Rimbeck, Ma len; S ump -Wolle sheim, Ju a; Rich e , Alexande
A icle — Published Ve sion
Un olding IoT Adop ion: A S a us Quo Bias Pe spec i e
Business & In o ma ion Sys ems Enginee ing
Sugges ed Ci a ion: Rimbeck, Ma len; S ump -Wolle sheim, Ju a; Rich e , Alexande (2024) :
Un olding IoT Adop ion: A S a us Quo Bias Pe spec i e, Business & In o ma ion Sys ems
Enginee ing, ISSN 1867-0202, Sp inge Fachmedien Wiesbaden, Wiesbaden, Vol. 67, Iss. 6, pp.
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RESEARCH PAPER
Un olding IoT Adop ion: A S a us Quo Bias Pe spec i e
Ma len Rimbeck •Ju a S ump -Wolle sheim •Alexande Rich e
Recei ed: 7 Sep embe 2022 / Accep ed: 11 May 2024 / Published online: 31 Augus 2024
ÓThe Au ho (s) 2024
Abs ac In e ne o Things (IoT) solu ions a e s ill a
om using hei eno mous po en ial, pa ly because mis-
concep ions lead employees o a oid using IoT solu ions
and s ick o es ablished wo king ou ines. To shed ligh on
he non- a ional pe spec i e o use s, which allows o
in e ence on he eme gence o cogni i e misconcep ions,
489 esponden s’ pe cep ions o bene i s and cos s o IoT
solu ions we e analyzed. Using he pe spec i e o ‘‘s a us
quo bias’’, he quali a i e analysis e eals ha he pe -
cep ions o expe ienced and inexpe ienced use s pa ly
o e lap on bene i s such as he educ ion o e o s and
elie o pe sonnel. Howe e , he pe cep ions also di e ge
in pa , as inexpe ienced use s conside IoT solu ions o be
gimmicky, os e ing mis us . In addi ion, inexpe ienced
use s o e es ima e lea ning phases o in e ac ing wi h IoT
solu ions, leading o loss a e sion and consequen ly o
cogni i e mispe cep ions. Hence, he s udy examines he
gap be ween expe ienced and inexpe ienced use s as a
neglec ed aspec in IoT adop ion. Fu he , iden i ying el-
e an d i e s o he implemen a ion o IoT solu ions a he
indi idual le el helps o ex end he hi he o echnical iew
o IoT solu ions owa ds a mul i-laye app oach ha
includes a holis ic, beha io al pe spec i e.
Keywo ds In e ne o Things S a us quo bias
Pe cep ion Adop ion beha io
1 In oduc ion
The In e ne o Things (IoT) ep esen s a co ne s one o he
u u e gene a ion o he In e ne and a no el echnology
pa adigm (A zo i e al. 2017; Ben-Daya e al. 2019; Lu and
Neng 2010; Mish a e al. 2019). As he adop ion o IoT
solu ions enables he in elligen c oss-linking o mul iple
de ices and he eal- ime collec ion o in o ma ion (Mish a
e al. 2019; Xia e al. 2012), o ganiza ions see oppo uni ies
o educe cos s (Sandu and Gide 2017), o imp o e cus-
ome sa is ac ion (Ve manen and Ha kke 2019) and o
s uc u e wo k lows mo e e icien ly (Scuo o e al. 2017).
Howe e , a he indi idual le el, IoT solu ions a e con-
side ed o be complex and he e ogeneous, equi ing
speci ic ools and p o ound expe ise o adop ion and
main enance (Mish a e al. 2019). Many employees do no
ha e a clea unde s anding o he po en ial o IoT solu ions
and he ex en o which hei implemen a ion a ec s
o ganiza ional and p ocedu al condi ions (Leye e al.
2017). P e ious s udies ha e iden i ied he need o s udy
en e p ise-based IoT adop ion a he indi idual le el (Hsu
and Lin 2016), alse pe cep ion o IoT solu ions (Laume
and Eckha d 2012), as well as algo i hm a e sion owa ds
au oma ed in o ma ion sys ems (IS) (e.g., Heßle e al.
2022). These misconcep ions le employees ace IoT
solu ions eluc an ly, leading o slow adop ion speed,
wo ka ounds and e e sions o old wo king ools and
ou ines (Venka esh 2006). F om a ‘‘s a us quo bias’’
Accep ed a e h ee e isions by Alexande Maedche.
M. Rimbeck J. S ump -Wolle sheim
Chai o In e na ional Managemen and Co po a e S a egy,
Technical Uni e si y o F eibe g, F eibe g, Ge many
e-mail: [email p o ec ed]
J. S ump -Wolle sheim
e-mail: [email p o ec ed]e
A. Rich e (&)
School o Business and Go e nmen , Vic o ia Uni e si y o
Welling on, Welling on, New Zealand
e-mail: [email p o ec ed]
123
Bus In Sys Eng 67(6):815–832 (2025)
h ps://doi.o g/10.1007/s12599-024-00891-6
pe spec i e, employeesp e e ence o emain in cu en
si ua ions o wo king p ac ices leads o inc eased demands
on ime and cos s, along wi h ad e se eac ions o he
implemen a ion o new in o ma ion sys ems (Kim and
Kankanhalli 2009; Kim 2011).
P e ious esea ch conce ning use sadop ion beha io
ega ding he IoT p ima ily ocused on IoT se ices, sma
home o heal hca e indus ies (Hsu and Lin 2016; Pal e al.
2018; Williams e al. 2017). Fu he s udies (e.g., Sie e s
e al. 2021) examined he impac o IoT solu ions a he
indi idual and he eam le el, con ibu ing o an enhanced
unde s anding ha IoT-speci ic a ibu es may lead o
employee empowe men and dynamic eam s uc u es.
