READ 3 articles

Consumer Attitudes Toward Fashion Counterfeits: Application of the Theory of Planned Behavior

Hyejeong Kim, 1

and Elena Karpova 2

Abstract This study examines consumer motivations that can explain attitudes toward purchasing fashion counterfeit goods and tests the underlying mechanism of intent to purchase fashion counterfeits based on the theory of planned behavior. A random sample of female college students (N ¼ 336) participate in this study. Product appearance, past purchase behavior, value consciousness, and normative susceptibility are significant predictors of attitude toward buying fashion counterfeit goods. Attitude, subjective norm, and perceived behavioral control are significantly related to intent to purchase fashion counterfeit goods. This research extends the theory of planned behavior and tests two additional paths that significantly improve explanatory power of the theory and prediction of consumer intent to buy fashion counterfeit goods.

Keywords counterfeits, fashion, theory of planned behavior

Product counterfeiting is a global issue that causes significant economic and social problems

(Gilgoff, 2004). Counterfeit trade is estimated at $500 billion globally, accounting for between

5% and 7% of the total world trade (Johnson, 2006). The U.S. share represents $286.8 billion (63%) of that (Tucker, 2005). The International Anti-Counterfeiting Coalition (ICC) reported that in the United States counterfeit goods and piracy are responsible for the loss of more than $200

billion and 750,000 jobs a year (Cook & Writer, 2006). The city of New York, with estimated annual

counterfeit sales of $23 billion, loses approximately $1 billion in tax revenue annually (Tucker, 2005).

‘‘Counterfeit’’ refers to copies made to deceive consumer into believing that the goods are

authentic (Bamossy & Scammon, 1985), whereas ‘‘knock-off’’ refers to copies that are not identical

but similar to the authentic goods in essence, name, form, or meaning (Prendergast, Chuen, & Phau,

2002). Counterfeiting is a serious problem for the fashion industry (Oldenburg, 2005). The U.S.

Customs and Border Control reported at midyear 2006 that 45% of seized counterfeits were fashion

1 Auburn University

2 Iowa State University

Corresponding Author:

Hyejeong Kim, PhD, Department of Consumer Affairs, Auburn University, 308 Spidle Hall, Auburn, AL 36849

E-mail [email protected]; phone: (334) 844-1316; fax: (334) 844-1340.

Clothing & Textiles Research Journal 28(2) 79-94 ª The Author(s) 2010 Reprints and permission: sagepub.com/journalsPermissions.nav DOI: 10.1177/0887302X09332513 http://ctrj.sagepub.com

79 at CALIFORNIA ST UNIV NORTHRIDGE on October 25, 2015ctr.sagepub.comDownloaded from

goods, including apparel and accessories (Casabona, 2006). Among the top five brands

counterfeited, four (with Microsoft the fifth) were fashion brands: Louis Vuitton, Nike, Gucci, and

Prada (McGlone, 2006). Many fashion companies (e.g., Rolex, Abercrombie & Fitch) use private

investigators and spend millions each year to fight counterfeiting (Pallay, 2006; Ryan, 2006).

Trademark protection costs directly affect consumers through higher prices on authentic goods

(Bamossy & Scammon, 1985).

Although an increasing body of literature has investigated why consumers purchase counterfeits,

most policies and previous studies have focused on the supply dimension (Bamossy & Scammon,

1985; Bush, Bloch, & Dawson, 1989). Despite the U.S. legal policies (e.g., the Trademark

Counterfeiting Act of 1984) and industry efforts to limit production and sale of counterfeits, fashion

counterfeiting is increasing (Casabona, 2006), driven by strong consumer demand for upscale brands

and perceived price advantage over authentic goods (Bloch, Bush, & Champbell, 1993). Many peo-

ple knowingly purchase counterfeit products (ICC Counterfeiting Intelligence Bureau, 2004), an

activity termed as nondeceptive counterfeiting (Grossman & Shapiro, 1988). Therefore, in many

cases the purpose of selling counterfeits is not to deceive but to satisfy consumers (Arellano,

1994). Thus, even though government authorities and industry fight to restrain this illegal activity,

counterfeits are in the market because there is a demand. To develop appropriate policies, it is

critical to focus on consumers’ motivations, attitudes, and the underlying mechanism of intent to

purchase fashion counterfeits. The purpose of this study was to (a) identify motivations that influ-

ence attitudes toward buying fashion counterfeits; (b) use the theory of planned behavior to examine

the relationships among attitude toward buying fashion counterfeits, subjective norms influencing

the purchase of fashion counterfeits, and intent to purchase fashion counterfeits; and (c) test the

inclusion of additional relationships that are expected to improve the explanatory power of the

theory in the context of buying fashion counterfeits.

Motivations for Buying Fashion Counterfeit Goods

Based on research that studied counterfeiting (e.g., Albers-Miller, 1999; Ang, Chen, Lim, &

Tambyah, 2001; Bloch et al., 1993; Ha & Lennon, 2006), eight motivations were selected for

investigation in the context of fashion counterfeits. These included psychographic characteristics,

product appearance, and past purchase behavior.

Psychographic characteristics. Others’ influence is one of the most important determinants of an individual’s behavior (Bearden, Netemeyer, & Teel, 1989). Ang et al. (2001) suggested that

informational susceptibility and normative susceptibility, as social influences, affect attitudes

toward purchasing counterfeits. Informational susceptibility is the tendency to learn about products

or brands by seeking information from knowledgeable others, or making inferences based on obser-

ving people’s behaviors (Bearden et al., 1989). For instance, a consumer may observe that some peo-

ple have luxury fashion items and they appear to be popular. Therefore, the consumer may purchase

counterfeits as an alternative to authentic goods. Normative susceptibility refers to ‘‘the tendency to

conform to the expectations of others’’ in consumption context (Bearden et al., 1989, p. 474). When

people think that significant others may not like or approve of buying fashion counterfeits, or that

buying these goods will not make good impressions, they are likely to have negative attitudes toward

purchasing counterfeits. Ang et al. (2001) reported a positive relationship between informational

susceptibility and a negative relationship between normative susceptibility and attitude toward coun-

terfeit music CDs.

Value consciousness is defined as ‘‘a concern for paying lower prices, subject to some quality

constraint’’ (Lichtenstein, Netemeyer, & Burton, 1990, p. 56). Value consciousness differs from

price consciousness in that value includes ‘‘get’’ (i.e., the benefits a buyer acquires from seller’s

80 Clothing & Textiles Research Journal 28(2)

80 at CALIFORNIA ST UNIV NORTHRIDGE on October 25, 2015ctr.sagepub.comDownloaded from

offering) and ‘‘give’’ (i.e., the cost the buyer pays to acquire the offering) components (Parasuraman

& Grewal, 2000). Consumers tend to select counterfeits when there is a distinct price advantage over

authentic goods (Albers-Miller, 1999; Bloch et al., 1993; Cordell, Wongtade, & Kieschnick, 1996;

Prendergast et al., 2002; Wee, Tan, & Cheok, 1995). Ang et al. (2001) found a positive relationship

between value consciousness and attitude toward counterfeit music CDs. Tom et al. (1998) reported

that counterfeit buyers rated fake t-shirts as comparable to the legitimate products in terms of brand,

durability/quality, and function, but superior in price. Therefore, in purchasing fashion counterfeits,

consumers may perceive that what they get exceeds the amount they pay because of the design and/

or status associated with upscale designer names.

