Adoption of digital technologies, business model innovation, and financial and sustainability performance in start-up firms

Au io, E kko e al.
Wo king Pape
Adop ion o digi al echnologies, business model
inno a ion, and inancial and sus ainabili y pe o mance in
s a -up i ms
ADB Economics Wo king Pape Se ies, No. 734
P o ided in Coope a ion wi h:
Asian De elopmen Bank (ADB), Manila
Sugges ed Ci a ion: Au io, E kko e al. (2024) : Adop ion o digi al echnologies, business model
inno a ion, and inancial and sus ainabili y pe o mance in s a -up i ms, ADB Economics Wo king
Pape Se ies, No. 734, Asian De elopmen Bank (ADB), Manila,
h ps://doi.o g/10.22617/WPS240356-2
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ASIAN DEVELOPMENT BANK
ASIAN DEVELOPMENT BANK
6 ADB A enue, Mandaluyong Ci y
1550 Me o Manila, Philippines
www.adb.o g
ADOPTION OF DIGITAL TECHNOLOGIES,
BUSINESS MODEL INNOVATION,
AND FINANCIAL AND SUSTAINABILITY
PERFORMANCE IN START-UP FIRMS
E kko Au io, Chi aphol Chiyachan ana, Cyn hia Cas illejos-Pe alco in, Kun Fu,
Raymund Haba adas, Yo hin Jinja ak, Anang Mu iadi, Donghyun Pa k,
Pa a awan P asa nphanich, Pham Minh Quyên, and Willem Smi
ADB ECONOMICS
WORKING PAPER SERIES
NO. 734
July 2024
Adop ion o Digi al Technologies, Business Model Inno a ion,
and Financial and Sus ainabili y Pe o mance in S a -Up Fi ms
This epo examines how digi aliza ion a ec s i m pe o mance using su ey da a om 681 digi al
en ep eneu s in six Associa ion o Sou heas Asian Na ions (ASEAN) coun ies. I inds ha selec digi al
applica ions and i m’s business model digi aliza ion d i e business model expe imen a ion.
These indings unde sco e he signi ican alue o he design o en ep eneu ial and digi aliza ion policies
in Asian de eloping economies and in eme ging economies mo e widely. The analysis poin s o impo an
pe o mance implica ions o digi al echnology adop ion by en ep eneu ial businesses.
Abou he Asian De elopmen Bank
ADB is commi ed o achie ing a p ospe ous, inclusi e, esilien , and sus ainable Asia and he Paci ic,
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—49 om he egion. I s main ins umen s o helping i s de eloping membe coun ies a e policy dialogue,
loans, equi y in es men s, gua an ees, g an s, and echnical assis ance.
ASIAN DEVELOPMENT BANK
The ADB Economics Wo king Pape Se ies
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and encou age deba e on de elopmen issues
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a e hose o he au ho s and do no necessa ily
e lec he iews and policies o ADB o
i s Boa d o Go e no s o he go e nmen s
hey ep esen .
ADB Economics Wo king Pape Se ies
Adop ion o Digi al Technologies, Business Model Inno a ion,
and Financial and Sus ainabili y Pe o mance in S a -Up Fi ms
E kko Au io, Chi aphol Chiyachan ana,
Cyn hia Cas illejos-Pe alco in, Kun Fu, Raymund
Haba adas, Yo hin Jinja ak, Anang Mu iadi,
Donghyun Pa k, Pa a awan P asa nphanich,
Pham Minh Quyên, and Willem Smi
No. 734 | July 2024
E kko Au io (e kko[email p o ec ed]) is a p o esso
and chai in he Technology Ven u ing a Impe ial
College Business School. Chi aphol Chiyachan ana
(chi [email protected]) is an assis an p o esso
a Singapo e Managemen Uni e si y. Kun Fu (kun.
[email p o ec ed]) is a senio lec u e a Loughbo ough
Uni e si y London. Raymund Haba adas ( aymund.
[email p o ec ed]) is a p o esso a De La Salle
Uni e si y. Anang Mu iadi (anang.mu iadi@unpad.
ac.id) is head magis e a he Uni e si as Padjadja an.
Pa a awan P asa nphanich (pa a aw[email p o ec ed])
is a lead esea che a Chulalongko n Uni e si y. Pham
Minh Quyên ([email p o ec ed]. n) is a lec u e a
Thu Dau Mo Uni e si y. Willem Smi (willem.smi @
ulb igh .edu. n) is lead acul y o en ep eneu ship
a Fulb igh Uni e si y Vie nam. Cyn hia Cas illejos-
Pe alco in ([email p o ec ed]g) is a senio inancial
sec o o ice in he Sec o s G oup; Yo hin Jinja ak
(yjinja [email protected] g) is a senio economis a he Eas
Asia Depa men ; and Donghyun Pa k
(dpa [email protected] g) is an economic ad iso a he
Economic Resea ch and De elopmen Impac
Depa men , Asian De elopmen Bank.
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ISSN 2313-6537 (p in ), 2313-6545 (PDF)
Publica ion S ock No. WPS240356-2
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ABSTRACT
This epo in es iga es he impac o digi aliza ion on i m-le el pe o mance using su ey da a
om 681 digi al en ep eneu s ac oss six Associa ion o Sou heas Asian Na ions (ASEAN)
coun ies. Resul s show ha he eliance o he business on selec digi al applica ions and he
digi aliza ion o di e en aspec s o he i m’s business models we e ound o be po en d i e s o
business model expe imen a ion in en ep eneu ial businesses. We also obse ed consis en
media ion e ec s o digi aliza ion a iables on pe o mance h ough hei e ec on business model
expe imen a ion, al hough he digi aliza ion a iables also exhibi ed s ong di ec e ec s on
pe o mance. This las obse a ion signals ha he adop ion o digi al echnologies by
en ep eneu ial businesses has mo e wide- anging bene icial impac s han hei acili a ing e ec
on business model expe imen a ion. We conside he indings epo ed he e o be o signi ican
alue o he design o en ep eneu ial and digi aliza ion policies in Asian de eloping economies
and in eme ging economies mo e widely. Ou analysis poin s o impo an pe o mance
implica ions o digi al echnology adop ion by en ep eneu ial businesses.
Keywo ds: digi aliza ion, business model inno a ion, en ep eneu ial pe o mance, ASEAN,
sus ainabili y pe o mance
JEL codes: L26, O32, O33

1 In oduc ion
O e ecen decades, ad ances in digi al echnologies ha e p ecipi a ed a majo s uc u al
ans o ma ion in he o ganiza ion o socie y and he economy. Ubiqui ous digi al connec i i y has
enabled economic and socie al p ocesses o be inc easingly e-o ganized o ake ad an age o
digi al echnologies. This p ocess has also ans o med he con ex wi hin which en ep eneu s
disco e and pu sue en ep eneu ial oppo uni ies and compe e agains es ablished i ms
(Nambisan, 2017). A guably he mos impo an cha ac e is ic o digi al echnologies is hei abili y
o enable business model inno a ion—i.e., a adical e- hink o how en ep eneu ial businesses
o ganize o he c ea ion and deli e y o cus ome alue and cap u e his alue as business p o i
(Bouwman, Nikou, and De Reu e , 2019; Massa and Tucci, 2013; Rachinge e al., 2019). This
is a pa icula ly impo an oppo uni y d i e o en ep eneu s, as es ablished businesses end o
ocus on op imizing hei exis ing business models, which may hampe hei abili y o ake
ad an age o he la es digi al oppo uni ies (Au io e al., 2018). Ye , su p isingly li le is known
abou he pe o mance e ec s o digi al echnology adop ion by en ep eneu ial businesses. In
his epo , we explo e such pe o mance e ec s by means o a six-coun y su ey o digi al
en ep eneu ial businesses.
