15
ACC JOURNAL 2016, Volume 22, Issue 2 DOI: 10.15240/ ul/004/2016-2-002
INTENSITY AND PERCEPTION OF BARRIERS OF CUSTOMER SATISFACTION
MEASUREMENT
Pe e Madzík1; Pa ol K ižo2
1Ca holic uni e si y in Ružombe ok, Facul y o Educa ion, Depa men o Managemen ,
Náb ežie Jána Pa la II., 15, 058 01 Pop ad, Slo akia
2College o Economics and Managemen in Public Adminis a ion in B a isla a,
Fu deko a 16, 051 04 B a isla a, Slo akia
e-mail: 1[email p o ec ed]; 2pa ol.k izo@ sem s.sk
Abs ac
Al hough in o ma ion esul ing om measu emen o cus ome sa is ac ion (CS) belongs o
wo hy s a e s o imp o emen ac i i ies in p ac ice o an o ganiza ion, hey ace a ious
ba ie s which p e en measu emen o become sys ema ic. The aim o his s udy is o
esea ch in ensi y and pe cep ion o ba ie s p e en ing CS measu emen . To achie e he goal,
s a is ic p ocessing o he esea ch esul s which was done in Slo ak epublic is used. To ally
435 alid ques ionnai es we e p ocessed and ela ions among indi idual ba ie s o CS
measu emen we e iden i ied and quan i ied. The esul s showed ha occasional measu emen
o CS and a lack o pe sonnel a e conside ed o be he bigges ones.
Keywo ds
Cus ome sa is ac ion measu emen ; Ba ie s; Su ey.
In oduc ion
Impac ed by globaliza ion g ow h and hype -compe i ion exis ence, quali y managemen
heo ies s a ed o concen a e on cus ome sa is ac ion mo e widely a he beginning o he
80’s o he 20 h cen u y. Cus ome sa is ac ion (CS) as a echnical e m ge s g adually in o
a highe numbe o indus ies (ma ke ing, indus ial enginee ing, se ice managemen , e c.)
and nowadays i belongs o pe manen challenges o e e y o ganiza ion. The e is empi ical
e idence con i ming ha CS is a key de e minan o o ganiza ion ma ke success [15].
Posi i e e ec s o high CS o en become he objec o esea ch o se e al s udies in
manage ial [12], economic [5] o social a eas [2]. A p esen i would be e y di icul o
disp o e he asse ion ha ocusing on CS high le el achie emen should belong among
ma ginalized a eas ela ed o o ganiza ion e o [12]. A p inciple o achie emen o high CS
was in eg a ed o se e al manage ial s anda dized and open concep s. One o he bes known
s anda ds which CS p esen s as one o key s a egic goals is ISO 9001: Quali y managemen
sys ems. The s anda d explici ly and sys ema ically “na iga es” an o ganiza ion h ough i s
p ocesses so ha also cus ome equi emen s aimed a achie emen o hei high sa is ac ion
a e aken in o conside a ion. Also o he concep s like EFQM o i s modi ied e sion CAF
p esen necessi y o ocus on CS as he mos conce ned pa .
To ge o know how CS “is c ea ed” i is necessa y o in oduce a wide con ex o quali y
managemen p ocess. In he pas , summa y app oaches o analyse, in eg a e, manage, and
imp o e cus ome equi emen s ul illmen we e de e mined and one o he mos uni e sal
one was c ea ed in he a ea o Se ice science. I s au ho s Pa asu aman, Zei haml, and Be y
[10] sugges ed a model based on GAP p inciple – i.e. di e ences be ween expec a ions and
16
eali y. La e he model was sligh ly modi ied ge ing i s uni e sal o m and named as quali y
loop.