Integrity, as it is related to lawfulness, is linked to responsibility, honesty, and self-control

(Rokeach, 1968). Although in the United States purchasing counterfeits is not criminal or illegal,

lawfulness may predict whether a consumer is likely to engage in the practice because counterfeiting

involves illegal activities (e.g., infringing intellectual property and selling unlawful products).

Researchers have found that more lawful-minded consumers are less willing to buy counterfeits

(Cordell et al., 1996), and integrity is negatively associated with attitude toward counterfeits (Ang

et al., 2001; de Matos, Ituassu, & Rossi, 2007). Researchers have tested informational and normative

susceptibility, value consciousness, and integrity in the context of counterfeited general consumer

products and CDs, not specifically fashion counterfeits. Because fashion goods are consumed pub-

licly, they are often acquired to make a statement and impress others. In contrast, CDs are often used

in private settings, when few people can observe the products. The difference in product usage may

trigger different motivations for buying counterfeits. Therefore, it is important to retest these

constructs in the context of fashion goods.

Status consumption is ‘‘the motivational process by which individuals strive to improve their social

standing through conspicuous consumption of products that confer or symbolize status for both the

individual and surrounding others’’ (Eastman, Fredenberger, Campbell, & Calvert, 1997, p. 54). Pos-

session of specific products or brands may symbolize status, such as social class (O’Shaughnessy,

1992). Fashion goods are used to project socioeconomic status (Damhorst, Miller, & Michelman,

2001). For instance, carrying designer goods is like having a permit into high society, even though the

item might be not real (Garza, 2006). When consumers cannot afford genuine goods, they may pur-

chase counterfeits hoping to convey the status associated with the authentic brand. Wee et al.

(1995) found that brand image was positively related to intent to purchase counterfeits and suggested

that status conscious consumers were more likely to purchase fashion counterfeits.

Materialism refers to the importance an individual attaches to worldly possessions (Belk, 1984).

Richins and Dawson (1992) identified three materialistic traits: acquisition centrality, acquisition as

the pursuit of happiness, and possession-defined success. Acquisition centrality means that

materialists view possessions and acquisitions as the core value of their lives. Acquisition as the

pursuit of happiness means that materialists consider possessions or acquisitions as requisite to

satisfaction and happiness. Possession-defined success refers to the tendency to judge people’s

achievements by their possessions. Researchers have found that consumers tend to perceive

counterfeits as a way to obtain lower-priced branded goods to satisfy materialistic needs (Albers-

Miller, 1999; Bloch et al., 1993).

Product appearance. Wee et al. (1995) identified three types of product characteristics related to purchase of counterfeits: durability, quality, and physical appearance. We considered only physical

appearance for two reasons. First, in fashion counterfeiting, product appearance, including trade-

marks or logos, is counterfeiters’ main reason for copying the product and indicates the original

source of the product. Second, consumers have reported (Kim & Karpova, 2005) that appearance

is the major reason for buying fashion counterfeits. Scholars argue that distinctive design of fashion

Kim and Karpova 81

81 at CALIFORNIA ST UNIV NORTHRIDGE on October 25, 2015ctr.sagepub.comDownloaded from

luxury goods, including trademark and logo, motivates consumers to purchase fashion counterfeits

(Ha & Lennon, 2006; Prendergast et al., 2002).

Past purchase behavior. Past behavior may predict attitude toward the behavior in the future. d’Astous, Colbert, and Montpetit (2005) suggested that an individual tends to use ‘‘I’ve-done-it-

in-the-past’’ justification when determining whether to engage in some activities (p. 293). Past beha-

vior is also a source of information for identifying one’s attitude (Bem, 1972). d’Astous et al. (2005)

found that past behavior was a significant predictor of attitude toward and intent to engage in

music piracy. Therefore, compared with consumers who have not purchased fashion counterfeits,

consumers who have purchased fashion counterfeit goods in the past may have more positive

attitudes toward engaging in the behavior in the future.

Based on the above discussion, we hypothesized relationships between consumer motivations and

attitudes toward buying fashion counterfeit goods as follows:

Hypothesis 1a: Informational susceptibility is positively related to attitude.

Hypothesis 1b: Normative susceptibility is negatively related to attitude.

Hypothesis 1c: Value consciousness is positively related to attitude.

Hypothesis 1d: Integrity is negatively related to attitude.

Hypothesis 1e: Status consumption is positively related to attitude.

Hypothesis 1f: Materialism is positively related to attitude.

Hypothesis 1g: Product appearance of counterfeits is positively related to attitude.

Hypothesis 1h: Past purchase behavior is positively related to attitude.

Attitude Toward Buying Fashion Counterfeit Goods

The theory of planned behavior (TPB) explains how an individual’s attitude toward behavior,

subjective norm, and perceived behavioral control predict intent, which in turn, leads to

behavior (Ajzen, 1985). The theory defines intent as decision to act in a particular way

(Fishbein & Ajzen, 1975), and subjective norm refers to social influence on a particular beha-

vior (Young & Kent, 1985). For instance, an individual might have a favorable attitude toward

buying counterfeit goods. However, intent to purchase may be influenced by the person’s belief

about the subjective norm related to counterfeit purchasing. Furthermore, behavior, at least in

part, may be beyond consumer voluntary control. TPB addresses the issue by including per-

ceived behavioral control, which refers to perception about how difficult it is to perform the

behavior of interest (Ajzen, 1991). If the behavior is not completely determined by the individ-

ual’s will, that person needs special resources and opportunities to carry out the behavior. The

perceived availability of resources and opportunities may influence behavioral intent and per-

formance of the behavior. Hypotheses 2 through 4 were based on TPB in the context of fashion

counterfeits (see Figure 1):

Hypothesis 2: Attitude toward purchasing fashion counterfeit goods is positively related to pur-

chase intent toward fashion counterfeits.

Hypothesis 3: Perceived behavioral control is positively related to purchase intent toward fashion

counterfeits.

Hypothesis 4: Subjective norm is positively related to purchase intent toward fashion

counterfeits.

