Schul e-Kulkmann, Nicole
A icle
In he eye o he beholde : Examining he ole o dynamic capabili ies,
indus y dynamics, and in e nal knowledge sha ing in s a egis s' en y
decisions
Junio Managemen Science (JUMS)
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Sugges ed Ci a ion: Schul e-Kulkmann, Nicole (2024) : In he eye o he beholde : Examining he ole
o dynamic capabili ies, indus y dynamics, and in e nal knowledge sha ing in s a egis s' en y
decisions, Junio Managemen Science (JUMS), ISSN 2942-1861, Junio Managemen Science e. V.,
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Volume 9, Issue 4, Decembe 2024
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Elisa Schul e genann Kulkmann, In he Eye o he Beholde :
Examining he Role o Dynamic Capabili ies, Indus y
Dynamics, and In e nal Knowledge Sha ing in
S a egis s' En y Decisions
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ISSN: 2942-1861
In he Eye o he Beholde : Examining he Role o Dynamic Capabili ies, Indus y
Dynamics, and In e nal Knowledge Sha ing in S a egis s’ En y Decisions
Elisa Schul e genann Kulkmann
Technical Uni e si y o Munich
Abs ac
Dynamic capabili ies a e a majo d i e o s a egic en y in o new indus ies. Building on he dynamic capabili ies app oach
and on s a egy li e a u e, I de elop a model o s a egis s’ assessmen o en y. I examine wo speci ic dynamic capabili ies,
namely abso p i e capaci y and new p oduc de elopmen capabili y and a gue ha bo h posi i ely in luence s a egis s’
pe cei ed a ac i eness o en e ing a new indus y. Fu he , I aim o espond o he call o conside he mode a ing e ec s o
bo h ex e nal and in e nal condi ions, by in eg a ing en i onmen al dynamism and in e nal knowledge sha ing as mode a o s
in my model. I es my hypo heses ia a conjoin expe imen and da a on 1,664 en y assessmen s embedded wi hin 52
s a egis s. As expec ed, I ind ha bo h high le els o pe cei ed abso p i e capaci y and new p oduc de elopmen capabili y
inc ease en y a ac i eness. Mo eo e , hose e ec s a e pa icula ly s ong when he en i onmen al dynamism in he new
indus y is expec ed o be low. In e nal knowledge sha ing s eng hens he ela ionship be ween pe cei ed new p oduc
de elopmen and en y a ac i eness. Rega ding pe cei ed abso p i e capaci y, I do no ind signi ican in e ac ions.
Keywo ds: abso p i e capaci y; dynamic capabili ies; en y assessmen ; new p oduc de elopmen ; s a egic en y
1. In oduc ion
The ques ion o wha o ganiza ional capabili ies lead
decision make s o pu sue ce ain s a egic di ec ions such
as s a egic en y and why hey do so has long been ea-
u ed in o ganiza ional, s a egic, and beha iou al esea ch
(e.g., Baía and Fe ei a 2019; Ga e i and Le in hal 2000;
La ie 2006). The dynamic capabili ies concep , which has
a ac ed inc easing a en ion among schola s, aims o p o-
ide answe s o his essen ial ques ion. O iginally oo ed
in he esou ce-based- iew (RBV) o he i m, such capabil-
i ies can be de ined as a i m’s po en ial o sol e p oblems
in a sys ema ic manne , which esul s om i s abili y o ec-
ognize oppo uni ies and haza ds, o ensu e e icien and
ma ke -d i en decision-making, and o quickly modi y i s
I would like o hank P o . D . Nicola B eugs o gi ing me he oppo -
uni y o w i e my mas e hesis a he TUM En ep eneu ship Resea ch
Ins i u e and o he suppo h oughou he w i ing p ocess. Addi ion-
ally, I would like o hank D . Lilia S a z o he supe ision and g ea
guidance.
exis ing esou ce base acco dingly (Ba e o, 2010). As busi-
ness en i onmen s become e e mo e dynamic in he wake o
globaliza ion, digi iza ion and s eady echnological p og ess,
dynamic capabili ies play a majo ole in secu ing compe i-
i e ad an age and supe io i m pe o mance (e.g., B e el
e al., 2011; D ne ich and K iauciunas, 2011; Teece, 2007).
Pa icula ly ega ding success ul en y in o new indus ies,
such capabili ies can be a highly aluable asse o he i m
since hey signi ican ly educe cos s associa ed wi h such a
mo e (A gy es e al., 2019).
Al hough e y in luen ial, li e a u e on dynamic capabil-
i ies su e s om se e al de iciencies. One impo an sou ce
o conce n is ha o e all, empi ical esea ch has paid in-
su icien a en ion o media o s and mode a o s (Schilke e
al., 2018). Dynamic capabili ies a e con ex -dependen and
he e o e, en i onmen al ea u es canno be excluded when
analysing hei impac on, o example, s a egic decision-
making o i m pe o mance. In pa icula , he e is a call
o he inclusion o bo h ex e nal as well as in e nal speci ic
mode a o s and o po en ial in e ac ions (Baía & Fe ei a,
DOI: h ps://doi.o g/10.5282/jums/ 9i4pp2050-2081
© The Au ho (s) 2024. Published by Junio Managemen Science.
This is an Open Access a icle dis ibu ed unde he e ms o he CC-BY-4.0
(A ibu ion 4.0 In e na ional). Open Access unding p o ided by ZBW.
E. Schul e genann Kulkmann /Junio Managemen Science 9(4) (2024) 2050-2081 2051
2019). Second, wi h ega d o me hodologies, many schol-
a s in he ield o s a egic decision-making, ha e ocused on
pos -hoc app oaches o examine he ole o dynamic capa-
bili ies. While highly impo an o ad ancemen s in his e-
sea ch domain, such app oaches inco po a e he isk o su -
ey da a e o s as a esul o biased decision-making o lack o
ele an in o ma ion (Zacha akis & Shephe d, 2018). Thi d,
he majo i y o esea ch has explo ed he ole o gene ic dy-
namic capabili ies a he han ocusing on mo e speci ic ones.
Focusing on speci ic and well-de ined dynamic capabili ies
would make i easie o de i e p ac ical implica ions ha a e
mo e angible. Finally, al hough schola s ha e acknowledged
he impo ance o hose capabili ies in en y decisions, he e
is compa ably li le li e a u e a ailable on his ela ionship
(A gy es e al., 2019).
To add ess he abo e-men ioned gaps, I empi ically in-
es iga e he link be ween wo speci ic dynamic capabili ies
(i.e., abso p i e capaci y and new p oduc de elopmen ca-
pabili y) and i ms’ s a egis s’ assessmen o s a egic en y.
Fu he , since he en y assessmen is dependen no only
on i ms pe cei ed dynamic capabili ies bu also on how he
s a egis s pe cei e addi ional ex e nal as well as in e nal ac-
o s, I de elop a model ha includes he mode a ing e ec s o
en i onmen al dynamism and in e nal knowledge sha ing on
he ela ionship o dynamic capabili ies on en y assessmen .
I es my model based on a me ic conjoin expe imen and
da a on 1,664 e alua ion poin s ha a e nes ed wi hin 52
s a egis s. I sugges a posi i e ela ionship be ween he pe -
cei ed dynamic capabili ies and s a egic en y assessmen
(hypo heses 1a and 1b). Bo h hypo heses a e suppo ed by
my esul s. In e ms o mode a o s, I assume he posi i e e -
ec o pe cei ed abso p i e capaci y on en y a ac i eness
o be mode a ed by en i onmen al dynamism in such a way
ha he pe cei ed abso p i e capaci y encou ages s a egis s
o en e new indus ies, especially when an icipa ed en i on-
men al dynamism is high (hypo hesis 2a). Fo pe cei ed new
p oduc de elopmen capabili y, I assume he mode a ing e -
ec o go in he opposi e di ec ion (hypo hesis 2b). While hy-
po hesis 2a is no consis en wi h my esul s, I ind p oo o
hypo hesis 2b. Finally, I assume an icipa ed in e nal knowl-
edge sha ing o s eng hen he posi i e ela ionships be ween
bo h pe cei ed abso p i e capaci y (hypo hesis 3a) and pe -
cei ed new p oduc de elopmen capabili y (hypo hesis 3b)
and en y a ac i eness. I ind suppo only o hypo hesis
3b. Figu e 1b ie ly illus a es he model es ed in my s udy.
My pape adds alue o exis ing li e a u e in he ollowing
ways. Fi s , I espond o he call o speci ic dynamic capabili-
ies o be s udied. Speci ically, I eac o an analysis o Schilke
e al. (2018), who ound ha an imp essi e numbe o schol-
a s ask o an addi ional examina ion o new p oduc de el-
opmen capabili y. By examining wo speci ic dynamic ca-
pabili ies, I ind ha bo h pe cei ed abso p i e capaci y and
new p oduc de elopmen capabili y play an essen ial ole in
s a egis s’ assessmen o s a egic en y. This could also help
manage s in hei u u e decision-making p ocesses. Second,
I am able o iden i y ac o s ha in luence he ela ionship be-
ween dynamic capabili ies and decision-making which jus-
i ies he s a emen o Baía and Fe ei a (2019) who ha e
a gued ha he examina ion o con ex -dependen dynamic
capabili ies equi es he inclusion o ex e nal and in e nal
mode a o s. Bo h, en i onmen al dynamism, and in e nal
knowledge sha ing mechanisms a e conside ed by s a egis s
in hei en y decisions. Finally, by using an expe imen al
eal- ime conjoin app oach, I educed he isks o biased
sel - epo ing o decision make s and ailu e o conside ha
decision-making is an e ol ing and dynamic p ocess (e.g.,
Sandbe g, 1986; Shephe d and Zacha akis, 2018).
2. Theo e ical backg ound and hypo heses
Dynamic capabili ies can p o ide i ms wi h c i ical ools
equi ed o s a egic en y. To be e unde s and hei cha -
ac e is ics, he nex sec ion i s p o ides a b ie de ini ion o
dynamic capabili ies, in pa icula o abso p i e capaci y and
new p oduc de elopmen capabili y. Second, I de elop my
hypo heses on he ela ionship be ween he wo capabili ies
and s a egic en y, and inally, I in oduce my mode a o s,
i.e., en i onmen al dynamism and in e nal knowledge sha -
ing.
2.1. De ining dynamic capabili ies
How i ms achie e and main ain compe i i e ad an age
and long- e m g ow h in en i onmen s cha ac e ized by
apid echnological change emain a he hea o s a egy
esea ch (e.g., Baía and Fe ei a, 2019; P o oge ou e al.,
2011; Schilke e al., 2018). By aking in o accoun pu -
pose ul modi ica ions o i ms’ esou ces and capabili ies,
he dynamic capabili ies app oach builds upon he basic as-
sump ion o he RBV o he i m which indica es ha a i m’s
compe i i e ad an age depends p ima ily on i s unique e-
sou ces and capabili ies (Ba ney, 1986,1991), and hus adds
a less s a ic bu mo e dynamic componen o he RBV ame-
wo k (Baía & Fe ei a, 2019). Ini ially de eloped by Pen ose
(1959) and subsequen ly ex ended and popula ized, he RBV
assumes ha i ms’ bundles o esou ces and capabili ies a e
he e ogeneously dis ibu ed ac oss compe ing i ms (Ba -
e o, 2010). Since such bundles’ o esou ces a e aluable,
a e, inimi able, and non-subs i u able (VRIN), hey may
ei he enable o limi i ms’ choices o ma ke en ies and
p o i le els i ms may gene a e (We ne el , 1989). How-
e e , aluable esou ces alone, do no necessa ily ensu e
supe io i m pe o mance. To le e age he ull po en ial o
hei esou ces, i ms addi ionally need o possess dis inc i e
o ganiza ional capabili ies (Pen ose, 1959).
In he ace o an inc easingly dynamic business en i on-
men , ini ial p oposi ions o he RBV we e ques ioned and
conside ed oo s a ic as hey igno ed he ine i able in luence
o ma ke dynamism (e.g., Eisenha d and Ma in, 2000;
P iem and Bu le , 2001), leading o he de elopmen o he
concep o dynamic capabili ies. In hei seminal con ibu-
ion, Teece e al. (1997, p. 516) de ine dynamic capabili ies
as “ he i m’s abili y o in eg a e, build, and econ igu e in-
e nal and ex e nal compe ences o add ess apidly changing
E. Schul e genann Kulkmann /Junio Managemen Science 9(4) (2024) 2050-20812052
Figu e 1: P oposed model
en i onmen s”. Thei app oach is based on mul iple main
elemen s ha suppo i s majo heo e ical ounda ions (Ba -
e o, 2010). Fi s , hey unde pinned he essen ial ole o
s a egic managemen and ca ego ized he na u e o he
amewo k as being an “abili y”, hus ex ending he RBV by
p oposing a special kind o capabili y. Second, a speci ic ole
o his capabili y was de ined, i.e., he abili y o in eg a e,
build, and econ igu e in e nal as well as ex e nal compe-
ences. Thi d, since hey conside ed he dynamic capabili ies
app oach as an ex ension o he RBV o u bulen en i on-
men s, he ex e nal con ex was gi en by he dominan ocus
on ma ke s cha ac e ized by dynamism and change which
indica es a di ec ion owa ds a mo e en ep eneu ial pe -
spec i e (Ba e o, 2010; Schumpe e , 1983). Fi h, in line
wi h he RBV and i s VRIN esou ces, an unde lying as-
sump ion is capabili y he e ogenei y ac oss compe ing i ms.
