digital marketing

1. Predicting consumer
digital piracy behavior
The role of rationalization and perceived
consequences
Irena Vida and Mateja Kos Koklič
Marketing Department, University of Ljubljana, Ljubljana, Slovenia
Monika Kukar-Kinney
Marketing Department, University of Richmond, Richmond, Virginia, USA and
University of Ljubljana, Ljubljana, Slovenia, and
Elfriede Penz
International Marketing Management, Wirtschaftsuniversität Wien,
Vienna, Austria
Abstract
Purpose – Thepurpose of thispaper isto investigateconsumer perceptionsof personal risk and benefits
ofdigitalpiracybehaviorasdeterminantsofone’sjustificationforsuchbehaviorandtheconsequentfuture
piracy intention. Temporal effects of rationalization in shaping future piracy intent are also addressed.
Design/methodology/approach – A conceptual model was developed using counterfeiting and
piracy literature. Data were gathered via mail and online survey of adults in five European Union
countries. The model was tested on pooled sample using confirmatory factor analysis and structural
equation modeling.
Findings – Rationalization mediates the relationship between perceived benefits and piracy
intention, but not between perceived risk and intention. Both perceived risk and benefits affect piracy
intent, with risk reducing it and benefits increasing it. Rationalization of past behavior increases future
digital piracy intent.
Research limitations/implications – Risk measure was limited to technical problems, thus future
studies should examine a wider scope of risk dimensions. The cross-sectional design of the study also
creates some limitations. A longitudinal methodology could provide a better insight into sequencing of
rationalization.
Social implications – Marketing communications should increase public awareness of risks and
reduce perceived piracy benefits to reduce future piracy intent. Public persuasion activities should
counter the arguments consumers use to rationalize their piracy behavior.
Originality/value – This research fills in a void in knowledge on how expected consequences drive
rationalization techniques, particularly with respect to future piracy intent. A realistic data set drawn
from adult population in five countries is used, enhancing external validity.
Keywords Digital piracy, Consequences, Risk, Benefits, Rationalization, Piracy intent,
Digital technology, Consumer behaviour, European Union
Paper type Research paper
The current issue and full text archive of this journal is available at
www.emeraldinsight.com/2040-7122.htm
Data collection for this study was supported by the Commission of European Community,
contract no. 217514 (EU – 7th Framework Programme). Authors gratefully acknowledge
contributions of research partners from all countries participating in this research project.
JRIM
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Received 15 February 2012
Revised 7 May 2012,
18 June 2012
Accepted 6 July 2012
Journal of Research in Interactive
Marketing
Vol. 6 No. 4, 2012
pp. 298-313
q Emerald Group Publishing Limited
2040-7122
DOI 10.1108/17505931211282418

2. 1. Introduction
With rapid advances in technology and the increasing global availability and
accessibility of digital channels for information/media distribution, illicit behavior
regarding digital goods continues to perplex practitioners and researchers alike. Digital
piracy represents a growing threat to the welfare of both producers and consumers
(Phau and Ng, 2010; Sinha et al., 2010). While the exact loss for the supply side remains
inconclusive, industry antipiracy group BASCAP (2011) estimated the income loss to
range from $30 to $75 billion in digitally pirated music, movies and software industries
alone, rising up to $240 billion by 2015. Some researchers question these estimates,
seeking a more balanced approach by identifying both positive and negative effects for
the producers (Bhattacharjee et al., 2006; Mattelart, 2009). Similarly, mixed effects have
been recognized for the consumers as stakeholders taking part in digital piracy: both
gains or benefits (such as price benefits) and losses or risks (such as a threat of computer
virus) (Hennig-Thurau et al., 2007; Phau and Ng, 2010; Sirkeci and Magnúsdóttir, 2011).
