Impacts Of Entry In Airline Markets Effects Of Revenue Management On Traditional Measures Of Airline Performance

ARTICLE IN PRESS

Journal of Air Transport Management 10 (2004) 259–270

Impacts of entry in airline markets: effects of revenue management on
traditional measures of airline performance
Thomas Gorin*, Peter Belobaba
International Center for Air Transportation, Massachusetts Institute of Technology, Cambridge, MA 02139, USA

Abstract
Assessment of unfair competitive practices in airline markets is typically based on the analysis of changes in aggregate measures of
airline performance, such as average fares, traffic and revenues. Simulation results show that these measures can be greatly affected
by the competitive revenue management situation. For example, average fares on the incumbent carrier can either increase or
decrease following entry by a new competitor, depending on whether one or both airlines perform revenue management.
Consequently, these measures on their own do not constitute a reliable indication of the response of incumbent carriers, and provide
even less information on their strategic intent, which is critical in identifying predation.
r 2004 Elsevier Ltd. All rights reserved.
Keywords: Revenue management; Low-fare airline entry; Airline pricing

1. Introduction
The more profitable days of the airline industry in the
late 1990s raised numerous questions regarding
the potential for unfair competition and predatory
pricing. In the US, American Airlines was criticized by
a number of its low-fare competitors (often referred to
as low-cost carriers or LCCs), and sued by the US
Department of Justice (United States of America vs.
American Airlines, 2001), while the Competition Tribunal in Canada attempted to determine whether Air
Canada competed unfairly against CanJet (Competition
Tribunal, 2000) and WestJet (Competition Tribunal,
2001). A large number of studies focused on market

changes brought about by low-cost carriers and
described their effect on fares and traffic. In 1998,
the United States Department of Transportation
(US Department of Transportation, 1998) proposed a
policy attempting to identify predatory practices based
on high-level market measures. Other studies of the
potential for predatory pricing in airline markets include
the work of Dodgson et al. (1991) for the European
Commission.

*Corresponding author.
Email-addresses: (T. Gorin),
(P. Belobaba).
0969-6997/$ - see front matter r 2004 Elsevier Ltd. All rights reserved.
doi:10.1016/j.jairtraman.2004.03.002

Here, the effect of airline revenue management on
traditional measures of airline market performance and its
importance in understanding the dynamics of airline
markets, in particular with respect to competition issues is
explored. It is demonstrated through simulation of a single
market scenario, that even when the incumbent carriers do
not respond to entry other than by matching the lowest
available fare in the market, aggregate measures (such as
average fares, revenues, loads and market share) change
with the competitive revenue management situation and
the entrant’s capacity. As a result, such measures do not
constitute a reliable indication of the response of
incumbent carriers, and provide even less information
on the strategic intent of the incumbent carriers, which is

critical in identifying predation.
Simulation confirms previous findings that under a
realistic representation of competition, average market
fares generally decrease following entry, while traffic
increases. For the nonstop incumbent carrier, however,
we show that average fares, traffic and revenues behave
very differently as a function of the competitive revenue
management situation (that is, whether the incumbents
and/or the low-fare new entrant perform revenue
management), as well as new entrant capacity. The
results indicate that even airline-specific average fares,
traffic and revenues provide a very incomplete picture of
the effects of entry in a market, contrary to the
suggestions of previous researchers.


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T. Gorin, P. Belobaba / Journal of Air Transport Management 10 (2004) 259–270

2. Literature review
In 1958, McGee (1958) argued that price predation
was often an unprofitable business strategy and concluded that it would be unlikely to occur except under
unusual market conditions, such as legal barriers to
mergers and acquisitions. Areeda and Turner (1975,
1976, 1978) claimed that pricing at or above average
total cost could not be considered predatory and
designed a test of predatory behavior, based on
marginal cost. In 1977, Williamson (1977) suggested a

short-term output-maximizing rule as an alternative to
Areeda and Turner’s marginal cost test. Baumol (1979),
Joskow and Klevorick (1979), and others also discussed
predatory pricing in its more general economic setting
and proposed tests or rules for evaluating whether a
pricing strategy is predatory. Most of the research on
predation thus focuses on the comparison of revenues
and costs, and the discussion among authors centers on
the correct way to measure the appropriateness of a
pricing strategy by an incumbent.
Research on entry into airline markets has focused
mostly on the effects of entry on traffic and fares. While
many of these studies indicated a growing concern with
respect to unfair competition and predatory pricing, few
of these research efforts focused on identifying and
understanding the dynamics of airline markets, and how
they affect competition. For instance, Bailey et al.
(1985), Morrison and Winston (1990), Windle and
Dresner (1995), Perry (1995), and Oster and Strong
(2001) all examined the impact of entry on average fares
and traffic, distinguishing between entry by a low-fare
carrier and a network carrier, and touch upon the issue
of predation. Perry, in particular, concludes that the
typical impact of entry, at the local market level, is an
increase in total traffic, a decrease in average market
fare, and an increase in total market revenues. For the
incumbent carriers, this translates into a decrease in
average fare, a decrease in its revenues (as the LCC
increases its own revenues) and an increase in its local
traffic. Dodgson et al. (1991) provide a definition of

