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Page 1: A Critical Review of the E-Satisfaction Literature

http://abs.sagepub.com/American Behavioral Scientist

http://abs.sagepub.com/content/52/1/38The online version of this article can be found at:

 DOI: 10.1177/0002764208321340

2008 52: 38American Behavioral ScientistQimei Chen, Shelly Rodgers and Yi He

A Critical Review of the E-Satisfaction Literature  

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http://www.sagepublications.com

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- Jul 26, 2008Version of Record >>

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Page 2: A Critical Review of the E-Satisfaction Literature

38

A Critical Review of theE-Satisfaction LiteratureQimei ChenShelly RodgersYi HeUniversity of Hawaii at Manoa

User satisfaction is essential to the success of any Web site. Satisfaction with electronicenvironments, or e-satisfaction, drives traffic to Web sites and encourages repeated use ofa site. However, the e-satisfaction literature has not been critically examined to assess e-satisfaction scales that currently exist in an effort to determine potential gaps or oppor-tunities for future research. The present study is intended to critically review the existinge-satisfaction literature. We identify problems in defining and measuring e-satisfactionand offer directions for future research.

Keywords: e-satisfaction; customer satisfaction; electronic commerce; web site quality; satisfaction measure.

The World Wide Web has more than 65.4 million domain names to date, includ-ing .com, .org, .gov, and .edu addresses (Zooknic Internet Intelligence, 2006).

Attracted by the tremendous potential afforded by an online presence, an increas-ing number of businesses and organizations have built Web sites as important com-munication and dissemination channels. The success and failure of these onlinesites depend on how well customers are satisfied. Given that online environmentscreate different experiences than offline environments (Wolfinbarger & Gilly,2003), traditional customer satisfaction models may not be appropriate when eval-uating consumers’ satisfaction with nontraditional environments such as theInternet.

To address this issue, a growing number of studies have begun to conceptualize,measure, and model user satisfaction in an e-environment. Known as electronic sat-isfaction, or e-satisfaction, the literature in this area has not been critically examinedor scrutinized (Szymanski & Hise, 2000) but represents a potentially fruitful areathat the online component of every business or organization could benefit from. It istherefore essential to assess e-satisfaction scales that currently exist in an effort todetermine potential gaps or opportunities for future research.

The present study is intended to critically examine the existing e-satisfaction lit-erature. In the present review, we examine the definition, dimensionality, and instru-ments of e-satisfaction, followed by a discussion of conceptual and methodologicalissues of past e-satisfaction measures. We then offer suggestions for future research.

American Behavioral ScientistVolume 52 Number 1

September 2008 38-59© 2008 Sage Publications

10.1177/0002764208321340http://abs.sagepub.com

hosted athttp://online.sagepub.com

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Page 3: A Critical Review of the E-Satisfaction Literature

Chen et al. / E-Satisfaction Literature Review 39

An Overview of E-Satisfaction Scales

A useful starting point in assessing the e-satisfaction literature is to identify generaltrends across existing e-satisfaction scales. To accomplish this, we conducted a broadsearch of the literature across a variety of disciplines to identify studies that aimed tocreate e-satisfaction and e-satisfaction–related scales. During our search, we discov-ered that efforts to develop e-satisfaction measures were predominantly centered inthe fields of marketing and e-commerce. Our final sample was therefore limited to thetop 20 journals in these two areas (Bharati & Tarasewich, 2002; Hult, Neese, &Bashaw, 1997). The sampling strategy was similar to network sampling, which is fea-tured by locating key e-satisfaction instruments by examining and analyzing the ref-erence list of journal articles. Network sampling is a reliable and efficient samplingprocedure particularly when it is difficult to access the population using probabilitysampling methods (e.g., Spreen & Zwaagstra, 1994; Watters & Biernacki, 1989), as inthe case of e-satisfaction measures. Our search process continued until the emerginge-satisfaction instruments were interchangeable and saturated, suggesting that thesearch successfully identified key e-satisfaction scales (see Heckathorn, 1997). Thisprocess resulted in 20 e-satisfaction instruments, outlined in Table 1.

The scales are listed in chronological order in Table 1 starting with Bailey andPearson’s (1983) User Information Satisfaction (UIS) Scale and ending with Bauer,Falk, and Hammerschmidt’s (2006) eTranQual scale. The scales were created byscholars from a variety of disciplines, including e-commerce, business, and infor-mation sciences, thus suggesting that e-satisfaction is a complex phenomenon thathas drawn attention from multiple disciplines. The number of items per scale rangedfrom 6 (Chen & Wells, 1999) to 156 (Bailey & Pearson, 1983). Two scales (Liu &Arnett, 2000, and Novak, Hoffman, & Yung, 2000) did not offer scale items. Morethan 100 factors or dimensions were identified by the e-satisfaction scales. Of these,six dimensions appeared across several scales, including design, convenience, trans-action, security, information or content, and function or usability. To a lesser extent,dimensions such as interactivity (Barnes & Vidgen, 2002), customization (Srinvasan,Anderson, & Ponnavolu, 2002), playfulness (Liu & Arnett, 2000), and entertainment(Chen & Wells, 1999) were identified as dimensions of e-satisfaction.

