airline industry.docx

7/26/2019 airline industry.docx

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PROJECT REPORT ON:ANALYSIS OF AIRLINE INDUSTRY

TOPICS COVERED: CREW SCHEDULING

FACTOR OCCUPANCY

IMPROVEMENT OF ROI


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AIRLINES INDUSTRY-AN INTRODUCTION

An airlineis a company that provides air transport services for travelling passeners

and freight . Airlines lease or own their aircraft with which to supply these services

and may form partnerships or alliances with other airlines for mutual benefit.

Generally, airline companies are recognized with an air operating certificate or

license issued by a governmental aviation body.

Airlines vary from those with a single aircraft carrying mail or cargo through full-

service international airlines operating hundreds of aircraft. Airline services can be

categorized as being intercontinental, domestic, regional, or international, and maybe operated as scheduled services or charters.


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SWOT analyi !" airline in#$%ry

A SWO analysis -- a review of strengths, wea!nesses, opportunities,

and threats a core re"uirement of any organization, and essential to understand any

industry. he volatile airline industry is no e#ception. While individual airlineseach analyze and ma!e decisions based on their own situations, there are overall

industry similarities that all airlines face, with each endeavoring to ma#imize

strengths and opportunities while minimizing wea!nesses and threats.

S%ren&%':

A ma$or strength of any airline is the product itself -- air travel. %espite downturns,

over time air travel continues to grow, not only due to population growth, but also

due to an increased propensity to fly.

Safety record and the associated public acceptance of air travel as both a fast and

safe way to travel. &oth traditional, brand recognized airlines and new low cost

carriers share this strength.

Airline staff is highly trained and e#perienced, from pilots and flight attendants to

mechanics and ground staff.

&usiness-wise, airlines have the ability to segment the mar!et, even on the same

routes. his allows airlines to establish different levels of service and ma!e

associated pricing decisions.


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Wea(ne:

Airlines have a high 'spoilage' rate compared to most other industries. Once a

flight leaves the gate, an empty seat is lost and non-revenue producing.

Aircraft is e#pensive and re"uires huge capital outlays. he return on investment

can be different than planned.

(arge wor!forces spread over large geographic areas, including international

points, re"uire continual communication and monitoring. his can be e#acerbated

during operational irregularities,

e.g. bad weather.

While the business climate can change "uic!ly, airlines have difficulty ma!ing

"uic! schedule and aircraft changes due to leases, staffing commitments and other

factors.

O))!r%$ni%ie:

Airline mar!et growth offers continual e#pansion opportunities for both leisure and

business destinations. his is particularly true for international destinations.

echnology advances can result in cost savings, from more fuel efficient aircraft to

more automated processes on the ground. echnology can also result in increased

revenue due to customer-friendly service enhancements li!e in-flight )nternet

access and other value-added products for which a customer will pay e#tra.

(in!-ups with other carriers can greatly increase passenger volumes. &y

coordinating schedules, airlines can offer service to destinations via a code shareagreement with a partner carrier.


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T'rea%:

A global economic downturn negatively affects leisure, optional travel, as well as

business travel.

he price of fuel is now the greatest cost for many airlines. An upward spi!e can

destabilize the business model.

A plague or terrorist attac! anywhere in the world can negatively affect air travel.

Government intervention can result in new costly rules or une#pected newinternational competition.

O**+A* /A*O0


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Occupancy factor is an important parameter for the assessment of the performance

of any transport system. Almost all transport systems have high fi#ed costs, and

these costs can only be recovered through selling tic!ets. Airlines often calculate a

load factor at which the airline will brea! even1 this is called the brea!-even load

factor. At a load factor lower then the brea! even level, the airline will lose money,

and above will record a profit.

he environmental performance of any transport mode improves as the load factor

increases. he weight of passengers is normally a small part of the total weight of

any transport vehicle, so increasing the number of passengers changes the

emissions and fuel consumption to only a small degree. As a vehicle is more highly

loaded, the fuel consumed per passenger drops, and fully loaded transport vehiclescan be very fuel efficient.

Occupancy factor or sometimes simply called load factor is a measure of an

airline2s passenger carrying capacity. )t is also !nown as a measure of efficiency

and hence most commonly used to describe the performance of an airline.