Research has supported predictability of TPB in the context of immoral activities. Chang (1998)

compared the validities of TPB and theory of reasoned action as applied to the context of illegal

82 Clothing & Textiles Research Journal 28(2)

82 at CALIFORNIA ST UNIV NORTHRIDGE on October 25, 2015ctr.sagepub.comDownloaded from

software copying. d’Astous et al. (2005) tested TPB in the area of online music piracy. Penz and

Stöttinger (2005) explored fashion counterfeiting using TPB. However, Randall and Gibson

(1991) criticized studies that tested only relationships hypothesized by the theory and ignored other

linkages between the constructs. Previous research has found that normative and attitudinal con-

structs may be dependent and, therefore, subjective norm could influence attitude toward behavior

(Shepherd & O’Keefe, 1984; Vallerand, Deshaies, Cuerrier, & Mongeau, 1992). Burke (2006)

argued that ‘‘norms not only prescribe attitudes and perceptions but also behavior’’ (p. 124). Atti-

tudes are formed through interactions with people (Kiecolt, 1988), who may influence an individual

through social pressure and behavioral regulations. Chang (1998) found that subjective norm was

positively related to attitude toward software piracy.

Subjective norm may also affect perceptions about the ease or difficulty of performing a

behavior. Perceived behavioral control reflects past experience, knowledge about products, and

anticipated obstacles (Randall & Gibson, 1991). Because people share information, knowledge,

and experiences with family and friends, opinions of significant others may influence percep-

tions about amount of control over certain behaviors. When a consumer thinks that others dis-

approve of buying fashion counterfeits, the consumer may experience a psychological barrier to

carrying out the behavior, which would result in decreased perceived behavioral control. In this

study, two paths (between subjective norm and attitude toward purchasing fashion counterfeit

goods and subjective norm and perceived behavioral control) were tested in addition to the

relationships suggested by TPB:

Hypothesis 5: Subjective norm is positively related to attitude toward purchasing fashion counter-

feit goods.

Hypothesis 6: Subjective norm is positively related to perceived behavioral control.

NORM1

C O

N 1

Purchase intent

.21 (3.75)***

.57 (8.28)***

.66 (10.40)***

.54 (4.73)*** .14 (2.58)**

Subjective norm

C O

N 2

C O

N 3

Perceived behavioral

control

A T

T I1

A T

T I2

A T

T I3

A T

T I4

A T

T I5

Attitude toward

purchasing

NORM2

NORM3

INTENT1

INTENT2

INTENT3

Figure 1. The Latent Model With 14 Indicators and 4 Latent Variables Note: Standardized estimates shown (t-values in parentheses) w2 ¼ 228.93, df ¼ 72, p ¼ 0.0, RMSEA ¼ 0.077, NFI ¼ 0.97, CFI ¼ 0.98. ** p <.01. *** p <.001.

Kim and Karpova 83

83 at CALIFORNIA ST UNIV NORTHRIDGE on October 25, 2015ctr.sagepub.comDownloaded from

Method

Sample and Procedure

The data were collected using a Web-based survey. A random sample of college women was drawn

from a large Midwestern university. College women constitute an appropriate sample for this study

because students are likely to be heavy users of product categories that are frequently counterfeited

(Cordell et al., 1996). Compared with men, women are more likely to be heavy buyers of clothing

and counterfeit clothing and accessories (Cheung & Prendergast, 2005). Researchers have identified

college students as one consumer segment that knowingly purchases counterfeits (Chakraborty,

Allred, Sukhdial, & Bristol, 1997). After Institutional Review Board approval, 4,000 e-mail

addresses were randomly generated from the pool of all female students enrolled in the university

at the time of data collection. A recruiting e-mail containing a letter of research introduction with

consent elements and the survey URL was distributed to students. Along with a definition of coun-

terfeits, the instructions defined fashion counterfeits to include apparel, bags, purses, shoes, watches,

and perfume. To encourage participation, all participants’ names were entered into 10 drawings for a

$10 department store gift certificate.

Instrument Development

All scales, except attitude toward purchasing fashion counterfeit goods and past purchase behavior,

used 7-point scales (1 ¼ strongly disagree; 7 ¼ strongly agree). Consumer susceptibility was mea- sured with eight normative (a¼ .82) and four informational (a¼ .88) susceptibility items developed by Bearden et al. (1989). Four items from Lichtenstein et al. (1990) were used to measure value con-

sciousness, a ¼ .81 (Ang et al., 2001). Integrity was assessed by four items (honesty, politeness, responsibility, and self-control) from Vinson, Munson, and Nakanishi (1977) and a 7-point scale

(1 ¼ least important; 7 ¼ most important) was used (a ¼ .78; Ang et al., 2001). Status consumption was measured using Marcoux, Filiatrault, and Chèron’s (1997) scale. Four (out of 18) conspicuous

consumption items (a ¼ .89) that measured social status demonstration and interpersonal mediation were adapted to reflect the fashion counterfeit context (e.g., ‘‘Well-known designers’ products mean

higher socioeconomic status’’). Materialism was measured using 18 items (6 Success: a¼ .74-.78, 7 Centrality: a ¼ .71-.75, and 5 Happiness: a ¼ .73-.83, subscale items) developed by Richins and Dawson (1992). Three product appearance items were developed for this study: ‘‘I would buy fash-

ion counterfeit goods because of the design’’; ‘‘I would purchase fashion counterfeit goods because

of the appearance’’; and ‘‘I would buy fashion counterfeit goods because they look good.’’ Past pur-

chase behavior was measured by a nominal scale, ‘‘Have you ever purchased fashion counterfeit

goods?’’

Five items from Chang (1998), Fitzmaurice (2005), and Madden, Ellen, and Ajzen (1992)

assessed attitude toward purchasing fashion counterfeits using a 7-point semantic differential scale.

The subjective norm measure (a ¼ .82) included three items from Fitzmaurice (2005). The per- ceived behavioral control scale (a ¼ .70) consisted of three items from Chang (1998). Purchase intent was measured by three items (a¼ .92) from Madden et al. (1992). Respondents’ demographic characteristics were collected: age and major (open-ended), gender and ethnicity (close-ended).

Results

A total of 385 responses were collected, resulting in a 9.6% response rate; of these, 366 were com- plete, usable questionnaires. The average respondent was 22-years-old and the majority of partici-

pants (90.6%) were Caucasian American. Participants were enrolled in 80 different majors. Only 328 out of 366 participants answered the question about past purchase behavior: 169 (51.5%) had

84 Clothing & Textiles Research Journal 28(2)

84 at CALIFORNIA ST UNIV NORTHRIDGE on October 25, 2015ctr.sagepub.comDownloaded from

purchased fashion counterfeits, whereas 159 (48.5%) had not. Although the survey response rate was relatively low, the proportion between fashion counterfeit buyers and nonbuyers was consistent with

those of other fashion counterfeit studies (e.g., Ha & Lennon, 2006).