Al hough he impo ance o digi aliza ion and i s impac on en ep eneu ship h ough business
model inno a ion a e widely ecognized (Au io e al., 2018), su p isingly li le is s ill known abou
he i m-le el pe o mance e ec s o he adop ion o digi al echnologies in he business model
(Bouwman, Nikou, and De Reu e , 2019). The e is widesp ead accep ance ha digi aliza ion has
a ans o ma i e e ec on en ep eneu ial oppo uni y landscapes in coun ies and on he op imal
modes o en ep eneu ial oppo uni y pu sui . Due o digi aliza ion, en ep eneu ial ac i i ies ha e
become less cons ained by spa ial, empo al, and sec o al bounda ies (Nambisan, 2017). The
digi ally-induced li ing o con en ional cons ain s limi ing en ep eneu ial agency means ha
en ep eneu ial oppo uni y pu sui has become a iable occupa ional op ion o la ge audiences
han e e be o e. A he same ime and la gely because o he same easons, he e ec i e means
o pu suing en ep eneu ial oppo uni ies ha e been ans o med, wi h en ep eneu s inc easingly
adop ing inno a ion echniques and p ac ices o iginally pionee ed elsewhe e, such as Design
Thinking, Design Sp in s, G ow h Hacking, and Agile De elopmen (B own, 2009; Kimbell, 2009;
Con igiani and Le in hal, 2019; Bocken and Snihu , 2020). Such ideas ha e p omp ed a no el,
i e a i e app oach o en ep eneu ial oppo uni y disco e y and alida ion, o en e e ed o as
‘Lean En ep eneu ship’ (Blank, 2013; Ries, 2011). The lean en ep eneu ship app oach builds
on he insigh ha en ep eneu ial oppo uni ies seldom appea eadily o med, in he ’ma ke ’,
eady o be exploi ed by en ep eneu s. Ins ead, oppo uni ies need o be g adually c ea ed and
shaped h ough en ep eneu ial expe imen s by which he en ep eneu es s ideas and hunches,
disca ding hose ha do no appea o wo k, and e aining hose ha ecei e suppo i e eedback
(Camu o e al., 2019; Dimo , 2016; Romme and Reymen, 2018). In he bounda yless and
in e connec ed digi al wo ld, s eady-s a e, independen ly exis ing and objec i ely disco e able
‘ma ke oppo uni ies’ ha e become a a i y, and en e p eneu s a e be e o by ha nessing digi al
echnologies o an i e a i e p ocess o oppo uni y de elopmen .
The abo e na a i e es s on wo impo an assump ions: i s , ha he adop ion o digi al
echnologies enables en ep eneu s o expe imen mo e e ec i ely, and second, ha he
alida ed ideas a e ope a ionalized h ough hei inco po a ion in he i m’s business model, o i s
ope a ional a chi ec u e o he disco e y, c ea ion, deli e y, and cap u e o cus ome alue.
2
These assump ions imply ha bo h he adop ion o digi al echnologies in hemsel es, and he
i e a i e expe imen a ion wi h hese in he i m’s business model should cons i u e impo an
d i e s o en ep eneu ial i m pe o mance in he digi al age. I en ep eneu s shape and pu sue
oppo uni ies mo e e ec i ely h ough i e a i e expe imen a ion, and i ha expe imen a ion is
enhanced by he adop ion o digi al echnologies, bo h should suppo mo e e ec i e oppo uni y
de elopmen , and he e o e, enhance he pe o mance o en ep eneu ial new businesses.
Howe e , hese assump ions ha e seldom been subjec ed o a di ec empi ical es , and he ew
es s ha ha e been conduc ed ha e mos ly aken place in he con ex o high-income Wes e n
economies, wi h only a e excep ions (Bouwman, Nikou, and De Reu e , 2019; Camu o e al.,
2019; Fe ei a, Fe nandes, and Fe ei a, 2019; Liu, Liu, and Gu, 2021). The e idence ega ding
he impac o digi aliza ion on en ep eneu ial pe o mance emains sca ce in gene al and
pa icula ly so o eme ging economies. This is an impo an gap, since eme ging economies
a guably s and o bene i he mos om digi aliza ion, as digi al echnologies o e he oppo uni y
o ca ching up h ough leap ogging s eps con en ionally equi ed o ad ance economic
de elopmen (Michelle, 2009; Xiong e al., 2021).
We add ess his gap by means o an in e iew su ey o ‘digi al en ep eneu s’ in six ASEAN
coun ies: Indonesia, Malaysia, he Philippines, Singapo e, Thailand, and Vie Nam. In a p ojec
sponso ed and coo dina ed by he Asian De elopmen Bank and conduc ed in collabo a ion wi h
esea ch eams om six leading academic ins i u ions om he six ASEAN coun ies, we iden i ied
and in e iewed a popula ion o 685 digi al en ep eneu s in hese coun ies, ocusing pa icula ly
on hei adop ion o digi al echnologies in hei business models, hei business model
expe imen a ion ac i i ies, and explo ed he implica ions o hese p ocesses o he business
pe o mance, and also, o hei pe o mance in e ms o con o ming o and ad ancing Uni ed
Na ions’ Sus ainable De elopmen Goals. We designed no el ope a ionaliza ions o business-
le el digi aliza ion and business model expe imen a ion in o de o es media ing ela ionships
be ween digi aliza ion, business model expe imen a ion, and business and sus ainabili y
pe o mance. Ou s uc u al equa ion modelling analysis e eals ha digi al echnology adop ion
by en ep eneu ial businesses is a po en enable o business model expe imen a ion, which is a
po en d i e o business and sus ainabili y pe o mance. Ou analysis also shows ha he
adop ion o digi al echnologies also exe cises a s ong di ec e ec o business and sus ainabili y
pe o mance in addi ion o i s media ing e ec h ough business model expe imen a ion, e ealing
ha digi al echnologies ha e b oad pe o mance implica ions o en ep eneu ial businesses.
Ou analysis makes se e al impo an con ibu ions. Fi s , his is one o he ela i ely ew s udies
con ibu ing insigh on he ela ionships be ween business model digi aliza ion, business model
expe imen a ion, and business and sus ainabili y pe o mance. The e idence con ibu ed in his
s udy should help in o m he design o en ep eneu ship and digi aliza ion policies. Second, we
con ibu e i s -hand e idence on he e ec o digi aliza ion on he pe o mance o en ep eneu ial
businesses in de eloping Asian economies, he eby add essing an impo an gap. Thi d, we
p o ide a heo y-g ounded accoun o how and why digi aliza ion should impac pe o mance in
en ep eneu ial new businesses, he eby illumina ing he mechanics o his impo an dynamic.
Fou h, we con ibu e new and enhanced ope a ionaliza ions o business model expe imen a ion,
digi al echnology adop ion in business models, and sus ainabili y pe o mance, he eby
acili a ing u he da a collec ion in his domain. Finally, we con ibu e e lec ions and insigh s o
en ep eneu ship policy design.
3
This epo is s uc u ed as ollows. We nex e iew heo izing on digi aliza ion, business models,
and en ep eneu ship. This e iew in oduces key ea u es o digi aliza ion, how i enables
business model inno a ion, and how i shapes and ans o ms en ep eneu ship and
en ep eneu ial oppo uni y pu sui . We hen cons uc ou heo e ical model, which explica es
ela ionships be ween business model digi aliza ion, business model expe imen a ion, and
business and sus ainabili y pe o mance. We hen desc ibe ou empi ical design and p esen ou
me hods, analysis, and indings. We conclude by discussing implica ions o policy and p ac ice.
