B aga, Thais Gue a; Casa o o Filho, Nelson; Wegne , Douglas; B ambilla, Flá io
Régio; Fe ei a, B uno Mo gado
A icle
S a egic ne wo ks' dynamics: E idence o membe i ms'
e en ion and depa u es in B azil
Adminis a i e Sciences
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Sugges ed Ci a ion: B aga, Thais Gue a; Casa o o Filho, Nelson; Wegne , Douglas; B ambilla, Flá io
Régio; Fe ei a, B uno Mo gado (2024) : S a egic ne wo ks' dynamics: E idence o membe i ms'
e en ion and depa u es in B azil, Adminis a i e Sciences, ISSN 2076-3387, MDPI, Basel, Vol. 14,
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Ci a ion: B aga, Thais Gue a, Nelson
Casa o o Filho, Douglas Wegne ,
Flá io Régio B ambilla, and B uno
Mo gado Fe ei a. 2024. S a egic
Ne wo ks’ Dynamics: E idence o
Membe Fi ms’ Re en ion and
Depa u es in B azil. Adminis a i e
Sciences 14: 65. h ps://doi.o g/
10.3390/admsci14040065
Recei ed: 16 Janua y 2024
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adminis a i e
sciences
A icle
S a egic Ne wo ks’ Dynamics: E idence o Membe Fi ms’
Re en ion and Depa u es in B azil
Thais Gue a B aga 1, Nelson Casa o o Filho 1, Douglas Wegne 2, Flá io Régio B ambilla 3
and B uno Mo gado Fe ei a 4,*
1Depa men o P oduc ion Sys em Enginee ing P og am, Fede al Uni e si y o San a Ca a ina (UFSC),
Flo ianopolis 88040-900, SC, B azil; [email p o ec ed] (T.G.B.); nelson.casa [email p o ec ed] (N.C.F.)
2Business School, Fundação Dom Cab al (FDC), No a Lima 34018-006, MG, B azil; [email p o ec ed]
3Business Managemen and Communica ion Depa men , Uni e si y o San a C uz do Sul (UNISC),
San a C uz do Sul 96815-900, RS, B azil; [email p o ec ed]
4Poly echnic Ins i u e o Viseu, Highe School o Technology and Managemen o Viseu, Resea ch Cen e in
Digi al Se ices (CISeD), 3504-510 Viseu, Po ugal
*Co espondence: mo gado. e ei a@es g .ip .p
Abs ac : S a egic Ne wo ks (SNs) ha e eme ged as a p e alen o ganiza ional o m ha o e s
syne gis ic bene i s o pa icipa ing i ms. Despi e hei po en ial, SNs o en expe ience membe
i ms’ depa u e, aising conce ns abou hei long- e m iabili y. This s udy explo es he ac o s
ha in luence i ms’ decisions o exi SNs by examining he in e play be ween ne wo k ma u i y,
membe i ms’ sa is ac ion, and hei indi idual cha ac e is ics. Using da a om 338 B azilian i ms
in ol ed in SNs, a clus e analysis was employed o iden i y dis inc g oups o i ms based on sha ed
a ibu es. The indings e ealed a signi ican associa ion be ween highe pe cei ed ma u i y, g ea e
sa is ac ion wi h SNs, and lowe likelihood o depa u e. These esul s sugges ha ne wo k leade s
should p io i ize cul i a ing a ma u e and sa is ying SN en i onmen o mi iga e membe exi s. By
iden i ying he c i ical dis inc ions be ween he emaining and depa ing i ms, his s udy p o ides
aluable insigh s o ne wo k manage s seeking o s eng hen he longe i y and s abili y o hei
s a egic pa ne ships.
