U ueña, Albe o; Sáenz, Manuel; Hidalgo Nuche a, An onio
A icle
Agency con lic s in inno a ion adop ion: Lessons om he
ai line indus y
Jou nal o Inno a ion & Knowledge (JIK)
P o ided in Coope a ion wi h:
Else ie
Sugges ed Ci a ion: U ueña, Albe o; Sáenz, Manuel; Hidalgo Nuche a, An onio (2024) : Agency
con lic s in inno a ion adop ion: Lessons om he ai line indus y, Jou nal o Inno a ion &
Knowledge (JIK), ISSN 2444-569X, Else ie , Ams e dam, Vol. 9, Iss. 3, pp. 1-14,
h ps://doi.o g/10.1016/j.jik.2024.100543
This Ve sion is a ailable a :
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Agency conflic s in inno a ion adop ion: Lessons om he ai line
indus y
Albe o U ue~
na*, Manuel S
aenz, An onio Hidalgo
Uni e sidad Poli
ecnica de Mad id. ETSI Indus iales, c/ Jos
e Gu i
e ez Abascal, 2, Mad id 28006, Spain
ARTICLE INFO
A icle His o y:
Recei ed 21 Feb ua y 2024
Accep ed 7 Augus 2024
A ailable online 23 Augus 2024
ABSTRACT
In oducing an inno a ion does no end, bu a he s a s, wi h adop ion. In ac , some inno a ions display
ne wo k elemen s and equi e mo e han one fi m o ake hem up in o de o be success ul and deli e he
in ended esul s. Such is he case o NDC (new dis ibu ion capabili y), an ai line- os e ed enhancemen o
he way ai a el se ices a e con eyed and dis ibu ed om ca ie s o a el agen s. The p omise behind
NDC is ha a el se ices will be sold mo e ichly and wi hin a mo e open and inclusi e amewo k. We
d aw on he di usion o inno a ions, ins i u ional heo y, and agency heo y o e iew he de e minan s o
adop ion and i s e ec s on pe o mance o se ice p o ide s. We use he In e na ional Ai T anspo Associa-
ion (IATA) icke da abase o es ablish he ole ha ins i u ional p essu e plays on inno a ion beha iou s
and fi ms’ esul s. We find ha ins i u ional p essu e, no jus inno a ion a ibu es, influence ou comes.
Also, gi en each playe ’s di e en incen i es and he asymme y o in o ma ion, icke sales a e selec i ely
dis ibu ed in ways ha fi he agen and only occasionally he ai line p incipal. Thus, we conclude ha a el
in e media ies assess ou comes wholis ically and ha he inno a ion’s e enue upli depends on such
assessmen .
© 2024 The Au ho s. Published by Else ie España, S.L.U. on behal o Jou nal o Inno a ion & Knowledge. This
is an open access a icle unde he CC BY license (h p://c ea i ecommons.o g/licenses/by/4.0/)
Keywo ds:
Ai line dis ibu ion
Inno a ion esul s
Agency heo y
Incen i es managemen
Classifica ion codes
O00
O30
O32
In oduc ion
The di usion o echnology- ela ed inno a ions, when such di u-
sion occu s a he o ganisa ional le el and use s a e manda ed ex e -
nally, makes o a complex, li le-analysed se ing in which one
should econcile he sou ce o he adop ion decision and he subjec
o i s u ilisa ion, which do no always align (Galli an, 2001). These
adop ion challenges inc ease when we mo e om wi hin he o gani-
sa ion o an indus y o in e -fi m case as he absence o hie a chies
makes adop ion elian on o he ac o s in o de o he inno a ion o
be success ully adop ed. Managemen suppo —a ac o ha has
been consis en ly ound o be key in explaining adop ion (Jeya aj e
al., 2006)—canno be le e aged and beha iou s mus be con ac ed
o ba gained o , wi h pa ies pe o ming an assessmen o cos s and
benefi s in ol ed ahead o hei decision making. I is p ecisely in
hese indus y-wide se ings ha he in e play o goals and incen-
i es akes cen e s age.
While o he analysis exis ha look a in e nal incen i es —
whe he sho o long- e m ewa ds —insu ficien a en ion appea s
o ha e been gi en o how some o ganisa ions p omp o he fi ms o
inno a e; ha is, o an o ganisa ion o adop an inno a ion chosen
and p omo ed by ano he . This pape in ends o con ibu e o he
discussion on in oduc ion o an inno a ion ac oss mul iple playe s
in an indus y, o which we d aw on ins i u ional heo y, and o
unde s and how adop ion is a ec ed by he alignmen in s a egies
o he pa ies in ol ed. We do his by e iewing one indus y and an
inno a ion in pa icula : he case o using new dis ibu ion capabili y
(NDC) o sell passenge ai a el. NDC is a s anda d in oduced
wi hin he ai line indus y in 2012 o acili a e he exchange o a el
se ice- ela ed in o ma ion be ween a el agen s ( he selle s) and
ai lines ( he se ice p o ide s) (Pie eanu, 2019). As an inno a ion,
NDC enables he ans e o addi ional and iche in o ma ion abou
a el se ices be ween selle s and se ice p o ide s so ha he o -
me can p esen i s cus ome s wi h a wide and deepe po olio o
se ice op ions, po en ially imp o ing p ofi abili y (Wes e mann,
2013;Boin e al., 2019). Howe e , o such a ne wo ked inno a ion o
p ospe he e needs o be coope a ion be ween many s akeholde s.
Teece (1992) no ed ha , o new p oduc and new p ocess de elop-
men inno a ion o happen success ully, he e needs o be bo h ho i-
zon al and e ical coope a ion. His wo k a gues ha , in high
echnology, compe i ion-in ense en i onmen s, his coope a ion is
e en mo e necessa y and akes mo e complex shapes. We belie e
ha he inno a ion a ec ing he dis ibu ion o ai a el se ices
p esen s such cha ac e is ics and p opose ha some concep s om
he ins i u ional heo y (coe ci e and mime ic p essu es) and
om agency heo y (in o ma ion asymme y and oppo unis ic
* Co esponding au ho .
E-mail add ess: [email p o ec ed] (A. U ue~
na).
h ps://doi.o g/10.1016/j.jik.2024.100543
2444-569X/© 2024 The Au ho s. Published by Else ie España, S.L.U. on behal o Jou nal o Inno a ion & Knowledge. This is an open access a icle unde he CC BY license
(h p://c ea i ecommons.o g/licenses/by/4.0/)
Jou nal o Inno a ion & Knowledge 9 (2024) 100543
Jou nal o Inno a ion
&Knowledge
h ps://www.jou nals.else ie .com/jou nal-o -inno a ion-and-knowledge
beha iou s) can help us add ess a scena io o inno a ion ha has
been insu ficien ly esea ched.