Finally, compe i i e ad an age and alue c ea ion a e he
main ou comes o dynamic capabili ies, which is ye ano he
indica ion ha his concep is an ex ension o he RBV, as i
e ains i s co e objec i es.
Since dynamic capabili ies can gi e i ms compe i i e
ad an age, he app oach has a ac ed inc easing a en ion
among s a egy and managemen schola s and he no ion
and concep ualiza ion o dynamic capabili ies ha e subse-
quen ly been expanded and e ined (e.g., Den o d, 2013;
Eisenha d and Ma in, 2000; Teece, 2007; Zollo and Win-
e , 2002). Howe e , a dis inc and uni o m de ini ion has
no been eached ye . Li e a u e e iews summa ize he
imp essi e body o published dynamic capabili ies esea ch
as somewha sca e ed and dispa a e (e.g., Pa lou and El
Sawy, 2011; Pe e a e al., 2013). Al hough exis ing li e a-
u e is pa ially complemen a y, i lacks a common and clea
heo e ical basis (Bu isch & Wohlgemu h, 2016). The e is
consensus ha he dynamic capabili ies concep has been
signi ican ly in luenced by wo main con ibu ions – i.e.,
Teece e al. (1997) and Eisenha d and Ma in (2000) – ha
ha e la gely s ee ed esea ch in o wo somewha di e ging
s eams which a e based on di e en assump ions, heo e -
ical easoning and pe spec i es ega ding ou comes (e.g.,
Di S e ano e al., 2014; Ringo , 2017). Teece e al. (1997)
o iginally cha ac e ized dynamic capabili ies as abili ies ha
a e unique o he i m, logically implying hey canno be
examined and s udied by compa ing hei quan i y be ween
compe ing i ms (Laaksonen & Pel oniemi, 2018). Following
Teece e al. (1997) app oach, nume ous schola s ha e classi-
ied dynamic capabili ies as skills, capabili ies, o capaci ies
(e.g., Win e , 2003; Zah a e al., 2006; Zollo and Win e ,
2002). Con a y o Teece e al. (1997), Eisenha d and
Ma in (2000) s a ed ha – al hough idiosync a ic in hei
de ails – dynamic capabili ies sha e conside able simila i ies
ac oss i ms and hence can be seen as “bes p ac ices”. Teece
(2007) a gued ha since bes p ac ices canno be he sou ce
o compe i i e ad an age, hey a e highly unlikely o con-
s i u e dynamic capabili ies. This is in line wi h he wo k o
Zollo and Win e (2002) and Win e (2003) who ound ha
dynamic capabili ies enable i ms o cons an ly econ igu e
hei ope a ional capabili ies and hus, o achie e long- e m
compe i i e ad an age.
Rega dless o he heo e ical unde pinnings, o unde -
s and he na u e o dynamic capabili ies, a s ic dis inc ion
mus be made be ween hese capabili ies and ope a ional
capabili ies (also called “ze o o de ” capabili ies) (Albo -
Mo an e al., 2018). “Ze o o de ” capabili ies ope a e in-
dependen ly, a e mo e s a ic and enable i ms o pu sue
speci ically de ined se s o ac i i ies (Sunde M e al., 2019;
Teece, 2007). Dynamic capabili ies (also called “highe o -
de ” capabili ies), in con as , ep esen a i m’s abili y o
modi y i s exis ing ope a ional capabili ies by sensing and
seizing new aluable business oppo uni ies and in eg a ing
hem o de elop supe io s a egies and hus achie e compe -
i i e ad an age (e.g., Amb osini and Bowman, 2009; Baía
and Fe ei a, 2019; Teece, 2007). Dynamic s ands o he
pa hey play in change and capabili ies classi ies hem as
a s a egic mo e o as a esponse o a new business con ex
(Ba ales-Molina e al., 2014). Making an empi ical dis inc-
ion be ween ope a ional capabili ies and dynamic capabil-
i ies ha d i e his change is c ucial since o he wise i ms’
supe io pe o mance may be alsely a ibu ed o a i ms’
dynamic capabili ies (Laaksonen & Pel oniemi, 2018). The
mos essen ial di e ences be ween ope a ional and dynamic
capabili ies a e summa ized in igu e 2.
In hei sys ema ic li e a u e e iew on dynamic capa-
bili ies and i m pe o mance, Baía and Fe ei a (2019) de-
no ed concep ual he e ogenei y o he dynamic capabili ies
E. Schul e genann Kulkmann /Junio Managemen Science 9(4) (2024) 2050-2081 2053
Figu e 2: Dis inc ion be ween ope a ional and dynamic capabili ies
cons uc and i s ela ed a iables, and o e lapping as he
mos essen ial challenges wi h ega d o compa abili y o em-
pi ical pape s and ad ancemen o ou unde s anding o he
concep o dynamic capabili ies. Thei sugges ions a e in line
wi h hose o E iksson (2014) who has iden i ied wo main
endencies in he s udy o dynamic capabili ies, i.e., a ocus
on gene ic s. a ocus on mo e speci ic dynamic capabili ies.
In his a icle, I ollow Teece’s (2007) line o easoning
and do no concei e dynamic capabili ies as easily eplica-
ble bes p ac ices bu much a he as a i m’s po en ial o
adap o cons an ly changing en i onmen s by e.g., building,
and econ igu ing in e nal and ex e nal compe ences. Dy-
namic capabili ies e e o he econ igu a ion and ans o -
ma ion o o dina y ope a ion capabili ies (P o oge ou e al.,
2011). Fu he , in my in es iga ion o dynamic capabili ies
and s a egic en y decisions, I ocus on wo speci ic dynamic
capabili ies, i.e., abso p i e capaci y and new p oduc de elop-
men capabili y. I chose hese wo dynamic capabili ies o he
ollowing easons: Fi s , abso p i e capaci y and new p od-
uc de elopmen capabili y a e bo h essen ial ins umen s o
eshaping a i m’s esou ce base. Second, es ablished de i-
ni ions o bo h capabili ies adequa ely ma ch wi h he con-
s uc o dynamic capabili ies adap ed in his s udy. Such
de ini ions a e u he explained in he ollowing subsec ions.
Thi d, abso p i e capaci y and new p oduc de elopmen ca-
pabili y a e wo o he mos equen ly ci ed dynamic capa-
bili y ypes in exis ing li e a u e (Baía & Fe ei a, 2019; Ba -
e o, 2010; Hel a e al., 2007). In combina ion, hese wo
capabili ies a e pa icula ly ep esen a i e o he dynamic ca-
pabili ies app oach which quali ies hem a good i o his
a icle.
2.1.1. De ining abso p i e capaci y
As i ms cons an ly ace compe i i e, inno a i e and glob-
aliza ion p essu es, abso p i e capaci y is conside ed one o
he mos essen ial ac o s o sus ainable compe i i e ad an-
age and i m su i al (e.g., Lane e al., 2006; Robe s, 2015).
Al hough he idea ha ex e nally acqui ing knowledge is a
spino o a i m’s own R&D e o s was also de eloped and
p oposed by o he schola s (e.g., E enson e al., 1975; Til on,
1971), he mos p ominen de ini ion o abso p i e capac-
i y (based on ci a ions) was o e ed by W. M. Cohen and
Le in hal (1990, p. 128) who de ined i as “a i m’s abili y
o ecognize he alue o new, ex e nal in o ma ion, assim-
ila e i , and apply i o comme cial ends, which suppo s
i s inno a i e capabili ies”. Building on he p oposi ions o
W. M. Cohen and Le in hal (1990), Zah a and Geo ge (2002)
econcep ualized abso p i e capaci y as a mul idimensional
dynamic capabili y cons uc and p oposed ou unde lying
componen ac o s which e e o ela ed e ms in he li -
e a u e on dynamic capabili ies (Pa lou & El Sawy, 2011).
Fi s , knowledge acquisi ion e e s o ob aining new (and
ex e nal) knowledge (W. M. Cohen & Le in hal, 1990). Sec-
ond, knowledge assimila ion e e s o knowledge a icula ion
and knowledge ans e (e.g., Eisenha d and Ma in, 2000;
Zande and Kogu , 1995). Thi d, knowledge ans o ma ion
e e s o c ea i e hinking, e icien decision-making, and
inno a i e p oblem-sol ing (Hende son & Cockbu n, 1994;
Teece e al., 1997). Finally, knowledge exploi a ion e e s o
seizing oppo uni ies and econ igu ing exis ing capabili ies
(G an , 1996; Teece, 2007). These ou ac o s build upon
each o he and na u ally combine o esul in a dynamic
capabili y (Camisón & Fo és, 2010).
Mul iple schola s ha e examined abso p i e capaci y and
i s ou comes and ha e ound ha i ms ha possess high le -
els o abso p i e capaci y demons a e conside ably s onge
abili ies o lea ning om s a egic pa ne s, sensing and in-
eg a ing ex e nal in o ma ion, and inally ans o ming he
inpu in o aluable i m-embedded knowledge (Domu a h &
Pa zel , 2016; C. L. Wang & Ahmed, 2007). Fu he , s udies
ha ocus on i m pe o mance as an ou come o abso p i e
capaci y, sugges a posi i e ela ionship be ween abso p i e
and i m pe o mance (e.g., Be gh and Lim, 2008; B e el e
al., 2011; Yeoh, 2009). Hence, abso p i e capaci y plays an
essen ial ole in ensu ing long- e m compe i i e ad an age.
Following Zah a and Geo ge’s (2002) line o easoning, I
classi y abso p i e capaci y as a i m’s dynamic capabili y and
adap he de ini ion p oposed by W. M. Cohen and Le in hal
(1990, p. 128), i.e., “a i m’s abili y o ecognize he alue
o new, ex e nal in o ma ion, assimila e i , and apply i o
comme cial ends”.
2.1.2. De ining new p oduc de elopmen capabili y
In e e changing and g owing indus ies, success is no
only dependen on i ms’ compe encies ela ed o ex e nal
knowledge exploi a ion, bu also on i ms’ inno a ion e o s
and on he apid de elopmen o new p oduc s (e.g., Baía
and Fe ei a, 2019; Deeds e al., 2000). Empi ical esea ch
in he ield o inno a ion is longs anding and o e ime, di -
e en dimensions o inno a i e capabili y, which a e c u-
E. Schul e genann Kulkmann /Junio Managemen Science 9(4) (2024) 2050-20812054
cial o measu ing a i m’s o e all inno a i e capabili y as
pa o he dynamic capabili ies concep , ha e been concep-
ualized (C. L. Wang & Ahmed, 2004). Inno a i e capabil-
i y e e s o “a i m’s abili y o de elop new p oduc s and/
o ma ke s, h ough aligning s a egic inno a i e o ien a ion
wi h inno a i e beha iou s and p ocesses” (C. L. Wang &
Ahmed, 2007, p. 38). As his de ini ion indica es, nume ous
dimensions a e embedded in he inno a i e capabili y con-
s uc and p e ious esea ch has ocused on di e en com-
bina ions o hese dimensions. Fo ins ance, Schumpe e
(1983) named he de elopmen o new p oduc s o se ices,
new p oduc ion me hods, and o ganiza ional o ms and he
disco e y o new sou ces o supply as inno a i e capabili ies.
Mille and F iesen (1983) u he included he isk o ien a-
ion o key execu i es and he endency o seek no el and
uncon en ional solu ions and Capon e al. (1992) sugges ed
ha he endency o pionee and o be a he cu ing edge
o echnology in i s new p oduc and se ice in oduc ions
plays ano he essen ial pa ega ding new p oduc de elop-
men capabili y and o ganiza ional inno a i eness.
Al hough nume ous combina ions o inno a i e capabil-
i y dimensions ha e been examined, he majo i y o s udies
on he opic o dynamic capabili ies has ocused on new p od-
uc de elopmen as an enable o a i m’s change and e-
newal (e.g., Hel a and Win e , 2011; Schilke, 2014). This
may be due o he ac ha new de elopmen capabili y pos-
i i ely in luences a i m’s compe i i e pe o mance making i
a key de e minan o success in dynamic and un amilia in-
dus ies (e.g., Deeds e al., 2000; D’Es e, 2002). To achie e
supe io pe o mance, i ms mus be able and willing o gen-
e a e new p oduc s and se ices, which in u n is dependen
on he i m’s echnological and scien i ic capabili ies (Hel a
& Raubi schek, 2000). In he con ex o dynamic capabili ies,
his also means a i m’s new p oduc de elopmen capabili y
mus be as dynamic as he indus y he i m ope a es in.
