Analysis of the demand for counterfeit goods pdf

Keywords United States of America, Consumer behaviour, Counterfeiting, Fashion, Demand model Paper type Case study Introduction A global trend that has been increasing at an alarming rat

Analysis of the demand for

counterfeit goods

Pamela S Norum Department of Textile and Apparel Management, University of Missouri,

Columbia, Missouri, USA, and

Angela Cuno Northcentral University, Prescott Valley, Arizona, USA

Abstract

Purpose – The production, distribution and consumption of counterfeit goods have been increasing

at an alarming rate Current legislation addresses the supply side of the problem, but not the demand

side of the problem The purpose of this paper is to examine, empirically, factors affecting consumer

demand for counterfeit goods were analyzed.

Design/methodology/approach – The economic theory of consumer demand provided the

theoretical framework Data were collected from students enrolled at a major mid-western university,

and logistic regression was used to estimate demand functions for counterfeit goods.

Findings – The results indicated that student sensitivity to the counterfeit problem did not

significantly deter the purchase of counterfeit goods.

Research limitations/implications – Educators in textiles and apparel should have a vested interest

in providing education about counterfeiting, resulting in students with greater sensitivity to the issue.

Originality/value – The production, distribution and consumption of counterfeit goods have been

increasing at an alarming rate Current legislation addresses the supply side of the problem, but not

the demand side of the problem Consumer education may be a feasible approach for addressing the

demand side of the problem.

Keywords United States of America, Consumer behaviour, Counterfeiting, Fashion, Demand model

Paper type Case study

Introduction

A global trend that has been increasing at an alarming rate is the production,

distribution and consumption of counterfeit goods In spite of legislation intended to

reduce the sale of counterfeit merchandise, industry leaders and designers all over the

world have identified this as a growing problem, and are working with groups such as

the International Anti-Counterfeiting Coalition (IACC) to protect their designs from being

copied The IACC (2008) estimates that 5-7 percent of world trade is in illegitimate goods

Trade in counterfeit goods has reached $600 billion annually on a worldwide basis This

problem has grown over 10,000 percent in the past 20 years, partly due to an increase in

consumer demand In the USA, counterfeiting costs businesses up to $250 billion each

year The highest profile counterfeit investigations and prosecutions have focused

luxury goods Often times these products are sold by street merchants and vendors at

mall kiosks Counterfeit handbags are the most widely copied product Kate Spade

executives believe that the sales ratio of real bags to counterfeits is one-to-one

Counterfeit luxury items have become a multi-million dollar business for traffickers

because of the commonplace acceptance of counterfeit purses in our society and the

sophisticated strategies for evading state or federal agents (Amendolara, 2005)

www.emeraldinsight.com/1361-2026.htm

Counterfeit goods

27

Received March 2009 Revised October 2009 Accepted February 2010

Journal of Fashion Marketing and

Management Vol 15 No 1, 2011

pp 27-40

q Emerald Group Publishing Limited

1361-2026

To deter counterfeit goods, Congress passed the Trademark Counterfeiting Act (TCA)

of 1984 Up to this point in time, penalties for counterfeiting were minimal and did not prevent counterfeiters from trafficking goods into the USA Under the Trademark Counterfeiting Act, any corporation or individual who is found guilty of intentionally trafficking counterfeit goods risks a maximum penalty of one million dollars and/or five years imprisonment (Amendolara, 2005) The Trademark Counterfeiting Act of 1984 was

a giant leap towards the protection of trademarks However, without bilateral action from countries that value trade relationships with the USA, it cannot be completely successful

In addition, this legislation does not address the demand side of the problem The demand side of the counterfeit problem is clearly an issue of consumer behaviour, or perhaps more appropriately termed, “consumer misbehaviour” (Albers-Miller, 1999)

With legislation, such as the TCA, the focus is on deterring the suppliers and sellers

of counterfeit goods, but not the consumers, or ultimate purchasers of the goods There are limited legal ramifications for consumers of counterfeit goods However, in recent years, with the growth in trafficking of counterfeit goods, greater interest in understanding consumer behaviour with regard to purchasing counterfeit goods has developed This shift has occurred because without the demand, there would be no need for the supply Legal consequences and consumer education are both options for addressing the demand side of the counterfeit issue

Educators in textiles and apparel, in particular, have a responsibility to educate their students about the counterfeit industry, and its consequences Singhapakdi (2004) indicated that sensitivity to an issue would reduce the likelihood of engaging in a negative or unethical behaviour If this is true, then one would expect that textile and apparel students would be, or should be, sensitive to the counterfeit issue and less likely to engage in it

