Huang, Fei ei; Luo, Xingwu; Xiao, Mimi; Dong, Wenhao
A icle
Dual pe o mance o business model inno a ion in
eme ging ma ke en e p ises: A con igu a ional app oach
Jou nal o Inno a ion & Knowledge (JIK)
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Dual pe o mance o business model inno a ion in eme ging ma ke
en e p ises: A con igu a ional app oach
Fei ei Huang
a
, Xingwu Luo
b
, Mimi Xiao
c,*
, Wenhao Dong
a
a
School o Business, Nanjing Uni e si y, China
b
School o Managemen , Zhejiang Uni e si y o Finance & Economics, China
c
School o Economics and Managemen , Nanjing Uni e si y o Science and Technology, China
ARTICLE INFO
JEL code:
D22
D23
Keywo ds:
Business model inno a ion
Eme ging ma ke en e p ises
Subs an ial pe o mance
Symbolic pe o mance
Fuzzy-se quali a i e compa a i e analysis
ABSTRACT
Business model inno a ion (BMI) is a c i ical d i e o en e p ise g ow h, ye i s implemen a ion in eme ging
ma ke en e p ises (EMEs) emains unde explo ed. To b idge his gap, ou s udy adop s a con igu a ional
app oach o sys ema ically in es iga e he complex causal ela ionships among hema ic BMI, s a egic o ien-
a ions, and en i onmen al cha ac e is ics, while conside ing he dual pe o mance impe a i es—subs an i e
and symbolic—o EMEs. Using uzzy-se quali a i e compa a i e analysis on EMEs om China, we e eal h ee
key indings: (1) Pionee ing and pe ec ing BMI ope a es h ough dis inc mechanisms. Pionee ing BMI enhances
subs an i e pe o mance by os e ing di e en ia ion ad an ages, whe eas pe ec ing BMI imp o es symbolic
pe o mance by e ining exis ing models o be e mee a icula ed cus ome needs. (2) In pu suing dual pe -
o mance ou comes, pionee ing and pe ec ing BMI a e mu ually ein o cing. Thei syne gis ic in eg a ion is
essen ial o achie ing dual pe o mance objec i es. (3) Dual BMI alone is insu icien o ealize dual pe o -
mance. Ins ead, alignmen wi h s a egic o ien a ion and en i onmen al cha ac e is ics is essen ial. Speci ically,
he syne gy o digi al o ien a ion enhances i ms’ subs an i e pe o mance, whe eas he in e play o policy
o ien a ion and en i onmen al muni icence enhances symbolic pe o mance.
In oduc ion
Eme ging ma ke en e p ises (EMEs) ace mul iple p essu es,
including ins i u ional de iciencies, esou ce sca ci y, and apidly
e ol ing socie al demands (Ka ou os e al., 2015), which challenge he
sus ainabili y o adi ional business p ac ices. Business model inno a-
ion (BMI) p o ides a s a egic a enue o EMEs by ede ining alue
c ea ion and deli e y mechanisms, enabling hem o pene a e new
ma ke s, ad ance echnological de elopmen , and unlock he g ow h
po en ial o exis ing businesses (Guo e al., 2022). Howe e , EMEs ace a
dual dilemma in BMI implemen a ion. They encoun e subs an i e
pe o mance p essu es om echnological and indus y unce ain ies
(Bouncken & K aus, 2013), equi ing inno a ion and di e en ia ion o
d i e inancial g ow h (Ka ou os e al., 2015; Po e , 1996). A he same
ime, eme ging echnologies and nascen indus ies o en s uggle wi h a
legi imacy de ici . Du ing he ea ly s ages o ma ke en y, i ms ypi-
cally lack c edibili y, c ea ing symbolic pe o mance challenges in
es ablishing legi imacy (Zhang & Whi e, 2016). To es ablish legi imacy,
i ms mus align wi h socie al no ms and ins i u ional expec a ions
(Meye & Nguyen, 2005; Xu e al., 2025), bu excessi e con o mi y may
hinde inno a ion and di e en ia ion. This ension be ween dis inc-
i eness and con o mi y p esen s a key challenge: balancing economic
alue c ea ion wi h legi imacy impe a i es o achie e dual pe o mance
(Zhao e al., 2017).
Despi e i s signi icance, exis ing esea ch has ye o ully elucida e
how BMI econciles hese compe ing demands o d i e he g ow h o
EMEs. Fi s , in e ms o BMI pe o mance, exis ing s udies ocus p i-
ma ily on inancial pe o mance me ics, ocusing less on symbolic
pe o mance (Ilyas e al., 2024; Men e e al., 2024). Howe e , in
eme ging ma ke s, a company’s success is no de e mined solely by
economic e u ns; i also equi es legi imacy h ough BMI o educe
ins i u ional unce ain y and gain long- e m compe i i e ad an age. Fo
ins ance, pee - o-pee (P2P) lending pla o ms, as an eme ging inancial
inno a ion model, ini ially a ac ed a la ge numbe o use s and in-
es o s, achie ing apid inancial g ow h. Howe e , due o an impe ec
egula o y en i onmen and low social us , many pla o ms ul ima ely
collapsed. The e o e, ocusing solely on he inancial pe o mance o
BMI, while neglec ing legi imacy and ins i u ional adap abili y, may
* Co esponding au ho .
E-mail add esses: [email p o ec ed] (F. Huang), [email p o ec ed] (X. Luo), [email p o ec ed] (M. Xiao), [email p o ec ed] (W. Dong).
Con en s lis s a ailable a ScienceDi ec
Jou nal o Inno a ion & Knowledge
jou nal homepage: www.else ie .com/loca e/jik
h ps://doi.o g/10.1016/j.jik.2025.100755
Recei ed 25 No embe 2024; Accep ed 9 June 2025
Jou nal o Inno a ion & Knowledge 10 (2025) 100755
A ailable online 25 June 2025
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unde mine he long- e m su i al capabili ies o en e p ises.
Second, exis ing s udies mainly adop a ansac ion-based pe spec-
i e, o e looking he embeddedness o BMI in eme ging ma ke ins i-
u ional con ex s (Ey ing e al., 2011; Luo e al., 2022). Fo example,
Ami and Zo ’s (2001) NICE (no el y, lock-in, complemen a i ies, e i-
ciency) amewo k ocuses on ansac ion cos op imiza ion bu assumes
a s able ins i u ional en i onmen , c ea ing heo e ical ension wi h
BMI’s con ex -dependen na u e (Ha gadon & Douglas, 2001). In
eme ging ma ke s, ins i u ional acuums and de ec s cons ain i ms’
s a egic choices, making legi imacy-building h ough BMI mo e c i ical
han jus cos educ ion (Luo e al., 2022). Fo example, he Indian
company Flipka aced us issues due o weak elec onic paymen
in as uc u e. In esponse, i de eloped a hyb id paymen sys em
combining cash-on-deli e y and mobile walle s, u ning ins i u ional
cons ain s in o a compe i i e ad an age. This illus a es ha EMEs
o en adap and shape hei ins i u ional en i onmen , a he han
me ely op imizing ansac ions.
Finally, exis ing esea ch has la gely o e looked he mul i ac o
syne gis ic mechanisms ha d i e success ul BMI (Lepp¨
anen e al.,
2023). While BMI is gene ally linked o enhanced i m pe o mance,
some companies ha e wi nessed pe o mance declines ollowing i s
implemen a ion (Ilyas e al., 2024; Wang e al., 2022). Resea ch has
ound ha singula ocus on BMI is unlikely o lead o high pe o mance,
as i p ima ily emphasizes alue c ea ion wi hou necessa ily enhancing
business model p o i abili y. Ins ead, achie ing subs an ial imp o e-
men s equi es addi ional en e p ise s a egies ha ocus on alue cap-
u e o con e inno a ion in o sus ainable inancial gains (Lepp¨
anen
e al., 2023).