The aim o his s udy is o e iew he s a e o adop ion o NDC in
he ai line indus y yea s in o i s in oduc ion by s udying i s e ec s
on he sales o a el se ices as epo ed o he BSP (billing se le-
men plan), a sys em o local clea ing houses ope a ed by he In e na-
ional Ai T a el Associa ion whe e he majo i y o a el-agen -
media ed passenge a el sales a e se led. Th ough he analysis o
he sales o ai a el a he icke le el du ing 2022 in h ee leading
ma ke s in he adop ion o NDC (Ge many, F ance, and G eece), we
posi ha he use o NDC should inc ease e enue pe icke based on
u he con ol by he se ice p o ide o e he o e ing (Wes e -
mann, 2013;Hoyles, 2015) and he abili y o con ey addi ional se -
ice op ions o he cus ome , which can be pe sonalised as pe
passenge s’willingness o pay (Wi man & Belobaba, 2017). Topol
sek
e al. (2014) e iewed he in eg a ion be ween a el se ice p o-
ide s and hei in e media ies a e ci ing lack o academic a en ion
in his space and ound coope a ion o be dependen on a el agen
size and con ingen on he cos e ec i eness o such coope a ion.
Then, B emne & Eisenha d (2022) e iewed he case o inno a ion
esul s in he d one indus y when a communi y o use s was behind
i and ound ha , in new o e ol ing ma ke s, he lack o coo dina-
ion be ween membe s was a disad an age when p oblems we e
complex and unce ain y high. In his con ex , ou esea ch ques ions
a e: Wha a e he mos ele an s imuli o agen s o use NDC? And
does NDC, as an inno a ion, gene a e highe e enues o ai lines?
We find ha such an augmen ed uni e enue appea s in a e y mod-
es amoun and i s e ec s could be flee ing and uns able. In ac ,
unde some o he models we use, hey e e when some p edic o s
ela ed o he o ganisa ion adop ion s age a e con olled o . We
belie e hese esul s sugges ha di e en selling pa e ns and
beha iou s a e eme ging ac oss he al e na i e dis ibu ion me hods
based on he playe s in ol ed, he go e nance mechanisms deployed
o hei ela ions, and pa icula ly he way each o hem p ocesses
incen i es agains hei compe i i e s a egies. Those beha iou s
poin o di e ging in e es s de eloping in selle s o e hose o hei
p incipals ( he ca ie s). Al hough he indus y-specific na u e o
NDC as an inno a ion should gi e us pause abou po en ial gene al-
isa ions, hese findings p o ide o an in e es ing discussion abou
how an indus y-wide inno a ion pa h o adop ion can be a ec ed by
ac o s ha anscend he bounda ies o a single o ganisa ion.
The emainde o his pape is o ganised as ollows. Sec ion wo
desc ibes he heo e ical backg ound ela ed o he opic. Sec ions
h ee and ou desc ibe he ma e ial and me hods and esul s, espec-
i ely. Sec ion fi e discusses he wo k and p esen s he s eng hs,
limi a ions, and u u e esea ch di ec ions, and sec ion six concludes
he pape .
Theo e ical backg ound
In e o ganisa ional adop ion o echnology inno a ions
So much has been said abou inno a ion in he li e a u e ha i is
di ficul o single ou one heo y o inno a ion, much less an all-
encompassing one, ha answe s ou ques ions. Ins ead, we should
s a by desc ibing he condi ions o ou in e es as we de e mine
which heo ies a e mos ele an and help ul o ou case (Wol e,
1994). Fo his wo k, we ocused ou a en ion on he way a echnol-
ogy inno a ion is adop ed by an o ganisa ion when i is p omp ed o
do so by ano he o ganisa ion. While s udies on he di usion o inno-
a ions (Roge s, 1995) and on he accep ance and use o echnology
(Venka esh e al., 2003) ha e con ibu ed g ea ly o ou unde s and-
ing o a ibu es o inno a ions in he adop ion p ocess, hey a e
somewha lacking in e ms o add essing he in e o ganisa ional con-
ex in which some inno a ions mus de elop (Pe i e al., 2024).
Whene e he inno a ion appea s as a echnology linking mul iple
fi ms, some o he mo i a ing ac o s behind i s di usion eme ge
om he confla ion o beha iou s, in e es s and goals o he many
playe s in ol ed. This gap can be filled h ough an ins i u ional
app oach ha o e s insigh s on a fi m’s sea ch o legi imacy, con o -
mi y o pa ne s, and ins i u ions’demands (Deephouse, 1996;Teo e
al., 2003;Mand inos & Lim, 2023) as d i e s o inno a ion. This se -
ing is u he comple ed by he ecogni ion o he di e ging, some-
imes ad e sa ial in e es s be ween dis ibu o s and hei se ice
p o iding p incipals, and he e ec s ha isk a e sion, asymme ic
in o ma ion, and claims o ou comes (Sapping on, 1991) ha e on
beha iou s.
Ai a el is an in o ma ion-in ensi e se ice indus y ha elies
in ensely on specialised echnology (Sismanidou e al., 2009;Ray-
mond & Be ge on, 1997), some o which is p o ided by in e media -
ies such as Global Dis ibu ion Sys ems (GDS). Fa hoomand (2000,p.
6) analysed how GDS came o occupy hei place as p i ileged
in e media ies: “A e de egula ion, he numbe o ca ie choices, a e
classes, and ou ing al e na i es we e beyond passenge s’comp ehen-
sion. Thei eliance on a el agen s’knowledge and expe ise g ew. A
he same ime, ai lines needed o achie e ope a ional e ficiency o com-
pe e in a ee ma ke . I was unde hese ci cums ances ha he CRS
came o p ominence”. The CRS (Cen al Rese a ion Sys ems, p ede-
cesso o he GDS) add essed he need o au oma e he ese a ion
and icke ing p ocess and in o ma ion flows.
Ai lines pay GDS booking ees o dis ibu ing i s o e ing o a ne -
wo k o a el agencies. In e u n, he GDS pays incen i es o hese
agencies o achie ing he sales olume i uses o jus i y i s ees o
he ai line, while also cha ging a el agen s o he use o i s echnol-
ogy. Also, ai lines pay commissions o a el agencies o he sales
ac i i y ha fills hei planes, e en hough commissions ha e been
g ea ly educed since he ad en o he In e ne (Alamda i, 2002).
Finally, consume s gain access o anspo a ion op ions h ough
a el agencies and pay ees o se ices ha ewa d he en i e alue
chain. O e ime, hese ela ionships ha e c ea ed an impo an ne -
wo k o in e es s ha can gi e ise o en enched posi ions and jus-
i y esis ance o changes ha endange hose in e es s.
Following he pa h o low-cos ca ie s, ai lines ha e been ackling
he cos s o dis ibu ion unde a ansac ion-cos -d i en, e ical
in eg a ion (Williamson, 1998), le e aging hei own dis ibu ion
channels, which ha e been enabled by he de elopmen s in e-com-
me ce and In e ne echnologies. Howe e , he exhaus ion o ha
p ocess and un elen ing compe i i e p essu e demand ha op imisa-
ion is also sough in he indi ec channels, seeking bo h e enues
and e ficiency. The NDC s anda d comes as an inno a ion ha
add esses hese issues (Alamda i & Mason, 2006), allowing ai lines o
c ea e o e s o a el agencies wi hou ha ing o go h ough he
GDS sys em. NDC p o ides he abili y o gene a e he o e dynami-
cally, allowing o g ea e cus omisa ion and elimina ing igidi ies in
communica ion messages. Wi man & Belobaba (2017a) ound ha
dynamically adjus ing o consume willingness o pay could lead o
highe incomes. In ac , ai lines ha e ecen ly s a ed o in oduce
dynamic p icing no only in he de elopmen o hei egula a es,
bu also in hei ancilla y se ice o e ings (Mumbowe e al., 2023).
