Beyond he combus ion mo o : A MCDM-based app oach o analyse he
al e na i e uel ehicle decision om he cus ome s’poin o iew
Da id Boix-Co s
a,*
, Alessio Ishizaka
b
, Albe de la Fuen e
a,**
, Pablo Pujadas
c,d
a
Depa men o Ci il and En i onmen al Enginee ing, School o Ci il Enginee ing o Ba celona (ETSECCPB), Poly echnic Uni e si y o Ca alonia, UPC, C/ Jo di Gi ona
1-3, Ba celona, 08034, Spain
b
Depa men o In o ma ion Sys ems, Supply Chain and Decision Making, NEOMA Business School, 1 Rue du Ma ´
echal Juin - BP 215, Mon -Sain -Aignan Cedex, 76825,
F ance
c
Depa men o P ojec and Cons uc ion Enginee ing, School o Indus ial Enginee ing o Ba celona (ETSEIB), Poly echnic Uni e si y o Ca alonia, UPC, A . Diagonal
647, Ba celona, 08028, Spain
d
G oup o Cons uc ion Resea ch and Inno a ion (GRIC), C/ Colom, 11, Ed. TR5, Te assa, Ba celona, 08222, Spain
ARTICLE INFO
Handling Edi o : Gio anni Baiocchi
Keywo ds:
Sus ainable mobili y
Low-ca bon anspo a ion
Emission educ ion
MCDM
MIVES
Policy ecommenda ions
ABSTRACT
In he anspo a ion sec o , one o he mos pollu ing indus ies, he adop ion o al e na i e uel ehicles is
essen ial o educing ca bon emissions and achie ing sus ainabili y goals ou lined by in e na ional bodies, such
as he Uni ed Na ions F amewo k Con en ion on Clima e Change. Despi e hei c i ical ole, he e is a signi ican
lack o scien i ic s udies ha ocus on di ec consume opinions ega ding ehicle selec ion by uel ype, e en
wi h he upcoming Eu opean egula ions poised o signi ican ly change he ehicle ma ke . This a icle p esen s a
no el amewo k o s udy consume pe cep ions ega ding he choice o ehicles wi h di e en uel ypes,
conside ing hei pe spec i es on all dimensions o sus ainabili y. The amewo k is adap able o any ci y and
inco po a es he opinions o local ci izens o de e mine ele an indica o s and hei weigh s. To accoun o he
inhe en unce ain y wi hin hese indica o s, Mon e Ca lo simula ions and disc e e p o iles we e ca ied ou . The
p oposed amewo k is applied o he ci y o Ba celona as a case s udy. By ac i ely in ol ing ci izens in he
decision-making p ocess, aluable insigh s a e gained, leading o ac ionable ecommenda ions o bo h he
p i a e sec o and public adminis a o s. These ecommenda ions a e aimed o add ess he p ima y conce ns o
po en ial cus ome s and p omo e he adop ion o al e na i e uel ehicles, aiding in he o mula ion o policies
and s a egies ha can e ec i ely mi iga e emissions and suppo he ansi ion o a low-ca bon economy. The
esul s show ha o e he h ee pe iod, con en ional uel ehicles (CFV) a e he mos p e e ed, e en when only
second-hand CFV a e pe mi ed.
1. In oduc ion
The wo ld is g appling wi h one o i s mos o midable challenges:
clima e change. Unan icipa ed loods, ex ended d ough s esul ing in
wa e es ic ions and hampe ed ood p oduc ion, o soa ing hea wa es
ele a ing he isk o wild i es a e jus a ew o he c i ical si ua ions he
wo ld is cu en ly con on ing. I has long been ecognized ha a p i-
ma y d i e o his clima e change is he excessi e CO
2
emissions
s emming om human ac i i ies (Koze a e al., 2024;Mac Dowell e al.,
2017), unc ioning as a po en g eenhouse gas (GHG). Among he con-
ibu o s o GHG emissions, he anspo a ion sec o holds he a he
unen iable dis inc ion o being he o emos con ibu o , esponsible o
27% o o al emissions (US EPA, 2022). The e o e, i comes as no su -
p ise ha nume ous au omobile manu ac u e s and scien is s ha e
dedica ed subs an ial esou ces and ime o he esea ch and de elop-
men o no el al e na i e uels designed o cu ail CO
2
emissions (Seol
e al., 2022).
Fo ins ance, ce ain a ian s o adi ional ossil uels, such as oil
and gas, ha e been enginee ed h ough p ocesses based on lique ac ion
and comp ession, esul ing in lique ied pe oleum gas (LPG), lique ied
na u al gas (LNG), and comp essed na u al gas (CNG). The use o hese
uels in al e na i e uel ehicles (AFVs) has been ex ensi ely examined,
p ima ily due o hei po en ial o educe bo h cos s and GHG emissions
compa ed o adi ional uels (B zezi´
nska, 2019;Dima a os e al., 2020;
* Co esponding au ho .
** Co esponding au ho .
E-mail add esses: [email p o ec ed] (D. Boix-Co s), [email p o ec ed] (A. Fuen e).
Con en s lis s a ailable a ScienceDi ec
Jou nal o Cleane P oduc ion
jou nal homepage: www.else ie .com/loca e/jclep o
h ps://doi.o g/10.1016/j.jclep o.2024.144564
Recei ed 4 Sep embe 2024; Recei ed in e ised o m 3 Decembe 2024; Accep ed 21 Decembe 2024
Jou nal o Cleane P oduc ion 486 (2025) 144564
A ailable online 24 Decembe 2024
0959-6526/© 2024 The Au ho s. Published by Else ie L d. This is an open access a icle unde he CC BY license (
h p://c ea i ecommons.o g/licenses/by/4.0/ ).
Sa ickis e al., 2021). Howe e , despi e hese ad an ages, ossil uels
and hei de i a i es all sho o aligning wi h he long- e m en i on-
men al sus ainabili y goals se by go e nmen s and socie y, which
highligh s he need o solu ions ha deli e subs an ial and las ing
educ ions in GHG emissions (Díaz-T ujillo e al., 2019;Swanson e al.,
2020). Among o he al e na i es, bio uels de i ed om biowas e ha e
a ac ed signi ican a en ion, al hough hei en i onmen al impac
a ies depending on li e-cycle analyses (Hoekman, 2009). Despi e his,
some o hem, such as hyd o ea ed ege able oil (HVO), ha e been
igo ously e alua ed o hei sui abili y in AFVs (Dimi iadis e al.,
2018). Ne e heless, wo al e na i e uels ha e long cap u ed he
a en ion o go e nmen s, socie y, and esea che s due o hei abili y o
p oduce ze o emissions a he poin o consump ion. The i s is elec-
ici y, ini ially inco po a ed in o combus ion ehicles as hyb id ehicles
(ˇ
Ceˇ
o ský and Mindl, 2008a;Hollins, 2008;Ka im and Shahid, 2018).
This de elopmen led o ull elec ic ehicles, which achie ed subs an-
ial emission educ ions (Michael e al., 2022;Pe o i´
c e al., 2020). The
second is hyd ogen, which p oduces only wa e as a by-p oduc when
used as an AFV uel (Babadzhano a e al., 2022;JinKun, 2021).
This di e se a ay o uels has b oadened consume op ions, signi -
ican ly in luenced by he de elopmen o inno a i e uel echnologies, a
choice ha has expanded signi ican ly wi h he de elopmen o inno-
a i e uel echnologies. Howe e , he Eu opean Union (EU) egula ions
in oduced in 2022 ep esen a u ning poin ha ampli ies his shi .
The Eu opean Union (EU) execu i e body, he Eu opean Commission,
p oposed a 55% educ ion in CO
2
emissions om new ca s by 2030
compa ed o 2021 le els, and a comple e elimina ion o CO
2
emissions
om new ehicles by 2035, a p oposal ha was accep ed by he Eu o-
pean Pa liamen . These measu es will undamen ally impac he
decision-making p ocess o all consume s, as adi ional op ions like
combus ion-engine ehicles will g adually be emo ed om he ma ke :
by 2030, ce ain ossil uel ehicles will no longe be a ailable, and by
2035, he sale o new ca s equipped wi h combus ion engines will be
p ohibi ed (Commission, 2022). In pa allel, hese egula ions a e ex-
pec ed o d i e he c ea ion o new pu chase incen i es o AFVs and
policies aimed a educing he inancial bu den on consume s, such as
ax educ ions, o encou age he ansi ion o mo e sus ainable op ions.