2 Digi aliza ion, Business Model Inno a ion, and En ep eneu ship
2.1 T ans o ma i e P ope ies o Digi al Technologies and In as uc u es
Digi al echnologies possess se e al ea u es ha dis inguish hem om o he ad anced
echnologies and explain why hey a e exe cizing such a ans o ma i e impac on socie y. The
key dis inguishing ea u e o digi al echnologies is he e y ac ha hey a e digi al and no
physical, in he sense ha digi al echnologies a e de ined by hei digi al and logical ea u es and
less by hei physical cha ac e is ics (Yoo e al., 2012). Digi al echnologies a e Tu ing machines:
hey accep bi s as inpu and p oduce bi s as ou pu s. In o he ad anced echnologies, he key
p ope ies o he echnology—and he e o e, he echnological e ec p oduced—a e coded in
physical a angemen s o a oms in ma e . A machine ool shapes physical objec s wi h sha p
blades ha ha e hemsel es been machine ooled in o desi ed o m. An engine c ea es o a ional
mo emen by ha nessing he powe o bu inng uel ha is channeled o pis ons ha ope a e a
o a ing axis. A lase cu ing de ice c ea es he desi ed cu ing e ec by concen a ing la ge
amoun s o wa e-synch onized elec omagene ic adia ion in o a small space. In con as o
desi ed echnical e ec s p oduced h ough manipula ing physical a angemen s o a oms in
ma e , digi al de ices manipula e in o ma ion, as exp essed in bi s. Al hough hose bi s, oo, a e
ul ima ely coded in physical media (e.g., elec ons, pho ons), wha ma e s o he ope a ion o
he digi al de ice is he a angemen o hose bi s in he abs ac , and he logical algo i hms hey
can be designed o accomplish. As digi al de ices accep bi s as inpu s, and as he ins uc ion
se s ha in o m how o p ocess inpu s a e hemsel es exp essed as bi s, digi al de ices can be
lexibly ep og ammed o pe o m di e en unc ions wi h minimal cos and ene gy expendi u e.
In con as , physical echnologies a e asse speci ic: hey canno be easily epu posed o pe o m
di e en unc ions wi hou signi ican loss o u ili y o signi ican expendi u e o ene gy (Tilson,
Lyy inen, and Sø ensen, 2010).
The ep og ammabili y and consequen lexibili y o digi al echnologies means ha digi al
echnologies a e gene ic echnologies: hey can be lexibily combined wi h o he echnologies and
p og ammed o pe o m o enhance i ually any desi ed unc ion in any sec o . As gene ic
echnologies a e adap ed h ough he economy, hey will ine i ably p ecipi a e changes in how
he economy o ganizes i s unc ions and open oppo uni ies h ough hei inno a i e applica ion
and h ough he enablemen o new unc ionali ies (Yoo e al., 2012). The impac o digi al
echnologies is pa icula ly pe asi e, since digi al p og ammabili y enables he coding o complex
and knowledge-in ensi e unc ions ha migh no ha e been possible be o e. This ea u e, hen,
is he key d i e o digi aliza ion, o he applica ion o digi al echnologies in he economy and
socie y such ha hose echnologies become in as uc u al (Tilson, Lyy inen, and Sø ensen,
2010). Th ough he p ocess o digi aliza ion, digial echnologies and in as uc u es become a
4
co e elemen o he con ex in which business i ms o ganize o he c ea ion, deli e y, and cap u e
o economic and cus ome alue, allowing hese o pe o m desi ed unc ions in adically new
ways. A co e aspec o he p ocess o economic digi aliza ion is ha h ough hei pe asi e
applica ion, digi al echnologies open up new oppo uni ies o inno a i e combina ion o exis ing
unc ions and ac oss p oduc and sec o bounda ies. This makes digi aliza ion a po en d i e o
combina o ial inno a ion—i.e., he c ea ion o new unc ions and unc ionali ies by combining
exis ing unc ions (Hen idsson e al., 2018). This dynamic d i es digi ally-induced s uc u al
ans o ma ion by b eaking down ba ie s ha used o sepa a e con en ional indus y sec o s. As
all indus y sec o s inc easingly ely on he pe asi e digi al in as uc u e o hei ope a ion,
oppo uni ies o undamen ally e- hink how he economy and socie y migh wo k a e c ea ed and
he p ospec o no el combina o ial inno a ions enhanced, opening unp eceden ed oppo uni ies
o en ep eneu s o disco e , in en , and ad ance new digi al eali y.
When conside ing he e ec s o digi aliza ion on he o ganiza ion o economic, inno a i e, and
en ep eneu ial ac i i y, i is use ul o dis inguish be ween h ee mani es a ions o digi al
echnologies: digi al a i ca s, digi al pla o ms, and digi al in as uc u es (Nambisan, 2017).
Digi al a i ac s a e digi al componen s, applica ions, o digi al con en and media (including da a
and machine lea ning algo i hms) ha o e speci ic unc ionali ies o alue o he end use
(Kallinikos, Aal onen, and Ma on, 2013). Many digi al a i ca s esul om digi ally-induced
se i iza ion by which exis ing, o en physical se ices a e encoded in o digi al o m (e.g., in ech
applica ions), on he one hand, o by which physical a i ac s a e se i ized by w apping hem in o
a digi al en elope (e.g., ede ining con en ional ca owne ship as a se ice o e ed as pa o a
digi ally coo dina ed mobili y se ice). Such a i ac s exploi he abili y o digi al echnologies o
decouple physical o m om ela ed in o ma ion (Cecez-Kecmano ic e al., 2014). This enhances
combina o ial lexibili y, as digi al a i ac s can be easily combined wi h one ano he and wi h
digi al pla o ms o enable new unc ionali ies and applica ions, he eby boos ing inno a i e
expe imen a ion wi h no el combina ions.
Digi al pla o ms a e sha ed se s o se ices, a chi ec u es, in e aces, and echnical s anda ds
ha enable many hie a chically independen s akeholde s o make hei o e ings a ailable o wide
audiences and combine hei digi al a i ac s wi h hose o o he s (Gawe , 2020; Gawe and
Cusumano, 2008; Thomas, Au io, and Gann, 2014; Van Als yne, Pa ke , and Chouda y, 2016).
Al hough digi al pla o m ope a e as an impo an medium o dis ibu ing and accessing digi al
a i ca s, hey also ope a e hei own dynamic, as pla o m owne s seek o ha ness gene a i i y
and ne wo k e ec s o he c ea ion and cap u e o economic and use alue h ough, e.g., da a
ne wo k e ec s (G ego y e al., 2020). By ope a ing as enues ha enable la ge, non-
hie a chically ela ed audiences o coo dina e and combine hei ac i i ies, digi al pla o m
ecosys ems ha e eme ged as an impo an no el o m o economic o ganiza ion in hei own igh ,
ope a ing as hubs o wide- anging ac i i y sys ems (Thomas and Au io, 2020). So doing, hey
ha e been ans o ming en ep eneu ial oppo uni y landscapes and g ea ly expanding he each
o en ep eneu ial oppo uni ies o new audiences p e iously disconnec ed om hem.
