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Taxi Demand Modeling to ensure appropriate taxi supply

Taxi Demand Modeling to ensure appropriate taxi supply. James M Cooper, Transport Research Institute, Edinburgh Napier University. Wither Taxicab?. Recognizable and understood mode. Single, dual and multiple licensing types.

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Taxi Demand Modeling to ensure appropriate taxi supply

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  1. Taxi Demand Modeling to ensure appropriate taxi supply James M Cooper, Transport Research Institute, Edinburgh Napier University

  2. Wither Taxicab? • Recognizable and understood mode. • Single, dual and multiple licensing types. • Supply impacted by licensed restricted and free entry markets in similar measure • Demand analysis models and their application

  3. What are taxi controls? • Quality, Quantity and Economic Regulation (QQE) • Deregulatory Movement • Taxi Reform • A central government view

  4. Unpacking the Taxi Model • Model? • Analysis by area of regulation • Aggregation, temporal and spatial difference • Legislated Tick Boxes?

  5. So what does the model do, really? • Applied in the UK to restricted markets • Seeks to identify where such restriction is “harmful” • Demonstrates an index of the level of harm • By extension, identifies the increase in licenses required to mitigate the level of harm • BUT: based on observed delay in one primary market

  6. How does this work? Definition of an Index of SUD (ISUD) ISUD= APD x ED x Pl x HP Where: APD Average passenger delay across all time periods ED Excess Demand, during the Monday to Friday daytime period PI The proportion of taxi users travelling in hours where the overall average delay at the stance was greater than or equal to 1 minute HP Adjustment factor where peaking is present (1 if no peaking; 0.5 with peaked demand)

  7. Comparative Results

  8. Best Practice • Department for Transport 2006 • Scottish Government 2007

  9. How has best practice helped? • YES!

  10. How has best practice helped? • YES! • Expanded beyond rank observation • Introduced “temporal” assessment based on peaks in demand • Suggested (but not imposed) seasonality

  11. Has best practice covered all bases? • NO!

  12. Has best practice covered all bases? • NO! • Impact of a licensing based solution • One solution need not fit all • Perverse and negative effects • Non-licensing solutions

  13. Some Driver Perceptions

  14. Night Time Reservations

  15. Achieving time savings

  16. Passenger Delay

  17. Non Licensing Solutions

  18. Other Issues at play

  19. Traffic Signal Delay

  20. Translated in to time saving Time saving in arrivals at stance is calculated on the basis of: TSAS = (CAD x EOT) / (EOT + IGP) Where TSAS = Time Saving at Stance CAD = Current arrival delay, departing from Hope Street to arrival at Gordon Street EGT = Effective Green Time IGP = Increase applied to Green Phase

  21. Impact of time saving

  22. Passenger Delay, at Gordon Street

  23. A quick reminder of principle • Duties • Responsibilities • VITALLY IMPORTANT:THIS NOT A DEFENSE OF A RESTRICTIVE MARKET • Impacts • Utopia gained?

  24. Final Critique • Does the use of “new” demand models provide the most appropriate method of determining market control? • Why are we ignoring infrastructure, price impact or quality controls?

  25. So what next? • Optimality • Licensinse and infrastructre are both appropriate • Modeled approach not the antithesis of the free market, but its facilitator

  26. Optimal Information as the guardian of optimal services • Restricted markets must not be closed shops • Deresricted markets must not leave everything to the market • Supply issues remain in derestricted market where infrastructure not appropriate or optimal • Actual form of regulation does not replace the need to uderstand, test and respond to the market

  27. Contact: James Cooper TRI Taxi Studies Group j.cooper@napier.ac.uk www.tri-napier.org www.taxiresearch.net

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