The impact (times cited) of each scale was noted and ranged from 0 (Yang, Cai,Zhou, & Zhou, 2005; Bauer et al., 2006) to 328 (Bailey & Pearson, 1983). To con-trol for the year the scale was published, we created an impact ratio by dividing thetotal number of citations by the number of years since the study had been published.For instance, because the Web Customer Satisfaction Scale (McKinney, Yoon, &Zahedi, 2002) was published in Information Systems Research in 2002, it has beencited 31 times, resulting in an impact ratio of 6.2 (31/5). This provides an apples-to-apples comparison of the scales and helps to equalize the impact of each scale acrosstime. Impact ratios ranged from 0 (Bauer et al., 2006; Yang et al., 2005) to 15.5(Novak et al., 2000), with an average impact ratio of 5.17 (see Table 1).

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Page 4: A Critical Review of the E-Satisfaction Literature

40

Inst

rum

ent

Use

rIn

form

atio

nSa

tisfa

ctio

n

End

Use

r C

ompu

ting

Satis

fact

ion

Dim

ensi

ons

Ele

ctro

nic

data

pr

oces

sing

staf

f,se

rvic

e in

form

atio

npr

oduc

t,ve

ndor

supp

ort,

info

rmat

ion

prod

uct,

know

ledg

e or

in

volv

emen

t

Con

tent

,ac

cura

cy,

form

at,

ease

of u

se,

timel

ines

s

Num

ber

ofIt

ems

156

12

Rel

iabi

lity

.75 (low

est)

.93 (a

vera

ge)

.92

Fit I

ndex

(if

CFA

Perf

orm

ed)

Five

fi

rst-

orde

rfa

ctor

s,on

e se

cond

-or

der

fact

ors

mod

el:

χ2=

126.

16df

= 6

1χ2 /d

f =

2.07

NFI

= .9

08G

FI =

.916

AG

FI =

.875

RM

SR =

.052

(Dol

l,R

aghu

nath

an,L

im,&

Gup

ta,

1995

)

Five

fi

rst-

orde

rfa

ctor

s,on

e se

cond

-or

der

fact

ors

mod

el:

Impa

ct(T

imes

Cite

d)

328

249

Rat

io(C

ites/

Yea

r)

13.7

13.1

Rep

licat

ion

(s)

Ives

,Ols

on,

& B

arou

di

(198

3),

Bar

oudi

&O

rlik

owsk

i(1

988)

,G

alle

tta &

L

eder

er

(198

9),

Ket

tinge

r &

Lee

(19

94),

Dol

l et a

l. (1

995)

,Se

ngup

ta &

Zvi

ran

(199

7),

Jian

g &

K

lein

(2

000)

,W

hitte

n (2

004)

Tork

zade

h &

Dol

l (2

001)

;D

oll e

t al.

(199

4);

Scop

e

Com

pute

r us

er

satis

fact

ion

Satis

fact

ion

of a

n en

d us

er w

ith a

syst

em

Aut

hor(

s)

Bai

ley

&

Pear

son

Dol

l &

Tork

zade

h

Yea

r

1983

1988

Jour

nal

Man

agem

ent

Scie

nce

MIS

Q

uart

erly

Are

a

E- co

mm

erce

E- co

mm

erce

Dis

cipl

inea

Info

rmat

ion

syst

ems

Info

rmat

ion

syst

ems

Tabl

e 1

Sum

mar

y an

d E

valu

atio

n of

E-S

atis

fact

ion

Inst

rum

ents

(con

tinu

ed)

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Page 5: A Critical Review of the E-Satisfaction Literature

41

Inst

rum

ent

Dim

ensi

ons

Num

ber

ofIt

ems

Rel

iabi

lity

Fit I

ndex

(if

CFA

Perf

orm

ed)

χ2= 18

5.81

df=

50

χ2 /df

=3.

72N

FI =

.940

GFI

= .9

29A

GFI

=.8

89R

MSR

=.0

35(D

oll,

Xia

,& To

rkza

deh,

1994

)χ2

= 6

1.08

df=

48

p=

.10

χ2 /df=

1.2

7C

FI =

.99

RM

SEA

=.0

4(A

bdin

nour

-H

elm

,C

hapa

rro,

& Farm

er,

2005

)

Impa

ct(T

imes

Cite

d)

Rat

io(C

ites/

Yea

r)R

eplic

atio

n (s

)

McH

aney

,H

ight

ower

,&

Pea

rson

(2

002)

;D

oll,

Den

g,R

aghu

nath

an,

Tork

zade

h,&

Xia

(2

004)

;So

mer

s,N

elso

n,&

K

arim

i (2

003)

;A

bdin

nour

-H

elm

et a

l. (2

005)

Scop

eA

utho

r(s)