Keywo ds: s a egic ne wo k; coope a ion ailu e; clus e analysis; membe i ms’ depa u e; ne -
wo k dissolu ion
1. In oduc ion
Coope a ion be ween small- and medium-sized i ms has led o he o ma ion o
in e -o ganiza ional ne wo ks o minimize he sca ci y o esou ces aced by hese i ms,
gene a ing g ea e inancial e iciency (Emami e al. 2022), oppo uni ies o collec i e
lea ning (He e al. 2021) and collabo a i e inno a ions (Cheboi e al. 2022). Fo mal and
long- e m coope a i e ag eemen s among he o ms o in e -o ganiza ional ne wo ks de ine
S a egic Ne wo ks (SNs). Th ough SNs, companies es ablish a join pu pose and o m o
ela ionship go e nance o achie e common goals and o gene a e compe i i e ad an ages
(Mandell e al. 2017;T ˛apczy´nski e al. 2018;An oldi and Ce a o 2020;Wegne e al. 2022).
Despi e a la ge numbe o s udies on SNs in ecen decades (T ˛apczy´nski e al. 2018;
An oldi and Ce a o 2020), he e a e s ill gaps in he knowledge abou how o manage hem
(Agos ini e al. 2015) and how hey de elop o e ime (Giuliani 2013;Popp e al. 2013).
Se e al s udies indica e ha despi e he success o his coope a ion model, a signi ican
numbe o SNs ace di icul ies in consolida ing, and a conside able numbe ail (Klein and
Pe ei a 2016;Tunisini and Ma chio i 2020).
Recen s udies ha e sough o iden i y he s ages o SN de elopmen , making i
possible o unde s and he changes ha occu o e ime and how some SNs assume upwa d
Adm. Sci. 2024,14, 65. h ps://doi.o g/10.3390/admsci14040065 h ps://www.mdpi.com/jou nal/admsci
Adm. Sci. 2024,14, 65 2 o 13
ajec o ies while o he s decline (Wegne e al. 2015;Klein and Pe ei a 2016). Th ough he
de elopmen o a SN, di e en p oblems can a ise (Tunisini and Ma chio i 2020).
Gi en his easoning, his s udy add esses he ollowing ques ion: Wha ac o s d i e
he decision o ne wo k membe i ms o lea e he ne wo k? This s udy aims o unde s and
how ne wo k pe o mance can be ela ed o membe i ms’ sa is ac ion and hei endency
o lea e he SN.
Da a we e collec ed om 338 i ms ha pa icipa ed in B azilian SNs. We hen pe -
o med a clus e analysis o associa e i ms wi h common cha ac e is ics in g oups o
unde s and he main ac o s ha a ec he pe manence o one o mo e membe s. This
analysis can help ne wo k manage s ac be o e a membe asks o lea e he ne wo k by
planning a ge ed ac ions o inc ease membe i ms’ sa is ac ion wi h hose ac o s ha
a ec membe i ms’ pe manence. Thus, i can enhance he su i al o a SN.
2. Li e a u e Re iew
2.1. S a egic Ne wo k Dynamics
In esea ch abou chambe s o comme ce, Cos anzo and Goodnigh (2015) suppo
he idea ha he exis ence and longe i y o membe ship-d i en non-p o i o ganiza ions
depend on membe ship e en ion and ec ui ing. When he ne wo k ails o e ain membe s,
when hey s op pa icipa ing in i s ac i i ies, and when hey lea e he ne wo k, i s a s o
ail and may dissol e.
Two ne wo k ou comes p edic membe ship e en ion: membe i ms’ sa is ac ion
and con inui y. Membe s’ sa is ac ion is de ined as he deg ee o which ne wo k membe s
belie e ha being pa o he ne wo k and in e ac ing wi h o he ne wo k membe s ha e
exceeded hei expec a ions. Ne wo k con inui y e e s o a g oup’s willingness o con inue
collabo a ing and being pa o he SN. In his way, membe s’ pe cep ions o he ne wo k
p edic hei u u e pa icipa ion and suppo (B ad o d e al. 2004).