As a esul , consume s a e now compelled o ac i ely engage wi h his
decision-making p ocess, which was once p ima ily d i en by con e-
nience o adi ion.
In his new scena io, unde s anding he decision-making p ocess o
consume s ega ding he ype o ehicle hey will pu chase has become
an essen ial subjec o s udy. Consume opinions and pe cep ions play a
c ucial ole in his p ocess, as hey can signi ican ly in luence ma ke
ends and he adop ion o AFVs. By ho oughly s udying hese opinions,
bo h businesses and go e nmen s can e ec i ely p omo e he adop ion
o sus ainable ehicles and iden i y key a eas o u he in es men . Fo
ins ance, as he phase-ou o combus ion engine ehicles p og esses,
consume s migh lean owa ds acqui ing AFVs, encou aged by go e n-
men al emphasis and suppo . Howe e , consume conce ns and ap-
p ehensions, such as doub s abou ehicle au onomy, he a ailabili y o
cha ging in as uc u e, and gene al unce ain ies in he AFV sec o ,
migh push hem owa ds he second-hand ma ke ins ead. By unde -
s anding hese consume pe spec i es, s akeholde s can add ess hese
issues mo e e ec i ely, he eby acili a ing a smoo he ansi ion o
sus ainable anspo a ion and ensu ing a ge ed in es men s ha mee
consume needs and p e e ences.
In his con ex , his pape endea ou s o pu o h a pionee ing
mul iple-c i e ia decision-making (MCDM) app oach oo ed in a no el
modi ied e sion o MIVES (Spanish ac onym: Modelo In eg ado de
Valo pa a una E aluaci´
on Sos enible, in English: Value Model o he
E alua ion o Sus ainabili y) o sc u inise, o he i s ime, po en ial
consume p e e ences ega ding ehicle pu chases in ligh o he
e ol ing Eu opean egula o y landscape. The me hod inco po a es he
cus ome ’s pe spec i e on he h ee pilla s o sus ainabili y: economic,
en i onmen al, and social ac o s. In pu sui o his objec i e, a ious
ime ames we e examined o assis consume s in hei decision-making
p ocesses while p o iding aluable insigh s o esea che s, au omobile
manu ac u e s, and go e nmen al bodies seeking a deepe unde s and-
ing o consume pe spec i es amids he changing legisla i e
amewo k.
The es o he pape is o ganised as ollows: he nex sec ion p esen s
a ehicle cus ome p e e ence analysis li e a u e e iew. Sec ion 3de-
ines he p oblem wi h i s assump ions, limi s and delimi a ions. Sec ion
4explains in de ail he p oposed me hod. Sec ion 5illus a es he
echnique wi h a case s udy. The inal sec ion gi es a gene al conclusion.
2. Li e a u e e iew
In he li e a u e, nume ous analyses o al e na i e uel-based ehicle
sys ems a e a ailable. While many s udies concen a e on he echnical
aspec s o AFVs, such as enhanced ba e ies (Daems e al., 2024), com-
pa isons o ai oxic emissions (Wineb ake e al., 2000;Wineb ake e al.,
2001), ozone educ ion (C. C. Chang e al., 2001), deca boniza ion cos s
(Kim e al., 2024), o disc epancies be ween emissions and consump ion
in a labo a o y and eali y en i onmen (Ka abasoglu and Michalek,
2013), his manusc ip ’s objec i e is o examine cus ome beha iou .
Thus, his sec ion ocuses on he ac o s in luencing his beha iou , a
opic ha has ecei ed ex ensi e a en ion om a ious pe spec i es.
Fo ins ance, some s udies ha e del ed in o he impac o public
policy. Kei h e al. (2020) analysed he di usion o AFV echnologies
and cus ome oppo uni ies, discussing bo h chances and exis ing ba -
ie s. These ba ie s encompass sha ed mobili y, ehicle pla o ms,
in as uc u e deploymen s a egies, and policymaking. Mohammed
e al. (2020) sc u inized his di usion h ough he adop ion o AFV
lee s, explo ing he ba ie s and enable s o adop ion by i ms. O he
au ho s ha e concen a ed on household ehicle choices in ela ion o
a ious uel axes and how cus ome s pe cei e hem (De Bo ge and
Rouwendal, 2014), he policy implemen a ion cos o AFVs (Zeng e al.,
2021), uel e iciency (Schou en e al., 2014), o p e e ence analysis
h ough su eys (Ba ley e al., 2004). They concluded ha AFVs equi e
u he in as uc u e de elopmen and economic incen i es o enhance
hei adop ion. Rega ding hese incen i es, So o e al. (2018) examined
public policies in Colombia o amelio a e cus ome a i udes and pe -
cep ions ega ding AFV adop ion, ul ima ely concluding ha mo e
in as uc u e and awa eness policies a e impe a i e. Sang and Bekhe
(2015) also analysed policies, ob aining a sensi i e guideline o policy
o mula ion and ma ke ing ecommenda ions o enhance AFV usage
h ough a mul iple eg ession model ha employs p i a e d i e da a.
These indings align wi h b oade li e a u e e iews (Co man e al.,
2017;Liao e al., 2017), which emphasize he impo ance o in a-
s uc u e and policy incen i es, such as ax educ ions and cha ging
in as uc u e de elopmen , as key d i e s o adop ion.
O he s udies ha e aken a mo e speci ic ocus on analysing he
adop ion ac o s o pa icula AFVs. Li e al. (2017) conduc ed a
comp ehensi e e iew o elec ic ehicle adop ion and ca ego ized hese
ac o s in o h ee main g oups: demog aphic, si ua ional, and psycho-
logical. Demog aphic ac o s pe ain o indi idual o amily cha ac e -
is ics, including age and educa ion (Ca ley e al., 2013;P akash e al.,
2014). Si ua ional ac o s a e associa ed wi h ehicle cha ac e is ics,
such as cos (Dumo ie e al., 2015), d i ing ange (Egbue and Long,
2012), o GHG emissions (Noppe s e al., 2014). Finally, psychological
ac o s a e di ec ly linked o cus ome s’a i udes and pe cep ions and
a ec he decision p ocess. Fo example, ange anxie y, a signi ican
psychological ba ie , has been ho oughly in es iga ed. Pe ec e al.
(2020) demons a ed ha s a egically expanding cha ging in as uc-
u e could alle ia e his conce n, pa icula ly i designed o mimic he
con enience o adi ional gas s a ions, e en i i emains as a challenge
in u al a eas (S eadman and Higgins, 2022). Simila ly, Ullah e al.
(2022,2023) and S aka e al. (2020) emphasized how insu icien
cha ging in as uc u e c ea es a eedback loop ha discou ages adop-
ion, unde sco ing he u gency o obus deploymen s a egies. Egbue
D. Boix-Co s e al. Jou nal o Cleane P oduc ion 486 (2025) 144564
2
and Long (2012) e ealed ha cus ome s’conce ns abou AFV ba e y
ange, p ice, and pe o mance ou weighed sus ainable cha ac e is ics in
signi icance, a ca ego iza ion which was subsequen ly employed by Jia
(2019) o examine AFV adop ion in he Uni ed S a es o Ame ica
h ough a no el p edic ion model aimed a de e mining AFV pene a ion
in each s a e. In his con ex , Doma chi and Che chi (2024) used a
c oss-nes ed logi model o p o e ha uel ype choice is highly co e-
la ed wi h ca segmen choice, wi h s onge co ela ions wi hin he
same segmen and weake co ela ions be ween segmen s sha ing he
same uel ype. Thei indings sugges ha p omo ing cleane uel al-
e na i es may be mo e e ec i e when conside ing subs i u ional pa -
e ns, while also highligh ing he c i ical ole o ope a ing cos s in
in luencing consume decisions. Meanwhile, Qian and Soop amanien
(2011) u ilized an online su ey o cap u e Chinese cus ome p e e -
ences, no ing ha mos s udies ely on empi ical ac o s wi hou di ec ly
engaging d i e s. The c i ical ac o s iden i ied in hei s udy included
cos , unning expenses, he a ailabili y o cha ging acili ies, au onomy,
and incen i es. Psychological ac o s ha e also been u he explo ed by
Pamidimukkala e al. (2023), who highligh ed how i s -hand expe i-
ences wi h elec ic ehicles can posi i ely in luence pe cep ions by
al e ing s e eo ypes and demons a ing bene i s such as low noise
emissions and accele a ion pe o mance, inally de i ing 63 ac o s
in luencing adop ion, g ouping hem in o echnological, psychological,
and con ex ual ca ego ies (Pamidimukkala e al., 2024). Among hose,
limi ed d i ing ange, leng hy cha ging imes, and high pu chase p ices
we e he mos signi ican ba ie s, wi h en i onmen al bene i s ac ing as
key mo i a o s o adop ion. In his ein (Co man e al., 2017), no ed
ha inc easing he isibili y o elec ic ehicles on he oad could
enhance awa eness and in e es .