predatory practices in the airline industry and concepts
of relevance in identifying these practices. In addition,
they highlight the irrelevance of cost-based tests of
predation in airline markets.
Baumol (1982), Baumol et al. (1983), Bailey and
Baumol (1984), Hurdle et al. (1989), Whinston and
Collins (1992) focus on the contestability of airline
markets and how it might affect competition in the
airline industry, but conclude that the hypothesis of
contestability is inappropriate. Thus, past efforts to
investigate competitive behavior in airline markets have
involved almost exclusively the analysis of aggregate
market measures of average fares and traffic to evaluate
the response and intent of incumbent carriers. Overall,
none of these studies have provided a satisfactory

method to evaluate the possibility of predation, given
the dynamics of airline networks and revenue management. More importantly, none of the previous research
has attempted to estimate the impact of airline revenue
management on incumbent performance after entry.

3. Approach
The approach used to examine the effects of revenue
management and new entrant capacity on airline
markets is based on simulation. Simulation presents
the advantage of allowing for the representation of a
dynamic competitive airline market where passenger
choice and revenue management controls applied by the
airlines are represented. Analytical models tend to be
limited to static observations that overlook the complexity of airline pricing, scheduling and revenue management processes, not to mention the intricacies of

modeling demand, booking behaviors, forecasting, and
competitive airline interactions. For example, in the case
of n flight legs with k fare classes per flight leg, with a
booking period of 360 days, revenue management
optimization involves in the order of nk optimizations
per time period within the booking horizon. This does
not account for multiple frequencies within a market. In
short, even in a single market case, the number of steps
required in an analytical model quickly makes it
intractable. In addition, the simplifications required to
manage such analytical representations inevitably lead
to inconclusive findings.
Rather than oversimplifying, the Passenger Origin
Destination Simulator (PODS), a simulator of a
competitive airline network, is used.1 To illustrate the
impacts of entry, a single market network is simulated,
with a set of competing airlines offering service in this
market. Initially there are two incumbent carriers,
Airline 1 offering nonstop service, and Airline 2 offering
connecting service. The new entrant carrier (Airline 3)
then comes in with a schedule identical to that of the
nonstop incumbent carrier and with different aircraft
capacity levels.
In the simulations, it is assumed that the market does
not structurally change after entry. For example, we
assume that conditional passenger preference towards
any particular airline remains unchanged by entry:
Given that the passenger does not choose to travel on
Airline 3, his/her preference between airlines 1 and 2 is
1

Abundant literature is available on PODS, including a detailed
description of the underlying algorithms (Hopperstad, 2000), general
discussions of the structure of PODS by Belobaba and Wilson (1997)
and Lee (1998), an explanation of the forecasting models used in
PODS by Zickus (1998) and Skwarek (1996), and a validation of the
passenger choice model by Carrier (2003). In all these references,
various revenue management methods used by airlines are also
described.


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the same as his/her preference when there are only
airlines 1 and 2 operating in the market. Similarly, we
assume that total potential demand remains a function
of price, as governed by the existing price–demand curve
in the market, irrespective of the number of competitors
in the market. While these assumptions are not overly
restrictive, it may be argued that low-fare entry has a
structural effect on the market. For tractability reasons,
and since there is little evidence of this in the literature,
structural change is not modeled.
In these simulations, airlines operate in a short-haul
market (283 miles) with a total maximum potential
demand of 165 one-way passengers per day at the
current lowest available fare level of $63. Of this
passenger demand, 35% is business oriented and the
remaining 65% is leisure demand. The difference
between leisure and business passengers resides in

business passengers’ willingness to pay a higher fare,
greater sensitivity to fare restrictions, and later booking
behavior. Fig. 1 shows the price–demand curves of
leisure and business passengers in the market, and the
potential for leisure demand stimulation at fares below
the current lowest fare of $63.
Two competitive scenarios are simulated to allow
comparisons ‘before’ and ‘after’ new entry into an
airline market. In the base case, two incumbent airlines
compete, one of which offers only nonstop service in the
market while its competitor offers only connecting
service. In the second scenario, we add a third
carrier—the new entrant—which then also offers nonstop service in this market, and competes with both
incumbents but more directly with the nonstop incumbent carrier.
The purpose of Airline 2—the connecting incumbent
carrier—is to act as a ‘relief valve’ for the excess market
demand and to allow passengers to have an alternative
to the nonstop carrier. Airline 2 thus represents all the
connecting alternatives available to passengers in a more

200
180
160

Business
Leisure

Demand

140

120
100
80
60
40
20
0
$50

$100

$150

$200
Fare

$250

$300

Fig. 1. Price–demand curves in PODS for the simulated market.