NDC-adop ing ai lines could finally e ail hei se ices as eely and
e ficien ly h ough in e media ies as hey do when selling di ec ly,
e en i some au ho s ound ha such pe sonalisa ion was lacking
(Azzolina e al., 2021).
Adop ion o inno a ions
Iaco ou e al.’s (1995) pa simonious model o adop ion o a ech-
nology inno a ion p omo es h ee ac o s: pe cei ed benefi s o he
inno a ion, o ganisa ional eadiness, and ex e nal p essu es in he
o ganisa ional en i onmen . The pe cei ed benefi s o NDC come as
ai lines ma ke se ices mo e e ec i ely and do no need specialised
in e media ies o ha e hei o e ing con eyed o he selling poin
A. U ue~
na, M. S
aenz and A. Hidalgo Jou nal o Inno a ion & Knowledge 9 (2024) 100543
2
(Pie eanu, 2019). O ganisa ional eadiness akes a esou ce-based
iew and poin s o echnological and capabili y endowmen in he
fi m ha is compa ible and conduci e o inno a ion adop ion. I is
wo h no ing ha , o a a el agen o adop NDC a i s mos basic
le el, a mode a e in es men is needed, as ai lines using NDC ha e
c ea ed web applica ions h ough which icke s can be issued. How-
e e , many o he benefi s o his inno a ion will no be eaped by
agen s unless he e is a mo e complex in eg a ion wi h hei e-com-
me ce sys ems, ans o ming he sales p ocess o con ey he ull
dep h o he ai line’s o e ing. I is his combina ion o se ice o e ing
and i s in eg a ion wi h ope a ions and o he adminis a i e sys ems
ha has he mos significan impac on he company’s esul s. NDC is
a ne wo ked inno a ion ha has no been de eloped coope a i ely,
bu ins ead comes om he op o he alue chain wi h he in en ion
o flowing down om he e. The e o e, he challenge o his inno a-
ion’s di usion and impac lies in he ac ha i a ises p ima ily as a
manda e om one side (ca ie ) o ano he (agen ). This esponse
om one o ganisa ion o he beha iou o ano he in oduces an
ins i u ional elemen , one ha Iaco ou e al. cap u ed as ex e nal
p essu e. This p essu e appea s as a di e en ia ion s a egy in he
ace o compe i ion (Song & Wen, 2023), bu also as o ganisa ional
isomo phism seeking he legi imacy and social endo semen
a ached o inno a o s (Deephouse, 1996;DiMaggio & Powell, 1983).
Ins i u ional heo y explo es how social choices a e shaped, medi-
a ed, and channelled by he ins i u ional en i onmen (Pin o, 2017).
Ins i u ional heo y sugges s ha because fi ms and o he o ganiza-
ions ine i ably pu sue hei in e es s and objec i es wi hin social
con ex s, hey end o con o m o he ules, expec a ions, and belie s
exp essed by hei en i onmen (Meye & Rowan, 1977). A co e p in-
ciple o he ins i u ional pe spec i e is ha o ganiza ions sha ing he
same en i onmen will adop simila p ac ices, becoming ‘isomo -
phic’and he eby a aining legi imacy, posi i e social e alua ions
and success (DiMaggio & Powell, 1983). Th ee ypes o p essu es a e
iden ified ha ein o ce isomo phism (DiMaggio & Powell, 1983;
Sco , 1987). Fi s , coe ci e p essu es esul om p essu es exe ed
by mo e powe ul o ganiza ions; second, mime ic p essu es a ise
when o ganiza ions espond o unce ain y by adop ing he p ac ices
and o ganiza ional pa e ns o o he success ul o ganiza ions and
hi d, no ma i e p essu es s em om o ganiza ions’ endency o
adop p ac ices deemed app op ia e in hei en i onmen .
Based on all o he abo e conside a ions, Fig. 1 shows he final
model ha we ha e used in his s udy.
Wi hin he li e a u e e iew, ex e nal p essu e was iden ified as
he mos significan p edic o associa ed wi h he adop ion o an IT
inno a ion (Jeya aj e al., 2006). Ex e nal p essu e e e s o influences
om he o ganisa ional en i onmen (Iaco ou e al., 1995), whe e i s
wo mani es a ions a e (1) compe i i e p essu e and (2) imposi ion
by ading pa ne s (wi h g ea e impac ). Thei analysis, p edica ed
on he adop ion o Elec onic Da a In e change, can be ela ed in se -
e al ways o he adop ion o NDC gi en ha hey a e bo h ne wo k
inno a ions ha a e supposed o d i e ansac ion cos s down and
acili a e p ocess imp o emen s. He e, ai lines a e p omp ing he
a el agen s (selle s) o adop he inno a ion. Teo e al. (2003) s ud-
ied he case o EDI adop ion amongs financial ins i u ions and ound
ha no ma i e p essu es, ollowed by coe ci e ones and hen by
mime ic ones, all significan ly explained decision o adop he inno-
a ion. Ali e al. (2022) did no find significan e ec s o ex e nal ac-
o s, bu hei analysis ocused on aspec s ela ed o in o ma ion
in ensi y and business equi emen s and no on p essu e om busi-
ness pa ne s. Mahdaly & Adeina (2022) s udied he case o RFID
adop ion and ound ha ading pa ne s’p essu e was a significan
de e minan o adop ion. Howe e , Tiwa i e al. (2023) ound ha
p essu e by a ading pa ne was no s a is ically associa ed wi h
adop ion o he case o elec onic in oicing adop ion by fi ms in
India. Shaha uddin e al. also e iewed en i onmen al ac o s and
ound ha compe i i e p essu e was posi i ely influencing he
up ake o elec onic comme ce among Malaysian a el agen s. We
posi ha his en i onmen al p essu e is disp opo iona ely ele an
in in e o ganisa ional inno a ions.
Hypo hesis 1. Ins i u ional ac o s o ex e nal p essu e exe g ea
e ec in adop ing in e o ganisa ional, ne wo ked inno a ions.
Agen
−
p incipal misalignmen
P essu e coming om he en i onmen can appea as posi i e o
nega i e incen i es. The la e —penal ies o dis ibu ion su cha ges,
which many ai lines le y whene e he icke is issued wi hou NDC
(Vellapala h, 2018;Azzolina e al., 2021, p.10)—we e ound o be
less impac ul han incen i es in p omo ing inno a ing beha iou s,
especially whe e unce ain y is high (Pe i e al., 2024). Ca ie s pos-
sess key asse s in a el ma ke s ha pu hem in a posi ion o powe
be o e o he playe s in he alue chain and hey can le e age ha
imbalance o se condi ions o doing business (Fo d e al., 2012).
Why do ai lines eso o penal ies o ge a el agen s o adop NDC?