Digi al in as uc u es a e de ined as digi al echnology ools and sys ems ha o e
connec i i y, communica ion, collabo a ion, and compu ing capabili ies o suppo inno a ion,
en ep eneu ship, and o he o ms o economic ac i i y (Nambisan, 2017). Digi al in as uc u es
p o ide he ab ic ha unde pins and enables mode n socie ies. Because o mobile connec i i y,
edge compu ing, In e ne o Things, cloud compu ing, and o he connec i i y echnologies and
digi al esou ces, i ually any hing anywhe e can be connec ed o digi al in as uc u es a any
11
- Reliance on Mobile and Web applica ions (ou business elies on... (1) ou own mobile
applica ions; (2) ou own applica ions in he In e ne )
- Reliance on Indus ial In e ne echnologies (ou business elies on... (1) In e ne o Things
(IoT), Indus ial In e ne o Things (IioT); (2) Robo ics, in elligen machine y; (3)
Blockchain, dis ibu ed ledge s)
The scale alues we e hen compu ed as weigh ed a e ages o indi idual s a emen s, using ac o
loadings as weigh s.
Applica ion o digi al echnologies in he i m’s business model. The applica ion o digi al
echnologies by he business que ied how he businesses used digi al echnologies in di e en
aspec s o hei business model. Fo hese scales we sough inspi a ion om p e ious li e a u e
on digi aliza ion and business models (e.g., Bouwman, Nikou, and De Reu e , 2019; Pa ida,
Sjödin, and Reim, 2019; P oksch e al., 2021). Consis en wi h ecei ed concep ualiza ions, we
de ined a business model as he i m’s a chi ec u e o ac i i ies o he c ea ion, deli e y, and
cap u e o cus ome alue (Zo and Ami , 2007, 2010). D awing on and inspi ed by ecei ed
heo y, p e ious empi ical ope a ions, and ou own easoning, we designed he ques ionnai e o
inco po a e a o al o 23 s a emen s que ying he applica ion o digi al echnologies in ou aspec s
o he i m’s business ope a ions: (1) in e nal ac i i ies (8 i ems); (2) ma ke ing, sales, and
cus ome in e ac ions (7 i ems); (3) p oduc s and se ices (3 i ems); (4) pa ne ships (4 i ems).
P incipal componen analyses yielded ou ac o s wi h Eigen alues g ea e han 1. A e emo ing
i ems wi h no s ong loadings on any ac o and i ems wi h s ong loadings on mo e han one
ac o , a o al o 17 indi idual i ems we e e ained: six o in e nal ac i i ies; six o ma ke ing,
sales, and cus ome in e ac ions; h ee o p oduc s and se ices; and wo o pa ne ships. The
scale alues we e compu ed as weigh ed a e ages o indi idual s a emen s, using ac o loadings
as weigh s. The scale composi ions a e shown in Table 1.
Table 1 Applica ion o Digi al Technologies in he Fi m’s Business Model: Scale
Composi ion
We a e in e es ed in how you use digi al echnologies in you business. How well do
he ollowing s a emen s desc ibe you ope a ions?
(1=no a all … 5=pe ec ly)
Scale I ems
In e nal
Ac i i ies
Ou human esou ce p ocesses a e ully digi alized (e.g., sala y paymen s,
ec ui men , aining…)
Ou cus ome managemen sys em and cus ome da abases a e ully
digi alized
Ou accoun ing sys em is ully digi alized
We use digi al echnologies and da a o op imize ou manu ac u ing,
se ice, and logis ics
We use digi al echnologies o esou ce and in en o y planning
We a e a ully da a-d i en company
Ma ke ing,
Sales,
Cus ome
In e ac ions
We ad e ise ou p oduc s and se ices p ima ily h ough digi al channels
We cons an ly use social media o in e ac wi h cus ome s (e.g., Facebook,
Ins ag am, TikTo
k
, LinkedIn, Twi e , Line)
We cons an ly moni o how ou cus ome s in e ac wi h ou websi e and
social media (e.g., clicks, iews, e c)
Con inued on he nex page

12
We a e in e es ed in how you use digi al echnologies in you business. How well do
he ollowing s a emen s desc ibe you ope a ions?
(1=no a all … 5=pe ec ly)
Ou cus ome s can o de o pay online (o bo h)
We ac i ely moni o ou online a ings and cus ome e iews online
We ope a e ou own online use communi y
P oduc and
Se ice
Ou p oduc s and se ices a e ully digi al
Ou p oduc s and se ices a e connec ed o a mobile app
We use digi al pla o ms o es new p oduc s and se ices and ge use
eedback
Pa ne ships
We ac i ely wo k wi h pa ne s o inc ease sales
We collabo a e wi h pa ne s o c ea e new se ices o ou cus ome s
Sou ce: Adap ed om Djukic (2024).
Business Model Expe imen a ion. In measu ing business model expe imen a ion, we wan ed
o cap u e he deg ee o which he i m had ecen ly adjus ed aspec s o i s business model. Any
change in he business model was in e p e ed as an expe imen o imp o e he business
ope a ion. Seeking inspi a ion om ecei ed empi ical and heo e ical li e a u e (e.g., Pa ida,
Sjödin, and Reim, 2019; Spie h and Schneide , 2016; Zo and Ami , 2007, 2010), we c ea ed 11
i ems ha que ied he deg ee o which he i m had changed any aspec s o i s business model
o e he pas yea (1=no change ... 5=comple e e- hink). A p incipal componen analysis showed
ha all s a emen s loaded cleanly on a single ac o . The scale alue was hen compu ed as he
weigh ed a e age o indi idual s a emen s, using ac o loadings as weigh s. The scale
composi ion o he business model expe imen a ion a iable is shown below.
Table 2 Business Model Expe imen a ion: Scale Composi ion
O e he pas 12 mon hs, ha e you changed any o he ollowing elemen s o you
business model?
(1=no change … 5=comple e e
-
hink)
Scale I ems
Business Model
Expe imen a ion
Ou a ge cus ome s and cus ome segmen
Ou sales and ma ke ing ope a ions
How we in e ac wi h ou cus ome s
How we make and deli e ou p oduc s and se ices
Ou pa ne ships (i.e., who we wo k wi h—o he han supplie s)
Ou supplie s
Ou p oduc s and se ices
Wha ac i i ies we do ou sel es and wha ac i i ies ou pa ne s do
How we gene a e e enue (e.g., how we cha ge o ou p oduc s)
Wha business oppo uni ies we add ess
Ou en i e business model—i.e., how ou company does business and
o ganizes i s ope a ions
Sou ce: Au ho s.
13
4.2.3 Ou come Va iables
We assessed wo se s o i m-le el pe o mance a iables in he s udy: business pe o mance
and sus ainabili y pe o mance. The i s se o ou come a iables measu ed he i m’s business
pe o mance and sough o cap u e any e ec s o i m-le el digi aliza ion on business
pe o mance, as media ed by he i m’s digi ally-enhanced abili y o expe imen wi h and adjus
i s business model o ake he bes possible ad an age o he business oppo uni y. The second
se o ou come a iables ocused on he sus ainabili y pe o mance o he business and sough o
cap u e any e ec o i m-le el digi aliza ion and business model expe imen a ion o h ee
dimensions o business sus ainabili y: en i onmen al sus ainabili y, social sus ainabili y, and
s akeholde wel a e.
