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A New Model o he Calcula ion o Cus ome
Li e- ime Value in I anian Telecommunica ion
Companies
Reza Samizadeh
Assis an P o esso , Depa men o Indus ial Enginee ing, Alzah a Uni e si y,
Teh an, I an
Hamid eza Koosha
Assis an P o esso , Depa men o Indus ial Enginee ing, Fe dowsi
Uni e si y o Mashhad, Mashhad, I an
Soudabeh Namda Zangeneh
Assis an P o esso , Depa men o Indus ial Enginee ing, Alzah a Uni e si y,
Teh an, I an
Saha Va ankhah
1
Depa men o Indus ial Enginee ing, Alzah a Uni e si y, Teh an, I an
Abs ac
In his pape , we p oposed a new model o e alua e a cus ome 's li e ime
alue, conside ing non- inancial elemen s such as he cus ome ’s chu n
p obabili y, coope a ion capabili y, willingness o e e , willingness o
ecommend, and inno a ion. We es ed ou p oposed model on cus ome da a
om a mobile phone ope a o o e alua e he e ec o each elemen on he
cus ome 's li e ime alue. Fou hund ed and wen y ques ionnai es we e
dis ibu ed and 400 ques ionnai es we e de e mined o be sui able o ou
s udy. We employed s uc u al equa ion modeling using Sma -PLS so wa e
and we ha e ound ha he inno a ion, cus ome ’s chu n, willingness o e e ,
and coope a ion elemen s ha e he s onges e ec on he cus ome 's li e ime
alue.
Keywo ds: Cus ome li e ime alue, cus ome inno a ion, coope a ion
po en ial, willingness o ecommend, willingness o e e , chu n
Ci e his a icle:Samizadeh, R., Koosha, H., Zangene, S. N., & Va ankhah, S. (2015). A
New Model o he Calcula ion o Cus ome Li e Time Value in I anian Telecommunica ion
Companies. In e na ional Jou nal o Managemen , Accoun ing and Economics, 2(5), 394-403.
1
Co esponding au ho ’s email: Sa. a an[email p o ec ed]m
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395
In oduc ion
Wi h he ad en o a mo e compe i i e economic en i onmen , concep s such as
cus ome o ien a ion and cus ome sa is ac ion a e conside ed a basis o business, and
o ganiza ions ha do no pay a en ion o hem will be elimina ed om he ma ke .
Nowadays, o ganiza ions do no ely on hei p oduc s selling, bu a he p e e o
a ac , and subsequen ly e ain, p o i able cus ome s. Resea ch demons a es ha some
o he mos success ul o ganiza ions ha e a cus ome e en ion a e o mo e han 90%
(Haenlein e al. 2007). The mos impo an challenges in cus ome -o ien ed
o ganiza ions can be exp essed as iden i ying cus ome s, unde s anding he di e ences
be ween hem and classi ying hem (Liang 2011). We canno say ha all cus ome s will
make a simila con ibu ion o an o ganiza ion’s success, so inc easing he sa is ac ion
o key cus ome s is i al (Gli o d 2005). In addi ion, o ganiza ions ha claim i is no
necessa y o spend money o gain cus ome s a e, ina en i e o cus ome p o i abili y
le els (Bla be g e al. 2001; Bla be g e al 1996) To de e mine which class o
cus ome s is mo e aluable han o he s, and which cus ome s (asse s) o a ge , while
ope a ing wi h a es ic ed budge , we mus p o ide a plan o maximize he in es men
p o i (choosing he bes cus ome s). A concep such as cus ome li e ime alue (CLV),
which ocuses on cus ome beha iou , makes his possible. The main idea o CLV, i s
de ined 30 yea s ago by Ko le , is o e alua e cus ome s based on hei p o i abili y o
he o ganiza ion, de e mining he cu en alue o he expec ed u u e income s eam
du ing a speci ic pe iod o ime, while communica ing wi h cus ome s (Han e al. 2012).
The main pu pose o calcula ing CLV is o es ima e cus ome weigh ing and, based on
his, assign hem he ele an le el o esou ces. E alua ing CLV p o ides a me hod o
cus ome compa ison and, in indus y o example, makes i possible o p o ide dis inc
p oduc s and be e se e cus ome s wi h highe CLV. A g ea deal o esea ch has been
de o ed o calcula ing CLV, wi h mos based on he equa ion p oposed by Be ge and
Nas (Be ge & Nas 1996) which can be conside ed as ollows.
