scieee Science in your language
[en] (orig)

Can carbon labels shift consumers towards sustainable food? Evidence from Chinese consumers

Author: Xu, Yalin,Zhang, Zhiwen,Ren, Yanjun,Yuan, Rong,Wang, Yanan,Li, Rui,Zhao, Shunan,Qiu, Lu
Publisher: Amsterdam: Elsevier,Amsterdam: Elsevier
Year: 2024
DOI: 10.1016/j.sftr.2024.100363
Source: https://www.econstor.eu/bitstream/10419/306867/1/Xu_2024_carbon_labels.pdf
Xu, Yalin e al.
A icle — Published Ve sion
Can ca bon labels shi consume s owa ds sus ainable
ood? E idence om Chinese consume s
Sus ainable Fu u es
P o ided in Coope a ion wi h:
Leibniz Ins i u e o Ag icul u al De elopmen in T ansi ion Economies (IAMO), Halle (Saale)
Sugges ed Ci a ion: Xu, Yalin e al. (2024) : Can ca bon labels shi consume s owa ds sus ainable
ood? E idence om Chinese consume s, Sus ainable Fu u es, ISSN 2666-1888, Else ie ,
Ams e dam, Vol. 8, pp. 1-13,
h ps://doi.o g/10.1016/j.s .2024.100363 ,
h ps://www.sciencedi ec .com/science/a icle/pii/S2666188824002120
This Ve sion is a ailable a :
h ps://hdl.handle.ne /10419/306867
S anda d-Nu zungsbedingungen:
Die Dokumen e au EconS o dü en zu eigenen wissenscha lichen
Zwecken und zum P i a geb auch gespeiche und kopie we den.
Sie dü en die Dokumen e nich ü ö en liche ode komme zielle
Zwecke e iel äl igen, ö en lich auss ellen, ö en lich zugänglich
machen, e eiben ode ande wei ig nu zen.
So e n die Ve asse die Dokumen e un e Open-Con en -Lizenzen
(insbesonde e CC-Lizenzen) zu Ve ügung ges ell haben soll en,
gel en abweichend on diesen Nu zungsbedingungen die in de do
genann en Lizenz gewäh en Nu zungs ech e.
Te ms o use:
Documen s in EconS o may be sa ed and copied o you pe sonal
and schola ly pu poses.
You a e no o copy documen s o public o comme cial pu poses, o
exhibi he documen s publicly, o make hem publicly a ailable on he
in e ne , o o dis ibu e o o he wise use he documen s in public.
I he documen s ha e been made a ailable unde an Open Con en
Licence (especially C ea i e Commons Licences), you may exe cise
u he usage igh s as speci ied in he indica ed licence.
h p://c ea i ecommons.o g/licenses/by-nc/4.0/
Can ca bon labels shi consume s owa ds sus ainable ood? E idence om
Chinese consume s
Yalin Xu
a
, Zhiwen Zhang
a
, Yanjun Ren
a,b
, Rong Yuan
c
, Yanan Wang
a,*
, Rui Li
a
,
Shunan Zhao
a
, Lu Qiu
a
a
College o Economics and Managemen , No hwes A&F Uni e si y, Yangling 712100, China
b
Leibniz Ins i u e o Ag icul u al De elopmen in T ansi ion Economies (IAMO), Theodo -Liese -S . 2, 06120 Halle (Saale), Ge many
c
School o Economics and Business Adminis a ion, Chongqing Uni e si y, Shazhengjie 174, 400040 Chongqing, China
ARTICLE INFO
Keywo ds:
Ca bon-labeled ag icul u al p oduc s
Willingness o pay
Theo y o planned beha io
No m ac i a ion model
China
ABSTRACT
Ca bon labels a e becoming an essen ial ool o policymake s in many coun ies o p omo e low-ca bon con-
sump ion. To assess cus ome s’willingness o pay o i e ca bon-labeled ag icul u al p oduc s (CAP), we used
paymen ca d o conduc a ques ionnai e su ey among 641 esponden s in Shanghai, Nanjing, Wuhan, and
Xi’an, all loca ed in China. This s udy quan i a i ely analyzes he in luencing ac o s and in e ac i e mechanisms
o he publicʼs willingness o pu chase CAP h ough he ex ended Theo y o Planned Beha io and No m Ac i-
a ion Model. The esul s show ha consume s’willingness o pay a p emium o ca bon-labeled milk, co n,
bananas, oma oes, and eggs is 27.50 %, 29.73 %, 26.86 %, 26.51 %, and 24.26 % espec i ely. Pe cei ed
beha io al con ol has he s onges posi i e in luence on pu chase in en ion, ollowed by subjec i e no ms,
a i udes owa d he beha io , and pe sonal no ms. The e is a signi ican media ing e ec be ween awa eness o
consequences and pe sonal no ms, which indi ec ly in luences pe sonal no ms h ough he asc ip ion o e-
sponsibili y and subsequen ly a ec s pu chase in en ion. Addi ionally, he e is a gap be ween pu chase in en ion
and beha io , and isk pe cep ion nega i ely mode a es he ela ionship be ween he wo. Based on he esea ch
indings o his pape , p ac ical and e ec i e policy sugges ions a e p oposed o he go e nmen o p omo e
ca bon labeling policies and educe ca bon emissions.
1. In oduc ion
The e is g owing awa eness o he impac o ood choices on clima e
change. The ood sys em is es ima ed o be esponsible o 26–34 % o
global g eenhouse gas (GHG) emissions [1,2]. Recen modeling in-
dica es ha e en i ossil uel emissions we e o cease immedia ely,
cu en ends in he wo ld’s ood sys em would make i challenging o
achie e he IPCC’s 1.5 ◦C objec i e. By he end o he cen u y, hese
ends would h ea en he 2 ◦C goal [3]. Though ood p oduce s should
ocus on lessening hei en i onmen al impac , consume beha io
changes can also impac p oduc ion sys em imp o emen s [2]. Shi ing
o low-ca bon oo p in die s has he po en ial o signi ican ly dec ease
ca bon emissions and alle ia e he s ain on he en i onmen [4–6].
Acco dingly, ca bon label p oduc s a e a good low-ca bon consump ion
o ien a ion, and cus ome s can educe hei ca bon oo p in by pu -
chasing ood ha is less ha m ul o he en i onmen [7,8].
Among he policy ools used o p omo e he de elopmen o low-
ca bon economy, ca bon labels ha e been implemen ed in se e al
coun ies, such as he Uni ed Kingdom, Ge many, F ance, Sweden, and
he Uni ed S a es [9]. Ca bon labels e e o using quan i a i e measu es
on p oduc labels o indica e he amoun o g eenhouse gas eleased
du ing p oduc ion [10]. Acco ding o Edwa ds-Jones e al. [11], ca bon
labels can help educe g eenhouse gas emissions. Rega ding co po a e
emissions educ ion, Shi [12] poin ed ou ha ca bon labels can b ing
economic bene i s o companies, such as educing emissions and
achie ing cos sa ings. A he consume le el, p o iding in o ma ion o
consume s abou he ca bon con en o p oduc s h ough labels can
assis hem in making in o med decisions abou pu chasing low-ca bon
p oduc s. This, in u n, con ibu es o he o e all educ ion o ca bon
emissions [13]. Despi e he need o a signi ican change in pe sonal
ood consump ion, esea ch indica es ha people a ely conside hei
die a y choices when asked wha hey can do o help he en i onmen
[14] and o en unde es ima e he en i onmen al impac o hei ood
[15,16]. Meanwhile, in some cases, consume s may be eluc an o pay
mo e o ca bon-labeled p oduc s. The gene al lack o awa eness
* Co esponding au ho a : College o Economics and Managemen , No hwes A&F Uni e si y: NO.3 Taicheng Road, Yangling, Shaanxi, China.
E-mail add ess: [email p o ec ed] (Y. Wang).