Measu emen
o sa is ac ion
SOUGHT QUALITY
( equi emen s)
TARGET QUALITY
( echnical speci ica ion
o p oduc )
DELIVERED QUALITY
(deg ee o ul illmen o
echnical speci ica ion)
PERCEIVED QUALITY
(deg ee o ul illmen o
equi emen s)
Measu emen o
pe o mance
Cus ome P o ide
A B
D C
1
2
3
4
Sou ce: Adap ed om [4]
Fig. 1: Quali y loop
Quali y loop is a g aphic ep esen a ion o quali y managemen p ocess which p esen s i s
elemen s and ela ions among hem (Figu e 1). As can be seen he e a e usually wo
conce ned pa ies in quali y p ocess – a cus ome and a p o ide . To achie e accep able
quali y deg ee, a i s , an o ganiza ion has o know cus ome equi emen s (pa A) and
in eg a e hem in o p oduc echnical speci ica ion (B). Designing echniques such as Quali y
unc ion deploymen [6] is mos equen ly used in case o p oduc quali y in eg a ion.
Consequen ly, an o ganiza ion has o ensu e he highes possible deg ee o echnical
speci ica ion ul illmen (C). A e he p oduc deli e y, cus ome s a e con on ed wi h i s
echnical (inhe en ) and assigned cha ac e is ics and pe cei e he deg ee o hei own
equi emen s ul illmen (D). De e mina ion o con o mi y a e be ween expec a ions (A) and
pe cep ion (D) is in he quali y heo y called measu emen o cus ome sa is ac ion [9].
1 Aims o Resea ch
In spi e o p o able bene i s o CS measu emen , he e a e s ill a ious ba ie s which p e en
he p ocess o CS measu emen o become a key p ocess o each o ganiza ion ac i i ies
alida ion. P o essional and scien i ic li e a u e in oduces se e al ba ie s ela ed especially
o economic di icul y o sa is ac ion measu emen p ocess [7], al hough a deepe analysis
which would explain he cha ac e and he s uc u e o he ba ie s wi h e e ence o a wide
con ex o o ganiza ion pe o mance is s ill missing. The aim o he s udy is o (1)
cha ac e ize mos equen ba ie s o CS measu emen , (2) ge o know hei mu ual ela ions
be e , (3) iden i y mu ual ela ions be ween pe cei ed bene i o CS measu emen and
pe cei ed impo ance o CS measu emen , (4) explo e ela ions be ween o ganiza ion esul s
and emphasis on pe iodici y and sys ema ic na u e o CS measu emen and (5) iden i y and
cha ac e ize g oups o o ganiza ions ha ing a simila s uc u e o ba ie s o CS measu emen .
2 Me hodology
To deal wi h he opic, a s anda d p ocedu e based on ou phases o esea ch was p oposed,
see Figu e 2. Du ing he planning phase p o essional and scien i ic sou ces we e e iewed and
mos equen ly men ioned CS measu emen ba ie s we e ex ac ed. Apa om he abo e
men ioned ba ie s he ques ionnai e con ains o he a iables, e.g. indica o s o company
pe cei ed success, addi ional ID a ibu es o app aisal o opinions ela ed o CS
measu emen . These addi ional a iables enabled deepe s a i ica ion o he esul s aimed a
be e unde s anding o CS measu emen ba ie s s uc u e. A e ha he ques ionnai e was
17
made and o ms o ques ions and ypology o esponses was conside ed o achie e da a o he
highes analy ical po en ial. Apa om common scaling in he in e al 1 o 5 and 0 o 100,
app oaches conce ning ag eemen e alua ion we e used [10], since some o hem in speci ic
cases show a mo e accu a e deg ee o assessmen om he poin o esponden s. When he
elec onic ques ionnai e had been p ocessed, a da abase con aining e-mail con ac s o
o ganiza ions ope a ing (pe o ming) in he Slo ak Republic was c ea ed.