Shouldn’ all pa ies be ag eeing ha con eying a iche o e o pas-
senge s is beneficial ac oss he en i e alue chain? Bingeme (2018,
p. 211) p o ided a compelling desc ip ion o he di e ging in e es s
a ound he dis ibu ion o se ices: “Ai lines usually o e ancilla y
se ices fi s on hei own ai line websi es as hey ha e ull con ol o he
Fig. 1. Model o inno a ion e ec s o ne wo ked inno a ions
A. U ue~
na, M. S
aenz and A. Hidalgo Jou nal o Inno a ion & Knowledge 9 (2024) 100543
3
o e in his channel. In consequence, hey do no ha monise hese ancil-
la y se ices (as hey a e mean o di e en ia e) wi h o he ai lines. The
GDS p o ide s, in con as , a e seeking o make he di e en ai line o e s
as compa able as possible in o de o educe he sea ch complexi y o
he a el agen s. Thus, hey ha e a na u al in e es o suppo only he
de elopmen o hose ancilla y se ices ha a e implemen ed by mul i-
ple ca ie s hos ed in hei sys ems. Fo he case o ancilla y se ices, i is
ob ious ha he e is a conflic o in e es be ween being as much di e -
en ia ed as possible (ai line need) and s anda dizing as much as possible
(GDS need)”.Mumbowe e al., (2023) also epo ed esis ance om
ai lines in he US o inc eased anspa ency on ancilla y p ices wi hin
he GDS displays. So, he e is a di e gen in e es in an ai line wan -
ing o o e i s se ices abo e hose o he compe i ion a he lowes
possible dis ibu ion cos and a selle looking o o e as wide a po -
olio o se ices as possible wi h li le ega d o he supplie excep
o i s p e e ence going o hose ha ne he highes ma gin. The
e ec s o his dispa i y may a ec he li ecycle o his inno a ion.
T a el agencies’ac i i y as in e media ies also equen ly goes
beyond he me e selling o ai anspo a ion. Fo one, hey p o ide
ad iso y se ices and assis ance wi h a el needs, such as isa
a angemen s o immig a ion clea ances (Camille i, 2018, p. 21).
They also play an ac i e ole in de e mining he o e ing a ailable in a
ma ke (Bilo kach e al., 2013) and building bundles ha encompass
mo e han ai a el. This knowledge o hei cus ome s and hei
needs canno be easily accessed by he ai line, which ope a es on pa -
ial in o ma ion abou he eques ed se ice package and i s compo-
nen s beyond i s own o e . In such a se ing, o ganisa ional heo y
a ou s ou come-based con ol (Eisenha d , 1985) such as he dis i-
bu ion cha ges quickly sp eading among eme ging NDC ca ie s’
ma ke ing s a egies. Howe e , ocusing s ic ly on he choice o dis-
ibu ion me hod a ached o he a el se ice sale as a con ol
mechanism can ha e unin ended consequences, such as missing ou
on he alue o he se ice sold −as we shall see. A e all, he ai -
lines’s a egy o doing away wi h commissions and asking a el
agen s o collec se ice ees o hei ac i i ies kicks a ed di e -
gence o agendas (Alamda i, 2002). Finally, he agen has ano he
p incipal in he GDS ha also ewa ds i based on he olume o es-
e a ions made h ough i s sys em (Ra ich, 2004). These paymen s
ope a e as a disincen i e o he specific beha iou o adop ing he
NDC inno a ion in ha NDC dis ibu ed icke s do no coun owa ds
he incen i e scheme he agen has wi h he GDS. Ai lines hen
secu e he agen ’s coope a ion by applying penal ies o sales p oc-
essed ia a GDS (unde he jus ifica ion ha he agen should bea
he cos he GDS le ies on he ca ie o ailing o employ he cos -
ee al e na i e) (Boehme , 2023). These su cha ges o en come in
he o m o a fixed cos pe segmen o icke booked. When aced
wi h he choice o a dis ibu ion h ough NDC o GDS, a el agen s
will likely choose he bes financial op ion; ha is, he one ha allows
hem o ob ain a g ea e su plus once he commissions, incen i es,
and su cha ges a e conside ed.
In ou iew, he adop ion and e ec i eness o ne wo ked inno a-
ions lies in he s a egic alignmen o he playe s wi hin he alue
chain. Fo his eason and ollowing Pe i e al. (2024) we posi ha
incen i e ou weigh penal ies in he di usion o a ne wo ked inno a-
ion by inc easing alignmen .
Hypo hesis 2. The impac o incen i es on adop ion is la ge han
ha o penal ies.
Impac on fi m pe o mance
Swanson & Ramille (2004) wa ned ha o ganisa ions inno a e
mind ully when hey ca e ully conside a ailable a ionales and hei
fi o he ci cums ances o he fi m. T a el agen s would be inno a -
ing mind ully by sepa a ing he benefi s NDC b ings (exclusi ely) o
ai lines om indus y-wide ones and om hose acc uing o hem
based on hei dis inc posi ion in he ai anspo alue chain. Xin
and Choudha y (2019) eflec ed on he ac ha o ganisa ions a e
unlikely o in es in IT inno a ions unless hey a e confiden hey
will eap he ewa ds. In he absence o financial ewa ds, a el
agen s would see li le upside in eo ganising hei selling p ocesses.
T a el agen s a e al eady o e ing a se ice package o hei cus om-
e s ha equen ly anscends ai anspo a ion (Buhalis, 2004,p.
808) so he e is isk o c owding ou hei cu en business wi h ai -
lines’new, NDC deli e ed se ices. Also, J€
ackel and Maie (2016)
wa ned o he complexi y in ol ed in adop ing an inno a ion ha
equi es coo dina ed and join in es men s ac oss he many s ake-
holde s o i o yield maximum esul s.
None heless, abundan li e a u e has ound ha inno a ions
imp o e o ganisa ional pe o mance. Jim
enez-Jim
enez and Sanz-
Valle (2011) e iewed a hos o ex an confi ma o y s udies and pe -
o med a c oss-sec ional s udy on Spanish fi ms and ound ha inno-
a ion makes a significan , posi i e con ibu ion o business
pe o mance. Kannebley e al. (2010) p o ided a longi udinal analysis
on B azilian companies and equally assessed ha inno a i e fi ms
ou pe o m hei non-inno a i e coun e pa s, pa icula ly o p o-
cess- ela ed inno a ions and mainly on he fi m’s ne e enue. On
his basis, we a gue ha NDC —a p ocess inno a ion i sel —will p o-
duce a posi i e impac on pe o mance as well.
Hypo hesis 3. NDC will be associa ed wi h a highe e enue (pe
icke sold).
Me hodology
Da a
Fo his analysis, we ha e used anonymised da a om he In e na-
ional Ai T anspo Associa ion’s (IATA) BSP (Billing & Se lemen
Plan) clea ance sys em. This da a includes de ails o icke s clea ed
be ween a el agen s and ca ie s ha olun a ily join and use he
sys em o se le sales o passenge anspo a ion se ices amongs
he pa ies. IATA’s BSP enjoys a majo i y ma ke sha e among indi ec
sales ( ha is, sales no conduc ed di ec ly be ween he ca ie and he
passenge ) and can he e o e be conside ed ep esen a i e o he dis-
ibu ion o ai a el se ices using an in e media y, he space whe e
NDC as an inno a ion was in oduced. The BSP da a allow o obse -
a ions a he se ice le el, which in u n pe mi s analysis on specific
p ices paid o anspo a ion ac oss di e en buye s.