To add ess hese gaps, we p opose he ollowing esea ch ques ion:
How can BMI coo dina e in e nal and ex e nal ac o s o achie e dual
pe o mance in EMEs? To answe his ques ion, we adop ed he hema ic
BMI amewo k p oposed by Luo e al. (2022), which is speci ically
designed o he unique con ex o EMEs—di e en ia ing be ween pio-
nee ing and pe ec ing BMI and o e ing a obus analy ical pe spec i e.
Addi ionally, we de eloped a comp ehensi e con igu a ional model o
cap u e he syne gis ic e ec s among business model alue d i e s,
s a egic o ien a ions, and en i onmen al cha ac e is ics. To empi ically
alida e his model, we employed uzzy-se quali a i e compa a i e
analysis ( sQCA). This me hod is pa icula ly e ec i e o unco e ing
complex causal ela ionships in he con ex s o limi ed sample sizes and
he e ogeneous condi ions. Using EMEs in China— he wo ld’s la ges
eme ging ma ke —as ou sample, we conduc ed an empi ical
in es iga ion.
This s udy’s co e con ibu ion lies in he ad ancemen o BMI pe -
o mance measu emen s by adop ing a dual amewo k (subs an i e and
symbolic pe o mance), mo ing beyond he adi ional inancial ocus.
Addi ionally, we alida ed he dis inc mechanisms o pionee ing and
pe ec ing BMI in eme ging ma ke s and hei di e en ia ed impac on
dual pe o mance. Speci ically, pionee ing BMI d i es subs an i e pe -
o mance by explo ing new echnologies, ma ke s, and alue p oposi-
ions. I es ablishes new ansac ion models and compe i i e ules in
eme ging ma ke s, helping i ms secu e i s -mo e ad an ages and
os e economic g ow h. Meanwhile, pe ec ing BMI enhances symbolic
pe o mance by op imizing business p ocesses, s eng hening s ake-
holde ela ionships, and aligning wi h ins i u ional equi emen s,
he eby secu ing social accep ance.
Finally, we unco e ed he syne gis ic mechanisms o BMI, empha-
sizing ha pionee ing and pe ec ing BMI mus align wi h s a egic
o ien a ion and en i onmen al ac o s o d i e i m g ow h. Fo
ins ance, digi al o ien a ion s eng hens compe i i e ad an age, while
policy o ien a ion and en i onmen al muni icence p o ide legi imacy
suppo o inno a ion. Ou indings deepen BMI heo y and o e s a-
egic insigh s o EMEs o e ec i ely le e age BMI in dynamic ma ke
en i onmen s.
A con igu a ion app oach o business model inno a ion o EMEs
EMEs na iga e he dual ension be ween dis inc i eness and con-
o mi y, equi ing BMI o d i e subs an i e pe o mance, such as
inancial g ow h, and o enhance symbolic pe o mance, including
legi imacy and social ecogni ion (Shi oko a e al., 2020; Zhang &
Whi e, 2016). Subs an i e pe o mance e e s o he gene a ion o objec-
i ely measu able inancial ou comes o he es ablishmen o a
compe i i e ma ke posi ion. This pe o mance dimension p o ides
di ec eedback on EMEs’ compe i i e e ec i eness (Ilyas e al., 2024;
Pede sen e al., 2018). In con as , symbolic pe o mance pe ains o he
pe cei ed legi imacy o a i m in he eyes o s akeholde s, e lec ing i s
alignmen wi h ins i u ional no ms and expec a ions. This dimension
signi ies s akeholde s’ con idence in he i m’s long- e m iabili y and,
o some ex en , ep esen s he s a egic esou ces ha he i m may
access in he u u e (Zimme man & Zei z, 2002). Toge he , subs an i e
and symbolic pe o mance cap u e he p esen and u u e g ow h a-
jec o ies o eme ging en e p ises, unde sco ing hei indispensable ole
in he sus ainable de elopmen o EMEs.
Eme ging ma ke s, cha ac e ized by he coexis ence o abundan
ma ke oppo uni ies and ins i u ional de iciencies, c ea e a con ex o
unique ma ke easibili y and ins i u ional legi imacy o BMI (Jia e al.,
2012; Wang e al., 2022). Howe e , a business model does no unc ion
in isola ion; a he , i cons i u es an in e connec ed ac i i y sys em ha
ex ends beyond i m bounda ies (Zo & Ami , 2010). I s success ul
implemen a ion elies on he dynamic in e play and coe olu ion be-
ween i ms and hei in e nal and ex e nal en i onmen s
(Casadesus-Masanell & Zhu, 2013; Lepp¨
anen e al., 2023). F om a
con igu a ional pe spec i e, wo key conside a ions o BMI heme
design eme ge: (1) complemen a i y o in e nal con igu a ions (Ches e
e al., 2019; Ghezzi & Ca allo, 2020) and (2) alignmen wi h ex e nal
en i onmen al condi ions (Lepp¨
anen e al., 2023; Wang e al., 2022).
In e nal con igu a ions de ine how i ms c ea e alue by op imizing
esou ce alloca ion and ac i i y design (Lepp¨
anen e al., 2023). To
enhance i m pe o mance, managemen mus es ablish a con igu a ion
ha maximizes syne gies, ha is, while a speci ic solu ion may appea
subop imal when conside ed in isola ion, i can cons i u e an op imal
decision a he sys em le el (A gy es & Liebeskind, 1999; Zhao e al.,
2017). Wi hin in e nal con igu a ions, we ocus on s a egic o ien a ion,
as i di ec ly shapes a i m’s compe i i e logic and se ice model (Zhou
e al., 2005). Speci ically, we examine policy and digi al o ien a ion, as
hese wo s a egic oci add ess he co e challenges aced by EMEs in
na iga ing ins i u ional en i onmen s and ma ke compe i ion. Policy
o ien a ion enables i ms o le e age go e nmen suppo o b idge
ins i u ional acuums o access sca ce esou ces, he eby enhancing
symbolic pe o mance (Ha gadon & Douglas, 2001). In con as , digi al
o ien a ion d i es subs an i e pe o mance by imp o ing ope a ional
e iciency and use expe ience h ough echnological inno a ion (Li
e al., 2024; T¨
ausche & Laudien, 2018). This complemen a i y posi ions
s a egic o ien a ion as a c i ical b idge linking a i m’s in e nal capa-
bili ies o dual pe o mance objec i es, ein o cing he in e connec ed
ole o policy and digi al s a egies in achie ing economic alue c ea ion
and legi imacy.
Con a ily, ex e nal alignmen emphasizes ha BMI mus be
cong uen wi h ex e nal en i onmen al cha ac e is ics o ensu e ha
alue-c ea ing ac i i ies a e e ec i ely adap ed o he ex e nal con ex
and ansla ed in o angible pe o mance ou comes (Lepp¨
anen e al.,
2023; Wang e al., 2022). In eme ging ma ke s, en i onmen al muni i-
cence and en i onmen al compe i i eness a e wo c i ical dimensions o
ex e nal en i onmen s. En i onmen al muni icence e lec s he deg ee o
socie al accep ance and ins i u ional suppo a ailable o i ms, di ec ly
in luencing hei abili y o achie e symbolic pe o mance (Fainshmid
e al., 2019). Fo ins ance, i ms ope a ing in mo e inclusi e egions may
ind i easie o gain legi imacy and social ecogni ion, as hese en i-
onmen s a e mo e ecep i e o inno a ion. Con e sely, en i onmen al
compe i i eness in luences subs an i e pe o mance by d i ing i ms o
F. Huang e al.
Jou nal o Inno a ion & Knowledge 10 (2025) 100755
2
inno a e and op imize esou ce alloca ion. In highly compe i i e en i-
onmen s, i ms mus adop di e en ia ion s a egies o cos leade ship
app oaches o sus ain hei compe i i e ad an age (Po e , 1996).
