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7/31/2019 Aviation Case Study Ppt_2
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Demand and Revenue Management
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Flow of Presentation Revenuw
2
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Revenue Management What is Revenue Management
Why do Revenue Management
Pricing Optimization
Demand Modeling and Forecasting
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What is Revenue Management Management of inventory, distribution channels
and prices to maximize profit over the long run
Selling the right product to the right customer atthe right time at the right price
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What is Revenue Management Revenue Management involves the
following activities
Demand data collection
Demand modeling
Demand forecasting
Pricing optimization System implementation and distribution
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What is Revenue Management Airline industry
How many seats to make available at each of the listed
fares, depending on the OD pair, time of year, time ofweek, remaining seats available, remaining time until
departure
What contracts and prices to provide to corporations
How many seats to make available to consolidators andtravel agents (if at all), and at what prices
How much capacity to make available to cargo shippers
and freight forwarders, and at what prices
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What is Revenue Management Hotel industry
How much to charge for a room depending on
the location, type of room, time of year, time ofweek, duration of stay
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What is Revenue Management Ocean cargo industry
Which types of contracts to enter into with
shippers
How much capacity to commit to each shipper
Which contract prices to have for each shipper
How to vary prices as a function of direction oftrade, commodity, and time of year
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What is Revenue Management Car rental industry
How much to charge for a rental car depending
on the class of car, time of year, time of week,duration of rent
Restaurant industry
How much to charge for lunch vs dinner
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What is Revenue Management Manufacturing industry
Make-to-stock: dynamic pricing of inventory
Make-to-order: dynamic pricing of orders, howmuch discount to give for orders in advance
Make-to-stock and make-to-order: prices of
advance orders vs prices of inventory
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What is Revenue Management Retail industry
Example: fashion apparel industry
Products in fashion for a single season
Retailer wants to sell available inventory for
maximum profit
Prices higher at start of season Retailer has to decide when to mark prices
down, and by how much
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What is Revenue Management Entertainment ticket pricing
Example: opera houses let their ticket pricesdepend on The performance
The reviews received so far
Location of seat in opera house
Day of the week of the performance
Time of the day of the performance
Time of performance in the season
Remaining time until the performance
Number of remaining seats available
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What is Revenue Management Golf courses
Variable pricing: Choose prices to vary by
time of day day of week
season of year
Round duration control
control tee-time interval control uncertainty in arrival time
control uncertainty in duration
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Hospital Contract Case Study Major customers of hospitals
Insurance companies
Medicare Medicaid
Individuals
Hospital contracts with major customers
Discount-off-listed-charges contracts Per-diem contracts
Case-rate contracts
Capitation contracts
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Hospital Contract Case Study Example of setting per-diem rates
ICU Patient Length of Stay
0%
2%
4%
6%
8%
10%
12%
14%
16%
1 2 3 4 5 6 7 8 9 10 11 12 13 14
Number of Days
%o
fP
atients
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Hospital Contract Case Study Example of setting per-diem rates
Observe that most patients stay for only a few
days, although a few patients make the averagelength of stay quite high
Stratified per-diem rates Charge more per day to patients who stay for only a
few days Results
Higher average revenue
Lower standard deviation of revenue
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Hospital Contract Case Study Higher average revenue clearly beneficial to
the hospital
Lower standard deviation of revenue
Beneficial to the hospital?
Yes. More predictable revenue
Beneficial to the insurance company? Yes. More predictable costs
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What is Revenue Management Overbooking may be part of revenue management
Overbooking important practice in many
industries that use reservations, and wherecancellations or no-shows may occur airlines
hotels
car rental cruise lines
restaurants
contractors (construction etc)
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What is Revenue Management Overbooking
Important trade-off between opportunity cost of unused
resources if cancellations or no-shows cause resourcesto be wasted, and cost of oversales
In 1960s, Simon and Vickrey proposed the use of
auctions to allocate airline seats in case of oversales
Airlines rejected idea for many years Nowadays, reverse Dutch auctions are widely used to
allocate airline seats in case of oversales, and seem to
be widely accepted
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What is Revenue Management Dynamic pricing and the bullwhip effect
Dynamic pricing can increase demand
variability The case of Campbell Soup
Wild swings in demand and in shipments of chickennoodle soup from the manufacturer to distributors
and retail stores Increase in production, storage and logistics costs
Frequent stockouts resulting in lost sales
The culprit: Trade promotions!
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What is Revenue Management Dynamic pricing and the bullwhip effect
Dynamic pricing can be used to decrease demand
variability Peak load pricing: lower prices during off-peak times,
higher prices during peak times
Airlines
Hotels Golf courses
Electricity wholesale market
Oil/gasoline?
