Airline Yield Management
Following deregulation of airline pricing in 1978, fare information
provided to travel agents became more extensive. Discount airlines
and dynamically adjusted pricing became a common response strategy.
Over time, the complexity and opaqueness of airline pricing has
increased, driving the need for Yield Management Systems
to ensure service profitability and airline economic viability.
Airline pricing is very challenging. Dynamic pricing, also known
as yield management or revenue management, is a set of pricing strategies
aimed at increasing profits by combining primary factors such as
multiple product characteristics and secondary impacts of those
For instance, once the first product expires [hotel rooms, airline
flights, or time-dated 'sell before' products], capacity is augmented
only at a relatively high marginal cost. This creates the potential
for very large movements in the opportunity cost of sale. The opportunity
cost of sale is a potential foregone subsequent sale.
The value of a unit in a shortage situation is the highest value
of an un-served customer. Forecasting this value given current sales
and available capacity represents dynamic pricing.
Yield management techniques can have a significant impact on airlines
amounting to hundreds of millions of dollars per year. This can
result from thousands of dynamic prices changes per day.
Other factors of yield management include:
- Damaged Good – such as stay-over restrictions
which facilitate static price discrimination
- Efficient Allocation - rather than the profit-maximizing
allocation. Many gains attributed to profit-maximization are actually
consequences of the dynamic efficiency.
- Selling Options - late arrivals may have significantly
higher value than early arrivals, suggesting the airline ought
to sell two kinds of tickets: a guaranteed use ticket and a ticket
that can be delayed at the airline’s request.
- Demand Pricing – including discrete prices,
time-dependent demand, overbooking, resupply and cancellations,
holding costs and discounting, and variable initial capacity.
- Customers willingness to pay - unknown when
they request a ticket.
- Capacity - time-dependent logistic equations
with maximum annual-sustainable yield. Seat inventory control
is especially complex in allocating seats in a multiple origin
and destination flight network.
- Time sensitivity - provides the option of re-stocking
at a unit cost.
Yield Management Strategies
There are a number of yield management strategies:
Revenue Maximisation - Most yield management solutions
focus on how to maximize revenue. However, this must be balanced
by long term customer lifetime value. If supporting a customer request
has a short term cost, the long term customer satisfaction component
will also pay back dividends in future sales.
Capacity Management - Rather than dynamically
changing prices to maximize revenue, some airlines ration capacity
with price classes to ensure that high-paying customers are served,
effectively implementing a mark-up policy based on remaining capacity
and, if seat allocation between classes is dynamically controlled,
This requires determination of:
- Demand and a fixed cost for creating each price class
- The optimal number of price classes
- The optimal number of capacity units [ hotel rooms] allocated
to each price class
- Optimal price at each class.
In doing so, one cannot assume that all low-fare customers will
arrive before high-fare customers, thereby forcing all high-fare
customers to pay their full acceptable price.
Demand Segmentation - controlled through sales
restrictions - such as advance purchasing, or minimum trip duration
for segmenting demand. Optimal restriction policies can be applied
to airline pricing, where leisure travelers’ relative price
elasticity compared to business travelers permits the efficient
use of restrictions.
Optimal pricing - under uncertain demand, increase
in value with the level of competition, meaning setting multiple
price levels on flights at different times can shift demand from
the higher-demand departure time to the alternate flight, even when
it is unknown which time is the peak.
Flight Network Management - In markets with competitive
and monopoly factors, high-fare customers may benefit from price
dispersion as well as low-fare customers. In multiple flight-leg
analysis, comprising of a network of multiple origins, one hub,
and one destination. Prices for each flight leg are distinct, and
demand at each origin is subject to a nested fare structure for
Analytics can find the optimal time thresholds for closing origin-hub
flights, then extend results to allow multiple fares on each origin-destination
flight and time-dependent demand.
Allocating seats in a flight network assumes a non-nested seat
allocation system, normally distributed random demand that is independent
between price levels, and a fixed number of fare classes. Considerations
must be made for varying demand on each day of the week, and airline
Analysing network-wide effects may increase revenue by 2-4%, but
only when the load factor is very high.
Marginal Revenue Management - Using a functional
form for demand as a common assumption, marginal revenue is price
minus a constant. A monopolist would choose to charge a price which
is marginal cost plus a constant. This feature of exponential demand
makes the solution to the monopoly problem reduce to the problem
of calculating marginal cost, a simpler problem.
Marginal revenue management is impacted by the arrival rate, requiring
the capability to detect the behavior of buyers when demand conditions
Peak-load pricing- impacts dynamic pricing. In
general, prices increase due to a correlation between high demand
and high prices.
Pricing To Sell Out - discounting to sell out
is commonly held as a bad strategy. In the hotel context, zero discounting
works as hotel bookings are made in advance but applies regardless
of payment not being made until the time one stays in the hotel.
The same discount factor is used for early or later bookings. With
airline tickets, generally payment is made at the time of booking,
not at the time of departure. The time intervals are long enough
for discounting to be significant, given the tickets may be booked
six months in advance.
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