Con en s lis s a ailable a ScienceDi ec
Sus ainable Fu u es
jou nal homepage: www.sciencedi ec .com/jou nal/sus ainable- u u es
h ps://doi.o g/10.1016/j.s .2024.100363
Recei ed 13 June 2024; Recei ed in e ised o m 30 Augus 2024; Accep ed 1 No embe 2024
Sus ainable Fu u es 8 (2024) 100363
A ailable online 3 No embe 2024
2666-1888/© 2024 The Au ho s. Published by Else ie L d. This is an open access a icle unde he CC BY-NC license (
h p://c ea i ecommons.o g/licenses/by-
nc/4.0/ ).
ega ding how die a y decisions a ec he en i onmen emains a majo
obs acle o educing emissions o g eenhouse gases caused by ood [17].
Globally, he e is a g owing body o esea ch on ca bon labeling,
pa icula ly ega ding how i a ec s consume pu chasing beha io [18,
19]. Se e al s udies ha e been done on consume s om a ious
geog aphic and cul u al backg ounds [20]. Ne e heless, e en i he e
ha e been some p elimina y in es iga ions o esea ch on Chinese
consume s, such as a s udy o ca bon-labeled bee among u ban Chinese
cus ome s [21], addi ional empi ical esea ch is equi ed o ob ain a
deepe unde s anding o he p e e ences and beha io al pa e ns o
a ious consume g oups. Cu en ly, go e nmen s, p oduce s, and
me chan s ha e no been able o ecei e comp ehensi e p omo ional
ad ice o guidance. To achie e he ansi ion o a low-ca bon con-
sump ion pa e n, China should in eg a e ca bon labeling in o a wide
ange o consume p oduc ca ego ies. To add ess he esea ch gaps
men ioned abo e, his pape aims o in es iga e Chinese consume s’
pe cep ions o ca bon-labeled ag icul u al p oduc s (CAP), including
hei willingness o pay and he speci ic amoun hey a e willing o pay
o di e en ypes o CAP. The inno a ions a e as ollows: i s ly, his
s udy c ea es a mo e ho ough explana o y amewo k, in eg a es he
No m Ac i a ion Model (NAM) and he Theo y o Planned Beha io
(TPB), and expands he o iginal model by adding ex e nal a iables
(such as isk pe cep ion, low-ca bon awa eness, and pe sonal knowl-
edge). All hese enhancemen s signi ican ly imp o e he modelʼs ca-
paci y o explain he willingness o he CAP and pu chasing beha io . In
addi ion o examining he di ec e ec s o esponden s’subjec i e
no ms, pe sonal no ms, and pe cei ed beha io al con ol on pu chase
in en ions, he s udy sheds ligh on he media ing a iables hese ac o s
use o a ec pu chase in en ions and beha io . Addi ionally, his s udy
con i ms ha isk pe cep ion mode a es he ela ionship be ween buy
in en ion and ac ion, p o iding a mo e comp ehensi e explana ion o
he inconsis ency be ween consume in en ion and beha io when
pu chasing CAP. Secondly, in o ma ion in e en ion is included in he
expe imen . This s udy uses an expe imen al design o explo e how
p o iding speci ic in o ma ion on ca bon labeling a ec s he publicʼs
WTP o CAP and how he ce ain y ha esponden s will choose o
imp o e he en i onmen changes. Th ough empi ical esea ch in spe-
ci ic cul u al and ma ke backg ounds, we p opose policies o p omo e
he implemen a ion o ca bon labels a all le els, including go e nmen
and en e p ises, o encou age widesp ead pa icipa ion in en i on-
men al p o ec ion and low-ca bon ac i i ies, ul ima ely achie ing “ca -
bon educ ion o all and bene i s o all.”
The emainde o he pape is s uc u ed as ollows: Sec ion 2 p e-
sen s he heo e ical amewo k and li e a u e e iew, Sec ion 3 de-
sc ibes he su ey’s me hodology and da a collec ion, Sec ion 4 p esen s
he model’s esul s, Sec ion 5 discusses he indings, and he inal sec ion
aises policy implica ions.
2. Li e a u e e iew and hypo heses
2.1. Ca bon labeling concep
The e is inc easing esea ch on ca bon labeling due o he u gen
need o ans o m he global low-ca bon economy. Ca bon labels can
success ully and e ec i ely aise consume unde s anding o he emis-
sions o mo e en i onmen ally haza dous oods, which can hen help
consume s choose mo e en i onmen ally iendly ood op ions [17].
Ra ing labels a e mo e e ec i e in guiding consume s o mo e sus ain-
able p oduc s han posi i e and nega i e labels [22]. Edenb and &
Lage k is [23] in es iga ed consume willingness o subs i u e
high-emissions mea p oduc s wi h lowe -emissions p o ein p oduc s,
including blends o mea and ege ables. They ound he a ic ligh
ca bon label a ec s choice beha io . In Canada and A gen ina, younge
consume s in he Ame icas exhibi di e ing pe cep ions o ca bon la-
beling, wi h hose who a e mo e educa ed demons a ing a p e e ence
o he a ic ligh ca bon label [24]. The g ea es impac is obse ed
when ca bon oo p in in o ma ion is exp essed in mone a y uni s and
colo -coded in a manne analogous o he a ic signal sys em [25].
T a ic ligh labels a e mos e ec i e in educing ca bon emissions,
p o iding empi ical suppo o he design o ca bon labels [26,27].
Howe e , he e a e also s udies ha ca bon labels don’ succeed in
a ac ing people’s a en ion when cus ome s a e unguided [28]. Ca bon
labeling has a posi i e bu small impac on sus ainable ood choices
[29]. As consume us in he label g ows, ca bon labeling boos s he
pe cei ed en i onmen al sus ainabili y o animal-based p oduc s bu
no ha o plan -based p oduc s.
Addi ionally, he “halo e ec ”o plan -based oods may lessen he
e ec s o ca bon labeling [30]. To change consume beha io , con-
sume s mus de elop us in labels and he o ganiza ions behind hem
[31]. This us and posi i e a i ude ema kably in luence he WTP and
he posi i e e ec o policy measu es on consume s’WTP [32]. In e -
es ingly, amily and pee in luences a e mo e likely o a ec consume s’
pu chasing decisions han media exposu e. This would appea o
emphasize he impo ance o social dynamics in p omo ing en i on-
men ally iendly consump ion [33,34].
By combining he esul s o hese s udies, we may conclude ha
ca bon labeling may encou age sus ainable consump ion, bu i s e ec s
may be a ec ed by cul u al, social, and psychological ac o s. In addi-
ion o enhancing ou knowledge o he mechanisms unde lying he
e ec s o ca bon labeling, in eg a ing na ional and in e na ional
esea ch o e s a solid scien i ic ounda ion o c ea ing mo e ocused
en i onmen al egula ions and ma ke ing s a egies. Fu u e esea ch
could u he explo e he bes p ac ices o ca bon labeling in di e en
cul u al con ex s and how o combine socio-cul u al ac o s o imp o e
i s accep ance and e ec i eness in he global ma ke .
2.2. Theo y o planned beha io
The TPB model has i s oo s in psychological and sociological he-
o ies and is based on he Theo y o Ra ional Beha io [35]. TPB, p o-
posed by Ajzen [36], is he classic social psychological model o