Despi e some esea ch ha e alua es and comp ehends he ailu e and dissolu ions o
ne wo ks (e.g., Tunisini and Ma chio i 2020), no empi ical esea ch is a ailable ha assesses
membe s’ sa is ac ion and con inui y in SNs. The ela ionships based on SNs a e “buil
o adap ” because hey mus adap acco ding o he compe i i e en i onmen , dynamics
o esou ces, new s a egies, and ies be ween pa ne s (Abbas e al. 2019). Th ough his
dynamic de elopmen p ocess, many challenges may be aced du ing di e en g ow h
phases (Tunisini and Ma chio i 2020). Also, du ing i s de elopmen , he SN can pe o m
success ul changes ha inc ease membe i ms’ sa is ac ion and boos ne wo k pe o mance.
S ill, some changes can lead he opposi e way, con ibu ing o poo sa is ac ion o less
ne wo k pe o mance.
Some esea che s p oposed amewo ks and models o be e unde s and a SN’s dy-
namic de elopmen p o ile. Tunisini and Ma chio i (2020) p esen ed i e ac o s ha a ec
ne wo k dynamics: indi idual a iables, s uc u al cha ac e is ics, legi imacy a iables,
in e ac ion a iables, and go e nance a iables. Simila ly, some au ho s p opose ha
o ganiza ional and ela ional changes dic a e i s de elopmen (e.g., Wegne e al. 2015;
Mo e i and Zi poli 2016). The i e ac o s p esen ed by Tunisini and Ma chio i (2020)
can be g ouped in o ela ional and o ganiza ional aspec s, as indi idual and in e ac ional
a iables a e ela ed o ela ional ac o s, and s uc u al, legi imacy, and go e nance a e di-
ec ly ela ed o he o ganiza ional aspec s o a SN. In his way, o conduc ou esea ch, we
conside ed o ganiza ional and ela ional aspec s as he ones ha in luence SN de elopmen ,
and by hei pe cep ion, hey can assess ne wo k ou comes, membe i ms’ sa is ac ion,
and con inui y.
Since o ganiza ional and ela ional dimensions a e la en cons uc s, and aspec s ha
canno be di ec ly obse ed o measu ed, hey mus be analyzed om he pe spec i e
o he cons uc ion o psychome ic scales. This pe spec i e aims o ensu e he alidi y
and eliabili y o he esul s (Pasquali 2009). We chose o apply he su ey de eloped by
Wegne e al. (2015), as i co e s o ganiza ional and ela ional dimensions o e alua e he
de elopmen o a SN and has e idence o alidi y as p esen ed by B aga e al. (2022). In
Adm. Sci. 2024,14, 65 3 o 13
Table 1, he o ganiza ional and ela ional dimensions o SNs a e p esen ed and discussed
in de ail in he ollowing sec ion.
Table 1. O ganiza ional and ela ional dimensions o s a egic ne wo ks.
Dimension Desc ip o
O ganiza ional
Managemen
- Managemen s uc u e
- S a egy
- Adminis a i e p ocedu es
Go e nance
- Decision-making
- Fo maliza ion
- Incen i es and sanc ions
- Con ols
P ocess de ini ion
- Se ice o e
Rela ional
In o ma ion exchange
T us in managemen
T us in associa es
In e pe sonal ela ionships
Sou ce: Adap ed om he s udy by Wegne e al. (2015).
2.2. O ganiza ional Dimensions
SNs a e a complex ype o o ganiza ion, mainly due o managing se e al ac o s and
hei sha ed ac i i ies simul aneously (Macciòand C is o oli 2017). Managemen in luences
pe o mance and esul s (Olsen e al. 2012). Oli ei a-Ribei o e al. (2021) highligh ed
ha go e nance and managemen unc ion as sys ems ha p esen in e ela ionships
ha a ec he ne wo k’s e iciency le el. They a gue ha analyzing his go e nance
managemen sys em and he elemen s cons i u ing each aspec in mo e de ail is necessa y.
Unde s anding he unc ioning o SNs is impo an as well as how ce ain condi ions and
s uc u es in luence collec i e esul s (P o an and Kenis 2008).