The e o e, examining en i onmen al muni icence and compe i i eness
p o ides aluable insigh s in o how i ms na iga e complex and dy-
namic ma ke condi ions o achie e dual pe o mance.
Building on he abo e analysis, we adop a con igu a ional app oach
o sys ema ically examine how BMI acili a es dual pe o mance in EMEs
h ough in e nal and ex e nal syne gy mechanisms. Ra he han ea ing
BMI as an independen con ibu o o i m pe o mance, his app oach
emphasizes he in e ac ions be ween a i m’s business model design and
key con ex ual ac o s. Speci ically, we explo e he syne gis ic e ec s o
BMI—including pionee ing and pe ec ing BMI—in conjunc ion wi h
s a egic o ien a ions (policy and digi al o ien a ion) and en i onmen al
cha ac e is ics (en i onmen al muni icence and en i onmen al
compe i i eness). To cla i y he mechanisms behind subs an i e and
symbolic pe o mance, his s udy adop s he compe i i e ad an age and
ins i u ional heo ies as i s ounda ions. The compe i i e ad an age
heo y explains how syne gis ic e ec s help i ms build unique ad an-
ages and enhance economic ou comes, while he ins i u ional heo y
examines how syne gy enables i ms o gain legi imacy and s eng hen
ex e nal ecogni ion (Po e , 1996; Suchman, 1995; Zhao e al., 2017).
The analy ical amewo k is illus a ed in Fig. 1, and he ollowing
sec ions p o ide a de ailed explana ion o hese componen s.
BMI and dual pe o mance in EMEs
The widesp ead p esence o ins i u ional acuums and ins i u ional
de ec s di e en ia es eme ging economies om ma u e ma ke s (Li
e al., 2008). This dis inc i e ins i u ional con ex p o oundly shapes he
hema ic ocus o BMI in EMEs and ac s as a key enable o achie ing
dual pe o mance in complex en i onmen s. Speci ically, an ins i u-
ional acuum e e s o he absence o a ully de eloped ins i u ional
amewo k, cha ac e ized by egula o y gaps, weak legal s uc u es, and
unde de eloped go e nance mechanisms (Li e al., 2008). Such an
en i onmen c ea es luc a i e oppo uni ies o i ms wi h s ong
explo a o y capabili ies, i s -mo e ad an ages, and a p opensi y o
winne - akes-all s a egies. Wi hin his con ex , pionee ing BMI eme ges
as a c i ical mechanism o iden i ying and capi alizing on new ma ke
oppo uni ies, as i enables i ms o b idge ins i u ional acuums and
es ablish no el ansac ion pa adigms and ma ke spaces.
The essence o pionee ing BMI lies in pu suing dis inc i eness by
explo ing new ma ke s, de eloping new echnologies, and c ea ing
no el alue p oposi ions, which signi ican ly d i e subs an i e pe o -
mance (Bashi e al., 2023). Fi s , pionee ing BMI enables i ms o
es ablish new ma ke s and build di e en ia ed compe i i e ad an ages.
I does so by iden i ying la en cus ome needs and le e aging
o wa d-looking ma ke insigh s o ede ine ansac ion s uc u es and
ules, he eby shaping ma ke beha io (Luo e al., 2022). This
i s -mo e ad an age gene a es new e enue s eams and expands
ma ke sha e, di ec ly enhancing subs an i e pe o mance. Second,
pionee ing BMI os e s inc emen al g ow h by c ea ing new alue
p oposi ions. Th ough he de elopmen o new echnologies,
c oss-sec o collabo a ions, o en i ely no el alue o e ings, pionee ing
BMI enables i ms o a ac new cus ome segmen s and di e si y e -
enue sou ces. EMEs can le e age pionee ing BMI o dis up con en ional
ma ke pa e ns, explo e new oppo uni ies, and pene a e eme ging
ma ke s (He & Wong, 2004). By o e ing dis inc i e p oduc s o se ices,
i ms can achie e unique alue c ea ion (Zo & Ami , 2007). Based on
his, we p opose he ollowing hypo hesis:
H1a. In eme ging ma ke s, pionee ing BMI plays a c i ical ole in
enhancing i ms’ subs an i e pe o mance.
Ins i u ional de ec s in eme ging ma ke s—such as a bi a y egu-
la ions, high en y ba ie s, and weak en o cemen —o en hinde ma -
ke e iciency and pose challenges o i ms (Li e al., 2008; Peng, 2003).
Howe e , hese ins i u ional oids also c ea e oppo uni ies o i ms o
adap and inno a e wi hin exis ing s uc u es.
Pe ec ing BMI e e s ocusing on e ining exis ing ope a ions,
p oduc s, o se ices, wi h an emphasis on mee ing clea and es ablished
cus ome needs (Luo e al., 2022). Unlike pionee ing BMI, which em-
phasizes explo ing new ma ke s and c ea ing unique alue p oposi ions,
pe ec ing BMI is cha ac e ized by p io i izing he managemen and
e inemen o ma u e p oduc s o se ices, ensu ing con inuous
imp o emen o enhance cus ome sa is ac ion (He & Wong, 2004; Luo
e al., 2022). This alignmen allows i ms o be e sa is y s akeholde
expec a ions and egula o y s anda ds, making hem mo e likely o gain
ex e nal accep ance, social ecogni ion, and legi imacy—key compo-
nen s o symbolic pe o mance (DiMaggio & Powell, 1983; Meye &
Rowan, 1977).
Mo eo e , in ma ke s cha ac e ized by weak ins i u ional ame-
wo ks and low le els o in ellec ual p ope y p o ec ion, whe e imi a ion
is ela i ely easy, pe ec ing BMI can le e age he spillo e e ec s om
pionee s (Haunschild & Mine , 1997). By building on exis ing models
a he han adically depa ing om hem, i ms a oid he high unce -
ain y and cos o explo a ion while o e ing imp o ed p oduc s o se -
ices ha align wi h ma ke needs. This “ ollowe ” s a egy enables
i ms o achie e ma ke alida ion mo e quickly and o be pe cei ed as
eliable, compe en , and complian wi h ins i u ional expec a ions (He &
Wong, 2004).
In summa y, pe ec ing BMI o en in ol es inc emen al imp o e-
men s and alignmen wi h dominan ins i u ional logics, which a e
gene ally mo e accep able and legi ima e in he eyes o egula o s, in-
es o s, and o he ex e nal s akeholde s. Based on hese a gumen s, we
p opose he ollowing hypo hesis:
H1b. In eme ging ma ke s, pe ec ing BMI plays a c i ical ole in
enhancing i ms’ symbolic pe o mance.
Gi en he di e gen objec i es and mechanisms unde lying dual
pe o mance, a single ype o BMI is unlikely o simul aneously add ess
he demands o bo h dimensions. Pionee ing BMI enhances subs an i e
pe o mance by explo ing new ma ke s, de eloping no el echnologies,
Fig. 1. Theo e ical model: he con igu a ion o hema ic BMI o EMEs.
F. Huang e al.
Jou nal o Inno a ion & Knowledge 10 (2025) 100755
3
and pu suing dis inc i eness, he eby c ea ing new ma ke oppo uni ies
and d i ing e enue g ow h. Howe e , i s con ibu ion o symbolic
pe o mance is ela i ely limi ed. The explo a o y na u e o pionee ing
BMI may con lic wi h exis ing ins i u ional egula ions o s akeholde
expec a ions, making i challenging o i ms o achie e b oad social
ecogni ion in he sho e m (Suchman, 1995; Zimme man & Zei z,
2002). Addi ionally, i s limi ed ocus on he needs o incumben ma ke
s akeholde s u he diminishes i s impac on symbolic pe o mance.
