Fo liano, Canio; De Be na di, Paola; Rozsa, Zol an; Be ello, Albe o
A icle
Sys ems dynamics esea ch in managemen and
o ganiza ion s udies: O e iew and esea ch agenda
Jou nal o Inno a ion & Knowledge (JIK)
P o ided in Coope a ion wi h:
Else ie
Sugges ed Ci a ion: Fo liano, Canio; De Be na di, Paola; Rozsa, Zol an; Be ello, Albe o (2024) :
Sys ems dynamics esea ch in managemen and o ganiza ion s udies: O e iew and esea ch
agenda, Jou nal o Inno a ion & Knowledge (JIK), ISSN 2444-569X, Else ie , Ams e dam, Vol. 9, Iss.
3, pp. 1-15,
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Sys ems dynamics esea ch in managemen and o ganiza ion s udies:
O e iew and esea ch agenda
Canio Fo liano
a,
*, Paola De Be na di
a
, Zol an Rozsa
b,c
, Albe o Be ello
a
a
Depa men o Managemen , Uni e si y o Tu in, I aly
b
Facul y o Social and Economic Rela ions, Alexande Dubcek Uni e si y o T encin, Slo ak Republic
c
Eu opean Cen e o Business Resea ch, Pan-Eu opean Uni e si y, P ague, Czechia
ARTICLE INFO
A icle His o y:
Recei ed 31 Augus 2023
Accep ed 6 July 2024
A ailable online 13 July 2024
ABSTRACT
This pape p esen s a bibliome ic analysis o he sys ems dynamics (SD) esea ch landscape, d awing on
2,091 documen s om Scopus and Web o Science. This esea ch employs bibliome ic echniques o explo e
he e olu ion o he scien ific communi y o e he pas 50 yea s and assess esea ch p oduc i i y and impac .
Th ough ne wo k analysis, he s udy u he e eals he field’s social and concep ual s uc u es. This
app oach e ealed ou pi o al hema ic clus e s, which we e discussed based on con en analysis: (1) ope a-
ions esea ch and s a egy o mula ion, (2) beha io al s udies and collabo a i e app oaches, (3) dynamic
pe o mance managemen , and (4) sys ems hinking o sus ainable de elopmen . The findings e eal a
di e se and in e disciplina y ajec o y o SD esea ch, eflec ing i s in eg a ion in o a b oad a ay o fields
and i s po en ial o in o m bo h heo e ical and p ac ical applica ions. The pape concludes by p o iding a -
ge ed ecommenda ions o u u e SD esea ch, wi h a pa icula emphasis on enhancing managemen and
o ganiza ional s udies h ough he inco po a ion o SD me hodologies. This includes he po en ial o SD o
influence he design o adap i e s a egies, he use o SD in pa icipa o y policymaking, and he applica ion
o SD ools in p omo ing o ganiza ional lea ning and sus ainabili y.
© 2024 Published by Else ie España, S.L.U. on behal o Jou nal o Inno a ion & Knowledge. This is an open
access a icle unde he CC BY-NC-ND license (h p://c ea i ecommons.o g/licenses/by-nc-nd/4.0/)
Keywo ds:
Sys ems dynamics
Sys ems hinking
Bibliome ics
Ne wo k analysis
Resea ch agenda
JEL classifica ion:
C19
C44
D01
D81
L25
M00
Q01
In oduc ion
In oday’s apidly changing wo ld, whe e echnological, ma ke ,
and en i onmen al complexi ies inc easingly challenge o ganiza-
ions, he adop ion o ad anced analy ical ools has become indis-
pensable (B esciani e al., 2022;Fo liano e al., 2022). Sys ems
dynamics (SD), which is oo ed in he b oade discipline o sys ems
hinking, o e s a powe ul lens h ough which o unde s and and
na iga e hese complexi ies. Unlike adi ional econome ic models,
which o en ely on linea assump ions and s a ic ela ionships, SD
excels in modeling dynamic sys ems cha ac e ized by eedback loops,
ime delays, and nonlinea in e ac ions (Woodside, 2013). In
esponse o hese analy ical sho comings, he e has been a disce n-
ible shi owa d complexi y heo ies and asymme ical echniques
ha be e accommoda e he in ica e dynamics o o ganiza ional
sys ems (Misangyi e al., 2017;Kuma e al., 2022).
As a ounda ional componen o SD, sys ems hinking p omo es an
unde s anding o o ganiza ions and hei en i onmen s as in e con-
nec ed wholes, a he han as collec ions o isola ed pa s (Riccia di
e al., 2020). This holis ic app oach is c i ical o add essing he mul i-
ace ed challenges aced by mode n o ganiza ions, which a e o en
sys emic and canno be e ec i ely unde s ood h ough educ ionis
me hods (Den oni e al., 2021;Mai & Seelos, 2021). SD, as an ex en-
sion o sys ems hinking, enable he explo a ion o how a ious ele-
men s wi hin an o ganiza ion in e ac o e ime, he eby p o iding
insigh s in o po en ial u u e beha io s and ou comes.
SD uniquely combines quali a i e and quan i a i e me hods o
enhance he modeling and analysis o complex sys ems (S e man,
2000;Bianchi, 2016). Quali a i ely, causal loop diag ams help elucida e
he ela ionships and eedback mechanisms wi hin sys ems, o e ing
insigh s in o he unde lying s uc u es and po en ial beha io pa e ns.
Quan i a i ely, s ock and flow diag ams p o ide a means o nume ically
simula e hese dynamics, allowing o de ailed scena io planning and
decision analysis. This in eg a ion o quali a i e and quan i a i e dimen-
sions enables a mo e comp ehensi e explo a ion o sys em dynamics
han is possible wi h adi ional me hods ha ely on s a ic linea
* Co esponding au ho .