Howe e , hus a , no s udy has in es iga ed use snon-
a ional, ela i e pe cep ions o cos s and bene i s as well
as po en ial cogni i e mispe cep ions ega ding IoT solu-
ions. Mo eo e , no s udy has add essed he di e ences in
pe cep ion be ween expe ienced use s (i.e., employees who
ha e used o a e cu en ly using IoT solu ions in hei
wo king en i onmen ) and inexpe ienced use s (i.e.,
employees who ha e ne e used IoT solu ions in hei
wo king en i onmen ). P e ious esea ch on inexpe ienced
use s explains he eluc ance o adop new in o ma ion
sys ems wi h isola ion, lack o educa ion, o nos algic
eelings (Kahma and Ma schoss 2017). As we assume ha
inexpe ienced use s end o s ick o hei es ablished ou-
ines due o cogni i e misconcep ions, we ocus on bo h
expe ienced and inexpe ienced use s equally. By examin-
ing bo h g oups o unco e whe he speci ic bene i s o
cos s a e consis en ly o e - o unde es ima ed a di e en
le els o expe ience, we add ess an impo an esea ch gap.
Speci ically, he explo a ion o employee pe cep ions
o e s a highly ele an complemen o esea ch ha
examines adop ion beha io a he o ganiza ional le el o
se e al easons. Fi s , add essing eac ions and eelings a
he indi idual le el con ibu es o psychological iden i i-
ca ion (Leso e al. 2022). Second, unde s anding employ-
ees’ beha io al in en ion ega ding he implemen a ion o
IoT solu ions is c ucial o he adop ion p ocess o p oceed
as en isioned by managemen . Thi d, unde s anding indi-
idual pe cep ions acili a es he es ablishmen o new
ou ines (Venka esh 2006). By conside ing bo h ends o he
expe ience spec um, his s udy aims o p o ide a com-
p ehensi e unde s anding o he ac o s in luencing IoT
adop ion, mo ing beyond a one-size- i s-all pe spec i e.
Fu he mo e, he inc easing di usion o echnology as a
cul u al and o ganiza ional phenomenon can be s udied
mo e e ec i ely by conside ing non-use (Sa chell and
Dou ish 2009). Consequen ly, unde s anding use s’ pe -
cep ion o cos s and bene i s as well as cogni i e mispe -
cep ion means o e coming a undamen al hu dle o achie e
g ea e adop ion a he indi idual le el (Boons a and
B oekhuis 2010).
We aim o (1) empi ically cap u e IoT use s’ non- a-
ional pe cep ions o cos s and bene i s o IoT solu ions in
indus y and (2) o iden i y cogni i e mispe cep ion and
po en ial di e ences in pe cep ion ha may lead o di -
e en indi idual adop ion beha io . We su eyed 489
employees abou hei use o he IoT wi h p ima ily open-
ended ques ions and a ocus on IoT solu ions in indus y,
conside ing bo h applica ions in o ice and p oduc ion
en i onmen s. On he basis o he cons uc s o he s a us
quo bias heo y (SQBT), we analyzed he da a h ough an
induc i e con en analysis, allowing o he cap u e o
use s’ non- a ional pe spec i es. Wi hin he g oups (i.e.,
expe ienced and inexpe ienced use s), we also di e en i-
a ed be ween employees a he ope a ional and manage-
men le el o gene a e in-dep h insigh s ela ed o ou
esea ch ques ion. Ou esul s, i s o all, show ha he
esponden s conside he educ ion o e o s, imp o ed
p ocess managemen , and he elie o pe sonnel o be he
key bene i s o IoT adop ion. Howe e , while expe ienced
use s see he IoT as a long- e m challenge o in e pe sonal
exchange, inexpe ienced use s end o conside IoT solu-
ions as a poin less gimmick ha only uels mis us .
Inexpe ienced use s also o e es ima e he amoun o ime i
akes o become amilia wi h IoT solu ions. Pa icula ly in
his aspec , i is s iking ha solely employees a he
ope a ional le el o e es ima e he amilia iza ion pe iod
wi h IoT solu ions. This o e es ima ion is due o he ac
ha IoT solu ions a e o en seen as complex and non-
anspa en .
Ou s udy p o ides wo highly ele an heo e ical
con ibu ions: Fi s , based on ou empi ical quali a i e
obse a ions, we con ibu e o an explana ion o use s
p e e ence ega ding he in eg a ion o IoT solu ions in
hei wo king ou ines. In doing so, we con ibu e o a
b oade unde s anding o he implica ions o he use o
IoT solu ions (Beck e al. 2022), ocusing in pa icula on
non- a ional pe cep ions and po en ial misconcep ions ha
eme ge om algo i hmic decision making, along wi h
ele an insigh s o manage s. We analyzed ou esul s
h ough he lens o SQBT acco ding o Samuelson and
Zeckhause (1988) and Kim and Kankanhalli (2009),
adding ha b idging he gap be ween expe ienced and
inexpe ienced use s is a neglec ed aspec in examining IS
adop ion and use pe cep ion. As we iden i y majo di -
e ences in pe cep ions, we u he con ibu e o an
imp o ed and in-dep h unde s anding o beha io al a i-
udes and (nega i e) adop ion decisions owa ds IoT solu-
ions. Speci ically, ou esea ch con ibu es o he
alida ion and ex ension o exis ing indings in IS esea ch,
especially in ela ion o SQBT. Ou esul s sugges ha
unce ain y cos s and sunk cos s ha e a signi ican impac
on esis ance and, as a esul , slowe adop ion o IS, as
p e iously shown by Hsieh and Lin (2020) and Kim
123
816 M. Rimbeck e al.: Un olding IoT Adop ion: A S a us Quo Bias Pe spec i e, Bus In Sys Eng 67(6):815–832 (2025)
(2011). Mo eo e , ou s udy indica es ha he majo i y o
inexpe ienced use s ha e no in en ion o adop he IoT. In
con as o p e ious indings sugges ing easons such as
isola ion, lack o educa ion, o nos algia (Kahma and
Ma schoss 2017), we p opose ha cogni i e misconcep-
ions a e a cen al ac o leading inexpe ienced use s o
s ick o hei habi ual pa e ns. Second, we de e mine el-
e an d i e s o he implemen a ion o IoT solu ions a he
o ganiza ional le el and hus ex end he hi he o echnical
iew o he IoT. Speci ically, in e e ence o well-known
mul i-laye app oaches (e.g., Al-Fuqaha e al. 2015), we
ex end in pa icula he applica ion and business laye , by
including a holis ic, beha io al pe spec i e. Hence, we
con ibu e conside ably o a b oade concep ual unde -
s anding o IoT solu ions. Addi ionally, ou s udy comes
along wi h impo an p ac ical implica ions: Fi s , by
add essing eal-wo ld cases, po en ial bene i s and cos s o
IoT adop ion a e pa icula ly emphasized o inexpe ienced
use s. Second, bo h expe ienced and inexpe ienced use s
can bene i om making s a egic decisions a di e en
managemen le els.
