Business Models and Digital Technology Platforms: Implementation and Complexities for Digital Business

Ba czak, K zysz o
Book
Business Models and Digi al Technology Pla o ms:
Implemen a ion and Complexi ies o Digi al Business
Rou ledge S udies in Inno a ion, O ganiza ions and Technology
P o ided in Coope a ion wi h:
Taylo & F ancis G oup
Sugges ed Ci a ion: Ba czak, K zysz o (2024) : Business Models and Digi al Technology Pla o ms:
Implemen a ion and Complexi ies o Digi al Business, Rou ledge S udies in Inno a ion,
O ganiza ions and Technology, ISBN 978-1-040-05002-6, Rou ledge, Abingdon, Oxon,
h ps://doi.o g/10.4324/9781003473022
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Business Models and Digi al
Technology Pla o ms
This book examines he in luence exe ed by digi al echnology pla o ms (DTPs)
on changes o business models. The au ho iden i ies c i ical ac o s o he suc-
cess ul implemen a ion and usage o such pla o ms, including ba ie s which may
be ela ed, o example, o he absence o su icien knowledge abou DTPs o he
inabili y o ob ain a su icien amoun o inancial esou ces.
Business Models and Digi al Technology Pla o ms de elops a comp ehensi e
model o DTPs based on empi ical esea ch in Poland. I demons a es how pla o ms
in luence changes in he ope a ions o companies, hei le el o compe i i eness, he
consume ’s ole in he p ocess o join de elopmen o inno a ions and he consum-
e ’s expe ience as well as implica ions o he use o AI o he au onomy o DTPs.
This book o e s a unique, holis ic unde s anding o he complexi ies in ol ed
and showcases hei ole wi hin digi al business. Combining heo y wi h p ac ice,
his book is a aluable esou ce o esea che s and academics o business model
inno a ion, s a egic managemen , inno a ion managemen , digi al ans o ma ion
and o ganisa ional change.
K zysz o Ba czak is an academic esea che and assis an p o esso a he Fac-
ul y o Managemen o he Wa saw Uni e si y o Technology. In 2014 he com-
ple ed a pos g adua e in e na ional MBA (Mas e o Business Adminis a ion)
p og amme a he Wa saw Uni e si y o Technology Business School. (This p o-
g amme was es ablished by he Wa saw Uni e si y o Technology, HEC School
o Managemen – Pa is, London Business School and he No wegian School o
Economics.) In 2015–2021 he ollowed a doc o al p og amme a he Collegium
o Business Adminis a ion o he Wa saw School o Economics (academic disci-
pline: Managemen Science).
He is p o essionally associa ed as a ounde wi h he i s Digi al Technology
Pla o m o Renewable Ene gy Sou ces in Poland (h ps://easyoze.pl) and ounde
o he global Digi al Technology Pla o m Sola es PRO – a sales pla o m o RES
companies o he en i e wo ld (h ps://sola esp o.com).
Impac o A i icial In elligence in Business and Socie y
Oppo uni ies and Challenges
Da ide La To e, F ancesco Paolo Appio, Ha em Mas i, F ancesca Lazze i
and F ancesco Schia one
Managemen Sys em o S a egic Inno a ion
Building Dynamic Capabili ies View o he Fi m
Mi su u Kodama
Digi al Business S a egy
Con en , Con ex and Cases
Ande s Peh sson
Cybe Secu i y and Business In elligence
Inno a ions and Machine Lea ning o Cybe Risk Managemen
Edi ed by Mohammad Zoynul Abedin and Pe Hajek
In e ne o Things in he Food Indus y
Challenges and Oppo uni ies o he In e ne o Food Things
Edi ed by Anna Rogala, Rena a Nes o owicz and Ewa Je zyk
Co po a e En ep eneu ship and Inno a ion in Tou ism and Hospi ali y
Global Pos Co id‑19 Reco e y S a egies
Edi ed by Te esa Aguia ‑Quin ana, Jona hon Day and F ancisca Rosa Álamo Ve a
G ass oo s Inno a ion
Discou se, Policy and P ac ice in he Global Sou h
Heman Kuma and Gau am Sha ma
Business Models and Digi al Technology Pla o ms
Implemen a ion and Complexi ies o Digi al Business
K zysz o Ba czak
Fo mo e in o ma ion abou his se ies, please isi : www. ou ledge.com/Rou ledge‑S udies‑in‑
Inno a ion‑O ganiza ions‑and‑Technology/book‑se ies/RIOT
Rou ledge S udies in Inno a ion, O ganiza ions and Technology
Business Models and Digi al
Technology Pla o ms
Implemen a ion and Complexi ies
o Digi al Business
K zysz o Ba czak
LONDON AND NEW YORK

Fi s published 2024
by Rou ledge
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© 2024 K zysz o Ba czak
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asse ed in acco dance wi h sec ions 77 and 78 o he Copy igh , Designs and
Pa en s Ac 1988.
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com, has been made a ailable unde a C ea i e Commons A ibu ion-
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A ca alogue eco d o his book is a ailable om he B i ish Lib a y
ISBN: 978-1-032-75229-7 (hbk)
ISBN: 978-1-032-75234-1 (pbk)
ISBN: 978-1-003-47302-2 (ebk)
DOI: 10.4324/9781003473022
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The publica ion is co- inanced by he s a e budge unde he p og am o
he Minis e o Educa ion and Science called “Excellen Science”, p ojec
numbe DNM/SP/548969/2022, amoun o co- inancing: PLN 79,927.05,
o al alue o he p ojec : PLN 88,809.22.
Con en s
Lis o Figu es ii
Lis o Tables ix
Lis o G aphs xi
In oduc ion 1
1 Digi al T ans o ma ion o Businesses 5
1.1 The O igin o Digi al Technologies 5
1.2 Di e si y o Digi al Technologies 8
1.3 Digi al T ans o ma ion o a Company Viewed as a P ocess 12
1.4 O ganisa ional Changes Accompanying Digi alisa ion 18
1.5 Impac o Digi alisa ion on Company Managemen 21
2 Digi al Technology Pla o ms 30
2.1 Concep o a Digi al Technology Pla o m 30
2.2 P ope ies o Digi al Technology Pla o ms 34
2.3 Typology o Digi al Technology Pla o ms 39
2.4 Global Ma ke o Digi al Technology Pla o ms 47
2.5   Fields o  Applica ion and Achie ed Bene i s  53
2.6   De elopmen  P ospec s Based on A i icial In elligence  62
3 Inno a i e Changes o Business Models 71
3.1 Business Model – Theo e ical App oach 71
3.2 The Essence o Inno a i e O ganisa ion 76
3.3 Concep and Model o Digi al Business 80
3.4 Inno a i e Changes o he Business Model Based
on a Digi al Technology Pla o m 83
3.5 Impac o Changes in Business Models on he
Compe i i eness o Companies 89
3.6 De elopmen P ospec s o Digi al Business Models 92
i Con en s
4 Findings o Empi ical Resea ch 102
4.1 Resea ch Me hodology 102
4.2 Changes o Business Models Based on Technology
Pla o ms 110
4.3 A Consume as a Co‑O igina o o Inno a i e Changes
o Business Models 140
4.4 Digi al Oppo uni ies o Expanding Consume
Expe ience 143
4.5   A i icial In elligence as a Fac o  Inc easing  he Au onomy
o Digi al Pla o ms 146
Final Conclusions 151
Appendix 1: Su ey Ques ionnai e 155
Appendix 2: Tabula Resul s o Quan i a i e Da a Collec ed
du ing he CATI Su ey 163
Re e ences 175
Index 189
Figu es
1.1 “Wa es” o economic de elopmen acco ding o J. Schumpe e
and his ollowe s 6
1.2 A eas whe e digi al ans o ma ion is implemen ed in a company 14
1.3 A eas o digi al ans o ma ion acco ding o Q. Co e
and G. Elkhuizen 15
1.4 S ages o digi al ans o ma ion o a company acco ding o B. Solis 16
1.5 A eas o o ganisa ional changes esul ing om digi alisa ion 19
1.6 E olu ion o o ganisa ional s uc u es o con empo a y
companies om a model cha ac e is ic o he indus ial age o a
model o he age o knowledge 21
1.7 Key aspec s o ma ke ing in a digi al company 24
2.1 Componen s o a business ecosys em 36
2.2 Classi ica ion o digi al echnology pla o ms acco ding
o H. LeHong, C. Howa d, D. Gaughan, D. Logan 40
2.3 Types o digi al pla o ms in his o ical pe spec i e acco ding
o he UN 44
2.4 Planned a chi ec u e o he Polish A i icial In elligence Pla o m
wi h he use o he Polish Da a In eg a ion Hub 63
3.1 A empla e acco ding o he concep o Business Model Can as 75
3.2 T iple Helix Theo y 79
3.3 VOPA leade ship model 88
3.4 Sha ing Business Model Compass 95
3.5 The T iple Laye ed Business Model Can as a chi ec u e 97
4.1 Componen s o he op imal scaling model p oduced wi h he
op‑down me hod – isual in e p e a ion aking in o accoun he
p opo ional impo ance o each ac o in he model 116
4.2 Digi al echnology pla o m as a ool o companies’ coope a ion
wi h consume s 142
2 In oduc ion
in ensi ely. This c ea es he need o ake a scien i ic app oach o digi al echnology
pla o ms and ill in he gap a ising om he absence o a su icien ly b oad discus-
sion in he li e a u e on he subjec ma e ega ding he impac o he pla o ms on
digi al business and companies’ capabili ies o implemen hem.
The main pu pose o his monog aph is o examine he in luence exe ed by
digi al echnology pla o ms on changes o business models. The u ili a ian aim
is o iden i y c i ical ac o s o he success ul implemen a ion and usage o such
pla o ms, including ba ie s which may be ela ed, o example, o he absence o
su icien knowledge abou digi al echnology pla o ms o he inabili y o ob ain a
su icien amoun o inancial esou ces.
De ailed objec i es ela ed o he o egoing include he scope and na u e o ben-
e i s ha may be gene a ed owing o he use o digi al echnology pla o ms as
well as business a eas whe e hey may be u ilised. Mo eo e , wha should be also
no ed is he desi e o ul il aims and objec i es ela ing o de e mina ion o he
ex en o which Polish companies a e p epa ed o implemen digi al echnology
pla o ms and he deg ee o which Polish businesses and manage s a e awa e how
such pla o ms may be used. Thus, he scien i ic aim o his monog aph may be
di ided in o wo basic a eas. The i s one conce ns he bene i s associa ed wi h
he implemen a ion o digi al echnology pla o ms, while he o he one is abou
hei p ac ical use by Polish companies. The achie emen o he said aims will help
answe he ollowing ques ions: Should digi al echnology pla o ms be ea ed
as me e suppo ing ools o he exis ing models used by speci ic companies?
Should hey be ega ded as he basis o he de elopmen and implemen a ion
o inno a i e changes o business models?
A discussion o hese opics equi es he o mula ion o speci ic p oblems and
esea ch hypo heses. The key esea ch p oblem has been de ined as ollows:
Wha is he ole played by digi al echnology pla o ms in he p ocess o p epa -
ing and implemen ing business models in a company?
Conside ing ha his monog aph also ocuses on achie ing a u ili a ian aim, i is
wo h o mula ing a p oblem ela ing s ic ly o his aim. The p oblem in ques ion
conce ns he ba ie s which hinde he implemen a ion and use o digi al echnol-
ogy pla o ms.
Re e ing o he esea ch p oblem s a ed abo e, he ollowing cen al esea ch
p oposi ion has been pu o wa d:
Digi al echnology pla o ms a e ools suppo ing he unc ioning o companies
and o m he basis o implemen ing inno a i e changes o business models.
The cen al p oposi ion is supplemen ed by he ollowing mo e de ailed hypo heses:
H1. Digi al echnology pla o ms acili a e he in oduc ion o changes o he ope a-
ions o companies, especially in he a ea o managemen , ma ke ing and sales.
H2. Inno a i e changes o he business model based on a digi al echnology pla -
o m make i possible o include he consume in he p ocesses o co‑c ea ing
inno a ions.
H3. Digi al echnology pla o ms c ea e new oppo uni ies, no encoun e ed o
da e, o inc easing cus ome expe ience.

In oduc ion 3
H4. The use o a i icial in elligence makes digi al pla o ms inc easingly mo e
au onomous in cus ome se ice applica ions.
H5. Digi al echnology pla o ms a e a new ac o o companies’ compe i i eness
in he digi al economy.
To e i y hese hypo heses, a su ey was conduc ed on a andomly selec ed g oup
o esponden s comp ised o people ep esen ing companies di ec ly in ol ed in
using digi al echnology pla o ms. To a ain he objec i es s a ed abo e and o
sol e he p oblems posed, i was necessa y o use h ee dis inc esea ch me h-
ods in his monog aph. The i s o hese, con en analysis o he li e a u e on he
subjec ma e , was applied du ing p elimina y s udies and a emp ing o con i m
he esea ch hypo heses. Du ing he analysis, he ollowing kinds o sou ces we e
examined – publica ions abou he concep o echnological de e minism, assigning
a c i ical ole o echnical and echnological issues and ela ed ans o ma ions in
shaping mode n socie y and he economy as well as showing he impac o digi al
echnology pla o ms on companies’ business ac i i ies.
The second me hod is called CATI o compu e ‑assis ed elephone in e iewing.
I is a modi ica ion o he classic me hod o quan i a i e esea ch – di ec s anda d-
ised in e iews using abula analysis ( wo‑ a iable ables) and induc i e es s o
in e ‑g oup di e ences.
The hi d esea ch me hod is called CATREG (ca ego ical eg ession) and akes
he o m o op imal scaling wi hin eg ession analysis o quali a i e a iables
whose pu pose is o assess quali a i e da a in quan i a i e e ms. Unde he me hod,
he co ela i es o opinions abou he deg ee o which DTPs impac he ope a ion
o companies we e aken in o conside a ion.
This monog aph is b oken down in o ou chap e s. The i s chap e discusses
basic issues conce ning he digi al ans o ma ion o companies. I desc ibes a -
ious aspec s o he o igin and di e si ica ion o digi al echnologies, he digi al
ans o ma ion o businesses iewed as a p ocess, o ganisa ional changes associ-
a ed wi h he ans o ma ion and he impac o digi isa ion on b oadly cons ued
company managemen .
The second chap e ocuses on he basic aspec s o digi al echnology pla o ms.
Fi s o all, based on he li e a u e, an o iginal de ini ion o he concep is p oposed,
wi h a speci ica ion o ea u es associa ed wi h he unc ioning o he pla o ms.
Wha ollows is a p esen a ion o ypologies o DTPs, a desc ip ion o he unc ion-
ing o he global ma ke o such pla o ms and an indica ion o ields whe e hey
may be used as well as bene i s achie ed om hei use. Fu he mo e, de elopmen
p ospec s o he pla o ms ha e been de e mined based on echnologies in ol ing
a i icial in elligence.
Chap e h ee deals wi h issues ha ing o do wi h inno a i e changes in business
models esul ing om he use o digi al echnology pla o ms. This, howe e , is
p eceded by a desc ip ion o he na u e o business models and inno a i e o gani-
sa ions as well as a p esen a ion o he concep and model o digi al business. Fu -
he mo e, ha pa o his monog aph desc ibes de elopmen p ospec s o digi al
business models, aking also in o conside a ion he use o DTPs.
4 In oduc ion
The ou h chap e p esen s indings o empi ical esea ch. The poin o
depa u e was a desc ip ion o he esea ch me hodology, showing how he model
o digi al echnology pla o ms was buil . Fu he on in he chap e , based on he
conduc ed su eys, each o he esea ch hypo heses is discussed, poin ing ou how
digi al echnology pla o ms in luence changes in he ope a ions o companies,
hei le el o compe i i eness, he consume ’s ole in he p ocesses o join de el-
opmen o inno a ions and he consume ’s expe ience as well as implica ions o
he use o a i icial in elligence o he au onomy o DTPs.
This monog aph is abou issues conce ning he science o managemen and
quali y. All pe inen analyses and hei indings may con ibu e in a signi ican
manne o he de elopmen o his scien i ic discipline. This wo k, o he i s ime,
aking in o conside a ion bo h Polish and o eign li e a u e, discusses ex ensi ely
he impac o digi al echnology pla o ms on inno a i e business models. The
discussion he ein ocuses no only on a ious aspec s o use ulness o digi al pla -
o ms in he con ex o de elopmen o mode n business models, including hose
based on consume s’ knowledge o expe ience, bu addi ionally examines which
a eas o companies’ ope a ions may be pe cei ed as especially a ou ably a ec ed
by DTPs and how impo an a i icial in elligence is in his espec . Such discus-
sions no jus deepen he esea ch oo ed in li e a u e ha has been pe o med o
da e bu also p o ide g ounds o aking up comple ely new issues in he science o
managemen and quali y. Thus, an impo an esea ch gap has been illed in ega d-
ing he knowledge o how mode n business models a e de eloped based on a ious
ypes o digi al pla o ms.
The cen al poin o he discussions in his monog aph is he cons uc ion o a
model o digi al echnology pla o ms based on indings om measu emen o com-
pany manage s’ a i udes o DTPs. The app oach o he esea ch p oblem p oposed
in his monog aph is inno a i e in na u e because, i s , no a emp has been made
so a o build such a model, and, second, such an app oach may o m he basis o
cons uc ing u he models o digi al echnology pla o ms which would ake in o
conside a ion o he a eas o business ac i i y, including, o example, hose which
conce n hei s ic ly echnical ( echnological) aspec s. De e mined on he basis o
analysis o li e a u e and indings o he au ho ’s own esea ch, hey may be used
by company manage s in managemen p ocesses. Owing o he cons uc ed model,
di ec ions o u he esea ch we e ou lined, no ing ha signi ican co ela i es
o a i udes o digi al echnology pla o ms may be ac o s conce ning he s uc-
u es o companies, including indus ies in which hey ope a e and he numbe o
employees. I is wo h emphasising ha a ce ain no el y is also he in eg a ion,
wi hin managemen heo y, o wo impo an esea ch me hods, namely a CATI
quan i a i e su ey and CATREG wi h op imal scaling. Such in eg a ion seems o
p o ide g ea possibili ies and, mos impo an ly, may b ing abou measu able e -
ec s, which is shown by he model p esen ed he ein. Acco dingly, his monog aph
demons a es he impo ance and he b ead h o pe spec i es o managemen and
quali y sciences b ough abou by he simul aneous use o such me hods.
DOI: 10.4324/9781003473022-2
1.1 The O igin o Digi al Technologies
In he con empo a y wo ld, digi al echnologies play an eno mous ole in he unc-
ioning o each coun y, socie y and o ganisa ion. Acco ding o E. B ynjol sson and
A. McA ee, “ he key building blocks a e al eady in place o digi al echnologies o
be as impo an and ans o ma ional o socie y and he economy as he s eam en-
gine.”1 In u n, A. Łaszek s a ed ha “o key impo ance o economic g ow h and,
consequen ly, o ou s anda d o li ing is he deploymen o new echnologies.”2
I is wo h no ing ha , con a y o appea ances, i is no ue ha such echnologies
we e in en ed and become popula only in he 21s cen u y. I needs o be obse ed
hough ha he 21s cen u y is p ecisely when he eno mous ole o echnologies
in he global economy became isible, o which, among o he ac o s, he in en-
si e de elopmen o mobile echnologies con ibu ed,3 bu hei o igin should be
al eady aced back o a much ea lie pe iod.
Digi al echnologies began o appea in he second hal o he 20 h cen u y. In li e a-
u e on he subjec ma e ,4 he i s men ion o he e m digi alisa ion (digi isa ion) wi h
e e ence o he wide‑ anging changes in he global economy in ol ing he inc eas-
ingly popula use o digi al echnologies is ound in a 1971 essay by R. Wachal en i led
“Humani ies and Compu e s. A Pe sonal View.”5 I discussed he impac on a ious
socie ies and hei membe s ha was o be exe ed by compu e s, which included u u e
social consequences o de elopmen o he ela ed echnologies. Such de elopmen ,
acco ding o R. Wachal, was likely o lead o he said digi alisa ion. A p esen , digi (al)
isa ion is hough o as a p ocess which in ol es he con e sion o analogue in o ma-
ion in o a digi al o ma . Such a p ocess is also desc ibed as digi al inclusion, which
is connec ed wi h he ac ha in he cou se o digi isa ion, an analogue i em is g adu-
ally ans o med in o a digi al o ma , wi h no o he subs an i e changes aking place.6
Impo an ly, acco ding o some au ho s, i is possible o alk abou digi (al)isa ion o
digi al echnologies wi h e e ence o a pe iod as ea ly as he 1950s.7
Analysing issues ega ding he o igin o he echnology, i is wo h going back
o he concep s which p oposed phases o economic g ow h in he wo ld. This is
because hose concep s ha e de o ed a lo o space o issues o ans o ma ion e-
la ed o digi alisa ion. One o hose concep s was de eloped by Aus ian economis
J. Schumpe e and con inua o s o his wo k, namely, C. F eeman and L. Soe e.
1 Digi al T ans o ma ion
o Businesses
This chap e has been made a ailable unde a CC‑BY‑NC‑ND license.
6 Digi al T ans o ma ion o Businesses
The au ho s dis inguished i e “wa es” in he cons uc ion o he global economic
sys em. They a e p esen ed in Figu e 1.1.
Analysing he concep o “wa es” o economic g ow h ad anced by J. Schum-
pe e and his con inua o s, i is clea ha he concep e e s o digi alisa ion and digi al
echnologies. Acco ding o his iew, a b eak h ough in he use o digi al ne wo ks
o new media occu ed a ound 1999, when hese in en ions began o impac , o an
inc easingly g ea e ex en , nume ous ans o ma ions in he wo ld economy o in he
sys em o goods and hei dis ibu ion. I is he e o e a conside ably la e pe iod han
he 1950s o 1970s, when people al eady s a ed alking abou he digi al o compu e
e olu ion.8 I should be poin ed ou , hough, ha J. Schumpe e and his ollowe s
dis inguished each “wa e” by aking in o conside a ion he decisi e impac ha each
in en ion had on economic de elopmen . In his espec , speaking o a “wa e” ela ed
o digi al ne wo ks o new media in he con ex o he u n o he 21s cen u y becomes
jus i ied, which ollows om he ac ha i was exac ly hen ha he use o he In e ne
s a ed o be mo e and mo e popula and ha has had p o ound impac on p omo ing
he use o knowledge being he main “d i ing o ce” o con empo a y economies.9
A di e en dis ibu ion o dis inc phases o economic g ow h was concei ed by
Ame ican w i e and u u ologis A. To le . In his opinion, he wo ld has wi nessed
h ee b eak h ough pe iods which should be e e ed o as “wa es,” jus like in
Schumpe e ’s concep . Fo he opics discussed in his wo k, he mos impo an o
hose is he hi d “wa e,” which, acco ding o A. To le , began o be obse able as
ea ly as in he second hal o he 1950s and whose mos dis inc i e ea u e became
he numbe o whi e‑colla wo ke s and se ice employees being highe han he
numbe o blue‑colla wo ke s. The e o e, e en as long ago as hen one could e e
o i as he age o a knowledge socie y, which has become o be cha ac e ised by
he mass use o digi al echnologies.10
Likewise, D. Bell, discussing he di ision o his o y in o de elopmen al pe i-
ods o socie y, dis inguished a phase inex icably connec ed wi h digi alisa ion and
an inc easingly mo e common use o digi al echnologies. He called ha phase a
pos ‑indus ial socie y o pos ‑indus ial economy. The mos impo an cha ac e is-
ics o his kind o economy men ioned by D. Bell include:
– shi ed impo ance o economic sec o s in he di ec ion o hose whose po en ial
is buil on knowledge;
– a change om ene gy‑based echnology p e ailing ill hen in o in o ma ion
echnology;
Figu e 1.1 “Wa es” o economic de elopmen acco ding o J. Schumpe e and his ollowe s
Sou ce: Au ho ’s own wo k based on A. Kukliński, Gospoda ka opa a na wiedzy jako wyzwanie dla
Polski XXI wieku, Komi e Badań Naukowych, Wa saw 2001, p. 14.
Digi al T ans o ma ion o Businesses 7
– inc eased impo ance o p ocesses associa ed wi h planning o moni o ing o
echnologies;
– explosi e g ow h o “in ellec ual echnology,” ha is one which is based o he
g ea es ex en on knowledge;
– domina ion o he se ice sec o .11
A eam o Ge man scien is s doing esea ch on echnology, ep esen ed by K.
Schwab, ou indus ial e olu ions a e alked abou , wo o which e e di ec ly
o he de elopmen o digi al echnologies. The hi d o hese was he compu e o
digi al e olu ion, which s a ed in he 1960s, when he p oduc ion o main ame
compu e s began (la ge‑sized compu e s o p ocessing qui e a lo o da a), and
con inued in he 1970s, when pe sonal compu e s appea ed, and in he 1990s, when
he In e ne was applied o comme cial pu poses. The ou h indus ial e olu-
ion is cha ac e ised by he dissemina ion o mobile echnologies (In e ne , sma -
phones, able s) o de ices based on a i icial in elligence.12
Following M. Olende ‑Sko ek, one may claim ha he e ha e been ou
indus ial (ci ilisa ion, echnological) e olu ions in he his o y o he wo ld,
each ma ked by a speci ic b eak h ough in en ion. Apa om s eam engine and
elec ici y, i was compu e and digi isa ion.13 Thus, he o igin o digi al ech-
nologies should be closely associa ed wi h he hi d and ou h e olu ions, he
o me e e ed o by many au ho s14 as he digi al e olu ion, while he la e
known as indus y 4.0 o digi alisa ion 4.0.15 The bi h o he digi al e olu ion
is usually da ed o he 1980s, al hough some au ho s a gue ha i al eady s a ed
in he 1950s16 o he 1960s.17 I s cha ac e is ic ea u e was a conside able ech-
nological p og ess, enabling he p omo ion o digi al solu ions, which g adu-
ally began supplan ing analogue de ices. A he same ime, compu e s s a ed
o a g ea e and g ea e ex en be used o pe o m speci ic p ojec s in a i ual
en i onmen .18 This e olu ion was ollowed by a s age e e ed o as indus y
4.0, which is also s ic ly ela ed o digi al echnologies and which in ol es
he cons uc ion o sma sys ems, inc easingly mo e in e connec ed, c ea ing
alue by ini ia ing and ein o cing coo dina ion and coope a ion among a ious
o ganisa ions and p ocesses.19
I should be no ed ha he digi al e olu ion would be impossible wi hou c ea -
ing condi ions o a as and au oma ed collec ion, p ocessing o ansmission o
in o ma ion. The e olu ion b ough abou he possibili y o gene a ing and ana-
lysing in o ma ion much easie han e e . I is he e o e jus i ied o s a e ha he
e olu ion accompanying digi al echnologies should be ac ually called a “digi al
in o ma ion e olu ion.”20
Nume ous di e se ac o s con ibu ed o he c ea ion and de elopmen o digi al
echnologies. The ollowing ones should be men ioned in his con ex :
– e e ‑inc easing echnological p og ess, educing ba ie s o access o in o ma ion;
– ee‑ma ke compe i ion;
– inc eased impo ance o knowledge wi hin he ope a ion o o ganisa ions;
– high supply o new p oduc s and se ices;