Prior research has shown that consumer’s ethical attitudes can affect the likelihood

of purchasing counterfeit goods (Muncy and Vitell, 1992) Economic benefits can also drive the demand for counterfeit goods (Bloch et al., 1993; Dodge et al., 1996) In addition, socio-economic and demographic characteristics also influence purchasing behaviour The purpose of this study is to gain a better understanding of selected factors affecting consumer demand for counterfeit goods Given the role that textile and apparel educators in higher education could play in addressing this issue, college students are the focus of the study The primary objectives are to:

. determine whether consumer attitudes towards counterfeiting differ between purchasers and non-purchasers of counterfeit goods;

. determine if consumer attitudes regarding the legal/ethical aspects of counterfeiting influences the purchase of counterfeit goods;

. identify whether sensitivity to the counterfeit problem affects purchase behaviour; and

. examine the effect of selected socio-economic and demographic characteristics on the demand for counterfeit goods

Background Attitudes

By almost any standard, US consumers are viewed as being very materialistic The desire to own possessions can lead to a consumer acting unethically in order to obtain

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the possessions they desire To study the ethical beliefs of consumers, Muncy and

Vitell (1992) developed and administered a consumer ethics scale which measured

consumer practices that have ethical implications Consumer ethics can be defined as

the moral rules, principles and standards guiding the behaviour of an individual (or

group) in the selection, purchase, use or selling of a good or service Based on their

sample of 1,900 heads of households within the USA, Muncy and Vitell’s respondents

tended to believe that it was more ethical to passively benefit in some way than to

actively benefit from an illegal activity According to the study, the “no harm no foul”

activities were considered to not be unethical Many of these activities included

intellectual property rights such as the copying of software, tapes, or movies

Tom et al (1998) investigated consumer attitudes toward counterfeiting on several

different dimensions, measuring attitudes about the economic, legal, anti-business, and

quality aspects of counterfeiting In this study, approximately, 40 percent of the 129

respondents had knowingly purchased counterfeit goods Purchasers had more lax

attitudes about the lawfulness of counterfeiting, were less likely to believe that

counterfeiting hurt the US economy, held greater anti-big business sentiments, and

perceived the quality of counterfeit goods to be as good legitimate goods Ang et al

(2001) surveyed a total 3,621 respondents, aged 15 and above, who had purchased CDs

in the past The results indicated that one’s attitude towards piracy was a significant

predictor of one’s purchase intentions Consumers who have bought pirated CDs before

had more favourable views about counterfeit goods than those who have never bought

counterfeit products Buyers and non-buyers alike did not consider anything wrong

with purchasing counterfeit goods

Hunt and Vitell (1986) argued that the perception of an ethical issue or problem is an

important prerequisite for the ethical decision-making process A person who perceives

an ethical problem more readily tends to behave more ethically than an individual who

does not A study of students in marketing classes from two major universities found

that perceived ethical problems and perceived importance of ethics have a positive

impact on the ethical intentions of students (Singhapakdi, 2004) The results of this

study concluded that a marketing student’s perceived importance of ethics is a

significant predictor of one’s ethical intentions

Gender differences

Early studies found gender to be unrelated to ethical behaviour, ethical problems,

and reasonable alternatives to resolving ethical problems (Hegarty and Sims, 1978;

Singhapakdi and Vitell, 1990) whereas more recent studies indicated gender

differences Recent studies have concluded that female students tend to be more

ethical in their intentions than male students (Singhapakdi, 2004) and more

accepting of questionable ethical responses (Cole and Smith, 1996) Kwong et al

(2003) found gender and age were significantly related to the intention to buy

pirated CDs, with male respondents more likely to purchase counterfeit CDs than

were female respondents A study conducted by Chen and Tang (2006) examined

business and psychology students’ attitudes toward unethical behaviour and the

likelihood of them engaging in unethical behaviour The study found that male

students tend to believe that theft, corruption and deception were more ethical than

their female counterparts

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Economic influences Past research has shown that direct economic consequences such as paying a lower price, influence the tolerance of questionable behaviour by consumers (Dodge et al., 1996) A study conducted by Bloch et al (1993) found that consumers would select a counterfeit item over a genuine product when there is a price advantage For their first study, 100 adult consumers were surveyed, using a mall intercept, to determine

a consumer’s willingness to knowingly buy counterfeit apparel Respondents were shown a set of three knit shirts (a designer label with a logo, a counterfeit of the designer label with a logo, and a store brand without a logo) Participants were made aware that of the products to choose from, one was counterfeit, and that counterfeit products are illegal Prices were also associated with each shirt ($45.00 for the designer shirt and $18.00 for the other two shirts) The respondents were then asked to select the shirt they were most likely to buy Of the 100 respondents,

