Gaile, Ani a; Baumane Vi olina, Ilona; S ibe, Agnis; Ki ipõld, Ku me
A icle
Expanding ca ee adap abili y: Connec ions as a c i ical
componen o ca ee success
Eu opean Jou nal o Managemen and Business Economics (EJM&BE)
P o ided in Coope a ion wi h:
Eu opean Academy o Managemen and Business Economics (AEDEM), Vigo (Pon e ed a)
Sugges ed Ci a ion: Gaile, Ani a; Baumane Vi olina, Ilona; S ibe, Agnis; Ki ipõld, Ku me (2024) :
Expanding ca ee adap abili y: Connec ions as a c i ical componen o ca ee success, Eu opean
Jou nal o Managemen and Business Economics (EJM&BE), ISSN 2444-8451, Eme ald, Leeds, Vol.
33, Iss. 4, pp. 411-428,
h ps://doi.o g/10.1108/EJMBE-06-2023-0185
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Expanding ca ee adap abili y:
connec ions as a c i ical
componen o ca ee success
Ani a Gaile
Riga Business School, Riga Technical Uni e si y, Riga, La ia
Ilona Baumane Vi olina
Facul y o Economics and Managemen , Uni e si y o La ia, Riga, La ia
Agnis S ibe
The Business School, RMIT Uni e si y, Ho Chi Minh Ci y, Vie nam and
Depa men o In o ma ics, EBIT, Uni e si y o P e o ia, P e o ia, Sou h A ica, and
Ku me Ki ip~
old
Uni e si y o Ta u, Ta u, Es onia
Abs ac
Pu pose –Subjec i e ca ee success has been widely esea ched by academics and esea che s as i p o ides
job and ca ee sa is ac ion ha can lead o he pe cei ed li e sa is ac ion o employees, as well as hei
engagemen in o ganiza ions. This s udy demons a es ha subjec i e ca ee success depends no me ely on
ca ee adap abili y bu also on he connec ions people build h oughou hei p o essional li es.
Design/me hodology/app oach –The s udy was conduc ed in he socioeconomic con ex o La ia wi h a
sample size o 390 esponden s. In e pe sonal beha io al ac o s om he pe cep ion o ca ee success measu e
and he in luence o he Ca ee Adap -Abili ies Scale (CAAS) on subjec i e ca ee success ( wo s a emen s om
Gaile e al., 2020) we e used. The cons uc ed esea ch model was es ed using he SPSS 28 and Wa pPLS 8.0
so wa e ools. The p ima y da a analysis me hod used was pa ial leas squa es s uc u al equa ion modeling
(PLS-SEM). Then 12 mode a o s and hei e ec s on he main ela ionships o he model we e e iewed.
Findings –The s udy con i ms ha ela ionships a wo k ha e he mos signi ican e ec on subjec i e ca ee
success, ollowed by con ol beha io s and cu iosi y beha io s. Mo eo e , a lis o signi ican and insigh ul
mode a ion e ec s was ound, mos signi ican ly he ela ionship be ween connec ions and subjec i e ca ee
success.
O iginali y/ alue –Un il now, he CAAS was no in eg a ed wi h he beha io s and a i udes ha depic he
social ela ionships o indi iduals a wo k. This s udy aims o na ow his gap by explo ing whe he (and, i so,
how) ca ee adap abili y and in e pe sonal ela ionships in he wo kplace (i.e. p o essional connec ions)
con ibu e o subjec i e ca ee success.
Keywo ds Ca ee adap abili y, Ca ee success, Social connec ions, Ca ee cons uc ion heo y
Pape ype Resea ch pape
In oduc ion
Ca ee success and he ole o p oac i e beha io s in shaping job- ela ed de elopmen ha e
been cen al opics in oca ional beha io esea ch (Spu k, 2021). The key p e equisi es o
main aining a success ul ca ee include, among o he ac o s, one’s s eng hs and co e in e es s
Expanding
ca ee
adap abili y
411
© Ani a Gaile, Ilona Baumane Vi olina, Agnis S ibe and Ku me Ki ip~
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Recei ed 12 June 2023
Re ised 31 July 2023
29 Sep embe 2023
17 Oc obe 2023
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Accep ed 17 No embe 2023
Eu opean Jou nal o Managemen
and Business Economics
Vol. 33 No. 4, 2024
pp. 411-428
Eme ald Publishing Limi ed
e-ISSN: 2444-8494
p-ISSN: 2444-8451
DOI 10.1108/EJMBE-06-2023-0185
(B own and Len , 2016), ca ee compe encies (P es i e al.,2022;Ayoobzadeh, 2022;F ancis-
Smy he e al.,2012;Kong, 2010;Kuijpe s and Schee ens, 2006), one’s abili y o o e come ca ee
hu dles (Ng and Feldman, 2014), he applica ion o a bounda yless ca ee app oach (Ba el,
2021;A hu and Rousseau, 1996), oppo uni ies o ollow one’s p o essional calling (Bloom
e al.,2021;P asko a e al.,2014) and ca ee adap abili y (Sa ickas and Po eli, 2012).