The managemen o a ne wo k comp ises o ganiza ional and manage ial ac i i ies e-
la ed o i s de elopmen and ope a ion (Agos ini e al. 2015). Es ablishing an o ganiza ional
s uc u e is necessa y o suppo i s ac i i ies, p o ec membe s and ins i u ions om ex e -
nal p essu e, and explo e ex e nal and in e nal oppo uni ies (Macciòand C is o oli 2017).
The co e managemen o a ne wo k is also esponsible o con olling he en ance and exi
o o ganiza ions in o he g oup and media ing he ela ionships be ween o ganiza ions
(Oli ei a and da Sil a 2022).
Go e nance delimi s managemen (Oli ei a-Ribei o e al. 2021) h ough a s uc u e
o collec i e ac ion ha includes de ining he ules o decision-making, esponsibili ies,
and limi s o pa icipan au onomy (P o an and Kenis 2008). In addi ion o being a ool o
engaging membe s in collec i e ac i i ies, i is also an essen ial ins umen o moni o ing
and con olling ne wo k managemen .
Ano he o ganiza ional aspec o ne wo ks is he o ganiza ion o se ices o e ed o
membe i ms. The p o ision o se ices has become a ne wo k managemen esponsibili y
ha aims o acili a e companies’ adap a ion o ma ke changes and inc ease hei com-
pe i i eness (Fe ei a and A magan 2011). T aining and quali ica ions, such as ma ke ing,
inancial, and echnology consul ancy, s and ou among he se ices o e ed.
2.3. Rela ional Dimensions
Ne wo ks ha e a dynamic p o ile because companies ha e di e en posi ions based
on hei connec ions wi h o he membe s. These connec ions cons an ly change depending
on how membe i ms combine esou ces and ac i i ies (Ab ahamsen e al. 2012). E ec i e
collabo a i e ela ionships be ween companies in a ne wo k equi e he de elopmen
Adm. Sci. 2024,14, 65 4 o 13
o ela ional skills. T us be ween membe s d i es he achie emen o collec i e goals
(Ch upała-Pniak e al. 2017). In in e -o ganiza ional ela ionships, us is a cyclical p ocess
es ablished by leade ship based on he media ion o ela ionships and ag eemen s and he
engagemen o pa ne s (Ch upała-Pniak e al. 2017).
In ne wo ks o small companies, each en ep eneu ends o know o he s pe sonally
and main ains ela ionships ha exis ed be o e he o ma ion o he ne wo k. The e o e,
adminis a ion is mo e in o mal and guided by social mechanisms. Howe e , wi h he
en y o new membe s, he ne wo k becomes mo e complex, in e pe sonal ela ionships
become sca ce, and i is necessa y o ha e a o maliza ion p ocess o guide ac ions and
moni o he g oup’s pe o mance (P o an and Kenis 2008).
3. Me hod
This sec ion desc ibes he me hodology used o unde s and how a SN’s o ganiza ional
and ela ional dimensions ela e o i s membe i ms’ sa is ac ion and endency o lea e he
SN. We p esen ou sample, da a collec ion p ocedu es, main a iables, and echniques o
es ou hypo heses. We used he clus e analysis echnique, which allows obse a ions o
be g ouped in o homogeneous g oups when he e is an in en ion o e i y he exis ence
o simila beha io s be ween obse a ions (Fá e o and Bel io e 2017), as is he pe cep ion
o membe s abou SN o ganiza ional and ela ional aspec s. In clus e analysis, based on
esea ch objec i es, he esea che mus choose clus e a iables ep esen ing he cha ac e -
is ics used o compa e obse a ions and ex e nal a iables o assess he di e ences among
he clus e s (Hai 2009;Fá e o and Bel io e 2017).
3.1. Da a Collec ion
A su ey was conduc ed o e alua e he signi icance o he sample popula ion (G o es
e al. 2009). This echnique equi es a clea de ini ion o he app op ia e uni o analysis.