Undeniably, industries, policy makers and consumers are faced with the challenging
environment and omnipotent institutional regime of existing digital copyright
management. Current efforts aimed at curtailing digital piracy have left various
stakeholders disgruntled due to either financial losses or by impinging on ideology of
consumer rights, free access and creativity expression (Goles et al., 2008; Mattelart,
2009). Given the interdisciplinary nature of the problem, researchers in the areas of
marketing, ethics, computer systems and criminology examined both the supply and the
demand sides of the issue. Yet, several voids remain in the literature before adequate
solutions can be identified.
This study offers empirical insights into factors underlying consumer illicit
behavior in the context of downloading, sharing and using digital products (e.g. music,
software, movie files) across five European Union (EU) countries. We aim to examine
consumer perceptions of expected personal consequences (e.g. perceived risk and
benefits) as drivers of an individual’s justifications for illicit behavior regarding digital
goods and behavioral intention to engage in such activities. Moreover, by applying
neutralization theory, we investigate the temporal effects of rationalization behavior in
shaping future piracy intent. When knowingly engaging in ethically questionable
behaviors, individuals tend to resort to rationalization, a common method of reducing
negative feelings by offering justification of their fraud, while still believing in their
ethical values (Dacin and Murphy, 2011).
The contribution of this study is threefold. First, we provide a balanced view by
examining both expected gains and losses associated with digital piracy intent and
rationalization of past piracy behavior. While previous studies acknowledged that
expected consequences of the action may affect an individual’s choice of behavior (Yoon,
2011), far less attention has been focused on ways in which such perceptions drive
rationalization techniques and thought processes behind digital piracy (McGregor,
2008). Insights into the drivers of rationalization, i.e. perceived risks and benefits, have
important implications for antipiracy communication campaigns, particularly due to the
low efficacy of existing appeals focusing mostly on adverse effects, such as emphasizing
guilt appeals (Lysonski and Durvasula, 2008; Zamoon and Curley, 2008). Second, we test
our conceptual model in a cross-national context using five EU countries. While
this region is one of the largest free-trade areas in the world, most existing piracy
research to date has been limited to the US and Asia (Aleassa et al., 2011; Eisend and
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3. Schuchert-Gueler, 2006). Third, we use realistic data sets drawn from adult computer
users across the five countries in the EU using multiple methods of data collection.
Previous empirical studies of the demand-side of piracy tend to rely on student samples
rather than generalpublic. This threatens generalizability as the illicit digitalbehavior is
by no means limited to university settings (Williams et al., 2010; Yoon, 2011).
The paper is structured as follows. First, we briefly review the existing literature on
digital piracy. Then, we develop a conceptual framework which serves as the basis for
the construction of the hypotheses. Next, we report on the measures used, the data
collection methodology and the analytical procedures. Finally, we present the findings
of the study and discuss their implications and future research avenues.
2. Conceptual model and hypotheses
Researchers delving into the demand-side of digital piracy have utilized different
methodological approaches and applied various theoretical frameworks to explain
unauthorized consumer activities on the internet. While this is not surprising given
the interdisciplinary nature of the problem (e.g. business ethics, marketing and
information systems), research community has yet to establish consistent theoretical
frameworks to guide empirical efforts on digital piracy (Eisend and Schuchert-Gueler,
2006; Williams et al., 2010). The two most prominent theoretical approaches to
studying illicit digital behavior have been the expectancy-value theories (e.g. the theory
of reasoned action), and the theories of ethical decision making (e.g. Hunt and Vitell’s
model of ethical decision making). Both of these are established on the fundamental
premise that individual’s intentions are mostly consistent with the underlying
attitudes (Chatzidakis et al., 2007).
However, consumers’ attitudes do not always translate into purchase intentions and
consequently behavior. For example, even though unauthorized downloading of digital
products is treated as an illegal activity in most countries, many computer users,
particularly among the youth and in the university settings, exhibit lenience and
acceptance of such activities (Harris and Dumas, 2009; Hinduja, 2007; Kini et al., 2003).