Achievement of high load is deemed essential for airline2s profitability and it is

interesting to investigate factors that are e#pected to affect load factors./urthermore, !nowing these factors would help organizations or companies ma!e

more effective decisions and planning. hese decisions or planning could include

providing training, changing the mind-set among airline staff, increasing the

number of travel agencies or changing the practices in their management,

increasing human resource, increasing investment in advertising, and many others

that can improve the performance of these companies. his paper focuses on

estimating load factors of the aircrafts in )ran. %uliba, 3auffman and (ucas 456678

modeled the impact of load factors using five variables. hese variables are the

number of travel agencies using each computerized reservation system, average

length in miles of all of the airline2s flight between city-pairs, number of departures

for each carrier, advertising e#penses for each carrier and the change in vehicle

miles as a control variable for industry growth.


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*A(*+(A)O O/ O**+A /A*O0

9#ample 7: he air distance between the two cities, A and &, is 7566 !ilometers

and the type of the aircraft used is &oeing ; seats and the numberof passengers in this flight is 56?.

A & 7566 !ilometers

%istance between A and & 7566

umber of passenger 56?

Avalable seats 5=>

he load factor is calculated as follows:

@766

tan

tan cedisseatAvalablecedispassengercarriedofumber

/actor(oad B

@55.;7@766 75665=> 756656? BB(oad/actor

he calculated load factor in this case is about ;7@, which is a pretty acceptable

value

CREW SCHEDULING


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A)0()9 *09W S*C9%+()G

An airline must cover each flight leg with a full complement of cabin crew in a

manner consistent with safety regulations and award re"uirements. Dethods are

investigated for solving the set partitioning and covering problem. A test e#ample

illustrates the problem and the use of heuristics.he Study Group achieved an

understanding of the problem and a plan for further wor!.

7. )ntroduction

his problem was presented to the 7EE5 D)SG at Dac"uarie +niversity by he

reston Group ty (td. he reston Group is a systems development company

providing

cost effective wor!station-based interactive scheduling and simulation products. )tsproducts for the international airline industry include

F otal Airspace and Airport Dodeller 4AAD8

F erminal Danagement Systems 4DS8

F Air *rew Scheduler 4A*S8

he Air *rew Scheduler is an interactive computer software system for air crew

scheduling. he system is used by planners to develop and modify crew pairings

for flight crews and cabin crews.*urrently the Air *rew Scheduler facilitates the production of legal crew

schedules.

he reston Group wishes to enhance the product by

developing a capability for


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F automatic generation of legal trips

F optimisation of crew schedules which cover all flight legs

he input tas!s are a set of flight legs. A flight 4sector, segment8 leg corresponds

to a flight between two cities, departing one city at a specified time and arriving at

the

other city at a specified time. A duty period is made up of a set of flight legs.

Safety re"uirements limit the number of flight legs in a duty period and the

duration of the period. A pairing 4pattern8 is a se"uence of re"uired duty periodsthat a crew must complete that starts and ends at the same domicile. A regulation

specifies the ma#imum duration of a pairing and the minimum rest period between

duty periods.

)n long haul operation, the duration of a pairing may be as long as 57 days and a

minimum rest period may be


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as hub and spo!e, short haul and long haul. (ong haul operations are characterised

by factors such as

F days away from base

F multi-base operations

F language re"uirements of crew

F pa#ing 4passengering crew between operating flights8

F comple# duty and rest rules

F crew splitting due to different size aircraft.

Dany airlines plan their

crewing via a three stage process:

F development of pairings or crewing patterns which specify a crew schedule from

base until return to base

F development of bid lines which lin! pairings and specify a crew schedule overthe planning horizon

F development of a roster from the preferences e#pressed by the crew for the bid

lines.

he costs of flight crew and cabin crew form a ma$or component of the direct

operating

costs of an airline. Air crew planners continually strive for more effective use

of available crews to reduce the total number of crews needed and to minimise

costs

of crew stopovers and allowances. Cowever, the plannersH tas!s usually involvemuch

time-consuming and laborious manual wor!. his reduces the time available to

research

various crewing options which may produce much more effective crewing

pairings.

he planner starts with a schedule or plan of aircraft movements for a period of


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time. he planner then constructs pairings of air crew movements from any crew

home base, along a number of sectors, with suitable rest or slip periods, and return

to home base, usually some days later. )n developing these pairings, the planner

must ensure that numerous government regulations, unionImanagement

agreements and safety rules are met.

he rules which specify duty and rest periods are determined by government and

management. Some rules are hard 4must8 while others are soft 4should8. 9#amples

of a duty rule and a rest rule follow.