These cus ome p e e ences and adop ion ac o s ha e also ound
applica ion in a ious MCDM me hods. Fo ins ance, he P e e ence
Ranking O ganiza ion Me hod o En ichmen E alua ion (PROM-
ETHEE) has been employed o assess di e en uel-based ehicles in
oad anspo a ion (Mohamadabadi e al., 2009). The In e al Tech-
nique o O de o P e e ence by Simila i y o Ideal Solu ion (TOPSIS)
has been u ilized o compa e AFVs in oad anspo al e na i es,
conside ing di e en li e cycle emissions and cos scena ios wi hin each
in e al (S eimikiene e al., 2013). This concep was u he e ined by
inco po a ing uzzy TOPSIS o add ess unce ain y (Liang e al., 2019) in
anking AFVs wi h espec o sus ainable anspo a ion. Wi h he same
objec i e, o he me hods like hie a chical hesi an uzzy linguis ic se s
(Ya uz e al., 2015) and he Decision-Making T ial and E alua ion
Labo a o y (DEMATEL) me hod in combina ion wi h an Analy ical
Ne wo k P ocess (ANP) de i ed om expe opinions (D. S. Chang e al.,
2015) ha e been u ilized. Mo e ecen ly, he uzzy Full Consis ency
Me hod (FUCOM-F) and he Neu osophic Fuzzy Measu emen Al e -
na i es and Ranking acco ding o he COmp omise Solu ion (MARCOS)
ha e been join ly employed o p io i ize six di e en AFVs in he Uni ed
S a es, ho oughly in es iga ing and selec ing he d i e s behind he
decision (Pamuca e al., 2021).
In summa y, he s udies and p oposed me hods men ioned abo e
ha e add essed a ious issues and made signi ican con ibu ions o
unde s anding he ac o s in luencing AFV adop ion by cus ome s.
Howe e , he e a e ce ain limi a ions in exis ing me hods. Fi s , many
exis ing s udies ocus on s a ic analyses ha do no adequa ely accoun
o he dynamic na u e o e ol ing egula o y and echnological land-
scapes. Second, psychological ba ie s, such as ange anxie y o con-
ce ns o e cha ging in as uc u e a ailabili y, a e o en examined in
isola ion a he han being in eg a ed holis ically wi h o he ac o s.
Thi d, he implica ions o new Eu opean egula ions, such as he 2030
educ ion a ge s and he 2035 ban on combus ion-engine ehicles,
emain unde explo ed. These egula ions a e likely o signi ican ly al e
ma ke dynamics, including echnology a ailabili y, in as uc u e
de elopmen , and consume p io i ies. Finally, many me hodologies
ely hea ily on expe -d i en e alua ions, which may o e look he
di e se expe iences, p e e ences, and psychological conside a ions o
ac ual consume s. This pape aims o add ess hese gaps by p oposing a
comp ehensi e amewo k ha in eg a es mul iple cus ome ac o s,
while explici ly conside ing he impac s o e ol ing egula ions h ough
mul iple imespans.
3. P oblem de ini ion
As ou lined in he in oduc ion, nume ous a ian s o con en ional
uels, speci ically oil and gas, ha e been de eloped. Concu en ly, he
adop ion o AFVs has inc eased as esea ch in o hei u iliza ion has
ad anced. In his s udy, i e al e na i es conce ning di e en uel
ehicle op ions we e de ined:
1. Con en ional uel ehicles (Diesel/Gasoline, CVFs): These ehicles
ep esen mos con empo a y au omobiles equipped wi h in e nal
combus ion engines (ICE). These uels gi e ise o subs an ial GHG
emissions, se ing as he p ima y impe us o he Eu opean
p ohibi ion.
2. Bio uel ehicles (BFVs): Bio uels a e de i ed om biomass, and a e
employed in an ICE. The mos p e alen bio uels include bioe hanol,
an alcohol syn hesized om biomass ia e men a ion, and biodiesel,
which is p oduced om oils and a s h ough a anses e i ica ion
p ocess. These uels can be inco po a ed in o con en ional uels in
a ious concen a ions, deno ed as EX o BX. He e, E and B deno e
bioe hanol and biodiesel, espec i ely, while X signi ies he bio uel
pe cen age wi hin he blend.
3. Hyb id elec ic ehicles (HEVs): These ehicles employ an elec ic
mo o (EM) in andem wi h an ICE o mi iga e GHG emissions, p i-
ma ily o sho e o mode a e dis ances. They u ilize a egene a i e
b aking sys em o ha ness elec ici y om he kine ic ene gy
gene a ed by he ehicle du ing ICE ope a ion, subsequen ly s o ing
i in a ba e y. Addi ionally, he e a e plug-in hyb id elec ic ehicles
(PHEVs), which can connec o he powe g id o echa ge hei EM.
4. Elec ic ehicles (EVs): EVs a e p opelled by elec ic mo o s, de i ing
hei powe om ene gy s o ed in onboa d ba e ies. While sola
panels can be u ilized o cha ge hese ba e ies, he mos p e alen
cha ging poin s a e ypically ound a p i a e esidences o se ice
s a ions.
5. Hyd ogen ehicles (HyVs): HyVs ha ness he chemical ene gy s o ed
in hyd ogen uel o powe gene a ion. These ehicles can ea u e an
EM ha de i es elec ici y om he chemical eac ion be ween
hyd ogen and oxygen in a uel cell, o hey may employ an ICE
uelled by hyd ogen.
Ha ing ou lined he conside ed al e na i es, i is essen ial o p esen
he assump ions, delimi a ions, and limi a ions o he p oblem. The as-
sump ions made in his s udy pe ain o he po en ial changes ha may
occu in go e nmen al policies, ma ke dynamics, and in as uc u e
acili ies:
1. Dynamic esul s: The newly accep ed EU egula ion s a es a educ-
ion o 55% in CO
2
ca emissions in 2030 and 100% in 2035
(Eu opean Commission, 2021). Hence, i is assumed ha hese yea s
se e as he dema ca ion poin s o dis inguishing among h ee
dis inc pe iods: p e-2030, spanning om 2030 o 2035, and
pos -2035.
2. Second-hand ma ke : The au ho s assume ha , in ligh o he EU
egula ions, ce ain cus ome s migh op o he seconda y ehicle
ma ke should newly a ailable ehicles ail o align wi h hei e-
qui emen s. S a ing in 2035 and beyond, i is pos ula ed ha all
non-ze o emission ehicles (CFVs, BFVs, PHEVs) can solely be ac-
qui ed in he second-hand ma ke .
3. In as uc u e di e ences and cus ome p e e ences: Gi en he p e-
sumed dispa i ies in AFV in as uc u e ac oss a ious geog aphic
egions, he p oposed me hodology should accommoda e hese
D. Boix-Co s e al. Jou nal o Cleane P oduc ion 486 (2025) 144564
3
a ia ions based on he ci y o o igin o each cus ome . Conse-
quen ly, he p oposed me hod should be applied indi idually o
each ci y.