Preliminary Analyses

All multi-item variables were subjected to principal component analysis with varimax rotation and

reliability (Cronbach’s alpha) analysis. Unidimensionality was confirmed for all scales, except

materialism; three factors were extracted for the scale (success, centrality, and happiness) as sug-

gested by Richins and Dawson (1992). The factor loadings of each item were above .50, but below

.30 on other factors (Kline, 1998). Cronbach’s alphas for all measures were above .60: normative

susceptibility (.92), informational susceptibility (.74), value consciousness (.85), status consumption

(.84), success (.84), centrality (.84), happiness (.81), product appearance (.93), integrity (.63), atti-

tude toward purchasing fashion counterfeit goods (.92), subjective norm (.82), perceived behavioral

control (.67), and purchase intent (.97). Although an alpha coefficient higher than .70 is preferable, it

may fall to .60 (Hair, Anderson, Tatham, & Black, 1998).

Hypotheses Testing

Hypotheses 1a through 1h were tested using a stepwise multiple regression analysis to determine

motivations that account for attitude toward purchasing fashion counterfeit goods. The independent

variables 1

were informational and normative susceptibility, value consciousness, integrity, status

consumption, materialism, product appearance, and past purchase behavior. The dependent variable

was attitude toward buying fashion counterfeit goods. The results showed that normative suscept-

ibility, value consciousness, product appearance, and past purchase behavior were significant pre-

dictors of attitude toward purchasing fashion counterfeit goods, supporting Hypotheses 1b, 1c,

1g, and 1h (see Table 1).

Hypotheses 2 through 6, based on the extended TPB, were tested through structural equation

modeling (SEM), using maximum likelihood estimation with covariance matrix as the input. A mea-

surement model, including 14 variables and 4 latent variables, was tested to examine the quality of

the measures. Although the w2 goodness-of-fit statistic for the perfect fit model was significant (w2 ¼ 218.53, df ¼ 71, p ¼ .00), based on established fit indices, the measurement model was considered to show a fair fit (RMSEA ¼ .075; NFI ¼ .97; and CFI ¼ .98). All factor loadings were significant at the level of .001. The results of the confirmatory factor analysis provide evidence of convergent and

discriminant validity of the measurement model (Fornell & Larcker, 1981) (see Table 2). Although

the variance of perceived behavioral control (.48) was lower than the standard (.50) recommended

by Fornell and Larcker (1981), the construct was included in the SEM model, considering the

Table 1. Results of Stepwise Multiple Regression

Step Variable b SE b Two-Tailed Significance

1 Product appearance .379 .040 .496 .000 2 Normative susceptibility �.111 .047 �.110 .018 3 Past purchase behavior .306 .124 .125 .014 4 Value consciousness .134 .054 .114 .014

Note. R 2 ¼ .330, F(4, 320) ¼ 40.851, p ¼ .000, b ¼ unstandardized coefficients, SE ¼ Std. Error, b¼ standardized coefficients,

Dependent variable: attitude toward purchasing fashion counterfeit goods.

Kim and Karpova 85

85 at CALIFORNIA ST UNIV NORTHRIDGE on October 25, 2015ctr.sagepub.comDownloaded from

adequate reliability of the scale and the importance of the construct in the model. 2

The correlations

among the latent variables are shown in Table 3.

Because the sample in the study included two groups of consumers (consumers who had pur-

chased fashion counterfeits and those who had not), multiple group analyses were performed to

examine the group difference in terms of the SEM. The data set was split into fashion counterfeit

buyers (N ¼ 169) and nonbuyers (N ¼ 159). Two multiple group models were tested, allowing the path coefficients to be variant and forcing the coefficients to be invariant. A chi-square difference

test was performed to examine whether the two models were statistically different—the model

allowing the coefficients to be variant (w2 ¼ 320.80, df ¼ 144, p ¼ .00) and the model forcing the coefficient to be invariant (w2 ¼ 326.90, df ¼ 149, p ¼ .00). The result showed that the two models were not significantly different (Dw2 ¼ 6.1, Ddf ¼ 5) in terms of the path coefficients. Therefore, the two groups of consumers (buyers and nonbuyers) were combined to test the theoretical model.

A latent model, combining buyers and nonbuyers, was tested to examine the hypothesized rela-

tionships (Hypotheses 2 through 6). As a result of testing the latent model with 14 indicators and 4

latent variables, w2 goodness-of-fit statistic for the perfect fit model was significant, but based on established fit indices, the model had a fair fit (w2 ¼ 228.93, df ¼ 72, p ¼ .00, RMSEA ¼ .077, NFI ¼ .97, CFI ¼ .98). Based on the SEM analysis, Hypotheses 2 through 6 were supported (see Table 4 and Figure 1). Attitude toward purchasing fashion counterfeits was positively related to pur-

chase intent (.21). Perceived behavioral control was positively associated with purchase intent (.14).

Subjective norm positively influenced purchase intent (.57). The squared multiple correlation

(SMC) of purchase intent was .65, indicating that a significant portion (65%) of variance in purchase intent was explained by attitude toward purchasing fashion counterfeits, subjective norm, and per-

ceived behavioral control. Subjective norm was positively related to attitude toward purchasing

Table 2. Measurement Model Properties (14 items)

Standardized factor loadings

Construct reliability Variance

Attitude (a ¼ .92) .92 .71 1. Harmful/Good .69 2. Useless/Beneficial .89 3. Foolish/Wise .89 4. Worthless/Worthwhile .94 5. Not valuable/Valuable .79

Perceived behavioral control (a ¼ .67) .70 .48 1. I have complete control of purchasing fashion counterfeit goods. .29 2. For me, to buy fashion counterfeit goods is easy. .89 3. If I want to, I could easily buy fashion counterfeit goods. .75

Purchase intent (a ¼ .97) .97 .92 1. I intend to buy fashion counterfeit goods in the future. .95 2. I will try to buy fashion counterfeit goods in the future. .99 3. I will make an effort to buy fashion counterfeit goods in the

future. .94

Subjective norm (a ¼ .82) .81 .59 1. Close friends and family think it is a good idea for me to buy

fashion counterfeit goods. .80

2. The people who I listen to could influence me to buy fashion counterfeit goods.

.75

3. Important people in my life want me to buy fashion counterfeit goods.

.75

86 Clothing & Textiles Research Journal 28(2)

86 at CALIFORNIA ST UNIV NORTHRIDGE on October 25, 2015ctr.sagepub.comDownloaded from

fashion counterfeits and perceived behavioral control. The SMCs of attitude and perceived beha-

vioral control were .43 and .29, respectively, indicating that 43% of variance in attitude and 29% of variance in perceived behavioral control were explained by subjective norm.

Table 5 compares the original model based on TPB and the two extended models. Chi-square dif-

ference tests indicated that Model 2, which included the path from subjective norm to attitude,

showed a significantly better fit compared with the original Model 1. Furthermore, Model 3, which

included two additional paths (from subjective norm to attitude and from subjective norm to

perceived behavioral control), showed a significantly better fit compared with the Models 1 and

2. Adding the two paths to TPB significantly improved the explanatory power of the theory in the

context of fashion counterfeits.