Planning Li e a u e (a icles,
books, epo s, web)
Inpu P ocess Ou pu
Con en analysis, induc ion Mos equen ly ba ie s
o CS measu emen
Scaling me hods
(Se qual, scale) In ol ing in o ma ion in o ques ionai es Ques ionai es
F ee da abases o
companies Ex ac ing email add ess Da abase o con ac s
Execu ing Elec onical da a collec ion Da ase (da abase o
esponses)
In e p e a ion
E alua ing Cha ac e is ic o ba ie s o CS
measu emen
Analysis o mu ual ela ions among
ba ie s (bi a ia e co ela ion analysis,
ac o analysis)
In o ma ion abou da a
analysis, own
knowledge
Re iew o bene i -impo ance ela ion
(K-means clus e )
Rela ion be ween o ganisa ion esul s
and CS measu emen impo ance (K-
means clus e )
Iden i ica ion o g oups o simila
o ganisa ions (Two-s ep clus e )
Analy ical ou pu s –
g aphs, ables
Li e a u e (a icles,
books, epo s, web) Syn hesis In e p e a iona and
gene aliza ion
Sou ce: Own
Fig. 2: Resea ch design
Du ing he ealiza ion phase he da a we e ga he ed in Ma ch and Ap il 2016 and he ou pu s
esul ing om he esponses – a e being checked due o da a consis ency – we e expo ed o
o ma s enabling execu ion o common (Excel) and mo e ad anced (IBM SPSS S a is ics)
s a is ic p ocedu es. These p ocedu es we e execu ed in he phase o esul s e alua ion and
e lec ed esea ch aims named in he inal pa o In oduc ion. Based on he acqui ed da a as
well as on in o ma ion om he planning phase, i was possible o explo e 5 main a eas
sys ema ically. The i s one was he cha ac e is ic o he main ba ie s o CS measu emen
and equency g aphs and s a i ica ion acco ding o size and sec o o o ganiza ion. The
second a ea o he esea ch was he analysis o mu ual ela ions among ba ie s by bi a ia e
co ela ion analysis and la e by ac o analysis based on p incipal componen analysis. In he
nex ( he hi d) a ea, mu ual ela ion be ween pe cep ion o CS measu emen impo ance and
expec ed bene i which a measu emen is o b ing was e iewed. To do so, k-means clus e
analysis was used and i was in e p e ed by a sca e -do cha . The objec i e o he ou h a ea
18
was o con i m alidi y o CS measu emen by analysis o ela ion be ween he esul s an
o ganiza ion achie es and impo ance which o ganiza ion a aches o he p ocess o CS
measu emen . The las i h a ea was aimed a summa y cha ac e is ic o simila o ganiza ions
conside ing hei size, sec o and ba ie s.
Analy ical ou pu s in a o m o cha s and ables we e explained du ing he phase o esea ch
in e p e a ion and gene alized in discussions and ela ed o he exis ing knowledge in he a ea
o CS measu emen o o he wide connec ions.
3 Resul s and Discussion
Elec onic su ey aimed a da a collec ion was ealized wi hin he Slo ak Republic du ing
Ma ch and Ap il 2016. To ally app oxima ely 10,000 o ganiza ions doing business in a ious
a eas we e add essed and he numbe o alid esponses was 435. O ganiza ions om 21
economic ac i i ies we e ep esen ed in he numbe o alid esponses (ca ego ies we e
adap ed om SR S a is ical O ice classi ica ion).
3.1 Main Ba ie s o CS Measu emen
Ga he ing and e alua ion o quan i a i e and quali a i e da a has a c i ical impo ance o an
o ganiza ion. The s uc u e o da a, pa ame e s, indica o s o o he nume ical, g aphical o
e bal o ms o assessmen o he pas , cu en , e en ually u u e si ua ion o an o ganiza ion
is usually named a Measu emen Sys em. This sys em is o suppo decision making based on
ac s and help an o ganiza ion o achie e s a egic goals [3]. I is nei he possible no
easonable o measu e e e y hing and so i is a na u al choice o an o ganiza ion o de ine
wha , why and how should be measu ed. In Figu e 3 simple esul s showing he a e o
sys ema ic CS measu emen a e displayed.
