and for commuters by residential locat io n.

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National Travel Summary According to the NPTS, U S population rose from over 197 rrillion in 1969to over 239 million in 1990 an Increase of 21 percent. The number of annual person trips increased 72 fromjustover 145 billion in 1969to nearly 250 billion in 1990. Similarty, a 65 percent increase was observed for annual person miles of travel from 1.404 billion in 1969 to 2,315 billion in 1990. The number of annual persons trips per capita increased fro m 736in 19691o 1 042 in 1990, an increase of 42 percent. Annua l person rriles of travel per capita inc reased 36 percent. from 7 ,120 miles in 9,671 miles in 1990. Average person trip l ength declined by 4 per cent, from 9 .67 miles in 1969 to 9.45 miles in 1990 Nearly 22 percent of all person trips are made as part of earning a l iving, includ in g commuting to work and other job-related trips According to th e 1990 NPTS, nea rly 62 percent of all vehicle trips made in th e morn ing peak (6 a.m to 9 a.m.) are home-based work trips.

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Table 2 Summary of National Travel 0 969 1977, 1983, and 1990 NPTS) 1989 1977 1983 ... %Change 1869-90 Persons (000) 197,213 213,141 229,.S3 238,416 21% Annual Person Trips COOO) 146,146 ,000 211 771,000 224, 385,000 249,582,000 72% Annual Person Miles ot Travel (000} 1,404.137,000 1,878,216,000 1,848,862,000 2,316,273,000 66% Annual PeJ$0n Trip$ ptr Capfta 736 994 978 1 ,0'2 4 2 % Annual Person Miles o f T rave l per Capita 7,12 0 8,817 1,484 9,671 36% Average P e r son Trip length (miles) 9 .67 8.87 8 68 9.45 Soure"' USDOT,fedoralligiMayAdmln-..,,1990-.,..;MPonontt/ 1990NPTS Datobooif. V ... ...,., Figure 1 Number and Petc:ent of Person Trip s by Trip Purpose 1990 NPTS (mUiions) Civic Educational, a n d Religious 28,397 Family and P erson al Sust.nus 1 03 ,608 Social and Recreational 61,799 Olher 1,831 Earn a Living 63,843 --------i-------

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Commute Mode Choice The number of workers using the private vehicle as the mai n means ofttansportation to work (driving alone and ridesharing) increased from 41.4 rrillion in 1960 to 99.6 rrillion in 1990, an Increase of 141 percent. The mode share Increased from 67 percent to 87 percent over the same time period. From 1980 to 1990, the number of workers driving to work alone inc reased from 622 million to 84.2 million. a growth rate of 35 pe rcent The share of work travel for driving alone i ncreased from 64.4 percent in 1980 to 73.2 percent i n 1990. All commuting atternatives experienced in mode share in each of the pastthree decades, with the one exception of working at home In 1990 Distinguished as a separate mode starting in 1980 the number of workers carpooling to work decreased from 19.1 million in 1980 to 15.4 rrillio n in 1990 a decline of 19 percent. The moae share also decl ined from 19.7 percent in 1980 to 13 .4 percent in 1990. The number of workers walking to wor k decreased from 6.4 rrillion In 1960 to 4.5 million in 1990, a decline of 30 percent. The walk to work mode share for these two years was 10.4 percent and 3.9 percent, respectively. From 1960 to 1990 the number of workers using public transportation as their main means of t ransportation to work declined 22 percent, from 7.8 million to 6 1 million. The resulting mode share for the work trip from 12.6 percent in 1960 to 5 3 percent in 1990. From 1960to 1980, the number of workers working at home fell sign ifi cantly from 4 7 rrillion to 2.2 million, a decline of 53 percent; however. the number increased to 3.4 million i n 1990, a 56 percent in crease in the 1980s As a result the work at home share declined from 7.5 percent in 1960 to 2.3 percent in 1980 and i ncreased to 3.0 percent in 1990. -------------11-------------

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Flgure2 Distn'butlon of Mode Choice for Commute to Work (1960.1990 census dato) Walk Public transportation Work at home Other means .1960 01980 IIIIIJ1990 Carpool 51Wo Flgure3 75 / 100% Growth Ra1es In Number of Workers by Commute Mode (1960.1990 census data) Private auto o r carpool Walk Public transportation Worlc at home Othet' means 30% 1980 1970 1 970-1980 0 19ao-199o llllilil1960-1990

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Vehicle Occupancy Vehicle occupancies dec l ined significantly from 1980 to 1990, as t he share for driving alone increased substantially and all categories of carpo o5ng (2person. 3-person, etc.) showed dec l i nes in share over the same time period The number of workers driving a lone increased 35 per cent. fro m 62.2 million in 1980 to 842 rriiUon in 1990 As a resun the p rop ortion of workers driving a lo ne increased from64.4 per cent to 73.2 p ercent over this time period The nu mber of wor k ers in eac h carpoo l cat egory decrtned from 1980 to 1990, in cluding a 9 percent decline for 2-person car p ools (13.3 million workers to 12. 1 million workers), a 40 percent de c l ine for 3-person carpoo l s (3 .4 mil lion workers to 2.0 milfion workers) and a 46 percent dec line for 4 or more person carpools (2 .4 milion workers to 1 3 rrillion work ers). From 1980 to 1990 the commute share de clined from 1 3 8 percentto 10.5 percentfor 2-person carpools, from 3 5 percent to 1.7 per cent for 3-perso n carpoo l s, and from 2 5 per centto 1.1 percentfor4ormoreperson carpools. -------------11-------------

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Figure4 Vehicle Occupancy for Commute to Work census dato) 80% 73% 60% I 1980 1990 1 40% 20% 3% 1% 0% Drive alone 2-person 3-person 4-person Other means FigureS Growth Rate in Number of Workers by Vehicle Occupancy (1980.1990 census dato) Drive alone 2-person carpool 3-person carpool 4-person+ carpool 01hermeans -60% -30% 0% 30% 60

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u.s. Northeast Midwest South West Departure Time to Work The proportion of U.S. workers departing for work between 6 and 9 a.m. was approximately 70 percent from 1985 to 1991 This same proportion by region was approximately 72 percent for the northeast and south, and 68 percent for the midwest and west. From 1985 to 1991 illle or no change was observed in the d is tribution for each region. In 1985,1989, and 1991, the proportion of U.S. workers departing for work was 21 percent between 6 and 7 a.m., 32 percent belween 7 and 8 a.m., and 17 percent between 8 and 9 a.m. The distribution of workers by departure time to work indicated virtually no change from 1985 to 1991. The same pattern also was observed for workers de parting in off-peak times with virutally no change in the percentage over time. Percent of Commutan Oeporfing for Work BetwMn 6 and 9 a.m. by Region (1985-1991 AHS) 60% 80% .1985 1989 &11991 100%

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Flgure7 Departure Time to Woct< (1985-1991 Amerlcon Housing SUMI'fl 12:00 a.m to 2:59a. m. 3 :0 0 a.m. to 5:59 a.m. 6 : 00 a.m. to 6 :5 9 a m 7:00 a.m. to 7:59 a m. 8:00 a.m. to 8:59 a.m. 9 : 00 a.m. to 9 : 59 a.m. 10: 00 a.m. to 3:59p.m. 4:00 p.m to 11 :59 p.m. 0% 10% 20% .1985 1989 @%11991 30% 40%

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Travel Time and Distance ta Work The distribution of travel times to work remained stable in all travel time categories from 1985 to 1991. In the U S approximately 35 percent of work trips took less t han 15 minutes, 34 percent took 15 to 29 minutes and 14 percent took 30 to 44 minutes Travel distance to work appears to be increasing as the proportion of shorter work trips has declined while the proportion oflonger work trips has increased. Given that travel times have remained stable and that travel distance appears to have increased, the clearly suggests an i ncrease i n average speed. Travel ti me to work was shortest in the mi dwest longest in the northeast, whil e the south and west had simil artravel times in between. Travel distance was shorter in the south and west relative to the northeast and midwest, as ind icated by the proportion of work trips in the "less than 1 mile" and "1 to 4 mile" catego ries. Trav el time to work for the Black population appeared to be generally longer than for tho population as a whole, while tho Hispanic and elderty populations were close to the national distribution Despite the longertravel times to work the data suggest that the Black popu lation have shorter distances to travel to work than the national average. Tra vel distance to work also appeared to be shorter than the natio nal average for both the H ispa nic and elderty populati ons. The trave l time and travel distance to work for commuters below the poverty level were both lower than for the U.S. population as a who le The data suggest that travel time and travel distance to work for suburban residents were generally longer than for the U.S. population as a whole. In contrast, travel time and travel distance for workers l iving outside the metropolitan area were much shorteithan the national average. The travel distance for central city residents appears to be shorter than the U S. total while t rave l time appears to be similar to the U.S. as a whole (perhaps slightly shorter)

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Figure a Travel nrne 1o Wortc, Uniiad Stallls (1985-1991 AHS) Less than 15 minutes 15to 29 minutes 30 to 44 minutes 45 to 59 m inutes 1 hour to 1 hour and 29 minutes 1 hour 30 minutes or more Works at home No fixed place of work 0% 10% 20% Flgure9 .1985 mE)1991 30% Trovel Distance 1o wortc, Uniiad Sla1as (1985-1991 AHS) Less than 1 mile 1 to 4 miles 5 to 9 miles 10 to 19 miles 20 to 29 miles 30 to 49 miles 50 miles or mora Works at home No fixed place of wor1< 0% 10% .1985 mm 199 1 40%

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Figure tO TI'CMII Time to Work by Region of 1he US. (1991 AHS) Less than 15 mirutos 15 to 29 minutes 30 to 44 minutes 45 to 59 minutes 1 hour to 1 hour and 29 mirlut
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Flgurel, Travel Distance to Wortc by Region of the U.S. (1991 AHSJ Less than 1 mile 1 to 4 miJes 5 to 9 miles 10 to 19 miles 20 to 29 miles 30 to 49 mil es 50 miles or more Works at home No fixe
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Flgunt12 Trove! nme to Work, SelaC'Iad Demographic Subgroups (1991 AHSI Less than 15 minutes 15 to 29 minutes 30 to 44 minutes 45 to 59 m inutes 1 hour to 1 hour and 29 minutes 1 hour 30 minute5 or more Works a t home No fixed pla<:e of work 10% 20% u.s. Black WfJ Hispanic lllllll Elderly 30% 40% SO%

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Flgunt 13 Travel Distance to Wolle, Selecllld Demographic Subgroups (1991 AHS) Less than 1 mile 1 to 4 miles 5 to 9 miles 10 to 19 miles 20 to 29 miles 30 to 49 miles SO miles or more No fixed place of work 10% 20% u.s. 1m Hispanic 111111 Elderty 30% 40% 50%

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Figunt14 Tea..t T"eme to Commi!M Below Po-lefty Level 0991 AHS) Les.s than 15 minutes 15 minutes 30 to 44 minutes 4S to 59 minutes 1 hour to 1 hour and 29 minutes 1 hour 30 m i nutes or more Works at home No fixed place of work 10% 20% .u. s. 30% 40% 50% -------------11-------------

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FlguretS TraYel Distance to Woril, Commutws Balow Powrty Lew! (1991 AHS) L"ss than 1 mil" 1to 4 miiH Sto 9 miles 10 to 19 m i les 20 to 29 miles 30 to 49 miles 50 mites or more Works at home No fixed pl.ace of work u s 30% 40% SO%

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Flgv .. 16 Trawl Time to Wortc by Residential Location 0991 AHS) Less than 15 mi"1utes 15 to 29 minutes 30 to 44 minutes 45 to 59 minutes 1 hour to 1 hour and 29 rhir1utEos 1 hour 30 minutes or more Works at home No fixed place of work 1.3% u s Central C ity liiJ Suburb 11111111 Outside MSA 0% 20% 30% 40% 50% 60% ------------------------111------------------------

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. 17 Trawl Distance to Work by Residential Loartlon (1991 AHS) Less than 1 mile 1 to 4 m iles 5 to 9 m iles 10 to 19 miles 20 to 29 miles 30 to 49 miles 50 miJes or more Works at home No fixed place of work 10% 20% u s Central City f&ID Suburb 11111111 Outside MSA 30% 40% 50% --------i------

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Puauc TRANSPORTAnON The use of pub lic transportation for the j ourney to work has dec l ined consistently over the past several decades. According to Census data, the transit share declined from 12. 6 percent in 1960 to 5.3 percent In 1990. Even more significant is the fact that the absolute number of commut ers using t ransit aiso dec-tined from ove r 7.8 million work ers In 1960 to 6.1 millen work ers in 1990. This occurred despi1e a 39 percent increase i n population and a 78 percent ine1ease In the total number of workers over the same t i me period From a strict policy perspective, it is reasonable toquestion whether continued investment and support of pub lic transportation is an appropriate and effective use of publ i c funds. This policy question is acknowledged and cons id ered by many i n the literature. Development patterns that exist i n America today are not conducive to wide-spread transit use. For this reaso n it is lmportantto have a clear and thorough understand i ng of spec ific market segments that are most incli ned to use transit. In particular the identification of market segme n ts that have a greater thah norma l p ro babi l ity of using t ransit for the work tr i p shou l d be a h i g h priority. The focus of this section is t o present recent trends in t h e use of pub lic transit for the journey to work as reported i n the American Housing Surveys conducted in 1985, 1989, and 1991 Commuting by transit is reported for a variety of geographic demographic, and housing characteristics T h erefore the trans i t mode spli t can be estimated for nume r ous market segments much of the data confirms expectetions regarding the characteristics ofthe traditional transit user, the information is useful since it provides recent t rends ove r a shorter period of time than i s typ i ca l ly presen t ed usi ng national databases. In addi tion, the availabil i ty o f public transportation will be re ported, along with the reported satisfaction oftransi t users i n the United States. All i nformation p r esented in th i s section was derived from the American Housing S u rvey. Journey-to-Work Supp l e ments The da t a are s u mmarized t h r oughout th i s section w i th a series of bullets followed by presentation of the data in a series of graphics.

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u.s. Northeast Midwest South West 0% Transit Share of Journey to Work, United States and Regions The transit share for lhe journey to work in lhe United States was 5.1 percent i n 1985,4.6 percent in 1989, and 4.8 percent in 1991. As expected, th e Northeast continued to have the greatest transit share at approximately 11 to 12 percent. The other regions had significantly lower transit shares in each year (nearly 4 percent In the West nearly 3.5 percent in the and approxi mately 2.5 percent in the South). There appears to be some Indication of increasing transit share in 1991 particularly in th e Northeast where the transit share increase d from 10.7 per cent in 1989 to 11. 4 percent in 1991. Transit Share of Journey to WO!ic by Region ofthe Unitad Stotas (1985-1991 AHS) 6% .1985 1989 IRi 1991 9% 12% 15%

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Transit Share of Journey to Work, Selected Demographic Subgroups The commute transit shares for Blacks, Hispanics, and the elderly continued to be larger than the national average in each of the years presented. The transit share for Blacks re mained significant despite declining from 15.3 percent in 1985 to 14.7 percent in 1989, to 13.8 pe rcent in 1991. The Hispanic transit share was also s i gnificant, faiUng from 10.3 percent In 1985 to 9.2 percent in 1989, but increasing back to 10 3 percentin 1991. Elderly transit use was 7.1 percentin 1985 and 5.3 percent in 1989 and 1991 Commuters below poverty level were more likely to use transrt with a share of 8.5 percent in 1985 6.8 percent in 1989, and 7.5 percent in 1991. Figure19 Transit Share of Joumey fa Work for Selected Demographic Subgroups (1985-1991 AHSl u.s. Black Hispanic Elderly (65+1 Poverty Level 0% 5% 10% .1985 1989 lim 1991 15% 20%

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Transit Share of Journey to Work, Residential Location Residential location continued fo be an important factor in use, with central c;ty residents being more l ike ly to c o mmute by transit than sub urban and nonMSA res ide nts. The transit share for central residents was 11.5percenlin 1985and 10.7 percent in 1989and 1991 Suburba n residents are not lik ely to commute by trans it. as thei r trans it share was 3.1 percent in 1985 2.6 percentin 1989 and 3.0 percent in 1991 Those residing outside the MSA virtually never use transit for commuting as their transit share was less than 1 percent in each of the years S i mi lar obse Natlons can be made with respect to urban and rural residential locations. The transit share in urban residential locations was greater than the national average, at 6 7 percent in 1985, 6 1 percent i n 1989, and 6 3 percent in 1991. The trans it share for rural res identia l l ocations was less than 1 perc ent in each of the three years.

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Flgure20 Transit Share of Journey to Work by Resldentlall.ocatlon (1985-1991 AHS) u .s. Central City Suburb Outside MSA 0% 3% 6% Flgure21 .1985 1989 1991 9% 12% Transit Share of Joumey to Work by Residential Location, Urban vs. Rural (1985-1991 AHS) u .s. Urban .1985 Rural 1989 lmJ1991 0% 2% 4% 6% 15% 8%

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Transit Share of Journey to Work, Selected Housing Characteristics Those who rent dwelling units were more likely to commute by transit than homeowners. The transit share for renters was 92 percent in 1985 8.6 percent in 1989, and 8 9 pereentin 1991 In contrast. the share for homeown ers was 3.2 percent in 1985, 2.7 percent in 1989, and 2.8 percent in 1991 Convnuters who have recentty moved were more fikely to commute by transit whil e getting settled. The transit share for commuters moving within the past year was 5.3 percent in 1985 and 1989, and 5 .8 percent in 1991. Commuters living in recently c onstructed homes (4 years) we re not likely to commute by transit with a share of 1 3 percent in 1985, 2. 1 percent in 1 989 and 2.0 percent in 1991. The transit share for commuters living in mobile homes was less than 1 percent in each of the three years. Commuters l iv ing in homes with physical prob lems were more likely to commute by transit. The transit share for commuters living in homes with severe physical problems was 15.9 percent in 1985, 7.7 percent in 1989, and 8.6 percent in 1991. Similarly, the share for commuters living in homes with moderate physical problems was 8.6 percent in 1985, 7.5 percent in 1989, and 6 1 p ercent in 1991.