explaining people’s beha io al in en ions and ac ions. I is a powe ul
and widely used ool o e alua ing, modeling, and in es iga ing peo-
ple’s beha io abou ac i i ies, p oduc s, o se ices [36]. Acco ding o
he Theo y o Planned Beha io , a i udes, subjec i e no ms, and
pe cei ed beha io al con ol impac beha io al in en ions. A i udes
owa d he beha io e e o he deg ee o which a pe son has a a o -
able o un a o able e alua ion o assessmen o he beha io unde
Nomencla u e
Abb e ia ions
ATT A i udes owa d he beha io
AR Asc ip ion o esponsibili y
AC Awa eness o consequences
CAP Ca bon-labeled ag icul u al p oduc s
CVM Con ingen alua ion me hod
LA Low-ca bon awa eness
NAM No m Ac i a ion Model
PBC Pe cei ed beha io al con ol
PN Pe sonal no ms
PK Pe sonal knowledge o CAP
PB Pu chase beha io
PI Pu chase in en ion
RP Risk pe cep ion
SEM S uc u al equa ion modeling
SN Subjec i e no ms
TPB Theo y o Planned Beha io
WTP Willingness o pay
Y. Xu e al. Sus ainable Fu u es 8 (2024) 100363
2
discussion. Subjec i e no ms ep esen he pe cei ed social p essu e o
engage in a beha io o e ain om doing so. The hi d an eceden o
in en ion is he deg ee o pe cei ed beha io al con ol, which, as we’ e
seen, e e s o how easy o di icul he beha io is ega ded o be o
ca y ou . This an eceden is hough o e lec p io expe ience as well
as an icipa ed impedimen s. The Theo y o Planned Beha io sugges s
ha beha io al pe o mance is in luenced by beha io al in en ions,
which a e s onge i he indi idual has a mo e posi i e a i ude, eels
mo e p essu e om ex e nal no ms, o eels ha he o she has mo e
con ol o e his o he beha io [36]. When a pe son can clea ly un-
de s and he objec i e condi ion es ic ions, such as esou ces and
abili ies, ha he o she equi es o conduc a gi en beha io , pe cei ed
beha io al con ol can also di ec ly in luence he occu ence o an in-
di idual’s beha io .
The TPB model has been widely deployed o s udy sus ainable ood
consump ion beha io . Fo example, Ve mei and Ve beke [37] con-
duc ed a s udy wi h young people in Belgium. They ound ha pe sonal
a i udes, pe cei ed social impac s, pe cei ed consume e ec s, and
pe cei ed a ailabili y we e key ac o s in luencing sus ainable con-
sump ion in en ions. In a sepa a e s udy, Alam e al. [38] employed he
ex ended TPB amewo k o asce ain he ac o s in luencing sus ainable
ood consump ion beha io s in Malaysia. Thei indings indica ed ha
social no ms, pe cei ed alue, and pe cei ed consume e ec s and a -
i udes signi ican ly impac ed consump ion in en ions.
In con as , pe cei ed a ailabili y and pe cei ed consume e ec s
and in en ions signi ican ly a ec ed ac ual beha io . In China, Qi and
Ploege [39] e ised and ex ended he TPB by inco po a ing ace con-
sciousness and g oup consis ency in o he model, eplacing subjec i e
no ms o enhance he modelʼs applicabili y in Chinese consume s’in-
en ions o pu chase g een ood. They also included con idence and
pe sonal cha ac e is ics as model componen s o be e e lec he cu -
en consume en i onmen and ea u es. Du ing he COVID-19
pandemic, Qi and Ploege [40] ex ended he TPB o include he e ec s
o e hical a i udes, heal h awa eness, and COVID-19 o explain Chinese
consume s’g een ood pu chase in en ions du ing he cu en and
pos -pandemic pe iods. Acco ding o he indings, Chinese consume s’
in en ions o pu chase g een oods a e be e explained and p edic ed by
he expanded TPB model han by he o iginal TPB model.
In conclusion, he TPB and i s ex ended model p o ide a solid
heo e ical ounda ion o unde s anding consume s’sus ainable ood
consump ion beha io s unde di e en cul u al and en i onmen al
condi ions. Howe e , ew s udies ha e used he model o analyze he
public’s willingness and beha io o pu chase CAP and hei links wi h
each o he . Based on hese esul s, we p opose he ollowing hypo heses:
H1. A i udes owa d he beha io (ATT) posi i ely a ec pu chase
in en ion (PI) in he pu chase o CAP.
H2. Subjec i e no ms (SN) ha e a posi i e impac on PI o CAP.
H3. Pe cei ed beha io al con ol (PBC) has a a o able e ec on PI
in CAP pu chasing.
H4. PBC posi i ely in luences pu chase beha io (PB) in CAP
pu chasing.
H5. PI posi i ely in luences PB in he pu chasing o CAP.
2.3. No m ac i a ion model
NAM is a beha io al heo y ha Schwa z [41] de eloped o explain
and p edic indi idual p o-social beha io . NAM con ends ha people’s
p o-social/al uis ic in en ions and beha io s, such as olun ee ing hei
ime and helping o he s, esul om hei no ms, which a e inspi ed by
hei awa eness o p oblems and obliga ions [41]. Pe sonal No ms (PN),
Awa eness o Consequences (AC), and Asc ip ion o Responsibili y (AR)
a e he h ee p ima y elemen s o NAM. The e m PN deno es an in-
di idual’s sel -expec a ions o beha io s in each si ua ion, and AC is he
p opensi y o be awa e o he consequences o one’s ac ions on o he s
[41]. The mo e likely indi iduals a e o pe cei e si ua ions in e ms o
he consequences o hei ac ions on o he s, he mo e likely hey a e o
a end o he alues and no ms associa ed wi h hose in e pe sonal
consequences, c ea ing a sense o obliga ion o exp ess hose no ms. AR
is a pe son’s sense o whe he hey a e esponsible o he consequences
o hei ac ions [41].
NAM has become one o he mos in luen ial heo ies [42]. I has
been used o s udy a a ie y o en i onmen ally iendly beha io s,
including d one ood deli e y se ices [43], li e educ ion and li e
picking beha io s [44], and en i onmen ally iendly pes con ol
adop ion beha io s [45]. S eg and G oo [46] applied NAM o explain
a ious p o-social and p o-en i onmen al beha io al in en ions. They
disco e ed ha he in e ac ion be ween AC, AR, PN, and beha io al
in en ions is a chain-media ed model, meaning ha AC ac i a es PN
h ough AR, leading o PI. Acco ding o some esea che s, ATT, SN, and
PN all indi ec ly impac consume s’in en ions o ecycle [47]. Song
e al. [48] inco po a ed SN and en i onmen al conce n in o an ex ended
NAM, a guing ha PN, es ablished by consume s’AC and AR, signi i-
can ly impac s hei beha io al in en ion. In he con ex o he opic
s udied in his pape , consume s’AC and AR may inc ease hei PN, hus
leading o suppo o pu chasing CAP.
The s udy pu s ou he ollowing hypo hesis conside ing he analyses
men ioned abo e.
H6. AC has a a o able impac on AR in pu chases o CAP.
H7. AC has a posi i e in luence on PN when pu chasing CAP.
H8. AR has a signi ican posi i e impac on PN when pu chasing
CAP.
H9. When consume s buy CAP, PN has a posi i e e ec on PI.
H10. SN has a posi i e in luence on PN when pu chasing CAP.
2.4. Ex ension o TPB and NAM