E-mail add ess: [email p o ec ed] (C. Fo liano).
h ps://doi.o g/10.1016/j.jik.2024.100512
2444-569X/© 2024 Published by Else ie España, S.L.U. on behal o Jou nal o Inno a ion & Knowledge. This is an open access a icle unde he CC BY-NC-ND license
(h p://c ea i ecommons.o g/licenses/by-nc-nd/4.0/)
Jou nal o Inno a ion & Knowledge 9 (2024) 100512
Jou nal o Inno a ion
&Knowledge
h ps://www.jou nals.else ie .com/jou nal-o -inno a ion-and-knowledge
assump ions o es ima e ne e ec s (Aminullah, 2024;Hasegan e al.,
2018). These capabili ies make SD pa icula ly e ec i e in en i onmen s
whe e adi ional s a is ical models ail o cap u e he essence o
dynamic in e ac ions. Fo hese easons, he adop ion o SD has become
inc easingly p ominen among schola s and p ac i ione s and has
p o en o be c ucial in decision-making ac oss bo h he public and p i-
a e sec o s (Bo gono i e al., 2018;Cosenz & Bi ona, 2020;Fo liano e
al., 2020). In ou con empo a y socie y, whe e complex sys emic issues
unde pin majo socie al challenges, SD is ecognized as an indispensable
ool o add essing “wicked p oblems”—challenges cha ac e ized by
complexi y and esis ance o s aigh o wa d solu ions (Wasieleski e
al., 2021). SD p o ides a powe ul analy ical amewo k capable o
e ealing and managing he dynamic and complex in e ela ions ha
hese p oblems p esen . The inhe en complexi y o such issues necessi-
a es inno a i e app oaches ha su pass adi ional linea analy ical
models, ad oca ing o a sys emic pe spec i e ha is in insic o SD
(G ewa sch e al., 2023). This app oach has been applied ac oss a wide
spec um o domains, e ec i ely add essing pe sis en issues such as
po e y and inequali y (Tey e al., 2020), en i onmen al sus ainabili y
(Ding e al., 2018), esou ces and ene gy managemen (Del Vecchio e
al., 2019;Sun e al., 2017), enhancing public heal h sys ems (Da abi &
Hosseinichimeh, 2020), imp o ing sa e y and educing c ime (Xa ie &
Bianchi, 2020), and ca alyzing educa ional e o ms (Ma uccia e al.,
2020). The b oad applica ion o SD and sys ems hinking in p o iding
insigh ul analyses and os e ing collabo a i e e o s owa d sus ainable
solu ions (Riccia di e al., 2020) unde sco es he need o comp ehen-
si e esea ch o explo e how hese pe spec i es a e implemen ed ac oss
di e se fields, hus con ibu ing o he academic discou se and p ac ical
applica ions o sys ems dynamics.
Second, as highligh ed by G ewa sch e al. (2023), sys ems hinking
and SD ha e been concep ualized in a ious o ms o e he yea s.
They ha e been seen as a comp ehensi e heo y aiming o a gene al
unde s anding o social sciences (Von Be alan y, 2010), a pa adigm
shi om mechanis ic o educ ionis wo ld iews o an in eg a i e,
sys emic app oach (Gladwin e al., 1995), a belie sys em o mindse
change (Senge, 1990), a pe spec i e o heo y−p ac ice engagemen
(Lewis, 1991), o a me hodological app oach o mul ile el, complex
p oblem analysis (Fo es e , 1994; S e man, 1994). This concep ual
di e si y unde sco es he necessi y o syn hesizing hese a ious appli-
ca ions and implica ions, he eby p o iding cla i y and di ec ion o
u u e esea ch wi hin managemen and o ganiza ion s udies. To cap-
u e and illus a e he inc easing end o SD publica ions in his
domain, nume ous a icles ha e a emp ed o sys ema ize SD esea ch.
Howe e , hese e o s ha e o en been confined o specificfields, such
as s a egic managemen (Cosenz & No o, 2016) o pe o mance man-
agemen (Oladimeji e al., 2020); specific con ex s, such as heal hca e
(Da abi & Hosseinichimeh, 2020) o ou ism planning (Seda a i e al.,
2019); o specialized jou nals, such as he Sys em Dynamics Re iew
(To es, 2019). This wo k aims o b oaden his pe spec i e by p o id-
ing a comp ehensi e and inclusi e o e iew o p io wo k using SD in
managemen and o ganiza ion s udies. By conduc ing a bibliome ic
analysis combined wi h science mapping echniques, we seek o
answe he ollowing pi o al esea ch ques ions:
RQ1. Wha ends cha ac e ize scien ific publica ions on sys ems
hinking and SD as e ie able in managemen and o ganiza ion
esea ch a eas?
RQ2. Wha social and concep ual s uc u es cha ac e ize he scien ific
deba e on sys ems hinking and SD in managemen and o ganiza ion
esea ch a eas?
RQ3. How can u u e esea ch on sys ems hinking and SD be de el-
oped in managemen and o ganiza ion esea ch a eas?
By answe ing hese esea ch ques ions, his pape con ibu es o
he esea ch by o e ing a b oad and comp ehensi e sys ema iza ion
o s udies on SD as e ie able in managemen and o ganiza ion s ud-
ies, poin ing a way o wa d o u u e esea ch di ec ions. In addi ion,
p ac i ione s and decision-make s may find a use ul bluep in o p o-
mo e he adop ion and de elopmen o SD models and ools in o ga-
niza ional and communi y-le el con ex s, he e conside ing hei
manage ial and o ganiza ional implica ions.
The emainde o he p esen a icle is o ganized as ollows: Sec-
ion 2 sys ema ically desc ibes he esea ch design and he me hods
employed. Sec ion 3 p esen s he desc ip i e esul s o he bibliome -
ic analysis. Sec ion 4 p esen s he esul s o he ne wo k analysis
and he di e en hema ic clus e s ha eme ged. Based on he p e i-
ous discussions, Sec ion 5 o e s possible u u e esea ch s eams
based on se e al p oposi ions and possible esea ch ques ions.
Finally, Sec ion 6 highligh s he pape ’s implica ions, limi a ions, and
u he de elopmen s.
Resea ch design
In his wo k, a bibliome ic app oach was adop ed o in es iga e
he scien ific p oduc ion ela ed o SD, ollowing he P e e ed
Repo ing I ems o Sys ema ic Re iews and Me a-Analyses (PRISMA)
p o ocol, as in o he sys ema ic li e a u e e iews in he business and
managemen esea ch fields (Be ello e al., 2023;K aus e al., 2022).
Bibliome ics, which ep esen s a subb anch o in o me ics, consis s
o s a is ical echniques aimed a measu ing bo h he p oduc i i y
and impac o scien ific esea ch (Cuccu ullo e al., 2016;Me ig
oe
al.,2015). By adop ing bibliome ic me hods, mo e a icles han adi-
ional li e a u e e iews could be in es iga ed, ensu ing high le els o
igo , anspa ency, and eplicabili y (Daim e al., 2006;Rey-Ma í e
al., 2016). In he cu en s udy, bibliome ics was used o unco e he
unde lying s uc u e o esea ch ela ed o he applica ion o SD p in-
ciples and ools, ocusing a en ion on he business and managemen
domains. Mo eo e , as in o he bibliome ic wo ks (Fo liano e al.,
2021;Secina o & Caland a, 2020), a ne wo k analysis aimed a
depic ing he unde lying s uc u es (i.e., concep ual and social) cha -
ac e izing he esea ch field was pe o med.