An illustration is provided by a software piracy study among computer science
students, which found that while future information system professionals recognize the
consequences of such behavior for the industry and others, and even admit to its
immoral character, such cognizance does not discourage them from illicit computer
behaviors (Konstantakis et al., 2010). An explanatory framework for this discrepancy
can be found in the neutralization theory, which explains individuals’ attempts to
minimize the negative feelings related to their norm-violating behavior based upon their
self-concept and the perceptions by others (Grove and Vitell 1989; Shields and Whitehall,
1994). In their seminal work, Skyes and Matza (1957) developed five neutralization
techniques: denial of responsibility (“it’s not my fault”), denial of injury (“no harm
resulted from my actions”), denial of victim (“nobody got hurt”), condemning the
condemners (“how darethey judge me when they are just as corruptor hypocritical”) and
appeal to higher loyalties (“there is a greater cause”).
Neutralization theorists suggest individuals may employ these techniques both
before committing fraud, in order to avoid the negative affect (i.e. feelings of guilt or
shame), or after committing fraud, in order to reduce or neutralize the negative affect.
This means that neutralization occurs as an after-the-fact rationalization that may
create conditions for future behavior (Harris and Dumas, 2009; Higgins et al., 2008).
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4. Employing neutralization techniques helps individuals reassure themselves of the
appropriateness of their choices, and demonstrates their acceptability to others
(Hinduja, 2007). The rationalization (justification or neutralization) theory has been
used when investigating digital piracy (Morris and Higgins, 2009), software piracy
(Hinduja, 2007; Phau and Ng, 2010), music piracy (Ingram and Hinduja, 2008) and
online misbehavior in general (Harris and Dumas, 2009).
Based on the overview of the digital piracy literature, a lack of studies exploring
determinants of neutralization has been recognized. Some authors suggest that
information and knowledge are the main influencing variables (D’Astous and Legendre,
2009; Nicholls and Lee, 2006). With respect to information, the most significant impact
is the difference in perception of positive and negative message framing. More
specifically, a message conveying information about negative consequences plays a
different role in the decision making than a message about positive consequences
(Block and Keller, 1995; Chang, 2008). Along these lines, perceived risk can be regarded
as a consumer’s belief in negative consequences, while perceived benefits can be
described as a consumer’s belief in positive consequences (Yoon, 2011).
Our synthesis of counterfeiting and piracy literature provided the basis for
development of a conceptual model for the study (Figure 1). In the model, we explore the
role of perceived risk and perceived benefits in shaping two focal constructs:
rationalization of past behavior and future piracy intent. To shed more light on the
attitude-intention discrepancy (Chatzidakiset al., 2007;Phauet al., 2009),we also examine
the effect of rationalization on future piracy intent. The proposed conceptual model,
including the construct definitions and rationale for the hypotheses, is discussed next.
2.1 Determinants of rationalization
The first set of hypotheses focuses on the determinants of rationalization. In our study,
we define “rationalization” as a consumer’s technique to counter feelings of guilt
associated with the past engagement in digital piracy (Moore and McMullan, 2009).
“Perceived risk” refers to the probability that using illegally downloaded files would
result in technical problems with the computer. The concept of perceived risk has been
previously investigated in the piracy context, suggesting that it plays an important role
in curtailing the digital piracy phenomenon (Sinha and Mandel, 2008). We base our
prediction on the framing effect literature, which contends there are substantial
differences in how we process negatively and positively framed information.
Specifically, since negative framing evokes comparison to internal norms or
standards (Block and Keller, 1995), we expect that perceived risk as negatively
Figure 1.
Conceptual model
H1
Perceived
risk
Perceived
benefits
Rationalization Piracy
intention
H2
H5
H3
H4
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5. framed information will reduce the extent to which an individual employs
rationalization techniques as a means to justify norm-violating behavior. Thus, the
more intensely an individual reviews his/her internal norms, the less likely s/he is to
justify his or her past behavior:
H1. The greater the perceived technical risk of digital piracy for consumers, the
lower the extent of their rationalization for the past digital piracy behavior.
