Farebox recovery ratio

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Lua error in package.lua at line 80: module 'strict' not found. The farebox recovery ratio (also called fare recovery ratio) of a passenger transportation system is the fraction of operating expenses which are met by the fares paid by passengers. It is computed by dividing the system's total fare revenue by its total operating expenses.

Fare structures

There are two schools of thought in fare collections: a simple, flat rate fare structure (pay a fixed fare regardless of time of day and/or travel distance) or a complex, variable rate fare structure (pay a variable fare depending on time of day and/or travel distance).

In North America, South America, and Africa, the majority of the cities use simple, flat rate fare structures due to budgetary constraints. With the majority of North America, most of South America, and almost all of Africa being heavily reliant on the automobile for both short and long distance travel, majority of the transit budgets are allocated toward construction and maintenance of freeways and roads, with very little funding making way to investments in new mass transit technologies. Inadvertently however, the reliance on simpler fare structures due to their cheaper costs ends up increasing the tax burden on the agencies as flat rate fare structures have lower farebox recovery ratios, placing more pressure to the transit agencies to increase taxes, pursue higher fare hikes, or to cut services to maintain the transit system.

In sharp contrast, majority of the cities in Europe and Asia are heavily dependent on mass transit. Therefore, the majority of their transit budgets are used extensively on mass transit technologies, which enables these countries to install and maintain self-supporting and profitable variable pricing structures. Transit agencies that have instituted a more variable fare structure depending on distances or zones traveled have higher farebox ratios over those that rely on a flat-rate model.[1] In addition, recent urban transit scholars agree that variable pricing methods on public transit would actually be a profitable business which can alleviate many municipal agencies' budget problems.[2] For example, transit riders will be discouraged to travel longer distance due to increasing price as one travels further, reducing human congestion of mass transit riders who ride lengthier trips. On the other hand, an increased number of riders will opt to frequently use the transit system for multiple short and quick hop-on and hop-off trips as prices would be cheaper for shorter trips, which mass transit is better suited for. The downside however is that institution of variable-rate fares requires a high value initial investment in fare ticketing technologies such as the use of contactless smart cards, turnstiles or fare gates, automated ticket machines, as well as the IT infrastructure in which the return on investment may take years depending on the expected transit ridership volumes.[3]

Variable vs. fixed fare models

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Agenda Variable fare model Fixed fare model
FBR ratio with high ridership figures 100%+ 50%+
FBR ratio with low ridership figures 60%+ 9%+
Most common system used Post-pay; fares are paid at the destination or upon disembarking at the end of each trip Pre-pay; fares are paid at the start of each trip
Unlimited ride passes Uncommon, but usually available for tourists Daily, weekly, or monthly unlimited ride passes
Incentives over cash Cheaper rates may be provided when using paperless contactless passes loaded with cash value Unlimited ride passes
Concessions Discounted variable rates for seniors, youths, disabled, or other groups as needed Discounted fixed rates for seniors, youths, disabled, or other groups as needed
Implementation costs Expensive, as both entry and exit points have to be accounted for to calculate variable fares. Fare-adjustment and change machines need to be installed. Cheap, as fare is collected at entry only. Since each rider is expected to have exact change, no fare-adjustment or change machines are needed.
Reliance on subsidies Less dependent, as each rider pays their share of distance traveled equally Heavily dependent, as fixed fares do not cover operational costs without regard to how each rider contributed to their distance traveled
Benefits Fairer fare structure; cheaper for shorter riders, more for longer rides. Entry and exit processes can also be used for data collection to efficiently manage how transit riders travel, allowing transit agencies to coordinate transfer times, reduce or increase transit needs based on hard ridership data. Simplicity; everyone pays the same price regardless of distance traveled.
Risks Confusing for first-time riders. Knowledge of the system requires an "acquired" skill Prone to higher rates and service cuts depending on subsidies received

Farebox ratios around the world

The following table lists farebox ratios for some public transportation systems around the world.