In con as , pe ec ing BMI enhances symbolic pe o mance by
op imizing exis ing p ocesses, mee ing s akeholde expec a ions, and
ensu ing o ganiza ional con o mi y, he eby s eng hening co po a e
legi imacy and social ecogni ion. Howe e , i s limi ed c ea i e capaci y
and he challenge o di e en ia ion in imi a ion-d i en en i onmen s
cons ain i s abili y o d i e subs an i e pe o mance g ow h.
Based on his, we p opose he ollowing hypo hesis:
H2. No single o m o business model inno a ion is su icien o ach-
ie e dual pe o mance in eme ging ma ke en e p ises.
The in e play o business model inno a ion, en i onmen al cha ac e is ics,
and s a egic o ien a ion
En i onmen al compe i i eness se es as a key indica o o ma ke
compe i ion in ensi y, di ec ly in luencing i ms’ su i al and g ow h
p ospec s wi hin a gi en ma ke (Fainshmid e al., 2019). In highly
compe i i e ma ke s, esou ces end o become inc easingly homoge-
neous, diminishing he e ec i eness o adi ional compe i i e s a egies
in es ablishing a sus ainable ad an age. The e o e, i ms mus le e age
new echnologies o gain a compe i i e edge, making he in eg a ion o
dual BMI wi h a digi al-o ien ed s a egy pa icula ly c ucial (Li e al.,
2024).
Digi al o ien a ion e e s o a i m’s s a egic inclina ion o con in-
uously explo e and apply new digi al ools and echnologies o enhance
inno a ion capaci y and ma ke compe i i eness (Kinde mann e al.,
2021). Digi al echnologies enable EMEs o apidly acqui e new e-
sou ces, es uc u e esou ce linkages, and acili a e dis up i e inno a-
ion (Bohnsack e al., 2021). By le e aging digi al echnologies, i ms
can mo e accu a ely cap u e ma ke dynamics and consume demands,
u ilize big da a analy ics o o ecas ends, and swi ly espond o
changes, he eby educing decision-making isks and imp o ing
esou ce e iciency. Addi ionally, hese echnologies suppo he
pe sonaliza ion o p oduc s and se ices, enhancing use expe ience and
c ea ing new e enue s eams o i ms.
While he syne gy be ween digi al o ien a ion and BMI p o ides
i ms wi h subs an ial echnological suppo and enhanced inno a ion
capaci y, he high isks associa ed wi h echnological unce ain y may
unde mine symbolic pe o mance. Eme ging echnologies o en in o-
duce unce ain ies ela ed o easibili y, ma ke accep ance, and eco-
nomic e u ns, aising conce ns among s akeholde s ega ding hei
long- e m iabili y, which nega i ely impac s symbolic pe o mance
(Ald ich & Fiol, 1994; Zimme man & Zei z, 2002). Mo eo e , he
in e play be ween digi al o ien a ion and BMI may lead i ms o
o e - ely on echnology-d i en solu ions, po en ially neglec ing
human-cen e ed alues and co po a e social esponsibili y. Fo ins ance,
in he pu sui o maximum e iciency, i ms may deploy au oma ion and
a i icial in elligence (AI) o eplace a signi ican po ion o he wo k-
o ce. While his app oach can educe cos s and enhance p oduc i i y, i
may also esul in job displacemen and skill dep ecia ion, a ac ing
c i icism o a lack o social esponsibili y. Addi ionally, he complexi y
and opaci y o eme ging echnologies can exace ba e public dis us ,
pa icula ly in ela ion o da a p i acy, algo i hmic bias, and e hical
conce ns. When consume s pe cei e ha a i m’s echnological appli-
ca ions in inge upon hei in e es s o ail o add ess hei needs, b and
loyal y and social ecogni ion may be signi ican ly comp omised.
The e o e, when i ms implemen a digi al-o ien ed s a egy, hey
should ope a e in a mo e muni icen en i onmen , which is ypically
cha ac e ized by ins i u ional p edic abili y and policy suppo , allow-
ing i ms o concen a e on long- e m, high- isk inno a ion ac i i ies.
Lowe ba ie s and cos s associa ed wi h esou ce acquisi ion can
acili a e i ms o in eg a e esou ces, expand inno a ion channels, and
explo e highe - isk ma ke oppo uni ies (Cas ogio anni, 1991).
Mo eo e , such en i onmen s encou age he pa icipa ion o mul iple
s akeholde s, os e ing communica ion and collabo a ion be ween i ms
and socie y, he eby enhancing public con idence in he p ospec s o
eme ging echnologies.
Addi ionally, EMEs can le e age policy o ien a ion o ully capi alize
on he guiding ole o policies in business ope a ions, he eby enhancing
o ganiza ional legi imacy and o e coming de elopmen al legi imacy
h esholds. In eme ging ma ke s, policies se e as a benchma k o
indus y-s anda d legi imacy, while simul aneously enhancing public
cogni i e legi imacy h ough media in e p e a ion and dissemina ion
(Minni i, 2008). By engaging wi h policy ac o s, i ms can adop s a-
egic sense-making (Na ayanan e al., 2011), inc easing hei policy
sensi i i y and enabling hem o espond e ec i ely o go e nmen di-
ec i es, ul ima ely s eng hening hei o ganiza ional legi imacy (Falck
e al., 2010).
Based on his, we p opose he ollowing hypo hesis:
H3. In compe i i e en i onmen s, i ms pu suing dual BMI in
conjunc ion wi h a digi al-o ien ed s a egy mus also adop a policy-
o ien ed s a egy o ope a e wi hin a muni icen en i onmen o ach-
ie e dual pe o mance.
Con e sely, in a muni icen en i onmen , i ms ace ewe ex e nal
cons ain s, enjoy easie access o esou ces, and ope a e wi hin a mo e
s able and suppo i e ins i u ional amewo k (Cas ogio anni, 1991).
This a o able se ing enables i ms o acqui e essen ial esou ces mo e
e icien ly, p o iding hem wi h g ea e lexibili y o engage in expe i-
men a ion and explo a ion inno a ion. Consequen ly, i ms a e mo e
likely o in eg a e eme ging echnologies in o hei BMI. By le e aging
ad anced echnologies, such as big da a and cloud compu ing, i ms can
u ilize pionee ing BMI o explo e new ma ke oppo uni ies and c ea e
unique alue p oposi ions, he eby enhancing subs an i e pe o mance.
Simul aneously, wi hin he con ex o pe ec ing BMI, digi al echnolo-
gies acili a e he op imiza ion o exis ing p ocesses, imp o e use
sa is ac ion, and enhance ope a ional e iciency and se ice quali y,
ul ima ely con ibu ing o symbolic pe o mance. Based on his, we
p opose he ollowing hypo hesis:
H4. In a muni icen en i onmen , he syne gy be ween dual BMI and a
digi al-o ien ed s a egy enables i ms o achie e dual pe o mance.
Me hods
Sample and da a
As one o he wo ld’s la ges eme ging ma ke s, China is cha ac e -
ized by apid echnological ans o ma ion, ins i u ional acuums, and
ins i u ional de ec s, making i an ideal con ex o his s udy (Luo e al.,
2022). Mo eo e , Chinese EMEs ha e demons a ed s ong engagemen
in BMI, p o iding a ich sou ce o cases and da a o suppo his esea ch.
We dis ibu ed ques ionnai es o 270 echnology en u es in Beijing,
Shenzhen, Nanjing, and Ningbo, China, achie ing a eco e y a e o 91.8
%. The su ey esponses we e sc eened based on he ollowing c i e ia:
(1) Fi ms mus ope a e in eme ging indus ies, including nex -
gene a ion in o ma ion echnology, bio echnology, g een echnology,
and ad anced manu ac u ing echnology; (2) i ms mus ha e an ope -
a ional enu e be ween one and eigh yea s; (3) esponden s mus ha e
mo e han one yea o wo k expe ience and no be in an en y-le el
posi ion ( his was o ensu e ha hey ha e a comp ehensi e unde -
s anding o he s a egic impac o BMI); (4) su eys mus ha e no mo e
han six missing alues and no o e ly homogeneous esponses. Ul i-
ma ely, 55 alid samples we e e ained o analysis.