261

realistic market. As a result, we assume that Airline 2
offers a large capacity relative to demand in this market
(identical to that of the nonstop incumbent carrier),
even though its connecting flight options (paths) are far
less desirable than those of Airline 1. The loads,
revenues and overall performance of Airline 2 are

therefore not of particular interest in this discussion.
From here on, we thus refer to the nonstop incumbent
simply as the incumbent carrier.
3.1. Base case: no entrant competition
Without new entrant competition, the market is
served by two competing incumbent carriers, each
offering three daily departures. Airline 1 offers three
daily nonstop flights while its competitor offers three
connecting flights, each with 30 seats on each flight, for a
total of 90 seats per day in the market for each carrier.
Table 1 summarizes the frequency, capacity and baseline
pricing of the incumbent carriers.
All other characteristics are exactly the same for both
airlines. There is no passenger preference for either
airline, other than the preference induced by path
quality (nonstop vs. connecting paths). With identical
fare levels and restrictions for each fare product, the
only difference between the two competitors is therefore
the fact that one carrier offers nonstop service while its
competitor offers connecting service, as shown in Fig. 2.
As a result of the connecting service, total travel times
(origin to destination, including connecting time) are
greater on Airline 2, which affects passenger choice in
the simulation.
The baseline prices for each fare class are set as shown
in Table 2, along with the restrictions associated with
each individual fare class in this baseline scenario. Y
class is the unrestricted fare class in the market; while B,
M and Q classes are increasingly restricted. The more
restrictive the fare class in terms of advance purchase

requirements and restrictions (roundtrip, Saturday night
stay, and nonrefundability requirements), the cheaper
the associated fare. We refer to this fare structure as the
standard fare structure.
As described in the literature on PODS, these fare
settings lead to a higher relative utility of higher fare
classes (Y and B) for business passengers, and conversely, a greater relative utility of lower fare classes
(M and Q) for leisure passengers.
Finally, since the purpose is in part to examine the
impact of revenue management on ‘traditional’ measures of incumbent performance, we allow the incumbent carriers to either accept requests for seats on a firstcome, first-serve basis (FCFS), or to use Fare Class
Revenue Management (FCRM). In the case of FCFS
seat request acceptance, passengers book seats in a
FCFS manner, and the only controls that enable airlines
to differentiate between fare products are advance


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T. Gorin, P. Belobaba / Journal of Air Transport Management 10 (2004) 259–270

262

Table 1
Capacity, frequency and pricing overview without entrant competition
Carrier

Capacity

Frequency

Pricing

Airline 1
Airline 2

90 seats (3 Â 30)
90 seats (3 Â 30)

Three daily flights
Three daily flights

Four fare classes with four different fare levels
Y, B, M and Q (see Table 2)

Table 3
Two-tier fare structure details (new entrant carrier)

Airline 1
Origin
Destination

Fare
class

Fare

Airline 2
Airline 2

Y
M

Hub H2

$135
$53

Restrictions
Roundtrip
requirement

Saturday
night stay

Nonrefundable Advance
purchase

No
Yes

No
Yes

No
No

No
14 days

Fig. 2. Single market network with two competing carriers.

Table 2
Fare classes, associated fares and restrictions for the standard fare
structure in the base case scenario
Fare
class

Y
B
M
Q

Fare

$261
$135
$92
$63

Restrictions
Roundtrip
requirement

Saturday
night stay

Nonrefundable Advance
purchase

No
Yes

Yes
Yes

No
No
Yes
Yes

No
No
No
Yes

No
7 days
14 days
21 days

purchase requirements that effectively close down a fare
class beyond a given deadline, or restrictions that have
an impact on the passengers’ buying decision.
In the case of FCRM, a combination of Booking
Curve detruncation, Pick-up forecasting, and Expected
Marginal Seat Revenue algorithm (Belobaba, 1987,
1992), is used (see Gorin, 2000). Under Fare Class
Revenue Management, advance purchase requirements
and restrictions still apply, and are reinforced by
revenue management controls to protect seats for
later-booking high-fare passengers, in turn limiting seats
made available to early-booking low-fare passengers. In

the remainder of the paper, Fare Class Revenue
Management is referred to simply as Revenue Management (RM), as opposed to FCFS acceptance of seat
requests.
3.2. New entrant scenario
Upon entry, the new entrant carrier offers three daily
nonstop flights scheduled at the exact same times as the
nonstop incumbent carrier’s flights (Airline 1). The
nonstop incumbent’s schedule is mirrored to eliminate
the effect of schedule preference on passenger choice. In