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Price Discrimination Revenue Management may involve price
discrimination, but it does not have to
P=130-QUnit cost = 10Firms profitsunder single price:
(130-Q-10)QP
q
MC=10
130
130
60
70
Consumer surplus=1800
Deadweight loss=1800
Firm profits=3600
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Price Discrimination (continued)P=130-QUnit cost = 10What if the firm
could segmentthe market andcharge twodifferent prices?
P
q
MC=10
130
130
80
90
Consumer surplus=1600
Deadweight loss=800
Firm profits=4800
50
40
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Price Discrimination (continued)
P
q
MC=10
130
130
80
110 Consumer surplus=1000
Deadweight loss=200
Firm profits=6000
90
40
70
50
30
20 60 100
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Price Discrimination (continued)Perfect pricediscrimination
P
q
MC=10
130
130
Consumer surplus=0
Deadweight loss=0
Firm profits=7200
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What is Revenue Management The same product sold at different times for different
prices is not necessarily price discrimination, because atdifferent times...
the production or distribution costs may be different inventory costs were incurred to keep the product in stock until a
later time
the product value may change over time, such as perishable ormaturing or seasonal products, fashion goods, antiques.
the remaining inventory may be different interest is earned if product is sold at an earlier time
consumers value products differently at different points in time
locking sales in early reduces uncertainty
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What is Revenue Management It is not spam
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Fairness and Legal Issues Depending on the industry, there may be legal
obstacles to revenue management
Examples Regulated prices of utilities (this is changing)
Prices in airline industry were regulated until 1978 -price and quantity changes had to be approved by CAB
Pricing in ocean cargo industry was regulated until1999 - carriers had to provide all shippers with thesame essential contract terms
Spot market pricing in ocean cargo industry is stillregulated - 30 days notice required for price increases
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Fairness and Legal Issues Golf course examples
Kimes and Wirtz survey results (1 = extremely
fair, 7 = extremely unfair) Time-of-day pricing: 3.41
Varying price (for example, as function of bookingson hand): 6.16
Two-for-one coupons for off-peak use: 1.80 Time-of-booking pricing: 5.12
Reservation fee/Charge for no-shows: 3.19
Tee-time interval pricing: 3.95
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Fairness and Legal Issues Amazon.com example
Fall 2000, Amazon conducted experiment to try todetermine price sensitivity of demand for DVDs
Discounts between 20% and 40% offered randomly
Customers who visited amazon.com multiple timesnoticed changing prices
Furious response by customers and press, suspecting
Amazon varied price by demographics Why are varying airline prices accepted by most, and
not varying DVD prices?
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Why do Revenue Management Success stories
American Airlines increased annual revenue with $500
million through revenue management Delta Airlines increased annual revenue with $300
million through revenue management
Marriott hotels increased annual revenue with $100
million through revenue management National Car Rental was saved from liquidation with
revenue management
Canadian Broadcasting Corporation increased revenue
with $1 million per week
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Why do Revenue Management Increasing competition
Fewer restriction on international trade
More efficient international transportation
Low cost foreign competitors
Competitors use revenue management
Use revenue management to stay on top
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Why do Revenue Management
At many companies, little cost-cutting juice can easily beextracted from operations. Pricing is therefore one of the fewuntapped levers to boost earnings, and companies that startnow will be in a good position to profit fully from the next
upturn. McKinsey Quarterly, 2003
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Revenue Management Optimization Control Methods
Resource Bucket Control Methods
Bid Price Control Methods
Dynamic Programming
Software
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Revenue Management Optimization Control Methods/Optimization Methods
Static Dynamic
Deterministic
StochasticLeg Based
OD based
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Revenue Management Optimization Resource Bucket Control Methods
If supply of different products are related, for exampleif different products use shared resources or capacity,
then revenue management should not be doneseparately for the different products
Also if demand for products are related, for examplecomplementary goods or substitutes
Examples Airlines: Itineraries with different origin-destination
pairs share the same flight legs (resource)
Hotels and rental cars: Multiple day bookings sharecapacity
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Revenue Management Optimization Bid price methods
Simple single-stage deterministic LP model
Input: Lines of flight (LOF)
The flights (legs/segments) each LOF traverses (flight-LOFincidence matrix A)
Fares f1,f2,,fkfor each LOF
Demand Dj for each LOF-fare combination j (not well-definednotion)
Capacity Qi of each flight (leg/segment) i
Primal decision variables: xj = number of seats allocated to LOF-fare combination j
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Revenue Management Optimization Dynamic programming
State of process: current bookings/seats available for each flight,competitor information
Transitions: take place through bookings and cancellations
Decisions: which prices/fares are quoted when booking requestsare received
Policy: decision for each state x and time t
Objective: determine optimal policy
Value function: expected value V(x,t) as function of state x and
time t Solving problem involves computing optimal value function
V*(x,t)
Another benefit: Optimal policy very simple:
accept booking request if fare > V*(x,t) - V*(x-1,t)
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Revenue Management Optimization Optimization Software Surveys
Fourer, R., Linear Programming, OR/MS Today, volume 32,number 3, pp. 46-55, June 2005,.