Since new p oduc de elopmen as a dynamic capabili y
aims a upda ing and econ igu ing a i m’s p oduc po o-
lio by e.g., adap ing unde lying p ocesses o changing con-
di ions, i should also play a c ucial ole o s a egis s when
conside ing s a egic en y. In my pape , I d aw on he a i-
cle by Capon e al. (1992) and sugges ha new p oduc de-
elopmen capabili y is dependen on he inno a i eness o
he ma ke , he inno a i eness o he o ganiza ion, and espe-
cially on he s a egic endency o a i m and i s employees o
pionee . Hence, I de ine new p oduc de elopmen capabil-
i y as a i m’s abili y o cons an ly a emp o pionee and o
be a he cu ing edge o echnology in i s new p oduc and
se ice in oduc ions. Fu he , i should be no ed ha I ag ee
wi h Zah a e al. (2006) who emphasized ha he quali ie
dynamic di e en ia es he abili y o de elop new p oduc s
om he dynamic capabili y o econ igu e and modi y he
way a i m de elops new p oduc s. The e o e, I de ine a new
ou ine o de eloping p oduc s as an ope a ional capabili y
and he abili y o adap such capabili ies as a dynamic capa-
bili y.
Al hough se e al dynamic capabili ies sha e simila cha -
ac e is ics and e en o e lap in hei de ini ions, I di e en ia e
be ween abso p i e capaci y and new p oduc de elopmen
capabili y based on he ollowing ac o s:
1. While my de ini ion o abso p i e capaci y empha-
sizes he i m’s abili y o acqui e and in e nalize ex e -
nal knowledge (i.e., knowledge ou side he i m) in a
alue-adding manne , he majo ocus o new p oduc
de elopmen capabili y ocus is on he i m’s abili y o
bene i om in e nal esou ces, p ocesses, and cou ses
o ac ion.
2. The abso p i e capaci y o a i m enables he i m o
cap u e alue om ex e nal sou ces – howe e , i does
no desc ibe he i m’s in insic d i e o do so. My de i-
ni ion o new p oduc de elopmen capabili y does in-
clude his h i e by assuming ha i ms p oac i ely aim
o be pionee s in hei new p oduc s and se ices.
Figu e 3b ie ly summa izes he di e ences be ween he
wo dynamic capabili ies.
2.2. Dynamic capabili ies and s a egic en y
How i ms espond o inno a i e ac ions aken by (po-
en ial) i als and which capabili ies lead i ms’ s a egis s o
pu sue a speci ic s a egic di ec ion a e wo cen al ques ions
in managemen and s a egy esea ch (e.g., A gy es e al.,
2019; Roy and Sa ka , 2016). Con a y o p io li e a u e
which is based mainly on U e back and Abe na hy’s (1975)
heo y abou indus y dynamics, A gy es e al. (2015, p. 216)
in oduce he inno a ion shock app oach and sugges ha
i is no he dominan design o an ex e nal shock bu he
“in oduc ion o a pionee ing new p oduc design by a single
i m” ha o ces incumben s o ake s a egic ac ions (i.e.,
eposi ioning, imi a ing, exi ing) and ha leads po en ial i-
als o conside ma ke en y. Fu he , he ques ion a ises o
which capabili ies enable a i m and i s manage s o pu sue
a speci ic s a egic di ec ion. Li e a u e on inno a ions and
dynamic indus ies has o en in es iga ed i ms’ capabili ies
and esou ces when seeking answe s o hei di icul ies in
esponding o inno a ion shocks and change and sugges s
ha he abili y o espond o new indus ies is pa o a i m’s
dynamic capabili ies (e.g., King and Tucci, 2002). As o -
dina y ope a ional capabili ies (ze o-o de capabili ies) a e
de ined as a “high-le el ou ine (o collec ion o ou ines)
ha , oge he wi h i s implemen ing inpu lows, con e s
upon an o ganiza ion’s managemen a se o decision op-
ions o p oducing signi ican ou pu s o a pa icula ype”
(Win e , 2003, p. 991), hey may no necessa ily enable a
i m o en e in o ela ed o en i ely new indus ies and o
in eg a e new echnologies o gene a e alue (La ie, 2006).
Much a he , decisions o whe he and how o en e new
indus ies a e dependen on he econ igu a ion o in e nal
esou ces and capabili ies and on he acquisi ion o equi ed
ex e nal knowledge (e.g., Leona d-Ba on, 1992; T ipsas
and Ga e i, 2000). As opposed o ope a ional capabili ies,
dynamic capabili ies (highe o de capabili ies) inco po a e
changing en i onmen s and a e hus c ucial when en e ing
E. Schul e genann Kulkmann /Junio Managemen Science 9(4) (2024) 2050-2081 2055
Figu e 3: Dis inc ion be ween abso p i e capaci y and new p oduc de elopmen capabili y
new ields and esponding o dis up i e shi s (Damanpou
& Wischne sky, 2006; Rosenbloom & Ch is ensen, 1994).
A gy es e al. (2015) a gued ha an inno a ion shock p o-
ides knowledge abou p oduc ea u es equi ed o p o i
om he newly de ec ed e enue pool and may lead o he
i ms o conside en y based on hei pe cei ed esou ces
and capabili ies.
The e o e, my heo e ical model in es iga es he e ec s
o pe cei ed dynamic capabili ies on he assessmen o s a e-
gic en y o an indus y ha has ecen ly expe ienced an in-
no a ion shock. Following he wo k o Me ikle and Joo dens
(1997) on cogni i e psychology, i should be no ed ha he
emphasis mus be on pe cei ed a he han objec i e dynamic
capabili ies o unde s and how co po a e abso p i e capaci y
shapes s a egis s’ alua ion app oaches.
Fu he , I build on he beha iou al heo y o he i m and
in pa icula on he indings o Ga e i and Le in hal (2000)
acco ding o which decision make s, al hough boundedly a-
ional, can an icipa e he b oad consequences o b oadly o -
mula ed ac ions as a esul o c ude and simpli ied ep esen-
a ions o he en i onmen in which hey ope a e. Ga e i
(2005) expanded his concep by including he ole o cog-
ni i e ep esen a ions. The way a senio s a egis o op
managemen eam po ays a compe i i e en i onmen has
a s ong impac on he s a egic ac ions and posi ioning o
he i m. This pe spec i e is desc ibed in mo e de ail in he
me hods sec ion.
2.2.1. Pe cei ed abso p i e capaci y and s a egic en y
The assessmen o s a egic en y is de e mined by mul-
iple ac o s which may ei he be o ex e nal o in e nal na-
u e. Abso p i e capaci y cons i u es one o he mos essen-
ial in e nal elemen s and hus, I assume he pe cei ed le el
o abso p i e capaci y o a i m o be o high ele ance o
s a egis s’ e alua ion o en y oppo uni ies.
While he unce ain y ollowing an inno a ion shock
lea es some i al i ms ulne able (e.g., Bigelow e al., 2019;
Ch is ensen, 1997), i c ea es aluable oppo uni ies o
o he incumben s and i ms conside ing s a egic en y (e.g.,
A gy es e al., 2015). By le e aging exis ing capabili ies –
pa icula ly knowledge-based ones – i ms may manage o
leap og i als and ensu e sus ained compe i i e ad an age
(Hel a & Raubi schek, 2000). In hei seminal a icle on
dynamic capabili ies and s a egic managemen , Teece e al.
(1997) name a misma ch be ween he bundle o o ganiza-
ional p ocesses equi ed o mee he needs o a new indus y
as a majo eason o en y ailu e. Fo ins ance, i ms may
lack he inancial esou ces o imi a e capabili ies in a imely
manne (e.g., Hel a and Eisenha d , 2004), may no be
able o le e age hei human capi al (e.g., Hi e al., 2001),
o may no succeed in acqui ing and assimila ing ex e nal
knowledge (e.g., Kogu and Zande , 1992).
Fu he , ollowe s’ s a egic choices a e dependen on
“compa a i e adjus men cos s” – cos s ha a e in luenced
by h ee ca ego ies o o ganiza ional ac o s, namely (1) in-
e nal knowledge, capabili ies, and esou ces, (2) in e nal in-
cen i es and o ganiza ional s uc u es, and (3) ela ionships
wi h hi d pa ies such a egula o s and supplie s (A gy es
e al., 2015) (see igu e 4).
The i s ca ego y includes a i m’s echnological knowl-
edge base and inancial asse s. Fi ms wi h highe le els o
embedded knowledge ace lowe adjus men cos s as hey
en e a new indus y o conside eposi ioning. Knowledge
ma ke s a e o en subjec o se e e in o ma ion asymme ies
(e.g., Ca es e al., 1983), making knowledge acquisi ion a
di icul and ime-consuming p ocess. Hence, he lowe he
i m’s embedded knowledge, he g ea e he expec ed ad-
jus men s cos s. The concep o abso p i e capaci y consis s
o a se ies o p ocesses ela ed o ex e nal knowledge: ac-
quisi ion, app op ia ion, ans o ma ion, and exploi a ion o
ex e nal knowledge, which is dynamic and he e ogenous.
The e is a consensus ha i ms wi h highe le els o ab-
so p i e capaci y possess s onge abili ies o lea n om
s a egic pa ne s, cap u e and in eg a e ex e nal in o ma-
ion, and ans o m his in o ma ion in o alue-enhancing,
i m-embedded knowledge (e.g., Baía and Fe ei a, 2019;
Ba e o, 2010; C. L. Wang and Ahmed, 2007). Building
on hese indings, a i m wi h s ong abso p i e capaci y
may ace ewe challenges when acqui ing and in eg a ing
knowledge han a i m wi h low abso p i e capaci y and
hus, ace conside ably lowe adjus men cos s. This line
o easoning is also in acco dance wi h he eposi ioning
amewo k de eloped by A gy es e al. (2019) which aims
o guide s a egis s who ha e do decide whe he and how o
eposi ion as a esponse o an inno a ion shock. Dynamic
capabili ies and adjus men cos s a e in ima ely linked as
bo h app oaches desc ibe po en ial ( inancial) ba ie s i ms
ace when modi ying o upda ing hei esou ces, capabili-
ies, and knowledge. Fu he , pa icula ly knowledge-based
dynamic capabili ies (including abso p i e capaci y) a e o
high ele ance when explaining di e ences in compe i i e
ad an age and i m pe o mance in dynamic en i onmen s.
When conside ing s a egic en y, i ms’ s a egis s mus
also ake in o accoun he iming o en y. I an inno a-
E. Schul e genann Kulkmann /Junio Managemen Science 9(4) (2024) 2050-20812056
Figu e 4: Fac o s ha de e mine compa a i e adjus men cos s
ion shock leads o a su icien i s mo e ad an age, ol-
lowe s may no be able o bene i om a su icien ly la ge
sha e o he inc eased demand and he e o e canno keep
up wi h he i s mo e (A gy es e al., 2015). In his pio-
nee ing wo k on indus y e olu ion, Kleppe (1996) ound
ha ea ly en an s ul ima ely gain an insu moun able cos
ad an age o e la e ollowe s since e u ns on in es men in
cos -cu ing p ocess R&D g ow wi h scale. Hence, as i ms ex-
pand and become la ge , he cos gap be ween ea ly and la e
en an s also widens, leading o he exi o la e en an s.
Those obse a ions we e also con i med o he speci ic case
o i ms en e ing an indus y ha has expe ienced an inno-
a ion shock (A gy es e al., 2015). The speed o change is
pa o s a egic change which is de ined as “a di e ence in
he o m, quali y, o s a e o e ime” (Van de Ven & Poole,
1995, p. 512). This de ini ion comp omises h ee change di-
mensions, i.e., he ype, he magni ude ( o m and quali y),
and he speed o change (o e ime). Yi e al. (2015) exam-
ined he ela ionship be ween dynamic capabili ies and he
speed o change and ound s ong echnological capabili ies
and abso p i e capaci y o ha e a posi i e impac on i ms’
speed o change. In he case o e e changing en i onmen s,
echnological skills and a s ong esou ce base we e ound
o complemen abso p i e capaci y, enabling i ms o quickly
implemen s a egic change. The as e s a egic change can
be in eg a ed, he mo e oppo uni ies a company can capi al-
ize on ahead o i s compe i o s o achie e supe io compe i-
i e ad an age (Liebe man & Mon gome y, 1988). The speed
o implemen a ion does no only p o ide insigh s abou he
need o change, bu also abou he abso p i e capaci y a i m
possesses o ealize s a egic change, as his capaci y is also
accompanied by he slack equi ed o espond quickly o ex-
e nal dynamism. Fi ms wi h high abso p i e capaci y may
he e o e also be quicke in implemen ing s a egic change
han i ms who possess low le els o abso p i e capaci y.