this scenario, passengers now have the option of flying
on the nonstop incumbent carrier, its nonstop new
entrant competitor, or the connecting incumbent carrier.
The new entrant offers a two-tier fare structure as
follows (Table 3):
1. Fully unrestricted Y class fare set at $135 (the same
fare as the B class fare on the incumbent carrier in the
base case), approximately 48% lower than the
previous Y fare.
2. Restricted M class fare (roundtrip and Saturday night
stay requirements with 14 days advance purchase)
priced $10 below the base case Q fare on the
incumbent, at $53.
This two-tier fare structure is based on the observation that low-fare new entrants typically offer a
simplified fare structure compared to incumbents. The
notion of simplification does not necessarily involve the
removal of all restrictions and advance purchase
requirements, but rather a decrease in the number of
fare classes offered, and consequently in the complexity
of the fare structure. In addition, low-fare new entrants

typically offer substantially lower fares relative to the
incumbents’ standard fare structure.
To test the effect of the entrant’s capacity on market
performance, various capacity levels offered by the new
entrant on its three daily flights were simulated. New
entrant capacity ranges between 15 and 50 seats per
flight, with intermediate capacity settings of 25 and 30
seats.
Finally, the new entrant carrier either accepts seat
requests on a FCFS basis, or use RM. In most of the
simulations presented here, we assumed that all competitors use the same revenue management system (or lack
thereof).
Upon entry, we assume that the incumbents do not
fully match the entrant’s fare structure. Nonetheless, it
would be unrealistic to presume that the incumbent


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T. Gorin, P. Belobaba / Journal of Air Transport Management 10 (2004) 259–270

carriers would let the entrant offer a lower fare than
their lowest available fare. We therefore model an
observed limited incumbent fare response in which the
incumbents match the lowest fare of the new entrant in
their most restrictive fare class. As a result, the
incumbent carriers are offering a fare of $53 in their Q
class, which is more restrictive than the M class fare
offered on the new entrant carrier at the same price.
Table 4 summarizes the type of service, frequency,
capacity, fares and revenue management approach of

each carrier in the competitive case.

4. Results
4.1. Impact of entry on market-level measures
Table 5 shows the effect of increasing new entrant
capacity on traffic, revenues and average fares for the
total market. It also shows the effect of revenue
management on each of the above-mentioned measures.
As new entrant capacity increases, total traffic
increases in all cases, total market revenues increase
(even though they initially decrease slightly following
entry in the case of RM), and average fares decrease.
The effects of increasing entrant capacity on these
traditional measures of airline performance are thus
relatively straightforward, and in line with previous
studies. It also appears that the initial effect of entry is

263

far greater than the effect of increasing new entrant
capacity.
Competitive revenue management settings do not
appear to significantly affect the relative impact of entry
on total traffic, as shown in Table 5. Total market
revenues and average fares, however, are affected quite
differently by the competitive revenue management
situation. In the case of entry without revenue management (by all carriers), total market revenues increase by
as much as 13% at 150 seats on the new entrant, and
increase with new entrant capacity. Comparatively,
when all carriers use RM, Table 5 shows that total

market revenues initially decrease slightly with entry,
but increase slowly as new entrant capacity increases. In
the case of RM, total market revenues remain below
baseline revenues (without a new entrant). In addition,
while pre-entry revenues were higher in the case of RM
than with FCFS, post-entry revenues are actually lower
in the case of RM at all entrant capacity levels tested.
We explain these results in Section 5, and show that they
are highly dependent on the assumption that the
incumbent carriers do not match the new entrant’s fare
structure.
While average fares decrease in both cases (whether
airlines are using FCFS or RM), the magnitude of the
decrease is greater in the case of RM. In addition, postentry average fares are generally lower when all carriers
use RM than when they accept seat requests on a FCFS
basis.

Table 4
Competitive case summary
Competitive case

Airline 1
Airline 2
Airline 3 (New entrant)

Service

Nonstop
Connecting
Nonstop

Frequency & capacity

3 Â 30
3 Â 30
3 Â 15–25–30 or 50

Fares by fare class

Revenue management

Y

B

M

Q

$261
$261
$135

$135
$135
n/a

$92
$92
$53

$53
$53
n/a

FCFS or FCRM
FCFS or FCRM
FCFS or FCRM

Table 5
Absolute and relative impact of entry on average market fare, revenues and traffic, as a function of entrant capacity and competitive revenue
management settings
Total market

Traffic

Revenues

Average fare

FCFS

FCRM

FCFS

FCRM

FCFS

FCRM

Absolute

No entrant
3 Â 15
3 Â 25
3 Â 30
3 Â 50

126
172
179
182
191

122
163
178
182
190

$15,205
$15,699
$16,639
$16,919
$17,232

$15,914
$15,237

$15,247
$15,420
$15,775

$121.15
$91.37
$92.88
$93.01
$90.32

$130.04
$93.52
$85.85
$84.93
$82.85

Relative to no entrant

3 Â 15
3 Â 25
3 Â 30
3 Â 50

37%
43%
45%
52%

33%
45%

48%
56%

3%
9%
11%
13%

À4%
À4%
À3%
À1%

À25%
À23%
À23%
À25%

À28%
À34%
À35%
À36%


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264

These results can be explained by looking more

closely at the impacts of entry on each carrier. The
greater relative (and absolute) decrease in total market
revenues and average fares in the case where all carriers
use RM is a direct consequence of the combination of all
carriers using RM with the incumbents not matching the
entrant’s fare structure. In particular, the new entrant is
now able to forecast, and thus protect seats for, latebooking high-fare demand. Combined with the fact that
the new entrant offers lower fares than the incumbent in
equivalently restricted fare classes, this leads to substantial revenue dilution at the market level (from the
incumbent carriers), causing the observed decrease in
market revenues and average fare, as shown in Table 5.
Fig. 3 shows the impact of revenue management on the
mix of passengers on the incumbent and new entrant
carrier, and illustrates that revenue management allows