Applying and expanding heo e ical amewo ks a e essen ial o a
mo e p o ound comp ehension o consume beha io wi hin sus ainable
ood consump ion. The TPB and NAM amewo ks ha e been ex ensi ely
u ilized o p edic and explain he en i onmen al beha io o in-
di iduals [49]. Ne e heless, he ex ension and in eg a ion o hese
heo ies become especially impo an as social and en i onmen al
challenges become complex. Ajzen [36] s a es ha TPB is an open heo y
o which addi ional a iables can be added i hey cap u e a signi ican
po ion o beha io al di e ences. Recen s udies such as he TPB-NAM
in eg a ion model ha e p o en supe io o he o iginal TPB model
when s udying ac o s a ec ing Vie namese a me s’in en ion owa d
o ganic ag icul u al p oduc ion [50]. He and Sui [51] in es iga ed he
willingness o Chinese college s uden s o consume g een ood by in e-
g a ing he TPB wi h he NAM. They ound ha SN, ATT, and PN we e
he key ac o s in luencing s uden s’willingness o buy, wi h ATT ha -
ing he s onges di ec e ec on willingness o buy. This wo k illus a es
he unc ion o NAM in p omo ing he o ma ion o PN while also
expanding he applica ion o TPB. The empi ical s udy by Vie nam Le
and Nguyen [52] con i ms he impo ance o ATT, social no ms, and
pe sonal no ms in o ganic ood pu chase in en ions. The s udy o e s
new empi ical e idence in suppo o NAM, emphasizing he signi ican
impac o en i onmen al awa eness and knowledge abou o ganic ood
on consume pu chase in en ions h ough a i udes.
Fu he mo e, Salmi aa a e al. [53] p o ide no el insigh s in o un-
de s anding sus ainable ood choices by delinea ing he dis inc ion be-
ween desc ip i e and no ma i e social no ms. Thei esea ch e eals
he impo ance o desc ip i e no ms in ac ual and expec ed ood choices,
while SN ails o show he expec ed ele ance. These indings challenge
adi ional heo ies and o e new s a egies o in luencing consume
beha io h ough desc ip i e no ms. Acco ding o hese esea ches,
combining TPB and NAM o e s a mo e ho ough analy ical amewo k
and highligh s he ela i e signi icance o a ious mo i a ing ac o s in
ce ain cul u al and ma ke con ex s [54]. We can be e unde s and
consume psychological and beha io al mechanisms when aced wi h
Y. Xu e al. Sus ainable Fu u es 8 (2024) 100363
3
sus ainable ood choices due o his heo e ical ex ension and in-dep h
empi ical s udy. This will enable us o de elop mo e use ul ecom-
menda ions and ac ics o encou aging sus ainable consump ion.
Awa eness is ealizing o comp ehending a si ua ion o ac [55].
Residen accep ance and beha io al implemen a ion a e posi i ely
impac ed by hei gene al pe cep ion, sa is ac ion, and posi i e a i udes
[56]. Acco ding o Xia e al. [57], aising consume knowledge o low
ca bon emissions is ad an ageous o ca bon educ ion. Pe sonal
knowledge can be de ined as he ex en o which a consume is awa e o
a speci ic p oduc , se ice, o si ua ion [58]. Consume s’le el o pe -
sonal knowledge ega ding a p oduc can in luence hei a i udes. Fo
example, Li e al. [10] ound ha consume s wi h in-dep h knowledge o
low-ca bon p oduc s a e mo e likely o hold posi i e a i udes, which is
consis en wi h he “ATT”componen o he heo e ical planned
beha io (TPB) p oposed by Ajzen [36]. In he con ex o sus ainable
consump ion, Ding e al. [49] conduc ed a comp ehensi e e iew o he
ole o pe sonal knowledge in in luencing consume choices owa ds
en i onmen ally iendly p oduc s. S udies by Xu and Lin [59] and Qi
and Ploege [39] ha e demons a ed ha pe sonal knowledge is a
pi o al ac o in luencing consume pu chasing in en ions, pa icula ly
in g een and heal hy p oduc s. In his s udy, “pe sonal knowledge”de-
sc ibes he esponden s’knowledge and unde s anding o CAP. This
knowledge can po en ially in luence hei a i udes, decision-making
p ocesses, and, ul ima ely, hei pu chasing beha io . Acco ding o
esea ch on consume beha io and willingness o pay, isk pe cep ion
and isk p e e ence a e signi ican ac o s o ood accep abili y, which
has p o ound implica ions o consume beha io and hei willingness
o pay [58,60,61]. Bha i and U Rehman [62] examined he ela ion-
ship be ween di e en ac o s, including pe cei ed bene i s, pe cei ed
isks, and online shopping beha io , wi h he media ing ole o con-
sume pu chase in en ion. The indings show ha isk pe cep ion ha ms
online shopping beha io and ha hese isks mus be minimized o
inc ease hei sense o secu i y.
Based on he abo e heo ies, his pape in eg a es he o iginal TPB
and NAM models. I adds h ee ex e nal a iables (i.e., pe sonal
knowledge, low-ca bon awa eness, and isk pe cep ion) o analyze he
en i onmen ally iendly beha io o he public’s beha io al willingness
o pu chase CAP. The ollowing hypo heses ha e eme ged, and he
esea ch amewo k is depic ed in Fig. 1.
H11. Consume s’ATT is posi i ely impac ed by pe sonal knowledge
(PK) o CAP.
H12. Low-ca bon awa eness (LA) among consume s in luences hei
AC o buy CAP.
H13. The associa ion be ween WTP and PB o CAP is mode a ed by
isk pe cep ion (RP).
3. Ma e ial and me hods
3.1. Con ingen alua ion me hod
The e a e se e al app oaches o elici indi iduals’willingness o pay:
con ingen alua ion, choice expe imen , and expe imen al auc ion
[63–65]. The con ingen alua ion me hod (CVM) was ini ially
employed in 1958 o analyze non-ma ke p ices o ec ea ional se ices
in he Delawa e Ri e Basin egion o he Uni ed S a es [66]. CVM has
been u ilized in a ious applica ions [59,67]. Typically, CVM employs
ques ionnai es ha le esponden s explici ly exp ess hei p e e ences
o speci ic goods in mone a y e ms [68]. The mone a y alue epo ed
by esponden s is gene ally exp essed in e ms o willingness o pay, i.e.,
he maximum mone a y alue ha an indi idual would be p epa ed o
pay o a hypo he ical imp o emen p og am [68]. Al e na i ely, will-
ingness o pay can be he minimum amoun an indi idual will accep as
compensa ion o he change [68]. Also, CVM has mos ly been used o
measu e “p e e ences o goods o se ices o which a con en ional
ma ke does no exis ”[69]. The use o CVM is deemed app op ia e, and
hence, CVM has been chosen o his s udy.
3.2. Econome ic model
S uc u al Equa ion Modeling (SEM) is a s a is ical me hod o
analyzing complex ela ionships among a iables, combining ac o and
pa h analysis. O igina ing in he 1970s, SEM has become popula in
economics [70]. I consis s o wo pa s: he measu ed model, which
links obse ed and la en a iables, and he s uc u al model, which
connec s la en a iables. Obse ed a iables a e di ec ly measu able,
Fig. 1. Resea ch amewo k.
Y. Xu e al. Sus ainable Fu u es 8 (2024) 100363
4