In addi ion o implemen a ion speed, he speed o s a e-
gic change co e s he speed and e iciency o s a egic
decision-making (Eisenha d , 1989). As abso p i e capac-
i y includes he abili y o ecognize he alue o new ex e nal
in o ma ion, his may also be bene icial when ha ing o
choose be ween s a egic di ec ions. Fo ins ance, i ms wi h
compa ably highe abso p i e capaci y a e much mo e likely
o imi a e an inno a ion shock mo e quickly. As new inno-
a ions limi he alue o es ablished i ms’ knowledge, hey
need o possess abso p i e capaci y o quickly ecognize he
alue o newly a ailable in o ma ion and o de elop a com-
pa able p oduc which s imula es he new demand (Bigelow
e al., 2019). This is in line wi h indings o Hende son and
Cockbu n (1994) who disco e ed a posi i e ela ionship be-
ween in-house knowledge and compe ence h ough R&D o
pha maceu ical i ms and i s disco e y p oduc i i y.
As e lec ed in i s de ini ion, abso p i e capaci y allows
i ms o be e “ ecei e” ex e nal knowledge, i.e., knowledge
gene a ed by o he i ms o pa ne s. The abili y o bene-
i om knowledge gene a ed ou side he i m may no only
be aluable when coope a ing wi h s a egic pa ne s o sup-
plie s, bu also in he con ex o knowledge spillo e s (see
igu e 5). Such spillo e s e e o he exis ence o ex e -
nali ies, commonly de ined as o en unan icipa ed ex e nal-
i ies associa ed wi h an ac i i y o p ocess (Aga wal e al.,
2010). Mo e p ecisely, knowledge spillo e s a e ex e nal
bene i s om he c ea ion o knowledge ha also bene i pa -
ies o he han hose in es ing in he c ea ion o knowledge.
Such bene i s include, among o he hings, imp o ed inno a-
ion and p oduc i i y (Aud e sch & Beli ski, 2023). Howe e ,
spillo e s as a o m o ex e nali y a e only u ilized in case
he a ailable knowledge esul s in a di ec and clea bene i .
Access o knowledge spillo e s s imula es i ms’ p oduc i i y
and inno a ion e o s since he a ailabili y o new knowl-
edge also s eng hens i ms’ abili y o de elop new p oduc s
and s eamline unde lying p ocesses. In con as o knowl-
edge spillo e s, knowledge collabo a ions a e based on ac-
i e knowledge sha ing h ough e.g., s a egic pa ne ships
(Cassiman e al., 2018). Such collabo a ions enable i ms
o alloca e cos s (e.g., R&D, equipmen ) be ween pa ne s
(Veugele s, 1997) and o sho en he p oduc de elopmen
phase in he inno a ion li e cycle (Aud e sch & Beli ski, 2023;
Hagedoo n, 1993). This, in u n, inc eases a i m’s compe i-
i eness (e.g., W. M. Cohen and Le in hal, 1989; Mio i and
Sachwald, 2003).
Some i ms a e be e able han o he s o cap u e alue
om collabo a ions which can pa ly be a ibu ed o he
le els o abso p i e capaci y a i m possesses (Ri ala &
Hu melinna-Laukkanen, 2013). Two dimensions o abso p-
i e capaci y a e especially ele an ega ding p o i ing om
ex e nal knowledge implemen a ion. The i s one cap u es
a i m’s p opensi y o acqui e new knowledge and i s unde -
s anding o wha kind o knowledge is ele an . The second
one is he i m’s abili y o u ilize and embed he ex e nal
knowledge o an ex en ha esul s in compe i i e ad an-
age.
Building on he abo e-men ioned indings and line o ea-
soning and pu ing hem in o he con ex o abso p i e ca-
paci y and s a egic en y, one may assume he ollowing:
Since adjus men cos s a e conside ably lowe o i ms wi h
high le els o embedded knowledge and since ex ensi e ab-
E. Schul e genann Kulkmann /Junio Managemen Science 9(4) (2024) 2050-2081 2057
Figu e 5: Fo ms o ex e nal knowledge s eams
so p i e capaci y enables i ms o mo e easily acqui e and
in eg a e ex e nal knowledge, a i m’s s a egis may also as-
sume ha he o ganiza ion aces lowe compa a i e adjus -
men cos s when en e ing a new indus y when i s pe cei ed
abso p i e capaci y is high han when i s pe cei ed abso p-
i e capaci y is low. Fu he , a i m’s p o i om en e ing
a new indus y is highly dependen on he speed o en y
and he speed o change. Fi ms wi h ex ensi e abso p i e ca-
paci y a e able o implemen s a egic change mo e quickly
han i als wi h limi ed abso p i e capaci y. Hence, akings
hese ac s in o accoun , a i m’s s a egis may a e he i m’s
speed in en e ing new indus ies highe when he pe cei ed
abso p i e capaci y is high han when he pe cei ed abso p-
i e capaci y is low. Finally, d awing on he posi i e im-
pac o knowledge spillo e s and knowledge collabo a ions
on i ms’ inno a i e beha iou and p oduc i i y, and he ac
ha s ong abso p i e capaci y simpli ies he p ocess o e-
cei ing ex e nal knowledge, a i m’s s a egis may ind he
i m o be able o cap u e mo e alue om knowledge ex-
e nali ies when he pe cei ed abso p i e capaci y is high
han when he pe cei ed capaci y is low. As s a ed in sec ion
2.2, I assume ha decision make s (i.e., s a egis s, senio
manage s) can an icipa e consequences o a i m’s cou ses
o ac ion and ha hei decisions ha e a signi ican impac
o he s a egic choices o a i m (Ga e i, 2005; Ga e i &
Le in hal, 2000). Thus, I hypo hesize:
Hypo hesis 1a) As a i m’s pe cei ed abso p i e capaci y
inc eases, so does he i m’s s a egis s’ assessmen o en y
a ac i eness.
2.2.2. Pe cei ed new p oduc de elopmen capabili y and
s a egic en y
Simila o abso p i e capaci y, new p oduc de elopmen
capabili ies play a c ucial ole wi h ega d o i ms’ compe i-
i e posi ion. To compe e in new indus ies, a i m should no
only be able o bene i om ex e nal knowledge bu also o
d i e inno a ion and ha e he in insic mo i a ion o do so.
The e o e, I also assume he le el o pe cei ed new p oduc
de elopmen capabili y o be highly impo an o he assess-
men o s a egic en y by he i m’s s a egis .
As s a ed in sec ion 2.2.1, a i m’s s a egic mo e in e-
sponse o changes in he en i onmen caused by a i al i m,
is no only dependen on inancial o o ganiza ional con-
s ain s o he i m, bu also on i s en y iming. Fi ms con-
side ing en e ing a new indus y mus ac quickly since, o h-
e wise, he cos gap be ween ea ly en an s and la e ol-
lowe s will widen o he poin ha la e en an s will ha e
no o he choice bu o lea e (A gy es e al., 2015; Kleppe ,
1996). Ea ly en an s, on he o he hand, may be able o
neu alize he i s mo e ad an age. The de ini ion o new
p oduc de elopmen capabili y as a dynamic capabili y in-
co po a es a s ong and pe manen de e mina ion o be a
he cu ing edge o echnology. Fi ms ha possess s ong
new p oduc de elopmen capabili ies aim o leap og hei
i als when en e ing new indus ies. Being able o quickly
adap new p oduc de elopmen p ocesses and o ans o m
echnical knowledge in o new o e ings enables i ms o e-
main compe i i e in changing en i onmen s. Fi ms ha ha e
high new p oduc de elopmen capabili ies may he e o e be
mo e likely o en e new indus ies quickly since hey al eady
ha e essen ial mechanisms in place o adap in e nal ope a-
ions lexibly and easily. On he o he side, i ms wi h low
new p oduc de elopmen capabili ies may ace a ious ob-
s acles when en e ing new indus ies ha delay he iming
o en y. Such obs acles could include ime-consuming R&D
ac i i ies, o he c ea ion o c oss- unc ional eams o ensu e
new knowledge combina ions. Hence, i ms wi h s ong new
p oduc de elopmen capabili y may be mo e likely o en e
new indus ies in a imely manne which enables hem o ex-
ploi mo e o he demand han hose wi h low new p oduc
de elopmen capabili y.
In addi ion o a i m’s “in insic” d i e o en e new in-
dus ies and o achie e echnological leade ship, his s a e-
gic decision is also linked o cos s and e o s associa ed
wi h echnology esou ces equi ed o supe io pe o -
mance. New p oduc de elopmen comes wi h a consid-
e able amoun o unds such as specialized acili ies, ain-
ings, and s a e-o - he-a equipmen (Hel a e al., 2007).
Hel a and Win e (2011) a gued ha i ms need o deploy
hei new p oduc de elopmen capabili y mul iple imes o
ac ually gene a e e enue o hei in es men s o pay o .
Schilke (2014) examined he ela ionship be ween new p od-
uc de elopmen capabili y and compe i i e ad an age unde
a ying le els on en i onmen al dynamism and s a ed ha
i ms wi h s ong new p oduc de elopmen p ocesses and
ou ines end o ely on expe ience which can esul in o -
E. Schul e genann Kulkmann /Junio Managemen Science 9(4) (2024) 2050-20812064
Figu e 8: New p oduc de elopmen phases and ma ke sensing capabili ies
e al., 2006; S. Wang and Noe, 2010). Mo e p ecisely, knowl-
edge sha ing means p o iding in o ma ion and know-how
wi h he in en ion o collabo a e and o help o he s (e.g.,
Cummings, 2004; S. Wang and Noe, 2010).
Exis ing esea ch esul s can be oughly classi ied in wo
di ec ions. One g oup o schola s sugges s ha o ganiza-
ional inno a i eness is gua an eed by knowledge sha ing
(e.g., Jackson e al., 2006; C.-P. Lin, 2007). O he esea che s
ag ee ha knowledge sha ing pa ially impedes he inno a-
ion pe o mance o i ms. Fo ins ance, Ri ala e al. (2015)
ound ha , al hough knowledge sha ing has a posi i e in-
luence on inno a ion pe o mance, unin en ional o in en-
ional ex e nal knowledge sha ing nega i ely mode a es his
ela ionship. Mo eo e , knowledge sha ing ine i ably leads
o knowledge esou ce he e ogenei y wi hin o ganiza ions,
which, in u n, can cause gaps in in e nal knowledge ex-
change and inally, inc ease knowledge managemen cos s
and hinde inno a i e pe o mance (Ancona & Caldwell,
1992).
Howe e , al hough he e a e some di e ences in he e-
sul s and concep ualiza ions o knowledge sha ing, he ma-
jo i y o s udies conclude ha , as knowledge is he i m’s mos
impo an esou ce, i ms and hei decision make s p o i
om knowledge sha ing mechanisms in mul iple ways. Fo
example, i can help educe p oduc ion cos s, inc ease he
speed o new p oduc de elopmen p ojec s, s eng hen eam
pe o mance, and op imize i m pe o mance h ough sales
g ow h and g ow h o e enue om new p oduc s and se -
ices (e.g., A hu and Hun ley, 2005; Mesme -Magnus and
DeChu ch, 2009; S. Wang and Noe, 2010) (see igu e 9).
In he ollowing, I use he e m knowledge sha ing when
e e ing o knowledge sha ing wi hin a i m.
When I e e o knowledge sha ing o ex e nal pa ies, I
use he e m ex e nal knowledge sha ing. Fu he , I assume
i ms o possess high le els o knowledge sha ing i in e nal
p ocesses o sha ing in o ma ion e ec i ely among indi id-
uals, decision make s, and in e nal uni s a e e y well de-
eloped. In con as , i such p ocesses a e only de eloped o
a limi ed ex en , a i m’s le el o knowledge sha ing mecha-
nisms is low.
2.4.1. Pe cei ed abso p i e capaci y and in e nal knowledge
sha ing
Abso p i e capaci y is a cen al o ganiza ional capabil-
i y as i enables i m o gain compe i i e ad an age h ough,
o ins ance, inc eased lea ning abili ies and knowledge ac-
quisi ion and in e naliza ion (e.g., Baía and Fe ei a, 2019).
