kawika pierson mit system dynamics group 3 nd year phd fall 2008 albany-mit phd colloquium the...
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Kawika Pierson MIT System Dynamics Group 3nd Year PhD
Fall 2008 Albany-MIT PhD Colloquium
The Cyclical Nature of Airline Industry Profits
OutlineRelevant LiteratureReference Mode for Airline ProfitsDigging DeeperThe Model
DemandPrice Capacity CostsProfit
Results
Relevant Literature “Cycles in the sky: understanding and managing business
cycles in the airline market” M Liehr, A Groessler, M Klein, PM Milling - System Dynamics Review, 2001 Made for Lufthansa as a guide for strategy Very limited scope (only one feedback loop)
Relevant Literature “System dynamics for market forecasting and structural
analysis” James Lyneis - System Dynamics Review, 2000Commercial jet aircraft industryFocused on use of SD models as forecasts for
Jet OrdersProprietary, but potentially similar to our
work "Analysis of Profit Cycles in the Airline Industry" 2004
Helen Jiang, R. John Hansman Very simple model, two stocks one feedback
loopControl theory perspective
Reference ModeThe data for US airline industry profits shows
some cyclicality since before deregulation
Taken from a presentation by Prof. R. John Hansman and Helen Jiang Nov. 2004
Digging DeeperProfit = Revenue – CostsRevenue = Price * sales in unitsCosts = unit cost * productionSales is Revenue Passenger MilesPrice is the Price of TicketsProduction is Available Seat MilesThis gives us ProfitHow does financial reporting effect our
modeling?
Capacity – Causal Loop Diagram
Demand
Capacity
+Forecasted
Demand
DesiredCapacity
Investment
CapacityShortfall
+-
+
+
+
CapacityControl
B
Capacity - Model Structure
Airline CapacityAirline Capacity
Supply LineOrders ofAirplanes
AirplaneManufacturing
Completion
AirplaneRetirements
Initial Capacityon Order
Initial AirlineCapacity <Retired>
AdjustmentFor Capacity
Time to AdjustCapacity
Adjustment for theSupply Line
Weight on SupplyLine Adjustment
IndicatedCapacity
Adjustment
Cancellation
<CancelledOrders>
Mothballed Capacity
Mothballing Off Mothballing
<IntoStorage>
<Return toService>
<Return toService>
DesiredCapacity
+
-
-
Desired AircraftSupply Line
+
<Time Required toManufacture an
Airplane>
+
PlannedReplacement
Orders
Desired CapacityAcquisition Rate
Supply LineAdjustment Time
+
-
-
Indicated Ordersfor Capacity
+
Order ApprovalDelay Time
<AirplaneRetirements>
Third Order Stocks –Cancellation and Mothballing
Time Required toManufacture an
Airplane
Capacity onOrder 1
Capacity onOrder 2
Capacity onOrder 3
Ordering 1 to 2 2 to 3 Completion
<Orders ofAirplanes>
CancelledOrders
Time to Cancel
<Indicated Ordersfor Capacity>
+
<AirplaneManufacturingCompletion>
New CapacityCapacity 1 Capacity 2
Cap 1 to 2Capacity 3
Cap 2 to 3 Retired
AverageService Life
<OperatingMargin>
Into Storage
Time toMothball
Capacity on Mothball
Margin Threshold toInitiate Mothballing
Return toService
<OperatingMargin>
<Time toMothball>
<Indicated Ordersfor Capacity>
<Indicated Ordersfor Capacity>
Forecasting Demand
PerceivedDemand
Time to PercieveChanges in Demand
Time Horizion forReference Demand
ReferenceDemand
Change inReference Demand
IndicatedGrowth Rate
<Time Horizion forReference Demand>
Time to PercieveTrend in Demand
Expected GrowthRate for Demand
Change inExpected Growth
Rate
Initial ExpectedGrowth Rate in
Demand
<Actual DemandFor Seat Miles>
