Using Blockchain to Improve Collaborative Business Process Management: Systematic Literature Review

SPECIAL SECTION ON BLOCKCHAIN TECHNOLOGY: PRINCIPLES AND APPLICATIONS
Recei ed June 12, 2020, accep ed July 24, 2020, da e o publica ion Augus 4, 2020, da e o cu en e sion Augus 14, 2020.
Digi al Objec Iden i ie 10.1109/ACCESS.2020.3013911
Using Blockchain o Imp o e Collabo a i e
Business P ocess Managemen : Sys ema ic
Li e a u e Re iew
JULIAN ALBERTO GARCIA-GARCIA 1, NICOLÁS SÁNCHEZ-GÓMEZ 1, DAVID LIZCANO 2,
M. J. ESCALONA1, AND TOMÁS WOJDYŃSKI3
1Escuela Técnica Supe io de Ingenie ía In o má ica, Uni e si y o Se ille, 41012 Se illa, Spain
2School o Compu e Science, Mad id Open Uni e si y, 28400 Mad id, Spain
3School o Banking and Managemen , 30-079 C acow, Poland
Co esponding au ho : Julian Albe o Ga cia-Ga cia ([email p o ec ed])
This esea ch pape was ca ied ou by he i s au ho du ing an in e na ional pos doc o al s ay a School o Compu e Science, Mad id
Open Uni e si y, UDIMA, Mad id, Spain. In addi ion, i is a pleasu e o men ion ha his esea ch is suppo ed by wo p ojec s: POLOLAS
(Explo ando Soluciones Guiadas pa a Sis ema iza el Asegu amien o Temp ano de la Calidad del So wa e) (TIN2016-76956-C3-2-R),
which is unded by Spanish Minis y o Economy and Compe i i eness; and TRoPA (Ea ly Tes ing in Medical Robo ics P ocess
Au oma ion) (CEI-12), which is unded by Andalusian Regional Minis y o Economy, Knowledge, Business and Uni e si y.
ABSTRACT BlockChain Technology (BCT) has appea ed wi h s eng h and p omises an au hen ic
e olu ion on business, managemen , and o ganiza ional s a egies ela ed o u iliza ion o ad anced so wa e
sys ems. In ac , BCT p omo es a decen alized a chi ec u e o p ocess managemen and he collabo a i e
wo k be ween en i ies when hese ones a e wo king oge he in a business p ocess. This pape aims o
know wha p oposals exis o imp o e any s age o business p ocess managemen using BCT because his
echnology could p o ide bene i s in his managemen . Fo his pu pose, his pape p esen s a sys ema ic
li e a u e e iew in a ea o Collabo a i e Business P ocesses (CBP) in BCT domain o iden i y oppo uni ies
and gaps o u he esea ch. This pape concludes he e is a apid and g owing in e es o public bodies,
scien i ic communi y and so wa e indus ies o know oppo uni ies ha BCT o e s o imp o e CBP
managemen in a decen alized manne . Howe e , al hough he opic is in ea ly s ages, he e a e e y
p omising lines o esea ch and ele an open issues, bu he e also is lack o scien i ic igo in alida ion
p ocess in o he di e en s udies.
INDEX TERMS Sys ema ic li e a u e e iew, collabo a i e business p ocesses, blockchain echnology,
business p ocess managemen , in e -o ganiza ional p ocess managemen , BPM.
I. INTRODUCTION
O e las decade, he use o p ocess enginee ing p inciples on
nume ous en i onmen s is wo ldwide accep ed as mechanism
o inc ease he excellence, p oduc i i y and quali y o any
kind o o ganiza ion [69], [70]. In ac , he e a e s anda ds [1]
and managemen guidelines [2], [3], [71], as well as
impo an echniques and me hods o ICT (In o ma ion
Communica ions Technology) business en i onmen s [4], [5]
ha ecommend o manage main business p ocesses as
mechanism o inc easing e iciency and e ec i eness wi hin
o ganiza ions associa ed wi h he u iliza ion o ad anced
in o ma ion sys ems [72].
In his con ex , BPM (Business P ocess Managemen ) [6]
is a well-known business s a egy o achie e hese goals
wha allows o ob ain di e en ad an ages [7] (e.g., highe
The associa e edi o coo dina ing he e iew o his manusc ip and
app o ing i o publica ion was Jun Wu .
p oduc i i y, compe i i eness, e iciency and educed cos ,
among o he s). In addi ion, he business p ocess de ini ion
is adi ionally o ien ed o be execu ed cen ally o a single
company. In ac , he e a e many echnologies (known as
BPM Sui es [8]) o manage, implemen and execu e hese
p ocesses and, al hough his echnology allows o assign
speci ic asks o he p ocess o ex e nal ac o s, all hose asks
a e o ches a ed in a cen alized way a p ocess le el.
This cen alized a chi ec u e is app op ia e o single
companies, bu i is no e icien when i is necessa y o
collabo a i ely in ol e mul iple en i ies o companies in o
he same p ocess. Some easons o his si ua ion a e ha
each company usually has i s in e es s and so wa e sys ems,
and hey a e usually eluc an o sha e business da a o he
p ocess [9], [10], among o he s. In addi ion, each en i y mus
also mee ce ain condi ions o legal clauses wi h emaining
en i ies pa icipa ing when he p ocess is execu ed by each
en i y. This aspec is e y ele an in some Collabo a i e
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J. A. Ga cia-Ga cia e al.: Using Blockchain o Imp o e Collabo a i e BPM
Business P ocesses (CBP) (e.g., supply chain o logis ics
p ocesses, among o he s [9]).
Mo eo e , o e he las decade, new echnology has
eme ged ha could p o ide a echnological solu ion o exe-
cu e and manage CBP. We e e o BlockChain Technology
(BCT) [11]. This echnology o e s alued cos educ ions
by enabling ansac ions o be un in a pee - o-pee (P2P)
way (i.e., as P2P p ocesses) di ec ly be ween en i ies o
indi idual use s. This execu ion can be ca ied ou wi hou
equi ing mu ual us be ween each pa y. The dis ibu ed
blockchain was con ex ualized in 2008 by Sa oshi Nakama o.
The goal o his p oposal was o es ablish a secu e his o y o
exchange da a using a imes amp o e i y each exchange.
This a chi ec u e was designed o wo k wi hou cen al
au ho i y. In ac , his solu ion was he echnological base ha
caused he bi h o c yp ocu encies such as Bi coin [12].
These ea u es ha e led o a apid and g owing a en ion
on Blockchain since i was applied in he inancial ield
wi h he de elopmen o c yp ocu encies. Since 2008,
many applica ions o BCT ha e been and a e been s udied
and esea ched in nume ous eal ield and se ice [13]
a ound he wo d (elec onic heal h eco ds [14], owne ship
managemen , inancial ma ke [15], ene gy supply [16],
supply chain [17] and In e ne o Things [18], among
o he s) o build decen alized so wa e applica ions whose
a chi ec u e is based on sha ed ag eemen s on decen alized
da a h ough a ne wo k o unknown pa icipan s [19].
Taking his con ex in o accoun , i is possible o see
he in e es o public bodies and so wa e indus ies o
know he easibili y and oppo uni ies ha BCT o e s o
imp o e he p ocess managemen ( om he b oad pe spec i e
o he wo d) in a decen alized manne . This collabo a i e
managemen could become o o e be e se ices o ci izens
and companies.
This s udy add esses he need o know he s a e-o - he-a
o esea ch pape s o e ed by he li e a u e whe e echniques,
app oaches o me hods a e p oposed o imp o e collabo a i e
BPM using blockchain echnology. Mo e p ecisely, his pape
p esen s a sys ema ic e iew and i deals wi h collabo a i e
BPM and BCT when ocusing on wo pa allel (bu com-
plemen a y) wo k lines: (i) suppo ing each ac i i y o he
BPM li ecycle wi h blockchain app oach, and (ii) execu ing
collabo a i e p ocesses using suppo ing ools based on BCT.
The e o e, main con ibu ion o his pape is o p o ide
comple e knowledge and e iew o esea ch pape s ha
p opose echniques, app oaches o me hods a e p oposed o
imp o e collabo a i e BPM using BCT. In he scien i ic li e -
a u e, we ound only a ew e iew pape s ha a ge speci ic
a eas, ins ead o a comple e o e iew o blockchain- ela ed
esea ch wi hin opic o collabo a i e BPM. In addi ion, ou
e iew co e s he mos upda ed pape s in he a o emen ioned
a eas. In his sense, he sys ema ic e iew has been ca ied ou
wi hou il e ing by publica ion da e wha allows o know all
esea ch p oduc ion ha has been published on his subjec .
Simila ly, his sys ema ic e iew analyzes and discusses
wha ac i i ies ( ela ed o he BPM li ecycle) a e suppo ed
by each p ima y s udy. This analysis has also allowed o:
(1) iden i y he business con ex s (heal hca e, manu ac u ing,
supply chains, e c.) whe e each p ima y s udy has been
applied; (2) know speci ic applica ions in he indus y abou
business p ocess imp o emen using BCT; and (3) iden i y
mos popula used blockchain echnologies in domain o
collabo a i e business p ocess managemen .