29 percent selected the designer label, 37.5 percent selected the counterfeit shirt, and 33.5 percent selected the non-brand name shirt When the study was repeated at a flea market, identical choice patterns were observed between the flea market and the local mall Their results indicate that even though counterfeit products compromise the quality, consumers are willing to over look this due to the cost saving prices The authors concluded that government and businesses must push to eliminate the demand-side of counterfeit Without more research to determine how to target these consumers, and which appeal to use, dollars spent on reducing the demand-side of counterfeit will likely be wasted

A study conducted by Albers-Miller (1999) was designed to assess consumer’s misbehaviour, and what causes a consumer to buy illicit goods, using the following three variables to predict consumer behaviour:

(1) the selling price;

(2) the situation under which the purchase takes place; and (3) the risk associated with the purchase

The study showed that all respondents were more likely to engage in illicit behaviour if there was peer pressure to do so While it has been shown that peer support of an illegal behaviour encourages deviant behaviour, peer rejection may also serve as a deterrent Albers-Miller concluded that legitimate business managers should consider lobbying for the strict enforcement of criminal sanctions against consumers as well as merchants of illicit goods

Theoretical model Consumer demand theory Consumer demand theory provides the theoretical framework for this study From this perspective, consumers maximize their utility subject to their budget constraint from which demand functions for various goods and services are derived (Varian, 1999)

A consumer’s utility function is defined as:

U ¼ uðX1; XAOGÞ where X ¼ good 1 and X ¼ all other goods

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A consumer maximizes utility subject to its budget constraint:

I ¼ P1X1þ PAOGXAOG

where I ¼ total income, P1¼ price of clothing, and PAOG¼ price of all other goods

Maximization of the utility function subject to the income constraint yields the

demand function for good one:

Q1¼ f ðP1; PAOG; I ; TÞ where Q1¼ quantity demanded of good one and T ¼ tastes & preferences

The quantity demanded of a good is function of income, prices, and tastes and

preferences (Varian, 1999) When using cross-sectional data, as in this study, prices are

assumed to be constant across consumers over the time period of the analysis Therefore,

prices can be suppressed in the empirical equation The empirical equation will include

measures for income, and factors to control for tastes and preferences Selected variables

found to influence the demand for counterfeit goods (e.g ethical attitudes, sensitivity,

and gender) in previous studies will be included to measure tastes and preferences

Method

Empirical model and analysis

For this study, both simple t-tests and logistic regression are used for the analyses To

achieve the first objective, t-tests are used to determine whether differences exist

between purchasers and non-purchasers of counterfeit goods with respect to their

attitudes about counterfeiting For the remaining objectives, a multivariate framework

is used in order to analyze the effect of one variable while controlling for other factors

that could influence demand Information is not available on the exact quantity of, or

expenditure on a counterfeit good It is known, however, whether the consumer

purchased a counterfeit good in the past year Consequently, the dependent variable is

a dichotomous variable, and logistic regression analysis is an appropriate statistical

technique (Tacq, 1997) The general form of the equation estimated in this study is:

CF ¼ a þ b1I þ b2A þ b3S þ b4S þ b5Y þ e where:

CF ¼ Counterfeit good purchase

I ¼ Income

A ¼ Attitudes

S ¼ Sensitivity

G ¼ Gender

Y ¼ Year in school

a ¼ the intercept

bi ¼ regression coefficient

e ¼ error term

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The coefficients produced by the logistic procedure cannot be interpreted in the same way as the regression coefficients from ordinary least squares regression However, the odds ratio provides coefficients that represent the effect of changes in the independent variables on the dependent variable In this context, the coefficient on a dummy variable can be interpreted as a percent difference relative to the comparison variable For each set of dummy variables, there is an omitted category that serves as the comparison category It is assigned a value of 1.00, or it can also be multiplied by 100 to get 100 percent) The value on the odds ratio is compared to the 1.00 (or 100 percent) by taking the difference between the values For example, in Table I, the omitted category for parental income, shown in parentheses, is for parental income less than $25,000 Thus, all other income categories will be compared to the , $25,000 category If an odds ratio is greater than 1.0 (or 100 percent), it indicates that students with that level

of parental income are more likely to buy counterfeit goods For parental income of

$100,000 or more, the odds ratio is 1.36 (or 136 percent) It indicates that students with parental income in this bracket are 36 percent more likely to buy counterfeit goods than students with parental income under $25,000 (1:36 2 1:00 ¼ 0:36 £ 100 ¼ 36 percent

or 136 percent 2 100 percent ¼ 36 percent) On the other hand, a coefficient of 0.92 for parental income of $50,000-74,999 indicates these students are 8 percent less likely to buy counterfeit goods compared to students with parental income under $25,000 (0:92 2 1:00 ¼ 20:08 £ 100 ¼ 28 percent or 92 percent 2 100 percent ¼ 28 percent) The choice of omitted category for each dummy variable is discussed below under the variable definitions, and shown in parentheses in the tables

Income , $25,000

Sensitivity (Didn’t discuss in class)

Gender Female

Education Freshmen

Notes: * p , 0.10; * * p , 0.05; * * * p , 0.01; n ¼ 437

Table I.