Sec o
F equency
Pe cen
Sphe e
Adnimis a i e and suppo se ice ac i i ies 15 3.4 Se ices
Households ac i i ies 1 0.2 Se ices
Ex a e i o ial o ganisa ion ac i i ies 1 0.2 Se ices
Real es a e ac i i ies 6 1.4 Se ices
Elec ici y, gas, s eam and ai condi ioning supply 4 0.9 Se ices
Wa e supply; sewe age, was e managemen ... 5 1.1 Se ices
T aspo a ion and s o age se ices 20 4.6 Se ices
Financial and assu ance ac i i ies 16 3.7 Se ices
In o ma ion and communica ion se ices 29 6.7 Se ices
P o essional, scien i ic and echnical ac i i ies 27 6.2 O he s
O he ac i i ies 86 19.8 O he s
Ag icul u e 15 3.4 P oduc ion
Manu ac u ing 31 7.1 P oduc ion
Cons uc ion 40 9.1 P oduc ion
Mining and qua ying 1 0.2 P oduc ion
Accommoda ion and ood se ice ac i i ies 27 6.2 Se ices
A , ec ea ion 17 3.9 Se ices
Wholesale and e ail 46 10.6 Se ices
Public sec o 16 3.7 Se ices
Educa ion 12 2.8 Se ices
Heal h 20 4.6 Se ices
To al 435 100
Sou ce: Own calcula ion
Fig. 3: Pe iodici y and sys em in CS measu emen om size o o ganiza ion and sec o
poin s o iew
As one can see, he absence o he sys em in CS measu emen is ob ious especially in mic o
companies. In luenced by inc easing numbe o o ganiza ion employees also i s app oach o
CS measu emen goes up, and majo i y o medium and la ge o ganiza ions conside hei
e o in his a ea as he sys ema ic one. The esul s also showed ha a di e ence be ween
p oduc ion and se ice sec o is – om he poin o iew o a io be ween sys ema ic and non-
sys ema ic CS measu emen – insigni ican .
In li e a u e se e al easons con i ming insu icien a en ion o o ganiza ions o p ocess o
CS measu emen can be ound [11] and he mos equen ly men ioned a e he ollowing ones:
19
 Needs o ou cus ome a e s able – his is an a gumen used especially by companies
o e ing commodi ies, o ope a ing in ne wo k- egula ed indus ies o in monopolis ic
en i onmen o s a e hei low in e es in CS measu emen . In p inciple, his s a emen
may no be co ec since globaliza ion and de elopmen ends accele a e endencies
ela ed o inc easing equi emen s o cus ome s [13].
 Lack o pe sonnel – a equen eason especially in o ganiza ions wi h cumula ed
unc ions and a low numbe o employees [14].
 Finance – easons ha CS measu emen is cos ly belong among mos equen ly
p esen ed ones [14].
 Occasional measu emen o CS – eac i e a i ude o an o ganiza ion is behind his
eason and he o ganiza ion uses CS measu emen only in a si ua ion when a sudden
ini ia o usually has a nega i e cha ac e eme ges (e.g. massi e complain s, decline in
sales, e c.). In his way o ganiza ions use CS measu emen as a ool o diagnose he cause
o a nega i e si ua ion [8].
 Annoyed cus ome – o ganiza ions a e a aid ha CS measu emen will make cus ome s
annoyed and his ac is seen as a ba ie o use CS measu emen sys ema ically [4].
 We do no need o do pe iodical measu emen o CS – a ole in sys ema ic
implemen a ion o CS measu emen is also played by supe io con ic ion o manage s ha
CS measu emen does no ha e o be egula and should ha e only suppo i e cha ac e
[8]. The main ad e sa ies o quali y a e a lack o in e es and a lack o knowledge – he
ba ie p esen ing he o me one.
 No bene i – he second ad e sa y o quali y is a lack o knowledge. The e a e se e al
s udies poin ing ou ha manage s a e no o en awa e o s a egic impo ance o CS
measu emen [8].
These se en main causes e alua ed by o ganiza ions which measu e CS non-sys ema ically o
do no measu e i a all became he objec o analysis esea ching he a e o in luence o
indi idual ba ie s o CS measu emen . Resul s in Figu e 4 show ha he bigges ba ie is
“Occasional measu emen o CS” (a e age ba ie in ensi y was 62.3 calcula ed in scale 0 o
100). A inding ha o ganiza ions a e awa e o bene i s esul ing om CS measu emen is
conside ed o be posi i e in o ma ion and his is p o ed by ela i ely low in ensi y o “No
bene i ” ba ie (a e age ba ie in ensi y 42.2). An excep ion is a g oup o esponden s
p esen ing ex a-la ge o ganiza ions bu since only a e y low numbe o such o ganiza ions
we e in ol ed in he esea ch i is no possible o de ine any conclusions.