Con enience sampling was used, as he choice o sample elemen s was ca ied ou non-
andomly, conside ing he pa icula cha ac e is ics o he g oup unde s udy and he
esea che s’ knowledge o wha hey we e in es iga ing. The s udy objec s o he concep ual
model we e SNs, speci ically hose in he building ma e ials ade sec o .
We used he su ey de eloped by Wegne e al. (2015), wi h e idence o alidi y
p esen ed by B aga e al. (2022). The su ey consis s o 41 ques ions on a i e-poin scale,
anging om “ o ally disag ee” o “ o ally ag ee”, ha measu es aspec s ega ding each
desc ip o de ailed in Table 1.
The su ey was sen digi ally o 600 companies associa ed wi h 19 SNs in B azil in
he cons uc ion ma e ials sec o be ween July and Augus 2021. A o al o 352 esponses
we e ob ained, esul ing in a inal sample o 338 a e excluding incomple e esponses.
This sample comp ised 56% o he expec ed esponses om he s udy g oup. Acco ding
o Mosca ola (1990)’s Law o La ge Numbe s, a sample o 300 esponden s is su icien o
ob ain esul s ha align wi h eali y and ha e a lowe chance o e o (Mosca ola 1990).
Al hough he su ey esul s using a con enience sample canno be gene alized o he en i e
popula ion, hey a e a sou ce o heo e ical in e ences o he eali y s udied.
3.2. Measu es
The clus e a iables used o cha ac e ize he companies in di e en clus e s a e he
O ganiza ional and Rela ional dimensions cap u ed by he 40 ques ions o he su ey
applied o da a collec ion (Appendix A).
The p edic ion a iable is he p obabili y o lea ing a ne wo k, e alua ed by one
i em: “Wha is he possibili y ha you company will disconnec om he ne wo k in he
nex 12 mon hs?”. The answe is ca ego ically measu ed on a i e-poin scale wi h 0%,
indica ing no chance o lea ing he ne wo k, wi h 25%, 50%, 75%, and 100% indica ing ha
he company is su e ha i will lea e he ne wo k.
Addi ionally, we asked he membe i ms h ee ques ions ega ding hei sa is ac ion
wi h he SN:
Adm. Sci. 2024,14, 65 5 o 13
(a)
o e all sa is ac ion wi h hei membe ship in he SN: “I am ully sa is ied wi h he
bene i s ha pa icipa ion in he ne wo k p o ides o my company”;
(b)
whe he he esul s ully jus i ied he cos s o being pa o he SN: “The esul s ha
my company is ob aining ully jus i y he cos s o being pa o he ne wo k”;
(c)
whe he pa icipa ion signi ican ly inc eased hei c edibili y in he ma ke ;
(d)
whe he membe s a e adhe en o ne wo k s a egies: “The e is a high le el o adhe -
ence by membe s o he collec i e s a egies p oposed by he ne wo k”.
These ques ions suppo and explain ou analysis, co e ing he wo ne wo k ou comes
unde s udy: membe i ms’ sa is ac ion and con inui y.
3.3. Da a P e-P ocessing
To apply clus e echniques, da a mus be on a quan i a i e scale, as hey a e submi ed
o calcula e ma ices and a e ages. The ini ial da a collec ed on a quali a i e Like scale
canno be analyzed using clus e ing echniques. I is necessa y o con e hese da a in o
an o dinal quan i a i e scale ob ained in his s udy by calcula ing ac o ial sco es. Fac o
analysis is a s a is ical echnique used o educe he complexi y and dimensionali y o
da abases, allowing analysis o he s uc u e o in e ela ionships be ween many a iables
(Hai 2009). This echnique helps c ea e smalle a iables om he o iginal se o acili a e
subsequen s a is ical analyses (Hai 2009).
By applying con i ma o y ac o analysis h ough he semi-s uc u al equa ion ech-
nique, we ound ha he su ey had an op imal i when ep esen ed by 13 la en a iables.