The widely used Ca ee Adap -Abili ies Scale (CAAS), g ounded in ca ee cons uc ion
heo y by Sa ickas and Po eli (2012), po ays indi iduals as ac i e c ea o s o hei wo k
en i onmen s. This heo y highligh s he pi o al ole o e e yday beha io s and choices in
c a ing ca ee s. The CAAS cen e s a ound ou key beha io s, known as he 4 C’s–cu iosi y,
conce n, con idence and con ol – ha a e es ablished an eceden s o ca ee success,
suppo ed by subs an ial empi ical e idence (Rudolph e al., 2017).
This s udy b idges a gap by p oposing he inclusion o wo kplace social ela ionships,
labeled as “Connec ions,”as he i h C in he CAAS. In con as o p io esea ch, i highligh s
he o e looked ole o mode a o s in indi iduals’ca ee cons uc ion e o s. Ca ego izing
hese mode a o s in o amily li e, job a ibu es, company size and demog aphic
cha ac e is ics enhances ou unde s anding o he di e se ac o s in luencing ca ee
success, complemen ing he ecognized impo ance o social capi al in p e ious s udies (Lin,
1999;Seibe e al., 2001;Chow, 2002;Lo P es i e al., 2019;Sou e al., 2022;Kau eld and Spu k,
2022;Boa e al., 2022).
The goal o his s udy is o examine he in luence o he CAAS and in e pe sonal
ela ionships on subjec i e ca ee success.
The s udy aims o de elop an expanded Subjec i e Ca ee Success Model by in eg a ing
in e pe sonal beha io wi h ca ee adap abili ies. Da a we e collec ed om 390 indi iduals
h ough social media pla o ms in La ia and subjec ed o igo ous eliabili y and alidi y
es ing using SPSS 28 and Wa pPLS 8.0 (specialized so wa e o s uc u al equa ion modeling).
The indings o he s udy demons a e he e ec i eness o he newly de eloped model.
The s udy concludes ha in e pe sonal ela ionships signi ican ly impac subjec i e
ca ee success, wi h sociodemog aphic ac o s like age, educa ion and gende ac ing as
mode a o s. Sugges ing an expansion o he CAAS o include a i h ac o , “Connec ions,” he
s udy ad oca es i s use in u u e ca ee success s udies. These nuanced indings se e as a
oadmap o indi iduals and ca ee counselo s, emphasizing he sui abili y o di e en
beha io s in di e se li e-cycle si ua ions, conside ing a ious sociodemog aphic and amily
backg ound ac o s.
This pape is s uc u ed as ollows. The li e a u e e iew depic s he heo ies o oca ional
beha io , in pa icula Sa ickas and P o eli’s heo y o ca ee adap abili y. Nex , he ole o
in e pe sonal ela ionships and connec ions in ca ee success is explo ed. The me hodology
add esses he measu emen explana ions and esea ch model desc ip ions o his s udy.
Following his a e a discussion and he au ho s’conclusions.
Li e a u e e iew
Ca ee Adap -Abili y Scale wi hin heo ies o oca ional beha io
Acco ding o B own and Len (2016), pas oca ional beha io esea ch can be classi ied in o
h ee b oad a eas: (1) agency in ca ee de elopmen , (2) equi y in he wo k o ce and (3) well-
being in wo k and educa ional se ings. Wi hin he agency ca ego y, he e is an emphasis on
ca ee success and ca ee adap abili y. To da e, much a en ion has been paid o human
capi al wi hin he ollowing opics: ca ee success (Ng e al., 2005;J€
a ls €
om e al., 2020),
psychological and demog aphic ac o s (Lyons e al., 2015;Haenggli and Hi schi, 2020;
Zache , 2014), social capi al (J€
a ls €
om e al., 2020;Ba haue e al., 2016), o ganiza ional
suppo , o ganiza ion–pe son i (Ng and Feldman, 2014), leade –membe exchange (e.g.