Sou ce: Own calcula ion
Fig. 4: In ensi y o CS measu emen ba ie s; s a i ica ion acco ding o size (on he le )
and sec o (on he igh )

20
P oblems ela ed o insu icien capaci y o pe sonnel o measu e CS (“Lack o pe sonnel”)
achie ed ela i ely high le el in mic o and small o ganiza ions. S a i ica ion o he esul s
acco ding o he size b ough only ela i ely consis en esul s. S a i ica ion o he esul s
acco ding o he sec o showed di e ences be ween se ice and p oduc ion sec o . Belie ha
“needs o ou cus ome s a e s able” and ha CS measu emen will make ou cus ome s
annoyed (“Annoyed cus ome s”) is highe in case o se ice sec o . To e i y s a is ical
signi icance o his di e ence Two-sample F- es o a iances in combina ion wi h - es
we e used. S a is ical p ocedu e based on F- es applying s a i ica ion o bo h men ioned
ba ie s esul ed o a pa ial conclusion ha a iances o bo h samples a e iden ical and ha
Two-sample - es assuming equal a iances is sui able o e i y s a is ical signi icance. In
bo h cases i con i med ha alues s a a e lowe han c i (in he i s case s a / c i esul s we e
a he le el –1.20/1.98, in he second one –1.65/1.98) and so i is possible o s a e ha
a di e ence be ween p oduc ion and se ices is no s a is ically signi ican .
3.2 Rela ions Among Ba ie s o CS Measu emen
To unde s and in e nal s uc u e o ba ie s in cus ome s’ minds be e i is app op ia e o
esea ch hei mu ual ela ions (connec ions, links). Fo his pu pose, app oaches based on
co ela ion indexes/coe icien s a e used mos equen ly [1]. Bes known a e co ela ion and
ac o analysis. In he i s phase ela ions among indi idual ba ie s we e examined by
bi a ia e co ela ion analysis, which p esen s in ensi y o mu ual dependencies by Pea son
co ela ion coe icien p mo ing in he in e al <–1; 1>.
The e a e esul s o bi a ia e co ela ion analysis in Table 1 ha do no show s ong explici
ela ions among in es iga ed ba ie s. Ba ie s wi h p ≤ –0.5 o p ≥ 0.5 a e conside ed as
s ong ones. Absence o s ong explici ela ions may no mean ha he e a e no la en
ela ions p esen ed by la en a iables among ba ie s. To esea ch his op ion ac o analysis
is applicable oo. Tha is why a da a se was subjec ed o a ac o analysis p ocedu e.
Tab. 1: Resul s o bi a ia e co ela ion analysis
Va iable
G No
bene i
F
E
D
C
B
A Needs o ou cus ome s a e s able
0.132
0.170
–0.050
0.129
0.058
–0.049
B Lack o pe sonnel
0.096
0.095
0.014
0.072
0.345
C Finance
0.277
0.149
0.161
0.138
D Occasional measu emen o CS
0.112
0.326
0.292
E Annoyed cus ome s
0.291
0.317
F We don’ need o do pe iodical
measu emen
0.462
Sou ce: Own calcula ion
Du ing examining se en ba ie s he ac o analysis p ocedu e iden i ied, h ee componen s
(la en a iables) in which alues lowe han 0.2 we e hidden ( o cla i y eason) in Figu e 5.
