Upload
mansoor-shaikh
View
229
Download
0
Embed Size (px)
Citation preview
7/26/2019 airline industry.docx
1/34
PROJECT REPORT ON:ANALYSIS OF AIRLINE INDUSTRY
TOPICS COVERED: CREW SCHEDULING
FACTOR OCCUPANCY
IMPROVEMENT OF ROI
7/26/2019 airline industry.docx
2/34
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.
7/26/2019 airline industry.docx
3/34
7/26/2019 airline industry.docx
4/34
7/26/2019 airline industry.docx
5/34
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.
7/26/2019 airline industry.docx
6/34
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.
7/26/2019 airline industry.docx
7/34
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
7/26/2019 airline industry.docx
8/34
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.
7/26/2019 airline industry.docx
9/34
*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
7/26/2019 airline industry.docx
10/34
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
7/26/2019 airline industry.docx
11/34
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
7/26/2019 airline industry.docx
12/34
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
7/26/2019 airline industry.docx
13/34
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
7/26/2019 airline industry.docx
14/34
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+
7/26/2019 airline industry.docx
15/34
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$B 1,2, ....n 4 of this report.
7/26/2019 airline industry.docx
16/34
S,'e#$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.
7/26/2019 airline industry.docx
17/34
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_safety7/26/2019 airline industry.docx
18/34
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 $unior and senior crew members is still very limited and
thus achievement of your choices is limited. *andler &roo!s, crew scheduling guy
for thirty years
Additional unplanned disruptions in schedules due to weather and air traffic
controldelays can disrupt schedules, so crew scheduling software remains an area
for ongoing research.
https://en.wikipedia.org/wiki/Air_traffic_controlhttps://en.wikipedia.org/wiki/Air_traffic_controlhttps://en.wikipedia.org/wiki/Air_traffic_controlhttps://en.wikipedia.org/wiki/Air_traffic_control7/26/2019 airline industry.docx
19/34
C!l$+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&
7/26/2019 airline industry.docx
20/34
$in& !nly 566 "li&'% in a 56 #ay in%er.al1 T'ee )airin& )r!.i#e rea!na*ly
i2e#
#a%a +a%ri,e "!r %e%in& e% )ar%i%i!nin& an# e% ,!.erin& al&!ri%'+ %! "in#
%'e !)%i+al
,'e#$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
7/26/2019 airline industry.docx
21/34
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$ective
functions for the matching process and in choosing the appropriate brea!ing up of
the
e#isting pairings.
7/26/2019 airline industry.docx
22/34
F$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.
7/26/2019 airline industry.docx
23/34
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/57177/26/2019 airline industry.docx
24/34
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 #
7/26/2019 airline industry.docx
25/34
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
7/26/2019 airline industry.docx
26/34
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$4' billion o their annual
net profts generated b air transport. 2he most proftable part o
the rest o the value chain is in distribution, with the computer
reservation sstems businesses o the three global distribution
sstem companies generating an average -/C o !"%, ollowed
b reight orwarders with an -/C o 1&%.
Jowever, high profts and ine=cient costs in the value chain are
onl part o the eplanation or persistentl poor airline
proftabilit. /n act over the past " ears the airline industr has
more than halved the cost o air transport in real terms, owing to
better uel e=cienc, asset utili7ation and input productivit. Let
these e=cienc gains have ended up in lower air transport ields
rather than improved investor returns. 2hat has created
tremendous value or customers and the wider econom, but has
let e+uit investors in the airline industr unrewarded. 2he stud
shows this aspect o the airlines) perormance lies more in the
industr)s highl ragmented and unconsolidated structure and
the nature o competition, rather than in the suppl chain,
although distribution is a @e part o the pu77le
7/26/2019 airline industry.docx
27/34
irline C0s and heads o cargo reported in pril that the epect
growth in passenger services over the net 1! months to be as
strong as in !"1" and earl !"11. Cargo is also epected to see
its strongest growth since !"1". 2he upturn in economic activit
driving these epectations is ragile, as wea@ness in Europe andsia has shown. Jowever, an easing in fscal austerit policies,
continued epansionar monetar polic and progress in
deleveraging the private sector, are all coming together to boost
growth, particularl in economies li@e the IM.
Consumers
Consumers will see a substantial increase in the value the derive
rom air transport this ear. ?ew destinations are up 1.% this
ear alread, and re+uencies have risen b even more. Ke
epect 1% o world GDP to be spent on air transport in !"1&,
totaling over #$" 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 $% lower than !"
ears earlier, ater ad*usting or inNation. ir reight had been in
the doldrums since !"1" but now a cclical upturn is evident.
Kider econom Economic development worldwide is getting a
signifcant boost rom air transport. 2his wider economic beneft is
being generated b increasing connections between cities O
enabling the Now o goods, people, capital, technolog and ideas 4
and reducing air transport costs. 2he number o uni+ue cit4pair
7/26/2019 airline industry.docx
28/34
connections is estimated at more than 1$,""", 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
7/26/2019 airline industry.docx
29/34
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 #!
7/26/2019 airline industry.docx
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
7/26/2019 airline industry.docx
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
7/26/2019 airline industry.docx
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 #
7/26/2019 airline industry.docx
33/34
Korldwide airline industr !"15 !"1 !"1&
Mpend on air transport &! $< $5
% change over ear 1.'% !.!% 4".%
% global GDP ".
7/26/2019 airline industry.docx
34/34