This analysis p o ides knowledge ha is ele an , use ul
and aluable o decision-make s because i iden i ies ends
and no -co e ed challenges ha can be add essed by he
esea ch communi y. In ac , new esea ch lines ha e been
opened in ou esea ch g oup a e conside ing he esul s
o his sys ema ic e iew. These esea ch lines a e ela ed o
so wa e es ing p ocess and aceabili y p ocess o biological
samples wi hin labo a o ies 4.0. Bo h esea ch lines a e
men ioned as u u e wo ks in conclusion sec ion o his pape .
In sho , his pape p esen s a comp ehensi e e iew o
blockchain echnology and i s applica ions in domain o
collabo a i e p ocess managemen , which we pe cei e o be
he s eng h o his pape .
Finally, i is impo an o men ion ha his sys ema ic
e iew has been ca ied ou ollowing he o mal Ki chen-
ham’s me hodology [24] o iden i y exis ing gaps and o e
u u e guidelines o esea ch on issues ela ed o BPM in
a collabo a i e con ex in BCT domain. This me hodology
is chosen because i has been success ully applied in many
ields (e.g., so wa e enginee ing). In addi ion, Ki chenham’s
me hodology has been ex ended wi h he snowball
echnique [30] in o de o imp o e he e iew p o ocol. This
echnique consis s o analyzing e e ence and ela ed wo ks,
among o he aspec s, o each p ima y s udy o be analyzed.
The es o his pape is s uc u ed as ollows. Rela ed
wo ks a e b ie ly p esen ed in Sec ion 2. This sec ion also
p esen s di e ences om ou sys ema ic e iew wi h all
p e ious wo ks ha a e iden i ied in Sec ion 2. Subsequen ly,
Sec ion 3 desc ibes he planning o ou sys ema ic e iew
p ocess and, once sea ch sys ema ic p o ocol has been
execu ed, esul s a e desc ibed in Sec ion 4. La e , discussions
on hese esul s a e o e ed in Sec ion 5, and, Sec ion 6 inally
es ablishes u u e wo ks and conclusions.
II. COMPARISON WITH RELATED WORKS
Al hough blockchain echnology is ela ed o inancial se -
ices and he implemen a ion o bi coin c yp ocu ency [20],
bo h he in e na ional esea ch communi y and p i a e
co po a ions a e ying o apply his echnology in di e en
a eas. Fo example, blockchain is being e y conside ed in
ecen yea s o imp o e he design o in e -o ganiza ional
p ocesses and hei managemen . This g owing in e es has
led o he publica ion in he scien i ic li e a u e o se e al
SLRs and e iews on his subjec . Thei main conclusions a e
b ie ly desc ibed below.
Kons an inidis e al. [21] ha e ca ied ou SLR o iden i y
business a eas (applica ions and se ices) whe e blockchain
echnology has been used o is being applied in ecen yea s.
Au ho s also iden i y some o he possible challenges o his
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J. A. Ga cia-Ga cia e al.: Using Blockchain o Imp o e Collabo a i e BPM
echnology o imp o e i s applicabili y in a g ea e numbe
o business a eas. Al hough au ho s iden i y challenges
ela ed o echnological aspec s (p i acy, secu i y, la ency,
and compu a ional cos ) o blockchain, i is no ocused on
he applica ion o his echnology in BPM domain wha
hinde s o add ess and know BPM challenges ha could be
suppo ed by BCT. These limi a ions a e esol ed in ou
pape , which iden i ies gaps and open issues o he s a e-o -
he-a on esea ch app oaches ha p opose echniques, ools
o me hods o imp o e he collabo a i e p ocess managemen
using BCT.
Mendling e al. [19] s udy challenges o BCT in BPM
con ex . Au ho s do no desc ibe a sys ema ic e iew
i sel , bu we conside hei pape is in e es ing because i
summa izes se en esea ch ends on he use o BCT in
he BPM domain. These ends a e ela ed o: execu ion
and moni o ing sys ems on BC; me hods o enginee ing
p ocess based on BC; edesigning p ocesses; e olu ion and
adap a ion o business p ocess; echniques which allow o
iden i y, disco e , and analyze ele an p ocesses o he
applica ion o BC; knowing wha is he impac associa ed
wi h he implemen a ion o BC in new business models; and
unde s anding he cul u al change ha in ol es he use o
his echnology in business p ocess execu ion as well as he
con ac ing o se ices.
Lu [22] p esen s a su ey which iden i ies u u e esea ches
and highligh ing open issues on blockchain. Au ho does no
ollow any sys ema ic e iew me hod, and i jus ocuses on a
pape published by IEEE. Howe e , i is in e es ing o know
how ea u es o he blockchain (decen aliza ion, openness
and anspa ency, independence, sa e y, e c.) a e suppo ed by
di e en esea che s.
As men ioned abo e, au ho s summa ize esea ch
ends [19] and open issues [22] on he use o blockchain
echnology, bu hey ha e no iden i ied he s a e-o - he-a
on exis ing speci ic whe e echniques, ools o me hods o
imp o e collabo a i e BPM using BCT a e p esen ed.
Rega ding weaknesses, Lu’s pape does no ollow any
me hodology (which hinde s i s ep oducibili y) and is only
ocused on pape s published by IEEE. Bo h weaknesses
a e mi iga ed by ou sys ema ic e iew. On he one hand,
ou pape ollows Ki chenham’s me hodology [24] which
imp o es he objec i i y o he esul s ha ha e been
ob ained, as well as he ep oducibili y o ou sea ch
p o ocol. On he o he hand, ou sys ema ic e iew is applied
on ou digi al lib a ies, which inc eases he p obabili y
o loca ing a signi ican sample o p ima y s udies o be
e alua ed. In his sense, a e pe o ming ou sys ema ic
e iew, ou pape inc eases scien i ic knowledge o BCT
applied o imp o e collabo a i e BPM.
Casino e al. [88] p esen a su ey wi h he cu en s a e o
he echnological applica ion o blockchain o di e en appli-
ca ion domains. Specially, au ho s conside he economic
applica ion o BCT as an immo able aspec (c yp omoney
and i s managemen ). Fo his pu pose, au ho s e iew how
he applica ion o BCT p oduces an unp eceden ed B2C
(Business o Consume ) and B2B (Business o Business) shi
in online business p ocesses. Howe e , au ho s do no add ess
o analyze implica ions, limi a ions o weaknesses o BCT
when i is used o imp o e he managemen o hese speci ic
ypes o business p ocesses. In addi ion, au ho s jus ocus on
business p ocesses ela ed o economic applica ions.
Some hing simila happens in [89] and [90]. On he one
hand, Hawli schek e al. [89] conduc a sys ema ic e iew
o he exis ing li e a u e on blockchain echnology, bu
au ho s lack a b oad pe spec i e in he ield o compu e
science. Au ho s conside only one opic o hei s udy
(i.e., blockchain echnology as a means o decen alized
us managemen in he business and social economy),
bu au ho s do no add ess he applica ion o BCT o
imp o e collabo a i e BPM. On he o he hand, Seebache
and Schü i z [90] p esen a sys ema ic e iew on BCT applied
o so wa e sys ems based on web se ices and p ocesses.
I does include he concep o suppo ing p ocesses based
on BCT as a possible aspec o BPM imp o emen in o
se ice-o ien ed a chi ec u es. Howe e , au ho s indica e his
possibili y as a lesson lea ned a e e iewing some p e ious
wo ks wi hin ollowing any me hodological e iew p ocess
i sel .
A e analyzing p e ious ela ed wo ks, i is possible o
conclude and summa y ha hese pape s a e ocused on opics
ela ed o BCT and some speci ic kind o business p ocesses,
bu hey do no p o ide an o e iew o he s a e-o - he-a
on his echnology and collabo a i e p ocess managemen .
In ac , hese ela ed wo ks ha e no add essed he speci ic
challenges and gaps o his opic. In his sense, he e o e, ou
sys ema ic e iew p o ides a gene al poin o iew o analyze
esea ch pape s ha p opose echniques, me hods o ools o
imp o e he in e -o ganiza ional p ocess managemen using
BCT. This analysis allows o iden i y gaps and open issues
in his opic which has eme ged epea edly in ecen yea s in
he ela ed wo ks, bu ha none has explo ed in dep h as a
esea ch objec i e.
III. PLANNING THE SYSTEMATIC REVIEW
One o mos impo an possible aspec s o any sys ema ic
e iew is o ensu e i s ep oducibili y and, o his pu pose,
i is necessa y o de ine and plan i s e iew p ocess. This
p ocess includes he de ini ion o he mo i a ion o conduc
his e iew, wha a e he esea ch ques ions o be answe ed
and he sea ch p o ocol o pe o m, as well as quali y
assu ance sea ch c i e ia o apply. The planning s age also
p esen s exclusion and inclusion c i e ia ha a e used o
loca e he mos ele an p ima y s udies. In his sense, i is
also impo an o men ion ha il e s on publica ion da e
ha e no been applied wha allows o know all esea ch
p oduc ion ha has been published on ou esea ch subjec .
Nex subsec ions desc ibe in de ail hese aspec s.