Logistic regression

indicating counterfeit

purchasing including

class discussion

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Sample and data collection

To collect data for this study, students enrolled in a major university located in a

medium-sized Midwestern town were asked to complete a questionnaire The

questionnaire was administered to seven classes Convenience sampling was used with

the intent of trying to have a wide representation of students from across campus Four

classes from a textile and apparel department were chosen based on the assumption

that these students were more likely to have been exposed to the negative aspects of

purchasing counterfeit goods, compared to other students They were also selected

since the behaviour of these students would be of most direct relevance to textile and

apparel academicians However, in order to ensure a diverse sample of students, the

surveys were also administered to two large classes, Principles of Microeconomics and

Introduction to Sociology and one small class, Introduction to Astronomy These

classes were selected based on their class sizes, different educational levels, and/or

representation of students from many different departments throughout campus A

total of 517 students responded to the questionnaire However, to be included in the

analyses, the students had to provide complete information on the variables of interest

which resulted in 437 respondents for the logistic regressions

Dependent variable

Counterfeit good purchase The introduction to the survey contained the following

statement:

Counterfeit or fake goods are items that imitate other products with the intent to deceive

Examples of these items include fake designer handbags, Rolex watches, Callaway golf clubs

and pirated CDs

Respondents were asked to respond to the statement “I have bought counterfeit goods in

the past year.” “Yes”, “no”, and “didn’t know” were the response options provided This

variable was coded as a one if they did make a counterfeit purchase, and a zero if they

did not If they “didn’t know” then they were excluded from the analysis This variable

was the dependent variable in the logistic regression equations Those respondents who

had made a counterfeit purchase were also asked to indicate the type(s) of goods or

services they had bought, and these results are shown in the descriptive statistics

Independent variables

Parent’s income Economics factors, and in particular income, greatly influence

purchasing behaviour To capture this effect, parental income was included in the

empirical equation since students are frequently dependent on their parents for their

support Dummy variables were created with the following categories:

. $25,000-49,999;

. $50,000-74,999;

. $75,000-99,999; and

. $100,000 or more

The omitted category was $25,000 and under Students who said they “didn’t know”

their parents income were excluded from the analysis Based on economic theory, as

income increases, the demand for normal goods increases However, if counterfeit

goods are viewed as inferior goods, then as income goes up, the demand for inferior

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goods decreases There is no prior research on the relationship between income and the demand for counterfeit goods that provides insight regarding the direction of this effect Counterfeit goods are generally considered to be of inferior quality to the actual good being copied, and therefore, one would expect a negative effect However, prior research indicates that some consumers perceive the quality of counterfeit goods to be

as good as legitimate goods (Tom et al., 1998), and from that perspective, a positive effect would be hypothesized In addition, if the trademark is the primary motivation for the purchase, and it is viewed in the consumer’s eye to be similar to the original (and not inferior), then the income effect could be positive

Consumer attitudes towards counterfeiting A total of 12 items, drawn from Tom et al (1998), were used to measure consumer attitudes towards counterfeiting Two of the items were designed specifically to measure consumer attitudes about the legality/illegality of selling and buying counterfeit goods These two items are used in the logistic regression equation as measures of consumer attitudes regarding the ethics

of purchasing counterfeit goods (since if something is viewed as illegal, then it would be more unethical to participate in it) The first of these items asked consumers the extent to which they agreed or disagreed with the statement “People who buy counterfeit products are committing a crime.” The second statement was “People who sell counterfeit products are committing a crime.” However, for the logistic regression, these items were reverse coded for ease of interpretation These items were originally coded on a five-point scale with one being strongly agree and five being strongly disagree Respondents who agree with these statements are expected to be less likely to buy counterfeit goods Five items were used to assess the extent to which buying counterfeit items was a way to express anti-big business attitudes An additional two items were designed to measure consumer attitudes regarding the impact of counterfeiting on the US economy and the manufacturers of legitimate goods Finally, three items measured consumer attitudes regarding the quality of counterfeit merchandise Each item was measured on

a five-point scale with one equal to strongly agree and five equal to strongly disagree All 12 of these items were included in the t-tests For the t-tests, the original scale was used for all calculations

