In e na ional Jou nal o Cu en Science Resea ch and Re iew
ISSN: 2581-8341
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DOI: 10.47191/ijcs /V8-i10-08, Impac Fac o : 8.048
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Cogni i e Dissonance in Online Shopping Expe iences and Impulsi e
Buying Among E-Comme ce Use s in Indonesia
Bayu Cunda Sa ia1, Re no Tanding Su yanda i2
1,2Mas e o Managemen , Sebelas Ma e Uni e si y, Indonesia
ABSTRACT: This s udy aims o analyze he in luence o Online Cus ome Shopping Expe ience on Impulsi e Buying and
Cogni i e Dissonance in he con ex o e-comme ce use in Indonesia. Based on da a om 420 esponden s, i was ound ha he
mos widely used e-comme ce pla o ms a e Tokopedia, TikTok Shop, and Shopee. The majo i y o esponden s pu chase p oduc s
such as clo hing, accesso ies, as well as beau y and pe sonal ca e p oduc s, which shows he dominance o li es yle needs in online
shopping beha io . The esul s o he analysis show ha he online shopping expe ience has a signi ican e ec on impulse
pu chases, which can hen igge pos -pu chase cogni i e dissonance. In addi ion, i was ound ha Impulsi e Buying also media es
he ela ionship be ween Online Cus ome Shopping Expe ience and Cogni i e Dissonance. Thus, an engaging and emo ional
shopping expe ience no only encou ages spon aneous pu chases, bu also con ibu es o dissa is ac ion i he pu chase esul s a e
no as expec ed. These indings p o ide impo an implica ions o e-comme ce se ice p o ide s o design shopping expe iences
ha a e no only isually appealing and p omo ional, bu also able o mee consume expec a ions o educe he po en ial o
cogni i e dissonance.
KEYWORDS: Cogni i e Dissonance, e-comme ce, Cus ome Expe ience, Impulsi e Buying, Online Cus ome Shopping
Expe ience.
I. INTRODUCTION
Consume pu chasing beha io in Indonesia has unde gone signi ican changes wi h he inc easing ease o acqui ing goods and
se ices bo h o line and online (Junejo, 2023; Mu diana e al., 2024). The digi al e a has ueled he global popula i y o online
shopping (D . B. K. Singh, 2022; Vi mani e al., 2023), wi h he numbe o e-comme ce use s in Indonesia eaching 178.94 million
in 2022 and p ojec ed o ise o 244.67 million by 2027 (da aindonesia.id). The Financial Se ices Au ho i y (OJK) epo s ha
88.1% o in e ne use s in Indonesia ha e u ilized e-comme ce se ices (Mahmood, 2016), unde sco ing he cen ali y o e-
comme ce in consume beha io . Pos -pandemic, bo h millennials and olde gene a ions ha e demons a ed a consis en inc ease in
online shopping due o he a ailabili y o essen ial goods online (Fi mandani e al., 2021; Les a i, 2019; Mu diana e al., 2024;
Su yadi e al., 2022; Wijaya e al., 2024).
The mos equen ly pu chased i ems by Indonesian consume s include ashion (68%), gadge s (44%), elec onics (35%), and o he
p oduc s such as ood and cosme ics (We A e Social; Su yadi e al., 2022). Bo h online and o line shopping expe iences in luence
consume pu chasing beha io , pa icula ly impulsi e buying, which occu s spon aneously wi hou p io planning (Rook, 1987;
Baumeis e , 2002; Ve planken & He abadi, 2001). Pla o ms such as Shopee, Tokopedia, Lazada, and TikTok Shop compe e by
inno a ing and in oducing new ea u es o enhance consume expe iences (Alam e al., 2020; Im iaz Ali e al., 2018; Lim e al.,
2016; Qin e al., 2020). E en s such as “Ha bolnas” (Na ional Online Shopping Day) and “da e-based” p omo ions (11.11, 12.12)
ha e s imula ed impulsi e buying, wi h ansac ions eaching IDR 25.7 illion in 2023 (idEA; kon an.id), and he FMCG sec o is
expec ed o g ow by 13.9% du ing Ha bolnas 2024 (Hand iani e al., 2024; Pu i, 2023; Sapu a e al., 2024; Wilson & Ch is ella,
2019).
P e e ences o online shopping a e d i en by ee shipping p omo ions (54.9%), coupons/discoun s, cus ome es imonials (52%),
ease o checkou (45%), s o e epu a ion (40.1%), e u n policies (28.8%), and cash-on-deli e y op ions (28.1%) (We A e Social,
2023). O he con ibu ing ac o s include ime sa ings, p ice compa isons, discoun s, and p oduc a ie y (goods a s.com). Howe e ,
isks such as aud, p oduc disc epancies, deli e y delays, and da a b eaches—as seen in he Tokopedia and Bhinneka cases
(2020)—e ode consume us (Pa lou, 2003; Fauzi e al., 2024; Pu a e al., 2022; Wu e al., 2020; Zhang & Yu, 2020). Such isks
may igge cogni i e dissonance, de ined as he psychological discom o expe ienced a e making a pu chase (Fes inge , 1957;
Coope & Ca lsmi h, 2001; Wahyuni e al., 2021).
In e na ional Jou nal o Cu en Science Resea ch and Re iew
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Cogni i e dissonance a ises when pu chases con lic wi h consume s’ alues o needs (B ehm, 1956; Singh, 2012; Ak am e al.,
2021; Yap & Gau , 2014). A Slickdeals su ey ound ha 74% o online shoppe s in Indonesia eg e ed hei pu chases; he main
easons we e goods no ma ching hei p ice (39%), unused i ems (34%), and o e spending (32%). Psychological ac o s such as
pe cep ion, mo i a ion, lea ning, belie s, and a i udes play a dominan ole in digi al consume beha io (Chowdhu y, 2023;
Hand iani e al., 2024; Islam e al., 2019; Panjai an e al., 2018; Solomon, 2013; Fe nandez-Lo es e al., 2024; P iya & Sha ma,
2023; Abigail e al., 2024; Haqiqi, 2019).
E-comme ce pla o ms p o ide in o ma ion ha shapes bo h a ional and impulsi e pu chase decisions, ye such in o ma ion is
o en excessi e o misleading, leading o consume con usion (Blagoe a e al., 2023; Kim e al., 2008; Kuma e al., 2017; Pe cha a
& Leelasan i ham, 2021; Salam e al., 2003; He e al., 2022; Lee e al., 2006). Pe cep ions o in o ma ion o e load posi i ely
in luence consume s’ in en ion o epu chase online h ough impulsi e buying and cogni i e dissonance (Ak am e al., 2021; C.
Liao e al., 2017; Se yani e al., 2019).
Unde s anding hese isks and adop ing p e en i e measu es—such as p oduc esea ch, sc u inizing selle epu a ion and e iews,
choosing us wo hy pla o ms, and u ilizing eliable cus ome se ice—can help consume s make mo e p uden pu chase decisions
and educe he likelihood o cogni i e dissonance in he u u e. This s udy aims o examine consume s’ eg e expe iences esul ing
om impulsi e pu chases and hei impac on u u e online shopping beha io .