F Given that %uty is a#ing and %uty is Operating and (ast Sector in %uty is not

Operating and %uty is not o Come then:

Operating time in Duty must be less than l2 hours

F Given that revious %uty is valid and Slip ime in revious %uty


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system

F selects trips from the mainframe

F partitions the trips in different geographical areas

F re-uses previous pairings

F produces multiple solutions

F compares the ratio of flight time to total time 4premium8

F returns the pairings to the mainframe

he sets of resulting pairings for a planning period are the basis for assigning

actual

crew names and are made available to a preferential bidding system, assembled

into pairing strings in a bid line system, or assigned to specific crew members in an

assignment system.

he Study Group was as!ed to address the particular issues of

F long haul operations where crews may be away from home base for as long as 57

days

F crew splitting in which a crew of 7; may finish a flight leg and then start new

flight legs as crews of = and E on smaller planes.

Se% )ar%i%i!nin& )r!*le+


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he airline crew scheduling problem is to find a minimum cost set of pairings

which

cover all flight legs.

he problem can be formulated as a set partitioning problem 4S8. he input data

is anA matri# whose rows are the flight legs and columns are the pairings. (et theinput

data be represented by

Airline crew scheduling

m B number of flight legsn B number of pairings

Cj B cost of pairingj

a.. B K) flight leg i contained in pairing$I) 6 otherwisehe decision variables are

7 if pairingj is flowno otherwise

he set partitioning problem 4S8 is

minimise L:CjXjj(1)

sub$ect toL:aijXj B 7 fori= 1,2, ... .mj458

Xj = KO,lL forj=1,2, ... .n 4?8he integer programming problem 47-?8, can be solved by first solving the rela#ed

linear programming problem where 4?8 is replaced by

Xj MO for$B 1,2, ....n 4 of this report.


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S,'e#$lin& is the process of assigning crews to operate transportation systems,

such as raiaircr

Dost transportation systems use software to manage the crew scheduling process.

*rew scheduling becomes more and more comple# as you add variables to theproblem. hese variables can be as simple as 7 location, 7 s!ill re"uirement, 7 shift

of wor! and 7 set roster of people. )n the ransportation industries, mainly Air

ravel, these variables become very comple#.

*OD(9N) O0 *OS0A)S

)n Air ravel for instance, there are numerous rules or 'constraints' that are

introduced. hese mainly deal with legalities relating to wor! shifts and time, and a

crew members "ualifications for wor!ing on a particular aircraft. Add numerous

locations to the e"uation and *ollective &argaining and /ederal labor laws and

these become new consideration for the problem solving method. /uel is also a

ma$or consideration as aircraft and other vehicles re"uire a lot of costly fuel to

operate. /inding the most efficient route and staffing it with properly "ualified

personnel is a critical financial consideration.

he problem is computationally difficult and there are competing mathematical

methods of solving the problem. Although not easy to describe in one sentence, the

goal is the essentially same for any method of attac!ing the problem:

Wi%'in a e% !" ,!n%rain% an# r$le +!.e a e% r!%er !" )e!)le /i%' ,er%ain

0$ali"i,a%i!n "r!+ )la,e %! )la,e /i%' %'e lea% a+!$n% !" )er!nnel an#

air,ra"% !r .e'i,le in %'e lea% a+!$n% !" %i+e1

(owest cost has traditionally been the ma$or driver for any crew scheduling

solution.


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Although not a 'rule', We can describe at least < parts of the e"uation that are

ingested by the computational process:

eople and their "ualifications and abilities.

Aircraft or vehicles and their 'eople' "ualification re"uirements and their cost to

operate over distance.

(ocations and the time and distance between each location.

Wor! rules for the personnel, including Shift hours and seniority.