8 Digi al T ans o ma ion o Businesses
– need o inc easing e ec i eness and e iciency and educing he cos s o busi-
ness p ocesses and ope a ions o achie e a high le el o compe i i eness;
– g adual disappea ance o a ious ba ie s agains business exchange among
s a es, which made as e low o in o ma ion o goods possible, including
know‑how;
– unp edic abili y o economic and echnological de elopmen and high g ow h
a e o his de elopmen , making i necessa y o con inue seeking mo e and
mo e inno a i e and compe i i e sys ems, ools and solu ions;
– necessi y o sa is y inc easingly changing needs o cus ome s;
– equi emen ha o ganisa ions should adjus o he dynamic si ua ion in he
en i onmen .21
Based on he abo e desc ip ion, i may be concluded ha while he o igin o
digi al echnologies should be aced back o he 1950s o he 1960s, hei eal and
in ensi e de elopmen occu ed when he use o pe sonal compu e s and he In e -
ne became widesp ead. I should be ema ked a his poin ha only in he 1990s
did he e m “digi al economy” appea in scien i ic li e a u e. I was coined by
D. Tapsco . He claimed ha he new o m o he global economy di e s conside -
ably om he old economic o de , he g ea es di e ences being ha digi al econ-
omy is inhe en ly cha ac e ised by a quick u n o i ual eali y ( i ualisa ion), he
powe o digi al echnologies (digi isa ion and digi alisa ion), in eg a ion h ough
in e connec i i y, p omo ion o using and sha ing knowledge as an imma e ial as-
se by o ganisa ions as well as ein o cing he pu sui o inno a ion.22 So e en i
digi al echnologies s a ed o appea al eady in he middle o he 20 h cen u y, i
would be un easonable o alk abou hei ac ual de elopmen un il he second hal
o he 1990s o e en he beginning o he 21s cen u y.23
1.2 Di e si y o Digi al Technologies
Because digi al echnologies ha e been de eloping o many yea s, i is possible
now o dis inguish hei nume ous and di e se kinds. Bu i s , hese echnolo-
gies should be de ined. They a e gene ally ega ded as any sys ems, applica ions,
se ices o ools ha employ digi al echnique and IT sys ems. Such echnologies
may be also cons ued as a ype o o ganisa ional, echnical o economic ac i i y
which in ol es he adap a ion o new sys ems and digi al de ices o he ac i i y
conduc ed by companies in a ious segmen s o he economy o ma ke sec o s.
Fu he mo e, hey a e dis inguished by co e ing all he sys ems and ools which
use digi ally encoded con en , so mainly by a bina y (consis ing o he nume als
0 and 1) sequence o digi s which may be ead by speci ic elec onic de ices.24
Digi al echnologies unde s ood in his manne include no only he In e ne and
e e y hing ha is connec ed wi h i (in a– and ex ane s, i ual communi ies
and o ganisa ions, e c.), bu also he en i e cybe space o a ce ain en i onmen
which unc ions on he basis o mul iple sys ems, ne wo ks and ypes o so -
wa e and which enables an indi idual o an o ganisa ion o engage in di e se
ac i i ies.25
Digi al T ans o ma ion o Businesses 9
The e m digi al echnologies is e y o en used in e changeably and iden i-
ied wi h he e ms in o ma ion echnologies o in o ma ion and communica ion
echnologies (ICTs).26 I seems, howe e , ha such p ac ice is no jus i ied. This is
shown by he ac ha ICTs co e only he echnologies o collec ing, eco ding,
s o ing, p ocessing, analysing, syn hesising, sending and p esen ing da a and in o -
ma ion in elec onic o m, bu i is also possible, h ough hem, o c ea e and use
mul imedia messages, o communica e wi h o he en i ies o ensu e he secu i y o
a ious sys ems and da a.27 In u n, “digi al echnologies” a e a e m b oade han
ICTs, because such echnologies e e o any applica ions, In e ne ools o sys ems
which a e digi al in na u e and which a e used, o example, o pe o m p ocu e-
men , p oduc ion o dis ibu ion p ocesses. Thei essence is no simply he collec-
ion o p ocessing o ce ain da a and in o ma ion, bu also he ope a ion o many
o he p ocesses. Wha bo h o hem ha e in common is ha hey a e implemen ed
in a digi al en i onmen , so hei na u e and scope may be e y b oad. In addi ion,
i should be emphasised ha digi al echnologies, as desc ibed abo e, a e also pe -
cei ed as a o m o ac i i y whose e ec is o in oduce mode n digi al sys ems o
speci ic a eas o he economy.
I is wo h poin ing ou ha he cu en ans o ma ions, which a e ela ed o he
inc easingly s onge in luence o digi al echnologies o he unc ioning o s a es
and socie ies, a e desc ibed and classi ied in di e en ways by a ious au ho s. As
al eady men ioned abo e, such au ho s as J. Schumpe e would ega d such changes
as a ce ain s age o “wa e” in he de elopmen o he global economy. In he li e a-
u e, one may encoun e , hough, many o he e ms o desc ibe he p esen s a e o
he economy whe e digi al echnologies play an eno mous ole. Those e ms de e -
mine how digi al echnologies a e pe cei ed o classi ied. They include: cybe econ‑
omy, digi al economy, in o ma ion economy, new economy o web economy.28 The
e ms e e ing o digi al echnologies in he wo ld economy ha e been analysed by
M. Goliński wi h ega d o hei equency o appea ance in he In e ne . The analy-
sis has showed ha he mos equen ly used exp essions a e new economy, digi al
economy o indus y 4.0.29 Such s udies demons a e ha he hemes o digi (al)
isa ion and digi al echnologies, and hei impac on he global economy, is e y
wide‑ anging, which undoub edly ollows om he ac ha he e a e a g ea many
such echnologies now and hei numbe is on he inc ease all he ime.
A p esen , i may be qui e di icul o a emp o iden i y o classi y hese ech-
nologies, p ecisely because o hei la ge numbe and cons an de elopmen . Wha
is also g ea ly impo an he e is ha po en ial a eas whe e hese echnologies could
be used a e ex ended all he ime. Fu he mo e, inno a i e p ojec s and ac i i ies
a e ini ia ed wi h he aim o build comple ely new echnologies o in eg a e ones
which ha e al eady been used. In spi e o all o ha , many au ho s do a emp o
dis inguish he mos impo an digi al echnologies which a e cu en ly used. Ac-
co ding o J. Pie iegud, con empo a y digi al echnologies p ima ily include:
– hype connec i i y, which will be discussed below a leng h;
– In e ne o Things (IoT) and In e ne o E e y hing (IoE) – hese e ms e e o
a global ne wo k due o which hings, such as household appliances (in he case
10 Digi al T ans o ma ion o Businesses
o IoT) and also human beings and p ocesses (in he case o IoE) may collec ,
p ocess and sha e da a, o ins ance, abou he manne he hings a e unc ioning.
– applica ions based on cloud compu ing, which is a kind o se ice en i ely p o-
ided on a speci ic se e , which makes i unnecessa y o pu chase and ha e
specialis ha dwa e o so wa e;
– sys ems based on au oma ion and obo isa ion;
– echnologies which allow o collec ing and analysing big da a se s (big da a
analy ics, BDA), including hose based on he ope a ion o cloud compu ing
(big‑da a‑as‑a‑se ice, BdaaS);
– a i icial in elligence (AI), o any echnologies and sys ems making i possible
o machines o compu e p og ams o simula e and pe o m speci ic ope a ions
ypical o he human b ain;
– mobile sys ems which make i possible o pe o m speci ic ope a ions in he
In e ne in a wi eless manne ;
– mode n secu i y sys ems – assuming he o m o bo h de ini e p oduc s and
digi al pla o ms, gua an eeing o use s an e e ‑inc easing le el o secu i y;
– social media, which allow people o communica e and ini ia e a ious in e ac-
ions as well o sha e con en (e.g. Facebook, Twi e , Ins ag am, YouTube);
– models o mul i‑channel and omni‑channel dis ibu ion o p oduc s and se -
ices, whe e, apa om he adi ional channel, some p oduc s and se ices a e
also o e ed online.30
I should be emphasised ha wi hin he said echnologies, many o he ancil-
la y digi al ools, sys ems o solu ions may be dis inguished. So, o example, as
a In e ne o Things is conce ned, i is possible o dis inguish some o i s ypes
and modi ica ions, such as cybe physical sys ems (which con ol, among o he
hings, oad a ic, which is possible owing o in eg a ion o compu a ional algo-
i hms wi h physical sys ems), ne wo ked con ol, machine lea ning (sel ‑lea ning
o machines), high pe o mance compu ing (which e e o Big Da a) o embedded
sys ems (which allow o au onomous ope a ion o ca s o ai planes).31
Issues conce ning digi al echnologies ha e been discussed in one s udy on
digi al ans o ma ion p epa ed by he Eu opean Commission. I s a ed ha apa
om In e ne o Things, Big Da a and obo ics, digi al echnologies which a e he
mos impo an now and ha e he g ea es impac on he wo ld economy also in-
clude blockchain echnology (which is used o eco ding inancial ope a ions and
is open and anspa en wi hou , howe e , a cen alised o m), 3D p in ing and
ad anced manu ac u ing (which use sys ems, de ices and machines con olled by
compu e s o mic oelec onics and used o designing, manu ac u ing and ans-
po ing a ious p oduc s).32
In u n, in a epo p epa ed by UNCTAD (Uni ed Na ions Con e ence on T ade
and De elopmen ), many digi al echnologies a e men ioned and cha ac e ised as
“ on ie echnologies o he sus ainable de elopmen .” These a e said o include
In e ne o Things (IoT), 3D p in ing, 5G mobile phones, a ious da a sha ing ech-
nologies, massi e open online cou ses, sma elec ici y g ids and inancial ansac-
ion sys ems (e.g. digi al walle s o mobile money).33
Digi al T ans o ma ion o Businesses 11
The analysis made by D. Ba o ski, E. Bendyk, M. Filiciak and A. Płoszaj
lis s he mos impo an ends in digi al echnologies and mani es a ions o hei use
in he con empo a y wo ld. A lis o he mos impo an o hose is gi en in Table 1.1.
Among he mos impo an ends which a e ele an o digi al echnologies
he e a e many o hose in which he key ole is played by digi al echnology pla -
o ms. Such pla o ms, a e all, gi e g ounds o inc easing e ec i eness o he
pe o mance o dis ibu ion asks o globalisa ion o compe i ion, esul ing in, on
he one hand, he appea ance o comple ely new oppo uni ies o companies con-
nec ed wi h in e na ionalisa ion o ac i i y conduc ed by hem and acquisi ion o
new ou le s o hei own p oduc s, and on he o he , an inc ease in he le el o
compe i ion, en ailing, among o he s, a be e quali y o cus ome se ice.
Table 1.1 The mos impo an ends in digi al echnologies acco ding o D. Ba o ski, E.
Bendyk, M. Filiciak and A. Płoszaj
T ends in digi al echnologies Types o digi al echnologies
Au onomysa ion o cus ome s • Sys ems o cus omising he digi al o e
Cybo gisa ion • Con olling a sma phone wi h you oice,
which is a mani es a ion o close coupling o he
con empo a y human being wi h a ious sys ems,
applica ions and digi al de ices
Ne wo k dis ibu ion • Digi al echnology pla o ms
E olu ion o business models • SaaS – so wa e as a se ice, p o iding an access
o he licence au ho ising o use he so wa e
Globalisa ion o compe i ion • Digi al echnology pla o ms
Con e gence o bi s and a oms • 3D p in ing
Con e gence o ICT ne wo ks • T iple and quad uple play, o b oadband and
wi eless access o he In e ne
• In e ne o Things
Mobili y • Mobile In e ne , sma phones, mobile i s
s a egies, whe e mobile sys ems a e buil i s
be o e physical sys ems
Openness as a new business model • Cu a ed compu ing sys em, in which
he manu ac u e enounces con ol, o a
conside able ex en , o i s p oduc s in exchange
o coope a ion wi h o he companies o use s
hemsel es
Pla o misa ion • Digi al echnology pla o ms
Online a ailabili y o compu ing
esou ces
• Cloud compu ing
Ne wo k o Things (au onomysa ion
o elec onic de ices)
• Moni o ing o heal h condi ion o condi ion o
household appliances
Declining impo ance o
in e media ies
• Jus ‑in‑ ime sys em, making i possible o
pe o m deli e ies o aw ma e ials and p oduc s
exac ly a he momen when he e is demand o
hem
Exchangeabili y o unc ions among
de ices
• Home en e ainmen cen es making i possible o
use digi al con en on many di e en de ices
Sou ce: D. Ba o ski, E. Bendyk, M. Filiciak, A. Płoszaj, Cy owa gospoda ka. Kluczowe endy e‑
wolucji cy owej. Diagnoza, p ognozy, s a egie eakcji, MGG Con e ences, Wa saw 2012, pp. 14–43.
18 Digi al T ans o ma ion o Businesses
case so ha he le el o he company’s compe i i eness o pu sui o inno a ion
migh g ow as .
When iewed as a p ocess, hen, digi al ans o ma ion should be ega ded as
a sequence o p ecisely planned, hough ou , coo dina ed ac ions, implemen ed a
he le el o he en i e company, aiming o b ing abou he si ua ion whe e digi al
echnologies a e e ec i ely deployed in he company, which may con ibu e o
he achie emen o compe i i e ad an age and an app op ia e deg ee o inno a-
i eness. In p inciple, such ans o ma ion may be ca ied ou a each s age o a
company’s unc ioning bu a p esen , conside ing hype compe i ion, highly ola-
ile en i onmen and ex emely in ensi e de elopmen o digi al echnologies, i
becomes nea ly necessa y o ans o m o all he en e p ises ha s ill ope a e in a
adi ional manne .
1.4 O ganisa ional Changes Accompanying Digi alisa ion
In any case, digi alisa ion causes many changes o o ganisa ional na u e. Acco d-
ing o W. Dob owolski and A. Dob owolska, “scien i ic and echnological p o-
g ess, especially dynamic as ega ds IT solu ions, has an impac on he changes
in oduced o he o ganisa ion’s p ocesses.”50
Fi s , i should be no iced ha in he con empo a y wo ld, digi isa ion has
been p og essing e y quickly. I is p o ed by da a showing ha digi al echnolo-
gies a e sp eading in he wo ld much mo e in ensi ely han any o he in en ions
om he indus ial age. As an example, i may be obse ed ha while i ook
30 yea s o elec ici y o each 10% ma ke pene a ion in households in he
Uni ed S a es, he same p ocess o landline elephones ook 25 yea s, o ele i-
sion se s, mobile phones and pe sonal compu e s – 10 yea s, and able s – me ely
2.5 yea s.51 This shows how as digi alisa ion is sp eading in he wo ld. And he
p ocess ac ually applies no only o de eloped coun ies bu also o de elop-
ing ones. An example can be Vie nam, whe e compu e s we e launched wi hin
15 yea s a e hey we e in en ed, while o mobile phones and he In e ne , i
was me ely a ew yea s.52
Wha is also signi ican is ha in 2014, o he i s ime in his o y, he numbe
o use s o mobile de ices became highe han he numbe o desk op compu -
e s connec ed o he In e ne . Conside ing his, a ious companies o an inc eas-
ingly la ge ex en place an emphasis on using he mobile i s s a egy, whe e
mobile solu ions and echnologies a e implemen ed i s , be o e hose ela ed o
b ick‑and‑mo a ac i i ies.53 The ans o ma ions desc ibed abo e ha e a g ea im-
pac on he o ganisa ional sphe e o companies.
Digi alisa ion in companies may ake place a an e e ‑ as e a e due o many
a ious ac o s. Acco ding o D. And iessen, he mos impo an o hese include:
– globalisa ion, which has wo kinds o consequences – i s o all, i leads o he
de elopmen o a ious ypes o ies and co‑dependencies among s a es, socie-
ies o o ganisa ions, which b ings abou he necessi y o hei cons an coop-
e a ion, o a la ge ex en wi h he use o digi al echnologies, and u he mo e

Digi al T ans o ma ion o Businesses 19
o ces hose en e p ises which wan o be compe i i e o show hei uniqueness
based on wide‑ anging deploymen o in angible esou ces, such as knowledge
and expe ise;
– g adual de egula ion o key sec o s o he economy, such as anspo , elecom-
munica ions o powe indus y, which esul s in in ensi ica ion o global lows
o esou ces and in o ma ion;
– d ama ic echnology‑ ela ed changes which, h ough he eme gence o new in-
o ma ion echnologies o communica ion channels ( he global mobile phone
ne wo k, he In e ne ), lead o a conside able educ ion o cos s o acqui ing,
s o ing, p ocessing o sha ing in o ma ion.54
Fas p og ess o digi alisa ion en ails changes in company managemen . Ac-
co ding o a epo by Capgemini Consul ing and he MIT Cen e o Digi al Busi-
ness,55 o ganisa ional changes accompanying digi alisa ion can be seen in h ee
undamen al a eas o a company’s ope a ions. They a e p esen ed in Figu e 1.5.
As o he cus ome se ice a ea, digi alisa ion allows, p ima ily, o be e un-
de s anding and iden i ica ion o cus ome s’ needs. As a esul , esponding o hese
needs becomes e ec i e bu also new needs a e gene a ed. Fu he mo e, cus ome
segmen a ion is pe o med ully e ec i ely on he basis o he mass o da a col-
lec ed due o digi al echnologies as well as nume ous a eas o coope a ion c ea ed
be ween a company and cus ome s, o example, wi h ega d o he kind o o e ed
p oduc s o se ices o ways o deli e ing hem o loca ions o consump ion, in-
cluding, o example, digi al o sel ‑se ice sales.56
Wi h espec o ope a ional p ocesses, as a esul o he implemen a ion o digi al
echnologies, he p ocesses a e pe o med mo e e icien ly and comple ely new unc-
ions may be in oduced in hem. In addi ion, conside able oppo uni ies a e c ea ed
Figu e 1.5 A eas o o ganisa ional changes esul ing om digi alisa ion
Sou ce: Au ho ’s own wo k based on A. Sobczak, “Koncepcja cy owej ans o macji sieci o ganizacji
publicznych,” Roczniki Kolegium Analiz Ekonomicznych 2013, no. 29, p. 280.
20 Digi al T ans o ma ion o Businesses
o implemen ing some inno a ions o speci ic wo ks a ions. Such inno a ions
may pe ain, in pa icula , o doing wo k a any place and ime, de elopmen o
mul i‑channel, au oma ic ways o communica ion o inally sha ing one’s own p o-
essional knowledge in he wo kplace wi h o he company employees, o example
ia In ane o a icles published in a newsle e .57
Digi alisa ion also con ibu es o modi ying exis ing business models o c ea ing
en i ely new ones. In his espec , such models may unc ion based on a digi ally
modi ied ac i i y which ocuses on cons an expansion o he o e ing o p oduc s
and se ices, changing om physical o m o goods in o digi al o m and using
digi al packaging. Wha is also impo an is digi al globalisa ion o ac i i y, which
may ake place h ough in eg a ing a company wi h nume ous en i ies ope a ing on
he ma ke and o e ing by hem join digi al se ices.58
Acco ding o M. Goliński, digi alisa ion causes many ans o ma ions in he
unc ioning o companies. Fi s and o emos , hese amoun o:
– conside able inc ease in he lexibili y le el o each o ganisa ional s uc u e and
business p ocesses pe o med wi hin hose s uc u es;
– con inuously g owing e ec i eness o such s uc u es, which ansla es in o
mo e e ec i e pe o mance o s a egic objec i es;
– globalisa ion o conduc ed ac i i y, suppo ed by g adual emo al o o gani-
sa ional o language ba ie s as a esul o using mode n digi al echnologies,
including communica ion echnologies;
– accele a ed speed o esponding o changes aking place in he company’s
su oundings;
– possibili y o adjus ing he company’s o ganisa ional s uc u e exac ly o he
needs and expec a ions o no jus cus ome s bu also any o he s akeholde s
(supplie s, local au ho i ies, socie y in gene al), which is in u n conduci e o
building he so‑called expe ience economy;
– p omo ing and s eng hening he pu sui o inno a ion on a la ge scale, a each
le el o he o ganisa ional s uc u e, which becomes possible by gene a ing
comple ely no el consume needs;
– possibili y o o e ing sma p oduc s and se ices in which in o ma ion compo-
nen is playing an inc easingly g ea e ole;
– expansion o he ne wo k o business connec ions;
– dec ease o he ole o human ac o in mul iple o ganisa ional p ocesses, which
hen makes i possible o educe he isk o e o s made by manage s o employ-
ees while ul illing hei p o essional du ies;
– oppo uni ies o sha ing esou ces wi h o he o ganisa ions and business en i-
ies (known as sha ing economy).59
Digi alisa ion leads companies o g adual e olu ion, which ollows om he
ac ha hei o ganisa ional s uc u es a e ge ing close and close o a model ypi-
cal o he age o knowledge. This is shown in Figu e 1.6.
Among he mos impo an changes associa ed wi h he ans o ma ion o a
company om a model cha ac e is ic o he indus ial age o a model o he age o
Digi al T ans o ma ion o Businesses 21
knowledge, he ollowing should be men ioned: conside able s eamlining o he
o ganisa ional s uc u e, ocusing on p ocesses a he han unc ions, and on in an-
gible esou ces a he han on inancial o angible goods, dominance o eamwo k,
cons an implemen a ion o inno a i e ideas and ini ia i es as well as handing o e
ce ain managemen unc ions o specialised ex e nal en i ies (possibly on he basis
o ou sou cing).
I ollows om he abo e discussion ha o ganisa ional changes esul ing om
digi alisa ion a e complex in na u e. In u n, hey esul mo e han once in a com-
ple e me amo phosis o a company’s o ganisa ional s uc u e. The aim o such
ans o ma ion is o he company o use digi al echnologies e ec i ely, gene a e
inno a i e ideas and pu hem in o p ac ice and ake ad an age as a as possible
om employees’ skills, abili ies and knowledge.
1.5 Impac o Digi alisa ion on Company Managemen
Apa om he o ganisa ional sphe e, digi alisa ion also has a g ea in luence on
company managemen . As emphasised by E. Czyż‑Gwiazda,
uni e sal digi alisa ion […] c ea ed oppo uni ies o he eme gence o a new
digi al business model and he bi h o he so‑called digi al economy. I is
digi alisa ion ha de e mines he con empo a y le el o ope a ional e ec-
i eness o an o ganisa ion and implies deep changes in p oduc ion sys ems
and managemen sys ems o o ganisa ions.60
Figu e 1.6 E olu ion o o ganisa ional s uc u es o con empo a y companies om a model
cha ac e is ic o he indus ial age o a model o he age o knowledge
Sou ce: Au ho ’s own wo k based on K. Beye , Od epoki ag a nej…, op. ci ., p. 14.
22 Digi al T ans o ma ion o Businesses
Acco ding o O. Kohnke, digi isa ion makes i necessa y o company manage-
men o conside ou majo a eas. They a e as ollows:
– aligning leade ship o inc ease employees’ pa icipa ion in company manage-
men ac i i ies;
– mobilising he o ganisa ion o ac ion, including mainly o demons a e inno a-
i e a i udes on a la ge scale;
– building capabili ies, including digi al skills;
– ensu ing sus ainabili y o a company’s ope a ion, o example, by con inuing o
imp o e and modi y digi al echnologies used, aiming o espond o challenges
p esen ed by he ma ke mo e e ec i ely han o da e.61
The impac o digi alisa ion on he managemen sphe e is isible h ough c ea -
ing plen y o oppo uni y o company g ow h, which he eby en ails he na u e o
company managemen . Such oppo uni ies, which ollows om he concep ion o
c ea i e des uc ion p oposed by Joseph Schumpe e , a e p o ided by inno a i e
(and hus based on digi al echnologies) ac i i y s ic ly o ien ed o cus ome needs
and c ea ing hei needs, which is able o b ing abou collapse o en i e indus-
ies o economies i hey canno mee he equi emen s connec ed wi h building a
digi al economy. Due o he abo e, he e is a g ow h o compe i i eness o hose
companies whose ac i i y is based on digi al echnologies, which in u n c ea es
wide‑ anging p ospec s o managing hem and di ec ing hei de elopmen e -
ec i ely.62 I is wo h poin ing ou ha su eys conduc ed in 2015 by he Global
Cen e o Digi al Business T ans o ma ion showed ha by 2020, as many as 40%
o companies could disappea om he ollowing ma ke s as a esul o digi alisa-
ion: elecommunica ions, media, en e ainmen , comme cial and inancial, in spi e
o holding s ong ma ke posi ions now. I would be so jus because i is p ecisely
hose ma ke sec o s ha a e a ec ed mos by he changes associa ed wi h he im-
plemen a ion o cu ing‑edge echnologies.63
Digi alisa ion is u he mo e conduci e o in ensi e deploymen o mode n
echnological solu ions and hei in eg a ion, which is mani es ed, o ins ance, by
hype connec i i y,64 o omnip esen connec edness.65 This e m has been used o
he i s ime by Canadians, A. Quan‑Haase and B. Wellman. These au ho s no iced
ha in he con empo a y economy, eno mous numbe s o in e ac ions a e ini ia ed
and, wha is signi ican , hey do no e e o people only (P2P – people‑ o‑people),
bu also, mo e and mo e o en, people and machines (P2M – people‑ o‑machine)
o e en machines hemsel es (M2M – machine‑ o‑machine). This way, he dis-
cussed hype connec i i y akes place, wi h ools such as online messenge s, mo-
bile phones, e‑mail o Web 2.0 se ices.66 This omnip esen connec i i y makes i
easie o manage a company. I happens because a p esen , i akes a ew minu es
o e en seconds o ge in ouch wi h a pe son s aying se e al housand kilome es
away and u he mo e he oppo uni y o build long‑ e m business ela ions using
communica ion echnologies allows o ob aining da a and in o ma ion abou he
mos e ec i e ways o manage a company. Besides, many ba ie s connec ed wi h
space, ime, echnology, languages o indus ies a e disappea ing, which c ea es
Digi al T ans o ma ion o Businesses 23
nea ly unlimi ed oppo uni ies o managing an o ganisa ion. I is no i ele an ,
ei he , ha digi alisa ion en ails ull au oma ion o in o ma ion exchange and c e-
a es condi ions o de eloping comple ely new business models, inno a i e in o -
ganisa ional, echnological, social o cul u al e ms, based on a combina ion o
mode n digi al echnologies.67
I should be emphasised ha new echnologies make i necessa y o manage-
men o be based o a g ea ex en on a simply eno mous amoun o a ious kinds
o da a and in o ma ion. They a e needed o ge indispensable knowledge, which is
he ounda ion o he ope a ion o mode n o ganisa ions and which makes i pos-
sible o manage con empo a y companies on he basis o building and ein o cing
he pu sui o inno a ion, c ea i i y and en ep eneu ship.68 As al eady men ioned
in one o he p eceding sec ions, digi isa ion b ings along a conside able ola ili y
o condi ions in which a ious companies ope a e. One o he esul s o his as a
as he managemen sphe e is conce ned is ha in o de o measu e o ganisa ional
esul s, i is necessa y now o use much mo e complex and comp ehensi e a ios
han hose used se e al decades ago o e en be ween en and wen y yea s ago. Such
a ios ha e o co e no only inancial indica o s bu also hose which a e able o
measu e in angible alues, including hose connec ed wi h knowledge.69 He e, how-
e e , digi alisa ion no jus c ea es addi ional p oblems conce ning measu emen o
esul s bu u he mo e p o ides en i ely new possibili ies in his a ea. I is a ac ,
a e all, ha , o example, big da a sys ems c ea e ample oppo uni y o collec ing
nea ly unlimi ed amoun o da a o pe o m complex measu emen s on hem.70
Managing a digi al en e p ise, compa ed o a adi ional o ganisa ion, has o a
much g ea e deg ee s a egic and social cha ac e . This means being o ien ed no
jus s ic ly o he ope a ional o in e nal sphe e o he o ganisa ion bu being based
on es ablishing b oad ela ions wi h a ious s akeholde s. Such ela ions may aim,
o ins ance, a coope a ion in he a ea o pe o ming complex, ad anced, inno a-
i e p ojec s o sha ing speci ic digi al echnologies. Thus, digi alisa ion make com-
pany managemen o become inc easingly open o in luences om he ou side.71
Unde he in luence o digi alisa ion, managemen unde goes a majo e olu ion
wi h ega d o ma ke ing. Conside ing a wide access o socie y o digi al ech-
nologies, including also he elde ly, as well as a a ie y o a ailable ma ke ing
o ms, managing a digi al en e p ise in he sphe e o ma ke ing mus be based on
possibly mos widesp ead ac i i ies. I is impo an ha hese ac i i ies should be
ca ied ou all he ime, e en 24 hou s a day ( his is possible, o example, wi h
online ad e isemen s), should be add essed o all g oups o consume s, should
use on a la ge scale all ypes o digi al echnologies (mobile apps, social media,
cloud compu ing), exploi ing hei in e ac i e na u e. Fu he mo e, hese ac i i ies
should con ey as much con en as possible, p o iding in o ma ion no only abou
speci ic ea u es o a p oduc o se ice bu also abou added alue o sma o e s.72
This is shown in Figu e 1.7.
Manage s a e signi ican ly a ec ed by changes esul ing om digi alisa ion.
This is because he implemen a ion o digi al echnologies o ces hem o acqui e
comple ely new compe ences and o change hei app oach o many issues in he
a ea o managemen . I is cha ac e is ic in ha ega d ha digi alisa ion causes

24 Digi al T ans o ma ion o Businesses
each manage o ac in a decen alised and lexible manne , adjus ing leade ship
s a egies o make i possible o ensu e he highes le el o inno a ion, o ge he
ull inno a ion po en ial ou o hei employees and o use digi al echnologies
as e ec i ely as possible. In addi ion, a mode n manage is obliged o es ablish
and suppo he unc ioning o eams o wo king p ojec s and o use new media
o communica e wi h employees.73 Wha plays an eno mous ole is also p o iding
employees wi h he oppo uni y o ake an ac i e pa in he pe o mance o man-
agemen asks and making decisions o key impo ance om he pe spec i e o
ensu ing he app op ia e le el o inno a i eness and e ec i eness.74
Acco ding o W. Goncia ski, changes in he sphe e o managemen ollowing
om digi isa ion amoun o he cons uc ion o he so‑called managemen 2.0 (new
gene a ion managemen ). Such managemen is based on mul i‑aspec ual use o
digi al echnologies. The undamen al ea u es o such managemen include:
– limi ing hie a chical s uc u es in a ou o lexible, ne wo ked and decen al-
ised and la ened sys ems;
– using mo e and mo e complex digi al echnologies wi hin managemen o ela-
ions wi hin he o ganisa ion and hose which conce n ex e nal s akeholde s;
– a aching o e iding impo ance o esou ces which a e in angible in na u e;
– ans e ing a majo pa o an en e p ise o a i ual le el, con inuing, howe e ,
i s ac i i y in he eal zone;
Figu e 1.7 Key aspec s o ma ke ing in a digi al company
Sou ce: Au ho ’s own wo k based on W. Świeczak, “Wpływ współczesnych echnologii na zmianę
działań ma ke ingowych w o ganizacji. Ma ke ing 4.0,” Ma ke ing Ins y ucji Naukowych i Badawczych
2017, no. 26, p. 183.
Digi al T ans o ma ion o Businesses 25
– ocusing a en ion o he en i onmen , including cus ome s and hei needs;
– dispe sed leade ship based on limi a ion o di ec i e powe o manage s and
p omo ion o mul i ace ed coope a ion and use o collec i e in elligence;
– ac ing bo h on a global and local scale;
– con inual implemen a ion o mode n solu ions in he a ea o knowledge and AI
managemen o adjus o e e changing condi ions in he en i onmen ;
– cons an sea ch o inno a i e business models due o which i is possible o use
cu ing‑edge solu ions in managemen .75
Issues o he impac o digi alisa ion on he sphe e o company managemen
ha e been discussed in a syn he ic manne by K. Jasińska. The au ho singles ou
mani es a ions o he impac in he con ex o each unc ion o managemen . They
a e discussed in Table 1.2.
Table 1.2 Impac o digi alisa ion on a ious managemen unc ions
Managemen
unc ion
Impac
Moni o ing • S ong de e mina ion o ensu e sel ‑moni o ing o manage s and
employees
• Pu ing an emphasis on moni o ing e ec i eness o he pe o mance
o each p ocess
• Moni o ing esou ces, aking in o conside a ion g ow h possibili ies
and based on eedback ecei ed om employees
Mo i a ing • Rein o cing any a i udes p omo ing inno a ion by ewa ding hem
wi h bonuses
• P omo ing a managemen s yle based on building a leade posi ion
• Mo i a ing in o de o build new compe ences, including digi al skills
O ganising • Implemen ing a la o ganisa ional s uc u e
• O ien a ion owa ds pe o ming p ocesses gene a ing speci ic alues
• O ganisa ional cul u e p omo ing he pu sui o inno a ion
• Cons an de elopmen o new business models
• Risk aking
• Implemen ing s uc u es and solu ions in he a ea o knowledge
managemen and au oma ion
• Building s uc u es making i possible o acqui e, s o e and p ocess
da a o c ea e alue
• Sha ing in o ma ion and messages in an in e ac i e manne
• P o‑ac i e decision‑making
Planning • Fo mula ing plans on he basis o con inuous obse a ion o he
si ua ion in he en i onmen
• Analysing many al e na i e solu ions
• Sho ‑ e m planning o p ojec s being pe o med
• Taking digi alisa ion in o conside a ion in he company’s s a egy
• Ensu ing he oppo uni y o modi y plans
• Allowing o imp o isa ion in planning
Sou ce: K. Jasińska, “Konsekwencje cy yzacji gospoda ki dla sys emu za ządzania p zedsiębio s wem
z sek o a IT,” [in:] J. Gajewski, W. Pap ocki, J. Pie iegud, eds., Cy yzacja gospoda ki i społeczeńs wa.
Szanse i wyzwania dla sek o ów in as uk u alnych, Ins y u Badań nad Gospoda ką Rynkową – Gdańska
Akademia Bankowa, Gdańsk 2016, pp. 100–101.
26 Digi al T ans o ma ion o Businesses
Finally, one may desc ibe as an example a company whose way o managemen
was comple ely edi ec ed as a esul o using digi al echnology. The company’s
name is Nike. Managemen he e is a p esen s ongly o ien ed owa ds digi ali-
sa ion and in p inciple mos o pe haps e en all he managemen decisions a e
s ongly dependen on he use o mode n digi al echnologies. This can be seen p i-
ma ily in managemen decisions abou ma ke ing (p omo ing p oduc s by ini ia ing
a global dialogue abou heal hy li es yle o spo s e en s, ob aining in o ma ion on
cus ome s and hei p e e ences om he company’s ac i i y in social media), cus-
ome se ice (cus ome s may design he colou o oo wea on hei own), sales
(nume ous digi al p oduc s, such as spo bands which allow o moni o ing un-
ning pa ame e s bu also aking ad an age o a i ual aine ’s ad ice and making
da a on unning achie emen s a ailable o o he s) o dis ibu ion (online channel).
Fo Nike, digi alisa ion changed comple ely he managemen philosophy, as a e-
sul o which he company’s ac i i y may be conduc ed in a much mo e inno a i e
and complex manne han be o e.76
Summing up, i should be obse ed ha he essence o company managemen
h ough digi alisa ion is aiming di ec ly, i s , o ha e any p ocesses and ac ions
pe o med in a mos e icien , coo dina ed and e ec i e manne , using any a ail-
able digi al echnologies, and also, second, o c ea e, also wi h he use o hese
echnologies, he g ounds o es ablishing b oad coope a ion wi h any s akehold-
e s. Such managemen places an emphasis on inno a i eness, which hus gene a es
he need o a comple ely new app oach compa ed o he adi ional model o issues
connec ed wi h managing employees o con ac s wi h he en i onmen .
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Towa zys wo Za ządzania P odukcją, Zakopane 2018, pp. 641–642.
27 A.W. Tomaszewska, “Dos ęp do echnologii in o macyjno‑komunikacyjnych w
społeczeńs wie in o macyjnym. P zykład polskich egionów,” Ac a Uni e si a is
Lodziensis. Folia Oeconomica 2013, no. 290, pp. 25–26.
28 J. Unold, “Basic Aspec s o he Digi al Economy,” Ac a Uni e si a is Lodziensis. Folia
Oeconomica 2003, no. 167, p. 42.
29 M. Goliński, op. ci ., p. 179.
30 J. Pie iegud, op. ci ., s. 11; see also: A. Ghosh, D. Chak abo y, A. Law, “A i icial
In elligence in In e ne o Things,” CAAI T ansac ions on In elligence Technol‑
ogy 2018, ol. 3, no. 4, pp. 208–218; L. Wang, C.A. Alexande , “Big Da a Analy -
ics and Cloud Compu ing in In e ne o Things ”, Ame ican Jou nal o In o ma ion
34 Digi al Technology Pla o ms
2.2 P ope ies o Digi al Technology Pla o ms
Each DTP, in iew o he scope and na u e o conduc ed ac i i y, may ha e dis inc
cha ac e is ics. I is a ac , hough, ha abou a dozen ea u es may be ound which
a e common o all DTPs. These common p ope ies will be discussed a his poin .
Fi s , he p ope ies should be men ioned which a e inex icably connec ed wi h
digi al economy and which he e o e may be ex ended also o he sphe e o he
ope a ion o DTPs. These p ope ies include:
Table 2.1 The mos impo an de ini ions o digi al echnology pla o ms acco ding o
R. Sun, B. Kea ing and S. G ego
De ini ion
au ho s
Yea o o mula ing
he de ini ion
Digi al echnology pla o m
Banke 2011 A websi e ha allows pa icipan s o pe o m
ce ain ading p ac ices
Basole 2009 Mul i‑sided ma ke ha b ings oge he a ious
ypes o ma ke pa icipan s
Ceccagnoli 2012 The se o componen s used in common ac oss
a p oduc amily ha can be ex ended by new
applica ions
Fichman 2004 A gene al‑pu pose echnology ha includes a
a ie y o applica ions
Hei ko e 2012 A combina ion o ha dwa e, ope a ing sys ems
and app s o e
Ma kus and
Loebbecke
2013 A ool suppo ing business p ocesses which may
be simul aneously used by mul iple companies
Meye and
Selige
1998 A se o subsys ems ha o m a common
s uc u e om which de i a i e p oduc s can
be e icien ly de eloped and p oduced
Rai e al. 2006 A pla o m which enables eal‑ ime ans e o
in o ma ion be ween a ious applica ions and
unc ions ha a e dis ibu ed ac oss pa ne s
Richa dson 2014 A ool o building a business in as uc u e ha
shapes he capaci y o companies o launch
compe i i e ac ions
Saa ikko 2014 A co e o ixed se o a ibu es ha can be
ex ended and supplemen ed wi h applica ions
and unc ionali ies o he bene i o i s use s
Shaw and
Holland
2010 A s uc u al solu ion which makes i possible o
suppo de elopmen o some phenomena
Tan e al. 2015 Two‑sided ma ke s, which b ings oge he wo
dis inc sides (in e ac ing pa ne s) allowing
hem o bene i om ne wo k e ec
Taudes e al. 2000 A so wa e package ha enables he ealisa ion
o ce ain sys ems and applica ions
Tiwana 2015 “A echnological ounda ion” wi h a ious
in e aces used by ex ensions ha in e ope a e
wi h i
Giessmann and
S anoe ska
2012 A se o echnologies ha a e de eloped and
e ol e in ce ain sys ems
Sou ce: R. Sun, B. Kea ing and S. G ego , op. ci ., p. 5.