II. LITERATURE REVIEW
Cus ome Expe ience (CX) and Online Cus ome 's Shopping Expe ience (OCSE)
CX encompasses all cus ome in e ac ions wi h he company be o e and a e he pu chase and in ol es he emo ional aspec s ha
a ec sa is ac ion and loyal y (Lemon & Ve hoe , 2016). The Schmi model iden i ies i e key dimensions o cus ome
expe ience—senso y, emo ional, cogni i e, social, and unc ional— ha companies can manage o c ea e posi i e expe iences
(Schmi , 1999). In online shopping, he con enience o 24-hou se ice, as deli e y, and comple e p oduc in o ma ion ha e a
posi i e impac on sa is ac ion (Pe e a & Sachi a, 2019), while si e quali y such as design, unc ionali y, and usabili y a e signi ican
p edic o s o sa is ac ion (Deyalage & Kula hunga, 2019).
OCSE encompasses cogni i e, emo ional, and beha io al in e ac ions when shopping digi ally (Rose e al., 2012). Si e design, ease
o na iga ion, ansac ion secu i y, and in e ac i i y a ec sa is ac ion and loyal y (Mclean & Wilson, 2016). Posi i e OCSEs
inc ease us , pu chases, and long- e m ela ionships (Bleie e al., 2019). Impo an ac o s in CX–OCSE include in ui i e in e ace
design and UX (Hassanein & Head, 2007), us and secu i y o ansac ions (Mccole, 2004), and pe sonaliza ion o p oduc
ecommenda ions (A o a e al., 2008; Schi man & Kanuk, 2008).
Impulsi e Buying
Impulse pu chases a e in luenced by in e nal ac o s such as pe sonali y and emo ions as well as ex e nal ac o s such as p omo ion
and p oduc placemen (S e n, 1962). S e n classi ies ou ypes: pu e impulse (spon aneous), eminde impulse ( emembe ing
p e ious needs) (Hube & G i i hs, 2018), sugges ion impulse (due o p oduc quali y/bene i s) (Nu linda e al., 2020; Pa k e al.,
2012), and planned impulse (a combina ion o plan and spon anei y) (Badgaiyan & Ve ma, 2015).
Pu e Impulsi e Buying
Impulse shopping is highe online han o line (Vi mani e al., 2023; Fe nando-Lo es e al., 2024; Rundle-Thiele e al., 2013; Vicdan
e al., 2007). Online consume s end o be unplanned and ind i di icul o con ol he buying impulse (Gong e al., 2020; Rook &
Fishe , 1995; Sa as ano e al., 2024; Xiang e al., 2016; Singh e al., 2023) as well as ha ing a s ong emo ional d i e o buy
(Ampadu e al., 2022; Kou a is e al., 2002; Pa bo eeah e al., 2009). Pu e impulsi e buying decisions a e spon aneous wi hou
conside ing he consequences and a e igge ed by si ua ional emp a ions ha a e di icul o con ol (U ama e al., 2021;
Ve planken & He abadi, 2001a; Hassan e al., 2016; Ak am e al., 2018). This emp a ion can esul in a s ong emo ional a achmen
o he p oduc (Gul az e al., 2022; Pa k e al., 2012; Smoke, n.d.; Spi e i Co nish, 2020). Impulsi e buying includes a ec i e
(pleasu e, joy, guil ) and cogni i e (absence o planning, elabo a i e hinking) aspec s (Rook & Fishe , 1995; Di ma , 2005; Bea y
& Fe ell, 1998; Sha ma e al., 2010; Sohn & Lee, 2017; Ve planken & He abadi, 2001). Websi e design and layou ac o s can
inc ease impulse pu chase in en (Chen e al., 2017), as well as consume us in he pla o m (Gong e al., 2020). The analysis o
Redine e al. (2023) iden i ied i e ca ego ies o online impulsi e d i e s: indi idual ac o s (Pa bo eeah e al., 2009; Khan e al.,
2016), p oduc ac o s, websi e ac o s (Vicdan e al., 2007), social ac o s, and si ua ional ac o s. A ac i e isual displays (Chen
In e na ional Jou nal o Cu en Science Resea ch and Re iew
ISSN: 2581-8341
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& Yao, 2018) as well as c edible posi i e e iews inc ease impulse pu chases (Huang e al., 2023; Lina & Ahluwalia, 2021; Xu e
al., 2020).
Cogni i e Dissonance
Cogni i e dissonance a ises when beha io s o opinions a e inconsis en and gi e ise o emo ional discom o (Hawkins &
Mo he sbaugh, 2016; Coope & Ca lsmi h, 2015; Fes inge , 1957; Mo an, 2017; Ha mon-Jones & Mills, 2019). The g ea e he
dissonance, he s onge he mo i a ion o educe i (B ehm, 1956; Ha mon-Jones & Mills, 2019; Weinga en & Lage k is , 2023).
Fes inge (1957) s a ed ha dissonance occu s due o inapp op ia e ela ionships be ween cogni ion, which is a mo i a ing ac o in
i sel . Indi iduals end o jus i y decisions e en i hey di e om hei belie s (Ta is & A onson, 2007; A onson, 1999). These
inconsis encies c ea e psychological ension and encou age he sea ch o consis ency (De ine e al., 1999; Ha mon-Jones, 2012;
S eele, 1988). Indica o s include emo ional discom o , changes in a i udes, beha io al a ionaliza ion, and in o ma ion a oidance.
In he con ex o pu chase, dissonance occu s a e pu chase i he p oduc does no mee expec a ions o is conside ed he w ong
choice (Sweeney & Sou a , 2001; Li & Choudhu y, 2021; Nam, 2023). Consume s hen ee alua e o use s a egies o educe non-
con o mi y (Fes inge , 1957 in Ba a e al., 2023; Cha e jee e al., 2023; Rees e al., 2015; Chung & Cheng, 2018; D ayco &
Dabbs, 1998).
Concep ual F amewo k
Figu e 1. Resea ch Concep Model
(Sou ces: Schmi , 1999; Lemon & Ve hoe , 2016; Hawkins–S e n, 1962; Fes inge , 1957).
III. METHODOLOGY
This s udy uses a quan i a i e app oach wi h desc ip i e and explana o y designs o es he hypo heses de eloped by he esea che .
The esea ch design se es as a bluep in o da a collec ion, measu emen , and analysis (Seka an & Bougie, 2016). The quan i a i e
app oach was chosen because i aims o es heo ies wi h s a is ical p ocedu es (Kusumas u i, 2020).
The a iables es ed included Online Cus ome Shopping Expe ience (OCSE) as an independen a iable (X), Impulsi e Buying
(IB) as a media ing a iable (M), and Cogni i e Dissonance (CD) as a dependen a iable (Y). OCSE indica o s e e o senso y,
emo ional, cogni i e, social, unc ional expe iences (Lemon & Ve hoe , 2016; Schmi , 1999) as well as online shopping
expe iences, including in e ace design, us , secu i y, and pe sonaliza ion (Bleie e al., 2019; Pandey & Chawla, 2018; Hassanein
& Head, 2007; McCole, 2004; A o a e al., 2008; Schi man, 2008). IB is measu ed based on aspec s o spon aneous buying, less
a en ion o consequences, and igge ed by si ua ional ac o s (Ve planken & He abadi, 2009; Hassan & Shiu, 2016; Khan & Dha ,
2006). CD is measu ed h ough emo ional discom o , a i udinal changes, beha io al a ionaliza ion, and in o ma ion a oidance
(Fes inge , 1957; 1962).