“Perceived benefits” or the extent to which consumers believe that illegally downloading
files will result in certain positive consequences have been scarcely explored in the
piracy context (Hennig-Thurau et al., 2007; Yoon, 2011). As in H1, we formulate our
prediction of the impact of perceived benefits on rationalization based on the framing
effect theory. Contrary to perceived technical risk (H1), perceived benefits lead an
individual to review his/her internal norms and standards less intensely, thus increasing
the extent to which consumers use rationalization (Block and Keller, 1995). Therefore, we
expect that perceived benefits of illegally downloading files will result in an increased
use of rationalization techniques:
H2. The greater the perceived benefits of digital piracy for consumers, the greater
the extent of their rationalization for the past digital piracy behavior.
2.2 Determinants of future digital piracy intention
The second set of hypotheses focuses on the antecedents of “future digital piracy
intention”, defined as the likelihood that consumers will illegally download files from the
internet in the future. Existing studies offer contradictory findings with respect to the role
ofperceivedrisksoradverseeffectsinshapingfuturepiracyintention.For example,while
perceived risk of getting caught downloading illegally (i.e. legal risk) is a strong deterrent
for certain consumers, it can actually increase piracy tendencies for others (Sinha and
Mandel, 2008). On the other hand, Hennig-Thurau et al. (2007) provide empirical evidence
of the impact of perceived risk on consumer’s actual behavior. They conclude that
while search and moral risks provide hurdles for obtaining illegal copies, technical risks
directly reduce the probability of watching such copies. Since perception of adverse
effects as determinants of piracy intentions and behaviors has been operationalized in
various ways and produced conflicting results, the testing of the hypotheses stated below
provides an opportunity to resolve this controversy. We predict that:
H3. The greater the perceived technical risk of digital piracy for consumers, the
lower the consumers’ future piracy intent.
Another hypothesized driver of consumer intentions to pirate digital goods is perceived
benefits. The underlying rationale is that a consumer intends to engage in digital
piracy because of certain preferred outcomes, i.e. perceived benefits. This relationship
has been empirically supported in several studies. For example, Yoon (2011) shows
that perceived benefits have a positive impact on an individual’s intention to commit
digital piracy. Similarly, Hennig-Thurau et al. (2007) demonstrate a significant causal
link between two specific benefits, illegal copies as collectibles and anti-industry
utility, and obtaining of illegal copies. Likewise, Lysonski and Durvasula (2008) find a
significant positive correlation between social benefits of dissemination and intention
to illegally download. To provide additional evidence of this relationship in a novel
setting, we hypothesize:
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6. H4. The greater the perceived benefits of digital piracy for consumers, the greater
the consumers’ future piracy intent.
Future piracy intent is also shaped by consumer’s use of neutralization techniques.
Neutralization techniques as an after-the fact rationalization may create conditions for
future piracy behavior (Higgins et al., 2008). This link has been previously tested by
several researchers. Ingram and Hinduja (2008) find that greater acceptance of the
neutralization techniques significantly predicts moderate to high levels of piracy
participation. Likewise, Morris and Higgins (2009) show that neutralization was a
significant determinant of the expected counts of various forms of digital piracy. This
relationship was strongest for music and video, and less so for software piracy. Thus, the
more the consumer rationalizes his downloading files illegally from the internet in the
past, the more likely s/he will continue to piratedigital content. In thiscase, rationalization
for the past digital piracy behavior serves as neutralization for future behavior:
H5. The greater the consumers’ rationalization for their past digital piracy
behavior, the greater the consumers’ future piracy intent.
3. Methodology
In order to test the conceptual model for the study, a self-administered survey was
conducted in EU. To ensure a broad representation of different parts of the EU, five
countries representing various geographic regions of the EU were included in data
collection: Austria, Italy,Slovenia, Sweden andUK.We used mixed method sampling and
data collection techniques using both probability (mail survey) and purposive sampling
strategies (online survey). For our mail survey, a sample representative of general adult
population in terms of age and gender was drawn in each country. The mailing lists were
obtained from local research institutions. In case of online survey, we recruited
participants by posting the link to the survey on various web pages. We also sent the link
to our acquaintances via e-mail and asked them to recruit future subjects from among
their acquaintances. The decision to use mixed methods was guided mostly by the
motivationtoincreasegeneralizabilityandincreaseinferencequality (Kemperetal.,2003).