<HistoricalAirline Demand>
Change inDemand
Perception
Gap in DemandPerception
<Switch forHistoricalVariables>
Correction For Growth
Airline CapacityAirline Capacity
Supply LineOrders ofAirplanes
AirplaneManufacturing
Completion
AirplaneRetirements
Desired LoadFactor
Initial Capacityon Order
Initial AirlineCapacity
Supply LineAdjustment for
Growth in Demand
<Retired>
AdjustmentFor Capacity
Desired SeatMiles
Time to AdjustCapacity
Adjustment for theSupply Line
Weight on SupplyLine Adjustment
IndicatedCapacity
Adjustment
Weight on DemandForecast Orders
Cancellation
<CancelledOrders>
Mothballed Capacity
Mothballing Off Mothballing
<IntoStorage>
<Return toService>
<Return toService>
DesiredCapacity
+
-
-
Desired AircraftSupply Line
+
<Time Required toManufacture an
Airplane>
+
PlannedReplacement
Orders
<AirlineCapacity>
<Airline CapacitySupply Line>
+
Desired CapacityAcquisition Rate
Supply LineAdjustment Time
+
-
-
Indicated Ordersfor Capacity
+
Order ApprovalDelay Time
ExpectedDemand
Demand ForecastHorizion
<Expected GrowthRate for Demand>
<Expected GrowthRate for Demand>
<Time to PercieveChanges in Demand>
<PerceivedDemand>
<Number of MilesFlown per Seat>
Capacity Adjustmentfor Growth in Demand
<AirplaneRetirements>
Fitting to DataGet historical data on important stocks
Airlines are great for thisAirlines.org, MIT Airline Data Project, BTS
Set up summary statisticsJohn Sterman’s Book plus MAE, RMSE, %E,
Thiel, SSE/M^2Drive each model sector with historical
variables Use Vensim’s model fitting functions
Lets walk through this
Summary Statistics
R^2
rM X
M Y
MxySx
Sy
Sum Xi
dt
Xi
pick
X
Historical
Count
Sum YiYi
Y
Simulated
<dt> SumXY
<Xi> <Yi>
MY2
SumY2
<Count>
<dt>
<M Y>
<Yi>
<Count>MX2
SumX2 <dt>
<Xi>
<M X>
<Count>
Start Time
End Time
Interval
<Time>
<TIME STEP>
<HistoricalAvailable Seat
Miles>
<Available SeatMiles>
<Historical>
<Simulated>
Percent Error
<Yi>
<Xi>
Residuals <Yi> <Xi> <dt>
Sum AE
Sum APE
<Count>
MAPE
MAE overMean
<M X>
<r>
<Sy> <Sx>
dif cov
dif var
dif mean
<M X>
<M Y>
MSE
RMSE
Um
Us
Uc <dif cov>
<dif mean>
<dif var>
RMSE overMean
Payoff Element
Error over MeanSquared
Sum of ErrorSquared over Mean
<M X>
<dt>
Example of Fitting the Model1. Open Simulation
Control
2. Create a
Payoff
Example of Fitting the Model3.
Run “Policy”
Negative
Example of Fitting the Model
4.
Set Parameters
Example of Fitting the Model
5.
Capacity Fit – Historical Inputs
Historical and Simulated Airline Capacity
1e+012
750 B
500 B
250 B
0
1970 1974 1978 1982 1986 1990 1994 1998Time (Year)
Sea
t*m
iles/
Yea
r
Historical Available Seat Miles : Match AllAvailable Seat Miles : Match All
“R^2” MAE/Mean RMSE/Mean Um Uc Us0.995 0.0224 0.0309 0.0043 0.7475 0.2480
Demand – Causal Loop Diagram
Demand
Capacity
+Forecasted
Demand
DesiredCapacity
Investment
CapacityShortfall
+-
+
+
+
CapacityControl
B
+
R
RouteNetworks
Load Factor
+-
Congestion+
-Delivery Delay
B
Ticket Price+
GDP+
-
R
Price War
Demand – Model Structure
Actual DemandFor Seat Miles
ReferenceTicket Price
Effect of Priceon Demand
<Ticket Price>
Historical PopulationData and Projections
Population
<Time>InitialPopulation
Demand for SeatMiles per Capita
Seat Miles Desiredfrom GDP per Capita
GDP perCapita
Miles per Person perDollar of GDP
Historical GDP Dataand Projections
Elasticity of Demandwith Respect to Price
<Time>
ConstantDemand
Adjustment
<Initial TicketPrice>