The s udy popula ion was e-comme ce use s who had made impulse pu chases. The sampling echnique used is con enience
sampling because he popula ion is no known o su e (E ikan e al., 2016). Based on he basic ules o he Pa ial Leas Squa es
(PLS) me hod, he minimum numbe o samples is de e mined o be 5–10 imes he numbe o indica o s (Hai e al., 2011; Kock
& Hadaya, 2018). Wi h 42 indica o s, he numbe o samples was se a 420 esponden s. Responden s we e selec ed based on he
ollowing c i e ia: (1) ac i e e-comme ce use s o e he age o 16 and (2) ha ing made impulse pu chases in he las six mon hs.
Da a was collec ed h ough an online su ey using a Google Fo m ques ionnai e a e esponden s exp essed hei willingness o
pa icipa e. This s udy uses p ima y da a om ques ionnai es and seconda y da a om documen s o li e a u e s udies. Va iables
a e measu ed on a Like scale o 1–5 (s ongly disag ee – s ongly ag ee).
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Da a analysis uses S uc u al Equa ion Modeling–Pa ial Leas Squa es (SEM-PLS) because o i s abili y o handle complex models
wi h ela i ely small samples (Hai J e al., 2017; Hensele e al., 2016). The analysis included a desc ip i e es o desc ibe he
cha ac e is ics o he da a, a alidi y es (Ghozali, 2009) using ac o analysis and AVE (>0.5), a eliabili y es using C onbach's
Alpha and Composi e Reliabili y (>0.7) (P iya no, 2018; Suha sapu a, 2014; Hai J e al., 2014), as well as hypo hesis es ing and
media ion h ough boo s apping me hods o de e mine he signi icance o di ec and indi ec in luences (Zhao e al., 2010; Hai e
al., 2017).
IV. RESULTS AND DISCUSSION
Responden Cha ac e is ics
This s udy in ol ed 420 esponden s using e-comme ce in Indonesia. The esul s showed a signi ican co ela ion be ween impulsi e
buying
4946
eha iou and he appea ance o eg e and dissa is ac ion a e a pu chase. A ound 71% o esponden s (300 people)
admi ed o making impulse pu chases o en o occasionally, wi h he main igge s being discoun s/p omos (187 esponden s),
ollowed by a ac i e ad e isemen s (58) and p oduc a ailabili y (37). A e impulse pu chases, 54% o esponden s (225) s a ed
o en/some imes eg e ed; 51% (216) admi hei pu chases a e in luenced by nega i e emo ions such as s ess o dissa is ac ion.
Dissa is ac ion wi h he p oduc is qui e dominan (190 some imes dissa is ied; 72 o en dissa is ied), mainly due o inapp op ia e
quali y (131) and p ice conside ed oo high (101); Majo /mode a e eg e was epo ed by 68% o esponden s (286).
In e ms o demog aphics, he majo i y o esponden s we e male (59.5%; 249 people) and we e in he age ange o 22–27 yea s
(51.9%; 218 people). The geog aphical dis ibu ion is qui e wide: he mos om Bandung (111), Jaka a (76), and o he ca ego ies
(212), s eng hening he alidi y o he da a (Raha jo, 2020).
P oduc p e e ences showed he dominance o clo hing and accesso ies (331 esponden s), ollowed by beau y/pe sonal ca e
p oduc s (189), elec onics (122), and home appliances (113). These indings show ha Indonesian consume s no only use e-
comme ce o basic needs, bu also o suppo li es yle and pe sonal com o ; The pu chase o elec onic and household p oduc s
indica es us in online pla o ms in p o iding high- alue goods.
Ou e Model Analysis Validi y Tes
The high ou e loading indica es a lo o simila i ies in he cons uc . The minimum alue o ou e loading is 0.7 (Hai e al., 2022).
The ollowing a e he esul s o he ou e loading es which can be seen in Table 1.
Table 1. Ou e Loading
Cogni i e
Dissonance
Impulsi e
Buying
Online
Cus ome
Shopping
Expe ience
Impulsi e
Buying x Online
Cus ome
Shopping
Expe ience
CD-1
0.791
CD-12
0.802
CD-13
0.831
CD-14
0.807
CD-15
0.787
CD-16
0.808
CD-2
0.795
CD-3
0.805
CD-4
0.806
CD-6
0.804
CD-7
0.818
CD-8
0.82
CD-9
0.811
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Con e gen alidi y e e s o he ex en o which a cons uc is able o measu e each o i s indica o s. Con e gen alidi y es ing
can be pe o med by e alua ing he A e age Va iance Ex ac ed (AVE). Acco ding o Hai e al. (2022), when he AVE alue is
g ea e han 0.5, he cons uc is able o explain mo e han 50% o he indica o ’s a ia ions.
Table 2. AVE
Cons uc
A e age a iance ex ac ed (AVE)
Cogni i e Dissonance
0.65
Impulsi e Buying
0.609
Online Cus ome Shopping Expe ience
0.638
Cogni i e
Dissonance
Impulsi e
Buying
Online
Cus ome
Shopping
Expe ience
Impulsi e
Buying x Online
Cus ome
Shopping
Expe ience
IB-1
0.783
IB-2
0.783
IB-3
0.784
IB-4
0.792
IB-6
0.786
IB-7
0.767
IB-8
0.767
OCSE-1
0.818
OCSE-10
0.783
OCSE-12
0.785
OCSE-13
0.8
OCSE-14
0.789
OCSE-15
0.801
OCSE-16
0.803
OCSE-17
0.778
OCSE-18
0.797
OCSE-2
0.78
OCSE-3
0.802
OCSE-5
0.803
OCSE-7
0.82
OCSE-8
0.833
OCSE-9
0.788
Impulsi e
Buying x Online
Cus ome
Shopping
Expe ience
1
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All cons uc s in his model ha e quali ied con e gen alidi y wi h AVE alues abo e 0.5. Cogni i e Dissonance has an AVE o
0.65, Impulsi e Buying o 0.609, and an Online Cus ome Shopping Expe ience o 0.638. This shows ha each cons uc is able o
explain mo e han 50% o he a iance o he indica o s used o measu e i .
The nex c i e ion ha needs o be conside ed is he alue o c oss loading. Acco ding o his c i e ion, he ou e loading o an
indica o on he ela ed cons uc mus be g ea e han he c oss loading on he o he cons uc . The alue o he loading ac o can
be seen in Table 3.