Conside ing ha ce ain p oposed al e na i es in ol e mul iple uels
and ha an MCDM me hod migh in ol e a subs an ial se o c i e ia,
his s udy has ou lined he ollowing delimi a ions:
1. Fossil uel a ian s: I is impo an o no e ha CNG, LPG, and LNG
a e no included as al e na i es in his s udy. The au ho s conside
ha hese echnologies a e unlikely o unde go u he de elopmen
due o hei ossil uel o igins and high GHG emissions. Ins ead, hey
an icipa e ha hese echnologies, i used a all, will be g adually
eplaced by low-GHG emission bio uels. The e o e, hese a ian s a e
no included in he s udy.
2. Bio uel a ian s: Only pu e bio uels, E100 and B100, a e conside ed.
Howe e , i acknowledges ha he e could be si ua ions whe e a
signi ican dispa i y exis s in bioe hanol o biodiesel in as uc u e.
In such cases, he analysis will employ he p edominan bio uel
a ailable in he espec i e coun y o egion.
3. Hyb id elec ic a ian s: This s udy speci ically ocuses on PHEVs as
he chosen hyb id al e na i e. This choice is mo i a ed by he simi-
la i y o PHEVs o con en ional ehicles and he po en ial o
enhanced elec ic cha ging in as uc u e o PHEVs.
4. Ca cha ac e is ics: The s udy’s p ima y ocus is on analysing
cus ome beha iou ega ding uel selec ion, a he han del ing in o
speci ic ehicle ypes o classes. Consequen ly, o indica o s
equi ing de ailed ehicle in o ma ion, da a will be sou ced ei he
om exis ing da abases o om he bes -selling ca s in he egion o
accu a ely ep esen he chosen a ea’s eal ci cums ances. Gi en he
limi ed a ailabili y o in o ma ion on AFV cha ac e is ics, mul iple
da a collec ion s a egies may be necessa y. Fo he same a ionale,
speci ic ehicle c i e ia like pe o mance, speed, com o , o aes-
he ics a e conside ed negligible o he c i e ia selec ion.
Finally, he only conside ed limi a ion encompass in o ma ion con-
s ain s and he po en ial dispa i ies ha may a ise be ween eal-wo ld
de elopmen s and he es ima es made o he speci ied ime pe iods.
The e o e, he p oposed model mus conside c i e ia and indica o s
sui able o accoun o unce ain ies.
4. Me hodology
In his sec ion, he p oposed me hodology is in oduced. The i s
subsec ion ou lines he MCDM me hod used o agg ega ing and p o-
cessing indica o alues. In he second subsec ion, he me hods imple-
men ed o add ess unce ain y a e desc ibed. Finally, he comp ehensi e
p oposed me hodology is p esen ed.
4.1. MIVES
MIVES is a well-es ablished mul i-a ibu e u ili y heo y (MAUT)
MCDM me hod used o assess bo h homogeneous and he e ogeneous
al e na i es aimed a ul illing an o e all objec i e (Boix-Co s e al.,
2022), by ypically inco po a ing he h ee pilla s o sus ainabili y
ac oss he e alua ion. Among he main cha ac e is ics o MIVES, se e al
ea u es make i pa icula ly well-sui ed o add essing he needs ou -
lined in he p e ious sec ion.
Fi s , MIVES exhibi s high lexibili y, allowing he inclusion o in-
dica o s wi h di e se uni s and scales, which can be assessed ei he
quali a i ely o quan i a i ely and a e subsequen ly con e ed in o a
non-dimensional scale. Second, MIVES acili a es he c ea ion o a s a ic
analy ical amewo k while accommoda ing dynamic al e na i es. This
means ha he inclusion o new al e na i es o modi ica ions o exis ing
ones does no al e he e alua ion o p e iously assessed al e na i es.
Thi d, MIVES employs alue unc ions ha enable p ecise
ep esen a ion o he e ec s p oduced by each indica o . Unlike linea
models, hese alue unc ions allow o he modula ion o p e e ence
cu es, cap u ing non-linea ela ionships and p o iding a mo e accu-
a e e lec ion o how a ying indica o alues impac he o e all
ou come. Finally, he me hod is designed o inco po a e s akeholde
p e e ences h ough he assignmen o weigh s o c i e ia and indica o s,
ensu ing ha he inal decision aligns wi h he p io i ies and alues o all
in ol ed pa ies. Fo hese easons, MIVES has been selec ed as he
me hodological amewo k in his s udy, as i e ec i ely add esses he
complexi y o e alua ing al e na i es unde dynamic, mul i-c i e ia
condi ions. Fo he applica ion o MIVES, h ee s eps a e equi ed:
de ining he hie a chical ee, speci ying he alue unc ions o each
indica o , and assigning a weigh o each elemen .
The i s s ep is he de ini ion o he hie a chical ee, which is based
on o ganizing he decision amewo k in o equi emen s, c i e ia, and
indica o s ( e e o Fig. 1A). These equi emen s ep esen high-le el
objec i es ha a e di ided in o c i e ia, cap u ing speci ic aspec s o
he decision p oblem, and u he subdi ided in o indica o s, which
measu e ele an a ibu es. This hie a chical s uc u e ensu es a sys-
ema ic and anspa en e alua ion, as each elemen ’s con ibu ion o
he o e all objec i e is explici ly de ined.
The second s ep is he de ini ion o he alue unc ions o each in-
dica o . These unc ions a e used o ansla e he aw alues o in-
dica o s, which may ha e di e en uni s and scales, in o a s anda dized,
non-dimensional p e e ence scale. In his s udy, he comp ehensi e
alue unc ion (CVF) has been employed (Boix-Co s e al., 2024), a
unc ion ecen ly in oduced o MIVES o add ess he need o consid-
e ing nega i e impac on sus ainabili y pe o mance o ce ain in-
dica o s (such as land deg ada ion o wa e quali y indexes). In his
con ex , he CVF enables indica o s o impac he o e all index bo h
posi i ely and nega i ely, wi h a p e e ence scale anging om 1 o −1.
This imp o emen allows o a mo e accu a e and nuanced e lec ion o
he al e na i e’s o e all pe o mance, pa icula ly in con ex s whe e
indica o s aise signi ican conce ns, such as some o he iden i ied in he
p e ious sec ion.
The CVF o e s lexibili y by adop ing mul iple shapes o cap u e he
di e se beha iou s o p e e ence ou comes ( e e o Fig. 1B), a choice
ha signi ican ly in luences he esul s, as i de e mines how p e e ence
e ol es ac oss he ange o indica o alues. A conca e cu e is used
when inc emen al imp o emen s yield diminishing e u ns, while a
con ex cu e is be e sui ed o cases whe e small changes ini ially ha e
less impac bu become mo e signi ican as alues inc ease. S-shaped
unc ions combine hese beha iou s, ep esen ing scena ios whe e he
impac o changes a ies ac oss he indica o s’ alue ange
(Monse a -L´
opez e al., 2024). Linea unc ions a e applied o in-
dica o s wi h s eady, p opo ional e ec s. Fu he mo e, all hese unc-
ions can be in e ed, enabling hei applica ion o nega i e impac s by
e e sing X
max
and X
min
, o a piecewise unc ion can be de ined.
The CVF alue unc ion is de ined by 6 pa ame e s: n, K
i
, C
i
, X
max
.,
X
min
. and P
i
as shown in Eq. (1). These a e used o endow he unc ion
wi h posi i e o nega i e p e e ence, maximum and minimum alues,
in lexion poin s and a ce ain shape. As is common in MAUT unc ions
(Zion s, 1979), he alues o hese pa ame e s a e decided by he expe s
and decision-make s, who ha e s udied he gene al p oblem and he
e ec o he indica o in de ail.
Vind =n*B*⎡
⎢
⎣1−e
−K⋅(X−Smin
C)P⎤
⎥
⎦(1)
whe e.
V
ind
is he p e e ence index o he e alua ed indica o ,
n is he posi i i y o nega i i y pa ame e .