𝐶𝐿𝑉 =∑(𝑅𝑖−𝐶𝑖)
(1+𝑑)𝑖
𝑛
𝑖=1
(1)
In equa ion (1), i co esponds o he ime ho izon, 𝑅𝑖 is he acqui ed income om he
cus ome o e a pe iod i, 𝐶𝑖 is he o al cus ome cos s o e a pe iod i and n is he
numbe o pe iods. The e exis o he models o calcula e cus ome li e ime alue.
Hwang e al (2004) we e he i s au ho s o use cus ome chu n p obabili y in hei
model. Cheng and Chen (2009) and Liang (2010) used he RFM model o e alua e
cus ome li e ime alue. In his model, R de i es om he wo d ‘ ecency’ ha e e s o
he in e al be ween he cus ome ’s las pu chase and now, F de i es om he wo d
‘ equency’ ha e e s o he numbe o cus ome pu chases o e a ce ain pe iod o
ime and M de i es om he wo d ‘mone a y’ ha e e s o he alue o cus ome
pu chases o e he same pe iod o ime in eal. In he RFM me hod, we i s calcula e
he pa ame e s M, F and R o each cus ome . Chan e al (2010) and Donke s e al
(2007) used a Ma ko Chain model o calcula e CLV. Glady e al (2009) used a
Pa e o/NBD model. Han e al (2012) used non-quan i a i e elemen s and u h o
calcula e CLV and ha e p oposed a new me hod o quan i y hese elemen s. Cheng e al
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(2012) in oduced a new model based on a Ma ko Chain model o calcula e CLV.
Chen and Fan (2013) conside ed cus ome dynamic pu chase beha io in hei p oposed
model.
A e e iewing he li e a u e, we ound ha mos o he s udies conside ed only
inancial elemen s ha a ec CLV bu didn’ pay a en ion o non inancial elemen s. In
he cu en pape , we conside inancial and non inancial elemen s simul aneously and
quan i y CLV based on hese elemen s. Figu e 1 shows he concep ual model o he
ela ionship be ween de ined elemen s o he esea ch. This concep ual model
demons a es he ela ionships be ween a iables in which accu acy is no examined
using expe imen al da a.
CLV
Coope a ion
P ice
En e ain
Quali y
In imacy
Sa is ac ion
T us
Change
obs acles
Chu n
Willingness o
ecommend
Willingness
o e e
Inno a ion
Figu e 1 Resea ch Concep ual model
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397
Ma e ials and me hods
In es iga ion me hodology
The p esen esea ch acco ding o i s goal can be classi ied o applied esea ches
ca ego y and acco ding o i s me hod is ca ego ized as a su ey esea ch, because we
use ques ionnai es o agg ega e da a. Based on ou s udies, esea ches, scien i ic pape s
and s udies in simila con ex p o ided by eliable in e na ional P o esso s, esea che s
and scien is s, o e alua e and measu e each desi ed c i e ion and pa ame e , we need 2
o 6 ques ions o acqui e scien i ic and documen a y esul s. So in ou esea ch, we ha e
used 2 o 6 ques ions o each a iable o agg ega e necessa y da a. The esea ch
ques ionnai e has included 36 ques ions, e alua ing 3ques ions abou cus ome chu n, 3
ques ions abou cus ome sa is ac ion, 6 ques ions abou change obs acles, 3 ques ions
abou se ice quali y, 2 ques ions abou se ice cos , 2 ques ions abou us wo hiness,
2 ques ions abou in imacy, 3 ques ions abou en e ainmen , 2 ques ions abou e e ing
willingness, 2 ques ions abou ecommenda ion, 3 ques ions abou coope a ion, 4
ques ions abou inno a ion and inally 1 ques ion abou cus ome li e ime alue
(acco ding o la e acqui ed p o i om cus ome ). These a iables a e exp essed in
Table-1. The ques ions a e g aded by 5 poin s Like Scale (in his scale, poin 1 means
e y low, poin 2 means low, poin 3 means mode a e, poin 4 means high and poin 5
means e y high). The esea ch s a is ical popula ion is he en i e se o cus ome s
co esponding o one o I anian mobile-phone ope a o s. 420 ques ionnai es ha e
p o ided o sample peoples and 400 o hese ques ionnai es de e mined as sui able o be
he base o S a is ical calcula ions. Figu e 1 shows he concep ual model o he
ela ionship be ween he a ious de ined elemen s o he esea ch. The concep ual
model demons a es he ela ionships be ween a iables, al hough hei accu acy is no
examined expe imen ally.
The main assump ion o ou esea ch can be conside ed as ollows: Non inancial
elemen s a ec ing cus ome li e ime alues consis o inno a ion, coope a ion
capabili y, willingness o e e , willingness o ecommend and chu n. We also ha e wo
seconda y assump ions:
- The chu n elemen has a nega i e e ec on a cus ome ’s li e ime alue.