Da a collec ion and ex ac ion
A e defining he s udy’s esea ch ques ions, he second s ep o a
bibliome ic s udy is o de e mine which keywo ds mus be used o col-
lec aw da a. Consis en wi h p e ious s udies ela ed o he SD opic
(Da abi & Hosseinichimeh, 2020;Oladimeji e al., 2020;Seda a i e al.,
2019) and he b oad in es iga ion aim o his s udy (Chen & Xiao, 2016),
high-le el keywo ds ela ed o sys ems hinking, SD, and ela ed me h-
ods such as causal loops and s ock and flow diag ams we e used.
Thi d, he da abase o be in es iga ed o collec he necessa y
me ada a ela ed o publica ions on SD had o be selec ed. In he
social sciences, he wo la ges and mos eliable da abases a e Cla i-
a e Analy ics’Web o Science (WoS) and Else ie ’s Scopus (Fo liano
e al., 2021). The e o e, acco ding o he syn ax o he wo da abases,
he s ing was de eloped using wildca ds o unca e he keywo ds
and cap u e singula and plu al a ian s o he sea ch e ms, while i
was possible o sea ch o al e na i es h ough he Boolean ope a o
“OR.”The sea ch was conduc ed in Janua y 2023 o sea ch o docu-
men s’ i les, abs ac s, and keywo ds, e u ning 37,605 esul s o
WoS and 55,241 esul s o Scopus. As shown in Fig. 1, di e en exclu-
sion c i e ia we e applied, excluding s udies no w i en in English o
ha passed h ough a pee - e iew p ocess. To answe he esea ch
ques ions o his s udy, all a icles ha we e no classified in he
“Business”o “Managemen ”domain we e u he excluded (Massa o
e al., 2016;T anfield e al., 2003). Al hough ep esen ing a possible
limi a ion o his s udy, applying hese selec ion c i e ia also allowed
us o pe o m a mo e accu a e compa ison o di e en p oduc i i y
and ele ance me ics. Indeed, o he ele an subdomains conce n
“STEM”disciplines (i.e., science, echnology, enginee ing, and
C. Fo liano, P. De Be na di, Z. Rozsa e al. Jou nal o Inno a ion & Knowledge 9 (2024) 100512
2
ma hema ics) o medicine, whose p oduc i i y and ele ance me ics
a e comple ely di e en om hose o he social sciences. Finally, as
in p e ious sys ema ic li e a u e e iews (Ba is i e al., 2021;Zheng
e al., 2022), he sea ch was es ic ed o only a icles published in
jou nals anked 2 o abo e in he 2021 Academic Jou nal Guide ( o -
me ly he Cha e ed Associa ion o Business Schools, ABS). In his
way, he mos ele an and igo ous a icles could be collec ed and
analyzed. Hence, a e he wo da abases we e me ged, 3404 a icles
we e iden ified, o which 1065 duplica es we e emo ed. Finally, by
analyzing he a icles’ i les and abs ac s while main aining a b oad
pe spec i e, i was possible o es ic he da a collec ion o a final
sample o 2091 eco ds.
Bibliome ic analysis
The final sample o 2091 a icles was analyzed h ough bibliome -
ic analysis. Thus, open-sou ce RS udio so wa e (RS udio Team,
2016) was used o conduc ing a pe o mance analysis o he scien-
ific li e a u e ela ed o he opic, especially he Bibliome ix package
(A ia & Cuccu ullo, 2017), which has been inc easingly adop ed by
esea che s in simila s udies (Fo liano e al., 2021;Secina o & Calan-
d a, 2020) because i enables he c ea ion o a no malized ma ix
comp ising all eco ds ex ac ed om Scopus and he pe o mance o
a bibliome ic analysis. A pe o mance analysis o s udies ela ed o
SD was comple ed by le e aging se e al indica o s buil on me ada a
ela ed o a icles, schola s, coun ies, and jou nals (Massa o e al.,
2016). In his sense, bo h hei p oduc i i y and impac on he scien-
ific communi y could be cap u ed by e alua ing gene al ends cha -
ac e izing his esea ch field in he business and managemen
domains.
Ne wo k analysis
Ano he widely used echnique in bibliome ic s udies is ne wo k
analysis, which maps he unde lying s uc u es cha ac e izing a gi en
esea ch field and hei e olu ion o e ime (Cobo e al., 2012). This
analysis is c ucial o iden i ying esea ch ends and gaps in a gi en
field. Thus, he social and concep ual s uc u es o s udies on SD we e
econs uc ed. No ably, he o me was analyzed by conside ing he
au ho s’coau ho ships. Con e sely, assuming ha keywo ds used
oge he e e o hemes ha a e ele an o each o he and can be
combined in o a hema ic clus e (Van Eck & Wal man, 2009), he la -
e was analyzed by in es iga ing keywo ds’co-occu ences. In pa -
icula , bo h he au ho s’keywo ds and index keywo ds we e used.
Howe e , o do so, he o iginal sample o 6343 di e en au ho s’key-
wo ds (ou o 10,120 in o al) and 7108 di e en index keywo ds
(ou o 16,044 in o al) had o be no malized. Indeed, keywo ds w i -
en in di e en ways bu e e ing o he same e m because o singu-
la /plu al o ms, uppe o lowe case le e s, B i ish/Ame ican English
a ian s, ac onyms, hyphens, and simila i ies had o be econciled.
This analysis was conduc ed using OpenRefine ( e . 3.3), an open-
sou ce ool o iginally de eloped by Google o managing and clean-
ing big da a, and success ully u ilized in se e al simila s udies (e.g.,
Mon oya e al., 2016). Conside ing he size o he da abase, he di e -
en specific algo i hms embedded in he so wa e and designa ed o
da a econcilia ion enabled us o ob ain mo e igo ous and eplicable
esul s han manual analysis. A he end o he da a cleaning phase,
5627 au ho s’keywo ds and 6512 index keywo ds we e e ained.
Thus, he efined da ase was p ocessed in VOS iewe ( e . 1.6.13),
which is a powe ul ool o isualizing he s uc u e and dynamics o
la ge ne wo ks. Indeed, VOS iewe c ea es dis ance-based maps o
ne wo ks based on he simila i y measu e o he nodes (Van Eck &
Wal man, 2010).