Fac o sco es we e ex ac ed o each esponden o each ac o in he model and used as
he inpu o he clus e echnique.
3.4. Da a Analysis
Clus e ing echniques a e di ided in o hie a chical and nonhie a chical echniques.
Based on s a is ical calcula ions, he numbe o app op ia e clus e s o es ima e o he
obse a ions and a iables unde s udy was e alua ed using he i s g oup o hie a chical
echniques. In non-hie a chical echniques, he numbe o clus e s (n) is de ined a p io i,
and s a is ical calcula ions a e used o dis ibu e he obse a ions o he da ase in he
n-de ined clus e s.
The hie a chical and nonhie a chical echniques p esen ed compa able esul s. The
esul s ob ained using hie a chical echniques on an adequa e numbe o clus e s can se e
as inpu s o alloca ing obse a ions using nonhie a chical echniques. Fá e o and Bel io e
(2017) sugges using bo h me hods when he e is no easonable es ima e o he numbe o
clus e s ha can be o med using da abase obse a ions and he a iables unde s udy.
Ini ially, he analysis pe o med a hie a chical clus e ing scheme o ob ain he ap-
p op ia e numbe o clus e s o he da ase . The agglome a i e me hod conside s all
obse a ions o be sepa a e. Based on he dis ances be ween obse a ions, g oups we e
o med, s a ing om se e al g oups equal o he numbe o obse a ions un il a single
g oup was o med. The comple e linkage ype was used o calcula e he dis ances, con-
side ing he mos signi ican dis ances be ween he obse a ions o es ima ions, which
is ecommended when he e is no conside able dis ance be ween obse a ion alues. We
used he Euclidean quad a ic dis ance, ecommended when he a iable alues ha e a
small dispe sion, as i acili a es he in e p e a ion o he analysis ou pu s and alloca ion
o obse a ions in he g oups (Fá e o and Bel io e 2017). The esul s we e analyzed by
in e p e ing he gene a ed ee- ype g aph, a dend og am ha summa izes he agglome a-
ion p ocess and explains he alloca ion o obse a ions in he g oups (Fá e o and Bel io e
2017). The analysis c i e ion o he magni ude o he dis ance gaps be ween he g oups
was used as he cu o poin . A gap o g ea e magni ude indica es ha conside ably
di e en obse a ions a e clus e ed and do no mee he in aclus e homogenei y c i e ia.
The e o e, he subsequen agglome a ion s age should no be conside ed. Fo he analysis
o he dend og am, he comple e linkage me hod and he calcula ion o he dis ance using
Adm. Sci. 2024,14, 65 6 o 13
he Euclidean quad a ic esul ed in a mo e e iden and explici gap, which a o ed he
iden i ica ion o he g oupings and he cu o poin and, he e o e, we e chosen in his wo k.
The nex s ep uses a non-hie a chical g ouping echnique o dis ibu e he g oup
obse a ions. The numbe o g oups ob ained by using he hie a chical me hod was used
as he inpu o he k-means me hod, which pe o ms he dis ibu ion o obse a ions
because i is mo e accu a e han hie a chical me hods.
Ce ain a iables mus be e alua ed o de e mine he dis ibu ion o he obse a ions
in he clus e s. The objec i e o a clus e is o ob ain in e nally homogeneous clus e s, ha
is, clus e s ha ha e high simila i ies wi hin each g oup (in a, wi hin) and low simila i ies
be ween each g oup (in e , be ween). In s a is ical e ms, his implies a low a iance wi hin
a clus e and a high a iance be ween clus e s. G oup a ia ion explained mos o he o al
da a a iance, as he clus e s di e ed om he ideal clus e . Thus, clus e analysis aims o
maximize he a iance a io be ween g oups (be ween) o e he o al a iance o he da a.
This a io ep esen s he pe cen age o da a a ia ion ha he p oposed model explains.