A. IDENTIFYING THE NECESSITY OF THE REVIEW
O e he las decade, many in es iga ions a e being ca ied
ou a ound he wo ld o e alua e and iden i y challenges
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J. A. Ga cia-Ga cia e al.: Using Blockchain o Imp o e Collabo a i e BPM
and obs acles o apply BCT on he ield o Collabo a i e
Business P ocesses (CBP). These esea ches ha e p esen ed
and e alua ed blockchain echnology in mul iple p ocesses
and se ices o di e en business a eas (logis ics, supply
chain, heal h, inancial sec o , e c.) wha could ha e iden i ied
possible challenges and ba ie s o his echnology o manage
collabo a i e p ocesses.
In his con ex , his pape sys ema ically e iews he ield
o CBP in BCT domain in o de o cha ac e ize and p esen
oppo uni ies and gaps o u he esea ch, as well as iden i y
he na u e o each p ima y s udy (i.e., academic p o o ype,
applica ion in indus y, e c.).
B. FORMULATING RESEARCH QUESTIONS
Acco ding o Ki chenham’s me hodology, Resea ch Ques-
ions (RQ) a e a mechanism ha allows o ocus any
sys ema ic e iew on speci ic opics. The objec i e is o
imp o e scien i ic knowledge a e analyzing esea ch pape
ha a e ela ed o his opic. In his con ex , he sys ema ic
e iew desc ibed in his pape is guided by he ollowing main
esea ch ques ion: Wha is he s a e-o - he-a abou he
use o blockchain echnology (BCT) o imp o e collabo a i e
p ocess managemen (CPM)?. This main RQ has been
di ided in o mo e speci ic RQ in o de o o e mo e speci ic
analysis and cha ac e iza ion o p ima y s udies abou BCT
and CPM. These speci ic RQs and hei mo i a ions a e
desc ibed in Table 1.
C. DEFINING THE REVIEW PROTOCOL
A e es ablishing backg ound and esea ch ques ions o be
answe ed, i is necessa y o speci y he e iew p o ocol o be
ca ied ou . Fo his pu pose, his p o ocol de ines aspec s
such as sea ch s a egy o ind p ima y s udies, wha a e
selec ion c i e ia o selec p ima y s udies and wha quali y
c i e ia will be applied on each p ima y s udy. These aspec s
a e desc ibed in ollowing subsec ions.
1) SEARCH STRATEGY
This sec ion aims o desc ibe he sea ch p ocedu e which
a e going o allow o loca e ele an esea ch pape s ela ed
o he imp o emen o CPM using BCT. Fo his pu pose,
esea ch pape s published in jou nal and ele an con e ences
a e going o be sea ched in a ious digi al lib a ies ollowing
a wo-s age s a egy.
On he one hand, p e-sea ches a e i s ly pe o med o
con i m he keywo ds o be used. These keywo ds imp o e
he quali y o he sys ema ic e iew because hese ones ocus
he loca ion o esea ch pape s unde s udy. Finally, Table 2
shows all keywo ds ha ha e been used in his sys ema ic
e iew (some synonyms ha e been also conside ed o
gua an ee he inclusion o ele an pape s).
On he o he hand, a e ca ying ou p elimina y sea ches,
and once keywo ds ha e been es ablished, hese keywo ds
a e combined o build sea ch exp essions, which a e
used o sea ch p ima y s udies in each digi al lib a y.
TABLE 1. Resea ch ques ions.
TABLE 2. Keywo ds.
The cons uc ion o hese exp essions is ma hema ically
o malized in Equa ion 1.
Ma hema ical exp ession o build sea ch exp essions using
keywo ds.
E1=[(V2
i=1Ai)∧(V4
j=1Bj)] ∧(V1
k=1Ck) (1)
Mo eo e , some au ho s ha e es ablished me hodological
c i e ia o selec ele an digi al lib a ies on which execu e
sys ema ic e iews. Fo example, Ngai e al. [31] conside s i
ele an o use he ollowing digi al lib a ies: ABI Da abase,
ScienceDi ec , Academic Sea ch P emie , Business Sou ce
P emie , ACM Digi al Lib a y, IEEE Xplo e Digi al Lib a y,
Science Di ec , Sp inge , Wo ld Scien i ic Ne and Web o
Knowledge.
Howe e , a e ca ying ou p elimina y sea ches, i is
possible o obse e ha many pape s a e simul aneously
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TABLE 3. Sea ch exp essions used on each digi al lib a y.
loca ed in nume ous o hese lib a ies, wha does no add
new alue o any sys ema ic e iew bu a he complica es
he execu ion because i is necessa y o disc imina e mo e
duplica e pape s. This ac has been co obo a ed a e
execu ing he p elimina y sea ches men ioned abo e.
In his con ex and conside ing hese conclusions, ol-
lowing digi al lib a ies ha e been selec ed o execu e and
manage1ou sys ema ic e iew: IEEE Xplo e Lib a y, ACM
Lib a y, Sp inge Link and ScienceDi ec . I is also necessa y
1Jab e [32] and Mic oso Excel sp eadshee ha e been used o
sys ema ize he managemen o pape s unde s udy.
o cla i y ha sea ch exp essions ( o malized in Equa ion 1)
a e going o be applied on i le-abs ac -keywo d me ada a o
each p ima y s udy acco ding o he ma hema ical o mula
exp essed in Equa ion 2.
Ma hema ical exp ession o iden i y p ima y s udies
acco ding o hei me ada a.
E2= i le (E1)∨abs ac (E1)∨keywo d (E1) (2)
Table 3 p esen s each sea ch exp ession (Equa ion 2) ha
has been used on each digi al lib a y. I is impo an o cla i y
ha some sea ch exp essions ha e been di ided in o se e al
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TABLE 4. Desc ip ion o exclusion and inclusion c i e ia.
sub-exp essions because o hei excessi e size (numbe o
logical clauses). Some digi al lib a ies do no suppo he use
o long logical exp essions o pe o m sea ches. Fo example,
IEEE Xplo e does no allow o indica e logical exp essions
wi h mo e han 15 logical clauses.
Finally, a e au oma ically execu ing he sea ch exp es-
sions (see Table 3) and, once pape s unde s udy a e
iden i ied, he snowball echnique is applied o ex end
he sea ch p ocess. In his sense, each e e ence used by each
pape has been analyzed o iden i y o he ele an pape s
ela ed o ou opic. The esul s o his s a egy a e in de ail
desc ibed in Sec ion V.A.
2) SELECTION PROCESS OF PRIMARY STUDIES
The selec ion p ocess allows o s anda dize he iden i ica ion
o p ima y s udies and i has been de ined o in eg a e
he pa icipa ion o se e al di e en esea che s who a e
join ly wo king on his sys ema ic e iew. Speci ically, his
sys ema ic e iew is ca ied ou by wo senio esea che s
and one junio esea che . In his con ex , six phases a e
p oposed o uni o mly and homogeneously execu e his
selec ion p ocess. In addi ion, exclusion and inclusion c i e ia
ha e been de ined o be applied in each phase o he selec ion
p ocess. Table 4 summa izes hese c i e ia.
Fi s ly, he objec i e o i s phase (P1) is o execu e all
sea ch exp essions desc ibed in Table 3. As men ioned abo e,
hese sea ches allow o selec candida e pape s conside ing
TABLE 5. Quali y ques ions.
hei me ada a ( i le, abs ac and keywo ds). Once he i s
phase is comple ed, inclusion and exclusion c i e ia a e
applied by all esea che s in he second phase (P2).
Subsequen ly, a e applying inclusion and exclusion
c i e ia, each p ima y s udy is analyzed in de ail o de e mine
i i s opic is ela ed o he opic o his e iew. This analysis
p ocess is execu ed in he hi d phase (P3). A e execu ing
his s age, i is possible ha some doub s appea abou
he adequacy o some p ima y s udies. In his si ua ion,
he selec ion p ocess p oposes o conduc ace- o- ace
mee ings ( ou h phase; P4) be ween esea che s in o de
o minimize bias o each esea che and a oid subjec i e
decisions, as well as es ablish consensual ag eemen s on
which p ima y s udies a e ele an .
A he ending, once ou h phase is inished, semi inal
p ima y s udies a e ob ained. These a e p elimina y because
i is s ill necessa y o apply he snowball echnique( i h
phase; P5) on hese semi inal s udies o ind new ele an
s udies. Du ing he execu ion o his s age, i is also possible
ha some doub s a ise when hese new s udies a e conside ed
by all esea che s. In his sense, a second ace- o- ace mee ing
(six h phase; P6) among all esea che s is p oposed o each
consensus on ele an pape s and a oid subjec i e decisions.
3) QUALITY QUESTIONS
Quali y Ques ions (QQ) allows o es ablish objec i e c i e ia
o de e mine he quali y o each p ima y s udy ha is
e iewed. Table 5 summa izes each quali y ques ion, which
has associa ed sco ing c i e ia ( inal quali y sco e is going
o be he cumula i e sco e pe quali y ques ion). I is
impo an o men ion ha his quali y sco e is no used o
exclude p ima y s udies, bu o es ablish he ele ance and
ep esen a i eness o each p ima y s udy in u u e esea ches.