while la en a iables canno be measu ed di ec ly and mus be
measu ed wi h he help o obse ed a iables. The equa ion o he
measu emen model is as ollows:
X=Λxξ+δ(1)
Y=Λy
η
+
ε
(2)
The equa ion o he s uc u al model is as ollows:
η
=B
η
+Γξ+ζ(3)
Table A1 displays he symbols and explana ions o he h ee equa-
ions abo e. Eigh la en a iables in luence consume s’pu chase
in en ion and pu chase beha io , and a s uc u al equa ion model is
es ablished o s udy his in luence.
3.3. Ques ionnai e design
Ques ionnai es a e commonly u ilized da a collec ion su ey ools
wi hin con ingen alua ion me hod s udies [71]. The me hodology
measu es he alue consume s place on non-ma ke p oduc s and en-
ables esea che s o de e mine a i udes and iews. Consequen ly, his
esea ch uses a ques ionnai e as a da a collec ion ins umen .
The ques ionnai e is spli in o ou blocks. The i s pa is an
in oduc ion o he su ey, which in oduces he esponden s o he
opic o he ques ionnai e, he esea ch o ganiza ion, and he goal and
ele ance o he s udy. S ep 1 asks esponden s o comple e indi idually
a se ies o ques ions ha cap u ed hei ini ial p e e ences and willing-
ness o pay wi hou en e ing any in o ma ion. In S ep 2, e ms in ol ed
in he ques ionnai e a e explained o imp o e he comp ehensibili y o
he ques ionnai e. Based on he heo e ical amewo k o TPB-NAM and
combined he cu en ma ke si ua ion o ag icul u al p oduc s wi h
pas esea ch indings ([72]; O eng-Pep ah e al. [73,74]), we ha e
designed a o al o 35 measu emen ques ions. All ques ions we e
measu ed on a i e-poin Like scale anging om “comple ely
disag ee” o “comple ely ag ee” ega ding low ca bon awa eness,
asc ip ion o esponsibili y, pe cei ed beha io al con ol, pe cep ion o
isk, and so on (Table 1).
CVM is he main opic o he hi d sec ion, which concen a es on
how o e alua e consume s’willingness o pay and beha io . A e
examining and con as ing se e al WTP boo s apping echniques, we
choose o employ he paymen ca d as a boo s apping mechanism o
p e en non- e lec i e bias in he ques ionnai e. We also c ea e a su ey
wi h wo ques ions o accoun o p o es answe s. I consis s o sample
selec ion ques ions and heu is ic ques ions as ollows. Rega ding “ca -
bon neu al”milk—cu en ly o e ed o sale in China’s ag icul u al
ma ke — esponden s a e in o med ha labeling he goods would
necessi a e measu ing g eenhouse gas emissions du ing p oduc ion and
ob aining ce i ica ion om a hi d-pa y o ganiza ion, which would
come a an ex a expense o he manu ac u e . Nex , we asked e-
sponden s i hey would pay mo e o CAP. I he answe is “yes”, he
nex leading ques ion is o ask how much ex a hey/he would like o pay
o each CAP. The poll indica es ha he e a e cu en ly ca bon-labeled
ag icul u al p oduc s on he ma ke , such as “ze o-ca bon” ege ables
and ca bon-neu al milk. We choose he ep esen a i e ype o ag icul-
u al p oduc s among many a ie ies and alk wi h he pa icipan s in
he in e iews, conside ing ac o s like he ypes o ag icul u al p od-
uc s, he a ailabili y o each ype in di e en egions, and he equency
o daily consump ion by consume s. Using he p ice da a al eady
collec ed, we in o m each esponden abou he coun yʼs a e age
ma ke p ice o se e al ag icul u al p oduc s. A he same ime, based on
he p ice, we gi e speci ic amoun s in pe cen age inc emen s ha he
esponden s chose hei la ges willingness o pay. I a esponden an-
swe s “no” o he sample selec ion ques ion, esponden s who indica e
hey a e unwilling o pay will be gi en a se ies o easons o explo e hei
in en ions. The a e age willingness o pay in he paymen ca d ques-
ionnai e can be de e mined o disc e e a iables using he
Table 1
De ini ion and desc ip ion o a iables.
Va iable Code I em Re e ences
Awa eness o
Consequences
AC01 Pu chasing high ca bon dioxide
emissions om ag icul u al
p oduc s will cause se ious
pollu ion and en i onmen al
damage.
[75]
AC02 Pu chasing ca bon-labeled
ag icul u al p oduc s can educe
en i onmen al pollu ion.