2 Theo e ical Founda ion
2.1 IoT Solu ions in Indus y and he Impac
a he O ganiza ional Le el
The e m ‘‘IoT’’ desc ibes he global in e connec ion o
small independen senso s, complex de ices o sys em
en i onmen s, ep esen ing a gene ic e m o a ange o
ad anced in o ma ion sys ems. Linking o he In e ne , he
de ices a e able o ga he in da a om hei en i onmen
and communica e wi h o he de ices (A zo i e al. 2017).
Despi e di e en o ien a ions o p e ious s udies
(Miho ska and Sa ka 2018), he commonali ies con e ge
on he ollowing key a ibu es: (1) he p esence o a
speci ic numbe o physical objec s in he (wo king)
en i onmen , (2) he collec ion and simul aneous ans-
mission o in o ma ion o applica ions o use s o access
and e alua e, and (3) an enhanced deg ee o au oma ion
ega ding human–machine in e ac ion. Unlike use -cen ic
in o ma ion sys ems (Bu ala and Mpo u 2014; Ma ins
e al. 2020), IoT sys ems communica e di ec ly wi h each
o he and au onomously conduc simila ly s uc u ed ou-
ine ac i i ies. Acco dingly, he IoT p o ides high olumes
o da a (Sie e s e al. 2021), imp o ing accu acy and
e iciency (Lu h a and Mangla 2018).
In an indus ial con ex , in pa icula in e connec ed
sys ems in he p oduc ion p ocess a e ecei ing inc easing
a en ion. Fo ins ance, addi i e manu ac u ing p o ides a
lexible app oach o digi ally cap u e in en o y and au o-
ma ically ini ia e manu ac u ing asks on demand (Haleem
and Ja aid 2019). In addi ion, he concep o a sma ac-
o y includes eal- ime moni o ing and con ol o he en i e
p oduc ion p ocess h ough IoT de ices, co e ing p oduc-
ion lines, wa ehouses and dis ibu ion hubs (Khan e al.
2020). As a esul , undamen al o ganiza ional and p ocess-
ela ed changes occu (B ous e al. 2020), which massi ely
in e e e wi h es ablished wo king ou ines a he indi id-
ual le el (Ellis and Mo is 2015; Hy ha e al. 2019; She i
and Al-Hi mi 2017). Conc e ely, he managemen and
in e p e a ion o he gene a ed da a as new componen s in
es ablished wo king ou ines as well as changes in p o-
duc i i y, in e nal con ol, sel - egula ion, and secu i y
aspec s a e becoming inc easingly c i ical a he o gani-
za ional le el (Abe a e al. 2016; Chang e al. 2020; Pa el
and Pa el 2016). Due o he objec -cen ic na u e o IoT
solu ions, employees a he indi idual le el a e hus
in ol ed wi h p ocess- igge ing in e ac ions wi h objec s
(e.g., scanning RFID ags) as well as handling in e aces
ha epo he acqui ed da a (e.g., na iga ing h ough he
sys em, in e p e ing da a, dealing wi h isual analy ics)
(Ko en and Klamma 2018). Consequen ly, a high le el o
s ess and ea s o new IoT solu ions a e expec ed a he
indi idual le el (Reil e al. 2020).
2.2 Beha io al Responses a he Indi idual Le el
Conside ing he h ee key a ibu es o he IoT and i s
deploymen in indus y, beha io al esponses owa ds IoT
solu ions om employees can be de i ed in mo e dep h.
Fi s , he p esence o a speci ic numbe o physical objec s
massi ely in e e es wi h exis ing wo king ou ines by
cap u ing a a ie y o in o ma ion om he wo king en i-
onmen and p o iding subsequen eedback. In his con-
ex , Laume e al. (2016) indica e ha , in addi ion o he
a ibu es o he IoT i sel , he pe cep ion o al e ed
wo king ou ines induces esis ance beha io s. Mo eo e ,
IoT objec s may be conside ed as su eillance mechanisms,
causing employees o es ablish in isibili y p ac ices owa d
managemen (An eby and Chan 2018). Second, modi ied o
new applica ions and in e aces, p esen ing he collec ed
da a o use s, may ein o ce he cogni i e loading. Lea ning
and na iga ing h ough new in e aces c ea es changes in
he use expe ience, eme ging in o a p e alen phenomenon
in he indus y con ex , and consequen ly may lead o
esis ance beha io s (Hu anu 2021). Thi d, an enhanced
deg ee o au oma ion may dis up he psychological bal-
ance (Newcomb 1953) o employees. This occu s, o
ins ance, when au oma ed ins uc ions o ac ion (e.g.,
when e o s appea in he p oduc ion p ocess) con lic wi h
es ablished ou ines o employees. Consequen ly, sys ems
a e pe cei ed as a h ea and igge esis ance (Schein and
Rauschnabel 2021). Thus, a ious o ms o esis ance
beha io a e o be expec ed du ing he adop ion o new IoT
123
M. Rimbeck e al.: Un olding IoT Adop ion: A S a us Quo Bias Pe spec i e, Bus In Sys Eng 67(6):815–832 (2025) 817
solu ions, which is o en he case in he con ex o IS
(Basyal and Seo 2017).
Resis ance beha io s include apa hy (e.g., disin e es ,
inac ion), passi e esis ance (e.g., main aining es ablished
beha io , excuses), ac i e esis ance (e.g., exp essing dis-
sen ing posi ions, g umbling), o agg essi e esis ance
(e.g., des uc i e sabo age, h ea s) (Ch eim 2006; Coe see
1999; Lapoin e and Ri a d 2005; Laume e al. 2014). A
he beginning o he adop ion p ocess, esis ance is pa -
icula ly e iden in ela ion o new IS i sel ; in la e s ages
o adop ion, esis ance becomes poli icized and ends o
a ge he subs ance o he IS (Lapoin e and Ri a d 2005).