4) CHARACTERIZATION SCHEME
Each p ima y s udy ha is analyzed in his sys ema ic
e iew may con ain a wide a ie y o in o ma ion, so,
he analysis o his in o ma ion could become a e y edious
ask. Table 6 de ines a cha ac e iza ion scheme o educe
he e o equi ed o ca y ou his ask. The p ocess o
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TABLE 6. Cha ac e iza ion scheme.
comple ing his scheme is based on wo s ages. Fi s ly,
each esea che analyzes each p ima y s udy and comple e
he cha ac e iza ion scheme. La e , all esea che s es ablish
o de ed discussions o ag ee on inal da a o his e alua ion.
5) EXTERNAL VALIDATION OF THE REVIEW PROTOCOL
Ki chenham’s me hodology ecommends es ablishing mech-
anisms o e ine he sea ch p o ocol o any sys ema ic
li e a u e e iew. The objec i e is o maximize he adequacy
o his p o ocol wi h he objec i es o he sys ema ic e iew.
In his sense, a couple o mechanisms ha e been p oposed
o ca y ou his e iew o he e iew p o ocol i sel . Fi s ly,
p elimina y sea ches ha e been se up o adjus keywo ds,
exclusion c i e ia and sea ch exp essions o his sys ema ic
e iew (as men ioned abo e; Sec ion III.C.1). Secondly,
an expe in conduc ing SLRs has been consul ed o e ine
ou e iew p o ocol. This pe son, who is Full p o esso
in So wa e Enginee ing a Uni e si y o Se ille (Spain),
p oposed some changes, which ha e allowed o imp o e ou
e iew p o ocol.
IV. CONDUCTING AND QUALITY RESULTS
This sec ion desc ibes he execu ion o he e iew p o ocol
ha has been desc ibed in p e ious sec ion. In his sense,
on he one hand, Sec ion IV.A p esen s he esul s o he
selec ion p ocess and s a is ical s udies o hese esul s.
On he o he hand, inal p ima y s udies ha a e conside ed
in his sys ema ic e iew a e indica ed in Sec ion IV.B. This
las sec ion also includes he quali y sco e o each p ima y
s udy a e applying he cha ac e iza ion scheme on each
one (see Table 5). Finally, some h ea s may ha e occu ed
du ing he e iew p ocess. These aspec s a e also discussed
in Sec ion IV.C.
A. EXTRACTION AND DETECTION OF PRIMARY STUDIES
A e applying sea ch que ies desc ibed abo e, ou selec ion
p ocess and inclusion/exclusion c i e ia ha e been applied.
Figu e 1 illus a es he comple e p ocess o selec ing he
p ima y s udies and Table 7 summa izes he dis ibu ion o
esea ch pape s ha ha e been analyzed in his selec ion
p ocess.
Rega ding Figu e 1, each phase o he selec ion p ocess
has been named using he abb e ia ions desc ibed in p e ious
TABLE 7. Cha ac e iza ion scheme.
FIGURE 1. Summa y diag am o he selec ion p ocess o p ima y s udies.
sec ions. Fu he mo e, i is impo an o men ion ha he
hi d phase has been ep esen ed by wo di e en s eps
in Figu e 1 in o de o show he e olu ion o p ima y s udies
when some exclusion c i e ia ha e been applied. Speci ically,
hese s eps ep esen wo exclusion c i e ia: duplica e a icles
(C1) and e iews/discussions/opinions/e c. (C2).
Table 7 summa izes o each esea ch da abase, he numbe
o pape s ha a e he esul o each s age o he e iew
p o ocol. This able also includes a eco d o pape s ob ained
a e applying he snowball echnique ( hese pape s ha e no
been classi ied by da abase o acili a e he managemen o
esul s). In addi ion, Figu e 2 shows how he e alua ion o
he sea ch p o ocol has been along h ee main miles ones.
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FIGURE 2. S udies e ie ed h ough sea ch engines.
Fi s ly, a e inishing he i s phase o he selec ion
p ocess, 1134 candida e pape s ha e been ound (see Table 7).
These candida e pape s ha e been e u ned a e execu ing
each sea ch exp ession (Table 3) on each digi al lib a y.
Secondly, exclusion c i e ia ha e been applied in he second
phase (P2), which e u ns 131 candida e esea ch pape s
and is conside ed he i s miles one o ou e iew p o ocol.
Figu e 2 shows his miles one in he i s da a se ies o he
his og am. Speci ically, his se ies ep esen s pape s ha a e
e ie ed om each digi al lib a y a e execu ing all sea ch
exp essions.
Subsequen ly, he nex execu ed phase (P3; hi d phase)
e u ns 56 candida e esea ch pape s when his one has
inished. These esul s a e he second miles one o he sea ch
p o ocol and a e associa ed wi h he second da a se ies o
he his og am (Figu e 2). This se ies means he numbe o
p ima y s udies ha a e ob ained om each digi al lib a y
a e dele ing duplica e pape s. Fu he mo e, hese esul s
also exclude esea ch pape s ela ed o compa a i e s udies,
sys ema ic mapping s udies, su eys, sys ema ic li e a u e
e iews, and opinion a icles, among o he s.
A his momen , he ou h phase (P4) o he selec ion
p ocess is ca ied ou and consis s in ca ying ou he i s
ace- o- ace mee ing o es ablish consensus when he e a e
doub s. Some candida e pape s could be doub ul because
hei subjec is on he bo de wi h espec o ou subjec .
A he ending o his phase, 24 candida e p ima y s udies ha e
been selec ed (see Table 7) and snowball echnique is
applied o hese ones ( i h phase; P5). In addi ion, he second
ace- o- ace mee ing is also pe o med (six h phase; P6) o
decide he adequacy o each candida e pape s ound a e
applying his echnique. The applica ion o his snowball
echnique has allowed o ind 10 new p ima y s udies ha a e
ela ed o ou subjec .
Finally, he hi d miles one in ou sea ch p ocess co e-
sponds o he o al numbe o p ima y s udies (i.e., 34 p ima y
s udies), which is he esul o adding he numbe o p ima y
s udies ob ained when P4 and P6 a e comple ed. This
miles one is ela ed o he hi d da a se ies o he his og am
shown in Figu e 2.
Mo eo e , Figu e 3 shows he dis ibu ion o p ima y
s udies ha a e e ie ed in each digi al lib a y wi h espec
FIGURE 3. Analysis o e ie ed esul s om digi al lib a ies espec o
o al inal p ima y s udies.
o he o al o selec ed s udies o all he sea ch engines. I is
in e es ing o no e ha Sp inge p o ides 42 % (app ox.)
o p ima y s udies and mos digi al lib a ies include 10%
(app ox.) o he s udies. This ac can be obse ed o
he second alue o he se ies shown in Figu e 3. This alue
p esen s p ima y s udies ha a e inally conside ed in he
analysis and e ie ed om he digi al lib a y di ided by all
he di e en p ima y s udies ha a e been e ie ed om he
same digi al lib a y.
B. THREATS IN THE VALIDATION
The exis ence o h ea s is an inhe en ac when any ask has
been ca ied ou by people. In his sense, i is possible o iden-
i y some h ea s associa ed wi h he selec ion p ocess and he
alida ion p ocess ha ha e been execu ed in his pape . Fo
ins ance, some mis akes could ha e appea ed du ing selec ion
o p ima y s udies o da a ex ac ion. Howe e , ou selec ion
p ocess (Sec ion III.C.2) has been planned in well-con olled
phases o minimize his isk. Fu he mo e, se e al e iews
and mee ings be ween esea che s ha e also been ca ied ou
o educe his isk.
Mo eo e , i is impo an o conside ha i is no possible
o gua an ee ull co e age o each esea ch pape on a speci ic
opic because some pape s a e no indexed and he e is g ay
li e a u e ha could no be included in ou e iew [35]. This
h ea has been mi iga ed using a signi ican sample o digi al
lib a ies. These lib a ies publish pape s on a wide ange o
scien i ic opics, which could be easonable enough o loca e
he la ges numbe o ele an pape s ela ed o he opic o
his sys ema ic e iew.
V. ANALYSIS
This sec ion answe s and discusses in de ail each esea ch
ques ion (Table 1) o de ec s eng hs and weaknesses o each
p ima y s udy.
A. RQ1. WHAT ARE THE EXISTING APPROACHES IN THE
LITERATURE THAT USE BCT IN THE DOMAIN OF
COLLABORATIVE PROCESS MANAGEMENT?
Table 8 p esen s a summa y o he p ima y s udies which
ha e been ound and, inally, conside ed in his SLR, as well
as he applica ion o all quali y c i e ia on each pape
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TABLE 8. P ima y s udies and hei quali y assessmen sco e.
(Sec ion III.C.3). Anyway, i is ele an o men ion ha hese
quali y c i e ia ha e no been used o educe he numbe o
p ima y s udies, bu a he o iden i y he mos impo an ones
o u u e esea ch.
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C. RQ3: WHAT IS RESEARCH METHOD APPLIED TO
VALIDATE EACH PRIMARY STUDY?
Once p ima y s udies (Table 8) ha e been analyzed, mo e
han hal o p ima y s udies (58,33%) ha e applied some
esea ch me hod o alida e each p oposal. The dis ibu ion
o p ima y s udies and esea ch alida ion me hods is
desc ibed in Table 10. Mos popula me hods a e expe imen s
(8 p ima y s udies), p oo -o -concep (9 p ima y s udies) and
case s udies (5 p ima y s udies).
