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Buying apparel over the InternetRonald E GoldsmithProfessor of Marketing Marketing Department College of BusinessFlorida State University Tallahassee Florida USA
Elizabeth B GoldsmithProfessor Department of Textiles and Consumer Science FloridaState University Tallahassee Florida USA
Keywords Internet Online transaction processing Consumer behaviour Clothing industry Marketing
Abstract Tests ten hypotheses describing characteristics that distinguish consumers whohave purchased apparel online from those who have not A sample of 263 men and 303women students completed a survey that measured their online and offline buyingbehavior attitudes and predispositions The results showed that the 99 online apparelbuyers had more online buying experience in general Online buyers did not differ fromnon-buyers in their belief in how cheap buying online is in their overall enjoyment ofshopping or in how often they bought clothing by any means The demographi c variablesof age sex and race were unrelated to online apparel buying A further analysis showedthat the online buyers used the Internet more hours per week and were more likely to buyonline in the future than non-buyers The findings are consistent with previous studies ofconsumer Internet behavior and with consumer theory and provide guidance for e-commerce apparel strategies
Introduction
Electronic retailing continues to grow in size and importance as increasing
numbers of consumers buy online and apparel purchases represent a
significant portion of online purchasing Not only does buying apparel online
represent a new form of consumer behavior in the ` computer-mediated
shopping environmentrsquorsquo (Hoffman and Novak 1996) apparel e-tailers face
intense competition Thus consumer researchers wish to extend current
theories of consumer behavior into this new consumption realm and apparel
marketers and managers seek to develop effective strategies based on
knowledge of their consumers (Goldsmith and McGregor 1999) Although
some research on consumer Internet behavior has begun to appear (eg Citrin
et al 2000) little attention has been devoted specifically to buying apparel
online Our study fills this gap by focusing on this new clothing behavior
While the number of online buyers and value of their purchases change
constantly growth is the dominant theme (Goldsmith and McGregor 2000)
Americans spent $184B on total apparel in 1999 with $11B or 06 per cent
attributed to online apparel purchases (Kuntz 2000) For 2000 the proportion
of total US apparel sales online is estimated at less than 3 per cent but still
nearly $35B (Vickery and Agins 2001) Apparel spending in the UK was
pound30B (Wilson 1999) According to one estimate approximately 67 per cent
of Americans use the Internet and 52 per cent of them buy online (UCLA
2000) Apparel is an important category of online purchases with new sites
constantly appearing (Murphy 1999) An Internet-based research company
estimated online sales in 2000 to be $37B up from $186B in 1999
(eMarketer 2000 p 9) One estimate of total weekly online purchases in
2000 puts the number at 3582 million with 300800 or 84 per cent of these
in the apparel category (Nelson 2000) Two separate surveys showed
The research register for this journal is available at
httpwwwemeraldinsightcomresearchregisters
The current issue and full text archive of this journal is available at
httpwwwemeraldinsightcom1061-0421htm
Electronic retailing
Growth the dominanttheme
JOURNAL OF PRODUCT amp BRAND MANAGEMENT VOL 11 NO 2 2002 pp 89-102 MCB UP LIMITED 1061-0421 DOI 10110810610420210423464 89
An executive summary formanagers and executivereaders can be found at theend of this article
clothing among the top six categories of holiday gifts in the USA for the
2000 Christmas season (eMarketer 2000 p 30) Thus apparel is an
important consumer purchase category with a significant online component
E-commerce is expensive however and many companies have found profits
hard to come by (Harvard Management Update 2000) Selling apparel
online presents unique challenges to cybermarketers Little is known of
consumer buyer behavior online and e-tailers need to attract those
consumers most likely to buy in order to cover the costs of e-commerce and
make a profit to justify this new form of distribution The first buyers of a
new product or service however are likely to be systematically different
from later buyers (Eastlick and Lotz 1999 Goldsmith 2000 Limayem et
al 2000) Hence the purpose of the present study was to compare
consumers who had purchased apparel online with consumers who had not
purchased apparel online with regard to demographics and attitudes toward
online purchasing Several hypotheses about buying apparel online were
derived from consumer research and tested using data from a survey of
student consumers Testing the hypotheses not only enhances our knowledge
of consumer behavior by extending the scope of theory into the new
shopping environment this information may help online apparel marketers
improve their strategies designed to entice customers to buy online
Hypotheses
Consumers differ in the extent of online buying in which they engage
According to the standard discussions of buying frequency relatively few
buyers in a product category account for the majority of purchases (Hallberg
1995) Since online buying is a new consumer activity we expect that
consumers who have previous experience in online buying will be more
likely to buy apparel online than those who lack such experience This is
because as consumers gain experience with online buying perhaps with
small purchases at first they will be likely to develop confidence and skills
that facilitate more ambitious buying (Seckler 2000) Thus H1 is that
consumers who have bought apparel online will have more experience
buying online in general
Consumers who have bought apparel online may likely be those who buy
more frequently than other consumers In other words consumers who buy
apparel frequently are likely involved with clothing as a product category
they not only shop frequently they probably spend more than less involved
less frequent shoppers Thus H2 is that consumers who purchase apparel
online shop for apparel by any means more frequently than those who have
not bought apparel online
Several studies of consumer online behavior have shown that attitudes toward
the Internet and toward online buying are systematically related to online
buying behavior (Eastlick and Lotz 1999 Goldsmith and Bridges 2000
Karson 2000 Katz and Aspden 1997) Goldsmith (2000) presents Likert
scales to measure five specific attitudes toward e-commerce describing
individual perceptions of its enjoyment safety speed how economical it is
and how much confidence consumers have in their ability to shop and buy
online These attitudes were all related to online buying Thus H3 through H7
are that compared with consumers who have not bought apparel online those
who have bought online feel that the Internet is more fun safer quicker
cheaper and they have more confidence in their ability to buy
Similarly how consumers feel about shopping in general should influence
whether they shop online and specifically purchase apparel online (see
Unique challenges
Previous experience
Online buying behaviour
90 JOURNAL OF PRODUCT amp BRAND MANAGEMENT VOL 11 NO 2 2002
Solomon 1999 pp 311-13) Thus H8 is that a positive disposition toward
shopping should be associated with buying apparel online Finally
consumers who are more innovative and knowledgeable with regard to the
Internet and its uses are more likely to buy online than less innovative and
knowledgeable consumers (Citrin et al 2000 Limayem et al 2000) H9
and H10 are that online apparel buyers will describe themselves as more
innovative and knowledgeable regarding the Internet than non-buyers
Method
Survey participants
The data came from a survey of 566 students at a large southern university in
the USA in the spring of 2000 The students were in either marketing or
human sciences classes Both undergraduates and MBAs participated
Although not representative of all consumers these young buyers are
important because they are heavy buyers of clothing influence the clothing
spending of many other consumers and represent the future of e-commerce
(Hogg et al 1998 Silverman 2000) There were 263 (465 per cent) men
and 303 (535 per cent) women in the sample Their ages ranged from 18 to
50 with a mean of 226 years (SD = 49) The modal age was 20 years Most
of the participants were juniors (276 488 per cent) and seniors (195 345
per cent) with the rest being 17 (3 per cent) sophomores 75 (133 per cent)
graduate students and 3 (05 per cent) other There were 419 (74 per cent)
whites 65 (115 per cent) African-Americans 42 (74 per cent) Hispanics
and 40 (71 per cent) others This distribution is quite similar to the ethnic
distribution on this campus There was no statistically significant (p lt 005)
difference in mean age between the men and women nor were the mean ages
of the four ethnic groups significantly different A cross-tabulation of sex by
race showed that the proportions of men and women in each ethnic category
were nearly identical with the exception that the sample contained
proportionally more African-American women and proportionally fewer
white women
Questionnaire
An initial version of the questionnaire was pilot-tested with 39 students in a
marketing research class for readability ease of use and clarity After
correcting obvious errors and making their suggested changes in wording
and organization the revised questionnaire was fielded by requesting student
volunteers to complete it
The questionnaire contained demographic questions asking for the
participantsrsquo sex age race and class standing Other questions asked
whether the respondents had access to the Internet how many hours they
used it per week and whether they had ever purchased any apparel online It
also contained rating scales to measure their online purchasing behavior
likelihood of future online purchases and apparel purchase Table I shows
these questions and the responses For the chief variable of interest to this
study whether a respondent had ever purchased apparel online (termed
EVER) 99 or 175 per cent of the respondents affirmed that they had so
purchased and 467 (825 per cent) said that they had not This is similar to
one report that 16 per cent of Internet users purchased apparel in cyberspace
during the previous month (Seckler 2000)
The next section of the questionnaire contained 25 Likert-type statements
reflecting attitudes toward shopping over the Internet and enjoyment of
shopping in general A portion of these items appears in Table II These
Internet shopping items were adapted from a set of online buying attitude
Ethnic distribution
Questions and responses
JOURNAL OF PRODUCT amp BRAND MANAGEMENT VOL 11 NO 2 2002 91
items developed by Goldsmith (2000) Three of the shopping enjoyment
items were adapted from OrsquoGuinn and Faber (1989) and one original
shopping item was added for this study
Finally came a section containing the Domain-Specific Innovativeness Scale
or DSI (Goldsmith and Hofacker 1991) This scale was included to measure
Internet innovativeness A factor analysis of the six items revealed a two-
factor solution with the three positive items forming one factor and the three
negative items a second factor We decided to use only the three negative
items as a summed scale because this subscale (termed DSI) had the higher
internal consistency (coefficient alpha = 079) The items appear in Table III
along with a five-item subjective knowledge scale (Flynn et al 2000) used
to measure knowledge of the Internet Factor analysis showed that these
Variable Questionnaire item Response N
ACCESS Do you have access to the
Internet
Yes
No
562
4
993
07
EVER Have you ever purchased any
clothing online
Yes
No
99
467
175
825
OFTEN How often would you say that
you purchase online
Very often
Often
Sometimes
Rarely
Never
4
18
119
201
224
07
32
210
355
396
BUY Asked another way how often
do you purchase online
More than once a week
About once a week
Only about once every two
weeks
Less than once every two
weeks but more than once
a month
Less than once a month
I never do
3
6
12
30
283
232
05
11
21
53
500
410
TIMES How many times have you
bought something online since
January 1 2000
plusmn plusmn times
MEANS How often do you purchase
clothing by any means
Very often
Often
Sometimes
Rarely
Never
Missing
83
179
226
55
21
2
147
316
399
97
37
04
HOURS On average about how many
hours a week do you spend
using the Internet
None
Less than one
One to five
Five to ten
Ten to 20
More than 20
Missing
5
68
244
164
63
21
1
09
120
431
290
111
37
02
LIKELY Regardless of how much you
buy online now how likely are
you to buy online in the
coming year
Definitely will buy
Probably will buy
Might buy
Probably will not buy
Definitely will not buy
Missing
82
107
208
141
23
5
145
189
367
249
41
09
SPEND How much do you spend on
clothing purchases in an
average month
Table I Internet and buying questions
Internet innovativeness
92 JOURNAL OF PRODUCT amp BRAND MANAGEMENT VOL 11 NO 2 2002
items formed a unidimensional scale (termed KNOW) with acceptably high
internal consistency (coefficient alpha = 090)
Results
The first preliminary analysis reduced the three online purchasing questions
(OFTEN BUY and TIMES from Table I) into a composite measure of the
self-reported amount of online buying of each respondent This was done
using a principal components analysis of the three items (Hair et al 1998
Ch 3) and computing factor scores using the SPSS regression method The
analysis extracted a single component with an eigenvalue of 237 that
explained 79 per cent of the variance in the correlation matrix of the three
variables The resulting variable was labeled PURCH Summary descriptive
statistics appear in Table IV
Attitude itema Fun Shop Safe Conf Cheap Quick
Buying over the Internet is more fun than
buying in a store 079
I enjoy buying over the Internet 056
I find shopping on the Internet less pleasant
than shopping in storesb 049
I sometimes shop for goods but then buy
them on the Internet 041
I get a real ` highrsquorsquo from shopping 086
Shopping is fun 083
I shop because buying things makes me
happy 080
I do not mind spending a lot of time
shoppingb 069
Buying over the Internet is no riskier than
buying in a store 084
It is risky to buy over the Internetb 073
Buying over the Internet is safer than buying
in a store plusmn033 048
I lack the confidence to buy correctly on the
Internetb 064
I am confident in my ability to buy
successfully over the Internet 055
There are so many dotcom companies out
there itrsquos confusingb 049
I cannot get the buying information I want
over the Internetb 040
I cannot save much money buying over the
Internetb 089
Buying over the Internet is cheaper than
buying in a store 067
Buying over the Internet is quicker than
buying in a store 064
Buying over the Internet is more efficient
than buying in a store 039
It takes a lot of time and trouble to buy on
the Internetb plusmn032 037
Eigenvalue 55 28 15 14 11 10
Percent of variance 274 139 76 68 54 51
Kaiser-Meyer-Olkin measure of sampling
adequacy = 0840
Notes Only loadings gt 030 are shown a using a five-point agree-disagree responseformat b reverse-coded items
Table II Factor analysis of attitude items
Composite measure
JOURNAL OF PRODUCT amp BRAND MANAGEMENT VOL 11 NO 2 2002 93
The second preliminary analysis examined the structure of the 25 attitude
items by submitting them to a common factor analysis followed by an
oblique rotation on the assumption that the attitude dimensions would be
correlated with one another (Hair et al 1998 Ch 3) The analysis was
conducted four times each time identifying items that did not load on a
factor with other items or which had small loadings (lt 003) or sizeable
(gt 030) cross-loadings on more than one factor Items were retained for
factors if they had sizeable loadings (gt 030) on factors made of items with
similar content These analyses reduced the initial pool of attitude items to
20 items that combined into six easily interpretable subscales that were
similar to those reported by Goldsmith (2000) The final analysis results
appear in Table II where the six factors represent the attitudes that shopping
on the Internet is fun safe cheap and quick and that the respondent had
confidence in hisher ability to shop online as well as the general
` enjoyment in shoppingrsquorsquo scale The scales are labeled FUN SAFE
CHEAP QUICK CONFIDENCE and SHOP The individual items were
summed to form short scales (see Table IV)
Next the Internet innovativeness and knowledge items were factor-analyzed
via common factor analysis which revealed that the items loaded on two
distinct factors indicating discriminant validity for these items (see Table
III) The individual items were summed to form two scales DSI and KNOW
Thus the focal variables in the study were amount of online buying
(PURCH) how often clothing was purchased by any means (MEANS) the
attitudes toward online buying (FUN SAFE CHEAP QUICK and
CONFIDENCE) attitude toward shopping (SHOP) Internet innovativeness
(DSI) and knowledge of the Internet (KNOW)
Cross-tabulation was used to assess the relationship between EVER (those
who had purchased apparel online versus those who had not) and sex and
race These analyses showed no statistically significant relationships
between these variables A t-test showed no statistically significant
difference in the mean age of those who had purchased apparel online versus
those who had not The correlations in Table IV provide internal evidence for
the validity of the measures The significant correlations of the DSI with
Scale itema Factor 1 Factor 2
Internet knowledge (KNOW)
When it comes to the Internet I really do not know a lotb 088
I know pretty much about the Internet 083
Compared with most other people I know less about the Internetb 082
I do not feel very knowledgeable about the Internetb 081
Among my circle of friends I am one of the ` expertsrsquorsquo on the
Internet 065
Internet innovativeness (DSI)
In general I am among the last in my circle of friends to purchase
something over the Internetb 081
Compared with my friends I do little shopping over the Internetb 079
In general I am the last in my circle of friends to know the names
of the latest places to shop on the Internetb 062
Eigenvalue 415 155
Percent of variance 518 194
Kaiser-Meyer-Olkin measure of sampling adequacy = 0865
Notes Only loadings gt 030 are shown a using a five-point agree-disagree responseformat b reverse-coded items
Table III Factor analysis of Internet knowledge and innovativeness items
Common factor analysis
Focal variables
94 JOURNAL OF PRODUCT amp BRAND MANAGEMENT VOL 11 NO 2 2002
Var
iable
sR
ange
Mea
nS
D1
23
45
67
89
10
11
12
13
14
15
16
1
Age
18-5
0226
49
plusmn
2
Sex
0-1
aplusmn
plusmn00
6plusmn
3
Ever
0-1
bplusmn
plusmn00
2plusmn00
5plusmn
4
Purc
hplusmn08
8-
86
80
10
00
801
804
2plusmn
5
Mea
ns
1-5
34
409
8plusmn01
1plusmn03
100
100
2plusmn
6
Fun
4-2
0105
27
00
801
603
505
600
2(0
74)c
7
Saf
e3-1
572
22
plusmn00
301
001
503
700
604
4(0
76)
8
Chea
p2-1
061
16
00
802
400
203
8plusmn00
804
402
9(0
75)
9
Quic
k3-1
593
27
01
000
901
702
9plusmn00
404
702
904
0(0
58)
10
Conf
4-2
0136
30
00
600
802
304
300
004
603
604
303
9(0
70)
11
Shop
4-2
0132
39
plusmn02
6plusmn04
500
5plusmn01
104
0plusmn01
6plusmn00
4plusmn02
1plusmn01
3plusmn01
6(0
86)
12
DS
I3-1
594
27
plusmn00
400
402
804
801
504
202
902
501
904
700
4(0
79)
13
Know
5-2
5184
40
plusmn00
000
801
102
800
602
601
201
601
704
9plusmn00
504
0(0
90)
14
Spen
d0-5
00
893
748
plusmn00
9plusmn02
200
300
604
3plusmn00
100
3plusmn00
8plusmn00
1plusmn00
103
001
300
1plusmn
15
Hours
1-6
35
10
01
101
101
803
600
403
101
602
001
603
4plusmn00
802
804
700
4plusmn
16
Lik
ely
1-5
32
11
00
801
203
306
700
405
904
003
503
704
6plusmn00
704
702
800
503
4plusmn
Note
sC
orr
elat
ions
of
00
9an
dla
rger
are
stat
isti
call
ysi
gnif
ican
tat
plt
00
5(t
wo-t
aile
d)
a1
=m
ale
and
0=
fem
ale
b1
=yes
and
0=
no
cco
effi
cien
tal
pha
inpar
enth
eses
Table
IV
Des
crip
tive
stati
stic
sand
corr
elati
ons
JOURNAL OF PRODUCT amp BRAND MANAGEMENT VOL 11 NO 2 2002 95
FUN SAFE CHEAP QUICK and CONFIDENCE are similar to those
reported by Goldsmith (2000) Moreover the correlation of the DSI with the
knowledge measure (r = 040) is comparable with that reported by Flynn et
al (2000)
An analysis was performed to assess the influence of age sex and race on the
dependent variables A MANCOVA with sex and race as the two
independent variables and age as a covariate was run with PURCH through
KNOW as the ten dependent variables The correlations in Table IV suggest
that age was only significantly correlated with shopping enjoyment and this
was confirmed by the results of the MANCOVA so age was no longer
incorporated in the analyses The results also showed no statistically
significant multivariate interaction between sex and race (F(33 1500) = 114
p = 0266) There was a statistically significant multivariate effect of race
(F(33 1500) = 162 p = 0014) but the only univariate differences were for
SAFE (p = 0033) where African-Americans rated the Internet as less safe
than whites and CHEAP (p = 0032) where the ` othersrsquorsquo rated the Internet as
cheaper than both whites and African-Americans These differences were
few and small in size and so race was no longer included in the analyses
The multivariate effect of sex was significant (F(11 498) = 48 p lt 0001)
Univariate tests showed that women reported purchasing apparel by any
means more often than men they spent more on apparel than men and they
enjoyed shopping more than men while the men reported purchasing more
online than the women and felt that the Internet was cheaper than the
women These differences suggest that sex should be included in the final
analysis of the differences between those who have purchased apparel online
and those who have not
For this analysis a 2 pound 2 (SEX pound EVER) MANOVA was run with the ten
dependent variables as before (see Table V) The interaction term was
Mean scoresa Observed
Dependent variables Men Women Fb p eta2 power
Univariate main effects for SEX
PURCH 0678 0126 308 lt 0000 0052 10
MEANS 306 375 378 lt 0000 0072 10
FUN 119 108 145 lt 0000 0025 0967
SAFE 77 73 29 0089 0005 0397
CHEAP 68 57 418 lt 0000 0070 10
QUICK 99 94 46 0032 0008 0576
CONFIDENT 145 139 35 0060 0006 0468
SHOP 115 148 687 lt 0000 0110 10
DSI 101 100 03 0601 0000 0082
KNOW 192 184 32 0074 0006 0431
Univariate main effects for EVER
H1 PURCH plusmn0184 0988 1391 lt 0000 0200 10
H2 MEANS 34 34 0075 0784 0000 0059
H3 FUN 101 127 879 lt 0000 0136 10
H4 SAFE 70 79 121 0001 0021 0934
H5 CHEAP 61 63 14 0245 0002 0213
H6 QUICK 92 102 197 lt 0000 0034 0993
H7 CONFIDENT 133 151 320 lt 0000 0054 10
H8 SHOP 130 133 0646 0422 0001 0126
H9 DSI 91 110 448 lt 0000 0074 10
H10 KNOW 182 194 78 0005 0014 0798
Notes a Estimated marginal means b df = 1558
Table V Comparisons of mean scores
Influence of age sex andrace
96 JOURNAL OF PRODUCT amp BRAND MANAGEMENT VOL 11 NO 2 2002
statistically significant (F(10 549) = 24 p = 001) Follow-up univariate
analyses showed that the interactions however were significant for only
two of the dependent variables For PURCH the amount of online buying
men reported buying more than women but men who had bought apparel
online reported buying disproportionately more online than women who
had bought apparel online The opposite effect was observed for MEANS
buying apparel by any means Women reported buying apparel by any
means more than men but men who had bought apparel online reported
buying disproportionately less apparel by any means than the women
online buyers
The multivariate main effect for SEX was significant (F(10 549) = 143
p lt 0001) In addition to significant main effect differences for PURCH and
MEANS women reported that they enjoyed shopping (SHOP) more than
men and men reported that they thought online buying was more fun
cheaper and quicker than the women These findings are similar to those
reported in other studies of online buying
The multivariate main effect for EVER whether a respondent had ever
bought apparel online was statistically significant (F(10 549) = 204
p lt 0001) The univariate analyses showed that compared with those who
had not bought apparel online those who had bought apparel online had
more experience purchasing online in general (PURCH) and thought that
buying over the Internet was more fun safer quicker and they were more
confident in their ability to buy online The online apparel buyers also were
more innovative and knowledgeable about the Internet than non-buyers
Thus H1 H3 H4 H6 H7 H9 and H10 were confirmed There were no
statistically significant differences in the self-reported apparel purchase
(MEANS) perceptions that online buying was cheaper (CHEAP) or in
shopping enjoyment (SHOP) Because Boxrsquos test of the equality of the
covariance matrices was significant (indicating that the covariance matrices
were not identical across the groups of respondents) and because Levenersquos
test of equality of error variances showed that the error variances of four of
the dependent variables were not equal thus violating the assumptions of
MANOVA (Huck and Cormier 1996 pp 313-15 374-7) a Mann-Whitney
non-parametric analysis was conducted testing whether the observations
from the two groups of online apparel buyers were equivalent in location
These analyses were consistent with the parametric tests
As a final analysis a 2 pound 2 (SEX pound EVER with age as a covariate)
MANCOVA was conducted comparing the buyers and non-buyers on three
additional variables These were
(1) the number of hours the respondent was online in an average week
(HOURS)
(2) the amount of reported spending on apparel (SPEND) and
(2) how likely the respondent was to buy online in the coming year
(LIKELY)
The results showed that men averaged more hours online per week than
women women spent more on apparel than men and the men were more
likely to shop online in the future than were the women Finally online
apparel buyers reported spending more time online and were more likely to
buy online in the future than non-buyers
Online apparel buyers
Additional variables
JOURNAL OF PRODUCT amp BRAND MANAGEMENT VOL 11 NO 2 2002 97
Discussion
The present study compared selected characteristics of consumers who had
purchased apparel online with those who had not The results showed that
online apparel buyers purchased online more often felt that online buying
was more fun safer and quicker than non-buyers Online apparel buyers
were more confident in their ability to buy online and were more innovative
and knowledgeable about the Internet than non-buyers Online apparel
buyers did not differ from non-buyers in their belief in how cheap buying
online is in their overall enjoyment of shopping or in how often they bought
apparel by any means Respondent demographics were also unrelated to
buying apparel online Online apparel buyers further differed from non-
buyers in that they spent more time online than non-buyers and were more
likely to buy online in the future than non-buyers These results reveal a
systematic pattern of psychological and behavioral factors that seem to
facilitate online apparel purchase
These findings confirm theoretical accounts of consumer behavior and
extend their generality into the new realm of cyber-commerce The findings
are consistent with other studies that show that favorable attitudes are related
to online buying From the methodological perspective the attitude measures
appear to be robust across studies and provide valid reliable
operationalizations of these constructs This should encourage researchers to
use them as standardized measures of e-commerce-related attitudes The
findings also confirm the reliability and validity of the innovativeness (DSI)
and knowledge scales consistent with a series of studies that have evidenced
their psychometric soundness (eg Flynn et al 2000 Goldsmith 2000)
The findings suggest that consumers are motivated to buy apparel online by a
combination of factors and that the special circumstances of e-commerce
make this a unique consumption activity Online apparel buyers obviously
must want and need clothing so this basic motivation partially underlies
their behavior They seem however to be motivated differentially by their
attitudes toward the Internet While online apparel buyers were clearly more
positive on the attitudinal and psychological characteristics they were no
more likely than non-buyers to shop for clothes by other means to enjoy
shopping in general or to spend money buying clothes That is they are not
disproportionately motivated by clothing as a product category or by interest
in shopping but by the perceived advantages of online buying and their
positive predisposition toward this mode of commerce
For managers the results suggest that their online buyers may be somewhat
different from their in-store customers and may represent new customers
Consumers who buy disproportionately more apparel likely enjoy shopping
and want the emotional and sensory pleasures of touching seeing and trying
on clothes (see Seckler 2000 Underhill 1999) Note the positive
intercorrelations in Table IV between spending on apparel and shopping
(r = 030) spending and buying by any means (043) and between shopping
and buying (040) None of these variables was correlated with amount of
online buying (PURCH) Online buyers in contrast appear to be motivated
by their positive attitudes toward the Internet Thus to attract apparel buyers
to Web sites e-marketers might focus on emphasizing the added advantages
of fun speed and safety They should first ensure that their sites are fun to
use load rapidly with prompt post-sale delivery of ordered merchandise and
are completely safe to use They might emphasize how different online
buying is and not pretend that it is the same as in-store shopping Joint or
cooperative strategies might display apparel online but suggest that a
Respondent demographics
Unique consumptionactivity
Positive attitudes
98 JOURNAL OF PRODUCT amp BRAND MANAGEMENT VOL 11 NO 2 2002
different experience could be had in the store where unique accessories or
combinations of clothes could be seen Online apparel buyers and non-
buyers did not differ in their perception that buying online is cheaper than
offline Thus Secklerrsquos (2000) argument that offering price discounts may be
a prime way to attract non-buyers is supported To attract new buyers onlineapparel e-tailers may have to change perceptions that online buying is unsafe
(see Robinson 2000) Web sites must be made simple and easy to use
because non-users are not very confident that they can buy online
successfully In-store demonstrations of online shopping might encourage
non-buyers to shop online As online apparel buying spreads beyond the
innovative and knowledgeable consumer to the less sophisticated shopper
apparel marketers should cater to their unique tastes abilities and habits
This is especially true since the results suggest that many online apparel
buyers will buy online again
The study is limited by the nature of the sample measures specificity and
time studied Lack of randomness in the sample limits generalizability of the
point and interval estimates to a larger population but since the main
purpose of the study was to test theoretical hypotheses about online buyingthis is a minor limitation (Calder et al 1981) No conclusions can be drawn
about concepts that might be related to online apparel buying but were not
measured and the results are limited to the measures employed Similarly
the focal topic was clothing in general and not a specific type (new fashion
sports clothes work clothes etc) Finally since e-commerce and online
consumer behavior are constantly changing phenomena the present study is
only a snapshot picture and not a longitudinal view
Advantages of the study lie in the large sample size and validity of the
measures used Future research should examine online apparel using data
from other demographic socio-economic and national groups of consumers
to expand the scope of the findings The online buyer behaviors studied
should be expanded beyond just buying to include browsing comparison
shopping and combining the Internet with in-store consumption as well asconsumption of specific categories of apparel such as new fashions or
unique sizes and needs As noted in the introduction growth is a major
theme of e-commerce Thus replication studies would be a valuable way to
track changes in online apparel buying over time Accumulation of such
studies would expand our knowledge of both apparel consumer behavior and
consumer Internet behavior to the advantage of both consumer theory and
apparel marketing Finally other researchers could make use of our measures
to study buying behavior in other areas as well
References
Calder BJ Phillips LW and Tybout AM (1981) ` Designing research for application rsquorsquo
Journal of Consumer Research Vol 8 September pp 197-207
Citrin AV Sprott DE Silveman SN and Stem DE Jr (2000) ` Adoption of Internet
shopping the role of consumer innovativenessrsquorsquo Industrial Management amp Data Systems
Vol 100 No 7 pp 294-300
Eastlick MA and Lotz S (1999) ` Profiling potential adopters and non-adopter s of an
interactive electronic shopping mediumrsquorsquo Internationa l Journal of Retail amp Distribution
Management Vol 27 No 6 pp 209-23
eMarketer (2000) ` The e-holiday shopping reportrsquorsquo available at wwwemarketercom
Flynn LR Goldsmith RE and Kim W (2000) ` A cross-cultural validation of three new
marketing scales for fashion research involvement opinion seeking and knowledgersquorsquo
The Journal of Fashion Marketing and Management Vol 4 No 2 pp 110-20
Goldsmith RE (2000) ` How innovativenes s differentiate s online buyersrsquorsquo Quarterly Journal
of Electronic Commerce Vol 1 No 4 pp 323-33
Snapshot picture
Expand the scope of thefindings
JOURNAL OF PRODUCT amp BRAND MANAGEMENT VOL 11 NO 2 2002 99
Goldsmith RE and Bridges E (2000) ` E-tailing vs retailing using attitudes to predict
online buying behavior rsquorsquo Quarterly Journal of Electronic Commerce Vol 1 No 3
pp 245-53
Goldsmith RE and Hofacker CF (1991) ` Measuring consumer innovativeness rsquorsquo Journal of
the Academy of Marketing Science Vol 19 No 3 pp 209-21
Goldsmith RE and McGregor S (1999) ` Electronic commerce an emerging issue in
consumer educationrsquorsquo Proceedings of XIX Internationa l Consumer Studies and Home
Economics Research Conference Belfast
Goldsmith RE and McGregor S (2000) ` E-commerce consumer protection issues and
implications for research and educationrsquorsquo Journal of Consumer Studies amp Home
Economics Vol 24 No 2 pp 124-7
Hair JF Anderson RE Tatham RL and Black WC (1998) Multivariate Data Analysis
5th ed Prentice-Hall Upper Saddle River NJ
Hallberg G (1995) All Consumers Are not Created Equal John Wiley New York NJ
Harvard Management Update (2000) ` Lessons from the online war for customersrsquorsquo
Harvard Management Update January pp 3-4
Hoffman DL and Novak TP (1996) ` Marketing in hypermedia computer-mediated
environments conceptua l foundationsrsquorsquo Journal of Marketing Vol 60 No 3 pp 153-61
Hogg MK Bruce M and Hill AJ (1998) ` Fashion brand preference s among young
consumersrsquorsquo Internationa l Journal of Retail amp Distribution Management Vol 26 No 8
pp 293-300
Huck SW and Cormier WH (1996) Reading Statistics and Research 2nd ed
HarperCollins College Publishers New York NY
Karson E (2000) ` Two dimensions of computer and Internet use a reliable and validated
scalersquorsquo Quarterly Journal of Electronic Commerce Vol 1 No 1 pp 49-60
Katz J and Aspden P (1997) ` Motivations for and barriers to Internet usage results of a
national public opinion surveyrsquorsquo Internet Research Vol 7 No 3 pp 170-88
Kuntz J (2000) ` Age and income play key roles in online salesrsquorsquo Daily News Record
27 March p 19
Limayem M Khalifa M and Frini A (2000) ` What makes consumers buy from the
Internet A longitudinal study of online shoppingrsquorsquo IEEE Transactions on Systems Man
and Cybernetics Part A Systems and Humans Vol 30 No 4 pp 421-32
Murphy R (1999) ` Download Internet news IIrsquorsquo The Journal of Fashion Marketing and
Management Vol 3 No 4 pp 376-7
Nelson J (2000) ` Internet at a glancersquorsquo Business 20 12 September p 279
OrsquoGuinn TC and Faber RJ (1989) ` Compulsive buying a phenomenologica l explorationrsquorsquo
Journal of Consumer Research Vol 16 No 2 pp 147-57
Robinson E (2000) ` Click and coverrsquorsquo Business 20 12 September pp 168-80
Seckler V (2000) ` Survey says Web apparel buys doubledrsquorsquo Womenrsquos Wear Daily 12 July
p 2
Silverman D (2000) ` More women wardrobe online than everrsquorsquo Womenrsquos Wear Daily
31 July p 20
Solomon MR (1999) Consumer Behavior Buying Having and Being 4th ed
Prentice-Hall Upper Saddle River NJ
UCLA (2000) ` The UCLA Internet report surveying the digital futurersquorsquo available at
wwwccpuclaedu
Underhill P (1999) Why We Buy The Science of Shopping Simon amp Schuster
New York NY
Vickery L and Agins T (2001) ` Retailers find Web apparel unprofitable rsquorsquo Wall Street
Journal 6 June p B6
Wilson J (1999) ` Keynote addressrsquorsquo The Journal of Fashion Marketing and Management
Vol 3 No 4 pp 370-6
amp
100 JOURNAL OF PRODUCT amp BRAND MANAGEMENT VOL 11 NO 2 2002
Executive summary and implications for managers andexecutives
Retailing online plusmn know your customer and learn from mail ordermarketingE-commerce and especially online retailing have received much attention agreat deal of thought and significant investment Despite this we still lackany clear understanding of the business models that can deliver successonline For every apparent e-retailing success we get a massive plusmn andusually very expensive plusmn failure We can say plusmn with some safety plusmn that theprospects for another Internet trading investment boom have gone
For marketers this situation is a disappointment We are after all theexperts on distribution and sales channels The failure to make e-retailingwork sits in our court and we continue to chew away at the e-commerce bonein the hope that it will eventually come good At the same time we haveraised questions about the capacity of the technology to deliver what wewant Doubts persist about the security of money transfers online Weak linksbetween real world distribution plusmn getting the product to the customer plusmn andthe cosy virtual world get in the way of seamless service And while gettingthe online equivalent of footfall is easy converting these visitors tocustomers is a massive challenge
Know your customer plusmn the marketerrsquos mantraGoldsmith and Goldsmith observe that while a great deal is said aboutonline processes technology and promotion little is known about the actualonline customer We know too little about the differences between theenthusiastic innovators who buy goods online and the rest who are happy tolook but do not buy
The difference between ` innovatorsrsquorsquo and ` early adoptersrsquorsquo is wellresearched and in general terms understood by marketers E-retailing hasnot taken off because the chasm between these two groups remainsunbridged As a result the apparent mass market for e-commerce remains afuture dream Two-thirds of Americans might have access to the Internet butthey are not using it to buy things plusmn at least not in sufficient numbers
Goldsmith and Goldsmith set out to compare clothes buyers who havebought online with those who have not made this sort of purchaseUnderlying the study is the assumption (supported by research and largelycommon sense) that ` consumers who have previous experience in onlinebuying will be more likely to buy apparel online than those who lack suchexperiencersquorsquo We should also note like Goldsmith and Goldsmith that thepeople who matter to e-retailers are those very similar to existing users whoat present are non-users
Are you frightened of the WebGoldsmith and Goldsmith find that there are substantial differences betweene-buyers and the rest of humanity (I always knew that Web enthusiasts werestrange) Some of these differences are pretty prosaic plusmn online buyers havefewer security worries appreciate the ` quicknessrsquorsquo and flexibility of onlinebuying and see the Web as making buying easier However the other (morepsychological) factors suggest that these preferences are symptomatic of thetype rather than definitional The remainder of Goldsmith and Goldsmithrsquosfindings throw up words like ` confidentrsquorsquo ` innovativersquorsquo ` knowledgeablersquorsquoand ` funrsquorsquo Our e-buyers take the view that ` the special circumstancesof e-commerce make this a unique consumption activityrsquorsquo These people aredifferent and we need to know why and at the same time to understand theresistance of others to e-commerce
Part of the resistance appears to lie in fear (characterised as being a lack ofconfidence) People who do not buy online do not have a great deal of trust in
JOURNAL OF PRODUCT amp BRAND MANAGEMENT VOL 11 NO 2 2002 101
This summary has beenprovided to allow managersand executives a rapidappreciation of the contentof this article Those with aparticular interest in thetopic covered may then readthe article in toto to takeadvantage of the morecomprehensive descriptionof the research undertakenand its results to get the fullbenefit of the materialpresent
the medium This seems to hold true even when they use the Internet for avariety of other activities (information gathering communications games etc)Until these issues of fear (or trust or confidence) are dealt with marketers willstruggle to take the idea of e-commerce into the mainstream of retailing
Removing the fearTwo elements are involved in removing consumer distrust of e-commerceThe first is more confidence with the technology involved in buying onlineBear in mind that most of us who use computers take advantage of a tiny partof the capacity of even basic software Even with comprehensible manualson-screen and online help and ` idiot guidesrsquorsquo we still stick to basicprocessing
Ease-of-use is fundamental to successful e-retailing and so far we havefailed to achieve sufficiently easy systems to remove the consumerrsquos worryabout getting it wrong But this is just one problem and its solution lies asmuch in the relationship between the ordinary consumer and Internettechnology as in specific marketing actions
The second element is purely promotional and is about securing trial andreducing the distrust E-commerce becomes accessible when these barriersare removed and there are many techniques available that marketers canuse