AC03 Pu chasing ca bon-labeled
ag icul u al p oduc s can ensu e
he quali y and sa e y o
ag icul u al p oduc s, which
bene i s us all.

Asc ip ion o
Responsibili y
AR01 As a consume , I should bea some
esponsibili y o educing ca bon
dioxide emissions.
[76]
AR02 I eel esponsible o
en i onmen al issues caused by
no pu chasing ca bon-labeled
ag icul u al p oduc s.

AR03 I would eel guil y i I didn’ buy
ag icul u al i ems wi h ca bon
labels, con ibu ing o inc eased
ca bon dioxide emissions.

AR04 I belie e ha e e y consume
bea s some esponsibili y o he
en i onmen al and social
p oblems caused by he
p oduc ion and consump ion o
ag icul u al p oduc s.

A i udes owa d
he Beha io
ATT01 I belie e ha pu chasing ca bon-
labeled ag icul u al p oduc s is
bene icial o he en i onmen .
[77]
ATT02 I belie e pu chasing ca bon-
labeled ag icul u al p oduc s is a
wise choice.

ATT03 Pu chasing ca bon-labeled
ag icul u al p oduc s will make
me eel physically and men ally
pleasan .

Low-ca bon
awa eness
LA01 When shopping, I keep plas ic
shopping bags and euse hem.
[78]
LA02 When p in ing, I ac i ely use bo h
sides o each shee o pape .

LA03 I o en pay a en ion o a icles o
epo s ela ed o en i onmen al
issues.

Pe cei ed
Beha io al
Con ol
PBC01 The p ice o ca bon-labeled
p oduce signi ican ly in luences
my decision o pu chase i .
[73]
PBC02 I hink ha consume s ind i
di icul o pu chase i ems wi h a
ca bon label because o he high
p ices.

PBC03 I am willing o buy ca bon-labeled
p oduc s when I ha e con idence
in hei en i onmen al bene i s.

Pu chase
In en ion
PI01 I am glad o pu chase ca bon-
labeled ag icul u al p oduc s.
[73,76]
PI02 I am likely o pu chase ca bon-
labeled ag icul u al p oduc s in
he u u e.

PI03 I plan o buy mo e ca bon-labeled
ag icul u al p oduc s in he
u u e.

PI04 I would ecommend ca bon-
labeled ag icul u al p oduc s o
my ela i es and iends.

Pe sonal
knowledge o
CAP
PK01 I unde s and he concep o
ca bon-labeled ag icul u al
p oduc s (such as “ze o-ca bon”
ege ables, ca bon-neu al milk,
e c.).
[79]
(con inued on nex page)
Y. Xu e al. Sus ainable Fu u es 8 (2024) 100363
5
ma hema ical expec a ion o mula.
E(WTP) = ∑
n
i=1
Pibi(4)
whe e E(WTP) is he maximum a e age alue o willingness o pay o
each CAP; P
i
is he p obabili y o esponden s selec ing each bid alue; b
i
is he bid amoun . The maximum a e age willingness o esponden s o
pay can be calcula ed by Eq. (4). In his pape , we combine he ele an
li e a u e [81] o measu e consume s’ac ual pu chase o CAP using wo
measu es, i.e., whe he hey pu chased CAP in he pas yea and he
exac equency o consump ion. The las pa is he socioeconomic
cha ac e is ics o he esponden s, including gende , age, cu en esi-
dence, educa ion le el, mon hly income, e c.
3.4. Da a collec ion
To co ec inaccu a e o eadily miscons ued con en , a pilo poll
was ca ied ou wi h 60 andomly chosen pa icipan s in Oc . 2022. The
o mal su ey was conduc ed om Ap il o June 2023 in Shanghai,
Nanjing, Wuhan, and Xi’an, China. The esea che s a e highly ained
g adua e and doc o al s uden s. Ta ge esponden s a e 18 yea s o age
o olde . A o al o 641 esponden s ag eed o pa icipa e in he esea ch.
A e excluding ques ionnai es wi h missing alues o ou lie s based on
he a iables equi ed o his esea ch, 580 alid samples we e eco -
e ed, wi h an e ec i e eco e y a e o 90.48 %. The demog aphic
cha ac e is ics o he sample da a a e as ollows. In e ms o gende ,
he e is an equal dis ibu ion o males and women (51.72 % and 48.28
%, espec i ely); in e ms o age, he p opo ion o hose aged 28 and
below eaches 70.86 %; and in e ms o educa ion, 90.69 % o he
samples ha e a high school diploma abo e. Table 2 p esen s a b ie
o e iew o demog aphic da a.
4. Resul s
4.1. Willingness o pay o ca bon-labeled ag icul u al p oduc s
This sec ion examines esponden s’WTP o i e dis inc CAP.
Desc ip i e s a is ics a e hen used o u he explo e dispa i ies in e-
sponden s’WTP and possible easons o consume s’ eluc ance o
pu chase CAP. Only 29.83 % o he 580 esponden s a e unwilling o pay
he CAP p emium, lea ing 70.17 % eage o do so. This sugges s ha
he e is al eady some basis o mo ing o wa d wi h he ca bon labeling
sys em in e ms o ini ial willingness o do so.
As shown in Table 3, he esul s demons a e ha emale esponden s
ha e sligh ly highe WTP on ca bon-labeled milk and co n han male
esponden s. In con as , male esponden s ha e a highe p emium WTP
on ca bon-labeled ui s, ege ables, and eggs han emale esponden s,
indica ing ha WTP does no appea o be in luenced by gende . Re-
sponden s unde 40 ha e he highes WTP o mos o CAP, and
Table 1 (con inued)
Va iable Code I em Re e ences
PK02 I unde s and he quali y
cha ac e is ics o ca bon-labeled
ag icul u al p oduc s (such as
“ze o-ca bon” ege ables, ca bon-
neu al milk, e c.).

PK03 I am amilia wi h he cos s
associa ed wi h ca bon-labeled
ag icul u al p oduc s (such as
“ze o-ca bon” ege ables, ca bon-
neu al milk, e c.).

Pe sonal No ms PN01 To sa egua d he en i onmen , I
should limi he numbe o
ag icul u al i ems I buy ha
elease much ca bon dioxide.
[75]
PN02 I eel mo ally obliga ed o
con ibu e o educing ca bon
dioxide emissions by pu chasing
ca bon-labeled ag icul u al
p oduc s.

PN03 I conside i a mo al du y o
socie y o pu chase ca bon-
labeled ag icul u al p oduc s o
educe ca bon dioxide emissions.

PN04 E e yone is esponsible o
conside ing he en i onmen al
impac when pu chasing
ag icul u al p oduc s.

Risk Pe cep ion PR01 I wo y ha I migh be was ing
money when buying ca bon-
labeled ag icul u al p oduc s.
Ma inho
e al., 2022;
[80]
PR02 I am conce ned ha ca bon-
labeled ag icul u al p oduc s may
no p o ide he necessa y
bene i s.

PR03 I wo y ha ca bon-labeled
ag icul u al p oduc s may no
pe o m as well as ad e ised.

PR04 Conside ing a ious ac o s, I
hink he e a e isks associa ed
wi h pu chasing ca bon-labeled
ag icul u al p oduc s.

Subjec i e No ms SN01 I p e e ca bon-labeled
ag icul u al p oduc s because my
iends and amily app o e
pu chasing hem.
[77]
SN02 My iends and amily hope I will
buy ag icul u al i ems wi h a
ca bon label, so I would like o do
so.

SN03 I p e e o buy ca bon-labeled
ag icul u al p oduc s because he
go e nmen encou ages me.

SN04 I p e e o buy ca bon-labeled
ag icul u al p oduc s because o
he en i onmen ally iendly
examples.