Fig. 3. Passenger distribution by fare class on the incumbent and new
entrant, as a function of the competitive revenue management
situation, and at 3 Â 30 seats on the new entrant.

the new entrant to increase loads in its higher fare class
(Y class). It also shows that revenue management leads
to an increase in unrestricted fare traffic (combined Y
and B class loads) at the total market level. Because the
higher fare class passengers on the new entrant actually
pay lower fares than they did on the nonstop incumbent,
overall market revenues and average fares decrease.
4.2. Impact of revenue management and new entrant
capacity on traditional measures of incumbent
performance
Table 6 summarizes the average fare, traffic, revenues,

and market and revenue share on the incumbent carrier
as a function of entrant capacity and competitive
revenue management settings. It shows that now, all
three aggregate measures of incumbent performance
(traffic, revenues and average fare) are affected very
differently by entry as a function of the competitive
revenue management situation. Comparatively, the
entrant’s capacity has a smaller impact.
The entrant’s capacity does nonetheless have some
impact on incumbent performance. When all carriers
accept requests for seats in a FCFS manner, the effects
on traffic, revenues and average fares are consistent with
usual expectations in the case of a limited response to
entry: Incumbent traffic and revenues decrease, while its
average fare increases (after initially decreasing due to
the lower Q fare after entry), with increasing new
entrant capacity. In the case of RM, the effect is far less
intuitive: Incumbent traffic decreases, but the relative
decrease is lower at intermediate new entrant capacity.
Similarly, the average fare also decreases, but to a
greater extent at intermediate new entrant capacity.
Revenues, on the other hand, behave more intuitively
and decrease with increasing new entrant capacity.
These intuitive—and less intuitive—results are actually
a consequence of the competitive revenue management

Table 6
Absolute and relative impact of entry on incumbent average fare, revenues and traffic, as a function of entrant capacity and competitive revenue
management settings
Airline 1

Traffic

Revenues

Average fare

Market share

Revenue share

FCFS

FCRM

FCFS

FCRM

FCFS

FCRM

FCFS
(%)

FCRM
(%)

FCFS

(%)

FCRM
(%)

67
47
40
37
22

61
34
36
34
22

56
44
42
41
34

75
41
31
30
21

Absolute

No entrant
3 Â 15
3 Â 25
3 Â 30
3 Â 50

84
80
72
67
43

75
56
64
61
42

$8,490
$6,923
$6,982
$6,925
$5,877

$12,003
$6,197
$4,794
$4,559
$3,370

$101
$86
$97
$103
$138

$160
$112
$75
$75
$80

Relative to no entrant

3 Â 15
3 Â 25
3 Â 30
3 Â 50

À4%
À14%
À20%
À49%

À26%
À15%
À19%
À43%

À18%
À18%
À18%
À31%

À48%
À60%
À62%
À72%

À15%
À4%
2%
36%

À30%
À53%
À53%
À50%


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Fig. 4. Incumbent revenues and average fares as a function of
competitive revenue management settings and new entrant capacity.

setting (combined with the limited fare match on the
part of the incumbent carriers). Fig. 4 illustrates the
differences in revenues and average fare on the incumbent carrier as a function of the competitive revenue

management situation and the new entrant’s capacity.
When airlines accept passenger requests on a FCFS
basis, incumbent traffic decreases with increasing new
entrant capacity, by up to 49% at high new entrant
capacity (150 seats). By adding capacity in the market at
fares that are relatively more attractive, the new entrant
is able to divert much of the incumbent’s former traffic.
Capacity constraints combined with demand stimulation limit the incumbent’s loss of passengers at low
entrant capacity levels. As capacity increases on the new
entrant, diversion also increases, hence the increasing
losses in traffic on the incumbent carrier. The fact that
none of the carriers practice revenue management then
affects the average fare on the incumbent carrier: Since
leisure passengers book first and airlines accept passenger requests on a FCFS basis, it is consequently not
surprising that the first passengers to be diverted from
the incumbent carrier are leisure passengers. The new
entrant carrier accepts bookings from the bottom up,
and thus starts with low-fare traffic, which frees up
capacity on the incumbent carrier.
The joint effect of demand stimulation (achieved
through the lower Q fare) and diversion of traffic to the
new entrant leads to a decrease in high-fare class (Y, B
and M) loads, but a slight increase in Q class loads on
the incumbent carrier when the new entrant comes in at
low capacity, as shown in Fig. 5. This leads to a decrease
in the average fare on the incumbent carrier. As new
entrant capacity increases, more of the low-fare traffic is
able to book the less restricted (but equally cheap) fare
on the new entrant, thus freeing capacity on the
incumbent. This leads to an increase in Y class bookings

on the incumbent (since seats are more likely to remain

265

Fig. 5. Incumbent loads by fare class as a function of entrant capacity
and with FCFS on all carriers.