Yea

rJo

urna

lA

rea

Dis

cipl

inea

Tabl

e 1

(con

tinu

ed)

(con

tinu

ed)

at Afyon Kocatepe Universitesi on May 22, 2014abs.sagepub.comDownloaded from

Page 6: A Critical Review of the E-Satisfaction Literature

42

Inst

rum

ent

Atti

tude

To

war

d th

e Si

te

Fact

ors

Ass

ocia

ted

With

W

ebsi

te

Succ

ess

Ant

eced

ents

to

E-

Satis

fact

ion

Dim

ensi

ons

Ent

erta

inm

ent,

info

rmat

ive-

ness

,org

a-ni

zatio

n

Info

rmat

ion

and

serv

ice

qual

ity,

syst

em u

se,

play

fuln

ess,

syst

emde

sign

qual

ity

Con

sum

er

perc

ep-

tions

ofon

line

con-

veni

ence

,m

erch

andi

s-in

g (p

rod-

uct

offe

ring

san

d pr

od-

uct i

nfor

-m

atio

n),

site

des

ign,

Num

ber

ofIt

ems

6

No ite

ms

offe

red

11

Rel

iabi

lity

.92−

.97

.63−

.92

Not

repo

rted

Fit I

ndex

(if

CFA

Perf

orm

ed)

Thr

ee fi

rst-

orde

rfa

ctor

s,on

ese

cond

-or

der

fact

ors

mod

el:

GFI

= .6

6N

NFI

= .8

3C

FA n

otpe

rform

ed

χ2=

143.

1df

= 35

p <

.05

GFI

= .9

8A

GFI

= .9

5R

MSE

A =

.06

NFI

= .9

7C

FI =

.97

Impa

ct(T

imes

Cite

d)

44

55 60

Rat

io(C

ites/

Yea

r)

5.5 7.

9

8.6

Rep

licat

ion

(s)

Che

n,C

liffo

rd,&

W

ells

(2

002)

Scop

e

Atti

tude

to

war

d a

Web

site

Fact

ors

asso

ciat

ed

with

Web

si

te

succ

ess

unde

r el

ectr

onic

co

mm

erce

co

ntex

tC

onsu

mer

satis

fact

ion

with

e-

taili

ng

expe

rienc

es

Aut

hor(

s)

Che

n &

W

ells

Liu

&

Arn

ett

Szym

ansk

i&

His

e

Yea

r

1999

2000

2000

Jour

nal

Jour

nal

of

Adv

erti

sing

R

esea

rch

Info

rmat

ion

and

Man

agem

ent

Jour

nal

of

Ret

aili

ng

Are

a

Mar

ketin

g

E- co

mm

erce

Mar

ketin

g

Dis

cipl

inea

Bus

ines

s

Info

rmat

ion

syst

ems

Bus

ines

s

Tabl

e 1

(con

tinu

ed)

(con

tinu

ed)

at Afyon Kocatepe Universitesi on May 22, 2014abs.sagepub.comDownloaded from

Page 7: A Critical Review of the E-Satisfaction Literature

43

Inst

rum

ent

Con

stru

cts

Rel

ated

toC

ompe

lling

Onl

ine

Exp

erie

nce

Cus

tom

er

Info

rmat

ion

Satis

fact

ion

Dim

ensi

ons

Eas

e of

cont

act,

easy

ord

erin

g,pa

ymen

tre

turn

s,ea

se o

fca

ncel

latio

n,cu

stom

ersu

ppor

t,cu

tting

edg

e,va

riety

,qu

ality

info

rmat

ion,

relia

bilit

y,se

curit

y,lo

wpr

ice

Cus

tom

ersu

ppor

t,se

curit

y,ea

se o

f use

,di

gita

lpr

oduc

ts/s

ervi

ces,

trans

actio

nan

dpa

ymen

t,in

form

atio

nco

nten

t,in

nova

tion

Num

ber

ofIt

ems

No

item

sof

fere

d

21

Rel

iabi

lity

Not re

port

ed

.84−

.93

Fit I

ndex

(if

CFA

Perf

orm

ed)

Not

re

port

ed

Seve

n fir

st-

orde

r fac

-to

rs,o

nese

cond

-or

der

fact

ors

mod

el:

χ2=

287

df=

182

χ2 /df=

1.5

8

Impa

ct(T

imes

Cite

d)

108

15

Rat

io(C

ites/

Yea

r)

15.5

2.5

Rep

licat

ion

(s)

Wan

g &

Tang

(200

4)

Scop

e

Cus

tom

erex

peri

-en

ce in

onlin

een

viro

n-m

ent

Cus

tom

ersa

tisfa

ctio

nto

war

dW

eb s

ites

that

mar

ket

digi

tal

prod

ucts

and

ser-

vice

s

Aut

hor(

s)

Nov

ak,

Hof

fman

,&

Yun

g

Wan

g,Ta

ng,&

Tang

Yea

r

2000

2001

Jour

nal

Mar

keti

ngSc

ienc

e

Jour

nal

ofE

lect

roni

cC

omm

erce

Res

earc

h

Are

a

Mar

ketin

g

Mar

ketin

g

Dis

cipl

inea

Bus

ines

s

Info

rmat

ion

syst

ems

Tabl

e 1

(con

tinu

ed)

