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and organized crime (IACC, 2007; Kelly, 2005; Noble, 2003 cited in Carpenter et
al., 2011). Basing on the counterfeiting activities, terrorists can get money easily
without taking the risk a lot. Moreover, pirating has become a means of funding
for radical fundamentalist groups such as Al Qaeda and Hizbullah (Noble, 2003;
Nurton, 2002, cited in Carpenter et al., 2011).

Job losses. Counterfeiting is one of the causes of job losses at a large scale in
authentic companies.


Loss of taxes: The government faces to the huge losses of tax revenues because the
production and sales of fake products usually evade the duties of paying business


Child and forced labour: The counterfeit producers do not follow the current labor
legislations. According to the International Labor Organization, that millions of
children are forced to work in pirated manufacturers in China, where most of
counterfeit products are produced to serve the US market (Goodwin, 2006).

Therefore, informing consumers to understand about the social consequences of
counterfeiting can be used to send potential consumers of faked products the negative
cues. Salembier, an editor of fashion magazine Harper’ s Bazzar, said, “ If people knew
where their dollars were directed when they buying a fake watch or fake handbag, there is
no question that they would think twice about purchasing a fake” (Harper’s Bazaar,
2007,p.1, as cited in Carpenter et al., 2011). In addition, Penz et al. (as cited in Carpenter
et al., 2011) found that when consumers know more about the specific negative business
practices associated with counterfeits, they will be harder in purchasing counterfeits.

However, according to Bloch et al. (1993) and Cordell et al. (1996) (as cited in
Carpenter et al., 2011), their studies state that consumers may buy counterfeit products
without considering public welfare issues. In some situations, it might be that consumers
are not aware of the social issues associated with pirates. Cuno (2008) found that there is
no difference in intention to purchase counterfeit products between a group with
awareness of the illegality and negative effects of counterfeiting and the other had not.
From these statements, the further hypothesis is:
H4: Social cost of counterfeits is negatively related to consumers’ attitude toward
purchasing counterfeit product.
H5: Social cost of counterfeits is negatively related to purchase intention to counterfeit
Basing on the review of the previous literature and hypotheses presented, the following
conceptual model is proposed.

Figure 2.1 Conceptual Model

This chapter mentions about definition and theoretical background of each concept
in the model. From previous literature, consumers’ attitude toward counterfeit products is
impacted by two factors: perceived risk in counterfeit buying and social cost while
purchase intention toward pirated goods is influenced by perceived risk in counterfeit
buying, social cost and consumers’ attitude toward purchasing these products. There are
five hypotheses in this study.


This chapter mentions about the ways to find the answer for research questions,
including: research design, research process, research scale, sample size, data collection
procedure and data analysis method.
In order to dress a design for research, researchers considered the kind of model
and measures were suitable to the subject of the research. The focus of this research was
examining the factors affecting consumers’ attitude and intention toward purchasing
counterfeit products which includes perceived risk, social cost, the attitude toward
purchasing counterfeits and purchase intention of counterfeit products. An operation
model was presented in Figure 2.1. This research used primary data that collected from
consumers in Ho Chi Minh City. Thus, a questionnaire survey design was used as the
data collecting method.
Based on the literature, the researcher set up the survey instrument, using scales
that were already validated in previous studies.
 Perceived risk was measured by 2 items according scale of Dowlingand Staelin
(cited in Hanzaee and Jalalian, 2012):

The risk that I take when I buy a counterfeited product is high.


There is high probability that the product does not work.

 Consumers’ attitude toward purchasing counterfeited products was measured by 3
items borrowed from scale of Huang et al. (cited in Hanzaee and Jalalian, 2012):


I like shopping for counterfeit products.


Counterfeit products generally benefit the consumer.


Generally speaking, buying counterfeit products is a better choice.

 Social cost was measured by 3 items from scale of Kwong et al. (cited in
Carpenter, 2011)

Counterfeit products hurt the companies that manufacture the

genuine product.

Counterfeit products hurt the world economy.


Counterfeit products discourage investment in innovation and brand

 Purchase intention of counterfeit products was measured by 2 items as the scale of
Summers et al. (cited in Zhang and Kim, 2013).

I would like to buy counterfeit products.


I intend to purchase counterfeit goods within the next year.

All of the measurement scales used Likert scales varying from 1 (completely
disagree) to 5 (completely agree) to explore the opinion of the respondents.
In this study, it was not clarify any counterfeit product in particular. Questions
considered the meaning of “counterfeit products/ pirated products/fake products” in
general because the purpose at this moment was to evaluate consumer attitudes and
purchase intention toward counterfeit products in overall. Next, the author mentioned the
process done to conduct the research.


3.3 Research process
The research comprised two phases, a pilot study and a main survey. The pilot
study was undertaken by qualitative method and a main survey by quantitative method.
 Qualitative research
Based on literature from previous research about the impact of perceived risk and
social cost on consumers’ attitude and purchase intention toward counterfeit products, the
author proposed five hypotheses which were proposed in Chapter 2. After that, the author
adjusted the model and selected the preliminary the scale for questionnaire of the study.
After finishing the preliminary questionnaire, the researcher conducted the indepth interviews with 10 people in Ho Chi Minh City to obtain the correct items in the
context of Vietnamese consumers, check the content and meaning of words used in the
initial measurement scales and modify them to be more suitable and understanding.
Although most of the measures of the constructs were mentioned in the previous
literature, this step is necessary to make them appropriate and easy to understand in the
context of studying. During the interview, the author received some significant feedback
and suggestions from the interviewees to make the improvement for the official
questionnaire. (See Appendix A).
 Quantitative research
After the qualitative research, the author adjusted the questionnaire again to be more
suitable with Vietnam market and easier to understand. When the author considered that
the questionnaire was designed properly, the main survey was conducted widely by using


convenience sample which collected from consumers in Ho Chi Minh City. The process
of the quantitative research was followed these steps:

Step 1: The author composed the questionnaire for the research:

Questionnaire was designed in English, after that the author translated into
Vietnamese for delivering to respondents. (See Appendix B&C).