Mail order and direct marketers have always faced resistance to theirchannel Indeed mail order people appreciate that there remains a largechunk of the population that will never buy mail order whatever theincentive Nevertheless these marketers have developed (and tested) avariety of simple techniques to secure trial and build confidence
product and service guarantees
payment on delivery rather than payment with the order
featuring low-risk entry products
no-quibble return policies
product endorsement plusmn by real customers
testimonials and
prize draws free gifts and other order incentives
E-commerce represents a new channel and for some businesses a differentmeans of delivering product But for most businesses and especiallyretailers the Internet does not change the nature of the product itself (a pairof shorts remains a pair of shorts) Rather than reinventing the wheel e-retailers should learn from direct marketers
E-commerce needs more confidence to sell itself successfully but in the finalanalysis the e-retailer does little that is different from the mail ordercompany And the direct marketer knows that profits come from repeatbusiness rather than from the first sale Too many e-commerce operationshave floundered because they ignored the experience of others and tried torun a business without good databases or the strategies to sustain incomefrom existing buyers
Do you want your e-retailing business to succeed Hire an experience directmarketer and you will stand a better than average chance of successPretending that the e-marketers have nothing to learn from old grizzled (andboring) mail order people is a mistake that is probably costing you money
(A preAcirccis of the article ` Buying apparel over the Internetrsquorsquo Supplied byMarketing Consultants for Emerald)
102 JOURNAL OF PRODUCT amp BRAND MANAGEMENT VOL 11 NO 2 2002
clothing among the top six categories of holiday gifts in the USA for the
2000 Christmas season (eMarketer 2000 p 30) Thus apparel is an
important consumer purchase category with a significant online component
E-commerce is expensive however and many companies have found profits
hard to come by (Harvard Management Update 2000) Selling apparel
online presents unique challenges to cybermarketers Little is known of
consumer buyer behavior online and e-tailers need to attract those
consumers most likely to buy in order to cover the costs of e-commerce and
make a profit to justify this new form of distribution The first buyers of a
new product or service however are likely to be systematically different
from later buyers (Eastlick and Lotz 1999 Goldsmith 2000 Limayem et
al 2000) Hence the purpose of the present study was to compare
consumers who had purchased apparel online with consumers who had not
purchased apparel online with regard to demographics and attitudes toward
online purchasing Several hypotheses about buying apparel online were
derived from consumer research and tested using data from a survey of
student consumers Testing the hypotheses not only enhances our knowledge
of consumer behavior by extending the scope of theory into the new
shopping environment this information may help online apparel marketers
improve their strategies designed to entice customers to buy online
Hypotheses
Consumers differ in the extent of online buying in which they engage
According to the standard discussions of buying frequency relatively few
buyers in a product category account for the majority of purchases (Hallberg
1995) Since online buying is a new consumer activity we expect that
consumers who have previous experience in online buying will be more
likely to buy apparel online than those who lack such experience This is
because as consumers gain experience with online buying perhaps with
small purchases at first they will be likely to develop confidence and skills
that facilitate more ambitious buying (Seckler 2000) Thus H1 is that
consumers who have bought apparel online will have more experience
buying online in general
Consumers who have bought apparel online may likely be those who buy
more frequently than other consumers In other words consumers who buy
apparel frequently are likely involved with clothing as a product category
they not only shop frequently they probably spend more than less involved
less frequent shoppers Thus H2 is that consumers who purchase apparel
online shop for apparel by any means more frequently than those who have
not bought apparel online
Several studies of consumer online behavior have shown that attitudes toward
the Internet and toward online buying are systematically related to online
buying behavior (Eastlick and Lotz 1999 Goldsmith and Bridges 2000
Karson 2000 Katz and Aspden 1997) Goldsmith (2000) presents Likert
scales to measure five specific attitudes toward e-commerce describing
individual perceptions of its enjoyment safety speed how economical it is
and how much confidence consumers have in their ability to shop and buy
online These attitudes were all related to online buying Thus H3 through H7
are that compared with consumers who have not bought apparel online those
who have bought online feel that the Internet is more fun safer quicker
cheaper and they have more confidence in their ability to buy
Similarly how consumers feel about shopping in general should influence
whether they shop online and specifically purchase apparel online (see
Unique challenges
Previous experience
Online buying behaviour
90 JOURNAL OF PRODUCT amp BRAND MANAGEMENT VOL 11 NO 2 2002
Solomon 1999 pp 311-13) Thus H8 is that a positive disposition toward
shopping should be associated with buying apparel online Finally
consumers who are more innovative and knowledgeable with regard to the
Internet and its uses are more likely to buy online than less innovative and
knowledgeable consumers (Citrin et al 2000 Limayem et al 2000) H9
and H10 are that online apparel buyers will describe themselves as more
innovative and knowledgeable regarding the Internet than non-buyers
Method
Survey participants
The data came from a survey of 566 students at a large southern university in
the USA in the spring of 2000 The students were in either marketing or
human sciences classes Both undergraduates and MBAs participated
Although not representative of all consumers these young buyers are
important because they are heavy buyers of clothing influence the clothing
spending of many other consumers and represent the future of e-commerce
(Hogg et al 1998 Silverman 2000) There were 263 (465 per cent) men
and 303 (535 per cent) women in the sample Their ages ranged from 18 to
50 with a mean of 226 years (SD = 49) The modal age was 20 years Most
of the participants were juniors (276 488 per cent) and seniors (195 345
per cent) with the rest being 17 (3 per cent) sophomores 75 (133 per cent)
graduate students and 3 (05 per cent) other There were 419 (74 per cent)
whites 65 (115 per cent) African-Americans 42 (74 per cent) Hispanics
and 40 (71 per cent) others This distribution is quite similar to the ethnic
distribution on this campus There was no statistically significant (p lt 005)
difference in mean age between the men and women nor were the mean ages
of the four ethnic groups significantly different A cross-tabulation of sex by
race showed that the proportions of men and women in each ethnic category
were nearly identical with the exception that the sample contained
proportionally more African-American women and proportionally fewer
white women
Questionnaire
An initial version of the questionnaire was pilot-tested with 39 students in a
marketing research class for readability ease of use and clarity After
correcting obvious errors and making their suggested changes in wording
and organization the revised questionnaire was fielded by requesting student
volunteers to complete it
The questionnaire contained demographic questions asking for the
participantsrsquo sex age race and class standing Other questions asked
whether the respondents had access to the Internet how many hours they
used it per week and whether they had ever purchased any apparel online It
also contained rating scales to measure their online purchasing behavior
likelihood of future online purchases and apparel purchase Table I shows
these questions and the responses For the chief variable of interest to this
study whether a respondent had ever purchased apparel online (termed
EVER) 99 or 175 per cent of the respondents affirmed that they had so
purchased and 467 (825 per cent) said that they had not This is similar to
one report that 16 per cent of Internet users purchased apparel in cyberspace
during the previous month (Seckler 2000)
The next section of the questionnaire contained 25 Likert-type statements
reflecting attitudes toward shopping over the Internet and enjoyment of
shopping in general A portion of these items appears in Table II These
Internet shopping items were adapted from a set of online buying attitude
Ethnic distribution
Questions and responses
JOURNAL OF PRODUCT amp BRAND MANAGEMENT VOL 11 NO 2 2002 91
items developed by Goldsmith (2000) Three of the shopping enjoyment
items were adapted from OrsquoGuinn and Faber (1989) and one original
shopping item was added for this study
Finally came a section containing the Domain-Specific Innovativeness Scale
or DSI (Goldsmith and Hofacker 1991) This scale was included to measure
Internet innovativeness A factor analysis of the six items revealed a two-
factor solution with the three positive items forming one factor and the three
negative items a second factor We decided to use only the three negative
items as a summed scale because this subscale (termed DSI) had the higher
internal consistency (coefficient alpha = 079) The items appear in Table III
along with a five-item subjective knowledge scale (Flynn et al 2000) used
to measure knowledge of the Internet Factor analysis showed that these
Variable Questionnaire item Response N
ACCESS Do you have access to the
Internet
Yes
No
562
4
993
07
EVER Have you ever purchased any
clothing online
Yes
No
99
467
175
825
OFTEN How often would you say that
you purchase online
Very often
Often
Sometimes
Rarely
Never
4
18
119
201
224
07
32
210
355
396
BUY Asked another way how often
do you purchase online
More than once a week
About once a week
Only about once every two
weeks
Less than once every two
weeks but more than once
a month
Less than once a month
I never do
3
6
12
30
283
232
05
11
21
53
500
410
TIMES How many times have you
bought something online since
January 1 2000
plusmn plusmn times
MEANS How often do you purchase
clothing by any means
Very often
Often
Sometimes
Rarely
Never
Missing
83
179
226
55
21
2
147
316
399
97
37
04
HOURS On average about how many
hours a week do you spend
using the Internet
None
Less than one
One to five
Five to ten
Ten to 20
More than 20
Missing
5
68
244
164
63
21
1
09
120
431
290
111
37
02
LIKELY Regardless of how much you
buy online now how likely are
you to buy online in the
coming year
Definitely will buy
Probably will buy
Might buy
Probably will not buy
Definitely will not buy
Missing
82
107
208
141
23
5
145
189
367
249
41
09
SPEND How much do you spend on
clothing purchases in an
average month
Table I Internet and buying questions
Internet innovativeness
92 JOURNAL OF PRODUCT amp BRAND MANAGEMENT VOL 11 NO 2 2002
items formed a unidimensional scale (termed KNOW) with acceptably high
internal consistency (coefficient alpha = 090)
Results
The first preliminary analysis reduced the three online purchasing questions
(OFTEN BUY and TIMES from Table I) into a composite measure of the
self-reported amount of online buying of each respondent This was done
using a principal components analysis of the three items (Hair et al 1998
Ch 3) and computing factor scores using the SPSS regression method The
analysis extracted a single component with an eigenvalue of 237 that
explained 79 per cent of the variance in the correlation matrix of the three
variables The resulting variable was labeled PURCH Summary descriptive
statistics appear in Table IV
Attitude itema Fun Shop Safe Conf Cheap Quick
Buying over the Internet is more fun than
buying in a store 079
I enjoy buying over the Internet 056
I find shopping on the Internet less pleasant
than shopping in storesb 049
I sometimes shop for goods but then buy
them on the Internet 041
I get a real ` highrsquorsquo from shopping 086
Shopping is fun 083
I shop because buying things makes me
happy 080
I do not mind spending a lot of time
shoppingb 069
Buying over the Internet is no riskier than
buying in a store 084
It is risky to buy over the Internetb 073
Buying over the Internet is safer than buying
in a store plusmn033 048
I lack the confidence to buy correctly on the
Internetb 064
I am confident in my ability to buy
successfully over the Internet 055
There are so many dotcom companies out
there itrsquos confusingb 049
I cannot get the buying information I want
over the Internetb 040
I cannot save much money buying over the
Internetb 089
Buying over the Internet is cheaper than
buying in a store 067
Buying over the Internet is quicker than
buying in a store 064
Buying over the Internet is more efficient
than buying in a store 039
It takes a lot of time and trouble to buy on
the Internetb plusmn032 037
Eigenvalue 55 28 15 14 11 10
Percent of variance 274 139 76 68 54 51
Kaiser-Meyer-Olkin measure of sampling
adequacy = 0840
Notes Only loadings gt 030 are shown a using a five-point agree-disagree responseformat b reverse-coded items
Table II Factor analysis of attitude items
Composite measure
JOURNAL OF PRODUCT amp BRAND MANAGEMENT VOL 11 NO 2 2002 93
The second preliminary analysis examined the structure of the 25 attitude
items by submitting them to a common factor analysis followed by an
oblique rotation on the assumption that the attitude dimensions would be
correlated with one another (Hair et al 1998 Ch 3) The analysis was
conducted four times each time identifying items that did not load on a
factor with other items or which had small loadings (lt 003) or sizeable
(gt 030) cross-loadings on more than one factor Items were retained for
factors if they had sizeable loadings (gt 030) on factors made of items with
similar content These analyses reduced the initial pool of attitude items to
20 items that combined into six easily interpretable subscales that were
similar to those reported by Goldsmith (2000) The final analysis results
appear in Table II where the six factors represent the attitudes that shopping
on the Internet is fun safe cheap and quick and that the respondent had
confidence in hisher ability to shop online as well as the general
` enjoyment in shoppingrsquorsquo scale The scales are labeled FUN SAFE
CHEAP QUICK CONFIDENCE and SHOP The individual items were
summed to form short scales (see Table IV)
Next the Internet innovativeness and knowledge items were factor-analyzed
via common factor analysis which revealed that the items loaded on two
distinct factors indicating discriminant validity for these items (see Table
III) The individual items were summed to form two scales DSI and KNOW
Thus the focal variables in the study were amount of online buying
(PURCH) how often clothing was purchased by any means (MEANS) the
attitudes toward online buying (FUN SAFE CHEAP QUICK and
CONFIDENCE) attitude toward shopping (SHOP) Internet innovativeness
(DSI) and knowledge of the Internet (KNOW)
Cross-tabulation was used to assess the relationship between EVER (those
who had purchased apparel online versus those who had not) and sex and
race These analyses showed no statistically significant relationships
between these variables A t-test showed no statistically significant
difference in the mean age of those who had purchased apparel online versus
those who had not The correlations in Table IV provide internal evidence for
the validity of the measures The significant correlations of the DSI with
Scale itema Factor 1 Factor 2
Internet knowledge (KNOW)
When it comes to the Internet I really do not know a lotb 088
I know pretty much about the Internet 083
Compared with most other people I know less about the Internetb 082
I do not feel very knowledgeable about the Internetb 081
Among my circle of friends I am one of the ` expertsrsquorsquo on the
Internet 065
Internet innovativeness (DSI)
In general I am among the last in my circle of friends to purchase
something over the Internetb 081
Compared with my friends I do little shopping over the Internetb 079
In general I am the last in my circle of friends to know the names
of the latest places to shop on the Internetb 062
Eigenvalue 415 155
Percent of variance 518 194
Kaiser-Meyer-Olkin measure of sampling adequacy = 0865
Notes Only loadings gt 030 are shown a using a five-point agree-disagree responseformat b reverse-coded items
Table III Factor analysis of Internet knowledge and innovativeness items
Common factor analysis
Focal variables
94 JOURNAL OF PRODUCT amp BRAND MANAGEMENT VOL 11 NO 2 2002
Var
iable
sR
ange
Mea
nS
D1
23
45
67
89
10
11
12
13
14
15
16
1
Age
18-5
0226
49
plusmn
2
Sex
0-1
aplusmn
plusmn00
6plusmn
3
Ever
0-1
bplusmn
plusmn00
2plusmn00
5plusmn
4
Purc
hplusmn08
8-
86
80
10
00
801
804
2plusmn
5
Mea
ns
1-5
34
409
8plusmn01
1plusmn03
100
100
2plusmn
6
Fun
4-2
0105
27
00
801
603
505
600
2(0
74)c
7
Saf
e3-1
572
22
plusmn00
301
001
503
700
604
4(0
76)
8
Chea
p2-1
061
16
00
802
400
203
8plusmn00
804
402
9(0
75)
9
Quic
k3-1
593
27
01
000
901
702
9plusmn00
404
702
904
0(0
58)
10
Conf
4-2
0136
30
00
600
802
304
300
004
603
604
303
9(0
70)
11
Shop
4-2
0132
39
plusmn02
6plusmn04
500
5plusmn01
104
0plusmn01
6plusmn00
4plusmn02
1plusmn01
3plusmn01
6(0
86)
12
DS
I3-1
594
27
plusmn00
400
402
804
801
504
202
902
501
904
700
4(0
79)
13
Know
5-2
5184
40
plusmn00
000
801
102
800
602
601
201
601
704
9plusmn00
504
0(0
90)
14
Spen
d0-5
00
893
748
plusmn00
9plusmn02
200
300
604
3plusmn00
100
3plusmn00
8plusmn00
1plusmn00
103
001
300
1plusmn
15
Hours
1-6
35
10
01
101
101
803
600
403
101
602
001
603
4plusmn00
802
804
700
4plusmn
16
Lik
ely
1-5
32
11
00
801
203
306
700
405
904
003
503
704
6plusmn00
704
702
800
503
4plusmn
Note
sC
orr
elat
ions
of
00
9an
dla
rger
are
stat
isti
call
ysi
gnif
ican
tat
plt
00
5(t
wo-t
aile
d)
a1
=m
ale
and
0=
fem
ale
b1
=yes
and
0=
no
cco
effi
cien
tal
pha
inpar
enth
eses
Table
IV
Des
crip
tive
stati
stic
sand
corr
elati
ons
JOURNAL OF PRODUCT amp BRAND MANAGEMENT VOL 11 NO 2 2002 95
FUN SAFE CHEAP QUICK and CONFIDENCE are similar to those
reported by Goldsmith (2000) Moreover the correlation of the DSI with the
knowledge measure (r = 040) is comparable with that reported by Flynn et
al (2000)
An analysis was performed to assess the influence of age sex and race on the
dependent variables A MANCOVA with sex and race as the two
independent variables and age as a covariate was run with PURCH through
KNOW as the ten dependent variables The correlations in Table IV suggest
that age was only significantly correlated with shopping enjoyment and this
was confirmed by the results of the MANCOVA so age was no longer
incorporated in the analyses The results also showed no statistically
significant multivariate interaction between sex and race (F(33 1500) = 114
p = 0266) There was a statistically significant multivariate effect of race
(F(33 1500) = 162 p = 0014) but the only univariate differences were for
SAFE (p = 0033) where African-Americans rated the Internet as less safe
than whites and CHEAP (p = 0032) where the ` othersrsquorsquo rated the Internet as
cheaper than both whites and African-Americans These differences were
few and small in size and so race was no longer included in the analyses
The multivariate effect of sex was significant (F(11 498) = 48 p lt 0001)
Univariate tests showed that women reported purchasing apparel by any
means more often than men they spent more on apparel than men and they
enjoyed shopping more than men while the men reported purchasing more
online than the women and felt that the Internet was cheaper than the
women These differences suggest that sex should be included in the final
analysis of the differences between those who have purchased apparel online
and those who have not
For this analysis a 2 pound 2 (SEX pound EVER) MANOVA was run with the ten
dependent variables as before (see Table V) The interaction term was
Mean scoresa Observed
Dependent variables Men Women Fb p eta2 power
Univariate main effects for SEX
PURCH 0678 0126 308 lt 0000 0052 10
MEANS 306 375 378 lt 0000 0072 10
FUN 119 108 145 lt 0000 0025 0967
SAFE 77 73 29 0089 0005 0397
CHEAP 68 57 418 lt 0000 0070 10
QUICK 99 94 46 0032 0008 0576
CONFIDENT 145 139 35 0060 0006 0468
SHOP 115 148 687 lt 0000 0110 10
DSI 101 100 03 0601 0000 0082
KNOW 192 184 32 0074 0006 0431
Univariate main effects for EVER
H1 PURCH plusmn0184 0988 1391 lt 0000 0200 10
H2 MEANS 34 34 0075 0784 0000 0059
H3 FUN 101 127 879 lt 0000 0136 10
H4 SAFE 70 79 121 0001 0021 0934
H5 CHEAP 61 63 14 0245 0002 0213
H6 QUICK 92 102 197 lt 0000 0034 0993
H7 CONFIDENT 133 151 320 lt 0000 0054 10
H8 SHOP 130 133 0646 0422 0001 0126
H9 DSI 91 110 448 lt 0000 0074 10
H10 KNOW 182 194 78 0005 0014 0798
Notes a Estimated marginal means b df = 1558
Table V Comparisons of mean scores
Influence of age sex andrace
96 JOURNAL OF PRODUCT amp BRAND MANAGEMENT VOL 11 NO 2 2002
statistically significant (F(10 549) = 24 p = 001) Follow-up univariate
analyses showed that the interactions however were significant for only
two of the dependent variables For PURCH the amount of online buying
men reported buying more than women but men who had bought apparel
online reported buying disproportionately more online than women who
had bought apparel online The opposite effect was observed for MEANS
buying apparel by any means Women reported buying apparel by any
means more than men but men who had bought apparel online reported
buying disproportionately less apparel by any means than the women
online buyers
The multivariate main effect for SEX was significant (F(10 549) = 143
p lt 0001) In addition to significant main effect differences for PURCH and
MEANS women reported that they enjoyed shopping (SHOP) more than
men and men reported that they thought online buying was more fun
cheaper and quicker than the women These findings are similar to those
reported in other studies of online buying
The multivariate main effect for EVER whether a respondent had ever
bought apparel online was statistically significant (F(10 549) = 204
p lt 0001) The univariate analyses showed that compared with those who
had not bought apparel online those who had bought apparel online had
more experience purchasing online in general (PURCH) and thought that
buying over the Internet was more fun safer quicker and they were more
confident in their ability to buy online The online apparel buyers also were
more innovative and knowledgeable about the Internet than non-buyers
Thus H1 H3 H4 H6 H7 H9 and H10 were confirmed There were no
statistically significant differences in the self-reported apparel purchase
(MEANS) perceptions that online buying was cheaper (CHEAP) or in
shopping enjoyment (SHOP) Because Boxrsquos test of the equality of the
covariance matrices was significant (indicating that the covariance matrices
were not identical across the groups of respondents) and because Levenersquos
test of equality of error variances showed that the error variances of four of
the dependent variables were not equal thus violating the assumptions of
MANOVA (Huck and Cormier 1996 pp 313-15 374-7) a Mann-Whitney
non-parametric analysis was conducted testing whether the observations
from the two groups of online apparel buyers were equivalent in location
These analyses were consistent with the parametric tests
As a final analysis a 2 pound 2 (SEX pound EVER with age as a covariate)
MANCOVA was conducted comparing the buyers and non-buyers on three
additional variables These were
(1) the number of hours the respondent was online in an average week
(HOURS)
(2) the amount of reported spending on apparel (SPEND) and
(2) how likely the respondent was to buy online in the coming year
(LIKELY)
The results showed that men averaged more hours online per week than
women women spent more on apparel than men and the men were more
likely to shop online in the future than were the women Finally online
apparel buyers reported spending more time online and were more likely to
buy online in the future than non-buyers
Online apparel buyers
Additional variables
JOURNAL OF PRODUCT amp BRAND MANAGEMENT VOL 11 NO 2 2002 97
Discussion
The present study compared selected characteristics of consumers who had
purchased apparel online with those who had not The results showed that
online apparel buyers purchased online more often felt that online buying
was more fun safer and quicker than non-buyers Online apparel buyers
were more confident in their ability to buy online and were more innovative
and knowledgeable about the Internet than non-buyers Online apparel
buyers did not differ from non-buyers in their belief in how cheap buying
online is in their overall enjoyment of shopping or in how often they bought
apparel by any means Respondent demographics were also unrelated to
buying apparel online Online apparel buyers further differed from non-
buyers in that they spent more time online than non-buyers and were more
likely to buy online in the future than non-buyers These results reveal a
systematic pattern of psychological and behavioral factors that seem to
facilitate online apparel purchase
These findings confirm theoretical accounts of consumer behavior and
extend their generality into the new realm of cyber-commerce The findings
are consistent with other studies that show that favorable attitudes are related
to online buying From the methodological perspective the attitude measures
appear to be robust across studies and provide valid reliable
operationalizations of these constructs This should encourage researchers to
use them as standardized measures of e-commerce-related attitudes The
findings also confirm the reliability and validity of the innovativeness (DSI)
and knowledge scales consistent with a series of studies that have evidenced
their psychometric soundness (eg Flynn et al 2000 Goldsmith 2000)
The findings suggest that consumers are motivated to buy apparel online by a
combination of factors and that the special circumstances of e-commerce
make this a unique consumption activity Online apparel buyers obviously
must want and need clothing so this basic motivation partially underlies
their behavior They seem however to be motivated differentially by their
attitudes toward the Internet While online apparel buyers were clearly more
positive on the attitudinal and psychological characteristics they were no
more likely than non-buyers to shop for clothes by other means to enjoy
shopping in general or to spend money buying clothes That is they are not
disproportionately motivated by clothing as a product category or by interest
in shopping but by the perceived advantages of online buying and their
positive predisposition toward this mode of commerce
For managers the results suggest that their online buyers may be somewhat
different from their in-store customers and may represent new customers
Consumers who buy disproportionately more apparel likely enjoy shopping
and want the emotional and sensory pleasures of touching seeing and trying
on clothes (see Seckler 2000 Underhill 1999) Note the positive
intercorrelations in Table IV between spending on apparel and shopping
(r = 030) spending and buying by any means (043) and between shopping
and buying (040) None of these variables was correlated with amount of
online buying (PURCH) Online buyers in contrast appear to be motivated
by their positive attitudes toward the Internet Thus to attract apparel buyers
to Web sites e-marketers might focus on emphasizing the added advantages
of fun speed and safety They should first ensure that their sites are fun to
use load rapidly with prompt post-sale delivery of ordered merchandise and
are completely safe to use They might emphasize how different online
buying is and not pretend that it is the same as in-store shopping Joint or
cooperative strategies might display apparel online but suggest that a
Respondent demographics
Unique consumptionactivity
Positive attitudes
98 JOURNAL OF PRODUCT amp BRAND MANAGEMENT VOL 11 NO 2 2002
different experience could be had in the store where unique accessories or
combinations of clothes could be seen Online apparel buyers and non-
buyers did not differ in their perception that buying online is cheaper than
offline Thus Secklerrsquos (2000) argument that offering price discounts may be
a prime way to attract non-buyers is supported To attract new buyers onlineapparel e-tailers may have to change perceptions that online buying is unsafe
(see Robinson 2000) Web sites must be made simple and easy to use
because non-users are not very confident that they can buy online
successfully In-store demonstrations of online shopping might encourage
non-buyers to shop online As online apparel buying spreads beyond the
innovative and knowledgeable consumer to the less sophisticated shopper
apparel marketers should cater to their unique tastes abilities and habits
This is especially true since the results suggest that many online apparel
buyers will buy online again
The study is limited by the nature of the sample measures specificity and
time studied Lack of randomness in the sample limits generalizability of the
point and interval estimates to a larger population but since the main
purpose of the study was to test theoretical hypotheses about online buyingthis is a minor limitation (Calder et al 1981) No conclusions can be drawn
about concepts that might be related to online apparel buying but were not
measured and the results are limited to the measures employed Similarly
the focal topic was clothing in general and not a specific type (new fashion
sports clothes work clothes etc) Finally since e-commerce and online
consumer behavior are constantly changing phenomena the present study is
only a snapshot picture and not a longitudinal view
Advantages of the study lie in the large sample size and validity of the
measures used Future research should examine online apparel using data
from other demographic socio-economic and national groups of consumers
to expand the scope of the findings The online buyer behaviors studied
should be expanded beyond just buying to include browsing comparison
shopping and combining the Internet with in-store consumption as well asconsumption of specific categories of apparel such as new fashions or
unique sizes and needs As noted in the introduction growth is a major
theme of e-commerce Thus replication studies would be a valuable way to
track changes in online apparel buying over time Accumulation of such
studies would expand our knowledge of both apparel consumer behavior and
consumer Internet behavior to the advantage of both consumer theory and
apparel marketing Finally other researchers could make use of our measures
to study buying behavior in other areas as well
References
Calder BJ Phillips LW and Tybout AM (1981) ` Designing research for application rsquorsquo
Journal of Consumer Research Vol 8 September pp 197-207
Citrin AV Sprott DE Silveman SN and Stem DE Jr (2000) ` Adoption of Internet
shopping the role of consumer innovativenessrsquorsquo Industrial Management amp Data Systems
Vol 100 No 7 pp 294-300
Eastlick MA and Lotz S (1999) ` Profiling potential adopters and non-adopter s of an
interactive electronic shopping mediumrsquorsquo Internationa l Journal of Retail amp Distribution
Management Vol 27 No 6 pp 209-23
eMarketer (2000) ` The e-holiday shopping reportrsquorsquo available at wwwemarketercom
Flynn LR Goldsmith RE and Kim W (2000) ` A cross-cultural validation of three new
marketing scales for fashion research involvement opinion seeking and knowledgersquorsquo
The Journal of Fashion Marketing and Management Vol 4 No 2 pp 110-20
Goldsmith RE (2000) ` How innovativenes s differentiate s online buyersrsquorsquo Quarterly Journal
of Electronic Commerce Vol 1 No 4 pp 323-33
Snapshot picture
Expand the scope of thefindings
JOURNAL OF PRODUCT amp BRAND MANAGEMENT VOL 11 NO 2 2002 99
Goldsmith RE and Bridges E (2000) ` E-tailing vs retailing using attitudes to predict
online buying behavior rsquorsquo Quarterly Journal of Electronic Commerce Vol 1 No 3
pp 245-53
Goldsmith RE and Hofacker CF (1991) ` Measuring consumer innovativeness rsquorsquo Journal of
the Academy of Marketing Science Vol 19 No 3 pp 209-21
Goldsmith RE and McGregor S (1999) ` Electronic commerce an emerging issue in
consumer educationrsquorsquo Proceedings of XIX Internationa l Consumer Studies and Home
Economics Research Conference Belfast
Goldsmith RE and McGregor S (2000) ` E-commerce consumer protection issues and
implications for research and educationrsquorsquo Journal of Consumer Studies amp Home
Economics Vol 24 No 2 pp 124-7
Hair JF Anderson RE Tatham RL and Black WC (1998) Multivariate Data Analysis
5th ed Prentice-Hall Upper Saddle River NJ
Hallberg G (1995) All Consumers Are not Created Equal John Wiley New York NJ
Harvard Management Update (2000) ` Lessons from the online war for customersrsquorsquo
Harvard Management Update January pp 3-4
Hoffman DL and Novak TP (1996) ` Marketing in hypermedia computer-mediated
environments conceptua l foundationsrsquorsquo Journal of Marketing Vol 60 No 3 pp 153-61
Hogg MK Bruce M and Hill AJ (1998) ` Fashion brand preference s among young
consumersrsquorsquo Internationa l Journal of Retail amp Distribution Management Vol 26 No 8
pp 293-300
Huck SW and Cormier WH (1996) Reading Statistics and Research 2nd ed
HarperCollins College Publishers New York NY
Karson E (2000) ` Two dimensions of computer and Internet use a reliable and validated
scalersquorsquo Quarterly Journal of Electronic Commerce Vol 1 No 1 pp 49-60
Katz J and Aspden P (1997) ` Motivations for and barriers to Internet usage results of a
national public opinion surveyrsquorsquo Internet Research Vol 7 No 3 pp 170-88
Kuntz J (2000) ` Age and income play key roles in online salesrsquorsquo Daily News Record
27 March p 19
Limayem M Khalifa M and Frini A (2000) ` What makes consumers buy from the
Internet A longitudinal study of online shoppingrsquorsquo IEEE Transactions on Systems Man
and Cybernetics Part A Systems and Humans Vol 30 No 4 pp 421-32
Murphy R (1999) ` Download Internet news IIrsquorsquo The Journal of Fashion Marketing and
Management Vol 3 No 4 pp 376-7
Nelson J (2000) ` Internet at a glancersquorsquo Business 20 12 September p 279
OrsquoGuinn TC and Faber RJ (1989) ` Compulsive buying a phenomenologica l explorationrsquorsquo
Journal of Consumer Research Vol 16 No 2 pp 147-57
Robinson E (2000) ` Click and coverrsquorsquo Business 20 12 September pp 168-80
Seckler V (2000) ` Survey says Web apparel buys doubledrsquorsquo Womenrsquos Wear Daily 12 July
p 2
Silverman D (2000) ` More women wardrobe online than everrsquorsquo Womenrsquos Wear Daily
31 July p 20
Solomon MR (1999) Consumer Behavior Buying Having and Being 4th ed
Prentice-Hall Upper Saddle River NJ
UCLA (2000) ` The UCLA Internet report surveying the digital futurersquorsquo available at
wwwccpuclaedu
Underhill P (1999) Why We Buy The Science of Shopping Simon amp Schuster
New York NY
Vickery L and Agins T (2001) ` Retailers find Web apparel unprofitable rsquorsquo Wall Street
Journal 6 June p B6
Wilson J (1999) ` Keynote addressrsquorsquo The Journal of Fashion Marketing and Management
Vol 3 No 4 pp 370-6
amp
100 JOURNAL OF PRODUCT amp BRAND MANAGEMENT VOL 11 NO 2 2002
Executive summary and implications for managers andexecutives
Retailing online plusmn know your customer and learn from mail ordermarketingE-commerce and especially online retailing have received much attention agreat deal of thought and significant investment Despite this we still lackany clear understanding of the business models that can deliver successonline For every apparent e-retailing success we get a massive plusmn andusually very expensive plusmn failure We can say plusmn with some safety plusmn that theprospects for another Internet trading investment boom have gone
For marketers this situation is a disappointment We are after all theexperts on distribution and sales channels The failure to make e-retailingwork sits in our court and we continue to chew away at the e-commerce bonein the hope that it will eventually come good At the same time we haveraised questions about the capacity of the technology to deliver what wewant Doubts persist about the security of money transfers online Weak linksbetween real world distribution plusmn getting the product to the customer plusmn andthe cosy virtual world get in the way of seamless service And while gettingthe online equivalent of footfall is easy converting these visitors tocustomers is a massive challenge
Know your customer plusmn the marketerrsquos mantraGoldsmith and Goldsmith observe that while a great deal is said aboutonline processes technology and promotion little is known about the actualonline customer We know too little about the differences between theenthusiastic innovators who buy goods online and the rest who are happy tolook but do not buy
The difference between ` innovatorsrsquorsquo and ` early adoptersrsquorsquo is wellresearched and in general terms understood by marketers E-retailing hasnot taken off because the chasm between these two groups remainsunbridged As a result the apparent mass market for e-commerce remains afuture dream Two-thirds of Americans might have access to the Internet butthey are not using it to buy things plusmn at least not in sufficient numbers
Goldsmith and Goldsmith set out to compare clothes buyers who havebought online with those who have not made this sort of purchaseUnderlying the study is the assumption (supported by research and largelycommon sense) that ` consumers who have previous experience in onlinebuying will be more likely to buy apparel online than those who lack suchexperiencersquorsquo We should also note like Goldsmith and Goldsmith that thepeople who matter to e-retailers are those very similar to existing users whoat present are non-users
Are you frightened of the WebGoldsmith and Goldsmith find that there are substantial differences betweene-buyers and the rest of humanity (I always knew that Web enthusiasts werestrange) Some of these differences are pretty prosaic plusmn online buyers havefewer security worries appreciate the ` quicknessrsquorsquo and flexibility of onlinebuying and see the Web as making buying easier However the other (morepsychological) factors suggest that these preferences are symptomatic of thetype rather than definitional The remainder of Goldsmith and Goldsmithrsquosfindings throw up words like ` confidentrsquorsquo ` innovativersquorsquo ` knowledgeablersquorsquoand ` funrsquorsquo Our e-buyers take the view that ` the special circumstancesof e-commerce make this a unique consumption activityrsquorsquo These people aredifferent and we need to know why and at the same time to understand theresistance of others to e-commerce
Part of the resistance appears to lie in fear (characterised as being a lack ofconfidence) People who do not buy online do not have a great deal of trust in
JOURNAL OF PRODUCT amp BRAND MANAGEMENT VOL 11 NO 2 2002 101
This summary has beenprovided to allow managersand executives a rapidappreciation of the contentof this article Those with aparticular interest in thetopic covered may then readthe article in toto to takeadvantage of the morecomprehensive descriptionof the research undertakenand its results to get the fullbenefit of the materialpresent
the medium This seems to hold true even when they use the Internet for avariety of other activities (information gathering communications games etc)Until these issues of fear (or trust or confidence) are dealt with marketers willstruggle to take the idea of e-commerce into the mainstream of retailing
Removing the fearTwo elements are involved in removing consumer distrust of e-commerceThe first is more confidence with the technology involved in buying onlineBear in mind that most of us who use computers take advantage of a tiny partof the capacity of even basic software Even with comprehensible manualson-screen and online help and ` idiot guidesrsquorsquo we still stick to basicprocessing
Ease-of-use is fundamental to successful e-retailing and so far we havefailed to achieve sufficiently easy systems to remove the consumerrsquos worryabout getting it wrong But this is just one problem and its solution lies asmuch in the relationship between the ordinary consumer and Internettechnology as in specific marketing actions
The second element is purely promotional and is about securing trial andreducing the distrust E-commerce becomes accessible when these barriersare removed and there are many techniques available that marketers canuse
Mail order and direct marketers have always faced resistance to theirchannel Indeed mail order people appreciate that there remains a largechunk of the population that will never buy mail order whatever theincentive Nevertheless these marketers have developed (and tested) avariety of simple techniques to secure trial and build confidence
product and service guarantees
payment on delivery rather than payment with the order
featuring low-risk entry products
no-quibble return policies
product endorsement plusmn by real customers
testimonials and
prize draws free gifts and other order incentives
E-commerce represents a new channel and for some businesses a differentmeans of delivering product But for most businesses and especiallyretailers the Internet does not change the nature of the product itself (a pairof shorts remains a pair of shorts) Rather than reinventing the wheel e-retailers should learn from direct marketers
E-commerce needs more confidence to sell itself successfully but in the finalanalysis the e-retailer does little that is different from the mail ordercompany And the direct marketer knows that profits come from repeatbusiness rather than from the first sale Too many e-commerce operationshave floundered because they ignored the experience of others and tried torun a business without good databases or the strategies to sustain incomefrom existing buyers
Do you want your e-retailing business to succeed Hire an experience directmarketer and you will stand a better than average chance of successPretending that the e-marketers have nothing to learn from old grizzled (andboring) mail order people is a mistake that is probably costing you money
(A preAcirccis of the article ` Buying apparel over the Internetrsquorsquo Supplied byMarketing Consultants for Emerald)
102 JOURNAL OF PRODUCT amp BRAND MANAGEMENT VOL 11 NO 2 2002
Solomon 1999 pp 311-13) Thus H8 is that a positive disposition toward