(con

tinu

ed)

at Afyon Kocatepe Universitesi on May 22, 2014abs.sagepub.comDownloaded from

Page 8: A Critical Review of the E-Satisfaction Literature

44

Inst

rum

ent

SIT

EQ

UA

L

Ele

ctro

nic

Com

mer

ceU

ser-

Con

sum

erSa

tisfa

ctio

nIn

dex

Dim

ensi

ons

Eas

e of

use

,ae

sthe

ticde

sign

,pr

oces

sing

spee

d,se

curit

y

Prod

uct

info

rmat

ion,

cons

umer

serv

ice,

purc

hase

resu

lt an

dde

liver

y,si

tede

sign

,

Num

ber

ofIt

ems

9 51

Rel

iabi

lity

.72−

.78

.69−

87

Fit I

ndex

(if

CFA

Perf

orm

ed)

CFI

= .9

7N

FI =

.91

RM

R =

.049

RM

SEA

=.0

47G

FI =

.92

AG

FI =

.90

PGFI

= .7

2

χ2=

32.0

7df

= 21

CFI

= .9

7IF

I = .9

8G

FI =

.97

AG

FI =

.93

NN

FI =

.96

SRM

R =

.044

RM

SEA

=.0

54C

FA n

otpe

r-fo

rmed

Impa

ct(T

imes

Cite

d)

17 7

Rat

io(C

ites/

Yea

r)

2.8

1.1

Rep

licat

ion

(s)

Scop

e

Perc

eive

dqu

ality

of

an Inte

rnet

shop

ping

site

Satis

fact

ion

inde

x fo

rIn

tern

etsh

oppi

ng

Aut

hor(

s)

Yoo

&D

onth

u

Cho

&Pa

rk

Yea

r

2001

2001

Jour

nal

Qua

rter

lyJo

urna

l of

Ele

ctro

nic

Com

mer

ce

Indu

stri

alM

anag

em

ent

and

Dat

aSy

stem

Are

a

E- co

mm

erce

E- co

mm

erce

Dis

cipl

inea

Bus

ines

s

Bus

ines

s

Tabl

e 1

(con

tinu

ed)

(con

tinu

ed)

at Afyon Kocatepe Universitesi on May 22, 2014abs.sagepub.comDownloaded from

Page 9: A Critical Review of the E-Satisfaction Literature

45

Inst

rum

ent

Web

Qua

l 4.0

Use

r-Pe

rcei

ved

Web

Qua

lity

Web

C

usto

mer

Sa

tisfa

ctio

n

Key

D

imen

sion

s of

Bus

ines

s-to

-Con

sum

er

Web

Site

s

Dim

ensi

ons

purc

hasi

ng

proc

ess,

prod

uct

mer

chan

dis

ing,

deliv

ery

time

and

char

ge,

paym

ent

met

hod,

ease

of u

seU

sabi

lity,

info

rmat

ion,

serv

ice

inte

ract

ion

Spec

ific

con-

tent

,con

tent

qual

ity,

appe

aran

ce,

tech

nica

lad

equa

cyU

nder

stan

dabi

lity,

relia

bil-

ity,u

sefu

l-ne

ss,a

cces

s,us

abili

ty,

navi

gatio

nIn

form

atio

nco

nten

t,de

sign

,se

curit

y,pr

ivac

y

Num

ber

ofIt

ems

22 25 16 15

Rel

iabi

lity

.70−

.90

.85−

.91

.79−

.98

.76−

.90

Fit I

ndex

(if

CFA

Perf

orm

ed)

CFA

not

per-

form

ed

CFA

not

per-

form

ed

χ2 /df

= 2

CFA

not

per-

form

ed

Impa

ct(T

imes

Cite

d)

5 20 31 27

Rat

io(C

ites/

Yea

r)

1 4 6.2

5.4

Rep

licat

ion

(s)

Bar

nes

&V

idge

n(2

001)

Scop

e

Qua

lity

ofIn

tern

etbo

oksh

opW

eb s

ites

Web

site

qual

ity

Cus

tom

ersa

tisfa

c-tio

n w

ithth

e on

line

purc

hasi

ngpr

oces

sB

-to-

C

Web

site

Aut

hor(

s)

Bar

nes

&V

idge

n

Ala

dwan

ian

dPa

lvia

McK

inne

y,Y

oon,

&Z

ahed

i

Ran

gana

than

& Gan

apat

hy

Yea

r

2002

2002

2002

2002

Jour

nal

Jour

nal

ofE

lect

roni

cC

omm

erce

Res

earc

hIn

form

atio

nan

dM

anag

emen

t

Info

rmat

ion

Syst

ems

Res

earc

h

Info

rmat

ion

and

Man

agem

ent

Are

a

E- co

mm

erce

E- co

mm

erce

E- co

mm

erce

E- co

mm

erce

Dis

cipl

inea

Info

rmat

ion

syst

ems

Info

rmat

ion

syst

ems

Info

rmat

ion

syst

ems

Info

rmat

ion

syst

ems

Tabl

e 1

(con

tinu

ed)