While abso p i e capaci y plays a majo ole in i ms’ com-
pe i i e pe o mance, i is no he only elemen ha has an
e ec on pe o mance and s a egic choices. Gi en he high
ele ance o bo h abso p i e capaci y and knowledge sha -
ing, he e is a g owing in e es in iden i ying and examining
ac o s ha de e mine he ela ionship be ween hese wo o -
ganiza ional mechanisms (e.g., Balle e al., 2020; Ceccagnoli
and Jiang, 2013; Van Wijk e al., 2008). Howe e , he esul s
o s udies on he ela ionship be ween abso p i e capaci y
and knowledge sha ing a e somewha puzzling and ambigu-
ous. While some schola s claim ha knowledge sha ing is
posi i ely in luenced by a i m’s abso p i e capaci y (e.g., Ai
and Tan, 2017; Be y, 2017; Miguélez and Mo eno, 2015),
o he s sugges a posi i e impac o knowledge sha ing on ab-
so p i e capaci y (e.g., Cos a and Mon ei o, 2016; Lim e al.,
2015; Pel oko pi, 2017).
Wi h espec o a icles ha ega d abso p i e capaci y as
an an eceden o knowledge sha ing, he majo i y o schola s
base hei line o easoning on he assump ion ha abso p i e
capaci y p o ides he knowledge base necessa y o es ablish
knowledge sha ing mechanisms in an o ganiza ion and a-
cili a es i s p ocess (Balle e al., 2020). I is assumed ha
abso p i e capaci y p o ides he g ounding needed o engage
in knowledge sha ing ac i i ies. This happens, among o he
hings, by applying bes p ac ices, and by iden i ying and
in eg a ing new knowledge oppo uni ies (e.g., G impe and
Hussinge , 2013). Howe e , hese a gumen s a e di icul
o econcile wi h he de ini ions o dynamic capabili ies and
abso p i e capaci y adap ed in his s udy. Fi s , I do no de-
ine dynamic capabili ies as bes p ac ices and, hence, do no
assume abso p i e capaci y o os e knowledge sha ing ia
he applica ion o such lea nings. Second, I de ine abso p i e
capaci y as he i m’s abili y o in e nalize and p o i om
knowledge ou side he i m, implying ha in e nal knowl-
edge sha ing is no necessa ily in luenced by knowledge
s eams a ising om he i m’s abso p i e capaci y. Finally,
al hough abso p i e capaci y inc eases knowledge ans e
om ex e nal sou ces, I sugges ha i ms can s ill imple-
men ex ensi e knowledge sha ing mechanisms and u ilize
al eady exis ing in e nal knowledge wi hou equi ing s ong
abso p i e capaci y.
On he o he hand, ega ding he li e a u e s eam ha
conside s abso p i e capaci y as an ou come o knowledge
sha ing mechanisms, he majo a gumen in quali a i e s ud-
ies is a boos in abso p i e capaci y esul ing om he exis-
ence o knowledge sha ing suppo p ac ices (e.g., Elezi and
Bambe , 2016). Quan i a i e a icles, which a e he majo -
E. Schul e genann Kulkmann /Junio Managemen Science 9(4) (2024) 2050-2081 2065
Figu e 9: Ou comes o in e nal knowledge sha ing
i y in his s eam, mainly sugges ha knowledge sha ing in-
c eases knowledge in mul iple uni s making i easie o i ms
o es ima e and ank he alue o ex e nal knowledge.
When aced wi h he choice o ei he en e new o e-
la ed indus ies o emain in he cu en s a egic posi ion,
i ms’ s a egis s mus ake in o accoun bo h ex e nal as
well as in e nal ac o s ha may acili a e o complica e en-
y. In e nal ac o s o conside include he i m’s le els o
knowledge sha ing. Zhao e al. (2021) ound ha , al hough
in e nal knowledge sha ing canno di ec ly os e i ms’ inno-
a ion pe o mance, abso p i e capaci y has a ull media ing
e ec on his ela ionship. Fu he , since knowledge sha -
ing exposes o ganiza ional eams o new knowledge and
sp eads i wi hin he i m, his knowledge dis ibu ion may
also help imp o e i ms’ abso p i e capaci y (Cu ado e al.,
2015). In e ms o ou comes o abso p i e capaci y, a consid-
e able numbe o schola s ha e ound a posi i e and di ec
ela ionship be ween abso p i e capaci y and i m and in-
no a ion pe o mance (e.g., Be gh and Lim, 2008; B e el
e al., 2011). I ag ee wi h his iew and u he sugges a
posi i e ela ionship be ween abso p i e capaci y and he
assessmen o s a egic en y. Howe e , I do no explo e he
ole o knowledge sha ing as a media o bu much a he as
a mode a o .
Knowledge sha ing sp eads knowledge ac oss depa -
men s which can s eamline he p ocess o acqui ing and
in e nalizing knowledge. Fu he , Liao e al. (2007), in
hei a icle on knowledge sha ing beha iou in knowledge-
in ense indus ies, a gue ha i i ms manage o es ablish a
s ong knowledge sha ing cul u e, employees a e likely o
be a ec ed in a way ha inc eases hei lea ning abili y and
mo i a ion. Since knowledge sha ing os e s in e ac ion and
emphasizes he i m’s suppo o collabo a ion, employees
a e able o be e unde s and hei i m’s posi ioning and
engage mo e in lea ning ac i i ies. A i m wi h s ong ab-
so p i e capaci y is able o in e nalize ex e nal knowledge
and cap u e alue om i ega dless o in e nal knowledge
sha ing and hence, may decide o en e a new indus y. How-
e e , he i m’s s a egis ’s pe cep ion o knowledge sha ing
may impac he ex en o which he o she assumes high le -
els o abso p i e capaci y can lowe he ba ie s o s a egic
en y, because i o en eases apid and balanced dis ibu ion
o newly acqui ed knowledge, and collabo a ion may lead
o knowledge syne gies. Fo example, a i m migh possess
high le els o abso p i e capaci y ha enable he i m o in-
e nalize ex e nal knowledge acqui ed om spillo e s and
collabo a ion. Howe e , sha ing his ex ac ed knowledge
be ween eams and ensu ing i also alls in o he hands o
specialis s who migh be able o u ilize i in o he bene icial
ways han hose who in e nalized he knowledge in he i s
place migh equi e conside able e o and ime. The e o e,
I assume a i m’s s a egis o a e s a egic en y as much
mo e a ac i e i he o she eels he o ganiza ion disposes
o su icien p ocesses o ensu e he knowledge is dis ibu ed
in a imely manne and ha in e nal esou ces a e ac ually
commi ed o sha ing knowledge and o lea ning om e-
cei ed knowledge. In con as , i he i m is able o acqui e
and in e nalize ex e nal knowledge bu i akes emendous
ime o sha e such knowledge wi hin he i m and he e is no
mo i a ion o do so, s a egis s migh ag ee ha he i m is
no able o ully capi alize on he newly acqui ed knowledge.
Thus, I hypo hesize:
Hypo hesis 3a) Pe cei ed abso p i e capaci y will en-
cou age a i m’s s a egis o en e a new indus y, especially
i i is assumed ha knowledge sha ing wi hin he i m is e y
well de eloped.
2.4.2. Pe cei ed new p oduc de elopmen capabili y and in-
e nal knowledge sha ing
Inno a ion is o en explained in e ms o modi ica ions
in i ms’ o e ings and he way i ms de elop and deli e
hese o e ings (F ancis & Bessan , 2005). D awing on Sam-
son’s (1991) inno a ion ca ego ies, i.e., p oduc , p ocess,
and manage ial and sys ems inno a ion, inno a i e capa-
bili y is commonly assumed o be e lec ed in he abili y o
show pe o mance in hese h ee ca ego ies. As s a ed in sec-
ion 2.1.2, new p oduc de elopmen capabili y ep esen s
one o he nume ous dimensions o inno a i e capabili ies
and is one o he mos explo ed dynamic capabili ies (e.g.,
Hel a and Win e , 2011; Schilke, 2014). While a conside -
able numbe o s udies ha e examined he ela ionship be-
ween knowledge sha ing, abso p i e capaci y as a speci ic
dynamic capabili y, and hei ou comes, compa ably li le e-
sea ch is a ailable on he ela ionship be ween new p oduc
de elopmen capabili y and knowledge sha ing. Howe e ,
mul iple schola s ha e ocused on he in es iga ion o how
inno a i e capabili ies (which inco po a e new p oduc de-
elopmen capabili ies) and knowledge sha ing ela e o each
o he .
Quinn e al. (2009) sugges ed ha in ellec and knowl-
edge g ow exponen ially when sha ed. I knowledge is only
exchanged be ween wo pe sons, his only esul s in linea
g ow h. Howe e , i his knowledge is u he dis ibu ed by
such pe sons, o he s in eg a e eedback and lea nings and i-
nally, he alue becomes exponen ial. This is he case in i ms
ha pu a s ong emphasis on he implemen a ion o com-
p ehensi e knowledge sha ing mechanisms. Building on his
logic, Liao e al. (2007) explo ed he ole o knowledge sha -
E. Schul e genann Kulkmann /Junio Managemen Science 9(4) (2024) 2050-20812066
ing in i ms’ inno a ion e o s and p o ed a posi i e e ec
o knowledge on inno a ion capabili y. Since p io esea ch
was able o p o e a posi i e impac o sha ed knowledge
on a ious inno a ion ou comes such as p oduc inno a ion
(Camelo-O daz e al., 2011), eam inno a ion (Hu & Ran-
del, 2014), and echnical inno a ion (Chen & Huang, 2009),
knowledge sha ing is likely o also imp o e o e all o gani-
za ional pe o mance (Cos a & Mon ei o, 2016). Fu he ,
knowledge sha ing mechanisms can be di ided in o knowl-
edge dona ing and knowledge collec ing (H.-F. Lin, 2007).
As knowledge is pe sonal (Da enpo & P usak, 1998), a
p e equisi e o e ec i e knowledge managemen in i ms is
he de e mina ion o employees o sha e hei knowledge and
o coope a e wi h colleagues. I a i m p omo es knowledge
dona ion, his encou ages he de elopmen o inno a i e
ideas and business oppo uni ies, and hus acili a es inno-
a i e ac ions (Da och & McNaugh on, 2002). Knowledge
collec ion, on he o he hand, e lec s mechanisms and p o-
cesses o ga he ing in e nal and ex e nal knowledge (H.-F.
Lin, 2007). Collec ing essen ial knowledge ep esen s a ma-
jo elemen o success ul inno a ion p ojec comple ion and
hus, also inc eases inno a ion capabili ies (Hansen, 1999).
Hence, employees’ willingness o bo h dona e and collec
knowledge a e posi i ely ela ed o a i m’s inno a ion capa-
bili y. As i ms’ pe o mance is pa ially de e mined by sales
and e enue numbe s, Collins and Smi h (2006) in es iga ed
he impac o knowledge p ac ices on new p oduc e enue
and sales g ow h in high- echnology i ms and p oposed
ha , as a highe le el o sha ed codes and language be ween
specialis s acili a es equen knowledge exchange and com-
bina ion among specialis s, his also inc eases bo h e enue
om new p oduc in oduc ions as well as sales g ow h.
The e o e, i is easonable o say ha , since e ec i e knowl-
edge sha ing as ens and op imizes p oduc inno a ion by
d i ing indi idual lea ning, i is an essen ial enable o idea
and p oduc inno a ions (Gao & Be na d, 2018).
Howe e , knowledge sha ing in i ms is hampe ed by a
a ie y o obs acles. One challenge ha accompanies i ms’
new p oduc de elopmen e o s, is he c oss- unc ional na-
u e o p oduc de elopmen p ocesses. I i ms do no ha e
a ious s anda dized knowledge sha ing p ac ices ac oss de-
pa men s in place, hey may no be able o maximize he
alue om new p oduc in oduc ions. Such gaps in knowl-
edge exchange migh lead o cos ly mis akes. Addi ional
main ba ie s o p ojec success include a lack o de ailed
and anspa en knowledge de ini ions, and o mechanisms
o ensu e access o ele an in o ma ion in he mul ilingual
en i onmen (B ad ield & Gao, 2007).
Simila o he e ec o knowledge sha ing on pe cei ed
abso p i e capaci y and s a egic en y, I expec he i m’s
s a egis ’s pe cep ion o knowledge sha ing o in luence he
ex en o which high le els o new p oduc de elopmen can
lowe s a egic en y ba ie s. In his a icle, a i m’s new
p oduc de elopmen capabili y is e lec ed in he abili y o
cons an ly a emp o pionee and o be a he cu ing edge
o echnology in i s new p oduc and se ice in oduc ions.
Knowledge sha ing acili a es, among o he hings, new ideas
de elopmen , he lea ning abili y o specialis employees,
and employees’ mo i a ion o ac i ely con ibu e o i m pe -
o mance.