available on the incumbent in this FCFS acceptance of
seat requests scheme), and accordingly an increase in the
average fare on the incumbent carrier.
The ensuing effect on revenues is initially a moderate
decrease (À18%) followed by a greater decrease as the
new entrant diverts more and more traffic from the
incumbent carrier, mostly from lower fares, to an extent
that cannot be compensated by the increase in Y class
bookings. Note that there is little competition between
the new entrant’s unrestricted fare class and that of the
incumbent carriers. Indeed, given the more attractive
fare structure on the new entrant, and the fact that seat
requests are accommodated on a FCFS basis, early
booking, low-fare passengers will overwhelmingly
choose to travel on the new entrant, and thus fill up
its capacity. This leaves the incumbents to share the
remainder of the demand, namely, the late-booking,
high-fare passengers. With even larger (greater than
total leisure demand) new entrant capacity, however, we
would have started to observe diversion from the
incumbent’s higher fare classes to the new entrant.
When all carriers use RM, the incumbent carrier loses
relatively more traffic at extreme levels of entrant

capacity (3 Â 15 and 3 Â 50) and relatively less traffic
at intermediate levels of entrant capacity (3 Â 25 or
3 Â 30). The traffic recovery at intermediate levels of
entrant capacity is a direct consequence of the incumbent’s use of revenue management. As shown in Fig. 6,
the incumbent carrier initially loses traffic in all fare
classes except the lowest class (Q), in which its loads
increase because of low-fare demand stimulation,
making up for some of the loss of higher-class revenues.
When new entrant capacity further increases to 3 Â 25
and 3 Â 30, the incumbent recovers some traffic, but in
the lowest fare class only. In both cases, the revenue
management system evaluates the trade-off between
carrying more passengers in lower fare classes at the


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expense of high-fare traffic, which has become less likely
to materialize on the incumbent, and thus opens the
availability of lower fare classes. This leads to an
increase in loads, but a decrease in overall revenues on
the incumbent.
As new entrant capacity keeps increasing, diversion
from the incumbent to the new entrant increases further,
and loads decrease on the incumbent in all fare classes
(including the lowest fare class). In addition, the fact
that the new entrant also practices revenue management

has an impact on the mix of traffic losses on the
incumbent: The new entrant is now able to forecast latebooking high-fare passengers, and thus protect seats for
these passengers. At the time of booking, these
passengers are now faced with a choice between airlines
1 and 3, and are more likely to choose Airline 3’s lower
fares (with comparable restrictions and advance purchase requirements) over those of Airline 1. This has the

Fig. 6. Incumbent loads by fare class as a function of entrant capacity
and with FCRM on all carriers.

effect of diverting passengers from all fare classes on the
incumbent carrier—a substantial difference from the
FCFS case where the new entrant only diverted early
booking (thus low-fare) passengers until it ran out of
seats to sell.
This behavior has a direct negative effect on the
incumbent’s average fare: It decreases sharply following
entry, by as much as 53%, as its traffic shifts towards
lower fare classes. The decrease in Q class loads on the
incumbent carrier also has the effect of leading to a
slight recovery in the incumbent’s average fare as the
new entrant’s capacity becomes very large (150 seats).
More passengers get diverted from the incumbent, and
in particular from Q class, hence the increase in average
fare. Entry also leads to a decrease in incumbent
revenues ranging from 48% of pre-entry revenues to
as much as 72% of pre-entry revenues at high entrant
capacity. In addition, the contribution of Y class to total
incumbent revenues shifts from over 66% of revenues
without a new entrant to about 38% when the new

entrant offers 150 seats in the market.
Fig. 7 illustrates the effect of entry on incumbent traffic
and the diversion from the incumbent to the new entrant
carrier, which is responsible for the variations in revenues
and average fares described previously. In particular,
Fig. 7 shows how pre-entry traffic on the incumbent gets
re-distributed when passengers are offered additional
competitive service by the new entrant.
Tables 5 and 6 also show the effect of revenue
management on average fares, traffic, revenues, and
revenue and market share as new entrant capacity
varies. Such a comparison shows that revenue management has a substantial impact on relative changes in
revenues, fares, traffic and revenue shares upon entry. In
particular, it appears that when all carriers use RM,
relative decreases in total average market fares, and
increases in total traffic, are greater than without

Fig. 7. Effect of entry on incumbent loads and diversion from incumbent to entrant at 3 Â 30 capacity on entrant.