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u.s. Owner Renter 0% Flguna22 Transit Shore of Journey to Work, Home Owner YS. Ren1w 0985-1991 AHS) Flgure23 .1985 1989 IB1991 9% 12% Transit Shont of Journey to Work, Selectad Housing Choradaristics 0985-1991 AHS) u.s. New Construction (4 years) Moved in Last Year Mobile Home Severe Housing Problem Moderate Housing Problem 0% 6% .1985 1989 lml1991 12% 18%

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Public Transportation Availability The proportion ofthe U.S. population reporting the availability of public transportation for all trip pur poses was 58.0 percent in 1985, 54.8 percent in 198 9 and 54.9 percen t In 1991. In 1985, 18.4 percent indicated having public trans portation available but did not use transit for any trip purpose This proportion increased to 21. 5 percent in 1989 and 21. 7 percent in 1991. In 1985 13.4 percent indicated that public trans portation was available and that they used it at least weekly tor some trip purpose. This same percentage was 11.4 percent In 198 9 and 11.7 percent in 1991 At Least Weekly Less Than Weekly Do Not Use Not Available Figuna24 Pubi'IC Tronspot fallon, Frequency of Use (1985-1991 AHS) .1985 1989 IEJ1991 60% 75% ------------------------111-----------------------

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Figure 25 Repor1ed Satisfaction With Public Tronspot1ullon of Those Using Tronslt at Least Weeldy (1985-1991 AHS) 100% .------------------.... 91.4% 91.9% 80% 60% 40% 20% 0% 1985 1989 1 991 Repor1ed Satisfaction With Public Transportation of Those Using Tronsit Lass Than Weeldy (1985 1991 AHS) 100% .--------------------, 90.7% 89 .4% 80% 60% 40% 20% 0% 1985 1989 1991

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RIDESHARING Ridesharing as a mode for commuting to work has declined significantly in the past 10 to 15 years. According to Census data, the carpool share for the journey to work in the U.S declined from 19.7 percent i n 1980 to 13.4 percent i n 1990 In addition, the absolute number of workers fell by 19 percent, from 19.1 mill i on In 1980 to 15.4 mlltion In 1990. Average vehicle occupancy also declined from 1.18 in 1970 to 1.151n 1980 to 1.09 in 1990. These are by the resui1s of recent national American Hous ing SUJveys which Indi cate a decl i ne in car pool share tor the wor1< trip from 14.1 percent in 1985 to 11.8 percent i n 1989 However, the share increased s6ghtly to 12.0 percent in 1991. The focus of this section i s to present recent trends In the use of ridesharing tor the journey to work as reported in the American Housing Surveys conducted in 1985, 1989, and 1991. Ridesharing to wor1< Is reported for a variety of geographic, demographic, and housing characteristics. As a resutt, the ridesharing mode split can be estimated for numerous market segments. Although m u ch of the data confirms expectations regarding the characteristics of Individuals that are most l ikely to rideshare, the informa tion Is useful since it provides recent trends over a shorter period of time thaA Is typically presented using national databases. All info rmation presented in this section was derived from the American Housing Survey, Journey-to-Work Supple ments. The data are summarized throughout th is section a series ofbuilets, followed by presentation ofthe data in a series of graphics.

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Carpool Share of Journey to Work, United Stotes and Regions The carpoo l share for the journey to work in the United States was 14.1 percentin 1985 11.8 percent in 1989 and 12.0 percent in 1991. the South had the greatest carpool share i n 1985 and 1989, the share fell I n each year from 16.5 percent i n 1985 to 13.1 percent In 1989 to 12.8 percent In f991 The West was the on ly region that maintained its share overtime, from13.2pe rcentin 1985to 12.7 percent in 1989 to 13.7 percent in 1991 The carpool share in the Northeast from 12.6 percentin 1 985 to 10.4 percent in 1989 and maintained this share in 1991. SirrVIarly, carpool share in the midwest was 12.8 percent in 1985, 10.5 percent in 1989, and 10.7 percent in 1991 Flgure27 Carpool Share af Journey to Wartc by Reglan afthe United States (1985-1991 AHS) u.s. Northeast Midwest South West 0% 5% .1985 1989 1991 20% 25%

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Carpool Share of Journey to Work, Selected Demographic Subgroups The carpool shares for Blacks and H i spanics were signifi cantly larger t ha n the national average In each of the years presented. In particular, the carpool share for Hispanics was maintained al19 to 20 percent over th i s time period. The carpool share for Blacks remained significant despite declining from 18.9 percent in 1985 to 15.4 percent in 1989, and increas ing slightly to 15.7 percent In 1991. The elderly carpool share was consistenUy lower than the national average (12.9 percent in 1985, 10. 7 percent in 1989, and 10.4 percent in 1991). Commuters below poverty leve l were more likely to carpool as the carpool share for this subgroup was 17.7 percent in 1985, 17.0 percent in 1989, and 16 .3 percent in 1991 Flgure28 Carpool Share of Journey to Watit for Selected Oemogrophlc Subgroups (1985 AHS) u .s. Black .1985 1989 lel1991 Hispanic Elderly (65+ I Poverty Level 24% 30%

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Carpool Share of Journey to Work, Residential Loc:otion The carpool share for residents tiving outside the MSA was 16. 1 percent in 1985 12. 7 percent in 1989, and 13.4 percent i n 1991. Although the carpool share for non MSA residents declined significantly since 198S, it remained the most significant residential location variable for carpool. use The carpoo l share for central city and suburban res idents was approximately the same as the national average. 1 3 to 14 percent in 1985 and 11 to 12 pe rcent in 1989 and 1991. Similar observations can be made with respect to urban and rural residential locations. The carpool share for commuters i n rural residential locations was greater than the national average, at 16. 3 percent in 1985, 12 .7 pe r cent in 1989, and 12. 5 p ercent in 1991. However, it is interesting t o note that the rural share Is converging and was nearly equal to the national ave r age in 1991. The carpool share for commuters in urban resi den tiallocatio ns was equal to the national average in each of the years

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u.s. Central City Suburb Outside MSA FlguN29 Carpool Shof Journey to Work by Residential Location (1985-1991 AHS) 15% Flgure30 .1985 1R 1991 1 % 20% Carpoal Share of Journey to Work by Residential LOcation, Utban vs. Rural (1985-1991 AHS) u .s. Urban Rural 15% .1985 1989 IEJ1991 20%

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. stf[r;are of Journey to Work, SelechKI:tiDusing Chon,tcteristics . ..... Tit"'! who rent units were more likely to carpcioitaWod< tllan hOmeowners. The carpool share forrenters was 14.9 percent in 1985, 13. 6 percent in 1989, and 14.6 percent in 1 ln contrast, the share for homeowners was in 1985:. 11.0 percent in 1989, and 1991 . C!i11111\lters iivlng in recently constructed homes (4 years) were not as fikely to carpool to work, with a 15.0 percent in 1985, 10.0 percent in 1989 anit11 5 percent in 1991 Commuters who have moved recently (within the past year) were more likely to carpool to work The carpoor,share for this subgroup was 15.7 percenfiri 1985. 13.9 percent In 1989 and 14.7 percent in 1991. The carpool share far commuters living in mobile homes was significantly greater than the na tio nal average at19.4 percent in 1985, 16.0 percent in 1989 and 16.4 percent in 1991. Cpmmuters.I!Ving in homes with physical prob1t: .. ... le..,. to carpool to work. The far living i n homes with problems was 22. 2 percent in 1985. 19Sij and 12. 7 percent in 1991. the share ftrr commuters tiving in . homes wiUt moderate physical problems was 19.7 percelllin 1985 and 1989, and 17.2 percent in 1991.

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. u.s. Owner Renter . ; ' . Figure31 Carpool Shore of Journey to Work, Home OWner 'IS. Renhit (1915-1991 AHS) 15% F'tgure32 .1985 1989 1991 20% Carpool Shara of Journey to Work, Seleclwd Housing Characieristics (1985-1991 AHS) u.s. New Construction (4 years) Moved in last Year Mobile Home Severe Housing Problem Moderate Housing Problem 0% 5% 10% .1985 1989 E 1991 20% 25%

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WORKING AT HOME In the last decade, working at home as a journey-to-work option has become inCfeasingly popular with U.S. work ers According to U.S. Census data, the number of wor kers who "worked at home increased more than 56 per c ent from2.2 million in 1980 to 3 4 million in 1990. This increase occurred despite only a 19 percent inaease in the total number of workers in the U S. during this time As a resun. the work at home share of the journey to work in the U S. increased from 2.3 percent to 3.0 percent be tween 1980 and 1990 Comparatively. data from the 1985-1991 American Hous ing Surveys Indicate thatthe share of U S commuters who worked at home declined from 3.0 percent in 1985 to 2 6 percent in 1 991 While the reasons for the difference between the results of the two surveys are not evident, it is assumed that dellnition did not play an important role s ince b o th surveys define working at home in broad, generic terms. For example it can be expected that the 3.4 million commuters who indicated "Worked at home .. as their primary place of work in the 1990 Census will include persons with manufacturing o r service-type jobs, persons who are self-employed, and telecommuters. Telecommuting, as defined by LINK Resources, a New Yor k-based tech n ology research and consulting firm involves company employees working at home part-or full-lime during normal business hours LINK Resour c es conducts an annual National Work-at-Home Survey in which 2 ,500 randomly selected U S. households are interviewed via telephone to identify telecommuters. Resuns ofthe latest survey conducted in 1993 found that there are 7 6 million telecommuters In the U S.' This represents a 38 percent increase over the 5 5 million telecommuters that were identified in LINK s 1991 survey.' In addition, the su.Vey data indicated that the share of the U.S. workforce that telecommutes also increased from 4.5 percent in 1991 to 6 1 percent In 1993. The focus of thts section is to present recent trends In working at home as reported i n the American Housing Surveys conducted in 1985, 1989, and 1991. Working at home is reported for a variety of geographic, demo graphic, and housing characteristics. As a result the mode share can be estimated for numer .. ous market segments. The information is particularly useful since it provides recenttrends over a shorter period of time than is typically presente;d using national databases. AJI information pre sented in this section was derived from the Amertcan Housing Survey, Journey to-Work Supplements. The data are summarized throughout this section with a series of bullets, followed by presentation of the data in a series of graphics.

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Work-at-Home Share, United States and Regions The work-at-home sha r e in the U.S was 3.0 percent in 1985 and 2.6 percent in 1989 and 1991. The West is the only region that has shown consis tent growth in the work -at-home share. increasing from2.6 percent in 1985to 2.9 percent in 1989 to 32 percent in 1 991 The work-at-home sha re in the N orth east was 2.8 percentiri 1985 2.3 percent in 1989, and 2.2 pe rcent in 1991. Similarly, the work-at-home in the Sout h was 2.4 percent in 1985 2 2 percenlin 1989, and 2.0 percent in 1991. The work -a t -h ome share In the Midwest was 4 1 percent in 1 985,2.9 percenlin 1989, a nd 3.2 percent in 1991 Flgure33 Work-at-Home Share of Journey to Work by Region of the United States (1985-1991 AHS) u.s. Northeast Midwest South West 0% 1% 2% 3% 4% .1985 1989 a 1991 5%

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Work-at-Home Share, Selected Demographic Subgroups The work-at-home shares for Blacks and H i spanics were much lower than the national average in. each of the years presented. The work -at-home share for Blacks was less than 1 percent In each of the years. The Hispanic work-at-home share was somewhat greater than for blacks but remained minimal at approximately 1 5 percent. The work-at-home share for the elderly was greater than the U.S. average with a share of6.8 percent in 1985,4.9 percent in 1989, and 5.9 percent in 1991. Commuters below poverty level were more l ikely to work at home as they had a share of6.7 percent in 1985, 5.4 percent in 1989, and 5.3 percent In 1991. Flgure34 Wortc-at-Home Share of Journey to Wortc for Selected Demographic Subgroups (1985-1991 AHS) u_s. Black Hispanic Elderly (65+) Poverty Level 0% .1985 1989 mJ1991 9%

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Work-at-Home Share, Residential Location Residential location was an important factor i n determining work-at-home share, as rural resi dents were more likely to work at home than central city and suburban residents The work-at-home share for rura l residents (or outside MSA) was much greater than the na tional average, at 5.5 percent in 1985, 4 2 per cent in 1989, and 4.0 percent In 1991. The workat home share for centra l city resi dents was lower than the national average, with a share of 2.0 percent in 1985, 1 .7 percent in 1989, and 1 .9 percent In 1991. Suburban residents were characterized by a work at-home share that was nearly equa l to the national average, at approximately 2.5 percent in each of the years.

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Flgure35 Shore of Joumey to Work by Resldentlollocotion 0985-1991 AHS) u.s. Central City Suburb Outside MSA F"tgure36 .1985 1989 f!ml1991 6% Shore of Journey to Work by Residential l.ocation, Urban vs. Rural 0985-1991 AHS) u.s. Urban Rural .1985 1989 g 1991 8% 6%

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Housing Characteristics The share for renters was lower than the national average, at 2.2 percent in 1985, 1.9 percent in 1989 and 1 7 percent in 1991. I n contrast, the work-at-home share fo r homeowners exceeded the national average in ea c h of the three years, including 3 3 percent in 1 985 2 9 percent in 1989 and 3 0 percent in 1 991. None of the selected housing characteristics ap peare d to besignificant i n resulting in higher work .. at home sha r es. With one exception (severe physical problems with hous i ng i n 1991), each of the housing characteristics res uHed in work-at home shares lower th an the national ave r age in 1 991.

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u.s. Work-at-Home Share of Joumey to Work. Home Owner YS. Rantw (1985-1991 AHS) Owner .1985 1989 1m 1991 Renter 2% 3% 4% Flgure38 Work-at-Home Share of Journey to Work, Selected Housing Charoclerisli.::s (1985-1991 AHS) u.s. New Construction (4 years) Moved in Last Year Mobile Home Severe Housing Problem Moderate Housing Problem 0% 1% 2% 5% .1985 1989 lli!1991 4% 5% -------!--------

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THE fUTURE oF CoMMUTING ALTERNATIVES The future of commuting in the United States is discussed in this section. Based on recent trends and a review of the opinions are offered regarding the future of commuting for the more than 115 mil ion workers in the States. PUBUCTRANSPORTATION Over the past few decades, the public transit induslly in the U.S. continuously has made efforts to provide quaWty services in extremely chaHenging environments. The range of efforts has been broad, includ ing i nstitutional and organizational modifications, techno l ogical and hardWare changes, and service delivery and marketing innovations. In spite of these changes, the industry has had limited success in its efforts to adapt to the challenges of markets that have been impacted by demographic, geo graphic, economic. technological, and societal trends. As a resu lt the ind ustry has experienced continued declines i n market share ongoing financial struggles, and continu in g challenges in attempting to meet the needs of chang ing markets. Finding fu nd ing sources for continues to occupy i ndustry attention, but many other agenda i tems h ave developed over the past decade. MultimodaVintermodal p lanning and implementation are rece-iving a great deal of attention. Trans i t captives continue to be the dominant share of riders i n most markets; the mobility need s of the elderly are growing ; safety, p ub lic participation, service quality a nd alternative fuels are among the issues receiv ing more attention; route structures still focus most nentty on the downtowns. but downtowns comprise ever more modest shares of urban employment. Articulated and small buses are increasingly convnon. Development patterns, public sector resource constraints, l ifestyle changes and the in cre as ing affordability of auto mobile travel all have contributed toward greater retianc e on privately-owned vehicle alternatives. The most suc cessful transit services have been those provi ded in trad itionally strong markets such as concentrations of trans it dependents in la rge and more densely populated urban areas However. in some instances. transit has experienced success in areas where the transit choice has become more attractive due to certain conditions, such as high automobile par1
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The remainder of this discussion provides a summary of some of the recent assessments of the future of pub5c transportation through the eyes of the American PubHc Transit Association (APTA) and the American Association of State Highway and Transportation Officials (AASHTO). This is followed by a review of recent lnerature on transit management and seNice strategies for the coming de cades. The section concludes with four recommend tions for the industry that were developed based on general agreement in the l iterature Recent Notional Studies on the Future of Public Transportation APT A's Transit 2000 APTA conducted a study to identify and examine trends that are affecting the future of kansit and recommended specific action items that could contribute to a more favorable future environment in which to operate. The study identifies five major forces that are tikely to affect transit in the 21st century: > congestion and auto dominance threats to the environment threats to energy independence inadequate Infrastructu re investment demographic change 'Mththese forces in mind, the report concludes that transit can play an important role in helping to deal wM these issues in the context of !he future of transportation as a whole. A series of goals are identified to help guide transn systems in the coming decades and are presented in Table 3. Future Directions (AASHTO) A Study on Future Directions of Public Transportation in the United States was published by AASHTO in 1985.' The study was designed to identify the important role that state transportation agencies could play in supporting public transportation The report states the belief that public transportation Is not a single mode, but a mixture Table3 Transit Industry Goals for the Future Goal1 Preserve protect, and expand cument markets and choices available to current public transportation users. Goal2 Pursue new markets, increased ridership and expanded market share by both traditional and i n novative means. Goat 3 seek increased Investment In public transportation at all leve ls Assume new responsibilrties and forge new relationships in both the Goal4 management of mobilrty as well as in the provis ion of public transportation services. Foster and participate in land-use planning actions thai more effectively GoalS integrate economic development and infrastructure investment decisions to enhance the use of public t ransportation i n rts many forms. Goal & Enhance public awareness and acceptance of the need for greater investment and new partnerships in preserving and enhancing mobilrty for all. Source: As summarized in Micha el D Mey.r, '"Publk Transportation in the 21st Century," Public Transports/Jon, p 639.

