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Pricing Simulation
Natascha Jung, Senior Operation Research Specialist
Proven solutions for open skies
Presentation, AGIFORS 200024th March 2000 in New York
Pricing Simulation Model24th March 2000Chart 2
Agenda
Pricing Simulation ModelingPricing Simulation Modeling
Supported Pricing ProcessesSupported Pricing Processes
SummarySummary
Pricing Simulation Model24th March 2000Chart 3
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
Pricing Simulation Model24th March 2000Chart 4
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
Pricing Simulation Model24th March 2000Chart 5
Agenda
Pricing Simulation ModelingPricing Simulation Modeling
Supported Pricing ProcessesSupported Pricing Processes
SummarySummary
Pricing Simulation Model24th March 2000Chart 6
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
Pricing Simulation Model24th March 2000Chart 7
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
Pricing Simulation Model24th March 2000Chart 8
Price ElasticityModel
Price Elasticity Model
Pricing Simulation Model24th March 2000Chart 9
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
Pricing Simulation Model24th March 2000Chart 10
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
Pricing Simulation Model24th March 2000Chart 11
The difficulties of the Price Elasticity Model ......
Independence of Irrelevant Alternatives (IIA - Property)
Customer Heterogeneity
Calibration data for estimation ofthe parameters
Price Elasticity
Model
Pricing Simulation Model24th March 2000Chart 12
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
Pricing Simulation Model24th March 2000Chart 13
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
Pricing Simulation Model24th March 2000Chart 15
Revenue ManagementSimulation
Revenue Management Simulation
Pricing Simulation Model24th March 2000Chart 16
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
Pricing Simulation Model24th March 2000Chart 17
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
Pricing Simulation Model24th March 2000Chart 18
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
Pricing Simulation Model24th March 2000Chart 19
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
Pricing Simulation Model24th March 2000Chart 21
SummarySummary
Agenda
Pricing Simulation ModelingPricing Simulation Modeling
Supported Pricing ProcessesSupported Pricing Processes
Pricing Simulation Model24th March 2000Chart 22
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
Pricing Simulation Model24th March 2000Chart 23