)n crew scheduling the rules and constraints are typically a combination of:

government regulations concerning flight time, duty time and re"uired rest,designed to promote aviation safetyand limit crew fatigue,

crew bid re"uests, vacations,

labor agreements

aircraft maintenanceschedules

crew member "ualification and licensing

other constraints related to training

pairing e#perienced crew members with more $unior crew members

returning crew to their base at the end of their trip 4called deadheading8

he first phase in crew planning is building the crew pairings 4also !nown as trips,

rotations, among other popular descriptions8. his process pairs a generic crew

member with a flight so that at the end of this process all aircraft flights are

covered and all trips 4combination of flights starting at a crew base and returning tothat crew base or co-terminal are crew legal. he ne#t step is the allocation of those

trips to the individual crewmember. /or the +S, *anada and Australia, seniority

generally rules. he two processes 4which are completely different8 are referred to

as bid lines and preferential bidding. )n seniority order, pilots bid for either a line

of time 4bidline8 or trips and days off 4preferential bidding. these are awarded
https://en.wikipedia.org/wiki/Aviation_safetyhttps://en.wikipedia.org/w/index.php?title=Crew_fatigue&action=edit&redlink=1https://en.wikipedia.org/w/index.php?title=Labor_agreements&action=edit&redlink=1https://en.wikipedia.org/wiki/Aircraft_maintenancehttps://en.wikipedia.org/wiki/Deadheading_(aviation)https://en.wikipedia.org/w/index.php?title=Crew_fatigue&action=edit&redlink=1https://en.wikipedia.org/w/index.php?title=Labor_agreements&action=edit&redlink=1https://en.wikipedia.org/wiki/Aircraft_maintenancehttps://en.wikipedia.org/wiki/Deadheading_(aviation)https://en.wikipedia.org/wiki/Aviation_safety


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based on seniority and modified only when their selections have already been

ta!en by a more senior crew member 4bidlines8 or their trip and day off selections

4preferential bidding8 do not ma!e up a complete line 4hours, days off, etc.

parameters agreed to by the company and the union8. he senior fol!s have more

time off, better choice of time off and fly better trips than the $unior crew members,generally spea!ing. )n the +S, this is considered fair. ) personally would not want

to be around +S pilots suggesting a move to the fair roster system common in the

rest of the world. /or 9uropean airlines and other airlines in the rest of the world,

the allocation process is completely different. he company builds the pilot

schedules directly to meet their needs, not the pilotHs needs. &efore assigning a

single trip, the schedulers put all planned absences 4vacation, training, etc.8 onto

the crew membersH schedule. Only then are trips assigned to the individual crew

members. As such, fairness means that the most senior captain and the most $uniorcaptain have the same amount of duty time, bloc! hours, night time, time away

from base, layovers, e#pense pay, etc. in a given schedule period. Seniority is out

and all wor! is completely homogenized. /or them, anything else is unfair,

undemocratic. hatHs not to say that a good bottle of li"uor to crew scheduling

wonHt get a pilot that specific trip or day off they want. Slowly over the last thirty

years, foreign airlines using the 'no seniority' rostering system have allowed some

measure of seniority to creep into the allocation process from pilots who may now

as! for a specific day off or trip once a "uarter or ma!e multiple re"uests within a

schedule period. Although this may sound very much li!e preferential bidding, it is

not. he disparity between $unior and senior crew members is still very limited and

thus achievement of your choices is limited. *andler &roo!s, crew scheduling guy

for thirty years

Additional unplanned disruptions in schedules due to weather and air traffic

controldelays can disrupt schedules, so crew scheduling software remains an area

for ongoing research.
https://en.wikipedia.org/wiki/Air_traffic_controlhttps://en.wikipedia.org/wiki/Air_traffic_controlhttps://en.wikipedia.org/wiki/Air_traffic_controlhttps://en.wikipedia.org/wiki/Air_traffic_control


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C!l$+n &enera%i!n

F!r reali%i,ally i2e# )r!*le+ i% i n!% )!i*le %! in,l$#e all )!i*le

,!l$+n

%'a% re)reen% le&al )airin&1 T'e )r!*le+ i %! &enera%e a 3&!!#3 e% !"

)airin&1 A "ile

,!n%ainin& "li&'% in"!r+a%i!n /a !*%aine# "r!+ T'e Pre%!n Gr!$)1 Par% !"