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of modes (transit, ridesharing. and paratransit ) each comp lem enting the other and interacting to form a system for passenger mobHity and a cost--effective group of ser vices One future scenario was envisioned where the development of the transrt industry would likely continue and would incorporate the following characteristics: Demographic and land use changes will present new problems and opportunities for the industry ... Less lederalfundingwould create problems for some transit systems. More stable funding sources will be needed with state and local governments but it Is un li kely that funds will be in adequate supply Transit managers will experience less polffical inter ference and have greater flexibility to run their sys tems Part of the reason for this change will be increase d invo lvement by the private sector. C-ost consciousness will be a key aspect of all transit system operations Failure tocontrol costs will lead to bankruptcy and the demise of various systems. Professionalism will take on new meaning in the industry as managers and governing boards recog nize that survival. and expansion are functions of better professional performance .... Moderate gains in technology will be of value to the transit industry. Such gains are not likely to be spectacular breakthroughs but more likely system innovations that develop over time. Increased industry involvement by all participants. leading to increased political involvement. seems i kely to occur .... The conclusion of the report provides recommendations to various groups that would necessarily be involved in the future of transportation including the federal gov ernment state governments, local governments, public transit operators. labor private operators ) the business community, transit users, and industry associations. Transportation 2020 (AASHTO) Transportation 2020 was a national effort to discuss and recommend a framework for future transportation programs AU aspects of a national transportation program were considered, including future considerations for public transportation. Three specific areas were emphasized in their discussions of transit including: Future Technological/nnovalions-Majortechnological advances anticipated within each form of public transportation were identi fied and dis cussed Institutional Structures-Four major factors were identified that could have significant in nuence on Institutional structures including the impact of budget deficits on transit funding programs, the impact of demands on the provision of transit service, the lmpect of private sector participation, and the impact offederallabor protection rules on the costs ot providing service. Financial Needs -Considerable attention was given to the financial needs of the industry and three major funding scenarios were used to esti malethe capital costs of achieving different policy objectives. These national studies provide recommendations for the transit industry from a more global perspective. With these issues in mind, it is appropriate to initiate discussion of more system-specific strategies, including those spe cifically related to management techniques and serv i ces. Strategies for the Coming Decade Recent literature offers several approaches to the devel opment of transit management and service strategies in the coming decades. A discussion of management and service strategies is provided below. Management Strategies Perkinson discussed a transit strategy for the 1990s by comparing two distinctly different views of transit-infra. structure vs. service. The traditional view suggests that transit is one component ot infrastructure-the system of utilities and services that supportS our every day exist ence. Charactertstie of an infrastructure organization is a conservative management strategy of status quo and a traditional hierarchical organizational structure with rela

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lively autonomous departments and discrete responsibili ties. In contrast, a transtt system also can be viewed as a seNice organization. designed to be proactive and customer oriented. Per1riented lfanslt system can anticipate user needs and future demand for currently provided services as well as services tha t have not yet been implemen ted. This management slfategy has distinct organizational Implications. It may require decislonmaklng asslstance from individuals at the lower end of the hierarchy-those who are c l oser to and have a better understanding ofthe customer. In addition, a seNice organization necessitates coordination and communication among departments. Marketing and planning departments must work closely to develop an understanding of existing and future transit markets and then to determne the best way to respond to these markets. A transformation from the traditional infrastructure organization to a service organization is the fundamental change that will enable transit to adapt and suNive in the future. Barker re commends a management strategy forthe 1990s in respo nse to a series of key trends that he believes will affect the future of the transit industry.' He discussed key trends i n the following areas: energy and environmental concerns l and development and urban growth not condu cive to transit use demographic trends (senior boom, birth dearth. aging of the baby boom) diverse workforce need for more education for the workforce social ills (crime, violence, etc.) computers and communications technology economics and the automobile industry In respons e to these key !fends, Barker re commends the following strategy for transit management in the 1990s: Upgrade Maintenance and Storage Capability Plan for projected changes in fuels and engines ov&r the next couple of decades by making sure adequate space is available. Learn to Manage a Diverse Workforce Unde r standing employees will enable you to get the most from them. Invest in People -Create a working environment that attracts and retains the best people. Plan to Change Compensation Programs-Move toward compensation based on performance and productivijy. Organize into Entrepreneurial Teams Organize employee groups to d evelop and implement irrr provements. Buy/Sell More Non-Transportation SeNices-Become more involved in buying and selling non transportation seNices, such as maintenance training parts storage, etc. Leapfrog in TechnologyThink about and plan for technology that can make a big difference in the way you do business. Get on the Anti-Crime Team -Involve the transit system in a community watch program to make visible effo rts toward safety improvements. Get Involved with the Site Design Review Process .. Review site designs in an effort to ensure that they are pedestrian and transit friendly. Market to the Image Generation-lmple mentsafe, comfortable, and convenient services for which a pre mum fare can be charged. Many general managers in the transit industry today appear to support the ideas discussed previously. For example recent comments that seem to reflect the gen era I sentiment of many of today s transit industry leaders and their new and evolving perspectives on transit include the following: believe the answer lies in reshaping our traditions/ view of transit, a view which does not extend beyond running trains and buses In order to attract new riders. I believe W6 have to shift our focus from opsrating vehicles to serving customers A sound -------------11-------------

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customflr servicfl program which responds to lhtJ needs oft he n 'dlng public can attract more rid&rs while retaining exisUng ridersh i p. y .-Kenn.rth M. Gf'e90r, General Manager, Metropolitan Atlanta Rapi d Ttansit Authority (Sus Ride, May 1992) roo many people think transit is a industry w i th no new ideas Ws must show how wrong that thinking is because it maybe the onJywaytogain entry intothevasttravelmsrhet of people who wouldn' t even think of using our We now havfl opportuni ties to show a different, progressive face. The pop culture may have lhtl right Idea ; JUST DO ITt" -John P. Bartoslewfez. General Manager Fort Worth Autho rity (Bus Rkl. May 1992) Service Strategies The trans i t ind u s t ry has reaNzed that fixed-route bus serv i c e is not t h e appropriate service defivery option for many of the evolvi n g markets in our society. Thi s was expressed in a recent article by Padron where he recom mends appropriate service strategies in response to chang ing demograp h ics and development patterns. His ma i n po int i s that it makes l ittle sense t o continue expanding fixed-rou t e service in suburban areas. This t raditional approach is expens ive and largely unproductive He indicates that transit systems would be better off avoiding t h is travel market and focusing their efforts on: Growth in the tracflffonal suburb-to-central city journey to worlc Desprte suburb-to-suburb trave l becoming the predominant n ational commuting pattern, growth i n trad i tional suburb-to central city commuting has been substantia l. Although reluctant to offer any service strategy for the suburbs, Padron indicates that the only realistic aRerna tive for servi n g a suburban environment is paratransit. Although the use of paratransit will not provide the defini tive ans wer to all transportation probl ems in the subu r bs, paratransit can serve an important r ole in the suburban operating environment. particularly since this market re mains l argely un t apped Meyer cites six major recommended structural changes for trans i t that he be lieves will be necessary for future success. These recommended changes are provided in Table 4. Wi thout these fundamen t a l changes rt is be lieved that the future of the industry will be characterized by gradual econ omi c attriti o n. C onclusion s Four major recommendations were identified as being important for the futu r e success of publ i c transportation based on review of the APTA and AASHTO studies, a l ong with other lrterature discussing the futu r e of trans portation. These recommendations are presented below 1. Incorporate New Management Str a tegies The transitsystemofthe future cannot continue to opera t e based on the traditional view of the transit o r ganization. In order t o achieve success. transit systems mus t foster a work ing environment that can quickly and easily adapt to the needs of i ts users Perkinson r efers to it as a s e rvice organization in contras t to the more trad i tional infrastruc ture Barker emphasizes the importance of involving empl oyees at all l evels in the decis i onmaki n g process. M e yer's recommendations inClude the need for a sales-oriented o r ganizational structure This approach to management in the transportat i on industry is often referred to as mobility management where transi t sys tems find ways to transport patrons by whatever means is most convenient and cost effective Worlc travel between metropolitan areas As s u burbs con tinue to expand and overlap, com2. Focu s on Tradition a l Trans i t Markets muting between metropolitan areas will become a sign ifiCant component of comm u ting patterns. The transportation needs of the central city The tr a nsit Industry should focus t h e majority of its efforts on ma rk ets and services thatthey have traditionally served well Service for the traditional suburb-to central city

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Table4 Recommended Structural Changes In Transit A new fare structure One that is differentiated by time of day and distance traveled. Greater discretion to price Achievable if a surtax is imposed on ali-day seiVice parking. in relation to cost A new One that is decentralized so that planning, routing, and scheduling decisions organizational structure can be based on an intimate knowledge of the market for loca lly customized seiVices. A d ifferent neet mix One wrth the capacrty necessary to serve the peak but better surted for shuttle, charter, and taxi-like operations in the off-peak. A wider diversity of service Some sold on a contract or subscription basis. some purchased from private offerings vendors. A new contract with labor One that permrts wider use of part-time and cross-trained employees while Cleating a wider range of promotion opportunities for transrt workers. Source: As summartz.ed In MJdtael D. Meyer. "'PubUc Transportation In tht 21st Cntury," Public TrattsporfMJon, p. 639. journey to work and circu l ati on within the central city has been the bread and butter" for most transit systems in the past several decades. Despite suburb-to-suburb travel becoming the predominant commute now pattern, growth in the trad itional suburb-to-central city commute now has been substantial. Efforts to serve suburb-t
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vices relative to other modes, including factors related to the following performance areas and i mpacts: technology-driven changes in comparative costs safety comfort/conveni ence energy and air quality Impacts fare payment methods ease of use (ITS/APTS impacts) rel iab
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Flgure3 9 Estlmatad Annual Carpool Share (1970.19901 ' ' ' ' ' ' ' ' ' 22% ' ' ' ' ' ' ' ' ' ' ' ... ' ' ' ' ' ' ' ' ' ' ' ' if, ..... . .... ' ' ' ' 20% ' ' "': ' ' ' ' ' ' ' ' ' ' ' ' ' ' ' '!' ' ' ' ' ' ' ' ' ' ' ' ' ' ' ' ' ' ' ' ' ' ' ' ' ' ' ' ' ' ': ' ' ' ' ' ' ' ' ' ' ' ' ' ' ' ' ' ' ' ' ' ' ' ' ' ' ' ' ' ' ' ' ' ' ' ' ' 18% 16% 14'4 ' ' ' ' ' ...' ' ' ' ' ' ' ' ' ' ' ' ' ' ' 12% ' ' ' ' ' ' ' 1970 1972 1974 1976 1978 1 980 1982 1984 198 6 1988 1990 Source : Erlk Ferguson .. An Exegesls of Recent NatJonwlde Oeel l nes I n Carpoolin g,'" Figure 5 Age and Education -Educational attainment level in t h e U S. has increased substantia l ly in rece n t decades T h e prop o rtio n of the U S population with a h i gh schoo l diploma or some advanced education increased from 66 percen t i n 1 980 l o 75 percent in 1990." I n addition the mean age of the U S. population increased from 28.1 years in 1970to 33 .0years in 1990. These cha n ges are bel ieved to contribute to a dec l i ne in car p oo l share Ferguson estimates that 96 percen t of the decfine i n c arpoo l share can be attributed to these three factors: 38 per cen t due to changes in household compositi o n 34 percent due to th e reduction in the rea l pri ce of fuel and changes in the fue l eco n omy and 24 percent due to an ag in g and more educated population." It i s cle ar that the decUne i n carpoo l share i s primaril y the resuH of fac t ors beyond the con trol of TOM professio n als. However, i t could be arg u ed that the decline w o uld have been greater had TOM not emerged o r r eemerged as an i mportant s t rategy for m a n y m e tropolit an areas of the U S. over the past decade. What Next? What does thi s mean for the future o f rideshari n g? A l though l imi t ed, dat a available describing recen t trends in rideshar i ng suggest that the decfine in the commute share for this mode has stabilized in recent y e ars and may be i ncreasing s l igh t ly Changes in the major factors identified previousty ca nnot c ontinue t o be a s dramatic as they have been in the past. For example, h o useholds can conti n ue to become smeller on l y t o a point; the real price of gasoline cannot continue t o decline at the rate that i t has in the 1 9 80s; the ris i ng cost of education suggests t hat fewer indi v i dua l s will be able to afford highe r ed ucation in the future'"' As a r e s utt, the i mpact of th ese fac t ors on the commut e share for ridesharing will not b e as significant in the coming decade as i t was in t h e p revio u s dec a de The d i fflcutt task will be for TOM organizations t o i dentify new and evolving strategies for encou r aging a n d facil i tating attematives to the single-occupant automobile This w ill incl ude innovative efforts to maintain and potentia l ly in crease the commute mode share for rideshar i ng Condusions Based o n recent t rends and a rev i ew of li t erature on c arpool ing, four major recommendations a r e offe r ed to carpool programs These reconvnendations stem from the need for carp o ol programs and TOM organizations i n gen eral to m o r e effective l y adaptto evolv in g demograp hic and geograp h ic trends in t h e U S.

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1. Identify and Learn From Areas of Success TOM efforts need to be evaluated objectively so resources can be focused on proven actions. In the process of evaluating carpooling trends in localized areas, some geographic areas can be identified where carpooling has r emained relatively stable or even increased from 1980 to 1990, both in absolute terms and In commute share These areas can be identified at any geographic level using Census data i.e county, place, census tract, block group. Additional research should then be conducted on these successful areas to serve as case studies to identity the reasons for success and what specific actions could be applied in other areas For example, a carpool program that serves a county coutd review the trends in carpool share for each census tract withi n that county. The characteristics of commuters residing in tracts in which the carpoOl share remained stable or increased could be identified and analyzed along with the characteristics of the commute (travel time, origin/destination, etc.) Signifi cant pote n tial exi sts for t eaming from tracts exhibiting a greater propensity for carpoo l ing For add itio n a l guidance on the implementation of TOM measures. see "Mak ing TOM Work in Your Convnunity" by CUTR and Implementing Effective Travel Demand Management Measures: A Series on TDM by Comsis. et al. 2. Reconsider Focus of Program The traditional focus of carpool programs has been on u rban travel with the primary objective being to marketthe program to emp l oyees of large businesses and nies within major activity centers. Programs should con s i der focusing some efforts on rural residents who com mute long distances to cities. Longer commutes, both In distance and time, have traditionally been perhaps the most i mportant variable in the carpool formation decision. Based on an evaluation of carpooling trends at the county level in North Caro l ina, Hartgen suggests that serious consideration should be given to replacing employer focused programs in urban areas with residence-based programs in rural areas.2 Agencies interested in pursuing this type of program should be aware that efforts such as these can result in some institutional conflicts between residential and employer-focused programs that serve many of the same trips. Conflict usually arises when trying to determine which program should receive for these trips. 3. Use Target Marketing In Section 4, the carpool share for the journey to work was presented for worker subgroups according to a series of demographic, geographic and housing characteristics. The purpose ofthis effort was to identify market segments that appear to have a greater probability of carpoo l ing based on the results of AHS surveys. There is some disagreement in the literature regarding whether this type of information i s useful in predicting carpool formation However, a review of descriptive statistics compiled from the AHS clearly Indicates that certain market segments have a significantly greater carpool share than the national average . Trad i tionally, organizations charged with encouraging and facifltating travel demand management initiatives, includ ing ridesharing, have focused on the work destination side of the commute and especially during peak travel periods, i .e., 6 a.m. to 9 a.m. This makes sense since it is logical to assume that workers with commute destinations that are in close proximity would be good candidates for carpooling. In addition, nearly 62 percent of all veh i cle trips made during the morning peak are home based work trips. However, marketing efforts shou l d be considered i n an effort to penetrate more specific market segments. Efforts to penetrate specific market segments could be initiated with two d i stinctly different approaches including emphasis on the residential end or emphas i s on the employment end. Narrowing the focus through target marketing should reduce not only the cost of undertaking some marketing initiatives, but also be more effective In reaching individuals who are more l ikely to participate in a carpool. The two approaches a r e discussed briefly below Residential End As ind i cated previously, recent trends in the use of carpools can be used to i dentify existing and evolving market segments that appear to have a greater probabitity of becoming involved i n a carpool. Once these market segments have been identified the specific char----------111-------