The overall response rates for the mail survey ranged between 10 percent to just over
13 percent across countries. A raffle with various prizes was offered as an incentive. The
data set used in this study was part of a large research project investigating EU consumer
attitudes andbehaviors regardingboth counterfeiting andpiracy. Hence,the originaldata
set was first reduced by including merely respondents having reported to use computers,
and have actually engaged in digital piracy in the past, which yield a sample of
6,666 respondents from five countries. Second, such large sample size is deemed too large
considering the use of covariance analysis in testing our hypotheses. Therefore, we
reduced the overall sample for use in the analysis by randomly selecting respondents
within the countries. In total, the final sample comprised of 1,213 respondents, including
215 from Austria, 244 from Italy, 250 from each Slovenia and Sweden, and 254 from the
UK. Slightly over 77 percent of the total sample used in this study was derived from the
mail survey and almost 23 percent from the online survey.
Overall, our sample consisted of more male than female respondents (52.9 percent
males). Across countries, the proportion of males ranged from 43.4 percent in Slovenia to
57.9 percent in Italy (UK 53.6 percent, Austria 53.7 percent, Sweden 56 percent).
Theaverageageofrespondentsinthesamplewas 36.4years(standarddeviation of14.3),
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7. with the lowest mean in the Slovene subsample (32.5 years), and the highest mean in the
Italian subsample (39.6 years) (Austria 33.8, UK 37.7, Sweden 38.2). The majority of the
respondents attained at least university education (43.6 percent), similar but slightly
lower proportion completed college (41.7 percent), and less than 15 percent completed
primary or vocational school. Country-wise, the highest proportion of respondents with
this education was in Italy (23.2 percent of the Italian subsample) and the lowest in
Austria (3.7 percent) (Sweden 16.6, UK 21.2, Slovenia 8.0). The proportion of
college-educated respondents ranged from 57.4 percent in Slovenia, 51.5 percent in Italy,
38.9 percent in Sweden, 38 percent in the UK, to 20 percent in Austria. The Austrian
subsample consisted of the highest share of people with university degree or more
(76.3 percent), followed by the Swedish (44.5 percent), the UK (40.8 percent), the Slovene
(34.5 percent), and the Italian subsample (25.3 percent).
All construct measures were either directly taken or adapted from existing literature.
The perceived technical risk associated with digital piracy or the potential technical
damage to the consumer’s computer was measured with six items, adapted from
Hennig-Thurau et al. (2007). The perceived benefits of digital piracy behavior were
measured with five statements, tapping into various specific benefits, such as collection
and technical benefits (Hennig-Thurau et al., 2007). Five statements, adapted from Skyes
and Matza’s five neutralization techniques (1957), measured the consumers’
rationalization of their past piracy behavior. To measure the future digital piracy
intention, two items from Taylor and Todd (1995) research were used. All measures,
individual statements used, standardized factor loadings from the confirmatory factor
analysis, and construct reliabilities are reported in Table I.
Measures used in this study were carefully adapted to the different linguistic and
culturalcontextswiththeadditionaltestingofreliability.Asperguidelinesforconducting
cross-national consumer research (Craig and Douglas, 2000; de Jong et al., 2009),
the process of developing the survey instrument and modifying the scale items included:
.
elimination of items with limited conceptual equivalence;
.
ensuring the translation is decentered from a literal language translation; and
.
careful pretesting of the research instrument on a convenience sample of relevant
individuals in each country, along with the subsequent modification of
individual items in our measures.