%'i "ile

/i%' "li&'% n$+*ere# "!r re"eren,e i '!/n *el!/11 QFA0009 744 SYD(31/03/91 13:15)->MEL(31/03/91

2 QFAOOOl 744 MEL(31/03/91 13:45)->SYD(31/03/91

3 QFA0009 744 MEL(31/03/91 16:00)->SIN(31/03/91

4 QFAOOOl 744 SYD(31/03/91 16:30)->BKK(31/03/91

5 QFA0009 744 SIN(31/03/91 23:05)->L!( 1/04/91

19 QFAOOOl 744 BKK( 2/04/91 00:30)->"!( 2/04/91

9# QFAOOI0 744 MEL( 9/04/91 06:45)->3YD( 9/04/91

99 QFAOOI0 744 L!( #/04/91 22:30)->SIN( 9/04/91

100 QFA0002 744 BKK( 9/04/91 0#:20)->SYD( 9/04/91

A )r!&ra+ 'a *een /ri%%en %! &enera%e )airin& "r!+ %'e in"!r+a%i!n in %'i

#a%a"ile1

T'e )r!&ra+ &enera%e %'e )airin& *y ,!n%r$,%in& a %ree in /'i,' a &i.en

"li&'% #e%ina%i!n

i lin(e# %! all $*e0$en% le&al "li&'% /'!e !$r,e i %'e a+e a %'i

l!,a%i!n1

On,e a %ree i ,!n%r$,%e# "!r a &i.en %ar%in& "li&'% %'e )airin& are e4%ra,%e#

*y

%ra.erin& %'e )a%' "r!+ %'e ini%ial n!#e %! ea,' !" %'e "inal n!#e an#e4%ra,%in& %'e

"li&'% n$+*er a% ea,' n!#e1

T'e )r!&ra+ i a% )reen% lin(e# %! a r$le *ae ,!ni%in& !" a $*e% !" %'e

"$ll

Pre%!n Gr!$) r$le *ae an# 'a *een $e# %! &enera%e rela%i.ely +all e% !"

)airin&


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$in& !nly 566 "li&'% in a 56 #ay in%er.al1 T'ee )airin& )r!.i#e rea!na*ly

i2e#

#a%a +a%ri,e "!r %e%in& e% )ar%i%i!nin& an# e% ,!.erin& al&!ri%'+ %! "in#

%'e !)%i+al

,'e#$le1

A le&al )airin& &enera%e# *y %'e )r!&ra+ i '!/n *el!/1 T'e li) an# #$%y

%i+e

are in '!$r an# %'e ,!% i ,al,$la%e# a %'e ra%i! !" %!%al %i+e %! #$%y %i+e1

4 SYD-BKK $l%& 0'00 "* 9'42 +,$" 1'00

19 BKK-L! $l%& 25'5# "* 12'42 +,$" 2'1#

44 L!-MAN $l%& 4#'00 "* 1'00 +,$" 4'22

50 MAN-L! $l%& 10'50 "* 0'92 +,$" 4'54

74 L!-SIN $l%& 51'17 "* 13'17 +,$" 4'66

92 SIN-MEL $l%& 25'5# "* 7'00 +,$" 4'669# MEL-SYD $l%& 1'50 "* 1'33 +,$" 4'59

T'i )airin& &i.e a ,!l$+n7 /i%'

*$ 89;

a..-{ 5 "!ri895;996

IJ - 6 "!r all !%'er i 8 5 111 566

.

He$ri%i, !l$%i!n +e%'!#

)n the related problem of bus and crew scheduling, one method which is !nown to

give good heuristic solutions is repeated matching. his method has been

developed

largely by Dichael /orbes and a commercial code has been developed by O*OD

ty

(td. )t has been applied successfully to problems of a size at least comparable with

the air crew scheduling one presented here and with greater comple#ity. his isalmost

certain to wor! for air crew scheduling but a test on a full data set would be needed

to

confirm that.

)n general terms, the method consists of first pairing the tas!s optima+y by using


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a matching (i.e. non-bipartite matching8 algorithm. hese then become potentialpairings.

he process is then iterated by continually brea!ing up the potential pairings, or

a specified fraction of them, and recombining, again with the use of the matching

algorithm.

he success of this method depends on having a fast matching code capable of

solving

very large scale matching problems. )t also re"uires that the feasibility and cost of

any potential pairings can be computed efficiently. As with the standard integer

programming

formulation, it also needs some user s!ill in setting up appropriate ob$ective

functions for the matching process and in choosing the appropriate brea!ing up of

the

e#isting pairings.