Res ubog e al., 2011;Spu k e al., 2014), membe –membe exchange (D abe e al., 2015),
EJMBE
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pe o mance (D ies e al., 2008) and ca ee adap abili y beha io s (Haenggli and Hi schi, 2020;
Zache , 2014) as ac o s ha in e play in he de elopmen o a success ul ca ee .
Sa ickas and Po eli’s (2012) CAAS, a ecognized an eceden o ca ee success
(Rudolph e al., 2017;Zache , 2014), aligns wi h he ocus on con inuous indi idual ac i i y
in ca ee de elopmen and success s udies. Lee e al. (2021) no e a lack o widesp ead
c i icism o he cu en CAAS e sion, es ablishing i s posi i e impac on indi iduals and
o ganiza ions. Howe e , his pape c i ically examines he CAAS, highligh ing i s ask-
ocused na u e and p oposing he inclusion o a i h “C”: connec ions, acknowledging he
unde alued impo ance o social skills and in e pe sonal ela ionships (Rigby and
Sanchis, 2006).
In e pe sonal ela ionships (connec ions) also play a signi ican ole when indi iduals
epo hei own subjec i e ca ee success (e.g. Ga ike and La wood, 1986;Shockley e al.,
2016;Ng and Feldman, 2014;Poona e al., 2015). Thus, connec ions should be added as a
sepa a e elemen o he CAAS o build a mo e p o ound and cohe en pic u e o he main
ac o s ha lead o ca ee success (which a e di ec ly a ec ed by each indi idual’s beha io ).
Social capi al and in e pe sonal connec ions as p edic o s o ca ee success
The wo kplace’s social con ex is pi o al o success, especially in cus ome -cen ic indus ies
like hospi ali y, e ail, ou ism and sales. Rela ionships s and as one o he h ee pilla s o
ca ee success in he pu sui o a bounda yless ca ee (A hu and De illippi, 2001),
in e wined wi h mo i a ion (De illippi and A hu , 1994).
In e pe sonal connec ions o m he nucleus o ca ee success p edic o s, encompassing
us (Wang, 2014), leade –membe exchanges (Res ubog e al., 2011;Spu k e al., 2014),
membe –membe exchanges (D abe e al., 2015), de elopmen al ne wo ks (Cholle e al., 2021;
Cheung e al., 2016;Co on e al., 2011;Dob ow e al., 2012), men o ing (Ng and Feldman, 2014;
Higgins and K am, 2001;Lancau and Scandu a, 2002;Kong, 2010;De illippi and A hu ,
1994) and sponso ed mobili y (Mau e and Chapman, 2013).
Nume ous s udies unde sco e how social capi al impac s execu i e compensa ion
(Belli eau e al., 1996;Bu , 1997), educes u no e a es (K ackha d and Hanson, 1993) and
in luences ca ee o ien a ions, especially o women (Rod igues e al., 2019;Choi, 2019).
Recen esea ch ex ends his impac o he ca ee and de elopmen ou comes o HR
p o essionals (Gubbins and Ga a an, 2016).
Subjec i e ca ee success
Ca ee success, encompassing job aspec s, inances, in e pe sonal ela ionships, pe sonal
li es, lea ning and de elopmen , is in luenced by an indi idual’s aised li e s anda d and
educa ional le el, leading o a ied needs (Ha ing on and Hall, 2007). This shi in
unde s anding subjec i e ca ee success emphasizes o e all job and ca ee sa is ac ion.
Voca ional beha io plays a c ucial ole in achie ing he desi ed ou come o subjec i e ca ee
success.