Nash, S. G., Nonlinear Programming, OR/MS Today, volume 25,number 3, pp. 36-45, June 1998,.
Grossman, T.A., Spreadsheet Add-Ins for OR/MS, OR/MSToday, volume 29, number 4, pp. 46-51, August 2002,.
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Revenue Management Optimization Decision Support Software Surveys
Aksoy, Y. and Derbez, A., Software Survey: Supply Chain Management, OR/MSToday, volume 30, number 3, pp. 34-41, June 2003,.
Buede, D., Decision Analysis Software Survey: Aiding Insight IV, OR/MS Today,
volume 25, number 4, pp. 56-64, August 1998.
Hall, R., Vehicle Routing Software Survey: On the Road to Recovery, OR/MSToday, volume 31, number 3, pp. 40-49, June 2004,.
Maxwell, D.T., Decision Analysis: Aiding Insight VII, OR/MS Today, volume 31,number 5, pp. 44-55, October 2004, .
Swain, J. J., 'Gaming' Reality: Biennial survey of discrete-event simulationsoftware tools, OR/MS Today, volume 32, number 6, pp. 44-55, December 2005,.
Swain, J. J., Power Tools for Visualization and Decision-Making, OR/MS Today,volume 28, number 1, pp. 52-53, February 2001.
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Demand Forecasting The first law of forecasting: The
forecast is always wrong
Sources of forecast error: Modeling error
Parameter error
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Demand Forecasting Modeling error
The basic form of the demand model is wrong
Example Suppose we want to forecast demand d as a function of
price p
The true demand function is d = exp(3-2p) / (1 + exp(3-2p))
We try to estimate a linear demand model d = a bp,with parameters a and b that are estimated with data
No matter what values we estimate for a and b, theestimated model is wrong modeling error
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Demand Forecasting Parameter error
The basic form of the demand model is correct,but we do not know the correct values of the
parameters Example
The true demand function is d = exp(3-2p) / (1 + exp(3-2p))
We try to estimate a demand model d = exp(a-bp) / (1+ exp(a-bp)), with parameters a and b that areestimated with data
If we estimate a=3 and b=2 (for example, with gooddata and a good statistical technique), then theestimated model is correct
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It is very important to understand and model
customer behavior accurately
Incorrect models of customer behavior canlead not only to suboptimal prices, but can
lead to the systematic deterioration of
models, prices, and profits over timethespiral-down effect
Demand Modeling
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Spiral-down effect in airline revenue management
For many years, airlines have used following simple
model of customer behavior
Some time before departure, customer requests a ticket in a
particular fare class
Airline accepts or rejects the request
Above model describes the way airline reservations
systems work
However, it does not accurately describe the way
customers behave
Demand Modeling
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Spiral-down effect in airline revenue
management
Low fare tickets and high fare tickets
Airlines set aside chosen number of seats for
high fare tickets
Airlines use observed sales to estimate thesupposed demand for high fare tickets
Demand Modeling
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Spiral-down effect in airline revenue management Spiral-down effect:
Airline allows some low fare sales
Some flexible customers (not modeled by the airlines) willingto buy high fare if that is the only option, now buy low faretickets
Airlines observe more low fare sales and less high fare salesdecrease their estimate of high fare demand
Airlines set aside fewer seats for high fare tickets, and allowmore low fare sales
More customers buy low fare tickets, and the spiral downcontinues
Spiral-down effect is the consequence of an incorrect
model of customer behavior
Demand Modeling
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Forecasting methods
Judgmental methods
Statistical forecasting methods
Demand Forecasting
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Judgmental forecasting methods
Expert opinion
Questionable: See the articles Armstrong, J.S., How Expert Are the Experts?,
Inc, pp.15-16, 1981
Armstrong, J.S., The Seer-Sucker Theory: The
Value of Experts in Forecasting, Technology
Review, pp.16-24, 1980
Consensus methods, such as Delphi technique
Demand Forecasting
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Statistical forecasting methods Non-causal methods
Exponential smoothing
Time series methods
Causal methods Linear regression
Nonlinear regression
Discrete choice models (logit, probit, etc) Whatever the method, the basic approach is to find
systematic behavior in data that one has reason tobelieve will continue in the future
Demand Forecasting
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Revenue Management Implementation Business case: assessment of
Revenue opportunity
Development and support personnel needs
Development cost
Maintenance cost
Hardware
Software DBMS
Forecasting
Optimization
Interfaces
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Revenue Management Implementation Distribution system
Communication network hardware
Interfaces with revenue managers Interfaces with customers
Management of customer awareness
and customer perceptions Management of organizational change
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