Ratio of fares to operating costs for public transport systems (%)
Continent Country System Ratio Fare system Fare rate Annual ridership Year
Asia Hong Kong Hong Kong (MTR) 186% Distance based HKD 3.50+ (cash)

HKD 3.50+ (Octopus card)

 1,553,000,000[4] 2012[5]
Asia Japan Osaka (Hankyu Railway) 123% Distance based JPY 150+ 1991[6]
Asia Japan Osaka (OMTB) 137% Distance based JPY 200+ 1991[6]
Asia Taiwan Taipei (MRT) 119% Distance based TWD 20+ (cash)

TWD 16+ (EasyCard)

 602,200,000[7] 2012[7]
Asia Japan Tokyo Metro 170% Distance based JPY 160+ 1991[6]
Asia Singapore Singapore (SMRT) 125% Distance based SGD 1.10+ (cash)

SGD 0.73+ (EZ-Link Card)

 2008[8]
Asia China Beijing Subway 59.5%[citation needed] Distance based CNY 3.00+ 2,460,000,000 2012[9]
Europe Netherlands Amsterdam 73.6% Distance based 2014[10]
Europe Germany Berlin 70.3% Zone based EUR 2.60+ 2010[11]
Europe Belgium Brussels 35.2% 2007[12]
Europe Denmark Copenhagen 52% 1991[13]
Europe UK London Underground 92% Zone based 1.265 billion (2013/14)[14][15] 2014[16]
Europe Spain Metropolitan lines of Ferrocarrils de la Generalitat de Catalunya (FGC) 93.18% Zone based 77,183,208 2014[17]
Europe Spain Madrid 41.3% 2007[12]
Europe Italy Milan 28% 1991[13]
Europe Germany Munich 42% Zone based 1991[13]
Europe Czech Republic Prague (DPP) 53.2% Flat rate CZK 24+ 1,232,000,000 2013[18]
Europe France Paris (STIF) 30.4% Zone based for passes
Distance based for tickets		 2013[19]
Europe Sweden Stockholm 37% Zone based SEK 44–88 (conductor)
SEK 25–50 (SL Access card)
Note: Tickets are not sold on buses.		 2007[12]
Europe Italy Rome 36% 2007[12]
Europe Austria Vienna 50% Flat rate EUR 2.00 1991[13]
Europe Finland Helsinki 49%[20] Zone based; each borough forms a zone. Boroughs with a small area are treated as being part of one of their neighbouring boroughs. EUR 2.80–7.00 (cash)
EUR 1.90–5.60 (travel card)
Transfer free of charge		 336,000,000[20] (boardings, one trip can include more than one boarding) 2011
Europe Switzerland Zurich 66% 1991[13]
North America USA Amtrak 71% Distance & demand based 2009[21]
North America USA Atlanta (MARTA) 31.8% Flat rate USD 2.50 2012[22]
North America USA Austin (CMTA) 12.4% Flat rate USD 1.00-2.75, depending on modality 2012[22]
North America Canada Brampton (BT) 46% Flat rate CAD 3.25 (cash)

CAD 2.65 (Presto Card)

 2012[23]
North America USA Boston (MBTA) 43.7% Flat rate USD 2.65 (cash) / USD 2.10 (CharlieCard) 2014[24]
North America Canada Calgary 50% Flat rate CAD 3.00 2011[25]
North America USA Chicago (CTA) 43.0% Flat rate USD 2.25 (cash)

USD 2.00 (ChicagoCard)

 2012[22]
North America USA Chicago (Metra) 55% Zone based USD 2.75+ 2012[26]
North America USA Cleveland (GCRTA) 21.5% Flat rate USD 2.25 2002[24]
North America USA Dallas (DART) 13.7% Flat rate USD 1.75 2012[22]
North America USA Detroit (DDOT) 13.9% Flat rate USD 1.50 2002[27]
North America Canada Edmonton (ETS) 39.4% Flat rate CAD 3.00 2007[28]
North America USA Harrisburg, PA (CAT) 35.0% Flat rate USD 1.75 2005
North America USA Las Vegas Monorail 56.0% Flat rate USD 5.00 2006[29]
North America USA Long Island (MTA) 50.0% Zone based USD 5.00+ 2012[22]
North America USA Los Angeles (LACMTA) 25.5% Flat rate USD 1.75, with discounts for seniors, disabled, students 2015[30]
North America USA Maryland 23.1% Variable USD 1.60-11, depending on distance & modality 2012[22]
North America USA Miami 24.1% 2012[22]
North America USA Minneapolis - St. Paul 31.4% Flat rate with rush hour and express surcharges USD 1.75 to USD 3.00 81,000,000 2008[31]
North America Canada Mississauga (MiWay) 46% Flat rate CAD 3.25 2011[25]
North America Canada Montreal (STM) 57.1% Flat rate CAD 3.00 2006[32]
North America USA New York City (MTA) 51.2% Flat rate USD 2.75 2015[33]
North America USA New York/Connecticut (MTA) 36.2% Distance based USD 2.25+ 2009 Q1[34]
North America USA New York/New Jersey (PATH) 41.0% Flat rate USD 2.75 2015[24]
North America USA New Jersey (NJT) 56% Distance based USD 2.25 2001[35]
North America USA Orlando (Lynx) 25.7% Flat rate USD 2.00 29,200,000 2012[36]
North America Canada Ottawa (OC Transpo) 52% Flat rate CAD 3.30 (Cash)