Possible mode a o s o subjec i e ca ee success
Recognizing he complexi y o ca ee beha io , he au ho s employ mode a o s o assess
in e en ion e ec s ac oss di e se esea ch sample g oups (MacKinnon, 2011). P e ious
s udies highligh demog aphic ac o s, such as age (Van de Heijden e al., 2022), gende
(Fe nandez e al., 2023) and ma i al s a us (Ag awal and Singh, 2022), in luencing subjec i e
ca ee success. To add ess his, employe s a e adop ing wo k– amily en ichmen op ions
(Awan e al., 2021) and age-adjus ed human esou ce de elopmen policies (Van de Heijden
e al., 2022).
Expanding
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413
Job sa is ac ion has always been ela ed o subjec i e ca ee success, bu i emains
deba ed whe he job sa is ac ion leads o pe cei ed ca ee success (D abe e al., 2015;
Schwo mal e al., 2017) o subjec i e ca ee success leads o job sa is ac ion (Leh onen e al.,
2022;Sou e al., 2022). Educa ion is he ounda ion o he indi idual’s p o ession and
pe cei ed sel -wo h in he labo ma ke (Du a e al., 2021;Hildenb and, 2015;S€
onmez e al.,
2021). Educa ion makes job c a ing possible, which la ely has been in oduced as an
an eceden o subjec i e ca ee success (Kundi e al., 2022;Lo P es i e al., 2023).
Mic oen i onmen s and mac oen i onmen s impac indi iduals’ca ee sa is ac ion.
Family in luence, while po en ially con ibu ing o ca ee success, may also hinde i i ca ee -
building o e shadows amily commi men s (Liu and Yu, 2021). O ganiza ions, as a
mic oen i onmen , o e ca ee esou ces like ne wo king and men o ing, os e ing ca ee
success h ough enhanced lea ning and p o essional g ow h oppo uni ies (Ag awal and
Singh, 2022;Leh onen e al., 2022). La ge o ganiza ions, wi h inc eased esou ces, a e
posi ioned o p o ide be e suppo o success ul ca ee s.
Conside ing he mac oen i onmen is c ucial in e alua ing ca ee success. Socioeconomic
s a us, global income inequali y and dependence on ins i u ional capi al like ci ies a e pi o al
ac o s (Awan e al., 2021;Bagdadli e al., 2021;Fe nandez e al., 2023;Guo and Ba uch, 2021).
Unemploymen expe ience, ied o mac oeconomic shi s, signi ican ly impac s indi iduals’
employabili y and ca ee success (Manzoni and Mooi-Reci, 2020;Bo gen e al., 2021).
The s udy’s mode a o s all in o ou g oups:
(1) Family- ela ed ac o s (ma i al s a us, numbe o child en, p opo ional con ibu ion
o amily budge and p e ious unemploymen expe ience).
(2) Job- ela ed ac o s ( o al wo k expe ience, yea s in a cu en posi ion, cu en mon hly
sala y le el, liking a cu en job om he s a and educa ion).
(3) O ganiza ional a ibu e (company size).
(4) Demog aphic cha ac e is ics (gende and age).
The me hodology applied o he esea ch is ou lined in he nex sec ion, and he applica ion
o hese mode a o s is designed o inc ease he p ac icali y o he s udy.
Me hodology
Subjec i e Ca ee Success model has been c ea ed. I includes he Sa ickas and Po eli (2012)
CAAS beha iou s: conce n, con ol, cu iosi y and con idence, and in e pe sonal beha io
(connec ion) beha iou s by Ga ike and La wood (1986). All s a emen s we e measu ed
using he en-poin Like scale, which has a highe alidi y and explana o y powe han he
i e-poin Like scale sugges ed by Coelho and Es e es (2007).
Finally, subjec i e ca ee success was measu ed in acco dance wi h Gaile e al. (2020) by
using wo s a emen s: “To wha ex en a e you sa is ied wi h you job?” om Colakoglu
(2011),Con e se e al. (2014) and Ve b uggen e al. (2015), and “I am sa is ied wi h he success
o my ca ee ” om G eenhaus e al. (1990). A calcula ed C onbach’s alpha wi h a alue o
0.768 indica es good in e nal consis ency o he cons uc o his ac o .
The s udy da a we e collec ed in Ap il 2020 by in i ing people om di e en backg ounds
ia social media pla o ms, such as LinkedIn and Facebook. The ques ionnai e was w i en in
La ian, sugges ing ha he esul s can be a ibu ed o La ia’s socioeconomic con ex . A
o al o 390 alid esponses we e ob ained. Table 1 de ails he s udy sample desc ip ions.