Digi al Technology Pla o ms 35
– being s ic ly based on digi al componen s;
– pu ing a hea y emphasis on inno a i eness, lexibili y and e ec i eness;
– hype connec i i y conce ning all he en i ies and elemen s o a DTP;
– combina ion o elemen s o adi ional and digi al economies in many as-
pec s ( o example, co‑exis ence wi hin a DTP dis ibu ion channel based on
b ick‑and‑mo a acili ies and an online channel), in many cases i being im-
possible o dema ca e he wo a eas p ecisely;
– being inno a i e;
– disappea ance o many ba ie s, including spa ial and empo al ones;
– nea ly unlimi ed de elopmen oppo uni ies;
– in ensi ica ion o business ela ions;
– use o cu ing‑edge echnologies;
– g ea impo ance o knowledge;
– co ela ion and con e gence o many a eas in which he economy and a ious
en e p ises unc ion, including mos ly IT echnology, elecommunica ions and
digi al con en ;
– de elopmen and deploymen o no el, inno a i e business models;
– ensu ing maximum bene i s o any s akeholde s;
– a consume qui e o en ac ing as a manu ac u e ;
– wo k and in eg a ion in a ne wo k;
– au oma ed in o ma ion sha ing;
– molecula isa ion as a esul o which DTPs a e de eloped whose applica ion
is es ic ed o a ela i ely na ow scope o ac i i y ( o example, pla o ms o
s a ‑ups ope a ing in a speci ic ma ke sec o ).35
The ac should be emphasised ha all he said p ope ies adi ionally assigned
o digi al economy a e also cha ac e is ic o DTPs. This is so since hei ope a ion
in ol es i s o all in eg a ion and coo dina ion o ac i i ies o many di e se en i-
ies, wi h key impo ance being acqui ed by he use o cu ing‑edge echnologies
o business models. This implies ha DTPs a e based on inno a i eness and op-
e a ional lexibili y, ha wi hin hem he e is a la ge‑scale p omo ion o p ocesses
o sea ching, collec ing and dissemina ing knowledge on a ious a eas o human
ac i i y and ha hey lead o in ensi ica ion o business ela ions and, u he mo e,
hey a e de eloped o educe a ious ypes o ba ie s.
One documen p epa ed by he Eu opean Commission lis s i e basic cha ac e -
is ics o online pla o ms. They include:
– he abili y o c ea e and shape new ma ke s, o challenge adi ional ones, which
is possible due o collec ing, p ocessing and edi ing la ge amoun s o da a;
– ope a ion in mul i‑sided ma ke s bu wi h each pla o m exe cising a ying de-
g ees o con ol o e use s;
– bene i ing om “ne wo k e ec ,” which may be ein o ced, o example, by an
inc ease in he numbe o use s;
– s ic eliance on cu ing‑edge echnologies o be able o each hei use s ins an ly;
– playing a key ole in digi al alue c ea ion, which is achie ed by ini ia ing new
business en u es and ein o cing s a egic dependencies.36
36 Digi al Technology Pla o ms
The discussed documen ocuses o a la ge ex en on hose p ope ies o online
pla o ms which a e connec ed wi h hei ope a ion wi hin speci ic ma ke s. This
is because such pla o ms may e en con ibu e o he de elopmen o en i ely new
ma ke s. A pe ec example in his espec a e online ma ke places, he e o e online
ma ke s, whe e i is possible o pe o m buying and selling ansac ions and which
a e ega ded as one o he mos impo an ype o a DTP.37 Among p ope ies o
he pla o ms which may be poin ed ou is he hei unc ioning on many ma ke s
(many pla o ms ha e a global cha ac e , which is exempli ied by Skype) and also
aking ad an age, due o es ablishmen o a ious connec ions among pa icipan s,
o he ne wo k e ec , which con ibu es o he c ea ion o digi al alues, esul ing,
o example, om inno a ions.
One o he mos signi ican p ope ies o all DTPs is he ac ha hey a e highly
complex ools, sys ems o echnologies consis ing o many di e se elemen s. In
he p e ious sec ion, i was men ioned ha DTPs b ing oge he s akeholde s
wi hin a ce ain ecosys em. Figu e 2.1 p esen s basic laye s and elemen s o such
an ecosys em.
A business ecosys em, a ound which DTPs usually ope a e, is made up o a i-
ous laye s, including he en i onmen consis ing o many di e se en i ies. They
include, o example, cus ome s, supplie s o esea ch ins i u ions suppo ing he
Figu e 2.1 Componen s o a business ecosys em
Sou ce: Au ho ’s own wo k based on A. Lipińska, op. ci ., p. 48.
Digi al Technology Pla o ms 37
ope a ion o pla o ms wi h echnical knowledge and an inno a i e app oach o
pe o ming p ocesses. The cons uc ion o a business ecosys em shows i clea ly
ha DTPs a e e y de eloped and complex sys ems, in which equen ly an eno -
mous numbe o en i ies pa icipa e. Fo his, examples may be p o ided by auc ion
se ices, such as Alleg o o eBay, which b ing oge he millions o en ep eneu s,
supplie s and p i a e use s.
I should be obse ed he e, hough, ha a business ecosys em, discussed in he
con ex o DTPs, is made up o no only ce ain en i ies which collabo a e wi hin
he pla o ms bu also e e s o any add‑ons in he o m o , say, applica ions which
a e p o ided o he pla o m by some o ganisa ions.38 Cons ued in his manne , a
business ecosys em wi hin a DTP becomes an e en mo e complex sys em which
has a eally eno mous numbe o componen s.
Conside ing ha DTPs ope a e on he basis o business ecosys ems, many p op-
e ies may be indica ed which a e ypical o such ecosys ems. Apa om a la ge
numbe o s akeholde s and nume ous connec ions among hem, hey a e also cha -
ac e ised by:
– sha ing a ious esou ces, mainly knowledge and echnology, by hose s ake-
holde s, while main aining, hough, a high le el o compe i i eness ( his is
known as co‑ope i ion, o coope a i e compe i ion);
– membe s o a DTP play speci ic oles, and each change o posi ion o one ele-
men in he sys em a ec s he emaining ones;
– dynamic s uc u e, cons an ly changing unde he in luence o ma ke condi-
ions o social needs, as a esul o which ecosys ems may e ol e and de elop
on he basis o mode n echnologies;
– possibili y o compe ing wi h o he ecosys ems;
– mul i‑di ec ional and complex in e ac ion wi h he en i onmen , which e e s o
he sphe e o poli ics, echnology, ma ke o human esou ces.39
These p ope ies may be also assigned o DTPs. A e all, hese pla o ms p o-
ide access o a ious echnologies and ela ed knowledge o be sha ed by pa ici-
pan s, cause he pa icipan s o play s ic ly de ined oles (e.g. selle s, supplie s and
buye s, as in auc ion sys ems, o eache s and s uden s, as in e‑lea ning pla o ms),
and DTPs a e subjec o la ge amoun o in e ac ion wi h he en i onmen ( his can
be seen, o example, in he possibili y o co‑c ea ing speci ic unc ionali ies o
pla o ms by use s) and DTPs cons an ly de elop, using cu ing‑edge echnologies,
due o which hey can compe e wi h o he pla o ms e ec i ely.
Wha de ini ely dis inguishes DTPs is also he possibili y o con inuing im-
p o emen and expansion wi h newe and newe unc ionali ies and elemen s. This
ea u e is emphasised in many de ini ions o DTPs.40 M. de Reu e , C. Sø ensen
and R. C. Basole desc ibed he abo e possibili y as openness o a DTP.41 In his
con ex , T. Saa iko s a ed accu a ely ha he a chi ec u e o any pla o m, including
a DTP, is made up o a s able co e, which is ela i ely nea ly in a iable, and many
complemen s o add‑ons, which a e cha ac e ised by high a ie y. This causes each
pla o m o be highly lexible.42
38 Digi al Technology Pla o ms
The discussed p ope y o DTPs is e y signi ican because due o i is becomes
possible o ensu e a high deg ee o inno a i eness o hei ope a ion, which ollows
om he ac ha hey a e cons an ly imp o ed using mos ecen echnologies.
This way, hey a e able o espond e ec i ely o con inuously changing equi e-
men s and needs o cus ome s as well as ma ke o indus y ans o ma ions. In
addi ion, H. LeHong, C. Howa d, D. Gaughan and D. Logan obse ed ha he
discussed openness may e e o he ollowing i e pe spec i es connec ed wi h he
ope a ion o a DTP:
– an in as uc u e and ope a ions pe spec i e, including da a cen es o cloud
compu ing;
– a da a managemen and e en ion pe spec i e;
– a secu i y and isk pe spec i e;
– a comp ehensi e in eg a ion s a egy, which assumes maximum lexibili y o
suppo shi ing ma ke o business demands;
– ou sou cing o cloud sou cing guidelines, which may assume a b oad combi-
na ion o in e nal and ex e nal esou ces and se ices ecei ed om a ious
pa ne s.43
Analysing undamen al p ope ies o DTPs, i is also wo h d awing a en ion o
he p oposals by R. Sun, B. Kea ing and S. G ego abou he mos impo an dimen-
sions o hese pla o ms, and he e o e also hei componen s. These dimensions
a e p esen ed in Table 2.2. In addi ion, i gi es examples o al e na i e e minolo-
gies ela i e o hese dimensions, used by o he au ho s.
The undamen al ea u es o a DTP may be desc ibed aking in o conside a-
ion he dimensions dis inguished in Table 2.2. The one which appea s o be he
leading dimension is he so‑called echnological base, which en ails bo h openness
and complexi y o DTPs and ela ed add‑ons o s anda ds, as well as in e ope -
abili y, ansac ionali y and pla o m go e nance. Each o hese dimensions is pa
o e e y DTP, so he exis ence o such dimensions is one o he key dis inguishing
ea u es o such pla o ms, which makes hem dis inc om, o example, IT o
ICT sys ems.
To ecapi ula e he issues discussed in his sec ion, i should be s essed ha
DTPs ha e many cha ac e is ic p ope ies. Some o hem ollow di ec ly om he
manne o ope a ing o he en i e digi al economy (e.g. inno a i eness, hype con-
nec i i y, unlimi ed de elopmen oppo uni ies, disappea ance o many ba ie s,
c ea ion o new business models) o business ecosys ems (sha ing speci ic e-
sou ces by DTP use s, playing by hem a ious oles, a dynamic s uc u e). O he s
conce n u he mo e la ge complexi y, openness, in e ope abili y, ansac ional-
i y and pla o m go e nance. In iew o such a g ea numbe o p ope ies, DTPs
should be ega ded as sys ems o ools s ongly de eloped echnologically which
a e cons an ly imp o ed and ha e a conside able impac on he con empo a y
economy as a whole. These issues will be discussed in mo e dep h in he u he
pa o he chap e .
Digi al Technology Pla o ms 39
2.3 Typology o Digi al Technology Pla o ms
A p esen , a huge numbe o DTPs a e a ailable on he ma ke . Fo his eason, i
is impossible o lis all o hei kinds. A desc ip ion o he mos impo an ypolo-
gies connec ed wi h DTPs will be p esen ed below.
One o such classi ica ion is ha p oposed by o H. LeHong, C. Howa d, D.
Gaughan and D. Logan I is p esen ed in Figu e 2.2.
Table 2.2 Dimensions o digi al echnology pla o ms acco ding o R. Sun, B. Kea ing and
S. G ego
Dimension Desc ip ion Al e na i e e minology
Technological
base
• Founda ion which allows
o using a ious add‑ons, as
a esul o which DTPs a e
echnologies used o e long
e m
• Se o componen s
• Gene al‑pu pose echnology
• Ex ensible code base
• Co e ixed se o a ibu es
• Co e p oduc s o se ices
• Common a chi ec u e, esou ce
o s uc u e
Add‑ons • A so wa e ex ension o he
echnological base o add
unc ionali y o a DTP
• Applica ions, dis ibu ed
applica ions
• Complemen a y ex ensions
(elemen s, p oduc s), including
modules
• Associa ed componen s
• Plug‑ins
• Complemen o s o e ing
p oduc s o se ices
complemen a y o he o e o
a DTP
In e ope abili y • The abili y o in e ac be ween a
echnological base and add‑ons
• Real‑ ime connec i i y
• Ways o connec ing
S anda ds • Design ules ha allow
p og amme s o access a DTP on
he same e ms and condi ions,
which is especially impo an o
e ec i e in eg a ion o add‑ons
wi h he echnological base
• A se o ules
• Pla o m o p og amming
in e aces
T ansac ionali y • Possibili y o pe o ming ce ain
ansac ions on a DTP, such
as buying and selling, which
suppo s in e es s o pla o m
use s
• In e ac ions
• T ansac ions
Go e nance • S uc u es, p inciples, policies,
mechanisms, communica ion
and ela ion models o license
ag eemen s in ol ed in
managing a DTP
• Coo dina ion
• Pla o m managemen
• T anspa ency
Sou ce: R. Sun, B. Kea ing, S. G ego , op. ci ., p. 6.

40 Digi al Technology Pla o ms
Acco ding o he au ho s, DTPs may be di ided in o i e ypes, wi h he di i-
sion being based on he c i e ion ega ding main a eas o applica ion o DTPs, o
cus ome s, pa ne s, employees and hings. I is ypical ha each kind o a DTP
ope a es in all o he abo e a eas, al hough ob iously he scope o ope a ion is di -
e en depending on a pa icula pla o m. The kind o pla o ms which pa icipa e
o a g ea es ex en in each o he a eas a e da a and analy ics pla o ms, which is
connec ed wi h he ac ha hey enable in o ma ion managemen and analysis,
and hus e ec i e decision‑making based on a ailable da a. Ano he kind o DTPs
a e cus ome expe ience pla o ms, which a e s ongly o ien ed o consume s by
o e ing hem access o applica ions dedica ed o hem o omni‑channel dis ibu-
ion sys ems. Ecosys em pla o ms make i possible o c ea e sys ems ex e nal o
a DTP o coope a ion wi h o he en i ies and hei in eg a ion, while in o ma ion
sys ems pla o ms a e solu ions due o which i is possible o con ol ce ain en i-
ies, including wi h he use o such sys ems as, o example, ERP (en e p ise e-
sou ce planning). The las kind o a DTP dis inguished by H. LeHong, C. Howa d,
D. Gaughan and D. Logan is In e ne o Things (IoT) pla o ms. They a e used o
combine esou ces, sys ems and physical de ices o moni o , con ol and op imise
hei ope a ion.44
A sligh ly di e en classi ica ion o DTPs was p oposed in one publica ion by
Oxe a, a consul ing i m. The classi ica ion is based on su eys pe o med by he
i m in many Eu opean coun ies, including F ance, Ge many, Spain and Poland,
Figu e 2.2 Classi ica ion o digi al echnology pla o ms acco ding o H. LeHong, C. Howa d,
D. Gaughan, D. Logan
Sou ce: Au ho ’s own wo k based on H. LeHong, C. Howa d, D. Gaughan, D. Logan, op. ci ., p. 3.
Digi al Technology Pla o ms 41
among 6,000 consume s (including 1,502 om Poland). The su eys we e abou
he le el o use o digi al pla o ms by consume s as well as ela ed bene i s o
conce ns.45 The abo e classi ica ion o DTPs is p esen ed below:
– communica ion pla o ms – pla o ms o communica ion among a ious en i ies;
– in o ma ion pla o ms – pla o ms o ob aining and sha ing all so s o
in o ma ion;
– compa ison pla o ms – pla o ms o compa ing a ious p oduc s o se ices;
– en e ainmen pla o ms – pla o ms o accessing and sha ing con en used o
en e ainmen ;
– online ma ke places – pla o ms o en e ing in o buying o selling ansac ions.46
A s ill di e en ypology o DTPs was p esen ed by A. Kosie adzka and K.
Ros ek. This ypology dis inguishes ou ypes o pla o ms, which a e es ic ed o
“ echnology pla o ms accessible ia web b owse s”:
– communica ion pla o ms – aiming o suppo g oup decisions;
– analy ics and communica ion pla o ms – make i possible o make decisions
aiming o, o example, inc ease a company’s compe i i eness;
– in eg a ion and in o ma ion pla o ms – used mainly in he a ea o da a and
in o ma ion analysis;
– pla o ms o sol ing p oblems and pe o m asks wi h he use o knowledge
and po en ial o ex e nal en i ies.47
Issues connec ed wi h ypes o DTPs we e discussed in a sligh ly mo e limi ed
manne by A. Gawe . She lis ed only h ee ypes. They a e desc ibed in Table 2.3.
Acco ding o A. Gawe , echnology pla o ms, including digi al ones, include
in e nal pla o ms, ope a ing wi hin one company, pla o ms ope a ing wi hin one
supply chain as well as hose de ined as indus ial ones. The di e om one an-
o he , in p inciple, in all componen s and aspec s, s a ing om he le el o use, up
o coo dina ion mechanisms o inno a ions. One common elemen ega ding hei
cons uc ion may be ne e heless ound. This is a chi ec u e, which is modula ,
making i possible o a ach o he co e ( echnological base) u he elemen s, such
as modules o applica ions.
R. G. Fichman dis inguished ou basic ypes o DTPs. These a e as ollows:
compu e pla o ms ( o example, ope a ing sys ems dedica ed o mobile de ices,
such as And oid), in as uc u al pla o ms (wi eless ne wo ks), co po a e applica-
ion pla o ms ( o example, ERP) and pla o ms o p og amming (Ja a).48
In u n, acco ding o K. Mohan y, a ious DTPs which a e claimed o be ea -
ma ked p ima ily o deli e echnology‑based se ices o business, may be di-
ided in o: social media pla o ms (Facebook, Twi e , Ins ag am, Pin e es ), which
a e used by companies o ad e ise hei p oduc s and se ices and es ablish ela-
ions wi h s akeholde s, emaining ad e ising pla o ms, including Google o a i-
ous blogs, cloud compu ing pla o ms ( o example, Mic oso Azu e o Amazon
Web Se ices), o e ing da a s o age o hos ing, as well as pla o my in he o m o
42 Digi al Technology Pla o ms
sepa a e e‑comme ce business models, such as Amazon o eBay, making i possible
o buy p oduc s wi hou lea ing home.49
DTPs may be also di ided in o ypes on he basis o ela ions ha ake place
be ween pa icipan s o ac i i ies in he digi al en i onmen , including e.g. wi hin
e‑business. This way, pla o ms may be dis inguished whe e he ollowing ypes o
ela ions occu :
– B2B (business‑ o‑business) – “classic” ela ionships on he ma ke be ween wo
en e p ises;
– B2C (business‑ o‑consume o business‑ o‑clien ) – ela ions conce ning DTPs,
which make in e ac ions be ween en e p ises and consume s possible;
– B2G (business‑ o‑go e nmen ) – ela ions be ween en e p ises and public ad-
minis a ion (pla o ms o ende s o public p ocu emen );
– C2C (cus ome ‑ o‑cus ome ) – ansac ions be ween consume s using pla o ms
in he o m o auc ion sys ems and po als;
– C2B (cus ome ‑ o‑business) – ela ions be ween consume s and en e p ises, ini-
ia ed by he o me ( o ins ance, compa ison‑shopping websi es);
– C2G (cus ome ‑ o‑go e nmen ) – ansac ions be ween ci izens and public ad-
minis a ion pe o med h ough public pla o ms o axes o social insu ance;
– G2C (go e nmen ‑ o‑ci izen) – low o adminis a i e in o ma ion be ween o -
ices and ci izens;
Table 2.3 Kinds o echnology pla o ms acco ding o A. Gawe
Pla o m
dimensions
In e nal pla o ms Supply‑chain pla o ms Indus y pla o ms
A chi ec u e • Modula cons uc ion
• Co e and add‑ons
Access o
inno a ions
• Wide • Inno a ions wi hin a
supply chain
• Po en ially unlimi ed
In e ace • Closed – accessible o
pla o m use s bu no
o ex e nal en i ies
• Selec i ely open,
he e o e accessible only
wi hin a supply chain
• Open o all
Coo dina ion
mechanisms
• S ic ly de ined
go e nance hie a chy
• Con ac ual ela ionships
wi hin a supply chain
• Ecosys em
go e nance
Le el o use • En e p ise • Supply chain • Indus ial ecosys ems
En i y es ablishing
he pla o m
• One en e p ise and i s
subcon ac o s
• Supply‑chain membe s • Pla o m leade and
complemen o s
Examples • Black and Decke
(p oduc ion o ools)
• Sony (p oduc ion o
elec onics)
• Boeing (p oduc ion o
ai planes)
• Renaul – Nissan
(p oduc ion o ca s)
• Apple (mobile
echnology)
• Facebook (social
po al)
• Google (sea ch
engine)
Sou ce: A. Gawe , “B idging Di e ing Pe spec i es on Technological Pla o ms: Towa d an In eg a i e F ame-
wo k,” Resea ch Policy. Else ie 2014, ol. 43, no. 7, p. 1244.
Digi al Technology Pla o ms 43
– G2B (go e nmen ‑ o‑business) – low o economic in o ma ion be ween o ices
and en e p ises;
– G2G (go e nmen ‑ o‑go e nmen ) – ela ions be ween public adminis a ion
au ho i ies making i possible o hem o coo dina e in e nal p ocesses.50
I should be added ha a p esen DTPs mos o en conce n ini ia ion and in en-
si ica ion o B2B, B2C, C2C and C2B ela ionships, he e o e be ween consume s
and en e p ises. I is a ac , hough, ha inc easingly as e de elopmen can be
obse ed also wi h espec o pla o ms o communica ion be ween ci izens and
en e p ises on he one hand and public adminis a ion on he o he . Examples o
hese a e pla o ms ope a ing in Poland, e.g. ePUAP (Elec onic Pla o m o Public
Adminis a ion Se ices), PUE ZUS (Elec onic Se ice Pla o m o he Social
Insu ance Company) o CEIDG (Cen al Regis a ion and In o ma ion on Busi-
ness).51 A decisi e majo i y o B2B, B2C, C2C o C2B pla o ms ope a e wi hin
e‑comme ce, which T. Wallace ega ds as applica ions allowing en e p ises con-
duc ing ac i i y in he In e ne o manage websi es, sales and ma ke ing, in addi ion
o e ing in eg a ion wi h adi ional business ools.52
The Uni ed Na ions also p epa ed i s own classi ica ion o DTPs. I conside ed
a g adual de elopmen o he pla o ms, di iding i in o h ee basic pe iods, which
also en ails h ee kinds o DTPs. This is depic ed in Figu e 2.3.
As shown in Figu e 2.3, he g adual dissemina ion o digi al pla o ms in he
wo ld began wi h he eme gence o main ame compu e s, which, as al eady men-
ioned, ook place in he 1960s. The s age las ed o he second hal o 1980s and
he beginning o he 1990s, when pe sonal compu e s we e in en ed and s a ed o
be commonly used, as well as he In e ne , which he UN conside s as he second
ype o digi al echnologies. Tha made i possible o build mo e de eloped digi al
pla o ms. The hi d pla o m g ow h s age, which s a ed in he beginning o he
second decade o he 21s cen u y and is ongoing, when mobile echnologies began
o be ubiqui ous and mo e and mo e solu ions appea ed such as big da a analy -
ics, he In e ne o Things, cloud se ices o social media, allowing o p omo ion
o inno a i e business models and se ices. Impo an ly, combined use o digi al
echnologies and pla o ms is now possible, which gi es ise o comple ely new
oppo uni ies, no only jus o indi idual use s o en e p ises bu also he public
sec o and social o ganisa ions. Wha should be also emphasised is ha whe eas
a he i s s age o de elopmen , DTPs we e used by se e al millions o people,
a he second and hi d s ages, he numbe o use s eached hund eds o millions
and se e al billions o use s espec i ely. This demons a es an unusually in ensi e
g ow h o DTPs.53
The classi ica ions o DTPs p esen ed abo e a e undoub edly gene al in na u e.
O he s concen a e on singling ou mo e speci ic pla o ms om he classi ica ion,
applying o ha a ious kinds o c i e ia. So, o example, in he epo by Aleo
and Deloi e, quo ed abo e, pla o ms we e selec ed which a e used in he pe o -
mance o p ocu emen p ocesses, known as sou ce‑ o‑se le pla o ms. Such p o-
cu emen pla o ms include:
50 Digi al Technology Pla o ms
Global DTPs play dominan oles no jus in he ma ke o echnology pla o ms
bu in gene al in he en i e wo ld economy. This is shown by he da a p esen ed in
Table 2.5.
Among he en mos aluable b ands in he wo ld which a ec he wo d econ-
omy o he g ea es ex en , he ou leading posi ions a e held by companies o e -
ing DTPs, while he six h posi ion is aken by Amazon. Those b ands gene a e jus
eno mous e enues. In 2018, he o al e enues we e 714 billion dolla s, wi h p o i
o 135.5 billion dolla s, which means p o i abili y o app oxima ely 19%. Such e-
sul s show ha e enues o he “digi al gian s” a e highe by USD 100 billion han
wha he Polish economy is able o p oduce on an annual basis, while he p o i s
alone would be su icien o co e all he expendi u es o he Polish budge .79
The echnologies implemen ed by “Big Tech” a e wi hou any doub decisi e
abou he le el o de elopmen and inno a i eness in he wo ld economy. I should
be obse ed ha he b ands a e g owing in ensi ely all he ime, which can be
seen om he ac ha in he yea s 2016–2017, hey eco ded inc ease in alue o
10% (Apple) up o o e 50% (Amazon). In his con ex , i should be added ha
he bigges DTPs achie e hei unusually s ong posi ion a he cos o en e p ises
om o he indus ies. I is equally ele an ha he documen en i led “Poli yka
Rozwoju Sz ucznej In eligencji w Polsce na la a 2019–2027” (“Policy o he De-
elopmen o A i icial In elligence in Poland o 2019–2027”), which is a p esen
a d a o social consul a ion, s essed ha
du ing se e al ecen decades, wi h ligh ning speed, a new economic eali y
un olded, whe e he key ole is no longe played by aw ma e ials, wo k o ce
o e en inancial capi al bu by knowledge o in angible asse s. Fo example,
oil companies and ca manu ac u e s disappea ed om he leading posi ions
on he lis o he mos aluable companies in he wo ld, eplaced by co po a-
ions ope a ing digi al pla o ms, whose majo asse s a e in isible bu a ec
he assessmen o he alue o each o hem.80
Table 2.5 The mos aluable b ands in he wo ld in 2017 acco ding o Fo bes’ epo
Rank B and B and alue
(in USD billion)
2017/2016 g ow h
(as %)
Re enues
(in USD billion)
Indus y
1 Apple 170.0 10 214.2 Technology
2 Google 101.8 23 80.5 Technology
3 Mic oso 87.0 16 85.3 Technology
4 Facebook 73.5 40 25.6 Technology
5 Coca‑Cola 56.4 −4 23.0 Be e ages
6Amazon 54.1 54 133.0 Technology
7 Disney 43.9 11 30.7 En e ainmen
8 Toyo a 41.1 −2 168.8 Mo o indus y
9 McDonald’s 40.3 3 85.0 Ca e ing
10 Samsung 38.2 6166.7 Technology
Sou ce: M. Lewicki, “E‑handel w Polsce – s an i pe spek ywy ozwoju,” Handel Wewnę zny 2018, no.
4, p. 177.