B is a pa ame e ha allows he unc ion o emain wi hin 0 and 1,
whe e 1 is assumed o be he highes p e e ence alue. This pa ame e is
de e mined by Eq. (2),
D. Boix-Co s e al. Jou nal o Cleane P oduc ion 486 (2025) 144564
4
S
min
is he minimum p e e ence alue poin on x-axis,
S
max
is he x maximum p e e ence alue poin on x-axis,
X is he indica o alue ha gene a es he alue equal o Vind,
P de ines he shape o he cu e. P =1 he cu e is linea , P <1 he
cu e is conca e o posi i e CVFs and con ex o nega i e CVFs; P >1
he cu e is S-shaped o con ex o posi i e CVFs and conca e o
nega i e CVFs,
C is a pa ame e ha de ines he in lexion x- alue poin o P >1
cu es,
K is a pa ame e ha de ines he y- alue C poin .
B=1
⎡
⎢
⎣1−e
−K⋅(Smax−Smin
C)P⎤
⎥
⎦
(2)
The hi d s ep is he assignmen o weigh s o each elemen wi hin he
hie a chical s uc u e, ensu ing ha he decision e lec s he ela i e
impo ance o he c i e ia and indica o s. These weigh s can be ob ained
wi h o he decision-making echniques, such as he analy ic hie a chy
p ocess, namely AHP (Saa y, 1980). When mul iple s akeholde s a e
in ol ed in he decision, hei opinions and p e e ences on he indica o
weigh s mus be agg ega ed. In his case, he Hie a chical In eg a ion o
Values and E alua ions unde Social cons ain s (HIVES) me hod is used
o in eg a e he p e e ences o mul iple decision-make s (Boix-Co s
e al., 2023). This me hod allows o ma hema ically combining di e se
opinions while conside ing he main social choice axioms, ensu ing ha
he inal decision e lec s a balanced and comp ehensi e e alua ion ha
espec s he inpu o all s akeholde s in ol ed. Fu he mo e, his
me hod is speci ically designed o mul iple c i e ia p oblems, using
combina o y analyses ha e alua e c i e ia indi idually, maximizing
he sa is ac ion o he solu ion.
Once hese s eps a e comple ed, he al e na i es can be e alua ed by
ans o ming he alues o hei indica o s in o p e e ence indexes using
he espec i e alue unc ions and agg ega ing hem h ough he Weigh
Sum Model (WSM).
4.2. Unce ain y
As desc ibed in Sec ion 3, his s udy o e s a holis ic analysis o
cus ome beha iou ac oss mul iple u u e pe iods. Wi hin hese
pe iods, he cu en indica o da a may unde go a ious luc ua ions,
equi ing he in oduc ion o unce ain y.
To embed his unce ain y, he adop ion o Mon e-Ca lo simula ion
(MCS) wi h a iangula dis ibu ion (MCS-TD) is p oposed. MCS-TD
s ands ou as an app op ia e ool o handling quan i a i e da a whe e
only app oxima e knowledge is a ailable o h ee key pa ame e e -
e ences: he minimum (L), he mos p obable (M), and he maximum (H)
alues ha he a iable can encompass (Hihn and Lum, 2004). Fo
example, i an indica o measu es uel cos s in a u u e scena io, expe s
migh es ima e a minimum alue o 1.20
€
pe li e, a mos p obable
alue o 1.50
€
, and a maximum o 1.80
€
. MCS-TD gene a es nume ous
andom samples om hese inpu s o model –unde he hypo hesis o TD
p obabili y densi y unc ion –po en ial luc ua ions in uel cos s and
assesses hei impac on he o e all decision.
This p obabilis ic app oach p o ides a ealis ic ep esen a ion o
unce ain y and allows he e alua ion o he alue dis ibu ion ac oss
di e en scena ios ( e e o Fig. 2) when he e is limi ed in o ma ion on
he magni udes ha he in ol ed a iables can p esen . These pa ame e
e e ences a e es ablished wi h he insigh s o expe s, aligning seam-
lessly wi h he p oposed model’s equi emen o expe assump ions.
MCS has al eady p o en i s e ec i eness when in eg a ed wi h classic
MIVES (De La C uz e al., 2014;Ja o-Espino e al., 2014).
Howe e , some indica o s do no ely on quan i a i e da a; ins ead,
hey a e based on whe he speci ic equi emen s ha e been me . To
Fig. 1. A) Gene al MIVES amewo k ee. B) CVF unc ion.
Fig. 2. T iangula p obabili y densi y unc ion.
D. Boix-Co s e al. Jou nal o Cleane P oduc ion 486 (2025) 144564
5
add ess hese indica o s, he use o disc e e p o ile dis ibu ions (DPDs)
is p oposed. This app oach is employed o manage unce ain y by
conside ing he p obabili y o achie ing speci ic p o iles, as indica ed by
he decision make (Kunsch and Ishizaka, 2018). Fo ins ance, conside
an indica o assessing whe he a cha ging in as uc u e is a ailable in
u al a eas. The decision make may speci y a se o p o iles (P), such as
“No in as uc u e,” “Limi ed in as uc u e,”o “Adequa e in as uc-
u e,”wi h p obabili ies o occu ence (V) assigned o each p o ile (e.g.,
20%, 50%, and 30%, espec i ely). This app oach models he unce -
ain y in mee ing speci ic quali a i e equi emen s and ans o ms hese
p obabili ies in o a weigh ed a e age ha e lec s he o e all likelihood
o achie ing he desi ed p o ile.
DPD is pa icula ly use ul when he e is hesi ance in he indica o
alues, as hey esemble a bina y p o ile, simila o a p obabili y unc-
ion exp essed as pe cen ages. These hesi an alues a e used o compu e
he g ade poin a e age (GPA). Conside ing a p o ile se P ={P
1,
P
2,
P
3
,
…, P
m
}; ∈P and i s co esponding membe ship alue se V ={V
1,
V
2,
V
3
,…, V
m
}; ∈V, o each indica o he GPA is de ined as ollows:
GPA =∑
m
=1
P ⋅V (3)
whe e:
m is he maximum numbe o p o iles,
P
is he “ ”p o ile,
V
is he indica o ’s p o ile “ ”membe ship pe cen age deg ee.
To simpli y, he GPA agg ega es he p obabili ies o each p o ile and
calcula es an o e all p e e ence sco e o he indica o . This allows
quali a i e indica o s, such as he likelihood o mee ing a speci ic con-
di ion, o be in eg a ed seamlessly in o he analysis. The e o e, in-
dica o s can be exp essed as exac da a alues, anges ha include
minimum, mos likely, and maximum alues, o as DPD p o ile alues.
These alues a e agg ega ed using he MIVES me hod o de i e an index,
which encapsula es no jus a p ecise p obabili y alue o selec ing an
al e na i e, bu he en i e dis ibu ion o selec ion p obabili ies.
4.3. P oposed me hodology
This s udy p oposes a s uc u ed, mul i-s age me hodology o e al-
ua e cus ome beha iou unde e ol ing condi ions, in eg a ing bo h
quan i a i e and quali a i e da a while add essing he speci ic as-
sump ions ou lined in Sec ion 3. The amewo k consis s o ou main
s ages ( e e o Fig. 3), each con ibu ing o he comp ehensi e e alu-
a ion o he p oposed al e na i es.
The p epa a ion s age es ablishes he ounda ion o he en i e
analysis by iden i ying he al e na i es, assump ions, limi a ions, and
cons ain s h ough a li e a u e e iew o he p oblem and i s speci i-
ca ions. In his s udy, he p epa a ion s age is closely ied o he hi d
assump ion, which emphasizes applicabili y on a ci y-by-ci y basis and
he impo ance o in ol ing ci izens in assigning weigh s o he in-
dica o s. Addi ionally, key conside a ions, such as managing unce -
ain y and ou lining po en ial scena ios, a e de ined a his s age.
The i s s age in ol es cons uc ing he hie a chical MIVES ee.
Conside ing he h ee sus ainabili y equi emen s (economic, ambien al
and socie al), ci izens’pe cep ions in he selec ed loca ion a e collec ed
o iden i y ele an indica o s, ensu ing ha he amewo k e lec s local
p io i ies and con ex ual eali ies. S uc u ed su eys a e ecommended
o cap u e compa able esponses, which a e hen ansla ed in o
measu able indica o s, which a e g ouped unde c i e ia. The second
s age ocuses on assigning alues o he indica o s and de ining hei
co esponding alue unc ions. Expe inpu is c i ical in his s age, as
assump ions speci ic o each indica o mus be es ablished o accoun o
unce ain ies, allowing o quan i y indica o alues o each u u e
pe iod. The hi d s age in ol es de e mining he ela i e impo ance o
each indica o by assigning weigh s. Ci izen inpu plays a key ole he e,
ensu ing ha he weigh s e lec he communi y’s p io i ies and alues.