F. Huang e al.
Jou nal o Inno a ion & Knowledge 10 (2025) 100755
4
Fuzzy-se quali a i e compa a i e analysis
This s udy employs sQCA, a me hod ha examines how he in e -
ac ion o an eceden condi ions esul s in obse able a ia ions o dis-
con inui ies in ou comes (Du & Kim, 2021; Rihoux & Ragin, 2009).
Compa ed o adi ional eg ession analysis, sQCA is a case-based,
asymme ic app oach ha emphasizes complex causal ela ionships
wi hin con ex ual con igu a ions, making i pa icula ly sui able o
explo ing in ica e social phenomena (Fiss, 2011; Ragin, 2008).
We a gue ha sQCA is highly app op ia e o his s udy o he
ollowing h ee easons. Fi s , sQCA iden i ies asymme ic ela ionships
and can explain cases ha de ia e om gene al ends (Douglas e al.,
2020). In adi ional eg ession analysis, ou lie obse a ions ha
signi ican ly di e om he o e all end a e o en excluded o ocus on
a e age e ec s. Howe e , hese ou lie s equen ly con ain aluable
esea ch insigh s. The ad an age o sQCA lies in i s abili y o e ain and
analyze hese ou lie s, unco e ing asymme ies in complex causal e-
la ionships. Fo ins ance, when examining he impac o policy o ien-
a ion on i ms’ di e en ia ion ad an ages, eg ession analysis migh
conclude ha policy o ien a ion weakens di e en ia ion ad an ages.
Howe e , sQCA, h ough con igu a ional analysis, may e eal ha
unde ce ain condi ions, i ms can achie e di e en ia ion ad an ages
despi e s ong policy o ien a ion. This capabili y makes sQCA pa icu-
la ly well-sui ed o analyzing mul idimensional causal ela ionships in
complex social phenomena.
Second, sQCA o e comes he limi a ions o eg ession analysis in
handling high-o de in e ac ions (Luo e al., 2021). Reg ession analysis
cap u es in e dependences be ween a iables by in oducing in e ac ion
e ms, bu when in e ac ions in ol e highe -o de e ec s (e.g.,
h ee-way in e ac ions), he esul s o en become o e ly complex and
di icul o in e p e . In con as , sQCA sys ema ically iden i ies all
po en ial in e dependencies among an eceden ac o s and clea ly il-
lus a es mul iple equi inal pa hways leading o he same ou come. This
ea u e makes sQCA an ideal ool o s udying mul i ac o in e ac ions.
The e o e, sQCA enables us o examine he in e play be ween BMI,
s a egic o ien a ion, and en i onmen al cha ac e is ics, as well as hei
collec i e impac on he dual pe o mance o EMEs.
Thi d, sQCA is pa icula ly well-sui ed o small o medium-sized
samples (Rihoux & Ragin, 2009). This s udy’s sample size (n =55)
mee s he equi emen s o he sQCA me hod, making i sui able o
e ec i ely suppo ing ou analysis and conclusions. Unlike adi ional
eg ession analysis, sQCA does no equi e la ge samples o s ic s a-
is ical assump ions; ins ead, i is based on se heo y and Boolean
minimiza ion logic, ocusing on he su iciency and necessi y o condi-
ion combina ions a he han on p obabili y dis ibu ions. E en wi h a
small sample size, sQCA can e ec i ely iden i y key causal pa hways as
long as cases clea ly exhibi ela ionships be ween condi ion combina-
ions and ou comes. In small o medium-sized samples, sQCA ypically
limi s he numbe o condi ions o p e en he combina o ial explosion
p oblem, wi h an op imal ange o ou o se en condi ions. This s udy
includes six explana o y a iables, making sQCA pa icula ly sui able
o he analysis.
Measu emen and calib a ion
The a iables in his s udy we e measu ed on a se en-poin Like
scale, wi h answe s anging om one (“s ongly disag ee”) o se en
(“s ongly ag ee”). The a iables a e as ollows.
EME pe o mance: The measu emen o subs an i e pe o mance
was based on he scale de eloped by Li and A uahene-Gima (2001) and
included nine i ems, such as e u n on in es men , sales e u n, and
p o i g ow h. The measu emen o symbolic pe o mance d ew on he
app oach o Deephouse (1996), inco po a ing assessmen s om 10
s akeholde g oups, including employees, cus ome s, and egula o y
o icials.
Thema ic BMI: We used he pionee ing and pe ec ing BMI scale,
de eloped by Luo e al. (2022), o measu emen . This scale included
eigh i ems o each o he wo condi ions. An example i em o pio-
nee ing BMI is, “P o iding cus ome s wi h dis inc i e and no el p od-
uc s, se ices, o in o ma ion.” An example i em o pe ec ing BMI is,
“Emphasizing he e inemen and enhancemen o p oduc o se ice
inno a ions.”
S a egic o ien a ion: The measu emen o policy o ien a ion was
adap ed om s udies, such as Kohli and Jawo ski (1990), and comp ised
h ee i ems. An example i em is, “Go e nmen agencies’ indus ial
de elopmen plans p o ide guidance o he echnological de elopmen
di ec ion o en ep eneu ial i ms.” The measu emen o digi al o ien-
a ion d ew on he scales de eloped by Ga ignon and Xue eb (1997) and
Zhou e al. (2005) and included i e i ems. An example i em is, “Ou i m
consis en ly u ilizes digi al echnologies o de elop new p oduc s o
se ices.”
En i onmen al cha ac e is ics: En i onmen al compe i i eness was
measu ed using he scale de eloped by Jansen e al. (2006), which
consis s o h ee i ems. An example i em is, “Compe i ion in ou local
ma ke is in ense.” En i onmen al muni icence was assessed using a
ou -i em scale adap ed om Su cli e (1994). An example i em is,
“The e a e abundan p o i oppo uni ies in he ma ke .”
In sQCA, he p ocess o assigning se membe ship is called calib a-
ion (Ragin, 2008). Speci ically, he esea che mus se h ee ancho
poin s o calib a ion based on exis ing heo y and he ac ual si ua ion
(Ragin, 2008): he “ ully in,” “c osso e ,” and “ ully ou ” poin s. The
ans o med se membe ship anges be ween ze o ( ully ou ) and one
( ully in). Following p e ious esea ch (Fiss, 2011), hese h ee ancho
poin s we e se as he 95 %, 50 %, and 5 % quan iles, espec i ely. The
desc ip ion o he measu emen indica o s and he de e mina ion o
ancho poin s o each condi ion a iable a e shown in Table 1.
P ocedu e and esul s
Necessa y condi ions analysis
1
Su iciency analysis ocuses on iden i ying condi ion combina ions
ha can gene a e a speci ic ou come, bu i may o e look indi idual
necessa y condi ions, po en ially esul ing in missing c i ical in o ma-
ion o d awing inco ec conclusions. To p e en necessa y condi ions
om being elimina ed du ing con igu a ional analysis, i is essen ial o
examine hem be o e conduc ing he u h able analysis.
In Table 2, we p esen he esul s o he necessa y condi ions analysis
(NCA). Acco ding o his me hod, a necessa y condi ion mus sa is y wo
c i e ia: (1) The e ec size (d) is a leas 0.1 (Dul, 2016); (2) Mon e Ca lo
simula ions o pe mu a ion es s (p alue) mus con i m ha he e ec
size is s a is ically signi ican (Dul e al., 2020). The esul s indica e ha
pionee ing and pe ec ing BMI, policy o ien a ion, digi al o ien a ion,
en i onmen al muni icence, and en i onmen al compe i i eness a e he
necessa y condi ions o he high subs an i e pe o mance o EMEs.