Table 3. C oss Loading
Cogni i e
Dissonance
Impulsi e Buying
Online Cus ome
Shopping
Expe ience
Impulsi e Buying x
Online Cus ome
Shopping Expe ience
CD-1
0.791
0.514
0.377
-0.171
CD-12
0.802
0.523
0.431
-0.177
CD-13
0.831
0.528
0.404
-0.169
CD-14
0.807
0.512
0.407
-0.153
CD-15
0.787
0.515
0.432
-0.17
CD-16
0.808
0.476
0.417
-0.108
CD-2
0.795
0.485
0.411
-0.19
CD-3
0.805
0.497
0.391
-0.143
CD-4
0.806
0.491
0.388
-0.123
CD-6
0.804
0.514
0.42
-0.152
CD-7
0.818
0.491
0.447
-0.144
CD-8
0.82
0.518
0.411
-0.179
CD-9
0.811
0.503
0.453
-0.17
IB-1
0.443
0.783
0.491
-0.354
IB-2
0.484
0.783
0.473
-0.355
IB-3
0.479
0.784
0.494
-0.378
IB-4
0.53
0.792
0.537
-0.379
IB-6
0.509
0.786
0.532
-0.359
IB-7
0.498
0.767
0.489
-0.41
IB-8
0.473
0.767
0.488
-0.336
OCSE-1
0.446
0.498
0.818
-0.475
OCSE-10
0.368
0.54
0.783
-0.507
OCSE-12
0.389
0.504
0.785
-0.471
OCSE-13
0.386
0.555
0.8
-0.475
OCSE-14
0.451
0.531
0.789
-0.484
OCSE-15
0.376
0.519
0.801
-0.467
OCSE-16
0.373
0.507
0.803
-0.484
OCSE-17
0.387
0.526
0.778
-0.484
OCSE-18
0.44
0.502
0.797
-0.446
OCSE-2
0.408
0.487
0.78
-0.494
OCSE-3
0.419
0.536
0.802
-0.473
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Cogni i e
Dissonance
Impulsi e Buying
Online Cus ome
Shopping
Expe ience
Impulsi e Buying x
Online Cus ome
Shopping Expe ience
OCSE-5
0.414
0.495
0.803
-0.488
OCSE-7
0.444
0.506
0.82
-0.46
OCSE-8
0.449
0.511
0.833
-0.465
OCSE-9
0.405
0.483
0.788
-0.462
Impulsi e Buying x
Online Cus ome
Shopping
Expe ience
-0.196
-0.471
-0.595
1
Based on Table 3, i can be s a ed ha he alue o each o he ou e loading is highe han he c oss loading in he o he cons uc s.
Ano he impo an c i e ion o conside in disc iminan alidi y is he he e o ai mono ai a io (HTMT). HTMT is he mean o
he en i e ela ionship be ween he c oss-cons uc indica o s. Acco ding o (Hai e al., 2022), he maximum alue o HTMT
co ela ion is 0.9. HTMT co ela ion alues o mo e han 0.9 indica e a lack o disc iminan alidi y.
Table 4. He e o ai Mono ai Ra ion (HTMT)
Cogni i e
Dissonance
Impulsi e
Buying
Online Cus ome
Shopping
Expe ience
Impulsi e Buying x
Online Cus ome
Shopping Expe ience
Cogni i e Dissonance
Impulsi e Buying
0.677
Online Cus ome Shopping
Expe ience
0.536
0.693
Impulsi e Buying x Online
Cus ome Shopping
Expe ience
0.2
0.498
0.608
Based on Table 4, he e is no HTMT co ela ion alue g ea e han 0.9. The alue has me he HTMT c i e ia and has me he
disc iminan alidi y es .
Reliabili y Tes
The nex es ha needs o be done on he ou e model is he in e nal consis ency eliabili y es . This es was ca ied ou h ough
C onbach alpha and composi e eliabili y alues.The C onbach alpha alue desc ibes he C onbach co ela ion in a cons uc ,
while he composi e eliabili y looks a he di e ence in he ou e loading o he C onbach Alpha. Hai e al. (2022) s a ed ha he
C onbach alpha and composi e eliabili y alues ecei ed mus be mo e han 0.7 (Hai e al., 2022).
Table 5. Composi e Reliabili y
Cons uc
C onbach’s
alpha
Composi e
eliabili y
( ho_a)
Composi e
eliabili y
( ho_c)
A e age a iance
ex ac ed (AVE)
Cogni i e Dissonance
0.955
0.955
0.96
0.65
Impulsi e Buying
0.893
0.894
0.916
0.609
Online Cus ome Shopping Expe ience
0.959
0.96
0.964
0.638
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The es esul s in able 5 show ha all la en a iables mee he eliabili y es c i e ia. This is based on he C onbach alpha alue
and composi e eliabili y o all la en a iables wi h alues abo e 0.7. The e o e, all la en a iables a e decla ed eliable a e
mee ing all measu emen c i e ia.
Inne Model Analysis
The nex e alua ion ha is ca ied ou when he model measu emen is decla ed alid and eliable is he S uc u al Model Assessmen
o commonly called he in e nal model e alua ion. Acco ding o (Hai e al., 2022), he e alua ion o he inne model is ca ied ou
wi h se e al es s, such as collinea i y, signi icance and ele ance o model ela ionships, Model’s Explana o y Powe , and Model’s
P edic i e Powe which will be discussed below.
Tes R Squa e (R2)
Table 6 shows he esul s o he es analysis o he R-Squa e alue.
Table 6. R-Squa e Tes (R2)
R-squa e
R-squa e adjus ed
Cogni i e Dissonance
0.452
0.449
Impulsi e Buying
0.413
0.412
The R Squa e alue o Cogni i e Dissonance o 0.452 indica es ha 45.2% a iabili y in cogni i e dissonance can be explained by
Impulsi e Buying, Online Cus ome Shopping Expe ience, and hei in e ac ions. While he R Squa e alue o Impulsi e Buying o
0.413 indica es ha 41.3% o he a iabili y in impulsi e
4950
eha iou is explained by he online shopping expe ience. The
Adjus ed R Squa e, which is no much di e en , indica es ha his model is s able and qui e powe ul.
Assess he s uc u al model o collinea i y issues (VIF)
Collinea i y is a condi ion in which wo o mo e (independen ) p edic o a iables in a model ha e a high linea ela ionship,
meaning hey a e highly co ela ed wi h each o he . The collinea i y es can be done by looking a he VIF alue. I he alue is
VIF<5, hen he model is i and can be con inued in he nex analysis. The esul s o he VIF alue es can be seen in Table 7
below.
Table 7. Cholini y Tes
VIVID
Impulsi e Buying -> Cogni i e Dissonance
1.74
Online Cus ome Shopping Expe ience -> Cogni i e Dissonance
2.098
Online Cus ome Shopping Expe ience -> Impulsi e Buying
1
Impulsi e Buying x Online Cus ome Shopping Expe ience -> Cogni i e
Dissonance
1.582
I can be seen in Table 7 abo e ha he VIF alue be ween he esea ch a iables has me he es limi , which is < 5. F om he
in e nal model es ing , i was ound ha he model in gene al is qui e good.
Pa h Analysis
A his s age, he es is ca ied ou by looking a he pa h coe icien alue and he - alue. A pa h coe icien alue close o 1
indica es a posi i e ela ionship and con e sely, a alue close o 0 indica es a weak ela ionship in he model s uc u e. Fu he mo e,
he alue indica es he signi icance o a ela ionship be ween a iables a a gi en e o le el. In his s udy, he esea che used a
signi icance le el e o o 5% which means ha he - alue mus be g ea e han 1.96. The ollowing a e he (Hai e al., 2022)
pa h coe icien and alues shown in Table 8.