Digi al Technology Pla o ms 51
This is co ec and shows a quickly inc easing ole o DTPs in oday’s economy.
He e, howe e , i mus be no ed ha e e mo e impo an oles a e played in he
global DTP ma ke by b and di e en om “Big Fi e.” They a e p ima ily com-
panies wi h egis e ed o ices in China, including Alibaba, Tence and he like. As
shown by he da a p esen ed in G aph 2.1, hey ha e al eady begun o hold anks
jus below “Big Tech” in e ms o capi alisa ion. In addi ion, an in ensi e g ow h in
he sha e o Chinese b ands in he capi alisa ion can be seen. In 2018, he sha e was
al eady 40%, while i was 48% o Ame ican companies, bu wi h a dec ease by
15% compa ed o 2017.81 The da a show ha e en hough US companies con inue
o domina e in he global DTP ma ke , hey may ne e heless g adually ace an
inc easingly g owing compe i ion om Chinese b ands.
I Is necessa y s ill o s ess ha he global ma ke o DTPs is no made up o
comme cial solu ions only bu also o hose which use a g ea con ibu ion om he
public sphe e and en i ies ope a ing he e. Good examples a e Eu opean echnol-
ogy pla o ms and Polish echnology pla o ms (ETPs and PTPs, espec i ely).82
They will be discussed in de ail in he nex sec ion. I should be no ed ha wha is
conduci e o p omo ing such pla o ms is he policy ca ied ou in many coun ies.
This is also ue o Poland. In his a ea, i is possible o in oke p o isions o he Fu-
u e Indus y Pla o m Founda ion (“Fundacja Pla o ma P zemysłu P zyszłości”)
Ac 83 ( he ounda ion will be u he also e e ed o as he FIPF). Those p o isions
en isage he es ablishmen o he Founda ion o suppo digi al ans o ma ion o
en e p ises, which is o be pe o med wi h e e ence o p ocesses o p oduc s which
use cu ing‑edge achie emen s om he a eas o ICT echnology, a i icial in elli-
gence, au oma ion o human‑machine communica ion. The main asks o he FIPF
include: o inc ease en ep eneu s’ awa eness how o use mode n digi al echnolo-
gies, o suppo pu chases o inno a i e echnological solu ions o da a sha ing
sys ems and o ini ia e in e na ional coope a ion o p omo ing he use o digi al
echnology. Be ween 2019 and 2018, o e PLN 236 million is o be ea ma ked
o he ac i i ies ca ied ou by he Founda ion.84 These ac i i ies will also include
ini ia i es o suppo ing he de elopmen o DTPs.
Fu he mo e, wha should be men ioned is he P og amme en i led “F om Pape
Poland o Digi al Poland,” we e plen y ac i i ies ha e been speci ied o he de el-
opmen o DTPs in he public sphe e. These ac i i ies a e o be pe o med in i e
basic a eas, conce ning, among o he s, he de elopmen o digi al compe ences
in he public sec o , p o ision o secu e and con enien access o online public
se ices and accele a ion o he de elopmen o mode n elecommunica ions in-
as uc u e. The pe o mance o he P og amme in ol es, o example, con inued
mode nisa ion and inc easing he unc ionali y o digi al public pla o ms, such as
PUE ZUS o ePUAP.85
Finally, i should be no iced ha in ensi e g ow h o DTPs makes i necessa y o
in oduce new egula ions o amendmen s o laws. This ollows om he inc eas-
ingly highe impac o he pla o ms on a ious en e p ises and consume s, and
consequen ly also on en i e ma ke s and economies. Signi ican ly, he impac does
no ha e o be posi i e; e y o en, i also has ad e se consequences. These include
un ai ade p ac ices, such as:
52 Digi al Technology Pla o ms
– imposi ion by a DTP un ai condi ions on use s ega ding mainly access o
da abases;
– unila e al in oduc ion by a DTP o amendmen s o condi ions o access o digi-
al ma ke o e en e ec i e p e en ion o such access, which also includes ac-
cess o signi ican comme cial da a;
– playing a double ole by pla o ms by acili a ing access o ma ke o o he
en i ies and simul aneously compe ing wi h hem, which may lead o excessi e
p omo ion o he pla o ms’ p oduc s o se ices;
– applica ion o un ai equali y clauses wi hin he ope a ion o DTPs;
– a lack o anspa ency ega ding a i s applied by pla o ms, he ex en o which
hey use use s’ da a o sea ch esul s, which may en ail losses o supplie s.86
In esponse o such ype o p oblems, Regula ion (EU) 2019/1150 o he
Eu opean Pa liamen and o he Council o 20 June 2019 on p omo ing ai ness
and anspa ency o business use s o online in e media ion se ices was adop ed
and published in 2019.87 The egula ion applies o abou 7,000 en e p ises ope a -
ing online, including p ima ily digi al sales pla o ms, applica ion s o es, social
media se ices and shopping compa ison websi es.88 The key p o isions include
s a emen s abou ai ea men o all use s o a DTP by o mula ing e ms and
condi ions o using he pla o ms, aking in o accoun equi emen s o , among o h-
e s, plain and in elligible language, eady accessibili y a all s ages o comme cial
ela ions wi h a supplie o conside a ion o he e ec o he e ms and condi ions
on he con ol o in ellec ual p ope y igh s es ed in use s.89 Simila ly impo an
a e also p o isions abou endo s o DTP se ices which a e obliged o in o m us-
e s abou he ex en o access o pe sonal da a90 and o ensu e an in e nal sys em o
handling use s’ complain s.91
The said egula ion demons a es ha he si ua ion on he global ma ke o
DTP is e y dynamic and cons an ly changes. T ans o ma ions conce n no only
amendmen s o law bu also ypes and cha ac e o o e ed sys ems, echnolo-
gies, applica ions o online ools. Al hough such sys ems o echnologies a e
de eloped by many di e se en e p ises, he decisi e impac on he global DTP
ma ke is exe ed by he so‑called “Big Fi e,” o Google, Amazon, Facebook,
Apple and Mic oso . In he coming yea s, he si ua ion will comple ely change,
in connec ion wi h he cons an s eng hening o he posi ion o he co po a ions
on he digi al ma ke , which o e mo e and mo e pla o ms and unc ionali ies
ope a ing wi hin hem and addi ionally ge in ol ed in o he segmen s o he
ma ke . I is wo h poin ing ou ha hese companies show inc easingly highe
ac i i y in he inancial ma ke , o e ing hei use s access o pe sonal accoun s
h ough online communica ion pla o ms (Wha sApp o Facebook o Messen-
ge by Mic oso ).92 Howe e , he g owing ole o Chinese b and should no be
o e looked. The global DTP ma ke is i s and o emos he i e bigges playe s,
o “Big Tech.” I is impo an ha he ma ke is mo e and mo e b inging abou
a si ua ion which may be e e ed o as pla o m economy o online pla o m
economy.93 This shows he cons an ly g owing dependence o he wo ld economy
on DTPs.
Digi al Technology Pla o ms 53
Addi ionally, in he yea s o come, he global DTP ma ke may unde go a
a ‑ eaching e olu ion. E en now, a s ong endency may be obse ed o DTPs
o be based on an app oach whe e designing is o u mos impo ance. Such an ap-
p oach, based on he combina ion o business s a egy and design hinking, makes
i possible, i s o all, o e ec i ely build and de elop business ecosys ems as well
as wide‑ anging implemen a ion o inno a ions, be e unde s anding o cus om-
e s’ needs, placing an emphasis o coope a ion, con inuing expe imen a ion and
achie emen o high lexibili y le el.94
2.5 Fields o Applica ion and Achie ed Bene i s
DTPs may be employed in many di e se a eas in which en e p ises and he econ-
omy unc ion. The e seems o be simply an unlimi ed numbe o such a eas now.
This ollows om he ac ha e e newe DTPs appea all he ime in he ma ke ,
he e o e he po en ial scope o hei applica ion in business p ac ice con inues o
g ow. Based on he ypologies o DTPs p esen ed in he p e ious sec ion, i may
be s a ed ha he pla o ms a e applicable in all business p ocesses pe o med bo h
inside an en e p ise (p oduc ion, in e nal anspo , s o age, in o ma ion and docu-
men low, human esou ce managemen , including aining) as well as in he ex-
e nal en i onmen ( ela ions wi h s akeholde s, coope a ion wi hin supply chains,
sha ing da a and documen s, p ocu emen , sales o p oduc s and se ices on a i-
ous ma ke s, ope a ion o dis ibu ion channels). Acco ding o A. Kosie adzka and
K. Ros ek, he key uses o con empo a y digi al pla o ms include ope a ional man-
agemen (access o knowledge, ini ia ing and in ensi ying collabo a ion wi h o he
en e p ises and scien i ic o consul ing ins i u ions, in e media ion in echnology
sha ing) and in e ‑o ganisa ional managemen (benchma king o g oups o compa-
nies, iden i ica ion o aining needs and o ganisa ion o ele an aining cou ses
and p og ammes, o ganisa ional lea ning).95 In addi ion, DTPs pe o m ac i i ies,
among o he s, in he a ea o educa ion (e‑lea ning pla o ms) and en e ainmen o
in he public sec o (PTP).
Wi h ega d o he ope a ion o en e p ises, R. Kapu indica es in pa icula ha
digi al pla o ms allow o c ea ing digi al jobs, and hus digi al o ganisa ions. In
addi ion, such pla o ms may ela e o such a eas as: communica ion, coope a ion,
in e ‑o ganisa ional ies, in o ma ion managemen s a egies (collec ing, analysing
and moni o ing in o ma ion and da a), oles and du ies o o ganisa ion membe s,
aining and ce i ica ion, c isis managemen , policy ega ding inno a ions and in-
c easing ope a ional lexibili y and e iciency, ec ui men o employees.96
U. Dola a conduc ed an analysis o he mos impo an ields o applica ion o
DTPs in ela ion o he unc ioning o he “digi al gian s,” o Apple, Amazon, Fa-
cebook, Google and Mic oso . The a eas a e p esen ed in Table 2.6.
The ields o applica ion o he bigges DTPs in he wo ld as p esen ed abo e
na u ally do no exhaus all he a eas. A g ea e numbe o hose may be gi en, o
example, o Google o Facebook pla o ms, hey a e ma ke ing and ad e ising.
The lis o uses o DTPs in Table 2.6 aims o demons a e in how many aspec s o
human ac i i y and he business sphe e such pla o ms may be used.
54 Digi al Technology Pla o ms
Wha shows a e y wide applicabili y o DTPs is he p ac ice o implemen -
ing ETPs and PTPs, as men ioned abo e (in he EU – since 2003, in Poland –
since 2004). These pla o ms a e
a g ea join p ojec o he Eu opean Commission, he indus y, scien i ic
and inancial ins i u ions, decision‑making g oups and he socie y o p epa e
de elopmen s a egies o sec o s o he economy impo an o Eu ope and
echnologies o he u u e. The ini ia i es a e aimed o concen a e he e o s
o key Eu opean pa ne s o pe o m hese s a egies in he o m o la ge
scien i ic and echnological p ojec s. Technology pla o ms a e expec ed o
play a majo ole in he ac i a ion o esea ch ideas and inancial esou ces a
he Eu opean le el. One o he main asks o he pla o ms is o be es ablish-
men o e ec i e public and p i a e pa ne ship o he implemen a ion o he
de eloped s a egies.97
Bo h Eu opean and Polish echnology pla o ms o m associa ions o “p ac ically
all he key inno a i e i ms in Poland in p io i y sec o s o he economy,”98 making
Table 2.6 Fields o applica ion o DTPs using oppo uni ies o e ed by he bigges echno-
logical companies in he wo ld
Pla o ms Fields o applica ion Elemen s and unc ionali ies o pla o ms
Apple • Media, en e ainmen • App S o e, iTunes S o e, music s eaming
• Mobile echnologies • iPhone, iPad, iPod, iOS ope a ing sys em,
Sa a i Mobile web b owse
• So wa e and co po a e
equipmen
• Apple‑IBM sys ems
• Cloud compu ing • iCloud
• Sma solu ions • In e ne o Things (Apple Ca )
• A i icial in elligence • Tu i C ea e
Amazon • Digi al sales • Amazon.com, Zappos.com
• Media, en e ainmen • Lo e ilm.com, AmazonGames.com, P ime
Ins an Video
• Mobile echnologies • Kindle (e‑book eade ), Fi e Phone
• Cloud compu ing • Amazon Web Se ices
Facebook • Media, en e ainmen • Ins ag am (pho og aphy)
• Communica ion • Wha sApp
• So wa e, i ual eali y • Oculus VR
Google • Media, en e ainmen • YouTube, Google Books, Google+ social
po al, Picasa (pho og aphy)
• Applica ion s o es • Google Play
• Mobile echnologies • B owse s Ch ome and Ch omecas , And oid
ope a ing sys em
• Sma solu ions • In e ne o Things (sma home and ca )
Mic oso • Media, en e ainmen • LinkedIn social ne wo k, Xbox console
• Communica ion • Ou look, Skype
• Mobile echnologies • Nokia, Bing
Sou ce: U. Dola a, op. ci ., pp. 12, 14.
Digi al Technology Pla o ms 55
i possible o hem o ake join ac ions o pe o m inno a i e p ojec s, including
also in he a ea o implemen ing DTPs.
A p esen , in he e i o y o Poland, se e al dozen echnology pla o ms a e
ope a ing and hei unc ioning co e s many di e se ields. The ollowing a eas
should be lis ed:
– new echnologies ha ing impac on adical ans o ma ion o sec o s – nano-
elec onics, hyd ogen uel and uel cells;
– new echnologies o manu ac u ing p oduc s and se ices – wi eless and mo-
bile echnology, inno a i e medica ions;
– sus ainable de elopmen – bio echnology, wa e supply;
– s a egic sec o s o he economy – ae onau ics;
– adi ional indus ial sec o s in he con ex o hei de elopmen , mode nisa ion
and s uc u ing – s eel.99
Table 2.7 lis s PTPs ope a ing in he e i o y o Poland. The e a e 30 o hem
al oge he .
Polish echnology pla o ms a e implemen ed wi hin se e al undamen al a eas,
including ene gy, anspo o bio echnology. I migh be hough ha i is jus hose
a eas ha ha e been ega ded in Poland as he mos impo an om he pe spec i e
o using digi al echnologies and pla o ms, de elopmen ac o s o he economy.
I should be no ed ha in he ac i i ies conce ning PTPs, a e y la ge numbe o
en i ies pa icipa e including en e p ises, scien i ic and esea ch ins i u es o highe
educa ion ins i u ions. I is a ac ha all he PTPs may be classi ied as DTPs as
hey exploi digi al echnologies on a la ge scale, enabling hem o es ablish coop-
e a ion be ween pla o m pa icipan s and o implemen inno a i e solu ions.
I should be added ha ETPs and PTPs s ongly suppo ac i i ies which con ib-
u e o (sus ainable) de elopmen o he economy o he Eu opean Union. In his con-
ex , hey should be associa ed wi h Eu ope 2020 S a egy,100 whe e h ee mu ually
ein o cing p io i ies we e pu o wa d. In p inciple, each o hem may be ela ed o
he sys em o building ETPs and PTPs because hey desc ibe kinds o g ow h:
– sma g ow h – de eloping an economy based on knowledge and inno a ion;
– sus ainable g ow h – p omo ing a mo e esou ce e icien , g eene and mo e
compe i i e economy;
– inclusi e g ow h – os e ing a high‑employmen economy deli e ing social and
e i o ial cohesion.101
Wi hin ETPs and PTPs, i is c ucially impo an o suppo any p ojec s which
a e inno a i e in na u e. Wi hin he p ojec s, he mos impo an hing is o p omo e
speci ic o ganisa ional solu ions, sys ems o ools, including IT sys ems o ools,
which aim o imp o e e ec i eness and e iciency o he ope a ion o en e p ises
conduc ing ac i i y in a ious sec o s as well as o ein o ce coope a ion be ween
di e se en i ies. The e ec is achie emen o sus ainable g ow h objec i es e-
e ed o in Eu ope 2020 S a egy – owing o ETPs and PTPs, echnologies may be

56 Digi al Technology Pla o ms
Table 2.7 Types o PTP ope a ing in Poland
Thema ic a ea Types o PTPs Coo dina o s Aims o ac i i y
Secu i y Wo k Sa e y in
P zemyśl
Cen al Ins i u e
o Labou
P o ec ion – Na ional
Resea ch Ins i u e
(CIOP PIB)
To inc ease wo k sa e y by
implemen ing mode n
echnologies
In e nal Secu i y Uni e si y o Białys ok Au oma ed oice
ecogni ion and ex
p ocessing echnologies
Secu i y Sys ems Mili a y Uni e si y o
Technology
P omo ion o new
echnologies o secu i y
Bio echnology,
ag icul u e,
medicine
Bio echnology Jagiellonian Cen e o
Inno a ion (JCI)
De elopmen o
biop ocesses, p oduc ion
o bioma e ials
Inno a i e
Medicine
Pome anian Medical
Academy in Szczecin
Suppo ing inno a ions in
he p oduc ion o new
medicines
Fo es and Wood
Sec o
Wood Technology
Ins i u e (ITD)
Inc ease compe i i eness
and e ec i eness o he
sec o
En i onmen Ins i u e o Ecology
o Indus ial A eas
(IETU)
Suppo ing p ojec s o
he p o ec ion o na u al
en i onmen
Food Uni e si y o Wa mia
and Mazu y in
Olsz yn
De elopmen o new
echnologies o ood
p oduc ion
Ene gy Bio uels and
Biocomponen s
Au omo i e Indus y
Ins i u e (PIMo )
In oduc ion o bio uels in
Poland
Nuclea
Technologies
Na ional Cen e o
Nuclea Resea ch
(NCBJ)
Pe o mance o p ojec s
in he a ea o nuclea
ene gy
Hyd ogen and Fuel
Cells
Indus ial Chemis y
Ins i u e (ICP)
P omo ing hyd ogen
echnology
Sus ainable Ene gy
Sys ems and Pu e
Ca bon Ene gy
Ins i u e o Hea
Technology a
Wa saw Uni e si y
o Technology
De elopmen o ene gy
and uel sec o
Me als Non‑ e ous Me als Ins i u e o Non‑ e ous
Me als
Pe o mance o esea ch
p ojec s in he indus y
o non‑ e ous me als
Founding Founding Ins i u e De elopmen o ounding
echnologies
S eel Ins i u e o Fe ous
Me allu gy
De elopmen o s eel
indus y
IT
echnologies
Pho onics PCO S.A. De elopmen o he
pho onics sec o
Op o– and
Nanoelec onics
Cen al Technical
O ganisa ion (NOT)
Pe o mance o esea ch
and p ojec s in he
a eas o op o – and
nano echnology
(Con inued)
Digi al Technology Pla o ms 57
implemen ed which allow o gene a ing and using knowledge e ec i ely, educ-
ing esou ces necessa y o pe o m p oduc ion p ocesses and also o c ea e new
jobs in sec o s in which inno a ions a e gene a ed on a la ge scale.
An example may be a Eu opean echnology pla o m “Sma G ids” (ETP
Sma G ids). I s majo aim is o de elop and dissemina e a echnology o make
Table 2.7 (Con inued)
Thema ic a ea Types o PTPs Coo dina o s Aims o ac i i y
IT Technologies Polish Chambe o
IT Technology and
Telecommunica ions
Implemen a ion
o inno a i e IT
echnologies
Mobile Technology
and Wi eless
Communica ion
MOST Founda ion De elopmen o
mobile and wi eless
echnologies
T anspo Sma T anspo
Sys ems
Mo o T anspo
Ins i u e (ITS)
De elopmen o sma
anspo Sys ems
A ia ion WSK
“PZL – Rzeszów”
Cons uc ion o new
gene a ion engines
Space Technologies Space Resea ch
Cen e o he Polish
Academy o Sciences
(CBK PAN)
De elopmen o new
echnologies o space
ac i i ies
Road T anspo Road and B idge
Resea ch Ins i u e
(IBDiM)
Cons uc ion o elec ic
ca s and ca s powe ed
by al e na i e uels
T ack T anspo Wa saw Uni e si y o
Technology
P oduc ion o new ack
ehicles
Wa e T anspo Ma i ime Ad anced
Resea ch Cen e
(CTO)
De elopmen o wa e
anspo in as uc u e
Ad anced
ma e ials
Cons uc ion ASM Ma ke Resea ch
and Analysis Cen e
De elopmen o he
cons uc ion sec o
P oduc ion
P ocesses
W ocław Uni e si y
o Science and
Technology
De elopmen o
cu ing‑edge machines
and de ices
Tex ile Indus y Łódź Uni e si y o
Technology
De elopmen o he ex ile
sec o
Ad anced
Ma e ials
Ins i u e o
High‑P essu e
Physics o he Polish
Academy o Sciences
(Unip ess, IWC
PAN)
Suppo ing inno a i e
solu ions in he
au omo i e, a ia ion
and de ence indus y
Sus ainable
Chemis y
Polish Chambe o
Chemical Indus y
De elopmen o
echnology o chemical
ma e ials
Sou ce: A. Siemaszko, M. Sna ska‑Świde ska, “Polskie Pla o my Technologiczne,” [in:] A. Bąkowski,
M. Mażewska, eds., Oś odki innowacji i p zedsiębio czości w Polsce. Rapo  2012, Polska Agencja
Rozwoju P zedsiębio czości, Wa saw 2012, pp. 169–172; B. Szumiec‑P esch, U wo zono nowe polskie
pla o my echnologiczne, h p://labo a o ia.ne /ak ualnosci/_i em,3691,p in ,1.h ml [accessed 28 No-
embe 2019]; h p://7p .kpk.go .pl/pp /pp .h ml‑id=815.h m [accessed 29 No embe 2019].
58 Digi al Technology Pla o ms
i possible o supply elec ici y o , mo e b oadly, o p o ide ene gy se ices, o
consume s, using digi al echnology. In his espec , ools a e es ed and in oduced
wi hin Sma G ids allowing o bi‑di ec ional ene gy lows as well as in eg a ion
o dispe sed sou ces, including hose based on enewable esou ces. Due o his,
i is possible o gene a e la ge sa ings, o ensu e g ea e ope a ing e ec i eness
o elec ici y sys ems ( hey a e mo e esis an o ailu es) as well as o p omo e
echnologies which educe g eenhouse gas emissions (pho o ol aic panels, small
wind u bines o small hyd oelec ic powe plan s). This way, sus ainable g ow h
objec i es a e achie ed, including hose conce ning en i onmen al p o ec ion o
inno a i eness, e ec i eness and compe i i eness o en e p ises.102
Desc ibing ields o applica ion o DTPs, i is also wo h p esen ing da a abou
o wha ex en such pla o ms a e used wi hin each sphe e o en e p ises’ ope a ion.
Rele an da a come om, among o he sou ces, a su ey pe o med in 2013 by
Ama ach Resea ch and Deloi e on a sample o 201 decision‑make s wo king in
he IT sec o in Poland (G aph 2.2).
In Polish companies, needs o using mode n echnologies, including DTPs, a e
sa is ied he mos in such a eas as cus ome se ice (high and e y high sa is ac ion
le el was decla ed by 37% o esponden s), e iciency (32%), cos s (31%) and en-
do managemen (29%), while hey a e sa is ied he leas in employee aining (low
o e y low sa is ac ion le el was indica ed by 56% o esponden s), ec ui men
managemen (51%) o supply chain managemen (41%). The da a show ha digi al
echnologies in Poland a e used mainly o pe o m sales, p ocu emen o cus ome
se ice p ocesses, while hese echnologies, he e o e also DTPs, a e needed mos
o human esou ces managemen .
The wide ange o using DTPs in he mode n economy ollows mos ly om he
ac ha hey gene a e many bene i s. In one egula ion o he Eu opean Commis-
sion and o he Council, i is s essed ha
G aph 2.2 Le el o using digi al echnologies o mee needs o Polish en e p ises acco ding
o a 2013 su ey by Ama ach Resea ch and Deloi e
Sou ce: Cy owa p zyszłość Polski…, op. ci ., p. 46.
Digi al Technology Pla o ms 59
[o]nline in e media ion se ices a e key enable s o en ep eneu ship and
new business models, ade and inno a ion, which can also imp o e con-
sume wel a e and which a e inc easingly used by bo h he p i a e and public
sec o s. They o e access o new ma ke s and comme cial oppo uni ies al-
lowing unde akings o exploi he bene i s o he in e nal ma ke . They allow
consume s in he Union o exploi hose bene i s, in pa icula by inc easing
hei choice o goods and se ices, as well as by con ibu ing o o e ing
compe i i e p icing online, bu hey also aise challenges ha need o be ad-
d essed in o de o ensu e legal ce ain y. […] Online in e media ion se ices
can be c ucial o he comme cial success o unde akings who use such se -
ices o each consume s.103
Thus, DTPs, c ea e g ounds no only o g ow h o en e p ises, o e ing hem
access o new ma ke s, bu also con ibu e o imp o emen o consume s’ wel a e
by, o example, allowing hem o pu chase speci ic p oduc s o se ices a com-
pe i i e p ices.
Conside ing ha he use o a DTP in many cases is associa ed wi h pe o m-
ing in en e p ises sys em ans o ma ion, bene i s gene a ed due o he pla o ms
la gely esul jus om such ans o ma ion. I is mos ly connec ed wi h:
– ans o ma ion o business p ocesses which became comple ely digi ised,
making i possible o manage human esou ces mo e e ec i ely, make be e
decisions, in ensi y coope a ion wi h a ious en i ies and inc ease employee
pa icipa ion;
– ede ini ion o business models in which he majo ole begins o be played by
de elopmen o digi al p oduc s, ex ending ac i i y o mo e and mo e ma ke s in
he wo ld and also building new dis ibu ion channels sha ed by many en i ies;
– inc easing e ec i eness o cus ome se ice by gaining deepe insigh s on con-
sume s, including hei needs o p oduc s and se ices.104
E. J. Al man and M. L. Tushman indica ed wo main aspec s o using DTPs.
Fi s , hey allow o a conside able g ow h o in e dependence among en i ies ope -
a ing on he ma ke , which includes all kinds o ela ionships, such as B2B o B2C.
Second, he pla o ms, because o hei openness, may be mode nised and upda ed
all he ime, which in u n cause hem, on he one hand, o g oup mo e and mo e
p og amme s and use s, con ibu ing o he cons uc ion o business ecosys ems,
and on he o he , o be con inuously adjus ed o e e changing ma ke equi emen s
o cus ome s’ needs. Thus, hei ope a ion is cons an ly op imised so ha hey a e
mode n and be able o compe e e ec i ely wi h o he IT sys ems o ools. This p o-
ides use s wi h many bene i s, including access o cu ing‑edge echnologies.105
R. Telles b oadly e e ed o he po en ial bene i s ha may be associa ed wi h
he use o online pla o ms, including in he con ex o he abo e‑men ioned sha -
ing economy. Acco ding o him, he use o DTPs leads o he de elopmen o he
66 Digi al Technology Pla o ms
7 M. Kulka, op. ci ., p. 4.
8 D.A. Myślak, “Telewizja cy owa i jej cy owe pochodne a oczekiwania współczesnego
odbio cy,” Media, Kul u a, Komunikacja Społeczna 2017, no. 1, pp. 31–55.
9 B. Twa dowski, SaaS:  Zmieniamy  podejście  z  lokalnych  ozwiązań  na  pla o my
usługowe, h ps://www.e p‑ iew.pl/i _solu ions/saas_zmieniamy_podejscie_z_loka-
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10 Digi alisacja ynku B2B. Cy owe pla o my zakupowe – apo Aleo i Deloi e,
Aleo – Deloi e, Wa saw 2017.
11 B. G ego , A. Łaszkiewicz, M. S awiszyński, “Obsza y gene owania wa ości p zez
wi ualne pla o my wymiany handlowej w sek o ze B2B ma le doświadczeń ope a-
o ów pla o m w Polsce,” S udia i Ma e iały Polskiego S owa zyszenia Za ządzania
Wiedzą 2009, no. 21, p. 22.
12 K. Wy wińska, M. Wy wiński, “Pla o my in e ne owe jako na zędzia ekonomii
współdzielenia,” T ans o macje P awa P ywa nego 2018, no. 2, pp. 91–112.
13 C . R. Sun, B. Kea ing, S. G ego , op. ci ., p. 2.
14 T. Saa ikko, An Inqui y in o he Na u e and Causes o Digi al Pla o ms, Depa men o
In o ma ics Umea Uni e si y, Umea 2016, p. 11.
15 M.A. Cusumano, “Pla o ms Ve sus P oduc s: Obse a ions om he Li e a u e and
His o y,” [in:] S. Kahl, B. Sil e man, M.A. Cusumano, eds., Ad ances in S a egic
Managemen , Eme ald G oup Publishing, Bingley 2012, p. 36.
16 L.D.W. Thomas, E. Au io, D.M. Gann, “A chi ec u al Le e age: Pu ing Pla o ms in
Con ex ,” Academy o Managemen Pe spec i es 2015, ol. 28, no. 2, pp. 199–201.
17 Such an app oach may be ound in he ollowing s udies: Digi alisacja ynku B2B…, op.
ci ., p. 3; R. Sun, B. Kea ing, S. G ego , op. ci ., pp. 1–2.
18 P. Cons an inides, O. Hen idsson, G. Pa ke , op. ci ., p. 1.
19 Technology  Pla o ms  om  De ini ion  o  Implemen a ion  o   a  Common  Resea ch
Agenda, Eu opean Commission, Luxembou g 2004, p. 15.
20 M. Kulka, op. ci ., p. 4.
21 M. de Reu e , C. Sø ensen, R.C. Basole, op. ci ., p. 5.
22 W. Pisa ek, ed., Słownik  e minologii medialnej, Towa zys wo Au o ów i Wydawców
P ac Naukowych Uni e si as, K aków 2006, p. 147.
23 L. Mo gan, F. Hin e mann, M. Vazi ani, Fi e Ways o Win wi h Digi al Pla o ms, Ac-
cen u e, Dublin 2016, p. 8.
24 D. Co in S ig, op. ci ., p. 17.
25 H. LeHong, C. Howa d, D. Gaughan, D. Logan, op. ci ., p. 4.
26 R. Sun, B. Kea ing, S. G ego , op. ci ., p. 5.
27 C. Busch, G. Dannemann, H. Schul e‑Nölke, A. Wiewió kowska‑Domagalska, F. Zoll
(Resea ch G oup on he Law o Digi al Se ices), “Discussion D a o a Di ec i e on
Online In e media y Pla o ms,” Jou nal o Eu opean Consume and Ma ke Law 2016,
no. 5, p. 164.
28 K. Wy wińska, M. Wy wiński, op. ci ., p. 97.
29 R.G. Fichman, “Real Op ions and IT Pla o m Adop ion: Implica ions o Theo y and
P ac ice,” In o ma ion Sys ems Resea ch 2004, no. 15, p. 132.
30 A. Fabe , F. Ma hes, F. Michel, Digi al Mobili y Pla o ms and Ecosys ems. S a e o he
A Repo , Technical Uni e si y o Munich, Munich 2016, p. 2.
31 Ibid., p. 2.
32 A. Lipińska, “Koncepcje i kluczowe czynniki ozwoju ekosys emów s a upów,” S udia
Ekonomiczne. Zeszy y Naukowe Uniwe sy e u Ekonomicznego w Ka owicach 2018, no.
351, p. 48.
33 A. Siemaszko, Pla o my echnologiczne w Polsce, Akademickie Mazowsze 2030, Wa -
saw 2012, p. 11.
34 B. G ego , A. Łaszkiewicz, M. S awiszyński, op. ci ., p. 22.
35 M. Goliński, op. ci ., pp. 181–182.