Desc ip i e esul s o he bibliome ic analysis
This sec ion p esen s he esul s o he pe o mance analysis,
which was conduc ed by analyzing a icles, au ho s, coun ies, and
jou nals as uni s o analysis. In his way, i is possible o answe RQ1
o his s udy.
The e olu ion o a icles o e ime
S udies on SD s a ed in he la e 1950s, when Fo es e (1958) le -
e aged a eedback iew and a compu e simula ion model o in es i-
ga e complex issues ela ed o o de oscilla ions and subsequen
supply chain managemen . Fo es e ’s e o s in applying SD in indus-
ial con ex s led o his seminal book Indus ial Dynamics (Fo es e ,
1961). Since hose p ominen s udies, esea ch on his opic has been
published o mo e han 70 yea s, and SD s udies ha e been ans-
la ed om he enginee ing and compu e science domains o analyze
di e en esea ch a eas a a ying analysis le els. Addi ionally, a e
indus ial applica ions o SD, Fo es e ocused his a en ion on man-
aging u ban planning issues and applying SD p inciples o guide he
sus ainable de elopmen o economies, which ga e ise o wo o he
seminal books, U ban Dynamics (Fo es e , 1970) and Wo ld Dynamics
(Fo es e , 1971). In his sense, as Fig. 2 shows, s a ing in he la e
1990s, schola s began de o ing inc easing in e es o SD, which
Fig. 1. PRISMA flow diag am showing he di e en phases o da a ex ac ion ac i i y.
C. Fo liano, P. De Be na di, Z. Rozsa e al. Jou nal o Inno a ion & Knowledge 9 (2024) 100512
3
eached i s fi s peak in e ms o he numbe o pape s published.
This inc ease was u he spu ed by he o ma ion o a SD esea ch
g oup a ound Jay W. Fo es e ’sfigu e a he MIT Sloan School o
Managemen . Indeed, some o he mos influen ial schola s om his
g oup ha e eme ged in his esea ch s eam. Fo example, Pe e
Senge, who w o e The Fi h Discipline (Senge, 1990), a cen al book in
di ulga ing sys ems hinking and SD p inciples o he b oad public;
John S e man, who w o e ano he seminal handbook in explaining
SD applied o businesses and o ganiza ional lea ning p ocesses (S e -
man, 2000); and John Mo ec o , who mainly in es iga ed bounded
a ionali y decision-making p oblems (Mo ec o , 2015). In pa icu-
la , Mo ec o played a undamen al ole in sp eading SD in Eu ope
by ein igo a ing he link be ween SD and s a egic managemen
s udies. Al hough schola s’in e es in SD has inc eased o e he
yea s, i has ecei ed significan a en ion only ecen ly, and mo e
han hal o he o al a icles ela ed o his opic ha e been published
only in he las 10 yea s. This end can also be explained by conside -
ing indus y and p ac i ione s’ ecogni ion o he ele ance o hink-
ing sys emically and le e aging SD o add ess complex and dynamic
p oblems. In conclusion, i can be assumed ha SD is s ill an unde de-
eloped esea ch s eam ha o e s plen y o p og ess and s udies
ha can ake place.
To de e mine which a icles mos influenced he scien ific deba e
a ound SD in he in es iga ed esea ch fields, he numbe o ci a ions
ecei ed by each a icle was conside ed. Indeed, ci a ions can ade-
qua ely syn hesize he influence o a publica ion among schola s
(Me ig
o e al., 2015). Table 1 shows he 10 mos ci ed documen s o
he sample, showing he o al ci a ions (TCs) ecei ed by o he pape s
in he da ase as accoun ed o by Scopus and he a e age ci a ions
ecei ed pe yea (TC/Y). Su p isingly, S e man occu s ou imes in
his anking and can be conside ed one o he seminal au ho s in
ad ancing SD knowledge in he business and managemen domains.
Mo eo e , as a e e ence jou nal o SD s udies, i is no su p ising
ha “Sys em Dynamics Re iew”appea s six imes in he lis o he
op en mos influen ial a icles. The mos ci ed pape is a me hodo-
logical one om Ba las (1996) add essing model alida ion issues,
such as s uc u al and beha io al issues, and coun ing 950 ci a ions.
The second mos ci ed a icle comes om Daim e al. (2006), in which
he au ho s mixed bibliome ic echniques and pa en analysis wi h
SD o model he ecosys em su ounding dis up i e echnologies and
o ecas hei u u e di usion. Thi d, i is possible o find a eflec ion
om Fo es e (1994) abou he use ulness o SD models o ad ance
heo y in he ope a ion esea ch field, ollowed by wo concep ual
pape s om S e man (2001,2002), bo h o which aimed a ein o c-
ing he gene al awa eness abou he ele ance o adop ing a sys emic
lens o in e p e complex sys ems, as well as using o mal models o
es decision-make s’men al models and simula ing he implemen-
a ion o di e en policies.
Au ho s and coun ies
A o al o 3552 au ho s om 65 coun ies and 2050 di e en ins i-
u ions con ibu ed o publishing he 2622 a icles in he analyzed
da ase . Thus, by le e aging au ho s as a uni o analysis, hei p o-
duc i i y and impac we e conside ed o in es iga e which schola s
mainly influenced business and managemen s udies on SD. Fig. 3
isually po ays he 15 mos influen ial au ho s, ma ching hei p o-
duc i i y, ep esen ed by he numbe o pape s published each yea
(i.e., bubble size), and impac , ep esen ed in e ms o ci a ions pe
yea ecei ed (i.e., bubble da kness). The TCs pe yea we e p e e ed
o TCs, no o penalize schola s whose ca ee s s a ed in mo e ecen
yea s. The e o e, Saeed, S e man, Richa dson, Ande sen, and Mo e-
c o show he mos ex ended imelines, wi h an unb oken se ies o
publica ions s a ing in he ea ly 1980s o da e. Howe e , conside ing
he h-index, S e man (24), Richa dson (19), and Lane (18) a e among
he mos influen ial au ho s. Indeed, he h-index indica es he mini-
mum numbe o publica ions ci ed a leas h imes by o he schola s
in he da ase (Hi sch, 2005) and is conside ed a well-es ablished and
obus indica o ha simul aneously combines p oduc i i y and ele-
ance (Vanclay, 2007). I is also in e es ing o no e ha Rahmandad
s a ed publishing in ecen yea s (his fi s publica ion in he da ase
was eleased in 2008) bu anks second in e ms o ci a ions pe yea
ecei ed by he 15 mos influen ial au ho s. To o e a mo e p ecise
Fig. 2. Dis ibu ion o publica ions ela ed o SD o e ime.