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Table 8. Pa h Coe icien Value
O iginal
Sample
Es ima e
S anda d
De ia ion
(STDEV)
T-S a is ics
P-Values
Impulsi e Buying -> Cogni i e Dissonance
0.542
0.048
11.373
0.000
Online Cus ome Shopping Expe ience ->
Cogni i e Dissonance
0.312
0.06
5.175
0.000
Online Cus ome Shopping Expe ience ->
Impulsi e Buying
0.643
0.037
17.144
0.000
Impulsi e Buying x Online Cus ome
Shopping Expe ience -> Cogni i e
Dissonance
0.187
0.044
4.228
0.000
Impulsi e Buying had a signi ican e ec on Cogni i e Dissonance wi h a coe icien o 0.542, a T- alue o 11.373, and a p- alue
o 0.000, which sugges s ha impulsi e buying
4951
eha iou can inc ease he cogni i e dissonance el by consume s a e
shopping. Online Cus ome Shopping Expe ience also has a di ec e ec on Cogni i e Dissonance wi h a coe icien o 0.312, a T-
alue o 5.175, and a p- alue o 0.000. In addi ion, Online Cus ome Shopping Expe ience also has a signi ican in luence on
Impulsi e Buying wi h a coe icien o 0.643, a T- alue o 17.144, and a p- alue o 0.000, which indica es ha he online shopping
expe ience el by consume s encou ages impulse pu chases. The in e ac ion be ween Impulsi e Buying and Online Cus ome
Shopping Expe ience as a mode a ion cons uc also had a signi ican e ec on Cogni i e Dissonance (coe icien 0.187, T = 4.228,
p = 0.000), which showed he p esence o a mode a ion e ec in he ela ionship. Fu he mo e, i is he pa h coe icien and alue
alues wi h indi ec in luence shown in he ollowing Table 9.
Table 9. Indi ec E ec
O iginal
sample
(O)
Sample mean
(M)
S anda d de ia ion
(STDEV)
T s a is ics
(|O/STDEV|)
P
alues
Online Cus ome Shopping
Expe ience -> Impulsi e
Buying -> Cogni i e
Dissonance
0.348
0.349
0.036
9.752
0.000
Online Cus ome Shopping Expe ience also has an indi ec in luence on Cogni i e Dissonance h ough Impulsi e Buying wi h a
coe icien o 0.348, a T alue o 9.752, and a p- alue o 0.000. This means ha mos o he in luence o he online shopping
expe ience on cogni i e dissonance occu s indi ec ly h ough impulse buying
4951
eha iou .
Media ion Tes
Table 10. Media ion Tes
O iginal
sample (O)
Sample
mean (M)
S anda d
de ia ion
(STDEV)
T s a is ics
(|O/STDEV|)
P alues
Online Cus ome Shopping
Expe ience -> Impulsi e Buying -
> Cogni i e Dissonance
0.348
0.349
0.036
9.752
0.000
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81. Lin, S.-W., Lo, L. Y.-S., & Chen, Y.-J. (2024). Unpacking Mobile Websi e Aes he ics and I s E ec : A Case o M-
comme ce Websi e O e ing Sea ch and Expe ience Goods. Jou nal o O ganiza ional Compu ing and Elec onic
Comme ce.
82. Lina, L. F., & Ahluwalia, L. (2021). Cus ome s' impulse buying in social comme ce: The ole o low expe ience in
pe sonalized ad e ising. Jou nal o Ma ana ha Managemen , 21(1).
83. L , J., & Liu, X. (2022). The Impac o In o ma ion O e load o E-Comme ce Pla o m on Consume Re u n In en ion:
Conside ing he Mode a ing Role o Pe cei ed En i onmen al E ec i eness. In e na ional Jou nal o En i onmen al
Resea ch and Public Heal h, 19(13). h ps://doi.o g/10.3390/ije ph19138060
84. Mahmood, S. M. F. (2016). e-Comme ce, Online Shopping and Cus ome Sa is ac ion: An Empi ical S udy on e-
Comme ce Sys em in Dhaka. In e na ional Jou nal o En ep eneu ship and De elopmen S udies (IJEDS) 4(3) 2016,
323–338 E-COMMERCE, 3(2018), 323–338. h ps://www. esea chga e.ne /publica ion/322791494%0AE-COMMERCE,
85. Ma in, L. M., Espel-Huynh, H. M., Ma ando-Blanck, S., E ans, B. C., Fo man, E. M., Bu yn, M. L., Bae , R. A., Wole e ,
R. Q., & He be , J. D. (2017). T us ing homeos a ic cues e sus accep ing hedonic cues: A andomized con olled ial
compa ing wo dis inc mind ulness-based in e en ion componen s. Jou nal o Con ex ual Beha io al Science, 6(4), 409–
417. h ps://doi.o g/10.1016/j.jcbs.2017.09.002
86. Ma zle , K., & Saue wein, E. (2002). The ac o s uc u e o cus ome sa is ac ion: An empi ical es o he impo ance
g id and he penal y- ewa d-con as analysis. In e na ional Jou nal o Se ice Indus y Managemen , 13(4), 314–332.
h ps://doi.o g/10.1108/09564230210445078
87. Mccole, P. (2004). Re ocusing ma ke ing o e lec p ac ice: The changing ole o ma ke ing o business. In Ma ke ing
In elligence & Planning (Vol. 22, Issue 5, pp. 531–539). h ps://doi.o g/10.1108/02634500410551914
88. Mclean, G., & Wilson, A. (2016). E ol ing he online cus ome expe ience... Is he e a ole o online cus ome suppo ?
89. Mi al, A. (2013). E-comme ce: I 's Impac on consume Beha io . In Global Jou nal o Managemen and Business S udies
(Vol. 3, Issue 2). h p://www. ipublica ion.com/gjmbs.h m
90. Mo an, C.; O. A. (2017). An Analysis o Leon Fes inge 's A Theo y o Cogni i e Dissonance (1s ed.) (1s ed.). Maca
Lib a y.
91. Mu diana, R., Abdinago o, S. B., Se iawa i, S., Lubis, A. L. P., & Rosalina, R. (2024). Online Shopping Cul u e And
In e ne Gene a ion Consume Beha io In Indonesia. In e na ional S uden Con e ence on Business, Educa ion,
Economics, Accoun ing, and Managemen (ISC-BEAM), 1(1), 576–586. h ps://doi.o g/10.21009/isc-beam.011.40
92. Nam, S. (2023). P edic ing Tou is Re isi In en ion by Applying he Ex ended Model o Goal-Di ec ed Beha iou and
Cogni i e Dissonance Theo y. Jou nal o Tou ism and Se ices, 14(26), 57–72. h ps://doi.o g/10.29036/jo s. 14i26.453
93. Nu linda, R., Ch is ina, D., A juna U a a No, J., Kepa, D., Kb Je uk, K., Wes Jaka a, K., & Special Capi al Jaka a, D.