Decomposition of effects was calculated to increase understanding about the results and examine

predictive validity of the model. Subjective norm indirectly affected purchase intent through attitude

toward purchasing fashion counterfeit goods and perceived behavioral control. The estimate of the

indirect effect from subjective norm to purchase intent through attitude was .14 (.66 � .21), whereas the indirect effect from subjective norm to purchase intent through perceived behavioral control was

.08 (.54 � .14), indicating that 14% of the indirect effect was explained through attitude, whereas 8% of the indirect effect was explained through perceived behavioral control (Shrout & Bolger, 2002).

Discussion

In this study, we examine consumer motivations that can explain attitudes toward purchasing fash-

ion counterfeit goods. The results indicate that product appearance, past purchase behavior, and

value consciousness are positively related to attitude toward purchasing fashion counterfeit goods,

whereas normative susceptibility is negatively related to the attitude. Consumers may be motivated

to purchase fashion counterfeit goods because of perceived attractive appearance that is similar or

identical to authentic goods. The beta for this relationship (b* ¼ .50) is the highest among the four predictors, implying that product appearance may be one of the main reasons for acquiring fashion

Table 3. Correlation Matrix of Model Constructs

Correlation

Model Construct (n ¼ 366) M SD 1 2 3 4

1. Attitude 3.93 1.23 1.00 2. Perceived behavioral control 4.34 1.30 .44*** 1.00 3. Purchase intent 3.24 1.58 .64*** .53*** 1.00 4. Subjective norm 3.12 1.27 .64*** .51*** .77*** 1.00

Table 4. Test of the Extended Theory of Planned Behavior

HP Path Est. S. Est. SE t

H2 Attitude –> purchase intent .38 .21 .10 3.75*** H3 Behavioral control –> purchase intent .45 .14 .17 2.58** H4 Subjective norm –> purchase intent .88 .57 .11 8.28*** H5 Subjective norm –> attitude .55 .66 .05 10.40*** H6 Subjective norm –> behavioral control .27 .54 .06 4.73***

Est. ¼ parameter estimate; S. Est. ¼ standardized estimate of parameter; SE ¼ standard error

Kim and Karpova 87

87 at CALIFORNIA ST UNIV NORTHRIDGE on October 25, 2015ctr.sagepub.comDownloaded from

counterfeits. This result supports the finding from the studies of Kim and Karpova (2005) and Wee

et al. (2005), who reported that product appearance, or design, was an important motivation to buy

fashion counterfeits.

Consumer past purchase behavior has a positive influence on attitude toward buying fashion

counterfeit goods, confirming the results of d’Astous et al. (2005). People who have purchased

fashion counterfeits in the past tend to have more positive attitudes toward buying those goods. The

finding implies that people may purchase fashion counterfeits habitually. Gentry, Putrevu, and

Shultz (2006) found that tourists, both Caucasians and Asians, were the main shoppers of fashion

counterfeit goods and considered them to be souvenirs. When purchasing fashion counterfeits

becomes habitual, it may be more problematic to discourage the behavior. Therefore, it is important

for the government and authorities to limit opportunities and resources (e.g., counterfeit-selling dis-

trict) to purchase fashion counterfeit goods. U.S. Customs may develop an educational campaign at

airports to provide people an opportunity to think about ethical issues and negative consequences

related to counterfeit goods.

Value conscious consumers are more likely to have a positive attitude toward purchasing fashion

counterfeits. Consumers who seek to maximize perceived utility for their money are more likely to

purchase fashion counterfeits. This finding is consistent with previous studies that examined other

product categories such as music CDs, clothing, and software (Ang et al., 2001; Bloch et al., 1993;

Higgins & Rubin, 1986; Tom et al., 1998). Normative susceptibility is negatively related to attitude

toward purchasing fashion counterfeits. Consumers who have a higher tendency to conform to soci-

etal expectations are likely to have negative attitudes toward fashion counterfeits. When a consumer

believes that significant others may disapprove of acquisition of fashion counterfeits, or if buying

these goods creates an unfavorable impression, the consumer is likely to have a negative attitude

toward purchasing counterfeits.

Integrity is not related to attitude toward purchasing fashion counterfeits. This finding is some-

what consistent with that of Ha and Lennon (2006) who found no difference between fashion coun-

terfeit buyers and nonbuyers in terms of ethical ideologies. In contrast, de Matos et al. (2007) found

that integrity is negatively associated with attitude toward counterfeits. However, they used an

Table 5. Fit Statistics Comparison of the Theory of Planned Behavior and Its Extensions

Models w2 df w2diff RMSEA NFI CFI

Null model 8068.87*** 91 .490 .46 .47 Model 1

Attitude –> purchase intent Subjective norm –> purchase intent Behavioral control –> purchase intent 427.96*** 74 7658.91*** .110 .95 .96

Model 2 Attitude –> purchase intent Subjective norm –> purchase intent Behavioral control –> purchase intent Subjective norm –> attitude 283.21*** 73 144.75*** .089 .96 .97

Model 3 Attitude –> purchase intent Subjective norm –> purchase intent Behavioral control –> purchase intent Subjective norm –> attitude Subjective norm –> behavioral control 228.93*** 72 54.28*** .077 .97 .98

*** p < .001.

88 Clothing & Textiles Research Journal 28(2)

88 at CALIFORNIA ST UNIV NORTHRIDGE on October 25, 2015ctr.sagepub.comDownloaded from

interview technique; therefore, it is possible that a social desirability effect influenced the results.

Although people may be aware that counterfeits are illegal, they may not necessarily view purchas-

ing fake fashion goods as a serious dishonest and irresponsible action. Indeed, in the United States,

unlike in some European countries, the act of purchasing counterfeits cannot be prosecuted (Custom

regulations, n.d.). Therefore, consumers may not automatically connect their personal values (i.e.,

honesty, responsibility) with purchasing a fake Coach purse. It is important to further investigate the

role of consumer values associated with lawfulness in the context of fashion counterfeits.

Status consumption and materialism are not associated with attitude toward purchasing fashion

counterfeit goods. This finding conflicts with that of Wee et al. (1995) who reported that for South-

east Asian students brand status is a significant predictor of intent to purchase counterfeits. It is pos-

sible that consumers in developed nations (i.e., the United States) may place less importance on

semi-durable goods such as apparel, bags, and shoes to convey social status than do consumers in

emerging markets, where relatively low average income prevents larger purchases such as cars or

houses (Belton, 2002). In the wealthier markets, with the advance of ‘‘fast’’ and ‘‘disposable’’ fash-

ion, clothing and accessories may be losing meaning as status symbols.