3.5. Pos -P ocessing
Once he clus e s a e es ima ed, he pos -p ocessing s age analyzes he dis ibu ion
o companies in he clus e s. To iden i y he sha ed cha ac e is ics be ween companies
in he same clus e , he coo dina es o he cen oids o each clus e we e analyzed o
each ma u i y de e minan o he in e -o ganiza ional ne wo ks. This analysis sough o
unde s and he dis ibu ion pa e ns o cen oid alues.
We hen assessed he p obabili y o lea ing he ne wo k in each clus e and sea ched
o he common ac o s ha p edic ed his a iable. This in ol ed e alua ing he le el
o sa is ac ion in each clus e , showing a di ec co espondence be ween high le els o
o ganiza ional and ela ional pe cep ion and membe i ms’ sa is ac ion and an indi ec
co espondence wi h he p obabili y o lea ing he SN.
4. Resul s and Discussion
The esul s below summa ize he 338 esponses o he su ey de eloped by Wegne
e al. (2015). The i ms pa icipa ed in a se o 19 di e en ne wo ks, wi h an adequa e
dis ibu ion o esponden s among each ne wo k, and no ne wo k ep esen ed mo e han
10% o he o al esponden s. Fai dis ibu ion o esponden s enables he esul s o be
gene alizable o he en i e se . The e was no bias a ising om a pa icula ne wo k ha
con ained many esponden s.
The p o iles o he esponden s showed ha mo e han 55% had comple ed highe
o pos g adua e educa ion, hus dealing wi h a sample o people who quali ied o he
esea ch. Six y pe cen did no hold managemen posi ions, and 40% held posi ions o
di ec o s, boa d membe s, o p esiden s. The p esence o people in he sample wi h and
wi hou a posi ion in he ne wo k is essen ial o a oid ision biases, as managemen and
membe s’ pe cep ions o he ne wo k a e o en di e en (Fe ei a and A magan 2011).
Rega ding he yea he esponden s’ companies joined he ne wo k, 80% joined be o e
2012 (see Figu e 1). This pa e n ensu es ha he sample comp ises esponden s who ha e
been associa ed wi h and know abou he ne wo k o a ew yea s.
Finally, conside ing he numbe o employees, Table 2shows ha he sample p edomi-
nan ly comp ises small companies wi h ewe han 40 employees. This p o ile is expec ed
since associa ion in s a egic ne wo ks is a mo e impo an s a egy o small companies
(B aga e al. 2022). The e o e, he sample was di e se and compe en in e alua ing he li e
cycle o he ne wo k in which hey we e membe s.
A e ex ac ing ac o ial sco es, a hie a chical g ouping echnique was used o es ima e
he numbe o clus e s sui able o he s udy. Using he jump me hodology p oposed by
Fá e o and Bel io e (2017), he cu o poin was de ined a a heigh o 50, co esponding o
a la ge leap in he clus e s. Fou pe pendicula lines mee his cu o line, es ablishing ou
clus e s o he s udied da a.
Adm. Sci. 2024,14, 65 7 o 13
Figu e 1. Accumula ed dis ibu ion o companies by he yea hey joined he ne wo k.
Table 2. Dis ibu ion o companies by numbe o employees.
Numbe o Employees Sha e o To al
1–10 32%
11–20 37%
21–40 22%
40+ 9%
To al 100%
The nex s ep is o dis ibu e he companies in he ou clus e s acco ding o he
sco es ob ained o he ne wo k li e cycle model ac o s. The a io be ween he explained
a iance be ween g oups and he o al da a a iance is 74.2%, ep esen ing a good i . The
338 companies we e g ouped acco ding o he ollowing dis ibu ion: 69 in Clus e 1 (20%),
97 in Clus e 2 (29%), 68 in Clus e 3 (20%), and 104 in Clus e 4 (31%).