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F$r%'er /!r(

he Study Group achieved

F an understanding of the airline crew scheduling problem

F a set of test problems for evaluation of solution methods

F hands on e#perience in the generation of pairings

F a literature search of e#act and heuristic solution methods for set partitioning

he re"uirements for further wor! on this problem are

F data sets of flight leg information and award rules

F costing information

F wor!ing pairings used by airlines

F documentation on the bidding process

he plan is to decouple the award rule base from the airline crew scheduler and

use the rules to generate aircrew pairings. he ne#t stage will incorporate heuristicalgorithms to provide improvement capability.


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RETURN ON INVESTMENT

Return on investment (ROI)measures the gain or loss generated on an investment relative to

the amount of money invested. RI is usually e!"ressed as a "er#entage and is ty"i#ally used

for "ersonal finan#ial de#isions$ to #om"are a #om"any%s "rofita&ility or to #om"are the

effi#ien#y of different investments.

'he return on investment formula is:

ROI = (Net Profit / Cost of Investment) x100

'he RI #al#ulation is fle!i&le and #an &e mani"ulated for different uses. #om"any

may use the #al#ulation to #om"are the RI on different "otential investments$ hile an

investor #ould use it to #al#ulate a return on a sto#*.

+or e!am"le$ an investor &uys ,1$--- orth of sto#*s and sells the sharesto yearslater for ,1$--. 'he net "rofitfrom the investment ould &e ,-- and the RI ould &e

#al#ulated as follos:

ROI = (200 / 1,000) x100 = 20%

'he RI in the e!am"le a&ove ould &e -/. 'he #al#ulation #an &e altered &y

dedu#ting ta!esand fees to get a more a##urate "i#ture of the total RI.

'he same #al#ulation #an &e used to #al#ulate an investment made &y a #om"any.

0oever$ the #al#ulation is more #om"le! &e#ause there are more in"uts. +or e!am"le$to figure out the net "rofit of an investment$ a #om"any ould need to tra#* e!a#tly ho

mu#h #ash ent into the "roje#t and the time s"ent &y em"loyees or*ing on it.

RI is one of the most used "rofita&ility ratios &e#ause of its fle!i&ility. 'hat &eing said$

one of thedonsidesof the RI #al#ulation is that it #an &e mani"ulated$ so results may

vary &eteen users. hen using RI to #om"are investments$ it%s im"ortant to use the

same in"uts to get an a##urate #om"arison.

lso$ it%s im"ortant to note that the &asi# RI #al#ulation does not ta*e time into

#onsideration. &viously$ it%s more desira&le to get a 213/ reuturn over one yearthan itis over to years.

9conomic performance of the airline industry
http://www.investinganswers.com/node/6392http://www.investinganswers.com/node/6392http://www.investinganswers.com/node/5150http://www.investinganswers.com/node/2011http://www.investinganswers.com/node/2230http://www.investinganswers.com/node/6392http://www.investinganswers.com/node/6392http://www.investinganswers.com/node/4567http://www.investinganswers.com/node/6160http://www.investinganswers.com/node/5717http://www.investinganswers.com/node/6392http://www.investinganswers.com/node/5150http://www.investinganswers.com/node/2011http://www.investinganswers.com/node/2230http://www.investinganswers.com/node/6392http://www.investinganswers.com/node/4567http://www.investinganswers.com/node/6160http://www.investinganswers.com/node/5717


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Consumers beneft rom lower oil prices with lower ares, more

routes, and spend 1% o world GDP on air transport.

Economic development big winner rom the doubling o cit

pairs and halving o air transport costs in past !" ears.

Governments gain substantiall rom #11$bn o taation this

ear and rom more than &' million (suppl chain) *obs.

E+uit owners see a ar better !"1& with a .&% average airline

-/C, above the cost o capital or the frst time.

0uel use per 23 to all a urther 1.&% 4o4, saving 11 million

tonnes o C! emissions and #5 billion o uel costs.

6oad actors orecast to stabili7e as capacit rises8 new aircrat

deliveries represent a #1'" billion investment.

9obs in the industr should reach !.& million, productivit will be

up 5.!% and G:;emploee almost #


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value chain in order to attract the #4& trillion that will be needed

over the net !" ears to meet the growing demand or aviation4

enabled connectivit.

2he call came in an /2 stud supported b analsis romc3inse Compan, FProftabilit and the ir 2ransport :alue

Chain, which shows that returns on capital invested in airlines

have improved in recent ears, but are still ar below what

investors would normall epect to earn.