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acteristics of these segments must be located geographi cally within the region in which a given TOM organization se-rves. For many characteristics, this can be aecom.. plished using Census data, which provide demographic and housing Information at geographic levels down to the census tract and block group. Once certain tracts or block groups have been identified that include concentrations of these market segments, marketing efforts can be focused within these more limited geographic areas. Employment End-One of theprimary objectives of most TOM organizations is the development of a database of potential carpool applicants and the preparation of match l ists for these appHcants in order to assist in carpool fo rmation. The information collected from potential appli cants usua lly includes chara c teristics such as those use d to distinguish market segments using the AHS. lndividu als with c ha racte ristics that sugge-st a greater probability for carpool formation could be specifically targeted for more aggressive marketing techniques, such as direct ma i l marketing or telep hone solicitation. 4. Develop Evaluation Program Many TOM programs in the U.S. do not have adequate evaluation programs in place. Vlllthout an evaluation mechanism, the effectiveness of the program cannot be determined. The objective should not be merely to count the nu m be r of matchpool appucants. Evaluation criteria should inc l ude data on the number of persons placed in carpools. h ow long they are maintained, and the change i n share of total trips Emphasis on reasonable and defendable evaluation and increased accountability shouJd be one of the major goals o f all TOM orga niza tions. These four recommendations do not provide all the answers. They do provide however a starting point from which various carpool programs and TOM organizations can in itia te some objective resea rch for determining what the best approaches will be for a given local area. WORKING AT HOME The type of employment of individuals working at home can vary significantly from farmers to self-employed individuals to telecommuters in the strict sense of the word. Data collected in national surveys such as the Decennial Census and American Housing Survey, do not distinguish between these subcategorie-s of working at home. Therefore specific information regarding the pro portion of workers in these subcategories i s uncertain. For the purposes of this discussion the focus is confined to telecommuting. The decision was made to focus on telecommuters since t his population segment is believed to be la.rgely untapped in a time period characterized by significant technological advances in telecommunications. Since the late 1980s many planners and decisionmakers in the transportation profession have placed a g.reater emphasis on the implementatio n of a variety of TOM activities to bring about declines in peak-period t ravel and in the utilization of singleoccupant vehicles thereby as sisting in congestion reduction. air quality improvement and energy conservation. One of the TOM techniques that has been drawing recent interest is telecommuti ng which can be defined as "working at home or at an alternate location and communicating with the usual place of work using electronic or other means, instead of physically traveling to a more distan! worksite."" An important aspect of this particular TOM activity is that current information transfer technology can be utilized as a surrogate for the journey to work on a part-or basis. The advent of the Information Age has brough t about a multitude ottechnological advances that are changi ng the face of the world and how communication and business transactions a.re conducted today Personal comp uters, modems fax machines cellular phones. voice mail fiber optics and communications networks (e.g Internet CompuServe, Prodigy, etc.) are some of the innovations that have enabled, among other things, greater ftexibitity in current working arrangements. Given it s widespread availability and continuing hardware cost reductions tele communications t echnology can now facilitate moving the work to the worker. Yet, anhough important and nece-s sary this Is only one of the reasons why telecommuting is attracting the attention of the transportation community. In addition to the advances in tel ecomm unications and compute r technology, several other factors have also contributed to the amount of inte.rest that has been gener ated in telecommuting in the last several years. In his article "Telecommuting in the United States; Rathbone highlights a number of these factors:'"

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The documented results of some of the first U.S. telecommuting projects have become availatile. Many of the findings have been positive In terms of the benefits that telecommuting has yielded. Pubfic policy and legislation have been adopted that directly or I ndirectly encourage tele commuting Examples cited by Rathbone include: the Clean f>Jr Act of 1990; the Americans with Disabifities Act of 1989; the lntermodal Surface Transportation Effi ciency Act of 1991; the 1989 directive to the federal Genera l Services Administration to implement telecommuting programs at federal agen cies; and the passage of legislation favorable to telecommuting in several states, including California, Florida, Virginia, and the state of Washington The telecommUting success stories are b e in g communicated to the corporate level where aware ness of telecommuting's positive impacts on both employees and employers is beginning to grow. Poss i bly due to supportive public policy and the success and benefits experienced by many of the early pilot projects. telecommuting in the U.S. appears to be grow ing. I t was discussed previously in Section 5 that LINK Resources "1993 National Work-at-Home Survey indi cated that there are 7.6 milijon telecommuters In the U.S. 38 percent more than the 5 5 million identified In LINK s 1991 survey." According to LINK. approximately 75 percent of these telec ommuters are info rmation work ers, that is, persons with jobs in the various information i ndustries such as programming, accounting, data pro cessing, marketing, planning, and engineering, among others. These occupa tions lend themse lves more readily to the concept oftelecommuting than do assembly line or construction jobs. Tasks common to information workers, such as data entry writing reports or proposals, extensive reading, or telephone communication, do not necessarily require them to be present in the office on a dally basis and often can be accomp 'ished with only remote access to the office via telephone and/or computer It seems, then, that telecommuting has the potential for continued growth in the foreseeable future given that current employment trends suggest that the rise in the number of information workers and jobs will continue. Only 17 percent of U S. workers had information and service-related occupations in 1950; however by 1980, the information/service worker share increased to more than 50 percent" In addition. the meny benefits that have resutted from early pilot projects provide strong incentives for further implementation of this particular TOM measure. The marketing and research l iterature for telecommuting is saturated with the various advantagesthattelecommuting can provide to employees, employers and the commu nity Some of the more w idely -p romoted benefits that can resutt from a successful telecommuting program are pre sented in Table 5." The remainder of this discussion summarizes the findings from a number ofrecentstudies on telecommuting. Some of the studies are national in scope . while others p re sent the experiences of smaller, more regional telecommuting efforts. Futu r e assessments of the potential of and participation in telecommuting are presented and d i s cussed to the extent that the l iterature allows. Unfortu nately, forecasts are somewhat lim ited due to the more recent emphasis of this TOM technique. This i s followed by a review of recent litera ture on implementation strate g ies that will promote the success ofstart up telecommuting programs. The section concludes with a number of recommendations that will increase the successful imple. mentation of telecommuting programs throughout the nation Recent Studies Current studies on telecommuting and pilot telecommuting programs show encouraging results although the true long-term impacts cann ot be examined for some time. Since telecommuting is at such an early stage of ment, it is difficutt to predict its rate of growth or its complete transportation impacts. One of the most com prehensive studies on telecommuting, Transportation Implications ofTolecommuting, was published by the U S.

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Table 5 Potential Bene fits o f Telecommuting BENEFIC IARY PO TENTIAL BEN EF I TS reduces wor1<. commuting wh ich can decrease stress and generate time savings increases to wor1<. w h en m ost productive reduces office-re l ated distractions (e.g .. meet ings socializing etc.) gives a greater sense of i mproves morale and satisfaction T h e Employ.., allows control of work envir o nment i ncreases overall saves money on transportation costs and other employment-related e)(J)enses (e. g., purchase and lau ndering of wor1<. attire. lunches, et c.) may be the o nly means for the or physicallyi mpaired to acquire and maintain emp l oyment allows pregnant employees to continue wor!<.ing longer i f they c h oo s e eases child care and elder care problems improves quant ity and of emp l oyees' work reduces absenteeism/sick leave usage Increases ability to retain valuable emp loye es, thus decreasing t he cost of hiring and retra i ning new staff -enables from an e)(J)anded pool of workers, such as the elderly The E m p loyer t h e p hysi cally-impaired and geographically-remote employees i mproves wor!<.er morale, sat isfaction and motivat ion saves on f acility costs and other ovemead e x penses increases employee adap t ability whic h can promote a problem-solvi n g environment mitigates disrupt i ons in a disaster hel ps achieve compliance a i r reduction regulations red u ces pea kperiod vehicle m i les of trave l by commu t ers reduces fuel consumption thereby conservi n g energy improves air through the reduction of C02 emissions allevia tes traffic congestion, possib l y red u c i ng the cost of and need for The Community h i ghway infrastructure e)(J)ansion and/or maintenance i mproves safety beca use of the dec reased l ikelihood of traffic accidents resu l ting from less congestion i ncreases economic deve l opmen t fo r small since p e rsons may not necessari l y need to move to the for a job Source: Cafifom&a Department of Transportation. Tti.commutlng: A Guide f o r Executives and Telee4mmutJng:: A Handboo k to Help You St up a Program Your company; and Telommutlng: Gttng to Wot* Wfehout Worldng to Get Th.,., Mlnne sota DOT Telecommuti n g Marketing Brochure.

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Department of Transportation (Usoon in Apri l 1993." T h e study i s based on a l itera t ure review and a USOOT workshop and its primary focus is the potential reduction in highway traffic associated with telecommuting. A l so discussed are some exogenous factors that could affect the growth of telecommuting, including: increase in government and local pressures increase i n technological a n d network enhance ments fasterthan-projectedimplementationofenhanced techno l ogy increase in regulatory incentives (il'lcreases in taxes parl(ing fees etc.) increase in direct incentives The adoption oftelecommuting as an is formed by technical. economic environmental legal social and demograph i c characteristics and trends. It is gaining prominence through technology; the changing nature of wo
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total trips are reduced by 20 percent If a person telecommutes twice per week, work trips decrease 30 percent. non-work trips decrease 10 percent, and total trip distance declines by nearly 30 percent. In addition, peak trips are reduced by approximately one-third in the morn ing, and about 10 percent in the evening. Using three-< Findings from this study "An Evaluation of Teleconvnuting as a Trip Reduction Measure," are that telecommuting leads to a substantial reduction in trip generation. vehicle rriles traveled, peak period travel, car use, and freeway travel. It does notleadto an increase in non work trips Sampath et al. used the same data to report preirrinary findings f rom an empirical study of the emissions impacts of tele commuting They found that telecommuting results in a significant reduction in the number ot cold engine starts along with a decrease in the distance traveled. These two factors lead to a decrease in errissions How ever the question remains whether enough people will often enough to make a difference. Telecommuting can affect travel in numerous ways both In the shortand long-term. Mokhtarian also used the survey data from the State of California Telecommuting Pilot Project to examine other transportation impacts of telecommuting such as time place, and frequency of travel who makes what trips mode choice, and residen tial loca tion." The average frequency oftelecommuting is s l i ghtly more than one day per week per person, and approximately 24 person miles (or 22 vehicle miles) of commute distance are saved during each teleeonvnute occurrence. In addition, very few new trips are created: almost four times as many vehicle miles of travel are saved as are generated. Telecommuting is found to affect the time, mode. and desti na tion of travel, as well as who makes the trip. However, It Is not found to impact house ho l d auto ownership. I mpacts o n residential location are determined to be long-term effects oftelecommoting, and could possibly increase the amount of work travel for some. Some studies argue that telecommuting can save money thus resulting in positive net benefits. Arthur D. Little Inc. conducted a study for several telephon e companies and concluded that $23.2 bilflon in annual benefits can be accrued if between 10 and 20 percent o f activities cur rently requiring transportation are instead accomp6shed by telecommuting." These benefits would be obtained through Increased productivity decreased energy con sumption and pollution, decreased transportation intra structure maintenance costs, and increased leisure hours. In 1992, COMSIS Corporation developed materials that would support the development of telecommuting pro grams within the private sector of California The final report describes the three main aspects of those efforts. First. a marketing memorandum was submitted to Caltrans relating potential marketing strategies. In addition a series of materials was produced and distributed to tar geted companies with telecommuting potential. Finally, two telecommuting workshops were conducted for TOM service providers. The report notes that telecommuting is ala break -thro ugh point." where widespread implemen tation is possible. Specific recommendations for Caltrans are provided and a comprehensive marketing strategy to position telecommuting as a mode that directly enhances business operations" Is stressed." Denver recently hosted several productive TRP (Travel Reduction Program) 2000 serrinars, which focused pri marily on telecommuting These serrinars were directed at management and included a wide range of strategies for businesses Telecommuting was promoted as an increasingly common cost--saving tool for management, as a way of "unload ing expensive office space. Also presented were success stories of local businesses and their experiences with telecommuting. As evaluations of pilot telecommuting projects in Califor nia and elsewhere are conducted an extensive federal pilot lelecommuti ng program is proving itself to be a success. This particular program was implemented by the U .S. Office of Personnel Management (OPM) i n January 1990 and involved 700 Federal employees. The project, known as Flexiplace, was analyzed utiUzing survey ques tionnaires covering three rating periods: the baseline period (six months immedia tely preceding impleme nta tion). the first six months of the pilot. and th e last six months of the pilot. Findings of this evalua tion i nclude the following:

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Thirty-fivepercentoftheparticipantsinthisprojecl work schedules, sateltite work locations, and indicated a decline in peak period travel. teleeommuting.2 More than 90 percent of supervisors and 95 percent of participants noted that job performance remained unchanged or improved in comparison to performance preceding the implementation of the program. More than 90 percent of all respondents (partici pants and their supervisors) befieved there was no change in the effectiveness of work-related interpe rsona l c onvnunication and of those sensing a change most perceived an i ncrease in communication effectiveness. More than 90 percent of the supervisors indicated that Flexiplace did not re sutt in significant organi zational expenses In general, Flexiplace has been recommended for adoption by those federal agencies where telecommuting is feasible. In October 1993, the White House issued the "C6mate Change Action Plan ." This plan consists of almost 50 strategies to reduce greenhouse gases to 1990 l eve ls by the year 2000." One of the strategies directs the USDOT to implement and assess a federal employee tel ecommuting program evaluate other telecommuting programs i n both the public and private sectors, and promote greater use of telecommuting throughout the country. One means of promoting telecommuting is through outreach methods, such as the open house held in Washington, D.C. in November 1994 where represen tatives ofthe four telecommuting centers in the Washing ton area shared information about telecommuting. I n addition a telecommuting seminar w il1 be he)d in Seattle to encourage Federal agencies there to adopt such pro grams. Nationally, the CNmate Change Action Plan set a goal of one to two percent ofthe wor1
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have indicated significant average annual growth rates in the U S telecommuter population in the last seve ral years." The use of this information as basefine data for telecommuter population forecas1s seems to have re sulted in overly optirristic projections. It may be t oo early in the maturation process of this TOM measure to be able to accurately forecast future participation. Ins tead of attempting to project the extent to whlch telecommuting will be utilized in the future some of the li terature ra ises issues involving the factors that may eventually telecommuting As one of tile more recent TOM measures it is obvious that changes in the traditional work environment brought about by telecommuting may meet with some resistance Management methods are going to have to evolve to deal with telecommuting em ployees, b ut it may be difficult due to force of habit. It is possible that overall employer policies may serve as an obstacle to the implementation of telecommuting on any worthwhile scale. as could union bylaws and require ments for certain industries. One of the chief concerns for e mployees is the need for face-to-face, social interaction Th i s need may ultimately determine the upperlirrit on how often a person could rea listi cally telecommute during any given time period. One to two days per week is currently the typical average telecommuting frequency.'' Other employee concerns include the following:'" Decreased visibility may hinder an employee's opportunity for a raise or promotion. Proper work space may not be ava ilable in some emp l oyees' ho mes. Home utility expen.ses may incr ease significantly The separation of "work" and 'home" may be come increasingly difflcutt. Tendencies toward 'workaholism" may be aggra vated. Some researchers believe thatthe currenttiterature leaves an un resolved picture" of the transportation implications of telecommuting since some studies show tllat long term effe<:ts may Include increased number of non-work related h ome-based trips (since will not be able to link trips during their morn ing or evening commute), the generation of new trips from the emergence of latent travel demand, and that some telecommuters may choose to live further from work, possibly Increasing overall rriles of travel." In addition, the posslbdllty exis1s that a telecommuter's vehicle may be used by a farrily member or mend, resulting in a trip that would not other wise have been made. Thus, some of the liter ature concludes will not have any significant impac1s on vehicle transportatio n or the aggregate con sumption of motor fuels. To summarize, it is not yet clear what the future holds for telecommuting as a formal comm ute alternative policy initiative. Currently, LINK estimates that less than half of the 7.6 million telecommuters in the U.S. participate in formal work-at-home programs'' For the most part, telecommuting In the U.S. is re la tively informal and takes place on a part time basis. Proponents point out that telecommuting will not only reduce traffic congestion, fuel consumption, and air pollution, but it will also help impro ve employee productivity retention, and morale ; reduce ab and sick leave usage; and benefit companies through reduced rea estate costs and employee recruit ment and training cos1s. On the other hand, the l rterature a lso contains less optimistic viewpoin1s that argue that telecommuting may result in increased non-work travel or that it can possibly stimulate urban sprawl in addition to hav ing adverse i mpacts on public transportation and ridesharing'' Unfortunate ly much of the information available on telecommuting's current succeSs and future potential is seemingty inconclusive, and often contrary in nature. In order to form ul ate better policy strategies additional data will be needed, as will further research on the actual benefi1s and disadvantages of telecommuting and a clearer understanding of a person's motivation to use or not to use this commute atternative Condusions Curiously. of those who study future trends and call for less dependence on fossil fuels and decreased traffic congestion and energy use, very few deal directly with telecommuting as a means of reaching these ends. How ever, according to The Road to 2012: Looking Towards

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the Next Two Decades, moving lnfonna tion Instead of p!Klple is becoming more prevalent." Several quotes from prominen t government and business indiv iduals stress the importance of telecommuting in the future: we can also replace conventional commuting whsrevfN'possiblev.lthvWJatisnowknownastelecommuting. This technology is already in widespread use, as incteasing numbers of people work at home but keep a direct connection to OOINOrkers through a communi cations/ink bwettn their computsr stations. As the capscityof computer networlcs incr&ases, this trend is likely to acce/erattJ. -Vice President A lbert Gore "I cannot think of a better way to launch any organization into the '90s including my own than by ... ttllecommuting."" -Tom Peters President, Tom Peters Group If an organization is looking for w ays to be more environmen.taJJyrssponsibleand to make its employ ees more pfoductive or to keep its more productive employees then telecommuting should be ered "$T Dick Watson. Washington State Energy-Offlce Sometimes the best transportation policy means not moving people, but moving their work ... Think of it as commuting to work at the of light."$$ -President George Bush Our contemporary t ransportation system has facilitated job, housing and business opportunities in dispersed locations, and the use of these loca tions has bee n made more s imple by significant improvements in.telecommuni .. cations technology." However, the scattered pattern of l and use which has resutted cann ot continue to be sup ported by the current transportation system. A new way of moving people to their work must be developed A possible way of alleviating th is p roblem is moving the work to the people through the widespread implementation of telecommuting. Telecommuting may not be a complete solution. but It can setve as a "bridge to the future while the relationship between land use, density, and the sup porting transportation system is reexarTined ... Instead of in.creasing transportation capacity at ever-growing costs, ways to provide access through telecommunications can be explored, perhaps through utilization of the flexible funding features ofthe lntermodal Surface Transportation Efficiency Act (ISTEA) of 1991. ISTEA, along with the 1990 Federa l Clean Air Act Amendments and federal economic growth policies, can expedite strategies and actions to replace travel demand with telecommunica tions setvices and telecommuting. There is not always agreement in the literature on the rate of growth oftelecommuting, the presence and magnitude of its potential advantages and d isadvantages, and the extent to which these advantages and disadvantages will affect the transportation system. However, current litera ture does tend to concede on what conditions are neces sary within an organization to achieve the maximum possible benefits (for employees and their families em ployers, organizations, and society) from a telecommuting program. The most common ly stated preconditions are lis ted below:'' Suitable job The wor1< must be able to be performed (at l east in part) at a remote loca tion. Suitable employees The personal characteris tics and abilities of the employee must be suited to working with no direct supetvision. Suitable telecommuting workplace The em ployee must have a place to work that is free of distractions. Top-down support Is vital The organization must consider telecommuting as a reasonable and desirable alternative. Senior management must provide support. Senior management support is necessary .. All managers and decision makers within the organi .. zation must accept the idea and practice of telecommuting. Telecommuters and thei r supervisors must be volunteers-Both employees and managers mustfeelcomfortablewithtelecommutinginterms of its suitability to persona l work hab i ts, its effects on social interaction and career advancement.