The da a used o he analysis co espond o sales o ai a el
clea ed in he BSP du ing 2022 in Ge many, F ance and G eece, ma -
ke s ha ha e been obse ed o ha e a head s a in adop ion o NDC
as an inno a ion. Se e al condi ions we e added o he da a se
be o e i was used in he model. Fi s , o isola e he issue o adop ion
( ha is, whe he he a el agen had de eloped some means and/o
capabili ies o issue icke s using he inno a ion), we only conside ed
a el agen s ha had logged a leas one icke using NDC as he dis-
ibu ion me hod du ing he pe iod e iewed. The eason o his was
o ensu e ha all agen s in he da a se ha e p o en he abili y o
employ he inno a ion and clea ed ini ial ba ie s o en y. Na u ally,
he abili y o conduc sales does no mean a comple e in eg a ion o
he echnology in o he back-o fice p ocesses in he selle , which is
wha should op imise he esul s and he benefi s acc ued by he
inno a o ; no does i gua an ee in e nal buy-in ha accompanies
success ul inno a ions (Iaco ou e al., 1995;Swanson & Ramille ,
2004). The o he es ic ion in oduced was, ollowing he app oach
in o he s udies, o conside only he fi s leg o icke s wi hou s op-
o e (Na angaja ana e al., 2014). This was done o ensu e compa a-
bili y and emo e e ec s om in e lining (s ill a he in ancy s age
unde NDC) and o he complexi ies de i ed om he a icula ion o
a el se ices h ough he combina ion and addi ion o di e en seg-
men s, which hemsel es can in oduce e ec s on he a e esul s
A. U ue~
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(Do inson & Belobaba, 2004). To elimina e any e ec s o equen
flye p og ammes, all eco ds wi h ze o a e amoun s we e dele ed
due o he suspicion ha hey could be icke s pu chased wi h miles
(Ge a di & Shapi o, 2009). Finally, only business class icke s we e
used: a p elimina y analysis shows bias in he mix o cabin a es ha
comes wi h he use o NDC. The e is a subs an ial highe weigh o
business cabin among GDS sales han in NDC sales conduc ed wi hou
he use o he GDS (business-class a es we e ou imes mo e e-
quen in GDS dis ibu ion han in NDC). This e ec alone is su ficien
o explain a subs an ially highe a e age e enue pe icke in GDS-
dis ibu ed icke s be o e any o he p edic o s a e accoun ed o . Fo
his eason, only business-class icke s we e conside ed. Once all con-
side a ions a e accoun ed o , he da a se used included 532,609
obse a ions.
Model o adop ion
We employed a logis ic eg ession o model o he classifica ion
o icke s o con ol o adop ion o NDC. Ou fi s s a is ical model
looks o p edic he odds o any gi en icke being dis ibu ed using
NDC o explain he ole a iables play in he choice o dis ibu ion
me hod. Logis ic eg ession gene a es esul s wi hin a ange o 0 and
1fi ing he needs o a p obabilis ic analysis (James e al., 2013,p.
144). Mahdaly and Adeina (2022) p oposed he use o logis ic
eg ession o model adop ion o he case o RFID adop ion in he
Saudi logis ic se ices indus y and ound i o ha e su ficien dis-
c imina ing powe , while Tiwa i e al. (2023) used i in hei model o
adop ion on elec onic in oicing. Ou p obabilis ic model o use o
NDC looks like his:
P NDCðÞ¼eb1
ðÞCOMM þb2
ðÞEMDþb3
ðÞPCTNDC þb4
ðÞSEGMNT þb5
ðÞHHI þb6
ðÞRTESHR þb7
ðÞCHARGE þb8
ðÞGDSSHR
The fi s con olling a iable is commissions (COMM), which a e
amoun s paid by ca ie s wi hou conside ing he o e ides. Fo his
analysis we ha e ob ained he commissions paid pe uni o dis ance
and no malised o a 0 o 1 ange.
Nex , we conside EMD (elec onic miscellaneous icke ), which
a e he documen s ha con ey ancilla y se ices sold along wi h he
basic anspo a ion se ice. Fo his analysis we used a dummy a i-
able ha no es whe he he icke was issued wi h a complemen a y
documen as a signal ha ancilla y se ices we e sold along wi h he
icke . Al hough EMDs a e qui e a flexible ehicle o include di e en
concep s, we ha e excluded all cases whe e he EMD was used o
con ey a penal y o he passenge . The economic alue o he final
anspo a ion bundle is se as he dependen a iable and accoun ed
o in he eg ession we desc ibe la e in his pape .
The pe cen age o icke s sold using he inno a ion ( ha is, sold
wi h he NDC s anda d) is he con ol PCTNDC. This a iable is ela ed
o p esen adop ion ( ha is, he ex en o which agen s a e using he
inno a ion). We ac o bo h he pe cen age o icke s wi h he inno-
a ion o a el agen s (NDCAG) and o ai lines (NDCAL), as wo
sepa a e a iables.
Since he a el agen s’ alue as in e media ies is essen ially
de e mined by hei abili y o each some segmen s o he ma ke
ha he ai line has di ficul y eaching by i sel (Chi cu e al., 2001), i
seems app op ia e o conside he specialisa ion o na u e o he
a el agen . Fo his eason, he model inco po a es some dummy
a iables o desc ibe he ype o a el agen selling, wi h h ee di e -
en g oups: online a el agen s (OTA), which ypically ocus on
younge a elle s wi h a high weigh o leisu e des ina ions; a el
managemen companies (TMC), which mos ly wo k a ound business
anspo a ion needs; and, finally, e e y o he a el agen is placed
in o a hi d ca ego y.
We de i e he sha e o ma ke o he ca ie h ough he es ima-
ion o he He findahl index (HHI), an indica o ha is equen ly
employed in ai line p icing li e a u e and can be seen as a measu e o
he abili y o a ca ie o d i e selle s. Concen a ion is also associa ed
wi h p icing powe , and he e a e di e ging analyses on he impac o
ma ke concen a ion on p ices. Somewha coun e -in ui i ely, Bo -
ens ein and Rose (1994) ound he concen a ion o be in e sely co -
ela ed wi h p ice dispe sion, which he au ho s a ibu ed o he
esul s o mo e sophis ica ed yield managemen allowing a be e
p ice disc imina ion ( he dominan ca ie s would be able o cap u e
highe -end consume s and maximise p ofi s). Ge a di and Shapi o
(2009) ob ained opposi e esul s using a longi udinal app oach, in
line wi h a mo e classical in e p e a ion o compe i ion educing dis-
pe sion. Mo e ecen ly, Howell and G i ell-Ta j
e (2022) claimed o be
able o econcile bo h iews by ac o ing he he e ogenei y o he
p oduc in each ou e. Following he abo e au ho s and Bilo kach and
Pejcino ska (2011), we compu ed he He findahl index o he ca -
ie s included in ou obse a ions as a con olling a iable on p ices.