shopping should be associated with buying apparel online Finally
consumers who are more innovative and knowledgeable with regard to the
Internet and its uses are more likely to buy online than less innovative and
knowledgeable consumers (Citrin et al 2000 Limayem et al 2000) H9
and H10 are that online apparel buyers will describe themselves as more
innovative and knowledgeable regarding the Internet than non-buyers
Method
Survey participants
The data came from a survey of 566 students at a large southern university in
the USA in the spring of 2000 The students were in either marketing or
human sciences classes Both undergraduates and MBAs participated
Although not representative of all consumers these young buyers are
important because they are heavy buyers of clothing influence the clothing
spending of many other consumers and represent the future of e-commerce
(Hogg et al 1998 Silverman 2000) There were 263 (465 per cent) men
and 303 (535 per cent) women in the sample Their ages ranged from 18 to
50 with a mean of 226 years (SD = 49) The modal age was 20 years Most
of the participants were juniors (276 488 per cent) and seniors (195 345
per cent) with the rest being 17 (3 per cent) sophomores 75 (133 per cent)
graduate students and 3 (05 per cent) other There were 419 (74 per cent)
whites 65 (115 per cent) African-Americans 42 (74 per cent) Hispanics
and 40 (71 per cent) others This distribution is quite similar to the ethnic
distribution on this campus There was no statistically significant (p lt 005)
difference in mean age between the men and women nor were the mean ages
of the four ethnic groups significantly different A cross-tabulation of sex by
race showed that the proportions of men and women in each ethnic category
were nearly identical with the exception that the sample contained
proportionally more African-American women and proportionally fewer
white women
Questionnaire
An initial version of the questionnaire was pilot-tested with 39 students in a
marketing research class for readability ease of use and clarity After
correcting obvious errors and making their suggested changes in wording
and organization the revised questionnaire was fielded by requesting student
volunteers to complete it
The questionnaire contained demographic questions asking for the
participantsrsquo sex age race and class standing Other questions asked
whether the respondents had access to the Internet how many hours they
used it per week and whether they had ever purchased any apparel online It
also contained rating scales to measure their online purchasing behavior
likelihood of future online purchases and apparel purchase Table I shows
these questions and the responses For the chief variable of interest to this
study whether a respondent had ever purchased apparel online (termed
EVER) 99 or 175 per cent of the respondents affirmed that they had so
purchased and 467 (825 per cent) said that they had not This is similar to
one report that 16 per cent of Internet users purchased apparel in cyberspace
during the previous month (Seckler 2000)
The next section of the questionnaire contained 25 Likert-type statements
reflecting attitudes toward shopping over the Internet and enjoyment of
shopping in general A portion of these items appears in Table II These
Internet shopping items were adapted from a set of online buying attitude
Ethnic distribution
Questions and responses
JOURNAL OF PRODUCT amp BRAND MANAGEMENT VOL 11 NO 2 2002 91
items developed by Goldsmith (2000) Three of the shopping enjoyment
items were adapted from OrsquoGuinn and Faber (1989) and one original
shopping item was added for this study
Finally came a section containing the Domain-Specific Innovativeness Scale
or DSI (Goldsmith and Hofacker 1991) This scale was included to measure
Internet innovativeness A factor analysis of the six items revealed a two-
factor solution with the three positive items forming one factor and the three
negative items a second factor We decided to use only the three negative
items as a summed scale because this subscale (termed DSI) had the higher
internal consistency (coefficient alpha = 079) The items appear in Table III
along with a five-item subjective knowledge scale (Flynn et al 2000) used
to measure knowledge of the Internet Factor analysis showed that these
Variable Questionnaire item Response N
ACCESS Do you have access to the
Internet
Yes
No
562
4
993
07
EVER Have you ever purchased any
clothing online
Yes
No
99
467
175
825
OFTEN How often would you say that
you purchase online
Very often
Often
Sometimes
Rarely
Never
4
18
119
201
224
07
32
210
355
396
BUY Asked another way how often
do you purchase online
More than once a week
About once a week
Only about once every two
weeks
Less than once every two
weeks but more than once
a month
Less than once a month
I never do
3
6
12
30
283
232
05
11
21
53
500
410
TIMES How many times have you
bought something online since
January 1 2000
plusmn plusmn times
MEANS How often do you purchase
clothing by any means
Very often
Often
Sometimes
Rarely
Never
Missing
83
179
226
55
21
2
147
316
399
97
37
04
HOURS On average about how many
hours a week do you spend
using the Internet
None
Less than one
One to five
Five to ten
Ten to 20
More than 20
Missing
5
68
244
164
63
21
1
09
120
431
290
111
37
02
LIKELY Regardless of how much you
buy online now how likely are
you to buy online in the
coming year
Definitely will buy
Probably will buy
Might buy
Probably will not buy
Definitely will not buy
Missing
82
107
208
141
23
5
145
189
367
249
41
09
SPEND How much do you spend on
clothing purchases in an
average month
Table I Internet and buying questions
Internet innovativeness
92 JOURNAL OF PRODUCT amp BRAND MANAGEMENT VOL 11 NO 2 2002
items formed a unidimensional scale (termed KNOW) with acceptably high
internal consistency (coefficient alpha = 090)
Results
The first preliminary analysis reduced the three online purchasing questions
(OFTEN BUY and TIMES from Table I) into a composite measure of the
self-reported amount of online buying of each respondent This was done
using a principal components analysis of the three items (Hair et al 1998
Ch 3) and computing factor scores using the SPSS regression method The
analysis extracted a single component with an eigenvalue of 237 that
explained 79 per cent of the variance in the correlation matrix of the three
variables The resulting variable was labeled PURCH Summary descriptive
statistics appear in Table IV
Attitude itema Fun Shop Safe Conf Cheap Quick
Buying over the Internet is more fun than
buying in a store 079
I enjoy buying over the Internet 056
I find shopping on the Internet less pleasant
than shopping in storesb 049
I sometimes shop for goods but then buy
them on the Internet 041
I get a real ` highrsquorsquo from shopping 086
Shopping is fun 083
I shop because buying things makes me
happy 080
I do not mind spending a lot of time
shoppingb 069
Buying over the Internet is no riskier than
buying in a store 084
It is risky to buy over the Internetb 073
Buying over the Internet is safer than buying
in a store plusmn033 048
I lack the confidence to buy correctly on the
Internetb 064
I am confident in my ability to buy
successfully over the Internet 055
There are so many dotcom companies out
there itrsquos confusingb 049
I cannot get the buying information I want
over the Internetb 040
I cannot save much money buying over the
Internetb 089
Buying over the Internet is cheaper than
buying in a store 067
Buying over the Internet is quicker than
buying in a store 064
Buying over the Internet is more efficient
than buying in a store 039
It takes a lot of time and trouble to buy on
the Internetb plusmn032 037
Eigenvalue 55 28 15 14 11 10
Percent of variance 274 139 76 68 54 51
Kaiser-Meyer-Olkin measure of sampling
adequacy = 0840
Notes Only loadings gt 030 are shown a using a five-point agree-disagree responseformat b reverse-coded items
Table II Factor analysis of attitude items
Composite measure
JOURNAL OF PRODUCT amp BRAND MANAGEMENT VOL 11 NO 2 2002 93
The second preliminary analysis examined the structure of the 25 attitude
items by submitting them to a common factor analysis followed by an
oblique rotation on the assumption that the attitude dimensions would be
correlated with one another (Hair et al 1998 Ch 3) The analysis was
conducted four times each time identifying items that did not load on a
factor with other items or which had small loadings (lt 003) or sizeable
(gt 030) cross-loadings on more than one factor Items were retained for
factors if they had sizeable loadings (gt 030) on factors made of items with
similar content These analyses reduced the initial pool of attitude items to
20 items that combined into six easily interpretable subscales that were
similar to those reported by Goldsmith (2000) The final analysis results
appear in Table II where the six factors represent the attitudes that shopping
on the Internet is fun safe cheap and quick and that the respondent had
confidence in hisher ability to shop online as well as the general
` enjoyment in shoppingrsquorsquo scale The scales are labeled FUN SAFE
CHEAP QUICK CONFIDENCE and SHOP The individual items were
summed to form short scales (see Table IV)
Next the Internet innovativeness and knowledge items were factor-analyzed
via common factor analysis which revealed that the items loaded on two
distinct factors indicating discriminant validity for these items (see Table
III) The individual items were summed to form two scales DSI and KNOW
Thus the focal variables in the study were amount of online buying
(PURCH) how often clothing was purchased by any means (MEANS) the
attitudes toward online buying (FUN SAFE CHEAP QUICK and
CONFIDENCE) attitude toward shopping (SHOP) Internet innovativeness
(DSI) and knowledge of the Internet (KNOW)
Cross-tabulation was used to assess the relationship between EVER (those
who had purchased apparel online versus those who had not) and sex and
race These analyses showed no statistically significant relationships
between these variables A t-test showed no statistically significant
difference in the mean age of those who had purchased apparel online versus
those who had not The correlations in Table IV provide internal evidence for
the validity of the measures The significant correlations of the DSI with
Scale itema Factor 1 Factor 2
Internet knowledge (KNOW)
When it comes to the Internet I really do not know a lotb 088
I know pretty much about the Internet 083
Compared with most other people I know less about the Internetb 082
I do not feel very knowledgeable about the Internetb 081
Among my circle of friends I am one of the ` expertsrsquorsquo on the
Internet 065
Internet innovativeness (DSI)
In general I am among the last in my circle of friends to purchase
something over the Internetb 081
Compared with my friends I do little shopping over the Internetb 079
In general I am the last in my circle of friends to know the names
of the latest places to shop on the Internetb 062
Eigenvalue 415 155
Percent of variance 518 194
Kaiser-Meyer-Olkin measure of sampling adequacy = 0865
Notes Only loadings gt 030 are shown a using a five-point agree-disagree responseformat b reverse-coded items
Table III Factor analysis of Internet knowledge and innovativeness items
Common factor analysis
Focal variables
94 JOURNAL OF PRODUCT amp BRAND MANAGEMENT VOL 11 NO 2 2002
Var
iable
sR
ange
Mea
nS
D1
23
45
67
89
10
11
12
13
14
15
16
1
Age
18-5
0226
49
plusmn
2
Sex
0-1
aplusmn
plusmn00
6plusmn
3
Ever
0-1
bplusmn
plusmn00
2plusmn00
5plusmn
4
Purc
hplusmn08
8-
86
80
10
00
801
804
2plusmn
5
Mea
ns
1-5
34
409
8plusmn01
1plusmn03
100
100
2plusmn
6
Fun
4-2
0105
27
00
801
603
505
600
2(0
74)c
7
Saf
e3-1
572
22
plusmn00
301
001
503
700
604
4(0
76)
8
Chea
p2-1
061
16
00
802
400
203
8plusmn00
804
402
9(0
75)
9
Quic
k3-1
593
27
01
000
901
702
9plusmn00
404
702
904
0(0
58)
10
Conf
4-2
0136
30
00
600
802
304
300
004
603
604
303
9(0
70)
11
Shop
4-2
0132
39
plusmn02
6plusmn04
500
5plusmn01
104
0plusmn01
6plusmn00
4plusmn02
1plusmn01
3plusmn01
6(0
86)
12
DS
I3-1
594
27
plusmn00
400
402
804
801
504
202
902
501
904
700
4(0
79)
13
Know
5-2
5184
40
plusmn00
000
801
102
800
602
601
201
601
704
9plusmn00
504
0(0
90)
14
Spen
d0-5
00
893
748
plusmn00
9plusmn02
200
300
604
3plusmn00
100
3plusmn00
8plusmn00
1plusmn00
103
001
300
1plusmn
15
Hours
1-6
35
10
01
101
101
803
600
403
101
602
001
603
4plusmn00
802
804
700
4plusmn
16
Lik
ely
1-5
32
11
00
801
203
306
700
405
904
003
503
704
6plusmn00
704
702
800
503
4plusmn
Note
sC
orr
elat
ions
of
00
9an
dla
rger
are
stat
isti
call
ysi
gnif
ican
tat
plt
00
5(t
wo-t
aile
d)
a1
=m
ale
and
0=
fem
ale
b1
=yes
and
0=
no
cco
effi
cien
tal
pha
inpar
enth
eses
Table
IV
Des
crip
tive
stati
stic
sand
corr
elati
ons
JOURNAL OF PRODUCT amp BRAND MANAGEMENT VOL 11 NO 2 2002 95
FUN SAFE CHEAP QUICK and CONFIDENCE are similar to those
reported by Goldsmith (2000) Moreover the correlation of the DSI with the
knowledge measure (r = 040) is comparable with that reported by Flynn et
al (2000)
An analysis was performed to assess the influence of age sex and race on the
dependent variables A MANCOVA with sex and race as the two
independent variables and age as a covariate was run with PURCH through
KNOW as the ten dependent variables The correlations in Table IV suggest
that age was only significantly correlated with shopping enjoyment and this
was confirmed by the results of the MANCOVA so age was no longer
incorporated in the analyses The results also showed no statistically
significant multivariate interaction between sex and race (F(33 1500) = 114
p = 0266) There was a statistically significant multivariate effect of race
(F(33 1500) = 162 p = 0014) but the only univariate differences were for
SAFE (p = 0033) where African-Americans rated the Internet as less safe
than whites and CHEAP (p = 0032) where the ` othersrsquorsquo rated the Internet as
cheaper than both whites and African-Americans These differences were
few and small in size and so race was no longer included in the analyses
The multivariate effect of sex was significant (F(11 498) = 48 p lt 0001)
Univariate tests showed that women reported purchasing apparel by any
means more often than men they spent more on apparel than men and they
enjoyed shopping more than men while the men reported purchasing more
online than the women and felt that the Internet was cheaper than the
women These differences suggest that sex should be included in the final
analysis of the differences between those who have purchased apparel online
and those who have not
For this analysis a 2 pound 2 (SEX pound EVER) MANOVA was run with the ten
dependent variables as before (see Table V) The interaction term was
Mean scoresa Observed
Dependent variables Men Women Fb p eta2 power
Univariate main effects for SEX
PURCH 0678 0126 308 lt 0000 0052 10
MEANS 306 375 378 lt 0000 0072 10
FUN 119 108 145 lt 0000 0025 0967
SAFE 77 73 29 0089 0005 0397
CHEAP 68 57 418 lt 0000 0070 10
QUICK 99 94 46 0032 0008 0576
CONFIDENT 145 139 35 0060 0006 0468
SHOP 115 148 687 lt 0000 0110 10
DSI 101 100 03 0601 0000 0082
KNOW 192 184 32 0074 0006 0431
Univariate main effects for EVER
H1 PURCH plusmn0184 0988 1391 lt 0000 0200 10
H2 MEANS 34 34 0075 0784 0000 0059
H3 FUN 101 127 879 lt 0000 0136 10
H4 SAFE 70 79 121 0001 0021 0934
H5 CHEAP 61 63 14 0245 0002 0213
H6 QUICK 92 102 197 lt 0000 0034 0993
H7 CONFIDENT 133 151 320 lt 0000 0054 10
H8 SHOP 130 133 0646 0422 0001 0126
H9 DSI 91 110 448 lt 0000 0074 10
H10 KNOW 182 194 78 0005 0014 0798
Notes a Estimated marginal means b df = 1558
Table V Comparisons of mean scores
Influence of age sex andrace
96 JOURNAL OF PRODUCT amp BRAND MANAGEMENT VOL 11 NO 2 2002
statistically significant (F(10 549) = 24 p = 001) Follow-up univariate
analyses showed that the interactions however were significant for only
two of the dependent variables For PURCH the amount of online buying
men reported buying more than women but men who had bought apparel
online reported buying disproportionately more online than women who
had bought apparel online The opposite effect was observed for MEANS
buying apparel by any means Women reported buying apparel by any
means more than men but men who had bought apparel online reported
buying disproportionately less apparel by any means than the women
online buyers
The multivariate main effect for SEX was significant (F(10 549) = 143
p lt 0001) In addition to significant main effect differences for PURCH and
MEANS women reported that they enjoyed shopping (SHOP) more than
men and men reported that they thought online buying was more fun
cheaper and quicker than the women These findings are similar to those
reported in other studies of online buying
The multivariate main effect for EVER whether a respondent had ever
bought apparel online was statistically significant (F(10 549) = 204
p lt 0001) The univariate analyses showed that compared with those who
had not bought apparel online those who had bought apparel online had
more experience purchasing online in general (PURCH) and thought that
buying over the Internet was more fun safer quicker and they were more
confident in their ability to buy online The online apparel buyers also were
more innovative and knowledgeable about the Internet than non-buyers
Thus H1 H3 H4 H6 H7 H9 and H10 were confirmed There were no
statistically significant differences in the self-reported apparel purchase
(MEANS) perceptions that online buying was cheaper (CHEAP) or in
shopping enjoyment (SHOP) Because Boxrsquos test of the equality of the
covariance matrices was significant (indicating that the covariance matrices
were not identical across the groups of respondents) and because Levenersquos
test of equality of error variances showed that the error variances of four of
the dependent variables were not equal thus violating the assumptions of
MANOVA (Huck and Cormier 1996 pp 313-15 374-7) a Mann-Whitney
non-parametric analysis was conducted testing whether the observations
from the two groups of online apparel buyers were equivalent in location
These analyses were consistent with the parametric tests
As a final analysis a 2 pound 2 (SEX pound EVER with age as a covariate)
MANCOVA was conducted comparing the buyers and non-buyers on three
additional variables These were
(1) the number of hours the respondent was online in an average week
(HOURS)
(2) the amount of reported spending on apparel (SPEND) and
(2) how likely the respondent was to buy online in the coming year
(LIKELY)
The results showed that men averaged more hours online per week than
women women spent more on apparel than men and the men were more
likely to shop online in the future than were the women Finally online
apparel buyers reported spending more time online and were more likely to
buy online in the future than non-buyers
Online apparel buyers
Additional variables
JOURNAL OF PRODUCT amp BRAND MANAGEMENT VOL 11 NO 2 2002 97
Discussion
The present study compared selected characteristics of consumers who had
purchased apparel online with those who had not The results showed that
online apparel buyers purchased online more often felt that online buying
was more fun safer and quicker than non-buyers Online apparel buyers
were more confident in their ability to buy online and were more innovative
and knowledgeable about the Internet than non-buyers Online apparel
buyers did not differ from non-buyers in their belief in how cheap buying
online is in their overall enjoyment of shopping or in how often they bought
apparel by any means Respondent demographics were also unrelated to
buying apparel online Online apparel buyers further differed from non-
buyers in that they spent more time online than non-buyers and were more
likely to buy online in the future than non-buyers These results reveal a
systematic pattern of psychological and behavioral factors that seem to
facilitate online apparel purchase
These findings confirm theoretical accounts of consumer behavior and
extend their generality into the new realm of cyber-commerce The findings
are consistent with other studies that show that favorable attitudes are related
to online buying From the methodological perspective the attitude measures
appear to be robust across studies and provide valid reliable
operationalizations of these constructs This should encourage researchers to
use them as standardized measures of e-commerce-related attitudes The
findings also confirm the reliability and validity of the innovativeness (DSI)
and knowledge scales consistent with a series of studies that have evidenced
their psychometric soundness (eg Flynn et al 2000 Goldsmith 2000)
The findings suggest that consumers are motivated to buy apparel online by a
combination of factors and that the special circumstances of e-commerce
make this a unique consumption activity Online apparel buyers obviously
must want and need clothing so this basic motivation partially underlies
their behavior They seem however to be motivated differentially by their
attitudes toward the Internet While online apparel buyers were clearly more
positive on the attitudinal and psychological characteristics they were no
more likely than non-buyers to shop for clothes by other means to enjoy
shopping in general or to spend money buying clothes That is they are not
disproportionately motivated by clothing as a product category or by interest
in shopping but by the perceived advantages of online buying and their
positive predisposition toward this mode of commerce
For managers the results suggest that their online buyers may be somewhat
different from their in-store customers and may represent new customers
Consumers who buy disproportionately more apparel likely enjoy shopping
and want the emotional and sensory pleasures of touching seeing and trying
on clothes (see Seckler 2000 Underhill 1999) Note the positive
intercorrelations in Table IV between spending on apparel and shopping
(r = 030) spending and buying by any means (043) and between shopping
and buying (040) None of these variables was correlated with amount of
online buying (PURCH) Online buyers in contrast appear to be motivated
by their positive attitudes toward the Internet Thus to attract apparel buyers
to Web sites e-marketers might focus on emphasizing the added advantages
of fun speed and safety They should first ensure that their sites are fun to
use load rapidly with prompt post-sale delivery of ordered merchandise and
are completely safe to use They might emphasize how different online
buying is and not pretend that it is the same as in-store shopping Joint or
cooperative strategies might display apparel online but suggest that a
Respondent demographics
Unique consumptionactivity
Positive attitudes
98 JOURNAL OF PRODUCT amp BRAND MANAGEMENT VOL 11 NO 2 2002
different experience could be had in the store where unique accessories or
combinations of clothes could be seen Online apparel buyers and non-
buyers did not differ in their perception that buying online is cheaper than
offline Thus Secklerrsquos (2000) argument that offering price discounts may be
a prime way to attract non-buyers is supported To attract new buyers onlineapparel e-tailers may have to change perceptions that online buying is unsafe
(see Robinson 2000) Web sites must be made simple and easy to use
because non-users are not very confident that they can buy online
successfully In-store demonstrations of online shopping might encourage
non-buyers to shop online As online apparel buying spreads beyond the
innovative and knowledgeable consumer to the less sophisticated shopper
apparel marketers should cater to their unique tastes abilities and habits
This is especially true since the results suggest that many online apparel
buyers will buy online again
The study is limited by the nature of the sample measures specificity and
time studied Lack of randomness in the sample limits generalizability of the
point and interval estimates to a larger population but since the main
purpose of the study was to test theoretical hypotheses about online buyingthis is a minor limitation (Calder et al 1981) No conclusions can be drawn
about concepts that might be related to online apparel buying but were not
measured and the results are limited to the measures employed Similarly
the focal topic was clothing in general and not a specific type (new fashion
sports clothes work clothes etc) Finally since e-commerce and online
consumer behavior are constantly changing phenomena the present study is
only a snapshot picture and not a longitudinal view
Advantages of the study lie in the large sample size and validity of the
measures used Future research should examine online apparel using data
from other demographic socio-economic and national groups of consumers
to expand the scope of the findings The online buyer behaviors studied
should be expanded beyond just buying to include browsing comparison
shopping and combining the Internet with in-store consumption as well asconsumption of specific categories of apparel such as new fashions or
unique sizes and needs As noted in the introduction growth is a major
theme of e-commerce Thus replication studies would be a valuable way to
track changes in online apparel buying over time Accumulation of such
studies would expand our knowledge of both apparel consumer behavior and
consumer Internet behavior to the advantage of both consumer theory and
apparel marketing Finally other researchers could make use of our measures
to study buying behavior in other areas as well
References
Calder BJ Phillips LW and Tybout AM (1981) ` Designing research for application rsquorsquo
Journal of Consumer Research Vol 8 September pp 197-207
Citrin AV Sprott DE Silveman SN and Stem DE Jr (2000) ` Adoption of Internet
shopping the role of consumer innovativenessrsquorsquo Industrial Management amp Data Systems
Vol 100 No 7 pp 294-300
Eastlick MA and Lotz S (1999) ` Profiling potential adopters and non-adopter s of an
interactive electronic shopping mediumrsquorsquo Internationa l Journal of Retail amp Distribution
Management Vol 27 No 6 pp 209-23
eMarketer (2000) ` The e-holiday shopping reportrsquorsquo available at wwwemarketercom
Flynn LR Goldsmith RE and Kim W (2000) ` A cross-cultural validation of three new
marketing scales for fashion research involvement opinion seeking and knowledgersquorsquo
The Journal of Fashion Marketing and Management Vol 4 No 2 pp 110-20
Goldsmith RE (2000) ` How innovativenes s differentiate s online buyersrsquorsquo Quarterly Journal
of Electronic Commerce Vol 1 No 4 pp 323-33
Snapshot picture
Expand the scope of thefindings
JOURNAL OF PRODUCT amp BRAND MANAGEMENT VOL 11 NO 2 2002 99
Goldsmith RE and Bridges E (2000) ` E-tailing vs retailing using attitudes to predict
online buying behavior rsquorsquo Quarterly Journal of Electronic Commerce Vol 1 No 3
pp 245-53
Goldsmith RE and Hofacker CF (1991) ` Measuring consumer innovativeness rsquorsquo Journal of
the Academy of Marketing Science Vol 19 No 3 pp 209-21
Goldsmith RE and McGregor S (1999) ` Electronic commerce an emerging issue in
consumer educationrsquorsquo Proceedings of XIX Internationa l Consumer Studies and Home
Economics Research Conference Belfast
Goldsmith RE and McGregor S (2000) ` E-commerce consumer protection issues and
implications for research and educationrsquorsquo Journal of Consumer Studies amp Home
Economics Vol 24 No 2 pp 124-7
Hair JF Anderson RE Tatham RL and Black WC (1998) Multivariate Data Analysis
5th ed Prentice-Hall Upper Saddle River NJ
Hallberg G (1995) All Consumers Are not Created Equal John Wiley New York NJ
Harvard Management Update (2000) ` Lessons from the online war for customersrsquorsquo
Harvard Management Update January pp 3-4
Hoffman DL and Novak TP (1996) ` Marketing in hypermedia computer-mediated
environments conceptua l foundationsrsquorsquo Journal of Marketing Vol 60 No 3 pp 153-61
Hogg MK Bruce M and Hill AJ (1998) ` Fashion brand preference s among young
consumersrsquorsquo Internationa l Journal of Retail amp Distribution Management Vol 26 No 8
pp 293-300
Huck SW and Cormier WH (1996) Reading Statistics and Research 2nd ed
HarperCollins College Publishers New York NY
Karson E (2000) ` Two dimensions of computer and Internet use a reliable and validated
scalersquorsquo Quarterly Journal of Electronic Commerce Vol 1 No 1 pp 49-60
Katz J and Aspden P (1997) ` Motivations for and barriers to Internet usage results of a
national public opinion surveyrsquorsquo Internet Research Vol 7 No 3 pp 170-88
Kuntz J (2000) ` Age and income play key roles in online salesrsquorsquo Daily News Record
27 March p 19
Limayem M Khalifa M and Frini A (2000) ` What makes consumers buy from the
Internet A longitudinal study of online shoppingrsquorsquo IEEE Transactions on Systems Man
and Cybernetics Part A Systems and Humans Vol 30 No 4 pp 421-32
Murphy R (1999) ` Download Internet news IIrsquorsquo The Journal of Fashion Marketing and
Management Vol 3 No 4 pp 376-7
Nelson J (2000) ` Internet at a glancersquorsquo Business 20 12 September p 279
OrsquoGuinn TC and Faber RJ (1989) ` Compulsive buying a phenomenologica l explorationrsquorsquo
Journal of Consumer Research Vol 16 No 2 pp 147-57
Robinson E (2000) ` Click and coverrsquorsquo Business 20 12 September pp 168-80
Seckler V (2000) ` Survey says Web apparel buys doubledrsquorsquo Womenrsquos Wear Daily 12 July
p 2
Silverman D (2000) ` More women wardrobe online than everrsquorsquo Womenrsquos Wear Daily
31 July p 20
Solomon MR (1999) Consumer Behavior Buying Having and Being 4th ed
Prentice-Hall Upper Saddle River NJ
UCLA (2000) ` The UCLA Internet report surveying the digital futurersquorsquo available at
wwwccpuclaedu
Underhill P (1999) Why We Buy The Science of Shopping Simon amp Schuster
New York NY
Vickery L and Agins T (2001) ` Retailers find Web apparel unprofitable rsquorsquo Wall Street
Journal 6 June p B6
Wilson J (1999) ` Keynote addressrsquorsquo The Journal of Fashion Marketing and Management
Vol 3 No 4 pp 370-6
amp
100 JOURNAL OF PRODUCT amp BRAND MANAGEMENT VOL 11 NO 2 2002
Executive summary and implications for managers andexecutives
Retailing online plusmn know your customer and learn from mail ordermarketingE-commerce and especially online retailing have received much attention agreat deal of thought and significant investment Despite this we still lackany clear understanding of the business models that can deliver successonline For every apparent e-retailing success we get a massive plusmn andusually very expensive plusmn failure We can say plusmn with some safety plusmn that theprospects for another Internet trading investment boom have gone
For marketers this situation is a disappointment We are after all theexperts on distribution and sales channels The failure to make e-retailingwork sits in our court and we continue to chew away at the e-commerce bonein the hope that it will eventually come good At the same time we haveraised questions about the capacity of the technology to deliver what wewant Doubts persist about the security of money transfers online Weak linksbetween real world distribution plusmn getting the product to the customer plusmn andthe cosy virtual world get in the way of seamless service And while gettingthe online equivalent of footfall is easy converting these visitors tocustomers is a massive challenge
Know your customer plusmn the marketerrsquos mantraGoldsmith and Goldsmith observe that while a great deal is said aboutonline processes technology and promotion little is known about the actualonline customer We know too little about the differences between theenthusiastic innovators who buy goods online and the rest who are happy tolook but do not buy
The difference between ` innovatorsrsquorsquo and ` early adoptersrsquorsquo is wellresearched and in general terms understood by marketers E-retailing hasnot taken off because the chasm between these two groups remainsunbridged As a result the apparent mass market for e-commerce remains afuture dream Two-thirds of Americans might have access to the Internet butthey are not using it to buy things plusmn at least not in sufficient numbers
Goldsmith and Goldsmith set out to compare clothes buyers who havebought online with those who have not made this sort of purchaseUnderlying the study is the assumption (supported by research and largelycommon sense) that ` consumers who have previous experience in onlinebuying will be more likely to buy apparel online than those who lack suchexperiencersquorsquo We should also note like Goldsmith and Goldsmith that thepeople who matter to e-retailers are those very similar to existing users whoat present are non-users
Are you frightened of the WebGoldsmith and Goldsmith find that there are substantial differences betweene-buyers and the rest of humanity (I always knew that Web enthusiasts werestrange) Some of these differences are pretty prosaic plusmn online buyers havefewer security worries appreciate the ` quicknessrsquorsquo and flexibility of onlinebuying and see the Web as making buying easier However the other (morepsychological) factors suggest that these preferences are symptomatic of thetype rather than definitional The remainder of Goldsmith and Goldsmithrsquosfindings throw up words like ` confidentrsquorsquo ` innovativersquorsquo ` knowledgeablersquorsquoand ` funrsquorsquo Our e-buyers take the view that ` the special circumstancesof e-commerce make this a unique consumption activityrsquorsquo These people aredifferent and we need to know why and at the same time to understand theresistance of others to e-commerce
Part of the resistance appears to lie in fear (characterised as being a lack ofconfidence) People who do not buy online do not have a great deal of trust in
JOURNAL OF PRODUCT amp BRAND MANAGEMENT VOL 11 NO 2 2002 101
This summary has beenprovided to allow managersand executives a rapidappreciation of the contentof this article Those with aparticular interest in thetopic covered may then readthe article in toto to takeadvantage of the morecomprehensive descriptionof the research undertakenand its results to get the fullbenefit of the materialpresent
the medium This seems to hold true even when they use the Internet for avariety of other activities (information gathering communications games etc)Until these issues of fear (or trust or confidence) are dealt with marketers willstruggle to take the idea of e-commerce into the mainstream of retailing
Removing the fearTwo elements are involved in removing consumer distrust of e-commerceThe first is more confidence with the technology involved in buying onlineBear in mind that most of us who use computers take advantage of a tiny partof the capacity of even basic software Even with comprehensible manualson-screen and online help and ` idiot guidesrsquorsquo we still stick to basicprocessing
Ease-of-use is fundamental to successful e-retailing and so far we havefailed to achieve sufficiently easy systems to remove the consumerrsquos worryabout getting it wrong But this is just one problem and its solution lies asmuch in the relationship between the ordinary consumer and Internettechnology as in specific marketing actions
The second element is purely promotional and is about securing trial andreducing the distrust E-commerce becomes accessible when these barriersare removed and there are many techniques available that marketers canuse
Mail order and direct marketers have always faced resistance to theirchannel Indeed mail order people appreciate that there remains a largechunk of the population that will never buy mail order whatever theincentive Nevertheless these marketers have developed (and tested) avariety of simple techniques to secure trial and build confidence
product and service guarantees
payment on delivery rather than payment with the order
featuring low-risk entry products
no-quibble return policies
product endorsement plusmn by real customers
testimonials and
prize draws free gifts and other order incentives
E-commerce represents a new channel and for some businesses a differentmeans of delivering product But for most businesses and especiallyretailers the Internet does not change the nature of the product itself (a pairof shorts remains a pair of shorts) Rather than reinventing the wheel e-retailers should learn from direct marketers
E-commerce needs more confidence to sell itself successfully but in the finalanalysis the e-retailer does little that is different from the mail ordercompany And the direct marketer knows that profits come from repeatbusiness rather than from the first sale Too many e-commerce operationshave floundered because they ignored the experience of others and tried torun a business without good databases or the strategies to sustain incomefrom existing buyers
Do you want your e-retailing business to succeed Hire an experience directmarketer and you will stand a better than average chance of successPretending that the e-marketers have nothing to learn from old grizzled (andboring) mail order people is a mistake that is probably costing you money
(A preAcirccis of the article ` Buying apparel over the Internetrsquorsquo Supplied byMarketing Consultants for Emerald)
102 JOURNAL OF PRODUCT amp BRAND MANAGEMENT VOL 11 NO 2 2002
items developed by Goldsmith (2000) Three of the shopping enjoyment
items were adapted from OrsquoGuinn and Faber (1989) and one original
shopping item was added for this study
Finally came a section containing the Domain-Specific Innovativeness Scale
or DSI (Goldsmith and Hofacker 1991) This scale was included to measure
Internet innovativeness A factor analysis of the six items revealed a two-
factor solution with the three positive items forming one factor and the three
negative items a second factor We decided to use only the three negative
items as a summed scale because this subscale (termed DSI) had the higher
internal consistency (coefficient alpha = 079) The items appear in Table III
along with a five-item subjective knowledge scale (Flynn et al 2000) used
to measure knowledge of the Internet Factor analysis showed that these
Variable Questionnaire item Response N
ACCESS Do you have access to the
Internet
Yes
No
562
4
993
07
EVER Have you ever purchased any
clothing online
Yes
No
99
467
175
825
OFTEN How often would you say that
you purchase online
Very often
Often
Sometimes
Rarely
Never
4
18
119
201
224
07
32
210
355
396
BUY Asked another way how often
do you purchase online
More than once a week
About once a week
Only about once every two
weeks
Less than once every two
weeks but more than once
a month
Less than once a month
I never do
3
6
12
30
283
232
05
11
21
53
500
410
TIMES How many times have you
bought something online since
January 1 2000
plusmn plusmn times
MEANS How often do you purchase
clothing by any means
Very often
Often
Sometimes
Rarely
Never
Missing
83
179
226
55
21
2
147
316
399
97
37
04
HOURS On average about how many
hours a week do you spend
using the Internet
None
Less than one
One to five
Five to ten
Ten to 20
More than 20
Missing
5
68
244
164
63
21
1
09
120
431
290
111
37
02
LIKELY Regardless of how much you
buy online now how likely are
you to buy online in the
coming year
Definitely will buy
Probably will buy
Might buy
Probably will not buy
Definitely will not buy
Missing
82
107
208
141
23
5
145
189
367
249
41
09
SPEND How much do you spend on
clothing purchases in an
average month
Table I Internet and buying questions
Internet innovativeness
92 JOURNAL OF PRODUCT amp BRAND MANAGEMENT VOL 11 NO 2 2002
items formed a unidimensional scale (termed KNOW) with acceptably high
internal consistency (coefficient alpha = 090)
Results
The first preliminary analysis reduced the three online purchasing questions
(OFTEN BUY and TIMES from Table I) into a composite measure of the
self-reported amount of online buying of each respondent This was done
using a principal components analysis of the three items (Hair et al 1998
Ch 3) and computing factor scores using the SPSS regression method The
analysis extracted a single component with an eigenvalue of 237 that
explained 79 per cent of the variance in the correlation matrix of the three
variables The resulting variable was labeled PURCH Summary descriptive
statistics appear in Table IV
Attitude itema Fun Shop Safe Conf Cheap Quick
Buying over the Internet is more fun than
buying in a store 079
I enjoy buying over the Internet 056
I find shopping on the Internet less pleasant
than shopping in storesb 049
I sometimes shop for goods but then buy
them on the Internet 041
I get a real ` highrsquorsquo from shopping 086
Shopping is fun 083
I shop because buying things makes me
happy 080
I do not mind spending a lot of time
shoppingb 069
Buying over the Internet is no riskier than
buying in a store 084
It is risky to buy over the Internetb 073
Buying over the Internet is safer than buying
in a store plusmn033 048
I lack the confidence to buy correctly on the
Internetb 064
I am confident in my ability to buy
successfully over the Internet 055
There are so many dotcom companies out
there itrsquos confusingb 049
I cannot get the buying information I want
over the Internetb 040
I cannot save much money buying over the
Internetb 089
Buying over the Internet is cheaper than
buying in a store 067
Buying over the Internet is quicker than
buying in a store 064
Buying over the Internet is more efficient
than buying in a store 039
It takes a lot of time and trouble to buy on
the Internetb plusmn032 037
Eigenvalue 55 28 15 14 11 10
Percent of variance 274 139 76 68 54 51
Kaiser-Meyer-Olkin measure of sampling
adequacy = 0840
Notes Only loadings gt 030 are shown a using a five-point agree-disagree responseformat b reverse-coded items
Table II Factor analysis of attitude items
Composite measure
JOURNAL OF PRODUCT amp BRAND MANAGEMENT VOL 11 NO 2 2002 93
The second preliminary analysis examined the structure of the 25 attitude
items by submitting them to a common factor analysis followed by an
oblique rotation on the assumption that the attitude dimensions would be
correlated with one another (Hair et al 1998 Ch 3) The analysis was
conducted four times each time identifying items that did not load on a
factor with other items or which had small loadings (lt 003) or sizeable
(gt 030) cross-loadings on more than one factor Items were retained for
factors if they had sizeable loadings (gt 030) on factors made of items with
similar content These analyses reduced the initial pool of attitude items to
20 items that combined into six easily interpretable subscales that were
similar to those reported by Goldsmith (2000) The final analysis results
appear in Table II where the six factors represent the attitudes that shopping
on the Internet is fun safe cheap and quick and that the respondent had
confidence in hisher ability to shop online as well as the general
` enjoyment in shoppingrsquorsquo scale The scales are labeled FUN SAFE