Digi al Technology Pla o ms 67
36 Communica ion om he Commission o he Eu opean Pa liamen , he Council,
he Eu opean Economic and Social Commi ee and he Commi ee o he Regions.
Online Pla o ms and he Digi al Single Ma ke . Oppo uni ies and Challenges
o Eu ope. B ussels, 25 May 2016, h ps://eu ‑lex.eu opa.eu/legal‑con en /PL/
TXT/?u i=CELEX%3A52016DC0288 [accessed 12 No embe 2019], pp. 2–3.
37 C . S. Ki chne , E. Schüßle , “The O ganisa ion o Digi al Ma ke places: Unmasking
he Role o In e ne Pla o ms in he Sha ing Economy ”, [in:] G. Ah ne, N. B unsson,
eds., O ganisa ion Ou side O ganisa ion, Camb idge Uni e si y P ess, Camb idge
2018, p. 131.
38 M. de Reu e , C. Sø ensen, R.C. Basole, op. ci ., p. 5.
39 A. Lipińska, op. ci ., p. 49.
40 Fo example: T. Saa ikko, op. ci ., p. 11; M. de Reu e , C. Sø ensen, R.C. Basole, op.
ci ., p. 5; R. Sun, B. Kea ing, S. G ego , op. ci ., p. 5.
41 M. de Reu e , C. Sø ensen, R.C. Basole, op. ci ., p. 5.
42 T. Saa ikko, op. ci ., p. 15.
43 H. LeHong, C. Howa d, D. Gaughan, D. Logan, op. ci ., p. 4–5.
44 Ibid., p. 4.
45 Bene i s  o   Online  Pla o ms, h ps://www.oxe a.com/ge media/84d 70 3‑8 e0‑4ad1‑
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46 Ibid., pp. 2–3.
47 A. Kosie adzka, K. Ros ek, “Koncepcja pla o my komunikacyjno‑usługowej dla
s uk u sieciowych,” [in:] R. Knosala, ed., XXI Kon e encja Innowacje w Za ządzaniu
i  Inżynie ii.  Ma e iały  kon e encyjne, ol. 1, Polskie Towa zys wo Za ządzania
P odukcją, Zakopane 2015, p. 462.
48 R.G. Fichman, op. ci ., p. 132.
49 K. Mohan y, T ends in Digi al Technology Pla o m, h ps://www. u o ialspoin .com/
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50 C. Combe, In oduc ion o e‑Business, Managemen and S a egy, Rou ledge, Ams e dam –
Bos on – Heidelbe g – London – New Yo k – Ox o d – Pa is 2006, p. 67.
51 E. Chilmon, “Adminis acja publiczna wymyślona na nowo,” IT w Adminis acji 2013,
special issue, pp. 8–11.
52 T. Wallace, The S a e o Ecomme ce Pla o ms in 2018. Cloud Comme ce, Open SaaS
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53 A. Bá cena, A. P ado, M. Cimoli, R. Pé ez, op. ci ., p. 29.
54 Digi alisacja ynku B2B…, op. ci ., p. 10.
55 K. Wy wińska, M. Wy wiński, op. ci ., p. 97.
56 A. Adamski, Media  w  analogowym  i  cy owym  świecie.  Wpływ  cy owej  ewolucji
na  ekon igu ację  komunikacji  społecznej, Dom Wydawniczy Elipsa, Wa saw 2012,
pp. 40–41.
57 M. Odlanicka‑Poczobu , S. Olko, M. K amnich, op. ci ., p. 18.
58 Communica ion om he Commission o he Eu opean Pa liamen , he Council, he Eu-
opean Economic and Social Commi ee and he Commi ee o he Regions. Online Pla -
o ms and he Digi al Single Ma ke . B ussels, 6 May 2015, h ps://eu ‑lex.eu opa.eu/
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59 Bene i s o online pla o ms…, op. ci ., p. 3.
60 N. Khan, A. No aziah, E.I. Ismail, M.M. De is, “Cloud Compu ing. Analysis o Va ious
Pla o ms,” In e na ional Jou nal o E‑En ep eneu ship and Inno a ion 2012, ol. 3,
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61 T. Ba uś, “Rozpoznanie wyb anych o e ynku cloud compu ing,” S udia Ekonom‑
iczne. Zeszy y Naukowe Uniwe sy e u Ekonomicznego w Ka owicach 2016, no. 270,
68 Digi al Technology Pla o ms
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ing in Poland,” Managemen Sciences 2018, ol. 23, no. 4, pp. 19–20.
66 D. Howc o , B. Be g all‑Ka ebo n, “A Typology o C owdwo k Pla o ms,” Wo k,
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68 Cy owa Polska, McKinsey&Company – Fo bes, Wa saw 2016, p. 20.
69 Klien  w świecie cy owym, PwC, Wa saw 2016, p. 16.
70 Cy owa p zyszłość Polski. Fundamen y ozwoju konku encyjnej gospoda ki w dobie
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71 C. Busch, G. Dannemann, H. Schul e‑Nölke, A. Wiewió kowska‑Domagalska, F. Zoll,
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73 K. Mohan y, op. ci .
74 S. Galloway, The Fou : The Hidden DNA o Amazon, Apple, Facebook, and Google,
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75 R. Milic‑Cze niak, “Rola in echów w ozwoju innowacji inansowych,” S udia BAS
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76 U. Dola a, Apple, Amazon, Google, Facebook, Mic oso : Ma ke Concen a ion –
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77 N. Smy naios, In e ne Oligopoly. The Co po a e Takeo e o Ou Digi al Wo ld, Em-
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79 Ibid.
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82 A. Siemaszko, op. ci ., p. 11; h ps://www.kpk.go .pl/?page_id=11408 [accessed 20 No-
embe 2019].
83 Jou nal o Laws o he Republic o Poland (Dz.U.) o 2019, I em 229.
84 A icle 1 Sec ion 1–2 and A icle 32 Sec ion 1 o he Ac on he Indus y o he Fu-
u e Pla o m Founda ion (‘Fundacja Pla o ma P zemysłu P zyszłości’) o 17 Janua y
2019.
85 P og am “Od papie owej do cy owej Polski” – najważniejsze in o macje i ak ualny
s a us p ac, h ps://www.go .pl/web/cy yzacja/dokumen y33 [accessed 20 No embe
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86 Communica ion om he Commission o he Eu opean Pa liamen , he Council, he
Eu opean Economic and Social Commi ee and he Commi ee o he Regions. Online
Pla o ms and he Digi al Single Ma ke ..., op. ci ., p. 14.
Digi al Technology Pla o ms 69
87 OJ UE L 186 o 11 July 2019.
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89 A icle 3(1) o Regula ion (EU) 2019/1150 o he Eu opean Pa liamen and o he
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90 A icle 9(1) o Regula ion (EU) 2019/1150 o he Eu opean Pa liamen and o he
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91 A icle 11 o Regula ion (EU) 2019/1150 o he Eu opean Pa liamen and o he
Council.
92 M. Ciesielski, Fi my echnologiczne wchodzą na ynek inansowy bocznymi d zwiami,
h ps://m.in e ia.pl/innowacje/news,nId,2660442 [accessed 20 No embe 2019].
93 I em 2 o Regula ion (EU) 2019/1150 o he Eu opean Pa liamen and o he Council.
94 N. Ismail, Digi al Pla o ms Eme ging as a C i ical Business Building Block – Ga ne ,
h p://www.in o ma ion‑age.com/digi al‑pla o ms‑eme ging‑c i ical‑business‑
123465429/ [accessed 20 No embe 2019].
95 A. Kosie adzka, K. Ros ek, op. ci ., p. 458.
96 R. Kapu , Signi icance o Digi al Technology, h ps://www. esea chga e.ne /publica‑
ion/323829721_Signi icance_o _Digi al_Technology [accessed 27 No embe 2019],
pp. 2–4.
97 h ps://www.kpk.go .pl/?page_id=11408 [accessed 28 No embe 2019].
98 A. Siemaszko, op. ci ., p. 11
99 h ps://www.kpk.go .pl/?page_id=11408 [accessed 28 No embe 2019].
100 Communica ion om he Commission Eu ope 2020. A s a egy o sma , sus ain-
able and inclusi e g ow h, B ussels, 3.3.2010, h ps://ec.eu opa.eu/eu2020/pd /1_PL_
ACT_pa 1_ 1.pd . [accessed 14 Ap il 2021].
101 Eu ope 2020, p. 5.
102 J. Malko, H. Wojciechowski, “Eu opejska pla o ma echnologiczna sieci in eligen ‑
nych ‘Sma G ids’,” Ins al 2009, no. 12, pp. 1–4.
103 I ems (1) and (2) o he p eamble o Regula ion (EU) 2019/1150 o he Eu opean Pa ‑
liamen and o he Council.
104 S. Locken, The De ini i e Guide o he Business Bene i s o Digi al T ans o ma ion,
h ps://www.edialliance.com/blog/ he‑de ini i e‑guide‑ o‑ he‑business‑bene i s‑
o ‑digi al‑ ans o ma ion [accessed 2 Decembe 2019].
105 E.J. Al man, M.L. Tushman, Pla o ms, Open/Use Inno a ion, and Ecosys ems.
A S a egic Leade ship Pe spec i e, Ha a d Business School, Camb idge 2017,
pp. 11–12.
106 R. Telles, “Digi al Ma ching Fi ms. A New De ini ion in he “Sha ing Economy”
Space,” ESA Issue B ie 2016, no. 1, pp. 3, 11–15.
107 E.G. Ande son, G.G. Pa ke , B. Tan, “Pla o m Pe o mance In es men in he P esence
o Ne wo k Ex e nali ies ”, In o ma ion Sys ems Resea ch 2014, no. 1, pp. 152–156.
108 E. B ousseau, T. Pena d, “The Economics o Digi al Business Models: A F amewo k
o Analyzing he Economics o Pla o ms,” Re iew o Ne wo k Economics 2007, ol.
6, no. 2, pp. 82–93.
109 Digi alisacja ynku B2B…, op. ci ., p. 6.
110 B. G ego , A. Łaszkiewicz, M. S awiszyński, op. ci …, pp. 22, 27–28.
111 A. Kosie adzka, K. Ros ek, op. ci ., pp. 467–468.
112 Examining he Impac o Technology on Small Business. How Small Business Use
Social Media and Digi al Pla o ms o G ow, Sell and Hi e, h ps://www.uschambe .
com/si es/de aul / iles/c ec_sme‑ p _ 3.pd [accessed 2 Decembe 2019], p. 3.
113 Ibid., pp. 3, 7.
114 K. Mohan y, op. ci .
115 The Pos ‑Digi al E a Is Upon Us. A e You Ready o Wha ’s Nex ? Accen u e Technol-
ogy Vision 2019, Accen u e, Dublin 2019, pp. 10–15.
70 Digi al Technology Pla o ms
116 The Founda ion is o suppo digi al ans o ma ion o Polish companies, among o he
hings, in he a ea o a i icial in elligence, see A icle 1 o he Ac on he Indus y o
he Fu u e Pla o m Founda ion.
117 Założenia do s a egii AI w Polsce. Plan działań Minis e s wa Cy yzacji (‘Assump-
ions o he AI S a egy in Poland. Ac ion Plan o he Minis y o Digi al A ai s’),
Minis e s wo Cy yzacji, Wa saw 2018, pp. 33–34.
118 B. Kiljan, RankB ain – sz uczna in eligencja w wyszukiwa ce Google, h ps://mobi-
le y.com/blog/ ankb ain‑sz uczna‑in eligencja‑w‑wyszukiwa ce‑google [accessed 10
Decembe 2019].
119 T. Pielas, O  ozwiązaniach AI, o k ó ych ma ke e om się nawe  nie śniło, h ps://ai-
business.pl/o‑ ozwiazaniach‑ai‑o‑k o ych‑ma ke e om‑sie‑nawe ‑nie‑snilo/ [accessed
10 Decembe 2019].
120 h ps://hema oonkologia.pl/ak ualnosci/news/id/3545‑nowa‑polska‑pla o ma‑ze‑
sz uczna‑in eligencja‑moze‑wyk ywac‑nowo wo y‑juz‑na‑wczesnym‑e apie [accessed
10 Oc obe 2019].
121 S. Bha acha ya, B. Czejdo, R. Ag awal, E. E demi , “Open Sou ce Pla o ms and
F amewo ks o A i icial In elligence and Machine Lea ning,” [in:] IEEE Sou heas ‑
Con 2018, Tampa Bay 2018, pp. 2–3.
122 K. Mohan y, op. ci .
123 M. Ciesielski, op. ci .
124 Alphabe is a conglome a e se up by Google in 2015.
DOI: 10.4324/9781003473022-4
3.1 Business Model – Theo e ical App oach
The e m o key impo ance o he discussion in his monog aph is “business
model.” I is he e o e necessa y o examine i in dep h o isola e i s mos impo an
aspec s om he poin o iew o inno a i eness and he use o digi al communica-
ion pla o ms.
Fi s , he e y e m “model” should be de ined. One o he basic de ini ions was
o mula ed by J. Zieleniewski. The au ho s essed he ac ha a model is a heo y
which allows o acqui ing knowledge abou he en i onmen and also o using
easoning in which alues o pa icula a iables a e changed o e i y he impac
o such ope a ions on he emaining a iables. In a model, i is impo an o ma-
nipula e di e se a iables which a e pa o i . This way, a model becomes use ul
o he applica ion o speci ic heo e ical solu ions o p ac ical ma e s.1
Acco ding o B. Glinkowska, a model may be examined om wo basic
pe spec i es – s uc u al and unc ional. Adop ing he i s pe spec i e, he model
is a cons uc wi h he use o which a ce ain objec is ep esen ed, ei he eal o
abs ac one. The e o e, such an app oach s esses ha a model has an ins umen-
al unc ion, demons a ing an objec by e ealing i s speci ic cha ac e is ics. The
unc ional pe spec i e, in u n, emphasises ha a model is a cons uc which in
he cou se o cogni i e ope a ions and expe imen s eplaces a speci ic eal objec .2
Z. Ma yniak dis inguishes h ee possible senses o he e m “model.” Fi s , i
may be pe cei ed as a heo y consis ing o a se o s a emen s which may be ound
o be ue. In his meaning, a model may be no as much as a heo y bu also a sup-
plemen o o simpli ica ion o a heo y. In he second sense, a model is a speci ic
pa e n, he e o e a ep esen ed objec . Finally, in he hi d sense, a model u ns ou
o be a ep esen a ion, so i should be ea ed as a ep esen ing objec .3
In he scien i ic li e a u e, a much g ea e numbe o de ini ions o a model can
be ound. The e is no need o discuss all o hem he e. Fo example, i migh be jus
men ioned ha R. L. Acko hough ha a model is a ep esen a ion o a ce ain
s a e, objec o e en , aking in o conside a ion ele an cha ac e is ics o he eal-
i y; acco ding o T. Gospoda ek, a model is a cohe en o comple e sys em o a gu-
men s o logical sequences ega ding a speci ic objec o e en ; s ill, acco ding o
E. V. K ick, a model should be cons ued as some hing which allows o desc ibing
3 Inno a i e Changes o Business
Models
This chap e has been made a ailable unde a CC‑BY‑NC‑ND license.

72 Inno a i e Changes o Business Models
he cha ac e o beha iou o he espec i e o iginal, so ep esen ing some hing,
wi h he use o numbe s, symbols, schema ic diag ams and g aphs.4
As a as a “business model” is conce ned, i should be s essed ha so a a
g ea numbe o de ini ions o he e m ha e been o mula ed and in gene al none
o hem can be ega ded as ully comp ehensi e.5 This is so because each au ho
ocuses on selec ed elemen s o a business model, in addi ion o e ing a di e en
classi ica ion o such models.6 In connec ion wi h his, i is wo h p esen ing only
some o he p oposed scien i ic de ini ions o a business model. Fi s o all, how-
e e , i should be no ed ha he e m “business model” goes back o he 1950s.7 I
was hen discussed mainly in e e ence o he azo and blades model, in which
companies sell hei own p oduc s a low p ices, o en a a loss, while he basic in-
come is gene a ed om selling goods and se ices complemen a y o he p oduc .8
One de ini ion o a business model comes om T. Doligalski. The au ho sug-
ges ed ha such a model is an image o a speci ic o ganisa ion cap u ed a he
espec i e momen which o a la ge ex en pe ains o ac i i ies aimed o c ea e
economic alue and o in e nal mechanisms o he o ganisa ion’s ope a ion. This
way, a business model may be ea ed as he essence o an en e p ise and, i s o
all, as hose aspec s o i s ope a ion which a e c ucial o i s s eng h.9 A. Jabłoński
s a ed ha a business model should be ega ded as a ep esen a ion o a s uc u e
o ela ions which may be disce ned in he espec i e o ganisa ion and i s en i-
onmen , wi h he p o iso ha i is a ep esen a ion a a speci ic place, ime and
business space. Acco ding o ha au ho , such a model is inex icably connec ed
wi h ac o s which in luence he sa is ac ion o he needs o cus ome s, business
pa ne s o social o ganisa ions, which in u n condi ion he achie emen o com-
pe i i e ad an age, making he mos adequa e decisions and un es ic ed g ow h o
he o ganisa ion.10 Acco ding o B. Nogalski, a business model is a gene al concep-
ion o conduc ing business ac i i y, which akes in o conside a ion di e se aspec s
ela ed o i . P ima y impo ance among hese mus be a ached o he alue o e ed
o he cus ome as well ela ions wi h pa ne s, inno a i eness o esou ces a ail-
able o he o ganisa ion.11 In u n, K. Obłój concluded ha a business model is a
concep ela ing p ima ily o he achie emen o a dominan compe i i e ad an age
by an en e p ise, i s u ilisa ion o i s own esou ces and skills as well as con igu a-
ion o a alue chain.12
De ini ions o a business model p oposed by o he esea che s han he Pol-
ish au ho s can be seen o ake a di e en o mo e de eloped app oach o issues
ela ed o he essence o he model. This is shown, o example, by he de ini ion
p oposed by A. Os e walde , Y. Pigneu and C. L. Tucci. The au ho s unde lined
ha a business model is a concep ual ool which makes i possible o p esen he
business logic o a i m, including he way in which p o i is gene a ed om he
c ea ed alue. Such a model con ains all he componen s o a i m and ela ionships
obse ed be ween hem.13 Acco ding o A. A uah and C. L. Tucci, a business model
is he me hod o inc easing esou ces adop ed by a i m o o e i s cus ome s be -
e alue o p oduc s and se ices han i s compe i o s and o achie e p o i doing
so.14 A. A. Thompson and A. J. S ickland esol ed ha a business model e e s
p ima ily o s eams o e enues, also u u e ones, as well as o he s uc u e o
Inno a i e Changes o Business Models 73
cos s incu ed by a i m o he le el o ma gin. In mos gene al e ms, he au ho s
no iced ha a business model amoun s o ela ions be ween a i m’s e enues, cos s
and p o i s.15 In u n, E. Fiel s essed he ac ha a business model should be
ega ded as he logic o an o ganisa ion’s ope a ion p ima ily in e ms o how i
c ea es cus ome alue.16
M. Mo is, M. Schindehu e and J. Allen indica ed ha i is possible o so
ou he basic app oaches o a business model. Ha ing analysed hi y de ini ions,
he au ho s concluded ha a business model may be iewed om he economic,
ope a ional o s a egic pe spec i es, wi h each o hem in ol ing a unique se o
decision a iables a ec ing he business model’s cons uc ion. In he economic
pe spec i e, a business model desc ibes how he i m gene a es p o i s o how i
makes money and sus ains i s p o i s eam o e ime. In his pe spec i e, he deci-
sion a iables include e enue sou ces, cos s uc u es, ma gin le el o company
alua ion me hods. The second, ope a ional, pe spec i e assumes ha a business
model e e s o all he in e nal p ocesses making i possible o he i m o c e-
a e alue. In his app oach, he key decision a iables include p oduc ion and ad-
minis a i e p ocesses, esou ce lows o se ice p o ision me hods. Finally, in
he s a egic pe spec i e, a business model pe ains o all he aspec s o he i m’s
ope a ion ela ed o i s g ow h, ma ke posi ioning and coope a ion wi h o he en-
i ies. This pe spec i e also conside s he i m’s ision and alues. Fu he mo e,
acco ding o he au ho s, using any business model, ega dless o he pe spec i e,
should lead o he achie emen o a sus ainable compe i i e ad an age.17
Acco ding o S. Sla ik and R. Bedna , business models should be desc ibed
in wo pe spec i es – pu ely economic (economic business model) as well as in
ha which combines he inancial aspec s wi h c ea ing alue (economic and alue
business model).18 Examples o de ining a business models om hese wo poin s
o iew a e p esen ed in Table 3.1.
An in e es ing app oach o he essence o a business model was p oposed by
S. M. Sha e , H. J. Smi h and J. C. Linde . In pa icula , he au ho s desc ibed he
e m, aking in o accoun key wo ds used in i s nume ous de ini ions. These key
wo ds we e pu in ou g oups. They ela e o he ollowing aspec s:
– s a egic choices – in his espec , a business model is abou cus ome s, s a egy,
mission, e enues o compe i o s;
– c ea ing alue – esou ces, asse s o p ocesses;
– cap u ing alue – inancial issues conce ning he ela ion be ween cos s and
p o i s;
– alue ne wo k – ela ionships wi h cus ome s and supplie s, p oduc , se ice
and in o ma ion lows.19
In u n, A. Os e walde and Y. Pigneu dis inguished many elemen s making
up a business model. They a e p esen ed by he au ho s wi hin ou a eas o busi-
ness ac i i y. Such elemen s wi hin he in as uc u e a e key esou ces, ac i i-
ies and pa ne s, and o cus ome s – cus ome segmen s (po en ial ecipien s o
he o ganisa ion’s o e ), ela ionships wi h hem as well as dis ibu ion channels
74 Inno a i e Changes o Business Models
(communica ion wi h cus ome s and ways o deli e ing hem alue p oposi ions),
wi h espec o he o e – alue p oposi ion (a bundle o p oduc s and se ices
b inging speci ic alue o cus ome s), and wi h espec o inancial posi ion –
e enue s eams and cos s uc u e.20
As shown by he de ini ions p esen ed abo e, a business model is a e m which
may be unde s ood e y b oadly. In addi ion, i is possible o dis inguish a ious he-
o ies o business models which, signi ican ly, a e conside ed o be pa o business
managemen heo y. An example may be he economic heo y o he i m and
business model app oach o inancial epo ing. This in okes he said economic
business models. He e a business model is examined om he poin o iew o
h ee aspec s associa ed wi h he ac i i y conduc ed by he o ganisa ion. They a e
as ollows:
– inancial epo ing should be a kind o es on p ac ical execu ion o a speci ic
business model;
– his o ical cos may be he mos eliable measu emen when he business model
is o con ibu e o he de elopmen o new asse s o se ices;
– ai alue may be he mos e ec i e measu e when he business model in ol es
buying and selling some asse s using changes in ma ke p ices.21
One o he app oaches wi hin business managemen heo ies which is used mo e
and mo e equen ly by companies is a ool o business model gene a ion known
as he Business Model Can as. I is a empla e which shows how o do business o
Table 3.1 Example de ini ions o economic business model and economic and alue busi-
ness mode
De ini ion au ho s Business model
Economic business model
H. Chesb ough F amewo k o link new ideas and echnologies o economic
ou comes
D. Debelak Ins umen by which a business is able o gene a e p o i s
A. Ganba della,
A. McGahan
Mechanism o ans o ma ion o ideas o e enues
J. Mullins, R. Komisa Basis o economic ac i i y in all i s aspec s ega ding cash lows
T. Wheelen, D. Hunge Me hod o making money in business ac i i y, in which speci ic
cha ac e is ics o he company a e o key impo ance
Economic and alue business model
J. Mag e a Desc ip ion o how an en e p ise is able o ea n money, who i s
cus ome s a e and how o deli e speci ic alue o hem
M. Rappa Me hod o doing business by which a company can gene a e
e enue and c ea e alue
D. J. Teece Tool o de ining me hods o gene a ing alue o he cus ome
D. Wa son Desc ip ion o a company’s ope a ions, including all o
i s p ocesses and unc ions which esul in alue o he
o ganisa ion and cus ome s
Sou ce: S. Sla ik, R. Bedna , op. ci ., pp. 20–21.
Inno a i e Changes o Business Models 75
gene a e conc e e eal bene i s. The concep is based on a logical jux aposi ion o
elemen s making up a business model so as o p esen a ull pic u e and o acili a e
planning p ocesses and assessmen o changes o he model.22
Acco ding o he au ho o his concep , A. Os e walde , he basic ask o a busi-
ness model is o desc ibe he a ionale o how an o ganisa ion c ea es, deli e s and
cap u es alue.23 The a ionale e e s o cus ome s, inance, in as uc u e o o e .
And he business model should be p esen ed on one shee o pape (“Can as”) o
simpli y i s cons uc ion as a as possible and, a he same ime, show i s essence
in an inno a i e manne . I is jus o his eason ha he concep is inc easingly
mo e used in business p ac ice.24 A empla e acco ding o he concep o Business
Model Can as is p esen ed in Figu e 3.1.
The Business Model Can as is made up o nine building blocks which a e
s ongly in e connec ed. The poin o depa u e a e cus ome segmen s and he e-
la ed alue p oposi ion.
Summing up, i should be emphasised ha a business model is de ined in many
aspec s, also as a concep o conduc ing business ac i i y, an image o he o gani-
sa ion’s ope a ion o he way o achie e compe i i e ad an age based on gene -
a ing p o i s and c ea ing alue. Such a model may be explained using business
managemen heo ies ( he economic heo y o he i m and epo ing, he Business
Model Can as), and u he mo e e en a business model i sel may be ega ded as
a sepa a e heo y.25 All o his show i s high complexi y and g ea ele ance o he
unc ioning o oday’s o ganisa ions.
Figu e 3.1 A empla e acco ding o he concep o Business Model Can as
Sou ce: au ho ’s own wo k based on J. Bis, op. ci ., p. 59.
82 Inno a i e Changes o Business Models
and in o ma ion sha ing e ec ed mainly h ough digi al pla o ms. I ollows om
his ha digi al business and he ela ed implemen a ion o digi al s a egies would
be impossible wi hou hese pla o ms.61
Digi al business may be conduc ed on he basis o many di e en models. Ac-
co ding o M. Ka das, hese models include:
– manu ac u ing model – use o he In e ne by o ganisa ions o ini ia e di ec
ela ionships wi h cus ome s;
– b oke age model – in his model, o ganisa ions c ea e i ual ma ke s o pe -
o ming pu chase and sale ansac ions wi h b oke s usually collec ing commis-
sion o a anging hese ansac ions;
– me chan model – sale o p oduc s o se ices h ough he In e ne o oge he
wi h adi ional dis ibu ion channels ( o example b ick and mo a acili ies);
– in omedia y model – collec ing, p ocessing da a o cus ome s and manu ac u -
e s’ o e s by o ganisa ions which p o ide he in o ma ion o a ee;
– ad e ising model – gene a ing e enues by imp o ing he a ac i eness o
websi es;
– a ilia e model – eaching b oad masses o cus ome s by es ablishing coope a-
ion wi h a ilia ed pa ne s who add links o he o ganisa ion’s po al on hei
websi es;
– subsc ip ion model – p o iding a pe iodical access o digi al se ices in ex-
change o paymen ;
– u ili y model – i is a model simila o he subsc ip ion model, wi h he di e -
ence ha he amoun o ees o using digi al se ices depends on hei ac ual
use ( o example, a ee o some quan i y o downloaded da a);
– communi y model – using olun a y wo ke s o pe o m ma ke ing ac i i ies.62
An a emp o dis inguish he mos impo an digi al business models used he
mos equen ly in he ma ke was also made by H. R. Va ian. Thei desc ip ions
a e gi en in Table 3.2, bu i mus be added ha hey e e mainly o he business
models in ol ing dis ibu ion o digi al con en which can be sen o e he web
(music, ilms, books, games).
H. R. Va ian p o ided a classi ica ion o digi al business models wi h di e en
ways o ma ke ing, selling and dis ibu ing digi al p oduc s. In such models, i is
possible o an o ganisa ion no only o pe o m hese p ocesses on i s own bu also
wi h he aid and suppo o business pa ne s o e en s a e adminis a ion (public
suppo ) o cus ome s hemsel es (e.g. he “ ansom” model).
Summing up, i should be said ha digi al business, unde s ood as pe o ming
business p ocesses based on a ious echnologies, mainly online ones, may be im-
plemen ed wi hin many di e en models. The ones desc ibed abo e do no exhaus
he ela ed opics, and u he mo e i is impo an ha changes o he models a e
made aiming o inc ease hei inno a i eness. Such changes ake place mos ly ow-
ing o he ope a ion o DTPs. Issues connec ed wi h he changes will be discussed
in he nex sec ion o his wo k.

