Buying apparel over the Internet

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

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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


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


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 over the Internet is quicker than


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


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


Table III Factor analysis of Internet knowledge and innovativeness items

Common factor analysis

Focal variables


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


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


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


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


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


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


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


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


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)


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









Method

Survey participants





















white women

Questionnaire






















Ethnic distribution

















Internet

Yes

No

562

4

993

07


clothing online

Yes

No

99

467

175

825


you purchase online

Very often

Often

Sometimes

Rarely

Never

4

18

119

201

224

07

32

210

355

396




About once a week


weeks



a month


I never do

3

6

12

30

283

232

05

11

21

53

500

410



January 1 2000

plusmn plusmn times



Very often

Often

Sometimes

Rarely

Never

Missing

83

179

226

55

21

2

147

316

399

97

37

04



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




coming year

Definitely will buy

Probably will buy

Might buy



Missing

82

107

208

141

23

5

145

189

367

249

41

09



average month






Results



















Shopping is fun 083


happy 080


shoppingb 069







Internetb 064








Internetb 089









Eigenvalue 55 28 15 14 11 10



adequacy = 0840



Composite measure










































Internet 065







Eigenvalue 415 155






Focal variables


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





al (2000)




























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


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














online buyers































(HOURS)



(LIKELY)









Discussion























































Positive attitudes






































References





Vol 100 No 7 pp 294-300










Snapshot picture





pp 245-53


















pp 293-300








27 March p 19











p 2


31 July p 20




wwwccpuclaedu


New York NY


Journal 6 June p B6


Vol 3 No 4 pp 370-6

amp






















testimonials and














Method

Survey participants





















white women

Questionnaire






















Ethnic distribution

















Internet

Yes

No

562

4

993

07


clothing online

Yes

No

99

467

175

825


you purchase online

Very often

Often

Sometimes

Rarely

Never

4

18

119

201

224

07

32

210

355

396




About once a week


weeks



a month


I never do

3

6

12

30

283

232

05

11

21

53

500

410



January 1 2000

plusmn plusmn times



Very often

Often

Sometimes

Rarely

Never

Missing

83

179

226

55

21

2

147

316

399

97

37

04



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




coming year

Definitely will buy

Probably will buy

Might buy



Missing

82

107

208

141

23

5

145

189

367

249

41

09



average month






Results



















Shopping is fun 083


happy 080


shoppingb 069







Internetb 064








Internetb 089









Eigenvalue 55 28 15 14 11 10



adequacy = 0840



Composite measure










































Internet 065







Eigenvalue 415 155






Focal variables


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





al (2000)




























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


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














online buyers































(HOURS)



(LIKELY)









Discussion























































Positive attitudes






































References





Vol 100 No 7 pp 294-300










Snapshot picture





pp 245-53


















pp 293-300








27 March p 19











p 2


31 July p 20




wwwccpuclaedu


New York NY


Journal 6 June p B6


Vol 3 No 4 pp 370-6

amp






















testimonials and





















Internet

Yes

No

562

4

993

07


clothing online

Yes

No

99

467

175

825


you purchase online

Very often

Often

Sometimes

Rarely

Never

4

18

119

201

224

07

32

210

355

396




About once a week


weeks



a month


I never do

3

6

12

30

283

232

05

11

21

53

500

410



January 1 2000

plusmn plusmn times



Very often

Often

Sometimes

Rarely

Never

Missing

83

179

226

55

21

2

147

316

399

97

37

04



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




coming year

Definitely will buy

Probably will buy

Might buy



Missing

82

107

208

141

23

5

145

189

367

249

41

09



average month






Results



















Shopping is fun 083


happy 080


shoppingb 069







Internetb 064








Internetb 089









Eigenvalue 55 28 15 14 11 10



adequacy = 0840



Composite measure










































Internet 065







Eigenvalue 415 155






Focal variables


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





al (2000)




























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


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














online buyers































(HOURS)



(LIKELY)









Discussion























































Positive attitudes






































References





Vol 100 No 7 pp 294-300










Snapshot picture





pp 245-53


















pp 293-300








27 March p 19











p 2


31 July p 20




wwwccpuclaedu


New York NY


Journal 6 June p B6


Vol 3 No 4 pp 370-6

amp






















testimonials and









Results



















Shopping is fun 083


happy 080


shoppingb 069







Internetb 064








Internetb 089









Eigenvalue 55 28 15 14 11 10



adequacy = 0840



Composite measure










































Internet 065







Eigenvalue 415 155






Focal variables


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





al (2000)




























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


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














online buyers































(HOURS)



(LIKELY)









Discussion























































Positive attitudes






































References





Vol 100 No 7 pp 294-300










Snapshot picture





pp 245-53


















pp 293-300








27 March p 19











p 2


31 July p 20




wwwccpuclaedu


New York NY


Journal 6 June p B6


Vol 3 No 4 pp 370-6

amp






















testimonials and















































Internet 065







Eigenvalue 415 155






Focal variables


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





al (2000)




























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


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














online buyers































(HOURS)



(LIKELY)









Discussion























































Positive attitudes






































References





Vol 100 No 7 pp 294-300










Snapshot picture





pp 245-53


















pp 293-300








27 March p 19











p 2


31 July p 20




wwwccpuclaedu


New York NY


Journal 6 June p B6


Vol 3 No 4 pp 370-6

amp






















testimonials and







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





al (2000)




























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


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














online buyers































(HOURS)



(LIKELY)









Discussion























































Positive attitudes






































References





Vol 100 No 7 pp 294-300










Snapshot picture





pp 245-53


















pp 293-300








27 March p 19











p 2


31 July p 20




wwwccpuclaedu


New York NY


Journal 6 June p B6


Vol 3 No 4 pp 370-6

amp






















testimonials and










al (2000)




























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


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














online buyers































(HOURS)



(LIKELY)









Discussion























































Positive attitudes






































References





Vol 100 No 7 pp 294-300










Snapshot picture





pp 245-53


















pp 293-300








27 March p 19











p 2


31 July p 20




wwwccpuclaedu


New York NY


Journal 6 June p B6


Vol 3 No 4 pp 370-6

amp






















testimonials and
















online buyers































(HOURS)



(LIKELY)









Discussion























































Positive attitudes






































References





Vol 100 No 7 pp 294-300










Snapshot picture





pp 245-53


















pp 293-300








27 March p 19











p 2


31 July p 20




wwwccpuclaedu


New York NY


Journal 6 June p B6


Vol 3 No 4 pp 370-6

amp






















testimonials and







Discussion























































Positive attitudes






































References





Vol 100 No 7 pp 294-300










Snapshot picture





pp 245-53


















pp 293-300








27 March p 19











p 2


31 July p 20




wwwccpuclaedu


New York NY


Journal 6 June p B6


Vol 3 No 4 pp 370-6

amp






















testimonials and











































References





Vol 100 No 7 pp 294-300










Snapshot picture





pp 245-53


















pp 293-300








27 March p 19











p 2


31 July p 20




wwwccpuclaedu


New York NY


Journal 6 June p B6


Vol 3 No 4 pp 370-6

amp






















testimonials and









pp 245-53


















pp 293-300








27 March p 19











p 2


31 July p 20




wwwccpuclaedu


New York NY


Journal 6 June p B6


Vol 3 No 4 pp 370-6

amp






















testimonials and



























testimonials and

















testimonials and







Documents

Buying apparel over the Internet