(con

tinu

ed)

at Afyon Kocatepe Universitesi on May 22, 2014abs.sagepub.comDownloaded from

Page 10: A Critical Review of the E-Satisfaction Literature

46

Inst

rum

ent

Ant

eced

ents

to

E

-Loy

alty

eTai

l

Web

Site

U

ser

Satis

fact

ion

Dim

ensi

ons

Cus

tom

izat

ion,

cont

act i

nter

-ac

tivity

,cu

ltiva

tion,

care

,com

-m

unity

,ch

oice

,con

-ve

nien

ce,

char

acte

r

Web

site

desi

gn,

fulfi

llmen

t/rel

i-ab

ility

,pr

ivac

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Page 11: A Critical Review of the E-Satisfaction Literature

47

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at Afyon Kocatepe Universitesi on May 22, 2014abs.sagepub.comDownloaded from

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48

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49

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at Afyon Kocatepe Universitesi on May 22, 2014abs.sagepub.comDownloaded from

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The quality of the scale was examined using scale reliability and fit indices of con-firmatory factor analysis (CFA) reported in each study. Table 1 shows that all but twoscales (Szymanski & Hise, 2000; Novak et al., 2000) reported alpha coefficients as evi-dence of the scale’s reliability. Most of the e-satisfaction instruments were reliable,with an acceptable Cronbach’s alpha higher than .7. To investigate the factor structureof a construct, both exploratory factor analysis and CFA are crucial steps. Table 1shows that 14 of 20 (70%) instruments performed CFA and these CFAs yielded accept-able fit indices. Central to the process of scale development is to replicate the study toverify the scale’s credibility. Of the 20 scales reviewed here, only 5 were replicated bysubsequent research (i.e., Bailey & Pearson, 1983; Barnes & Vidgen, 2002; Chen &Wells, 1999; Doll & Torkzadeh, 1988; Wang, Tang, & Tang, 2001).

In sum, the accumulating body of research on user satisfaction has led to the devel-opment of a variety of instruments to measure e-satisfaction. However, our evaluationreveals that in spite of these scholarly efforts, it appears that e-satisfaction instrumentsto date have had only a limited impact on the overall e-commerce and business areas.The fact that scales ranged markedly on the number of dimensions and items measuredsuggests that scholars cannot agree on how, or possibly what, to measure to determinee-satisfaction. Many of the dimensions reviewed were of a functional versus emotionalnature, suggesting that the literature has not advanced past early conceptualizations ofWeb site usage and design. E-satisfaction scales reviewed here were cited an averageof five times per year, further revealing the narrow impact of most instruments.Although appropriate statistical analyses were conducted on the majority of the scales,replications are lacking and therefore warrant caution against the use of scales thathave not been appropriately tested and validated.

We argue that the slow adoption of e-satisfaction scales is because of inherentlimitations in this stream of research. Specifically, two primary arguments areadvanced: (a) Conceptual and operational definitions of e-satisfaction are inconsis-tent, leading to a general lack of understanding of what e-satisfaction is and how tomeasure it; and (b) the dimensions of e-satisfaction scales are redundant and/orignore aspects of Web sites that are important to e-satisfaction, resulting in poten-tially inadequate measures of e-satisfaction.

Defining E-Satisfaction

Our first argument pertains to defining e-satisfaction. We argued that conceptualand operational definitions of e-satisfaction are inconsistent. First, the definition ofe-satisfaction is grounded in the customer satisfaction literature, and many defini-tions are based on consumer satisfaction with traditional retail channels. Forexample, using Oliver’s (1997) definition of customer satisfaction as the overall sub-sequent psychological state following the appraisal of the consumer experienceagainst the prior expectations, Anderson and Srinvasan (2003) suggest a definition

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of e-satisfaction as “the contentment of the customer with respect to his or her prior pur-chasing experience with a given electronic commerce firm” (p. 125). Similarly,Wang et al. (2001) propose a construct called “customer information satisfaction” (CIS)for Web sites that market digital products and services. The authors define CIS as “a sum-mary affective response of varying intensity that follows consumption, and is stimulatedby focal aspects of sales activities, information systems (websites), digital products/services, customer support, after-sales service, and company culture” (p. 91).