CAD 2.60 (Tickets/Presto Card)

 2011[37]
North America USA Philadelphia (SEPTA) 40.7% Flat rate USD 2.00 (cash) / USD 1.55 (Token) / USD 1.00 (Transfer) 2013[38]
North America USA Pierce County, WA 13.0% Flat rate USD 2.00 2009[39]
North America USA Philadelphia/New Jersey (PATCO) 66.2% Distance based USD 1.40+ 2012[40]
North America USA Portland Metro Area (TriMet) 22% Flat rate USD 2.50 2010[41]
2012[42]
North America USA Greater Seattle Area (King County Metro) 29.1% Zone and peak based USD 2.25+ 2013[43]
North America USA Puget Sound Region (Sound Transit) 22.2% Zone & distance based USD 1.50+ 2007[44]
North America Canada Quebec City (RTC) 39% Flat rate CAD 3.00 2011[25]
North America USA San Antonio (VIA) 12.8% Flat rate USD 1.20 46,700,000 2012[45]
North America USA San Diego MTS 40% Flat rate USD 2.50 34,500,000[46] 2012[47]
North America USA San Francisco Bay Area (BART) 68.2% Distance based USD 1.85+ 2012[48]
North America USA San Francisco Bay Area (Caltrain) 51.3% Zone based USD 2.75+ 2011[49]
North America USA Staten Island (MTA) 15.2% Flat rate USD 2.75 2015[24]
North America Canada Toronto (TTC) 73% Flat rate CAD 3.00 2013[50]
North America Canada Toronto, Hamilton and area (GO Transit) 78.2% Distance based CAD 4.68+ 2013[51]
North America Canada Vancouver (TransLink) 51.9% Zone based CAD 2.50+ 2010[52]
North America USA Washington, DC (WMATA) 62.1% Distance based USD 1.95+ 2010[53]
North America Canada Winnipeg 60% Flat rate CAD 2.50 2011[25]
Oceania New Zealand Auckland 44% Zone Based 69,000,000[54] 2012/13[55]
Oceania Australia Canberra 21% Flat rate AUD 4.20 2007[56]
Oceania Australia Sydney 20% Distance Based AUD 0.15 / km 281,000,000[57] 2014[58]
Oceania Australia Melbourne ~30% Zone and time based From 3.76 AUD / hour / zone 2014[59]
Oceania New Zealand Christchurch 35% Zone Based 13.500,000[54] 2012/13[55]
Oceania New Zealand Dunedin 54% Zone Based 2.900,000[54] 2012/13[55]
Oceania New Zealand Hamilton 34% Flat rate 5,000,000[54] 2012/13[55]
Oceania New Zealand Wellington 57% Zone Based 35,000,000[54] 2012/13[55]