CHEAP QUICK CONFIDENCE and SHOP The individual items were
summed to form short scales (see Table IV)
Next the Internet innovativeness and knowledge items were factor-analyzed
via common factor analysis which revealed that the items loaded on two
distinct factors indicating discriminant validity for these items (see Table
III) The individual items were summed to form two scales DSI and KNOW
Thus the focal variables in the study were amount of online buying
(PURCH) how often clothing was purchased by any means (MEANS) the
attitudes toward online buying (FUN SAFE CHEAP QUICK and
CONFIDENCE) attitude toward shopping (SHOP) Internet innovativeness
(DSI) and knowledge of the Internet (KNOW)
Cross-tabulation was used to assess the relationship between EVER (those
who had purchased apparel online versus those who had not) and sex and
race These analyses showed no statistically significant relationships
between these variables A t-test showed no statistically significant
difference in the mean age of those who had purchased apparel online versus
those who had not The correlations in Table IV provide internal evidence for
the validity of the measures The significant correlations of the DSI with
Scale itema Factor 1 Factor 2
Internet knowledge (KNOW)
When it comes to the Internet I really do not know a lotb 088
I know pretty much about the Internet 083
Compared with most other people I know less about the Internetb 082
I do not feel very knowledgeable about the Internetb 081
Among my circle of friends I am one of the ` expertsrsquorsquo on the
Internet 065
Internet innovativeness (DSI)
In general I am among the last in my circle of friends to purchase
something over the Internetb 081
Compared with my friends I do little shopping over the Internetb 079
In general I am the last in my circle of friends to know the names
of the latest places to shop on the Internetb 062
Eigenvalue 415 155
Percent of variance 518 194
Kaiser-Meyer-Olkin measure of sampling adequacy = 0865
Notes Only loadings gt 030 are shown a using a five-point agree-disagree responseformat b reverse-coded items
Table III Factor analysis of Internet knowledge and innovativeness items
Common factor analysis
Focal variables
94 JOURNAL OF PRODUCT amp BRAND MANAGEMENT VOL 11 NO 2 2002
Var
iable
sR
ange
Mea
nS
D1
23
45
67
89
10
11
12
13
14
15
16
1
Age
18-5
0226
49
plusmn
2
Sex
0-1
aplusmn
plusmn00
6plusmn
3
Ever
0-1
bplusmn
plusmn00
2plusmn00
5plusmn
4
Purc
hplusmn08
8-
86
80
10
00
801
804
2plusmn
5
Mea
ns
1-5
34
409
8plusmn01
1plusmn03
100
100
2plusmn
6
Fun
4-2
0105
27
00
801
603
505
600
2(0
74)c
7
Saf
e3-1
572
22
plusmn00
301
001
503
700
604
4(0
76)
8
Chea
p2-1
061
16
00
802
400
203
8plusmn00
804
402
9(0
75)
9
Quic
k3-1
593
27
01
000
901
702
9plusmn00
404
702
904
0(0
58)
10
Conf
4-2
0136
30
00
600
802
304
300
004
603
604
303
9(0
70)
11
Shop
4-2
0132
39
plusmn02
6plusmn04
500
5plusmn01
104
0plusmn01
6plusmn00
4plusmn02
1plusmn01
3plusmn01
6(0
86)
12
DS
I3-1
594
27
plusmn00
400
402
804
801
504
202
902
501
904
700
4(0
79)
13
Know
5-2
5184
40
plusmn00
000
801
102
800
602
601
201
601
704
9plusmn00
504
0(0
90)
14
Spen
d0-5
00
893
748
plusmn00
9plusmn02
200
300
604
3plusmn00
100
3plusmn00
8plusmn00
1plusmn00
103
001
300
1plusmn
15
Hours
1-6
35
10
01
101
101
803
600
403
101
602
001
603
4plusmn00
802
804
700
4plusmn
16
Lik
ely
1-5
32
11
00
801
203
306
700
405
904
003
503
704
6plusmn00
704
702
800
503
4plusmn
Note
sC
orr
elat
ions
of
00
9an
dla
rger
are
stat
isti
call
ysi
gnif
ican
tat
plt
00
5(t
wo-t
aile
d)
a1
=m
ale
and
0=
fem
ale
b1
=yes
and
0=
no
cco
effi
cien
tal
pha
inpar
enth
eses
Table
IV
Des
crip
tive
stati
stic
sand
corr
elati
ons
JOURNAL OF PRODUCT amp BRAND MANAGEMENT VOL 11 NO 2 2002 95
FUN SAFE CHEAP QUICK and CONFIDENCE are similar to those
reported by Goldsmith (2000) Moreover the correlation of the DSI with the
knowledge measure (r = 040) is comparable with that reported by Flynn et
al (2000)
An analysis was performed to assess the influence of age sex and race on the
dependent variables A MANCOVA with sex and race as the two
independent variables and age as a covariate was run with PURCH through
KNOW as the ten dependent variables The correlations in Table IV suggest
that age was only significantly correlated with shopping enjoyment and this
was confirmed by the results of the MANCOVA so age was no longer
incorporated in the analyses The results also showed no statistically
significant multivariate interaction between sex and race (F(33 1500) = 114
p = 0266) There was a statistically significant multivariate effect of race
(F(33 1500) = 162 p = 0014) but the only univariate differences were for
SAFE (p = 0033) where African-Americans rated the Internet as less safe
than whites and CHEAP (p = 0032) where the ` othersrsquorsquo rated the Internet as
cheaper than both whites and African-Americans These differences were
few and small in size and so race was no longer included in the analyses
The multivariate effect of sex was significant (F(11 498) = 48 p lt 0001)
Univariate tests showed that women reported purchasing apparel by any
means more often than men they spent more on apparel than men and they
enjoyed shopping more than men while the men reported purchasing more
online than the women and felt that the Internet was cheaper than the
women These differences suggest that sex should be included in the final
analysis of the differences between those who have purchased apparel online
and those who have not
For this analysis a 2 pound 2 (SEX pound EVER) MANOVA was run with the ten
dependent variables as before (see Table V) The interaction term was
Mean scoresa Observed
Dependent variables Men Women Fb p eta2 power
Univariate main effects for SEX
PURCH 0678 0126 308 lt 0000 0052 10
MEANS 306 375 378 lt 0000 0072 10
FUN 119 108 145 lt 0000 0025 0967
SAFE 77 73 29 0089 0005 0397
CHEAP 68 57 418 lt 0000 0070 10
QUICK 99 94 46 0032 0008 0576
CONFIDENT 145 139 35 0060 0006 0468
SHOP 115 148 687 lt 0000 0110 10
DSI 101 100 03 0601 0000 0082
KNOW 192 184 32 0074 0006 0431
Univariate main effects for EVER
H1 PURCH plusmn0184 0988 1391 lt 0000 0200 10
H2 MEANS 34 34 0075 0784 0000 0059
H3 FUN 101 127 879 lt 0000 0136 10
H4 SAFE 70 79 121 0001 0021 0934
H5 CHEAP 61 63 14 0245 0002 0213
H6 QUICK 92 102 197 lt 0000 0034 0993
H7 CONFIDENT 133 151 320 lt 0000 0054 10
H8 SHOP 130 133 0646 0422 0001 0126
H9 DSI 91 110 448 lt 0000 0074 10
H10 KNOW 182 194 78 0005 0014 0798
Notes a Estimated marginal means b df = 1558
Table V Comparisons of mean scores
Influence of age sex andrace
96 JOURNAL OF PRODUCT amp BRAND MANAGEMENT VOL 11 NO 2 2002
statistically significant (F(10 549) = 24 p = 001) Follow-up univariate
analyses showed that the interactions however were significant for only
two of the dependent variables For PURCH the amount of online buying
men reported buying more than women but men who had bought apparel
online reported buying disproportionately more online than women who
had bought apparel online The opposite effect was observed for MEANS
buying apparel by any means Women reported buying apparel by any
means more than men but men who had bought apparel online reported
buying disproportionately less apparel by any means than the women
online buyers
The multivariate main effect for SEX was significant (F(10 549) = 143
p lt 0001) In addition to significant main effect differences for PURCH and
MEANS women reported that they enjoyed shopping (SHOP) more than
men and men reported that they thought online buying was more fun
cheaper and quicker than the women These findings are similar to those
reported in other studies of online buying
The multivariate main effect for EVER whether a respondent had ever
bought apparel online was statistically significant (F(10 549) = 204
p lt 0001) The univariate analyses showed that compared with those who
had not bought apparel online those who had bought apparel online had
more experience purchasing online in general (PURCH) and thought that
buying over the Internet was more fun safer quicker and they were more
confident in their ability to buy online The online apparel buyers also were
more innovative and knowledgeable about the Internet than non-buyers
Thus H1 H3 H4 H6 H7 H9 and H10 were confirmed There were no
statistically significant differences in the self-reported apparel purchase
(MEANS) perceptions that online buying was cheaper (CHEAP) or in
shopping enjoyment (SHOP) Because Boxrsquos test of the equality of the
covariance matrices was significant (indicating that the covariance matrices
were not identical across the groups of respondents) and because Levenersquos
test of equality of error variances showed that the error variances of four of
the dependent variables were not equal thus violating the assumptions of
MANOVA (Huck and Cormier 1996 pp 313-15 374-7) a Mann-Whitney
non-parametric analysis was conducted testing whether the observations
from the two groups of online apparel buyers were equivalent in location
These analyses were consistent with the parametric tests
As a final analysis a 2 pound 2 (SEX pound EVER with age as a covariate)
MANCOVA was conducted comparing the buyers and non-buyers on three
additional variables These were
(1) the number of hours the respondent was online in an average week
(HOURS)
(2) the amount of reported spending on apparel (SPEND) and
(2) how likely the respondent was to buy online in the coming year
(LIKELY)
The results showed that men averaged more hours online per week than
women women spent more on apparel than men and the men were more
likely to shop online in the future than were the women Finally online
apparel buyers reported spending more time online and were more likely to
buy online in the future than non-buyers
Online apparel buyers
Additional variables
JOURNAL OF PRODUCT amp BRAND MANAGEMENT VOL 11 NO 2 2002 97
Discussion
The present study compared selected characteristics of consumers who had
purchased apparel online with those who had not The results showed that
online apparel buyers purchased online more often felt that online buying
was more fun safer and quicker than non-buyers Online apparel buyers
were more confident in their ability to buy online and were more innovative
and knowledgeable about the Internet than non-buyers Online apparel
buyers did not differ from non-buyers in their belief in how cheap buying
online is in their overall enjoyment of shopping or in how often they bought
apparel by any means Respondent demographics were also unrelated to
buying apparel online Online apparel buyers further differed from non-
buyers in that they spent more time online than non-buyers and were more
likely to buy online in the future than non-buyers These results reveal a
systematic pattern of psychological and behavioral factors that seem to
facilitate online apparel purchase
These findings confirm theoretical accounts of consumer behavior and
extend their generality into the new realm of cyber-commerce The findings
are consistent with other studies that show that favorable attitudes are related
to online buying From the methodological perspective the attitude measures
appear to be robust across studies and provide valid reliable
operationalizations of these constructs This should encourage researchers to
use them as standardized measures of e-commerce-related attitudes The
findings also confirm the reliability and validity of the innovativeness (DSI)
and knowledge scales consistent with a series of studies that have evidenced
their psychometric soundness (eg Flynn et al 2000 Goldsmith 2000)
The findings suggest that consumers are motivated to buy apparel online by a
combination of factors and that the special circumstances of e-commerce
make this a unique consumption activity Online apparel buyers obviously
must want and need clothing so this basic motivation partially underlies
their behavior They seem however to be motivated differentially by their
attitudes toward the Internet While online apparel buyers were clearly more
positive on the attitudinal and psychological characteristics they were no
more likely than non-buyers to shop for clothes by other means to enjoy
shopping in general or to spend money buying clothes That is they are not
disproportionately motivated by clothing as a product category or by interest
in shopping but by the perceived advantages of online buying and their
positive predisposition toward this mode of commerce
For managers the results suggest that their online buyers may be somewhat
different from their in-store customers and may represent new customers
Consumers who buy disproportionately more apparel likely enjoy shopping
and want the emotional and sensory pleasures of touching seeing and trying
on clothes (see Seckler 2000 Underhill 1999) Note the positive
intercorrelations in Table IV between spending on apparel and shopping
(r = 030) spending and buying by any means (043) and between shopping
and buying (040) None of these variables was correlated with amount of
online buying (PURCH) Online buyers in contrast appear to be motivated
by their positive attitudes toward the Internet Thus to attract apparel buyers
to Web sites e-marketers might focus on emphasizing the added advantages
of fun speed and safety They should first ensure that their sites are fun to
use load rapidly with prompt post-sale delivery of ordered merchandise and
are completely safe to use They might emphasize how different online
buying is and not pretend that it is the same as in-store shopping Joint or
cooperative strategies might display apparel online but suggest that a
Respondent demographics
Unique consumptionactivity
Positive attitudes
98 JOURNAL OF PRODUCT amp BRAND MANAGEMENT VOL 11 NO 2 2002
different experience could be had in the store where unique accessories or
combinations of clothes could be seen Online apparel buyers and non-
buyers did not differ in their perception that buying online is cheaper than
offline Thus Secklerrsquos (2000) argument that offering price discounts may be
a prime way to attract non-buyers is supported To attract new buyers onlineapparel e-tailers may have to change perceptions that online buying is unsafe
(see Robinson 2000) Web sites must be made simple and easy to use
because non-users are not very confident that they can buy online
successfully In-store demonstrations of online shopping might encourage
non-buyers to shop online As online apparel buying spreads beyond the
innovative and knowledgeable consumer to the less sophisticated shopper
apparel marketers should cater to their unique tastes abilities and habits
This is especially true since the results suggest that many online apparel
buyers will buy online again
The study is limited by the nature of the sample measures specificity and
time studied Lack of randomness in the sample limits generalizability of the
point and interval estimates to a larger population but since the main
purpose of the study was to test theoretical hypotheses about online buyingthis is a minor limitation (Calder et al 1981) No conclusions can be drawn
about concepts that might be related to online apparel buying but were not
measured and the results are limited to the measures employed Similarly
the focal topic was clothing in general and not a specific type (new fashion
sports clothes work clothes etc) Finally since e-commerce and online
consumer behavior are constantly changing phenomena the present study is
only a snapshot picture and not a longitudinal view
Advantages of the study lie in the large sample size and validity of the
measures used Future research should examine online apparel using data
from other demographic socio-economic and national groups of consumers
to expand the scope of the findings The online buyer behaviors studied
should be expanded beyond just buying to include browsing comparison
shopping and combining the Internet with in-store consumption as well asconsumption of specific categories of apparel such as new fashions or
unique sizes and needs As noted in the introduction growth is a major
theme of e-commerce Thus replication studies would be a valuable way to
track changes in online apparel buying over time Accumulation of such
studies would expand our knowledge of both apparel consumer behavior and
consumer Internet behavior to the advantage of both consumer theory and
apparel marketing Finally other researchers could make use of our measures
to study buying behavior in other areas as well
References
Calder BJ Phillips LW and Tybout AM (1981) ` Designing research for application rsquorsquo
Journal of Consumer Research Vol 8 September pp 197-207
Citrin AV Sprott DE Silveman SN and Stem DE Jr (2000) ` Adoption of Internet
shopping the role of consumer innovativenessrsquorsquo Industrial Management amp Data Systems
Vol 100 No 7 pp 294-300
Eastlick MA and Lotz S (1999) ` Profiling potential adopters and non-adopter s of an
interactive electronic shopping mediumrsquorsquo Internationa l Journal of Retail amp Distribution
Management Vol 27 No 6 pp 209-23
eMarketer (2000) ` The e-holiday shopping reportrsquorsquo available at wwwemarketercom
Flynn LR Goldsmith RE and Kim W (2000) ` A cross-cultural validation of three new
marketing scales for fashion research involvement opinion seeking and knowledgersquorsquo
The Journal of Fashion Marketing and Management Vol 4 No 2 pp 110-20
Goldsmith RE (2000) ` How innovativenes s differentiate s online buyersrsquorsquo Quarterly Journal
of Electronic Commerce Vol 1 No 4 pp 323-33
Snapshot picture
Expand the scope of thefindings
JOURNAL OF PRODUCT amp BRAND MANAGEMENT VOL 11 NO 2 2002 99
Goldsmith RE and Bridges E (2000) ` E-tailing vs retailing using attitudes to predict
online buying behavior rsquorsquo Quarterly Journal of Electronic Commerce Vol 1 No 3
pp 245-53
Goldsmith RE and Hofacker CF (1991) ` Measuring consumer innovativeness rsquorsquo Journal of
the Academy of Marketing Science Vol 19 No 3 pp 209-21
Goldsmith RE and McGregor S (1999) ` Electronic commerce an emerging issue in
consumer educationrsquorsquo Proceedings of XIX Internationa l Consumer Studies and Home
Economics Research Conference Belfast
Goldsmith RE and McGregor S (2000) ` E-commerce consumer protection issues and
implications for research and educationrsquorsquo Journal of Consumer Studies amp Home
Economics Vol 24 No 2 pp 124-7
Hair JF Anderson RE Tatham RL and Black WC (1998) Multivariate Data Analysis
5th ed Prentice-Hall Upper Saddle River NJ
Hallberg G (1995) All Consumers Are not Created Equal John Wiley New York NJ
Harvard Management Update (2000) ` Lessons from the online war for customersrsquorsquo
Harvard Management Update January pp 3-4
Hoffman DL and Novak TP (1996) ` Marketing in hypermedia computer-mediated
environments conceptua l foundationsrsquorsquo Journal of Marketing Vol 60 No 3 pp 153-61
Hogg MK Bruce M and Hill AJ (1998) ` Fashion brand preference s among young
consumersrsquorsquo Internationa l Journal of Retail amp Distribution Management Vol 26 No 8
pp 293-300
Huck SW and Cormier WH (1996) Reading Statistics and Research 2nd ed
HarperCollins College Publishers New York NY
Karson E (2000) ` Two dimensions of computer and Internet use a reliable and validated
scalersquorsquo Quarterly Journal of Electronic Commerce Vol 1 No 1 pp 49-60
Katz J and Aspden P (1997) ` Motivations for and barriers to Internet usage results of a
national public opinion surveyrsquorsquo Internet Research Vol 7 No 3 pp 170-88
Kuntz J (2000) ` Age and income play key roles in online salesrsquorsquo Daily News Record
27 March p 19
Limayem M Khalifa M and Frini A (2000) ` What makes consumers buy from the
Internet A longitudinal study of online shoppingrsquorsquo IEEE Transactions on Systems Man
and Cybernetics Part A Systems and Humans Vol 30 No 4 pp 421-32
Murphy R (1999) ` Download Internet news IIrsquorsquo The Journal of Fashion Marketing and
Management Vol 3 No 4 pp 376-7
Nelson J (2000) ` Internet at a glancersquorsquo Business 20 12 September p 279
OrsquoGuinn TC and Faber RJ (1989) ` Compulsive buying a phenomenologica l explorationrsquorsquo
Journal of Consumer Research Vol 16 No 2 pp 147-57
Robinson E (2000) ` Click and coverrsquorsquo Business 20 12 September pp 168-80
Seckler V (2000) ` Survey says Web apparel buys doubledrsquorsquo Womenrsquos Wear Daily 12 July
p 2
Silverman D (2000) ` More women wardrobe online than everrsquorsquo Womenrsquos Wear Daily
31 July p 20
Solomon MR (1999) Consumer Behavior Buying Having and Being 4th ed
Prentice-Hall Upper Saddle River NJ
UCLA (2000) ` The UCLA Internet report surveying the digital futurersquorsquo available at
wwwccpuclaedu
Underhill P (1999) Why We Buy The Science of Shopping Simon amp Schuster
New York NY
Vickery L and Agins T (2001) ` Retailers find Web apparel unprofitable rsquorsquo Wall Street
Journal 6 June p B6
Wilson J (1999) ` Keynote addressrsquorsquo The Journal of Fashion Marketing and Management
Vol 3 No 4 pp 370-6
amp
100 JOURNAL OF PRODUCT amp BRAND MANAGEMENT VOL 11 NO 2 2002
Executive summary and implications for managers andexecutives
Retailing online plusmn know your customer and learn from mail ordermarketingE-commerce and especially online retailing have received much attention agreat deal of thought and significant investment Despite this we still lackany clear understanding of the business models that can deliver successonline For every apparent e-retailing success we get a massive plusmn andusually very expensive plusmn failure We can say plusmn with some safety plusmn that theprospects for another Internet trading investment boom have gone
For marketers this situation is a disappointment We are after all theexperts on distribution and sales channels The failure to make e-retailingwork sits in our court and we continue to chew away at the e-commerce bonein the hope that it will eventually come good At the same time we haveraised questions about the capacity of the technology to deliver what wewant Doubts persist about the security of money transfers online Weak linksbetween real world distribution plusmn getting the product to the customer plusmn andthe cosy virtual world get in the way of seamless service And while gettingthe online equivalent of footfall is easy converting these visitors tocustomers is a massive challenge
Know your customer plusmn the marketerrsquos mantraGoldsmith and Goldsmith observe that while a great deal is said aboutonline processes technology and promotion little is known about the actualonline customer We know too little about the differences between theenthusiastic innovators who buy goods online and the rest who are happy tolook but do not buy
The difference between ` innovatorsrsquorsquo and ` early adoptersrsquorsquo is wellresearched and in general terms understood by marketers E-retailing hasnot taken off because the chasm between these two groups remainsunbridged As a result the apparent mass market for e-commerce remains afuture dream Two-thirds of Americans might have access to the Internet butthey are not using it to buy things plusmn at least not in sufficient numbers
Goldsmith and Goldsmith set out to compare clothes buyers who havebought online with those who have not made this sort of purchaseUnderlying the study is the assumption (supported by research and largelycommon sense) that ` consumers who have previous experience in onlinebuying will be more likely to buy apparel online than those who lack suchexperiencersquorsquo We should also note like Goldsmith and Goldsmith that thepeople who matter to e-retailers are those very similar to existing users whoat present are non-users
Are you frightened of the WebGoldsmith and Goldsmith find that there are substantial differences betweene-buyers and the rest of humanity (I always knew that Web enthusiasts werestrange) Some of these differences are pretty prosaic plusmn online buyers havefewer security worries appreciate the ` quicknessrsquorsquo and flexibility of onlinebuying and see the Web as making buying easier However the other (morepsychological) factors suggest that these preferences are symptomatic of thetype rather than definitional The remainder of Goldsmith and Goldsmithrsquosfindings throw up words like ` confidentrsquorsquo ` innovativersquorsquo ` knowledgeablersquorsquoand ` funrsquorsquo Our e-buyers take the view that ` the special circumstancesof e-commerce make this a unique consumption activityrsquorsquo These people aredifferent and we need to know why and at the same time to understand theresistance of others to e-commerce
Part of the resistance appears to lie in fear (characterised as being a lack ofconfidence) People who do not buy online do not have a great deal of trust in
JOURNAL OF PRODUCT amp BRAND MANAGEMENT VOL 11 NO 2 2002 101
This summary has beenprovided to allow managersand executives a rapidappreciation of the contentof this article Those with aparticular interest in thetopic covered may then readthe article in toto to takeadvantage of the morecomprehensive descriptionof the research undertakenand its results to get the fullbenefit of the materialpresent
the medium This seems to hold true even when they use the Internet for avariety of other activities (information gathering communications games etc)Until these issues of fear (or trust or confidence) are dealt with marketers willstruggle to take the idea of e-commerce into the mainstream of retailing
Removing the fearTwo elements are involved in removing consumer distrust of e-commerceThe first is more confidence with the technology involved in buying onlineBear in mind that most of us who use computers take advantage of a tiny partof the capacity of even basic software Even with comprehensible manualson-screen and online help and ` idiot guidesrsquorsquo we still stick to basicprocessing
Ease-of-use is fundamental to successful e-retailing and so far we havefailed to achieve sufficiently easy systems to remove the consumerrsquos worryabout getting it wrong But this is just one problem and its solution lies asmuch in the relationship between the ordinary consumer and Internettechnology as in specific marketing actions
The second element is purely promotional and is about securing trial andreducing the distrust E-commerce becomes accessible when these barriersare removed and there are many techniques available that marketers canuse
Mail order and direct marketers have always faced resistance to theirchannel Indeed mail order people appreciate that there remains a largechunk of the population that will never buy mail order whatever theincentive Nevertheless these marketers have developed (and tested) avariety of simple techniques to secure trial and build confidence
product and service guarantees
payment on delivery rather than payment with the order
featuring low-risk entry products
no-quibble return policies
product endorsement plusmn by real customers
testimonials and
prize draws free gifts and other order incentives
E-commerce represents a new channel and for some businesses a differentmeans of delivering product But for most businesses and especiallyretailers the Internet does not change the nature of the product itself (a pairof shorts remains a pair of shorts) Rather than reinventing the wheel e-retailers should learn from direct marketers
E-commerce needs more confidence to sell itself successfully but in the finalanalysis the e-retailer does little that is different from the mail ordercompany And the direct marketer knows that profits come from repeatbusiness rather than from the first sale Too many e-commerce operationshave floundered because they ignored the experience of others and tried torun a business without good databases or the strategies to sustain incomefrom existing buyers
Do you want your e-retailing business to succeed Hire an experience directmarketer and you will stand a better than average chance of successPretending that the e-marketers have nothing to learn from old grizzled (andboring) mail order people is a mistake that is probably costing you money
(A preAcirccis of the article ` Buying apparel over the Internetrsquorsquo Supplied byMarketing Consultants for Emerald)
102 JOURNAL OF PRODUCT amp BRAND MANAGEMENT VOL 11 NO 2 2002
items formed a unidimensional scale (termed KNOW) with acceptably high
internal consistency (coefficient alpha = 090)
Results
The first preliminary analysis reduced the three online purchasing questions
(OFTEN BUY and TIMES from Table I) into a composite measure of the
self-reported amount of online buying of each respondent This was done
using a principal components analysis of the three items (Hair et al 1998
Ch 3) and computing factor scores using the SPSS regression method The
analysis extracted a single component with an eigenvalue of 237 that
explained 79 per cent of the variance in the correlation matrix of the three
variables The resulting variable was labeled PURCH Summary descriptive
statistics appear in Table IV
Attitude itema Fun Shop Safe Conf Cheap Quick
Buying over the Internet is more fun than
buying in a store 079
I enjoy buying over the Internet 056
I find shopping on the Internet less pleasant
than shopping in storesb 049
I sometimes shop for goods but then buy
them on the Internet 041
I get a real ` highrsquorsquo from shopping 086
Shopping is fun 083
I shop because buying things makes me
happy 080
I do not mind spending a lot of time
shoppingb 069
Buying over the Internet is no riskier than
buying in a store 084
It is risky to buy over the Internetb 073
Buying over the Internet is safer than buying
in a store plusmn033 048
I lack the confidence to buy correctly on the
Internetb 064
I am confident in my ability to buy
successfully over the Internet 055
There are so many dotcom companies out
there itrsquos confusingb 049
I cannot get the buying information I want
over the Internetb 040
I cannot save much money buying over the
Internetb 089
Buying over the Internet is cheaper than
buying in a store 067
Buying over the Internet is quicker than
buying in a store 064
Buying over the Internet is more efficient
than buying in a store 039
It takes a lot of time and trouble to buy on
the Internetb plusmn032 037
Eigenvalue 55 28 15 14 11 10
Percent of variance 274 139 76 68 54 51
Kaiser-Meyer-Olkin measure of sampling
adequacy = 0840
Notes Only loadings gt 030 are shown a using a five-point agree-disagree responseformat b reverse-coded items
Table II Factor analysis of attitude items
Composite measure
JOURNAL OF PRODUCT amp BRAND MANAGEMENT VOL 11 NO 2 2002 93
The second preliminary analysis examined the structure of the 25 attitude
items by submitting them to a common factor analysis followed by an
oblique rotation on the assumption that the attitude dimensions would be
correlated with one another (Hair et al 1998 Ch 3) The analysis was
conducted four times each time identifying items that did not load on a
factor with other items or which had small loadings (lt 003) or sizeable
(gt 030) cross-loadings on more than one factor Items were retained for
factors if they had sizeable loadings (gt 030) on factors made of items with
similar content These analyses reduced the initial pool of attitude items to
20 items that combined into six easily interpretable subscales that were
similar to those reported by Goldsmith (2000) The final analysis results
appear in Table II where the six factors represent the attitudes that shopping
on the Internet is fun safe cheap and quick and that the respondent had
confidence in hisher ability to shop online as well as the general
` enjoyment in shoppingrsquorsquo scale The scales are labeled FUN SAFE
CHEAP QUICK CONFIDENCE and SHOP The individual items were
summed to form short scales (see Table IV)
Next the Internet innovativeness and knowledge items were factor-analyzed
via common factor analysis which revealed that the items loaded on two
distinct factors indicating discriminant validity for these items (see Table
III) The individual items were summed to form two scales DSI and KNOW
Thus the focal variables in the study were amount of online buying
(PURCH) how often clothing was purchased by any means (MEANS) the
attitudes toward online buying (FUN SAFE CHEAP QUICK and
CONFIDENCE) attitude toward shopping (SHOP) Internet innovativeness
(DSI) and knowledge of the Internet (KNOW)
Cross-tabulation was used to assess the relationship between EVER (those
who had purchased apparel online versus those who had not) and sex and
race These analyses showed no statistically significant relationships
between these variables A t-test showed no statistically significant
difference in the mean age of those who had purchased apparel online versus
those who had not The correlations in Table IV provide internal evidence for
the validity of the measures The significant correlations of the DSI with
Scale itema Factor 1 Factor 2
Internet knowledge (KNOW)
When it comes to the Internet I really do not know a lotb 088
I know pretty much about the Internet 083
Compared with most other people I know less about the Internetb 082
I do not feel very knowledgeable about the Internetb 081
Among my circle of friends I am one of the ` expertsrsquorsquo on the
Internet 065
Internet innovativeness (DSI)
In general I am among the last in my circle of friends to purchase
something over the Internetb 081
Compared with my friends I do little shopping over the Internetb 079
In general I am the last in my circle of friends to know the names
of the latest places to shop on the Internetb 062
Eigenvalue 415 155
Percent of variance 518 194
Kaiser-Meyer-Olkin measure of sampling adequacy = 0865
Notes Only loadings gt 030 are shown a using a five-point agree-disagree responseformat b reverse-coded items
Table III Factor analysis of Internet knowledge and innovativeness items
Common factor analysis
Focal variables
94 JOURNAL OF PRODUCT amp BRAND MANAGEMENT VOL 11 NO 2 2002
Var
iable
sR
ange
Mea
nS
D1
23
45
67
89
10
11
12
13
14
15
16
1
Age
18-5
0226
49
plusmn
2
Sex
0-1
aplusmn
plusmn00
6plusmn
3
Ever
0-1
bplusmn
plusmn00
2plusmn00
5plusmn
4
Purc
hplusmn08
8-
86
80
10
00
801
804
2plusmn
5
Mea
ns
1-5
34
409
8plusmn01
1plusmn03
100
100
2plusmn
6
Fun
4-2
0105
27
00
801
603
505
600
2(0
74)c
7
Saf
e3-1
572
22
plusmn00
301
001
503
700
604
4(0
76)
8
Chea
p2-1
061
16
00
802
400
203
8plusmn00
804
402
9(0
75)
9
Quic
k3-1
593
27
01
000
901
702
9plusmn00
404
702
904
0(0
58)
10
Conf
4-2
0136
30
00
600
802
304
300
004
603
604
303
9(0
70)
11
Shop
4-2
0132
39
plusmn02
6plusmn04
500
5plusmn01
104
0plusmn01
6plusmn00
4plusmn02
1plusmn01
3plusmn01
6(0
86)
12
DS
I3-1
594
27
plusmn00
400
402
804
801
504
202
902
501
904
700
4(0
79)
13
Know
5-2
5184
40
plusmn00
000
801
102
800
602
601
201
601
704
9plusmn00
504
0(0
90)
14
Spen
d0-5
00
893
748
plusmn00
9plusmn02
200
300
604
3plusmn00
100
3plusmn00
8plusmn00
1plusmn00
103
001
300
1plusmn
15
Hours
1-6
35
10
01
101
101
803
600
403
101
602
001
603
4plusmn00
802
804
700
4plusmn
16
Lik
ely
1-5
32
11
00
801
203
306
700
405
904
003
503
704
6plusmn00
704
702
800
503
4plusmn
Note
sC
orr
elat
ions
of
00
9an
dla
rger
are
stat
isti
call
ysi
gnif
ican
tat
plt
00
5(t
wo-t
aile
d)
a1
=m
ale
and
0=
fem
ale
b1
=yes
and
0=
no
cco
effi
cien
tal
pha
inpar
enth
eses
Table
IV
Des
crip
tive
stati
stic
sand
corr
elati
ons
JOURNAL OF PRODUCT amp BRAND MANAGEMENT VOL 11 NO 2 2002 95
FUN SAFE CHEAP QUICK and CONFIDENCE are similar to those
reported by Goldsmith (2000) Moreover the correlation of the DSI with the
knowledge measure (r = 040) is comparable with that reported by Flynn et
al (2000)
An analysis was performed to assess the influence of age sex and race on the
dependent variables A MANCOVA with sex and race as the two
independent variables and age as a covariate was run with PURCH through
KNOW as the ten dependent variables The correlations in Table IV suggest
that age was only significantly correlated with shopping enjoyment and this
was confirmed by the results of the MANCOVA so age was no longer
incorporated in the analyses The results also showed no statistically
significant multivariate interaction between sex and race (F(33 1500) = 114
p = 0266) There was a statistically significant multivariate effect of race
(F(33 1500) = 162 p = 0014) but the only univariate differences were for
SAFE (p = 0033) where African-Americans rated the Internet as less safe
than whites and CHEAP (p = 0032) where the ` othersrsquorsquo rated the Internet as
cheaper than both whites and African-Americans These differences were
few and small in size and so race was no longer included in the analyses
The multivariate effect of sex was significant (F(11 498) = 48 p lt 0001)
Univariate tests showed that women reported purchasing apparel by any
means more often than men they spent more on apparel than men and they
enjoyed shopping more than men while the men reported purchasing more
online than the women and felt that the Internet was cheaper than the
women These differences suggest that sex should be included in the final
analysis of the differences between those who have purchased apparel online
and those who have not
For this analysis a 2 pound 2 (SEX pound EVER) MANOVA was run with the ten
dependent variables as before (see Table V) The interaction term was
Mean scoresa Observed
Dependent variables Men Women Fb p eta2 power
Univariate main effects for SEX
PURCH 0678 0126 308 lt 0000 0052 10
MEANS 306 375 378 lt 0000 0072 10
FUN 119 108 145 lt 0000 0025 0967
SAFE 77 73 29 0089 0005 0397
CHEAP 68 57 418 lt 0000 0070 10
QUICK 99 94 46 0032 0008 0576
CONFIDENT 145 139 35 0060 0006 0468
SHOP 115 148 687 lt 0000 0110 10
DSI 101 100 03 0601 0000 0082
KNOW 192 184 32 0074 0006 0431
Univariate main effects for EVER
H1 PURCH plusmn0184 0988 1391 lt 0000 0200 10
H2 MEANS 34 34 0075 0784 0000 0059
H3 FUN 101 127 879 lt 0000 0136 10
H4 SAFE 70 79 121 0001 0021 0934
H5 CHEAP 61 63 14 0245 0002 0213
H6 QUICK 92 102 197 lt 0000 0034 0993
H7 CONFIDENT 133 151 320 lt 0000 0054 10
H8 SHOP 130 133 0646 0422 0001 0126
H9 DSI 91 110 448 lt 0000 0074 10
H10 KNOW 182 194 78 0005 0014 0798
Notes a Estimated marginal means b df = 1558
Table V Comparisons of mean scores
Influence of age sex andrace
96 JOURNAL OF PRODUCT amp BRAND MANAGEMENT VOL 11 NO 2 2002
statistically significant (F(10 549) = 24 p = 001) Follow-up univariate
analyses showed that the interactions however were significant for only
two of the dependent variables For PURCH the amount of online buying
men reported buying more than women but men who had bought apparel
online reported buying disproportionately more online than women who
had bought apparel online The opposite effect was observed for MEANS
buying apparel by any means Women reported buying apparel by any
means more than men but men who had bought apparel online reported
buying disproportionately less apparel by any means than the women
online buyers
The multivariate main effect for SEX was significant (F(10 549) = 143
p lt 0001) In addition to significant main effect differences for PURCH and
MEANS women reported that they enjoyed shopping (SHOP) more than
men and men reported that they thought online buying was more fun
cheaper and quicker than the women These findings are similar to those
reported in other studies of online buying
The multivariate main effect for EVER whether a respondent had ever
bought apparel online was statistically significant (F(10 549) = 204
p lt 0001) The univariate analyses showed that compared with those who
had not bought apparel online those who had bought apparel online had
more experience purchasing online in general (PURCH) and thought that
buying over the Internet was more fun safer quicker and they were more
confident in their ability to buy online The online apparel buyers also were
more innovative and knowledgeable about the Internet than non-buyers
Thus H1 H3 H4 H6 H7 H9 and H10 were confirmed There were no
statistically significant differences in the self-reported apparel purchase
(MEANS) perceptions that online buying was cheaper (CHEAP) or in
shopping enjoyment (SHOP) Because Boxrsquos test of the equality of the
covariance matrices was significant (indicating that the covariance matrices
were not identical across the groups of respondents) and because Levenersquos
test of equality of error variances showed that the error variances of four of
the dependent variables were not equal thus violating the assumptions of
MANOVA (Huck and Cormier 1996 pp 313-15 374-7) a Mann-Whitney
non-parametric analysis was conducted testing whether the observations
from the two groups of online apparel buyers were equivalent in location
These analyses were consistent with the parametric tests
As a final analysis a 2 pound 2 (SEX pound EVER with age as a covariate)
MANCOVA was conducted comparing the buyers and non-buyers on three
additional variables These were
(1) the number of hours the respondent was online in an average week
(HOURS)
(2) the amount of reported spending on apparel (SPEND) and
(2) how likely the respondent was to buy online in the coming year
(LIKELY)
The results showed that men averaged more hours online per week than
women women spent more on apparel than men and the men were more
likely to shop online in the future than were the women Finally online
apparel buyers reported spending more time online and were more likely to
buy online in the future than non-buyers
Online apparel buyers
Additional variables
JOURNAL OF PRODUCT amp BRAND MANAGEMENT VOL 11 NO 2 2002 97
Discussion
The present study compared selected characteristics of consumers who had
purchased apparel online with those who had not The results showed that
online apparel buyers purchased online more often felt that online buying
was more fun safer and quicker than non-buyers Online apparel buyers
were more confident in their ability to buy online and were more innovative
and knowledgeable about the Internet than non-buyers Online apparel
buyers did not differ from non-buyers in their belief in how cheap buying
online is in their overall enjoyment of shopping or in how often they bought
apparel by any means Respondent demographics were also unrelated to
buying apparel online Online apparel buyers further differed from non-
buyers in that they spent more time online than non-buyers and were more
likely to buy online in the future than non-buyers These results reveal a
systematic pattern of psychological and behavioral factors that seem to
facilitate online apparel purchase
These findings confirm theoretical accounts of consumer behavior and
extend their generality into the new realm of cyber-commerce The findings
are consistent with other studies that show that favorable attitudes are related
to online buying From the methodological perspective the attitude measures
appear to be robust across studies and provide valid reliable
operationalizations of these constructs This should encourage researchers to
use them as standardized measures of e-commerce-related attitudes The