F2he airline industr has created tremendous value or its

customers and the wider economies we serve. viation supports

some & million *obs globall and we ma@e possible #!.! trillion

worth o economic activit. H value, over 5&% o the goodstraded internationall are transported b air, said 2on 2ler,

/2)s Director General and CE. FHut in the !""4!"11 period,

investors would have earned #1 billion more annuall b ta@ing

their capital and investing it in bonds and e+uities o similar ris@.

Inless we fnd was to improve returns or our investors it ma

prove di=cult to attract the #4& trillion A1B o capital we need to

serve the epansion in connectivit over the net two decades,

the vast ma*orit o which will support the growth o developingeconomies.

During the !""4!"11 period, returns on capital invested in the

airline industr worldwide averaged .1%A!B . 2his is an

improvement on the average o 5.'% generated in the previous

business ccle over 1


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2he stud showed that over the past " ears virtuall all

industries have generated higher returns on invested capital

A-/CB than the airline industr. oreover, airlines are the least

proftable segment o the air transport value chain while other

segments consistentl generate good returns or their investors.2he biggest cost or airlines toda is uel and companies in this

sector benefted rom an estimated #1$4' billion o their annual

net profts generated b air transport. 2he most proftable part o

the rest o the value chain is in distribution, with the computer

reservation sstems businesses o the three global distribution

sstem companies generating an average -/C o !"%, ollowed

b reight orwarders with an -/C o 1&%.

Jowever, high profts and ine=cient costs in the value chain are

onl part o the eplanation or persistentl poor airline

proftabilit. /n act over the past " ears the airline industr has

more than halved the cost o air transport in real terms, owing to

better uel e=cienc, asset utili7ation and input productivit. Let

these e=cienc gains have ended up in lower air transport ields

rather than improved investor returns. 2hat has created

tremendous value or customers and the wider econom, but has

let e+uit investors in the airline industr unrewarded. 2he stud

shows this aspect o the airlines) perormance lies more in the

industr)s highl ragmented and unconsolidated structure and

the nature o competition, rather than in the suppl chain,

although distribution is a @e part o the pu77le


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irline C0s and heads o cargo reported in pril that the epect

growth in passenger services over the net 1! months to be as

strong as in !"1" and earl !"11. Cargo is also epected to see

its strongest growth since !"1". 2he upturn in economic activit

driving these epectations is ragile, as wea@ness in Europe andsia has shown. Jowever, an easing in fscal austerit policies,

continued epansionar monetar polic and progress in

deleveraging the private sector, are all coming together to boost

growth, particularl in economies li@e the IM.

Consumers

Consumers will see a substantial increase in the value the derive

rom air transport this ear. ?ew destinations are up 1.% this

ear alread, and re+uencies have risen b even more. Ke

epect 1% o world GDP to be spent on air transport in !"1&,

totaling over #$" billion. ir travel is accelerating, with growth o

$.% epected this ear, the best since !"1", well above the

&.&% trend o the past !" ears. 2his is being driven mainl b

the upturn o the economic ccle. Hut price is also attracting

consumers. 2he average return are Abeore surcharges and taB

o #!< in !"1& is orecast to be more than $% lower than !"

ears earlier, ater ad*usting or inNation. ir reight had been in

the doldrums since !"1" but now a cclical upturn is evident.

Kider econom Economic development worldwide is getting a

signifcant boost rom air transport. 2his wider economic beneft is

being generated b increasing connections between cities O

enabling the Now o goods, people, capital, technolog and ideas 4

and reducing air transport costs. 2he number o uni+ue cit4pair


28/34

connections is estimated at more than 1$,""", almost double the

connectivit b air twent ears ago. 2he price o air transport to

users continues to all, ater ad*usting or inNation. Compared to

twent ears ago real transport costs have more than halved.

6ower transport costs and improving connectivit have boostedtrade Nows8 trade itsel has resulted rom globali7ing suppl

chains and associated 0D/.

Government

Governments have also gained substantiall rom the goodperormance o the airline industr. irlines and their customers

are orecast to generate #11$ billion in ta revenues this ear.