These definitions of e-satisfaction are arguably grounded in an affect-basedmodel, which emphasizes the emotional aspect of Web site use. For instance, simi-lar to Oliver’s (1997) use of the term emotion, Wang et al. (2001) use the term affec-tive response, and Anderson and Srinvasan (2003) refer to experiences, a term thatis arguably affect derived and based on feelings, emotion, and so on. However, thereare inconsistencies between conceptual and operational definitions. Whereas theconceptual definitions emphasize an affective aspect of e-satisfaction, the opera-tional extensions of those definitions seem to emphasize a rational evaluative per-spective. Specifically, the dimensionality or factor structure of e-satisfaction representsthe attributes of the online shopping experience that “rational” customers consider inevaluating their encounter in e-environments. As shown in Table 1, Wang et al.(2001) and Wang and Tang (2004) identify seven dimensions in their CIS instrument,such as customer support, security, and ease of use, which emphasize a cognitiverather than affective experience. Therefore, instead of emphasizing an affectiveresponse, as defined at the conceptual level, e-satisfaction is usually operationalizedvia an expectancy-value approach, as a benchmarking outcome based on the evalu-ation of each attribute. With its roots on Fishbein and Azjen’s (1975) theory of rea-soned action, expectancy-value approach usually operationalizes user satisfactionbased on the evaluation of product-service attributes, and overall satisfaction isexpressed mathematically assuming that all attributes will be accessible and evalu-ated by the customer at the point of evaluation (Melone, 1990).

There are several potential reasons for these trends. First, the inconsistencybetween conceptual and operational definitions may be attributed to the fact thatmost e-satisfaction studies do not adequately define the e-satisfaction constructbefore developing the instrument (Wolfinbarger & Gilly, 2003). The satisfaction lit-erature as a whole has been criticized for its inconsistent use of consumer satisfac-tion definitions (Giese & Cote, 2000). Given that most e-satisfaction definitionswere derived from the general satisfaction literature, it is logical to think that e-satisfaction definitions suffer from the same issues and challenges identified byearlier scholars (e.g., Giese & Cote, 2000; McQuitty, Finn, & Wiley, 2000).Furthermore, the operationalization of e-satisfaction appears to overlap with otherdefinitions, such as e-quality, further blurring the meaning of e-satisfaction.Consider the following definition of “e-SERVQUAL”: the extent to which a Web sitefacilitates efficient and effective shopping, purchasing, and delivery of products and ser-vices (Zeithaml, Parasuraman, & Malhotra, 2000, 2002). This definition stresses the

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evaluation of the overall process of the online shopping experience, which is based ona rational and computational model. As a result, existing studies that aim to develop e-satisfaction instruments by drawing on related definitions or existing definitions inthe traditional literature have yielded contradictory definitions, resulting in confusionabout the definition and dimensions of e-satisfaction, our next argument.

Dimensions of E-Satisfaction

Our second argument is that the lack of consensus on how to define e-satisfactionhas led to disagreement on the number and types of dimensions represented bye-satisfaction scales. Two related trends that support this argument are revealed inTable 1. First, many dimensions are redundant across e-satisfaction scales, and second,different labels are used for the same construct or, alternatively, the same label isused for different constructs. For example, design is a recurring factor in a numberof scales. Returning to Table 1, note that the construct that captures design is labeledsite design (Szymanski & Hise, 2000), aesthetic design (Yoo & Donthu, 2001),design (Ranganathan & Ganapathy, 2002), and system design (Liu & Arnett, 2000)in the four e-satisfaction scales cited. The term design is used redundantly but ismeasured differently and therefore means something different than what is impliedby the label. For instance, the site design dimension identified by Szymanski andHise (2000) consists of three items: “uncluttered screens,” “easy search paths,” and “fastpresentations” (p. 316), whereas design in the scale by Ranganathan and Ganapathy(2002) is represented by “ease of navigation for information search,” “time taken fornavigation,” and “presence of visual presentation aids (graphics, audio, video)” (p. 463).The items that compose the former dimension emphasize convenience, whereas thelatter dimension emphasizes convenience and multimedia, which is a completely dif-ferent interpretation of design.

In some cases, the design dimension is given a different label, such as format (Doll& Torkzadeh, 1988), appearance (Aladwani & Palvia, 2002), and layout (Muylle,Moenaert, & Despontin, 2004). Additionally, whereas many of the dimensions identi-fied by the e-satisfaction scales capture features or characteristics of an e-environment,some dimensions appear to capture the “personality” of Web sites (e.g., see the dimen-sion character in the scale by Srinvasan et al., 2002), which is arguably a separate con-struct that requires a separate scale (see Chen & Rodgers, 2006).

In addition to these limitations, there are aspects of Web sites that are largelymissing or that are ignored entirely by current e-satisfaction scales. For instance,emotional dimensions, such as playfulness (Liu, & Arnett, 2000) and enjoyment(Bauer et al., 2006), are captured by only two scales. Other emotional aspects,such as a Web site’s ability to entertain, also are missing with rare exceptions (seeChen & Wells, 1999; Chen, Clifford, & Wells, 2002). With the exception ofAladwani and Palvia (2002) and Yang et al. (2005), other important features such

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as interactivity are not represented, and for those that contain interactive ele-ments, the definitions are somewhat limited (see McMillan & Downes, 2000).Ignoring affective components of Web sites as well as features that may be impor-tant to Web site users limits existing scales to inform only the rational compo-nents of Web sites and further reduces the generalizability and applicability of theinstruments. In sum, we believe not only that the use of redundant factors andmixed labels has created confusion about which dimensions constitute a soundmeasure of e-satisfaction, but also scales that are cyclic in nature do little toadvance our understanding of e-satisfaction.