findings also confirm the reliability and validity of the innovativeness (DSI)
and knowledge scales consistent with a series of studies that have evidenced
their psychometric soundness (eg Flynn et al 2000 Goldsmith 2000)
The findings suggest that consumers are motivated to buy apparel online by a
combination of factors and that the special circumstances of e-commerce
make this a unique consumption activity Online apparel buyers obviously
must want and need clothing so this basic motivation partially underlies
their behavior They seem however to be motivated differentially by their
attitudes toward the Internet While online apparel buyers were clearly more
positive on the attitudinal and psychological characteristics they were no
more likely than non-buyers to shop for clothes by other means to enjoy
shopping in general or to spend money buying clothes That is they are not
disproportionately motivated by clothing as a product category or by interest
in shopping but by the perceived advantages of online buying and their
positive predisposition toward this mode of commerce
For managers the results suggest that their online buyers may be somewhat
different from their in-store customers and may represent new customers
Consumers who buy disproportionately more apparel likely enjoy shopping
and want the emotional and sensory pleasures of touching seeing and trying
on clothes (see Seckler 2000 Underhill 1999) Note the positive
intercorrelations in Table IV between spending on apparel and shopping
(r = 030) spending and buying by any means (043) and between shopping
and buying (040) None of these variables was correlated with amount of
online buying (PURCH) Online buyers in contrast appear to be motivated
by their positive attitudes toward the Internet Thus to attract apparel buyers
to Web sites e-marketers might focus on emphasizing the added advantages
of fun speed and safety They should first ensure that their sites are fun to
use load rapidly with prompt post-sale delivery of ordered merchandise and
are completely safe to use They might emphasize how different online
buying is and not pretend that it is the same as in-store shopping Joint or
cooperative strategies might display apparel online but suggest that a
Respondent demographics
Unique consumptionactivity
Positive attitudes
98 JOURNAL OF PRODUCT amp BRAND MANAGEMENT VOL 11 NO 2 2002
different experience could be had in the store where unique accessories or
combinations of clothes could be seen Online apparel buyers and non-
buyers did not differ in their perception that buying online is cheaper than
offline Thus Secklerrsquos (2000) argument that offering price discounts may be
a prime way to attract non-buyers is supported To attract new buyers onlineapparel e-tailers may have to change perceptions that online buying is unsafe
(see Robinson 2000) Web sites must be made simple and easy to use
because non-users are not very confident that they can buy online
successfully In-store demonstrations of online shopping might encourage
non-buyers to shop online As online apparel buying spreads beyond the
innovative and knowledgeable consumer to the less sophisticated shopper
apparel marketers should cater to their unique tastes abilities and habits
This is especially true since the results suggest that many online apparel
buyers will buy online again
The study is limited by the nature of the sample measures specificity and
time studied Lack of randomness in the sample limits generalizability of the
point and interval estimates to a larger population but since the main
purpose of the study was to test theoretical hypotheses about online buyingthis is a minor limitation (Calder et al 1981) No conclusions can be drawn
about concepts that might be related to online apparel buying but were not
measured and the results are limited to the measures employed Similarly
the focal topic was clothing in general and not a specific type (new fashion
sports clothes work clothes etc) Finally since e-commerce and online
consumer behavior are constantly changing phenomena the present study is
only a snapshot picture and not a longitudinal view
Advantages of the study lie in the large sample size and validity of the
measures used Future research should examine online apparel using data
from other demographic socio-economic and national groups of consumers
to expand the scope of the findings The online buyer behaviors studied
should be expanded beyond just buying to include browsing comparison
shopping and combining the Internet with in-store consumption as well asconsumption of specific categories of apparel such as new fashions or
unique sizes and needs As noted in the introduction growth is a major
theme of e-commerce Thus replication studies would be a valuable way to
track changes in online apparel buying over time Accumulation of such
studies would expand our knowledge of both apparel consumer behavior and
consumer Internet behavior to the advantage of both consumer theory and
apparel marketing Finally other researchers could make use of our measures
to study buying behavior in other areas as well
References
Calder BJ Phillips LW and Tybout AM (1981) ` Designing research for application rsquorsquo
Journal of Consumer Research Vol 8 September pp 197-207
Citrin AV Sprott DE Silveman SN and Stem DE Jr (2000) ` Adoption of Internet
shopping the role of consumer innovativenessrsquorsquo Industrial Management amp Data Systems
Vol 100 No 7 pp 294-300
Eastlick MA and Lotz S (1999) ` Profiling potential adopters and non-adopter s of an
interactive electronic shopping mediumrsquorsquo Internationa l Journal of Retail amp Distribution
Management Vol 27 No 6 pp 209-23
eMarketer (2000) ` The e-holiday shopping reportrsquorsquo available at wwwemarketercom
Flynn LR Goldsmith RE and Kim W (2000) ` A cross-cultural validation of three new
marketing scales for fashion research involvement opinion seeking and knowledgersquorsquo
The Journal of Fashion Marketing and Management Vol 4 No 2 pp 110-20
Goldsmith RE (2000) ` How innovativenes s differentiate s online buyersrsquorsquo Quarterly Journal
of Electronic Commerce Vol 1 No 4 pp 323-33
Snapshot picture
Expand the scope of thefindings
JOURNAL OF PRODUCT amp BRAND MANAGEMENT VOL 11 NO 2 2002 99
Goldsmith RE and Bridges E (2000) ` E-tailing vs retailing using attitudes to predict
online buying behavior rsquorsquo Quarterly Journal of Electronic Commerce Vol 1 No 3
pp 245-53
Goldsmith RE and Hofacker CF (1991) ` Measuring consumer innovativeness rsquorsquo Journal of
the Academy of Marketing Science Vol 19 No 3 pp 209-21
Goldsmith RE and McGregor S (1999) ` Electronic commerce an emerging issue in
consumer educationrsquorsquo Proceedings of XIX Internationa l Consumer Studies and Home
Economics Research Conference Belfast
Goldsmith RE and McGregor S (2000) ` E-commerce consumer protection issues and
implications for research and educationrsquorsquo Journal of Consumer Studies amp Home
Economics Vol 24 No 2 pp 124-7
Hair JF Anderson RE Tatham RL and Black WC (1998) Multivariate Data Analysis
5th ed Prentice-Hall Upper Saddle River NJ
Hallberg G (1995) All Consumers Are not Created Equal John Wiley New York NJ
Harvard Management Update (2000) ` Lessons from the online war for customersrsquorsquo
Harvard Management Update January pp 3-4
Hoffman DL and Novak TP (1996) ` Marketing in hypermedia computer-mediated
environments conceptua l foundationsrsquorsquo Journal of Marketing Vol 60 No 3 pp 153-61
Hogg MK Bruce M and Hill AJ (1998) ` Fashion brand preference s among young
consumersrsquorsquo Internationa l Journal of Retail amp Distribution Management Vol 26 No 8
pp 293-300
Huck SW and Cormier WH (1996) Reading Statistics and Research 2nd ed
HarperCollins College Publishers New York NY
Karson E (2000) ` Two dimensions of computer and Internet use a reliable and validated
scalersquorsquo Quarterly Journal of Electronic Commerce Vol 1 No 1 pp 49-60
Katz J and Aspden P (1997) ` Motivations for and barriers to Internet usage results of a
national public opinion surveyrsquorsquo Internet Research Vol 7 No 3 pp 170-88
Kuntz J (2000) ` Age and income play key roles in online salesrsquorsquo Daily News Record
27 March p 19
Limayem M Khalifa M and Frini A (2000) ` What makes consumers buy from the
Internet A longitudinal study of online shoppingrsquorsquo IEEE Transactions on Systems Man
and Cybernetics Part A Systems and Humans Vol 30 No 4 pp 421-32
Murphy R (1999) ` Download Internet news IIrsquorsquo The Journal of Fashion Marketing and
Management Vol 3 No 4 pp 376-7
Nelson J (2000) ` Internet at a glancersquorsquo Business 20 12 September p 279
OrsquoGuinn TC and Faber RJ (1989) ` Compulsive buying a phenomenologica l explorationrsquorsquo
Journal of Consumer Research Vol 16 No 2 pp 147-57
Robinson E (2000) ` Click and coverrsquorsquo Business 20 12 September pp 168-80
Seckler V (2000) ` Survey says Web apparel buys doubledrsquorsquo Womenrsquos Wear Daily 12 July
p 2
Silverman D (2000) ` More women wardrobe online than everrsquorsquo Womenrsquos Wear Daily
31 July p 20
Solomon MR (1999) Consumer Behavior Buying Having and Being 4th ed
Prentice-Hall Upper Saddle River NJ
UCLA (2000) ` The UCLA Internet report surveying the digital futurersquorsquo available at
wwwccpuclaedu
Underhill P (1999) Why We Buy The Science of Shopping Simon amp Schuster
New York NY
Vickery L and Agins T (2001) ` Retailers find Web apparel unprofitable rsquorsquo Wall Street
Journal 6 June p B6
Wilson J (1999) ` Keynote addressrsquorsquo The Journal of Fashion Marketing and Management
Vol 3 No 4 pp 370-6
amp
100 JOURNAL OF PRODUCT amp BRAND MANAGEMENT VOL 11 NO 2 2002
Executive summary and implications for managers andexecutives
Retailing online plusmn know your customer and learn from mail ordermarketingE-commerce and especially online retailing have received much attention agreat deal of thought and significant investment Despite this we still lackany clear understanding of the business models that can deliver successonline For every apparent e-retailing success we get a massive plusmn andusually very expensive plusmn failure We can say plusmn with some safety plusmn that theprospects for another Internet trading investment boom have gone
For marketers this situation is a disappointment We are after all theexperts on distribution and sales channels The failure to make e-retailingwork sits in our court and we continue to chew away at the e-commerce bonein the hope that it will eventually come good At the same time we haveraised questions about the capacity of the technology to deliver what wewant Doubts persist about the security of money transfers online Weak linksbetween real world distribution plusmn getting the product to the customer plusmn andthe cosy virtual world get in the way of seamless service And while gettingthe online equivalent of footfall is easy converting these visitors tocustomers is a massive challenge
Know your customer plusmn the marketerrsquos mantraGoldsmith and Goldsmith observe that while a great deal is said aboutonline processes technology and promotion little is known about the actualonline customer We know too little about the differences between theenthusiastic innovators who buy goods online and the rest who are happy tolook but do not buy
The difference between ` innovatorsrsquorsquo and ` early adoptersrsquorsquo is wellresearched and in general terms understood by marketers E-retailing hasnot taken off because the chasm between these two groups remainsunbridged As a result the apparent mass market for e-commerce remains afuture dream Two-thirds of Americans might have access to the Internet butthey are not using it to buy things plusmn at least not in sufficient numbers
Goldsmith and Goldsmith set out to compare clothes buyers who havebought online with those who have not made this sort of purchaseUnderlying the study is the assumption (supported by research and largelycommon sense) that ` consumers who have previous experience in onlinebuying will be more likely to buy apparel online than those who lack suchexperiencersquorsquo We should also note like Goldsmith and Goldsmith that thepeople who matter to e-retailers are those very similar to existing users whoat present are non-users
Are you frightened of the WebGoldsmith and Goldsmith find that there are substantial differences betweene-buyers and the rest of humanity (I always knew that Web enthusiasts werestrange) Some of these differences are pretty prosaic plusmn online buyers havefewer security worries appreciate the ` quicknessrsquorsquo and flexibility of onlinebuying and see the Web as making buying easier However the other (morepsychological) factors suggest that these preferences are symptomatic of thetype rather than definitional The remainder of Goldsmith and Goldsmithrsquosfindings throw up words like ` confidentrsquorsquo ` innovativersquorsquo ` knowledgeablersquorsquoand ` funrsquorsquo Our e-buyers take the view that ` the special circumstancesof e-commerce make this a unique consumption activityrsquorsquo These people aredifferent and we need to know why and at the same time to understand theresistance of others to e-commerce
Part of the resistance appears to lie in fear (characterised as being a lack ofconfidence) People who do not buy online do not have a great deal of trust in
JOURNAL OF PRODUCT amp BRAND MANAGEMENT VOL 11 NO 2 2002 101
This summary has beenprovided to allow managersand executives a rapidappreciation of the contentof this article Those with aparticular interest in thetopic covered may then readthe article in toto to takeadvantage of the morecomprehensive descriptionof the research undertakenand its results to get the fullbenefit of the materialpresent
the medium This seems to hold true even when they use the Internet for avariety of other activities (information gathering communications games etc)Until these issues of fear (or trust or confidence) are dealt with marketers willstruggle to take the idea of e-commerce into the mainstream of retailing
Removing the fearTwo elements are involved in removing consumer distrust of e-commerceThe first is more confidence with the technology involved in buying onlineBear in mind that most of us who use computers take advantage of a tiny partof the capacity of even basic software Even with comprehensible manualson-screen and online help and ` idiot guidesrsquorsquo we still stick to basicprocessing
Ease-of-use is fundamental to successful e-retailing and so far we havefailed to achieve sufficiently easy systems to remove the consumerrsquos worryabout getting it wrong But this is just one problem and its solution lies asmuch in the relationship between the ordinary consumer and Internettechnology as in specific marketing actions
The second element is purely promotional and is about securing trial andreducing the distrust E-commerce becomes accessible when these barriersare removed and there are many techniques available that marketers canuse
Mail order and direct marketers have always faced resistance to theirchannel Indeed mail order people appreciate that there remains a largechunk of the population that will never buy mail order whatever theincentive Nevertheless these marketers have developed (and tested) avariety of simple techniques to secure trial and build confidence
product and service guarantees
payment on delivery rather than payment with the order
featuring low-risk entry products
no-quibble return policies
product endorsement plusmn by real customers
testimonials and
prize draws free gifts and other order incentives
E-commerce represents a new channel and for some businesses a differentmeans of delivering product But for most businesses and especiallyretailers the Internet does not change the nature of the product itself (a pairof shorts remains a pair of shorts) Rather than reinventing the wheel e-retailers should learn from direct marketers
E-commerce needs more confidence to sell itself successfully but in the finalanalysis the e-retailer does little that is different from the mail ordercompany And the direct marketer knows that profits come from repeatbusiness rather than from the first sale Too many e-commerce operationshave floundered because they ignored the experience of others and tried torun a business without good databases or the strategies to sustain incomefrom existing buyers
Do you want your e-retailing business to succeed Hire an experience directmarketer and you will stand a better than average chance of successPretending that the e-marketers have nothing to learn from old grizzled (andboring) mail order people is a mistake that is probably costing you money
(A preAcirccis of the article ` Buying apparel over the Internetrsquorsquo Supplied byMarketing Consultants for Emerald)
102 JOURNAL OF PRODUCT amp BRAND MANAGEMENT VOL 11 NO 2 2002
The second preliminary analysis examined the structure of the 25 attitude
items by submitting them to a common factor analysis followed by an
oblique rotation on the assumption that the attitude dimensions would be
correlated with one another (Hair et al 1998 Ch 3) The analysis was
conducted four times each time identifying items that did not load on a
factor with other items or which had small loadings (lt 003) or sizeable
(gt 030) cross-loadings on more than one factor Items were retained for
factors if they had sizeable loadings (gt 030) on factors made of items with
similar content These analyses reduced the initial pool of attitude items to
20 items that combined into six easily interpretable subscales that were
similar to those reported by Goldsmith (2000) The final analysis results
appear in Table II where the six factors represent the attitudes that shopping
on the Internet is fun safe cheap and quick and that the respondent had
confidence in hisher ability to shop online as well as the general
` enjoyment in shoppingrsquorsquo scale The scales are labeled FUN SAFE
CHEAP QUICK CONFIDENCE and SHOP The individual items were
summed to form short scales (see Table IV)
Next the Internet innovativeness and knowledge items were factor-analyzed
via common factor analysis which revealed that the items loaded on two
distinct factors indicating discriminant validity for these items (see Table
III) The individual items were summed to form two scales DSI and KNOW
Thus the focal variables in the study were amount of online buying
(PURCH) how often clothing was purchased by any means (MEANS) the
attitudes toward online buying (FUN SAFE CHEAP QUICK and
CONFIDENCE) attitude toward shopping (SHOP) Internet innovativeness
(DSI) and knowledge of the Internet (KNOW)
Cross-tabulation was used to assess the relationship between EVER (those
who had purchased apparel online versus those who had not) and sex and
race These analyses showed no statistically significant relationships
between these variables A t-test showed no statistically significant
difference in the mean age of those who had purchased apparel online versus
those who had not The correlations in Table IV provide internal evidence for
the validity of the measures The significant correlations of the DSI with
Scale itema Factor 1 Factor 2
Internet knowledge (KNOW)
When it comes to the Internet I really do not know a lotb 088
I know pretty much about the Internet 083
Compared with most other people I know less about the Internetb 082
I do not feel very knowledgeable about the Internetb 081
Among my circle of friends I am one of the ` expertsrsquorsquo on the
Internet 065
Internet innovativeness (DSI)
In general I am among the last in my circle of friends to purchase
something over the Internetb 081
Compared with my friends I do little shopping over the Internetb 079
In general I am the last in my circle of friends to know the names
of the latest places to shop on the Internetb 062
Eigenvalue 415 155
Percent of variance 518 194
Kaiser-Meyer-Olkin measure of sampling adequacy = 0865
Notes Only loadings gt 030 are shown a using a five-point agree-disagree responseformat b reverse-coded items
Table III Factor analysis of Internet knowledge and innovativeness items
Common factor analysis
Focal variables
94 JOURNAL OF PRODUCT amp BRAND MANAGEMENT VOL 11 NO 2 2002
Var
iable
sR
ange
Mea
nS
D1
23
45
67
89
10
11
12
13
14
15
16
1
Age
18-5
0226
49
plusmn
2
Sex
0-1
aplusmn
plusmn00
6plusmn
3
Ever
0-1
bplusmn
plusmn00
2plusmn00
5plusmn
4
Purc
hplusmn08
8-
86
80
10
00
801
804
2plusmn
5
Mea
ns
1-5
34
409
8plusmn01
1plusmn03
100
100
2plusmn
6
Fun
4-2
0105
27
00
801
603
505
600
2(0
74)c
7
Saf
e3-1
572
22
plusmn00
301
001
503
700
604
4(0
76)
8
Chea
p2-1
061
16
00
802
400
203
8plusmn00
804
402
9(0
75)
9
Quic
k3-1
593
27
01
000
901
702
9plusmn00
404
702
904
0(0
58)
10
Conf
4-2
0136
30
00
600
802
304
300
004
603
604
303
9(0
70)
11
Shop
4-2
0132
39
plusmn02
6plusmn04
500
5plusmn01
104
0plusmn01
6plusmn00
4plusmn02
1plusmn01
3plusmn01
6(0
86)
12
DS
I3-1
594
27
plusmn00
400
402
804
801
504
202
902
501
904
700
4(0
79)
13
Know
5-2
5184
40
plusmn00
000
801
102
800
602
601
201
601
704
9plusmn00
504
0(0
90)
14
Spen
d0-5
00
893
748
plusmn00
9plusmn02
200
300
604
3plusmn00
100
3plusmn00
8plusmn00
1plusmn00
103
001
300
1plusmn
15
Hours
1-6
35
10
01
101
101
803
600
403
101
602
001
603
4plusmn00
802
804
700
4plusmn
16
Lik
ely
1-5
32
11
00
801
203
306
700
405
904
003
503
704
6plusmn00
704
702
800
503
4plusmn
Note
sC
orr
elat
ions
of
00
9an
dla
rger
are
stat
isti
call
ysi
gnif
ican
tat
plt
00
5(t
wo-t
aile
d)
a1
=m
ale
and
0=
fem
ale
b1
=yes
and
0=
no
cco
effi
cien
tal
pha
inpar
enth
eses
Table
IV
Des
crip
tive
stati
stic
sand
corr
elati
ons
JOURNAL OF PRODUCT amp BRAND MANAGEMENT VOL 11 NO 2 2002 95
FUN SAFE CHEAP QUICK and CONFIDENCE are similar to those
reported by Goldsmith (2000) Moreover the correlation of the DSI with the
knowledge measure (r = 040) is comparable with that reported by Flynn et
al (2000)
An analysis was performed to assess the influence of age sex and race on the
dependent variables A MANCOVA with sex and race as the two
independent variables and age as a covariate was run with PURCH through
KNOW as the ten dependent variables The correlations in Table IV suggest
that age was only significantly correlated with shopping enjoyment and this
was confirmed by the results of the MANCOVA so age was no longer
incorporated in the analyses The results also showed no statistically
significant multivariate interaction between sex and race (F(33 1500) = 114
p = 0266) There was a statistically significant multivariate effect of race
(F(33 1500) = 162 p = 0014) but the only univariate differences were for
SAFE (p = 0033) where African-Americans rated the Internet as less safe
than whites and CHEAP (p = 0032) where the ` othersrsquorsquo rated the Internet as
cheaper than both whites and African-Americans These differences were
few and small in size and so race was no longer included in the analyses
The multivariate effect of sex was significant (F(11 498) = 48 p lt 0001)
Univariate tests showed that women reported purchasing apparel by any
means more often than men they spent more on apparel than men and they
enjoyed shopping more than men while the men reported purchasing more
online than the women and felt that the Internet was cheaper than the
women These differences suggest that sex should be included in the final
analysis of the differences between those who have purchased apparel online
and those who have not
For this analysis a 2 pound 2 (SEX pound EVER) MANOVA was run with the ten
dependent variables as before (see Table V) The interaction term was
Mean scoresa Observed
Dependent variables Men Women Fb p eta2 power
Univariate main effects for SEX
PURCH 0678 0126 308 lt 0000 0052 10
MEANS 306 375 378 lt 0000 0072 10
FUN 119 108 145 lt 0000 0025 0967
SAFE 77 73 29 0089 0005 0397
CHEAP 68 57 418 lt 0000 0070 10
QUICK 99 94 46 0032 0008 0576
CONFIDENT 145 139 35 0060 0006 0468
SHOP 115 148 687 lt 0000 0110 10
DSI 101 100 03 0601 0000 0082
KNOW 192 184 32 0074 0006 0431
Univariate main effects for EVER
H1 PURCH plusmn0184 0988 1391 lt 0000 0200 10
H2 MEANS 34 34 0075 0784 0000 0059
H3 FUN 101 127 879 lt 0000 0136 10
H4 SAFE 70 79 121 0001 0021 0934
H5 CHEAP 61 63 14 0245 0002 0213
H6 QUICK 92 102 197 lt 0000 0034 0993
H7 CONFIDENT 133 151 320 lt 0000 0054 10
H8 SHOP 130 133 0646 0422 0001 0126
H9 DSI 91 110 448 lt 0000 0074 10
H10 KNOW 182 194 78 0005 0014 0798
Notes a Estimated marginal means b df = 1558
Table V Comparisons of mean scores
Influence of age sex andrace
96 JOURNAL OF PRODUCT amp BRAND MANAGEMENT VOL 11 NO 2 2002
statistically significant (F(10 549) = 24 p = 001) Follow-up univariate
analyses showed that the interactions however were significant for only
two of the dependent variables For PURCH the amount of online buying
men reported buying more than women but men who had bought apparel
online reported buying disproportionately more online than women who
had bought apparel online The opposite effect was observed for MEANS
buying apparel by any means Women reported buying apparel by any
means more than men but men who had bought apparel online reported
buying disproportionately less apparel by any means than the women
online buyers
The multivariate main effect for SEX was significant (F(10 549) = 143
p lt 0001) In addition to significant main effect differences for PURCH and
MEANS women reported that they enjoyed shopping (SHOP) more than
men and men reported that they thought online buying was more fun
cheaper and quicker than the women These findings are similar to those
reported in other studies of online buying
The multivariate main effect for EVER whether a respondent had ever
bought apparel online was statistically significant (F(10 549) = 204
p lt 0001) The univariate analyses showed that compared with those who
had not bought apparel online those who had bought apparel online had
more experience purchasing online in general (PURCH) and thought that
buying over the Internet was more fun safer quicker and they were more
confident in their ability to buy online The online apparel buyers also were
more innovative and knowledgeable about the Internet than non-buyers
Thus H1 H3 H4 H6 H7 H9 and H10 were confirmed There were no
statistically significant differences in the self-reported apparel purchase
(MEANS) perceptions that online buying was cheaper (CHEAP) or in
shopping enjoyment (SHOP) Because Boxrsquos test of the equality of the
covariance matrices was significant (indicating that the covariance matrices
were not identical across the groups of respondents) and because Levenersquos
test of equality of error variances showed that the error variances of four of
the dependent variables were not equal thus violating the assumptions of
MANOVA (Huck and Cormier 1996 pp 313-15 374-7) a Mann-Whitney
non-parametric analysis was conducted testing whether the observations
from the two groups of online apparel buyers were equivalent in location
These analyses were consistent with the parametric tests
As a final analysis a 2 pound 2 (SEX pound EVER with age as a covariate)
MANCOVA was conducted comparing the buyers and non-buyers on three
additional variables These were
(1) the number of hours the respondent was online in an average week
(HOURS)
(2) the amount of reported spending on apparel (SPEND) and
(2) how likely the respondent was to buy online in the coming year
(LIKELY)
The results showed that men averaged more hours online per week than
women women spent more on apparel than men and the men were more
likely to shop online in the future than were the women Finally online
apparel buyers reported spending more time online and were more likely to
buy online in the future than non-buyers
Online apparel buyers
Additional variables
JOURNAL OF PRODUCT amp BRAND MANAGEMENT VOL 11 NO 2 2002 97
Discussion
The present study compared selected characteristics of consumers who had
purchased apparel online with those who had not The results showed that
online apparel buyers purchased online more often felt that online buying
was more fun safer and quicker than non-buyers Online apparel buyers
were more confident in their ability to buy online and were more innovative
and knowledgeable about the Internet than non-buyers Online apparel
buyers did not differ from non-buyers in their belief in how cheap buying
online is in their overall enjoyment of shopping or in how often they bought
apparel by any means Respondent demographics were also unrelated to
buying apparel online Online apparel buyers further differed from non-
buyers in that they spent more time online than non-buyers and were more
likely to buy online in the future than non-buyers These results reveal a
systematic pattern of psychological and behavioral factors that seem to
facilitate online apparel purchase
These findings confirm theoretical accounts of consumer behavior and
extend their generality into the new realm of cyber-commerce The findings
are consistent with other studies that show that favorable attitudes are related
to online buying From the methodological perspective the attitude measures
appear to be robust across studies and provide valid reliable
operationalizations of these constructs This should encourage researchers to
use them as standardized measures of e-commerce-related attitudes The
findings also confirm the reliability and validity of the innovativeness (DSI)
and knowledge scales consistent with a series of studies that have evidenced
their psychometric soundness (eg Flynn et al 2000 Goldsmith 2000)
The findings suggest that consumers are motivated to buy apparel online by a
combination of factors and that the special circumstances of e-commerce
make this a unique consumption activity Online apparel buyers obviously
must want and need clothing so this basic motivation partially underlies
their behavior They seem however to be motivated differentially by their
attitudes toward the Internet While online apparel buyers were clearly more
positive on the attitudinal and psychological characteristics they were no
more likely than non-buyers to shop for clothes by other means to enjoy
shopping in general or to spend money buying clothes That is they are not
disproportionately motivated by clothing as a product category or by interest
in shopping but by the perceived advantages of online buying and their
positive predisposition toward this mode of commerce
For managers the results suggest that their online buyers may be somewhat
different from their in-store customers and may represent new customers
Consumers who buy disproportionately more apparel likely enjoy shopping
and want the emotional and sensory pleasures of touching seeing and trying
on clothes (see Seckler 2000 Underhill 1999) Note the positive
intercorrelations in Table IV between spending on apparel and shopping
(r = 030) spending and buying by any means (043) and between shopping
and buying (040) None of these variables was correlated with amount of
online buying (PURCH) Online buyers in contrast appear to be motivated
by their positive attitudes toward the Internet Thus to attract apparel buyers
to Web sites e-marketers might focus on emphasizing the added advantages
of fun speed and safety They should first ensure that their sites are fun to
use load rapidly with prompt post-sale delivery of ordered merchandise and
are completely safe to use They might emphasize how different online
buying is and not pretend that it is the same as in-store shopping Joint or
cooperative strategies might display apparel online but suggest that a
Respondent demographics
Unique consumptionactivity
Positive attitudes
98 JOURNAL OF PRODUCT amp BRAND MANAGEMENT VOL 11 NO 2 2002
different experience could be had in the store where unique accessories or
combinations of clothes could be seen Online apparel buyers and non-
buyers did not differ in their perception that buying online is cheaper than
offline Thus Secklerrsquos (2000) argument that offering price discounts may be
a prime way to attract non-buyers is supported To attract new buyers onlineapparel e-tailers may have to change perceptions that online buying is unsafe
(see Robinson 2000) Web sites must be made simple and easy to use
because non-users are not very confident that they can buy online
successfully In-store demonstrations of online shopping might encourage
non-buyers to shop online As online apparel buying spreads beyond the
innovative and knowledgeable consumer to the less sophisticated shopper
apparel marketers should cater to their unique tastes abilities and habits
This is especially true since the results suggest that many online apparel
buyers will buy online again
The study is limited by the nature of the sample measures specificity and
time studied Lack of randomness in the sample limits generalizability of the
point and interval estimates to a larger population but since the main
purpose of the study was to test theoretical hypotheses about online buyingthis is a minor limitation (Calder et al 1981) No conclusions can be drawn
about concepts that might be related to online apparel buying but were not
measured and the results are limited to the measures employed Similarly
the focal topic was clothing in general and not a specific type (new fashion
sports clothes work clothes etc) Finally since e-commerce and online
consumer behavior are constantly changing phenomena the present study is
only a snapshot picture and not a longitudinal view
Advantages of the study lie in the large sample size and validity of the
measures used Future research should examine online apparel using data
from other demographic socio-economic and national groups of consumers
to expand the scope of the findings The online buyer behaviors studied
should be expanded beyond just buying to include browsing comparison
shopping and combining the Internet with in-store consumption as well asconsumption of specific categories of apparel such as new fashions or
unique sizes and needs As noted in the introduction growth is a major
theme of e-commerce Thus replication studies would be a valuable way to
track changes in online apparel buying over time Accumulation of such
studies would expand our knowledge of both apparel consumer behavior and
consumer Internet behavior to the advantage of both consumer theory and
apparel marketing Finally other researchers could make use of our measures
to study buying behavior in other areas as well
References
Calder BJ Phillips LW and Tybout AM (1981) ` Designing research for application rsquorsquo
Journal of Consumer Research Vol 8 September pp 197-207
Citrin AV Sprott DE Silveman SN and Stem DE Jr (2000) ` Adoption of Internet
shopping the role of consumer innovativenessrsquorsquo Industrial Management amp Data Systems
Vol 100 No 7 pp 294-300
Eastlick MA and Lotz S (1999) ` Profiling potential adopters and non-adopter s of an
interactive electronic shopping mediumrsquorsquo Internationa l Journal of Retail amp Distribution
Management Vol 27 No 6 pp 209-23
eMarketer (2000) ` The e-holiday shopping reportrsquorsquo available at wwwemarketercom
Flynn LR Goldsmith RE and Kim W (2000) ` A cross-cultural validation of three new
marketing scales for fashion research involvement opinion seeking and knowledgersquorsquo
The Journal of Fashion Marketing and Management Vol 4 No 2 pp 110-20
Goldsmith RE (2000) ` How innovativenes s differentiate s online buyersrsquorsquo Quarterly Journal
of Electronic Commerce Vol 1 No 4 pp 323-33
Snapshot picture
Expand the scope of thefindings
JOURNAL OF PRODUCT amp BRAND MANAGEMENT VOL 11 NO 2 2002 99
Goldsmith RE and Bridges E (2000) ` E-tailing vs retailing using attitudes to predict
online buying behavior rsquorsquo Quarterly Journal of Electronic Commerce Vol 1 No 3
pp 245-53
Goldsmith RE and Hofacker CF (1991) ` Measuring consumer innovativeness rsquorsquo Journal of
the Academy of Marketing Science Vol 19 No 3 pp 209-21
Goldsmith RE and McGregor S (1999) ` Electronic commerce an emerging issue in
consumer educationrsquorsquo Proceedings of XIX Internationa l Consumer Studies and Home
Economics Research Conference Belfast
Goldsmith RE and McGregor S (2000) ` E-commerce consumer protection issues and
implications for research and educationrsquorsquo Journal of Consumer Studies amp Home
Economics Vol 24 No 2 pp 124-7
Hair JF Anderson RE Tatham RL and Black WC (1998) Multivariate Data Analysis
5th ed Prentice-Hall Upper Saddle River NJ
Hallberg G (1995) All Consumers Are not Created Equal John Wiley New York NJ
Harvard Management Update (2000) ` Lessons from the online war for customersrsquorsquo
Harvard Management Update January pp 3-4
Hoffman DL and Novak TP (1996) ` Marketing in hypermedia computer-mediated
environments conceptua l foundationsrsquorsquo Journal of Marketing Vol 60 No 3 pp 153-61
Hogg MK Bruce M and Hill AJ (1998) ` Fashion brand preference s among young
consumersrsquorsquo Internationa l Journal of Retail amp Distribution Management Vol 26 No 8
pp 293-300
Huck SW and Cormier WH (1996) Reading Statistics and Research 2nd ed
HarperCollins College Publishers New York NY
Karson E (2000) ` Two dimensions of computer and Internet use a reliable and validated
scalersquorsquo Quarterly Journal of Electronic Commerce Vol 1 No 1 pp 49-60
Katz J and Aspden P (1997) ` Motivations for and barriers to Internet usage results of a
national public opinion surveyrsquorsquo Internet Research Vol 7 No 3 pp 170-88
Kuntz J (2000) ` Age and income play key roles in online salesrsquorsquo Daily News Record
27 March p 19
Limayem M Khalifa M and Frini A (2000) ` What makes consumers buy from the
Internet A longitudinal study of online shoppingrsquorsquo IEEE Transactions on Systems Man
and Cybernetics Part A Systems and Humans Vol 30 No 4 pp 421-32
Murphy R (1999) ` Download Internet news IIrsquorsquo The Journal of Fashion Marketing and
Management Vol 3 No 4 pp 376-7
Nelson J (2000) ` Internet at a glancersquorsquo Business 20 12 September p 279
OrsquoGuinn TC and Faber RJ (1989) ` Compulsive buying a phenomenologica l explorationrsquorsquo
Journal of Consumer Research Vol 16 No 2 pp 147-57
Robinson E (2000) ` Click and coverrsquorsquo Business 20 12 September pp 168-80
Seckler V (2000) ` Survey says Web apparel buys doubledrsquorsquo Womenrsquos Wear Daily 12 July
p 2
Silverman D (2000) ` More women wardrobe online than everrsquorsquo Womenrsquos Wear Daily
31 July p 20
Solomon MR (1999) Consumer Behavior Buying Having and Being 4th ed
Prentice-Hall Upper Saddle River NJ
UCLA (2000) ` The UCLA Internet report surveying the digital futurersquorsquo available at
wwwccpuclaedu
Underhill P (1999) Why We Buy The Science of Shopping Simon amp Schuster
New York NY
Vickery L and Agins T (2001) ` Retailers find Web apparel unprofitable rsquorsquo Wall Street
Journal 6 June p B6
Wilson J (1999) ` Keynote addressrsquorsquo The Journal of Fashion Marketing and Management
Vol 3 No 4 pp 370-6
amp
100 JOURNAL OF PRODUCT amp BRAND MANAGEMENT VOL 11 NO 2 2002
Executive summary and implications for managers andexecutives
Retailing online plusmn know your customer and learn from mail ordermarketingE-commerce and especially online retailing have received much attention agreat deal of thought and significant investment Despite this we still lackany clear understanding of the business models that can deliver successonline For every apparent e-retailing success we get a massive plusmn andusually very expensive plusmn failure We can say plusmn with some safety plusmn that theprospects for another Internet trading investment boom have gone
For marketers this situation is a disappointment We are after all theexperts on distribution and sales channels The failure to make e-retailingwork sits in our court and we continue to chew away at the e-commerce bonein the hope that it will eventually come good At the same time we haveraised questions about the capacity of the technology to deliver what wewant Doubts persist about the security of money transfers online Weak linksbetween real world distribution plusmn getting the product to the customer plusmn andthe cosy virtual world get in the way of seamless service And while gettingthe online equivalent of footfall is easy converting these visitors tocustomers is a massive challenge
Know your customer plusmn the marketerrsquos mantraGoldsmith and Goldsmith observe that while a great deal is said aboutonline processes technology and promotion little is known about the actualonline customer We know too little about the differences between theenthusiastic innovators who buy goods online and the rest who are happy tolook but do not buy
The difference between ` innovatorsrsquorsquo and ` early adoptersrsquorsquo is wellresearched and in general terms understood by marketers E-retailing hasnot taken off because the chasm between these two groups remainsunbridged As a result the apparent mass market for e-commerce remains afuture dream Two-thirds of Americans might have access to the Internet butthey are not using it to buy things plusmn at least not in sufficient numbers
Goldsmith and Goldsmith set out to compare clothes buyers who havebought online with those who have not made this sort of purchaseUnderlying the study is the assumption (supported by research and largelycommon sense) that ` consumers who have previous experience in onlinebuying will be more likely to buy apparel online than those who lack suchexperiencersquorsquo We should also note like Goldsmith and Goldsmith that thepeople who matter to e-retailers are those very similar to existing users whoat present are non-users
Are you frightened of the WebGoldsmith and Goldsmith find that there are substantial differences betweene-buyers and the rest of humanity (I always knew that Web enthusiasts werestrange) Some of these differences are pretty prosaic plusmn online buyers havefewer security worries appreciate the ` quicknessrsquorsquo and flexibility of onlinebuying and see the Web as making buying easier However the other (morepsychological) factors suggest that these preferences are symptomatic of thetype rather than definitional The remainder of Goldsmith and Goldsmithrsquosfindings throw up words like ` confidentrsquorsquo ` innovativersquorsquo ` knowledgeablersquorsquoand ` funrsquorsquo Our e-buyers take the view that ` the special circumstancesof e-commerce make this a unique consumption activityrsquorsquo These people aredifferent and we need to know why and at the same time to understand theresistance of others to e-commerce
Part of the resistance appears to lie in fear (characterised as being a lack ofconfidence) People who do not buy online do not have a great deal of trust in
JOURNAL OF PRODUCT amp BRAND MANAGEMENT VOL 11 NO 2 2002 101
This summary has beenprovided to allow managersand executives a rapidappreciation of the contentof this article Those with aparticular interest in thetopic covered may then readthe article in toto to takeadvantage of the morecomprehensive descriptionof the research undertakenand its results to get the fullbenefit of the materialpresent