Table 1
The 10 mos ele an documen s in he da ase .
# Au ho (s) Ti le Yea Jou nal TC TC/Y
1 Ba las Fo mal Aspec s o Model Validi y and Valida ion in Sys em
Dynamics
1996 Sys . Dynam. Re . 950 33.93
2 Daim, Rueda, Ma in, & Ge ds i Fo ecas ing eme ging echnologies: Use o bibliome ics and pa -
en analysis
2006 Technol. Fo ecas . Soc. Change 765 42.50
3 Fo es e Sys em dynamics, sys ems hinking, and so OR 1994 Sys . Dynam. Re . 609 20.30
4 S e man Sys em Dynamics Modeling: Tools o Lea ning in a Complex
Wo ld
2001 Cali . Manage. Re . 549 26.14
5 S e man All Models A e W ong: Reflec ions on Becoming a Sys ems
Scien is
2002 Sys . Dynam. Re . 539 24.50
6 Rahmandad & S e man He e ogenei y and Ne wo k S uc u e in he Dynamics o Di u-
sion: Compa ing Agen -Based and Di e en ial Equa ion Models
2008 Manage. Sci. 456 28.50
7 Dejonckhee , Disney,
Lamb ech , & Towill
Measu ing and a oiding he bullwhip e ec : A con ol heo e ic
app oach
2003 Eu . J. Ope . Res. 437 20.81
8 Vennix G oup model building: ackling messy p oblems 1999 Sys . Dynam. Re . 375 15
9 Wilson The impac o anspo a ion dis up ions on supply chain
pe o mance
2007 T ansp. Res. E: Logis . T ansp. Re . 345 20.29
10 Gino & Pisano Towa d a Theo y o Beha io al Ope a ions 2008 Manu . Se . Ope . Manag 341 21.31
No e: Pape s a e o de ed by o al ci a ions ecei ed by o he documen s in he da ase (TC). The igh column epo s he o al ci a ions ecei ed pe yea (TC/Y).
C. Fo liano, P. De Be na di, Z. Rozsa e al. Jou nal o Inno a ion & Knowledge 9 (2024) 100512
4
iew o he pe o mance indica o s associa ed wi h each schola ep-
esen ed in Fig. 3, he p oduc i i y (i.e., o al publica ions in he da a-
se ) and impac measu es (i.e., TCs ecei ed, h-index, and TCs pe
yea ecei ed) a e also epo ed in Table 2.
Fu he mo e, conside ing he au ho s’a filia ions, bo h coun ies’
p oduc i i y and impac we e analyzed. Hence, he op 15 coun ies,
he e based on hei p oduc i i y, a e plo ed in Fig. 4. In pa icula ,
p oduc i i y was di e en ia ed o cap u e he a e o in acoun y
collabo a ion (i.e., single-coun y publica ion o SCP) and in e coun-
y collabo a ion (i.e., mul iple-coun y publica ion o MCP). Thus,
he SCP includes publica ions wi h all au ho s a filia ed wi h he
same coun y, while he MCP includes publica ions wi h au ho s
om di e en coun ies. Ou o he 65 o al coun ies in ol ed, only
457 documen s we e single-au ho ed (app oxima ely 21.86 % o he
da ase ), meaning ha collabo a ion is a significan aspec o au ho s
adop ing o in es iga ing SD. This assump ion is u he co obo a ed
by Fig. 4, which shows how bo h ad anced economies (e.g., he USA,
he UK, Ge many) and de eloping ones (e.g., China, India, I an)
appea among he mos p oduc i e coun ies and a e all open o mul-
ina ional collabo a ion. In e es ingly, nei he A ican no La in
Ame ican (excep o Colombia) coun ies appea on his lis .
Table 3 epo s he op 15 coun ies in e ms o he o al numbe
o ci a ions ecei ed. The e o e, as shown in Fig. 4, he USA p o es o
be a leade in bo h p oduc i i y and ele ance, ollowed by he UK.
In e es ingly, almos all he mos p olific coun ies a e also he mos
influen ial, wi h only India and Spain gi ing way o Sweden and
G eece.
Jou nals
The 15 mos p olific jou nals in which he da ase ’s documen s
we e published a e p esen ed in Table 4. No su p isingly, Sys em
Dynamics Re iew anks fi s , wi h 495 publica ions (i.e., app oxi-
ma ely one-qua e o he da ase ). Indeed, his jou nal ocuses exclu-
si ely on ad ancing sys ems hinking and SD and hei applica ions in
a b oad ange o a eas (e.g., socie al, echnical, manage ial, and en i-
onmen al). Howe e , i is in e es ing o no e ha he Jou nal o
Cleane P oduc ion also pe o ms e y well in e ms o publica ions
ela ed o SD used as a heo e ical lens and p ac ical app oach o
in es iga ing sus ainabili y- ela ed issues. The analysis o he o he
mos p oduc i e jou nals p esen on he lis shows ha g ea a en-
ion was gi en by schola s o manu ac u ing, indus ial enginee ing,
and ope a ions esea ch, oge he wi h he socio echnical implica-
ions o adop ing a sys emic iew. In addi ion o jou nals’
Fig. 3. Top 15 au ho s in e ms o p oduc i i y and impac .
Table 2
Top 15 schola s in he da ase based on p oduc i i y.
# Au ho NP TC h_index PY_s a TC/Y
1S e man J 34 4238 24 1985 114.54
2Richa dson G 30 2138 19 1985 57.78
3Lane D 30 1444 18 1991 46.58
4Ande sen D 29 1646 16 1988 48.41
5Saeed K 26 273 10 1982 6.82
6Mo ec o J 24 727 15 1983 18.64
7Wols enholme E 22 1044 14 1982 26.1
8Vennix J 20 1280 16 1992 42.67
9Kunc M 18 520 13 2007 34.67
10 Fo d D 17 1032 9 1998 43
11 La sen E 17 368 12 1993 12.69
12 G €
oßle A 17 306 9 2001 14.57
13 Rouwe e E 16 971 13 1996 37.35
14 Rahmandad H 16 907 12 2008 64.79
15 Naim M 15 782 12 1991 25.23
No e: Reco ds a e o de ed by he o al numbe o publica ions in he da ase (TP).
O he pe o mance measu es a e ela ed o ci a ions ecei ed (TC), h-index, fi s
documen e ie ed in he da ase (PY_s a ), and o al ci a ions pe yea ecjei ed
(TC/Y).