2hat)s the e+uivalent o almost '% o the industr)s G: AGross

:alue dded, which is the frm4level e+uivalent to GDPB, paid to

governments in paroll, social securit, corporate and product

taes A?ote that charges or services are ecludedB. /n addition

the industr continues to create high value added *obs.

Hut in man countries the value o aviation or governments, and

the wider econom, is not well understood. 2he commercial

activities o the industr remain highl constrained b bilateral

and other regulations. oreover, regulation is ar rom (smart)

with unnecessaril high costs in man situations. Passenger

rights;consumer protection laws are one eample o

wellintentioned but badl designed regulation that can lead to

disproportionate, inconsistent and badl targeted costs. 2here are

now &< regimes currentl in orce, based on inormation currentl

available.

Capital providers

Debt providers to the airline industr are well rewarded or their

capital, usuall invested with the securit o a ver mobile aircrat


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asset to bac@ it. n average during the business ccle the airline

industr has been able to generate enough revenue to pa its

suppliers bills and service its debt. Hut tpicall net post4ta proft

margins have been small, leaving little to pa e+uit investors.

E+uit owners have not been rewarded ade+uatel or ris@ingtheir capital in most ears, ecept at a handul o airlines.

/nvestors should epect to earn at least the normal return

generated b assets o a similar ris@ profle, the weighted average

cost o capital AKCCB. Much is the intensit o competition, and

the challenges to doing business, that average returns are rarel

as high as the industr)s cost o capital. E+uit investors have

tpicall seen their capital shrin@. Hut this ear we epect the

industr to generate a return on invested capital A-/CB o .&%,which does, or the frst time, ade+uatel reward e+uit owners.

n invested capital o almost #"" billion, the industr is orecast

to generate #.< billion o value or investors this ear. Hut it

should be clear that #!


30/34

should not be ta@en as reNecting the perormance o individual

airlines, which can diRer signifcantl. Mource /2, c3inse,

/C. ircrat 2his ear commercial airlines will ta@e deliver o

more than 1,"" new aircrat, representing an investment b the

industr o around #1'" billion. 2he trend improvement inaverage returns A-/CB has given the industr the confdence to

invest on this scale. Mustained high uel costs had also made it

economic to retire older aircrat at a higher rate, but that eRect

will clearl wea@en this ear. ver hal o this ear)s deliveries will

replace eisting Neet, ma@ing a signifcant contribution to

increasing Neet uel e=cienc, as described below.

2he Neet is orecast to increase b over


31/34

airline industr net ear will generate #1$ billion o proft or the

upstream part o the *et uel suppl chain

Ke orecast that uel e=cienc, in terms o capacit use i.e. per

23, will improve b 1.&% in !"1&. Jigher load actors areorecast to improve uel use per -23 b 1.% this ear. Continued

uel e=cienc gains have partiall decoupled C! emissions rom

epanding air transport services. /n the absence o the epected

uel e=cienc gain this ear, uel burn and C! emissions would

be 1.&% higher in !"1&. 2hat represents a saving o over 11

million tonnes o C!, as well as saving on uel that would have

cost the industr and its consumers an additional #5 billion. 0uel

is such a large cost that it ocuses intense eRort in the industr to

improve uel e=cienc, through replacing Neet with new aircrat,

better operations and eRorts to tr to persuade governments to

remove the airspace and airport ine=ciencies that waste around

&% o uel burn each ear.

Regions

2he strongest fnancial perormance is being delivered b airlinesin ?orth merica. ?et post4ta profts are the highest at #1&.

billion this ear. 2hat represents a net proft o #1'.1! per

passenger, which is a mar@ed improvement rom *ust 5 ears

earlier. ?et margins orecast at .&% eceed the pea@ o the late

1


32/34

o !.'%. irlines in sia4Pacifc have ver diverse perormances.

n average proft per passenger is #.! as lower uel costs and

stronger cargo mar@ets, particularl important in this

manuacturing region, help to boost net margins moderatel to

!.&% and net profts to #&.1 billion. iddle Eastern airlines haveone o the lower brea@even load actors. verage ields are low

but unit costs are even lower, partl driven b the strength o

capacit growth8 1!.$% this ear. Post4ta profts are epected to

grow to #1.' billion net ear, representing a proft o #


33/34

Korldwide airline industr !"15 !"1 !"1&

Mpend on air transport &! $< $5

% change over ear 1.'% !.!% 4".%

% global GDP ".


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airline industry.docx

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