1. Pricing Simulation Proven solutions for open skies
Presentation, AGIFORS th March 2000 in New York
Pricing Simulation
Natascha Jung, Senior Operation Research Specialist
Proven solutions for open skies 1 1

2. Agenda
Supported Pricing Processes
Pricing Simulation Modeling
Summary

3. Pricing Simulation in Reactive Pricing
Trigger
Automated Decision
Decision Support
Decision
Action
Statistics
Competitor
Fare Action
Pricing Simulation No No
Auto Matching
Manual Matching
Don’t know !
Yes
Yes
We distinguish between different phases, which are a trigger phase, the automated decision making phase, the decision support phase, the decision phase and the final action phase
A competitor fare action is the trigger in Reactive Pricing.
An auto matching procedure can handle many reactions based on easy to define rules.
Life Fare Mapping helps in identifying the competing own fare classes.
Via Pricing Simulation the impact of matching/non- matching can be calculated/predicted.
Reactions are distributed via an automated distribution procedure.
Automated Distribution

4. Pricing Simulation in Proactive Pricing
Trigger Possible Actions Simulation/ Action Evaluation
Pricing Simulation
Open Capacity
Special Event Pricing
What-If
Modeling
Evaluate Scenario
Automated Distribution
Yes
New Destination
Many different triggers exist for Proactive Pricing, e.g.
open capacity
special event pricing
new destination
Based on the trigger a lot of different action scenarios can be taken into consideration.
Via Pricing Simulation the impact of the scenarios can be calculated/predicted; Like Fare Mapping again helps in getting a structured market overview.
Reactions are distributed via an automated distribution procedure.
...

5. Agenda
Supported Pricing Processes
Pricing Simulation Modeling
Summary

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

7. How should a Pricing Simulation Model work ?
Constrained Processing
Unconstrained Processing
Market Share
Constrained Processing
Passenger Demand
Revenue
Revenue
Management
Simulation
Competitor
Reaction
Market Stimulation
Price Elasticity
Model
Unconstrained
Demand Model
Revenue Calculation

8. Price Elasticity Model

9. What should a Price Elasticity Model do?
Depiction of Passenger Behavior:
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

10. 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

11. The difficulties of the Price Elasticity Model ......
Independence of Irrelevant Alternatives (IIA - Property)
Customer Heterogeneity
Calibration data for estimation of the parameters

12. 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

13. Customer Heterogeneity - Which passengers might behave homogenous?
Price Elasticity
Model
Business passengers
Spilled Passengers (Constrained Processing)
Leisure passengers
Stimulated passengers

14. How could the Price Elasticity Model be estimated?
For each passenger type
Passenger Preference Parameter
Compartment
Carrier Preference/Schedule Quality
Amount
Minimum Stay
Maximum Stay
Price Elasticity
Model
Calibration Input Data
Merge of MIDT- and ATPCO Data

15. Revenue Management Simulation

16. Why Revenue Management Simulation?
Passenger Preference
Airline Interest

17. What should a Revenue Management Simulation do ?
Optimization of revenue by determining the size of booking classes
Capacities
expected Demand
Depiction the yield management impact on the passenger behavior

18. How should a Revenue Management Simulation work?
Algorithm for optimizing revenue
Back Loop to Price Elasticity Model for depicting influence of the yield management on passenger behavior

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

20. 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
Revenue Management Simulation

21. Agenda
Supported Pricing Processes
Pricing Simulation Modeling
Summary

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