(2020). THE ROLE OF POSITIVE EMOTION AS A MEDIATOR OF HEDONIC SHOPPING AND SHOPPING
LIFESTYLE TOWARDS IMPULSE BUYING ON LAZADA unde a C ea i e Commons A ibu ion (CC-BY-NC-SA)
4.0 license. Jou nal o Managemen and Business Resea ch (JRMB) Facul y o Economics UNIAT, 5(1).
h p://j mb.ejou nal- eunia .ne /index.php/JRMB/a icle/ iew/380
94. Ny hinen, J., Si ola, A., Koskelainen, T., Munnukka, J., & Wilska, T. (2024). Compu e s in Human Beha io Online
an eceden s o young consume s' impulse buying beha io . Compu e s in Human Beha io , 153(No embe 2022),
108129. h ps://doi.o g/10.1016/j.chb.2023.108129
95. O e b ing, T., Bha naga , R., Samuelsson, P., & Bo au, S. (2021). Posi i e gende cong uency e ec s on shoppe
esponses: Field e idence om a gende egali a ian cul u e. Jou nal o Re ailing and Consume Se ices, 63(June), 102738.
h ps://doi.o g/10.1016/j.j e conse .2021.102738
96. Pandey, S., & Chawla, D. (2018). Online cus ome expe ience (OCE) in clo hing e- e ail: Explo ing OCE dimensions and
hei impac on sa is ac ion and loyal y – Does gende ma e ? In e na ional Jou nal o Re ail and Dis ibu ion
Managemen , 46(3), 323–346. h ps://doi.o g/10.1108/IJRDM-01-2017-0005
97. Panjai an, S. P., Usage, P., Payla e , S., P omo, D., & Ma paung, N. (n.d.). HARBOLNAS (NATIONAL ONLINE
SHOPPING DAY) AGAINST IMPULSE BUYING OF SHOPEE USERS IN THE CITY OF MEDAN. Jou nal o
C ea i e Economy and Digi al Business Managemen , 1(3), 479–496.
h ps:// anspublika.co.id/ojs/index.php/JEKOMBITAL
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4959 *Co esponding Au ho : Bayu Cunda Sa ia Volume 08 Issue 10 Oc obe 2025
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Page No. 4943-4962
98. Pa bo eeah, D. V., Valacich, J. S., & Wells, J. D. (2009a). The in luence o websi e cha ac e is ics on a consume 's u ge o
buy impulsi ely. In o ma ion Sys ems Resea ch, 20(1), 60–78. h ps://doi.o g/10.1287/is e.1070.0157
99. Pa bo eeah, D. V., Valacich, J. S., & Wells, J. D. (2009b). The in luence o websi e cha ac e is ics on a consume 's u ge
o buy impulsi ely. In o ma ion Sys ems Resea ch, 20(1), 60–78. h ps://doi.o g/10.1287/is e.1070.0157
100. Pa k, E. J., Kim, E. Y., Funches, V. M., & Foxx, W. (2012). Appa el p oduc a ibu es, web b owsing, and e-impulse
buying on shopping websi es. Jou nal o Business Resea ch, 65(11), 1583–1589.
h ps://doi.o g/10.1016/J.JBUSRES.2011.02.043
101. Pa lou, P. A. (2003a). Consume accep ance o elec onic comme ce: In eg a ing us and isk wi h he echnology
accep ance model. In e na ional Jou nal o Elec onic Comme ce, 7(3), 101–134.
h ps://doi.o g/10.1080/10864415.2003.11044275
102. Pa lou, P. A. (2003b). Consume accep ance o elec onic comme ce: In eg a ing us and isk wi h he echnology
accep ance model. In e na ional Jou nal o Elec onic Comme ce, 7(3), 101–134.
h ps://doi.o g/10.1080/10864415.2003.11044275
103. Pe e a, G. A. B. S., & Sachi a, K. M. V. (2019). Cus ome Sa is ac ion owa ds Online Shopping in S i Lanka: Mode a ing
E ec o Income Le el. Asian Jou nal o Ad anced Resea ch and Repo s, 1–10.
h ps://doi.o g/10.9734/aja /2019/ 6i230149
104. Pe cha a , T., & Leelasan i ham, A. (2021). A e en i e consume beha io assessmen model o he online pu chase
decision-making p ocess. Heliyon, 7(10). h ps://doi.o g/10.1016/j.heliyon.2021.e08169
105. P iya, B., & Sha ma, V. (2023). Explo ing use s' adop ion in en ions o in elligen i ual assis an s in inancial se ices:
An an h opomo phic pe spec i es and socio-psychological pe spec i es. Compu e s in Human Beha io , 148.
h ps://doi.o g/10.1016/j.chb.2023.107912
106. P iya no, D. (2018). Independen Lea ning Da a Analysis wi h SPSS. Mediakom.
107. P og am, N. P., Managemen , S., Pg i, S., & Jombang, D. (2022). THE INFLUENCE OF CUSTOMER EXPERIENCE
ON WORD OF MOUTH MEDIATED BY CUSTOMER SATISFACTION (S udy on Consume s o Bank Sya iah Mandi i
Jombang B anch). Jou nal o Managemen and Applied Accoun ing (JIMAT), 13(1).
108. Qin, X., Liu, Z., & Tian, L. (2020). The s a egic analysis o logis ics se ice sha ing in an e-comme ce pla o m. Omega
(Uni ed Kingdom), 92, 102153. h ps://doi.o g/10.1016/j.omega.2019.102153
109. Raden Vina Iskandya Pu i1, T. A. R. (2023). THE EFFECT OF THE USE OF SHOPEE PAYLATER AND THE
HARBOLNAS PROMO (NATIONAL ONLINE SHOPPING DAY) ON THE IMPULSE BUYING OF SHOPEE USERS
IN MEDAN CITY. The Role o Cus ome Sa is ac ion in Media ing he In luence o Cus ome Rela ionship Ma ke ing on
Cus ome Loyal y, 2(3), 310–324. h ps://bn .bg/pos /101787017/bsp-za-balga ia-e-pod-nome -1- -bule ina a-za- o a-
ge b-s-nome -2-pp-db-s-nome -12
110. Redine, A., Deshpande, S., Jeba ajaki hy, C., & Su acha kum onkun, J. (2023). Impulse buying: A sys ema ic li e a u e
e iew and u u e esea ch di ec ions. In In e na ional Jou nal o Consume S udies (Vol. 47, Issue 1, pp. 3–41). John
Wiley and Sons Inc. h ps://doi.o g/10.1111/ijcs.12862
111. Rees, J. H., Klug, S., & Bambe g, S. (2015). Guil y conscience: mo i a ing p o-en i onmen al beha io by inducing
nega i e mo al emo ions. Clima ic Change, 130(3), 439–452. h ps://doi.o g/10.1007/s10584-014-1278-x
112. Ronaldo Yolanda Pu a, Syi a Nu ul Fadillah, Annisa A i ah Nug oho, & I a Fi dausa Nuzula. (2022). Analysis o Fac o s
Con ibu ing o Impulse Buying Beha io o E-Comme ce Use s. Jou nal o Managemen S udies and De elopmen , 1(01),