Conside ing he in ensi y o hei ela ions wi h ba ie s hey we e named as (1) Conce ns o
consequences, (2) Capaci y cons ain s, and (3) Illusion o s a us quo. These h ee componen s
explain in o al 62.65% o a iables a iabili y. The componen “Conce ns o consequences”
mos ly consis s o ba ie s like “Annoyed cus ome s”, “We do no need o do pe iodical
measu emen ”, “Occasionally measu emen o CS” and “No bene i ”. I conce ns gene al
ba ie s which esul om no knowing bene i s and wo ies o some hing he e ec o which
is no seen immedia ely bu a e some ime. The second iden i ied componen was “Capaci y
cons ain s” which mos ly con ains wo ba ie s – “Lack o pe sonnel” and “Finance”. I
conce ns closely connec ed ba ie s which, as he p e ious analysis p o ed in Chap e 3.1, a e
21
cha ac e is ic especially o mic o and small o ganiza ions. The las iden i ied componen was
“Illusion o s a us quo”, i.e. belie ha “Needs o ou cus ome s a e s able”. In a la ge ex en
his componen consis ed only o one ba ie o he same name. This in p inciple no o ally
app op ia e a i ude o esponden s may esul om ei he sel -con ic ion abou pe ec
ma ke knowledge, o ganiza ion monopolis ic posi ion o simply om no being awa e o he
g owing equi emen s o cus ome s in ma ke en i onmen .
1: Conce ns o
consequences
2: Capaci y
cons ain s
3: Illusion o
s a us quo
Annoyed_cus ome s 0.781 -0.284
We_don _need_ o_do_pe iodical_
measu emen
0.696 0.322
Occasionally_measu emen _o _CS 0.609
No_bene i 0.563 0.296 0.318
Lack_o _pe sonel 0.834
Finance 0.223 0.769
Needs_o _ou _cus ome s_a e_s a
ble
0.917
Ro a ed Componen Ma ixa
Componen
Ex ac ion Me hod: P incipal Componen Analysis. Ro a ion Me hod: Va imax wi h Kaise
No maliza ion.
a. Ro a ion con e ged in 5 i e a ions.
Sou ce: Own calcula ion
Fig. 5: Iden i ica ion o la en a iables by ac o analysis
3.3 Rela ion Be ween Pe cei ed Bene i and A ibu ed Impo ance o CS
Measu emen
Li e a u e b ings a lo o logical and empi ical easons o make o ganiza ions pay sys ema ic
a en ion o CS measu emen . Bu how do o ganiza ions pe cei e i ? One o he aims o his
pape is o cla i y i in pa . To do so, wo indi idual a iables (ques ions in he ques ionnai e)
we e used. The i s one was pe cei ed bene i o CS measu emen . I may be assumed ha
o ganiza ions will pay mo e e o o ac i i ies b inging demons able bene i . The second
ques ion was o se he impo ance o CS measu emen . This is no duplici y o he i s
ques ion since his one helps unde s and posi ioning o “measu emen o CS” ac i i y in he
hie a chy o all o ganiza ion ac i i ies. Responden s could esponse o bo h ques ions in a
scale 0–100 and consequen ly a sca e -do g aph enabled o display mu ual con igu a ion o
indi idual cases, see Figu e 6.
Sca e ing o indi idual cases in a wo-dimension sys em was used o enable linea eg ession
(in bo h cases i has g owing cha ac e ). In case o he p oduc ion sec o a eg ession cu e
has a s eepe inclina ion ha in he se ice sec o . I means ha se ing he impo ance o CS
measu emen is highe in he p oduc ion sec o . I may be assumed ha he eason is one
pa icula ea u e o se ices, i.e. a di ec con ac wi h he cus ome / a ge consume . Since in
case o se ices his con ac is mo e equen han in case o p oduc ion, i may be p edic ed
ha cus ome s’ equi emen s a e eco ded immedia ely in he p ocess o se ices p o ision
and po en ial co ec ions in se ice cha ac e is ic migh be done ela i ely quickly. CS
measu emen migh be pe cei ed only as complemen o cus ome s´ equi emen s
unde s anding. Bu in case o he p oduc ion he inal p oduc is alida ed a e i s p oduc ion
has been inished and o an o ganiza ion CS measu emen is a way o iden i y he deg ee o
which a p oduc mee s cus ome s’ equi emen s.
22
Sou ce: Own calcula ion
Fig. 6: Rela ion be ween pe cei ed bene i and impo ance o CS measu emen ; se ice
sec o (le ), p oduc ion sec o ( igh )
Se e al isks a e o be men ioned due o he abo e men ioned s a emen s. They a e ela ed o
a gumen s s eng h. Rela i ely low alue o R2 (coe icien o de e mina ion) which
de e mines how close he da a a e o he i ed eg ession should be conside ed, and so hese
in e p e a ions should be aken as possible explana ion.