In descending o de o he ac o sco e alues, he clus e s we e o ganized in he
ollowing o de : 1, 2, 4, and 3. Table 3shows ha clus e s 1 and 2 p esen posi i e alues,
and clus e s 3 and 4 p esen nega i e alues o all li e cycle ac o s. Conside ing ha
he ac o sco es ep esen he alues o he a iables ha make up each ac o (Hai
2009), a highe ac o sco e indica es ha he esponses o he ac o i ems a e mainly
dis ibu ed in high ca ego ies 4 and 5 (pa ially ag ee and s ongly ag ee), and lowe
ac o ial sco es co espond o answe s mainly in low ca ego ies 1 and 2 (comple ely disag ee
and pa ially disag ee).
Table 3. Analysis o some a iables o he ou clus e s.
Clus e s
Va iables 1 2 4 3
A e age cen oid 0.63 0.21 −0.20 −0.63
Ins ances numbe s 69 97 104 68
P obabili y o lea ing ne wo k = 0% 92% 85% 68% 50%
P obabili y o lea ing ne wo k = 50% 0% 2% 8% 21%
As he i ems o he applied su ey a e posi i e, high ac o ial sco es in all ac o s
co espond o a be e pe cep ion o he company abou he ne wo k o which i belongs
and consequen ly sugges a highe le el o ne wo k ma u i y in he li e cycle o SNs. In his
way, we can label he clus e s based on he le el o he pe cep ion o o ganiza ional and
Adm. Sci. 2024,14, 65 8 o 13
ela ional aspec s o he SN: clus e 1 wi h a Ve y high pe cep ion clus e , clus e 2 wi h a
High pe cep ion, clus e 4 wi h a Low pe cep ion, and clus e 3 wi h a Ve y Low pe cep ion
clus e . Clus e 1 could be designa ed “The Visiona y”. I ep esen s he g oup wi h a e y
high pe cep ion, seeing he ull po en ial o o ganiza ional and ela ional aspec s o he SN.
Clus e 2 co esponds o “The Op imis ”. This g oup has a high pe cep ion, main aining a
posi i e and hope ul iew o he SN aspec s. Clus e 3 agg ega es “The P agma is ”. This
g oup, wi h a low pe cep ion, sees he SN aspec s as hey a e, wi hou ose-colo ed glasses.
Clus e 4 eg oups “The Skep ic”. This clus e has a e y low pe cep ion, ques ioning he
e ec i eness o he SN’s o ganiza ional and ela ional aspec s.
In Figu e 2, he Visiona y clus e (in ed) shows he highes alues o all ac o s in
he model; he companies wi hin i be e pe cei e hei ne wo k. I is one o he smalles
clus e s ega ding he numbe o companies (69) and he clus e in which he companies
a e closes and mos homogeneous (smalles clus e size).
Figu e 2. G aphical ep esen a ion o he ou clus e s.
The P agma is and Skep ic clus e s (pu ple and blue) had he lowes alues o all
model ac o s and he lowes cen oid alues. The cha ac e is ics o he wo clus e s a e
a mo e elonga ed o ma on he y-axis and a signi ican numbe o companies ou side
he pe ime e . This is cha ac e is ic o clus e s wi h less homogenei y and smalle in a-
clus e ela ionships.
Rega ding he p obabili y o lea ing SNs in he nex yea , 93% o he companies
answe ed ha he chance was ze o in he Visiona y clus e . In addi ion, when asked
abou “ hei sa is ac ion wi h he ne wo k”, 80% esponded ha hey we e e y sa is ied
wi h he h ee i ems ha measu ed hei sa is ac ion ( esponses ocused on op ion 5: I
comple ely ag ee).
Ins ead, in he Skep ic clus e (blue), he pe cen age o companies ha indica ed a
chance o lea ing SNs in he nex yea inc eased o 50%, and 21% o hem a es ed ha
he chance was a leas 50%. Rega ding he h ee ques ions abou sa is ac ion, in he one
ha measu es he pe cei ed bene i s o pa icipa ion, 41% o he answe s we e alloca ed