I is possible o obse e a ele an h ea in hese
s udies: ew pape s (e.g., [P6] [P11] [P13], among o he s)
desc ibe comp ehensi e alida ion plans. This si ua ion could
hinde he ep oducibili y o hese alida ions. Howe e , his
si ua ion would be sol ed i a igo ous alida ion plan is
pe o med o e i y he con ibu ion o each p ima y s udy.
TABLE 10. Resea ch alida ion me hods and p ima y s udies.
D. RQ4. WHAT ARE THE BUSINESS OR INDUSTRIAL
CONTEXTS WHERE BCT IS USED TO IMPROVE CBP
MANAGEMENT?
A e analyzing and discussing p e ious RQs, i has been
possible o e i y ha BCT is becoming inc easingly popula
by he esea ch and indus ial communi ies o sol e use cases
in many ields ela ed o CBP managemen . Al hough he e
a e sys ema ic e iews ha a e ocused on iden i ying appli-
ca ions o his echnology in indus ial con ex s [21], [22],
i is in e es ing o include a b ie analysis o indus ial
applica ions ha a e desc ibed by p ima y s udies (Table 8)
in his pape .
In his sense, Table 11 shows he dis ibu ion o p ima y
s udies pe business en i onmen s whe e he esul s o hese
p ima y s udies ha e been applied.
TABLE 11. Business sec o s and p ima y s udies.
Acco ding o he p ima y s udies ha ha e been analyzed
in his pape , i e speci ic business domains ha e been iden-
i ied, in which BCT is been used o imp o e collabo a i e
p ocess managemen .
These domains mainly a e supply chain, indus y 4.0,
logis ic, banking, and scien i ic con ex . I is also possible o
highligh a ele an ac : 58.84% o p ima y s udies p esen
gene al-pu pose p oposals wha ein o ces he commi men
o he esea ch communi y o p opose ans e sal solu ions
ha can be applied in di e en business con ex s ins ead o
p oposing ad hoc solu ions in speci ic business sec o s.
Al hough he applica ion o each p ima y s udy in i s
business con ex has been desc ibed in p e ious sec ions,
below, A summa y o how BCT can imp o e CPM is
p esen ed by each business sec o men ioned in Table 11.
Rega ding supply chain & logis ic sec o , BCT ensu es
iden i ica ion o p oduc p o enance and acili a es acking
o p ocesses. This sec o implies complica ed p ocess ha
equen ly in ol e di e en and independen ac o s and
s akeholde s which ha e o wo k oge he assu ing he
compliance be ween hem. I is one o he main sec o s whe e
BCT is being success ully applied. I s own cha ac e is ic
wi h he cons ain s and collabo a i e equi emen s can be
imp o ed wi h blockchain p inciples [100].
Rega ding indus y 4.0 sec o , BCT in indus ial appli-
ca ions is ha ing immense po en ial o imp o e nume ous
aspec s (secu i y aspec s, sha ed da a collec ion, e iciency,
e ec i eness, e c.) in he in e -o ganiza ional p ocess man-
agemen [87]. In his sec o , he assu ance ha each s ep o he
collabo a i e p ocess is execu ed ollowing ime, esou ces
and quali y equi emen s is c i ical o he good esul s.
Besides, some o hese s eps a e execu ed by obo s o
machines which equi es an obliga o y collabo a ion be ween
hem. The use o sma con ac and blockchain o de ine
hese collabo a i e p ocesses o e s success ul cases and e y
in e es ing esul s as some au ho s a gue [101].
Rega ding banking sec o , some au ho s ha e p oposed
echniques o imp o e he collabo a i e p ocess execu ion
be ween inancial ins i u ions using BCT. The banking sec o
is p obably he i s sec o ha go bene i s om blockchain.
In his sec o , he secu i y o collabo a i e p ocesses and
he independence be ween hem is c ucial o gua an ee good
esul s and banks a ound he wo ld a e applying blockchain
echnology in hei IT solu ions [102].
Mo eo e , i is possible o ind also ano he se o
applica ions and success ul examples in he applica ion o
BCT on CBP wi hin scien i ic sec o . As his pape p esen s,
he esea ch communi y a e in e es ed in his echnology,
bo h o esea ching and o sha ing knowledge be ween
esea che join ly. Thus, we can ind a high numbe o
examples in esea ch sec o s like medicine, educa ional
among o he , ha a e assuming blockchain o imp o e hei
p ocesses [103].
Finally, he applica ion o blockchain p inciples is so huge
ha we ha e o conside o he sec o s, en i led in his pape
like gene al sec o s. In his sense, i is impo an o highligh
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TABLE 12. Technical ea u es by p ima y s udy.
ha many p ima y s udies p opose gene al-pu pose ech-
niques o ools, which allow hei applica ion in nume ous
business con ex s. Howe e , i is also ele an o men ion
he e a e o he business sec o s whe e BCT can be used o
imp o e he collabo a i e p ocess managemen such as public
sec o and public go e nance [104] o social and indus ial
sec o [105].
E. RQ5. WHAT ARE THE MOST RELEVANT TECHNICAL
CHARACTERISTICS OF EACH PRIMARY STUDY?
Once p ima y s udies ha e been p esen ed and discussed
in p e ious sec ions, i is possible o iden i y he mos
used echnologies ha a e used by au ho s o suppo hei
p oposals. Table 12 summa izes echnical cha ac e is ics o
each p ima y s udy. These cha ac e is ics ha e been g ouped
in o ou echnical ca ego ies: (1) blockchain pla o ms o
a chi ec u es, (2) p ocess modeling languages, (3) sma
con ac echnologies, and (4) p ocess execu ion pla o m
o p ocess engine wi h blockchain suppo . Abo e, nex
subsec ions discuss hese echnical ca ego ies o all p ima y
s udies.
1) BLOCKCHAIN PLATFORM OR ARCHITECTURE
Today, he e a e many open-sou ce o p op ie a y blockchain
pla o ms o suppo blockchain ea u es ( ansac ion ali-
da ion, sha ed da a and consensus and iden i y managemen
mechanisms, among o he ea u es) [92]. Table 12 iden i ies
mos popula pla o ms ha ha e been used o de elop each
p oposal. These pla o ms a e: Hype ledge (F1), E he eum
(F2) and Bi coin (F3) blockchains. Ne e heless, some
au ho s ha e used o he sha ed ledge , o hey e en men ion
he use o blockchain pla o ms, bu hey do no indica e
in hei pape wha speci ic pla o m is. This ca ego y
includes his possibili y using he alue o he sha ed ledge
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o unspeci ied pla o m(F4). Figu e 5 also e eals he
deg ee o which he blockchain pla o ms o a chi ec u es a e
co e ed.
FIGURE 5. Repo ing - de ail o blockchain pla o ms o a chi ec u es
co e ed by he p ima y s udies.
The mos commonly used blockchain pla o m is he
pla o m o e ed by E he eum [57], which is an open sou ce,
public, blockchain-based dis ibu ed compu ing pla o m ha
also suppo s p og amming languages (e.g., Solidi y and
Se pen ) o encode sma con ac s. I is possible o obse e
E he eum is applied in 18 p ima y s udies ( ep esen ing 53 %
o o al) as shown Figu e 5.
The nex wo pla o ms used o suppo each p oposal a e
Hype ledge [93] and Bi coin blockchain [41].
On he one hand, Hype ledge is an open-sou ce p ojec
o blockchains ha was c ea ed by he Linux Founda ion.
I includes own consensus p o ocols and s o age mechanisms,
as well as se ices o iden i y and access con ol. I also
suppo s p og amming languages (such as, Ja a, o Solidi y,
among o he s) o encode sma con ac s. In his case,
Hype ledge is obse ed in 5 p ima y s udies (Figu e 5),
which ep esen s 15 % o he p oposals.
On he o he hand, Bi coin blockchain is well-known i s
gene a ion blockchain and public ledge , which s o es all
ansac ions o he Bi coin ne wo k. I has been implemen ed
o suppo use cases o inancial p ocesses associa ed wi h
c yp ocu encies. This pla o m is obse ed in a single o al
p oposal ( ep esen ing 3% o p ima y s udies) as shown
Figu e 5.
Finally, a e analyzing each p ima y s udy, i is possible
o obse e ha he h ee p e iously men ioned pla o ms
a e e y popula (especially E he eum) o implemen each
p oposal. Howe e , a signi ican numbe o au ho s men ion
he use o blockchain pla o ms o de elop hei p oposals, bu
hese pla o ms a e no iden i ied. O he au ho s also decide
o implemen hei own blockchain a chi ec u es, p o ocols
and algo i hms; al hough his op ion is no signi ican .
Figu e 5 shows his si ua ion wi h he alue o he sha ed
ledge o unspeci ied pla o m(F4). In his sense, his
si ua ion is obse ed in 10 p ima y s udies, which ep esen s
29% o he p oposals.
2) PROCESS MODELING LANGUAGES
Since 1980s, many no a ions and languages ha e been
p oposed by esea ch communi y o model p ocesses, each o
which wi h a conc e e pu pose. In his con ex , some au ho s
ha e es ablished axonomies o g oup hese P ocess Modeling
Languages (PMLs) [94], [95], and hese axonomies ha e
been used in his pape o g oup each p ima y s udy.