Sensitivity Sensitivity was measured in two ways Since students enrolled in textile and apparel courses were of specific interest in this study, one measure was whether a student was a textile and apparel major, or not The variable was coded as a one if they were a textile and apparel major, and a zero otherwise Textile and apparel students were hypothesized to be more sensitized to the issue of counterfeiting, and therefore, less likely to purchase counterfeit goods This sensitivity may have come through classroom instruction, or their own market interactions since fashion items, such as handbags, are a common counterfeit product

The second measure was by asking students the extent to which they agreed or disagreed with the following statement “Counterfeit products have been discussed in

my classes.” A scale of one to five was used with one equal to strongly agree and five equal to strongly disagree Separate regression equations were estimated using the two measures for this variable

Gender A dummy variable for gender was created with females equal to a one, and males equal to a zero Although there were some mixed results in the prior literature (Singhapakdi and Vitell, 1990; Hegarty and Sims, 1978), males appeared more likely to engage in, or approve of, unethical behaviour than females (Chen and Tang, 2006;

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Singhapakdi, 2004) Thus, it is hypothesized that males will be more likely to purchase

counterfeit goods relative to females

Education level Education level was measured based on the students’ year in school

Three dummy variables were created A dummy variable was assigned a value of one

for each of the following years in school: sophomore, junior, and senior/graduate

students Freshmen were used as the comparison category and assigned a value equal

to zero These variables were included to control for possible exposure to the

counterfeit issue throughout the college experience For example, freshmen students

who are a textile and apparel major would not have had the same level of exposure as a

senior in that major

Descriptive statistics

The mean age of the respondents was 19.69 years Almost 70 percent (69.9 percent) of

the respondents were female and 30 percent male (see Table I) The freshman class

made up the largest group in the sample (47.52 percent), followed by sophomores (21.39

percent), seniors (15.45 percent), juniors (14.26 percent) and graduate students (1.39

percent) Over 40 percent (42.17 percent) of the sample came from households with

parental income of $100,000 or more Textile and apparel majors accounted for 26.08

percent of the sample Almost one-third (30.35 percent) of the sample had purchased

counterfeit goods while a little over one-half (53.89 percent) had not Nine categories of

counterfeit goods were identified as having been previously purchased by respondents

(see Table II) The most commonly purchased counterfeit items were handbags (61.84

percent), music (31.58 percent), clothing (22.37 percent) and jewellery (18.42 percent)

Results

T-tests for attitudinal variables

A total of 12 attitudinal questions regarding counterfeit goods were taken from the study

conducted by Tom et al (1998) Table III presents the t-tests showing whether or not a

significant difference exists between buyers and non-buyers of counterfeit goods with

respect to these 12 attitudes The results indicate significant differences between buyers

of counterfeit goods and non-buyers on 11 of the 12 attitudinal questions Only one

question was not statistically significant, “I like buying counterfeit products because it’s

like playing a practical joke on the manufacturer of the non-counterfeit product.”

Purchasers were more likely to express anti-big business sentiments, and were less likely

to believe that counterfeiting hurt the US economy Purchasers were more likely to

believe that counterfeit goods are just as good as designer goods, and less to view

counterfeiting as unlawful These results support those of Tom et al (1998) However,

both purchasers and non-purchasers believe that sellers of counterfeit goods are

committing a crime relative to the buyers of counterfeit goods

Logistic regression results

In general, income was not a significant factor affecting the purchases of counterfeit

goods for this sample However, in the first regression equation, (see Table IV) one

income category, parental income over $100,000 was significant The odds ratio

indicates that students with parents in this income bracket were 99 percent more likely

to buy a counterfeit product compared to students with parental income of less than

$25,000 This positive effect does suggest that counterfeit goods are a normal good

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Attitudes about counterfeit buyers and sellers (being criminals) were significant (see Tables I and IV) If the respondent believed that the buyers and/or sellers were committing a crime, they were less likely to buy counterfeit goods themselves Two variables were used to measure sensitivity, which accounts for the two different logistic regression equations Major was used in one equation (see Table IV), and class discussion was used in the second equation (see Table I) Neither variable was statistical significant This suggests that textile and apparel majors are no more or less likely to buy counterfeit goods relative to other majors It also suggests that exposure to the issue through class discussion has little impact on whether or not students buy counterfeit goods

Variable

Frequency

Gender

Education

Income

Major verses non-major

Purchased counterfeit items

Counterfeit items purchased

Table II.

Demographic

characteristics and

purchase of counterfeit

goods

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