In acking he business pe o mance o he i ms, we aced a dilemma o choosing be ween
co e age and da a quali y. Ou a ge popula ion was new, en ep eneu ial businesses ha used
digi al echnologies. No eadily a ailable eco ds exis ed acking hei inancial pe o mance. The
coun y eams also hough ha i he su ey we e o inqui e abou inancial de ails, his would
likely push up non- esponse a e and make i di icul o sample a la ge enough numbe o
companies. The e o e we op ed o mo e quali a i e p oxies o business pe o mance ha did no
equi e que ying po en ially sensi i e in o ma ion. Ins ead o measu ing pe o mance based on
accoun ing da a, we que ied business pe o mance in wo di e en ways. Fi s , we asked he
company o assess how well hei business had pe o med, as compa ed agains he goals and
expec a ions ha hey had had o hei companies 12 mon hs ea lie . Six s a emen s we e
de eloped, some o which ocused mo e on inancial pe o mance (sales g ow h, p o i abili y, and
numbe o paying cus ome s), and h ee ocusing mo e on ope a ional pe o mance (new p oduc s
and se ices, ope a ional e iciency, and abili y o he business o cope wi h he COVID-19 c isis).
Second, we asked he esponden s o compa e he pe o mance o hei business agains a ypical
compe i o o e he pas 12 mon hs. The same six scales we e used.
As expec ed, he pe o mance-agains -own-expec a ions s a emen s loaded on wo ac o s, bo h
o which had an Eigen alue o e 1. One se o s a emen s cap u ed inancial pe o mance and
he o he ope a ional pe o mance, as shown in Table 3. As be o e, he scales we e compu ed
as weigh ed a e ages o he s a emen s, using ac o loadings as weigh s.
Table 3 Business Pe o mance Agains En ep eneu ’s Expec a ions: Scale Composi ion
Compa ing agains you goals and expec a ions you had o he company one yea
ago, how well has you company pe o med du ing he pas 12 mon hs? (1=much
wo se … 5=much be e )
Scale I ems
Financial
Pe o mance
Agains
Expec a ions
Sales g ow h
P o i abili y
Numbe o paying cus ome s
Ope a ional
Pe o mance
Agains
Expec a ions
De elopmen o new p oduc s and se ices
E iciency o ou ope a ions
Ou abili y o cope wi h he COVID-19 c isis
Sou ce: Au ho s.
14
In con as o pe o mance agains own expec a ions, he s a emen s inqui ing he companies’
sel -assessed pe o mance agains ypical compe i o s all loaded on a single ac o wi h an
Eigen alue o e 1. This p obably e lec s he ac ha he en ep eneu s migh no ha e had a
de ailed unde s anding o he di e en aspec s o he pe o mance o hei compe i o s. In addi ion,
he s a emen conce ning abili y o cope wi h he COVID-19 pandemic did no load s ongly on
he ac o and was excluded om he inal composi e a iable. The s a emen s measu ing sel -
assessed pe o mance agains pee s a e shown in Table 4.
Table 4 Business Pe o mance Agains Pee s: Scale Composi ion
How does you company’s pe o mance compa e agains you ypical compe i o
o e he pas 12 mon hs?
(1=much wo se … 5=much be e )
Scale I ems
Pe o mance
Agains
Pee s
Sales g ow h
P o i abili y
Numbe o paying cus ome s
De elopmen o new p oduc s and se ices
E iciency o ou ope a ions
Sou ce: Au ho s.
Ou business pe o mance measu es being quali a i e sel -assessmen s, ou analysis does no
p o ide ‘ha d’ da a on inancial pe o mance. Howe e , quali a i e pe o mance me ics also ha e
ad an ages, especially when measu ing he pe o mance o new, en ep eneu ial businesses ha
a e s ill e ol ing apidly. Gene ally speaking, inancial pe o mance me ics apply bes o going
conce ns, who a e ully de eloped and es ablished as a s eady-s a e business ope a ion. I
usually akes oughly a decade o an en ep eneu ial business o each ha s age. Because
di e en en ep eneu ial businesses migh be going h ough di e en s ages in hei de elopmen ,
measu es o pe o mance agains he owne ’s easonable expec a ions may be less suscep ible
o bias esul ing om ha ac . In addi ion, ou measu e o ope a ional pe o mance also cap u es
some aspec o he esilience o he business in he ace o he COVID-19 pandemic, which would
ha e impac ed he su eyed businesses du ing he pe iod o s udy. Finally, pe o mance
expec a ions a e calib a ed by gene al pe o mance expec a ions in a gi en sec o , which is
help ul gi en he c oss-sec o na u e o ou sample.
Finally, we measu ed he sel -assessed sus ainabili y pe o mance o he businesses. Consis en
wi h UN Sus ainable De elopmen Goals and ela ed li e a u e, we sough sel -assessmen s o
h ee aspec s o business sus ainabili y: en i onmen al sus ainabili y, social sus ainabili y, and
s akeholde sus ainabili y (Fiksel, 2012; Lüdeke-F eund e al., 2018; Muhmad and Muhamad,
2020; Nikolaou, Tsalis, and E angelinos, 2019; Pa ida, Sjödin, and Reim, 2019; Robe s and
T ibe, 2008). En i onmen al sus ainabili y app oxima es he impac he business ope a ion has
on i s na u al en i onmen , o he size o i s ‘en i onmen al oo p in ’. A business wi h a la ge
en i onmen al oo p in would gene a e a la ge nega i e ex e nali y on i s na u al en i onmen .
Social sus ainabili y measu es he impac he business ope a ion has on i s local communi y a
la ge. A socially sus ainable business would c ea e a posi i e ex e nali y on i s local social
communi y. S akeholde sus ainabili y measu es how well he business ea s i s key
15
s akeholde s, such as employees, supplie s, and business pa ne s. A s akeholde sus ainable
business would ea i s s akeholde s ai ly and equi ably.
D awing on ecei ed li e a u e, we designed a o al o 21 s a emen s o measu e di e en aspec s
o business sus ainabili y pe o mance. Nine o hese measu ed en i onmen al sus ainabili y, six
s a emen s measu ed social sus ainabili y, and six s a emen s measu ed s akeholde
sus ainabili y. The p incipal-componen s ac o analysis (o hogonal a imax o a ion) e ealed
ha all s a emen s measu ing social sus ainabili y loaded on a single ac o wi h an Eigen alue
g ea e han 1. Fou o he i e s a emen s measu ing s akeholde sus ainabili y also loaded on a
single ac o . Howe e , he s a emen s measu ing en i onmen al sus ainabili y loaded on wo
sepa a e ac o s, each wi h an Eigen alue o e 1. A close inspec ion e ealed ha h ee o he
s a emen s measu ed he en i onmen al sus ainabili y, as p ac iced in he in e nal ope a ions o
he business. Six o he s a emen s measu ed ex e nally-o ien ed en i onmen al sus ainabili y, as
e lec ed in he sus ainabili y mission o he business. The s a emen composi ion o he ou
measu es o sus ainabili y pe o mance a e shown in Table 5.
Table 5 Business Sus ainabili y Measu es: Scale Composi ion
We a e in e es ed in any ac ions you may ha e aken o enhance he en i onmen al
and social sus ainabili y o you business. How well do he ollowing desc ibe you
company?