3.4 Rela ion Be ween O ganiza ion Resul s and Emphasis on CS Measu emen
Se e al posi i e examples con i med ha o ganiza ions which pay sys ema ic a en ion o CS
measu emen achie e be e ma ke esul s [8]. The esea ch which was a pa o his
p esen ed one was a e y good oppo uni y o e i y he s a ed esul s empi ically. Since he
elec onic way o ques ioning was anonymous, only subjec i e indica o s o o ganiza ion
esul s we e ob ained. To p e en p oblems conce ning esul s compa ison, since
o ganiza ions ha e di e en esul s indica o s ac oss sec o s and also di e en ones due o
hei size, i was decided o use a scale 0–100 o e alua e hei own esul s. The esul s we e
e alua ed by wo a iables: success o o ganisa ion and ma ke posi ion o an o ganisa ion.
Responses we e di ided in o wo ca ego ies, he i s one being p esen ed by o ganiza ions
which pay sys ema ic a en ion o CS measu emen and he second one including
o ganiza ions which do no measu e CS sys ema ically. The esul s we e p ocessed in a o m
o sca e -do cha u ilizing he p inciple o clus e analysis, see Figu e 7.
The coo dina e sys em migh be di ided in o ou quad an s. The e a e unsuccess ul
o ganiza ions wi h a low ma ke posi ion (powe , sha e) a he le bo om. A he igh bo om
he e a e se e al o ganiza ions whose ma ke powe is e y high bu a e no conside ed o be
success ul – hey a e supposed o ope a e in monopolis ic en i onmen . On he le op he e
a e usually small o ganiza ions wi h a ela i ely low ma ke posi ion bu conside ed as a he
success ul. On he igh op he e a e ma ke leade s om bo h poin s o iew – hei ma ke
posi ion and pe cep ion o hei own success.
23
Sou ce: Own calcula ion
Fig. 7: Achie emen o o ganiza ion esul s due o pe iodici y and sys em in CS
measu emen ; all he o ganiza ions (on he le ), se ice sec o (in he middle) and
p oduc ion sec o (on he igh )
Indi idual o ganiza ions a e ep esen ed in he coo dina e sys em by co esponding poin s
dis inguished acco ding o he ac whe he an o ganiza ion (1) pays o (2) does no pay
sys ema ic a en ion o CS measu emen . Calcula ion o cen oid o hese wo g oups esul s o
a e age posi ion o o ganiza ions. In he coo dina e sys em (x; y) he cen oid o o ganiza ions
paying sys ema ic a en ion o CS measu emen was in he igh op quad an and i s
coo dina es we e (56.6; 78.2) and he cen oid o o ganiza ions which do no measu e CS
sys ema ically was in he le op quad an and i s coo dina es we e (45.6; 66.3). Based on
his, i may be s a ed ha CS measu emen has an impac on o ganiza ion esul s pa icula ly
on hei success (in highe ex en ) and la e also on hei ma ke posi ion (in lowe ex en ).
Simila conclusions may be induced om da a s a i ica ion o he se ice as well as o he
p oduc ion sec o , see Figu e 7 in he middle and on he igh .
3.5 G oups o Simila O ganiza ions
The su ey which had been pe o med enabled execu ion o u he s a is ical p ocedu es
cla i ying unce ain ies conce ning causes ba ie s o CS measu emen . Rela i ely aluable
in o ma ion is he iden i ica ion o ype ep esen a i es, i.e. g oups o compa a i ely
homogeneous subjec s whe eby hese g oups a e mu ually he e ogeneous. Fo his pu pose, i
is bes o use clus e analysis and in his pape wo-s ep clus e analysis was applied. Fi e
a iables en e ed he p ocedu e o clus e ing: he size o he o ganiza ion, sec o , conce ns o
consequences, capaci y cons ain s and illusion o s a us quo. Las h ee a iables p esen ed
an ou pu om ac o analysis in oduced in Chap e 3.2. The esul s o his clus e ing a e
displayed in Figu e 8.