Fig. 4. The 15 mos p oduc i e coun ies based on au ho s’a filia ions.
Table 3
The op 15 coun ies we e o de ed by he o al
numbe o ci a ions ecei ed.
# Coun y TC TC/TP
1 USA 22,957 48.33
2 Uni ed Kingdom 10,762 39.57
3 China 5002 25.26
4 Ne he lands 3487 40.55
5 Aus alia 2215 27.01
6 Ge many 2158 24.80
7 Sweden 1829 87.10
8 I aly 1201 23.55
9 G eece 1043 61.35
10 Canada 984 23.43
11 Ko ea 930 22.14
12 Colombia 854 35.58
13 Swi ze land 850 24.29
14 No way 824 21.13
15 I an 605 18.33
Table 4
The 15 mos ele an jou nals a e o de ed by he o al num-
be o publica ions in he da ase .
# Jou nal TP TC
1Sys . Dynam. Re . 495 17,911
2J. Clean. P od. 229 6598
3Eu . J. Ope . Res. 103 4896
4J. Ope . Res. Soc. 138 4313
5Technol. Fo ecas . Soc. Change 97 3107
6In . J. P od. Econ. 52 2027
7Sys . Res. Beha . Sci. 150 2200
8In . J. P od. Res. 66 2104
9J. Cons . Eng. Manag. 26 1048
10 In . J. P oj. Manag. 18 1031
11 J. Manag. Eng. 21 648
12 Decis. Suppo Sys . 16 658
13 Reliab. Eng. Sys 20 507
14 Manage. Sci. 12 1518
15 Sys . P ac . Ac . Res. 27 392
C. Fo liano, P. De Be na di, Z. Rozsa e al. Jou nal o Inno a ion & Knowledge 9 (2024) 100512
5
p oduc i i y, Table 4 also conside s hei impac in e ms o TCs. In
his sense, howe e , he e a e no significan di e ences compa ed
wi h so ing jou nals o hei p oduc i i y, excep in he case o Man-
agemen Science. Indeed, some e y influen ial a icles coau ho ed by
S e man (e.g., Oli a & S e man, 2001;Rahmandad & S e man, 2008;
S e man e al., 1997) ha e been published in ha ou le .
Mo eo e , in Fig. 5, he publica ion ends o he six mos p oduc-
i e jou nals a e shown. In his sense, i can be easily no ed ha ,
excluding he Sys em Dynamics Re iew, he Jou nal o Cleane P oduc-
ion’spublica ion end ou s ands all o he jou nals. On he o he
hand, he Jou nal o he Ope a ional Resea ch Socie y and Sys ems
Resea ch and Beha io al Science shows an inc easing end, ollowed
by he Eu opean Jou nal o Ope a ional Resea ch and he Technological
Fo ecas ing and Social Change.
Discussion o he social and concep ual s uc u es
To comple e he bibliome ic analysis o s udies abou SD in he
business and managemen domains, his sec ion p esen s he esul s
o he ne wo k analysis pe o med o p o ide an o e iew o he
social and concep ual s uc u es cha ac e izing such s udies and hei
au ho s. The e o e, i would be possible o answe RQ2 o his s udy.
Social s uc u e
Conce ning he social s uc u e o s udies ela ed o SD, he co-
occu ences o he op 50 au ho s (i.e., coau ho ship) we e analyzed
(Fo liano e al., 2021). Fig. 6 shows he ne wo k esul ing om apply-
ing he no maliza ion o associa ion s eng h (Van Eck & Wal man,
2009). In pa icula , he g ea e he numbe o documen s au ho ed
by a schola , he g ea e i s node; he g ea e he numbe o docu-
men s coau ho ed by wo o mo e schola s, he close hei bubbles
appea , and he mo e obus he links connec ing hem a e. In e es -
ingly, by applying Lou ain’s clus e algo i hm (Blondel e al., 2008),
Fig. 6 shows he exis ence o 15 clus e s (each defined by a di e en
colo ) among he 50 mos influen ial au ho s. In his sense, mos o
hem ac as isola ed nodes o as niche esea ch g oups, sugges ing
he exis ence o ew influen ial communi ies o schola s. I mus be
no ed ha he la ges SD communi y includes some o he a he s o
his discipline (e.g., John S e man, Da id Ande sen, Geo ge Richa d-
son) and he ounde s o he Sys em Dynamic Re iew, he e e ence
jou nal in his esea ch field. In e es ingly, mos o hem s udied as
Ph.D. s uden s a MIT (such as Saeed o Mo ec o , which appea in a
di e en clus e ), whe e Fo es e s a ed o each SD in he ea ly
yea s o such a discipline.
Mo eo e , conside ing he au ho s’a filia ions, in line wi h he
pe o mance analysis esul s, a high le el o engagemen exis s
a ound SDs wo ldwide. This collabo a ion a e is ep esen ed by
mo e obus lines connec ing coun ies in Fig. 7, while he coun ies’
p oduc i i y is po ayed based on colo in ensi y. Thus, a e y high
collabo a ion a e exis s be ween China and English-speaking coun-
ies (i.e., he USA, Aus alia, Hong Kong, and he UK), which also col-
labo a e wi h each o he . Wi h espec o Eu ope, excep o he UK,
he mos ac i e communi ies can be ound in No way, he Ne he -
lands, and I aly, h ee coun ies whe e some consis en esea ch
g oups on SD a e loca ed (i.e., especially No way, which hos ed he
fi s in e na ional con e ence on SD in 1976). In con as , he e is s ill
a pauci y o engagemen om La in Ame ican (apa om Colombia)
and A ican au ho s.
Concep ual s uc u e
This analysis highligh s he ela ional pa e ns among keywo ds
ha equen ly co-occu wi hin ou da ase , which a e known as co-
Fig. 5. The publica ion ends o he six mos p oduc i e jou nals.
Fig. 6. Coau ho ship analysis depic ing he social s uc u e o he discipline.
Fig. 7. The a e o collabo a ion be ween coun ies, he e based on au ho s’a filia ions.