Inno a i e Changes o Business Models 83
3.4 Inno a i e Changes o he Business Model Based on a Digi al
Technology Pla o m
Business models a e subjec o con inual ans o ma ions and, which is especially
impo an o he hema ic a ea o he wo k, DTPs ha e a g ea impac on hem.
Fi s , i is necessa y o s ess, as men ioned by C. M. Olszak, ha nowadays, o in-
c ease hei inno a i eness and compe i i eness, many o ganisa ions d aw up digi-
al s a egies. Such s a egies become he poin o depa u e o inno a i e business
models which a e based on digi al esou ces. In addi ion, such models ypically go
beyond he adi ional iew o he ole o IT in a company’s ac i i y; ins ead, hey
demons a e implemen a ion o a esou ce‑based iew and a e s ic ly connec ed
wi h gene a ing alue o he company and i s s akeholde s. This way, he majo
eason o implemen ing mode n business models, also hose based on DTPs, a e
limi a ions o he adi ional models, he de elopmen o echnologies and a g ea e
awa eness o hese among business use s.63
Table 3.2 Types o digi al business models acco ding o H. R. Va ian
Model name Desc ip ion
The o iginal cheape han
a copy
Sales o digi al p oduc s conside ably cheape han in
egula dis ibu ion by, o example, adding hem as ex a
i ems o newspape s and magazines
A copy mo e expensi e
han he o iginal
Use o echnological o legal p o ec ions by manu ac u e s
Physical complemen s Va ious addi ional i ems supplied wi h digi al con en , o
example a T‑shi o a code o ee music downloads o
p omo e a CD
In o ma ion complemen s P o iding use s who ha e been gi en digi al con en o
ee wi h addi ional componen s o se ices ( o example
access o new unc ionali ies) o a ee
Subsc ip ions Regula deli e y o speci ic con en in exchange o a ee
Pe sonalised e sion Adding o pu chased con en o iginal excep ional i ems
Ad e ise you sel A digi al p oduc deli e ed ee o cha ge is an ad e isemen
o he same p oduc in physical o m a ailable o a ee
Ad e ise o he hings B oadcas ing ad e isemen s ela ed o digi al con en , o
example on an In e ne po al
Licences Collec i e ees o g oups o use s
Ransom Po en ial use s bid o con en which is p o ided i he
o al amoun o he bids is su icien ly high, o example,
S ephen King o e ed ins almen s o his book The Plan
and hen indica ed he would con inue pos ing ins almen s
a e ecei ing paymen s o a speci ied amoun
Public p o ision Co‑ inancing he publica ion o digi al con en by public
ins i u ions o he Eu opean Union
P izes, awa ds and
commissions
Fo example, commissions om public ins i u ions
Sou ce: H.R. Va ian, “Copying and Copy igh s,” Jou nal o Economic Pe spec i es 2005, ol. 19, no.
2, pp. 134–136.
84 Inno a i e Changes o Business Models
Inno a i e changes o business models a e in oduced o a g ea ex en due o
es ablishmen and g ow h o DTPs. In his con ex , i needs o be no iced ha , as
o example in he media indus y, he e has been a g adual con e gence o many
di e en ools and channels o c ea e la ge in eg a ed pla o ms. The changes we e
also connec ed wi h he appea ance o new communica ion channels, including
hose based on mobile echnology. In addi ion, such channels made i possible o
de elop new business models.64
The changes desc ibed abo e may be aced by analysing s ages in he de elop-
men o he SMAC echnology. This is discussed in Table 3.3.
The de elopmen o SMAC echnologies, which a ec conside ably he c ea-
ion o inno a i e digi al business models, would no ha e been possible wi hou
DTPs. This is because hese echnologies ha e been accompanied by he eme -
gence o such pla o ms, ensu ing, among o he hings, exploi a ion o ne wo ked
e ec o con e gence as well as a g ea e scope o o e ed se ices and unc ionali-
ies. I may be concluded hen ha owing o DTPs, he app oach which p e ails in
he con empo a y business models is based on p omo ing coope a ion and pa ne -
ship be ween a ious en i ies o achie e speci ic business objec i es.
Such an app oach assumes a g adual eplacemen o hie a chical and e i-
cally in eg a ed managemen s uc u es o supply chains in a ou o ne wo k
Table 3.3 S ages in he de elopmen o he SMAC echnology and he ela ed ole o DTPs
Type o
echnology
SMAC 1.0 SMAC 2.0 SMAC 3.0
Social media C ea ing condi ions o
as e communica ion
be ween
acquain ances
De elopmen o
DTPs o ien ed o
communica ion
among all people
and c ea ion o
new ma ke ing
channels
In eg a ion o pla o ms
wi h CRM (cus ome
ela ionship
managemen ) sys ems
o inc ease he le el
o coope a ion wi h
consume s
Mobile
echnologies
De elopmen o BYOD
(b ing you own
de ice) concep , o
use o p i a e mobile
de ices by employees
o he needs o an
o ganisa ion
Inc ease in mobili y
o employees
because o using
inc easingly
g ea e numbe o
de ices
Coope a ion o
employees om
a ious o ganisa ions
wi hin digi al
echnology pla o ms
Big da a Desc ip ion o p esen
ends wi h he aid
o a g ea amoun o
da a
Se ing u u e ends
based on complex
DTPs designed o
da a analysis
In eg a ion o many
di e en ools,
including DTPs, o
make da a analysis
mo e e icien
Cloud
compu ing
Cloud es ing De elopmen o
cloud uses
Uploading mo e and
mo e amoun o da a in
a cloud, de elopmen
o cloud managemen
Sou ce: SMAC 3.0: digi al is he e. En e p ise IT ends and in es men s, E ns & Young LLP, Kolka a
2015, pp. 14–25.
Inno a i e Changes o Business Models 85
o ganisa ions which show a di e gen le el o o malisa ion o ela ionships
be ween a ious en i ies. Such o ganisa ions ope a ed e y equen ly on a global
scale, which is possible due o la es echnologies, including also hose in ol ing
DTPs. Mode n business models, howe e , ocus no only on inc easing collabo a-
ion be ween o ganisa ions bu also on ein o cing in e ac ions wi h cus ome s. In
such models, i is no jus a company i sel bu also he cus ome ha gene a es
speci ic alues o he company. They migh conce n he cus ome ’s commen s
o ecommenda ions abou wha should be done by he o ganisa ion o e ec i ely
mee consume s’ needs and equi emen s o a g ea e ex en han so a . This is
wha ecommenda ion and opinion sys ems, commonly used in many DTPs, a e
o . In his con ex , W. Rudny s a ed ha “analysis o business models o many
companies ha ha e achie ed a spec acula ma ke success shows a econs uc ion
o he models wi h he use o digi al echnologies o mu ual communica ion wi h
cus ome s and join c ea ion o alues.”65
E. B ousseau and T. Pena d no iced ha he con empo a y business models
which a e digi al in na u e, do no en ail changes only in he digi al sphe e. The
au ho s indica ed ha he changes should be pe cei ed as “in e modal” o such ha
a e isible in a ious a eas o a company’s ope a ion. The changes hen conce n no
only digi al con en bu also physical p oduc s and se ices and he ela ed in a-
s uc u e. Wha is mo e, digi al business models o a la ge ex en “a e c ossed” wi h
adi ional models, which hus b ing abou implemen a ion and use o new ma ke -
ing s a egies also in he indus ies no di ec ly associa ed wi h he digi al ma ke .
This shows a g ea complexi y o changes caused in mode n business models, also
on he basis o he unc ioning o DTPs.66
The aim o inno a i e changes wi hin he p esen business model based on
he pla o ms is mainly o ensu e quali y and imeliness o se ices a he highes
possible le el so ha di e se expec a ions o cus ome s a e me and, simul a-
neously, he pla o ms ecei e sa is ac o y, inc easingly highe p o i s. In such
a model, he aim is o make cus ome s au onomous so ha hey a e able o ha e
in luence on he shape o he espec i e p oduc o se ice, hus gene a ing alue
o he pla o m o he o ganisa ions c ea ing i . Wha is also e y signi ican is
pe sonalisa ion o he o e add essed o cus ome s ( he pla o ms make i possible
o con igu e p oduc s and se ices, no jus use eady‑made packages), algo i h-
imisa ion and au oma ion o p oduc and se ice sales (many choices abou he
shape o p oduc s and se ices a e made au oma ically by a ious pla o ms based
on a ious algo i hms, which makes i easie o cus ome s o pu chase goods)
as well as p o iding cus ome s, wi hin speci ic pla o ms, wi h access o con en
in he wides possible scope a he han o selec ed wo ks o book iles only (e.g.
ideo on demand se ices). In u n, wha should be men ioned is he de elopmen
o cu a ed compu ing model, based on which he App S o e pla o m ope a es.
Such a pla o m con ains digi al con en selec ed s ic ly on he basis o consum-
e s’ needs, which makes i possible o p e en he p oblem o consume s ha ing an
excessi e amoun o such con en and being unable o choose i ems which would
ma ch hei p e e ences as closely as possible. Bo h models, ideo on demand and
cu a ed compu ing, in spi e o di e ences, a e esponses o mo e and mo e apidly
changing consume needs.67
86 Inno a i e Changes o Business Models
In connec ion wi h inc easingly s ongly p og essing digi alisa ion and imple-
men a ion o ecen echnologies o managemen me hods, o ganisa ions apply-
ing adi ional business models ( e e ed o as “incumben ”) s a o be g adually
d i en ou by en i ies using inno a i e business models. This si ua ion is desc ibed
in e ms o a phenomenon known as ube isa ion ( om Ube , a company which
has in oduced a simply e olu iona y way o o e ing anspo se ices based
on a DTP). This phenomenon causes he dissemina ion o mode n business mod-
els, i.e. hose which lead o supplan ing pa e ns and me hods o unc ioning on
he ma ke which ha e wo ked well o da e. These new models a e e e ed o as
hype ‑dis up i e business models.68 A desc ip ion o he mos impo an o hem is
ound in Table 3.4.
The inno a i eness o he business models desc ibed abo e esul s no only
om he ac ha all o hem use ad anced echnologies, including equen ly
Table 3.4 The mos impo an hype ‑dis up i e business models
Model name Desc ip ion Examples o pla o ms
using he model
Access o e
Owne ship
Using p oduc s and se ices wi hou he
need o pu chase hem
Panek Ca Sha ing and
Zipca pla o ms o ca
en al o minu es
Expe ience Pe suading use s o pu chase p oduc s
and se ices o highe p ices due
o posi i e expe ience o p e ious
pu chases on he espec i e pla o m
Apple, Tesla (pla o m
o he manu ac u e o
elec ic ca s)
F eemium Model
( ee + p emium)
A p oduc o se ice a e a ailable ee o
cha ge bu ees mus be paid o using
addi ional, expanded unc ionali ies
D opbox (da a s o age),
Skype, Spo i y (access
o music)
F ee Model F ee access o p oduc s and se ices in
exchange o being o ced o iew
ad e isemen s and send da a abou he
use ’s p e e ences and beha iou in he
digi al ma ke
Facebook, Google
Hype ma ke E‑comme ce companies Amazon, Zalando
Ma ke place Ope a ion o a pla o m designed
o pe o ming pu chase and sale
ansac ions by o he en i ies
Alibaba, eBay
On demand O e ing p oduc s and se ices ins an ly
as soon as demand o hem a ises
Ne lix, Ube
Subsc ip ion
model
Fixed ee o using a p oduc o se ice Kindle (pla o m o
eading e‑books), Ne lix
The ecosys em C ea ing a closed ecosys em, which
causes use s o be in a way o ced
o ge o he p oduc s and se ices
a ailable on he espec i e pla o m
Apple, Google
The py amid O e ing p oduc s and se ices by
di e en o ganisa ions om hose
which manage he espec i e pla o m
E‑s o es, such as Amazon
Sou ce: J. Pie iegud, op. ci ., p. 19.
Inno a i e Changes o Business Models 87
a i icial in elligence. Such inno a i eness also ollows om a no el app oach
o esponding o consume s’ needs and equi emen s. Many business models and
DTPs concen a e on p o iding cus ome s wi h access o he wides possible ange
o p oduc s and se ices, including hose o e ed by di e en companies om
he en i ies managing he espec i e pla o m (Amazon, eBay), on o e ing goods
which may well be expensi e bu ma ch closely consume s’ p e e ences (Expe i-
ence model), on s a ing o p o ide a se ice ins an ly when i is demanded ( ideo
on demand) and e en on ee access o a ious se ices (Google, Skype).
In his espec , i may be obse ed ha he concep o sha ing economy, which
amoun s o a p ac ical applica ion o he Access o e Owne ship model, is becom-
ing mo e and mo e popula , also in he Polish socie y. The abo e concep makes i
possible o bo ow o en a good wi hou making a pu chase o own i . This is also
an inno a i e app oach o implemen ing business models as i is based on inc eas-
ingly widesp ead belie in he socie y ha he esou ces a ailable in he en i on-
men a e being deple ed and canno be eplaced he e o e people should ake ca e
o hem wi hou consuming hem needlessly. Consequen ly, pla o ms o sha ing
goods be ween use s a e becoming mo e and mo e popula , o example BlaBlaCa
(sha ing a ca ), Ai bnb (sha ing accommoda ion) o Ea Wi h (cooking meals).69 I
should be added ha he ope a ion o such ype o pla o ms as well as he Ma ke
Place model a e bo h mani es a ions o economics o in e media ion, in which a
pla o m se es as an in e media y be ween use s who wan o make a pu chase o
sale o exchange goods.70
A p esen , DTPs ha e much mo e uses han hose desc ibed abo e. As a esul
o his, u he business models a e being de eloped. Acco ding o W. Szp inge ,
he mos inno a i e o hose, excep o models ea ma ked o e‑comme ce o o
sha ing echnologies o so wa e wi h use s, include he ollowing:
– c owd  inancing – in he model, a pla o m is used o sea ch o sou ces o i-
nancing as well as collabo a o s and new cus ome s and ma ke s ( o example,
Kicks a e );
– mic o‑manu ac u ing – he model makes i possible o design and manu ac u e
goods using ools a ailable online (Ponoko, Make Bo Indus ies);
– inno a ion ma ke places – in his model, a ious o ganisa ions ha e he oppo -
uni y o pu chase echnologies (InnoCen i e, NineSigma).71
The e o e, inno a i e business models based on DTPs also make i possible o
ans e echnologies be ween a ious o ganisa ions o e en o a ange manu ac u -
ing p ocesses. Owing o hese models, en e p ises ac i e in di e se indus ies a e
p o ided wi h oppo uni ies o ini ia e and in ensi y ac i i y.
Inno a i e ans o ma ions o business models based on he ope a ion o DTPs
also include he de elopmen o he said ecosys ems. This is he aim o , among
o he s, he PFI model which is being mo e and mo e commonly used. This model
allows o ganisa ions o plan and pe o m inno a i e ac i i ies, including o make a
decision how o implemen hem, ha is ei he on hei own o in coope a ion wi h
ano he en e p ise. I coope a ion is chosen, hen an ecosys em is g adually c ea ed,

88 Inno a i e Changes o Business Models
ha ing in i s cen e a digi al pla o m which is cha ac e ised by in e ope abili y and
he possibili y o expanding i all he ime.72
The inno a i eness o business models which exploi he possibili ies o e ed
by DTPs is also connec ed wi h issues conce ning leade ship 4.0. Such leade ship
mus ully espond o he challenges posed be o e o ganisa ions by digi alisa ion.
This way, e e y manage , apa om adi ional compe ences, mus also ha e be
able o use new digi al media e ec i ely in he cou se o ongoing ac i i y, also
o communica ing wi h employees and o adjus ing he leade ship s a egies o
he digi al eali y, which means c ea ing an a mosphe e conduci e o c ea i i y
and inno a i eness o p omo ion o coope a i e ne wo k. A esponse o such chal-
lenges is he VOPA leade ship model, in which he key impo ance is a ached o
ne wo king (Ge man: Ve ne zung), openness (O enhei ), employee pa icipa ion
(Pa izipa ion) and agili y (Agili ä ).73 This is p esen ed in Figu e 3.3.
To sum up he abo e discussion, i is wo h obse ing ha a p esen nume ous
changes a e aking place in business models. They a e caused o a la ge ex en by
digi alisa ion and echnological p og ess, including he g ow h o DTPs. Such pla -
o ms g ea ly con ibu e o p omo ing mode n business models, in which inno a-
ion plays a key ole. The e a e plen y such models, o example hype ‑dis up i e
business models o inno a ion ma ke places, which aim o p omo e mode n ech-
nologies. Cu en changes which conce n business models based on DTPs ela e
mos ly o p omo ing mode n echnologies and digi al ools o e en a ious beha -
iou s o consume s (pla o ms such as Ube o hose in ol ing sha ing economy),
inc easing he numbe o en i ies ha coope a e wi h one ano he while being cen-
ed a ound hese models and pla o ms (due o ne wo k e ec and syne gy, hey a e
able o implemen inno a ions mo e e ec i ely and as e ) as well as es ablishing
Figu e 3.3 VOPA leade ship model
Sou ce: au ho ’s own wo k based on U. S. Foe s e ‑Me z, K. Ma qua d , N. Golowko, A. Kompalla,
C. Hell, op. ci ., p. 7.
Inno a i e Changes o Business Models 89
he b oades coope a ion wi h cus ome s by he o ganisa ions ( hey pa icipa e, o
example, in p oduc designing ac i i ies). Such changes a e possible i s o all due
o he unc ionali ies p o ided by DTPs.
3.5 Impac o Changes in Business Models on he
Compe i i eness o Companies
The na u e and ype o business models used by o ganisa ions a ec s signi ican ly
hei compe i i eness. The la e e m e e s o he mos pa o en e p ises’ ca-
pabili y o emain on he espec i e ma ke and o g ow i s own ac i i y, which
also includes s anding up o o he en i ies ope a ing on he ma ke . The capabili y
allows o con inual de elopmen o an o ganisa ion, o achie ing p o i s and o
gaining ad an age o e he emaining en e p ises. I is no i ele an ei he ha due
o compe i i eness, a company is able o deli e goods o cus ome s in acco dance
wi h hei needs in e ms o ime, quali y o loca ion.74
In iew o he abo e discussion, he e m “compe i i e ad an age” is highly im-
po an as well. In he scien i ic li e a u e, his e m is de ined p ima ily in e ms o
g ea e a ac i eness o he espec i e company’s o e compa ed o compe i o s.75
In o he app oaches, i is s essed ha compe i i e ad an age lies in he o e all
dis inc i eness o a company om i s compe i o s o any hing ha a company does
be e om o he en i ies ac i e on he same ma ke .76
Wi h ega d o compe i i eness o an o ganisa ion, wha is o g ea impo ance
is digi alisa ion and he ela ed p ocesses o mo e and mo e wide‑ anging use o
new echnologies and DTPs in he ac i i y o companies. As no ed by S. Łobejko,
he p og essing digi alisa ion exe s an inc easingly s onge in luence on he
adi ional business ela ions, o e ing new business models making i pos-
sible o cap u e alues a each s age o he alue chain and o gain compe i-
i e ad an age. Companies which achie e success in he ace o compe i ion
ha e hei business models, ope a ion and in e nal cul u e based on he idea
o digi alisa ion. In ending o de elop, hey mus in es in new echnologies
allowing o digi isa ion o business ac i i y, changing he business model as
well as ways and me hods o compe ing on he ma ke .77
In he scien i ic li e a u e, i is indica ed ha he achie emen o compe i i e
ad an age may be exp essed by a ious kinds o ac ions, successes o inancial
indica o s. In his espec , wo app oaches may be dis inguished. In he i s , he ad-
an age is hough o be demons a ed by a company’s g ea e e iciency compa ed
o compe ing o ganisa ions. In u n, he e iciency is connec ed wi h be e inancial
indica o s, he company’s high p o i abili y o ela i ely low cos s o doing busi-
ness. The second app oach places emphasis on analysing compe i i e ad an age
om he pe spec i e o i s sou ces o de e minan s. These ela e in pa icula o
echnologies used by he company, esou ces held by i , capabili ies o ope a ing on
a compe i i e ma ke o inally cos leade ship.78 I is a ac ha inno a i e changes
o business models may be conside ed wi hin bo h o he p esen ed app oaches.
90 Inno a i e Changes o Business Models
A e all, such changes con ibu e o minimisa ion o cos s, which consequen ly
imp o es he company’s inancial s anding and leads o an inc ease in i s p o i -
abili y ( he i s app oach), and u he mo e, hey a e inex icably connec ed wi h
inno a i e ac i i ies and wi h e ec i e use o a ailable esou ces ( he second ap-
p oach), which, acco ding o S. Łobejko, esul s om comple ely new combina-
ions o in o ma ion, human capi al and echnological po en ial.79
Acco ding o A. A uah and C. L. Tucci, a business model has become he mos
impo an de e minan o an o ganisa ion’s e iciency. This is because i is exac ly
due o such a model a i m is able o build and hen use i s esou ces o o e i s cus-
ome s be e alue han i s compe i o s and o achie e highe p o i s. A business
model allows o de ining me hods o making money, bo h now and in he u u e.
I is a ac o which has an impac on a i m’s compe i i eness.80
I mus be emphasised ha each business model, e en a adi ional one, may be
a sou ce o compe i i e ad an age. I is so since, acco ding o H. Chesb ough, all
business models ha e simila unc ions, including, apa om gene a ing alue o
cus ome o desc ibing cos s uc u e and p o i po en ial, he o mula ion o he
compe i i e s a egy by which he i m will gain compe i i e ad an age.81
When such models, howe e , a e buil in an inno a i e manne , ad an ages ha
may be gained by en e p ises a e much g ea e . This happens because, among o he
hings, any inno a ions help iden i y a ious oppo uni ies ha appea in he i m’s
en i onmen , which by i sel p o ides g ounds o aking ad an age o any chances
o inc easing g ow h. This is especially impo an when an o ganisa ion ope a es in
condi ions, many o which a e no conduci e o i s g ow h, o example legal es ic-
ions ( egula ed ac i i y), con ac ing aw ma e ial supplies o social p essu es.82
Acco ding o W. Szp inge , inno a i e business models, including inno a i e
changes in oduced o hem, become he sou ce o gaining compe i i e ad an age.
They do so because hey g ea ly accele a e and acili a e he pe o mance o busi-
ness p ocesses and, in addi ion, hey p o ide he oppo uni y o o e a ela i ely
la ge quan i y o goods on many di e se ma ke s (in e na ionalisa ion o ac i i y).
Since wi hin inno a i e business models, mode n echnologies, including DTPs,
a e used, hey make i possible o communica e wi h cus ome s as e , deploy a i-
ous dis ibu ion channels and c ea e new alues. Such oppo uni ies, and many o h-
e s, ollow om he use o DTPs in inno a i e business models. An example ha
can be gi en he e is inno a ion ma ke places, due o which mode n echnologies
which a e sou ces o compe i i e ad an age a e ans e ed be ween companies.83
Acco ding o J. Bis,
inno a i e business models con ibu e o inc easing companies’ p o i abili y.
P oduc s and se ices may be copied by i als e y quickly, whe eas a busi-
ness model is much ha de o ep oduce by compe i o s because i consis s o
all ele an ac i i ies pe o med in a speci ic manne .84
This is undoub edly ue. Many among business models de eloped in ecen
yea s a e cha ac e ised by o iginali y, because o he scope o applied solu ions
and echnologies, and compe i o s could no copy hem al hough hey ha e ied
Inno a i e Changes o Business Models 91
many imes; such a emp s ha e no been en i ely success ul. Wha may be o key
impo ance in such cases is implemen a ion o p o ec ion o he espec i e model,
which may be based on a sys em o copy igh s o adema ks.85
An example may be he model used wi hin he Ube pla o m, which o e s
anspo se ices o cus ome s. In he model, which is an elemen o sha ing econ-
omy o on demand sys em, a DTP is used due o which cus ome s may look o
d i e s o e ing anspo se ices. The inno a ion o e en a e olu iona y na u e
o he model ollows om he ac ha i is no used wi hin any axi co po a ion
o i m, he e o e i is comple ely independen o hem. The model makes i pos-
sible o o de ides on ehicles which a e sui able o cus ome s a a gi en ime
( o example, highe s anda d ehicles – Ube SELECT). Wha is mo e, cus ome s
may selec d i e s on he basis o opinions w i en abou hem by o he use s and
hey pay o a ide no by axime e a es bu depending on he leng h o he ac ual
ou e (measu ed by GPS ecei e s). I is also wo h poin ing ou ha Ube ini ia es
coope a ion only wi h s ic ly selec ed g oup o d i e s ( he mus ha e ehicles no
olde han he se age limi and conduc business ac i i y in he scope o anspo -
ing people) and u he mo e o e s as esolu ion o complain s ( hey may be e-
po ed ia an app o email) as well as au oma ic cashless paymen s o ides. E en
hough he e ha e appea ed compe i o s agains he Ube pla o m (in Eu ope, i
is in pa icula Es onian s a ‑up Taxi y) bu s ill Ube de ini ely domina es on he
ma ke o passenge anspo . This ollows om he highly inno a i e business
model applied by he company, including mainly he use o an app op ia e digi al
pla o m o associa ing se ice p o ide s wi h consume s.86
Such inno a i e model o ope a ion is imi a ed by many o he en e p ises, no
only hose ope a ing on he ma ke o passenge anspo , o example he Ai bnb
pla o m on he eal p ope y ma ke ). This way he phenomenon o “ube isa ion”
akes place, whose essence is ha a ious companies and pla o ms managed by
hem a e no se ice p o ide s bu only deli e an app which allows o con ac ing
business people wi h hei cus ome s. So, in he p ocess o gene a ing alue, wha
is mos ly used a e esou ces con olled by use s o he pla o ms. Wha is impo -
an , such a model leads o p ice educ ions because in e media ies a e elimina ed
(Ube does no coope a e wi h axi co po a ions). Fu he mo e, he model allows
o being ac i e in many di e en a eas o ac i i y, also wi h ega d o he go e n-
men sec o . Fo se e al yea s, Ube has made a ailable o he au ho i ies o Bos on
company da a abou ou es idden by cus ome s o he pla o m, which con ib-
u es o, among o he hings, mo e e ec i e public anspo managemen (planning
ou es). In u n, San F ancisco uses da a ecei ed om he Ai bnb pla o m abou
he equency and loca ion o accommoda ion whe e cus ome s o he pla o m
s ay. This helps, among o he hings, in he expansion o he ho el in as uc u e.87
Many s udies ha e shown ha inno a i eness is one o he mos impo an ac-
o s o achie ing compe i i e ad an age. Thus, o ins ance, acco ding o analyses
ca ied ou in 2005 by he Economis In elligence Uni agency, mo e han hal o
he ou housand su eyed manage s hough ha implemen ing inno a ions is
mo e impo an han launching new p oduc s o se ices o achie e a compe i i e
ad an age in he ma ke .88 Then, based on s udies conduc ed in 2014 on a g oup o
98 Inno a i e Changes o Business Models
No es
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2 B. Glinkowska, “Modelowanie w p ocesach usp awniania o ganizacji – uwagi
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3 Z. Ma yniak, Modele me od s osowanych w badaniach o ganiza o skich, Wyższa
Szkoła Ekonomiczna, K aków 1973, p. 22.
4 M. Sza ucki, “Modelowanie w ozwiązywaniu p oblemów za ządzania,” [in:] J. Czekaj,
M. Lisiński, eds., Rozwój koncepcji i me od za ządzania, Fundacja Uniwe sy e u Eko-
nomicznego w K akowie, K aków 2011, pp. 268–269.
5 E. Fiel , “Concep ualising Business Models: De ini ions, F amewo ks and Classi ica-
ions,” Jou nal o Business Models 2013, ol. 1, no. 1, p. 87.
6 J. Bis, “Innowacyjny model biznesowy – sposób na zwiększenie p zewagi konku en-
cyjnej,” P zedsiębio czość i Za ządzanie 2013, ol. 13, p. 55.
7 Ibid., p. 54.
8 M. Kowalczuk, O. Kosch, D. Mucha, “Modele biznesu w eo ii za ządzania,” Secu i y,
Economy & Law 2017, no. 2, p. 63.
9 T. Doligalski, Modele biznesu w In e necie. Teo ia i s udia p zypadków, PWN, Wa saw
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10 A. Jabłoński, Modele biznesu w sek o ach pojawiających się i schyłkowych. Two zenie
p zewagi konku encyjnej p zedsiębio s wa opa ej na jakości i k y e iach ekologic-
znych, Wydawnic wo Wyższej Szkoły Biznesu w Dąb owie Gó niczej, Dąb owa Gó -
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11 B. Nogalski, “Rozważania o modelach biznesowych p zedsiębio s w jako ciekawym
poznawczo kie unku badań p oblema yki za ządzania s a egicznego,” [in:] R. K upski,
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12 K. Obłój, Two zywo sz ucznych s a egii, PWE, Wa saw 2002, pp. 98–100.
13 A. Os e walde , Y. Pigneu , C.L. Tucci, “Cla i ying Business Models: O igins, P esen
and Fu u e o he Concep ,” Communica ions o he Associa ion o In o ma ion Sys‑
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14 A. A uah, C. Tucci, In e ne Business Models and S a egies: Tex and Cases.
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15 A.A. Thompson, A.J. S ickland, S a egic Managemen : Concep s and Cases,
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16 E. Fiel , op. ci ., p. 92.
17 M. Mo is, M. Schindehu e, J. Allen, “The En ep eneu ’s Business Model: Towa d a
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19 S.M. Sha e , H.J. Smi h, J.C. Linde , “The Powe o Resea ch Models,” Business Ho i‑
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20 A. Os e walde , Y. Pigneu , Business Model Gene a ion: A Handbook o Visiona ‑
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21 B. Bek‑Gaik, “Model biznesu w sp awozdawczości o ganizacji – p zegląd badań,” S u‑
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22 J. D zewiecki, A. Równicka, “Model biznesu jako na zędzie planowania i opisu p ojek u
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23 A. Os e walde , Y. Pigneu , C. Tucci, op. ci ., p. 18.
24 M. Pie ścieniak, “The Business Model Can as – na zędzie za ządzania dla s a ‑upów,”
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Inno a i e Changes o Business Models 99
25 J. Mag e a, Wha  Managemen  Is: How I  Wo ks and Why I ’s E e yone’s Business,
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26 J. Siko a, A. Uziębło, “Innowacja w p zedsiębio s wie – p óba zde iniowania,”
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27 T. Nicholas, “Why Schumpe e Was Righ : Inno a ion, Ma ke Powe , and C ea i e De-
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28 M. Ścigała, “Innowacyjność jako cecha o ganizacji – sys ema yzacja i koncep ual-
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29 J.A. Schumpe e , Theo y o  Economic De elopmen : An Inqui y in o P o i s, Capi al,
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30 P. Mielca ek, “Innowacje a ksz ał owanie p zewagi konku encyjnej p zedsiębio s wa,”
[in:] M. Sławińska, ed., Gospoda ka,  echnologia, za ządzanie, Wydawnic wo Uniwe -
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31 C. F eeman, The Economic o Indus ial Inno a ion, Pin e , London 1982, p. 7.
32 M. Ha e , De e minan y  s a egii  nowego  p oduk u  polskich  p zedsiębio s w
p zemysłowych, Wydawnic wo UMK, To uń 1998, p. 27.
33 M.C. Schippe s, M.A. Wes , J.F. Dawson, “Team Re lexi i y and Inno a ion: The Mod-
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34 M.E. Po e , On Compe i ion. Upda ed and Expaned Edi ion. Ha a d Business School
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35 W. Janasz, K. Kozioł, De e minan y działalności innowacyjnej p zedsiębio s w, PWE,
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36 A. Olejniczuk‑Me a, “Od innowacyjności konsumen ów do innowacyjnej gospoda ki,”
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37 E. S awasz, “P zedsiębio s wo innowacyjne,” [in:] K.B. Ma usiak, ed., Innowacje I
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38 Oslo Manual. P oposed Guidelines o Collec ing and In e p e ing Technological In‑
no a ion Da a, OECD, Pa is 2005, p. 11.
39 A. Sosnowska, S. Łobejko, A. Kłopo ek, Za ządzanie  i mą innowacyjną, Wydawnic wo
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40 L. Białoń, “Fi ma innowacyjna,” [in:] Białoń, L., ed., Za ządzanie  działalnością
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41 P.M. Senge, The Fi h Discipline. The A & P ac ice o he Lea ning O ganisa ion,
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42 K. Kudelska, “O ganizacja ucząca się w świe le współczesnych koncepcji za ządzania,”
Wa mińsko‑Mazu ski Kwa alnik Naukowy. Nauki Społeczne 2013, no. 3, pp. 23–24.
43 Y.Y. Yusu , M. Sa hadi, A. Gunaseka an, “Agile Manu ac u ing: The D i e s, Concep s and
A ibu es,” In e na ional Jou nal o P oduc ion Economics 1999, ol. 62, no. 1–2, p. 39.
44 U. Słupska, “P oces k eowania o ganizacji wi ualnej we współczesnym świecie bi-
znesu,” Roczniki  Ekonomiczne  Kujawsko‑Pomo skiej  Szkoły  Wyższej  w  Bydgoszczy
2016, no. 9, pp. 142–143.
45 A. Sosnowska, S. Łobejko, A. Kłopo ek, op. ci ., p. 11.
46 L. Białoń, op. ci ., pp. 172–173.
47 Działalność innowacyjna, h ps://s a .go .pl/me ain o macje/slownik‑pojec/pojecia‑
s osowane‑w‑s a ys yce‑publicznej/759,pojecie.h ml [accessed 15 Janua y 2020]. The
de ini ion o inno a i e ac i i y p o ided by S a is ics Poland is based on he app oach
p oposed by he OECD, see: Oslo Manual…, op. ci ., p. 10.
48 K. Kozioł‑Nadolna, “Modele za ządzania innowacjami w XXI wieku,” [in:] B. Mikuła,
ed., His o ia i pows anie nauk o za ządzaniu, Wydawnic wo Uniwe sy e u Ekonomicz-
nego w K akowie, K aków 2012, pp. 297–298.
49 W.H. Chesb ough, Open Inno a ion. The New Impe a i e  o  C ea ing and P o i ing
om Technology, Ha a d Business School P ess, Bos on, MA 2003, pp. 43–52.
100 Inno a i e Changes o Business Models
50 K. Kozioł‑Nadolna, op. ci ., p. 300.
51 A. Busłowska, “T iple Helix Model – Possibili ies o Sus ainable De elopmen ,” Roc‑
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pp. 45–46.
52 M. Ponia owska‑Jasch, “Biznes cy owy – wyzwania wobec s a egii in e nacjonali-
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53 C. Zo , R. Ami , L. Massa, “The Business Model: Recen De elopmen s and Fu u e
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54 M. Cigaina, U.V. Riss, Digi al Business Modeling. A S uc u al App oach Towa d Digi al
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55 B. Ocicka, “Cy owaI)ewolucja w za ządzaniu łańcuchem dos aw,” S udia Ekonomic‑
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56 E. B ousseau, T. Pena d, op. ci ., pp. 83–86.
57 C.M. Olszak, “S a egia cy owa współczesnej o ganizacji,” S udia Ekonomiczne. Zeszy y
Naukowe Uniwe sy e u Ekonomicznego w Ka owicach 2015, no. 232, pp. 164–165.
58 M.H. Ismail, M. Kha e , M. Zaki, Digi al Business T ans o ma ion and S a egy: Wha
Do We Know So Fa ?, Uni e si y o Camb idge, Camb idge 2017, p. 15; A. Bha adwaj,
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Gene a ion o Insigh s ”, MIS Qua e ly 2013, ol. 37, no. 2, p. 472.
59 C. Tä nell, Implemen ing Digi al Business S a egies. A S udy o he Impac and Appli‑
ca ion in he Medical Technology Indus y, KTH Royal Ins i u e o Technology School
o Indus ial Enginee ing and Managemen , S ockholm 2018, p. 8.
60 S. Łobejko, op. ci ., p. 645.
61 C.M. Olszak, op. ci ., pp. 169–170.
62 M. Ka das, “PojęIia i ypy modeli biznesu,” [in:] K. Klincewicz, ed., Za ządzanie,
o ganizIcja i o ganizowanie, Wydawnic wo Naukowe Wydziału Za ządzania Uniwe -
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63 C.M. Olszak, op. ci ., pp. 168–169.
64 C. Zo , R. Ami , L. Massa, op. ci ., p. 1026.
65 W. Rudny, “Modele biznesowe a p oces wo zenia wa ości w gospoda ce cy owej,”
Za ządIanie i Finanse 2015, no. 1, p. 140.
66 E. Rousseau, T. Pena d, op. ci ., p. 83.
67 M. Filiciak, T eści cy owe. P zemiany modeli bizneIowych i  elacji między p oduIen‑
ami i konsumen ami, MGG Con e ences, Wa saw 2012, pp. 38–40.
68 J. Pie iegud, op. ci ., p. 18.
69 M. Such‑Py giel, “Nowe modele biznesu w dobie ans o macji cy owej,” [in:] M.
Si ek, M. Such‑Py giel, eds., SIołeczne i ekonomiczne aspek y za ządzania w o ganizac‑
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70 E. B ousseau, T. Pena d, op. ci ., pp. 86–90.
71 W. Szp inge , “Innowacyjne modele e‑biznesowe – pe spek ywy ozwojowe,” P ob‑
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72 D.J. Teece, G. Linden, “Business Models, Value Cap u e, and he Digi al En e p ise,”
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73 U.S. Foe s e ‑Me z, K. Ma qua d , N. Golowko, A. Kompalla, C. Hell, op. ci ., pp. 6–7.
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75 A.S. Hosseini, S. Sol ani, M. Mehdizadeh, “Compe i i e Ad an age and I s Impac on
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76 K. Beye , “Kapi ał in elek ualny jako pods awa p zewagi konku encyjnej p zedsiębio s w,”
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Inno a i e Changes o Business Models 101
77 S. Łobejko, op. ci ., p. 645.
78 C. Sigalas, “Compe i i e Ad an age: The Known Unknown Concep ,” Managemen
Decision 2015, ol. 53, no. 9, p. 2007.
79 S. Łobejko, op. ci ., p. 644.
80 A. A uah, C.L. Tucci, op. ci ., p. 10.
81 H. Chesb ough, “Business Model Inno a ion: Oppo uni ies and Ba ie s,” Long
Range Planning 2010, ol. 43, no. 2–3, p. 355.
82 N.M.P. Bocken, S.W. Sho , P. Rana, S. E ans, “A Li e a u e and P ac ice Re iew
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83 W. Szp inge , op. ci ., p. 68.
84 J. Bis, op. ci ., p. 58.
85 A. Szcześniak, “Innowacyjne modele biznesowe,” [in:] M. Bąk, P. Kulawczuk, A.
Szcześniak, eds., Modele  biznesowe  p zedsiębio s w  wo zonych  na  bazie  szkół
wyższych, Fundacja Ins y u Badań nad Demok acją i P zedsiębio s wem P ywa nym,
Wa saw 2011, pp. 28–29.
86 Ł. K yśkiewicz, Innowacje  –  zmieniają  eguły.  S udium  p zypadku  Ube a, h p://
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88 D. Gajda, “Rola innowacji w modelach biznesu,” S udia Ekonomiczne. Zeszy y Nau‑
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89 M.K. Gąsowska, “Rola innowacji w p ocesie za ządzania p zedsiębio s wem w
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p. 519.
90 A. Szcześniak, op. ci ., pp. 34–35.
91 S. Łobejko, op. ci ., p. 644.
92 T. Koch, J. Windspe ge , “Seeing Th ough he Ne wo k: Compe i i e Ad an age in he
Digi al Economy,” Jou nal o O ganisa ion Design 2017, ol. 6, no. 6, pp. 1, 23.
93 D. Tilson, K. Lyy inen, C. Sø ensen, “Digi al In as uc u es: The Missing IS Resea ch
Agenda,” In o ma ion Sys ems Resea ch 2010, ol. 21, no. 4, p. 749.
94 J. Papińska‑Kacpe ek, K. Polańska, “Analiza zaawansowania ealizacji idei Open Go -
e nmen Da a w wyb anych k ajach,” Zeszy y Naukowe Uniwe sy e u Szczecińskiego.
S udia In o ma ica 2015, no. 37, p. 104.
95 M. Jabłoński, “Open Da a Business Model: innowacyjne aspek y p ojek owania mod-
eli biznesu,” S udia i P ace Wydziału Nauk Ekonomicznych i Za ządzania Uniwe ‑
sy e u Szczecińskiego 2018, no. 2, p. 45.
96 F.W. Donke , “Funding Open Da a,” [in:] B. an Ole en, G. Vancauwenbe ghe,
J. C omp oe s, eds., Open Da a Exposed, Sp inge , Be lin 2018, pp. 58–59; S. Tu ki,
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97 P. Munoz, B. Cohen, “A Compass o Na iga ing Sha ing Economy Business Mod-
els,” Cali o nia Managemen Re iew 2018, ol. 61, no. 1, p. 129.
98 Ibid., pp. 129–130.
99 E. Okoń‑Ho odyńska, “W poszukiwaniu modelu biznesowego dla echnologiczno‑
społecznej innowacji: p zypadek SyNa ,” P zedsiębio czość i Za ządzanie 2013, no.
13, pp. 12–19.
100 A. Jabłoński, “Twó czy model biznesu w koncepcji gospoda ki sieciowej,” S udia i
P ace Kolegium Za ządzania i Finansów Szkoły Głównej Handlowej w Wa szawie
2018, no. 162, pp. 175–179.
101 A. Joyce, R.L. Paquin, op. ci ., pp. 1476–1483.
DOI: 10.4324/9781003473022-5
4.1 Resea ch Me hodology
In su eys conduc ed o his monog aph, h ee esea ch me hods ha e been used.
The i s o hese, o con en analysis o he li e a u e on he subjec ma e , was
pe o med du ing p elimina y s udies as well as a emp s o con i m se e al e-
sea ch hypo heses. The i s me hod in ol ed analysis o publica ions abou he
concep o echnological de e minism, assigning a c i ical ole o echnical and
echnological issues and ela ed ans o ma ions in shaping he mode n socie y and
he economy as well as showing he impac o digi al echnology pla o ms (DTPs)
on companies’ business ac i i ies.
The second me hod is CATI o compu e ‑assis ed elephone in e iews. I is a
modi ica ion o he classic me hod o quan i a i e esea ch – di ec s anda dised
in e iews. S anda dised s uc u ed in e iews o igina e om he neo‑posi i is ic
esea ch pa adigm, al hough he in e p e a i e pa adigm and he c i ical pos ‑
mode nis ic pa adigm also con ibu ed o hei de elopmen . In his esea ch pa a-
digm, known as quan i a i e, he aim is o disco e he u h abou he wo ld using
me hods which a e sys ema ic, s anda dised, based on ac s, syn hesising, non‑
subjec i e and cumula i e.1 The o igin o his es ablished esea ch me hod can be
aced back o he su eys conduc ed by A hu Bowley and William Bene ‑Hu s
in G ea B i ain in 1912 o ge o know he li ing condi ions o he wo king class in
he owns o S anley and Reading. Howe e , he mos impo an con ibu ion o he
de elopmen o he me hod is hough o ha e been made by Geo ge Gallup, who
in 1940, du ing he popula ion census, conduc ed su eys on a i e‑pe cen sample
o Ame ican popula ion.2
In con as o he classic s anda dised in e iews, compu e ‑assis ed elephone
in e iews ha e many me hodological cha ac e is ics which make hem pa icu-
la ly use ul in his esea ch p ojec . Fi s , CATI is a echnique s anda dised o a
e y high deg ee and making i possible o en e only p e‑de ined da a wi h e-
ga d o hei o m and con en . Second, elephone su eys allow o ongoing su-
pe ision o in e iewe s who collec da a and con inuous moni o ing o sample
size and esponden s’ answe s. Thi d, he CATI echnique ensu es he oppo u-
ni y o make su eys in he sec o o en e p ises which a e ep esen a i e because
o he a ailabili y o he en i e sampling ame, elimina ion o he clus e ing o
4 Findings o Empi ical Resea ch
This chap e has been made a ailable unde a CC‑BY‑NC‑ND license.
Findings o Empi ical Resea ch 103
en i ies a ound loca ions geog aphically close o each o he and because o possible
(as he da abase was in elec onic o m) sampling p ocedu es. Fu he mo e, CATI
su eys may be combined wi h online su eys as well as wi h quali a i e ech-
niques, including p ojec ion es s. CATI is a echnique which equi es lowe inan-
cial and o ganisa ional expendi u es han he classic s uc u ed F2F ( ace o ace)
in e iew. The CATI echnique makes i possible o modi y he esea ch ools e en
a e he ield esea ch phase has s a ed. Ques ions, o e en blocks o ques ions,
may be hen added o modi ied. The mos impo an ad an age and a he same
ime a desc ip ion o his esea ch me hod is he ac ha on he basis o a co ‑
ec ly selec ed sample, sa is ying app op ia e equi emen s, i is possible o
gene alise he indings o he popula ion.
The quan i a i e da a collec ed du ing compu e ‑assis ed elephone in e iews
(CATI) we e subjec ed o quan i a i e analysis in acco dance wi h he classic pa a-
digm o such su eys. A abula analysis was ca ied ou , aking in o accoun bi-
a ia e ables and hen induc i e es s o in e ‑g oup di e ences we e used.
The su ey using CATI was conduc ed on 18–28 Feb ua y 2019. S anda dised
s uc u ed in e iews included ques ions in s ic ly de ined o de and unchangeable
wo ding, gene ally closed (see Appendix 1). In he su ey, a mode n e sion o he
me hod p esen ed abo e was used. The ace‑ o‑ ace con e sa ion o in e iewe
and esponden was eplaced by a elephone in e iew, and he adi ional p in ed
ques ionnai e – by a compu e .
The sample was selec ed a andom. The in e iews we e conduc ed wi h ep-
esen a i es o manage ial s a ha ing knowledge on he ope a ion o DTPs and
how hey a e used by he company. The sampling ame in he su ey was a g oup
o bene icia ies o he Inno a i e Economy Ope a ional P og amme pe o med by
he Polish Agency o En e p ise De elopmen (PARP), who ecei ed co‑ inancing
unde he p og amme o he implemen a ion and de elopmen o DTPs. The o al
numbe o bene icia ies was N=320. To ensu e he possibili y o gene alising he
collec ed indings on he es ed popula ion, a minimum esea ch sample was calcu-
la ed be o e s a ing he su ey.
Calcula ions we e pe o med on he basis o he ollowing o mula:
=