Pionee ing and pe ec ing BMI, digi al o ien a ion, en i onmen al
muni icence and compe i i eness a e he necessa y condi ions o he
high symbolic pe o mance o EMEs.
Su iciency analyses
Following p e ious esea ch (Fiss, 2011), we se he consis ency
h eshold, p opo ional educ ion in inconsis ency (PRI), and case
1
In he su iciency analysis o sQCA, necessa y condi ions unc ion as con-
s ain s in gene a ing condi ion combina ions. QCA so wa e includes a speci ic
op ion o designa ing necessa y condi ions. Be o e cons uc ing he u h able,
he necessa y condi ions iden i ied h ough necessa y condi ions analysis
should be explici ly designa ed. This ensu es ha hese condi ions a e no
elimina ed in he pa simonious solu ion du ing subsequen su iciency analysis,
he eby main aining he comple eness and accu acy o he analysis.
F. Huang e al.
Jou nal o Inno a ion & Knowledge 10 (2025) 100755
5
h eshold a 0.8, 0.70, and 1, espec i ely. We ob ained in e media e
solu ions and dis inguished be ween co e and ma ginal condi ions o he
con igu a ion based on in e media e and pa simonious solu ions. The
in e media e solu ion
2
was de i ed h ough coun e ac ual analysis,
assuming he p esence o necessa y condi ions, such as pionee ing BMI,
pe ec ing BMI, policy o ien a ion, digi al o ien a ion, en i onmen al
muni icence, and en i onmen al compe i i eness, which may con ibu e
o high subs an i e pe o mance. Addi ionally, assuming he p esence o
necessa y condi ions, such as pionee ing BMI, pe ec ing BMI, digi al
o ien a ion, en i onmen al muni icence, and en i onmen al compe i-
i eness, he p esence o absence o policy o ien a ion may gene a e
high symbolic pe o mance.
Using sQCA, we iden i ied h ee high subs an i e pe o mance
con igu a ions, wi h a consis ency index o a leas 0.882. The consis-
ency o he solu ion was 0.878, exceeding he commonly accep ed
h eshold o 0.80 (Ragin, 2008). Addi ionally, he co e age was 0.715,
u he demons a ing ha hese h ee con igu a ions se e as su icien
condi ions o high subs an i e pe o mance, explaining 70 % o he
a iance (solu ion co e age) in i . Addi ionally, sQCA iden i ied h ee
high symbolic pe o mance con igu a ions, wi h a consis ency index o
a leas 0.957. The consis ency o he solu ion was 0.951, and he
co e age was 0.740. This inding con i ms ha hese h ee con igu a-
ions also ep esen su icien condi ions o high symbolic pe o mance,
explaining 74 % o he a iance in high symbolic pe o mance. The e-
o e, bo h se s o solu ions p esen ed an accep able i . The esul s o he
analysis a e shown in Table 3.
High subs an i e pe o mance
Con igu a ion P1 (pioBMI*pe BMI*PO*DO*EM)
3
: In a muni icen
en i onmen , EMEs can achie e high subs an i e pe o mance h ough
he syne gy o dual BMI, policy o ien a ion, and digi al o ien a ion. This
pa hway accoun s o 57.5 % o high subs an i e pe o mance cases
among EMEs, ep esen ing a policy-d i en pa hway ypical o eme ging
ma ke con ex s.
In eme ging ma ke s, when go e nmen policies p io i ize a speci ic
indus y, he sec o is o en pe cei ed as an oppo uni y- ich ma ke . Fo
example, he Chinese go e nmen has ac i ely p omo ed he new-
ene gy– ehicle indus y by in oducing a se ies o suppo i e policies,
such as pu chase subsidies and ee license pla e egis a ion. These
measu es ha e signi ican ly s imula ed ma ke demand. By p o iding
ex ensi e policy esou ces and alen suppo , he go e nmen helps
guide EMEs in iden i ying ma ke expansion oppo uni ies. EMEs ha
ac i ely espond o hese policies can e ec i ely mi iga e ma ke en y
isks and le e age he ad an ages o a muni icen en i onmen o unlock
g ea e g ow h oppo uni ies.
Table 1
Summa y s a is ics and calib a ion h esholds.
Va iables Mean S.D. Min Max Fully in C osso e Fully ou
BMI hemes Pionee ing BMI (pioBMI) 5.38 0.77 3.13 7.00 6.35 5.50 3.45
Pe ec ing BMI (pe BMI) 5.41 0.75 3.00 7.00 6.90 5.50 4.08
S a egic o ien a ion Policy o ien a ion (PO) 4.14 1.43 1.00 6.67 6.40 4.00 1.67
Digi al o ien a ion (DO) 5.37 0.82 2.80 7.00 6.68 5.40 3.36
En i onmen al cha ac e is ics En i onmen al muni icence (EM) 5.31 0.83 3.00 7.00 6.60 5.50 3.60
En i onmen al compe i i eness (EC) 5.44 0.74 3.33 7.00 7.00 5.33 4.00
Pe o mance Subs an i e pe o mance (P) 5.32 0.63 3.67 6.44 6.33 5.44 4.18
Symbolic pe o mance (L) 5.53 0.57 4.00 6.60 6.42 5.60 4.40
Table 2
Analysis esul s o necessa y condi ions o necessa y condi ions analysis
me hod.
Va iables Ou come Scope Ceiling
zone
Accu acy E ec size
(d)
a
p alue
b
pioBMI P 0.93 0.309 85.5 % 0.332 0.000
L 0.92 0.213 92.7 % 0.213 0.002
pe BMI P 0.91 0.235 85.5 % 0.258 0.001
L 0.90 0.157 90.9 % 0.173 0.024
PO P 0.91 0.179 81.8 % 0.196 0.025
L 0.90 0.098 87.3 % 0.105 0.207
DO P 0.92 0.224 92.7 % 0.243 0.002
L 0.91 0.224 89.1 % 0.246 0.001
EM P 0.92 0.237 81.8 % 0.258 0.000
L 0.91 0.288 76.4 % 0.316 0.000
EC P 0.90 0.191 87.3 % 0.212 0.011
L 0.89 0.161 90.9 % 0.180 0.035
No e: a. 0.0 ≤d <0.1: low le el; 0.1 ≤d <0.3: mode a e le el; 0.3 ≤d <0.5:
medium high le el; 0.5 ≤d: high le el. b. Pe mu a ion es (numbe o esam-
plings =10,000).
Table 3
Con igu a ions o high subs an i e and symbolic pe o mance.
Va iables Subs an i e pe o mance Symbolic pe o mance
P1 P2 P3 L1 L2 L3
pioBMI ● ● ● ● ●
pe BMI ● ● ● ● ●
PO ●⊗● ●
DO ● ● ● ● ●
EM ●●● ●
EC ●●●●
Raw co e age 0.575 0.648 0.450 0.622 0.615 0.667
Unique co e age 0.038 0.027 0.030 0.040 0.034 0.085
Consis ency 0.882 0.883 0.944 0.957 0.967 0.968
O e all solu ion co e age 0.715 0.740
O e all solu ion
consis ency
0.878 0.951
● indica es p esence o a condi ion; ⊗indica es i s absence. La ge cha ac e s
indica e co e condi ions; small cha ac e s indica e pe iphe al condi ions; Blanks
indica e “does no ma e ”.
2
QCA analysis p oduces h ee ypes o solu ions: complex, in e media e, and
pa simonious. The complex solu ion conside s only con igu a ions wi h
empi ically obse ed cases, while he pa simonious solu ion inco po a es all
logical emainde s wi hou e alua ing hei plausibili y. The in e media e so-
lu ion, howe e , in eg a es heo e ically and p ac ically meaning ul logical
emainde s, guided by he esea che ’s domain knowledge and expe ise
(Rihoux & Ragin, 2009). Compa ed o he o he wo solu ions, he in e media e
solu ion s ikes a balance be ween complexi y and pa simony, enabling he
inclusion o a b oade ange o po en ial causal pa hways while main aining
heo e ical in e p e abili y. Mos impo an ly, he in e media e solu ion ensu es
ha necessa y condi ions a e no elimina ed, he eby p e en ing he loss o
c i ical in o ma ion o he o e sigh o causal mechanisms due o excessi e
simpli ica ion.