There are several explanations for the redundant use of dimensions. First, thedevelopment of e-satisfaction instruments often draws from the end-user satis-faction literature on information systems and quality measures in the marketingliterature. Following both traditions, these scholarly attempts focused on generat-ing a list of attributes that online customers use in evaluating the online experi-ence. These attributes are usually considered the dimensions of e-satisfaction.These two literature streams, however, adopt different perspectives on the user ofthe e-environment. The information systems literature usually views users as endusers of information systems. From the end-user perspective, Web sites areviewed through an engineering lens that analyzes the functional characteristics ofa Web site, focusing on attributes such as ease of use—the degree to which asystem is “user friendly” (Doll & Torkzadeh, 1998)—information quality andtimeliness—whether information on the Web site is up-to-date (Cheung & Lee,2005)—Web site security, and so on.

In contrast, the marketing literature adopts a customer focus, which affords abroader interpretation of the functions, features, and characteristics of Web sites. Tointegrate the customer perspective into e-satisfaction measures, numerous studieshave drawn from the marketing literature and have added dimensions or items thatmeasure the general aspects of goods or services quality related to the e-tailingexperience; for example, merchandising (variety, newness, and assortment of prod-ucts that are available for an online store; Cho & Park, 2001), transaction proce-dure, payment system, and so on. In addition to the generic aspects of onlineshopping, the marketing literature has examined the interactive nature of servicequality (i.e., SERVQUAL; Parasuraman, Zeithaml, & Berry, 1988). In line with thistradition, consumer-centric measures of e-satisfaction have attempted to accountfor the interactive aspect of service quality (e.g., Parasuraman et al., 1988) and tan-gible dimensions—which refers to physical environments offline and Web siteappearance online (Cheung & Lee, 2005; Gefen, 2002). In sum, the customer per-spective requires e-satisfaction instruments to encompass measurements that cap-ture the actual product and service and the process of receiving those products andservices online, implying that scale dimensions are influenced by the traditionsfrom which they are derived as well as assumptions about the end user.

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Future Research on E-Satisfaction

The gaps identified above provide abundant opportunities for future research. First,as argued by Bagozzi, Gopinath, and Nyer (1999), although emotion can perform asantecedents, moderators, or mediators in individuals’ evaluation formation, it has beengiven minimal consideration in the e-satisfaction literature (for an exception, seeÉthier, Hadaya, Talbot, & Cadieux, 2006) and therefore warrants future investigation.As noted earlier, although the construct of satisfaction has both emotional (Bagozzi et al., 1999; Éthier et al., 2006; Wang et al., 2001) and cognitive aspects (Muylle et al.,2004), most studies on e-satisfaction follow a rational-evaluative approach and ignorethe emotional aspect of e-satisfaction. This limitation inherent in the definitions of e-satisfaction has led to a myopic approach to constructing e-satisfaction models anddeveloping e-satisfaction scales. By simply listing the attributes of objects to be eval-uated without examining subjective attributes (individual factors and situational factors), existing research provides “a limited, if not entirely distorted, picture” of usersatisfaction (Melone, 1990 p. 85).

One way to alleviate this criticism is to center the operationalization of e-satisfactionon the well-developed and established model expectancy–disconfirmation para-digm, where the actual performance is compared to a reference point and satisfac-tion is considered the result of the discrepancy between the actual and the referencepoint (Oliver, 1997; Parasuraman, Zeithaml, & Berry, 1988). The disconfirmationparadigm, based on an individual psychological appraisal process, thus far, is ubiq-uitous in the customer satisfaction area. Therefore, examining its generalizabilityunder an online context not only offers a stronger theoretical foundation for build-ing e-satisfaction models, it also helps to identify the similarities and differencesbetween online versus offline customers’ formation of satisfaction (for initialefforts, please refer to McKinney et al., 2002; Wolfinbarger & Gilly, 2003; andZeithaml et al., 2002).

Next, by adopting the disconfirmation paradigm and by taking the emotionalaspects of e-satisfaction into consideration, future investigations should focus on theprocess that consumers adopt in forming their satisfaction with e-environments. Asnoted by Bagozzi et al. (1999), it is more important to examine the processes andexperiences constituting an individual’s response and reaction to an event rather thanfocusing solely on antecedents. A process-based e-satisfaction model will more real-istically reflect how users form evaluations in actuality and will provide greater sen-sitivity to individual and contextual variables, hence will serve as a more usefulmodel to gauge the effectiveness of the online channel than existing models basedon expectancy and value.