We also ac o he sha e o he ca ie wi hin he ou e, RTESHR.
While we do no accoun o ca ie s ha do no epo sales in he
IATA BSP, his dimension can be hough o as a p oxy o he ca ie ’s
ma ke powe in each ou e.
We ha e conside ed he dis ibu ion su cha ges (CHARGE) le ied
by ca ie s om he a el agen s as he las independen a iable
wi hin he ex e nal p essu e g oup. The e is significan noise a ound
hese cha ges as ai lines include hem unde a gene ic codifica ion
o ai lines and so-called uel su cha ges, so i is no possible o ell
when he ca ie is in ac collec ing o he hings. While he e enue
a iable ha we use as dependen a iable is ne o hese cha ges, i
is expec ed ha he e will be some co ela ion be ween a iables
since some o hese ees a e buil as a unc ion o he se ice cos . All
cha ge a iables he e ha e been exp essed on a pe km basis and no -
malised o a 0 o 1 ange.
The sha e o sales wi hin he GDS sys em, GDSSHR, is calcula ed as
he pe cen age o icke s wi hin a GDS a gi en a el agen has
eco ded, and we ake his as a measu e o alignmen . GDS p o ides
incen i es o a el agen s based on hei sales, so he sha e o sales
ha a gi en selling poin has wi hin a GDS can be conside ed a mea-
su e o misalignmen be ween he ca ie and he a el agen . Duliba
e al., (2001) in es iga ed loca ions wi h a gi en ese a ion sys em
o p edic ai line ma ke sha e and ound ha a iable o be he sec-
ond mos explica i e (a e numbe o depa u es). By obse ing he
alue o ha agen o i s o he p incipal we ge a measu e o align-
men be ween ca ie and a el agen . Alignmen and ope a ional
pe o mance a e ha dly s ange s. Aslam e al. (2021) e iewed he
e ec s o blockchain in he oil indus y in Pakis an and ound ha a
close ela ionship wi h supplie s was he dimension ha had he
s onges and mos significan impac on pe o mance, ollowed by a
close ela ionship wi h cus ome s.
Fu he desc ip ion o he a iables is p o ided in he appendix.
Using ou adap ed model o adop ion and e ec s o inno a ion we
can asc ibe he abo e con ols o he ollowing ca ego ies: pe cei ed
benefi s (COMM, EMD), o ganisa ional eadiness (NDCAG, NDCAL,
SGMNT), ex e nal p essu e (HHI, CHARGE, RTESHR), and alignmen
(GDSSHR). Table 1 cap u es he main s a is ical desc ip o s o he
da a used.
A co ela ion ma ix on he a iables is p o ided in Table 2. Va ia-
bles adding o he final icke cos we e e iewed o endogenei y as
he cha ges hemsel es could be a unc ion o he base a e applied.
Co ela ion indices do no show abno mal alues ha would sugges
he eg ession esul s a e no alid. We also es ima ed VIF ( a iance
infla ion ac o ) and confi med absence o collinea i y (James e al.,
2013, p. 112), wi h alues consis en ly unde fi e.
Model o o ganisa ional pe o mance
We employed a linea mul i a ia e eg ession o es ima e he
impac o NDC in he ai line financial pe o mance; ha is, o explain
he e enues ob ained by he ca ie on a gi en icke so we can
A. U ue~
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5
assess he specific e ec o NDC as he dis ibu ion choice on i . Mul i-
a ia e lineal eg ession model is an app oach ha has been used o
icke p ice beha iou analysis by se e al au ho s (Mumbowe e al.,
2014;Bilo kach & Pejcino ska, 2011). We wo k wi h he e enue pe
km ne o any cha ges and ees as he dependen a iable, and he e-
o e use he p ice pe icke sold (a financial dimension) as a measu e
o impac o NDC ( he inno a ion).
The model has he ollowing o m:
xðÞ¼a1þb1
ðÞCOMM þb2
ðÞEMD þb3
ðÞPCTNDC þb5
ðÞSEGMNT
þb6
ðÞHHI þb7
ðÞRTESHR þb8
ðÞCHARGE þb9
ðÞGDSSHR
þb10
ðÞNDCF þb11
ðÞWEEKMONTH þb12
ðÞDAYS
þb13
ðÞDIST þb14
ðÞINTL
The dimensions employed in he eg ession a e he same as hose
ha we used in he logis ic eg ession, along wi h some o he s
known o be p esen in he ai line e enue managemen sys ems,
which we desc ibe nex .
We ha e in oduced dummy a iables o weekdays and o he
mon h o depa u e (WEEK MONTH) he fligh has. The an icipa ion
o he pu chase ahead o he fligh da e is he a iable DAYS. I is a
common elemen in e enue managemen o segmen he ma ke ia
di e en in en o ies ha inc ease in p ice as he ime o depa u e
app oaches. Along wi h he day o he week on which he fligh
occu s, hey ha e been ound o be significan in p ice de e mina ion
(Mumbowe e al., 2014;Koenigsbe g e al., 2008) and o be disc imi-
nan abou he ype o cus ome segmen /pu pose o fligh and o be
posi i ely co ela ed wi h p ice, wi h business/co po a e a el being
skewed owa ds sho e no ice and s ays ha do no include week-
ends (i is wo h ei e a ing ha ou da a se only conside s business-
a e-class icke s, al hough his does no mean ha he fligh is neces-
sa ily o business pu poses).
To al ip dis ance (DIST) is ano he a iable p edic ing final e e-
nue (B ueckne e al., 2013). He e we ha e no malised dis ances o a
ange be ween 0 and 1. Whils longe ips do come a a highe cos
o he passenge , he ma ginal e enue pe addi ional uni o dis-
ance is a diminishing one. Along wi h he dis ance, we ha e used a
dummy a iable ha flags when he ou e is in e na ional ( ha is, o
a des ina ion ou side he coun y), INTL.
Impo an ly, we now include he choice o dis ibu ion —NDCF, a
bina y a iable desc ibing whe he he icke was issued using NDC
o no , which was ou dependen a iable in he adop ion model—as
a a iable explaining obse ed p ices, so we can s udy he e ec s o
he inno a ion on financial esul s.