the medium This seems to hold true even when they use the Internet for avariety of other activities (information gathering communications games etc)Until these issues of fear (or trust or confidence) are dealt with marketers willstruggle to take the idea of e-commerce into the mainstream of retailing
Removing the fearTwo elements are involved in removing consumer distrust of e-commerceThe first is more confidence with the technology involved in buying onlineBear in mind that most of us who use computers take advantage of a tiny partof the capacity of even basic software Even with comprehensible manualson-screen and online help and ` idiot guidesrsquorsquo we still stick to basicprocessing
Ease-of-use is fundamental to successful e-retailing and so far we havefailed to achieve sufficiently easy systems to remove the consumerrsquos worryabout getting it wrong But this is just one problem and its solution lies asmuch in the relationship between the ordinary consumer and Internettechnology as in specific marketing actions
The second element is purely promotional and is about securing trial andreducing the distrust E-commerce becomes accessible when these barriersare removed and there are many techniques available that marketers canuse
Mail order and direct marketers have always faced resistance to theirchannel Indeed mail order people appreciate that there remains a largechunk of the population that will never buy mail order whatever theincentive Nevertheless these marketers have developed (and tested) avariety of simple techniques to secure trial and build confidence
product and service guarantees
payment on delivery rather than payment with the order
featuring low-risk entry products
no-quibble return policies
product endorsement plusmn by real customers
testimonials and
prize draws free gifts and other order incentives
E-commerce represents a new channel and for some businesses a differentmeans of delivering product But for most businesses and especiallyretailers the Internet does not change the nature of the product itself (a pairof shorts remains a pair of shorts) Rather than reinventing the wheel e-retailers should learn from direct marketers
E-commerce needs more confidence to sell itself successfully but in the finalanalysis the e-retailer does little that is different from the mail ordercompany And the direct marketer knows that profits come from repeatbusiness rather than from the first sale Too many e-commerce operationshave floundered because they ignored the experience of others and tried torun a business without good databases or the strategies to sustain incomefrom existing buyers
Do you want your e-retailing business to succeed Hire an experience directmarketer and you will stand a better than average chance of successPretending that the e-marketers have nothing to learn from old grizzled (andboring) mail order people is a mistake that is probably costing you money
(A preAcirccis of the article ` Buying apparel over the Internetrsquorsquo Supplied byMarketing Consultants for Emerald)
102 JOURNAL OF PRODUCT amp BRAND MANAGEMENT VOL 11 NO 2 2002
Var
iable
sR
ange
Mea
nS
D1
23
45
67
89
10
11
12
13
14
15
16
1
Age
18-5
0226
49
plusmn
2
Sex
0-1
aplusmn
plusmn00
6plusmn
3
Ever
0-1
bplusmn
plusmn00
2plusmn00
5plusmn
4
Purc
hplusmn08
8-
86
80
10
00
801
804
2plusmn
5
Mea
ns
1-5
34
409
8plusmn01
1plusmn03
100
100
2plusmn
6
Fun
4-2
0105
27
00
801
603
505
600
2(0
74)c
7
Saf
e3-1
572
22
plusmn00
301
001
503
700
604
4(0
76)
8
Chea
p2-1
061
16
00
802
400
203
8plusmn00
804
402
9(0
75)
9
Quic
k3-1
593
27
01
000
901
702
9plusmn00
404
702
904
0(0
58)
10
Conf
4-2
0136
30
00
600
802
304
300
004
603
604
303
9(0
70)
11
Shop
4-2
0132
39
plusmn02
6plusmn04
500
5plusmn01
104
0plusmn01
6plusmn00
4plusmn02
1plusmn01
3plusmn01
6(0
86)
12
DS
I3-1
594
27
plusmn00
400
402
804
801
504
202
902
501
904
700
4(0
79)
13
Know
5-2
5184
40
plusmn00
000
801
102
800
602
601
201
601
704
9plusmn00
504
0(0
90)
14
Spen
d0-5
00
893
748
plusmn00
9plusmn02
200
300
604
3plusmn00
100
3plusmn00
8plusmn00
1plusmn00
103
001
300
1plusmn
15
Hours
1-6
35
10
01
101
101
803
600
403
101
602
001
603
4plusmn00
802
804
700
4plusmn
16
Lik
ely
1-5
32
11
00
801
203
306
700
405
904
003
503
704
6plusmn00
704
702
800
503
4plusmn
Note
sC
orr
elat
ions
of
00
9an
dla
rger
are
stat
isti
call
ysi
gnif
ican
tat
plt
00
5(t
wo-t
aile
d)
a1
=m
ale
and
0=
fem
ale
b1
=yes
and
0=
no
cco
effi
cien
tal
pha
inpar
enth
eses
Table
IV
Des
crip
tive
stati
stic
sand
corr
elati
ons
JOURNAL OF PRODUCT amp BRAND MANAGEMENT VOL 11 NO 2 2002 95
FUN SAFE CHEAP QUICK and CONFIDENCE are similar to those
reported by Goldsmith (2000) Moreover the correlation of the DSI with the
knowledge measure (r = 040) is comparable with that reported by Flynn et
al (2000)
An analysis was performed to assess the influence of age sex and race on the
dependent variables A MANCOVA with sex and race as the two
independent variables and age as a covariate was run with PURCH through
KNOW as the ten dependent variables The correlations in Table IV suggest
that age was only significantly correlated with shopping enjoyment and this
was confirmed by the results of the MANCOVA so age was no longer
incorporated in the analyses The results also showed no statistically
significant multivariate interaction between sex and race (F(33 1500) = 114
p = 0266) There was a statistically significant multivariate effect of race
(F(33 1500) = 162 p = 0014) but the only univariate differences were for
SAFE (p = 0033) where African-Americans rated the Internet as less safe
than whites and CHEAP (p = 0032) where the ` othersrsquorsquo rated the Internet as
cheaper than both whites and African-Americans These differences were
few and small in size and so race was no longer included in the analyses
The multivariate effect of sex was significant (F(11 498) = 48 p lt 0001)
Univariate tests showed that women reported purchasing apparel by any
means more often than men they spent more on apparel than men and they
enjoyed shopping more than men while the men reported purchasing more
online than the women and felt that the Internet was cheaper than the
women These differences suggest that sex should be included in the final
analysis of the differences between those who have purchased apparel online
and those who have not
For this analysis a 2 pound 2 (SEX pound EVER) MANOVA was run with the ten
dependent variables as before (see Table V) The interaction term was
Mean scoresa Observed
Dependent variables Men Women Fb p eta2 power
Univariate main effects for SEX
PURCH 0678 0126 308 lt 0000 0052 10
MEANS 306 375 378 lt 0000 0072 10
FUN 119 108 145 lt 0000 0025 0967
SAFE 77 73 29 0089 0005 0397
CHEAP 68 57 418 lt 0000 0070 10
QUICK 99 94 46 0032 0008 0576
CONFIDENT 145 139 35 0060 0006 0468
SHOP 115 148 687 lt 0000 0110 10
DSI 101 100 03 0601 0000 0082
KNOW 192 184 32 0074 0006 0431
Univariate main effects for EVER
H1 PURCH plusmn0184 0988 1391 lt 0000 0200 10
H2 MEANS 34 34 0075 0784 0000 0059
H3 FUN 101 127 879 lt 0000 0136 10
H4 SAFE 70 79 121 0001 0021 0934
H5 CHEAP 61 63 14 0245 0002 0213
H6 QUICK 92 102 197 lt 0000 0034 0993
H7 CONFIDENT 133 151 320 lt 0000 0054 10
H8 SHOP 130 133 0646 0422 0001 0126
H9 DSI 91 110 448 lt 0000 0074 10
H10 KNOW 182 194 78 0005 0014 0798
Notes a Estimated marginal means b df = 1558
Table V Comparisons of mean scores
Influence of age sex andrace
96 JOURNAL OF PRODUCT amp BRAND MANAGEMENT VOL 11 NO 2 2002
statistically significant (F(10 549) = 24 p = 001) Follow-up univariate
analyses showed that the interactions however were significant for only
two of the dependent variables For PURCH the amount of online buying
men reported buying more than women but men who had bought apparel
online reported buying disproportionately more online than women who
had bought apparel online The opposite effect was observed for MEANS
buying apparel by any means Women reported buying apparel by any
means more than men but men who had bought apparel online reported
buying disproportionately less apparel by any means than the women
online buyers
The multivariate main effect for SEX was significant (F(10 549) = 143
p lt 0001) In addition to significant main effect differences for PURCH and
MEANS women reported that they enjoyed shopping (SHOP) more than
men and men reported that they thought online buying was more fun
cheaper and quicker than the women These findings are similar to those
reported in other studies of online buying
The multivariate main effect for EVER whether a respondent had ever
bought apparel online was statistically significant (F(10 549) = 204
p lt 0001) The univariate analyses showed that compared with those who
had not bought apparel online those who had bought apparel online had
more experience purchasing online in general (PURCH) and thought that
buying over the Internet was more fun safer quicker and they were more
confident in their ability to buy online The online apparel buyers also were
more innovative and knowledgeable about the Internet than non-buyers
Thus H1 H3 H4 H6 H7 H9 and H10 were confirmed There were no
statistically significant differences in the self-reported apparel purchase
(MEANS) perceptions that online buying was cheaper (CHEAP) or in
shopping enjoyment (SHOP) Because Boxrsquos test of the equality of the
covariance matrices was significant (indicating that the covariance matrices
were not identical across the groups of respondents) and because Levenersquos
test of equality of error variances showed that the error variances of four of
the dependent variables were not equal thus violating the assumptions of
MANOVA (Huck and Cormier 1996 pp 313-15 374-7) a Mann-Whitney
non-parametric analysis was conducted testing whether the observations
from the two groups of online apparel buyers were equivalent in location
These analyses were consistent with the parametric tests
As a final analysis a 2 pound 2 (SEX pound EVER with age as a covariate)
MANCOVA was conducted comparing the buyers and non-buyers on three
additional variables These were
(1) the number of hours the respondent was online in an average week
(HOURS)
(2) the amount of reported spending on apparel (SPEND) and
(2) how likely the respondent was to buy online in the coming year
(LIKELY)
The results showed that men averaged more hours online per week than
women women spent more on apparel than men and the men were more
likely to shop online in the future than were the women Finally online
apparel buyers reported spending more time online and were more likely to
buy online in the future than non-buyers
Online apparel buyers
Additional variables
JOURNAL OF PRODUCT amp BRAND MANAGEMENT VOL 11 NO 2 2002 97
Discussion
The present study compared selected characteristics of consumers who had
purchased apparel online with those who had not The results showed that
online apparel buyers purchased online more often felt that online buying
was more fun safer and quicker than non-buyers Online apparel buyers
were more confident in their ability to buy online and were more innovative
and knowledgeable about the Internet than non-buyers Online apparel
buyers did not differ from non-buyers in their belief in how cheap buying
online is in their overall enjoyment of shopping or in how often they bought
apparel by any means Respondent demographics were also unrelated to
buying apparel online Online apparel buyers further differed from non-
buyers in that they spent more time online than non-buyers and were more
likely to buy online in the future than non-buyers These results reveal a
systematic pattern of psychological and behavioral factors that seem to
facilitate online apparel purchase
These findings confirm theoretical accounts of consumer behavior and
extend their generality into the new realm of cyber-commerce The findings
are consistent with other studies that show that favorable attitudes are related
to online buying From the methodological perspective the attitude measures
appear to be robust across studies and provide valid reliable
operationalizations of these constructs This should encourage researchers to
use them as standardized measures of e-commerce-related attitudes The
findings also confirm the reliability and validity of the innovativeness (DSI)
and knowledge scales consistent with a series of studies that have evidenced
their psychometric soundness (eg Flynn et al 2000 Goldsmith 2000)
The findings suggest that consumers are motivated to buy apparel online by a
combination of factors and that the special circumstances of e-commerce
make this a unique consumption activity Online apparel buyers obviously
must want and need clothing so this basic motivation partially underlies
their behavior They seem however to be motivated differentially by their
attitudes toward the Internet While online apparel buyers were clearly more
positive on the attitudinal and psychological characteristics they were no
more likely than non-buyers to shop for clothes by other means to enjoy
shopping in general or to spend money buying clothes That is they are not
disproportionately motivated by clothing as a product category or by interest
in shopping but by the perceived advantages of online buying and their
positive predisposition toward this mode of commerce
For managers the results suggest that their online buyers may be somewhat
different from their in-store customers and may represent new customers
Consumers who buy disproportionately more apparel likely enjoy shopping
and want the emotional and sensory pleasures of touching seeing and trying
on clothes (see Seckler 2000 Underhill 1999) Note the positive
intercorrelations in Table IV between spending on apparel and shopping
(r = 030) spending and buying by any means (043) and between shopping
and buying (040) None of these variables was correlated with amount of
online buying (PURCH) Online buyers in contrast appear to be motivated
by their positive attitudes toward the Internet Thus to attract apparel buyers
to Web sites e-marketers might focus on emphasizing the added advantages
of fun speed and safety They should first ensure that their sites are fun to
use load rapidly with prompt post-sale delivery of ordered merchandise and
are completely safe to use They might emphasize how different online
buying is and not pretend that it is the same as in-store shopping Joint or
cooperative strategies might display apparel online but suggest that a
Respondent demographics
Unique consumptionactivity
Positive attitudes
98 JOURNAL OF PRODUCT amp BRAND MANAGEMENT VOL 11 NO 2 2002
different experience could be had in the store where unique accessories or
combinations of clothes could be seen Online apparel buyers and non-
buyers did not differ in their perception that buying online is cheaper than
offline Thus Secklerrsquos (2000) argument that offering price discounts may be
a prime way to attract non-buyers is supported To attract new buyers onlineapparel e-tailers may have to change perceptions that online buying is unsafe
(see Robinson 2000) Web sites must be made simple and easy to use
because non-users are not very confident that they can buy online
successfully In-store demonstrations of online shopping might encourage
non-buyers to shop online As online apparel buying spreads beyond the
innovative and knowledgeable consumer to the less sophisticated shopper
apparel marketers should cater to their unique tastes abilities and habits
This is especially true since the results suggest that many online apparel
buyers will buy online again
The study is limited by the nature of the sample measures specificity and
time studied Lack of randomness in the sample limits generalizability of the
point and interval estimates to a larger population but since the main
purpose of the study was to test theoretical hypotheses about online buyingthis is a minor limitation (Calder et al 1981) No conclusions can be drawn
about concepts that might be related to online apparel buying but were not
measured and the results are limited to the measures employed Similarly
the focal topic was clothing in general and not a specific type (new fashion
sports clothes work clothes etc) Finally since e-commerce and online
consumer behavior are constantly changing phenomena the present study is
only a snapshot picture and not a longitudinal view
Advantages of the study lie in the large sample size and validity of the
measures used Future research should examine online apparel using data
from other demographic socio-economic and national groups of consumers
to expand the scope of the findings The online buyer behaviors studied
should be expanded beyond just buying to include browsing comparison
shopping and combining the Internet with in-store consumption as well asconsumption of specific categories of apparel such as new fashions or
unique sizes and needs As noted in the introduction growth is a major
theme of e-commerce Thus replication studies would be a valuable way to
track changes in online apparel buying over time Accumulation of such
studies would expand our knowledge of both apparel consumer behavior and
consumer Internet behavior to the advantage of both consumer theory and
apparel marketing Finally other researchers could make use of our measures
to study buying behavior in other areas as well
References
Calder BJ Phillips LW and Tybout AM (1981) ` Designing research for application rsquorsquo
Journal of Consumer Research Vol 8 September pp 197-207
Citrin AV Sprott DE Silveman SN and Stem DE Jr (2000) ` Adoption of Internet
shopping the role of consumer innovativenessrsquorsquo Industrial Management amp Data Systems
Vol 100 No 7 pp 294-300
Eastlick MA and Lotz S (1999) ` Profiling potential adopters and non-adopter s of an
interactive electronic shopping mediumrsquorsquo Internationa l Journal of Retail amp Distribution
Management Vol 27 No 6 pp 209-23
eMarketer (2000) ` The e-holiday shopping reportrsquorsquo available at wwwemarketercom
Flynn LR Goldsmith RE and Kim W (2000) ` A cross-cultural validation of three new
marketing scales for fashion research involvement opinion seeking and knowledgersquorsquo
The Journal of Fashion Marketing and Management Vol 4 No 2 pp 110-20
Goldsmith RE (2000) ` How innovativenes s differentiate s online buyersrsquorsquo Quarterly Journal
of Electronic Commerce Vol 1 No 4 pp 323-33
Snapshot picture
Expand the scope of thefindings
JOURNAL OF PRODUCT amp BRAND MANAGEMENT VOL 11 NO 2 2002 99
Goldsmith RE and Bridges E (2000) ` E-tailing vs retailing using attitudes to predict
online buying behavior rsquorsquo Quarterly Journal of Electronic Commerce Vol 1 No 3
pp 245-53
Goldsmith RE and Hofacker CF (1991) ` Measuring consumer innovativeness rsquorsquo Journal of
the Academy of Marketing Science Vol 19 No 3 pp 209-21
Goldsmith RE and McGregor S (1999) ` Electronic commerce an emerging issue in
consumer educationrsquorsquo Proceedings of XIX Internationa l Consumer Studies and Home
Economics Research Conference Belfast
Goldsmith RE and McGregor S (2000) ` E-commerce consumer protection issues and
implications for research and educationrsquorsquo Journal of Consumer Studies amp Home
Economics Vol 24 No 2 pp 124-7
Hair JF Anderson RE Tatham RL and Black WC (1998) Multivariate Data Analysis
5th ed Prentice-Hall Upper Saddle River NJ
Hallberg G (1995) All Consumers Are not Created Equal John Wiley New York NJ
Harvard Management Update (2000) ` Lessons from the online war for customersrsquorsquo
Harvard Management Update January pp 3-4
Hoffman DL and Novak TP (1996) ` Marketing in hypermedia computer-mediated
environments conceptua l foundationsrsquorsquo Journal of Marketing Vol 60 No 3 pp 153-61
Hogg MK Bruce M and Hill AJ (1998) ` Fashion brand preference s among young
consumersrsquorsquo Internationa l Journal of Retail amp Distribution Management Vol 26 No 8
pp 293-300
Huck SW and Cormier WH (1996) Reading Statistics and Research 2nd ed
HarperCollins College Publishers New York NY
Karson E (2000) ` Two dimensions of computer and Internet use a reliable and validated
scalersquorsquo Quarterly Journal of Electronic Commerce Vol 1 No 1 pp 49-60
Katz J and Aspden P (1997) ` Motivations for and barriers to Internet usage results of a
national public opinion surveyrsquorsquo Internet Research Vol 7 No 3 pp 170-88
Kuntz J (2000) ` Age and income play key roles in online salesrsquorsquo Daily News Record
27 March p 19
Limayem M Khalifa M and Frini A (2000) ` What makes consumers buy from the
Internet A longitudinal study of online shoppingrsquorsquo IEEE Transactions on Systems Man
and Cybernetics Part A Systems and Humans Vol 30 No 4 pp 421-32
Murphy R (1999) ` Download Internet news IIrsquorsquo The Journal of Fashion Marketing and
Management Vol 3 No 4 pp 376-7
Nelson J (2000) ` Internet at a glancersquorsquo Business 20 12 September p 279
OrsquoGuinn TC and Faber RJ (1989) ` Compulsive buying a phenomenologica l explorationrsquorsquo
Journal of Consumer Research Vol 16 No 2 pp 147-57
Robinson E (2000) ` Click and coverrsquorsquo Business 20 12 September pp 168-80
Seckler V (2000) ` Survey says Web apparel buys doubledrsquorsquo Womenrsquos Wear Daily 12 July
p 2
Silverman D (2000) ` More women wardrobe online than everrsquorsquo Womenrsquos Wear Daily
31 July p 20
Solomon MR (1999) Consumer Behavior Buying Having and Being 4th ed
Prentice-Hall Upper Saddle River NJ
UCLA (2000) ` The UCLA Internet report surveying the digital futurersquorsquo available at
wwwccpuclaedu
Underhill P (1999) Why We Buy The Science of Shopping Simon amp Schuster
New York NY
Vickery L and Agins T (2001) ` Retailers find Web apparel unprofitable rsquorsquo Wall Street
Journal 6 June p B6
Wilson J (1999) ` Keynote addressrsquorsquo The Journal of Fashion Marketing and Management
Vol 3 No 4 pp 370-6
amp
100 JOURNAL OF PRODUCT amp BRAND MANAGEMENT VOL 11 NO 2 2002
Executive summary and implications for managers andexecutives
Retailing online plusmn know your customer and learn from mail ordermarketingE-commerce and especially online retailing have received much attention agreat deal of thought and significant investment Despite this we still lackany clear understanding of the business models that can deliver successonline For every apparent e-retailing success we get a massive plusmn andusually very expensive plusmn failure We can say plusmn with some safety plusmn that theprospects for another Internet trading investment boom have gone
For marketers this situation is a disappointment We are after all theexperts on distribution and sales channels The failure to make e-retailingwork sits in our court and we continue to chew away at the e-commerce bonein the hope that it will eventually come good At the same time we haveraised questions about the capacity of the technology to deliver what wewant Doubts persist about the security of money transfers online Weak linksbetween real world distribution plusmn getting the product to the customer plusmn andthe cosy virtual world get in the way of seamless service And while gettingthe online equivalent of footfall is easy converting these visitors tocustomers is a massive challenge
Know your customer plusmn the marketerrsquos mantraGoldsmith and Goldsmith observe that while a great deal is said aboutonline processes technology and promotion little is known about the actualonline customer We know too little about the differences between theenthusiastic innovators who buy goods online and the rest who are happy tolook but do not buy
The difference between ` innovatorsrsquorsquo and ` early adoptersrsquorsquo is wellresearched and in general terms understood by marketers E-retailing hasnot taken off because the chasm between these two groups remainsunbridged As a result the apparent mass market for e-commerce remains afuture dream Two-thirds of Americans might have access to the Internet butthey are not using it to buy things plusmn at least not in sufficient numbers
Goldsmith and Goldsmith set out to compare clothes buyers who havebought online with those who have not made this sort of purchaseUnderlying the study is the assumption (supported by research and largelycommon sense) that ` consumers who have previous experience in onlinebuying will be more likely to buy apparel online than those who lack suchexperiencersquorsquo We should also note like Goldsmith and Goldsmith that thepeople who matter to e-retailers are those very similar to existing users whoat present are non-users
Are you frightened of the WebGoldsmith and Goldsmith find that there are substantial differences betweene-buyers and the rest of humanity (I always knew that Web enthusiasts werestrange) Some of these differences are pretty prosaic plusmn online buyers havefewer security worries appreciate the ` quicknessrsquorsquo and flexibility of onlinebuying and see the Web as making buying easier However the other (morepsychological) factors suggest that these preferences are symptomatic of thetype rather than definitional The remainder of Goldsmith and Goldsmithrsquosfindings throw up words like ` confidentrsquorsquo ` innovativersquorsquo ` knowledgeablersquorsquoand ` funrsquorsquo Our e-buyers take the view that ` the special circumstancesof e-commerce make this a unique consumption activityrsquorsquo These people aredifferent and we need to know why and at the same time to understand theresistance of others to e-commerce
Part of the resistance appears to lie in fear (characterised as being a lack ofconfidence) People who do not buy online do not have a great deal of trust in
JOURNAL OF PRODUCT amp BRAND MANAGEMENT VOL 11 NO 2 2002 101
This summary has beenprovided to allow managersand executives a rapidappreciation of the contentof this article Those with aparticular interest in thetopic covered may then readthe article in toto to takeadvantage of the morecomprehensive descriptionof the research undertakenand its results to get the fullbenefit of the materialpresent
the medium This seems to hold true even when they use the Internet for avariety of other activities (information gathering communications games etc)Until these issues of fear (or trust or confidence) are dealt with marketers willstruggle to take the idea of e-commerce into the mainstream of retailing
Removing the fearTwo elements are involved in removing consumer distrust of e-commerceThe first is more confidence with the technology involved in buying onlineBear in mind that most of us who use computers take advantage of a tiny partof the capacity of even basic software Even with comprehensible manualson-screen and online help and ` idiot guidesrsquorsquo we still stick to basicprocessing
Ease-of-use is fundamental to successful e-retailing and so far we havefailed to achieve sufficiently easy systems to remove the consumerrsquos worryabout getting it wrong But this is just one problem and its solution lies asmuch in the relationship between the ordinary consumer and Internettechnology as in specific marketing actions
The second element is purely promotional and is about securing trial andreducing the distrust E-commerce becomes accessible when these barriersare removed and there are many techniques available that marketers canuse
Mail order and direct marketers have always faced resistance to theirchannel Indeed mail order people appreciate that there remains a largechunk of the population that will never buy mail order whatever theincentive Nevertheless these marketers have developed (and tested) avariety of simple techniques to secure trial and build confidence
product and service guarantees
payment on delivery rather than payment with the order
featuring low-risk entry products
no-quibble return policies
product endorsement plusmn by real customers
testimonials and
prize draws free gifts and other order incentives
E-commerce represents a new channel and for some businesses a differentmeans of delivering product But for most businesses and especiallyretailers the Internet does not change the nature of the product itself (a pairof shorts remains a pair of shorts) Rather than reinventing the wheel e-retailers should learn from direct marketers
E-commerce needs more confidence to sell itself successfully but in the finalanalysis the e-retailer does little that is different from the mail ordercompany And the direct marketer knows that profits come from repeatbusiness rather than from the first sale Too many e-commerce operationshave floundered because they ignored the experience of others and tried torun a business without good databases or the strategies to sustain incomefrom existing buyers
Do you want your e-retailing business to succeed Hire an experience directmarketer and you will stand a better than average chance of successPretending that the e-marketers have nothing to learn from old grizzled (andboring) mail order people is a mistake that is probably costing you money
(A preAcirccis of the article ` Buying apparel over the Internetrsquorsquo Supplied byMarketing Consultants for Emerald)
102 JOURNAL OF PRODUCT amp BRAND MANAGEMENT VOL 11 NO 2 2002
FUN SAFE CHEAP QUICK and CONFIDENCE are similar to those
reported by Goldsmith (2000) Moreover the correlation of the DSI with the
knowledge measure (r = 040) is comparable with that reported by Flynn et
al (2000)
An analysis was performed to assess the influence of age sex and race on the
dependent variables A MANCOVA with sex and race as the two
independent variables and age as a covariate was run with PURCH through
KNOW as the ten dependent variables The correlations in Table IV suggest
that age was only significantly correlated with shopping enjoyment and this
was confirmed by the results of the MANCOVA so age was no longer
incorporated in the analyses The results also showed no statistically
significant multivariate interaction between sex and race (F(33 1500) = 114
p = 0266) There was a statistically significant multivariate effect of race
(F(33 1500) = 162 p = 0014) but the only univariate differences were for
SAFE (p = 0033) where African-Americans rated the Internet as less safe
than whites and CHEAP (p = 0032) where the ` othersrsquorsquo rated the Internet as
cheaper than both whites and African-Americans These differences were
few and small in size and so race was no longer included in the analyses
The multivariate effect of sex was significant (F(11 498) = 48 p lt 0001)
Univariate tests showed that women reported purchasing apparel by any
means more often than men they spent more on apparel than men and they
enjoyed shopping more than men while the men reported purchasing more
online than the women and felt that the Internet was cheaper than the
women These differences suggest that sex should be included in the final
analysis of the differences between those who have purchased apparel online
and those who have not
For this analysis a 2 pound 2 (SEX pound EVER) MANOVA was run with the ten
dependent variables as before (see Table V) The interaction term was
Mean scoresa Observed
Dependent variables Men Women Fb p eta2 power
Univariate main effects for SEX
PURCH 0678 0126 308 lt 0000 0052 10
MEANS 306 375 378 lt 0000 0072 10
FUN 119 108 145 lt 0000 0025 0967
SAFE 77 73 29 0089 0005 0397
CHEAP 68 57 418 lt 0000 0070 10
QUICK 99 94 46 0032 0008 0576
CONFIDENT 145 139 35 0060 0006 0468
SHOP 115 148 687 lt 0000 0110 10
DSI 101 100 03 0601 0000 0082
KNOW 192 184 32 0074 0006 0431
Univariate main effects for EVER
H1 PURCH plusmn0184 0988 1391 lt 0000 0200 10
H2 MEANS 34 34 0075 0784 0000 0059
H3 FUN 101 127 879 lt 0000 0136 10
H4 SAFE 70 79 121 0001 0021 0934
H5 CHEAP 61 63 14 0245 0002 0213
H6 QUICK 92 102 197 lt 0000 0034 0993
H7 CONFIDENT 133 151 320 lt 0000 0054 10
H8 SHOP 130 133 0646 0422 0001 0126
H9 DSI 91 110 448 lt 0000 0074 10
H10 KNOW 182 194 78 0005 0014 0798
Notes a Estimated marginal means b df = 1558
Table V Comparisons of mean scores
Influence of age sex andrace
96 JOURNAL OF PRODUCT amp BRAND MANAGEMENT VOL 11 NO 2 2002
statistically significant (F(10 549) = 24 p = 001) Follow-up univariate
analyses showed that the interactions however were significant for only
two of the dependent variables For PURCH the amount of online buying
men reported buying more than women but men who had bought apparel
online reported buying disproportionately more online than women who
had bought apparel online The opposite effect was observed for MEANS
buying apparel by any means Women reported buying apparel by any
means more than men but men who had bought apparel online reported
buying disproportionately less apparel by any means than the women
online buyers
The multivariate main effect for SEX was significant (F(10 549) = 143
p lt 0001) In addition to significant main effect differences for PURCH and
MEANS women reported that they enjoyed shopping (SHOP) more than
men and men reported that they thought online buying was more fun
cheaper and quicker than the women These findings are similar to those
reported in other studies of online buying
The multivariate main effect for EVER whether a respondent had ever
bought apparel online was statistically significant (F(10 549) = 204
p lt 0001) The univariate analyses showed that compared with those who
had not bought apparel online those who had bought apparel online had
more experience purchasing online in general (PURCH) and thought that
buying over the Internet was more fun safer quicker and they were more
confident in their ability to buy online The online apparel buyers also were
more innovative and knowledgeable about the Internet than non-buyers
Thus H1 H3 H4 H6 H7 H9 and H10 were confirmed There were no
statistically significant differences in the self-reported apparel purchase
(MEANS) perceptions that online buying was cheaper (CHEAP) or in
shopping enjoyment (SHOP) Because Boxrsquos test of the equality of the
covariance matrices was significant (indicating that the covariance matrices
were not identical across the groups of respondents) and because Levenersquos
test of equality of error variances showed that the error variances of four of
the dependent variables were not equal thus violating the assumptions of
MANOVA (Huck and Cormier 1996 pp 313-15 374-7) a Mann-Whitney
non-parametric analysis was conducted testing whether the observations
from the two groups of online apparel buyers were equivalent in location
These analyses were consistent with the parametric tests
As a final analysis a 2 pound 2 (SEX pound EVER with age as a covariate)
MANCOVA was conducted comparing the buyers and non-buyers on three
additional variables These were
(1) the number of hours the respondent was online in an average week
(HOURS)
(2) the amount of reported spending on apparel (SPEND) and
(2) how likely the respondent was to buy online in the coming year
(LIKELY)
The results showed that men averaged more hours online per week than
women women spent more on apparel than men and the men were more
likely to shop online in the future than were the women Finally online
apparel buyers reported spending more time online and were more likely to
buy online in the future than non-buyers
Online apparel buyers
Additional variables
JOURNAL OF PRODUCT amp BRAND MANAGEMENT VOL 11 NO 2 2002 97
Discussion
The present study compared selected characteristics of consumers who had
purchased apparel online with those who had not The results showed that
online apparel buyers purchased online more often felt that online buying
was more fun safer and quicker than non-buyers Online apparel buyers
were more confident in their ability to buy online and were more innovative
and knowledgeable about the Internet than non-buyers Online apparel
buyers did not differ from non-buyers in their belief in how cheap buying
online is in their overall enjoyment of shopping or in how often they bought
apparel by any means Respondent demographics were also unrelated to
buying apparel online Online apparel buyers further differed from non-
buyers in that they spent more time online than non-buyers and were more
likely to buy online in the future than non-buyers These results reveal a
systematic pattern of psychological and behavioral factors that seem to
facilitate online apparel purchase
These findings confirm theoretical accounts of consumer behavior and
extend their generality into the new realm of cyber-commerce The findings
are consistent with other studies that show that favorable attitudes are related
to online buying From the methodological perspective the attitude measures
appear to be robust across studies and provide valid reliable
operationalizations of these constructs This should encourage researchers to
use them as standardized measures of e-commerce-related attitudes The
findings also confirm the reliability and validity of the innovativeness (DSI)
and knowledge scales consistent with a series of studies that have evidenced
their psychometric soundness (eg Flynn et al 2000 Goldsmith 2000)
The findings suggest that consumers are motivated to buy apparel online by a
combination of factors and that the special circumstances of e-commerce
make this a unique consumption activity Online apparel buyers obviously
must want and need clothing so this basic motivation partially underlies
their behavior They seem however to be motivated differentially by their
attitudes toward the Internet While online apparel buyers were clearly more
positive on the attitudinal and psychological characteristics they were no
more likely than non-buyers to shop for clothes by other means to enjoy
shopping in general or to spend money buying clothes That is they are not
disproportionately motivated by clothing as a product category or by interest
in shopping but by the perceived advantages of online buying and their
positive predisposition toward this mode of commerce
For managers the results suggest that their online buyers may be somewhat
different from their in-store customers and may represent new customers
Consumers who buy disproportionately more apparel likely enjoy shopping
and want the emotional and sensory pleasures of touching seeing and trying
on clothes (see Seckler 2000 Underhill 1999) Note the positive
intercorrelations in Table IV between spending on apparel and shopping
(r = 030) spending and buying by any means (043) and between shopping
and buying (040) None of these variables was correlated with amount of
online buying (PURCH) Online buyers in contrast appear to be motivated
by their positive attitudes toward the Internet Thus to attract apparel buyers
to Web sites e-marketers might focus on emphasizing the added advantages
of fun speed and safety They should first ensure that their sites are fun to
use load rapidly with prompt post-sale delivery of ordered merchandise and
are completely safe to use They might emphasize how different online
buying is and not pretend that it is the same as in-store shopping Joint or
cooperative strategies might display apparel online but suggest that a
Respondent demographics
Unique consumptionactivity
Positive attitudes
98 JOURNAL OF PRODUCT amp BRAND MANAGEMENT VOL 11 NO 2 2002
different experience could be had in the store where unique accessories or
combinations of clothes could be seen Online apparel buyers and non-
buyers did not differ in their perception that buying online is cheaper than
offline Thus Secklerrsquos (2000) argument that offering price discounts may be
a prime way to attract non-buyers is supported To attract new buyers onlineapparel e-tailers may have to change perceptions that online buying is unsafe
(see Robinson 2000) Web sites must be made simple and easy to use
because non-users are not very confident that they can buy online
successfully In-store demonstrations of online shopping might encourage
non-buyers to shop online As online apparel buying spreads beyond the
innovative and knowledgeable consumer to the less sophisticated shopper
apparel marketers should cater to their unique tastes abilities and habits
This is especially true since the results suggest that many online apparel
buyers will buy online again
The study is limited by the nature of the sample measures specificity and
time studied Lack of randomness in the sample limits generalizability of the
point and interval estimates to a larger population but since the main
purpose of the study was to test theoretical hypotheses about online buyingthis is a minor limitation (Calder et al 1981) No conclusions can be drawn
about concepts that might be related to online apparel buying but were not
measured and the results are limited to the measures employed Similarly
the focal topic was clothing in general and not a specific type (new fashion
sports clothes work clothes etc) Finally since e-commerce and online
consumer behavior are constantly changing phenomena the present study is
only a snapshot picture and not a longitudinal view
Advantages of the study lie in the large sample size and validity of the
measures used Future research should examine online apparel using data
from other demographic socio-economic and national groups of consumers
to expand the scope of the findings The online buyer behaviors studied
should be expanded beyond just buying to include browsing comparison
shopping and combining the Internet with in-store consumption as well asconsumption of specific categories of apparel such as new fashions or
unique sizes and needs As noted in the introduction growth is a major
theme of e-commerce Thus replication studies would be a valuable way to
track changes in online apparel buying over time Accumulation of such
studies would expand our knowledge of both apparel consumer behavior and
consumer Internet behavior to the advantage of both consumer theory and
apparel marketing Finally other researchers could make use of our measures
to study buying behavior in other areas as well
References
Calder BJ Phillips LW and Tybout AM (1981) ` Designing research for application rsquorsquo
Journal of Consumer Research Vol 8 September pp 197-207
Citrin AV Sprott DE Silveman SN and Stem DE Jr (2000) ` Adoption of Internet
shopping the role of consumer innovativenessrsquorsquo Industrial Management amp Data Systems
Vol 100 No 7 pp 294-300
Eastlick MA and Lotz S (1999) ` Profiling potential adopters and non-adopter s of an
interactive electronic shopping mediumrsquorsquo Internationa l Journal of Retail amp Distribution
Management Vol 27 No 6 pp 209-23
eMarketer (2000) ` The e-holiday shopping reportrsquorsquo available at wwwemarketercom
Flynn LR Goldsmith RE and Kim W (2000) ` A cross-cultural validation of three new
marketing scales for fashion research involvement opinion seeking and knowledgersquorsquo
The Journal of Fashion Marketing and Management Vol 4 No 2 pp 110-20
Goldsmith RE (2000) ` How innovativenes s differentiate s online buyersrsquorsquo Quarterly Journal
of Electronic Commerce Vol 1 No 4 pp 323-33
Snapshot picture
Expand the scope of thefindings
JOURNAL OF PRODUCT amp BRAND MANAGEMENT VOL 11 NO 2 2002 99