C. Fo liano, P. De Be na di, Z. Rozsa e al. Jou nal o Inno a ion & Knowledge 9 (2024) 100512
6
occu ences (Van Eck & Wal man, 2009). In ou s udy, we examined
bo h au ho s’keywo ds and index keywo ds, wi h he la e added
by p o essional indexe s and some imes deemed mo e in o ma i e
han he au ho s’keywo ds (Campedelli, 2020). Wi h VOS iewe , we
concen a ed on he 100 mos co-occu ing keywo ds, each occu ing
a leas 18 imes. Using he Lou ain algo i hm wi h a esolu ion
pa ame e o one ac oss 10 i e a ions (Blondel e al., 2008), we iden i-
fied ou dis inc hema ic clus e s, each ep esen ed by a di e en
colo in Fig. 8. The size o a keywo d’s node in he ne wo k signifies
i s equency o use by schola s, and he p oximi y and line hickness
be ween keywo ds indica e hei co-occu ence a es. These clus e s
se e as p elimina y au oma ic s uc u ing acili a ed by VOS iewe ’s
use o he Lou ain algo i hm, a communi y de ec ion me hod ha
op imizes modula i y o pa i ion he ne wo k in o clus e s o
densely in e connec ed nodes wi h spa se connec ions be ween
clus e s. Acco ding o he analysis p esen ed in Fig. 8, he ollowing
ou hema ic clus e s eme ged:
Clus e 1: Ope a ions esea ch and s a egy o mula ion (blue
clus e );
Clus e 2: Beha io al s udies and collabo a i e app oaches (yel-
low clus e );
Clus e 3: Dynamic pe o mance managemen ( ed clus e );
Clus e 4: Sys ems hinking o suppo sus ainable de elopmen
(g een clus e ).
Following o he bibliome ic s udies and sys ema ic li e a u e
e iews (e.g., Be ello e al., 2023;Ma ínez-Climen e al., 2018;
S
anchez-Robles e al., 2023), a e his algo i hmic clus e ing, we con-
duc ed a manual con en analysis o he 30 mos ci ed a icles in each
clus e o ex ac deepe hema ic insigh s. This manual analysis
allowed us o u he un eil how he co e opics defined he concep-
ual s uc u e o he opics unde in es iga ion. The findings om
his de ailed manual examina ion o m he basis o he discussions
p esen ed in he ollowing subsec ions.
Ope a ions esea ch and s a egy o mula ion
The oo s o SD as a esea ch field ha e been deeply connec ed
wi h ope a ions esea ch since i s o igins, when Fo es e (1958) ec-
ognized ha a company’s supply chain managemen could be
desc ibed as a complex sys em cha ac e ized by eedback loops ha
imply ime delays, nonlinea i ies, unin ended consequences, and
subop imal beha io al decisions. Thus, keywo ds in he fi s clus e
eflec how SD has been b oadly adop ed o in es iga e indus ial
issues, such as in en o y con ol, capaci y building adjus men s,
oscilla ions in o de backlog, and ins abili y in ma ke sha es
(Richa dson, 1999;Rahmandad & Repenning, 2016). Fo example,
schola s ha e made g ea e o s o ame he financial and in o ma-
ion flows ha can lead o fluc ua ions in in en o ies (Ba las & Gun-
duz, 2011;Fiala, 2005), which we e fi s concep ualized by Fo es e
(1961) as he amous bullwhip e ec .
In his sense, se e al schola s conside SD simula ion and ma he-
ma ical models o be be e han adi ional linea app oaches o
aming ope a ion managemen issues ha o he wise would be di fi-
cul o iden i y and handle (G €
oßle e al., 2008;Wa en, 2005).
Indeed, SD can be le e aged o explain e e y complex sys em, whose
beha io is in ima ely de e mined by he in e ac ions occu ing
among he a iables cons i u ing i s unde lying s uc u e (S e man,
2000). These a iables a e mainly ela ed o hose esou ces ha can
be conside ed s a egic in he closed bounda ies o he sys em unde
analysis and he capaci y o e ec i ely manage he flows be ween
hem. Fo his eason, se e al SD s udies ha e adop ed he esou ce-
based iew (RBV) o a fi m and i s knowledge-based (knowledge-
based iew, KBV) o in angible-based (in ellec ual capi al-based
iew, ICBV) ex ensions as heo e ical lenses o analyzing success ul
s a egies cha ac e izing a fi m a he han ano he (Johnson, 1999;
Fig. 8. The concep ual s uc u e o he da ase , he e based on co-occu ence keywo ds.
C. Fo liano, P. De Be na di, Z. Rozsa e al. Jou nal o Inno a ion & Knowledge 9 (2024) 100512
7
Kunc & Mo ec o , 2009;Wassme & Dussauge, 2012). Howe e , pos-
sessing he igh esou ces is no enough o spu fi m pe o mance,
and he causal ela ionship be ween esou ce acquisi ion and deple-
ion should also be cap u ed and amed (Bianchi e al., 2010;Kim &
Pa k, 2006;Kunc & O’B ien, 2017). Cu en ly spu ed by he ise o
he Indus y 4.0 pa adigm, no el echnologies such as big da a, cloud
compu ing (Ho mann, 2017;Kochan e al., 2018), and open inno a-
ion s a egies (Yun e al., 2016;Vignie i, 2020) seem o play a unda-
men al ole in guiding such p ocesses and helping o cope wi h hose
egula o y and ma ke -based challenges in exis ing and eme ging
ma ke s (Kobos e al., 2018).
Gi en he abo e, he way manage s and decision-make s espond
o a gi en si ua ion la gely depends on SD models’capaci y o e e
o co ec assump ions. Indeed, hese assump ions guide s a egic
and ope a ional decisions, such as pe cei ing o de s, e alua ing
ma e ial flows and in en o y adjus men s, scheduling p oduc ion,
and hi ing a new wo k o ce. Hence, SD has s ic links wi h esou ce
accumula ion and implemen a ion (Li e al., 2018) and s a egy o -
mula ion (Ga y e al., 2008;Cosenz & No o, 2016) and can ep esen a
p ope app oach o a oid capabili y e osion (Rahmandad & Repen-
ning, 2016). SD modeling can suppo u u e esea ch in unde s and-
ing he nonlinea and delayed e ec s o supply chain policies and
s a egies, he causal ela ionships be ween he business en i on-
men and o ganiza ional capabili ies, and he ole o Indus y 4.0
echnologies in eshaping ope a ions esea ch in dynamic and com-
plex con ex s.
Beha io al s udies and collabo a i e app oaches
The second clus e e eals he in e es o schola s in applying SD
o unde s and how models can a ec people’s beha io al changes
and ice e sa; since ea ly s udies on SD le e aged some insigh s
om psychology and cogni i e sciences (Bendoly, 2014;Bendoly e
al., 2010;Gino & Pisano, 2008). Fo example, Liu e al. (2015) showed
how people who ac in u n-based simula ions a e in ol ed in lea n-
ing p ocesses ha i e a i ely guide hei decisions. The e o e, hey
esponded o o he ac o s’decision ules, al e ing hei beha io and,
a he same ime, he s eady s a e o he sys em, which, in u n, al e s
o he people’s expe iences.