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T. Gorin, P. Belobaba / Journal of Air Transport Management 10 (2004) 259–270

revenue management, while in fact the actual response
of the incumbent carriers was identical in both cases
(Table 5).
Similar conclusions can be drawn at the incumbent
carrier level. Table 6 shows, for example, that when the
entrant comes in with 90 seats per day, the relative
decrease in revenues on the incumbent is 18% in the case

of FCFS, or 62% in the case of RM. The incumbent’s
average fare in the case of FCFS increases by 2% while
it decreases by 53% in the case of RM. A naive
comparison of the case of entry when all carriers
allocate seats on a FCFS basis with the case where all
carriers use revenue management could lead to the
conclusion that the response of the incumbent carrier
was far more aggressive in the latter case. However, the
response was identical—the incumbent effectively did
not match the new entrant’s fare structure.

5. Performance of RM relative to FCFS, on the
incumbent carrier
As discussed in Section 4.2, and as shown in Table 6,
the absolute and relative impacts of entry on the
incumbent carriers are much more dramatic in the case
of RM, relative to that of FCFS acceptance of seat
requests. It is important to stress here that these results
by no means imply that RM negatively impacts the
revenues of the airline using it. Rather, we show in the
following paragraphs that the incumbent carrier does in
fact gain from using revenue management—compared
to where it would accommodate requests for seats on a
FCFS basis. The apparent greater impact of entry on
incumbent revenues is a combination of the effect of all
carriers using RM and lower fares on the new entrant
carrier diverting high-fare traffic from the incumbent
carrier.
5.1. Incumbent revenue gains from fare class revenue
management

Table 7 shows Airline 1’s traffic, revenues, average
fare and market and revenue share, as a function of new

267

entrant capacity, in the case where only the new entrant
uses revenue management while the incumbent carriers
use FCFS (labeled FCFS vs. FCRM), and where all
carriers use RM (labeled FCRM All).
Airline 1 benefits from using RM as opposed to
FCFS, given that the new entrant carrier uses RM. The
relative increase in revenues from using RM decreases
with increasing new entrant capacity, as the excess
capacity on the new entrant still leads to revenue
dilution. Nonetheless, relative revenue gains attributable
to RM over FCFS for the incumbent vary from 27% at
low entrant capacity (3 Â 15), to 6% when the new
entrant has a very high capacity.
By comparison, loads are lower on the nonstop
incumbent carrier in the case where all carriers use RM
than when the incumbents are using FCFS. Once again,
this is a consequence of the fact that all carriers protect
seats for late-booking passengers, and thus spill lowfare, early-booking passengers when they use RM.
Average fares, however, are much higher (up to
+90% on the incumbent carrier at a capacity of
3 Â 15 on the new entrant carrier) when all carriers use
RM, as the mix of passengers includes more high-fare
customers.
Therefore, RM brings revenue gains to the incumbent
carrier, as would be expected. In the previous simulation

results, it is the fact that the new entrant is also using
revenue management in conjunction with a two-tier fare
structure (not matched by the incumbents) that leads to
lower incumbent revenues than in the case where none
of the carriers apply revenue management.
These results show that upon entry, it is not revenue
management that is responsible for the decrease in
revenues on the incumbent carrier, but rather the
combination of revenue management, differentiated
products, and lower fares on the new entrant that lead
to a change in traffic mix by fare class, and a decrease in
Airline 1’s revenues. When the incumbent carriers switch
to revenue management, their revenues increase compared to the case where only the new entrant carrier uses
revenue management. Finally, the new entrant’s revenues increase as it begins to use RM as opposed to FCFS
(against FCFS on the incumbents), as shown in Table 8.

Table 7
Airline 1 traffic, revenues, average fares and market and revenue share as a function of the revenue management situation
Airline 1

No entrant
3 Â 15
3 Â 25
3 Â 30
3 Â 50

Traffic

Revenues

Average fare

Market share

Revenue share

FCFS vs.
FCRM

FCRM All

FCFS vs.
FCRM

FCRM All

FCFS vs.
FCRM

FCRM All

FCFS vs.
FCRM

FCRM All

FCFS vs.
FCRM

FCRM All

84
82
77
72
47

75
56
64
61
42

$8,490
$4,862
$4,421
$4,250
$3,173

$12,003
$6,197
$4,794
$4,559
$3,370

$101.11
$58.94
$57.28
$58.62
$68.11

$160.07
$111.62
$74.94
$74.68
$79.54

67%
48%
43%
40%
24%

61%
34%
36%
34%
22%

56%
31%
27%
25%
18%

75%
41%
31%
30%
21%

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268

Table 8
Airline 3 traffic, average fares and revenues
Airline 3

3 Â 15
3 Â 25
3 Â 30
3 Â 50

Traffic

Average fare

Revenues

FCFS All

FCFS vs. FCRM

FCFS All

FCFS vs. FCRM

FCFS All

FCFS vs. FCRM

45
74
88
139

41
66
80
133

$66.53
$67.23
$67.55
$69.67

$132.78
$115.12
$104.43
$85.39

$2,969
$4,949
$5,925
$9,674

$5,412

$7,606
$8,395
$11,372

Table 9
Incumbent traffic, revenues and average fares under revenue management as a function of whether the incumbents match the new entrant’s two-tier
fare structure
Airline 1