<Available SeatMiles>
Effect of NewCapacity on
Demand
Strength of NewCapacity Effect on
Demand
One Year PercentChange in Capacity
<Lag forMeasuringChanges>
Effect ofCongestion on
Demand
Indicated Effect ofCongestion on
Demand
CongestionPerception Time
Sensitivity ofDemand toCongestion
<ComfortableIndustry Load
Factor>
<Indicated LoadFactor>
Demand Fit – Historical Inputs
“R^2” MAE/Mean RMSE/Mean Um Uc Us0.99 0.0273 0.0356 0.0033 0.9595 0.0371
Historical and Simulated Revenue Passanger Miles
800 B
600 B
400 B
200 B
0
1970 1974 1978 1982 1986 1990 1994 1998Time (Year)
Sea
t*m
iles/
Yea
r
Historical Airline Demand : Match AllActual Demand For Seat Miles : Match All
Price – Model Structure
Ticket PriceChange in
Ticket Price
MinimumTicket Price
Time to AdjustTicket Prices
Indicated TicketPrice per Seat Mile
Indicated Price
Initial TicketPrice
TargetPercentageAbove Cost
<Cost perAvailable Seat
Mile>Effect of DemandSupply Balance
on Price
+
<Desired LoadFactor>
Sensitivity of Priceto Demand Supply
Balance
<Load Factor>
-+
<Cost perAvailable Seat
Mile>
Effect of Costson Price
<Ticket Price>
Sensitivity ofPrice to Costs
Effect of Marginon Price
<OperatingMargin>
Sensitivity ofPrice to Margin
Target Margin
Price Fit – Historical Inputs
“R^2” MAE/Mean RMSE/Mean Um Uc Us0.98 0.0583 0.0710 0.0004 0.2980 0.7015
Historical and Simulated Ticet Price
0.2
0.15
0.1
0.05
0
1970 1974 1978 1982 1986 1990 1994 1998Time (Year)
dolla
rs/(
Sea
t*m
ile)
Historical Airline Ticket Prices : Match PriceTicket Price : Match Price
Costs – Causal Loop Diagram
Demand
Capacity
+Forecasted
Demand
DesiredCapacity
Investment
CapacityShortfall
+-
+
+
+
CapacityControl
B
+
R
RouteNetworks
Load Factor
+-
Congestion+
-Delivery Delay
BRevenue
Ticket Price+
+
Profit
+
+
Costs+
+
-
Costs
B
R
Investment
Competition
B
GDP+
-
R
Price War
Costs - Model Structure
Operating Costsfrom Passengers
Costs fromWages
Variable Costfrom Operations
Variable Costsper Seat Mile
<AirlineCapacity>
<Available SeatMiles>
Cost per AvailableSeat Mile
Variable Costsfrom Jet Fuel
Other VariableCosts
Gallons perSeat Mile
Fuel Cost perGallon
Historical Jet FuelCost per Gallon
<Time>
Projected FuelCost
Total WorkerSalary by Type Total Workers
by Type
Workers Per Seatof Capacity
++
+
+
<Average WorkerCompensation>
Initial OtherVariable Costs
1982 OtherVariable Costs
Producer PriceIndex
Table forProducer Price
Index
<Time>
Operating CostsFrom Freight
Total OperatingCosts
Freight as aPercentage of
Passenger Operations
Cost Fit – Historical Inputs
“R^2” MAE/Mean RMSE/Mean Um Uc Us0.99 0.055 0.0719 0.0603 0.6697 0.2698
Historical and Simulated Operating Costs
200 B
150 B
100 B
50 B
0
1970 1974 1978 1982 1986 1990 1994 1998Time (Year)
dolla
rs/Y
ear
Historical Airline Operating Costs : Match CostTotal Operating Costs : Match Cost
Wages – Model Structure
<OperatingMargin>
AverageWorker
CompensationChange in Worker
Compensation
IndicatedCompensation
Initial WorkerCompensation
<AirlineCapacity> One Year Change in
New Hires
Effect of Inflation inWorker Compensation
<Lag forMeasuringChanges>
Effect of OutsideOpportunities on Worker
Compensation
Effect of New Hireson Worker
Compensation
Recent AirlineCapacity
Time to ChangeWorker
Compensation
Effect of OperatingMargin on Worker
Compensation
Gap For WorkerCompensation
National AverageWage Data
NationalAverage Wage
Wage Relative toAverage
<Time>
CPI PercentageChange
CPI Data