+








α
n
1
4d
u
1
N
,
2
2
whe e:
d – maximum es ima ion e o exp essed as a ac ion, is po en ially con ained
in he ange om 0 o 1. In gene al, es ima ion e o is de e mined a bi a -
ily a accep able le els as accep ed in esea ch and analy ical p ac ice o so-
cial sciences – om 0.03 o 0.1. Fo example, an e o assumed a he le el
o 0.08 means ha we accep ha speci ic dis ibu ion esul s ob ained in he
su ey when es ima ing whe he hey a e ep esen a i e o he popula ion may
con ain an e o up o ±8 pe cen age poin s. The alue o coe icien d assumed
as accep able in he su ey was 5% (a he le el o 0.05);

104 Findings o Empi ical Resea ch
α
u2
– con idence le el o in e al. Commonly accep ed in social sciences a he le el
o 95%. The alue means ha he e is a me ely i e pe cen (100%–95% = 5%)
p obabili y o commi ing he so‑called Type I e o , o ejec ing a esul which
is in ac ue. A a 95% con idence le el, he alue
α
u2
is 1.96;
N – size o ixed popula ion, which in his su ey was equal o he numbe o com-
panies, he e o e i is 320.
Ha ing subs i u ed he abo e alues in he o mula, we ha e ecei ed he minimum
necessa y sample size o n = 122.
Because he su ey was conduc ed on a ixed popula ion, while se ing he mini-
mum sample size, a sample size adjus men ac o should be applied. I is calcu-
la ed by applying he ollowing o mula:
nnN
Nns,
′=
++
whe e:
n′ – unknown alue;
n – o iginally de ined sample size;
N – size o he su eyed popula ion;
s – con idence in e al is exp essed by he o mula,
s
p1 p
n
()
=− wi h p in he
con idence in e al se a he mos disad an ageous le el, he e o e sa e o he
esea che , o 0.5 (i is assumed ha he su eyed popula ion is, as a as pos-
sible, non‑homogeneous, o di e si ied).
A e subs i u ing alues in he o mula, we ge adjus ed sample size equal o
88. To ensu e he possibili y o conduc ing analyses o collec ed da a and aking
ad an age o a ious s a is ical es s, i was decided o inc ease he ealised sample
size o N = 120 ( equi emen s o pa ame ic and non‑pa ame ic es s assume he
minimum size a he le el o 120). A andomisa ion algo i hm embedded in he
so wa e o elephone su eys (algo i hms embedded in he so wa e o quan i a-
i e su eys use he so‑called andom numbe gene a o s, whose ask is o ensu e
he same p obabili y o d awing each o he eco ds om he sampling ame; in
his su ey, his means ha each o he 320 bene icia ies o he p og amme had
equal chances o being included in he sample) ensu ed ha each eco d in he
da abase was equally likely o be ound in he sample. While conduc ing he
su ey, each o he companies we e con ac ed on he elephone. The in e iews
wi h bene icia ies we e ca ied ou by a eam o quali ied in e iewe s, ained on
he subjec o he su ey. Thei ask was o each he igh pe son in a company
who would ha e knowledge on he ope a ion and u ilisa ion o DTPs. Da a col-
lec ion and in e iews we e s ic ly supe ised ad hoc and pos hoc, in acco d-
ance wi h he equi emen s o he In e iewe s’ Wo k Quali y P og amme, which
gua an ees high quali y o ob ained esul s. 120 in e iews we e conduc ed, 49
Findings o Empi ical Resea ch 105
companies e used o pa icipa e in he su ey, wo o hem decla ed ha hey had no
implemen ed any pla o ms and wi h he emaining ones i was impossible o ca y
ou in e iews on he a anged da es. A company could be included in he sample
i i sa is ied one o he ollowing o c i e ia:
• decla ed use o DTPs by he company;
• planning o implemen DTPs in he company in he nea u u e.
The in e iewe s conduc ed in e iews wi h ep esen a i es o manage ial s a
ha ing knowledge on he ope a ion and use o DTPs in he company. The abula
da a can be ound in Appendix 2.
The hi d esea ch me hod is eg ession analysis. This analysis is o making a
quan i a i e assessmen o quali a i e da a, which is based on assigning speci ic
alues o ce ain ca ego ies. Wi hin he me hod, op imal scaling was used in he
o m o ca ego ical eg ession (CATREG), o eg ession analysis o quali a i e
a iables, o p edic alues o ce ain a iables. Analy ical echnique made is possi-
ble o disclose co ela ion coe icien s o assessmen s o he impac o DTPs on he
company’s ope a ion. Op imal scaling belongs o he amily o eg ession me hods.
I is a me hod in ol ing p edic ion o he alue o a selec ed a iable on he basis o
alues adop ed by o he a iables, also selec ed by he esea che . Wha is impo an
is he ac ha op imal scaling makes i possible o include in analyses a iables
a each measu emen le el: nominal, o dinal, in e al and a io. This is a de ini e
ad an age o he me hod, which makes i impossible o include in analyses nominal
a iables (because o ha , we canno ge o know wha ole hey play). This me hod
may be ega ded as he “ i s choice” in social sciences because a iables a e gene -
ally measu ed he e a he quali a i e le el. The aim o using he me hod is o quan-
i y co ela ions be ween many independen a iables and one dependen a iable.
I is “ eg ession o quali a i e a iables,” which mainly in ol es es ing o e all
e ec o a iables (in e ac ion means “ he p oduc ” o all a iables). The concep
o op imal scaling is de i ed om se e al sou ces – co espondence analysis3 and
mul idimensional scaling (MDS)4 – and i is ega ded as he successo o hese wo
me hods. I is, howe e , mo e co ec and mo e s a is ically igo ous.5
One o he main objec i es o his monog aph is o cons uc a model o DTPs.
Acco dingly, he ele an p ocedu e should be discussed he e. Cons uc ing a
model o a phenomenon in ol es some kind o ma hema isa ion o hypo heses (in
he o m o an app op ia e equa ion o a sys em o equa ions), he e o e p esen ing
hem in a pa ame ised manne in he so‑called “s a is ical space.” Such a model
p esen s a simpli ied bu basic and mos impo an connec ions be ween s udied
phenomena. Fo his pu pose, ools o induc i e s a is ics a e used, mos o en e-
g ession models.
This model conce ns measu emen o a i udes o DTPs in companies. The
concep o “a i ude” is deeply oo ed in social sciences, in pa icula in soci-
ology, bu i is also widely used in economy.6 Scien is s ag ee ha an a i ude
has a h ee‑pa s uc u e: a ec i e (wha is el ), cogni i e (wha is known) and
106 Findings o Empi ical Resea ch
beha iou al (wha is done).7 The concep o a i ude se ed o o mula e he
ques ion indica ing an independen a iable:
Ques ion 13. To wha  ex en  do digi al  echnology pla o ms a ec  an in‑
c ease in quali y and in ensi y o ela ions es ablished by he company in
which you pe o m you p o essional du ies wi h any s akeholde s, including
mainly supplie s, business pa ne s, dis ibu o s o  cus ome s?
The ques ion made i possible o measu e a i udes o he phenomenon o DTPs.
The e a e ollowing elemen s he e: e alua i e elemen s e e ing o knowledge
and elemen s e e ing o he app aisal o he phenomenon (“inc ease in he quali y
and in ensi y”). Wha is o key impo ance is co ela ion o he gene al assess-
men o he impac o DTPs on he quali y and in ensi y o he company’s ope a-
ion wi h he emaining e alua i e, cogni i e elemen s (ques ions 5 and 12 – abou
a ec i e elemen s and ques ion 9 – abou a ec i e and cogni i e elemen s) and
beha iou al ones (ques ions: 1, 4, 8, 10, 11, 14). The impac o socio‑demog aphic
a iables conce ning he company was also s udied (ques ions 22 and 23) as well
as he p obable impac o he so‑called la en a iables conce ning he e y e-
sponden (ques ions 16, 17, 18, 19, 20). Each indica o may be also classi ied om
ano he impo an pe spec i e – aspec s o he company’s ope a ion (a lis o a i-
ables aken in o accoun is p esen ed in Table 4.1). I was assumed ha a company
may be ans o med by DTPs in he ollowing dimensions: human (e alua ion o
he phenomenon by people, he ex en o which pla o ms a e used, expec a ions,
e c.), cybe secu i y (new IT challenges ela ed o ha dwa e and so wa e), eco‑
nomic (connec ed wi h he calcula ion o ac ual and po en ial p o i s and losses)
and social (changes in he s uc u e o he company and in he manne , ype and
in ensi eness o i s ela ionships wi h he en i onmen ).
Using he abo e a iables, a model was buil , indica ing which a iables and
how s ongly a ec he independen a iable. As men ioned abo e, CATREG op-
imal scaling was used o he analysis. Such scaling is a echnique which en-
su es mul idimensional da a explo a ion: he accep able numbe o p edic o s is
wo hund ed, al hough only one independen a iable may be p edic ed. I is also
jus i ied, howe e , o limi he numbe o a iables. In ac , each a iable should
be assigned o a leas en, and ideally wen y, uni s o analysis; o he wise, we may
expe ience ins abili y o eg ession line. This means ha in his analysis, whe e he
se is N = 121, a mos wel e independen a iables may be used, and op imally,
no mo e han six. This is highly impo an in he con ex o he selec ed abo e
(Table 4.1) numbe o six een a iables. I means ha a leas ou o hem should
be elimina ed a p io i. The a iables selec ed o elimina ion we e hose which
in a ious sys ems o a iables, es ed many imes, showed he lowes in e ac ion
wi h o he independen a iables and he dependen a iable.
A his poin , ways o in e p e ing he eg ession model o quali a i e a iables
should be discussed. In e p e a ions a e simila o an o dina y eg ession model,8
al hough i has mo e indica o s and hey a e mo e e ined.
Findings o Empi ical Resea ch 107
Table 4.1 Classi ica ion o indica o s o en ep eneu s’ a i udes o he phenomenon o digi-
al echnology pla o ms
In e iew ques ion Dimension o
he company’s
ope a ion
Commen s
Ques ion 1. Does you company use digi al
echnology pla o ms, which a e ools ha
allow o connec ing business pa ne s
and p o ide oppo uni ies o in ensi ying
con ac s and pe o ming ansac ions
be ween hem?
Human ac o Va iable measu emen
le el: o dinal
Ques ion 4. Please s a e which kind o
digi al echnology pla o ms is used
o will be used (i he e a e plans o
implemen a ion) in you company? (please
selec all possible esponses)
S uc u al
ac o
Va iable measu emen le el:
nominal (mul i‑choice
ques ion), con e ed in o
a io a iable – coun ing
he numbe o selec ions
Ques ion 5. Please s a e wha a i ude is
aken by he pe sonnel in you company
abou he implemen a ion and use o
digi al echnology pla o ms?
Human ac o Va iable measu emen
le el: o dinal
Ques ion 8. Please s a e whe he in
connec ion wi h he implemen a ion
o digi al echnology pla o ms in he
company in which you pe o m you
p o essional du ies any o he ollowing
ad e se cybe secu i y e en s and h ea s
ha e occu ed di ec ly as a esul o using
hese pla o ms?
Cybe secu i y
ac o
Va iable measu emen le el:
nominal (mul i‑choice
ques ion), con e ed in o
a io a iable – coun ing
he numbe o selec ions
Ques ion 10. In which a eas o you
company’s ope a ion digi al echnology
pla o ms a e o will be used (i he e a e
plans o hei implemen a ion)? (please
selec all possible esponses)
S uc u al
ac o
Va iable measu emen le el:
nominal (mul i‑choice
ques ion), con e ed in o
a io a iable – coun ing
he numbe o selec ions
Ques ion 11. Please s a e wha basic bene i s
a e gene a ed due o he use o digi al
echnology pla o ms in you company?
Economic
ac o
Va iable measu emen
le el: nominal (no
subjec o, e.g. ac o
analysis)
Ques ion 12. Do you ag ee wi h he
s a emen ha digi al echnology pla o ms
make i possible o c ea e and de elop
inno a i e business models?
S uc u al
ac o
Va iable measu emen
le el: o dinal
Ques ion 14. Has he implemen a ion
o digi al echnology pla o ms in he
company in which you pe o m you
p o essional du ies o ced he company
o in oduce speci ic changes o i s
o ganisa ional s uc u e o will you be
o ced o do so?
S uc u al
ac o
Va iable measu emen
le el: o dinal
Ques ion 22. Please s a e in wha kind o
company in e ms o headcoun size you
pe o m you p o essional du ies?
S uc u al
ac o
Va iable measu emen
le el: in e al
(Con inued)
114 Findings o Empi ical Resea ch
Table 4.5 (Con inued)
Name o he componen
(p edic o )
Be a
coe icien
The numbe
o deg ees o
eedom (d )
FSigni icance Ze o‑o de
co ela ion
Pa ial
co ela ion
Semi‑pa ial
co ela ion
Impo ance Tole ance a e
ans o ma ion
Tole ance be o e
ans o ma ion
Ques ion 19. Please
s a e how long you
ha e been employed
in he company in
which you pe o m
you p o essional
du ies now.
0.235 2 3.527 0.034 0.150 0.290 0.225 0.079 0.917 0.828
Ques ion 4. Please
s a e wha kind o
digi al echnology
pla o ms a e o will
be used (i he e
a e plans o hei
implemen a ion)
in you company
(please selec all
possible esponses).
0.202 1 1.941 0.167 0.130 0.245 0.188 0.059 0.865 0.847
Ques ion 12. Do
you ag ee wi h
he s a emen ha
digi al echnology
pla o ms make
i possible o
c ea e and de elop
inno a i e business
models?
0.209 2 1.675 0.193 0.116 0.265 0.204 0.055 0.955 0.914

Findings o Empi ical Resea ch 115
Ques ion 10. In
which a eas o
you company’s
ope a ion digi al
echnology
pla o ms a e o will
be used (i he e
a e plans o hei
implemen a ion)?
(please selec all
possible esponses)
0.153 1 1.919 0.170 0.135 0.197 0.150 0.046 0.954 0.918
Ques ion 21. Please
s a e you posi ion
in he company in
which you pe o m
you p o essional
du ies now.
0.187 2 3.443 0.036 0.100 0.236 0.181 0.042 0.936 0.828
Ques ion 18. Please
s a e you educa ion
le el.
−0.114 1 0.981 0.325 −0.066 −0.146 −0.110 0.017 0.934 0.931
Sou ce: Au ho ’s own wo k.
116 Findings o Empi ical Resea ch
he indus y in which he en e p ise ope a es and he in ensi eness o ans o ma-
ions in he en e p ise’s in e nal s uc u e ( his is al oge he 47.5%, o nea ly a
hal o he model’s componen s). I should be s essed ha i has been commonly
pe cei ed o many yea s ha he s uc u al ac o is a om being i ele an .
Douglas No h, a Nobel p ize winning economis , main ained ha de elopmen
akes place mo e as a esul o o ganisa ional a he han echnological p og ess.13
In u n, human ac o s, he e o e ac o s s ic ly socio‑psychological and demo-
g aphic ea u es o esponden s, a e o low impo ance (in e ms o explana o y
powe ), and hey a e ep esen ed by such i ems as yea s o employmen , posi ion
and educa ion (13.8%). This is p esen ed in Figu e 4.1.
An al e na i e model was a emp ed o be buil wi h he bo om‑up me hod, o by
adding u he a iables h ough ial and e o . Howe e , i u ned ou o be impossi-
ble o comple e. An a emp was made o base co ela ion by he bo om‑up me hod on
assump ions de i ed om he cogni i e heo y. The majo ac o was sough among
bo h “ha d” elemen s e e ing o econog aphic ea u es o an en e p ise, and “so ,”
e e ing o ea u es o he esponden in hei p o essional ole (educa ion, expe i-
ence and o he socio‑psycho‑demog aphic cha ac e is ics). Selec ed g oups o ac o s
showed mode a ely high alues wi h ega d o F s a is ic, co ela ion and impo ance
bu hey we e s a is ically insigni ican (a high isk o commi ing Type I e o ).
I Is possible o base a model also on syn he ic indica o s – indexes o scales. In
such a case, independen a iables would be syn he ic alues de i ed om wo o
mo e di ec indica o s (in e iew ques ions). A di ec ad an age o his app oach is e-
duc ion o he numbe o independen a iables, which allows o dec easing he dis-
ance be ween he R‑squa ed and adjus ed R‑squa ed coe icien s. As a esul , a model
explaining a g ea e pa o a ia ion o he dependen a iable could be po en ially
Figu e 4.1 Componen s o he op imal scaling model p oduced wi h he op‑down
me hod – isual in e p e a ion aking in o accoun he p opo ional impo ance
o each ac o in he model
Sou ce: Au ho ’s own wo k.
Findings o Empi ical Resea ch 117
gene a ed. An undeniable ad an age o such an app oach is ob aining anspa ency by
in oducing o de liness and s uc u ing ac o s by pu ing hem in o g oups.
Da a we e syn hesised by summing hem up in a simple a bi a y manne and
hen a e aging se s o indica o s. F om he me hodological poin o iew, hese
a e he so‑called e lexi e indica o s, he e o e no ela ed o one ano he due o
a common cause bu in acco dance wi h he esea ch assump ions, classi ied o a
mo e gene al ca ego y. Fi e syn he ic indexes we e dis inguished: cybe secu i y
( ep esen ed by one indica o ), economic (one indica o ), human (eigh pa ial indi-
ca o s), s uc u al ( ou indica o s) and s uc u al‑demog aphic ( wo pa ial indica-
o s). This is p esen ed in Table 4.6.
Table 4.6 Classi ica ion o indica o s o en ep eneu s’ a i udes o he phenomenon o
digi al echnology pla o ms
Index In e iew ques ion Commen s
Cybe secu i y Ques ion 8. Please s a e whe he in
connec ion wi h he implemen a ion
o digi al echnology pla o ms in he
company in which you pe o m you
p o essional du ies any o he ollowing
ad e se cybe secu i y e en s and h ea s
ha e occu ed di ec ly as a esul o
using hese pla o ms?
Va iable measu emen
le el: nominal
(mul i‑choice ques ion),
con e ed in o a io
a iable – coun ing he
numbe o selec ions
Economic Ques ion 11. Please s a e wha basic
bene i s a e gene a ed due o he use
o digi al echnology pla o ms in you
company?
Va iable measu emen
le el: nominal (no
subjec o, e.g. ac o
analysis)
Human Ques ion 1. Does you company use
digi al echnology pla o ms, which a e
ools ha allow o connec ing business
pa ne s and p o ide oppo uni ies o
in ensi ying con ac s and pe o ming
ansac ions be ween hem?
Va iable measu emen
le el: o dinal
Ques ion 5. Please s a e wha a i ude is
aken by he pe sonnel in you company
abou he implemen a ion and use o
digi al echnology pla o ms?
Va iable measu emen
le el: o dinal
Ques ion 16. Please s a e you gende . Va iable measu emen
le el: nominal (no
subjec o, e.g. ac o
analysis)
Ques ion 17. Please s a e you age. Va iable measu emen
le el: in e al
Ques ion 18. Please s a e you educa ion
le el.
Va iable measu emen
le el: in e al
Ques ion 19. Please s a e how long you
ha e been employed in he company in
which you pe o m you p o essional
du ies now.
Va iable measu emen
le el: in e al
(Con inued)
118 Findings o Empi ical Resea ch
The a emp o cons uc a model using ques ion no. 13 as he dependen a i-
able and he indexes desc ibed abo e as independen a iables gene a ed he ol-
lowing esul s, p esen ed in Tables 4.7 and 4.8.
In social sciences, esul s o calcula ions in induc i e s a is ics which show he
alue o coe icien p (p obabili y alue) abo e 0.05 a e ega ded as s a is ically
insigni ican . Some imes, an excep ion is made o he p inciple, quo ing esul s
o es s which ac ually exceeded he alue o 0.05 bu a e no highe han 0.1.
Table 4.6 (Con inued)
Index In e iew ques ion Commen s
Ques ion 20. Please s a e how long has
he company in which you pe o m you
p o essional du ies been ac i e on he
ma ke .
Va iable measu emen
le el: in e al
Ques ion 21. Please s a e you posi ion in
he company in which you pe o m you
p o essional du ies now.
Va iable measu emen
le el: nominal (no
subjec o, e.g. ac o
analysis)
S uc u al Ques ion 4. Please s a e wha kind o
digi al echnology pla o ms a e o
will be used (i he e a e plans o hei
implemen a ion) in you company
(please selec all possible esponses).
Va iable measu emen
le el: nominal
(mul i‑choice ques ion),
con e ed in o a io
a iable – coun ing he
numbe o selec ions
Ques ion 10. In which a eas o you
company’s ope a ion digi al echnology
pla o ms a e o will be used (i he e
a e plans o hei implemen a ion)?
(please selec all possible esponses)
Va iable measu emen
le el: nominal
(mul i‑choice ques ion),
con e ed in o a io
a iable – coun ing he
numbe o selec ions
Ques ion 12. Do you ag ee wi h he
s a emen ha digi al echnology
pla o ms make i possible o c ea e and
de elop inno a i e business models?
Va iable measu emen
le el: o dinal
Ques ion 14. Has he implemen a ion
o digi al echnology pla o ms in he
company in which you pe o m you
p o essional du ies o ced he company
o in oduce speci ic changes o i s
o ganisa ional s uc u e o will you be
o ced o do so?
Va iable measu emen
le el: o dinal
S uc u al (socio‑
demog aphic)
Ques ion 22. Please s a e in wha kind o
company in e ms o headcoun size you
pe o m you p o essional du ies?
Va iable measu emen
le el: in e al
Ques ion 23. Which indus y does you
company ope a e in?
Va iable measu emen
le el: nominal (no
subjec o, e.g. ac o
analysis)
Sou ce: Au ho ’s own wo k.
Findings o Empi ical Resea ch 119
The e is a high isk he e (a he le el o 10%) o commi ing Type I e o , such a
esul should be ne e heless a leas eco ded as a ma ginal no e.
The model based on syn he ic indexes explains o a conside ably lowe ex en
han he model buil as he i s he a ia ion in ques ion 13. The mos ele an
explana o y ac o o e one ou h (25.4%) o he a ia ion o an independen a i-
able is he s uc u al (socio‑demog aphic) ac o , which includes he company’s
size and indus y. This may be a eason o explo ing he issue u he .
Du ing a sys ema ic analysis o a iables, a egula i y was disco e ed, con-
i med abo e and al eady men ioned, a he le el o single indica o s o induc i e
s a is ics using Pea son’s chi‑squa ed es . The esul is p esen ed in Table 4.9.
In a summa y, i should be unde lined ha he hypo hesis o join impac o
cha ac e is ics, e e ed o in he s a is ical li e a u e as in e ac ion, has been e i-
ied. To his end, a eg ession model o quali a i e a iables was buil using he
op‑down me hod. I u ned ou o be sa is ac o y in e ms o ob ained esul s. Con-
s uc ing he model wi h he use o he op‑down me hod, in he i s phase, all he
a iables we e included o i , and hen hose wi h he lowes ole ance le el we e
sys ema ically elimina ed in o de o s a ejec ing, s ep by s ep, a iables wi h
he lowes goodness o i exp essed by F s a is ic. The mos signi ican ac o ,
s ongly connec ed wi h he a i ude o DTPs, u ned ou o be he economic ac-
o , o inancial bene i s om using he pla o ms. The assessmen o DTPs is also
a ec ed by nume ous s uc u al elemen s o he ex e nal and in e nal en i onmen
o he company. A small, hough signi ican ole is played by cha ac e is ics o he
esponden – hei leng h o employmen , posi ion in he company and educa ion.
In addi ion, he model was buil on he basis o a bi a y indexes (Table 4.10). I
u ned ou o be bo de line s a is ically signi ican and was excluded om u he
discussion, bu i was decided ha he di ec ion o esea ch indica ed by i should
Table 4.7 Summa y o gene al coe icien s
o he op imal scaling model p o-
duced wi h he op‑down me hod
Mul iple R 0.361
R‑squa ed 0.131
Adjus ed R‑squa ed 0.052
Sou ce: Au ho ’s own wo k.
Table 4.8 ANOVA a iance analysis o he op imal scaling model p oduced wi h he op‑down
me hod
The sum o
he squa es
The numbe o deg ees
o eedom (d )
Mean
squa e
FSigni icance
Reg ession 15.805 10 1.580 1.653 p ≤ 0.1
Residual 105.195 110 0.956
To al 121.000 120
Sou ce: Au ho ’s own wo k.