48–67. h ps://doi.o g/10.56741/jmsd. 1i01.43
113. Rook, D. W. (n.d.). The Buying Impulse.
114. Rook, D. W. (1987). The buying impulse. Jou nal o Consume Resea ch. Jou nal o Consume Resea ch, 14(2), 189–199.
115. Rook, D. W., & Fishe , R. J. (1995). No ma i e In luences on Impulsi e Buying Beha io .
116. Rose, S., Cla k, M., Samouel, P., & Hai , N. (2012). Online Cus ome Expe ience in e-Re ailing: An empi ical model o
An eceden s and Ou comes. Jou nal o Re ailing, 88(2), 308–322. h ps://doi.o g/10.1016/j.j e ai.2012.03.001
117. Rundle-Thiele, S., Russell-Benne , R., Leo, C., & Die ich, T. (2013). Mode a ing een d inking: Combining social
ma ke ing and educa ion. Heal h Educa ion, 113(5), 392–406. h ps://doi.o g/10.1108/HE-07-2012-0041
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118. Salam, A. F., Rao, H. R., & Pegels, C. C. (2003). Consume -pe cei ed isk in e-comme ce ansac ions. www.pen on.com
119. Sapu a, D., Abigail, J., Sa i, V. P., & Sapu a, D. (2024). ScienceDi ec ScienceDi ec The In luence o P oduc Quali y
and Online Shopping Expe ience ( OSE ) on Consume Loyal y Th ough Cus ome Sa is ac ion on The In luence o
P oduc Quali y and Online Shopping Expe ience Local Skinca e P oduc s ( OSE ) on Con. P ocedia Compu e Science,
234(2023), 537–544. h ps://doi.o g/10.1016/j.p ocs.2024.03.037
120. Sa as ano, M., Anagnos e, S., Biclesanu, I., & Amendola, C. (2024). The impac o e-comme ce pla o ms' quali y on
cus ome sa is ac ion and epu chase in en ion in pos COVID-19 se ings. TQM Jou nal. h ps://doi.o g/10.1108/TQM-
04-2024-0143
121. Schi man, L., & Kanuk, L. L. (2008). Consume Beha io (7 h ed.).
122. Schmi , B. (1999). Expe ien ial Ma ke ing. Jou nal o Ma ke ing Managemen , 15(1–3), 53–67.
h ps://doi.o g/10.1362/026725799784870496
123. Seka an, U., & Bougie, R. (2016). Resea ch Me hods o Business: A Skills De elopmen App oach. (Vol. 7). Wiley &
Sons, Wes Sussex.
124. Se yani, V., Zhu, Y. Q., Hidayan o, A. N., Sandhyaduhi a, P. I., & Hsiao, B. (2019). Explo ing he psychological
mechanisms om pe sonalized ad e isemen s o u ge o buy impulsi ely on social media. In e na ional Jou nal o
In o ma ion Managemen , 48, 96–107. h ps://doi.o g/10.1016/j.ijin omg .2019.01.007
125. Sha ma, A., Iye , G. R., Meh o a, A., & K ishnan, R. (2010). Sus ainabili y and business- o-business ma ke ing: A
amewo k and implica ions. Indus ial Ma ke ing Managemen , 39(2), 330–341.
h ps://doi.o g/10.1016/J.INDMARMAN.2008.11.005
126. Sha ma, P., Si akuma an, B., & Ma shall, R. (2010). Impulse buying and a ie y seeking: A ai -co ela es pe spec i e.
Jou nal o Business Resea ch, 63(3), 276–283. h ps://doi.o g/10.1016/j.jbus es.2009.03.013
127. Singh, D . B. K. (2022). CONSUMER BEHAVIOR IN ONLINE VS. OFFLINE SHOPPING: A CASE STUDY. 11, 2258–
2268.
128. Singh, P., Sha ma, B. K., A o a, L., & Bha , V. (2023). Measu ing social media impac on Impulse Buying Beha io .
Cogen Business and Managemen , 10(3). h ps://doi.o g/10.1080/23311975.2023.2262371
129. SIVAKUMAR, V., & MOHAN, R. (2020). Sus ainable solid was e managemen in lea he and ex ile indus y: Lea he &
ex ile was e ib e-polyme composi e and nanocomposi e - o e iew and e iew. In Tex ile and Lea he Re iew (Vol. 3,
Issue 2, pp. 54–63). Seniko s udio L d. h ps://doi.o g/10.31881/TLR.2020.04
130. Sohn, H. K., & Lee, T. J. (2017). Tou is s' impulse buying beha io a du y- ee shops: he mode a ing e ec s o ime
p essu e and shopping in ol emen . Jou nal o T a el and Tou ism Ma ke ing, 34(3), 341–356.
h ps://doi.o g/10.1080/10548408.2016.1170650
131. Solomon, M. R.; B. G. A. S. H. M. K. (2013). Consume Beha iou . Pea son Educa ion Limi ed.
132. Spi e i Co nish, L. (2020). Why did I buy his? Consume s' pos -impulse-consump ion expe ience and i s impac on he
p opensi y o u u e impulse buying beha iou . Jou nal o Consume Beha io , 19(1), 36–46.
h ps://doi.o g/10.1002/cb.1792
133. S eele, C. M. (1988). The psychology o sel -a i ma ion: Sus aining he in eg i y o he sel . Ad ances in Expe imen al
Social Psychology, 21.
134. S e n, H. (n.d.). The Signi icance o Impulse Buying Today.
135. Suha sapu a, U. (2014). Quan i a i e, Quali a i e, and Ac ion Resea ch Me hodology. (2nd ed.). Adi ama Re iew.
136. Sunds öm, M., Hjelm-Lidholm, S., & Radon, A. (2019). Clicking he bo edom away – Explo ing impulse ashion buying
beha io online. Jou nal o Re ailing and Consume Se ices, 47, 150–156.
h ps://doi.o g/10.1016/J.JRETCONSER.2018.11.006
137. Su yadi, N., Angg aeni, R., A iyan o, D., & Faj ul Islam, M. (2022). The e ec o he COVID-19 pandemic on consume
beha io s: A s udy on gen-z in Indonesia. In e na ional Jou nal o Resea ch in Business and Social Science (2147– 4478),
10(8), 313–318. h ps://doi.o g/10.20525/ij bs. 10i8.1490
138. S obodo á, Z., & Rajchlo á, J. (2020). S a egic beha io o e-comme ce businesses in online indus y o elec onics om
a cus ome pe spec i e. Adminis a i e Sciences, 10(4). h ps://doi.o g/10.3390/admsci10040078
In e na ional Jou nal o Cu en Science Resea ch and Re iew
ISSN: 2581-8341
Volume 08 Issue 10 Oc obe 2025
DOI: 10.47191/ijcs /V8-i10-08, Impac Fac o : 8.048
IJCSRR @ 2025
www.ijcs .o g
4961 *Co esponding Au ho : Bayu Cunda Sa ia Volume 08 Issue 10 Oc obe 2025
A ailable a : www.ijcs .o g
Page No. 4943-4962
139. Sweeney, J. C., & Sou a , G. N. (2001). Consume pe cei ed alue: The de elopmen o a mul iple i em scale. Jou nal o
Re ailing, 77(2), 203–220. h ps://doi.o g/10.1016/S0022-4359(01)00041-0
140. Szymanski, D. M., Hise, R. T., & Al, M. (2000). e-Sa is ac ion: An Ini ial Examina ion. Jou nal o Re ailing, 76(3), 309–
322.
141. Ta is, Ca ol., & A onson, Ellio . (2007). Sel -jus i ica ion in public and p i a e sphe es. The Gene al Psychologis , 42,
4–7.