- The elemen s o inno a ion, coope a ion, willingness o e e , and willingness o
ecommend ha e posi i e e ec s on a cus ome ’s li e ime alue.
Table 1 Visible a iables o he cus ome li e- ime alue model
Va iable
Symbol
Indica o s
Sou ce
Chu n
𝑦11
Unwillingness o use se ices
Kim and Shin
(2008)
𝑦12
No ecommending se ices o o he s
Kim and Shin
(2008)
𝑦13
Need o o he o ganiza ions se ices
Kim and Shin
(2008)
Sa is ac ion
𝑦21
Being sa is ied om o ganiza ion se ices
Kim and Shin
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398
Va iable
Symbol
Indica o s
Sou ce
(2008)
Liu e al
(2011)
𝑦22
Mee ing needs
Kim and Shin
(2008)
Liu e al
(2011)
𝑦23
To al sa is ac ion o O ganiza ion
Liu e al
(2011)
T us
𝑦31
Reliabili y o O ganiza ion
Liu e al
(2011)
𝑦32
Keeping p omises
Liu e al
(2011)
Change obs acles
𝑦41
Time consuming o changes
Kim and Shin
(2008)
𝑦42
Changes cos
Kim and Shin
(2008)
𝑦43
Di icul ies o changes in o ganiza ion
Kim and Shin
(2008)
Liu e al
(2011)
𝑦44
Di icul ies in use o o he o ganiza ions
se ices
Kim and Shin
(2008)
𝑦45
Unin e es ingly o o he o ganiza ions
Liu e al
(2011)
𝑦46
Di icul ies o in o ma ion gaining abou
o he o ganiza ions
Kim and Shin
(2008)
P ice
𝑦51
O ganiza ion main se ice cos s sui abili y
Kim and Shin
(2008)
𝑦52
Sidelong se ice cos s sui abili y
Kim and Shin
(2008)
Quali y
𝑦61
Sa is ac ion o o ganiza ion pe sonnel
beha io
Kim and Shin
(2008)
𝑦62
Good sense abou o ganiza ion se ices
Kim and Shin
(2008)
𝑦63
Be e se ice quali y compa ed o o he
o ganiza ions
Kim and Shin
(2008)
En e ainmen
𝑦71
Deligh ully deg ee
Liu e al
(2011)
𝑦72
Happiness deg ee
Liu e al
(2011)
𝑦73
Fun deg ee
Liu e al
(2011)
In imacy
𝑦81
F iendly ela ionship wi h pe sonnel
Liu e al
(2011)
𝑦82
Willingness o iendly ela ionship
Liu e al
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399
Va iable
Symbol
Indica o s
Sou ce
(2011)
Willingness o
ecommend
𝑦91
Recommending o ganiza ion as a good one
o o he s
Boles e al
(1997)
𝑦92
O ganiza ion eques accep ance o
ecommend i o o he s
Boles e al
(1997)
Willingness o e e
𝑦101
O ganiza ion eques accep ance o e e
o he s o i
Boles e al
(1997)
𝑦102
P esen ing o amilia who a e no
o ganiza ion cus ome s i he o ganiza ion
wan
Boles e al
(1997)
coope a ion
𝑦111
Coope a ion in en wi h o ganiza ion
Tang e al
(2013)
Rudol -Sipö z
(2001)
𝑦112
Ha ing echnology, p oduc , so wa e and
… which a e p o i able o o ganiza ion
Rudol -Sipö z
(2001)
𝑦113
Ha ing o ganiza ion equi ed special y
Tang e al
(2013)
Inno a ion
𝑦121
In e e ing wi h e alua ion and idea pu ge
Ballan ine
(2003)
𝑦122
Being ull o idea
Ballan ine
(2003)
𝑦123
Tes ing p o o ype by cus ome
Ballan ine
(2003)
𝑦124
In e e ing wi h design and ex ension o
p oduc s
Ballan ine
(2003)
CLV
𝑦13
Ob ained p o i om cus ome in he pas
yea s o his li e ime
Bla be g e al
(2009)
Da a analysis and esea ch assump ions es
E alua ing he sui abili y o he ques ionnai e
Ou in en ion om sui abili y is o ensu e ha he con en o he ools o he
ques ions p o ided in hese ools mus e alua e he a iables and he issue unde s udy
in an accu a e manne . Using unsui able ools will esul in agg ega ing un ela ed
in o ma ion and des oying he discipline o he in es iga ion s ages and da a analysis.