Fo ins ance, a i m migh ha e ex ensi e new p oduc de-
elopmen capabili ies and hus, bene i om inc eased com-
pe i i eness wi h ega d o echnological pe o mance and
quali y o new p oduc s. Howe e , i he i m lacks app o-
p ia e knowledge sha ing mechanisms, he new p oduc de-
elopmen p ocess migh in ol e high cos s as a esul o in-
e icien knowledge pa hs and un anspa en echnological
documen a ions. The i m’s s a egis mus belie e ha he
i m has su icien p ocedu es in place o ensu e high-quali y
knowledge sha ing, o a e en y as a highly aluable s a e-
gic mo e. On he con a y, i he pe cei ed new p oduc de-
elopmen capabili y o he i m is high bu he s a egis s as-
sume ha no adequa e knowledge sha ing mechanisms a e
implemen ed, he i m migh be expec ed o ace cos ly ob-
s acles and hus, he s a egis migh a e he abili y o he
i m o capi alize as a he limi ed. Thus, I hypo hesize:
Hypo hesis 3b) Pe cei ed new p oduc de elopmen ca-
pabili y will encou age a i m’s s a egis o en e a new in-
dus y, especially i i is assumed ha knowledge sha ing
wi hin he i m is e y well de eloped.
3. Me hod
To es my hypo heses, I conduc ed an online conjoin ex-
pe imen wi h 52 s a egis s as he su ey sample. The ol-
lowing sec ion b ie ly explains he app oach I used o de ine
my sample, he bene i s o conjoin analyses, and he main
s eps o my da a collec ion. Fu he , I p o ide an o e iew
o he pa icipan s’ demog aphics, desc ibe he assessmen
si ua ion, and in oduce he model’s a iables.
3.1. Resea ch app oach
The concep o bounded a ionali y (Simon, 1955) indi-
ca es ha , as limi ed a ional agen s, we canno imagine all
se s o a ailable choices, no can we speci y he en i e ela-
ionships be ween possible ac ions and hei ou comes. The
a he limi ed ep esen a ions, based on which ac o s shape
hei en i onmen al models, bo h simpli y he in e ac ions
among decision make s and choices, and causal and spa ial
ela ionships (Ga e i & Le in hal, 2000; Weick, 1979).
Howe e , wi h ega d o manage ial decisions and cou ses
o ac ions, cogni i e ep esen a ions ha e p o en o be a
highly ele an ac o (e.g., Ga e i, 2005; Ga e i e al.,
2012; Walsh, 1995). Speci ically, i ms’ s a egic di ec ions
a e, in many cases, a esul o hei decision make s cog-
ni i e ep esen a ions. Al hough decisions a e de eloped
and o med in ac o s simpli ied men al space, i is possible
o hem o iden i y he mos p omising ac ions by ans-
la ing hei cogni ion in o ac ual o ganiza ional beha iou .
This happens ough bo h a backwa d-looking and o wa d-
looking logic (lea ning s. consequences o ac ions) (Ga e i
& Le in hal, 2000). By u he examining he in e play be-
ween cogni ion and ac ion, Ga e i (2005) ound ha he
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way a i m’s manage o s a egis ep esen s a gi en con-
ex ual si ua ion, undamen ally a ec s he i m’s s a egic
di ec ion i will pu sue (see igu e 10). This implies ha a
i m’s u u e ac ions and business agenda a e ypically shaped
by such expe s’ ad ice which is o pa icula ele ance when
i ms en e new ields o when ex e nal shocks esul in a
new s uc u e o i ms’ s a egic decision p oblem (Ga e i,
2005; Zajac & K aa z, 1993).
Building on his logic, I pe o med my expe imen wi h
s a egis s since I assume hey adequa ely ep esen hei e-
spec i e i ms ( u he in o ma ion on he sample is summa-
ized in sec ion 3.2). O cou se, he answe s in su eys a e
subjec i e and dependen on a a ie y o o he ac o s – ne -
e heless, s a egis s’ pas and u u e di ec ions shape i ms’
beha iou and hey can pa ially an icipa e he impac o
hei s a egic decision-making on hei i m’s posi ion. Fu -
he , s a egic oles in o ganiza ions equi e deep heo e ical
and p ac ical unde s anding ega ding i ms’ s a egic posi-
ioning beha iou . Hence, I do no only assume s a egis s o
be able o an icipa e b oad consequences o hei own s a e-
gic ac ions bu also o conside essen ial i m heo ies and
p ac ical implica ions in hei decision-making p ocess. This
is in line wi h o he s udies ha ocus on s a egic manage-
men since hey also commonly use manage s and s a egis s
as p oxies (e.g., Schilke (2014): in e iews wi h op-le el
manage s, Koh amäki e al. (2020): su ey wi h CEOs, de-
elopmen , p oduc ion, and inno a ion manage s).
Fo my s udy, I used an online conjoin expe imen o
ga he da a on s a egis s’ assessmen o s a egic en y. In
such an expe imen , esponden s a e equi ed o make a
se ies o assessmen s o a numbe o decision scena ios
(Domu a h & Pa zel , 2016). The se o a ibu es enables
disman ling o decisions in o hei composing pa s using
hie a chical linea modelling (G een e al., 2001; McMullen
& Shephe d, 2006). While he a ibu es in a scena io e-
lec he independen a iables, he dependen a iable is
ep esen ed by pa icipan s’ scena io assessmen . The con-
join me hod has been used in plen y o decision-making and
judgemen a icles and is highly app op ia e o his ype
o s udy o se e al easons. Fi s , i allows o examina-
ion o in e ac ions be ween he de ined a ibu es which is
e lec ed in some o my hypo heses (Domu a h & Pa zel ,
2016). Second, ins ead o elying on pos hoc echniques
and hus, accep ing an inc eased isk o biased epo ing
(e.g., Sandbe g and Ho e , 1987) and igno ance o a dy-
namic decision-making p ocess (e.g., Hall and Ho e , 1993),
conjoin analysis conside s he ecogni ion o oppo uni ies
ins ead o e alua ing ecognized oppo uni ies (e.g., Ellis
and Peco ich, 2001). Thi d, I in eg a e he call om Shep-
he d and Zacha akis (2018) o ake in o accoun complex
and u bulen en i onmen s by conside ing en i onmen-
al dynamism and inno a ion shocks, and ou h, I aim o
spu u u e conjoin esea ch aking he pe spec i e o i ms’
s akeholde s since his iew alls, o his da e, compa ably
sho (Shephe d & Zacha akis, 2018).
3.2. Sample and da a collec ion
My sample consis ed o p o essionals employed in he po-
si ion o s a egis /s a egic g ow h expe , business de el-
opmen expe , o inno a ion expe (summa ized unde he
e m s a egis ). Such posi ions p o ide a good popula ion
o he opic o my s udy o he ollowing easons. Fi s , as-
sessing s a egic mo es and hei po en ial ou comes is pa
o hei daily wo k and hence, hey know how o app oach
complex decision-making p ocesses. Second, hei pe o -
mance is measu ed o a la ge ex en by igu es esul ing om
ce ain s a egic decisions and expansion plans hey make.
This ensu es hei commi men in such asks. Thi d, s a egic
decision-making equi es a deep unde s anding o wha ca-
pabili ies a e equi ed o ce ain s a egic ac ions and he e-
o e, such expe s know he ele ance o a i m’s abili y o in-
e nalize ex e nal knowledge (abso p i e capaci y). Fou h,
i is common ha hese p o essionals a e in egula exchange
wi h, o ins ance, R&D, p oduc ion, and sales depa men s
and a e he eby in o med abou p og ess, challenges, and
depa men -speci ic needs (new p oduc de elopmen ). Al-
oge he , I assume ha my sample has a easonable unde -
s anding o he in e play be ween i ms’ capabili ies and he
likelihood o indus y su i al and compe i i e ad an age.
The su ey was buil in Unipa k and w i en in English.
The channels I used o each ou o po en ial pa icipan s
included LinkedIn, The Global Business De elopmen Ne -
wo k (BDN) – a ne wo k o sc eened business de elopmen
expe s, execu i es, and business owne s –, and i ms’ web-
si es. To ensu e pa icipan s’ sui abili y o my su ey, I ap-
plied wo selec ion c i e ia: Fi s , I only con ac ed p o ession-
als wi h a leas h ee yea s o wo k expe ience since I do no
assume ha pa icipa ion in majo s a egic decisions is he
no m in ea ly yea s. Second, o ensu e ha he assessmen
o s a egic en y explo ed in my expe imen al app oach is
ele an o pa icipan s, a leas o some ex en , he majo -
i y o con ac ed p o essionals wo k in knowledge-ex ensi e
and/o echnology indus ies cha ac e ized by mode a ely
o high le els o en i onmen al dynamism. Since such en-
i onmen s a e highly compe i i e and inco po a e equen
change, hey ypically ha e highe expansion end eposi ion-
ing po en ial (Domu a h & Pa zel , 2016; Zacha akis & Shep-
he d, 2018). Al oge he , I eached ou o 173 po en ial pa -
icipan s. When con ac ing he p o essionals, I ound ha 37
we e ei he no a ailable unde he email add ess p o ided
on he i ms’ websi es, did no ma ch my selec ion c i e ia,
o we e no in e es ed in pa icipa ing. Hence, 136 po en-
ial candida es emained. In case he su ey was no com-
ple ed wi hin h ee weeks, I sen a second email o pe sonal
message on LinkedIn as a eminde . In o al, 52 p o ession-
als conduc ed he en i e su ey, which is e lec ed in a e-
sponse a e o 30.1 % in e ms o s a egis s con ac ed. The
sample size is consis en wi h hose o o he conjoin s udies
(e.g., Choi and Shephe d (2004) wi h 55 and McMullen and
Shephe d (2006) wi h 54 pa icipan s) and exceeds he min-
imum sample size o 50 pa icipan s p oposed by Shephe d
and Zacha akis (2018). Since conjoin analysis o e s mul i-
ple da a poin s wi hin one indi idual, hus allowing indi id-
E. Schul e genann Kulkmann /Junio Managemen Science 9(4) (2024) 2050-20812068
Figu e 10: Decision-making p ocess and impac on i m s a egy
ual subjec analysis, i equi es a conside able smalle sample
size han s anda d su ey o ma s (Zacha akis & Shephe d,
2018).
The majo i y o pa icipan s we e aged be ween 18 and
36 yea s, 40% we e emale, and mo e han 69% o he pa ic-
ipan s indica ed a Mas e ’s deg ee o highe as hei highes
educa ional le el. Fu he , mo e han hal o he pe sons who
conduc ed he su ey had a leas 6 yea s o wo k expe ience
in (51.8%) and only 17.3% ha e wo ked o hei cu en
company o less han 3 yea s. The mos equen ly men-
ioned indus ies he pa icipan s a e ac i e in we e “Com-
pu e and Technology” (19.2%), “Finance and Economics”
(21.2%), and “Pha ma” (19.2%). Mo e de ailed in o ma ion
ega ding he expe imen ’s pa icipan s is summa ized in a-
ble 1.
3.3. Expe imen al design
A hypo he ical scena io desc ibed an indus y ha has
ecen ly expe ienced an inno a ion shock and included in-
o ma ion on he i m’s abso p i e capaci y, i s new p oduc
de elopmen capabili y, in e nal knowledge sha ing p ocess,
and on indus y dynamics (i.e., en i onmen al dynamism) in
he new indus y. I chose hese a iables as e alua ion in-
pu s since he assessmen o a ying scena ios e lec s s a e-
gis s’ assessmen o s a egic en y in di e se indus ies and
wi h di e en unde lying le els o o ganiza ional capabili ies
and p ocesses. Mo e p ecisely: he e a e di e ences in he
s a egis ’s pe cep ion o each o he a iables. Fo example,
a s a egis may pe cei e his o he i m as capable o in e-
g a ing ex e nal knowledge in some cases, while in o he s,
he o she does no . Fu he , in some cases i may be an-
icipa ed ha he i m s i es o pionee and ou pe o m i s
compe i o s, while in o he s, i may lack he unde lying al-
ues and echnology esou ces o do so. The same accoun s o
he wo mode a o s. In some cases, s a egis s may assume
he i m is able o quickly alloca e essen ial knowledge o he
igh pe son, while in o he s, he s a egis s may assume he
knowledge sha ing p ocess is highly ime-consuming. Wi h
ega d o en i onmen al dynamism, he assessmen depends
upon whe he he s a egis s ega d he indus y as highly
unp edic able o assumes ha shocks and shi s in demand
cons i u e he excep ion.
Hence, each hypo he ical scena io included wo a -
ibu es ha desc ibed dynamic capabili ies (i.e., abso p i e
capaci y, new p oduc de elopmen capabili y), one a ibu e
ha desc ibed ano he o ganiza ional ac o (i.e., knowledge
sha ing), and one a ibu e ha desc ibed an ex e nal ac o
(i.e., en i onmen al dynamism). Each o hese a ibu es
was a ied a wo le els esul ing in 24=16 p o iles. These
p o iles we e ully eplica ed o ensu e eliabili y, inc easing
he numbe o 32 p o iles in o al (Shephe d & Zacha akis,
2018). Since my model inco po a es mul iple in e ac ions,
I applied a ull ac o ial design (as opposed o a ac ional
ac o ial design) o accoun o all in e ac ion e ms.