The cons uc s’ eliabili y and alidi y we e assessed using SPSS 28 (S a is ical Package
o he Social Sciences). Subsequen ly, a ma hema ical model was implemen ed in Wa pPLS
8.0, a use - iendly so wa e package o a iance- and ac o -based s uc u al equa ion
EJMBE
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modeling (SEM) employing he pa ial leas squa es me hod (PLS), as ecommended by Hai
e al. (2014). PLS-SEM is a widely accep ed me hod o explo a o y esea ch in a ious ields,
including managemen and o ganiza ional de elopmen (Al-Em an e al., 2018;Kock and
Hadaya, 2018).
Wa pPLS, a so wa e p og am de eloped by Sc ip Wa p Sys ems, is a powe ul ool o
p edic i e PLS-SEM cases oo ed in es ablished heo ies (Hai e al., 2014). No ably, o
explo a o y esea ch, PLS-SEM is a o ed (Kock and Hadaya, 2018), and Wa pPLS s ands
ou by allowing he explici iden i ica ion o nonlinea unc ions connec ing la en a iables
in SEM models and calcula ing associa ed mul i a ia e coe icien s o associa ion, a
capabili y unique o his so wa e (Kock, 2010). Unlike o he ools ha o e solely linea
unc ions, Wa pPLS is he i s o p o ide classic PLS algo i hms alongside ac o -based PLS
algo i hms o SEM (Kock, 2019).
To al numbe o esponden s: 390 # %
Gende Female 283 72.56
Male 107 27.44
Age Range 23–67
Mean 40.07
S.D. 9.65
Educa ion P ima y school 2 0.51
Seconda y school 40 10.26
Bachelo ’s deg ee 104 26.67
Mas e ’s deg ee 229 58.72
Doc o al deg ee 15 3.85
Ma i al s a us No ma ied 174 44.62
Ma ied 216 55.38
Child en Range 0–5
Mean 1.04
S.D. 1.1
Con ibu ion o amily budge (%) Range 10–100
Mean 64.09
S.D. 25.30
Sala y le el (EUR) 500 o less 0 0.00
501–1,000 101 25.90
1,001–2,000 177 45.38
2,001–5,000 85 21.79
Mo e han 5,000 27 6.92
Company size Solo 25 6.41
Small 106 27.18
Midsized 112 28.72
La ge 147 37.69
Liking cu en job a i s s a (Like -10) Range 0–10
Mean 7.82
S.D. 1.76
Yea s in cu en posi ion Range 0–44
Mean 5.63
S.D. 6.14
To al wo k expe ience (yea s) Range 0–50
Mean 18.93
S.D. 9.75
Unemploymen expe ience Yes 214 54.87
No 176 45.13
Sou ce(s): Au ho s
Table 1.
S udy’s sample
desc ip i es
Expanding
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415
Resea ch model
Figu e 1 p esen s he ini ial esea ch model, which con ains he in e pe sonal beha io
cons uc (connec ions) as well as he ou ca ee adap abili ies cons uc s (con ol, cu iosi y,
con idence and conce n). This e lec s he s a ing poin o he esea ch me a-model in his
pape and he key cons uc s o u he PLS-SEM analysis.
The gene al PLS-SEM analysis esul s include model i and quali y indexes: a e age pa h
coe icien (APC), a e age R-squa ed (ARS), a e age adjus ed R-squa ed (AARS), a e age block
a iance in la ion ac o (AVIF) and a e age ull collinea i y VIF (AFVIF). I is ecommended
ha he p alues (signi icance) o APC, ARS andAARS should all be equal o o lowe han 0.05;
his was he case o he main esea ch model (APC 50.220, p<0.001;ARS50.410, p<0.001;
AARS 50.402, and p< 0.001). Ideally, bo h AVIF and AFVIF should be equal o o lowe han
3.3 (pa icula ly in models whe e mos o he cons uc s a e measu ed h ough wo o mo e
indica o s); his was ue o he model used (AVIF 51.699 and AFVIF 51.863).