3
In sQCA, A*B*~C means he in e sec ion o he se whe e condi ions A and
B a e p esen , and he se whe e condi ion C is absen . He e, * ep esen s he
in e sec ion ope a o and ~ signi ies nega ion o absence.
F. Huang e al.
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6
Mo eo e , in esou ce-abundan ma ke s, EMEs bene i om g ea e
ole ance o ial and e o , making hem mo e inclined o engage in
expe imen a ion and explo a o y inno a ion. Digi al echnologies, as
apidly e ol ing inno a ions, play a c i ical ole in cap u ing and
esponding o ma ke dynamics in a comp ehensi e and imely manne .
Fi ms ac i ely in eg a e digi al echnologies in o hei BMI, le e aging
hem in wo key ways.
Fi s , digi al echnologies enhance he e ec i eness o pe ec ing
BMI by imp o ing p oduc ion e iciency and educing cos s, ul ima ely
con ibu ing o inancial g ow h. Fo example, unmanned ac o ies
boos p oduc i i y and signi ican ly lowe ope a ional cos s. Second,
digi al echnologies se e as a c ucial d i e o pionee ing BMI, enabling
i ms o explo e new ma ke oppo uni ies. Fo ins ance, new-ene -
gy– ehicle manu ac u e s a e making subs an ial in es men s in in el-
ligen d i ing echnologies, engaging in ex ensi e explo a ion
inno a ion o c ea e new g ow h a enues. In his scena io, i ms ha
adop a hyb id app oach, combining pionee ing and pe ec ing BMI, can
achie e signi ican subs an i e pe o mance gains.
Con igu a ion P2 (pioBMI*pe BMI*DO*EC): In a compe i i e en i-
onmen , EMEs can achie e high subs an i e pe o mance h ough he
syne gy o dual BMI and a digi al-o ien ed s a egy. This ep esen s a
s eady ye p og essi e pa hway, explaining he b oades ange o high
subs an i e pe o mance cases among EMEs, wi h a aw co e age o
64.8 %. Unde compe i i e ma ke condi ions, EMEs end o sc u inize
hei co e esou ces and p io i ize digi al inno a ion capabili ies o
enhance hei dynamic compe i i e ad an age. Speci ically, in eg a ing
digi al echnologies in o pionee ing and pe ec ing BMI enables i ms o
explo e new ma ke s, a ac new use s, and c ea e new e enue s eams
h ough pionee ing BMI, while simul aneously s eng hening hei
exis ing ma ke sha e h ough pe ec ing BMI, ensu ing long- e m s a-
bili y and sus ainable g ow h.
Con igu a ion P3 (pioBMI*~PO*DO*EM*EC): In a simul aneously
muni icen and compe i i e en i onmen , EMEs can achie e high sub-
s an i e pe o mance h ough he syne gy o pionee ing BMI and a
digi al-o ien ed s a egy. This ep esen s a mo e agg essi e pa hway,
explaining 45.0 % o high subs an i e pe o mance cases. In such an
en i onmen , EMEs ace a ce ain su i al c isis and hey may p e e o
o e come he cu en ma ke bo leneck ia digi al inno a ion. In his
con ex , pionee ing BMI is mo e conduci e o such a b eak h ough and
he de elopmen o EMEs in new models and ma ke s. Rega dless o he
en i onmen al con ex , pionee ing BMI is p esen in e e y high sub-
s an i e pe o mance con igu a ion, hus, suppo ing H1a.
High symbolic pe o mance
Con igu a ion L1 (pe BMI*PO*EC): In highly compe i i e en i on-
men s, EMEs can achie e high symbolic pe o mance h ough he syn-
e gy o pe ec ing BMI and a policy-o ien ed s a egy. This pa hway
explains 62.2 % o high symbolic pe o mance cases among EMEs. This
may be because, in compe i i e en i onmen s, s akeholde s place
g ea e emphasis on a i m’s s abili y. Consequen ly, EMEs adop a
policy-o ien ed s a egy o secu e go e nmen endo semen and social
ecogni ion, he eby enhancing hei legi imacy and social capi al.
Addi ionally, by ocusing on op imizing and e ining exis ing ma ke s,
EMEs imp o e use sa is ac ion, align wi h socie al expec a ions, u he
ein o cing hei high symbolic pe o mance.
Con igu a ion L2 (pioBMI*pe BMI*PO*DO*EM): In a muni icen
en i onmen , EMEs can achie e high symbolic pe o mance h ough he
syne gy o dual BMI, policy o ien a ion, and digi al o ien a ion. This
pa hway explains 61.5 % o high symbolic pe o mance cases among
EMEs, aligning wi h P1 and demons a ing he e ec i eness o a policy-
d i en app oach. While pionee ing BMI and digi al o ien a ion may pose
sho - e m challenges o symbolic pe o mance, policy o ien a ion p o-
ides i ms wi h go e nmen endo semen , and a muni icen en i on-
men enhances EMEs’ ole ance o ial and e o , he eby educing he
isks associa ed wi h adop ing new echnologies. These ac o s collec-
i ely enhance s akeholde ecogni ion and imp o e i ms’ symbolic
pe o mance. Thus, his in eg a ed s a egy enables i ms o explo e new
ma ke s and echnologies and ensu es hei s abili y and legi imacy in
exis ing ma ke s, he eby os e ing b oad social suppo and us .
Con igu a ion L3 (pioBMI*pe BMI*DO*EM*EC): In a simul aneously
muni icen and compe i i e en i onmen , he syne gy o dual BMI and
digi al inno a ion o ien a ion enables eme ging en e p ises o achie e
high symbolic pe o mance. This pa hway explains 66.7 % o high
symbolic pe o mance cases. This may be because, in a compe i i e
en i onmen , EMEs ely on he in eg a ion o pionee ing BMI and digi al
o ien a ion o es ablish compe i i e ad an age. While such an app oach
may ini ially pose challenges o symbolic pe o mance, a muni icen
en i onmen p o ides a a o able se ing o inno a ion, o e ing
g ea e ole ance o adical inno a ion among s akeholde s. Conse-
quen ly, his con igu a ion also acili a es high symbolic pe o mance.
Simila ly, we ind ha pe ec ing BMI appea s in e e y high symbolic
pe o mance con igu a ion, hus, suppo ing H1b.
Fu he analysis
Using Boolean algeb a, we can iden i y common solu ions ha ach-
ie e dual pe o mance by compa ing con igu a ions (Pa k e al., 2017).
Th ough his app oach, we ind ha L3 is a subse o P2, as bo h con-
igu a ions sha e he same elemen s, excep o en i onmen al muni i-
cence. These wo con igu a ions can be exp essed as ollows: L3=
{pioBMI, pe BMI, PO, DO, EM}, P2={pioBMI, pe BMI, PO, DO, (EM o
~EM)}. The e o e, L3 is a subse o P2 (i.e., P2⊃L3). O e all, we iden i y
h ee con igu a ions leading o dual pe o mance (Fig. 2). We obse e
ha e e y dual pe o mance con igu a ion includes pionee ing and
pe ec ing BMI, indica ing ha a single BMI app oach (e.g., P3 and L1)
canno achie e dual pe o mance, he eby suppo ing H2.