The AHP and HIVES me hods a e ecommended o de i ing hese
weigh s, as hey p o ide a consis en and a ional me hod o assessing
and agg ega ing p e e ences.
Finally, he ou h s age is based on he applica ion o he de eloped
alue unc ions and he MIVES ee o e alua e he al e na i es. By
agg ega ing he c i e ia weigh s and ans o ming he indica o alues,
sus ainabili y index dis ibu ions a e ob ained, p o iding ac ionable
ecommenda ions o decision-making.
5. Case s udy
A eal case s udy is p o ided o illus a e he p oposed app oach,
which is implemen ed in Ba celona, Spain. Ba celona, a Medi e anean
ci y, has a popula ion o 1.6 million and co e s an a ea o 101.9 km
2
. I
s ands as Spain’s second-la ges ci y and se es as he economic hub o
Ca alonia, i s au onomous communi y. Consequen ly, his s udy in-
ol es he ci y’s esiden s in he da a collec ion p ocesses. Conside ing
he p epa a ion s age done in sec ion 3, he p edominan BF al e na i e
has o be selec ed. Ba celona p ima ily elies on Bioe hanol as i s mos
p e alen Bio uel op ion, as opposed o Biodiesels like HVO100, which
a e mo e common in No he n Eu ope (glpau ogas.in o, 2022). Hence,
he al e na i e se encompasses CFVs, BFVs (E100), PHEVs, EVs and
HyVs. Wi h his in o ma ion, he ollowing amewo k s eps can be
applied.
5.1. S age 1
Fo he p esen s udy, he au ho s ha e used he sus ainabili y e-
qui emen s o gene a e a semi-s uc u ed in e iew o he i s da a
collec ion p ocess ca ied ou on Ba celona ci izens, a quali a i e
esea ch me hod ha combines p ede ined ques ions wi h he lexibili y
Fig. 3. Scheme and s ages o he p oposed me hodology.
D. Boix-Co s e al. Jou nal o Cleane P oduc ion 486 (2025) 144564
6
o explo e addi ional insigh s p o ided by he pa icipan s, including
b oad, open-ended ques ions ha ensu e ha esponden s can eely
exp ess hei pe spec i es wi hou being cons ained by o e ly igid
ca ego ies. This app oach was chosen because i allows o bo h he
collec ion o s anda dized da a ( o ensu e compa abili y) and he
explo a ion o nuanced, con ex -speci ic pe cep ions. The ques ionnai e
(see Table 1) was cons uc ed o align wi h he h ee sus ainabili y e-
qui emen s (economic, en i onmen al, and social) and o cap u e ci i-
zens’p ima y conce ns and p e e ences ega ding AFVs. Due o he
p ima y objec i e o his a icle being o show a new consis en and
obus me hod, and conside ing he academic na u e o his s udy, he
sample size es ablished was su icien o ensu e he e ogenei y. In o al,
82 ci izens answe ed he ques ions shown in Table 1 (59 men and 23
women, wi h a e ages o 40 and 27 yea s).
The esponses p o ided insigh s in o speci ic cha ac e is ics ha a e
common conce ns among hose in e iewed. I was e iden ha he cos
o bo h he ehicle and uel we e c i ical ac o s in hei decision-making
p ocess. A signi ican majo i y, 63 esponden s (76.83%), exp essed
conce ns abou he expenses associa ed wi h epai ing and main aining
an AFV, emphasising he need o mo e knowledge in his ega d.
Meanwhile, 33 esponden s (40.24%) conside ed AFV incen i es ela ed
o ehicle axes as a de e mining ac o . Rega ding en i onmen al in-
e es s, he e was unanimous ag eemen among esponden s on
conside ing uel emissions as a decisi e ac o . Howe e , only six e-
sponden s (7.32%) highligh ed he impo ance o ac o ing in he
en i onmen al impac o uel p oduc ion. The e we e also conce ns
abou echnical ac o s ha could impac he social aspec s o he e-
sponden s’li es, which exhibi ed a deg ee o uni o mi y. All e-
sponden s conside ed ac o s such as cha ging ime, a ailabili y o
cha ging poin s, and ehicle au onomy as cu en a eas o conce n.
Howe e , i is impo an o emphasize ha hei conce ns we e no
e enly dis ibu ed. A signi ican majo i y o he esponden s exp essed
ha issues ela ed o cha ging ime and he accessibili y o cha ging
poin s we e no only majo conce ns bu also c i ical ba ie s ha could
de e hem om adop ing AFVs, which we e pe cei ed as signi ican
enough o ou weigh o he conside a ions.
To p ocess hese esponses, a hema ic analysis was conduc ed. This
app oach in ol es coding he esponses o iden i y pa e ns o ca ego ies
ha eme ge om he da a. Each esponse was e iewed, and ecu ing
ac o s we e ca ego ized in o hemes co esponding o he sus ainabili y
equi emen s. Once hese hemes we e es ablished, he me hodological
ansi ion o he MIVES ee was pe o med. Each heme was ansla ed
in o measu able indica o s and ca ego ized unde he app op ia e
c i e ia (see Fig. 4), ensu ing alignmen wi h he hie a chical s uc u e
o he MIVES amewo k.
5.2. S age 2
A his s age, he alues and alue unc ions associa ed wi h he in-
dica o s depic ed in Fig. 4 mus be es ablished. In he ollowing, each
indica o is de ined, along wi h i s da a collec ion p ocesses and i s alue
unc ions.
5.2.1. Vehicle cos (I
1
)
This indica o speci ies he a e age ehicle cos o each al e na i e.
Following he 4 h delimi a ion, he ehicle alues a e de ined as ollows.
In he case o CFVs, he known alue is 22,755
€
o new passenge
ehicles, a igu e p o ided by he Spanish ax agency in Ap il 2022
(Agencia T ibu a ia, n.d.). Howe e , ob aining a e age da a o o he
al e na i es is mo e challenging since he e a e no eadily a ailable
da abases in Spain o compa ison. This equi es employing a ious
s a egies o ga he in o ma ion. Fo BFVs, an es ima ed cos o 1200
€
is
added due o he adap a ion ki equi ed o modi y he ca ’s cha ac-
e is ics. This adap a ion is necessa y because blended e hanol can be
used in sel -igni ion engines, while E100 ehicles equi e spa k igni ion
engines (Chłopek, 2007). As o PHEVs, he a e age cos is calcula ed
based on he h ee bes -selling ca s in Spain o his ca ego y: Peugeo
2008, Kia Xceed, and Me cedes A-Class, wi h an a e age cos o 36,455
€
. Fo EVs, he a e age cos is de e mined using he Tesla Model 3, FIAT
500 elec ic, and KIA e-Ni o, wi h an a e age p ice o 40,400
€
. Finally,
HyVs, ep esen ed by he Toyo a Mi ai and Hyundai Nexo, ha e an
a e age cos o 69,225
€
.
Addi ionally, inancial incen i es om he Spanish go e nmen , such
as he Mo es III Plan, can impac he ehicle’s cos . Unde his plan,
buye s ecei e 7000
€
( o EVs and HyVs) o 5000
€
( o PHEVs) i hey
sc ap hei old ca . These incen i es a e educed o 4500
€
( o EVs and
HyVs) o 2500
€
( o PHEVs) o he wise. The a e age o hese alues has
been used o adjus he cu en cos o PHEVs, EVs, and HyVs in he i s
pe iod, conside ing ha hese incen i es a e likely o disappea a e
2030.
To analyse u u e ehicle p ice alues, he au ho s ha e conside ed
he ollowing a iables:
•An annual p ice inc ease o 7.3% due o he Consume P ice Index
(CPI) sou ced om he Na ional S a is ical Ins i u e o Spain. This
inc ease is applied di e en ly depending on scena ios: i ’s ully
applied o wo s -case scena ios, hal ed o he mos likely scena ios,
and qua e ed o he bes -case scena ios.
