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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

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Revenue benefits of sell up models l.jpg

Revenue Benefits of Sell-up Models

Thomas Gorin, MIT

AGIFORS RM Study Group Meeting

New York, March 21-25, 2000


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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


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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


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“Differential” Input Sell-up Rates

T. Gorin, Sell-up Results


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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


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T. Gorin, Sell-up Results


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T. Gorin, Sell-up Results


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T. Gorin, Sell-up Results


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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


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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


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T. Gorin, Sell-up Results


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T. Gorin, Sell-up Results


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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


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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


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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


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T. Gorin, Sell-up Results


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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


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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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