Examining P&L2 and P&L3, we ind ha in compe i i e en i on-
men s, i ms pu suing dual BMI in conjunc ion wi h a digi al-o ien ed
s a egy mus also ei he adop a policy-o ien ed s a egy o ope a e
wi hin a muni icen en i onmen o achie e dual pe o mance, he eby
suppo ing H3. Speci ically, P&L2 and L3 sha e he same con igu a ion
and can be conside ed a subse o P2. Compa ed o P2, P&L2 in-
co po a es he syne gis ic e ec o a muni icen en i onmen . This
sugges s ha , while digi al echnologies c ea e oppo uni ies o BMI in
compe i i e en i onmen s, hey also in oduce isks ha may aise
conce ns among s akeholde s. The esou ce abundance and ma ke op-
po uni ies p o ided by a muni icen en i onmen help i ms be e
manage hese isks, acili a ing digi al echnology inno a ion and
s eng hening compe i i eness and legi imacy. Simila ly, P&L3 ep e-
sen s he in e sec ion o P2 and L1. Compa ed o P2, P&L3 in eg a es he
syne gis ic e ec o policy o ien a ion, which unc ions simila o
en i onmen al muni icence. Go e nmen endo semen and policy sup-
po educe s akeholde s’ pe cei ed isks, he eby enhancing i ms’
legi imacy and social ecogni ion, ul ima ely imp o ing symbolic pe -
o mance. In con as o L1, P&L3 inco po a es pionee ing BMI and
digi al o ien a ion, indica ing ha , in compe i i e en i onmen s, me ely
e ining use needs and esponding o go e nmen policies is insu icien
o achie ing a di e en ia ed compe i i e ad an age. Ins ead, pionee -
ing BMI, which ocuses on iden i ying no el ma ke oppo uni ies, en-
ables i ms o disco e and seize new g ow h a eas by de eloping
F. Huang e al.
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inno a i e p oduc s and se ices, he eby achie ing di e en ia ion.
Ou esul s did no iden i y he con igu a ion p edic ed by H4.
Ins ead, we disco e ed a new con igu a ion (P&L1) ha eme ges om
he syne gy be ween policy o ien a ion and en i onmen al muni icence.
I is he same con igu a ion as P1 and L2, whe e EMEs ac i ely espond
o go e nmen policies and le e age s a e suppo o speci ic indus ies
o enhance he legi imacy and social ecogni ion o hei inno a ions.
Addi ionally, go e nmen -backed policies s imula e ma ke demand,
while digi al o ien a ion s eng hens i ms’ compe i i e ad an age in
BMI, ul ima ely d i ing inancial g ow h and achie ing dual pe o -
mance. The con igu a ion p edic ed by H4 (whe e i ms ely solely on
en i onmen al muni icence o achie e he syne gis ic e ec ) possibly
did no eme ge because o he absence o clea s a egic guidance and a
s uc u ed suppo mechanism, which could lead i ms o engage in
un ocused explo a o y e o s. Wi hou a well-de ined di ec ion, i ms
may s uggle o e ec i ely iden i y and cap u e new ma ke oppo u-
ni ies, ul ima ely ailing o achie e high le els o subs an i e and sym-
bolic pe o mance.
Robus ness es s
We also conduc ed obus ness es s on he high subs an i e and
symbolic pe o mance o EMEs (e.g., Fiss, 2011; Luo e al., 2021). In his
s udy, while keeping o he pa ame e s unchanged, we inc eased he
equency h eshold o 2, which yielded he new high subs an i e pe -
o mance g ouping (Pa) and new high symbolic pe o mance g oupings
(La1 and La2). Then, we inc eased he consis ency h eshold o PRI
om 0.7 o 0.75. As he na u al b eaking poin o he o iginal high
symbolic con igu a ion was 0.761, we u he aised he PRI h eshold
o he high symbolic con igu a ion o 0.8. This adjus men esul ed in
he new high subs an i e (Pb1 and Pb2, PRI =0.75) and new high
symbolic (Lb, PRI =0.8) pe o mance con igu a ions. The newly
gene a ed con igu a ions exhibi a clea subse ela ionship wi h he
o iginal con igu a ions, indica ing ha he esul s a e obus (Appendix
A).
Discussion
Adop ing a con igu a ional app oach o BMI, his s udy sough o
unde s and how pionee ing and pe ec ing BMI in e ac wi h i ms’
s a egic o ien a ion and en i onmen al cha ac e is ics o achie e dual
pe o mance. We emphasize ha pionee ing BMI p ima ily enhances
subs an i e pe o mance h ough i s -mo e ad an ages and di e en-
ia ion, whe eas pe ec ing BMI s eng hens symbolic pe o mance by
op imizing exis ing models. As an icipa ed, pionee ing BMI and pe -
ec ing BMI we e p esen in all con igu a ions associa ed wi h high
subs an i e and high symbolic pe o mance, espec i ely, u he ali-
da ing he hema ic BMI amewo k p oposed by Luo e al. (2022).
Beyond p io esea ch, his s udy empi ically demons a es ha BMI
alone is insu icien o p edic supe io pe o mance; i s e ec i eness
depends on i s alignmen wi h a i m’s s a egic app oach and en i-
onmen al condi ions. E en when i ms implemen pionee ing and
pe ec ing BMI, misaligned con igu a ions may esul in subop imal
pe o mance ou comes (see Con igu a ions ~P3 and ~L3 in Appendix
B). This inding challenges he con en ional no ion ha BMI is a pe -
o mance d i e (Ami & Zo , 2001), unde sco ing he c i ical need o
i o dynamically adap o en i onmen al con ingencies o achie e
meaning ul impac .
To u he in es iga e he impac o BMI con igu a ions on dual
pe o mance, his s udy employed Boolean algeb a o examine he
in e sec ion o all con igu a ions and hei se –subse ela ionships. The
objec i e was o iden i y uni e sal solu ions ha simul aneously
enhance mul iple dimensions o pe o mance (Pa k e al., 2017; Ragin,
2008). The analysis e eals ha he combina ion o pionee ing and
pe ec ing BMI is essen ial o achie ing dual pe o mance. No ably, all
high-pe o ming con igu a ions include pionee ing and pe ec ing BMI,
indica ing ha nei he app oach alone is su icien . Pionee ing BMI,
while os e ing ma ke compe i i eness, does no gua an ee legi imacy,
whe eas pe ec ing BMI, while ein o cing legi imacy, s uggles o d i e
compe i i eness. This inding suppo s H2 and unde sco es he com-
plemen a y na u e o pionee ing and pe ec ing BMI.
Fu he mo e, we explo ed he syne gis ic e ec s o BMI combina-
ions and con ex ual ac o s, using he MSDO (mos simila , di e en
ou come) analy ical logic (Rihoux & Ragin, 2009). By compa ing simila
con igu a ions yielding di e en pe o mance ou comes, we aimed o
unco e he unde lying d i e s o pe o mance a ia ion. Ou indings
indica e ha policy o ien a ion signi ican ly enhances symbolic pe o -
mance, co obo a ing p io esea ch sugges ing ha go e nmen pol-
icies acili a e co po a e legi imacy. Speci ically, subsidies, ax
incen i es, and egula o y lexibili y enable i ms o gain ma ke
ecogni ion and social accep ance mo e e icien ly. Addi ionally, en i-
onmen al muni icence exe s a dual e ec on i ms. While abundan
ma ke esou ces c ea e mo e inno a ion oppo uni ies, i ms wi hou a
clea s a egic di ec ion may s uggle o iden i y and capi alize on hese
oppo uni ies e ec i ely. Impo an ly, ou analysis did no iden i y any
con igu a ion whe ein en i onmen al muni icence alone signi ican ly
enhanced BMI pe o mance (i.e., PioBMI*Pe BMI*DO*EM). This sug-
ges s ha en i onmen al muni icence mus be complemen ed by policy
o ien a ion o o he s a egic impe a i es o yield meaning ul im-
p o emen s in symbolic pe o mance and ma ke compe i i eness.
Based on hese indings, he s udy makes he ollowing con ibu ions o
he esea ch on BMI and EMEs.
Fig. 2. Se –subse ela ions o con igu a ions om in e sec ion analysis.
F. Huang e al.
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