Goldsmith RE and Bridges E (2000) ` E-tailing vs retailing using attitudes to predict
online buying behavior rsquorsquo Quarterly Journal of Electronic Commerce Vol 1 No 3
pp 245-53
Goldsmith RE and Hofacker CF (1991) ` Measuring consumer innovativeness rsquorsquo Journal of
the Academy of Marketing Science Vol 19 No 3 pp 209-21
Goldsmith RE and McGregor S (1999) ` Electronic commerce an emerging issue in
consumer educationrsquorsquo Proceedings of XIX Internationa l Consumer Studies and Home
Economics Research Conference Belfast
Goldsmith RE and McGregor S (2000) ` E-commerce consumer protection issues and
implications for research and educationrsquorsquo Journal of Consumer Studies amp Home
Economics Vol 24 No 2 pp 124-7
Hair JF Anderson RE Tatham RL and Black WC (1998) Multivariate Data Analysis
5th ed Prentice-Hall Upper Saddle River NJ
Hallberg G (1995) All Consumers Are not Created Equal John Wiley New York NJ
Harvard Management Update (2000) ` Lessons from the online war for customersrsquorsquo
Harvard Management Update January pp 3-4
Hoffman DL and Novak TP (1996) ` Marketing in hypermedia computer-mediated
environments conceptua l foundationsrsquorsquo Journal of Marketing Vol 60 No 3 pp 153-61
Hogg MK Bruce M and Hill AJ (1998) ` Fashion brand preference s among young
consumersrsquorsquo Internationa l Journal of Retail amp Distribution Management Vol 26 No 8
pp 293-300
Huck SW and Cormier WH (1996) Reading Statistics and Research 2nd ed
HarperCollins College Publishers New York NY
Karson E (2000) ` Two dimensions of computer and Internet use a reliable and validated
scalersquorsquo Quarterly Journal of Electronic Commerce Vol 1 No 1 pp 49-60
Katz J and Aspden P (1997) ` Motivations for and barriers to Internet usage results of a
national public opinion surveyrsquorsquo Internet Research Vol 7 No 3 pp 170-88
Kuntz J (2000) ` Age and income play key roles in online salesrsquorsquo Daily News Record
27 March p 19
Limayem M Khalifa M and Frini A (2000) ` What makes consumers buy from the
Internet A longitudinal study of online shoppingrsquorsquo IEEE Transactions on Systems Man
and Cybernetics Part A Systems and Humans Vol 30 No 4 pp 421-32
Murphy R (1999) ` Download Internet news IIrsquorsquo The Journal of Fashion Marketing and
Management Vol 3 No 4 pp 376-7
Nelson J (2000) ` Internet at a glancersquorsquo Business 20 12 September p 279
OrsquoGuinn TC and Faber RJ (1989) ` Compulsive buying a phenomenologica l explorationrsquorsquo
Journal of Consumer Research Vol 16 No 2 pp 147-57
Robinson E (2000) ` Click and coverrsquorsquo Business 20 12 September pp 168-80
Seckler V (2000) ` Survey says Web apparel buys doubledrsquorsquo Womenrsquos Wear Daily 12 July
p 2
Silverman D (2000) ` More women wardrobe online than everrsquorsquo Womenrsquos Wear Daily
31 July p 20
Solomon MR (1999) Consumer Behavior Buying Having and Being 4th ed
Prentice-Hall Upper Saddle River NJ
UCLA (2000) ` The UCLA Internet report surveying the digital futurersquorsquo available at
wwwccpuclaedu
Underhill P (1999) Why We Buy The Science of Shopping Simon amp Schuster
New York NY
Vickery L and Agins T (2001) ` Retailers find Web apparel unprofitable rsquorsquo Wall Street
Journal 6 June p B6
Wilson J (1999) ` Keynote addressrsquorsquo The Journal of Fashion Marketing and Management
Vol 3 No 4 pp 370-6
amp
100 JOURNAL OF PRODUCT amp BRAND MANAGEMENT VOL 11 NO 2 2002
Executive summary and implications for managers andexecutives
Retailing online plusmn know your customer and learn from mail ordermarketingE-commerce and especially online retailing have received much attention agreat deal of thought and significant investment Despite this we still lackany clear understanding of the business models that can deliver successonline For every apparent e-retailing success we get a massive plusmn andusually very expensive plusmn failure We can say plusmn with some safety plusmn that theprospects for another Internet trading investment boom have gone
For marketers this situation is a disappointment We are after all theexperts on distribution and sales channels The failure to make e-retailingwork sits in our court and we continue to chew away at the e-commerce bonein the hope that it will eventually come good At the same time we haveraised questions about the capacity of the technology to deliver what wewant Doubts persist about the security of money transfers online Weak linksbetween real world distribution plusmn getting the product to the customer plusmn andthe cosy virtual world get in the way of seamless service And while gettingthe online equivalent of footfall is easy converting these visitors tocustomers is a massive challenge
Know your customer plusmn the marketerrsquos mantraGoldsmith and Goldsmith observe that while a great deal is said aboutonline processes technology and promotion little is known about the actualonline customer We know too little about the differences between theenthusiastic innovators who buy goods online and the rest who are happy tolook but do not buy
The difference between ` innovatorsrsquorsquo and ` early adoptersrsquorsquo is wellresearched and in general terms understood by marketers E-retailing hasnot taken off because the chasm between these two groups remainsunbridged As a result the apparent mass market for e-commerce remains afuture dream Two-thirds of Americans might have access to the Internet butthey are not using it to buy things plusmn at least not in sufficient numbers
Goldsmith and Goldsmith set out to compare clothes buyers who havebought online with those who have not made this sort of purchaseUnderlying the study is the assumption (supported by research and largelycommon sense) that ` consumers who have previous experience in onlinebuying will be more likely to buy apparel online than those who lack suchexperiencersquorsquo We should also note like Goldsmith and Goldsmith that thepeople who matter to e-retailers are those very similar to existing users whoat present are non-users
Are you frightened of the WebGoldsmith and Goldsmith find that there are substantial differences betweene-buyers and the rest of humanity (I always knew that Web enthusiasts werestrange) Some of these differences are pretty prosaic plusmn online buyers havefewer security worries appreciate the ` quicknessrsquorsquo and flexibility of onlinebuying and see the Web as making buying easier However the other (morepsychological) factors suggest that these preferences are symptomatic of thetype rather than definitional The remainder of Goldsmith and Goldsmithrsquosfindings throw up words like ` confidentrsquorsquo ` innovativersquorsquo ` knowledgeablersquorsquoand ` funrsquorsquo Our e-buyers take the view that ` the special circumstancesof e-commerce make this a unique consumption activityrsquorsquo These people aredifferent and we need to know why and at the same time to understand theresistance of others to e-commerce
Part of the resistance appears to lie in fear (characterised as being a lack ofconfidence) People who do not buy online do not have a great deal of trust in
JOURNAL OF PRODUCT amp BRAND MANAGEMENT VOL 11 NO 2 2002 101
This summary has beenprovided to allow managersand executives a rapidappreciation of the contentof this article Those with aparticular interest in thetopic covered may then readthe article in toto to takeadvantage of the morecomprehensive descriptionof the research undertakenand its results to get the fullbenefit of the materialpresent
the medium This seems to hold true even when they use the Internet for avariety of other activities (information gathering communications games etc)Until these issues of fear (or trust or confidence) are dealt with marketers willstruggle to take the idea of e-commerce into the mainstream of retailing
Removing the fearTwo elements are involved in removing consumer distrust of e-commerceThe first is more confidence with the technology involved in buying onlineBear in mind that most of us who use computers take advantage of a tiny partof the capacity of even basic software Even with comprehensible manualson-screen and online help and ` idiot guidesrsquorsquo we still stick to basicprocessing
Ease-of-use is fundamental to successful e-retailing and so far we havefailed to achieve sufficiently easy systems to remove the consumerrsquos worryabout getting it wrong But this is just one problem and its solution lies asmuch in the relationship between the ordinary consumer and Internettechnology as in specific marketing actions
The second element is purely promotional and is about securing trial andreducing the distrust E-commerce becomes accessible when these barriersare removed and there are many techniques available that marketers canuse
Mail order and direct marketers have always faced resistance to theirchannel Indeed mail order people appreciate that there remains a largechunk of the population that will never buy mail order whatever theincentive Nevertheless these marketers have developed (and tested) avariety of simple techniques to secure trial and build confidence
product and service guarantees
payment on delivery rather than payment with the order
featuring low-risk entry products
no-quibble return policies
product endorsement plusmn by real customers
testimonials and
prize draws free gifts and other order incentives
E-commerce represents a new channel and for some businesses a differentmeans of delivering product But for most businesses and especiallyretailers the Internet does not change the nature of the product itself (a pairof shorts remains a pair of shorts) Rather than reinventing the wheel e-retailers should learn from direct marketers
E-commerce needs more confidence to sell itself successfully but in the finalanalysis the e-retailer does little that is different from the mail ordercompany And the direct marketer knows that profits come from repeatbusiness rather than from the first sale Too many e-commerce operationshave floundered because they ignored the experience of others and tried torun a business without good databases or the strategies to sustain incomefrom existing buyers
Do you want your e-retailing business to succeed Hire an experience directmarketer and you will stand a better than average chance of successPretending that the e-marketers have nothing to learn from old grizzled (andboring) mail order people is a mistake that is probably costing you money
(A preAcirccis of the article ` Buying apparel over the Internetrsquorsquo Supplied byMarketing Consultants for Emerald)
102 JOURNAL OF PRODUCT amp BRAND MANAGEMENT VOL 11 NO 2 2002
statistically significant (F(10 549) = 24 p = 001) Follow-up univariate
analyses showed that the interactions however were significant for only
two of the dependent variables For PURCH the amount of online buying
men reported buying more than women but men who had bought apparel
online reported buying disproportionately more online than women who
had bought apparel online The opposite effect was observed for MEANS
buying apparel by any means Women reported buying apparel by any
means more than men but men who had bought apparel online reported
buying disproportionately less apparel by any means than the women
online buyers
The multivariate main effect for SEX was significant (F(10 549) = 143
p lt 0001) In addition to significant main effect differences for PURCH and
MEANS women reported that they enjoyed shopping (SHOP) more than
men and men reported that they thought online buying was more fun
cheaper and quicker than the women These findings are similar to those
reported in other studies of online buying
The multivariate main effect for EVER whether a respondent had ever
bought apparel online was statistically significant (F(10 549) = 204
p lt 0001) The univariate analyses showed that compared with those who
had not bought apparel online those who had bought apparel online had
more experience purchasing online in general (PURCH) and thought that
buying over the Internet was more fun safer quicker and they were more
confident in their ability to buy online The online apparel buyers also were
more innovative and knowledgeable about the Internet than non-buyers
Thus H1 H3 H4 H6 H7 H9 and H10 were confirmed There were no
statistically significant differences in the self-reported apparel purchase
(MEANS) perceptions that online buying was cheaper (CHEAP) or in
shopping enjoyment (SHOP) Because Boxrsquos test of the equality of the
covariance matrices was significant (indicating that the covariance matrices
were not identical across the groups of respondents) and because Levenersquos
test of equality of error variances showed that the error variances of four of
the dependent variables were not equal thus violating the assumptions of
MANOVA (Huck and Cormier 1996 pp 313-15 374-7) a Mann-Whitney
non-parametric analysis was conducted testing whether the observations
from the two groups of online apparel buyers were equivalent in location
These analyses were consistent with the parametric tests
As a final analysis a 2 pound 2 (SEX pound EVER with age as a covariate)
MANCOVA was conducted comparing the buyers and non-buyers on three
additional variables These were
(1) the number of hours the respondent was online in an average week
(HOURS)
(2) the amount of reported spending on apparel (SPEND) and
(2) how likely the respondent was to buy online in the coming year
(LIKELY)
The results showed that men averaged more hours online per week than
women women spent more on apparel than men and the men were more
likely to shop online in the future than were the women Finally online
apparel buyers reported spending more time online and were more likely to
buy online in the future than non-buyers
Online apparel buyers
Additional variables
JOURNAL OF PRODUCT amp BRAND MANAGEMENT VOL 11 NO 2 2002 97
Discussion
The present study compared selected characteristics of consumers who had
purchased apparel online with those who had not The results showed that
online apparel buyers purchased online more often felt that online buying
was more fun safer and quicker than non-buyers Online apparel buyers
were more confident in their ability to buy online and were more innovative
and knowledgeable about the Internet than non-buyers Online apparel
buyers did not differ from non-buyers in their belief in how cheap buying
online is in their overall enjoyment of shopping or in how often they bought
apparel by any means Respondent demographics were also unrelated to
buying apparel online Online apparel buyers further differed from non-
buyers in that they spent more time online than non-buyers and were more
likely to buy online in the future than non-buyers These results reveal a
systematic pattern of psychological and behavioral factors that seem to
facilitate online apparel purchase
These findings confirm theoretical accounts of consumer behavior and
extend their generality into the new realm of cyber-commerce The findings
are consistent with other studies that show that favorable attitudes are related
to online buying From the methodological perspective the attitude measures
appear to be robust across studies and provide valid reliable
operationalizations of these constructs This should encourage researchers to
use them as standardized measures of e-commerce-related attitudes The
findings also confirm the reliability and validity of the innovativeness (DSI)
and knowledge scales consistent with a series of studies that have evidenced
their psychometric soundness (eg Flynn et al 2000 Goldsmith 2000)
The findings suggest that consumers are motivated to buy apparel online by a
combination of factors and that the special circumstances of e-commerce
make this a unique consumption activity Online apparel buyers obviously
must want and need clothing so this basic motivation partially underlies
their behavior They seem however to be motivated differentially by their
attitudes toward the Internet While online apparel buyers were clearly more
positive on the attitudinal and psychological characteristics they were no
more likely than non-buyers to shop for clothes by other means to enjoy
shopping in general or to spend money buying clothes That is they are not
disproportionately motivated by clothing as a product category or by interest
in shopping but by the perceived advantages of online buying and their
positive predisposition toward this mode of commerce
For managers the results suggest that their online buyers may be somewhat
different from their in-store customers and may represent new customers
Consumers who buy disproportionately more apparel likely enjoy shopping
and want the emotional and sensory pleasures of touching seeing and trying
on clothes (see Seckler 2000 Underhill 1999) Note the positive
intercorrelations in Table IV between spending on apparel and shopping
(r = 030) spending and buying by any means (043) and between shopping
and buying (040) None of these variables was correlated with amount of
online buying (PURCH) Online buyers in contrast appear to be motivated
by their positive attitudes toward the Internet Thus to attract apparel buyers
to Web sites e-marketers might focus on emphasizing the added advantages
of fun speed and safety They should first ensure that their sites are fun to
use load rapidly with prompt post-sale delivery of ordered merchandise and
are completely safe to use They might emphasize how different online
buying is and not pretend that it is the same as in-store shopping Joint or
cooperative strategies might display apparel online but suggest that a
Respondent demographics
Unique consumptionactivity
Positive attitudes
98 JOURNAL OF PRODUCT amp BRAND MANAGEMENT VOL 11 NO 2 2002
different experience could be had in the store where unique accessories or
combinations of clothes could be seen Online apparel buyers and non-
buyers did not differ in their perception that buying online is cheaper than
offline Thus Secklerrsquos (2000) argument that offering price discounts may be
a prime way to attract non-buyers is supported To attract new buyers onlineapparel e-tailers may have to change perceptions that online buying is unsafe
(see Robinson 2000) Web sites must be made simple and easy to use
because non-users are not very confident that they can buy online
successfully In-store demonstrations of online shopping might encourage
non-buyers to shop online As online apparel buying spreads beyond the
innovative and knowledgeable consumer to the less sophisticated shopper
apparel marketers should cater to their unique tastes abilities and habits
This is especially true since the results suggest that many online apparel
buyers will buy online again
The study is limited by the nature of the sample measures specificity and
time studied Lack of randomness in the sample limits generalizability of the
point and interval estimates to a larger population but since the main
purpose of the study was to test theoretical hypotheses about online buyingthis is a minor limitation (Calder et al 1981) No conclusions can be drawn
about concepts that might be related to online apparel buying but were not
measured and the results are limited to the measures employed Similarly
the focal topic was clothing in general and not a specific type (new fashion
sports clothes work clothes etc) Finally since e-commerce and online
consumer behavior are constantly changing phenomena the present study is
only a snapshot picture and not a longitudinal view
Advantages of the study lie in the large sample size and validity of the
measures used Future research should examine online apparel using data
from other demographic socio-economic and national groups of consumers
to expand the scope of the findings The online buyer behaviors studied
should be expanded beyond just buying to include browsing comparison
shopping and combining the Internet with in-store consumption as well asconsumption of specific categories of apparel such as new fashions or
unique sizes and needs As noted in the introduction growth is a major
theme of e-commerce Thus replication studies would be a valuable way to
track changes in online apparel buying over time Accumulation of such
studies would expand our knowledge of both apparel consumer behavior and
consumer Internet behavior to the advantage of both consumer theory and
apparel marketing Finally other researchers could make use of our measures
to study buying behavior in other areas as well
References
Calder BJ Phillips LW and Tybout AM (1981) ` Designing research for application rsquorsquo
Journal of Consumer Research Vol 8 September pp 197-207
Citrin AV Sprott DE Silveman SN and Stem DE Jr (2000) ` Adoption of Internet
shopping the role of consumer innovativenessrsquorsquo Industrial Management amp Data Systems
Vol 100 No 7 pp 294-300
Eastlick MA and Lotz S (1999) ` Profiling potential adopters and non-adopter s of an
interactive electronic shopping mediumrsquorsquo Internationa l Journal of Retail amp Distribution
Management Vol 27 No 6 pp 209-23
eMarketer (2000) ` The e-holiday shopping reportrsquorsquo available at wwwemarketercom
Flynn LR Goldsmith RE and Kim W (2000) ` A cross-cultural validation of three new
marketing scales for fashion research involvement opinion seeking and knowledgersquorsquo
The Journal of Fashion Marketing and Management Vol 4 No 2 pp 110-20
Goldsmith RE (2000) ` How innovativenes s differentiate s online buyersrsquorsquo Quarterly Journal
of Electronic Commerce Vol 1 No 4 pp 323-33
Snapshot picture
Expand the scope of thefindings
JOURNAL OF PRODUCT amp BRAND MANAGEMENT VOL 11 NO 2 2002 99
Goldsmith RE and Bridges E (2000) ` E-tailing vs retailing using attitudes to predict
online buying behavior rsquorsquo Quarterly Journal of Electronic Commerce Vol 1 No 3
pp 245-53
Goldsmith RE and Hofacker CF (1991) ` Measuring consumer innovativeness rsquorsquo Journal of
the Academy of Marketing Science Vol 19 No 3 pp 209-21
Goldsmith RE and McGregor S (1999) ` Electronic commerce an emerging issue in
consumer educationrsquorsquo Proceedings of XIX Internationa l Consumer Studies and Home
Economics Research Conference Belfast
Goldsmith RE and McGregor S (2000) ` E-commerce consumer protection issues and
implications for research and educationrsquorsquo Journal of Consumer Studies amp Home
Economics Vol 24 No 2 pp 124-7
Hair JF Anderson RE Tatham RL and Black WC (1998) Multivariate Data Analysis
5th ed Prentice-Hall Upper Saddle River NJ
Hallberg G (1995) All Consumers Are not Created Equal John Wiley New York NJ
Harvard Management Update (2000) ` Lessons from the online war for customersrsquorsquo
Harvard Management Update January pp 3-4
Hoffman DL and Novak TP (1996) ` Marketing in hypermedia computer-mediated
environments conceptua l foundationsrsquorsquo Journal of Marketing Vol 60 No 3 pp 153-61
Hogg MK Bruce M and Hill AJ (1998) ` Fashion brand preference s among young
consumersrsquorsquo Internationa l Journal of Retail amp Distribution Management Vol 26 No 8
pp 293-300
Huck SW and Cormier WH (1996) Reading Statistics and Research 2nd ed
HarperCollins College Publishers New York NY
Karson E (2000) ` Two dimensions of computer and Internet use a reliable and validated
scalersquorsquo Quarterly Journal of Electronic Commerce Vol 1 No 1 pp 49-60
Katz J and Aspden P (1997) ` Motivations for and barriers to Internet usage results of a
national public opinion surveyrsquorsquo Internet Research Vol 7 No 3 pp 170-88
Kuntz J (2000) ` Age and income play key roles in online salesrsquorsquo Daily News Record
27 March p 19
Limayem M Khalifa M and Frini A (2000) ` What makes consumers buy from the
Internet A longitudinal study of online shoppingrsquorsquo IEEE Transactions on Systems Man
and Cybernetics Part A Systems and Humans Vol 30 No 4 pp 421-32
Murphy R (1999) ` Download Internet news IIrsquorsquo The Journal of Fashion Marketing and
Management Vol 3 No 4 pp 376-7
Nelson J (2000) ` Internet at a glancersquorsquo Business 20 12 September p 279
OrsquoGuinn TC and Faber RJ (1989) ` Compulsive buying a phenomenologica l explorationrsquorsquo
Journal of Consumer Research Vol 16 No 2 pp 147-57
Robinson E (2000) ` Click and coverrsquorsquo Business 20 12 September pp 168-80
Seckler V (2000) ` Survey says Web apparel buys doubledrsquorsquo Womenrsquos Wear Daily 12 July
p 2
Silverman D (2000) ` More women wardrobe online than everrsquorsquo Womenrsquos Wear Daily
31 July p 20
Solomon MR (1999) Consumer Behavior Buying Having and Being 4th ed
Prentice-Hall Upper Saddle River NJ
UCLA (2000) ` The UCLA Internet report surveying the digital futurersquorsquo available at
wwwccpuclaedu
Underhill P (1999) Why We Buy The Science of Shopping Simon amp Schuster
New York NY
Vickery L and Agins T (2001) ` Retailers find Web apparel unprofitable rsquorsquo Wall Street
Journal 6 June p B6
Wilson J (1999) ` Keynote addressrsquorsquo The Journal of Fashion Marketing and Management
Vol 3 No 4 pp 370-6
amp
100 JOURNAL OF PRODUCT amp BRAND MANAGEMENT VOL 11 NO 2 2002
Executive summary and implications for managers andexecutives
Retailing online plusmn know your customer and learn from mail ordermarketingE-commerce and especially online retailing have received much attention agreat deal of thought and significant investment Despite this we still lackany clear understanding of the business models that can deliver successonline For every apparent e-retailing success we get a massive plusmn andusually very expensive plusmn failure We can say plusmn with some safety plusmn that theprospects for another Internet trading investment boom have gone
For marketers this situation is a disappointment We are after all theexperts on distribution and sales channels The failure to make e-retailingwork sits in our court and we continue to chew away at the e-commerce bonein the hope that it will eventually come good At the same time we haveraised questions about the capacity of the technology to deliver what wewant Doubts persist about the security of money transfers online Weak linksbetween real world distribution plusmn getting the product to the customer plusmn andthe cosy virtual world get in the way of seamless service And while gettingthe online equivalent of footfall is easy converting these visitors tocustomers is a massive challenge
Know your customer plusmn the marketerrsquos mantraGoldsmith and Goldsmith observe that while a great deal is said aboutonline processes technology and promotion little is known about the actualonline customer We know too little about the differences between theenthusiastic innovators who buy goods online and the rest who are happy tolook but do not buy
The difference between ` innovatorsrsquorsquo and ` early adoptersrsquorsquo is wellresearched and in general terms understood by marketers E-retailing hasnot taken off because the chasm between these two groups remainsunbridged As a result the apparent mass market for e-commerce remains afuture dream Two-thirds of Americans might have access to the Internet butthey are not using it to buy things plusmn at least not in sufficient numbers
Goldsmith and Goldsmith set out to compare clothes buyers who havebought online with those who have not made this sort of purchaseUnderlying the study is the assumption (supported by research and largelycommon sense) that ` consumers who have previous experience in onlinebuying will be more likely to buy apparel online than those who lack suchexperiencersquorsquo We should also note like Goldsmith and Goldsmith that thepeople who matter to e-retailers are those very similar to existing users whoat present are non-users
Are you frightened of the WebGoldsmith and Goldsmith find that there are substantial differences betweene-buyers and the rest of humanity (I always knew that Web enthusiasts werestrange) Some of these differences are pretty prosaic plusmn online buyers havefewer security worries appreciate the ` quicknessrsquorsquo and flexibility of onlinebuying and see the Web as making buying easier However the other (morepsychological) factors suggest that these preferences are symptomatic of thetype rather than definitional The remainder of Goldsmith and Goldsmithrsquosfindings throw up words like ` confidentrsquorsquo ` innovativersquorsquo ` knowledgeablersquorsquoand ` funrsquorsquo Our e-buyers take the view that ` the special circumstancesof e-commerce make this a unique consumption activityrsquorsquo These people aredifferent and we need to know why and at the same time to understand theresistance of others to e-commerce
Part of the resistance appears to lie in fear (characterised as being a lack ofconfidence) People who do not buy online do not have a great deal of trust in
JOURNAL OF PRODUCT amp BRAND MANAGEMENT VOL 11 NO 2 2002 101
This summary has beenprovided to allow managersand executives a rapidappreciation of the contentof this article Those with aparticular interest in thetopic covered may then readthe article in toto to takeadvantage of the morecomprehensive descriptionof the research undertakenand its results to get the fullbenefit of the materialpresent
the medium This seems to hold true even when they use the Internet for avariety of other activities (information gathering communications games etc)Until these issues of fear (or trust or confidence) are dealt with marketers willstruggle to take the idea of e-commerce into the mainstream of retailing
Removing the fearTwo elements are involved in removing consumer distrust of e-commerceThe first is more confidence with the technology involved in buying onlineBear in mind that most of us who use computers take advantage of a tiny partof the capacity of even basic software Even with comprehensible manualson-screen and online help and ` idiot guidesrsquorsquo we still stick to basicprocessing
Ease-of-use is fundamental to successful e-retailing and so far we havefailed to achieve sufficiently easy systems to remove the consumerrsquos worryabout getting it wrong But this is just one problem and its solution lies asmuch in the relationship between the ordinary consumer and Internettechnology as in specific marketing actions
The second element is purely promotional and is about securing trial andreducing the distrust E-commerce becomes accessible when these barriersare removed and there are many techniques available that marketers canuse
Mail order and direct marketers have always faced resistance to theirchannel Indeed mail order people appreciate that there remains a largechunk of the population that will never buy mail order whatever theincentive Nevertheless these marketers have developed (and tested) avariety of simple techniques to secure trial and build confidence
product and service guarantees
payment on delivery rather than payment with the order
featuring low-risk entry products
no-quibble return policies
product endorsement plusmn by real customers
testimonials and
prize draws free gifts and other order incentives
E-commerce represents a new channel and for some businesses a differentmeans of delivering product But for most businesses and especiallyretailers the Internet does not change the nature of the product itself (a pairof shorts remains a pair of shorts) Rather than reinventing the wheel e-retailers should learn from direct marketers
E-commerce needs more confidence to sell itself successfully but in the finalanalysis the e-retailer does little that is different from the mail ordercompany And the direct marketer knows that profits come from repeatbusiness rather than from the first sale Too many e-commerce operationshave floundered because they ignored the experience of others and tried torun a business without good databases or the strategies to sustain incomefrom existing buyers
Do you want your e-retailing business to succeed Hire an experience directmarketer and you will stand a better than average chance of successPretending that the e-marketers have nothing to learn from old grizzled (andboring) mail order people is a mistake that is probably costing you money
(A preAcirccis of the article ` Buying apparel over the Internetrsquorsquo Supplied byMarketing Consultants for Emerald)
102 JOURNAL OF PRODUCT amp BRAND MANAGEMENT VOL 11 NO 2 2002
Discussion
The present study compared selected characteristics of consumers who had
purchased apparel online with those who had not The results showed that
online apparel buyers purchased online more often felt that online buying
was more fun safer and quicker than non-buyers Online apparel buyers
were more confident in their ability to buy online and were more innovative
and knowledgeable about the Internet than non-buyers Online apparel
buyers did not differ from non-buyers in their belief in how cheap buying
online is in their overall enjoyment of shopping or in how often they bought
apparel by any means Respondent demographics were also unrelated to
buying apparel online Online apparel buyers further differed from non-
buyers in that they spent more time online than non-buyers and were more
likely to buy online in the future than non-buyers These results reveal a
systematic pattern of psychological and behavioral factors that seem to
facilitate online apparel purchase
These findings confirm theoretical accounts of consumer behavior and
extend their generality into the new realm of cyber-commerce The findings
are consistent with other studies that show that favorable attitudes are related
to online buying From the methodological perspective the attitude measures
appear to be robust across studies and provide valid reliable
operationalizations of these constructs This should encourage researchers to
use them as standardized measures of e-commerce-related attitudes The
findings also confirm the reliability and validity of the innovativeness (DSI)
and knowledge scales consistent with a series of studies that have evidenced
their psychometric soundness (eg Flynn et al 2000 Goldsmith 2000)
The findings suggest that consumers are motivated to buy apparel online by a
combination of factors and that the special circumstances of e-commerce
make this a unique consumption activity Online apparel buyers obviously
must want and need clothing so this basic motivation partially underlies
their behavior They seem however to be motivated differentially by their
attitudes toward the Internet While online apparel buyers were clearly more
positive on the attitudinal and psychological characteristics they were no
more likely than non-buyers to shop for clothes by other means to enjoy
shopping in general or to spend money buying clothes That is they are not
disproportionately motivated by clothing as a product category or by interest
in shopping but by the perceived advantages of online buying and their
positive predisposition toward this mode of commerce
For managers the results suggest that their online buyers may be somewhat
different from their in-store customers and may represent new customers
Consumers who buy disproportionately more apparel likely enjoy shopping
and want the emotional and sensory pleasures of touching seeing and trying
on clothes (see Seckler 2000 Underhill 1999) Note the positive
intercorrelations in Table IV between spending on apparel and shopping
(r = 030) spending and buying by any means (043) and between shopping
and buying (040) None of these variables was correlated with amount of
online buying (PURCH) Online buyers in contrast appear to be motivated
by their positive attitudes toward the Internet Thus to attract apparel buyers
to Web sites e-marketers might focus on emphasizing the added advantages
of fun speed and safety They should first ensure that their sites are fun to
use load rapidly with prompt post-sale delivery of ordered merchandise and
are completely safe to use They might emphasize how different online
buying is and not pretend that it is the same as in-store shopping Joint or
cooperative strategies might display apparel online but suggest that a
Respondent demographics
Unique consumptionactivity
Positive attitudes
98 JOURNAL OF PRODUCT amp BRAND MANAGEMENT VOL 11 NO 2 2002
different experience could be had in the store where unique accessories or
combinations of clothes could be seen Online apparel buyers and non-
buyers did not differ in their perception that buying online is cheaper than
offline Thus Secklerrsquos (2000) argument that offering price discounts may be
a prime way to attract non-buyers is supported To attract new buyers onlineapparel e-tailers may have to change perceptions that online buying is unsafe
(see Robinson 2000) Web sites must be made simple and easy to use
because non-users are not very confident that they can buy online
successfully In-store demonstrations of online shopping might encourage
non-buyers to shop online As online apparel buying spreads beyond the
innovative and knowledgeable consumer to the less sophisticated shopper
apparel marketers should cater to their unique tastes abilities and habits
This is especially true since the results suggest that many online apparel
buyers will buy online again
The study is limited by the nature of the sample measures specificity and
time studied Lack of randomness in the sample limits generalizability of the
point and interval estimates to a larger population but since the main
purpose of the study was to test theoretical hypotheses about online buyingthis is a minor limitation (Calder et al 1981) No conclusions can be drawn
about concepts that might be related to online apparel buying but were not
measured and the results are limited to the measures employed Similarly
the focal topic was clothing in general and not a specific type (new fashion
sports clothes work clothes etc) Finally since e-commerce and online
consumer behavior are constantly changing phenomena the present study is
only a snapshot picture and not a longitudinal view
Advantages of the study lie in the large sample size and validity of the
measures used Future research should examine online apparel using data
from other demographic socio-economic and national groups of consumers
to expand the scope of the findings The online buyer behaviors studied
should be expanded beyond just buying to include browsing comparison
shopping and combining the Internet with in-store consumption as well asconsumption of specific categories of apparel such as new fashions or
unique sizes and needs As noted in the introduction growth is a major
theme of e-commerce Thus replication studies would be a valuable way to
track changes in online apparel buying over time Accumulation of such
studies would expand our knowledge of both apparel consumer behavior and
consumer Internet behavior to the advantage of both consumer theory and
apparel marketing Finally other researchers could make use of our measures
to study buying behavior in other areas as well
References
Calder BJ Phillips LW and Tybout AM (1981) ` Designing research for application rsquorsquo
Journal of Consumer Research Vol 8 September pp 197-207
Citrin AV Sprott DE Silveman SN and Stem DE Jr (2000) ` Adoption of Internet
shopping the role of consumer innovativenessrsquorsquo Industrial Management amp Data Systems
Vol 100 No 7 pp 294-300
Eastlick MA and Lotz S (1999) ` Profiling potential adopters and non-adopter s of an
interactive electronic shopping mediumrsquorsquo Internationa l Journal of Retail amp Distribution
Management Vol 27 No 6 pp 209-23
eMarketer (2000) ` The e-holiday shopping reportrsquorsquo available at wwwemarketercom
Flynn LR Goldsmith RE and Kim W (2000) ` A cross-cultural validation of three new
marketing scales for fashion research involvement opinion seeking and knowledgersquorsquo
The Journal of Fashion Marketing and Management Vol 4 No 2 pp 110-20
Goldsmith RE (2000) ` How innovativenes s differentiate s online buyersrsquorsquo Quarterly Journal
of Electronic Commerce Vol 1 No 4 pp 323-33
Snapshot picture
Expand the scope of thefindings
JOURNAL OF PRODUCT amp BRAND MANAGEMENT VOL 11 NO 2 2002 99
Goldsmith RE and Bridges E (2000) ` E-tailing vs retailing using attitudes to predict
online buying behavior rsquorsquo Quarterly Journal of Electronic Commerce Vol 1 No 3
pp 245-53
Goldsmith RE and Hofacker CF (1991) ` Measuring consumer innovativeness rsquorsquo Journal of
the Academy of Marketing Science Vol 19 No 3 pp 209-21
Goldsmith RE and McGregor S (1999) ` Electronic commerce an emerging issue in
consumer educationrsquorsquo Proceedings of XIX Internationa l Consumer Studies and Home
Economics Research Conference Belfast
Goldsmith RE and McGregor S (2000) ` E-commerce consumer protection issues and
implications for research and educationrsquorsquo Journal of Consumer Studies amp Home
Economics Vol 24 No 2 pp 124-7
Hair JF Anderson RE Tatham RL and Black WC (1998) Multivariate Data Analysis
5th ed Prentice-Hall Upper Saddle River NJ
Hallberg G (1995) All Consumers Are not Created Equal John Wiley New York NJ
Harvard Management Update (2000) ` Lessons from the online war for customersrsquorsquo
Harvard Management Update January pp 3-4
Hoffman DL and Novak TP (1996) ` Marketing in hypermedia computer-mediated
environments conceptua l foundationsrsquorsquo Journal of Marketing Vol 60 No 3 pp 153-61
Hogg MK Bruce M and Hill AJ (1998) ` Fashion brand preference s among young
consumersrsquorsquo Internationa l Journal of Retail amp Distribution Management Vol 26 No 8
pp 293-300
Huck SW and Cormier WH (1996) Reading Statistics and Research 2nd ed
HarperCollins College Publishers New York NY
Karson E (2000) ` Two dimensions of computer and Internet use a reliable and validated
scalersquorsquo Quarterly Journal of Electronic Commerce Vol 1 No 1 pp 49-60
Katz J and Aspden P (1997) ` Motivations for and barriers to Internet usage results of a
national public opinion surveyrsquorsquo Internet Research Vol 7 No 3 pp 170-88
Kuntz J (2000) ` Age and income play key roles in online salesrsquorsquo Daily News Record
27 March p 19
Limayem M Khalifa M and Frini A (2000) ` What makes consumers buy from the
Internet A longitudinal study of online shoppingrsquorsquo IEEE Transactions on Systems Man
and Cybernetics Part A Systems and Humans Vol 30 No 4 pp 421-32
Murphy R (1999) ` Download Internet news IIrsquorsquo The Journal of Fashion Marketing and
Management Vol 3 No 4 pp 376-7
Nelson J (2000) ` Internet at a glancersquorsquo Business 20 12 September p 279
OrsquoGuinn TC and Faber RJ (1989) ` Compulsive buying a phenomenologica l explorationrsquorsquo
Journal of Consumer Research Vol 16 No 2 pp 147-57
Robinson E (2000) ` Click and coverrsquorsquo Business 20 12 September pp 168-80
Seckler V (2000) ` Survey says Web apparel buys doubledrsquorsquo Womenrsquos Wear Daily 12 July
p 2
Silverman D (2000) ` More women wardrobe online than everrsquorsquo Womenrsquos Wear Daily
31 July p 20
Solomon MR (1999) Consumer Behavior Buying Having and Being 4th ed
Prentice-Hall Upper Saddle River NJ
UCLA (2000) ` The UCLA Internet report surveying the digital futurersquorsquo available at
wwwccpuclaedu