13% o he 52 pa icipan s did no answe eliably (p
>.05) – howe e , excluding hei esponses om my sample
did no lead o signi ican changes in he s a is ical esul s.
The mean co ela ion be ween he o iginal p o iles and hei
eplica ions was 0.912. This indica es he assessmen s we e
eliable and consis en . Fu he , o a oid o de e ec s, I an-
domly assigned he o de o a ibu es wi hin a p o ile and
he p o iles o ou e sions o he expe imen . A a iance
analysis e ealed no majo di e ences ac oss he di e en
e sions (p >.10).
3.4. Assessmen si ua ion and esea ch a iables
The expe imen s a ed wi h he desc ip ion o he assess-
men si ua ion. The s a egis s we e asked o pu hemsel es
in he posi ion o he head o business de elopmen o an
es ablished i m. In hei las s a egy mee ing wi h hei
boa d, hey ecei ed he in o ma ion ha he i m is look-
ing o expand o o he indus ies as pa o i s new s a egy.
Hence, pa icipan s we e p imed ha hey a e expec ed o
make a s a egic mo e. Fu he , in he hypo he ical si ua-
ion, he head o business de elopmen (i.e., he s a egis )
ecei ed an in e nal s a egy epo ha con ained in o ma-
ion abou a ela ed indus y ha has ecen ly expe ienced
an inno a ion shock. A de ini ion o an inno a ion shock
was also included in he desc ip ion, i.e., “a shi in an indus-
y ha occu s wi h he in oduc ion o a b eak h ough new
p oduc design by a single i m whose demand inc eases in
an unan icipa ed way” (A gy es e al., 2015, p. 216). The
epo also indica ed ha i ms wi h p io expe ience in e-
la ed indus ies a e much mo e likely o succeed in a new
indus y a ec ed by an inno a ion shock when compa ed o
de no o en an s (e.g., A gy es e al., 2015; Kleppe , 1996).
The e o e, in he expe imen al ask, he head o business de-
elopmen could an icipa e ha s a egic en y o he ela ed
E. Schul e genann Kulkmann /Junio Managemen Science 9(4) (2024) 2050-2081 2069
Table 1: In o ma ion o su ey pa icipan s
A ibu es N In %
Gende
Female 21 40.4%
Male 31 59.6%
Age
Unde 18 3 5.8%
Be ween 18 and 36 34 65.4%
Be ween 37 and 46 10 19.2%
47 onwa ds 5 9.6%
Wo k expe ience
Be ween 3 and 5 25 48.2%
Be ween 6 and 10 yea s 20 38.4%
11 yea s o mo e 7 13.4%
Highes educa ion
Bachelo ’s deg ee 16 30.7%
Mas e ’s deg ee 32 61.5%
Ph.D. o highe 4 7.8%
Yea s in cu en i m
Be ween 1 and 2 yea s 9 17.3%
Be ween 3 and 5 yea s 34 65.4%
Be ween 6 and 10 yea s 7 13.5%
11 yea s o mo e 2 3.8%
Top 3 indus ies and emaining
Compu e and Technology 10 19.2%
Finance and Economics 11 21.2%
Pha ma 10 19.2%
O he 21 40.4%
indus y is a po en ially aluable business oppo uni y. This
was u he emphasized by he no e ha ini ial analyses ha e
no e ealed any ed lags o en y and ha he i m is no
cons ain by capi al. A he end o he desc ip ion, he head
o business de elopmen ecei ed he ask o assess whe he
o en e he ela ed indus y o no .
To ensu e ha pa icipan s did no conduc he expe i-
men in pa allel wi h o he ac i i ies, igno ing ele an ac-
o s and e ms, I in eg a ed a ime which allowed hem o
p oceed wi h he ques ionnai e only a e hi y seconds o
eading and an a en ion check ha had o be passed o con-
inue pa icipa ing in he su ey. The check was illus a ed
by a mul iple-choice ques ion ha asked he s a egis s wha
he epo indica ed (co ec answe : i ms wi h p io expe i-
ence in ela ed indus ies a e much mo e likely o succeed in
a new indus y). I he w ong answe was selec ed, he su -
ey was cancelled, o he wise pa icipan s we e o wa ded o
he nex page which in ol ed de ailed ins uc ions ega d-
ing he a ying p o iles, hei assessmen , and he adap ed
scale. Mo eo e , he page included an o e iew o he a -
ibu es’ le els’ de ini ions, which a e summa ized in able 2.
The explana ion page was ollowed by he expe imen ask
(i.e., a ying p o iles) and ended wi h he pos expe imen al
ques ionnai e. Figu e 11 summa izes he su ey p ocedu e.
To make su e ins uc ions we e clea and he de ined a -
ibu es we e ep esen a i e, I conduc ed a p e- es wi h wo
PhD s uden s (s a egy ocus and ma ke -o ien ed co po a e
managemen ) and wo senio manage s in he ield o s a e-
gic inno a ion.
Dependen a iable –I de ined s a egic en y as he
poin in ime we e he i m ini ia ed he sales o i s p od-
uc s and/o se ice in he new indus y (Domu a h & Pa zel ,
2016). Based on he a ying hypo he ical scena ios, s a e-
gis s we e asked o e alua e he a ac i eness o en y on
a 7-poin Like scale. The scale anged om de ini ely no
en e (1) o de ini ely en e (7).
Independen a iables –The p o iles o my conjoin ex-
pe imen consis ed o ou a ibu es. This numbe is consis-
en wi h o he conjoin s udies and he indings o W igh
(1975) showing ha a high numbe o a ibu es (eigh o
mo e) dis o s pa icipan s’ ue decision-making p inciples
as his emp s hem o use simpli ying ac ics.
Two o he ou a ibu es in my expe imen desc ibed he
s a egis ’s i m’s dynamic capabili ies (abso p i e capaci y,
new p oduc de elopmen capabili y), one a ibu e e lec ed
ano he o ganiza ional elemen (in e nal knowledge sha -
ing), and one he cha ac e is ics o he en i onmen in he
new indus y (en i onmen al dynamism). In line wi h p e-
ious conjoin analyses, I di e en ia ed be ween wo le els
when desc ibing he a ibu es (e.g., Domu a h and Pa zel ,
E. Schul e genann Kulkmann /Junio Managemen Science 9(4) (2024) 2050-20812070
Table 2: Decision a ibu e de ini ions
A ibu e [le el]Desc ip ion
Abso p i e capaci y
[High]You company’s abili y o ecognize he alue o new, ex-
e nal in o ma ion, assimila e i , and apply i o comme -
cial ends is e y well de eloped
[Low]You company’s abili y o ecognize he alue o new, ex-
e nal in o ma ion, assimila e i , and apply i o comme -
cial ends is only de eloped o a limi ed ex en
New p oduc de elopmen capabili y
[High]You company cons an ly a emp s o pionee and o be
a he cu ing edge o echnology in i s new p oduc and
se ice in oduc ions
[Low]You company a ely a emp s o pionee and o be a he
cu ing edge o echnology in i s new p oduc and se ice
in oduc ions
En i onmen al dynamism
[High]The new po en ial ma ke is highly ola ile in e ms o he
a e and amoun o change and he ac ions o compe i o s
and cus ome s a e e y di icul o p edic
[Low]The new po en ial ma ke is e y s able in e ms o he
a e and amoun o change and he ac ions o compe i o s
and cus ome s can be p edic ed e y well
Knowledge sha ing
[Ex ensi e]P ocesses o sha ing in o ma ion e ec i ely among indi-
iduals, decision make s, and in e nal uni s a e e y well
de eloped in you i m
[Limi ed]P ocesses o sha ing in o ma ion e ec i ely among indi-
iduals, decision make s, and in e nal uni s a e only de-
eloped o a limi ed ex en in you i m
Figu e 11: Online su ey p ocedu e
2016; Haynie e al., 2009; McMullen and Shephe d, 2006).
As shown in able 2, abso p i e capaci y, new p oduc de-
elopmen capabili y, and en i onmen al dynamism can be
ei he high o low. Knowledge sha ing in he s a egis ’s i m
can be ei he ex ensi e o limi ed.
Con ol a iables –In o al, I con olled o i e ac o s.
Age – Fi s , I con olled o he age o he su ey pa ici-
pan s since, among o he s, Sche e e al. (1990) ound ha
di e ences in age can esul in di e en en ep eneu ial be-
ha iou and s a egic decision-making in gene al.
E. Schul e genann Kulkmann /Junio Managemen Science 9(4) (2024) 2050-2081 2071
Wo k expe ience – Fu he , nume ous s udies ound yea s
o wo k expe ience o impac s a egic posi ioning decisions
and inno a ion beha iou (e.g., Nu uzzaman e al., 2019;
Shao e al., 2020). Hence, I also con olled o he o al num-
be o wo k expe ience o he s a egis . A leas one o wo
c i e ia had o be me o he wo k expe ience o be consid-
e ed in he s udy. Fi s , he p io posi ion o he s a egis had
o be in he ield o business de elopmen , s a egic g ow h,
o inno a ion s a egy and/o second, i had o be a highe -
o de posi ion. Fo ins ance, I did no include wo k expe i-
ence as a PR assis an in a newspape since I expec his wo k
expe ience o be i ele an o e alua ing he a ac i eness
o s a egic en y.
Field o s udy in educa ional backg ound – Since, o exam-
ple, Colombo and G illi (2005) a gued ha specializa ion in
speci ied educa ional ields a e associa ed wi h s a egic de-
cisions, I u he con olled o s a egis s’ educa ional back-
g ound in business and economics, enginee ing, and na u-
al sciences (ca ego ies adap ed om Domu a h and Pa zel
(2016)). A bina y coded a iable was used o each o he
ca ego ies ( emaining educa ional ields as e e ence ca e-
go y).
Indus y ocus – I also con olled o he indus y he
s a egis s cu en ly wo k in. Some indus y cha ac e is ics
a e mo e likely o equi e s a egic expansions in o de o
s ay compe i i e and hus, his may in luence he s a egis ’s
decision-making p ocess (Zacha akis & Shephe d, 2018).
This is pa icula ly he case o high echnology indus ies,
such as compu e and echnology, pha ma, and enginee ing.
As wi h educa ional backg ound, I used a bina y coded a i-
able o each o he h ee indus ies and he o he indus ies
se ed as e e ence ca ego ies.
Yea s in company – Finally, I included he yea s he s a e-
gis has wo ked o his o he cu en employe in my con-
ol a iables. S a egic decision-making is in luenced by
p io expe ience in compa able con ex s (Ba on & Ensley,
2006; Domu a h & Pa zel , 2016). The e o e, as i m speci ic
knowledge ega ding e.g., inno a i e beha iou , p ocesses,
and isk p opensi y o boa d membe , I did no only accoun
o gene al wo k expe ience bu also wo k expe ience wi hin
he cu en i m.
Since expe imen al esea ch is based on hypo he ical sce-
na ios, i is a challenge o selec a iables ha a e also aken
in o accoun by he expe imen ’s pa icipan s in eal-li e de-
cisions (Domu a h & Pa zel , 2016; Zacha akis & Shephe d,
2018). To educe his isk, I only de ined a ibu es which el-
e ance o alue c ea ion h ough knowledge and esou ces
is unde pinned by a s ong heo e ical ounda ion (Aud e sch
& Beli ski, 2023; Deeds e al., 2000; Schilke, 2014). To u -
he secu e he in o ma i e alue o my a iables, I adap ed
he app oach o Domu a h and Pa zel (2016) and asked
he s a egis s o assess he impo ance o each o he in-
dependen a iables o hei eal-li e decisions in a pos -
expe imen al ques ionnai e. Pa icipan s had o a e he pe -
cei ed impo ance o eal-li e s a egy decisions on en y o
each a ibu e on a se en-poin Like scale (1-no impo an
a all, 7-highly impo an ). Fo all a iables, he a e ages
answe s exceeded he scale mean o 3.5 (i.e., 5.5 o abso p-
i e capaci y, 5.1 o new p oduc de elopmen capabili y, 4.4
o in e nal knowledge sha ing, and 3.8 o en i onmen al
dynamism). The e o e, based on sel - epo ing o he pa -
icipan s, he ele ance o he a ibu es ega ding s a egic
en y decisions is con i med (a leas o a ce ain ex en ).
3.5. Da a analysis
My da a analysis was done ia he so wa e R-s udio. Fol-
lowing scale and da a eliabili y checks, I es ed o my hy-
po heses using he lme4-package o mul ile el models. R-
s udio is pa icula ly sui able o my se ing, as i allows o
plo and in e p e in e ac ion e ms which we e inco po a ed
in hypo hesis 2a, 2b, 3a, and 3b.