•A sca ci y ac o in he p oduc ion o CFVs, BFVs, and PHEVs is
conside ed un il 2035. This ac o esul s in an annual 1% p ice in-
c ease. A e 2035, his ac o ansi ions o a socie al ac o : I is
hypo hesized ha some ehicle owne s will op o e ain hei
exis ing uel ypes, leading o a 5% p ice inc ease.
•Con e sely, a ac o p omo ing inc eased p oduc ion o EVs and
HyVs is conside ed, leading o an annual 1% educ ion in hei p i-
ces. A e 2035, his ac o is doubled.
The e o e, he au ho s ha e conside ed he ehicle’s possible cos
alues shown in Table 2.
5.2.2. Incen i es (I
2
)
This indica o assesses he po en ial o ecei ing incen i es on
Table 1
Ques ions used o ga he he ci izens’pe cep ions on AFVs.
Requi emen Ques ion
Economic Wha economic ac o s would you conside when pu chasing an
AFV?
Ambien al Wha en i onmen al cha ac e is ics would you conside when
pu chasing an AFV?
Social Wha socio- echnical ac o s would be o u mos conce n o you
when buying an AFV?
Fig. 4. P oposed MIVES ee.
D. Boix-Co s e al. Jou nal o Cleane P oduc ion 486 (2025) 144564
7
ecu ing axes. In Ba celona, he sole ecu ing ax is he mo o ehicle
ax, which is an annual paymen based on a ehicle’s e ec i e powe .
Cu en ly, he ax discoun s in Ba celona a e as ollows: 0% o CFVs,
75% o BFVs and PHEVs, and 100% o EVs and HyVs. I mus be no ed
ha hese alues a e subjec o change, ansi ioning om being a sus-
ainabili y commi men o a manda o y equi emen o e ime.
Fu he mo e, i also mus be conside ed ha his ax con ibu es
signi ican ly o he ci y council budge , amoun ing o 5%, making i
challenging o sus ain mul iple ax discoun s.
A DPD sys em is employed o analyse mul iple u u e scena ios,
which a e ca ego ized in o ou cases based on qua iles (0–25%,
25–50%, 50–75%, and 100% ax discoun ). The DPDs conside ed o
analysis a e p esen ed in Table 3, ollowing he subsequen c i e ia:
•CFVs a e assumed o emain unchanged, as hey ep esen he
al e na i e ha he go e nmen aims o phase ou .
•BFVs, a decline in he discoun class is conside ed du ing he ini ial
pe iod due o hei ICE usage. This decline becomes mo e signi ican
in he second pe iod, ul ima ely leading BFVs o be classi ied in he
1s qua ile om 2035 onwa ds. A simila app oach is applied o
PHEVs, wi h a ela i ely smalle dec ease due o hei elec ic mo o .
•Bonuses o EVs and HyVs will be g adually phased ou as hese al-
e na i es become mo e commonplace. Howe e , i was ound
ep esen a i e o conside ha HyVs may e ain some incen i es due
o hei limi ed adop ion in Spain.
Following Eq. (3), he disc e e alues o each al e na i e in each
pe iod a e CFV [1.0, 1.0, 1.0], BFV [1.7, 1.2, 1.0], PHEV [1.5, 1.3, 1.0],
EV [3.8, 3.0, 1.75], HyV [3.8, 3.0, 1.75].
5.2.3. Fuel cos (I
3
)
This indica o speci ies he uel cos o each al e na i e in he o m
o uel cos pe 100 km due o hei di e ences in uni s o measu emen
(li es and kW). Acco ding o da a om he Spanish Minis y o
Ecological T ansi ion and Demog aphic Challenge as o Sep embe
2022, he uel cos pe 100 km is as ollows: 10.86
€
o CFVs, 8.46
€
PHEVs, and 6.06
€
o EVs. Fo BFVs, despi e hei po en ial cos sa ings
o up o 25% when compa ed o con en ional uel, hey can consume up
o 30% mo e uel han CFVs. The e o e, he CFV’s alue is used as a
e e ence o BFVs in his analysis. Finally, HyVs ha e an es ima ed
consump ion cos o app oxima ely 9
€
pe 100 km.
To analyse u u e uel cos alues p esen ed in Table 4, he au ho s
ha e conside ed he ollowing a iables:
•S a is a, a specialized da a collec ion websi e (www.s a is a.com),
p o ided da a o calcula e he pe cen age a iance o each ype o
uel. Di e en pe iods a e conside ed, accoun ing o e en s such as
he Russia-Uk aine con lic ’s impac on Spain’s uel p ices. The i s
pe iod assumes he Russian oil and gas sub-supply cu -o is in e ec ,
while he second one conside s he end o he wa and p ice s abi-
liza ion. The hi d pe iod includes a ax inc ease o CFVs and BFVs
while educing p ices o EVs and HyVs. This change is d i en by he
Eu opean Union’s di ec i es o educe dependence on ossil uels and
p omo e enewable ene gy in es men .
•Fo CFVs and BFVs, he p ice a iance is based on es ima ed e ail
p ices pe li e. PHEVs use an a e age be ween CFVs and EVs. HyVs,
as hyd ogen is p ima ily ob ained h ough elec olysis, sha e a i-
ables wi h EVs.
5.2.4. Repa a ion (I
4
)
This indica o uses main enance cos da a om Spence (2021). CFVs
and EVs ha e main enance cos s o 28,538.06
€
and 17,235.85
€
,
espec i ely, o a li espan o 482,803 km. I is assumed ha BFVs sha e
he same main enance cos as CFVs, and PHEVs ha e an a e age o CFVs
and EVs. HyVs incu 18% highe cos s o some commonly eplaceable
componen s compa ed o elec ic componen s (O e e al., 2010), which
leads o a main enance cos o 20,338
€
a 482,803 km. Acco ding o
Eu os a , he a e age annual dis ance a elled in Eu ope is 10,000 km
(Focas and Ch is idis, 2017). Conside ing he ca cha ac e is ic delimi-
a ion men ioned in sec ion 3, an a e age li espan o 150,000 km is
assumed o each ehicle ype. The e o e, he es ima ed li ecycle
main enance cos s o he di e en al e na i es a e: 8866
€
o CFVs and
BFVs, 7111
€
o PHEVs, 5355
€
o EVs, and 6318.82
€
o HyVs. To
ob ain da a p esen ed in Table 5, he au ho s ha e conside ed he
ollowing a iables:
•The same CPI alues a e applied ac oss all ehicles as hey ha e a
simila impac on spa e pa s and mechanic p ices.
•Fac o s a ec ing CFVs, BFVs, and PHEVs a e assumed o be simila ,
conside ing ac o s like sca ci y and socie al demand.
•EVs and HyVs main ain hei educ ion ac o in main enance cos s.
This is a ibu ed o an expec ed inc ease in he numbe o mechanics
capable o pe o ming epai s (W ´
oblewski e al., 2021).
5.2.5. Emissions (I
5
)
This indica o assesses he GHG emissions p oduced by each uel
Table 2
Al e na i es likely cos ega ding each pe iod.
Vehicle <2030 2030 < <2035 >2035
CFVs [22755, 30162,
35976]
[30469, 35452,
45419]
[24765, 29038,
37586]
a
BFVs
(E100)
[23955, 31922,
38112]
[32076, 37322,
47814]
[26287, 30824,
39897]
a
PHEVs [32705, 43351,
51707]
[48813, 56797,
72764]
[39675, 46521,
60215]
a
EVs [34690, 41125,
49988]
[44444, 53300,
71013]
[38782, 47638,
65351]
HyVs [63475, 75250,
91467]
[76078, 91239,
121559]
[66387, 81547,
111868]
a
Second hand ma ke .
Table 3
Incen i es disc e e p o ile dis ibu ions o each al e na i e and pe iod.
<2030 2030 < <2035 >2035
Case 1 2 3 4 1 2 3 4 1 2 3 4
CFVs 100.00% 100.00% 100.00%
BFVs 30.00% 70.00% 80.00% 20.00% 100.00%
PHEVs 50.00% 50.00% 70.00% 30.00% 100.00%
EVs 20.00% 80.00% 25.00% 50.00% 25.00% 50.00% 25.00% 25.00%
HyVs 20.00% 80.00% 25.00% 50.00% 25.00% 25.00% 50.00% 25.00%
Table 4
Fuel cos pe 100 km in
€
o each al e na i e and pe iod.