This study tests TPB in the context of fashion counterfeits. As proposed by the theory, we find

that attitude toward purchasing fashion counterfeits, subjective norm, and perceived behavioral con-

trol are positively related to purchase intent. People who have favorable attitudes toward purchasing

fashion counterfeits are likely to express stronger intent to acquire them in the future. This is con-

sistent with previous research related to dishonest behaviors such as shoplifting (Tonglet, 2001),

music (Kwong & Lee, 2002), and software piracy (Peace, Galletta, & Thong, 2003). In these studies,

the attitude is the strongest predictor of intent to perform the behavior. However, in the context of

fashion counterfeits, subjective norm appears to be the most important predictor of purchase intent.

The fact that social pressures from others have greater impact on fashion counterfeits purchase intent

than consumers’ attitudes toward the behavior is promising. Because people are influenced by opi-

nions of significant others, purchasing counterfeits may be discouraged if potential buyers perceive

that their family and friends will not support the behavior.

Perceived behavioral control is found to be the least important predictor of purchase intent. This

might be because the contemporary consumer has more opportunities to purchase counterfeits, for

example, through the Internet. However, the significant relationship between perceived behavioral

control and purchase intent suggests the usefulness of the construct in non-volitional conditions,

such as performing unethical behaviors. For instance, although consumers may not think about pur-

chasing fashion counterfeit goods, if the resources (fashion counterfeits) and opportunities are read-

ily available (e.g., counterfeit district in New York), they are likely to have a higher degree of

purchase intent. In contrast, although some people may be interested in purchasing fashion counter-

feits, if resources and opportunities are not easily available, or it requires some effort to find counter-

feit goods (e.g., online search), purchase intent could be discouraged.

The findings provide empirical evidence that two additional paths (subjective norm to attitude

and subjective norm to perceived behavioral control) are important extensions of TPB (see Figure

1) because they help improve the ability of the theory to predict purchase intent of fashion counter-

feits. Subjective norm is significantly related to perceived behavioral control, and this path substan-

tially improves the model fit. According to TPB, perceived behavioral control is predicted by control

belief and perceived facilitation. Because people may influence each other by sharing information

and opinions, consumer beliefs about the availability of counterfeits and perceived facilitation may

come from friends or family members.

A positive relationship between subjective norm and attitude toward purchasing fashion counter-

feit goods indicates that influence of one’s community on buying fashion counterfeits not only

directly affects consumer intent to purchase them but also may play an important role in shaping

attitudes toward the behavior. For example, if a community expresses strong views on behaviors

Kim and Karpova 89

89 at CALIFORNIA ST UNIV NORTHRIDGE on October 25, 2015ctr.sagepub.comDownloaded from

as socially undesirable and harmful to the society as a whole, such behaviors can be perceived as

unworthy to engage in despite promising individual gains (i.e., famous brands for less money). This

implies that anticounterfeiting campaigns should stress the link between fashion counterfeits and

highly undesirable social phenomena such as sweatshops, loss of legitimate manufacturing jobs

in the country, and unpaid taxes. Furthermore, it is important to emphasize consumers’ personal

responsibility for these social problems if they purchase fashion counterfeits. Taking into account

that normative susceptibility (consumer willingness to conform) is negatively related to the attitude

toward the behavior, the anticounterfeiting campaigns might be especially effective if highly-

respected and well-known politicians or celebrities were to communicate the message. For instance,

Sean John Canada, a popular hip–hop clothing brand designed by Sean ‘‘Diddy’’ Combs, initiated

the ‘‘Don’t Buy A Lie’’ campaign to make consumers aware that when they buy counterfeits, they

are supporting an underground economy, such as factories that operate illegally, have no code of

conduct, pay employees unfair wages, and frequently exploit child labor (Sean John Canada, n.d.).

Another strategy to fight counterfeiting would be not only to educate consumers who tend to

believe that purchasing fashion counterfeits is practical, but also target those who already recognize

the damaging effect of the phenomenon and do not engage in this behavior. It is important to let this

segment of consumers realize the power they have in influencing others’ intentions and behaviors

related to counterfeits. Encouraging people to openly express negative opinions on this socially

undesirable behavior in casual conversations (i.e., word-of-mouth communication) might be an

effective approach to prevent counterfeit purchasing.

In the fashion industry, the concept of copying (knocking-off) designers’ creations is a pervasive

and widely accepted practice (Marcketti & Parsons, 2006). Therefore, college students as well as

other consumers may not take fashion counterfeiting seriously and do not think that the practice

is illegal or unethical. To help students understand the fashion counterfeiting phenomenon and its

damaging consequences, educators might develop special anticounterfeiting units as a part of a cur-

riculum that addresses social responsibility. In connection with consumer social responsibility, stu-

dents might conduct group projects investigating counterfeiting of different product categories and

share the information in class.

Limitation and Future Research

Generalization of the research findings may be limited because of the use of a specific population

(i.e., female college students) and relatively low response rate. Future research may use a sample

that is more heterogeneous in terms of gender, age, educational and income levels, marital status,

ethnic group, and geographic location to confirm the findings. It may be important to investigate the

effect of demographic variables on attitude and purchase intent toward fashion counterfeits. The

investigation of consumer demographic information may benefit policy makers to influence the

market of fashion counterfeits.

In this study, the reliability of integrity scale is relatively low (.63). Although research shows that

reliability higher than .60 is acceptable (Hair et al., 1998), the findings involving the variable should

be interpreted with caution. The variance of perceived behavioral control is slightly lower than .50,

which indicates that the variance because of measurement error is larger than the variance explained

by the construct. Consequently, the validity of the individual indicators and the construct may be

questionable (Fornell & Larcker, 1981). Future studies may consider including additional items

to improve the variance of the variable.

Through this study, we find that product appearance is the most important predictor of attitudes

toward purchasing fashion counterfeit goods. To tap into consumers’ underlying perceptions and

impressions of fashion counterfeits and the association between product appearance and brand

status, an in-depth exploration of the topic is needed. As discussed above, with the growth of

90 Clothing & Textiles Research Journal 28(2)

90 at CALIFORNIA ST UNIV NORTHRIDGE on October 25, 2015ctr.sagepub.comDownloaded from

e-commerce, there are numerous opportunities for consumers to purchase fashion counterfeits

through the Internet. According to a report, online counterfeit sales exceed $25 billion (Imitating

property is theft, 2003). Investigating consumers’ awareness of online fashion counterfeits and atti-

tude and intent toward purchasing fashion counterfeit goods via Internet is an important topic for

future research.

Notes 1. Based on the tolerance (.468-.920) and VIF (1.087-2.137) values (Stevens, 2002), no multicollinearity was

evident among independent variables. The correlations between the independent variables were lower than

.70 (Tabachnick & Fidell, 2007).

2. Low variance of perceived behavioral control appears to be because of the low factor loading of the first

item. The item was retained in the analysis because, according to the measurement model, it was signifi-

cantly related to the factor at the .001 level. When another latent model was tested without the item, the sig-

nificance of path coefficients among variables remained consistent with the model with the item. Other fit

indices were better when the item was included.