Traffic

Absolute

No Entrant
3 Â 15
3 Â 25
3 Â 30
3 Â 50

Rel. to limited match

3 Â 15
3 Â 25
3 Â 30
3 Â 50

Revenues

Average fare

Limited match

Full match

Limited match

Full match

Limited match

Full match

75
56
64
61
42

75
79
78
78
76

$12,003
$6,197
$4,794
$4,559
$3,370

$12,003
$6,707
$6,388
$6,300
$6,149

$160.07
$111.62
$74.94
$74.68
$79.54

$160.07
$84.39
$81.63
$81.18
$80.51

43%
22%
27%
80%

Revenue management therefore increases airline revenues, and it is the new entrant’s pricing structure which is
primarily responsible for the decrease in revenues on
Airline 1.
5.2. Incumbent performance under revenue management
when it matches the new entrant’s two-tier fare structure
Table 9 shows the nonstop incumbent’s traffic,
revenues and average fares when incumbents match

the new entrant’s two-tier fare structure, under the
assumption that all carriers use revenue management.
The incumbent’s revenues increase by as much as 82%
over the case where it does not match the new entrant’s
fare structure (at 3 Â 50 seats on the new entrant
carrier). The reason for this dramatic increase in
revenues lies in the impact of matching the new entrant’s
two-tier fare structure on incumbent loads, and the
distribution of this traffic between fare classes. Table 9
shows that the average fare on the incumbent carrier
actually increases when it matches the new entrant’s
lower fares. The incumbent’s passengers, on average,
now generate more revenues than when the incumbents
maintained their traditional fare structure and did not
fully match the new entrant. The only exception arises at
low entrant capacity, where in this case the nonstop
incumbent’s average fare decreases, but revenue increases nonetheless. In this case, the large increase in

8%
33%
38%
82%

À24%
9%
9%
1%

loads offsets the decrease in average fare, leading to an
increase in revenues.

Table 9 shows that incumbent performance, when it
uses revenue management, is highly dependent on the
incumbent’s fare structure relative to that of the new
entrant. As mentioned, the apparently poorer revenue
performance of the incumbent carrier in the case where
it uses revenue management but does not match the new
entrant’s fare structure, is mostly caused by the
difference in fare structure between carriers.

6. Conclusions
The simulations show that even with a minimal
response by incumbents to new entry—consisting of a
match of only the lowest new entrant fare, with more
restrictions placed upon it—traditional measures of the
performance of an incumbent carrier are affected
dramatically based solely on whether the airlines in a
market practice revenue management. In particular, in
the case where the new entrant comes in with the same
capacity as the incumbent (90 seats per day), the
simulated relative effect on the nonstop incumbent’s
revenues and average fares is À18% and +2%,
respectively, when all carriers accept passenger requests
on a FCFS basis, as compared to À62% and À53%,
respectively, when all competitors use RM.


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Simulation results also show that average fares on the

nonstop incumbent carrier can either increase or
decrease following entry, depending on whether the
airlines perform revenue management, again with no
difference in the incumbents’ pricing response. For
example, when all carriers accept seat requests on a
FCFS basis, the nonstop incumbent’s average fare
increases with new entrant capacity, as primarily lowfare passengers are diverted from the incumbent carriers
to the new entrant. In contrast, the incumbent’s average
fare decreases with increasing new entrant capacity
when all carriers use revenue management, as more
high-fare passengers shift to the new entrant, which is
now protecting seats for them. Focusing on average
fares in the evaluation of airline performance before and
after entry could lead to the incorrect conclusion that
there is a difference in response from the incumbent
carrier between the two cases, when in fact there is none.
The effect of entry on the incumbent is far greater
(and worse) when both the incumbents and the new
entrant use revenue management. Given the new
entrant’s more attractive fares and use of revenue
management, it diverts mostly high-fare passengers
from the nonstop incumbent, and thus substantially
hurts incumbent revenues. This result illustrates that
revenue management can be as important for new
entrant carriers as for incumbents.
The simulations also show that under revenue
management on all carriers, matching the new entrant’s
fare structure substantially increases incumbent revenues by up to 82% (compared to limited match by the
incumbents). This emphasizes the importance of the
competitive pricing situation on individual airlines’

revenue performance, even in a simple single market
environment.

Acknowledgements
This research would not have been possible without
the programming talent of Craig Hopperstad, who
wrote the Passenger Origin Destination Simulator, and
implemented the revenue management methods in the
simulation environment. We also thank the Sloan
Foundation for its generous support of the MIT Global
Airline Industry Program.

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