(1=no a all … 5=pe ec ly)
Scale I ems
En i onmen al
Sus ainabili y
(in e nal)
We go well beyond he minimum equi ed by legal au ho i ies o
minimize any nega i e impac o ou business on he en i onmen (e.g.,
was e, ecycling, e c)
We ake g ea e o o use enewable and en i onmen ally iendly
ma e ials in ou p oduc s and ope a ions
We ecycle all ou was e
En i onmen al
Sus ainabili y
(ex e nal)
We ha e applied o o been awa ded a g een label o ce i ica ion
We moni o ou supplie s closely o ensu e hey a e en i onmen ally
sus ainable
We o en dona e o en i onmen al causes
We ha e a clea ly de ined mission o help sa e he en i onmen and
plane
We a e widely ecognized as an en i onmen ally iendly company
We ha e a sys em in place o ensu e we keep ocused on en i onmen al
iendliness
Social
Sus ainabili y
We go well beyond he minimum equi ed by legal au ho i ies o
minimize any nega i e impac o ou business on ou local communi y
We ake g ea e o o make a posi i e con ibu ion o he social
communi y whe e we ope a e
We ha e a clea ly de ined social mission in addi ion o ou business
mission
We o en dona e o hose in need
I is e y impo an o us o be a good co po a e ci izen in ou
communi y
Con inued on he nex page
16
We a e in e es ed in any ac ions you may ha e aken o enhance he en i onmen al
and social sus ainabili y o you business. How well do he ollowing desc ibe you
company?
(1=no a all … 5=pe ec ly)
We ha e a sys em in place o ensu e we keep ocused on ou social
mission
S akeholde
Sus ainabili y
We ake ex a e o o ea ou employees well, like amily
I is e y impo an o us o ea ou supplie s and pa ne s ai ly and no
ake un ai ad an age o e hem
We pay close a en ion o wo kplace sa e y
I is impo an o us o ea all ou employees equally ega dless o
gende , age, e hnici y, o eligion
Sou ce: Au ho s.
5 Analysis and Findings
We es ed wo media ion models o e i y ou hypo heses. These we e: H1 Digi al Technology
Adop ion enables Business Model Expe imen a ion; H2 Business Model Expe imen a ion D i es
Business Pe o mance; H3 Business Model Expe imen a ion D i es Sus ainabili y Pe o mance;
and H4 Business Model Expe imen a ion media es he impac o Digi al Technology Adop ion on
Business and Sus ainabili y Pe o mance.
All hypo hesis es s we e ca ied ou wi h s uc u al equa ion modelling, using he ‘sem’ command
o S a a 12. S uc u al equa ion modelling o e s he bene i o allowing o es ima e he sha e o
he media ed in luence o independen a iables on he ou come a iable ela i e o he di ec
in luence o hese on he ou come a iable. In o he wo ds, i pe mi s he es ima ion o he ela i e
s eng h o media ion in he model.
Table 6 shows sample desc ip i es by coun y. The mean age in he o e all sample was 4.4 yea s
and he mean employmen size ( ull- ime equi alen s) was 38.6 employees.
Table 6 Sample Desc ip i es by Coun y
Coun y n Mean
(age)
Min
(age)
Max
(age)
Mean
(size)
Min
(size)
Max
(size)
Indonesia 114
5.5 0 38 57.1 0 588
Malaysia 139
3.5 0 8 22.0 1 500
Philippines 109
3.0 1 10 13.1 0 350
Singapo e 124
3.0 0 20 12.5 0 150
Thailand 100
4.1 0 12 39.8 0 588
Vie Nam 100
7.6 1 57 102.2 3 588
Employmen size was winso ized a 1%, hence max(size) o 588.
n=686.
Sou ce: Su ey da a.
Table 7 shows he co ela ion ma ix. We can see signi ican co ela ions among digi aliza ion
a iables, as expec ed. Fi m age exhibi s a nega i e bi a ia e co ela ion wi h business model
expe imen a ion, indica ing ha he equency o business model expe imen a ion ends o

17
a enua e o e ime. In e es ingly, he i m’s eliance on mobile and web applica ions is no
co ela ed wi h i s eliance on indus ial in e ne applica ions (IoT, IIoT, Robo ics, Blockchain).
Table 7 Co ela ion Ma ix
Va iables 1
2
3
4
5
6 7 8
1 Mobile and Web applica ion 1
2 IoT, IIoT, Robo ics, Blockchain 0.00
1
3 In e nal Ac i i ies 0.17*
0.23*
1
4 Ma ke ing, Sales, Cus ome
In e ac ions -0.01
0.10*
0.42*
1
5 P oduc s and Se ices 0.11*
0.48*
0.46*
0.27*
1
6 Pa ne ships 0.15*
0.21*
0.39*
0.23*
0.40*
1
7 Business Model Expe imen a ion 0.03
0.14*
0.13*
0.10*
0.20*
0.27* 1
8 En i onmen al Sus ainabili y
(in e nal) 0.19*
0.14*
0.08*
0.10*
0.09*
0.12* 0.09* 1
9 En i onmen al Sus ainabili y
(ex e nal) 0.09*
0.05
0.13*
0.09*
0.07
0.13* -0.02 0.00
10 Social Sus ainabili y 0.08*
0.15*
0.29*
0.31*
0.24*
0.28* 0.18* 0.40*
11 S akeholde Sus ainabili y 0.07
-0.07
0.17*
0.17*
0.00
0.15* 0.04 -0.05
12 Financial Pe o mance 0.07
-0.03
0.11*
0.16*
0.04
0.06 -0.02 0.02
13 Ope a ional Pe o mance 0.05
0.13*
0.29*
0.24*
0.19*
0.11* 0.17* -0.05
14 Pe o mance (pee compa ison) 0.11*
0.09*
0.33*
0.30*
0.14*
0.16* 0.13* 0.11*
15 Fi m Age 0.18*
0.18*
0.10*
0.05
0.07
0.12* -0.08* 0.20*
16 Fi m Size (FTE) 0.24*
0.14*
0.06
-0.01
0.01
0.05 -0.02 0.18*
* = p< 0.05, n=681.
Va iables 9
10
11
12
13
14 15 16
9 En i onmen al Sus ainabili y
(ex e nal) 1
10 Social Sus ainabili y 0.38*
1
11 S akeholde Sus ainabili y 0.23*
0.26*
1
12 Financial Pe o mance 0.00
0.03
0.05
1
13 Ope a ional Pe o mance 0.10*
0.16*
0.12*
0.00
1
14 Pe o mance (pee compa ison) 0.07
0.21*
0.14*
0.39*
0.43*
1
15 Fi m Age 0.03
0.10*
0.01
0.09*
0.02
0.12* 1
16 Fi m Size (FTE) -0.02
0.07
-0.01
0.01
0.04
0.09* 0.42* 1
* = p< 0.05, n=681.
Sou ce: Au ho s’ calcula ions.
18
Be o e conduc ing he media ion analysis, we i s conside he in luence o he eliance on mobile
and ixed-line In e ne applica ions on he p opensi y o he i m o expe imen wi h i s business
model. The esul s o his s uc u al equa ion modelling analysis shown in Table 8. The able
shows e ec s o di ec pa hways.
Table 8 In luence o Reliance on Digi al Tech Applica ions on Business Model
Expe imen a ion (Di ec Pa hways)
Business Model
Expe imen a ion
Coe .
S d.
E .
Reliance on Mobile and Web Applica ions 0.1148** 0.040
Reliance on Indus ial In e ne Applica ions 0.1715***
0.040
Con ols
Fi m Age Included
Employees (FTE) Included*
Malaysia Included
Philippines Included
Singapo e Included
Thailand Included
Vie Nam Included
*** = p<0.001, ** = p<0.01, * = p< 0.05, n = 681, One- ailed signi icances.
Sou ce: Au ho s’ calcula ions.
Table 8 con i ms he basic e ec o digi al echnologies on business model expe imen a ion:
g ea e eliance on mobile and web applica ions was s ongly associa ed wi h he likelihood o he
business in oducing non- i ial changes in i s business model o e he pas 12 mon hs (p<0.01**).
