Pricing Simulation

Natascha Jung, Senior Operation Research Specialist

Proven solutions for open skies

Presentation, AGIFORS 200024th March 2000 in New York

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Agenda

Pricing Simulation ModelingPricing Simulation Modeling

Supported Pricing ProcessesSupported Pricing Processes

SummarySummary

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Pricing Simulation in Reactive Pricing

CompetitorFare Action

AutoMatching

ManualMatching

Pricing Simulation

Automated Distribution

Yes Yes

Statistics

No No

Don’t know !

Trigger AutomatedDecision

Decision Support

Decision Action

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Pricing Simulation in Proactive Pricing

Special Event Pricing

Evaluate Scenario

Pricing Simulation

Automated Distribution

Yes

Open Capacity

New Destination

...

What-IfModeling

Trigger Possible Actions Simulation/ Action Evaluation

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Agenda

Pricing Simulation ModelingPricing Simulation Modeling

Supported Pricing ProcessesSupported Pricing Processes

SummarySummary

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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

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Constrained Processing

How should a Pricing Simulation Model work ?

Constrained Processing

Unconstrained Processing

RevenueMarket Share

Price ElasticityModel

Passenger Demand

UnconstrainedDemandModel

RevenueManagement

Simulation

RevenueCalculation

CompetitorReaction

Market Stimulation

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Price ElasticityModel

Price Elasticity Model

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What should a Price Elasticity Model do?

Depiction of Passenger Behavior:

Price Elasticity

Model Passenger books on a special Ticketing 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

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How could passenger behavior be depicted? Qualitative Choice Model

Multinomial Logit Model

–

Price Elasticity

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

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The difficulties of the Price Elasticity Model ......

Independence of Irrelevant Alternatives (IIA - Property)

Customer Heterogeneity

Calibration data for estimation ofthe parameters

Price Elasticity

Model

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How could IIA - Property be avoided ? Selection of the choice set dependent

on the Ticketing - and Travel day

Clustering of the choice set

Compartment

Carrier

Amount

Minimum/Maximum Stay

Price Elasticity

Model

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Customer Heterogeneity -Which passengers might behave homogenous?

Business passengers

Leisure passengers Stimulated passengers

Spilled Passengers (Constrained Processing)

Spilled Passengers (Constrained Processing)

Price Elasticity

Model

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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

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Revenue ManagementSimulation

Revenue Management Simulation

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Why Revenue Management Simulation?

Carrier Fareclass Amount MIN MAX APNW VSNOW 669,00 7 30DL LLSSDE2 669,00 SU 30SN BLSSDE2 669,00 SU 30AA MWINTER1 669,00 SU 30 7BA QWINSPL 669,00 SU 30 7LH WINTER1 669,00 SU 30 7UA VL7AP1M 669,00 SU 30 7

AA VLPX3MDE 1029,00 SU 90DL KLAP1 1029,00 SU 90BA QLAP3MS 1029,00 SU 90 7LH LLAP3MUS 1029,00 SU 90 7SN KLAPDE1 1029,00 SU 90 7UA HLAP3MUS 1029,00 SU 90 7

Passenger Preference

Airline Interest

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What should a Revenue Management Simulation do ?

RevenueManagement

Simulation

Optimization of revenue by determining the size of booking classes

Capacities expected Demand

Depiction the yield management impact on the passenger behavior

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How should a Revenue Management Simulation work?

Algorithm for optimizing revenue

Back Loop to Price Elasticity Modelfor depicting influence of the yield management on passengerbehavior

RevenueManagement

Simulation

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The difficulties of Revenue Management Simulation ....

The need of simulating revenue management effects for all carriers

Optimization Algorithm

Re - Calculation of Protection Level

Estimation of expected Demand and Capacities

RevenueManagement

Simulation

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How could the difficulties be solved?

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

RevenueManagement

Simulation

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SummarySummary

Agenda

Pricing Simulation ModelingPricing Simulation Modeling

Supported Pricing ProcessesSupported Pricing Processes

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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

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