Figu e 6 e eals he deg ee o which PMLs a e co e ed by
he p ima y s udies.
FIGURE 6. Repo ing - de ail o p ocess modeling languages co e ed by
he p ima y s udies.
As obse ed in Figu e 6, no all p ima y s udies suppo
some p ocess modeling language. In ac , he e a e only
22 p ima y s udies (64% o o al o he p ima y s udies)
ha include some mechanisms o model blockchain ea u es
in o p ocess models. This ac may be jus i ied because
no all p ima y s udies suppo Disco e y & modeling
ac i i y o he BPM li ecycle (see Table 9). Ne e heless, a e
conside ing p e ious axonomies and analyzing each p ima y
s udy, some PMLs ha e been iden i ied as he mos widely
used pa adigms o de ine o model blockchain ea u es in o
p ocess models (see Table 12): BPMN (Business P ocess
Model and No a ion) o BPMN ex ensions (F5), languages
based on s a e machines (F6), g aph-based no a ions (F7),
me amodel-based no a ions (F8), and languages based on
Pe i-ne s (F9).
As men ion abo e, Figu e 6 shows he dis ibu ion o ype
o PMLs ha a e suppo ed by he p ima y s udies. The
lowes ones a e g aph-based languages (1 p ima y s udy),
languages based on s a e machines (1 p ima y s udy) o based
on Pe i-ne s (1 p ima y s udies). The pe cen age associa ed
wi h hese ypes is 9% o p ima y s udies.
Mo eo e , he mos popula choice o de ining blockchain
ea u es wi hin p ocess models is o use BPMN (o ex ensions
o BPMN) and me amodel-based languages; al hough he
o me is mo e widely used han he la e . In his sense,
BPMN is obse ed in 16 p ima y s udies ( ep esen ing 47%
o p ima y s udies) while me amodel-based languages a e
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only used by 3 p oposals ( ep esen ing 9% o p ima y
s udies). P e e ed no a ion by au ho s o p ocess modeling
wi h BC ea u es seems BPMN. This si ua ion could be
jus i ied because BPMN is an in e na ional s anda d o
business p ocess modeling and is he mos suppo ed no a ion
by many p ocess execu ion engines wha acili a es i s
deploymen in eal en i onmen s [8].
3) SMART CONTRACT TECHNOLOGIES
Be o e men ioning he deg ee o co e age o hese echnolo-
gies by he p ima y s udies o his e iew, i is impo an o
know he meaning o sma con ac . Some au ho s b ie ly
de ine he concep o sma con ac as a Tu ing-comple e
p og am ha encodes a digi al p o ocol p ede ined by pa ies
who p oceed o an ag eemen [99]. This p o ocol checks and
execu es a se o ules (clauses o he ag eemen ) o e a
blockchain ne wo k.
In his con ex , he combina ion o BPM and blockchain
echnology can imp o e e iciency and e ec i eness o he
execu ion o in e -o ganiza ional p ocesses be ween se e al
o ganiza ions. These en i ies can ag ee on business ules,
con ac ual condi ions, e c., associa ed wi h ansac ions ha
occu du ing he execu ion o hese collabo a i e p ocesses.
Be o e he exis ence o blockchain echnology, hese en i ies
usually collabo a ed wi h o he ex e nal en i ies, which
e i ied he con ac ual condi ions o collabo a e p ocesses.
This si ua ion usually caused ex a cos and unce ain y o
he companies ha we e collabo a ing. Today, sma con ac s
allow o au oma ically e i y hese business ules and
con ac ual condi ions o in e -o ganiza ional p ocesses when
he sma con ac is deployed and execu ed on a blockchain
ne wo k. In addi ion, hese con ac ual condi ions a e also
au oma ically e i ied a un ime wi hou he need o an
in e media y o audi o o e i y compliance. This ad an age
inc eases con idence and educes cos s o all o ganiza ions
when hese ones join ly collabo a e in in e -o ganiza ional
p ocesses.
Today, he e a e wo ypes o sma con ac s [96]:
de e minis ic and non-de e minis ic sma con ac s. The i s
one is a sma con ac ha when i is un, i does no
equi e any in o ma ion om an ex e nal pa y (i.e., om
ou side he blockchain ne wo k), whe eas he second one
is a sma con ac ha depends on in o ma ion (called
o acles o da a eeds) om an ex e nal pa y. Nowadays, he e
a e echnologies (based on Tu ing-comple e p og amming
languages) o encode bo h kind o sma con ac s. Fo
example, Tu ing-comple e p og amming languages such as
Solidi y and Se pen allow o de elop de e minis ic and
non-de e minis ic sma con ac s, while o he p og amming
languages (such as Ja a, Go, and Fab ic, among o he s) allow
only o de elop de e minis ic sma con ac s [91].
Figu e 7 also e eals he deg ee o which he sma
con ac echnologies a e co e ed by he p ima y s udies. I is
possible o obse e ha no all p ima y s udies suppo sma
con ac echnologies. In ac , 21 p oposals only use hese
echnologies.
FIGURE 7. Repo ing - de ail o sma con ac echnologies co e ed by
he p ima y s udies.
The p og amming languages mos used by au ho s o
encode sma con ac s a e Solidi y (F10) and Go (F11);
al hough he o me is mo e widely used han he la e
as is shown in Table 12. Specially, Solidi y is obse ed
in 11 p ima y s udies ( ep esen ing 32 % o p ima y s udies),
whe eas Go p og amming language is used by 5 au ho s
( ep esen ing 15 % o all p ima y s udies).
Finally, i is possible o obse e some au ho s men ion he
use o p og amming language o encode sma con ac s, bu
hey do no speci y in hei pape wha p og amming language
is used. This ac is included wi hin his ca ego y using he
unspeci ied p og amming language(F12) alue, and i
is possible o no e his si ua ion in 5 p ima y s udies (see
Table 12) wha ep esen s 15% o all p ima y s udies (see
Figu e 7).
4) PROCESS EXECUTION PLATFORM OR PROCESS ENGINE
Business p ocess engines (named usually Business P ocess
Managemen Sys ems; BPMS) a e so wa e solu ions ha
enables he execu ion and main enance o p ocess wo k lows.
I p o ides business p ocess in e ac ion and communica ion
be ween di e en da a/p ocess sou ces sp ead ac oss one
o mo e IT (in o ma ion echnology) applica ions and se -
ices [97].
These so wa e ools include di e en unc ionali ies o
suppo each phase o BPM li ecycle, bu hese engines a e
usually gene al-pu pose ools [97], and hei co e ea u es do
no p o ide usually speci ic mechanisms o in eg a e BCT.
This eason has p omo ed esea ch communi y designs and
de elops speci ic p ocess engine o suppo ea u es o BCT.
In his con ex , a e analyzing he p ima y s udies,
i is possible o obse e h ee main echnological solu ions
ha ha e been used o p oposed o suppo and imp o e
he execu ion o collabo a i e p ocess using BCT. These
pla o ms a e: BCWMS (F13), Zeebe p ocess engine (F14)
and Ca e pilla (F15). In addi ion, i is possible o obse e
wo ac s. Fi s ly, some au ho s p opose hei own execu ion
pla o m, bu hey do no p o ide de ailed echnical in o ma-
ion abou his pla o m. This ca ego y includes his si ua ion
using his alue: o he execu ion pla o m o unspeci ied
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pla o m(F16). Secondly, i is also possible o no e ha
no all au ho s p o ide mechanisms o execu e hei p oposals
wi h some execu ion pla o m. In his sense, only 24 p ima y
s udies include he de elopmen o some p ocess execu ion
pla o m wi h BCT suppo . The es o pape s ha e been
heo e ically p esen ed and do no p o ide e idence on he
use o his kind o execu ion pla o m.
FIGURE 8. Repo ing - de ail o p ocess execu ion pla o m o p ocess
engine co e ed by he p ima y s udies.
Table 12 iden i ies hese echnological solu ions and
Figu e 8 also e eals he deg ee o which he p ocess engines
a e co e ed by he p ima y s udies. Below, da a on p ocess
engines o execu ion echnology pla o ms ha a e used by
he p ima y s udies a e analyzed.
On he one hand, he lowe co e ed execu ion pla o ms a e
BCWMS and Zeebe p ocess engine, which has been p oposed
and used o suppo he execu ion o wo and one p ima y
s udies, espec i ely (see Table 12). Bo h echnological
solu ions co e 9% o all p ima y s udies. Fi s ly, BCWMS
is a blockchain-enabled wo k low managemen sys em o
specially suppo logis ic wo k low models wi h di e en
cus ome s. F om a echnological pe spec i e, his pla o m
is o e ed as an IaaS (in as uc u e-as-a-se ice) pla o m
and has been de eloped wi h Ja a echnology, as well
as Sp ing, Sp ingMVC and MyBa is amewo ks [97].