Measu emen model: eliabili y and alidi y
To ensu e he alidi y and eliabili y o he e lec i e measu emen model, a ious es s we e
conduc ed using he mos equen echniques acco ding o Ringle e al. (2012). Thus, he
in e nal consis ency eliabili y wi h C onbach’s alpha (CA) and composi e eliabili y (CR), he
con e gen alidi y wi h he a e age ex ac ed a iance (AVE) and he disc iminan alidi y
wi h he Fo nell–La cke c i e ion (Ringle e al., 2012) we e es ed. Validi y indica es he
deg ee o which a measu emen model can p edic wha will be measu ed. By con as ,
eliabili y checks he deg ee o which he same measu ed alues lead o he same esul s; his
ep esen s he ailu e a e (Bu ns and Bu ns, 2008;Weibe and M€
uhlhaus, 2014).
In he beginning, he in e nal consis ency eliabili y was es ed ( o which he a e age
co ela ion o all o he indi idual i ems o he same cons uc a e compa ed). Thus, his
shows he accu acy o a g oup o a iables o i ems measu ing a la en a iable. In e nal
consis ency eliabili y is mos ly measu ed wi h CA and CR (Ringle e al., 2012). The highe he
alues o CA and CR, he mo e cong uen he i ems (e go, he highe he in e nal eliabili y). In
he model, he CA o all he cons uc s was conside ably g ea e han 0.7 (Table 2), which is
men ioned as he h eshold. The CR should ha e a alue o a leas 0.6, which is e lec ed in
he cu en model alues in Table 2 ( anging om 0.855 o 0.903) (Weibe and M€
uhlhaus,
2014). Thus, his model is in e nally eliable.
Figu e 1.
Subjec i e ca ee
success model o s udy
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Rega ding es ing he con e gen alidi y, AVE was used; his de e mined he a e age
pe cen age o he i ems ha explain he dispe sion o he la en cons uc . In he li e a u e, a
h eshold o 0.5 is men ioned o his ac o (Fo nell and La cke , 1981;Bagozzi and Yi, 1988);
his was he case o all he cons uc s in he model (Table 2). Las ly, he disc iminan alidi y
wi h he Fo nell–La cke c i e ion (Fo nell and La cke , 1981) was checked. The e o e, he
squa e oo o each AVE in a diagonal mus be compa ed wi h he co ela ion coe icien s o
each cons uc . Table 2 shows ha he AVE was highe in each case in he model, so he
disc iminan alidi y is accep ed. Table 3 p o ides s uc u e loadings and c oss-loadings o
deepe insigh s in o he cons uc ’s eliabili y and alidi y.
CR CA AVE PCS CONN CONT CURI CONF CONC
PCS 0.896 0.768 0.811 0.901 0.511 0.389 0.114 0.268 0.251
CONN 0.881 0.797 0.712 0.511 0.844 0.353 0.140 0.234 0.248
CONT 0.860 0.803 0.506 0.389 0.353 0.712 0.511 0.562 0.468
CURI 0.855 0.788 0.543 0.114 0.140 0.511 0.737 0.666 0.634
CONF 0.903 0.871 0.609 0.268 0.234 0.562 0.666 0.780 0.461
CONC 0.890 0.844 0.619 0.251 0.248 0.468 0.634 0.461 0.787
No e(s): (CR: composi e eliabili y; CA: C onbach’s alpha; AVE: a e age a iance ex ac ed) as well as in e -
cons uc co ela ion ma ix (wi h squa e oo s o AVEs shown in i alic on diagonal)
Sou ce(s): Au ho s
PCS CONN CONT CURI CONF CONC
PCS1 0.901 0.466 0.367 0.113 0.245 0.223
PCS2 0.901 0.456 0.333 0.092 0.238 0.23
CONN1 0.447 0.844 0.355 0.146 0.251 0.239
CONN2 0.458 0.865 0.317 0.108 0.18 0.212
CONN4 0.387 0.821 0.217 0.1 0.16 0.175
CONT1 0.493 0.362 0.632 0.231 0.321 0.423
CONT2 0.292 0.281 0.767 0.41 0.384 0.393
CONT3 0.267 0.273 0.773 0.465 0.539 0.37
CONT4 0.124 0.146 0.699 0.339 0.327 0.236
CONT5 0.267 0.281 0.733 0.386 0.492 0.305
CONT6 0.24 0.164 0.653 0.326 0.312 0.273
CURI1 0.025 0.003 0.337 0.759 0.365 0.458
CURI2 0.116 0.115 0.38 0.809 0.48 0.583
CURI3 0.107 0.163 0.441 0.67 0.445 0.403
CURI4 0.253 0.234 0.46 0.713 0.669 0.407
CURI6 0.077 0.011 0.277 0.726 0.508 0.472
CONF1 0.229 0.222 0.403 0.436 0.739 0.28
CONF2 0.216 0.211 0.42 0.454 0.73 0.242
CONF3 0.173 0.128 0.429 0.635 0.788 0.487
CONF4 0.197 0.114 0.384 0.563 0.779 0.428
CONF5 0.162 0.203 0.461 0.527 0.837 0.35
CONF6 0.283 0.22 0.529 0.499 0.806 0.363
CONC1 0.007 0.069 0.135 0.43 0.212 0.734
CONC2 0.143 0.148 0.276 0.441 0.3 0.753
COCN3 0.234 0.206 0.437 0.52 0.43 0.842
CONC4 0.259 0.218 0.458 0.487 0.353 0.744
CONC5 0.336 0.315 0.508 0.604 0.494 0.851
Sou ce(s): Au ho s
Table 2.
