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Presentation, AGIFORS 2000 24th March 2000 in New York. Pricing Simulation Natascha Jung, Senior Operation Research Specialist. Proven solutions for open skies. Agenda. Supported Pricing Processes. Pricing Simulation Modeling. Summary. Pricing Simulation in Reactive Pricing.

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slide1

Presentation, AGIFORS 200024th March 2000 in New York

Pricing Simulation

Natascha Jung, Senior Operation Research Specialist

Proven solutions for open skies

agenda
Agenda

Supported Pricing Processes

Pricing Simulation Modeling

Summary

slide3

Pricing Simulation in Reactive Pricing

Pricing Simulation

ManualMatching

AutoMatching

Trigger

Decision

Action

AutomatedDecision

Decision Support

Statistics

Competitor

Fare Action

No

No

Don’t know !

Yes

Yes

Automated Distribution

slide4

Pricing Simulation in Proactive Pricing

Pricing Simulation

Evaluate Scenario

Trigger Possible Actions Simulation/ Action Evaluation

Open Capacity

Special Event Pricing

What-If

Modeling

Automated Distribution

Yes

New Destination

...

agenda5
Agenda

Supported Pricing Processes

Pricing Simulation Modeling

Summary

what should a pricing simulation model do
What should a Pricing Simulation Model do?
  • Simulating the impact of
    • Amount Changes
    • Condition and Restriction changes
    • New or Canceled Fares
  • on
    • Market Share
    • Passenger Demand
    • Revenue
  • by considering
    • Cannibalization
    • Competitor Reaction
    • Market Stimulation
    • Revenue Management effects
how should a pricing simulation model work
How should a Pricing Simulation Model work ?

Market Share

Passenger Demand

Revenue

Market Stimulation

Revenue

Management

Simulation

Competitor

Reaction

Unconstrained Processing

Constrained Processing

Constrained Processing

Unconstrained

DemandModel

RevenueCalculation

Price Elasticity

Model

slide8

Price Elasticity

Model

Price Elasticity Model

what should a price elasticity model do
What should a Price Elasticity Model do?

Price Elasticity

Model

Depiction of Passenger Behavior:

Passenger books on a specialTicketing Day and chooses among the offered fares, which are valid on his Travel day - The day, on which passenger wants to fly

  • Customer makes decision along several attributes of the fare
how could passenger behavior be depicted
How could passenger behavior be depicted?

Price Elasticity

Model

  • Qualitative Choice Model
    • Multinomial Logit Model
  • Choice Set: Applicable fares per Ticketing/Travel - combination
      • Day Application
      • Advance Purchase
      • Booking Class open (Constrained Processing)
  • Attribute Set:
      • Compartment
      • Carrier
      • Amount
      • Minimum/Maximum Stay
the difficulties of the price elasticity model
The difficulties of the Price Elasticity Model ......

Price Elasticity

Model

  • Independence of Irrelevant Alternatives (IIA - Property)
  • Customer Heterogeneity
  • Calibration data for estimation ofthe parameters
how could iia property be avoided
How could IIA - Property be avoided ?

Price Elasticity

Model

  • Selection of the choice set dependent on the Ticketing - and Travel day
  • Clustering of the choice set
    • Compartment
    • Carrier
    • Amount
    • Minimum/Maximum Stay
customer heterogeneity which passengers might behave homogenous
Customer Heterogeneity -Which passengers might behave homogenous?

Price Elasticity

Model

Spilled Passengers (Constrained Processing)

Spilled Passengers (Constrained Processing)

  • Business passengers
  • Leisure passengers
    • Stimulated passengers
how could the price elasticity model be estimated
How could the Price Elasticity Model be estimated?

Price Elasticity

Model

  • For each passenger type
    • Passenger Preference Parameter
      • Compartment
      • Carrier Preference/Schedule Quality
      • Amount
      • Minimum Stay
      • Maximum Stay
  • Calibration Input Data
    • Merge of MIDT- and ATPCO Data
slide15

Revenue ManagementSimulation

Revenue Management Simulation

why revenue management simulation
Why Revenue Management Simulation?

Passenger Preference

Airline Interest

what should a revenue management simulation do
What should a Revenue Management Simulation do ?

RevenueManagementSimulation

  • Optimization of revenue by determining the size of booking classes
    • Capacities
    • expected Demand

Depiction the yield management impact on the passenger behavior

how should a revenue management simulation work
How should a Revenue Management Simulation work?

RevenueManagementSimulation

  • Algorithm for optimizing revenue
  • Back Loop to Price Elasticity Modelfor depicting influence of the yield management on passengerbehavior
the difficulties of revenue management simulation
The difficulties of Revenue Management Simulation ....

RevenueManagementSimulation

  • The need of simulating revenue management effects for all carriers
    • Optimization Algorithm
    • Re - Calculation of Protection Level
    • Estimation of expected Demand and Capacities
how could the difficulties be solved
How could the difficulties be solved?

RevenueManagementSimulation

  • Optimization Algorithm
    • Usage of a common Algorithm
      • nested EMSRb
  • Re- Calculation of Protection Level
    • Re-Calculation in view to the results of the PEM in the Back-Loop
  • Estimation of expected Demand/Capacities
    • Estimation with
      • MIDT Data
      • Actual Flown Data
      • OAG
agenda21
Agenda

Supported Pricing Processes

Pricing Simulation Modeling

Summary

summary
Summary
  • Pricing Simulation should take into account all essential Pricing Decision Rules
    • Competitor Reaction
    • Cannibalization
    • Market Stimulation
    • Revenue Management Effects

The model should be designed along data sources available in practice