Simila ly, he eliance o he business on indus ial in e ne applica ions was also s ongly
associa ed wi h in oduc ions o non- i ial changes in he i m’s business model o e he pas 12
mon hs (p<0.001***). Bo h hese associa ions we e consis en wi h hypo hesis H1.
Rega ding con ol a iables, i m size was nega i ely associa ed wi h business model
expe imen a ion: businesses wi h a g ea e numbe o ull- ime equi alen employees we e less
likely o ha e in oduced non- i ial changes in hei business models o e he pas 12 mon hs.
Howe e , al hough s a is ically signi ican , he e ec size was mino . As such, his associa ion is
no su p ising, as la ge businesses end o be mo e ma u e and mo e likely o be in he scale-up
phase, whe e he business model is mo e likely o be se and he need o business model
expe imen a ion will g adually g ow smalle .
The e ec s o digi aliza ion o di e en aspec s o he i m’s business model a e shown in Table
9. We show he di ec e ec s o each o he digi aliza ion a iables sepa a ely—i.e., o in e nal
ac i i ies, ma ke ing and sales, p oduc s and se ices, and o pa ne ships. As can be seen in
he able, all digi aliza ion a iables exhibi ed s ong and s a is ically signi ican e e s on business
model expe imen a ion: g ea e deg ees o digi aliza ion in he i m’s ac i i ies we e associa ed
wi h g ea e likelihood o non- i ial business model changes du ing he pas 12 mon hs. These
indings u he ein o ce suppo o ou i s hypo hesis (H1): ha he applica ion o digi al
19
echnologies in he i m’s business model enhances he i m’s abili y o make changes o i s
business model, and he e o e, expe imen wi h al e na i e business model con igu a ions. No e
ha when en e ed oge he , he digi aliza ion o in e nal ac i i ies is shown as a non-signi ican
in luence on business model expe imen a ion. This is likely due o s ong co ela ions be ween
he digi aliza ion a iables, which may be con ounding he s uc u al equa ion modelling esul s.
Rega ding con ol a iables, i m size in ull- ime employees exhibi s a mild nega i e e ec on he
likelihood o business model expe imen a ion. O he coun y dummies, hose o he Philippines
and Vie Nam show signi ican nega i e e ec s, indica ing ha he in e iewed i ms in hese
coun ies we e less likely o epo business model changes o e he pas 12 mon hs.
Table 9 E ec o Digi al Technology Applica ion in he Fi m’s Business Model on
Business Model Expe imen a ion (Di ec Pa hways)
Digi aliza ion Va iables Model 1 Model 2 Model 3 Model 4
Digi aliza ion o In e nal
Ac i i ies
0.1395
***
Dig’n o Ma ke ing and Sales
0.1707
***
Dig’n o P oduc s and Se ices
0.1930
***
Dig’n o Pa ne ships
0.2823
***
Con ol Va iables
Fi m Age n.s.
n.s.
n.s.
n.s.
Employees (FTE) +
+
+
*
Malaysia n.s.
n.s.
n.s.
+
Philippines **
***
*
***
Singapo e n.s.
n.s.
n.s.
n.s.
Thailand n.s.
n.s.
n.s.
n.s.
Vie Nam ***
***
***
***
*** = p<0.001, ** = p<0.01, * = p< 0.05, + = p < 0.1, n = 681.
Sou ce: Au ho s’ calcula ions.
We nex conside he e ec s o digi aliza ion a iables on pe o mance. Table 10 shows he
e ec s o he eliance o he business on Mobile and Web Applica ions and on Indus ial In e ne
Applica ions, espec i ely, on sus ainabili y pe o mance and business pe o mance. The ‘Di ec
E ec ’ column shows he di ec e ec s o he p edic o a iables on pe o mance only. The
‘Indi ec E ec ’ column shows only he e ec s o he eliance o digi al applica ions on
pe o mance, as media ed h ough hei e ec on business model expe imen a ion. The ‘To al
E ec ’ column shows he combined di ec and media ed e ec s. The ‘% Med.’ column shows he
p opo ion o he e ec o he independen a iables ha we e media ed h ough hei e ec on
business model expe imen a ion. Fo simplici y, we do no show he e ec s o con ol a iables,
al hough hese we e included in all equa ions.
20
Table 10 E ec s o Reliance on Digi al Technologies on Sus ainabili y and Business
Pe o mance
Di ec
E ec
Indi ec
E ec
To al
E ec
%Med.
En i onmen al
Sus ainabili y (in e nal)
Business Model Expe imen a ion
Reliance on Mobile and Web Applica ions
Coe .
S d. E .
0.1125*** 0.0325
0.1538*** 0.0341
Coe .
0.0129*
S d. E .
(no pa h)
0.0058
Coe .
S d. E .
0.1125*** 0.0325
0.1667*** 0.0342
7.7%
Reliance
on Indus ial In e ne Applica ions
0.0442+
0.0345
0.0193**
0.0072
0.0635*
0.0343
30.4%
En i onmen al
Sus ainabili y (in e nal)
Business Model Expe imen a ion
Reliance on Mobile and Web Applica ions
Coe . S d. E .
0.0127
0.0382
0.1026**
0.0401
Coe .
0.0015
S d. E .
(no pa h)
0.0044
Coe .
S d. E .
0.0127*** 0.0382
0.1041***
0.0398
n.s.
Reliance
on Indus ial In e ne Applica ions
0.0758*
0.0405
0.0022
0.0066
0.078***
0.04
n.s.
Social Sus ainabili y
Business Model Expe imen a ion
Reliance on Mobile and Web Applica ions
Coe . S d. E .
0.2163***
0.0372
0.0489
0.039
Coe .
0.0248**
S d. E .
(no pa h)
0.0096
Coe . S d. E .
0.2163***
0.0372
0.0737*** 0.0397
33.7%
Reliance
on Indus ial In e ne Applica ions
0.0946**
0.0394
0.0371***
0.0108
0.1317*** 0.0399
28.2%
S akeholde Sus ainabili y
Business Model Expe imen a ion
Reliance on Mobile and Web Applica ions
Coe . S d. E .
0.092**
0.0375
0.0269
0.0394
Coe .
0.0106*
S d. E .
(no pa h)
0.0057
Coe .
S d. E .
0.092***
0.0375
0.0374*** 0.0393
28.2%
Reliance
on Indus ial In e ne Applica ions -0.0239 0.0398
0.0158*
0.0074
-0.0082***
0.0394
n.s.
Financial
Pe o mance ( s expec a ions)
Business Model Expe imen a ion
Reliance on Mobile and Web Applica ions
Coe . S d. E .
-0.0089 0.0394
0.0705*
0.0414
Coe .
-0.001
S d. E .
(no pa h)
0.0045
Coe . S d. E .
-0.0089***
0.0394
0.0695*** 0.0411
n.s.
Reliance
on Indus ial In e ne Applica ions
0.0039
0.0418
-0.0015
0.0068
0.0023*** 0.0413
n.s.
Ope a ional Pe o mance ( s expec a ions)
Coe . S d. E . Coe . S d. E . Coe . S d. E .
Business Model Expe imen a ion 0.1442 *** 0.0374
(no pa h)
0.1442 *** 0.0374
Reliance
on Mobile and Web Applica ions
0.0627+
0.0393
0.0166*
0.0072
0.0792*** 0.0394
20.9%
Reliance
on Indus ial In e ne Applica ions
0.1585*** 0.0397
0.0247**
0.0086
0.1832*** 0.0396
13.5%
Pe o mance
s Pee s
Business Model Expe imen a ion
Reliance on Mobile and Web Applica ions
Coe . S d. E .