References

Ajzen, I. (1985). From intentions to actions: A theory of planned behavior. In J. Kuhland & J. Beckman (Eds.),

Action control: From cognitions to behavior (pp. 11-39). New York: Springer-Heidelberg.

Ajzen, I. (1991). The theory of planned behavior. Organizational Behavior & Human Decision Process, 50(2),

179-211.

Albers-Miller, N. D. (1999). Consumer misbehavior: Why people buy illicit goods. Journal of Consumer Mar-

keting, 16(3), 273-287.

Ang, S. H., Cheng, P. S., Lim, E. A. C., & Tambyah, S. K. (2001). Spot the difference: Consumer responses

toward counterfeits. Journal of Consumer Marketing, 18(3), 219-235.

Arellano, R. (1994). Informal-underground retailers in less-developed countries: An exploratory research from

marketing point of view. Journal of Macromarketing, 14(2), 21-35.

d’Astous, A., Colbert, F., & Montpetit, D. (2005). Music piracy on the Web: How effective are antipiracy argu-

ments? Evidence from the theory of planned behavior. Journal of Consumer Policy, 28, 289-310.

Bamossy, G., & Scammon, D. L. (1985). Product counterfeiting: Consumers and manufacturers beware. In E.

C. Hirschman & M. B. Holbrook (Eds.), Advances in Consumer Research (Vol. 7, pp. 334-339). Provo, UT:

Association for Consumer Research.

Bearden, W. O., Netemeyer, R. G., & Teel, J. E. (1989). Measurement of consumer susceptibility to interper-

sonal influence. Journal of Consumer Research, 15(4), 473-481.

Belk, R. W. (1984). Three scales to measure construct related to materialism of happiness. In T. Kinnear (Ed.),

Advances in consumer research (Vol. 11, pp. 291-297). Provo, UT: Association for Consumer Research.

Belton, C. (2002, September 16). To Russia with love: The multinationals’ song. The country’s becoming the

darling of consumer giants. Business Week, 44.

Bem, D. J. (1972). Self-perception theory. In L. Berkowitz (Ed.), Advances in experimental social psychology

(Vol. 6, pp. 1-62). San Diego, CA: Academic Press.

Bloch, P. H., Bush, R. F., & Campbell, L. (1993). Consumer ‘‘accomplices’’ in product counterfeiting. Journal

of Consumer Marketing, 10(4), 27-36.

Burke, P. J. (Ed.). (2006). Contemporary social psychological theories. Stanford, CA: Stanford Social Sciences.

Bush, R. F., Bloch, P. H., & Dawson, S. (1989, January-February). Remedies for product counterfeiting. Busi-

ness Horizons, 59-65.

Casabona, L. (2006, December 21). Counterfeiters’ holiday payday: Real money for fake goods. Women’s

Wear Daily.

Kim and Karpova 91

91 at CALIFORNIA ST UNIV NORTHRIDGE on October 25, 2015ctr.sagepub.comDownloaded from

Charkraborty, G., Allred, A., Sukhdial, A. S., & Bristol. T. (1997). Use of negative cues to reduce demand

for counterfeit products. In M. Brucks & D. MacInnis (Eds.), Advances in consumer research (Vol. 24,

pp. 345-349). Chicago: Association for Consumer Research.

Cheung, W-L., & Prendergast, G. (2005). Buyers’ perceptions of pirated products in China. Marketing Intelli-

gence & Planning, 24(5), 446-462.

Chang, M. K. (1998). Predicting unethical behavior: A comparison of the theory of reasoned action and the

theory of planned behavior. Journal of Business Ethics, 17(16), 1825-1834.

Cook, D., & Writer, S. (2006, August 27). Fake goods, real problem. Chattanooga Times Free Press.

Cordell, V. V., Wongtade, N., & Kieschnick, R. L., Jr. (1996). Counterfeit purchase intentions: Role of law-

fulness attitudes and product traits as determinants. Journal of Business Research, 35(1), 41-53.

Custom regulations. (n.d.). Seeitalia.com. Retrieved December 5, 2006, from http://www.seeitalia.com/

essentials/customs/.

Damhorst, M. L., Miller, K. A., & Michelman, S. O. (2001). The meaning of dress. New York: Fairchild.

Eastman, J. K., Fredenberger, B., Campbell, D., & Calvert, S. (1997). The relationship between status consump-

tion and materialism: A cross-cultural comparison of Chinese, Mexican, and American students. Journal of

Marketing Theory & Practice, 5(1), 52-65.

Fishbein, M., & Ajzen, I. (1975). Beliefs, attitudes, intention, and behavior: An introduction to theory and

research. Reading, MA: Addison-Wesley.

Fitzmaurice, J. (2005). Incorporating consumers’ motivations into the theory of reasoned action. Psychology &

Marketing, 22(11), 911-929.

Fornell, C., & Larcker, D. F. (1981). Evaluating structural equation models with unobservable variables and

measurement error. Journal of Marketing Research, 18(1), 39-50.

Garza, X. (2006, November 10). Faking it. Las Vegas Review.

Gentry, J. W., Putrevu, S., & Shultz, C. J., II. (2006). The effects of counterfeiting on consumer search. Journal

of Consumer Behaviour, 5, 245-256.

Gilgoff, H. (2004, December 4). Counterfeiting causes problems for companies, taxpayers, consumers. News-

day. Retrieved October 12, 2005, from http://www.search.epnet.com.proxy.lib.ohio-state.edu/login.aspx?

direct¼true&db¼nfh&an¼2W63456673477 Grossman, G. M., & Shapiro, C. (1988). Foreign counterfeiting of status goods. Quarterly Journal of Econom-

ics, 103(1), 79-100.

Ha, S., & Lennon, S. J. (2006). Purchase intent for fashion counterfeit products: Ethical ideologies, ethical judg-

ments, and perceived risks. Clothing and Textile Research Journal, 24(4), 297-315.

Hair, J. F., Jr., Anderson, R. E., Tatham, R. L., & Black, W. C. (1998). Multivariate date analysis. Upper Saddle

River, NJ: Prentice-Hall.

Higgins, R. S., & Rubin, P. H. (1986). Counterfeit goods. Journal of Law & Economics, 29(2), 211-230.

ICC Counterfeiting Intelligence Bureau. (2004). The international anti-counterfeiting directory 2004.

Retrieved September 20, 2005, from http://www.occwbo.org/ccs/cib_bureau/IACD%202004.pdf.

Imitating property is theft. (2003, May 17). Economist, 32-54.

Johnson, J. (2006, October 20). Trademark counterfeiting takes flight beyond luxury brands. Colorado Springs

Business Journal.

Kiecolt, K. J. (1988). Recent developments in attitudes and social structure. Annual Review of Sociology, 14,

381-403.

Kim, H., & Karpova, E. (2005). Exploring consumers’ perceptions and motivations toward fashion counter-

feits. Unpublished manuscript, Auburn University.