In his esea ch, in o de o de e mine sui abili y, he ques ionnai es we e examined by
expe s so ha hey could de e mine he accu acy le el and ele ance o he ques ions.
Consequen ly, some o hese ques ionnai es we e p esen ed o he pa icipan s and
inally some o he ques ions ha e co ec ed.
E alua ing he eliabili y o he ques ionnai e
In o de o e alua e he eliabili y o he ques ionnai e, we used he C onbach's alpha
me hod. This me hod calcula es he in e nal consis ency o measu emen ools ha
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400
measu e di e en ea u es. We used SPSS so wa e o calcula e C onbach's alpha.
Conside ing ha he C onbach's alpha alue o elemen s and he ques ionnai e is highe
han 0.7, he eliabili y o he ques ionnai e and elemen s is con i med.
Discussion
The esul ing da a om he ques ionnai es ha e been p ocessed using sui able
so wa e. The esul s ob ained om execu ing he model ia he so wa e, a e exp essed
in Table 3. I he s a is ic alue is mo e han 1.96, wi h mo e han %95con idence
in e al, hen he acqui ed ela ion is meaning ul. Acco ding o he able, he e ec s o
us on chu n and o in imacy on us ha e been ejec ed. In Figu e 2, accep able and
meaning ul pa hs a e ep esen ed. R2Values o models elemen a e ep esen ed in Table
2. Based on ou calcula ed R2 alue o 60% o cus ome li e- ime alue, we p opose
ha he model includes 60% o elemen s ha can a ec cus ome li e- ime alue.
Table 2R2 alues o models elemen
Dependen a iable
R2
CLV
0.60
Chu n
0.782
Sa is ac ion
0.914
Willingness o e e
0.57
Willingness o ecommend
0.51
Table 2 Resul ob ained om execu ing he model ia Sma PLS
Pa h
S anda dized coe icien
- alue
Resul
Coope a ion-CLV
0.143
3.101
Accep ed
Inno a ion-CLV
0.285
2.97
Accep ed
willingness o e e - CLV
0.208
2.346
Accep ed
willingness o ecommend- CLV
0.215
2.526
Accep ed
chu n-CLV
-0.249
2.99
Accep ed
sa is ac ion-chu n
-0.554
6.243
Accep ed
us -chu n
-0.143
1.11
Rejec ed
Chu n obs acles-chu n
-0.301
4.28
Accep ed
P ice-sa is ac ion
0.382
3.346
Accep ed
En e ainmen -sa is ac ion
0.299
2.03
Accep ed
Quali y-sa is ac ion
0.399
4.626
Accep ed
Quali y- us
0.802
7.23
Accep ed
In imacy- us
0.109
1.36
Rejec ed
Sa is ac ion-willingness o
ecommend
0.241
3.230
Accep ed
Sa is ac ion-willingness o e e
0.251
3.520
Accep ed
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Discussion
In his esea ch, we p oposed a new model o e alua e cus ome ’s li e ime alue.Ou
model is di e en om he o he models as i conside s non- inancial elemen s ha
a ec cus ome li e ime alue. These elemen s include: Cus ome chu n p obabili y,
coope a ion capabili y, willingness o e e , willingness o ecommend and cus ome
inno a ion. We es ed ou p oposed model on a se o da a agg ega ed om a mobile-
phone ope a o and de e mined he coe icien o each elemen in he cus ome li e ime
alue. Fo his pu pose, he s uc u al equa ion modeling was used ia he Sma -PLS
so wa e. Howe e he mos impo an es ic ion in his esea ch was he inaccessibili y
o he company’s da abase, which has concluded inco ec calcula ion o cus ome
li e ime alue. Fu u e esea ch can ocus o he ollowing poin s:
0.241
CLV
Coope a ion
P ice
En e ain
Quali y
Sa is ac ion
Change obs acles
Chu n
Willingness o
ecommend
Willingness o
e e
Inno a ion
Figu e 2 Accep able and meaning ul pa hs
0.285
0.215
0.218
0.143
-0.249
-0.554
-0.301
0.251
0.382
0.299
0.399
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402
- Measu ing he e ec s o demog aphic a iables on he cus ome ’s li e ime
alue, as his s udy dis ega ds he e ec o hese a iables.
- Using a mo e p ecise me hod o calcula e he s uc u e o cus ome li e ime
alue: in he cu en esea ch, he s uc u e is calcula ed app oxima ely and is based on
dis ibu ed ques ionnai es. I should be calcula ed acco ding o he cus ome ’s da abase.
This model should be implemen ed in o he se ice o ganiza ions and i ms.
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