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and its impa cts on management style and the organization. Training is key S ignifica ntly higher perfor mance results are noted when both the telecommuters and their d i rect supervisors par ticipated in telecommuting-specific training prior to initiating a p rogra m Availability of adequate, cost..,ffective tech nology -It is essential that the telecommuter has sufficient technological equipment to complete work at home. However, most of the Wterature finds that major capital investments are not nee-essary. It is clear that a better understanding of telecommuting and its potential market will be necessary to properly incorporate this technique into today' s travel deman d management arsenal. Knowledge on which jobs and individuals are amenable to the prospect of telecommuting is important to its future success, as is understanding why people will or will not choose to participate in or support telecommuting. The fortun e of subsequent te lecomm uting programs will depend on prope r implementation the SUI>port of all parties involved, and the avoidance of the pitfalls that predecessors may have encountered. Since many benefits will be reahzed no matter if the level oflmplemen tation is national, regional or merely local it is imperative that planners and decisionmakers concentrate on starting telecommuting programs, and not on potential limiting factors or projections of future participation. SUMMARY Encoureglng the use of commuting atternatives, such as public transportation, ridesharing, and wor1
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APPENDIX A: URBAN AREA CoMPARISONS A database of population demographic and journey-to-work characteristics was compiled for urban areas In the U.S with a population exceeding 500 ,000 in 1990 Since !his information may be useful to transportation planners and decisionmakers. thi s information is p rovided in this appendix. This enables the identification of areas with similar characteristi cs which can then be contacted, potentially resulting In opPortun ities to learn from expariences i n other parts of th e country The following data elements were compiled for urbanized areas in the U.S. as defined by the Census Bureau. In addition, the urbanized areas are ranked for each data element. Total Population Number of Workers EmploymenVPopulation Ratio Age< 16, Percent of Total Popula tion Age 16 to 59, P ercent of Tota l Population Age 6()+, Pe rcent of Total Population Age 65+ Pe r cent of Total Population Did Not Finish High School Percent o f Persons Age 18+ Females Percent of Tota l Population Minorities, Percent of Total Population Median Household Income Household Size Below Poverty Level, Percent of Total Population Work O i sabifity, Percen t of Age 15+ Carpooi/Vanpool to Work, Percen t of Workers Age 16+ Use Trans n for Work Trip, Percent of Workers Age 16+ Work at H ome. Percent of Workers Age 16+ Average Travel Time to Work (minutes) D rive Alone to Work Percent of Workers Age 16+ Work Departure Time 6-8 a.m. Percent of Workers Age 16+ Work Departure Time 6-9 a.m .. Percent of Workers Age 16+ Work Outside Home County o r State Percent of Workers Age 16+ 0 -Vehicle Households, Percent of Total Households Number of Private Vehicles par Household Number of Workers pe r Household

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UNrn::D STATES Table 6 Tota l Population N ew Y ol1c, NYNor1hNstem New JIN'Sey Loa Angtle$, CA Chlea90, ll-riorthwestem Indiana Phllohla. PA-NJ Detroit, M l San Franeiseo-Qakland, CA \Mts h ington, OC-MO-VA O.llu-Fon Wonh. TX Houston, TX Boston, MA San Oiego, CA Atlanta GA Minneapo!C$-St. Pa\1 MN Phoenlx.AZ St. l..ouls. MO-I L Miami-Hialeah, Fl. Baltimore, MO Seattle, WA Tamp a-SI. Peter&burg-Ciearwater, Fl Pittsl>urgh,PA Cleveland, OH Denver. CO San Jose. CA Norfolk-Vtrginia News VA Kansas City, MQ-KS Fort Laucltrdalt-Hollywood-Pompeno S.ach, FL Mltwauk;ee, WI Cincinnati OH-KY ORWA Riverside-San Bernar'dino. CA San Antonio, TX SaQfamtnto. CA New Orleans, LA Buffalo-Niagara Fats, NY Co llmbus. O H Indianapolis. I N Otlando. Fl. Providence-Pawtucket, RJ-MA Memphis, WHt Palm Stach-Boea Rston-Oeny Bea.eh, Fl. SaR Lake Cily, UT Ol
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UNITED STATES Table7 Number of Workers New York, NY -Northeast em New Jef'M)' Los Ano-les CA Chicago IL4lorttrwe5tem I n diana Philade lphia, PA NJ WUhi ngton OC-MO-VA San Francisco-Oaklan d CA Dallas-Fort Worth, TX Detroit, Ml Boston,MA Houston, TX Sin O l ego CA Atlanta. GA Minneapolis-St. Paul. MN Phoenix. /IZ. Baltimore, MO Seattle, WA St. louis, MO-IL Miami-Hialeih, FL Denver, CO Tampa-St. Petersburg-clearwater, FL SanJote, CA Clenland OH Plttsburgl'l, PA Norfollt-Virginia 8eaeh-Newport News, VA Kansas City, M O -KS Portland-Vancouver, OR-WA Mi!Waui(H Vv1 F.ort Lauderdal e -Hollywood-Pompano Beach Fl Cincinnati, OH-KY' Sa(;ramento. CA. Riverside-San Bernardino, CA San Antonio. TX Columbu s OH Or1ando, F L Indianapolis, I N New Orleans. LA B utfaJo-Niagara F alls, NY P r ovidence Pawtucket, RI-MA Ok lahOma City. OK TN-AR-MS JaebOnvillo, FL Salt Lak e City, UT lOUiSVille, KY I N Las V egas. NV \Nest Palm B e ach-Boca Raton-Oehy Beaeh, FL Honoh.Jiu, H I Richmond, VA Rochestef, NY Austin, TX N ashville, TN Dayton, OH Birmingham, AL Omaha, NE-I A Hartfotd-Midd l e town, CT Tucson, AZ Albany-Scheneclady-Troy, NY Spllnglle l d MA..CT A kron, OH E l Paso, TX-NM 1 1 5,070.27 4 7,528,518 5.457.037 3.217 ,890 1 959 405 1 9 1 2 605 1 ,859,904 1 642,966 1 6 1 3 125 1 442,168 1 401,906 1 ,160, 790 1,148 978 1,116,683 949,681 928,084 927, 316 918,967 878,S.S 7a!l,327 780,275 766.234 752,260 735 310 662.616 638 759 582.478 582,205 578 ,861l 570,304 507,788 495,769 492,678 479,0 1 2 487,196 .SS,907 433.327 422 980 4013.974 376,756 375,523 368,307 357,260 352,717 351,935 350.622 336 364 306 362 298 539 297,716 294.184 285.924 278 312 275 880 273 152 261,730 249.865 249, 071 234,835 219,684 2 3 4 5 6 7 8 9 1 0 11 12 13 14 15 16 1 7 18 19 20 2 1 22 23 24 25 26 27 28 29 30 31 32 33 34 35 3Q 37 38 39 40 41 4 2 43 44 45 46 4 7 48 49 so 51 52 53 54 58 96 57 96 59

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Toble8 WorlcerAopulotlon Rallo WOshii'Qion, DC-MD-VA Mlnneapolia-St. Paul, MN San Joae, CA Atlanta, GA HI Seattle, WA Austin 1X Orfando .Fl Denver, CO Boston, MA Richmond, VA Dallas-Fort Worth. TX Nashville. TN San Francisco-Oakland, CA Omaha, NE-IA COIUI"'U>Us, OH Las Vegas, NV l ndianapoli$, IN NorlolkVwglnia Beach-Newport News, VA Hortforo-Middletown CT Kansu City MO-KS J acksonville FL OR WA San Qiego, CA Bammo.r. MD Albany-Sehenedady-Troy, NY Houston, lX Rochester, NY Oldahoma City, OK Los A ng efes, CA Ptovld&nct-Pawtucket. Rt-MA Milwaukee, w Chica.:g9, I L-Norttwtest em l n cia na PhoeniX, AZ St loui$, Mo-fl Clr\Qnnatl. OH-K New York NY -Northeastern New Jers.ey Fort lauderdale-Holtywood-Pornpano B eaeh Fl Springlleld, MA-CT Louisville, t
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Table 9 Age < 16 Percent of Total Populat ion Sak lAke C;ty, UT Rive r&ide-San Bernardino, CA El Paso, TX-NM San Antonio TX H ouston, TX omaha. NE-IA M emp his J'N-AR-MS N.w Ol'ltaM, LA Dallu'-Fon W>rltl, 1X Saaamento CA Clnclnnad OH-'it,MI Atlnla. GA Tuc...,,AZ Binningham, AL Portland-Vancouver. OR-WA Oayton OH Columbus, OH las Vegas NV San 01090, CA Rochester. N)' Austin. 1X Loui:svile, KY-I N Orta.ndo, FL Richmond, VA Philadelphia PA-NJ C""' eland, OH Baltimore, MO A kron, OH Miami-HMah, FL Sptlnglleld MA-CT San Jose, CA t-lashvile, T N Seattle, WA Honolulu, H I Buffalo-Niagara Fa its, NY Washington, DC-MD--VA N e w York NY-NOI'Iheast em Ntw Jtt.My ProvidenCe-Pawtucket RI-MA H artford-Middletown, CT San Franei:seo-Oakland, CA A lbany-Scheneetady-Troy, NY Pitlsburgh, PA Fort Lauderdale-Holywood-Pompan o Sta c h F l Tampa-St. PMenburg-Ciearwater, FL Boston, MA \Nest Palm B e aetH:loea Raton-Delray Beach. FL 31.84% 28.73% 28 67% 28.00% 25.83% 24.98
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TablelO Age16 to 59, Percent of Total Population Auofu,TX Wsshinglon, DC-MD-VA Atlanta, GA S.nJose .CA Dallas-fort VVorth, TX Seam., WA Columbus. OH San Francisco-Oakland CA Boston MA Houolon,TX Nashville T N Orlando Fl Los Angeles CA Norlolk-VgirUa Beacn-Newport News. VA Denver. CO San Diego, CA Mlnne:apoii$-St. P au l, MN LasVegu, NV Richmond, VA HonolulU, HI Jacksonville. Fl Baltimore, MD New York, NY -Northeastern New Jersey Portland-Vancouver, OR-WA O*homa City OK Sacramento, CA Indianapolis, IN Chleago. IL-Northwestem lna1ana Hartford-Mi ddle town. CT Dayton, OH Albany-ScheneetadyTroy, NY Memphis, TN-AR-M$ Tuc:100, AZ Rochester, NY Karms City, Mo-KS Omaha, NE-IA San Antonio, 1X UNITCD STATES Detroit, Ml Phoenix:, AZ Rivlf'Side-San Bernard ino, CA Akton. OH New Or1eans, LA Louisville, KY-ni PA-NJ Miami-Hialeah, Fl Providenc e-Pawtucket. RI-MA Springfteid MA-CT El Paso, TX-NM Milwaukee, w Sl loui&, Clnc:::innatt, OH-KY 8 1 rmingMm AL Cleveland OH Burr.Jo-Niagata Falls. NY Pittsburgh, PA s. Lake City, UT fort B e ach, Fl Tampa-St. FL West Palm Beaeh-Boea Beaeh, FL 68.70'11 66.70'11 ee: -64.66'11> 64.50'11> 64. 45% 6437% 64.26'); 64.15% 64,02'); 63.81% 63. 73% 63 68% 63.54% 63,49% 63.40'); 63. 13% 62.84% 62.74% 62. 13% 61.78% 6 1.6211b 6 1.-61 15% 61 .13'% 61 04% 60. 94% 60,89% 60. 78% 60.78'!6 60.47% 60.S2 % 60.30'11 60. 21% 60. 04% 59.93'll> 59. 88% 59.85% 59, 791\ 59.75% 59. 75% 59. 61% 59.43% 59.39'16 59.37'16 59.36% 59,26% 58.45% 58,3 1 '4 57.54% 56.68% 56.08% 55.57'16 51.n% 1 2 3 4 5 6 7 8 9 10 II 12 1 3 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 35 36 37 38 39 40 41 42 43 44 45 46 47 46 .. 50 51 52 53 54 55 56 57 58 59 -------------11-------------

PAGE 91

Tablell Age 60+, Percent of Total Population \Most Polm Beac:h-l!oca Rator>-Dtlray S..eh, Fl Tampa-St. Petefsburg-Ciearwaler, FL Fort L.auclerdate-Holtywood-Pompano 8each, FL Pm.burgh,PA ButraJo-tiaagara Falls, NY Prov ic:knc:e-Pawtuel<.et, RI-MA Cleveland OH Albany-scheneela 16. 55% 16.39'16 16.39% 1 6 t0'% 15 .94'16 1 5 ,8W 15 79% 15. 75% 15, 54% 15.24% 1 5 .04'16 1 4 74% 1 4 61% 1 4 59% t 4.57% 1 4.44% 14.43'16 14.43% 14.35'16 14.30% 13.54'16 13.5 1 % 13.3 1 % 13.26'16 13.06'16 12.38'16 12.24'16 12 .23'16 11.90% 1 1.4704 11.23% 11.06% 10.69% 10.0211> 9.43% 1 2 3 4 5 6 7 8 9 1 0 11 12 1 3 1 4 15 16 17 18 19 20 2 1 22 23 24 25 26 27 28 29 30 31 32 33 34 3 5 36 37 38 39 40 41 42 43 44 45 45 47 48
PAGE 92

Table 12 Age 65+, Percent of Total Population Wist Palm Btaeh-Boca Retoo-llehy Beodl FL Pettraburg-Cieanvater, Fl Fort LoUdt-H ollywood-l'ompono Bttch, FL Pltl>l>urgh,PA Faits, t4Y ProvidtnotP awtuektt. R.I-MA Albl:ny-Sehene<:tacty-Troy, NY Clev-OH SpinQI11d. MA-CT Mil-looh,Fl f'tllocltlpllio PA-NJ AJcron, OH BirmingNm AL. LOultvlllt, KY -lN 8oston,MA New Yortc, NY -Northeastern New Jersey Roc::tluter, NY Sl Louis MO-ll Milwaukee, WI TUC$0n, AZ l'lloenb( .I>Z UNital STATl:S Cft:innoli. OH-' 12. 19'1(, 12 .08'1(, 12.07'1(, 12.02'1(, 11.94'1(, 11.69'1(, 11.68% 11.54'1(, 11.18'tb 11,(16'1(, 10 .9:rJJ 10JWt6 10 .84'1(, 10 .s.:n& 10.52'1(, 10 .49'1(, 10.28'1(, 10.0 1% 9 ,94'1(, 9 .58'1(, 9 58% 9 .54'1(, 8 .95'1(, 8 .74% 8 .73'1(, 8 .44'CJf.. 8.31'1!. 8.22'1(, 7 .02'1(, 7 .63,. 6 .90'1(, 6.87'1(, 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 2 1 22 23 24 25 26 Tl 28 29 30 31 32 33 34 35 3S 37 38 39 ) 41 42 43 44 45 46 47 48 .OS 50 51 52 53 54 55 56 57 58 59