0.1295*** 0.038
0.102**
0.0399
Coe .
0.0149*
S d. E .
(no pa h)
0.0068
Coe . S d. E .
0.1295*** 0.038
0.1168***
0.04
12.7%
Reliance
on Indus ial In e ne Applica ions
0.0843*
0.0403
0.0222**
0.0083
0.1066*** 0.0401
20.8%
Con ols
Fi m Age
Employees (FTE)
Malaysia
Philippines
Singapo e
included
included
included
included
included
included
included
included
included
included
included
included
included
included
included
Thailand
included
included
included
Vie Nam included included included
*** = p<0.001, ** = p<0.01, * = p< 0.05, + = p < 0.1. Two- ailed signi icances shown.
Sou ce: Au ho s’ calcula ions.
We i s conside he e ec o business model expe imen a ion on pe o mance. Looking a he
To al E ec column, we can see ha all associa ions be ween he business model
expe imen a ion a iable and he di e en ou come a iables a e s a is ically highly signi ican ,
con i ming he basic hesis ha business model expe imen a ion is an impo an d i e o bo h
sus ainabili y and business pe o mance. Howe e , o one pe o mance a iable— he i m’s
27
su ey da a om 681 digi al en ep eneu ial businesses om Indonesia, Malaysia, he Philippines,
Singapo e, Thailand, and Vie Nam.
Ou analysis p o ided b oad and consis en suppo o ou heo e ical model: he eliance o he
business on selec digi al applica ions and he digi aliza ion o di e en aspec s o he i m’s
business models we e ound o be po en d i e s o business model expe imen a ion in
en ep eneu ial businesses. Business model expe imen a ion was ound o be a po en p edic o
o bo h business pe o mance and sus ainabili y pe o mance. We also obse ed consis en
media ion e ec s o digi aliza ion a iables on pe o mance h ough hei e ec on business model
expe imen a ion, al hough he digi aliza ion a iables also exhibi ed s ong di ec e ec s on
pe o mance. This las obse a ion signals ha he adop ion o digi al echnologies by
en ep eneu ial businesses has mo e wide- anging bene icial impac s han hei acili a ing e ec
on business model expe imen a ion.
We conside he indings epo ed he e o be o signi ican alue o he design o en ep eneu ial
and digi aliza ion policies in Asian de eloping economies and in eme ging economies mo e
widely. Ou analysis poin s o impo an pe o mance implica ions o digi al echnology adop ion
by en ep eneu ial businesses. Because a non- i ial pa o his dynamic ope a es h ough
business model expe imen a ion, his makes digi al en ep eneu ial businesses po en d i e s o
digi al ans o ma ion in he economy. Uncons ained by legacy in es men in legacy business
models, en ep eneu ial businesses a e ee o explo e ways o ake ad an age in hei business
models o ad ances in digi al echnologies and in as uc u es. So doing, hey challenge
es ablished indus y incumben s who compe e wi h legacy business models, o cing hese o e-
s uc u e hei ope a ions in esponse. This dynamic should help d i e To al Fac o P oduc i i y in
he digi al economy. As digi aliza ion o e s p omise o de eloping economies o leap og s ages
in de elopmen , his dynamic means ha acili a ing he digi aliza ion o en ep eneu ial
businesses should be a high p io i y o go e nmen s in such economies. In p ac ice his means
in es ing in digi al in as uc u es, ex ending he geog pahical co e age o hese in as uc u es,
and making su e ha hose in as uc u es can be accessed a an a o dable cos . I is impo an
o de elop he digi al li e acy o en ep eneu s such ha hese will be be e posi ioned o bene i
om ad ances in digi al echnologies and in as uc u es. Go e nmen s should also in es in
acili a ing egional en ep eneu ial ecosys ems, as hese end o ope a e as impo an hubs o
business model expe imen a ion and inno a ion. Finally, because digi aliza ion ends o make
en ep eneu ial oppo uni y pu sui a iable and accessible ca ee op ion o inc easingly la ge
audiences, go e nmen s should make su e ha educa ional sys ems de elop en ep eneu ial
skills such as oppo uni y ecogni ion, ac ion o ien a ion, expe imen a ion, eamwo k, and
collabo a ion.
Al hough epo ing impo an e idence, his s udy is no wi hou limi a ions. In o de o secu e a
la ge enough esponden sample, we did no ask o inancial accoun ing da a om he
businesses. Ins ead, we used quali a i e pe o mance measu es, as sel - epo ed by he
in e iewed en ep eneu s. Al hough quali a i e pe o mance measu es ha e hei own
ad an ages as epo ed in he me hod sec ion, and al hough we belie e ou indings o emain
alid o al e na i e pe o mance measu es, we ne e heless belie e ha ou indings should
alida ed using a ious al e na i e pe o mance measu es, such as sales g ow h and p o i abili y.
Ano he limi a ion is ha we a e pe o ming ou analyses in c oss-sec ional da a in he absence
o longi udinal da abases eco ding da a on pe inen a iables. The e o e, ou causal in e ences
a e based on heo e ical easoning a he han di ec empi ical es ing. Fu u e s udies should

28
implemen longi udinal designs o alida e he indings epo ed he e. These limi a ions
acknowledged, we ne e heless hope ha policymake s in ADB egional membe coun ies will
ind ou indings inspi ing and use ul backg ound ma e ial o en ep eneu ship and digi aliza ion
policy design.
29
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ASIAN DEVELOPMENT BANK
ASIAN DEVELOPMENT BANK
6 ADB A enue, Mandaluyong Ci y
1550 Me o Manila, Philippines
www.adb.o g
ADOPTION OF DIGITAL TECHNOLOGIES,
BUSINESS MODEL INNOVATION,
AND FINANCIAL AND SUSTAINABILITY
PERFORMANCE IN START-UP FIRMS
E kko Au io, Chi aphol Chiyachan ana, Cyn hia Cas illejos-Pe alco in, Kun Fu,
Raymund Haba adas, Yo hin Jinja ak, Anang Mu iadi, Donghyun Pa k,
Pa a awan P asa nphanich, Pham Minh Quyên, and Willem Smi
ADB ECONOMICS
WORKING PAPER SERIES
NO. 734
July 2024
Adop ion o Digi al Technologies, Business Model Inno a ion,
and Financial and Sus ainabili y Pe o mance in S a -Up Fi ms
This epo examines how digi aliza ion a ec s i m pe o mance using su ey da a om 681 digi al
en ep eneu s in six Associa ion o Sou heas Asian Na ions (ASEAN) coun ies. I inds ha selec digi al
applica ions and i m’s business model digi aliza ion d i e business model expe imen a ion.
These indings unde sco e he signi ican alue o he design o en ep eneu ial and digi aliza ion policies
in Asian de eloping economies and in eme ging economies mo e widely. The analysis poin s o impo an
pe o mance implica ions o digi al echnology adop ion by en ep eneu ial businesses.
Abou he Asian De elopmen Bank
ADB is commi ed o achie ing a p ospe ous, inclusi e, esilien , and sus ainable Asia and he Paci ic,
while sus aining i s e o s o e adica e ex eme po e y. Es ablished in 1966, i is owned by 68 membe s
—49 om he egion. I s main ins umen s o helping i s de eloping membe coun ies a e policy dialogue,
loans, equi y in es men s, gua an ees, g an s, and echnical assis ance.