Reliabili y and alidi y
measu es
Table 3.
S uc u e loadings and
c oss-loadings
Expanding
ca ee
adap abili y
417
Resul s
The s udy esul s in his sec ion a e p esen ed in h ee sub-sec ions. The i s desc ibes he main
model, as well as he key ela ionships be ween he dependen a iable o he subjec i e ca ee
success and he independen a iables o connec ions (con ol, cu iosi y, con idence and conce n).
The second ou lines he s a is ically signi ican mode a ing e ec s o he 12 a iables (Table 4)on
he main ela ionships in he esea ch model. The hi d explo es how he signi ican mode a ing
e ec s al e ed he ela ional s eng hs among he independen and dependen cons uc s.
Main model
The main esul s o he s uc u al model a e p esen ed in Figu e 2. The β alues ha a e no ed
nex o each a ow demons a e he s eng h o he ela ionships among he cons uc s, and
he as e isks ma k hei s a is ical signi icance ( he R
2
con ibu ions a e p esen ed in
b acke s). All he pa hs in he model a e s a is ically signi ican . The model isibly
demons a es how signi ican ly s ong he e ec o he connec ions is on explaining
subjec i e ca ee success (β50.412, p< 0.001). This is especially ue when compa ing i wi h
he pa h coe icien s o he o he ou cons uc s ha ep esen he ca ee adap abili y ac o s
(β50.236–0.117, p< 0.001–0.050).
The o al e ec s and e ec sizes a e also p o ided in Figu e 2. The e ec sizes (
2
)
de e mine whe he he e ec s indica ed by he pa h coe icien s a e small (0.02), medium
(0.15) o la ge (0.35). This s udy e eals ha ela ionships a wo k (connec ions) domina e in
he size o hei e ec on subjec i e ca ee success (
2
50.217) as compa ed o he e ec sizes
o he o he ou cons uc s (
2
50.096–0.023) ela ed o he CAAS. The cu en model in
Figu e 2 po ays he di e ences by changing he a ow sizes and hicknesses acco dingly.
O he ou ca ee adap abili y ac o s, con ol had he s onges p edic i e powe
on subjec i e ca ee success (β50.236, p< 0.001), wi h a medium o small e ec size
(
2
50.096). The nex la ges e ec on subjec i e ca ee success (β50.198, p< 0.001) came
CONN →PCS CONT →PCS CURI →PCS CONF →PCS CONC →PCS
Ma i al β50.160***
p< 0.001
β50.090*
p50.036
Child en β50.147**
p50.002
β50.099*
p50.024
FamilyBudge β50.100*
p50.023
Unemploymen β50.195***
p< 0.001
Yea sTo al β50.094*
p50.030
Yea sCu en ––– – –
Sala y ––– – –
LikeS a β50.193***
p< 0.001
Educa ion β50.085*
p50.045
β50.104*
p50.019
CompanySize β50.107*
p50.016
Gende β50.087*
p50.042
Age β50.095*
p50.028
Sou ce(s): Au ho s
Table 4.
O e iew o
mode a ing e ec s in
main esea ch model
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Co esponding au ho
Ani a Gaile can be con ac ed a : [email p o ec ed]
Fo ins uc ions on how o o de ep in s o his a icle, please isi ou websi e:
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