142. U ama, A., Sawi i, H. S. R., Ha yan o, B., & Wahyudi, L. (2021). Impulse Buying: The In luence o Impulse Buying
Tendency, U ge o Buy and Gende on Impulse Buying o he Re ail Cus ome s. Jou nal o Dis ibu ion Science, 19(7),
101–111. h ps://doi.o g/10.15722/jds.19.7.202107.101
143. Ve hagen, T., & Van Dolen, W. (2011). The in luence o online s o e belie s on consume online impulse buying: A model
and empi ical applica ion. In o ma ion and Managemen , 48(8), 320–327. h ps://doi.o g/10.1016/j.im.2011.08.001
144. Ve planken, B. A. S., & He abadi, A. (2001). Indi idual Di e ences in Impulse Buying Tendencies: Feeling and No
Thinking. 83(May), 71–83.
145. Ve planken, B., & He abadi, A. (2001a). Indi idual di e ences in impulse buying endency: Feeling and no hinking.
Eu opean Jou nal o Pe sonali y, 15(1 SUPPL.). h ps://doi.o g/10.1002/pe .423
146. Ve planken, B., & He abadi, A. (2001b). Indi idual di e ences in impulse buying endency: Feeling and no hinking.
Eu opean Jou nal o Pe sonali y, 15(1 SUPPL.). h ps://doi.o g/10.1002/pe .423
147. Vicdan, H., Chapa, S., & de Los San os, G. (2007). Unde s anding compulsi e buye s' online shopping incidence: a close
look a he e ec s o sales p omo ions and ba gains on Hispanic Ame icans. Jou nal o Cus ome Beha iou , 6(1), 57–74.
h ps://doi.o g/10.1362/147539207x198374
148. Vi mani, N., Sha ma, S., Kuma , A., & Lu h a, S. (2023a). Adop ion o indus y 4.0 e idence in eme ging economy:
Beha io al easoning heo y pe spec i e. Technological Fo ecas ing and Social Change, 188 (No embe 2022), 122317.
h ps://doi.o g/10.1016/j. ech o e.2023.122317
149. Vi mani, N., Sha ma, S., Kuma , A., & Lu h a, S. (2023b). Adop ion o indus y 4.0 e idence in eme ging economy:
Beha io al easoning heo y pe spec i e. Technological Fo ecas ing and Social Change, 188.
h ps://doi.o g/10.1016/j. ech o e.2023.122317
150. Wahyuni, S., Lukman, & Fakh i, N. (2021). The E ec o Cogni i e E o on Cogni i e Dissonance A e Online
Pu chases. Jou nal O A , Humani y And Social S udies, 1(6), 63–69.
151. Weinga en, N., & Lage k is , C. J. (2023). Can images and ex ual in o ma ion lead o mea a oidance? The media ing
ole o cogni i e dissonance. Food Quali y and P e e ence, 104. h ps://doi.o g/10.1016/j. oodqual.2022.104747
152. Wesely, P. M. (2012). Lea ne A i udes, Pe cep ions, and Belie s in Language Lea ning. Fo eign Language Annals,
45(S1), 98–117. h ps://doi.o g/10.111/j.1944-9720.2012.01181.x
153. Wijaya, L., Meng, C. K., Tunku, U., Rahman, A., Ng, K. C., & Vale ie, J. (2024). Towa ds Sus ainable E-Comme ce:
Unde s anding Pos -Pandemic Online Shopping In en ions in Indonesia. Jou nal o Sys em and Managemen Sciences,
July. h ps://doi.o g/10.33168/jsms.2024.0813
154. Wilson, N., & Ch is ella, R. (2019). An Empi ical Resea ch o Fac o s A ec ing Cus ome Sa is ac ion: A Case o he
Indonesian E-Comme ce Indus y. DeReMa (De elopmen Resea ch o Managemen ): Jou nal o Managemen , 14(1), 21.
h ps://doi.o g/10.19166/de ema. 14i1.1108
155. Wilson, N., Ken, & Tan, P. H. P. (2019). The e ec o websi e design quali y and se ice quali y on epu chase in en ion
in he E-comme ce indus y: A c oss-con inen al analysis. . Gadjah Mada In e na ional Jou nal o Business, 21(2), 187–
222.
156. Wu, I. L., Chiu, M. L., & Chen, K. W. (2020). De ining he de e minan s o online impulse buying h ough a shopping
p ocess o in eg a ing pe cei ed isk, expec a ion-con i ma ion model, and low heo y issues. In e na ional Jou nal o
In o ma ion Managemen , 52. h ps://doi.o g/10.1016/j.ijin omg .2020.102099
157. Xiang, L., Zheng, X., Lee, M. K. O., & Zhao, D. (2016). Explo ing consume s' impulse buying beha io on social
comme ce pla o m: The ole o pa asocial in e ac ion. In e na ional Jou nal o In o ma ion Managemen , 36(3), 333–347.
h ps://doi.o g/10.1016/j.ijin omg .2015.11.002
In e na ional Jou nal o Cu en Science Resea ch and Re iew
ISSN: 2581-8341
Volume 08 Issue 10 Oc obe 2025
DOI: 10.47191/ijcs /V8-i10-08, Impac Fac o : 8.048
IJCSRR @ 2025
www.ijcs .o g
4962 *Co esponding Au ho : Bayu Cunda Sa ia Volume 08 Issue 10 Oc obe 2025
A ailable a : www.ijcs .o g
Page No. 4943-4962
158. Xu, H., Zhang, K. Z. K., & Zhao, S. J. (2020a). A dual sys ems model o online impulse buying. Indus ial Managemen
and Da a Sys ems, 120(5), 845–861. h ps://doi.o g/10.1108/IMDS-04-2019-0214
159. Xu, H., Zhang, K. Z., & Zhao, S. J. (2020b). A dual sys ems model o online impulse buying. Indus ial Managemen &
Da a Sys ems, 120(5), 845–861.
160. Xu, X., Liu, J., & Cai, R. (2022). How do cus ome s na iga e pe cei ed inapp op ia eness o collec i e emo ion in g oup
se ice eco e y? An applica ion o cogni i e dissonance heo y. Tou ism Managemen , 93, 104615.
h ps://doi.o g/10.1016/J.TOURMAN.2022.104615
161. Yap, S. F., & Gau , S. S. (2014). Consume Dissonance in he Con ex o Online Consume Beha io : A Re iew and
Resea ch Agenda. Jou nal o In e ne Comme ce, 13(2), 116–137. h ps://doi.o g/10.1080/15332861.2014.934647
162. Youn, S., & Fabe , R. J. (2000). Impulse Buying: I s Rela ion o Pe sonali y T ai s and Cues. Ad ances in Consume
Resea ch, 27, 179–185.
163. Za a, I., Velicu, B. C., Mun hiu, M., & Tu a, M. (2012). Using analy ics o unde s anding he consume online. . Anal. I
would be economical. Timisoa a, 18, 788–793.
164. Zhang, X., & Yu, X. (2020). The Impac o Pe cei ed Risk on Consume s' C oss-Pla o m Buying Beha io . F on ie s in
Psychology, 11(Oc obe ). h ps://doi.o g/10.3389/ psyg.2020.592246
Ci e his A icle: Sa ia, B.C., Su yanda i, R.T. (2025). Cogni i e Dissonance in Online Shopping Expe iences and Impulsi e
Buying Among E-Comme ce Use s in Indonesia. In e na ional Jou nal o Cu en Science Resea ch and Re iew, 8(10), pp.
4943-4962. DOI: h ps://doi.o g/10.47191/ijcs /V8-i10-08