4. Analysis and findings
Even though our goal was not focused on comparing different countries within the EU,
we assessed invariance of measures across the countries included in our sample. First,
we evaluated “configural invariance” of measures to see whether the same pattern of
zero and non-zero factor loadings exists in different countries (Horn et al., 1983). Using
confirmatory factor analysis, all salient factor loadings were substantially and
significantly different from zero and the factor inter-correlations were significantly
below unity in all five counties. Thus, the measures achieved the configural invariance.
Next, we assessed “metric invariance” or the requirement of equal metrics or scales
(Rock et al., 1978). Metric invariance allows a meaningful comparison of ratings or
difference scores across countries, with these differences indicative of similar
cross-national difference in the underlying construct (Steenkamp and Baumgartner,
1998). To test for metric invariance, we constrained all factor loadings to be the same
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8. across the five countries. The full metric invariance model fit the data as well as the
configural model and achieved even a slight decrease in the value of x 2
per degree of
freedom. Therefore, the measures exhibited cross-national metric invariance. Next,
we proceeded with evaluation of the pooled sample.
To assess the adequacy of measures in the pooled sample, confirmatory factor
analysis in AMOS was conducted. As the x 2
-statistic is sample size dependent, other fit
indices better serve as indicators of the model fit (Bagozzi and Yi, 1988). The fit of the
confirmatory factor model with the data was good (x 2
¼ 790 df ¼ 129; NFI ¼ 0.93;
IFI ¼ 0.94; CFI ¼ 0.94; RMSEA ¼ 0.065). All construct reliabilities exceeded the
recommended 0.70 (Table I). Discriminant validity was checked by constraining the
covariance in any set of two constructs (Anderson and Gerbing, 1988) and then
performing a x 2
difference test on the values obtained for the constrained and
unconstrainedmodels.Sincetheunconstrainedmodelshadsignificantlylowerx 2
values,
Constructs and construct items
Reliabilities
(Cronbach a) Stand. factor loadings
Perceived risk (adapted from Hennig-Thurau et al.
(2007)) 0.89
Illegally downloading files is risky because
They might not work properly 0.57
You might have your internet access terminated 0.60
They might infect your computer with a virus or
malware 0.76
It could allow access to your data, files or passwords 0.91
They might enable your identity to be stolen 0.89
They might damage your computer 0.82
Perceivedbenefits(adaptedfromHennig-Thurauetal.
(2007)) 0.82
Illegally downloading files offers a real bargain 0.71
Illegally downloaded files work as well as the legal
ones 0.61
Illegally downloading files increases my ability to
collect music/films/games 0.77
Illegally downloading files allows me to have files
that I would not be able to afford 0.71
Illegal downloading helps me get music/films/games
faster compared to legal channels 0.69
Rationalization (Skyes and Matza, 1957) 0.76
I couldn’t help myself; I had to illegally download the
files 0.56
It’s no big deal as no one was hurt 0.73
It’s the industry’s own fault they were taken
advantage of 0.61
I was only doing what others do all the time 0.64
I wouldn’t have bought the legal ones anyway 0.58
Piracy intention (Taylor and Todd, 1995) 0.88
I intend to illegally download files from the internet
in the future 0.89
If the need or opportunity arises within the next
month, I would illegally download files 0.90
Table I.
Constructs, construct
items, reliabilities and
standardized factor
loadings
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9. it can be concluded that the measures exhibit acceptable discriminant validity. Next, the
conceptual model was tested using structural equation modeling in AMOS. Structural
model provided a good fit with the data (x 2
(df) ¼ 790 (129); NFI ¼ 0.93; IFI ¼ 0.94;
CFI ¼ 0.94; RMSEA ¼ 0.065). Individual hypotheses test statistics and results are
displayed in Table II and are discussed next. Because the hypotheses were directional,
one-sided hypotheses tests were employed.
