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Defining Revenue Management as a Game

Defining Revenue Management as a Game. Gert Hartmans Agifors - Berlin 2002. Objectives. Better understanding revenue management for system development Breakdown processes in small sub-processes Represent each sub-process as a game

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Defining Revenue Management as a Game

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  1. Defining Revenue Managementas a Game Gert Hartmans Agifors - Berlin 2002

  2. Objectives • Better understanding revenue management for system development • Breakdown processes in small sub-processes • Represent each sub-process as a game • Link all games to reflect total process and enable review of strategies • Derive system implications

  3. Conceptual view of RevMgt 2000 Group Desk Reservations & Departure Control Forecast Display Availability Optimise Capacity Fares& Rules Fares Capacity Competitor

  4. But daily issues ... 2002 • Corporate account access/effects • Loyalty Program redemption access • Alliance partner access • Interline/SPA (non-) access • Product differentiation (Economy +) • CRS costs • Ticket Class / Booked Class mismatch • Waivers by sales

  5. Sales contracts Pricing Inventory Control Account- ing Loyalty SPA’s Reserva- tions Departure Control Systems - ‘ modular design ’

  6. Pricing Inventory Control Account- ing Loyalty SPA’s Reserva- tions Sales contracts Departure Control Systems - links

  7. Departure Control Pricing Inventory Control Account- ing Loyalty SPA’s Reserva- tions Sales contracts Departure Control Pricing Inventory Control Account- ing Loyalty SPA’s Reserva- tions Sales contracts Systems in Alliance

  8. Game Concept • Players/Rules • Rewards/Loss • Choices/Strategy • Enables modeling • Expectations/Guessing • Deception/Cheating • Cooperation/Retaliation

  9. Inventory Control - Game • Players Objectives • Maximize Revenue • Rules • Players set availability access per round without prior knowledge of others steps • Two classes: H earns 1 points, L earns 0.5 points • L books first • Actions • Open class or Close class

  10. Inventory Control - Game 1.1:2 Blue Pay-off Matrix • Capacity 2 per player, Demand H1 L1 per round • Pay off matrix for Blue • Per round one H-pax books valued at 1 and one L-pax books valued at .5 • Dominant strategy = All open

  11. Inventory Control - Game 2.1:2 Blue Pay-off Matrix • Capacity still 2, demand H2 L1, L books first • Pay off matrix for Blue • Per round two H-pax books valued at 1 and one L-pax books valued at .5 • Dominant strategy = H Open/ L Closed

  12. Inventory Control - Game 1.4:2 Blue Pay-off Matrix spill • Capacity still 2, demand H1 L4, L books first • Pay off matrix for Blue • Per round one H-pax books valued at 1 and four L-pax books valued at .5 • Dominant strategy = Keep L open* Reward for H needs to be > 1.14 to close L

  13. Usage of concepts • Dominant strategy best for both, can be used for guessing expected competitor action (leads to Nash Equilibrium) • If competitor deviates from dominant strategy alternatives do not seem more profitable,avoid copy-cat marketing • When reality/rules differs for both players, different strategies may be advantageous(larger capacity, different fares, lower frequency etc.)

  14. Sub-processes • Inventory control game • Pricing game • Fare Rule game • Sales game • Sales - Agents game • Agents - Customer game… products … loyalty ….

  15. Pricing - Game 2.2:2 Blue Pay-off Matrix • Capacity 2 per player, demand H2L2, L books first • Pay off matrix for Blue • Per round two H-pax books valued at 1 and twoL-pax books valued at .5 • Dominant strategy = Offer H fares only

  16. Fare Rule - Game 2.2:2 Blue Pay-off Matrix • Capacity 2 per player, demand H2L2 • L books first, H books L if no rule exists • Pay off matrix for Blue • Per round two H-pax books valued at 1 and twoL-pax books valued at .5 • Dominant strategy = Add fare rules

  17. Sales Game 4.4:4 Blue Pay-off Matrix • Capacity 4 is shared per 2 players (sales office) based on bids H:L 3:1 or evenly 2:2 (gray area) • Demand H2 L2 per round per player, 4 per market • Dominant strategy = bid high and sell high, but potential for cheating

  18. Sales - Agents Game Blue Pay-off Matrix • Commission % differs, Demand 1 per round • Pay off matrix for Blue (Sales office) • Dominant strategy = Surpass competitor commission levelsif possible

  19. Agents - Customer Game Blue Pay-off Matrix • Discount differs, Demand 1 per round • Pay off matrix for Blue (agent) • Dominant strategy = Match or surpass competitor agent

  20. Value Chain Airlines - Inventory game Airlines - Pricing game Airlines - Fare Rules game Sales game Sales - Agents game Agents - Customers game

  21. Conclusions • Market position is chain of games • Organization, systems do not reflect inter-relations which are reflected in processes • Open to cheating and deception • System alignment and interfaces should help in achieving more optimal results

  22. Enforcing rules • Currently: Booking =/= Sale =/= Fare • Commission variation, rule waivers, or over stating fares, leads to incorrect information • Objective: 1 product= 1 contract =1 booking = 1 sale = 1 fare

  23. Place Commercial Here

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