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Table13 Did Not Finish High School, Percent of Persons Age 18+ E l Puo, 1X-N M 36.19% I Mlaml4ilalaoh, FL 35.03% 2 29.96% 3 New Olleal\$, LA 28.04% 4 Los Angeles, CA 27.59% 5 San Antonio, TX 27.30% 6 Balimore, MD 28.94% 7 louisville KY -IN 28.39% 8 New Y one, NY -Northeastern New J fl('$8'f 25.97% 9 Mempllis, TN-AR-MS 25.64% 10 Springftetd, MA-CT 25.45% II Riverside-San Bernardino, CA 25.23% 1 2 Detroi t M l 24.91% \3 Philadelphia, PA-N J 1 4 C leveland, OH 24.69'JE> IS UNITED STATES 24.61 % Bul'hllo-Nfagara F a ts, NY 24.48% 16 Houoto 35 Oalla.sFort Wort h TX 20.64% 36 West Palm Such-Boca Rato n -Delray Beach. Fl 20.13% 37 Albany-ScMnectady-Troy NY 1 9 .49% 38 Oklahoma City, O K 19.25% 39 Orlando FL 19. 1S't. 40 TU<$0n, PZ. 19.08% 41 Hono l ulu HI 1 9 .07% 42 Col.lmbus, OH ta.n% 43 Phol1\lx PZ. 1 8 16% 44 San Diego, CA 1 8 13% 45 AlSanta, GA 17.65% 46 San Jose. CA 17.64% 47 Sacramento CA 17.61% 46 Kansat Cily MO-KS 17.06% 49 San Franelseo-OJJCtand, CA 16.95% so Boston, MA 16.75% 51 Austi n TX I 5 .97% 52 Omaha NEI A 15.71% 53 Portland-Vancower, OR-WA 14.82% 54 Oerwer, CO 1 4.76% 55 w .. IWnglon, DC-MD-VA 1 4.29% 56 san Ul
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Table14 F e males P e rcent of Total Population Sirmingham. AL 53.-a% 1 R ichmond VA 53.16% 2 Pitob urgh, PA 53.12% 3 Louisville, KY-IN 52.90'l; 4 Memphis, TN-AR-MS 52.62% 5 Buff8Jo-Niagara F aJit, NY 52.61 % 6 C leveland, OH 52. 76% 7 New Orleans, 1.A 52.69'0 8 Tampa-sL Petersburg-Clearwater, FL 52.62% 9 Sl. Louis, MQ.-,IL 52.60'lb to Philadt l phia, PA-NJ 52.47% ,, Sprlnglleld. MA-CT 52. 46% 12 Cincinnati, OH-KY 52.44% 13 I ndianapolis, I N 52.38% 14 AJ)any-SehenedadyTroy, NY 52.37% 15 Akton, OH 52. 37% 16 New York, NY -Northeastern New Jersey 52,37% 17 Nashv ille. TN 52.36% 18 Hartf o n:t-Midd l e town, CT 52.36% 19 Weat Pakn B each, Fl 52.32% 20 Rochester, NY 52. 30% 2 1 Provkft;nee-Pa'Mueket, R I-MA 52. 30% 22 SO&ton MA 52.26% 23 Milwaukee. 'M 52.21% 24 Fl. 52. 19'0 25 Ka n sas City, MO-KS 52.18% 28 a.,_re,"'lO 52.16% 27 Ot1, 31 Oklahoma City OK 5 1.63% 32 Chicago, I L-Notttlwestem Indian a 51.63% 33 Oma ha, NEIA 51 .62% 34 San Arionio, TX 51.58% 35 Atlanta, GA 51 56% 35 Washington, OC-MO-VA 5 1 54% 37 E l Paso. TX-NM 51 52% 38 M inneapolis St. P aul, MN 5 1. 43% 39 PortlandVancouver OR-WA 5 1. 40% 40 1\IC$00, p.z 51.30% 41 UNITED STATES SUI% J ackaonville, Fl 51. 20% 42 Sacramento CA 51.15% 43 Oenver. co 51 04l6 44 Phoeni x AZ 50. 8 7 % 45 Se ame, WA 50. 76l6 46 Orlando, Fl 50. 70% 47 Dallas-Fort Wortft, TX 50,69,., .a Sin Franeiseo-OI!Oanc:t, CA 50.68% 49 SaK Lake City, UT 50.46% 50 Houtton, TX 50. 34% 5 1 RNerside-San Bernardino, CA 50. 29% 52 A ustin, 1X 50.12% 53 los Angel es CA SO.OI'l; 54 Norfolk-VIrginia 8eaci\.-N ewport News, VA 49.84% 55 Las Vegas., NV 49.4 t % 58 Stn l);ego, CA 49.36% 57 Honolulu H I 49.3 4 % 58 San Jose. CA 49.30% 59 II

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TablelS Minorities, Percent of Total Population HonolJiu, HI 70.86% 1 Memphis, TN-AR-MS 45.20% 2 New Orteana.. LA 41.52% 3 los Angeles, CA 38.70% 4 \Mtshingt o n DC-MD-VA 37.75% 5 Birmingham, AL 38.89% 6 H OU$lOn. TX 35.89% 7 San F'ranelseo-Oa kland, CA 35.06% 8 Atlanta GA 33.53% g Blltlmo,., MD 33.02% 10 Norfolk -VIrgtnla Beach-Newport News. VA 11 New NY -Northeastern New Jersey 12 Chicago, IL-Northwestem In diana 32.13% 1 3 R ich mond, VA 31.57% 14 SanJos.e, CA 3 1 .37% 1 5 Riverside-San Bernardino CA 30.00% 16 M1 27.82% 17 Dallas-Fort WOrth, TX 27.70% 18 Miami-Hialeah Fl 27.19% 19 Auotln. TX 28.66% 20 San Antonio, TX 26.43% 2 1 Philadelphia PA-NJ 25.81% 22 San O iego CA 25. 8 1 % 23 JaekSOnvllle, F L 25.43% 2 4 Sacramento, CA 24.28% 25 UNITED STATES 24.24% Cleveland. OH 23.55% 28 El Paso, 1X-NM 27 Nashville, TN 22.87% 28 H artfotd Mid dle town, CT 22.86% 29 st. louis, MO-l l 22.49% 30 Tucso n .AZ. 21.61% 31 lndiana.polis, I N 20.16% 32 ... WI 20.12% 33 Oklahoma City, OK 20.04% 34 las Vegas NV 19.42% 35 C o lumbus, OH 1 8 .80% 3S Fort B each FL 1 8 .51% 37 Dayton OH 18.48% 38 011an40,F l 18.45% 39 Kanns Cjty MO-KS 18.06% 40 Roehe$-t.r NY 17.82% 41 Cincinnati, OH-KY 16.79% 42 louisvi l le, KY-IN 16.76% 43 Oerwer CO 15.06% 44 F alls N Y 15.07% 45 Phoenlx,AZ 1 4 6 4 % 46 Seattle, WA. 47 Springlleld, 13.97% 48 Sos1on,MA 13. 15% 49 AkrOn, OH 13. 1 4 % 50 VVest Pam Beach. Fl 13 .09% 51 Tampa-St. Petersburg-Clearwater F l 12. 44% 52 Oma ha, NE-IA 12.22% 53 Pmsbutgh, P A 11 .10% S4 Portland-Vancouver OR-WA 9.92% 55 Albany-SchenectadyTroy, NV 9.57% 56 Prov idence-Pawtucket, RI-MA 9.41% 57 Mimeapolis-St. Paul, MN 9.06% 58 L:ake Cl1y, UT 6 .58% 59

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Table16 Median Household Income San Jose CA WUhlngton, DC-MD-VA Sin Franei$00-Qaldand, CA HonoliJ1u HI Botton. MA Hartford-Middletown, CT New Yort, NY-Northeastem New Jersey los Angeles, CA M lnneapolfs-St Pa u l. MN Seattle WA Atlanta GA Chicago, IL-Northwestem Indiana Riverside-San Berna r dino, CA Baltimore, MD San Olego. CA P hiladelphia PA-NJ Roch ester, NY Detroit, Ml Riehmond, VA Oallu-Fort 'M)rth, TX 'Nest Palm Beaeh-Boc:a Raton-Qetray Beach, F l. Sacramento, CA Springfield, MA-CT Albany-schenectadyTroy NY O.nver, CO St. louis MO-i l Kansas Clty, MO-KS Houston, TX Orlando, Fl Providence-Pawtuck e t, RI-MA Mimauk ... WI lndlanapo6s. IN Phoenbt,AZ Dayton OH Las Vegas NV Norlolk -VIrginla Beach-Newport News VA Sal lake City UT Cincimati, OH-KY Po rtfan d-Vancouve.r, OR-WA Fort Lauderdalt-Hollywo<>d-Pomf)3M St-ach. FL CoiumbU1, OH Cltvttand, OH UNITED STATES Omaha, NE-IA Nash\lillt, TN Jacksonville Fl AlMn, TX Oldahoma City. OK. Pilt$burgh PA Akron, OH Birmlngf'wlm. AI. Miami-Hialeah FL Louisville, KY-IN Buffalo-Niagara Fall$, NY Memphis. TN-AR-MS Tampa-st. F L Sin Antonio, TX Tucaon AZ. New Ortuns, LA EiPuo, TX-NM $48,151 $46,718 $<0,428 $39,826 $a9,691 $38,145 $37,262 $37,029 $36,519 $36,058 $36,034 $35,224 $34,644 $34.612 $34,611 $34,400 $34,223 $33,824 $33.250 $32,713 $32,474 $32,306 $32,255 $32,165 $32,162 $31,960 $31,639 $31,526 $31,466 $31,427 $31.048 $30,687 $30,681 $30,657 $30,620 $30,619 $30,592 $30,5lH $30,499 $30,381 $30,373 $30,107 $3<),058 $29,869 $29,848 $29,655 $27,371 $27. 261 $27,25:3 $27,252 $26,858 $26,826 $26,n6 $26.762 $26,717 $26,290 $25,698 $25,102 $23,590 $22,676 1 2 3 4 s 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 2 1 22 23 24 25 26 27 28 29 30 3 1 32 33 34 35 36 37 38 39 4() 41 42 43 44 45 46 47 46 49 so 51 52 53 54 55 56 57 58 59 -------------11-------------

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Tobie 1 7 House h old Size, Persons Per Household El f'Ho, TX-NM Riverside-San CA san tak e Cily,LJT HonolulU, HI San Antonio, TX s:an Jose, CA Norfolk-Virginia Beach-Newport News. VA Sin Otego, CA M iami-H i a)Nh. F L Houston. TX Chiea90, IL-Northwtstem Indiana New Yottc, NY -North eastern New Jersey Philad.elphi a PA-N J Mmphl$ TN AR M S New011earos. LA Springfield, MA-CT Ml Balimote, MD Dallas-Fort 'hbrth. TX 011ando. FL Washington, OC-MD-VA Omaha, NE-IA Saeramtnto, CA U NITED STATES FL Providence-Pawtucket, Rl-MA Ailanta ,GA. M ilWauk ee WJ Boston. MA PhoenllC, AZ. St. Louio. MO-ll Cincinnati, OH-KY San Fnmciseo-Oaldand, CA Hartford-Middtetown, CT Rochester, NY Akron. OH Minne.apolis-Sl P aul, MN Birmingham, A L las Ve ga&, NV Oklahoma City OK Dayton, OH Karosa Cily, MO..KS Cleveland, OH Cotumbos, OH TUC$0n, AZ l n cianapolis I N LouiS"'ile KY -IN A l bony-$eh..,ectady-Troy, NY Fall s NY Rich mond, VA Na s hVilt, TN Portland-Vancouver, ORWA Pilt>burgh PA Otnve r CO Auotin, TX S..ttto, WA Fort Lauderdale-Hollywood-Pompano St-ach. FL Tampa-St FL Ptlm 8ta<:h-8oca Ralon-O e lray Beach, FL 3 . 30 3 .11 3.04 3.03 2 .96 2.89 2.86 2.83 2.79 2.79 2.78 2.75 2.72 271 270 2.69 2 .69 2JS7 2Jf1 2.64 2 .64 2 .84 2 .84 2.63 2.83 263 262 2 .62 2.62 2 62 2.60 2.60 2.60 2.59 2.58 2.58 2.58 2 .58 2.58 2 .57 2.56 2.55 2.54 2.54 2 .54 2.53 2 .53 2.52 2 .52 2 .52 2 5 1 2 .51 2 .4 9 2 48 2 .48 2.47 2 .46 2 .37 234 2 .31 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 35 36 37 38 39 40 41 42 43 44 45 46 4 7 46 49 50 51 52 53 54 55 56 57 58 59

PAGE 98

Table18 lelow Poverty Level, Percent of Total Population El Paso, lX-NM 26.54% 1 New OltNnt, LA 22.28% 2 San Antonio. TX 20 .1"4'!4 3 M"""hls. TN-A R-M S 18.73 % 4 FL 18.01'!4 5 Tueson.I>Z 17.32'!4 6 Austin, lX 15.81% 7 Birmingham, Al 15. 70% 8 Houston. TX 15.31% 9 Detrok. M l 13.91'!4 1 0 Akron, OH 13.78'!4 11 LOUi:SVIIt, KY-IN 13.67'!4 12 LOS AngelOS. CA 13.63'!4 13 Oklahoma City. OK 13.59'!4 14 Butralo-Niagva Falls, NY 13. 18% 15 UNITED S T ATES 13.12% Columbus, OH 13.09% 1 8 Mitttaukee, \M 13.05% 17 Dayto n OH 12.60% 16 Riverside-San Bematdino, CA 12.60'!4 1 9 New York, NY-Nol1heastem New Jersey 12.42% 20 Sacramento, CA 12.39'!4 2 1 12.31'!4 22 Chicago. I L N orthwutem Indiana 12.30'!4 23 Phoenlx.I>Z 12.06'!4 24 S prirlgfield. MA-CT 12.03'!4 25 Jack sorwile, FL 12.01% 26 Dallas-Fort '11\brth, 1X 1 1.92% 27 Cincinnati, OH-K'Y 11.66'!4 26 Nashville, TN 11.83'!4 29 Piltsburgn.P A 11.79'!4 30 Norfolk-Virginia News, VA 11.66 % 3 1 San Diego, CA 11.49'*> 32 Baltimore. MD 11. 42% 33 Phila
PAGE 99

Table19 Work Disability, Percent of Civilians Age15+ UNITED STATES Tampa-st. PtteJ'$burg-Ciearwater. FL Pmsburgh PA Loui:svile, K'f-IN Ottrolt, Ml Akron, OH New Orteans. LA RI-MA Cleveland ; OH Tucson, /a. Birmingham, AL West Palm Beach-Boca Ralon-Dmy Beach, FL Dayton OH Fort Lauderdale -Holtywo o d-Pompano BeaCh, FL. Portland-Vanoouver, OR-WA Buffalo-Niagara Falls N Y Sactame!U, CA Oklahoma City, OK P hiade\'h la, PA-NJ Baltimoce, MD Cincinnati, OH-KY Jacksonville, FL Springfiekt, MA-CT Memphis, TN-AR.....US Las Vegas, NV st Louis, Mo-IL Albany-Sclleneelady-Troy, NY Columbus, OH NaShVIlle. TN San Anton!o TX Phoenix AZ I ndianapolis IN Milwaukee, 1M San f tllnelsco -Oakfand CA Rochester, NY Miami-Hialeah, FL Boston, MA seattle. WA. Richmond, VA New Yotk, NY -Nol1heasle rn New Je rsey 011ando, FL Kansu City, Mo-KS Ha rtford-Middletown CT Denver, CO San Diego, CA Riverside-San Bernardino, CA Omaha, NE-IA Noc'folk-Virginia Beach-Newport News VA Chicago, IL-North westem Indian a El P aso, 1X-NM M inneapolis-St. PaUl MN Atlanta, GA los Angell$, CA Sallak UT Dalla$-FortWorth TX Honolulu, HI H ouston, TX SanJose,CA Wathlnglon, OC-MO.VA Austin, TX 12.0C% 11.SH6 1 10 .42% 2 10.19% 3 10.08% 4 10.07% 5 9.94% 6 9.91% 7 9.88% 6 9.63% 9 9.61% 10 9.79% 11 9.79% 12 9.701!4 t3 9.59% 14 9.56% 15 9.30% 16 9.29% 1 7 9.13% 18 9 .11% 1 9 9.07% 20 9 03% 21 8.95% 22 8 94% 23 8.87% 24 8.54% 25 26 8 53% 27 8 .44,. 28 8 43% 29 8.40% 30 8 32% 31 8.30% 32 8.12% 33 8.06% 34 8.04% 35 8 00% 36 7.98% 37 7.95% 38 7 68% 3 9 40 7.8CJ 42 7 .Tl"Ao 43 7 75% 44 7.72% 45 7 .5$% 46 7 50% 47 7.54% 46 7.46% 49 7.10% 50 7 .03% 5 1 6.98% 52 8.84% 53 6 70% 54 6.27')(, 55 6 25% 56 6.23% 57 6 21% 5S 5.98% 59

PAGE 100

Table 20 CarpooiNanpool to Work, Percent of Workers Age 16+ Honolulu, H I 20.35% 1 Rl\larslde-San Betnardlno. CA 17.48% 2 EJPaso, 16.96% 3 Mlatri-HiaJeah, FL 15.56% 4 washington, OC-MO-VA 15.37% 5 t..nVegn,NV 15,34% 6 LOS A.lt$, CA 15.05% 7 New Orleans, LA 14.80% 8 Tucson, AZ 14.80% 9 San Antonio. TX 14.74% 10 Boltlmort, MD 14.54% 11 Houston.TX 14.33% 12 Phoenix, AZ 14.21% 13 Norfolk-Virgtnla Btac:h-Newport Ntw$, VA 13.93% 14 Jaek$0nville, FL 13. 93% 15 Sacramento. CA 13 87% 16 san Ole!jO, CA 13.81% 17 S.k Lake Clly, UT 13.57% 18 Oalas-Fort VVOrth, TX 13.56% 19 Memphi&, 13.44% 20 UNITED STATES 13.36% Austin, TX 1 3 .07% 21 Pittsburgh. PA 12. 90% 22 San Fra ncisco-Oakland, CA 12.88% 23 Nashvi l le. TN 12.88% 24 P ttert:bur9-Cit1rwater, Fl 12.87% 25 Fort Laude rdale-Hol!ywood-Pompano B each, FL 12.83% 26 Indianapol is I N 12.77% 27 Orlando. FL 12.78% 28 Richmond VA 1 2 .88% 29 Birmingham. AL 12.65% 30 Oldahoma Ci1y, OK 12.57% 31 Denver CO 1 2 .50% 32 Al:lany-Sc:heneetadyTroy, NY 33 We$1 Pam Be a ch-Boca Raton-Del ray Beach, FL 12. 45% 34 louisville, KY-I N 12.32% 35 ProvldtneePawtucJ<:tt. RI-MA 12.29% 36 San Jose. CA 12.22% 37 Portland-Vancouver OR WA 12.05% 38 Kansas City, MO-KS 12.02% 39 Chicago, IL-Northwestem Indiana 12.01% 40 P hiladelphia PA-NJ 12.01% 41 Hartford-Middletown, CT 11 .98% 42 Omahe, NE-IA 11 .92% 43 Atlanta, GA 11 .82% .. Sprlngllold, MA-CT 11 .88% 45 Seattle WA 1 1.45 % 46 Buffalo-Niagara Fab, NY 1 1.42% 47 ClncO>nsU, OH-KY 11 .37% 46 St Loul$, Mo-I L 11 .37% 49 Columbus, OH 1 1 .22% 50 Milwaukee, W 11 .02% 51 Rochester NY 10 85% 52 Minneapolis-St Paul, M N 10. 62% 53 Cleveland, OH 10. 43% 54 New York. NY-Northea.stem New Jef'Wy 10 22% 55 Oe
PAGE 101