C i ical d i e s o esis ance include pe cei ed use ulness,
ease o use, and h ea s o isks (Bha ache jee and Hikme
2007; Laume e al. 2016; Maie e al. 2013; Schein and
Rauschnabel 2021). I is immensely c ucial o companies
o de ec impelling ac o s o nega i e eac ions a an ea ly
s age, as esis ance beha io s a e a cen al eason o no
using IS solu ions (Basyal and Seo 2017; Laume and
Eckha d 2012). Fu he s udies emphasize he eluc ance
o employees o engage wi h IoT solu ions, due o conce ns
abou hei inabili y o adap and ea s o inc easing
au oma ion and au onomy (Ahme oglu e al. (2022) and
highligh he social dimensions o IoT implemen a ion,
ci ing p i acy conce ns, su eillance, and dis us as c i i-
cal challenges ha o ganiza ions encoun e (Bi kel and
Ha mann 2019). Simila ly, de Vass e al. (2021) shed ligh
on he challenges aced by o ganiza ions in deploying IoT
echnologies, including esis ance om s akeholde s,
eluc ance o sha e da a, and in e ope abili y issues. Fu -
he mo e, Anca ani e al. (2020) con ibu e insigh s in o he
a ying deg ees o IoT eadiness and echnological capa-
bili ies wi hin o ganiza ions. By iden i ying di e en
clus e s o IoT p ojec s, he s udy emphasizes he di e se
na u e o IoT solu ions and he co esponding impac s on
o ganiza ional p ocesses and capabili ies. In ligh o hese
indings, i becomes e iden ha unde s anding and
add essing employee conce ns and esis ance beha io s a e
essen ial o success ul IoT adop ion. In addi ion, s udies
indica e ha isks owa ds new IS a e a ed highe by
inexpe ienced use s (Schein and Rauschnabel 2021),
impeding he indi idual adop ion beha io (Shahbaz e al.
2019).
2.3 F amewo k o Adop ion Beha io
a he Indi idual Le el
Adop ion a he o ganiza ional, eam, and indi idual le el
plays a majo ole in he ield o IS and con ains a b oad
knowledge base, as he p ocess o IS adop ion is essen ial
o ealize i s esul ing bene i s (Venka esh 2006; Xia and
Lee 2000). Fo his eason, esea che s in es iga ed he
adop ion p ocess and ac o s de e mining adop ion decision
o IS in o ganiza ions o a conside able ex en (Hameed
and A achchilage 2020). The examina ion o indi idual-
le el IS adop ion aised se e al heo e ically g ounded
models, explo ing he unde lying mechanisms o use
adop ion beha io . These include he SQBT, which aims o
explo e non- a ional decision making (Samuelson and
Zeckhause 1988) and p o ides an explana ion o
employees’ p e e ence o emain in cu en si ua ions o
ou ines (Kim and Kankanhalli 2009). To add ess he
eme gence o he s a us quo bias, h ee ca ego ies a e
conside ed (Kim and Kankanhalli 2009; Samuelson and
Zeckhause 1988). Fi s , a ional decision making in ol es
weighing he cos s (i.e., ansi ion cos s and unce ain y
cos s) and bene i s ha a ise om de ia ing om he cu -
en s a us o he end use (Samuelson and Zeckhause
1988). Second, cogni i e mispe cep ion o po en ial losses
leads o a s onge pe cep ion o po en ial (insubs an ial)
losses caused by de ia ing om he cu en s a us han
po en ial bene i s, hus c ea ing a bias (Kahneman and
T e sky 1979; No emsky and Kahneman 2005). Thi d,
sunk cos s ela i e o p io commi men s, social no ms
owa d change in he wo king en i onmen , and e o s o
main ain a eeling o con ol c ea e a psychological com-
mi men owa d he change (Samuelson and Zeckhause
1988). The pe cei ed alue o he change is de e mined by
swi ching bene i s (i.e., inc ease in ou come while dec ease
in inpu ) and swi ching d awbacks (i.e., inc ease in inpu
while dec ease in ou come) (Kim and Kankanhalli 2009).
Acco dingly, he ca ego ies inco po a e no me ely a ional
c i e ia, which p ima ily include a p ice dimension, bu
also non- a ional aspec s a he psychological le el, which
cause a s a us quo bias.
The SQBT is used in IS esea ch and is pa icula ly
sui able o in es iga ing manda o y IS implemen a ion
(i.e., decisions made a managemen le el). In his ega d,
s udies e eal ha unce ain y cos s, sunk cos s, and pe -
cei ed alue o IS-based change ha e a signi ican impac
on use esis ance (Hsieh and Lin 2020; Kim 2011). In
addi ion, ansi ion cos s and pe cei ed loss nega i ely
a ec pe cei ed alue and hus indi ec ly impac use
esis ance o change (Kim 2011). T ansi ion cos s and
pe cei ed sunk cos s, along wi h he associa ed habi ual use
o amilia sys ems, also ein o ce ine ia o adop new IS
(Poli es and Ka ahanna 2012; Shanka and Nigam 2022).
Acco dingly, s a us quo bias signi ican ly in luences use
esis ance and slowe adop ion o change, which a e
e lec ed, o example, in g umbling among employees
(Alzah ani e al. 2021), con lic , and inc eased esou ce
consump ion (Kim 2011).
Despi e he ich abundance o esea ch on IS adop ion a
he indi idual le el h ough he lens o SQBT, some
aspec s ha e emained la gely unconside ed so a . Fi s , i
equi es u he esea ch ha conside s he speci ic na u e
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818 M. Rimbeck e al.: Un olding IoT Adop ion: A S a us Quo Bias Pe spec i e, Bus In Sys Eng 67(6):815–832 (2025)
o IS and i s associa ed a ibu es o gene a e an in-dep h
unde s anding o use s and hei beha io (Venka esh
2006). Second, in spi e o comp ehensi e, empi ical esul s
on he indi idual-le el adop ion o IS-use s, he pe cep ion
o inexpe ienced use s ecei ed li le conside a ion
(Jahanmi and Ca adas 2018; Sa chell and Dou ish 2009).