H1 predicted that the perceived technical risk of digital piracy will be negatively
associated with the consumers’ rationalization of their past piracy behavior. The
findings do not provide support for this hypothesis, as the standardized regression
coefficient of the proposed structural path was not significantly different from zero
(b ¼ 0.05, t ¼ 1.58, p ¼ 0.11). H1 is thus rejected. H2 proposed that the perceived
benefits of digital piracy will be positively related with the consumers’ rationalization of
piracy behavior. According to the analysis, as perceptions of benefits of piracy increased,
so did the rationalization for the behavior (b ¼ 0.778, t ¼ 14.88, p ¼ 0.000), providing
support for H2. In addition to predicting an indirect effect of perceived technical risk and
perceived benefits through rationalization, we anticipated that both the perceived
technical risk and the perceived benefits will also directly influence consumers’ future
piracy intent (H3 and H4). The findings show that, as the perceived technical risk
increased, the consumers’ intent to digitally pirate decreased (b ¼ 20.13, t ¼ 25.14,
p ¼ 0.000), supporting H3. In addition, as the perceived benefits increased, so did the
intent to digitally pirate in the future (b ¼ 0.41, t ¼ 7.71, p ¼ 0.000), supporting H4.
Lastly, we predicted that the extent of consumers’ rationalization for their past piracy
will be positively associated with their future piracy intent. Indeed, as the extent of
rationalization increased, so did the respondents’ future piracy intent (b ¼ 0.38, t ¼ 6.92,
p ¼ 0.000). Thus, H5 is also supported. Based on the squared correlations in the final
model, approximately 59 percent of variance in rationalization can be explained by
perceived benefits and perceived technical risk, and 61 percent of variance in piracy
intention by perceived benefits, perceived technical risk, and rationalization.
5. Discussion of findings
In developing and empirically evaluating our conceptual model, we first investigated
determinants of consumers’ use of rationalization for past piracy behavior
Hypothesis:
direction Structural path
Std. regr.
coefficient t-statistics p-value
Hypothesis
outcome
H1.: 2 Perceived
risk ! rationalization
0.05 1.58 0.11 Rejected
H2.: þ Perceived
benefits ! rationalization
0.78 14.88 0.000 Supported
H3.: 2 Perceived risk ! piracy
intention
20.13 25.14 0.000 Supported
H4.: þ Perceived
benefits ! piracy intention
0.41 7.71 0.000 Supported
H5.: þ Rationalization ! piracy
intention
0.38 6.92 0.000 Supported
Notes: x 2
(df) ¼ 790 (129); NFI ¼ 0.93; IFI ¼ 0.94; CFI ¼ 0.94; RMSEA ¼ 0.065;
n (sample size) ¼ 1,213
Table II.
Testing the
conceptual model
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10. (i.e. perceived technical risk and perceived benefits), and second, the antecedents of
consumers’ future piracy intent (i.e. perceived technical risk, perceived benefits and
rationalization of past piracy behavior). All proposed hypotheses were supported with
an exception of the effect of perceived technical risk of digital piracy on consumers’
rationalization of their past piracy behavior (H1). We anticipated a negative
association between the two constructs, but the effect was not significant. Similarly,
although in a somewhat different context of ethical consumption, Sander (2010) failed
to provide empirical evidence for a significant impact of negatively framed information
(such as perceived risk) on the use of neutralization techniques, and used sensitivity of
the topic as a possible explanation. This reasoning may also be applicable to our study.
In addition, given the focus of the perceived risk measure on technical damage
associated with digital piracy, another plausible explanation is that other types of
risks, such as those tapping into the ethics or morality (e.g. prosecution risk), may more
prominently shape the use of rationalization techniques. Research on attitudes and
behaviors finds similar gaps and suggests that the specificity of measures might
interfere with the predictability of behavior. In addition, perceived technical risk and
rationalization of past behavior may not be cognitively related. Perceived technical
problems might be salient when actually performing the behavior, while rationalizing
one’s past behavior focuses on the positive effects and the risk is not relevant anymore.
This points towards a distinction between performing a behavior (e.g. using a service,
such as downloading files), where certain risks occur, and evaluating one’s own
behavior retrospectively, where the benefits of the behavior are more salient.