Kline, R. B. (1998). Principles and practice of structural equation modeling. New York: Guilford.

Kwong, T. C. H., & Lee, M. K. O. (2002). Behavioral intention model for the exchange mode Internet music

piracy. Proceedings of the 35th Annual Hawaii International Conference on System Sciences, Computer

Society. Retrieved February 10, 2008, from http://csdl2.computer.org/comp/proceedings/hicss/2002/1435/

07/14350191.pd.

92 Clothing & Textiles Research Journal 28(2)

92 at CALIFORNIA ST UNIV NORTHRIDGE on October 25, 2015ctr.sagepub.comDownloaded from

Lichtenstein, D. R., Netemeyer, R. G., & Burton, S. (1990). Distinguishing coupon proneness from value con-

sciousness: An acquisition-transaction utility theory perspective. Journal of Marketing, 54(3), 54-67.

Madden, T. J., Ellen, P. S., & Ajzen, I. (1992). A comparison of the theory of planned behavior and the theory of

reasoned action. Personality and Social Psychology Bulletin, 18(1), 3-9.

Marcketti, S. B., & Parsons, J. L. (2006). Design piracy and self-regulation: The fashion originator’s guild of

America, 1932-1941. Clothing and Textiles Research Journal, 24(3), 214-228.

Marcoux, J., Filiatrault, P., & Chèron, E. (1997). The attitudes underlying preferences of young urban educated

Polish consumers towards products made in Western countries. Journal of International Consumer Market-

ing, 9(4), 5-30.

de Matos, C. A., Ituassu, C. T., & Rossi, C. A. V. (2007). Consumer attitudes toward counterfeits: A review and

extension. Journal of Consumer Marketing, 24(1), 36-47.

McGlone, T. (2006, November 24). Cracking down on counterfeiting. The Virginian – Pilot.

Oldenburg, D. (2005, January 4). Counterfeit goods that trigger the ‘‘false’’ alarm. Washington Post.

Retrieved October 12, 2005, from http://www.search.epnet.com.proxy.lib.ohio-state.edu/login.aspx?

direct¼true&db¼nfh&an¼WPT265703580405 O’Shaughnessy, J. (1992). Explaining buyer behavior. New York: Oxford University Press.

Pallay, J. (2006, October 23). Ripping off labels no longer satisfied with designer handbags, counterfeiters are

moving into men’s wear. Daily News Record.

Parasuraman, A., & Grewal, D. (2000). The impact of technology on the quality-value-loyalty chain: A research

agenda. Journal of the Academy of Marketing Science, 28, 168-174.

Peace, A. G., Galletta, D. F., & Thong, J. Y. L. (2003). Software piracy in the workplace: A model and empiri-

cal test. Journal of Information Systems, 20, 153-177.

Penz, E., & Stöttinger, B. (2005). Forget the ‘‘real’’ thing – take the copy! An explanatory model for the voli-

tional purchase of counterfeit products. In G. Menon & A. R. Rao (Eds.), Advances in consumer research

(Vol. 32, pp. 568-575). Duluth, MN: Association for Consumer Research.

Prendergast, G., Chuen, L. H., & Phau, I. (2002). Understanding consumer demand for non–deceptive pirated

brands. Marketing Intelligence & Planning, 20(7), 405-416.

Randall, D. M., & Gibson, A. M. (1991). Ethical decision making in the medical profession: An application of

the theory of planned behavior. Journal of Business Ethics, 10(2), 111-122.

Richins, M., & Dawson, S. (1992). A consumer values orientation for materialism and its measurement: Scale

development and validation. Journal of Consumer Research, 19(3), 303-316.

Rokeach, M. J. (1968). A theory of organization and change within value-attitude systems. Journal of Social

Issues, 24, 13-22.

Ryan, E. (2006, July 19). Abercrombie & Fitch cracking down on counterfeiting. Associated Press State &

Local Wire.

Sean John Canada. (n.d.). Don’t buy a lie. Retrieved February 1, 2007, from http://dontbuyalie.com/

intro-english.html.

Shepherd, G. J., & O’Keefe, D. J. (1984). Separability of attitudinal and normative influences on behavioral

intentions in the Fishbein-Ajzen Model. Journal of Social Psychology, 122(2), 287-288.

Shrout, P. E., & Bolger, N. (2002). Mediation in experimental and nonexperimental studies: New procedures

and recommendations. Psychological Methods, 7, 422-445.

Stevens, J. (2002). Applied multivariate statistics for the social sciences. Mahwah, NJ: Erlbaum Associates.

Tabachnick, B. G., & Fidell, L. S. (2007). Using Multivariate Statistics (5th ed.). New York: Pearson Education

Co.

Tom, G., Garibaldi, B., Zeng, Y., & Pilcher, J. (1998). Consumer demand for counterfeit goods. Psychology &

Marketing, 15(5), 405-421.

Tonglet, M. (2001). Consumer misbehaviour: An exploratory study of shoplifting. Journal of Consumer

Behavior, 1, 336-354.

Kim and Karpova 93

93 at CALIFORNIA ST UNIV NORTHRIDGE on October 25, 2015ctr.sagepub.comDownloaded from

Tucker, R (2005, February 2). Battling counterfeits: Divulging the danger of $500b global industry. Women’s

Wear Daily, 1-2.

Vallerand, R. J., Deshaies, J., Cuerrier, L. G., & Mongeau, C. (1992). Ajzen and Fishbein’s theory of reasoned

action as applied to moral behavior: A confirmatory analysis. Journal of Personality and Social Psychology,

62, 98-109.

Vinson, D. E., Munson, J. M., & Nakanishi, M. (1977). An investigation of the Rokeach Value Survey for con-

sumer research applications. In W. E. Perreault (Ed.), Advances in Consumer Research (Vol. 4, pp. 247-

252). Provo, UT: Association for Consumer Research.

Wee, C. H., Tan, S. J., & Cheok, K. H. (1995). Non-price determinants of intent to purchase counterfeit goods.

International Marketing Review, 12(6), 19-46.

Young, R. A., & Kent, A. T. (1985). Using the theory of reasoned action to improve the understanding of recrea-

tion behavior. Journal of Leisure Research, 17(2), 90-106.

Bios

Hyejeong Kim, PhD, is an Assistant Professor in the Department of Consumer Affairs at Auburn University.

Her research interests include online shopping environment, body image in relation to online shopping, and

social responsibility associated with fashion counterfeiting.

Elena Karpova, PhD, is an assistant professor at the Department of Apparel, Educational studies, and Hospi-

tality Management at the Iowa State University. Her research interests include international and cross-cultural

aspects of textile and apparel production, distribution and consumption; professional development.

94 Clothing & Textiles Research Journal 28(2)

94 at CALIFORNIA ST UNIV NORTHRIDGE on October 25, 2015ctr.sagepub.comDownloaded from