One excep ion is a s udy ha indica es ha a dec ease in
skep icism and an imp o emen in he posi i e pe cep ion
o po en ial consume s owa ds IS leads o accele a ed
adop ion and subsequen di usion (Jahanmi and Ca adas
2018). F om a use engagemen pe spec i e, Melby e al.
(2016) also sugges ha i is impo an o conside ha no
all use s a e equally engaged and willing o adop new IS
acco ding o managemen speci ica ions. Mo eo e , IS
use s should be iewed in conjunc ion wi h inexpe ienced
use s o c ea e sensi i i y o he easons o non-use (e.g.,
skep icism, ea s) and o p omo e a di e en ia ed unde -
s anding o exis ing concep s (Wya 2014; Wya e al.
2002). The pe cep ion bo h o expe ienced use s and
inexpe ienced use s is hus aluable o encou age he
adop ion o IS a he indi idual le el. Thi d, o in es iga e
and ex end he SQBT, esea che s p ima ily use quan i a-
i e app oaches, which p o ide highly ele an esul s.
Howe e , quali a i e esea ch allows o closely examine
he speci ic ype o IS, he e IoT solu ions, and he ac ual
deploymen (Vogelsang e al. 2013) in indus y. Acco d-
ingly, quali a i e app oaches migh con ibu e o an in-
dep h unde s anding o pe cei ed cos s and bene i s o IoT
solu ions as well as a di e en ia ed conside a ion o
expe ienced and inexpe ienced use s. Due o i s non- a-
ional pe spec i e, he SQBT seems app op ia e as an
unde lying basis o quali a i e esea ch designs.
Figu e 1shows he adap a ion o ou quali a i e
app oach. The g ay a ows indica e ha we do no examine
he al eady e y well-s udied ela ionships be ween he
single cons uc s, bu conduc an in-dep h analysis o he
ele an ac o s o pe cei ed bene i s, and cos s as well as
psychological commi men and cogni i e mispe cep ion o
IoT solu ions. Acco dingly, we unde s and ha an adop ion
decision a he indi idual le el is a longe - e m e o ha
equi es meaning and alue o IS o be iden i ied. We a e
con iden ha ou analysis, clus e ed by using he SQBT,
will con ibu e o a ich unde s anding o IoT
implemen a ion.
3 Me hod
3.1 Su ey Design
To in es iga e pe cei ed bene i s, and cos s as well as
psychological commi men and cogni i e mispe cep ion o
IoT solu ions, depending on use s’ expe ience, we su -
eyed 489 employees om di e en indus ies and com-
pany sizes om June o July 2020 on hei use pe cep ion
o IoT solu ions. To gain deepe insigh s in o he pe cep-
ion o IoT solu ions by expe ienced and inexpe ienced
use s, a ques ionnai e wi h mainly open ques ions was
d awn up. In line wi h Kim and Kankanhalli (2009), we
ope a ionalized a ional decision making by ne bene i s
(i.e., inc easing e ec i eness and e iciency o using new
IS), ansi ion cos s (i.e., lea ning cos s, pe manen cos s),
and unce ain y cos s (i.e., pe cep ion o isks, psycholog-
ical unce ain y). Psychological commi men is ope a-
ionalized by sunk cos s (i.e., abili ies ela ed o p e ious
wo king ou ines), and e o s o eel in con ol (i.e., ea o
losing con ol when using new IS). Cogni i e mispe cep-
ion is ope a ionalized ough loss a e sion (i.e., highe
weigh ing o losses han gains). Fu he mo e, we ope a-
ionalized a i ude owa ds using IoT solu ions by pe -
cei ed alue (i.e., an o e all e alua ion by compa ing
bene i s and cos s) (Kim 2011). In he ollowing, we will
Fig. 1 Adap ed SQB app oach
o quali a i e esea ch design
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M. Rimbeck e al.: Un olding IoT Adop ion: A S a us Quo Bias Pe spec i e, Bus In Sys Eng 67(6):815–832 (2025) 819
g oup he ca ego ies unde he e ms ‘‘bene i s’’ and
‘‘cos s’’ o ease o unde s anding. We would like o
emphasize ha we include bo h he a ional and non- a-
ional aspec s ha may cause a s a us quo bias unde he
wo e ms.
Fi s , o que y whe he IoT solu ions a e cu en ly used
by he esponden s, we used a 5-poin Like scale o
de e mine he deg ee o which hey de ine wo king de ices
as IoT-objec s, i.e., objec s ha a e equipped wi h senso
echnology and in elligen ly connec ed (1 = no objec s o
his ype a e in elligen ly connec ed; 5 = all objec s o his
ype a e in elligen ly connec ed). We p o ided he
esponden s wi h a p e-de ined lis o IoT solu ions ypical
o indus y o selec om (see Appendix 1; a ailable
online ia h p://link.sp inge .com). We iden i ied he sin-
gle i ems (e.g., o ice desk, p in e , ga bage can) and
in e connec ed sys ems (e.g., building in as uc u e,
machines, p oduc ion objec s) based on a li e a u e e iew
ha e ealed he mos commonly used IoT solu ions in an
indus ial con ex . Acco ding o he ques ion o use, we
di ided he pa icipan s in o expe ienced use s and inex-
pe ienced use s: In he case ha pa icipan s s a ed ha
none o he objec s in hei wo king en i onmen was
in elligen ly connec ed, hey we e iden i ied as an inexpe-
ienced use . In he case ha pa icipan s s a ed a leas
once ha hey use hese i ems, hey we e iden i ied as an
expe ienced use . Inco ec assump ions abou hei IoT use
we e a oided by asking abou he in e connec ion o
wo king de ices in hei immedia e wo king en i onmen ,
which can be well e alua ed by he esponden s. Inexpe-
ienced use s we e hen asked open ques ions abou he
in ended use, po en ial a eas o applica ion as well as
pe cei ed bene i s, and cos s (see Appendix 2, Ques ions
1–5). Simul aneously, we asked expe ienced use s abou
he du a ion o use, exis ing a eas o use as well as bene i s,
and cos s (Ques ions 6–9). He e we ha e adap ed he
wo ding o he ques ions sligh ly. We decided o o mula e
he ques ions in an open manne in o de o ob ain a wide
ange o di e se, unbiased answe s. Fou h, we asked he
esponden s pe sonal ques ions abou he indus y, com-
panies, and asks.