Thus, i a g ea a ie y o SD s udies assume ha manage s and
decision-make s a e a ional agen s, hey o en do no adequa ely
pe cei e he unde lying s uc u e o he complex and dynamic sys-
ems in which hey beha e. Subsequen ly, hey o en su e om mis-
pe cep ion issues, e en i hey ha e o deal wi h simple dynamic
sys ems (Moxnes, 2004;Moxnes & Da idsen, 2016).
Al hough ecen s udies ha e ocused on e ealing he mic o oun-
da ions o p oblem sol e s’and decision-make s’beha io s (Moha-
ghegh & G €
oßle , 2020) and knowledge managemen p ac ices (Chen
& Fong, 2015), hese p oblems a e no new o sys ems dynamicis s.
Indeed, hey we e al eady ecognized in he la e 1980s, when Fo es-
e concep ualized a beha io al heo y endogenously cha ac e izing
ac o s’decision ules by in es iga ing he expe imen al scena io o
i s amous “Bee Dis ibu ion Game”(S e man, 1989). Hence, he ec-
ognized how he sho - e mism and lack o a sys emic pe spec i e o
people in ecognizing he eedback loops cha ac e izing a supply
chain could lead o nonlinea i ies and ime delays ypical o he bull-
whip e ec . Based on his conclusion, se e al a icles ha e in es i-
ga ed mispe cep ion p oblems in expe imen al se ings. Fo example,
Weinha d e al. (2015) in es iga ed how people’s di e en cogni i e
s yles and analy ical o ien a ions a ec hei unde s anding o he
accumula ion and deple ion p ocesses ypical o sys ems cha ac e -
ized by he p esence o s ocks and flows. In his sense, hey confi med
he same esul s as C onin and Gonzalez (2007), who ound ha e en
highly educa ed people o en do no unde s and he basic p inciples
guiding s ock and flow model beha io .
In addi ion, i mus be highligh ed ha he fi s applica ions o SD
adop ed in o ganiza ional se ings we e mos ly le e aging SD
specialis s as consul an s who used o build models wi hou in ol -
ing he impac ed s akeholde s in he p ocess (Cosenz & No o, 2016).
Howe e , hanks o he book “The Fi h Discipline”by Senge (1990),
which shed ligh on he impo ance o sys ems hinking and he ise
o a new public go e nance pa adigm, schola s, and p ac i ione s
s a ed gi ing mo e a en ion o collabo a i e me hods aimed a
model building and alue coc ea ion p ocesses. Indeed, sys ems
hinking se es as a heo e ical amewo k o guiding human ac ions
and men al models o unde s and he big pic u e a ound specific
issues and a oid concen a ing on di ec , sho - e m, and linea
causal ela ionships (Meadows, 1989;Riccia di e al., 2020). Collabo-
a i e app oaches and g oup model building came o he o e as
me hods o in ol e he ele an s akeholde s o de e mined p o-
cesses in aming he eedback loops cha ac e izing he complex and
in e connec ed sys ems unde analysis in which hey a e embedded
(Rouwe e e al., 2002). Thus, in ol ing such ac o s in a p io explo a-
ion o a model’s esul o building a causal loop o s ock and flow
diag am would help un angle he complexi y o specific sys ems and
aise SD models o ull po en ial, hence aking ca e o hei di e en
in e es s and logics, which o en compe e wi h each o he (Kopainsky
e al., 2014;Fo liano e al., 2020). In his ein, by le e aging ins i u-
ional heo ies, adap i e comanagemen , and he body o knowledge
on he (new) commons, Riccia di e al. (2020) ecen ly p oposed a
concep ual causal loop diag am aimed a o e ing a pa icipa o y SD
modeling me hod o o e come he agili ies aised when common
esou ces a e a s ake. The e o e, in ol ing manage s, decision-mak-
e s, p ac i ione s, o e en ci izens h ough pa icipa o y echniques
and g oup model building could ep esen a c i ical s ep in achie ing
sha ed consensus behind SD models and di e en s akeholde s’
unde s anding o he sys em o in e es , e ec i ely guiding beha -
io al change p ocesses.
The insigh s om his clus e sugges many ways o ad ance SD
esea ch in managemen and o ganiza ion s udies. SD mus be used,
o ins ance, o include/mi iga e human biases in complex decision-
making p ocesses, o explo e he dynamics o sense-making p o-
cesses in e ms o s akeholde s impac ed, and o shed ligh on he
in e play be ween indi iduals, o ganiza ions, and communi ies in
alue coc ea ion p ocesses.
Dynamic pe o mance managemen
As wi h he o he hema ic clus e s, pe o mance managemen
has also been a opic ha has cha ac e ized SD s udies since he
o igins o his esea ch field. To o e come he di ficul ies ela ed o
applying SD p inciples by sol ing di e en ial equa ions and using
sp eadshee s, he de elopmen o simula ion so wa e and com-
pu e -aided modeling is a c i ical s ep (Richmond, 1994). Indeed,
he possibili y o g aphically ep esen ing sys em a che ypes,
causal loop diag ams, and s ock and flow models is undamen al o
disclosing SD o a b oade public han specialis s and ma hema ics
(Wols enholme, 2003). Following his idea, schola s s a ed build-
ing “managemen fligh simula o s” o applying SD me hods o
business managemen in he 1980s (Fo es e , 2007;S e man,
2014). Th ough use - iendly dashboa ds and key pe o mance
indica o s, hese ools p o ide inexpe ienced use s wi h an in e -
ac i e lea ning en i onmen ha can be used o design and es
di e en policies, e alua e di e se scena ios, and inc ease hei
accep ance o complex SD models (Bianchi & Bi ona, 2000;Da id-
sen, 2000;G €
oßle e al., 2000). Con e sely, in o he cases, i was
ound ha pa icipan s’pe o mances can be le e aged by in ol -
ing hem in a p io explo a ion o he model, e en i i is no in i s
final o m (Kopainsky e al., 2014). Whe eas i s unde lying s uc-
u e cha ac e izes he beha io o a sys em, o ganiza ional pe o -
mance esul s om ha beha io . Thus, unde s anding and
communica ing how ha beha io is ela ed o a sys em’sp o-
cesses and ac i i ies ep esen c i ical s eps o ensu ing pa ici-
pan s’pe o mance (Schoenbe g e al., 2020).
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