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

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 m

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

r2004 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

Tribu-nal 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 workof Dodgson et al (1991) for the European

Commission

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

*Corresponding author.

Email-addresses: gorint9@mit.edu (T Gorin), belobaba@mit.edu

(P Belobaba).

0969-6997/$ - see front matter r 2004 Elsevier Ltd All rights reserved.

doi:10.1016/j.jairtraman.2004.03.002

2 Literature review

In 1958, McGee (1958) argued that price predation

was often an unprofitable business strategy and

con-cluded 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 networkcarrier, 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 manage-ment 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 overlookthe complex-ity of airline pricing, scheduling and revenue manage-ment processes, not to manage-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.

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

non-stop service in this market, and competes with both

incumbents but more directly with the nonstop

incum-bent 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

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 1summarizes 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 inFig 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 con-versely, 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’ mea-sures of incumbent performance, we allow the incum-bent carriers to either accept requests for seats on a first-come, first-serve basis (FCFS), or to use Fare Class Revenue Management (FCRM) In the case of FCFS seat request acceptance, passengers bookseats in a FCFS manner, and the only controls that enable airlines

to differentiate between fare products are advance

0

20

40

60

80

100

120

140

160

180

200

Fare

Business Leisure

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

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

Manage-ment (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 observa-tion 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 compe-titors 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

Table 1

Capacity, frequency and pricing overview without entrant competition

Airline 1 90 seats (3  30) Three daily flights Four fare classes with four different fare levels Airline 2 90 seats (3  30) Three daily flights Y, B, M and Q (see Table 2 )

Origin

Hub H2

Destination Airline 2

Airline 2 Airline 1

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

Fare Restrictions

Roundtrip

requirement

Saturday night stay

Nonrefundable Advance

purchase

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

class Fare Restrictions Roundtrip requirement

Saturday night stay

Nonrefundable Advance

purchase

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

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 manage-ment (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, post-entry 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 Service Frequency & capacity Fares by fare class Revenue management

Airline 3 (New entrant) Nonstop 3  15–25–30 or 50 $135 n/a $53 n/a 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

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,

late-booking 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

sub-stantial revenue dilution at the market level (from the

incumbent carriers), causing the observed decrease in

market revenues and average fare, as shown inTable 5

Fig 3shows the impact of revenue management on the

mix of passengers on the incumbent and new entrant

carrier, and illustrates that revenue management allows

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 6summarizes 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

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  30 seats on the new entrant.

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

(%)

FCRM (%)

FCFS (%)

FCRM (%)

Relative to no entrant 3  15 4% 26% 18% 48% 15% 30%

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

incum-bent 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

stimula-tion 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 bookfirst and airlines accept

passen-ger 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 inFig 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 bookthe 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

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 ( 18%) 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  15 and 3  50) and relatively less traffic

at intermediate levels of entrant capacity (3  25 or

3  30) The traffic recovery at intermediate levels of entrant capacity is a direct consequence of the incum-bent’s use of revenue management As shown inFig 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  25 and 3  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

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

Fig 4 Incumbent revenues and average fares as a function of

competitive revenue management settings and new entrant capacity.

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

late-booking 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

pur-chase requirements) over those of Airline 1 This has the

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 7illustrates 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 7shows 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 manage-ment 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 6 Incumbent loads by fare class as a function of entrant capacity

and with FCRM on all carriers.

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

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 6shows, 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 inTable 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

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  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 low-fare, 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  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 com-pared to the case where only the new entrant carrier uses revenue management Finally, the new entrant’s reven-ues increase as it begins to use RM as opposed to FCFS (against FCFS on the incumbents), as shown inTable 8

Table 7

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

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

Revenue management therefore increases airline

reven-ues, 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  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

in-creases nonetheless In this case, the large increase in

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

Table 9shows 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 18% and +2%, respectively, when all carriers accept passenger requests

on a FCFS basis, as compared to 62% and 53%, respectively, when all competitors use RM

Table 8

Airline 3 traffic, average fares and revenues

FCFS All FCFS vs FCRM FCFS All FCFS vs FCRM FCFS All FCFS vs FCRM

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

Limited match Full match Limited match Full match Limited match Full match