3.2 Sample and Da a Collec ion
To ensu e ha only pe sons pa icipa e, who can e alua e
he p esence (o absence) o IoT solu ions in an o ganiza-
ional con ex , we excluded non-employees om he u -
he su ey p io o da a analysis (n= 74). The inal a ge
popula ion o he su ey included employees o o ganiza-
ions in Ge many (N= 489), including manage s (n= 155)
and employees wi hou a manage posi ion (n= 334).
O e all, he p opo ion o emale (n= 266) and male
pa icipan s (n= 219) was ela i ely equal, wi h an a e age
age o 45.90 yea s (SD = 11.24). We ec ui ed pa icipan s
h ough an access panel, which was p o ided by consume
ieldwo k. The esponden s co e ed a ious unc ional
a eas: A high p opo ion o esponden s we e in ol ed in
p ima y ac i i ies, wi h pe sons om se ice (n= 67) as
well as ma ke ing and sales (n= 58) being pa icula ly
p ominen as compa ed o employees om ope a ions
(n= 30) and logis ics (n= 19). Employees om seconda y
ac i i ies we e mainly engaged in i m in as uc u e and
managemen (n= 64) and echnology de elopmen
(n= 35). Pe sons om he unc ional a eas o p ocu emen
(n= 12) and human esou ces managemen (n= 14) we e
ba ely ep esen ed. In addi ion, he e was a ela i ely high
numbe o esponden s classi ied in he ca ego y ‘‘o he ’’
(n= 132). O hose su eyed, mo e han hal wo ked in
small and medium-sized en e p ises (n= 275); 42.90%,
howe e , in companies wi h mo e han 250 employees
(n= 210). The companies ha e been assigned o di e en
indus ies. In e e ence o he Global Indus y Classi ica-
ion S anda d, depic ing 11 sec o s, mainly employees om
indus ials (n= 134) and consume disc e iona y (n= 142)
we e included. Besides medium (e.g., se ice, n= 69;
heal h and social ca e, n= 47; inancials, n= 26; in o -
ma ion echnology, n= 15) and low ep esen ed sec o s, a
ela i ely high numbe o pa icipan s assigned o ‘o he ’
(n= 102). Tables 1,2, and 3indica e he desc ip i e
s a is ics in de ail.
3.3 Coding P ocedu e
In quali a i e esea ch, coding e e s o he p ocess o
o ganizing and ca ego izing da a o iden i y pa e ns,
hemes, and concep s (May ing e al. 2004). Thus, coding
allows o he iden i ica ion o simila i ies and di e ences
wi hin he da a se and helps o s uc u e he da a in a way
ha acili a es analyses and in e p e a ion. We used
MAXQDA ( e sion 18.2.4) o conduc a quali a i e con en
analysis (May ing e al. 2004). Using he p og am, we
calcula ed he B ennan-P edige coe icien (B ennan and
P edige 1981) since his p edic o is obus o he e-
quency dis ibu ion o he codes o be a ed (Qua oo and
Le ine 2016). To ensu e an objec i e coding o he pa -
icipan s’ answe s, we ollowed a s epwise induc i e p o-
cedu e. A e we sepa a ed he answe s depending on he
use s’ expe ience wi h IoT solu ions, we iden i ied pe -
cei ed bene i s, cos s, and psychological commi men o
he adop ion o IoT solu ions. F om he agg ega ed esul s,
we de e mined subsequen cogni i e mispe cep ion and
a i ude owa ds using.
Fi s , o he de elopmen o he coding scheme ‘di e -
ences in IoT pe cep ion’, he i s au ho o he a icle and
one addi ional code independen ly analyzed he ques-
ionnai es and coded he open ques ions (Ques ions 4–5; 8–
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820 M. Rimbeck e al.: Un olding IoT Adop ion: A S a us Quo Bias Pe spec i e, Bus In Sys Eng 67(6):815–832 (2025)
9; see Table 4). Di e ences in coding we e hen discussed,
and an ini ial coding scheme was c ea ed. Second, we
passed he coding scheme as well as coding desc ip ions
and guidelines on o wo subsequen code s, who e-ana-
lyzed he open ques ions. Due o he insu icien in e code
ag eemen in some o he ca ego ies ( _min = 0.20, _-
max = 0.72), we modi ied he coding scheme o hese
pa icula ca ego ies. Conc e ely, we combined some ca -
ego ies o a mo e agg ega ed le el. Fo example, when
bene i s we e e iewed, he ca ego ies ‘imp o ed
in o ma ion low’ and ‘loca ion and ime-independen da a
access’ we e summa ized in o a new ca ego y. In addi ion,
we added he p e iously sepa a ely lis ed ca ego y ‘in-
c eased e iciency and e ec i eness’ and ‘ ime eco ding
and ime sa ings’ o he ca ego y ‘p ocess managemen ’.
Claims ha he e is no unde s anding o bene i s o cos s
we e each assigned an addi ional ca ego y. Al hough his
ca ego y is no aluable in e ms o con en , i se es he
pu pose o comple eness.
Based on hese e isions, we c ea ed a inal coding
scheme con aining 11 ca ego ies o expe ienced use s
(se en o ne bene i s, wo o cos s, and wo o psy-
chological commi men ) and 15 ca ego ies o inexpe i-
enced use s o IoT solu ions ( wo addi ional ca ego ies o
assumed ne bene i s, one addi ional ca ego y o assumed
cos s, one addi ional ca ego y o assumed psychological
commi men ). The esul ing in e code ag eemen in he
hi d ound was highe han 0.75 o all codes ( _min =
0.89, _max = 0.99, M = 0.95, SD = 0.04), which is ol-
e able o an induc i e con en analysis (Landis and Koch
1977). In Table 4, he inal coding scheme o di e ences
in IoT pe cep ion is shown, which includes he code
desc ip ions, he coding equencies (n), and he in e code
ag eemen ( ). The coding equency ep esen s he num-
be o codings ha occu ed among all pa icipan s. The
lowe ed numbe s indica e he co esponding g oups; i.e.,
1
ep esen s expe ienced use s and
2
ep esen s inexpe i-
enced use s.