Vehicle <2030 2030 < <2035 >2035
CFVs [8.99, 10.86, 13.02] [7.29, 8.39, 9.20] [8.02, 9.23, 10.11]
BFVs (E100) [8.99, 10.86, 13.02] [7.29, 8.39, 9.20] [8.02, 9.23, 10.11]
PHEVs [6.71, 8.46, 10.86] [4.19, 5.94, 8.33] [4.50, 6.18, 8.41]
EVs [4.43, 6.07, 8.71] [1.09, 3.49, 7.46] [0.98, 3.14, 6.71]
HyVs [6.58, 9.00, 12.92] [1.62, 5.18, 11.07] [1.29, 4.14, 8.86]
D. Boix-Co s e al. Jou nal o Cleane P oduc ion 486 (2025) 144564
8
ype. To de e mine i s po en ial alues, a DPD is employed o analyse
a ious u u e scena ios in alignmen wi h Eu opean egula ions ha
suppo he p inciples o his manusc ip . These scena ios adhe e o he
maximum emissions pe mi ed by hese egula ions: (i) 2021 CO
2
limi
(95 g /km), (ii) 2030 a ge (55% CO
2
educ ion compa ed o 2021),
and (iii) he 2035 goal: 100% CO
2
educ ion compa ed o 2021. In
acco dance wi h he DPDs p esen ed in Table 6, he au ho s ha e
conside ed he ollowing:
•CFVs con o m o Eu opean egula ions di ec ly. An in e media e
alue is assumed o BFVs, as some s udies ha e ques ioned he 90%
CO
2
educ ion (Wa d and Singh, 2002), analysing he alues in
non-expe imen al d i ing (Liaqua e al., 2010). PHEVs also assume
an in e media e alue, ecognising hei emissions a e highly
dependen on d i ing pa e ns (ˇ
Ceˇ
o ský and Mindl, 2008b;Wol am
and Lu sey, 2016). EVs and HyVs consis en ly achie e 100% CO
2
educ ion in all pe iods.
•In he second pe iod, i is assumed ha manu ac u e s o CFVs, BFVs,
and PHEVs will mee Eu opean egula ions, and no new ehicles
wi h lowe emissions will be de eloped due o egula o y
es ic ions.
•In he hi d pe iod, a second-hand ma ke o CFVs, BFVs, and PHEVs
is supposed o eme ge, wi h alues se a 2/3 o he i s pe iod and
1/3 o he second pe iod.
Following Eq. (3), he disc e e alues o each al e na i e in each
pe iod a e CFV [1.0, 2.0, 1.67], BFV [1.7, 2.0, 1.9], PHEV [1.6, 2.0,
1.87], EV [3.0, 3.0, 3.0], HyV [3.0, 3.0, 3.0].
5.2.6. Cha ging ime (I
6
)
This indica o assesses he ime equi ed o ull ehicle cha ging. I
compa es he cha ging imes o a ious al e na i es o con en ional
CFVs, which is abou 3–5 min, acco ding o one o Spain’s leading
elec ic cha ging poin and gas s a ion p o ide s (Repsol, n.d.). Addi-
ionally, elec ic cha ging poin s a e ca ego ized in o ou ypes: slow
cha ging (4–8 h), semi- as cha ging (1–3 h), as cha ging (app oxi-
ma ely 40 min), and ul a- as cha ging (5–10 min). To de e mine he
alues in Table 7 ela ed o cha ging imes, he au ho s ha e conside ed
he ollowing:
•BFVs and HyVs ha e he same cha ging ime as CFVs, gi en hei
simila cha ging p ocesses. Addi ionally, since PHEVs ha e bo h uel
sys ems, hey adop he cha ging imes o CFVs, which is conside ed
he mos common ou -o -home p ocedu e.
•Slow cha ging is no conside ed, as i is ypically u ilized in domes ic
ins alla ions. Semi- as cha ging, as cha ging, and ul a- as
cha ging a e assigned alues o 2 h, 40 min, and 10 min, espec i ely.
•While he abili y o ehicles o use ce ain cha ging in as uc u es
depends on hei speci ica ions, i is assumed ha hese will g adu-
ally ansi ion o accep as and ul a- as cha ging.
5.2.7. Cha ging poin s (I
7
)
This indica o examines he a ailabili y o cha ging poin s o each
al e na i e, using da a sou ced om he Minis y o Ecological T an-
si ion and Demog aphic Challenge in (Minis e io pa a la ansici´
on
ecol´
ogica y el e o demog ´
a ico, n.d.), which p o ides comp ehensi e
in o ma ion on pe ol s a ions and hei dis ibu ion ac oss he coun y.
In he me opoli an a ea o Ba celona, he ollowing s a ions a e
cu en ly a ailable: 81 o CFVs, 1 o BFVs, and 1 o HyVs. Addi ion-
ally, he ci y council’s ne wo k o cha ging poin s (Plug-in Ba celona) is
planned o ob ain he alues o 43 semi- as cha ge and 41 as cha ge
poin s o EVs and PHEVs. The alues p esen ed in Table 8 a e de e -
mined based on he ollowing conside a ions:
•The numbe o CFV s a ions emains cons an as no addi ional pe -
mi s o new s a ions a e issued in Ba celona. PHEVs and BFVs a e
assumed o u ilize CFV cha ging in as uc u e, conside ing ha he
numbe o s a ions o e ing BFVs will inc ease du ing he ini ial
pe iod bu will le el o in he second pe iod, aligned wi h he 2035
ban.
Table 5
Repa a ion indica o da a, conside ing o al li ecycle ehicle main enance cos .
Vehicle <2030 2030 < <2035 >2035
CFVs [8866, 12165, 14754] [12123, 14226, 18443] [12566, 14669, 18876]
BFVs (E100) [8866, 12165, 14754] [12123, 14226, 18443] [12566, 14669, 18876]
PHEVs [7111, 9756, 11832] [9722, 11409, 14783] [10078, 11765, 15139]
EVs [5355, 6490, 8054] [5929, 7200, 9741] [5233, 6504, 9044]
HyVs [6319, 7658, 9504] [6997, 8496, 11494] [6175, 7674, 10672]
Table 6
Disc e e p o ile dis ibu ions o each al e na i e and pe iod.
T<2030 2030 < <2035 >2035
Case 1 2 3 1 2 3 1 2 3
CFVs 100.00% 100.00% 66.67% 33.33%
BFVs 30.00% 70.00% 100.00% 10.00% 90.00%
PHEVs 40.00% 60.00% 100.00% 13.33% 86.67%
EVs 100.00% 100.00% 100.00%
HyVs 100.00% 100.00% 100.00%
Table 7
Cha ging ime alues o each al e na i e compa ed o CFVs.
Vehicle <2030 2030 < <2035 >2035
CFVs [1.0, 1.0, 1.0] [1.0, 1.0, 1.0] [1.0, 1.0, 1.0]
BFVs (E100) [1.0, 1.0, 1.0] [1.0, 1.0, 1.0] [1.0, 1.0, 1.0]
PHEVs [1.0, 1.0, 1.0] [1.0, 1.0, 1.0] [1.0, 1.0, 1.0]
EVs [8.00, 24.00, 24.00] [2.00, 8.00, 24.00] [2.00, 8.00, 8.00]
HyVs [1.0, 1.0, 1.0] [1.0, 1.0, 1.0] [1.0, 1.0, 1.0]
Table 8
Cha ging poin s indica o alues.
Vehicle <2030 2030 < <2035 >2035
CFVs [81, 81, 81] [81, 81, 81] [81, 81, 81]
BFVs (E100) [1, 20, 40] [20, 40, 60] [40, 50, 60]
PHEVs [81, 81, 81] [81, 81, 81] [81, 81, 81]
EVs [41, 50, 60] [50, 80, 90] [80, 100, 120]
HyVs [1, 10, 20] [10, 30, 50] [30, 40, 60]
D. Boix-Co s e al. Jou nal o Cleane P oduc ion 486 (2025) 144564
9
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