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Revenue Benefits of Sell-up Models. Thomas Gorin, MIT AGIFORS RM Study Group Meeting New York, March 21-25, 2000. Outline. EMSRb Sell-up Models in a Small Network Revenue Gains Effect on Loads Hopperstad-B/W vs. Belobaba/Weatherford Comparisons with BW Revenues and Average Load Factors

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revenue benefits of sell up models

Revenue Benefits of Sell-up Models

Thomas Gorin, MIT

AGIFORS RM Study Group Meeting

New York, March 21-25, 2000

outline
Outline
  • EMSRb Sell-up Models in a Small Network
    • Revenue Gains
    • Effect on Loads
  • Hopperstad-B/W vs. Belobaba/Weatherford
    • Comparisons with BW
    • Revenues and Average Load Factors
  • Sell-up in a Bigger Network
    • Revenue Gains

T. Gorin, Sell-up Results

input sell up rates to bw model
Input Sell-up Rates to BW Model
  • In the Belobaba/Weatherford heuristic, estimates of sell-up rates are required as input:
    • We tested various input sell-up rate combinations and determined through literature review and experimentation, that “differential” input sell-up rates were the “best”.
    • The sell-up rates we refer to as “differential” are shown on the next slide.
    • These are not necessarily the “actual” sell-up rates in the PODS simulation.

T. Gorin, Sell-up Results

sell up models in small pods network
Sell-up Models in Small PODS Network
  • The Network
    • 6 cities, 2 hubs
    • 2 competing airlines
    • 24 flight legs (12 per airline), 54 markets
    • 4 Fare Classes
  • Base Case
    • Both competitors use EMSRb Fare Class Yield Management (FCYM)
    • Neither airline accounts for sell-up

T. Gorin, Sell-up Results

sell up in a small network results
Sell-up in a Small Network: Results
  • Revenue Gains
    • In the small network, accounting for sell-up leads to revenue gains for all the methods tested (compared to the base case EMSRb vs. EMSRb)
    • The incremental revenue gains from the B/W sell-up model are about 1% for EMSRb, and 0.64% to 1.25% for the different O-D methods tested.
    • These incremental gains are smaller when both airlines account for sell-up
  • Loads
    • Average Load Factors decrease as we account for sell-up (compared to the base case)
    • As expected, passenger loads in high fare classes increase

T. Gorin, Sell-up Results

hbw vs bw sell up heuristics
HBW vs. BW Sell-Up Heuristics
  • Revenues
    • The following chart shows that, generally, the revenue gains with HBW are 0.1%-0.2% higher than with BW
    • But, in a few cases that we tested, the revenues were slightly lower with HBW
  • Loads
    • The Average Load Factors are lower yet when the airline uses HBW, as compared to the BW sell-up heuristic

T. Gorin, Sell-up Results

hbw vs bw sell up models summary
HBW vs. BW Sell-up Models: Summary
  • Revenues
    • In most of the cases tested, HBW leads to slightly higher revenue gains than the original BW heuristic
    • These revenue gains range between 0.1% and 0.2%
    • As Craig pointed out earlier, HBW is most beneficial when demand is high relative to capacity
  • Load Factors
    • HBW generally leads to slightly lower Average Load Factors than BW

T. Gorin, Sell-up Results

use of sell up models in a larger pods network
Use of Sell-up Models in a Larger PODS Network
  • The Network
    • 40 spoke cities, “20 on each side”
    • 2 hubs (one per airline, with interhub flights)
    • Unidirectional flow of traffic (West to East)
    • 3 banks per day per airline, 252 flight legs, 482 O-D markets

T. Gorin, Sell-up Results

sell up in larger network results
Sell-up in Larger Network: Results
  • Revenues
    • In all cases tested, accounting for sell-up led to increased revenues over the base case (EMSRb vs. EMSRb)
  • Network Effects
    • The revenue gains over the “no sell-up” cases are similar to those observed in the smaller PODS network
    • Using the B/W heuristic, incremental gains of 1.35% for EMSRb FCYM, and about 1% for O-D methods

T. Gorin, Sell-up Results

summary
Summary
  • Benefits of Accounting for Sell-up
    • Revenue gains from accounting for sell-up in EMSRb-based RM systems (FCYM, GVN, DAVN and HBP)
    • In our largest and most realistic network to date, accounting for sell-up added about 1% to revenue gains
    • Unclear to what extent these revenue gains come from:
      • Properly estimating passenger sell-up behavior
      • “Forcing” sell-up by increasing unconstrained demand forecasts and closing down low-fare availability
      • Limited alternative airline and path options in PODS

T. Gorin, Sell-up Results

next steps
Next Steps
  • How do we estimate sell-up rates in the real world?
    • One approach is to use the following approximation:
    • The sell-up rates generated by this formula are too high and lead to overprotection.
      • There is a sample bias. The higher the demand, the earlier the lower fare classes close down, and therefore, the higher the estimate of the sell-up rates.

T. Gorin, Sell-up Results

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