Resul s
NDC adop ion model es ima ion
Since all ou a iables ha e been no malised o anges be ween 0
and 1, he esul s allow us o compa a i ely e iew he independen
a iables by looking a he ela i e sizes o hei coe ficien s. The
adop ion model based on he logis ic eg ession showed ha com-
missions paid by ai lines was he independen a iable ha had he
g ea es impac on he odds o a ansac ion ( a el se ice sale)
occu ing unde NDC. The pe cen age o ansac ions unde NDC
(which we ha e indica ed as a measu e o he eadiness and deg ee
o adop ion o he inno a ion by he ca ie ) comes a dis an second
a e he commissions e ec bu sugges s ha ( echnological) eadi-
ness is a ele an ac o . The su cha ge s uc u e ( ha is, penal y o
no using he inno a ion) and he ma ke powe o he ca ie a e
also s a is ically significan and ele an , sugges ing ha ins i u ional
Table 1
S a is ical desc ip ion o he a iables
NDC sha e commission Dis ance To al Re . HHI R e. Sha e Days o Fly Cha ge Km
Numbe o Values 530,277 530,277 530,277 530,277 530,277 530,277 530,277 530,277 530,277
Null alues - 155,010 450,071 - - 10,014 - 50,445 82,406
min 0 0 0 18 -476 0.0 0.0 0.0 -0.5
max 1 1 676.12 17,039 60,713 0.2 1.0 351.0 6.4
ange 1 1 676.12 17,021 61,189 0.2 1.0 351.0 6.9
median 0 0.03 0 1,218 440 0.0 0.9 14.0 0.0
mean 0.089 0.245 2.114 2,363 1,020 0.0 0.8 33.1 0.0
SE. mean 0.00 0.00 0.01 4 2 0.0 0.0 0.1 0.0
a 0.08 0.14 107.05 7,439,555 2,369,563 0.0 0.1 2315.0 0.0
s d. de 0.28 0.38 10.35 2,728 1,539 0.1 0.3 48.1 0.1
coe . a 0.26 1.55 4.89 1 2 1.6 0.4 1.5 1.6
Table 2
Co ela ion among key a iables
TMC OTA NDCF EMD GDSSHR HHI RTESHR CHARGE COMM Re Km NDCAG NDCAL DAYS DIST INTL
TMC 1.0
OTA 0.363 1.0
NDCF 0.060 0.012 1.0
EMD 0.054 0.138 0.017 1.0
GDSSHR 0.282 0.831 0.024 0.156 1.0
HHI 0.271 0.263 0.082 0.004 0.301 1.0
RTESHR 0.003 0.076 0.052 0.049 0.116 0.241 1.0
CHARGE 0.007 0.053 0.006 0.043 0.078 0.068 0.055 1.0
COMM 0.043 0.063 0.195 0.019 0.046 0.110 0.102 0.083 1.0
Re Km 0.143 0.221 0.084 0.043 0.241 0.244 0.000 0.710 0.298 1.0
NDCAG 0.252 0.310 0.412 0.058 0.364 0.229 0.041 0.057 0.131 0.102 1.0
NDCAL 0.112 0.205 0.584 0.042 0.207 0.204 0.090 0.082 0.298 0.240 0.228 1.0
DAYS 0.144 0.065 0.024 0.041 0.069 0.098 0.020 0.037 0.058 0.133 0.063 0.101 1.0
DIST 0.064 0.186 0.102 0.016 0.203 0.099 0.055 0.100 0.094 0.120 0.147 0.067 0.184 1.0
INTL 0.189 0.122 0.162 0.023 0.123 0.416 0.053 0.004 0.159 0.225 0.003 0.331 0.174 0.310 1.0
A. U ue~
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elemen s do ha e e ec s on he a el agen ’s beha iou s, confi ming
ou fi s hypo hesis ha , in he case o in e o ganisa ional inno a-
ions, ins i u ional p essu es (coe ci e, and mime ic, and no ma i e)
exe ele an e ec s on he fi ms’beha iou s. I is impo an o
emembe ha NDC is s ill in i s in ancy, adop ion-wise, so NDC
ansac ions a e mo e likely han no o no happen in he fi s place.
Pe o ming McFadden’sR
2
calcula ion, which allows o an es i-
ma e o he model fi in he case o logis ic eg essions, we ob ain
esul s consis en wi h a solid explaining powe o he model
(Table 3). Using AIC −−Akaike In o ma ion C i e ion, a s a is ic ha
helps find he bes model by conside ing bo h esidual e o
minimisa ion and a iance explana ion maximisa ion (James e al.,
2013)−− on bo h models, we see ha he model wi h he combined
adop ion ( ha is, ac o ing he in e ac ion o NDC bo h by ai line and
agen ) a iable imp o es fi . We fi o he models wi h less a iables,
emo ing hose wi h he lowe coe ficien s in a backwa d s epwise
selec ion, and disca ded hem based on wo se AIC sco es; we ha e
no included hem in his analysis o b e i y. A Chi-squa e es on
no mali y o esiduals was posi i e. Table 3 and Fig. 2 include he
coe ficien s o he model, which a e significan a p<0.001 excep o
RTESHR, which is no significan .
The ci cums ance o an agen being ocused on he co po a e ma -
ke (SEGMNT unde i s TMC o m) educes he odds o an NDC ans-
ac ion, bu he e ec is mode a e. As discussed abo e, adop ion o
he co po a e ma ke demands a bigge ans o ma ion o he agen ’s
sys ems and p ocesses. Con e sely, o online a el agen s, which
a e ech- iendly bu leisu e-o ien ed o ganisa ions, he odds o use
o NDC imp o e, also by a modes bu significan amoun . I seems
ha his dimension poin s o a eadiness elemen cap u ed as well in
he pe cen age o NDC ansac ions (NDCAG). The ma ke dominance
by he ca ie —a p oxy o ading pa ne p essing powe and
encapsula ed in he HHI indica o —has a modes e ec bu a deg ee
o adop ion by he ca ie (NDCAL, pe cen age o ansac ion wi h he
inno a ion) and he a el agen (NDCAG) shows a ma e ial impac .
This sugges s ha he in es men s made and changes commi ed by
he pa ies —wha Roge s (1995) called edefining/ es uc u ing o
he inno a ion adop ion p ocess—in adap ing o NDC is a ele an
condi ion.
Do incen i es ou weigh penal ies in he decision o adop NDC, as
we posi ed in ou second hypo hesis? Ou da a do sugges so. Com-
pa ing he coe ficien s o commissions and penal ies, we find he
o me o be ma e ially highe . Bo h a e significan .
To explo e he ques ion o whe he syne gies s em om he syn-
ch onisa ion o o ganisa ions, we in oduced a new dimension,
NDCAL * NDCAG, in a second logis ic eg ession model. The pu pose
was o unde s and how he combined eadiness impac s adop ion.
This new dimension, which akes he p oduc o ela i e adop ion in
bo h in e ening o ganisa ions, jumps in he anks o p edic ing
powe wi h a coe ficien ha comes close o COMM (no malised
commissions pe dis ance a elled) and is also significan . F om an
ins i u ional pe spec i e, we can assess ha he esponse o one o ga-
nisa ion ( he selle ) o ano he ’s ( he ca ie ), whe he as a mime ic
Table 3
NDC classifica ion logis ic model coe ficien s
Independen Va iables Logis ic eg ession Log. Reg ession w
combined u iliza ion
TMC -0.468780744***
(0.02297759)
-0.4108781***
(0.02360588)
OTA 0.147124295***
(0.0338049)
0.28592617***
(0.03602893)
GDSSHR 2.272817086***
(0.04228743)
1.90895978***
(0.04448348)
HHI 2.820960316***
(0.02479877)
2.45203637***
(0.02517513)
CHARGE -3.463312597***
(0.1042646)
-3.72195296***
(0.10996386)
COMM 73.945899938***
(2.05501775)
69.07785439***
(1.93873083)
EMD 0.231708241***
(0.02661537)
0.26735666***
(0.02627165)
NDCAL 18.81923533***
(0.09805977)
12.15557411***
(0.1692055)
NDCAG 11.756058209***
(0.0749929)
6.20779316***
(0.13701939)
RTESHR 0.001038124
(0.03184458)
-0.04358914
(0.03234165)
NDCAL * NDCAG 39.39349452***
(0.84957)
Model Fi
McFadden’s Pseudo R2 0.5882469 0.5957534
AIC (Akaike In o ma ion
C i e ion)
130,959 128,574
No e: s anda d e o s o he coe ficien s in pa en hesis
Significance le els: ‘***’=p<0.001, ‘**’=p<0.01, ‘*’=p<0.05
Fig. 2. Coe ficien s o he logis ic eg ession
A. U ue~
na, M. S
aenz and A. Hidalgo Jou nal o Inno a ion & Knowledge 9 (2024) 100543
7
o coe ced beha iou , appea s as ele an ac o in adop ion. We
should be cau ious abou causali y gi en he c oss-sec ional na u e o
ou analysis, and we ouch on his on limi a ions o ou analysis
below.