Table 21 Use Transit for Work Trip, Percent of Workers Age 16+ NewYOI1c, NY-NMheastem N ew J ersey 29 .48% 1 C h icago I L-NorthwHttm Indiana 2 Vlta&Nngton, DC-MD-VA 3 Booton,MA 14.69'Ao. 4 San CA 14.03% 5 Phi l ade l phia PANJ 13.2Mb 6 HonoiUkl, HI 7 Pitsburgh PA 10.09'Ao & 8att:Wnore. MD 9 .43% 9 New Orleans, lA 8 .51% 10 Seanle .WA 8.09'Ao 1 1 OH 6 7 1'lb 12 Portllnd-Vaneower OR-WA 6 .52'lb 13 Al>any-Sd>e nedady-Troy. NY 6 43'l; 1 4 M ilwauk e e Vv1 I S M inneapolis-St. Pau l M N 6.1 1 % 16 Hartford-Midd l e&owo, CT 17 Miami-HII ... h. Fl 18 Allanto,GA 5 .92'11> 19 ButraJo-Niagara F a lls NY 5.87'lb 20 Los Angeles, CA S .SO'lb 21 UNnal STATES 5.17% Cincin nati OH-KV 4 .9G% 22 Roehuter, NY 4 .60% 23 Richmond VA 4.76 % 24 Oenver, CO 4.58% 25 H o u ston, TX 4 48% 26 AU$tin. 1X 4 .35% 27 S a n A nt o ni o, TX 4.19% 26 loui&v. K'f-IN 3 .92% 29 Col umbuS OH 3 .66% 30 St. louis, MO-l l 3 56% 3 1 S a n Diego CA 3 44% 32 Tucson,AZ 3 40% 33 Sal Lake City, UT 3 39% 34 Mem pl\ls, TN-AR-MS 3 34% 35 Providence-Pawt u c k et R I-MA 3 10% 36 San Jose, CA 3 04% 37 El Paso, TX-NM 2.88% 36 Dayton, OH 2 83% 39 Oetroil. M l 2 .81% 40 Oallas-FortWorth, TX 2 78% 41 Sacra mento CA 2 .76% 42 Indianapo l is, IN 2.75% 43 NashVill e TN 2 .56'lb 44 Kansas City, MO-KS 2.49% 45 Springl\eld, MA-CT 2.49% 46 Jacksonv ill e F L 2. 47'1\ 47 Omaha, NE-IA 2.30% 48 Norfolk-VIrginia Beach-Newport News VA 2.25% 4S Phoenix. 1\Z. 2.20% 50 F ort Laudef'dale-HolywoodPompan o Beach, F L 2 .08% 51 Las Vegn, NV 2 .04% 52 A k ron, OH 53 B irmingham, A L 1 67% 54 TampaSt. Pe t ersbufg-Ciearwate t FL 1.64% 55 Oolando, FL 1.54% 56 \Nett Pal m Beaen-8oea R a ton-Delray Bead'!, FL 0 .9&% S7 Riverside-S a n Bernardi no, CA 0 .94 % 56 ot
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Table22 Work ot Home Percent of Workers Age 16+ Norfolk-Vwglni:a Beach-Newport News, VA 5 44% I San Diego CA 4 .83% 2 San Francis 4 POJUand-Vancower OR-WA 3.31% s Oerwer, CO 3 .29% 6 SU\'Ue W/14. 3 .27% 7 SaHke City, UT 3.2()% 8 Tucson, A2. 3.07% 9 MinnHpolis-St. Pau l MN 3.01% 10 U N ITED STATES 2.911% P1loenlx, A2 2.84% II Austri,TX 2.75% 1 2 Sacramento, CA 2.75% 13 W..shingCon, OC-MO -VA 2.74% 1 4 lOS AngtMs. CA 2 .69% IS Jacksonvil le FL 2 .68% 16 W.sc Palm Sta ch-Boea Raton-Delray Beach, FL 2.63% 17 Omoho, NE-IA 2.55% 18 Konsas City MO-I(S 2 .52% 19 Boston, MA 2 45% 20 San Jos e CA 2 .43% 21 Nashville TN 2 .34% 22 Rivef'$ide-San Bernardin o CA 2 3()% 23 Oklal>oma City, OK 2 .27% 24 Atlanta, GA 2.25% 25 Ne.w Yor1<. NY-Northeastem New Jersey 2 .2S% 26 Tampa-st. Peteraburg-Ciearwaler, FL 2 2()% 27 O a las-Fort Wonh, TX 2.19% 28 St. Lolli&, M O--t l 2 .12% 29 El Paso, TX-NM 2 .12% 30 Phllodelpl>ia PA-NJ 2 10% 31 Richmond, VA 2 .09% 32 San Antonio. TX 2.07% 33 I ndianapolis I N 2.06'16 34 COlumbus, OH 2.06% 3S Clnc:innati. OH-KY 2 06% 36 Roehester, NY 2.03% 37 Milwaukee, WI 2.01% 38 Fl 2.00'16 39 Houston. TX 1.9910. 40 Chicago. IL-Northwettem Indiana 1 98% 41 Baltimore, MD 1.s3% 42 Orlando, F L 1 92% 43 Akron, OH 1 91% 44 Pittsburgh, PA 1 89% 45 Springftt l d MA-CT 1 .89% 46 Fort Beach, Fl 1.87% 47 Albany-sch enectadyTroy, NY 1 .85% 48 Dayton, OH 1 .84% 49 Cleveland, OH 1.81% 50 Hartford-Middletown. CT 1.73% Sl New Or l e ans, LA 1.68% 52 Loulwille KY -IN 1.64% 53 Buffalo-Niaga ra Fats NY 1 .58q{, 54 Providence-Pawtucket, RI-MA 1 .56% ss Detroit. M l 1.49'% 56 Slrmlngham AL 1.46% S7 las Vegas, NV 1.42% 58 lAO% S9 II

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Table23 Average Travel Time ta Work (minutes) New York NY -North eastem New Jel'lty 31.28 1 1/VashingiDn, DC-MD-VA 29 00 2 Chicago, I L -Notttwtoe stem I ndiana 28.54 3 RiVerside-San Bernardino, CA 28.40 4 San Francisco-Oa klan d C A 26. 49 5 Los Angeles. CA 26.20 6 Hooston 1X 25.85 7 Atlanta, GA 25.59 8 Bal1lmort, MD 25.43 9 P h iladelphia, PA-NJ 24.92 1 0 Miami-Hialeah. F L 24.n 11 Boston, MA 24 08 12 Seattte WA 23. 9 1 13 Honol\lu, H I 23.52 14 O a J ias-Fort Worth, TX 23.50 15 New Orte an$. LA 23.44 1 6 San Jose, CA 23.20 17 o.uon Ml 23.12 1 8 Phoen ix, AZ 22.94 19 F ort Lauderdale-Hol lywood-Pompano S6ach FL 22.86 20 Orlando Fl 22.66 2 1 P ittsburgh., PA 22.62 22 Sl Louis Mo-IL 22 48 23 UNITED STATES 22..40 C ltvl land, O H 22.35 2 4 Oenver, CO 22.18 25 Ja dcsonv il le, FL 21.97 26 san D i ego, CA 2 1.92 27 Sacramento, CA 21.62 28 Cincin nati OH-KY 21.59 29 San Anton io. TX 2 1. 5 1 30 Tampa-st. Petersburg Cftarwate r Fl 21.40 3 1 Nolfolk-Virginia Beach-Newport Newe. VA 2 1.37 32 Birmingham. AL 21.2 1 33 MemphiS. TN-ARMS 21.18 34 I n dianapo lis, I N 21.01 35 Na-shvill e TN 20.93 35 Portlal"'dVa neo uve r ORWA 20.90 37 R ich m ond, VA 20.88 38 KaMas City, MO-KS 20.69 39 . Tucson, AZ 20.62 40 West Pall!1 Beach-Boca Ralon-Oeltay 8each, Fl 20.60 41 Minn e apo lis-St. Pau l MN 20.44 42 l.oUI$VIIe, KY-IN 20.41 43 C o l um bu$ OH 20. 30 44 Las Vega s NV 20. 27 45 Salt Lak e City, U T 20 .05 46 E l P aso TX-N M 20. 01 47 Aust i n lX 1 9 .85 48 Milwaui< ... \M 1 9 .72 49 AkiWI, OH 19, 7 1 so Oklahoma City O K 1 9 .41 5 1 CT 1 9 .40 52 Dayton OH 1 9.22 53 Providence Pawtucket RI-MA t 9 12 54 Faits, NY 1 8 .90 55 Al:lany SchenectactyTroy NY 1 8 .79 58 Sp ri ngft e kt, MA-CT 1 8 .64 5 7 Rochest.r,NY 1 8.11 58 O ma h a NE-IA 17.61 59

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Table24 Drive Alone to Work, Percent of Workers Age 16+ Oetrolt Ml 83. t7% 1 Daykm,OH 2 Akron, OH 3 Birmingham. AL t 4 Oklahoma City, OK 81.14% 5 Ka nsas Ci1y, MO-l SO BaJtimote. MD 69.23% 51 Pitbburgh PA S Z PhUadtlphia, PA-NJ 65 .97% S3 80$10<1, MA 65 10% 54 Chicago, I L-Northweste m I n dia na 64.97% 55 San Fnu -.eisco-oakland. CA 62.75% 56 Wuhlngtoo, OC-MDVA 61.39% 57 Hono l ulu HI 57.11% 58 New Yo rk NY -Northea.sttm New Jei'My 50 .4S% 59

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Table25 Work Departura Time U a.m .. Perant of WCN1cers Age 16+ Birmingham, AL 59.01'11. I Houston. TX 55.55'11. 2 lndianapolio, I N 54.9'M!. 3 KaMaS City MO-KS 54.91'11. 4 San Antonio, TX 54.88'11. 5 TN 5464'11. 6 Omaha, N E-tA 54.38'11. 7 Denver, CO 54.3'M!. 8 Dallas-Fort \1\brth, TX 5423'11.. 9 Jaeksorwile, FL 54.00% 10 El Paso, TX-NM 53.92'11. II Memphia, TN-AR-MS 53.53'11. 12 53.50% 13 Sacramento. CA 52.91'11. 1 4 PM'InNpoli:s-St. Paul, MN 52.82'11. 1 5 R ichmond, VA 52.72'11. 16 Dayton, OH 52.85'11. 17 St. Louis, MO-IL 52.46% 18 Oltlahoma City, OK 52.08'11. 1 9 A!lam,GA 51.74'11. 20 Austin, TX 51.52'11. 21 Colt.mbus, OH 51.43'11. 22 PotUanct-Vaneouver. OR -WA 51.35% 23 Honolulu, H I 51.29'11. 24 Orlando, FL 51.23% 25 MilwaukM, W! 51.17'11. 26 Tampa-St. PetersbUrg-Cle arwater Fl 51.16% ZT New Ortnns,lA 51.03% 28 Cincinnati, OH-KY 50.80% 29 Provid.,.ce-Paw1ucktt, RI-MA 50.70% 30 UNITED STATES 50.55% Roehetter N V 50.48% 3 1 Baltimore, MD 50.35% 32 San Lake City UT 50.13% 33 San Diego, CA 49.82% 34 Chicago, IL-NOf1hwestem t ndiana 49.62'11. 35 Seattll WA 49 .59% 38 Pitt sburgh. PA 49 .57% 37 Phoenix, AZ 49.48% 38 Tucson AZ 49.47% 39 Cleveland, OH 49.39% 40 Wuhington, DC-MD-VA 49.35'11. 4 1 Nodolk-VIfginia Beach-Newport News, VA 49.13% 42 Akron, OH 48.97% 43 Phlladt lj:lhil. P A-NJ 48 .87% 44 S anJos.,CA 48 .50% 45 Springfiel d, MA-CT 48.08% 46 Louisville, KY -IN 48.06% 47 Miami-Hialeah, FL 47.93% 48 Fort Laueler di.Je-Hollywood-Pompeno Beaeh, F l 49 West Palm Beach-Boca R aton-Delray Beach. F l 47.89% 50 Los Angeles, CA 47.89% 51 Albany-SchenectadyTroy NY 47 .44% 52 Detroit, Mt 46.56% 53 San Francisco-Oakland CA 46.55% 54 Riverside-S a n Bernardino, CA 46.50% 55 Bostoo,MA 48.33'11. 56 8ult.lb-Niag1ra Fab, NY 45.65% 57 New Yonc. NY -Northeastern New Jersey 45.15% 58 L.asV0900,NV 41.62% 59

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Table26 Work Departure Time 6 9 a.m Perc8nt of Workers Age 16+ Riohmoncl. VA 73.18'11> 1 Hal1for 2 Birmingham, AL 72.20'11> 3 A l bany-Sche n ect ady-Troy, NY 71.42'11> 4 At l anta, GA 71.39% 5 Wasl"'ington, OC-MO-VA 71 .20% 6 Oalla$-FOrtWorth. TX 7 1,13"' 7 West Pa l m B e ach-Boca Raton-De l ray Bea ch F l 70 .98'11> 8 B0$1on, MA 70.89'11> 9 PNI&delphla. PA-NJ 70.80'11> 10 Houston, TX 70.59'11> 1 1 New Yotk, NY -NCW'ttltascem New Jersey 70 .48'11> 12 Kansas City, MO-KS 70 .35'11> 1 3 Providence PawtuCket. R I-MA 70.34'11> 1 4 Fort Lauderdal e -Hollywood-Pompano Beach, FL 70 .28'11> 1 5 J a c ksonville, FL 69.83'11> 1 6 i ndianapolis I N 69 .76'11> 17 Rochnte r NY 69 .52'11> 18 Tampe-S t Petersburg-CieafWaler FL 69 .37'11> 19 Naorn;ue TN 69 .25'11> 20 Miami-Hialeah F l 69. 19% 21 Austin, TX 69. 16% 22 Ot1ando. Fl 69. 17% 23 B altimore, MD 69.14'11> 24 New Of1eans,lA 68 .82'11> 25 Memphis, TN-AR-MS 68. 74% 26 Oklah oma Clly. OK 68 .69'11. 27 Denver. CO 68 .69'11> 28 San Antonto, TX 68 .68'11> 29 Columbus. OH 68 .54'11> 30 St. L o u is, MO-l l 68 .38'11> 31 Sacramento, CA 68 .09'11> 3 2 Cincinnat i OH-KY 68 .06'11> 33 M l n ntapolls-st. Paul M N 67 .99'11> 34 C leveland, O H 67 .88'11> 35 San Jose, CA 67.81'11> 36 Pittsburgh P A 6 7 80% 37 Dayton OH 67 75% 38 Oma ha, .NE-IA 67.52'11> 39 P ortland-Vancouver, OR-WA 67 04% 40 UNITED STA'reS 811.8& % Chic:::ago,IL-NOfttfwestem Indian a 68 68% 41 Sa Lak e C ity, UT 66.61 'II> 4 2 EJ Puo. lX-NM 88$3% 43 San Francisco-Oakfand, CA 66. 41% 44 Butfa5o-Niagara Falls, NY 65 2e% 45 Springfield, MA-CT 66 22% 46 Lou isville. KY I N 65 43% 47 Ml,....., k ee WI 64 99% 48 SeattSe, WA 64 76% 49 AJtton, OH 84.73 % 50 los A ngtlt$, CA 64 62% 5 1 Detroit, Ml 84. 55% 52 San D iego CA 64 .50 % 53 Tucson, AZ 64 30% 54 Norfolk-Virginia News, VA 63 39% 55 Phoenix. AZ. 82.86'11> 56 Honolulu, H I 61.71'11> 57 RNerside-Sa n Bernardino, CA 56.06'11> 58 Las Vegas, NV 54.85'11> 59 II