Table 2
Desc ip i e s a is ics o socio-economic cha ac e is ics o esponden s.
Cha ac e is ic F equency Pe cen (%)
Gende  
Female 280 48.28
Male 300 51.72
Age  
[18,28] 411 70.86
[29,39] 112 19.31
40 and abo e 57 9.83
Occupa ion  
Voca ional o blue-colla wo ke s 30 5.17
Ci il se an 50 8.62
Company s a 172 29.65
S uden 264 45.52
F eelance 35 6.04
No wo king/Re i ed 29 5
Region  
Eas 301 51.90
Middle 243 41.90
Wes 36 6.20
Mon hly Income (CNY)  
5000 o below 323 55.69
5001–10,000 107 18.45
10,001–20,000 101 17.41
20,000 abo e 49 8.45
Educa ion  
High School and below 54 9.31
Unde g adua e 372 64.14
Mas e o abo e 154 26.55
Household Size  
Two people o below 55 9.48
3–4 people 404 69.66
O e i e people 121 20.86
Y. Xu e al. Sus ainable Fu u es 8 (2024) 100363
6
esponden s o e 40 ha e he highes WTP ega ding he p emium o
exclusi ely ca bon-labeled eggs. This migh be because di e en age
g oups ha e di e en opinions on he same issue. Eas e n Chinese e-
sponden s ha e he g ea es p emium WTP, ollowed by cen al and
wes e n Chinese esponden s. This may be because he eas e n pa o
he coun y is economically de eloped, and i s esiden s ha e ela i ely
s onge inancial esou ces and highe incomes. The household loca ion
is an impo an geog aphical ac o o consume s, and i is ela ed o he
o ma ion o hei pe cep ions, belie s, e c., which in u n a e ela ed o
ood consump ion beha io .
Meanwhile, esponden s wi h mon hly incomes o ¥20,000 o mo e
ha e he highes p emium WTP o 80 % o CAP men ioned in he su -
ey. I is no di icul o unde s and ha p ice is one o he main ac o s
in luencing consume s’decisions o buy p oduc s. Acco ding o he
s udy, he amily dimension appea s o impac consume s’WTP, wi h
esponden s wi h smalle amily sizes epo ing highe WTP. A one-way
analysis o a iance (ANOVA) was pe o med o explo e whe he socio-
s a is ical cha ac e is ics ha e a ole in esiden s’WTP o CAP. Six in-
dependen a iables, such as gende , age, and educa ion, and one
dependen a iable, willingness o pay, we e examined. The analysis’s
indings e eal ha h ee a iables— esponden s’place o esidence,
deg ee o educa ion, and occupa ion—subs an ially impac hei WTP
o CAP. In con as , he emaining a iables ailed o pass he es . This
implies ha an indi idual’s inclina ion o buy a CAP is somewha
in luenced by hei place o esidence’s ai s, le el o educa ion, and
line o wo k.
Among he esponden s who a e no willing o pay a p emium o
CAP, he mos common answe (almos 20 %) is ha hey canno pay o
pe sonal inancial easons bu would be willing o pay i hei income
inc eased. This is ollowed by a eluc ance o spend mo e money (16 %)
and a belie ha he go e nmen should shoulde mo e esponsibili y o
educing emissions han he esponden s should (11 %). Mo e han 9 %
o pa icipan s eel ha ag icul u al p oduc s had no signi ican en i-
onmen al impac a any poin along he supply chain, om p oduc ion
o consump ion, and ano he 8 % s a es ha he eason o hei e usal
is ha hey a e unwilling o y new hings. Some pa icipan s o e
“o he s”jus i ica ions o declining o pay a p emium o CAP, wi h a
signi ican po ion ci ing hei belie ha ag icul u al p oduc s a e
necessa y o ou daily li es, ha hey shouldn’ be excessi ely p iced,
and ha we should look o ways o cu cos s. Cu en ly, he e a en’
enough op ions on he ma ke , and he ca bon labeling ma ke should be
expanded. Some esponden s also no e ha hei decisions would be
impac ed i hey didn’ know he au hen ici y and sa e y o CAP a ail-
able on he ma ke .
4.2. Measu emen model es ing
As seen h ough he esul s in Table 4, all he ac o loadings ha e
alues in he ange o 0.631–0.913, which mee s he c i e ia p oposed by
Hai e al. [82]. A e analyzing he ac o loadings, he eliabili y and
alidi y o he ques ionnai e we e analyzed. C onbach’s alpha was used
o con i m he eliabili y o he ac o s, and 0.7 was chosen as he
s anda dized c i ical alue, as indica ed by Nunnally and Be ns ein [83].
The o e all C onbach’s alpha o all la en a iables was 0.960, and he
es ima es o he ac o s’C onbachʼs alpha anged om 0.722 o 0.928,
all o which we e abo e 0.7. This sugges s ha he esponden s’in e nal
consis ency in assessing he obse ed a iables eached an accep able
le el, as did he eliabili y o he ac o s. Addi ionally, he s udy con-
duc ed KMO and Ba le ’s es s on he ac o s (Table 5). KMO es ima-
ions g ea e han 0.7 implied good adequacy o he sample collec ed
[84]. The a e age ex ac ed analysis o a iance (AVE) anged om
0.479 o 0.766, wi h nea ly all o hem being g ea e han 0.5, and he
composi e eliabili y (CR) o all la en a iables anged om 0.733 o
0.929, all o which we e g ea e han 0.7. The s udy demons a es good
alidi y and eliabili y in examining he p oposed hypo heses as all he
indica o s me he c i e ia [82].
4.3. S uc u al model assessmen
Se e al key me ics o de e mining model i a e he NC alue
(CMIN/DF), oo mean squa e o he app oxima ion e o (RMSMA),
goodness-o - i index (GFI), compa a i e i index (CFI) and no ma i e
i index (NFI). In gene al, a easonable i can be de ined as ha ing NC
alues be ween 1 and 5, RMSEA <0.08, and GFI, CFI, and NFI g ea e
han 0.8 [85–87]. Table 6 shows ha , ollowing a ew model modi i-
ca ions, all i ness indica o s pe o m well, demons a ing ha he
model o he pu chasing beha io o consume s o CAP and he collec ed
da a i well.
The s udy’s hypo heses a e pu o he es based on he s uc u al
modeling. Fig. 2 displays he speci ic isualiza ion indings. The s udy
Table 3
Willingness o pay o ca bon-labeled ag icul u al p oduc s.