To examine pe cep ions wi h ega d o IoT solu ions in
u he de ail, we compa ed pe cep ions a he managemen
and he ope a ional le el in he nex s ep. Fo his pu pose,
we calcula ed he ela i e codings o pa icipan s wi h and
wi hou managemen esponsibili y in ela ion o he
absolu e numbe o codings. The le e s in b acke s indica e
he ope a ional le el (o) and he managemen le el (m).
4 Findings
The esul s a e s uc u ed as ollows: Fi s , we analyze ne
bene i s, cos s, and psychological commi men o IoT
adop ion, di e en ia ed in o expe ienced use s (k1) and
inexpe ienced use s (k2), conside ing ope a ional and
managemen le el. Second, we examine cogni i e mis-
pe cep ion and a i ude owa ds using.
4.1 Ne Bene i s
In o al, we iden i ied 595 codes o ne bene i s o IoT
adop ion. Use ul ac o s ha we e equally desc ibed by
expe ienced and inexpe ienced use s can be classi ied in o
se en ca ego ies, speci ically (1) unc ionali y and e o
educ ion (k1 = 109, k2 = 56), (2) p ocess managemen
Table 1 F equencies and dis ibu ions
Np
Gende
Male 219 44.8
Female 266 54.4
No answe 4 0.8
Le el o esponsibili y
Managemen le el 155 31.7
Ope a ional le el 334 69.3
A ea o expe ise
Se ice 67 13.7
Ma ke ing and sales 58 11.9
Ope a ions 30 6.1
Logis ics 19 3.9
Fi m in as uc u e 12 2.5
Managemen 52 10.6
Technology de elopmen 35 7.2
P ocu emen 12 2.5
HR managemen 14 2.9
O he 132 27.0
Company size
B9 90 18.4
B49 81 16.6
B249 104 21.3
250 and mo e 210 42.9
In e na ionali y
In e na ional 179 36.6
Domes ic 305 62.4
No answe 5 1.0
Table 2 Desc ip i e s a is ics
N Min Max M SD
Age 487 18 68 45.90 11.24
Du a ion in company 451 1 45 11.67 9.53
Du a ion in wo king en i onmen 447 1 47 14.68 10.26
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(k1 = 89, k2 = 77), (3) elie o pe sonnel (k1 = 69,
k2 = 35), (4) ne wo king and da a (k1 = 36, k2 = 19), (5)
cos educ ion (k1 = 22, k2 = 22), (6) esou ces and sus-
ainabili y (k1 = 21, k2 = 16), and (7) mode ni y (k1 = 10,
k2 = 14). Compa ing he wo g oups, i is ema kable ha
he expec a ions o inexpe ienced use s co espond la gely
wi h he pe cep ion o IoT expe ienced use s. Howe e , i
is appa en ha he pe cep ions o employees a he ope -
a ional and managemen le els di e conside ably in some
ca ego ies.
Rega ding he mos men ioned ca ego y (1) unc ional-
i y and e o educ ion, esponden s s a ed ha he imple-
men a ion o IoT solu ions leads o a educ ion in ailu es,
as IoT sys ems p o ide au oma ic solu ions, especially o
o de s, e-o de s, and schedules (see Table 5). By elimi-
na ing he necessi y o manual esubmissions, e o s a e
a oided a an ea ly s age, hus educing he e o a e. In
his con ex , IoT sys ems a e conside ed o be anspa en ,
accu a e, unc ional and eliable. While hese bene i s a e
pe cei ed o be ela i ely simila in s eng h by IoT-ex-
pe ienced employees a he ope a ional and managemen
le els, inexpe ienced employees a he managemen le el
in pa icula a e much less likely o pe cei e he oppo u-
ni y o inc ease unc ionali y and educe e o s, po en ially
leading o a educed willingness o implemen IoT solu-
ions in hei depa men s.
In ca ego y (2) p ocess managemen , esponden s we e
posi i ely imp essed by how wo k lows un as e , mo e
e ec i ely and wi hou idle ime, bo lenecks and wai ing
imes as a esul o adop ing he IoT. In addi ion, IoT
solu ions enable a mo e lexible and as e esponse o
changing equi emen s, which esul s in imp o ed coo di-
na ion and deli e y p ocedu es. A simila pa e n eme ges
he e as in he p e ious ca ego y, namely ha IoT inexpe-
ienced manage s may unde es ima e he po en ial wi h
ega d o p ocess managemen .
In addi ion o he wo mos equen ly men ioned ca e-
go ies, he (3) elie o pe sonnel is named as a posi i e
aspec ega ding he ne bene i s o IoT solu ions. In pa -
icula , he elimina ion o ou ine ac i i ies, which a e o en
pe cei ed as ime-consuming and bu densome, is com-
monly epo ed. Fu he mo e, he esponden s indica e ha
ewe ou ine ac i i ies and ewe wo k in e up ions,
educes e o and allow hem o concen a e on essen ial
wo k con en . Again, pe cep ions in his ca ego y a e el-
a i ely simila among he subg oups o expe ienced use s,
whe eas inexpe ienced use s a he managemen le el ha e
a subs an ially weake pe cep ion o he impac o IoT
solu ions on elie ing pe sonnel. Since his g oup o
employees makes s a egic decisions ela ing o he
implemen a ion o IoT solu ions, hese esul s mus be
conside ed a he c i ical (Tables 6,7,8).