<Time>
Strength of OutsideOpportunities on Worker
Compensation
Strength of New HireEffect on WorkerCompensation
Strength of Margin onWorker Compensation
Strength of Inflationon Worker
Compensation
Wage Premiumfor Skill
<Number of MilesFlown per Seat>
Historical AirlineCapacity
CPI
Normal Margin
HistoricalUnemployment
Data
HistoricalUnemployment
<Time>
Strength ofUnemployment Effect
on Wages
Effect ofUnemployment on
Worker Compensation
NormalUnemployment
Recent MarginMargin
Perception Delay
Profits – Model Structure
Revenue SeatMiles
PassengerRevenue
OperatingProfit
OperatingMargin
<Available SeatMiles>
<Load Factor>
<Ticket Price>
OperatingRevenue
AccumulatedOperating
ProfitNew OperatingProfit
Drain OperatingProfit
<TIME STEP>
check year
<Time>
<Total OperatingCosts>
FreightRevenue
Freight as aPercentage of
Passenger Operations
ReportedOperating Profit
Wages Fit – Historical Inputs
“R^2” MAE/Mean RMSE/Mean Um Uc Us0.99 0.0278 0.0398 0.0294 0.9426 0.0278
Historical and Simulated Average Wages
80,000
60,000
40,000
20,000
0
1970 1974 1978 1982 1986 1990 1994 1998Time (Year)
dolla
rs/(
Yea
r*w
orke
r)
Historical Airline Salaries : Match AllAverage Worker Compensation : Match All
Real Wages Fit – Historical Inputs
“R^2” MAE/Mean RMSE/Mean Um Uc Us0.68 0.0262 0.0339 0.0290 0.9370 0.0339
Real Wages sim vs actual
20,000
17,500
15,000
12,500
10,000
1970 1974 1978 1982 1986 1990 1994 1998Time (Year)
dolla
rs/(
Yea
r*w
orke
r)
Simulated Real Wage : Match AllHistorical Real Wage : Match All
Full model OptimizationMove from partial model tests to full model
parameterizationFits are slightly worse, parameters more
believable
Historical and Simulated Airline Capacity
2e+012
1.5e+012
1e+012
500 B
0
1971 1975 1979 1983 1987 1991 1995 1999Time (Year)
Sea
t*m
iles/
Yea
r
Historical Available Seat Miles : Match AllAvailable Seat Miles : Match All
Historical and Simulated Ticet Price
0.2
0.15
0.1
0.05
0
1971 1975 1979 1983 1987 1991 1995 1999Time (Year)
dolla
rs/(
Sea
t*m
ile)
Historical Airline Ticket Prices : Match AllTicket Price : Match All
MAE/Mean RMSE/Mean MAE/Mean RMSE/Mean 0.0459 0.0564 0.0508 0.0595
Full model Optimization
MAE/Mean RMSE/Mean MAE/Mean RMSE/Mean 0.0345 0.0434 0.0372 0.0465
Historical and Simulated Revenue Passanger Miles
800 B
600 B
400 B
200 B
0
1971 1975 1979 1983 1987 1991 1995 1999Time (Year)
Sea
t*m
iles/
Yea
r
Historical Airline Demand : Match AllActual Demand For Seat Miles : Match All
Historical and Simulated Operating Costs
200 B
150 B
100 B
50 B
0
1971 1975 1979 1983 1987 1991 1995 1999Time (Year)
dolla
rs/Y
ear
Historical Airline Operating Costs : Match AllTotal Operating Costs : Match All
Parameters More BelievableIn Partial Model Test SLAT = 0.05 TAC = 1
Theoretically should be very similarIn Full Model Parameterization SLAT = 0.18
TAC = 0.19
Time to Adjust Prices Partial = 0.05 Full =0.64
Sensitivity of Price to Cost Partial = 3 Full = 0
Profits Still Questionable
Historical and Simulated Profit
10 B
5 B
0
-5 B
-10 B
1971 1975 1979 1983 1987 1991 1995 1999Time (Year)
dolla
rs/Y
ear
Historical Airline Operating Profit : Match AllReported Operating Profit : Match All
ConclusionsGrowth CorrectionPartial Model Tests with Historical InputsCyclical Nature not alleviated by
Cancellations or MothballingStandard SD Structures fit the industry
reasonably wellMore dynamics exist in the real system
Comments? Questions?