References

  1. ↑ Teik-Soon Looi, Kim-Hong Tan , "Singapore’s case of institutional arrangement for fare affordability", 11th Conference on Competition and Ownership in Land Transport, 2009-08-27
  2. ↑ Allison Yoh, Brian D. Taylor, and John Gahbauer, "Does Transit Mean Business? Reconciling academic, organizational, and political perspectives on Reforming Transit Fare Policies", UCLA Luskin School of Public Affairs, Institute of Transportation Studies , June 2012
  3. ↑ Dr. Jean-Paul Rodrigue, "The Geography of Transport Systems, Third Edition, 2013
  4. ↑ Lua error in package.lua at line 80: module 'strict' not found.
  5. ↑ Lua error in package.lua at line 80: module 'strict' not found.
  6. ↑ 6.0 6.1 6.2 Dr. Kenichi Shoji, "Lessons from Japanese Experiences of Roles of Public and Private Sectors in Urban Transport", Japan Railway & Transport Review, December 2001
  7. ↑ 7.0 7.1 Lua error in package.lua at line 80: module 'strict' not found.
  8. ↑ Lua error in package.lua at line 80: module 'strict' not found.
  9. ↑ "杭州地铁拟定票价 “贵”为全国前三 市民喊吃不消" 钱江晚报 (in Chinese) 2012-07-20
  10. ↑ Lua error in package.lua at line 80: module 'strict' not found.
  11. ↑ Lua error in package.lua at line 80: module 'strict' not found.
  12. ↑ 12.0 12.1 12.2 12.3 Lua error in package.lua at line 80: module 'strict' not found.
  13. ↑ 13.0 13.1 13.2 13.3 13.4 Lua error in package.lua at line 80: module 'strict' not found.
  14. ↑ Lua error in package.lua at line 80: module 'strict' not found.
  15. ↑ Lua error in package.lua at line 80: module 'strict' not found.
  16. ↑ Lua error in package.lua at line 80: module 'strict' not found.
  17. ↑ Lua error in package.lua at line 80: module 'strict' not found.
  18. ↑ Lua error in package.lua at line 80: module 'strict' not found.
  19. ↑ Lua error in package.lua at line 80: module 'strict' not found.
  20. ↑ 20.0 20.1 Lua error in package.lua at line 80: module 'strict' not found.
  21. ↑ Lua error in package.lua at line 80: module 'strict' not found.
  22. ↑ 22.0 22.1 22.2 22.3 22.4 22.5 22.6 [1][dead link]
  23. ↑ Lua error in package.lua at line 80: module 'strict' not found.
  24. ↑ 24.0 24.1 24.2 24.3 Lua error in package.lua at line 80: module 'strict' not found.
  25. ↑ 25.0 25.1 25.2 25.3 [2][dead link]
  26. ↑ Lua error in package.lua at line 80: module 'strict' not found.
  27. ↑ [3][dead link]
  28. ↑ City of Edmonton
  29. ↑ Calculation based on figures of "$159,000 needed daily to cover operating costs and debt service" and "falling as much as $70,000 a day short". Lua error in package.lua at line 80: module 'strict' not found.
  30. ↑ Lua error in package.lua at line 80: module 'strict' not found.
  31. ↑ Lua error in package.lua at line 80: module 'strict' not found.
  32. ↑ [4][dead link]
  33. ↑ [5][dead link]
  34. ↑ Metro-North Railroad Financial Ratios (March 2009)
  35. ↑ CT Ridership Fare Revenue and Cost Database
  36. ↑ 2012 Annual report Lynx
  37. ↑ [6][dead link]
  38. ↑ Lua error in package.lua at line 80: module 'strict' not found.
  39. ↑ Lua error in package.lua at line 80: module 'strict' not found.
  40. ↑ [7][dead link]
  41. ↑ TriMet Funding Retrieved 2011-06-03
  42. ↑ TriMet Fare Charges Retrieved 2012-11-12
  43. ↑ [8][dead link]
  44. ↑ Q4 2007 Financial Report
  45. ↑ [9] Archived 8 September 2013 at the Wayback Machine
  46. ↑ Lua error in package.lua at line 80: module 'strict' not found.
  47. ↑ Metropolitan Transit System General Information
  48. ↑ Lua error in package.lua at line 80: module 'strict' not found.
  49. ↑ Lua error in package.lua at line 80: module 'strict' not found.
  50. ↑ TTC Annual Report, 2013
  51. ↑ Metrolinx Annual Report 2012-2013
  52. ↑ [10][dead link]
  53. ↑ [11][dead link]
  54. ↑ 54.0 54.1 54.2 54.3 54.4 Lua error in package.lua at line 80: module 'strict' not found.
  55. ↑ 55.0 55.1 55.2 55.3 55.4 Lua error in package.lua at line 80: module 'strict' not found.
  56. ↑ [12][dead link]
  57. ↑ [13]
  58. ↑ Lua error in package.lua at line 80: module 'strict' not found.
  59. ↑ [14][dead link]
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