4.2 T ansi ion and Unce ain y Cos s
Rega ding he ansi ion and unce ain y cos s, a o al o
286 s a emen s we e coded and alloca ed o he ollowing
ca ego ies: (1) employees and emo ions (k1 = 96,
k2 = 47), and (2) inancial and pe sonnel expenses
(k1 = 85, k2 = 58). We iden i ied simila i ies be ween
expe ienced and inexpe ienced use s in (2) inancial and
pe sonnel expenses, ep esen ing ansi ion cos s. Financial
e o s a ise in pa icula om he acquisi ion, con inuous
se ice and da a main enance, suppo se ices and con-
ac ual obliga ions. F om he pe spec i e o he inexpe i-
enced use s, pe sonnel expendi u e is caused in pa icula
Table 3 Di e en ia ion be ween expe ienced and inexpe ienced use s acco ding o he ques ionnai e
Expe ienced use s Inexpe ienced use s
np n p
1 O ice desk/chai (e.g., au oma ic adjus men o use da a) 62 12.7 424 86.7
2 P in e (e.g., au oma ic eo de ing when one is emp y) 203 41.5 281 57.5
3 T ash can (e.g., disposal o de , when i is ull) 45 9.2 439 89.8
4 Filing sys ems (e.g., eminde i some hing has been s o ed o oo long) 90 18.4 396 81.0
5 Robo s (e.g., acuum cleane obo s, logis ics obo s) 88 18.0 394 80.6
6 Key obs (e.g., au oma ic wo king ime eco ding) 118 24.1 368 75.3
7 Building in as uc u e (e.g., au oma ic blinds, he mos a s) 181 36.9 305 62.4
8 Machines (e.g., au oma ic main enance, o de o wa ding) 143 29.3 344 70.3
9 P oduc ion objec s (e.g., au oma ic s a us no i ica ion, commissioning o ac i i ies) 127 25.9 359 73.4
10 O he objec s 97 19.8 387 79.1
Pa icipan s had he op ion o selec only hose IoT solu ion op ions ha applied o hem. The e o e, he dis ibu ion o esponses ac oss he
op ions a ies; he di ision be ween expe ienced and inexpe ienced use s was he p ima y c i e ion o subsequen da a e alua ion
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822 M. Rimbeck e al.: Un olding IoT Adop ion: A S a us Quo Bias Pe spec i e, Bus In Sys Eng 67(6):815–832 (2025)
quan i a i e (expe imen al) da a o in es iga e bo h pe -
cep ion and cu en adop ion beha io in o de o make
causal p edic ions abou whe he a posi i e (nega i e)
pe cep ion o he IoT leads o a posi i e (nega i e) adop-
ion decision, conside ing he dis inc ion be ween expe i-
enced and inexpe ienced use s. Based on he empi ical
esul s om a ious IoT indus ies, ou s udy con i ms ha
he pe cep ion o ne bene i s, cos s, and psychological
commi men a e ele an when implemen ing IoT solu-
ions. Fu he mo e, wi h ou me hodological design, we
canno ully exclude ha esponden s migh no ha e been
awa e o hei use o IoT de ices in hei wo king en i-
onmen and, acco dingly, may ha e inad e en ly deli -
e ed inco ec esponses. Howe e , based on an
obse a ion om a p e es sugges ing ha a conside able
p opo ion o pa icipan s we e unawa e o he IoT concep ,
we decided o ask indi ec ly abou expe ience wi h IoT
solu ions in o de o p e en esponden s om unin en-
ionally gi ing inco ec answe s. A plausible explana ion
o his obse a ion migh be ha he su ey ocused on
Ge man employees and ha IoT implemen a ion in com-
panies in Ge many is ela i ely low. Acco dingly, u u e
esea ch may use expe imen al designs o p o ide dis inc
in e ences ega ding he impac o a ying le els o he
deploymen o he IoT. Thi d, mo e esea ch is equi ed o
in es iga e he ela ionship be ween IoT adop ion and he
esul ing consequences a he o ganiza ional, eam, and
indi idual le el. Fo ins ance, o wha ex en he inc easing
di usion o IoT solu ions os e s changes in he luidi y o
eams and wha impac s a e o be an icipa ed a he o ga-
niza ional and a he eam le el should be subjec o u u e
esea ch. In his con ex , i is c ucial o conside ha he
posi i e o nega i e consequences o implemen ing IoT
solu ions depend la gely on a ious pa ame e s and hus
canno be gene alized o all ypes o o ganiza ions. These
pa ame e s include, in pa icula , inancial and pe sonnel
aspec s, co e ing p ocu emen , commissioning and main-
enance as well as consul ing se ices by in e nal o
ex e nal expe s. Acco dingly, u u e esea ch migh con-
side conduc ing case s udies in companies o di e en
sizes and indus ies o analyze how di e en economic
ac o s in luence he decision-making p ocess and ou -
comes o IoT adop ion. In addi ion, amewo ks o pe -
o ming comp ehensi e cos –bene i analyses speci ic o
IoT adop ion can be de eloped o help o ganiza ions
e alua e he angible and in angible cos s and bene i s
associa ed wi h in eg a ing IoT in o hei ope a ions.
6 Conclusion
In ou s udy, we highligh ed he ele ance o conside ing
use pe cep ions h ough he lens o SQBT and e ealed
how IoT solu ions a e pe cei ed by expe ienced and
inexpe ienced use s. In addi ion o he simila i ies and
di e ences, we also ound ha IoT solu ions may change
eam s uc u es and lead o so-called luid eams. In gen-
e al, he compulsi e inc ease in lexible wo king o ms is
o cing a g owing numbe o manage s o alloca e pe -
sonnel lexibly and o exploi he inc easing le el o
au oma ion, i ual pla o ms and da a analysis o a g ea e
ex en . To emain compe i i e in bo h he ongoing digi-
aliza ion p ocess and he p e ailing unce ain ma ke si -
ua ion, i is e en mo e impo an o o e come
misconcep ions, educe esis ance and adop IoT in he
long e m.
Supplemen a y In o ma ionThe online e sion con ains
supplemen a y ma e ial a ailable a h ps://doi.o g/10.1007/s12599-
024-00891-6.
Acknowledgemen s This wo k was suppo ed by he Ge man Fed-
e al Minis y o Educa ion and Resea ch and he Eu opean Social
Fund [g an numbe 02L18B030 ].
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