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TCRP Report 134: Transit, Call Centers, and 511: A Guide for Decision Makers (2009)
Transit Cooperative Research Program (TCRP)

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Transportation Research Board. "3.4 Transit Agency Case Studies." TCRP Report 134: Transit, Call Centers, and 511: A Guide for Decision Makers. Washington, DC: The National Academies Press, 2009.

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Page
35
Front Matter (R1-R11)
Summary (1-7)
1.1 Background (8-8)
1.3 Research Tasks (9-9)
2.2 National Inventory of Operational 511 Systems (10-10)
2.3 Transit Agency Case Studies (11-12)
2.4 Non-Transit Call Center Interviews (13-13)
2.6 Transit Rider Focus Group (14-16)
3.1.1.1 Customer Information Needs and Preferences (17-17)
3.1.1.2 Information Provided by Transit Agencies (18-18)
3.1.1.3 Dissemination Methods/Technologies Utilized (19-19)
3.1.1.4 Matching Dissemination Methods/Technologies with Customer Needs and Preferences (20-21)
3.1.2.3 Technologies (22-24)
3.1.2.4 Metrics (25-25)
3.1.3 Implications of Agency Size and Type (26-27)
3.2.2 Implications for Transit Agencies (28-28)
3.3.2.1 Operational 511 Systems (29-29)
3.3.2.2 Transit Agency Participation in 511 Systems (30-31)
3.3.3.1 Customer Information and Call Center Approaches (32-32)
3.3.3.2 Participation in Non-511 Traveler Information Systems (33-33)
3.3.4 Transit-Related 511 Operating Statistics (34-34)
3.4 Transit Agency Case Studies (35-35)
3.4.1.1 Arizona 511 (36-37)
3.4.1.2 El Dorado Transit (Sacramento California, Area) (38-38)
3.4.1.4 Central Florida Regional Transportation Authority (39-39)
3.4.1.5 Island Explorer (Bar Harbor, Maine) (40-40)
3.4.1.7 Charlotte Area Transit (North Carolina) (41-41)
3.4.1.8 San Diego 511 (42-44)
3.4.1.10 Washington Metropolitan Area Transportation Authority (45-45)
3.4.1.12 Southeast Florida 511 (46-51)
3.4.1.13 San Francisco Bay Area 511 (52-61)
3.4.2.1 Manchester Transit Authority (New Hampshire) (62-62)
3.4.2.3 King County Metro Transit (Seattle) (63-63)
3.4.3.2 Regional Transit District (Denver) (64-64)
3.4.3.4 Tri-Met (Portland) (65-65)
3.5.1 Rationale for Transit Content Decisions (66-66)
3.6 Transit Rider Focus Group (67-67)
3.6.2 Transit Information on 511 (68-69)
4.1.1.1 National Overview of 511 Systems and Transit Participation (70-70)
4.1.1.3 Transit Rationale for Participation/Non-Participation in 511 (71-71)
4.1.1.4 Impacts of 511 Participation on Transit Agencies (72-73)
4.1.2.1 Buy-In on 511 as a Multimodal Resource (74-74)
4.1.3.2 Transit Information on 511 (75-75)
4.1.4.1 The Role of the Telephone in Transit Customer Information (76-76)
4.2.1.1 General Recommendations on the Applicability of Basic and Additional Transit Information on 511 (77-77)
4.2.1.2 Basic Transit Information (78-78)
4.2.2.1 Consider Greater Utilization of Proven, Advanced Technologies and Techniques (79-80)
4.3 Plan for Implementing the Research Findings (81-82)
References (83-84)
Appendix A - Transit Agency Interview Questionnaire (85-87)
Appendix B - Transit Rider Focus Group Discussion Guide (88-89)
Abbreviations used without definitions in TRB publications (90-90)

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35 Table 13. Sample of available transit-related 511 statistics. 511 System/Transit Agency 511 Transit- Related 511 Deployment LYNX MTC Coalition Statistic (Central (San Francisco Arizona 511 (National Florida 511) 511)* 511 Virginia Statistics) 1%-2% of Transit-related 24% of all 511 menu all 511 9% of all calls/menu selections menu 511 calls selections selections 32,800 transfers per month to AC Transit 5.2% of all calls (1,650 0.4% of all Transit 6,600 transfers per call 511 calls transfers from month to Golden transfers < 1% (~350 transfers 511 Gate Transit per month per month) to Valley 6,100 transfers per Metro) month to Muni 15% for AC Transit Transit agencies' 511 80% for Muni menu requests 23% for Golden Gate that are for Transit something other than a 42% for Santa Clara transfer to a Valley transit operator 35% SamTrans * Statistics associated with individual transit agencies are available for all of the more than 20 transit agencies that participate in the San Francisco 511 system; only a few examples for 3 agencies are shown here. high percentage of transfers is probably related to the fact standing exactly what types of calls these are would increase the that that agency advertises 511 as their primary customer understanding of the impact of 511 on participating transit service number. Therefore, rather than getting just, or agencies. Case studies shown in Section 3.4 revealed that 511- mostly, callers interested in getting automated 511 infor- participating transit agencies did not detect any 511-related mation, they get the full spectrum of customer inquiries. change in their customer service call volumes, which may be In fact, because AC funnels all calls to 511, this statistic is evidence enough that most 511 transfers are probably "shifted" a good indicator of the overall percentage of their customer rather than "new" calls to transit. inquiries that can be handled without a live operator (15%). The analysis of sample transit-related 511 statistics indicates This would confirm the subjective perceptions of most that there is not enough data available to understand any other transit agency personnel that were interviewed, who feel impacts and effectiveness for transit. Further, the fact that prac- that most customer service calls to their agency will require tically none of the transit agencies interviewed were aware of, interaction with an operator. or provided access to, what limited statistics are available sug- gests that 511 operators have not reached out to their partici- What is not revealed in the sampling of available transit- pating transit agencies. This also may indicate that the transit related 511 statistics shown in Table 13 is whether the calls agencies have not asked the operators for such data. transferred from 511 to specific transit agencies are "new" calls to transit or "shifted" calls. The amount of transferred calls can be significant--on the order of tens of thousands per 3.4 Transit Agency Case Studies month for large transit agencies in large, transit-oriented 511 This section presents the 29 case studies of transit agencies systems like San Francisco. New calls would represent calls that were performed. Conclusions based on the case studies from people who would not otherwise have called the transit are presented in Chapter 4. agency directly (such as tourists) and these would represent a The case studies are organized into the following three major net increase in calls to the transit agency. Shifted calls would categories based upon the level of transit involvement in the be calls that would otherwise have gone to the transit agency 511 system: directly, but the caller decided to try 511 instead. An example of this type of caller would be a veteran transit user and caller 1. Transit agencies integrated with 511--These transit agen- to the transit agency who noticed a reference to 511 on some cies are all represented on the menu system of their respec- of the transit agency's materials and decided to try it. Under- tive 511 systems and 511 callers can automatically transfer