120 Findings o Empi ical Resea ch
Table 4.9   S uc u al (socio‑demog aphic) index – chi‑squa ed  es  o  co ela ion signi icance
S uc u al (socio‑
demog aphic)
index
Ques ion 13. To wha ex en do digi al echnology pla o ms a ec an inc ease in quali y and in ensi y o ela ions es ablished by
he company?
To a e y la ge
ex en
To a la ge ex en Nei he o a la ge
no o a small
ex en
To a small ex en To a e y small
ex en
I ha e no opinion To al
N % N % N % N % N % N % N %
0–25 4 30.8 6 46.2 2 15.4 0 0.0 0 0.0 1 7.7 13 100.0
26–50 10 35.7 11 39.3 3 10.7 2 7.1 0 0.0 2 7.1 28 100.0
51–75 15 36.6 16 39.0 5 12.2 0 0.0 5 12.2 0 0.0 41 100.0
76–100 15 38.5 14 35.9 1 2.6 0 0.0 1 2.6 8 20.5 39 100.0
K uskal‑Wallis es o in e ‑g oup compa isons S a is ically insigni ican
Pea son’s chi‑squa e es o associa ions be ween a iables and C amé ’s V
con ingency coe icien
χ² (15, N = 121) = 26.27; p ≤ 0.05, V = 0.269
Sou ce: Au ho ’s own wo k.
Findings o Empi ical Resea ch 121
Table 4.10 Componen s o he op imal scaling model p oduced wi h he op‑down me hod
Name o he
componen
(p edic o )
Be a
coe icien
The
numbe o
deg ees o
eedom
(d )
FSigni icance Ze o‑o de
co ela ion
Pa ial
co ela ion
Semi‑pa ial
co ela ion
Impo ance Tole ance a e
ans o ma ion
Tole ance
be o e
ans o ma ion
Index – s uc u al
(socio‑
demog aphic) ac o
0.261 0.201 1 10.682 0.197   0.274   0.262  0.254 0.547 0.944
Index – s uc u al
ac o
0.147 0.163 3 0.816 0.488   0.140   0.154  0.145 0.157 0.975
Index – human ac o  0.141 0.163 2 0.749 0.475  0.145   0.148   0.139 0.157 0.972
Index – economic
ac o
0.070 0.207 3 0.114 0.952  0.105   0.072   0.067 0.056 0.932
Index – cybe secu i y
ac o
−0.138 0.159 1 0.756 0.386 −0.078 −0.141 −0.133 0.083 0.928
Sou ce: Au ho ’s own wo k.
122 Findings o Empi ical Resea ch
con inue o be explo ed ( ac o s connec ed wi h he en e p ise’s s uc u e, such as
he indus y and he numbe o employees, as co ela i es o a i udes o DTPs).
Fu he esea ch was done wi h he use o c oss ables. Ques ion 13 was jux a-
posed wi h ques ions: P2, P4, P5, P9, P10, P11, P16, P17, P18, P19, P20, P21, P22,
P23. The c oss ( wo‑ a iable) ables we e used o ca y ou analysis and o suppo
induc i e es s o in e ‑g oup di e ences (Tables 4.11–4.14). To ind di e ences
and simila i ies among g oups selec ed du ing concep ual wo k, wo es s we e
used: he K uskal‑Wallis es by anks, also known as non‑pa ame ic a iance
analysis, and he Mann‑Whi ney U es . The i s s a is ical ool was in oduced o
scien i ic p ac ice in he 1950s by William H. K uskal and W. Allen Wallis.14 The
es makes i possible o de e mine whe he in a la ge (k > 2) g oup consis ing o
many elemen s, he e a e s a is ically signi ican di e ences be ween he elemen s.
I he es shows such di e ences, hen he nex es is conduc ed – one in oduced
by Hen y B. Mann and Donald R. Whi ney o compa e pai s o elemen s making
up he g oup.15 The second es allows o s a ing s a is ically signi ican di e ences
be ween elemen s o hei absence. The es s may be applied when he a iables o
be es ed ha e been measu ed a leas a he o dinal le el and also a he in e al
o a io le el.
The esul o he K uskal‑Wallis es is eco ded in he ollowing way:
()
()
[]
[] [] []
χ=
=≤
α
Hx
,N yz;p
2
I is in e p e ed as ollows:
– x is he numbe o deg ees o eedom;
– y is he size o he sample which was es ed;
– z is he alue o chi‑squa ed es ;
– α is he signi icance le el o comple ed K uskal‑Wallis es .
The esul o he Mann‑Whi ney U es is eco ded in he ollowing way:
()
[]
[] []
== ≤α
UN
xy;p
I is in e p e ed as ollows:
– x is he size o he sample which was es ed;
– y is he alue o he Mann‑Whi ney U es ;
– α is he signi icance le el o comple ed es .
In hese es s, simila ly o o he induc i e es s, he ollowing wo s a is ical
hypo heses a e o mula ed: he null hypo hesis (H0), assuming ha he compa ed
g oups a e iden ical, and al e na i e hypo hesis (H1), acco ding o which hey a e
di e en . A es is ound o be s a is ically signi ican i p ≤ 0.05. The ables be-
low p esen he assessmen o changes caused as a esul o using DTPs, aking
in o conside a ion many a iables. Those a iables which had been ound no o
Findings o Empi ical Resea ch 123
Table 4.11 Assessmen o he impac o DTPs . he ype o pla o m used in he company
Ques ion 4. Please s a e
which kind o digi al
echnology pla o ms is used
o  will be used?
Ques ion 13. To wha  ex en  do digi al  echnology pla o ms a ec  an inc ease in quali y and in ensi y o   ela ions
es ablished by  he company?
To a e y
la ge ex en
To a la ge
ex en
Nei he o a
la ge ex en
no o a small
ex en
To a small
ex en
To a e y
small ex en
I ha e no
opinion
To al
N % N % N % N % N % N % N %
Communica ion 37 38.9 36 37.9 9 9.5 2 2.1 3 3.2 8 8.4 95 100.0
In o ma ion 28 32.9 36 42.4 7 8.2 2 2.4 4 4.7 8 9.4 85 100.0
Compa ison ools, o
example o compa ing
p ices o p oduc ea u es
3 25.0 5 41.7 3 25.0 1 8.3 0 0.0 0 0.0 12 100.0
En e ainmen 2 22.2 5 55.6 0 0.0 0 0.0 0 0.0 2 22.2 9 100.0
Online ma ke s 13 27.1 18 37.5 8 16.7 2 4.2 3 6.3 4 8.3 48 100.0
All o he abo e 0 0.0 2 100.0 0 0.0 0 0.0 0 0.0 0 0.0 2 100.0
K uskal‑Wallis es o
in e ‑g oup compa isons
Communica ion pla o ms . deg ee o impac – s a is ically insigni ican
In o ma ion pla o ms . deg ee o impac – s a is ically insigni ican
Compa ison pla o ms, o example o compa ing p ices o p oduc ea u es – s a is ically insigni ican
En e ainmen pla o ms . deg ee o impac – s a is ically insigni ican
Online ma ke s . deg ee o impac – s a is ically insigni ican
All o he abo e . deg ee o impac – s a is ically insigni ican
Pea son’s chi‑squa e es
o associa ions be ween
a iables and C amé ’s V
con ingency coe icien
Communica ion pla o ms . deg ee o impac – s a is ically insigni ican
In o ma ion pla o ms . deg ee o impac – s a is ically insigni ican
Compa ison pla o ms, o example o compa ing p ices o p oduc ea u es – s a is ically insigni ican
En e ainmen pla o ms . deg ee o impac – s a is ically insigni ican
Online ma ke s . deg ee o impac – s a is ically insigni ican
All o he abo e . deg ee o impac – s a is ically insigni ican
Sou ce: Au ho ’s own wo k.
130 Findings o Empi ical Resea ch
Ques ion 4. Please s a e wha kind o digi al echnology pla o ms a e o
will be used (i he e a e plans o hei implemen a ion) in you company
(please selec all possible esponses)
Ques ion 22. Please s a e in wha kind o company in e ms o headcoun
size you pe o m you  p o essional du ies?
A his poin , he esul s which e e s ic ly o hypo heses H1 and H5 will be
p esen ed (in Tables 4.15–4.24). Wi h ega d o hem, co ela ion be ween ques-
ions 2 and 6 should be desc ibed. The ele an da a a e p esen ed in Table 4.15.
The ma ginal dis ibu ions in Table 4.15 show he ollowing di e gence: he
longe a company uses DTPs, he mo e he employees a e willing o pa icipa e in
aining and ac i e in gene a ing new ideas connec ed wi h he use o DTPs. A he
same ime, he ollowing simila i ies a e obse ed: bo h g oups mos o en poin ed
ou he ollowing ac o s: (1) gi ing consen o any changes esul ing om he im-
plemen a ion o DTPs, including changes connec ed wi h he o ganisa ional s uc-
u e (85.4% o hose using pla o ms o h ee yea s o sho e and 85.2% o hose
using he longe ), (2) g ea in ol emen in he pe o mance o asks (75% om he
i s g oup and 85.2% om he second) and (3) being in e es ed in nex in es men s
ega ding he implemen a ion o DTPs (68.8% and 77.8% espec i ely) as e ec s
o a posi i e a i ude o pe o med p ojec s.
In his espec , he e a e no s a is ically signi ican di e ences be ween he ana-
lysed g oups. Bo h ag ee nea ly in 100% wi h he s a emen ha DTPs make i pos-
sible o c ea e and de elop inno a i e business models. I should be no ed ha he
o ce o posi i e con ic ion ha he s a emen is ue is highe o hose companies
which use pla o ms longe (mo e han h ee yea s).
Bo h g oups o he su eyed en e p ises adop he same posi ion abou a high o
e y high impac o using DTPs on inc ease in quali y and in ensi eness o ela-
ions es ablished by he companies. In his case, he e a e no s a is ically signi ican
di e ences be ween he g oups.
The e a e no signi ican di e ences be ween bo h g oups also wi h ega d o he
issue o he necessi y o in oduce changes in he company’s o ganisa ional s uc-
u e as a esul o using DTPs. In bo h g oups, a simila pe cen age o esponden s
decla e ha such changes should ha e been in oduced (60.4% o he esponden s
using pla o ms o h ee yea s o sho e and 53.2% o hose using hem longe ). A
cau ious in e p e a ion o he esul s is ha people using DTPs o mo e han h ee
yea s no longe no ice e y well he al eady implemen ed o po en ial changes in
he o ganisa ional s uc u e.
Bo h g oups make simila decla a ions abou he changes which ha e aken
place as a esul o he in oduc ion o DTPs. The mos equen o hese include
c ea ion o a new job/posi ion(s) o pe sons who will be esponsible o he main-
enance o he pla o ms (51.4% – en e p ises using pla o ms o h ee yea s o
sho e and 63.6% – hose using hem longe han h ee yea s), and ans o ma ions
in he go e nance and manage ial s uc u e (28.6% and 45.5% espec i ely). The
only s a is ically signi ican di e ence is ound in selec ions abou liquida ion o
exis ing jobs. In en e p ises using pla o ms o mo e han h ee yea s, he e a e

Findings o Empi ical Resea ch 131
Table 4.15 Du a ion o using digi al echnology pla o ms . in ol emen o manage ial s a
Ques ion 6. Wha shows he posi i e
a i ude o he pe sonnel o he
implemen a ion and use o digi al
echnology pla o ms in you
company?
Ques ion 2. Please s a e how long digi al echnology
pla o ms ha e been used in he company in which
you pe o m you  p o essional du ies?
Up o h ee yea s Mo e han h ee yea s
N % N %
Ac i e in ol emen in he
pe o mance o asks ela ed o he
implemen a ion and use o digi al
echnology pla o ms
36 75.0 46 85.2
G ea spon aneous willingness o
pa icipa e in aining in his a ea
26 54.2 37 68.5
Ac i e gene a ion o new ideas
connec ed wi h he use o digi al
echnology pla o ms
33 68.8 42 77.8
Gi ing consen o any changes
esul ing om he implemen a ion
o digi al echnology pla o ms,
including changes connec ed wi h
he o ganisa ional s uc u e
41 85.4 46 85.2
Being highly eady o changes
conce ning one’s own p o essional
du ies
37 77.1 43 79.6
Being in e es ed in nex in es men s
ega ding he implemen a ion o
digi al echnology pla o ms
33 68.8 42 77.8
Mann‑Whi ney U es o in e ‑g oup
compa isons
In ol emen in he pe o mance o asks .
du a ion o use – s a is ically insigni ican
Willingness o pa icipa e in aining . du a ion o
use – s a is ically insigni ican
Ac i e gene a ion o new ideas . du a ion o
use – s a is ically insigni ican
Consen o changes . du a ion o
use – s a is ically insigni ican
Readiness o changes o own p o essional du ies
. du a ion o use – s a is ically insigni ican
Fu he in es men s . du a ion o
use – s a is ically insigni ican
Pea son’s chi‑squa e es o
associa ions be ween a iables and
C amé ’s V con ingency coe icien
In ol emen in he pe o mance o asks .
du a ion o use – s a is ically insigni ican
Willingness o pa icipa e in aining . du a ion o
use – s a is ically insigni ican
Ac i e gene a ion o new ideas . du a ion o
use – s a is ically insigni ican
Consen o changes . du a ion o
use – s a is ically insigni ican
Readiness o changes o own p o essional du ies
. du a ion o use – s a is ically insigni ican
Fu he in es men s . du a ion o
use – s a is ically insigni ican
Sou ce: Au ho ’s own wo k.
132 Findings o Empi ical Resea ch
Table 4.17 Du a ion o using digi al echnology pla o ms . imp o emen in he quali y o
he en e p ise’s ela ions
Ques ion 13. To wha ex en do
digi al echnology pla o ms a ec
an inc ease in quali y and in ensi y
o ela ions es ablished by he
company?
Ques ion 2. Please s a e how long digi al echnology
pla o ms ha e been used in he company in which
you pe o m you p o essional du ies?
Up o 3 yea s Mo e han 3 yea s
N % N %
To a e y la ge ex en 21 36.2 23 37.1
To a la ge ex en 22 37.9 24 38.7
Nei he o a la ge ex en no o a
small ex en
5 8.6 6 9.7
To a small ex en 0 0.0 2 3.2
To a e y small ex en 3 5.2 3 4.8
I ha e no opinion abou ha opic 7 12.1 4 6.5
Mann‑Whi ney U es o in e ‑g oup
compa isons
s a is ically insigni ican
Pea son’s chi‑squa e es o
associa ions be ween a iables
and C amé ’s V con ingency
coe icien
s a is ically insigni ican
Sou ce: Au ho ’s own wo k.
Table 4.16 Du a ion o using digi al echnology pla o ms . de elopmen o inno a i e
business models
Ques ion 12. Do you ag ee wi h he
s a emen ha digi al echnology
pla o ms make i possible o c ea e
and de elop inno a i e business
models?
Ques ion 2. Please s a e how long digi al echnology
pla o ms ha e been used in he company in which
you pe o m you p o essional du ies?
Up o h ee yea s Mo e han h ee yea s
N % N %
De ini ely ag ee 25 43.1 37 59.7
Ra he ag ee 29 50.0 16 25.8
Nei he ag ee no disag ee 4 6.9 8 12.9
Ra he disag ee 0 0.0 1 1.6
De ini ely disag ee 0 0.0 0 0.0
Mann‑Whi ney U es o in e ‑g oup
compa isons
S a is ically insigni ican
Pea son’s chi‑squa e es o
associa ions be ween a iables
and C amé ’s V con ingency
coe icien
S a is ically insigni ican
Sou ce: Au ho ’s own wo k.
Findings o Empi ical Resea ch 133
Table 4.18 Du a ion o using digi al echnology pla o ms . necessi y o o ganisa ional
changes
Ques ion 14. Has he
implemen a ion o digi al
echnology pla o ms in he
company in o ced he company o
in oduce speci ic changes  o i s
o ganisa ional s uc u e o will i be
o ced  o do so?
Ques ion 2. Please s a e how long digi al echnology
pla o ms ha e been used in he company in which
you pe o m you  p o essional du ies?
Up o h ee yea s Mo e han h ee yea s
N % N %
De ini ely so 8 13.8 7 11.3
Ra he so 27 46.6 26 41.9
Nei he ag ee no disag ee 13 22.4 7 11.3
Ra he no 9 15.5 17 27.4
De ini ely no 1 1.7 5 8.1
Mann‑Whi ney U es o in e ‑g oup
compa isons
S a is ically insigni ican
Pea son’s chi‑squa e es o
associa ions be ween a iables
and C amé ’s V con ingency
coe icien
S a is ically insigni ican
Sou ce: Au ho ’s own wo k.
Table 4.19 Du a ion o using digi al echnology pla o ms . o ganisa ional changes
Ques ion 15. Wha a e (will be)
he changes in  he company’s
o ganisa ional s uc u e esul ing
om he implemen a ion o digi al
echnology pla o ms?
Ques ion 2. Please s a e how long digi al echnology
pla o ms ha e been used in he company in which
you pe o m you  p o essional du ies?
Up o h ee yea s Mo e han h ee yea s
N % N %
Opening a new b anch o he
en e p ise
0 0.0 0 0.0
Liquida ion o an exis ing b anch o
he en e p ise
0 0.0 1 3.0
Se ing up a new depa men (s) o
he en e p ise
10 28.6 11 33.3
Liquida ion o an exis ing
depa men /exis ing depa men s
o he en e p ise
0 0.0 2 6.1
C ea ion o a new job/posi ion(s) 18 51.4 21 63.6
Liquida ion o an exis ing job/
posi ion(s)
0 0.0 4 12.1
T ans e ing speci ic g oups o
employees o ano he depa men /
o he depa men s o he
en e p ise
1 2.9 4 12.1
T ans o ma ions in he go e nance
and manage ial s uc u e
10 28.6 15 45.5
(Con inued)
134 Findings o Empi ical Resea ch
Table 4.19 (Con inued)
Ques ion 15. Wha a e (will be)
he changes in  he company’s
o ganisa ional s uc u e esul ing
om he implemen a ion o digi al
echnology pla o ms?
Ques ion 2. Please s a e how long digi al echnology
pla o ms ha e been used in he company in which
you pe o m you  p o essional du ies?
Up o h ee yea s Mo e han h ee yea s
N % N %
Mann‑Whi ney U es o in e ‑g oup
compa isons
Opening a new b anch o he en e p ise . du a ion
o use – s a is ically insigni ican
Liquida ion o an exis ing b anch o he en e p ise .
du a ion o use – s a is ically insigni ican
Se ing up a new depa men (s) o he en e p ise .
du a ion o use – s a is ically insigni ican
Liquida ion o an exis ing depa men /exis ing
depa men s o he en e p ise . du a ion o
use – s a is ically insigni ican
C ea ion o a new job/posi ion(s) . du a ion o
use – s a is ically insigni ican
Liquida ion o an exis ing job/posi ion(s) . du a ion
o use – U(N = 68) = 507.5;
p ≤ 0.05
T ans e ing speci ic g oups o employees o ano he
depa men /o he depa men s o he en e p ise .
du a ion o use – s a is ically insigni ican
T ans o ma ions in he go e nance and manage ial
s uc u e . du a ion o use – s a is ically
insigni ican
Pea son’s chi‑squa e es o
associa ions be ween a iables
and C amé ’s V con ingency
coe icien
Opening a new b anch o he en e p ise . du a ion
o use – s a is ically insigni ican
Liquida ion o an exis ing b anch o he en e p ise .
du a ion o use – s a is ically insigni ican
Se ing up a new depa men (s) o he en e p ise .
du a ion o use – s a is ically insigni ican
Liquida ion o an exis ing depa men /exis ing
depa men s o he en e p ise . du a ion o
use – s a is ically insigni ican
C ea ion o a new job/posi ion(s) . du a ion o
use – s a is ically insigni ican
Liquida ion o an exis ing job/posi ion(s) . du a ion
o use – χ² (1, N = 121) = 4.50; p ≤ 0.05, V = 257
T ans e ing speci ic g oups o employees o ano he
depa men /o he depa men s o he en e p ise .
du a ion o use – s a is ically insigni ican
T ans o ma ions in he go e nance and manage ial
s uc u e . du a ion o use – s a is ically
insigni ican
Sou ce: Au ho ’s own wo k.
Findings o Empi ical Resea ch 135
Table 4.20 Company size . bene i s om using he pla o ms
Ques ion 11. Bene i s a e
gene a ed due o he use o
digi al echnology pla o ms in
he company
Company size
Mic o Small Medium La ge
Rank
sum
Rank Rank
sum
Rank Rank
sum
Rank Rank
sum
Rank
G ow h o p o i s 75.9 2 100.0 1 100.0 1 100.0 1
G ow h o compe i i eness 100.0 1 74.8 2 70.9 2 73.6 3
Enla ging he p oduc o e ing 70.7 3 48.9 4 51.5 4 66.7 4
Inc ease in ma ke sha e 41.4 645.8 5 33.5 635.8 6
Inc ease in he le el o
inno a i eness
43.1 5 30.5 9 37.4 5 35.8 6
Inc ease in he numbe o
cus ome s
70.7 3 38.9 613.7 11 14.4 9
Imp o emen o cus ome
se ice and inc eased
consume sa is ac ion le el
44.8 4 36.6 7 17.6 10 8.0 12
Inc ease in he numbe o
ma ke s in which he company
is ac i e
8.6 9 31.3 8 28.6 8 28.9 7
Inc easing he numbe o
business pa ne s, including
hose ope a ing on in a i ual
en i onmen
— — 29.8 10 33.0 7 37.8 5
Op imisa ion o pe o mance o
a ious business p ocesses,
including hose ela ing o
cus ome se ice
12.1 8 74.0 3 63.9 3 87.6 2
De elopmen o digi al supply
chains
— — 16.8 11 12.8 13 3.0 13
Inc ease in he gene al
e ec i eness o he company’s
ope a ions
29.3 7 30.5 9 13.2 12 22.4 8
Inc easing lexibili y o
ope a ions, which shows in he
capabili y o launching new
p oduc s and se ices quickly
8.6 9 15.3 12 7.5 14 11.4 11
Oppo uni y o ge in ol ed
ac i ely in p og ammes
ini ia ed in he i ual space
o expand he ange o goods
and se ices o he da abase o
cus ome s
— — 8.4 13 20.7 9 12.9 10
Sou ce: Au ho ’s own wo k.

136 Findings o Empi ical Resea ch
Table 4.22 Company size . company’s ela ionships wi h he en i onmen
Ques ion 13. To wha ex en do
digi al  echnology pla o ms a ec  an
inc ease in quali y and in ensi y o
ela ions es ablished by  he company?
Company size
Mic o Small Medium La ge
N % N % N % N %
To a e y la ge ex en 4 33.3 10 35.7 15 36.6 15 38.5
To a la ge ex en 5 41.7 11 39.3 16 39.0 14 35.9
Nei he o a la ge ex en no o a small
ex en
2 16.7 3 10.7 5 12.2 1 2.6
To a small ex en 0 0.0 2 7.1 0 0.0 0 0.0
To a e y small ex en 0 0.0 0 0.0 5 12.2 1 2.6
K uskal‑Wallis es o in e ‑g oup
compa isons
S a is ically insigni ican
Pea son’s chi‑squa e es o
associa ions be ween a iables and
C amé ’s V con ingency coe icien
S a is ically insigni ican
Sou ce: Au ho ’s own wo k.
Table 4.21 Company size . c ea ing inno a i e business models
Ques ion 12. Do you ag ee wi h he
s a emen ha digi al echnology
pla o ms make i possible o c ea e
and de elop inno a i e business
models?
Company size
Mic o Small Medium La ge
N % N % N % N %
De ini ely ag ee 10 83.3 18 64.3 15 36.6 19 48.7
Ra he ag ee 1 8.3 5 17.9 24 58.5 15 38.5
Nei he ag ee no disag ee 1 8.3 5 17.9 1 2.4 5 12.8
Ra he disag ee 0 0.0 0 0.0 1 2.4 0 0.0
De ini ely disag ee 0 0.0 0 0.0 0 0.0 0 0.0
K uskal‑Wallis es o in e ‑g oup
compa isons
S a is ically insigni ican
Pea son’s chi‑squa e es o
associa ions be ween a iables and
C amé ’s V con ingency coe icien
S a is ically insigni ican
Sou ce: Au ho ’s own wo k.
Findings o Empi ical Resea ch 137
Table 4.23 Company size . changes in he company’s o ganisa ional s uc u e
Ques ion 14. Has he implemen a ion
o digi al echnology pla o ms in
he company in o ced he company
o in oduce speci ic changes  o i s
o ganisa ional s uc u e o will i be
o ced  o do so?
Company size
Mic o Small Medium La ge
N % N % N % N %
De ini ely so 3 25.0 3 10.7 5 12.2 4 10.3
Ra he so 2 16.7 13 46.4 18 43.9 20 51.3
Nei he ag ee no disag ee 1 8.3 3 10.7 7 17.1 9 23.1
Ra he no 4 33.3 621.4 11 26.8 5 12.8
De ini ely no 2 16.7 3 10.7 0 0.0 1 2.6
K uskal‑Wallis es o in e ‑g oup
compa isons
s a is ically insigni ican
Pea son’s chi‑squa e es o
associa ions be ween a iables and
C amé ’s V con ingency coe icien
s a is ically insigni ican
Sou ce: Au ho ’s own wo k.
Table 4.24 Company size . o ganisa ional changes
Ques ion 15. Wha a e (will be)
he changes in  he company’s
o ganisa ional s uc u e esul ing
om he implemen a ion o
digi al  echnology pla o ms?
Company size
Mic o Small Medium La ge
N % N % N % N %
Opening a new b anch o he
en e p ise
0 0.0 0 0.0 0 0.0 0 0.0
Liquida ion o an exis ing b anch
o he en e p ise
1 20.0 0 0.0 0 0.0 0 0.0
Se ing up a new depa men (s)
o he en e p ise
3 60.0 9 56.3 626.1 3 12.5
Liquida ion o an exis ing
depa men /exis ing
depa men s o he en e p ise
0 0.0 1 6.3 0 0.0 1 4.2
C ea ion o a new job/posi ion(s) 5 100.0 8 50.0 13 56.5 13 54.2
Liquida ion o an exis ing job/
posi ion(s)
1 20.0 1 6.3 0 0.0 2 8.3
T ans e ing speci ic g oups
o employees o ano he
depa men /o he depa men s
o he en e p ise
0 0.0 3 18.8 0 0.0 2 8.3
T ans o ma ions in he
go e nance and manage ial
s uc u e
1 20.0 8 50.0 7 30.4 9 37.5
(Con inued)
138 Findings o Empi ical Resea ch
cases o liquida ing jobs as a esul o he in oduc ion o new solu ions. In he
si ua ion, he e is also a s a is ically signi ican ela ion be ween a iables bu i is
no s ong.
Fo all en e p ises, ega dless o he headcoun le el, he mos impo an bene i s
gene a ed due o he use o digi al pla o ms include g ow h o p o i s and inc ease
in he compe i i eness le el. Fo companies employing up o 49 people, he ac o s
Table 4.24 (Con inued)
Ques ion 15. Wha a e (will be)
he changes in  he company’s
o ganisa ional s uc u e esul ing
om he implemen a ion o
digi al  echnology pla o ms?
Company size
Mic o Small Medium La ge
N % N % N % N %
K uskal‑Wallis es o in e ‑g oup
compa isons
Opening a new b anch o he en e p ise . du a ion o
use – s a is ically insigni ican
Liquida ion o an exis ing b anch o he en e p ise .
du a ion o use – s a is ically insigni ican
Se ing up a new depa men (s) o he en e p ise .
du a ion o use – s a is ically insigni ican
Liquida ion o an exis ing depa men /exis ing
depa men s o he en e p ise . du a ion o
use – s a is ically insigni ican
C ea ion o a new job/posi ion(s) . du a ion o
use – s a is ically insigni ican
Liquida ion o an exis ing job/posi ion(s) . du a ion o
use – s a is ically insigni ican
T ans e ing speci ic g oups o employees o ano he
depa men /o he depa men s o he en e p ise .
du a ion o use – s a is ically insigni ican
T ans o ma ions in he go e nance and manage ial
s uc u e . du a ion o use – s a is ically insigni ican
Pea son’s chi‑squa e es o
associa ions be ween a iables
and C amé ’s V con ingency
coe icien
Opening a new b anch o he en e p ise . du a ion o
use – s a is ically insigni ican
Liquida ion o an exis ing b anch o he en e p ise .
du a ion o use – s a is ically insigni ican
Se ing up a new depa men (s) o he en e p ise .
du a ion o use – s a is ically insigni ican
Liquida ion o an exis ing depa men /exis ing
depa men s o he en e p ise . du a ion o
use – s a is ically insigni ican
C ea ion o a new job/posi ion(s) . du a ion o
use – s a is ically insigni ican
Liquida ion o an exis ing job/posi ion(s) . du a ion o
use – s a is ically insigni ican
T ans e ing speci ic g oups o employees o ano he
depa men /o he depa men s o he en e p ise .
du a ion o use – s a is ically insigni ican
T ans o ma ions in he go e nance and manage ial
s uc u e . du a ion o use – s a is ically insigni ican
Sou ce: Au ho ’s own wo k.
Findings o Empi ical Resea ch 139
o inc easing he numbe o cus ome s, imp o ing cus ome se ice and aising
he cus ome sa is ac ion le el anked highe han in he case o medium‑sized and
la ge companies. In u n, o companies employing o e 250 people, in con as o
he emaining ypes o en e p ises, a highe ank is gi en o inc easing he numbe
o business pa ne s.
Rep esen a i es o all en e p ises, ega dless o he headcoun le el, nea ly
comple ely ag ee wi h he s a emen ha DTPs make i possible o c ea e and de-
elop inno a i e business models.
Fo all he en e p ises, he ypical esponses a e ha using DTPs a ec s “ o a
e y la ge” o “la ge ex en ” an inc ease in quali y and in ensi y o ela ions es ab-
lished by he company wi h o he en i ies ope a ing in he en i onmen . The e a e
no signi ican di e ences in his espec among he analysed g oups.
Fo mos companies, he implemen a ion o DTPs was connec ed wi h he in o-
duc ion o changes in he o ganisa ional s uc u e. Fo en e p ises employing o e
en people, selec ions o changes we e mo e han hal (small – 57.1%, medium‑
sized – 56.1%, la ge – 61.6%). The e a e no signi ican di e ences be ween he
g oups when conside ing his aspec .
The mos equen ly in oduced changes in he companies’ o ganisa ional s uc-
u e should include c ea ion o new jobs, and o hose employing up o 49 people –
opening new depa men s. T ans o ma ions in he go e nance and manage ial
s uc u e we e selec ed by esponden s om companies employing o e en em-
ployees. Howe e , he popula ions o he g oups a e oo small o d aw conclusions
abou signi ican di e ences be ween he g oups.
Summing up his pa o he wo k, i should be s essed ha a model was buil
using he CATREG eg ession model o quali a i e a iables, which made i pos-
sible o e i y he main p oposi ion and esea ch hypo heses H1 and H5. The model
u ned ou o be s a is ically signi ican and explained 21.8% o a ia ion o he de-
penden a iable (P13). The model included nine independen a iables. The mos
signi ican impac ac o s o he ex en o which DTPs a ec an inc ease in quali y
and in ensi y o ela ions es ablished by he company wi h s akeholde s a e:
– he a iable conce ning bene i s gene a ed by using DTPs (P11) – explains
38.6% o he a ia ion o he dependen a iable;
– he indus y in which he company ope a es (P23) – explains 20.8% o he a i-
a ion o he dependen a iable;
– cu en o u u e changes made necessa y by he implemen a ion o DTPs
(P14) – explains 10.7% o he a ia ion o he dependen a iable.
The model was supplemen ed wi h addi ional me iculous analyses. Many weak
bu p omising ails ha e been ound, bu hey will need o be con i med in u he
esea ch. In his espec , i may be only men ioned ha acco ding o ep esen a i es
o he su eyed companies, a co ela i e o he dependen a iable is he con ic ion
abou a mul i ace ed impac o DTPs on a company (P10 . P13).
Fu he mo e, a en ion should be d awn o he ollowing disclosed co‑ a iances
( hey a e no oo high bu egula and s a is ically signi ican ; hey should be