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Tobie 27 Work Outside Home County or State Percent of Workers Age 16+ Woshinglon OC-"'D-VA 49.96'lb 1 Denver, CO 2 Rk:hmond, VA 47.85'100 3 Allanlo GA 47 4 B.altimor t MD 44 .41% S NOffolk -Virginia Beach-Newport NeW$, VA 42.89% 6 New Vorl<, NY-Northeastem New Jerwy 42.71% 7 St. loui&, MO-IL 38 67% 8 Soston,MA 36 .3116 9 Pl\ll a delphlo, PA-NJ 35.54'16 10 KaMas C ity, MO-KS 34.87% 11 San F rancisco-Oaldand. CA 33 86% 12 Provkt enee-Pawtueke1, Rl-MA 33.45% 13 A l bany-$ehtntetady-Trcy, NY 33 .06'4 1 4 Riverside-San Bernardino. CA 32.94'4 15 Minneapolis-St. Paul. MN 3 2 88% 16 Portland-Vaneouver OR-WA 32 01% 1 7 New Orleans. LA 31.7196 18 Detroit, M l 29 ,4,'t 19 CJnclnnall, OH-KY 28.11% 20 UNill!D STATES 23.88% O rlandO, Fl 23 28% 21 MiwaUkH, WI Akron, OH City. OK Fort Lauderdale-Hollywo od-Pompano Beach, FL Daylon, OH Oma ha NE-IA Dallas-fort Wort h TX Chicago I L Nort hwestem I n diana Sptlng11eld, MA-CT I ndianapolis IN Hartford-M iddletown, CT SaerarMnto CA NaShVill e TN C l eve land, OH t.ou iavilte, KY-I N PittSbl.l'gh, PA Se.anle, WA A\. Jadnol'*'. HI 22.54% 2 1.51% 20,26% 1 9 53% 1 9.39% 1 8.93% 18.52% 17.42% 17 16% 16 .22'16 15.99% 15 .58'16 15 .43'16 15.25'16 13.9696 13.64'16 13. 48% 12.37% 11. 93% 11.74'4 11.11'4 10.92% 1 0.30% 10.10% 10. 06% 9.48% 7 9 1 % 7 .64% 6 37% 4 89% 4.48% 3.57% 3.30% 3 .013% 2 7 114 236% 2.24% 0.96'!6 22 23 24 25 26 27 28 29 30 31 32 33 34 35 36 37 38 39 40 4 1 42 43 44 45 46 47 48 49 50 51 52 53 54 S5 58 57 58 58

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Table28 o-Vehlde Households Percent of Total Households New Yofic, NY -No rtheastem N ew Jers e y 33. 27% I Phiodolphlo, PA-NJ 20.2A'if> 2 Nwtw Ofttans, LA 20.08'1!. 3 ll .. lmoufgh.PA 18.37% 7 Boston, MA 17. 57% 8 Miami-Hialeah. FL 16. 11'1!. 9 'M 15 .-r'lf. 10 Alblny-schentady-Troy. NY 15.08'1!. 11 CJeveland, OH 14.98'1!. 1 2 CT 14,71q(. 1 3 Memphis, 1 4 Spri ngfi eld, MA-cT 1 4 .08'1!. 15 RochHte-r, N Y 13. 94% 1 6 C l""'natl, OH-KY 1 3 .90'1!. 17 Oetroil, Ml 13.81'1!. 18 San Francisco-Oakland CA 1 3 60% 19 louisville, KY-IN 20 washington DC-MO-VA 12.99'1!. 21 Honolulu, H I 12.73'1!. 22 Rictvnond. VA 1 2 .20'1!. 23 St L olli$ MO-tl 11.98'1!. 24 Pfovldtnee-Pawtl.ld
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Table29 Number of Private Vehicles per Household SanJoso.CA 1.98 1 Sal lake City UT 1.87 2 Rivef'lilte-san Bernard ino, CA 1 .86 3 S eattle, WA 1 .79 4 San Die go, CA 1.75 5 Los Angeles, CA 1 ,74 6 Atlanta. GA 1 .74 7 D e nve r CO 1 .74 8 S &Ctamtnto CA 1 .73 g Dallao-FortVIAlrltl, TX 1.71 10 Oldah oma ely, OK 1.71 11 Orlando. FL 1 .70 12 M i nneapolis-St. Paul MN 1 .69 13 Omaha, NE-IA 1.89 14 Portland-Vancouver O R -WA 1.68 15 Akton, OH 1 .68 16 Kanoos Cily, MO-KS 1.87 17 B i nn i r9tam. Al 1.87 1 8 Daytx>n, OH 1.87 19 UNITal STATES 1.67 Norfolk-Virginia BeachNewport N ews, VA 1.87 20 Nash v ilr., T N 1 ,68 21 El P aso, lX-NM 1.65 22 P hoenix AZ. 1.65 23 San Franci&co-Oakland, CA 1.63 2 4 Richmond, VA 1 .63 25 las Vegas.., NV 1.63 28 COI!Inbu s OH 1 .62 2:1 Providence-Pawtucket. RI4M 1 .62 26 Houston lX 1.62 29 Indianapolis. I N 1 61 30 Jacksonville FL 1 61 3 1 Wasrnnglon, OC -MC-VA 1.61 32 Oelroii M I 1 .61 33 SL Louil. Mo-tl 1.61 34 Cinci nn ati OH-KY 1.60 35 Honolulu, HI 1 .60 36 san Anton i o, TX 1.59 37 Tueson,AZ. 1 .56 36 Loul$viDe, KY I N 1.56 39 Aust in. lX 1 .56 40 Hart!ORI-M,_, CT 1.55 41 Rochester, NY. 1.54 42 \Nest Pal m Beach-Boca Raton-Delray Beach, FL 1 .53 43 C l eveland. OH 1 .53 44 Memphis, TN-AR-MS 1.53 4S Spri n g1ield MAC T 1 .53 M ilwauk ee, Vv1 1 .51 47 Petersburg-Cieatwate r Fl 1.50 48 Fort Lauderdale-Hollywood-Po m pan o S.aeh Fl 1 .49 49 Fl 1.49 50 Albony..Schenedlldy-Troy, NY 1.47 51 S.ltimore. MD 1 .45 52 Boston, MA 1.44 53 Chicago, I L-Northwestem I nd iana 1.42 54 Phifadetphi a. PA-NJ 1.36 55 Buffalo-Niagara Falls NY 1 .36 56 Plllsburgh PA 1.36 5T New O Mans, LA 1.34 56 NY -Northe.estem New Jersey 1.16 59

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Table30 Number of Workers per Household Honolulu, Hl 1.61 1 San Jose. CA 1.53 2 Wlshil1g1on, DC-MD-VA 1.50 3 Lo$AI1gtM, CA 1.42 4 Norfolk-Virginia Beach-Newport N ews, VA 1.42 5 Atlanta, GA 1.39 6 O rtando,Fl 1.39 7 Minneapolis-St. PauJ, MN 1.39 6 San Ottgo CA 1.38 9 Sal Lake City, UT 1.38 10 Boston, MA 1 .36 11 Dalles-Fort V'IA:Irth. TX 1.36 12 Omaha NE-IA 1.34 1 3 Houston TX 1.33 14 San Franeisco-0akland, CA 1.32 15 RN'ei'SicSe-San Bernardino. CA 1.32 16 Baltimore. MD 1. 31 17 Seattle, WA 1.31 1 6 Jacksonville. F L 1.31 19 Aust i n 1X 1 3 1 20 Richmond, VA 1.30 2 1 Chicago IL Nort h westem Indiana 1.30 22 Las V&gas, NV 1.30 23 tulrtford-Midc.tletown CT 1.29 24 Oerwer, CO 1 .29 25 Nastwillt, TN 1.29 26 Columbus OH 1 .:1.8 27 Miami-HiaiMh, Fl 1 .:1.8 26 NewYotk, NY-Notthea stem New Jersey 1 .:1.8 29 E1 Paso TX-NM 1.27 30 Kansas City, MD-KS 1.27 31 Indianapolis I N 1.27 32 San Antonio. TX 1 .:1.8 33 Pnilaclelph ia, PA-NJ 1 .:1.8 34 Sp
PAGE 111

NoTES U S. Tel e c ommuting Po p u l ation Estima t ed a t 7.6 milion, The Urban Transporlation Monitor, (Ju l y 9, 1993), p 3. '"U S. Tel ecommuting Statistics The Urban Transporlation Monitor (September 18, 1 9 9 2), p. 9. 'APTA 2000, as summarized in Michael D. Meye r, "Publ i c T r ansportation i n the 21st Century; Pubfic Tran s porta edtted by Geo rge E G ray and lester A. Ho el (Englewood C i ffs N ew J ersey: Prentice-Hall Inc. 1 992) pp. 637, 638. 'MSHTO, A Study on Future Directions of Public T r ansportetion In the United Stales as summarized in Meyer pp. 639 640 . 'MSHTO. Transportation 2020 as summari zed in M e yer, pp. 64G-642 'Denni s G Perk i nson "I nfras t ructure Versus Serv i ce : A Trans i t Strategy for the ITE Journal (September 1 992), pp. 1 9 -21. IMIIiam G. Bar ker, "A T r ansit Management Strategy for the 1990's Transportation Quarterly (Eno T r ansportation Fou ndation October 1992), pp. 529-5 4 0. 'Manuel P adron Impacts of Changing Demographics on Transit Pla n ning," (Manue l Padron & Associates) 'Meyer, p. 645 Barker pp. 536 537 Center tor Urban Transportation Research (CUTR), Demographic and Commuting Trends in Florida (February 1 994) p 22. "Eri k Ferguson "An Exegesis of Recent Nationw i de Dec l i nes in Carpool i ng." "Journey-to-work questions wer e n ot included i n the 1 987 A H S survey "Ferguso n p 5 C UTR p 5 Ferguson, Table 1 CUTR p 1 5 'Ferguson p. 27. ''Ibid .. pp. 27, 28. "'Ibid .. p 30. Dav i d T H artgen and Kev i n Bulla r d "Wha t s Happened to Carpooling: 1 980 -1990 Trends in North Ca r ol in a ," (J uly 1992) p. 11 "Beverly Ward, "Telecommuting: Why Not? Tampa Bay News & Views (Spring 1993): p 1. Da n ie l B Rathbone, "Tel ecommuting In the United States ITE Journal (December 1 992) p 40. ''" U S Te l ecommuting Popu l ation Estimated at 7 6 mi ll ion," The Urban Transportation Monitor(July 9 1993) : p 3 ; and U.S Te l ecommuting Statisti c s ," The Urban Transportat ion Monitor (September 18, 1992) p. 9. 2!Coms i s Corporation, Implementing Effective Trave l Demand Management Measures report prepared for In stit ute of T ransportation Engineers (June 1 993), p. 2.

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"Cali fornia Department of Transportation, Telecommuting: A Guide for Executives ; and California Department of Transportation, Telecommuting: A Handbook to Help You Set up a Program et Your Company; and Telecommuting: Getting to Worlc Without Worlcing to Get There, Minnesota DOT Telecommuting Marketing Brochure. "U.S. Department of Transportation, Transportation Implications of Telecommuting (Washington: Government Printing Office 1993) "Ibid., p. 8 "Ibid., p. 21. "Ibid., p. 70. "Ibid., pp. 89-93. ""New National Telecommuting Study Complete The Urban Transportation Monitor (January 21, 1994) p. 6. "Center for Urban Transportation Research (CUTR) and Florida Department of Transportation Florida's Com muter Assistance Program: Program Director's Manual (Tampa : 1992) p. 11-21. "Ryuich i Kitamura, Patricia L. Mokhtarian, Ram M. Pendyala and Konstadinos G. Goulias "An Evaluation of Telecommuting as a Trip Reduction Measure," University of California Transportation Center Worlting Paper No 5 (Un i versity of California at Berkeley: 1991). "Srikanlh Sampath Somltra Saxena and Patricia L. Mokhtarian "The Effectiveness of Telecommuting as a Transportation Control Measure." University of California Transportation Center Working Paper No. 78 (University of Ca l ifornia at Berkeley : 1991).' "Patricia L Mokhtarian, An Empirical Analysis of the Tra nsportation Impa cts of Telecommuting Un i versity of Californ i a Transportation Center, UCTC No.131 (University ofCa6fomia at Berkeley: 1991). ""Study Shows Telecommuting Can Save $23 Bill io n." The Urban Transportation Monitor (June 21, 1991), p. 3. "Comsis Corporation, "Fina l Report Te le commuting," report prepared for (December 1 992) p. 4. "Denver Hosts Successful Telecommuting SerTinars," The Urban Transportation Monitor (August 5, 1994), p 3 "''Federa l Te le commuting Project Proves Successful The Urban Transportation Monilor(March 1 9 1993), p 3 "Ed Weiner, Office of the Assistant Secretary lor Pol i cy, phone interview (October 21, 1994). " Cl i nton Directive Will Significantly Increase Telecommuting ," The Urban Transportation Monitor (Augus t 5, 1994), p 3. ''Rathbone, p. 44. "U.S Dep artm ent of Transportation Transportation Implications of Telecommuting p 29. "Ibid, p. 54. ""Telecommuting to Grow Significantly in the N ext Decade ." The Urban Transportation Monitor (April 30, 1993), p. 2. "Patricia L. Mokhtarian, "Te lecommuting i n the United States: Letting Our Fingers Do the Commuting," TR News 158 (January-February 1992), p. 3 "Center for EconorTic and Management Resea rch (CEMR) and CUTR. Trends and Forecast of Florida s Trans portation Needs (Tampa: October 1993) p. 33

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"U.S. Department of Transportation, Transportation Implications of Telecommuting (1993), p. 30; and Mokhtarian "Telecommuting in the United States : Letting Our Fingers Do the Commuting . "Caltrans, Telecommuting: A Guide for Executives, p. 6 ' CEMR and CUTR, pp. 34 35. ""U.S. Telecommuting Population Estimated at 7.6 MiQion, The Urban Transportation Monitor (July 9, 1993) p 3. "U. S Department of Transportation, Transportation Implications of T&lecommuting pp. 89-93 "The Arlington Institute. The Road to 2012: Looking Toward the Next Two "Decades, prepared for the U .S. Coast Guard's Strategic Planning Staff (March 1993), p 265 Ib id., pp. 253-254 "Telecommuting: Getting to Work IMthout Working to Get There Minnesota DOT Telecommuting Marketing Brochure p 11. "Ibid. "Patricia L Mokhtarian, ''The State of Te lec ommuting," ITS Review 13 (August 1990) p 4 ""Impact of Telecommunications Techno l ogy," resource paper in TDM Innovation and Research: Setting a Strategic Agenda for the Future (Washington : Transportation Research Board. November 1993): p. 7 .. Ibid .. p. 7 JALA Associates Inc The California Telecommuting Pilot Project Final Report Executive Summary prepared for the Department of General Services State of California, June 1990, p 3 ; and U .S. Department of Trans porta tion, Transportation Implications of Telecommuting p x ..... ----------------------.....

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REFERENCES Arlington Institute, The Road to 2012: Looking Toward the Next Two Decades. prepared for the U.S. Coast Guard's Strategic Planning Staff (March 1993). Barker William G ., "A Management Strategy for the 1990 s," Transportation Quarterly (Eno Transportation Foundation. October 1992), pp. 529-540. California Department of Transportation Telecommuting: A Guide for Executives. California Department of Transportation, Telecommuting: A Handbook to Help You Set up a Program at Your Company Center for Economic and Management Research and Center for Urban Transportation Research, Trends and Forecast of Florida's Transportaffon Needs (Tampa: October 1993) Center for Urban Transportation Research (CUTR) Demographic and Commuting Trends in Floricla (February 1994). CUTR and Florida Department of. Transportation, Florida's Commuter Assistance Program: Program Director's Manual (Tampa: 1992). CUTR, "Making TOM Work in Your Community" (National Urban Transit Institute, December 1994) Comsis Corporation, "Final Report Telecommuting," report prepared for Caltrans (December 1992). Comsis. Implementing Effective Travel Demand Management Measures, A Series on TOM (Institute of Transpor tation Engineers, June 1993) Ferguson. Erik An Exegesis of Recent Nationwide Declines in Carpooling." Hartgen Dav i d T and Kevin Bullard "Whafs Happened to Carpooling: 1980-1990 Trends in North Carolina," (July 1992). JALA Associates Inc., The California Telecommuting Pilot Project Final Report Executive Summary, prepared for the Department of General Services, State of California (June 1990). Kitamura Ryuichi Patricia L Mokhtarian Ram M. Pendyala and Konstadinos G Goutias, "An Evaluation of Telecommuting as a Trip Reduction Measure," University of Ca5fomia Transportation Center Working Paper No 5 (University of California at Berkeley: 1991). Meyer. Michael D., Public Transportation in the 21st Century," Public Transportation, by George E. Gray and Lester A. Hoel, (Englewood Cliffs, New Jersey : Prentice-Hall Inc., 1992), pp. 636-653 Minnesota Department of Transportation, Getting to Work Wthout Working to Get There, Minne sota DOT Telecommuting Marketing Brochure Mokhtarian, Patricia L .. "An Empirical Analysis of the Transportation Impacts of Telecommuting," University of California Transportation Center UCTC No 131 (University o!Cafifomia at Berkeley: 1991). Mokhtarian Patricia L. "The State of Telecomrrwting ," ITS Review 13 (August 1990) Mokhtarian Patricia L .. "Telecommuting in the United States: Letting Our Fingers Do the Commuting," TR News 158 (January-February 1992). Padron Manuel, Impacts of Changing Demographics on Transit Planning ," (Manuel Padron & Associates). Perkinson, Dennis G. Infrastructure Versus Service: A Transit Strategy for the 90s," ITE Journal (September 1992), pp. 19-21

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Rathbone Daniel B "Telecommuting in the United States ITE Jouma/62 (December 1992). Sampath. Srikanth Somitra Saxena and Patricia L. Mokhtarian The Effectiveness of Telecommuting as a Transportation Control Measure; University of Catifomia Transportation Center. Working Paper No. 78 (University of Catiforn i a at Berl