Step 2: The author defined the sample size of the research:

According to many researchers, the size of the sample depends on the method of
estimate the sample. According to Hair et al. (2010), a general rule, the sample
size should be 100 or greater and the minimum sample is 5 observations for each
scale. The model in this study consists of 4 factors with 10 scales so that the
minimum sample size should be: 10*5 = 50 observations.
For standard multiple regression analysis, the required sample is recommended by
Tabachnick and Fidell (1991) should be n>50+8m (where m=number of
independent variables). There are 4 independent variables in this research. Hence,
the minimum sample required to run multiple regression in this study is n > 50+
8*4= 82 observations.
The author used the sample size at 176 observations. This sample size was
appropriate for EFA and multiple regression analysis. After that, sampling was
conducted based on convenience sampling. All respondents were asked to know
about counterfeit products before answering the questionnaire.

Step 3: The author issued the questionnaire to the interviewees


The author issued questionnaires to respondents who live in Ho Chi Minh City at
the time the research was deployed by delivering directly hard copy to
respondents. In order to be more convenient for respondents, the questionnaires
were also broadcasted via the internet by Google docs. By this way, the author
sent the survey link to respondents via gmail, facebook and yahoo chat. The
respondents could answer the survey by clicking on the link and keying their
answers and submitting the link to the researcher. To make sure respondents
understanding clearly at the beginning of interviews, counterfeit products were
defined as products that bear a brand name or logo without the permission of the
registered owner or an illegally manufactured copy of the genuine item. Data
collection was conducted during 2 weeks. The author collected 120 questionnaires
from online channel and out of 120 questionnaires in hard copies, respondents
returned 103 questionnaires. 120 hard copies were delivered researcher’s
colleagues at the working place and students at University of Economics and at the
library of university of social sciences and humanities in Ho Chi Minh city. In
total, the author collected 223 answers.

Step 4: The author received the questionnaire and checked again for suitable

The author collected 223 answers. After checking and removing the error
questions which were missed answering or answered with value number “3” for
more than fifty percent of the number of questions in the questionnaire from the


list of response. As a result, the usable data or this study was 176 observations. It
is suitable with the requirement of minimum sample size: 82 observations.
Below table summarized collected data from the survey
Table 3.1
The results of collecting questionnaires
Number of
Number of
questionnaires Number of
were usable
after cleaning
were returned Percentage data













From the results showed on Table 3.1, the percentage of questionnaires that surveyed
online returned to researcher and was useful for analysis was higher than delivering
questionnaires in hard copies. This could explain that survey via online, respondents were
answered truly with their thinking because their information was secret and nobody could
know who they were even the author. Moreover, the online survey required respondents
to answer all the questions before submitting the result. Therefore, when one item that
respondent forgot to answer, they could not finish the survey. While conducting the
survey by hard copies, some respondents missed answering ore ignore the item in
questionnaire. As a result, questionnaire without finishing all questions were removed for
data analysis.

 Data code:
Data were reviewed for completion, coded and input the raw data in IBM SPSS
Statistic version 16 with the scale as mentioned in Part 3.2.
3.4 Data analysis method
The SPSS (Statistical Package for Social Science) software version 16.0 was used
in this study for analyzing collected data. Moreover, in order to statistic the sample,
compare the results, other main tools of SPSS version 16.0 and Microsoft Excel were
used for sample description. For the next steps, the reliability and validity of
measurement scales were evaluated by using Cronbach’s alpha and exploratory factor
analysis (EFA). After that, the author used Muliple Regression to test the relationship
between independent variables and dependent variables as proposed hypotheses.
3.4.1 Cronbach’s alpha.
According to Connely (2011):
Cronbach’s alpha is used as only one criterion for judging instruments or scales. It
only indicates if the items “hang together”; it does not determine if they are
measuring the attribute they supposed to measure. Therefore, scales also should be
judged on their content and construct validity (p.45).
As Leech et al. (2005), the acceptable value of Cronbach’s alpha for reliability is
obove 0.7. However, it can reduce to 0.60 – 0.69 range, especially if there is only a
handful of items in the scale. When the Cronbach’s alpha is very high (greater than 0.90),
it probably means that the items are repetitious or there are more items in the scale than
are really necessary for a reliable measure of the concept (Leech et al., 2005).

Beside of evaluating the value of the Cronbach’s alpha, the Corrected Item – Total
Correlation is also important to consider. According to (Leech et al., 2005), if this
correlation is quite high or high (equal 0.40 or above), the item is probably correlated
with most of the other items and make a good component of this summated rating scale.
If the item – total correlation is negative or too low (less than 0.30), it is necessary to
consider the item for wording problems and conceptual fit by modifying or deleting such
3.4.2 Exploratory factor analysis (EFA)
Norris and Lecavalier (2010, p.9) declared that “EFA is based upon a testable model and
can be evaluated in terms of its fit to the hypothesized population model; it indices can be
generated to help with model interpretation”. On other hand, EFA method is used to
identify which of a large set of items go together as a group, or are answered most
similarly by respondents (Leech et al., 2005).
3.4.3 Multiple regression analysis
The multiple regression analysis is used to test the hypotheses and predict one
outcome measure from several independent variables (Leech et al., 2005). According to
Leech et al. (2005), the multiple regression analysis requires many assumptions but it is
better to focus on the major ones that are tested easily with SPSS. The assumptions
1. The independence of residuals (errors).
2. A linear relationship between each of the predictor variables and the dependent