4. Resul s
The ollowing sec ion summa izes he esul s o my da a
analysis including co ela ions and indings o he hie a chi-
cal linea modeling analysis. Fu he , plo s o explain in e -
ac ion e ec s a e p esen ed.
4.1. Co ela ions
Co ela ions o he Le el 2 a iables a e summa ized in
able 3. As desc ibed in sec ion 3.3, I adap ed an o hogo-
nal ull ac o ial design o my conjoin expe imen . Hence,
co ela ions be ween Le el 1 a iables a e ze o and he e-
o e no included in he able. Co ela ions be ween Le el 1
and Le el 2 a iables a e also excluded since all pa icipan s
we e p o ided wi h he same p o iles, and hence, Le el 1 a -
ibu e le els do no di e be ween su ey pa icipan s and
do no co ela e wi h Le el 2 a ibu e le els. Since no alue
o he co ela ion be ween he emaining a iables exceeds
0.7, mul icollinea i y is no a conce n o my u he analy-
ses. This was u he suppo ed by a VIF analysis (all alues
<10) (e.g., Hai , 2011). An analysis o he co ela ion ma ix
based on he wo k o J. Cohen (1988) e ealed no s ong co -
ela ions be ween he Le el 2 a iables (| | <0.5). The e a e
mode a e posi i e co ela ions be ween age and wo k expe-
ience and yea s in a company, and educa ional backg ound
and indus y ocus. Howe e , hey do no cons i u e a p ob-
lem o u he e alua ions.
4.2. Resul s o he hie a chical linea modeling (HLM) anal-
ysis
Gi en ha he e a e 32 decisions o each o he 52 pa -
icipan s o my s udy, he o al numbe o 1,664 da a poin s
in my analysis a e no independen o each o he (32 de-
cisions a e nes ed wi hin each s a egis ). To ake in o ac-
coun he nes ed da a s uc u e, I used hie a chical linea
modeling (HLM). Since his app oach accoun s o po en ial
he e oskedas ici y o da a and o au oco ela ion, i is well
sui ed o my da a analysis (Osbo ne, 2000). A andom coe -
icien model was speci ied o accoun o be ween-indi idual
a iance (i.e., bo h in e cep s and slopes could a y be ween
indi iduals) (e.g. Domu a h and Pa zel , 2016; Snijde s and
E. Schul e genann Kulkmann /Junio Managemen Science 9(4) (2024) 2050-20812072
Table 3: Co ela ions
Va iables 1 2 3 4 5 6 7 8 9
1 Age 1.000
2 Business educa ion -0.029 1.000
3 Enginee ing educa ion 0.152 -0.279** 1.000
4 Science educa ion 0.033 -0.388** -0.291** 1.000
5 Enginee ing indus y 0.139 -0.052 0.368** -0.064 1.000
6 IT indus y 0.054 -0.025 -0.130 0.457** -0.179 1.000
7 Pha ma indus y 0.036 -0.084 -0.165 -0.097 -0.118 -0.198 1.000
8 Wo k expe ience 0.454** -0.069 0.009 0.137 0.166 0.178 -0.148 1.000
9 Yea s in company 0.543*** -0.143 -0.031 0.287** 0.064 0.212** -0.033 0.554** 1.000
* p<.05, ** p<.01, *** p<.001
No e: N=52 s a egis s
IT, in o ma ion echnology; SD, s anda d de ia ion.
Boske , 1999). In he ollowing, I epo he coe icien (in-
cluding he le el o signi icance [indica ed by he as e isks]),
and he obus s anda d e o s o all a iables. Le el 1 a i-
ables include he ou e alua ion c i e ia, i.e., abso p i e ca-
paci y, new p oduc de elopmen capabili y, en i onmen al
dynamism, and in e nal knowledge sha ing, and hei in-
e ac ion e ms (abso p i e capaci y wi h en i onmen al dy-
namism and in e nal knowledge sha ing; new p oduc de el-
opmen capabili y wi h en i onmen al dynamism and in e -
nal knowledge sha ing). A le el 2, I en e ed he con ol a i-
ables o accoun o di e ences be ween pa icipa ing s a e-
gis s.
Null model (model 1) –HLM models accoun s o a i-
ance ha occu s a di e en le els o analysis since i consid-
e s nes ed da a s uc u es (B yk & Raudenbush, 1992; Ho -
mann, 1997). In my expe imen , a iance a he lowes le el
(i.e., le el 1) would be isible in a iance in he ou come
a iable a ac i eness o s a egic en y, while he a iance
among subjec s a he highe le el (i.e., le el 2) would e-
la e o di e ences be ween s a egis s. To assess whe he
he e is e idence o clus e ing o da a in e ms o my ou come
a iable, I i s es ed a model wi h no p edic o s (i.e., null
model). Since clus e ing e ec s can p oduce biases in pa-
ame e es ima es and s anda d e o s, which in u n lead o
e oneous conclusions in single le el models, he null model
is an impo an p e equisi e o assessing whe he a mul i-
le el app oach is wa an ed. Resul s o he null model which
was used o calcula ing he in aclass co ela ion (ICC) a e
shown in model 1 ( able 4). In HLM, he ICC se es as a ba-
sis o quan i ying he dis ibu ion o a ia ion a he di e en
le els o he hie a chy. An ICC o 0 means he a ia ion occu s
exclusi ely a he indi idual le el, while an ICC o 1 indica es
he a ia ion occu s exclusi ely a he g oup le el (Aguinis e
al., 2013; Domu a h & Pa zel , 2016). In my se ing, he ICC
akes a alue o .058, indica ing ha 5.8% o o al a ia ion in
my dependen a iable is accoun ed o by indi idual di e -
ences. Hedges and Hedges and Hedbe g (2007) no e ha he
ICC in educa ional and s a egy esea ch o en anges om
.05 o .20 which is also con i med in he book on mul ile el
modeling echniques by Heck e al. (2013) who s a e ha .05
is equen ly conside ed a ough cu -o o e idence o sub-
s an ial clus e ing. Howe e , e en i ial se s o clus e s can
s ill ha e a conside able impac on conclusions when unning
single le el eg essions (Pi uch & S e ens, 2015; Sca iano &
Da enpo , 1987). These numbe s demons a e ha he e
is su icien a iabili y among indi iduals in my s udy which
jus i ies he u iliza ion o HLM.
Le el 1 main e ec s and le el 2 con ol a iables
(model 2) –In model 2, I included he con ol a iables
which we e in oduced in sec ion 3.4. As can be seen in
able 4, only one o my con ol a iables (i.e., yea s in com-
pany) is signi ican beyond he .05 le el, and hus explains
a iance in he s a egis s’ assessmen s o s a egic en y
(coe icien =0.209). This is in line wi h analyses o o he
schola s who a gue ha indus ies cha ac e ized by s ong
compe i ion and echnological p og ess ypically equi e
s a egic ac ions o keep up wi h compe i o s (Zacha akis
& Shephe d, 2018). Fu he , I expanded my analysis in
model 2 by in oducing he le el 1 a iables, i.e., abso p i e
capaci y, new p oduc de elopmen capabili y, en i onmen-
al dynamism, and in e nal knowledge sha ing. As p esen ed
in able 4, h ee ou o he ou assessmen c i e ia a le el
1 exhibi s a is ically signi ican de ia ions om ze o. In
pa icula , s a egis s a e s a egy en y as mo e a ac i e
i he i m has (1) high abso p i e capaci y (coe icien =
1.742, p <.001), (2) high new p oduc de elopmen capa-
bili y (coe icien =1.832, p <.001), and i (3) p ocesses o
sha ing in o ma ion e ec i ely wi hin he i m a e e y well
de eloped (coe icien =0.679, p <.001). Only he ou h
a ibu e, i.e., en i onmen al dynamism shows a nega i e
coe icien (-0.308, p <.05). O e all, he esul s suppo
hypo hesis 1a) and 1b) since bo h he posi i e ela ionship
be ween abso p i e capaci y and en y assessmen and be-
ween new p oduc de elopmen and en y assessmen a e
signi ican beyond 0.05.
Le el 1 in e ac ion e ec s (model 3) –Model 3 ex ends
model 2 by including in e ac ion e ec s. Speci ically, I exam-
ined he in e ac ion o en i onmen al dynamism wi h abso p-
E. Schul e genann Kulkmann /Junio Managemen Science 9(4) (2024) 2050-2081 2073
Table 4: S a egis s’ assessed en y a ac i eness (models)
E alua ion C i e ia Null model Le el 1 main e ec s Le el 1 in e ac ions
(Model 1) Le el 2 con ol a iables (Model 3)
(Model 2)
Coe icien Rob. SE Coe icien Rob. SE Coe icien Rob. SE
In e cep 4.06*** 0.07 4.06*** 0.07 4.06*** 0.07
Le el 2
Age -0.18†0.10 -0.18†0.10
Business educa ion 0.11 0.17 0.11 0.17
Enginee ing educa ion 0.12 0.21 0.12 0.21
Science educa ion 0.11 0.19 0.11 0.19
Enginee ing indus y 0.23 0.23 0.23 0.23
IT indus y -0.00 0.11 -0.00 0.11
Pha ma indus y 0.33†0.21 0.33†0.21
Wo k expe ience -0.11 0.08 -0.11 0.08
Yea s in company 0.21** 0.07 0.21** 0.07
Le el 1
Abso p i e capaci y AC 1.74*** 0.06 1.74*** 0.06
New p oduc de elopmen capabili y NPDC 1.83*** 0.08 1.83*** 0.08
En i onmen al dynamism ED -0.30* 0.12 -0.30* 0.12
In e nal knowledge sha ing IKS 0.69*** 0.05 0.69*** 0.05
AC ×ED -0.18* 0.08
AC ×IKS -0.02 0.08
NPDC ×ED -0.20** 0.07
NPDC ×IKS 0.20** 0.07
Va iance componen s
Le el 1 a iance 2.73 0.64 0.63 ∆1.36%‡
Le el 2 a iance 0.17 0.20 0.20
ICC§0.06
Pseudo R2Le el 1¶0.66 0.66
Pseudo R2Le el 2¶0.08 0.08
†p<.1, *p<.05, **p<.01, ***p<.001
No e: N=1,664 a he assessmen le el; N =52 a he indi idual le el
‡This alue highligh s he p opo iona e inc ease in explained a iance a ained by including in e ac ions a Le el 1 wi hin he model (de i ed om he
educ ion in e o a iance a Le el 1 due o inclusion o independen a iables when compa ed o he p e ious model as a e e ence poin )
§ICC =Le el 2 a iance/Le el 1 a iance =.165/(.165 +2.733)
¶Pseudo R2based on Snijde s and Boske (1999)
IT, in o ma ion echnology; Rob. SE, obus s anda d e o ; AC, abso p i e capaci y; NPDC, new p oduc de elopmen capabili y; ED, en i onmen al
dynamism; IKS, in e nal knowledge sha ing
i e capaci y and new p oduc de elopmen capabili y and
he one o in e nal knowledge sha ing wi h abso p i e capac-
i y and new p oduc de elopmen capabili y. I p edic ed ha
en i onmen al dynamism s eng hens he posi i e in luence
o abso p i e capaci y on s a egis s’ assessmen o en y (hy-
po hesis 2a) and weakens he posi i e in luence o new p od-
uc de elopmen capabili y (hypo hesis 2b). As o in e nal
knowledge sha ing, I assumed ha his would ein o ce bo h
he posi i e e ec o abso p i e capaci y and new p oduc
de elopmen on s a egis s’ en y e alua ion (hypo heses 3a,
3b). In able 4i can be seen ha he e a e signi ican in e -
ac ions be ween abso p i e capaci y and en i onmen al dy-
namism (coe icien =-0.183, p <.05), new p oduc de el-
opmen and en i onmen al dynamism (coe icien =-0.205,
p<.01), and new p oduc de elopmen and in e nal knowl-
edge sha ing (coe icien =0.203, p <.01).
To speci y he ype o signi ican le el 1 in e ac ions, I ol-
lowed he ad ice o J. Cohen (1988) o plo he in e ac ions.
On a y axis o assessed en y a ac i eness and an x axis
o abso p i e capaci y/new p oduc de elopmen capabil-
i y, I plo ed low and high le els o en i onmen al dynamism
and in e nal knowledge sha ing (sepa a e lines). The plo
o he in e ac ion be ween abso p i e capaci y and en i on-
men al dynamism, illus a ed in igu e 12, shows ha en y
a ac i eness inc eases wi h s onge pe cei ed abso p i e
capaci y. Howe e , his ela ionship is weake o high le els
o en i onmen al dynamism ( la e line). Thus, i does no
suppo hypo hesis 2a. Figu e 13 plo s he in e ac ion e ec s
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