Secondly, Zeebe [98] is a wo k low engine o mic ose ices
o ches a ion ha is in eg a ed wi h Camunda and i p o ides
wo k low o ches a ion, me ics associa ed wi h hese wo k-
lows, and moni o ing o p ocess ins ance. In his speci ic
case, au ho s [P25] ha e used Zeebe o execu e hei p oposal,
bu his p ocess engine has no been ex ended wi h new
unc ionali ies.
On he o he hand, he second mos used p ocess engine
is Ca e pilla [39]. Ca e pilla is an open-sou ce BPMS wi h
he ampe -p o ess o a blockchain pla o m, and i p o ides
a REST API ha exposes h ee ypes o componen s: BPMN
models; se o unning p ocess ins ances; and API se ices,
i.e. e e ences o sma con ac s used o communica ing
wi h ex e nal se ices. Ca e pilla also p o ides ex ension
mechanisms wha allows o e ol e and inc ease i s ea u es
and unc ionali ies. In his sense, some au ho s ha e used
hese mechanisms o de elop and in eg a e hei p oposals on
Ca e pilla . Speci ically, 7 au ho s use (o ex end) Ca e pilla
o suppo he execu ion o hei p oposals ( ep esen ing 21%
o p ima y s udies). Main con ibu ions o hese 7 p ima y
s udies a e desc ibed in Sec ion V.B.
Finally, ega ding he o he p oposals, hese ones ha e
been ca ego ized as o he p ocess execu ion pla o m
o unspeci ied pla o m ollowing wo c i e ia: (i) when
au ho s do no p o ide echnical e idences o de ailed
echnical in o ma ion abou hei p ocess execu ion pla o m
wi h BCT suppo ; o (ii) when au ho s desc ibe hei
execu ion pla o m, and his one is no a gene al-pu pose
pla o m, bu i is an ad-hoc execu ion pla o m. In his
con ex , 15 p ima y s udies ( ep esen ing 41% o o al) ha e
been included in his ca ego y (see Figu e 8). The mos
popula main echnologies o de elop hese ad-hoc execu ion
pla o ms a e: (i) Ja a, Sp ing amewo k and REST ul HTTP
APIs (which a e used in [P6] [P11] [P15] [P28], among
o he s); and (ii) Py hon (which a e used in [P20]). O he
p ima y s udies also use web echnologies such as Ja aSc ip
and Node.js (e.g., [P11] [P17] [P33]).
VI. CONCLUSION AND OPEN ISSUES
BlockChain Technology (BCT) has eme ged as new ech-
nology and o e s alued cos educ ions by enabling
ansac ions o be execu ed in a pee - o-pee manne di ec ly
be ween en i ies o indi idual use s, wi hou delega ing us
o cen al o icial au ho i ies no equi ing mu ual us
be ween each couple o pa ies. These ea u es ha e led o a
apid and g owing a en ion on BCT wi hin di e en con ex s;
o ins ance, BPM [73]. In ac , i is possible o see he
in e es o public bodies, scien i ic communi y and so wa e
indus ies o know he easibili y and oppo uni ies ha BCT
o e s o imp o e collabo a i e p ocess managemen in a
decen alized manne .
In his con ex , a sys ema ic e iew is p esen ed in his
pape , which iden i ies and analyses he s a e-o - he-a o
esea ch pape s abou collabo a i e BPM in BCT domain.
Fo his pu pose, Ki chenham’s me hod has been ollowed,
wha allows o loca e di e en ypes o p oposals ha
add ess he CBP managemen using BCT. Speci ically,
34 p ima y s udies ha e been iden i ied once he sea ch
p o ocol desc ibed in his pape has been execu ed.
These s udies ha e been also classi ied acco ding o he
ac i i ies o he BPM li ecycle o which hey o e suppo .
Fo his pu pose, Dumas’ BPM li ecycle has been used o
pe o m his classi ica ion. A e ca ying ou his e iew,
open issues ha e been iden i ied.
As men ioned abo e, he BPM ac i i ies ha a e
mainly suppo ed by he p ima y s udies a e, espec i ely,
(Figu e 4.A): (i) p ocess implemen a ion & execu ion (47%),
(ii) p ocess modeling (37%), and (iii) p ocess analysis (16%).
Howe e , i is impo an o men ion ha some p ima y
s udies (such as, [P1], [P2], [P3], [P7] o [P12], among
o he s) ha e no p o ided enough e idence o e i y his
suppo . Howe e , i is possible o conclude ha he cu en
e o s by he scien i ic communi y in in eg a ing BCT in o
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BPM a e a a e y ea ly s age. In addi ion, he e a e also
impo an challenges ha ha e o be add essed o p o ide
e ec i e and adequa e suppo in each ac i i y o he BPM
li ecycle.
On he one hand, he e is a lack o p oposals ha p o ide
suppo o he i s and las ac i i y o he Dumas’ li ecycle,
ha is, A1 - Iden i ica ionand A7 - Adap a ion
ac i i ies ( hese ones a e suppo ed by 0 and 1 p oposals,
espec i ely). This si ua ion is an oppo uni y o inno a ion
o he esea ch communi y o be pionee s in his ield. This
also occu s in A4 - Redesignand A6 - Moni o ing
ac i i ies (bo h ones a e suppo ed by 4% and 1% o p ima y
s udies, espec i ely). Al hough i has been possible o ind
one p ima y s udy ([P1]) wi h suppo o hese ac i i ies,
au ho s only desc ibe good in en ions o hei p oposal, and
i does no p o ide any e idence o his suppo ei he . In his
sense, i is also a ele an oppo uni y o be in es iga ed o
imp o e he modeling o p ocesses using pa e ns.
On he o he hand, i is possible o es ablish some
conclusions and iden i y some ends in p ocess modeling.
A e ca ying ou his e iew, 37 % o p ima y s udies
p o ide suppo o A2 - Disco e y & modelingac i i y.
Speci ically, wo main ends ha e been iden i ied. The i s
one is based on i s own languages; o example, [P1] [P5] [P7]
suppo his ac i i y h ough hei own modeling language,
bu e y li le e idence is p esen ed abou his language.
The second one ([P13], [P15], [P16] o [P17], among o he s)
is based on ex ensions o BPMN (s anda d no a ion) wha
could be conside ed he mos app op ia e op ion o gua an ee
he compa ibili y and in eg a ion o hese p oposals wi h
comme cial p ocess engines ( he as majo i y o which
suppo s BPMN).
Finally, i is possible o obse e ha A3 - Analysis
and A5 - Implemen a ion & execu ionac i i ies a e
also well-suppo ed BPM ac i i ies wi h 16% and 47%,
espec i ely. Rega ding he i s one, we conclude ha six
p ima y s udies suppo his Analysis ac i i y, bu hese
s udies a e jus ocused on e i ying he e aci y o he
p ocess du ing i s execu ion (speci ically, he e i ica ion
o he ansac ions ca ied ou be ween in e -o ganiza ional
ac i i ies). Howe e , he e is a lack o p oposals ha p o ide
pe o mance analysis and da a ans o ma ion when a p ocess
is execu ed. This aspec is ele an in A3 - Analysis
ac i i y. As an opposi e si ua ion, we ha e obse ed ha
he execu ion ac i i y is he mos ac i i y suppo ed by
he p ima y s udies. A e pe o ming his e iew, i is
possible o in e wo cu en ends in his ield. The i s
one is o de elop ad-hoc ools o implemen he au ho s’
amewo ks whe eas he second end consis s o in eg a ing
he p oposals wi h comme cial BPMS (e.g., [P4], [P11],
[P14], among o he s). This las end could be conside ed
he mos app op ia e op ion o gua an ee p ac ical applica ion
in eal en i onmen s since i p o ides compa ibili y and
in eg a ion wi h comme cial p ocess engines. Howe e ,
we ha e obse ed a ele an ac . Many p oposals wi h
execu ion suppo a e o ien ed owa ds speci ic domains
(supply chain p ocesses and indus ial p ocesses, mainly).
I could be, he e o e, in e es ing and impo an o p opose
solu ions ha allow execu ing any ype o p ocess o any
business scope.
Mo eo e , ega ding he ype o p oposal o p ima y
s udies, i is possible o obse e ha he as majo i y a e
concep ual and heo e ical p oposals (71%; Figu e 4.B) on
how BCT could be applied, bu a lo o hem a e amed in o
speci ic con ex s o p ocess managemen (mainly indus ial
p ocesses and supply chain p ocesses). Fu he mo e, he e a e
no me hodologies and measu es ha suppo he de ini ion
and p ac ical de elopmen o hese p oposals. In ac , i migh
be con enien o p opose an on ology o glossa y o de ine
each o hese elemen s, because we ha e iden i ied ha
hese concep s a e indisc imina ely used by many au ho s
( o example, some au ho s may iden i y hei p oposal
an app oach, while in he glossa y o hei pape a e
men ioned as model, o a amewo k, o some hing else).
Anyway, his si ua ion shows mo e weak poin s conce ning
he me hodological ypes (app oaches, model, amewo ks
and me hods), ha is, he e is no au ho s who desc ibes wha
me hodological ea u es is p oposing. This weak desc ip ion
wi hou a clea oadmap (beyond heo e ical and scien i ic
con en ) could end up hinde ing he ans e o knowledge
o he p oduc i e ab ic o socie y, as well as he design and
de elopmen o echnological solu ions ha p o ide p ac ical
suppo in eal en i onmen s.