The foregoing discussion also calls for multidisciplinary efforts in integrating theexisting literature to eliminate redundant dimensions and clarify items that representand measure those dimensions. As e-commerce is an ever-changing field,researchers need to be sensitive about the constant need to update the measurement

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scale of e-satisfaction. Specifically, new features offered through technologicaladvancement call for the need to take these features into consideration when examin-ing the dimensionality of e-satisfaction, particularly, innovative features of technology,such as interactivity, personalization, and customization. Additionally, future researchshould investigate the predictability of existing dimensions and factors identified ine-satisfaction scales and the relationship of these dimensions to key outcome variablesin an effort to help businesses identify their strategic priorities. Last, more research isneeded to understand not just the what of e-satisfaction, as measured by existingscales, but also the why of e-satisfaction, which attempts to understand underlyingprocesses that drive and consequences that result from e-satisfaction.

Conclusions

The present review has identified a number of gaps in the existing e-satisfaction lit-erature that warrant future study. Inconsistent definitions and redundant dimensionsare but two limitations noted here. We argue that these two limitations are related.Specifically, confusion about how to define e-satisfaction has led to disagreementabout the number and types of dimensions of e-satisfaction. In view of these limita-tions, we have identified several opportunities for future research. One direction is toexamine e-satisfaction from the cognitive and affective perspectives by taking emotioninto consideration when investigating consumers’ e-satisfaction formation processbased on expectancy–disconfirmation instead of expectancy–value paradigm. Theseconsiderations should help to clarify the definition of e-satisfaction and encourageprogress in the creation of scales that more comprehensively measure e-satisfaction.Another direction is to examine the dimensionality of e-satisfaction from both end-user and customer perspectives. These multidisciplinary efforts will ultimately helpeliminate redundancy in identifying the dimensionality of e-satisfaction and help toprioritize the dimensions based on their predictive power in relationship to outcomevariables.

The present review informs practice in many ways. First, as e-satisfaction hasbecome the primary driver of success or failure of a Web site (Zeithaml, 2002),many businesses and organizations have shifted their focus from how to attractcustomers to a Web site to how to keep customers coming back. The inconsisten-cies and trends identified in this study caution organizations to be aware of the lim-itations of current e-satisfaction instruments and present future directions andopportunities in gauging this important concept. Second, as Web sites usuallyserve very different functions, e-satisfaction by its definition applies to nearlyevery type of business, organization, or group represented online, including gov-ernment, education, nonprofit, and political Web sites. This suggests a need todevelop more comprehensive measures of e-satisfaction that can be used acrossdisciplines to assess the effectiveness of Web sites of all varieties. By linking the

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new dimensions of e-satisfaction with outcome variables that are relevant and specificto a particular site, more fruitful results can be found with regard to users’ satisfactionwith those Web sites. For instance, for .com Web sites, repeated patronage might be animportant consequence, whereas for .org, compliance or volunteerism may be impor-tant outcomes. Thus, constructing contingency frameworks of e-satisfaction within thespecific contexts in which e-satisfaction measures are used will provide greater empir-ical potential for evoking rich insights. Replicating current e-satisfaction scales acrosssite types will also help to overcome the lack of validation currently existing with moste-satisfaction scales. Last, Web sites in such fields as health care and education willbenefit from taking the affective aspects of e-satisfaction into consideration, becauseaffect and emotion-laden constructs might be dominant in customer e-satisfactionformation toward such sites.

In sum, the area of e-satisfaction has yet to incorporate the collective intelligence inall related disciplines such as psychology, education, and marketing to offer a compre-hensive picture of users’ online experience and satisfaction with that experience.Consequently, there is tremendous research potential for behavioral scientists who wishto explore e-satisfaction and to advance the e-satisfaction literature as a whole.

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Qimei Chen is the Shidler Distinguished Professor, associate professor of marketing, and chair of theMarketing Department in the Shidler College of Business at the University of Hawaii at Manoa and anadvisory professor at Fudan University in Shanghai, China. She received her PhD from the University ofMinnesota, Twin Cities, and prior to that, she has years of industrial experience in China, Germany, andHong Kong. Her current research interests include online and offline health care marketing and innova-tion and knowledge. Her research has been widely published in journals such as Journal of Advertising,Journal of Advertising Research, Journal of Business Research, Journal of Product InnovationManagement, and Journal of Retailing.

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Shelly Rodgers is an associate professor of strategic communication at the Missouri School of Journalism.She teaches in the areas of strategic communication and health communication with expertise on Internethealth advertising, marketing, and communication. Rodgers is nationally ranked as one of the most pro-ductive Internet advertising scholars and is among the top 10 most cited Internet advertising researchers.Rodgers’ research examines the effects of interactive communications on audience processing withemphasis on how to use the Internet to promote healthy behaviors.

Yi He is an assistant professor of marketing in the College of Business and Economics at California StateUniversity, East Bay. She completed her PhD in international management (marketing concentration) atthe University of Hawaii at Manoa. She received her master’s degree from University of Cincinnati. Hercurrent research interests include consumer behavior and psychology, cross-cultural consumer behavior,psychology of social technology, and advertising effectiveness. Her studies have appeared in journalssuch as Journal of International Marketing, International Marketing Review, and International Journalof Advertising.

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