Underhill P (1999) Why We Buy The Science of Shopping Simon amp Schuster
New York NY
Vickery L and Agins T (2001) ` Retailers find Web apparel unprofitable rsquorsquo Wall Street
Journal 6 June p B6
Wilson J (1999) ` Keynote addressrsquorsquo The Journal of Fashion Marketing and Management
Vol 3 No 4 pp 370-6
amp
100 JOURNAL OF PRODUCT amp BRAND MANAGEMENT VOL 11 NO 2 2002
Executive summary and implications for managers andexecutives
Retailing online plusmn know your customer and learn from mail ordermarketingE-commerce and especially online retailing have received much attention agreat deal of thought and significant investment Despite this we still lackany clear understanding of the business models that can deliver successonline For every apparent e-retailing success we get a massive plusmn andusually very expensive plusmn failure We can say plusmn with some safety plusmn that theprospects for another Internet trading investment boom have gone
For marketers this situation is a disappointment We are after all theexperts on distribution and sales channels The failure to make e-retailingwork sits in our court and we continue to chew away at the e-commerce bonein the hope that it will eventually come good At the same time we haveraised questions about the capacity of the technology to deliver what wewant Doubts persist about the security of money transfers online Weak linksbetween real world distribution plusmn getting the product to the customer plusmn andthe cosy virtual world get in the way of seamless service And while gettingthe online equivalent of footfall is easy converting these visitors tocustomers is a massive challenge
Know your customer plusmn the marketerrsquos mantraGoldsmith and Goldsmith observe that while a great deal is said aboutonline processes technology and promotion little is known about the actualonline customer We know too little about the differences between theenthusiastic innovators who buy goods online and the rest who are happy tolook but do not buy
The difference between ` innovatorsrsquorsquo and ` early adoptersrsquorsquo is wellresearched and in general terms understood by marketers E-retailing hasnot taken off because the chasm between these two groups remainsunbridged As a result the apparent mass market for e-commerce remains afuture dream Two-thirds of Americans might have access to the Internet butthey are not using it to buy things plusmn at least not in sufficient numbers
Goldsmith and Goldsmith set out to compare clothes buyers who havebought online with those who have not made this sort of purchaseUnderlying the study is the assumption (supported by research and largelycommon sense) that ` consumers who have previous experience in onlinebuying will be more likely to buy apparel online than those who lack suchexperiencersquorsquo We should also note like Goldsmith and Goldsmith that thepeople who matter to e-retailers are those very similar to existing users whoat present are non-users
Are you frightened of the WebGoldsmith and Goldsmith find that there are substantial differences betweene-buyers and the rest of humanity (I always knew that Web enthusiasts werestrange) Some of these differences are pretty prosaic plusmn online buyers havefewer security worries appreciate the ` quicknessrsquorsquo and flexibility of onlinebuying and see the Web as making buying easier However the other (morepsychological) factors suggest that these preferences are symptomatic of thetype rather than definitional The remainder of Goldsmith and Goldsmithrsquosfindings throw up words like ` confidentrsquorsquo ` innovativersquorsquo ` knowledgeablersquorsquoand ` funrsquorsquo Our e-buyers take the view that ` the special circumstancesof e-commerce make this a unique consumption activityrsquorsquo These people aredifferent and we need to know why and at the same time to understand theresistance of others to e-commerce
Part of the resistance appears to lie in fear (characterised as being a lack ofconfidence) People who do not buy online do not have a great deal of trust in
JOURNAL OF PRODUCT amp BRAND MANAGEMENT VOL 11 NO 2 2002 101
This summary has beenprovided to allow managersand executives a rapidappreciation of the contentof this article Those with aparticular interest in thetopic covered may then readthe article in toto to takeadvantage of the morecomprehensive descriptionof the research undertakenand its results to get the fullbenefit of the materialpresent
the medium This seems to hold true even when they use the Internet for avariety of other activities (information gathering communications games etc)Until these issues of fear (or trust or confidence) are dealt with marketers willstruggle to take the idea of e-commerce into the mainstream of retailing
Removing the fearTwo elements are involved in removing consumer distrust of e-commerceThe first is more confidence with the technology involved in buying onlineBear in mind that most of us who use computers take advantage of a tiny partof the capacity of even basic software Even with comprehensible manualson-screen and online help and ` idiot guidesrsquorsquo we still stick to basicprocessing
Ease-of-use is fundamental to successful e-retailing and so far we havefailed to achieve sufficiently easy systems to remove the consumerrsquos worryabout getting it wrong But this is just one problem and its solution lies asmuch in the relationship between the ordinary consumer and Internettechnology as in specific marketing actions
The second element is purely promotional and is about securing trial andreducing the distrust E-commerce becomes accessible when these barriersare removed and there are many techniques available that marketers canuse
Mail order and direct marketers have always faced resistance to theirchannel Indeed mail order people appreciate that there remains a largechunk of the population that will never buy mail order whatever theincentive Nevertheless these marketers have developed (and tested) avariety of simple techniques to secure trial and build confidence
product and service guarantees
payment on delivery rather than payment with the order
featuring low-risk entry products
no-quibble return policies
product endorsement plusmn by real customers
testimonials and
prize draws free gifts and other order incentives
E-commerce represents a new channel and for some businesses a differentmeans of delivering product But for most businesses and especiallyretailers the Internet does not change the nature of the product itself (a pairof shorts remains a pair of shorts) Rather than reinventing the wheel e-retailers should learn from direct marketers
E-commerce needs more confidence to sell itself successfully but in the finalanalysis the e-retailer does little that is different from the mail ordercompany And the direct marketer knows that profits come from repeatbusiness rather than from the first sale Too many e-commerce operationshave floundered because they ignored the experience of others and tried torun a business without good databases or the strategies to sustain incomefrom existing buyers
Do you want your e-retailing business to succeed Hire an experience directmarketer and you will stand a better than average chance of successPretending that the e-marketers have nothing to learn from old grizzled (andboring) mail order people is a mistake that is probably costing you money
(A preAcirccis of the article ` Buying apparel over the Internetrsquorsquo Supplied byMarketing Consultants for Emerald)
102 JOURNAL OF PRODUCT amp BRAND MANAGEMENT VOL 11 NO 2 2002
different experience could be had in the store where unique accessories or
combinations of clothes could be seen Online apparel buyers and non-
buyers did not differ in their perception that buying online is cheaper than
offline Thus Secklerrsquos (2000) argument that offering price discounts may be
a prime way to attract non-buyers is supported To attract new buyers onlineapparel e-tailers may have to change perceptions that online buying is unsafe
(see Robinson 2000) Web sites must be made simple and easy to use
because non-users are not very confident that they can buy online
successfully In-store demonstrations of online shopping might encourage
non-buyers to shop online As online apparel buying spreads beyond the
innovative and knowledgeable consumer to the less sophisticated shopper
apparel marketers should cater to their unique tastes abilities and habits
This is especially true since the results suggest that many online apparel
buyers will buy online again
The study is limited by the nature of the sample measures specificity and
time studied Lack of randomness in the sample limits generalizability of the
point and interval estimates to a larger population but since the main
purpose of the study was to test theoretical hypotheses about online buyingthis is a minor limitation (Calder et al 1981) No conclusions can be drawn
about concepts that might be related to online apparel buying but were not
measured and the results are limited to the measures employed Similarly
the focal topic was clothing in general and not a specific type (new fashion
sports clothes work clothes etc) Finally since e-commerce and online
consumer behavior are constantly changing phenomena the present study is
only a snapshot picture and not a longitudinal view
Advantages of the study lie in the large sample size and validity of the
measures used Future research should examine online apparel using data
from other demographic socio-economic and national groups of consumers
to expand the scope of the findings The online buyer behaviors studied
should be expanded beyond just buying to include browsing comparison
shopping and combining the Internet with in-store consumption as well asconsumption of specific categories of apparel such as new fashions or
unique sizes and needs As noted in the introduction growth is a major
theme of e-commerce Thus replication studies would be a valuable way to
track changes in online apparel buying over time Accumulation of such
studies would expand our knowledge of both apparel consumer behavior and
consumer Internet behavior to the advantage of both consumer theory and
apparel marketing Finally other researchers could make use of our measures
to study buying behavior in other areas as well
References
Calder BJ Phillips LW and Tybout AM (1981) ` Designing research for application rsquorsquo
Journal of Consumer Research Vol 8 September pp 197-207
Citrin AV Sprott DE Silveman SN and Stem DE Jr (2000) ` Adoption of Internet
shopping the role of consumer innovativenessrsquorsquo Industrial Management amp Data Systems
Vol 100 No 7 pp 294-300
Eastlick MA and Lotz S (1999) ` Profiling potential adopters and non-adopter s of an
interactive electronic shopping mediumrsquorsquo Internationa l Journal of Retail amp Distribution
Management Vol 27 No 6 pp 209-23
eMarketer (2000) ` The e-holiday shopping reportrsquorsquo available at wwwemarketercom
Flynn LR Goldsmith RE and Kim W (2000) ` A cross-cultural validation of three new
marketing scales for fashion research involvement opinion seeking and knowledgersquorsquo
The Journal of Fashion Marketing and Management Vol 4 No 2 pp 110-20
Goldsmith RE (2000) ` How innovativenes s differentiate s online buyersrsquorsquo Quarterly Journal
of Electronic Commerce Vol 1 No 4 pp 323-33
Snapshot picture
Expand the scope of thefindings
JOURNAL OF PRODUCT amp BRAND MANAGEMENT VOL 11 NO 2 2002 99
Goldsmith RE and Bridges E (2000) ` E-tailing vs retailing using attitudes to predict
online buying behavior rsquorsquo Quarterly Journal of Electronic Commerce Vol 1 No 3
pp 245-53
Goldsmith RE and Hofacker CF (1991) ` Measuring consumer innovativeness rsquorsquo Journal of
the Academy of Marketing Science Vol 19 No 3 pp 209-21
Goldsmith RE and McGregor S (1999) ` Electronic commerce an emerging issue in
consumer educationrsquorsquo Proceedings of XIX Internationa l Consumer Studies and Home
Economics Research Conference Belfast
Goldsmith RE and McGregor S (2000) ` E-commerce consumer protection issues and
implications for research and educationrsquorsquo Journal of Consumer Studies amp Home
Economics Vol 24 No 2 pp 124-7
Hair JF Anderson RE Tatham RL and Black WC (1998) Multivariate Data Analysis
5th ed Prentice-Hall Upper Saddle River NJ
Hallberg G (1995) All Consumers Are not Created Equal John Wiley New York NJ
Harvard Management Update (2000) ` Lessons from the online war for customersrsquorsquo
Harvard Management Update January pp 3-4
Hoffman DL and Novak TP (1996) ` Marketing in hypermedia computer-mediated
environments conceptua l foundationsrsquorsquo Journal of Marketing Vol 60 No 3 pp 153-61
Hogg MK Bruce M and Hill AJ (1998) ` Fashion brand preference s among young
consumersrsquorsquo Internationa l Journal of Retail amp Distribution Management Vol 26 No 8
pp 293-300
Huck SW and Cormier WH (1996) Reading Statistics and Research 2nd ed
HarperCollins College Publishers New York NY
Karson E (2000) ` Two dimensions of computer and Internet use a reliable and validated
scalersquorsquo Quarterly Journal of Electronic Commerce Vol 1 No 1 pp 49-60
Katz J and Aspden P (1997) ` Motivations for and barriers to Internet usage results of a
national public opinion surveyrsquorsquo Internet Research Vol 7 No 3 pp 170-88
Kuntz J (2000) ` Age and income play key roles in online salesrsquorsquo Daily News Record
27 March p 19
Limayem M Khalifa M and Frini A (2000) ` What makes consumers buy from the
Internet A longitudinal study of online shoppingrsquorsquo IEEE Transactions on Systems Man
and Cybernetics Part A Systems and Humans Vol 30 No 4 pp 421-32
Murphy R (1999) ` Download Internet news IIrsquorsquo The Journal of Fashion Marketing and
Management Vol 3 No 4 pp 376-7
Nelson J (2000) ` Internet at a glancersquorsquo Business 20 12 September p 279
OrsquoGuinn TC and Faber RJ (1989) ` Compulsive buying a phenomenologica l explorationrsquorsquo
Journal of Consumer Research Vol 16 No 2 pp 147-57
Robinson E (2000) ` Click and coverrsquorsquo Business 20 12 September pp 168-80
Seckler V (2000) ` Survey says Web apparel buys doubledrsquorsquo Womenrsquos Wear Daily 12 July
p 2
Silverman D (2000) ` More women wardrobe online than everrsquorsquo Womenrsquos Wear Daily
31 July p 20
Solomon MR (1999) Consumer Behavior Buying Having and Being 4th ed
Prentice-Hall Upper Saddle River NJ
UCLA (2000) ` The UCLA Internet report surveying the digital futurersquorsquo available at
wwwccpuclaedu
Underhill P (1999) Why We Buy The Science of Shopping Simon amp Schuster
New York NY
Vickery L and Agins T (2001) ` Retailers find Web apparel unprofitable rsquorsquo Wall Street
Journal 6 June p B6
Wilson J (1999) ` Keynote addressrsquorsquo The Journal of Fashion Marketing and Management
Vol 3 No 4 pp 370-6
amp
100 JOURNAL OF PRODUCT amp BRAND MANAGEMENT VOL 11 NO 2 2002
Executive summary and implications for managers andexecutives
Retailing online plusmn know your customer and learn from mail ordermarketingE-commerce and especially online retailing have received much attention agreat deal of thought and significant investment Despite this we still lackany clear understanding of the business models that can deliver successonline For every apparent e-retailing success we get a massive plusmn andusually very expensive plusmn failure We can say plusmn with some safety plusmn that theprospects for another Internet trading investment boom have gone
For marketers this situation is a disappointment We are after all theexperts on distribution and sales channels The failure to make e-retailingwork sits in our court and we continue to chew away at the e-commerce bonein the hope that it will eventually come good At the same time we haveraised questions about the capacity of the technology to deliver what wewant Doubts persist about the security of money transfers online Weak linksbetween real world distribution plusmn getting the product to the customer plusmn andthe cosy virtual world get in the way of seamless service And while gettingthe online equivalent of footfall is easy converting these visitors tocustomers is a massive challenge
Know your customer plusmn the marketerrsquos mantraGoldsmith and Goldsmith observe that while a great deal is said aboutonline processes technology and promotion little is known about the actualonline customer We know too little about the differences between theenthusiastic innovators who buy goods online and the rest who are happy tolook but do not buy
The difference between ` innovatorsrsquorsquo and ` early adoptersrsquorsquo is wellresearched and in general terms understood by marketers E-retailing hasnot taken off because the chasm between these two groups remainsunbridged As a result the apparent mass market for e-commerce remains afuture dream Two-thirds of Americans might have access to the Internet butthey are not using it to buy things plusmn at least not in sufficient numbers
Goldsmith and Goldsmith set out to compare clothes buyers who havebought online with those who have not made this sort of purchaseUnderlying the study is the assumption (supported by research and largelycommon sense) that ` consumers who have previous experience in onlinebuying will be more likely to buy apparel online than those who lack suchexperiencersquorsquo We should also note like Goldsmith and Goldsmith that thepeople who matter to e-retailers are those very similar to existing users whoat present are non-users
Are you frightened of the WebGoldsmith and Goldsmith find that there are substantial differences betweene-buyers and the rest of humanity (I always knew that Web enthusiasts werestrange) Some of these differences are pretty prosaic plusmn online buyers havefewer security worries appreciate the ` quicknessrsquorsquo and flexibility of onlinebuying and see the Web as making buying easier However the other (morepsychological) factors suggest that these preferences are symptomatic of thetype rather than definitional The remainder of Goldsmith and Goldsmithrsquosfindings throw up words like ` confidentrsquorsquo ` innovativersquorsquo ` knowledgeablersquorsquoand ` funrsquorsquo Our e-buyers take the view that ` the special circumstancesof e-commerce make this a unique consumption activityrsquorsquo These people aredifferent and we need to know why and at the same time to understand theresistance of others to e-commerce
Part of the resistance appears to lie in fear (characterised as being a lack ofconfidence) People who do not buy online do not have a great deal of trust in
JOURNAL OF PRODUCT amp BRAND MANAGEMENT VOL 11 NO 2 2002 101
This summary has beenprovided to allow managersand executives a rapidappreciation of the contentof this article Those with aparticular interest in thetopic covered may then readthe article in toto to takeadvantage of the morecomprehensive descriptionof the research undertakenand its results to get the fullbenefit of the materialpresent
the medium This seems to hold true even when they use the Internet for avariety of other activities (information gathering communications games etc)Until these issues of fear (or trust or confidence) are dealt with marketers willstruggle to take the idea of e-commerce into the mainstream of retailing
Removing the fearTwo elements are involved in removing consumer distrust of e-commerceThe first is more confidence with the technology involved in buying onlineBear in mind that most of us who use computers take advantage of a tiny partof the capacity of even basic software Even with comprehensible manualson-screen and online help and ` idiot guidesrsquorsquo we still stick to basicprocessing
Ease-of-use is fundamental to successful e-retailing and so far we havefailed to achieve sufficiently easy systems to remove the consumerrsquos worryabout getting it wrong But this is just one problem and its solution lies asmuch in the relationship between the ordinary consumer and Internettechnology as in specific marketing actions
The second element is purely promotional and is about securing trial andreducing the distrust E-commerce becomes accessible when these barriersare removed and there are many techniques available that marketers canuse
Mail order and direct marketers have always faced resistance to theirchannel Indeed mail order people appreciate that there remains a largechunk of the population that will never buy mail order whatever theincentive Nevertheless these marketers have developed (and tested) avariety of simple techniques to secure trial and build confidence
product and service guarantees
payment on delivery rather than payment with the order
featuring low-risk entry products
no-quibble return policies
product endorsement plusmn by real customers
testimonials and
prize draws free gifts and other order incentives
E-commerce represents a new channel and for some businesses a differentmeans of delivering product But for most businesses and especiallyretailers the Internet does not change the nature of the product itself (a pairof shorts remains a pair of shorts) Rather than reinventing the wheel e-retailers should learn from direct marketers
E-commerce needs more confidence to sell itself successfully but in the finalanalysis the e-retailer does little that is different from the mail ordercompany And the direct marketer knows that profits come from repeatbusiness rather than from the first sale Too many e-commerce operationshave floundered because they ignored the experience of others and tried torun a business without good databases or the strategies to sustain incomefrom existing buyers
Do you want your e-retailing business to succeed Hire an experience directmarketer and you will stand a better than average chance of successPretending that the e-marketers have nothing to learn from old grizzled (andboring) mail order people is a mistake that is probably costing you money
(A preAcirccis of the article ` Buying apparel over the Internetrsquorsquo Supplied byMarketing Consultants for Emerald)
102 JOURNAL OF PRODUCT amp BRAND MANAGEMENT VOL 11 NO 2 2002
Goldsmith RE and Bridges E (2000) ` E-tailing vs retailing using attitudes to predict
online buying behavior rsquorsquo Quarterly Journal of Electronic Commerce Vol 1 No 3
pp 245-53
Goldsmith RE and Hofacker CF (1991) ` Measuring consumer innovativeness rsquorsquo Journal of
the Academy of Marketing Science Vol 19 No 3 pp 209-21
Goldsmith RE and McGregor S (1999) ` Electronic commerce an emerging issue in
consumer educationrsquorsquo Proceedings of XIX Internationa l Consumer Studies and Home
Economics Research Conference Belfast
Goldsmith RE and McGregor S (2000) ` E-commerce consumer protection issues and
implications for research and educationrsquorsquo Journal of Consumer Studies amp Home
Economics Vol 24 No 2 pp 124-7
Hair JF Anderson RE Tatham RL and Black WC (1998) Multivariate Data Analysis
5th ed Prentice-Hall Upper Saddle River NJ
Hallberg G (1995) All Consumers Are not Created Equal John Wiley New York NJ
Harvard Management Update (2000) ` Lessons from the online war for customersrsquorsquo
Harvard Management Update January pp 3-4
Hoffman DL and Novak TP (1996) ` Marketing in hypermedia computer-mediated
environments conceptua l foundationsrsquorsquo Journal of Marketing Vol 60 No 3 pp 153-61
Hogg MK Bruce M and Hill AJ (1998) ` Fashion brand preference s among young
consumersrsquorsquo Internationa l Journal of Retail amp Distribution Management Vol 26 No 8
pp 293-300
Huck SW and Cormier WH (1996) Reading Statistics and Research 2nd ed
HarperCollins College Publishers New York NY
Karson E (2000) ` Two dimensions of computer and Internet use a reliable and validated
scalersquorsquo Quarterly Journal of Electronic Commerce Vol 1 No 1 pp 49-60
Katz J and Aspden P (1997) ` Motivations for and barriers to Internet usage results of a
national public opinion surveyrsquorsquo Internet Research Vol 7 No 3 pp 170-88
Kuntz J (2000) ` Age and income play key roles in online salesrsquorsquo Daily News Record
27 March p 19
Limayem M Khalifa M and Frini A (2000) ` What makes consumers buy from the
Internet A longitudinal study of online shoppingrsquorsquo IEEE Transactions on Systems Man
and Cybernetics Part A Systems and Humans Vol 30 No 4 pp 421-32
Murphy R (1999) ` Download Internet news IIrsquorsquo The Journal of Fashion Marketing and
Management Vol 3 No 4 pp 376-7
Nelson J (2000) ` Internet at a glancersquorsquo Business 20 12 September p 279
OrsquoGuinn TC and Faber RJ (1989) ` Compulsive buying a phenomenologica l explorationrsquorsquo
Journal of Consumer Research Vol 16 No 2 pp 147-57
Robinson E (2000) ` Click and coverrsquorsquo Business 20 12 September pp 168-80
Seckler V (2000) ` Survey says Web apparel buys doubledrsquorsquo Womenrsquos Wear Daily 12 July
p 2
Silverman D (2000) ` More women wardrobe online than everrsquorsquo Womenrsquos Wear Daily
31 July p 20
Solomon MR (1999) Consumer Behavior Buying Having and Being 4th ed
Prentice-Hall Upper Saddle River NJ
UCLA (2000) ` The UCLA Internet report surveying the digital futurersquorsquo available at
wwwccpuclaedu
Underhill P (1999) Why We Buy The Science of Shopping Simon amp Schuster
New York NY
Vickery L and Agins T (2001) ` Retailers find Web apparel unprofitable rsquorsquo Wall Street
Journal 6 June p B6
Wilson J (1999) ` Keynote addressrsquorsquo The Journal of Fashion Marketing and Management
Vol 3 No 4 pp 370-6
amp
100 JOURNAL OF PRODUCT amp BRAND MANAGEMENT VOL 11 NO 2 2002
Executive summary and implications for managers andexecutives
Retailing online plusmn know your customer and learn from mail ordermarketingE-commerce and especially online retailing have received much attention agreat deal of thought and significant investment Despite this we still lackany clear understanding of the business models that can deliver successonline For every apparent e-retailing success we get a massive plusmn andusually very expensive plusmn failure We can say plusmn with some safety plusmn that theprospects for another Internet trading investment boom have gone
For marketers this situation is a disappointment We are after all theexperts on distribution and sales channels The failure to make e-retailingwork sits in our court and we continue to chew away at the e-commerce bonein the hope that it will eventually come good At the same time we haveraised questions about the capacity of the technology to deliver what wewant Doubts persist about the security of money transfers online Weak linksbetween real world distribution plusmn getting the product to the customer plusmn andthe cosy virtual world get in the way of seamless service And while gettingthe online equivalent of footfall is easy converting these visitors tocustomers is a massive challenge
Know your customer plusmn the marketerrsquos mantraGoldsmith and Goldsmith observe that while a great deal is said aboutonline processes technology and promotion little is known about the actualonline customer We know too little about the differences between theenthusiastic innovators who buy goods online and the rest who are happy tolook but do not buy
The difference between ` innovatorsrsquorsquo and ` early adoptersrsquorsquo is wellresearched and in general terms understood by marketers E-retailing hasnot taken off because the chasm between these two groups remainsunbridged As a result the apparent mass market for e-commerce remains afuture dream Two-thirds of Americans might have access to the Internet butthey are not using it to buy things plusmn at least not in sufficient numbers
Goldsmith and Goldsmith set out to compare clothes buyers who havebought online with those who have not made this sort of purchaseUnderlying the study is the assumption (supported by research and largelycommon sense) that ` consumers who have previous experience in onlinebuying will be more likely to buy apparel online than those who lack suchexperiencersquorsquo We should also note like Goldsmith and Goldsmith that thepeople who matter to e-retailers are those very similar to existing users whoat present are non-users
Are you frightened of the WebGoldsmith and Goldsmith find that there are substantial differences betweene-buyers and the rest of humanity (I always knew that Web enthusiasts werestrange) Some of these differences are pretty prosaic plusmn online buyers havefewer security worries appreciate the ` quicknessrsquorsquo and flexibility of onlinebuying and see the Web as making buying easier However the other (morepsychological) factors suggest that these preferences are symptomatic of thetype rather than definitional The remainder of Goldsmith and Goldsmithrsquosfindings throw up words like ` confidentrsquorsquo ` innovativersquorsquo ` knowledgeablersquorsquoand ` funrsquorsquo Our e-buyers take the view that ` the special circumstancesof e-commerce make this a unique consumption activityrsquorsquo These people aredifferent and we need to know why and at the same time to understand theresistance of others to e-commerce
Part of the resistance appears to lie in fear (characterised as being a lack ofconfidence) People who do not buy online do not have a great deal of trust in
JOURNAL OF PRODUCT amp BRAND MANAGEMENT VOL 11 NO 2 2002 101
This summary has beenprovided to allow managersand executives a rapidappreciation of the contentof this article Those with aparticular interest in thetopic covered may then readthe article in toto to takeadvantage of the morecomprehensive descriptionof the research undertakenand its results to get the fullbenefit of the materialpresent
the medium This seems to hold true even when they use the Internet for avariety of other activities (information gathering communications games etc)Until these issues of fear (or trust or confidence) are dealt with marketers willstruggle to take the idea of e-commerce into the mainstream of retailing
Removing the fearTwo elements are involved in removing consumer distrust of e-commerceThe first is more confidence with the technology involved in buying onlineBear in mind that most of us who use computers take advantage of a tiny partof the capacity of even basic software Even with comprehensible manualson-screen and online help and ` idiot guidesrsquorsquo we still stick to basicprocessing
Ease-of-use is fundamental to successful e-retailing and so far we havefailed to achieve sufficiently easy systems to remove the consumerrsquos worryabout getting it wrong But this is just one problem and its solution lies asmuch in the relationship between the ordinary consumer and Internettechnology as in specific marketing actions
The second element is purely promotional and is about securing trial andreducing the distrust E-commerce becomes accessible when these barriersare removed and there are many techniques available that marketers canuse
Mail order and direct marketers have always faced resistance to theirchannel Indeed mail order people appreciate that there remains a largechunk of the population that will never buy mail order whatever theincentive Nevertheless these marketers have developed (and tested) avariety of simple techniques to secure trial and build confidence
product and service guarantees
payment on delivery rather than payment with the order
featuring low-risk entry products
no-quibble return policies
product endorsement plusmn by real customers
testimonials and
prize draws free gifts and other order incentives
E-commerce represents a new channel and for some businesses a differentmeans of delivering product But for most businesses and especiallyretailers the Internet does not change the nature of the product itself (a pairof shorts remains a pair of shorts) Rather than reinventing the wheel e-retailers should learn from direct marketers
E-commerce needs more confidence to sell itself successfully but in the finalanalysis the e-retailer does little that is different from the mail ordercompany And the direct marketer knows that profits come from repeatbusiness rather than from the first sale Too many e-commerce operationshave floundered because they ignored the experience of others and tried torun a business without good databases or the strategies to sustain incomefrom existing buyers
Do you want your e-retailing business to succeed Hire an experience directmarketer and you will stand a better than average chance of successPretending that the e-marketers have nothing to learn from old grizzled (andboring) mail order people is a mistake that is probably costing you money
(A preAcirccis of the article ` Buying apparel over the Internetrsquorsquo Supplied byMarketing Consultants for Emerald)
102 JOURNAL OF PRODUCT amp BRAND MANAGEMENT VOL 11 NO 2 2002
Executive summary and implications for managers andexecutives
Retailing online plusmn know your customer and learn from mail ordermarketingE-commerce and especially online retailing have received much attention agreat deal of thought and significant investment Despite this we still lackany clear understanding of the business models that can deliver successonline For every apparent e-retailing success we get a massive plusmn andusually very expensive plusmn failure We can say plusmn with some safety plusmn that theprospects for another Internet trading investment boom have gone
For marketers this situation is a disappointment We are after all theexperts on distribution and sales channels The failure to make e-retailingwork sits in our court and we continue to chew away at the e-commerce bonein the hope that it will eventually come good At the same time we haveraised questions about the capacity of the technology to deliver what wewant Doubts persist about the security of money transfers online Weak linksbetween real world distribution plusmn getting the product to the customer plusmn andthe cosy virtual world get in the way of seamless service And while gettingthe online equivalent of footfall is easy converting these visitors tocustomers is a massive challenge
Know your customer plusmn the marketerrsquos mantraGoldsmith and Goldsmith observe that while a great deal is said aboutonline processes technology and promotion little is known about the actualonline customer We know too little about the differences between theenthusiastic innovators who buy goods online and the rest who are happy tolook but do not buy
The difference between ` innovatorsrsquorsquo and ` early adoptersrsquorsquo is wellresearched and in general terms understood by marketers E-retailing hasnot taken off because the chasm between these two groups remainsunbridged As a result the apparent mass market for e-commerce remains afuture dream Two-thirds of Americans might have access to the Internet butthey are not using it to buy things plusmn at least not in sufficient numbers
Goldsmith and Goldsmith set out to compare clothes buyers who havebought online with those who have not made this sort of purchaseUnderlying the study is the assumption (supported by research and largelycommon sense) that ` consumers who have previous experience in onlinebuying will be more likely to buy apparel online than those who lack suchexperiencersquorsquo We should also note like Goldsmith and Goldsmith that thepeople who matter to e-retailers are those very similar to existing users whoat present are non-users
Are you frightened of the WebGoldsmith and Goldsmith find that there are substantial differences betweene-buyers and the rest of humanity (I always knew that Web enthusiasts werestrange) Some of these differences are pretty prosaic plusmn online buyers havefewer security worries appreciate the ` quicknessrsquorsquo and flexibility of onlinebuying and see the Web as making buying easier However the other (morepsychological) factors suggest that these preferences are symptomatic of thetype rather than definitional The remainder of Goldsmith and Goldsmithrsquosfindings throw up words like ` confidentrsquorsquo ` innovativersquorsquo ` knowledgeablersquorsquoand ` funrsquorsquo Our e-buyers take the view that ` the special circumstancesof e-commerce make this a unique consumption activityrsquorsquo These people aredifferent and we need to know why and at the same time to understand theresistance of others to e-commerce
Part of the resistance appears to lie in fear (characterised as being a lack ofconfidence) People who do not buy online do not have a great deal of trust in
JOURNAL OF PRODUCT amp BRAND MANAGEMENT VOL 11 NO 2 2002 101
This summary has beenprovided to allow managersand executives a rapidappreciation of the contentof this article Those with aparticular interest in thetopic covered may then readthe article in toto to takeadvantage of the morecomprehensive descriptionof the research undertakenand its results to get the fullbenefit of the materialpresent
the medium This seems to hold true even when they use the Internet for avariety of other activities (information gathering communications games etc)Until these issues of fear (or trust or confidence) are dealt with marketers willstruggle to take the idea of e-commerce into the mainstream of retailing
Removing the fearTwo elements are involved in removing consumer distrust of e-commerceThe first is more confidence with the technology involved in buying onlineBear in mind that most of us who use computers take advantage of a tiny partof the capacity of even basic software Even with comprehensible manualson-screen and online help and ` idiot guidesrsquorsquo we still stick to basicprocessing
Ease-of-use is fundamental to successful e-retailing and so far we havefailed to achieve sufficiently easy systems to remove the consumerrsquos worryabout getting it wrong But this is just one problem and its solution lies asmuch in the relationship between the ordinary consumer and Internettechnology as in specific marketing actions
The second element is purely promotional and is about securing trial andreducing the distrust E-commerce becomes accessible when these barriersare removed and there are many techniques available that marketers canuse
Mail order and direct marketers have always faced resistance to theirchannel Indeed mail order people appreciate that there remains a largechunk of the population that will never buy mail order whatever theincentive Nevertheless these marketers have developed (and tested) avariety of simple techniques to secure trial and build confidence
product and service guarantees
payment on delivery rather than payment with the order
featuring low-risk entry products
no-quibble return policies
product endorsement plusmn by real customers
testimonials and
prize draws free gifts and other order incentives
E-commerce represents a new channel and for some businesses a differentmeans of delivering product But for most businesses and especiallyretailers the Internet does not change the nature of the product itself (a pairof shorts remains a pair of shorts) Rather than reinventing the wheel e-retailers should learn from direct marketers
E-commerce needs more confidence to sell itself successfully but in the finalanalysis the e-retailer does little that is different from the mail ordercompany And the direct marketer knows that profits come from repeatbusiness rather than from the first sale Too many e-commerce operationshave floundered because they ignored the experience of others and tried torun a business without good databases or the strategies to sustain incomefrom existing buyers
Do you want your e-retailing business to succeed Hire an experience directmarketer and you will stand a better than average chance of successPretending that the e-marketers have nothing to learn from old grizzled (andboring) mail order people is a mistake that is probably costing you money
(A preAcirccis of the article ` Buying apparel over the Internetrsquorsquo Supplied byMarketing Consultants for Emerald)
102 JOURNAL OF PRODUCT amp BRAND MANAGEMENT VOL 11 NO 2 2002
the medium This seems to hold true even when they use the Internet for avariety of other activities (information gathering communications games etc)Until these issues of fear (or trust or confidence) are dealt with marketers willstruggle to take the idea of e-commerce into the mainstream of retailing
Removing the fearTwo elements are involved in removing consumer distrust of e-commerceThe first is more confidence with the technology involved in buying onlineBear in mind that most of us who use computers take advantage of a tiny partof the capacity of even basic software Even with comprehensible manualson-screen and online help and ` idiot guidesrsquorsquo we still stick to basicprocessing
Ease-of-use is fundamental to successful e-retailing and so far we havefailed to achieve sufficiently easy systems to remove the consumerrsquos worryabout getting it wrong But this is just one problem and its solution lies asmuch in the relationship between the ordinary consumer and Internettechnology as in specific marketing actions
The second element is purely promotional and is about securing trial andreducing the distrust E-commerce becomes accessible when these barriersare removed and there are many techniques available that marketers canuse
Mail order and direct marketers have always faced resistance to theirchannel Indeed mail order people appreciate that there remains a largechunk of the population that will never buy mail order whatever theincentive Nevertheless these marketers have developed (and tested) avariety of simple techniques to secure trial and build confidence
product and service guarantees
payment on delivery rather than payment with the order
featuring low-risk entry products
no-quibble return policies
product endorsement plusmn by real customers
testimonials and
prize draws free gifts and other order incentives
E-commerce represents a new channel and for some businesses a differentmeans of delivering product But for most businesses and especiallyretailers the Internet does not change the nature of the product itself (a pairof shorts remains a pair of shorts) Rather than reinventing the wheel e-retailers should learn from direct marketers
E-commerce needs more confidence to sell itself successfully but in the finalanalysis the e-retailer does little that is different from the mail ordercompany And the direct marketer knows that profits come from repeatbusiness rather than from the first sale Too many e-commerce operationshave floundered because they ignored the experience of others and tried torun a business without good databases or the strategies to sustain incomefrom existing buyers
Do you want your e-retailing business to succeed Hire an experience directmarketer and you will stand a better than average chance of successPretending that the e-marketers have nothing to learn from old grizzled (andboring) mail order people is a mistake that is probably costing you money
(A preAcirccis of the article ` Buying apparel over the Internetrsquorsquo Supplied byMarketing Consultants for Emerald)
102 JOURNAL OF PRODUCT amp BRAND MANAGEMENT VOL 11 NO 2 2002