Despi e his si ua ion, his sys ema ic e iew shows ha
he in e na ional scien i ic communi y has an impo an and
g owing in e es o add ess he imp o emen o p ocess
managemen using BCT. In addi ion, mo e han hal o
p ima y s udies use some ype o esea ch alida ion me hod
(expe imen , case s udies o p oo s-o -concep a e he mos
popula me hods), bu i is possible o obse e mis akes
when hese me hods a e named in esea ch pape s ela ed
o so wa e enginee ing. In o he wo ds, some au ho s
mis akenly use he concep ‘‘case s udy’’ since hey a e eally
desc ibing p ac ical applica ion expe iences. In any case, his
ac is no a bad p ac ice since i is some hing ha also occu s
in o he esea ch ields. I is also possible o obse e ha
he e a e no p ima y s udies wi h unde s andable alida ion
plans, which hinde s he ep oducibili y o he esul s o each
s udy. In his con ex , i could be in e es ing o p omo e o mal
guidelines wi hin scien i ic communi y o alida e esul s o
each esea ch p oposal ha is published. The pu pose is o
imp o e con ibu ions and quali y o in e na ional scien i ic
p oduc ion.
Finally, i is possible o obse e a ac ela ed o he suppo
ools o he applica ion o each p oposal in p ac ice. A e
ca ying ou his sys ema ic e iew, we ha e obse ed ha
mos o he suppo ools a e ini ial p o o ypes. Howe e ,
we ha e been able o iden i y a p o o ype (called Ca e pil-
la [P4] [P32]) ha s ands ou om he es and is eme ging
s ongly because i is in eg a ed wi h Camunda (a comme cial
BPMS). Anyway, his ac is no a disad an age i sel , bu
qui e he opposi e because i allows opening new esea ch
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J. A. Ga cia-Ga cia e al.: Using Blockchain o Imp o e Collabo a i e BPM
lines o design and de elop obus echnological solu ions
soon.
Once his e iew has been comple ed, some esea ch
lines a e going o be explo ed as u u e wo k. Specially,
we will esea ch model-d i en mechanisms o acili a e he
in eg a ion be ween blockchain echnology and collabo a i e
p ocess managemen . The use o model-d i en enginee -
ing pa adigm has ob ained sa is ac o y esul s in o he
a eas [66]–[68] and i could be in e es ing i s applica ion in
his opic o educe cos s and imp o e quali y. Fo example,
we a e explo ing model-d i en ea ly es ing echniques o
app o e and alida e sma con ac s ha a e ied o business
ules on c i ical p ocesses. In his sense, we a e applying
and e alua ing i s esul s on a case s udy ela ed o
he collabo a i e execu ion o so wa e p ocesses be ween
so wa e o ganiza ions. Fu he mo e, we plan o explo e
how o imp o e he de ini ion o aceabili y equi emen s
on collabo a i e p ocess wi hin SoS (Sys em o Sys ems)
con ex . Once his de ini ion has been comple ed, we plan
o e i y and audi hese aceabili y equi emen s (using
blockchain echnology) when hese a i ac s a e manipula ed.
These echniques a e being e i ied in he con ex o
labo a o ies 4.0 and ART (Assis ed Rep oduc i e T ea men )
p ocess [86].
ACKNOWLEDGMENT
This esea ch pape has been ca ied ou by he i s
au ho du ing an in e na ional pos doc o al s ay a School
o Compu e Science, Mad id Open Uni e si y, UDIMA,
Mad id, Spain.
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pp. 18–28, 2017.
JULIAN ALBERTO GARCIA-GARCIA ecei ed
he Ph.D. deg ee in compu e science om he
Uni e si y o Se ille, Spain, in 2015. Since 2008,
he has been a Resea che wi h he Web Enginee -
ing and Ea ly Tes ing G oup (IWT2) pa icipa ed
in Resea ch and De elopmen p ojec s. He is
cu en ly a P o esso wi h he Depa men o
Compu e Languages and Sys ems, Uni e si y o
Se ille. He is also a Lec u e wi h he Uni e si y
o Se ille. He is esponsible o he BPM a ea and
esponsible o secu i y o in IWT2. His cu en esea ch in e es s include
p ope y enginee ing, business p ocess managemen (BPM), model-d i en
enginee ing, and quali y assu ance. He manages se e al echnological
ans e p ojec s wi h companies. He pa icipa es as a membe commi ee
in se e al in e na ional cong esses and jou nals.
NICOLÁS SÁNCHEZ-GÓMEZ ecei ed he
deg ee in compu e enginee ing and he mas e ’s
deg ee in enginee ing and so wa e echnology
om he Uni e si y o Se ille, wi h he knowledge
and skills o people managemen , ICT p ojec
managemen , cus ome managemen and p ac ical
applica ion o compu e enginee ing me hodolo-
gies and echniques. He is cu en ly a Resea che
wi h he Depa men o Compu e Languages and
Sys ems, Uni e si y o Se ille.
F om 1990 o 2001, he wo ked wi h Co i el (Accen u e g oup), whe e
he also ca ied ou managemen and p ojec managemen ac i i ies. F om
2001 o 2009, he de eloped his p o essional ac i i y as a Manage o E e is
Spain, being esponsible o di e en accoun s in bo h he public and p i a e
sec o s. He has de eloped a la ge pa o i s p o essional ca ee in he
echnology and p ocess consul ancy sec o , bo h in he p i a e and public
sec o s. Th oughou mo e han hi y yea s o p o essional expe ience, he has
gone om implemen ing ICT solu ions o supe ising wo k eams, managing
clien s, and leading ICT p ojec s. He is cu en ly a membe o he Web
Enginee ing and Ea ly Tes ing Resea ch G oup. He has a b oad knowledge
o he unc ions and p ocesses ha make up he ac i i y en i onmen o he
sec o s in which he has pa icipa ed. In ecen yea s, he has been coo dina ing
di e en p ojec s o he esea ch g oup, including he P ojec Managemen
O ice o he Minis y o Cul u e (Andalusian Regional Go e nmen ).
DAVID LIZCANO ecei ed he M.Sc. deg ee
in esea ch in complex so wa e de elopmen
and he Ph.D. deg ee in compu e science om
UPM in 2008 and 2010, espec i ely. He is
cu en ly a P o esso and a Senio Resea che wi h
Mad id Open Uni e si y (UDIMA). He is cu -
en ly in ol ed in se e al na ional and Eu opean
unded p ojec s ela ed o EUP, Web Enginee ing,
Pa adigms o P og amming, and HCI. He held
a esea ch g an om he Eu opean Social Fund
unde hei Resea ch Pe sonnel T aining p og am, he Ex ao dina y
G adua ion P ize o bes academic eco d UPM, and he Na ional Accen u e
P ize o he Bes Final-Yea Compu ing P ojec . He has published mo e
han 25 a icles in p es igious in e na ional jou nals. He a ended mo e han
70 in e na ional con e ences.
VOLUME 8, 2020 142335
J. A. Ga cia-Ga cia e al.: Using Blockchain o Imp o e Collabo a i e BPM
M. J. ESCALONA ecei ed he Ph.D. deg ee in
compu e enginee ing wi h in e na ional acc edi a-
ion om he Uni e si y o Se ille, in 2004. She is
cu en ly a Full P o esso wi h he Depa men o
Compu e Languages and Sys ems, Uni e si y o
Se ille. She is also he Di ec o o he Web Engi-
nee ing and Ea ly Tes ing Resea ch G oup. She
has di ec ed se e al Ph.D. heses and published
nume ous pape s in jou nals and cong esses. She
has managed and pa icipa ed in a high numbe o
p ojec s ela ed o he a eas o esea ch. He main esea ch in e es s include
so wa e enginee ing, speci ically o so wa e equi emen s, so wa e ea ly
quali y assu ance and ea ly so wa e es ing. She is also a membe o he
Edi o ial Boa d o JWE and IEEE IT P o essional. She collabo a es as a
Regula Re iewe wi h se e al con e ences and jou nals.
TOMÁS WOJDYŃSKI was an O igina o o he
implemen a ion o he Uni e si y Managemen
Sys ems, in 1999, de eloped and used ill nowa-
days. He s a ed his ca ee in an in as uc u e
deploying and managing. Since 2001, he has
been a Cisco Ne wo king Academy Ins uc o ,
an AWS Ins uc o , since 2018, h ough ope a ing
sys ems (lec u es and labo a o ies in Compu e
Science acul y), con inuing wi h Business P ocess
Managemen No a ion (labo a o ies a g adua e
s udies), and inally in aining on a ious applica ions on-p emise and cloud
echnology. He is cu en ly a Lec u e and a P ac i ione in he ield o IT
echnology. He is also a P o esso wi h he School o Managemen and
Banking, K aków, whe e he is also he Di ec o o he IT Depa men . His
knowledge, also e i ied by ce i ica es (CCNA, Mic oso Technical and
MS O ice, ECDL-A, Agiel PM Founda ion, P ince-2 Founda ion, AWS
Founda ion), is success ully used in his ole o CIO (wi h a s a o a ca ee
as an IT Inspec o a he Zgie z Commune O ice).
142336 VOLUME 8, 2020