Pe o mance esul s
Ha ing e iewed he ac o s behind adop ion, we now use lineal
eg ession models o add ess he impac on e enue, and he ole
NDC plays in i , as a measu e o pe o mance. We employed h ee di -
e en models he e o analyse and discuss some in e ac ion be ween
p edic o s. We s a wi h a model ha does no conside in e ac ions.
Looking a he esul s, some o he coe ficien s a e consis en wi h
p io analysis on ai line a es: uni e enues inc ease wi h sho e
pe iod o fligh da e, o when s a ing da e alls on a weekday s
weekend (Koenigsbe g e al., 2008). Concen a ion o ma ke powe
co ela es wi h a highe e enue bu sha e o a fic in each ou e
showed a small nega i e coe ficien ( his could be ela ed o he leas
p ofi able ou es a ac ing a smalle numbe o supplie s, bu also
could be a ec ed by low-cos ca ie s, which do no ypically use
in e media ies o hei dis ibu ion and a e no conside ed in hese
es ima es). The dummy a iable o agen segmen showed ha
a el managemen companies do co ela e wi h highe e enues,
consis en wi h a a ge cus ome willing o pay highe a es o a oid
es ic ions ( o example, he need o s ay o e a weekend, cancella-
ion, o modifica ion e ms) ha come wi h he lowe p ices (G ana-
dos e al., 2011;Vinod & Moo e, 2009). Online a el agen s, which
ha e an expec ed highe concen a ion o leisu e a el, p esen a
nega i e coe ficien . All coe ficien s a e ound o be significan (p <
0.001). Model coe ficien s a e included in Table 4.
The p edic o s ha showed he s onges e ec on uni p ices (ou
measu e o impac ) we e hose eflec ing cha ges and commission
le els; ha is, hose o ming he incen i e scheme behind he NDC
adop ion and hose belonging o he ex e nal p essu e exe ed by
ading pa ne s o he fi m (Fig. 3). Conside ing ha all alues in he
da ase had been no malised o anges be ween 0 and 1, he size o
he coe ficien s p o ides a ela i e measu e and alida es ou asse -
ions so a ha in hese ypes o ne wo k inno a ions ins i u ional,
alue chain dimensions a e o fi s -o de impo ance.
Ou esul s showed ha using NDC as he dis ibu ion me hod
( he inno a ion) has a weak bu posi i e e ec on dis ance adjus ed
e enue. In e es ingly, i we build a second model adding he pe -
cen age o NDC icke s sold by he ai line (NDCAG) as a eg esso ,
he e is a flip o he sign o he coe ficien o NDC, which becomes
nega i e, albei almos ze o. The e e sal sugges s he exis ence o
some in e ac ions amongs a iables (James e al., 2013). When using
a ( hi d) model ha bo h con ols o he pe cen age o NDC icke s
by he ca ie in he pe iod and i s in e ac ion wi h he use o NDC,
he sign o he NDCDST dimension becomes posi i e again. Howe e ,
he ac ha he in e ac ion o NDC adop ion by he ca ie and use o
NDC by he a el agen appea s nega i e implies ha ai lines wi h a
highe adop ion (and hus p essu e o hei a el agen s) we e no
ealising highe e enues pe uni o dis ance han less ad anced
pee s. These in e ac ions me i some a en ion and, in ou iew, illus-
a e a possibly ele an business p oblem, which we elabo a e on
nex .
Using a simplified model o jus wo a iables in e ac ing ( ha is,
he NDCDST a iable and he pe cen age o NDC ansac ions by he
ai line NDCAL, along wi h hei in e ac ion, NDC*NDCAG) shows ha
he ipping poin on he e enue coe ficien comes a an adop ion
a e o app oxima ely 15 pe cen ; in o he wo ds, ai lines wi h o e
Table 4
Lineal eg ession es ima ing ne e enue pe uni o dis ance.
Independen Va iables Model wi h ALNDCPCT Model wi hou ALNDCPCT Model wi h In e ac ions
COMM 29.683145
(0.1186685) ***
30.274005
(0.116632) ***
29.986262
(0.119452) ***
EMD 0.0489439
(0.002417) ***
0.047975
(0.002418) ***
0.048998
(0.002416) ***
NDCAG -0.1408861
(0.005383) ***
-0.123276
(0.005345) ***
-0.13508
(0.005387) ***
NDCAL 0.1176568
(0.0044401) ***
N/A 0.269129
(0.008328) ***
TMC 0.0367373
(0.0014003) ***
0.03883
(0.001399) ***
0.036567
(0.0014) ***
OTA -0.0748308
(0.0021882) ***
-0.077194
(0.002188) ***
-0.074962
(0.002187) ***
HHI 0.2569301
(0.0018565) ***
0.260532
(0.001853) ***
0.235
(0.002118) ***
RTESHR -0.1035083
(0.0019893) ***
-0.107236
(0.001986) ***
-0.10533
(0.00199) ***
CHARGE 32.452457
(0.0493701) ***
32.559022
(0.049239) ***
32.14418
(0.051391) ***
GDSSHR -0.1036631
(0.0026753) ***
-0.110378
(0.002665) ***
-0.101135
(0.002677) ***
NDCF -0.0003904
(0.0024956)
0.032852
(0.002159) ***
0.037549
(0.003056) ***
DAYS -0.2124246
(0.0040559) ***
-0.21738
(0.004054) ***
-0.210504
(0.004055) ***
DIST -0.1492281
(0.0038551) ***
-0.145388
(0.003855) ***
-0.147378
(0.003854) ***
INTL -0.1478521
(0.0018072) ***
-0.157023
(0.001775) ***
-0.156223
(0.001848) ***
NDC*NDCAL N/A N/A -0.227289
(0.010575) ***
Model fi
Adjus ed R
2
0.5832 0.5827 0.5836
No e: s anda d e o s o he coe ficien s in pa en hesis
No e 2: o b e i y we do no include coe ficien s o he day o he week and mon h dummy a iables. They a e
all smalle han 0.0723 and significan a p <0.001 excep dummy weekend which is a p <0.01.
A. U ue~
na, M. S
aenz and A. Hidalgo Jou nal o Inno a ion & Knowledge 9 (2024) 100543
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