Va iables Ca ego y WTP-Milk (%) WTP-Co n (%) WTP-Banana (%) WTP-Toma o (%) WTP-Egg (%)
To al 27.50 29.73 26.86 26.51 24.26
Gende Male 27.06 29.59 27.15 27.33 24.91
Female 27.96 29.88 26.55 25.63 23.56
Age [18,28] 27.83 29.59 26.74 26.22 24.01
[29,39] 27.22 31.36 27.55 27.60 24.55
40 and abo e 25.70 27.65 26.63 26.57 25.62
Occupa ion Voca ional o blue-colla wo ke s 31.45 30.46 30.19 31.07 29.12
Ci il se an 24.78 27.04 39.52 26.80 23.92
Company s a 27.83 25.70 27.03 26.84 24.29
S uden 26.18 27.98 25.65 24.82 22.67
F eelance 32.46 35.59 32.70 32.68 31.43
No wo king/Re i ed 32.09 33.38 29.53 27.21 25.50
Region Eas 28.85 31.53 27.74 27.24 25.01
Middle 26.38 28.17 26.39 26.24 23.76
Wes 23.71 25.20 22.71 22.16 21.34
Mon hly Income (CNY) 5000 o below 26.57 28.02 26.00 25.13 23.21
5001–10,000 29.66 32.44 27.86 27.61 25.25
10,001–20,000 27.66 29.99 27.59 28.49 25.56
20,000 abo e 28.55 34.57 28.86 29.09 26.38
Educa ion High School and below 28.70 31.69 26.73 28.57 28.45
Unde g adua e 27.74 29.80 27.01 26.45 23.94
Mas e o abo e 26.48 28.87 26.57 25.92 23.56
Household Size Two people o below 30.48 33.18 28.61 28.44 26.06
3–4 people 27.28 29.55 27.05 26.50 24.50
O e i e people 26.85 28.76 25.46 21.35 22.64
Y. Xu e al. Sus ainable Fu u es 8 (2024) 100363
7
esul s indica e ha ATT signi ican ly and posi i ely in luences PI
(β=0.219, P<0.001) wi hin he heo e ical amewo k o TPB, hus
suppo ing H1. SN posi i ely in luences PI (β=0.404, P<0.001) and H2
is suppo ed. H3 is con i med, wi h a signi ican posi i e e ec o PBC on
PI (β=0.408, P<0.001). Among hem, he s anda dized pa h coe icien
o PBC is signi ican ly highe han ha o ATT and SN, indica ing ha
he main ac o s in luencing consume s’WTP abou CAP a e hei con-
ol o e ele an esou ces like money, ime, knowledge, and skills, as
well as hei access o in o ma ion abou CAP. PBC has a signi ican
posi i e e ec on PB (β=0.261, P=0.002), and H4 is alid. This sugges s
ha PBC can also di ec ly in luence he occu ence o a consume ’s
beha io when he o she can pe cei e he objec i e cons ain s, such as
esou ces and capabili ies, ha he o she needs o pe o m a ce ain
beha io . The signi icance es e uses H5 wi h he esul ha PI ha ms
PB (β=− 0.307, P<0.001). In he amewo k o NAM, consume s’AC o
pu chasing CAP posi i ely a ec s hei AR (β=0.683, P<0.001) and PN
(β=0.435, P<0.001), suppo ing H6 and H7. Consume s’AR posi i ely
a ec s PN (β=0.389, P<0.001), implying ha a consume ’s sense o
esponsibili y o he ad e se consequences o ailing o pu chase CAP
ac i a es his o he sense o mo al obliga ion o pu chase hem, and H8
is alida ed. The posi i e e ec o consume s’PN on PI passes he sig-
ni icance es (β=0.113, p=0.002); hus, H9 holds, meaning ha people
wi h g ea e e hical obliga ions ha e a highe CAP pu chase in en ion.
In he ex ended TPB-NAM heo e ical amewo k, he hypo hesized e-
la ionships o SN posi i ely a ec ing PN (β=0.164, P<0.001), con-
sume s’pe cep ions o CAP a ec ing hei ATT (β=0.6, P<0.001), and
consume s’low-ca bon awa eness a ec ing hei AC (β=0.903, P<
0.001) all pass he signi icance es , and H10, H11, and H12 a e
con i med, indica ing ha p essu e om socie y posi i ely a ec s hei
sense o mo al obliga ion owa ds he ac o pu chasing CAP and ha he
le el o consume s’knowledge o he backg ound and exis en ial sig-
ni icance o he p oposed CAP signi ican ly and posi i ely a ec s hei
ATT. A he same ime, he mo e en i onmen ally conscious cus ome s
hemsel es a e, he mo e hey a e awa e o he ha m ha no buying
CAP can do o he en i onmen .
4.3.1. Mode a ing e ec s
The SEM esul s indica e ha pu chase in en ion nega i ely in-
luences pu chase beha io . To unde s and he mechanism o RPʼs in-
luence in he p ocess o PI’s e ec on consume s’CAP pu chase,
s uc u al equa ion modeling wi h la en a iable in e ac ion e ms was
cons uc ed using AMOS 26.0, and he mode a ing e ec o he
in en ion-beha io gap was analyzed based on he heo y o likelihood.
Table 4
Validi y and eliabili y o he s udy.
Va iable Coding Fac o loading C onbach’s alpha Composi e eliabili y A e age a iance ex ac ed (AVE)
Awa eness o Consequences AC01 0.631 0.796 0.804 0.581
AC02 0.795   
AC03 0.845   
Asc ip ion o Responsibili y AR01 0.649 0.851 0.857 0.602
AR02 0.831   
AR03 0.826   
AR04 0.784   
A i udes owa d he Beha io ATT01 0.855 0.890 0.892 0.735
ATT02 0.889   
ATT03 0.826   
Low-ca bon awa eness LA01 0.660 0.730 0.733 0.479
LA02 0.735   
LA03 0.678   
Pe cei ed Beha io al Con ol PBC01 0.668 0.722 0.762 0.519
PBC02 0.66   
PBC03 0.822   
Pu chase In en ion PI01 0.859 0.928 0.929 0.766
PI02 0.87   
PI03 0.891   
PI04 0.88   
Pe sonal Knowledge o CAP PK01 0.795 0.874 0.8772 0.705
PK02 0.913   
PK03 0.806   
Pe sonal No ms PN01 0.822 0.886 0.889 0.666
PN02 0.86   
PN03 0.805   
PN04 0.776   
Risk Pe cep ion PR01 0.686 0.877 0.879 0.647
PR02 0.85   
PR03 0.855   
PR04 0.816   
Subjec i e No ms SN01 0.907 0.905 0.909 0.715
SN02 0.912   
SN03 0.82   
SN04 0.73   
Table 5
KMO and Ba le ’s es esul s o ac o analysis.
KMO and Ba le ’s Tes
Kaise –Meye –Olkin Measu e o Sampling Adequacy. 0.958
Ba le ’s Tes o Sphe ici y App ox. Chi-Squa e 16,148.911
Deg ee o eedom 630
Signi icance 0.000
Table 6
Resul s o model i ness es .
Measu e Th eshold Es ima e In e p e a ion
CMIN/DF (NC) 1<NC <5 4.957 Accep able
RMSEA <0.1 0.083 Accep able
GFI >0.8 0.810 Accep able
CFI >0.8 0.878 Accep able
NFI >0.8 0.852 Accep able
PCFI >0.5 0.765 Accep able
PNFI >0.5 0.742 Accep able
Y. Xu e al. Sus ainable Fu u es 8 (2024) 100363
8