This explanation seems likely, particularly in the light of support found for H2.
With respect to expected positive consequences of digital piracy, we find that
perceived benefits have a significant and relatively large effect on the consumers’
rationalization for their piracy behavior (H2). Although we do not explicitly address
the mechanisms of this impact, we suggest that the more benefits consumers expect
from illegally downloading files, the less they adhere to their norms. Instead, in order to
reap those benefits, consumers resort to rationalization techniques, thus providing
excuses for their behavior.
All three hypotheses regarding the antecedents of an individual’s intention to engage
in future digital piracy (H3, H4, and H5) were empirically supported. Specifically,
perceived technical risk, perceived benefits and rationalization proved to be significant
predictors of consumer’s intention to illegally download files in the future. Although
previous results with respect to the relationship between risk and intention are
somewhat equivocal (Sinha and Mandel, 2008), our research findings are unambiguous,
indicating an inverse relationship between perceived technical risk and consumer’s
intention to engage in digital piracy (H3). This is consistent with several other empirical
studies (Hennig-Thurau et al., 2007; Lysonski and Durvasula, 2008; Yoon, 2011).
The results of our study further support the positive effect of perceived benefits on
digital piracy intention (H4). This corresponds to Hunt and Vitell’s (1986) contention
that an individual veers toward a certain type of behavior directly because of certain
preferred consequences. The third significant predictor of consumer’s intention to
illegally download files identified in this study is consumer’s use of rationalization for
past piracy behavior (H5), corroborating existing research findings (Ingram and
Hinduja, 2008; Morris and Higgins, 2009). This finding can be also explained by the
effect of past behavior on future behavior intentions. The more positive one perceives
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11. his/her own behavior to be (through rationalizing it and thus making it more positive),
the more confident the person might be to perform the same behavior in the future.
An interesting finding, although not the primary objective of this study, is the
relative importance of the three determinants of future piracy intention. Our results
suggest that the strongest driver of one’s piracy intent is his/her perception of benefits,
closely followed by the use of rationalization techniques. Perception of technical risk is
the weakest predictor of behavioral piracy intention. It appears that the negative
factors (risks) and positive drivers (benefits) have a different role in affecting future
behavior. Perceived benefits seem to strengthen the piracy intent, while the risks might
reduce the magnitude of the behavior, but not fully eliminate the intention to actually
perform the behavior.
These empirical findings add to the limited body of knowledge pertaining to
neutralization and rationalization techniques previously rather neglected in
customer-focused studies (Harris and Dumas, 2009). Although the study was
cross-sectional and the measures of intention were gathered concurrently with
rationalization, the study provides evidence that rationalization occurs after piracy
behavior takes place, which potentially enhances continuity in future behavior.
6. Implications, limitations and future research
The present research offers useful implications for marketing communications and
public policy strategies as well as for academic research. Digital piracy importantly
affects various stakeholders, including recorded music, movie and software
industries, distributors and consumers. So far, the efforts to curtail this practice
included mostly promoting public awareness through consumer education and
protecting intellectual property rights through legal threats and actions against
individuals and operators of networks facilitating digital piracy activities. However,
such deterrent strategies tend to be ineffective (Bhattacharjee et al., 2006; Sinha and
Mandel, 2008).
Instead, emphasizing preventive strategies is more strongly encouraged (Gopal et al.,
2004; Sinha and Mandel, 2008). Our findings provide a roadmap to guide marketers
and policy makers in meeting the challenge of digital piracy by focusing attention on
three areas to directly impinge on individual’s piracy intent: perceptions of specific
benefits from downloading, consumers’ perceptions of technical risk, and justifications
for their past actions. In more practical terms, this means first, perceived benefits
should be lessened. Second, perceived technical risks should be emphasized and, third,
the acceptance and the impact of rationalization arguments need to be weakened so
that they do not serve as a way out anymore. Hence, marketing communications
centering on public awareness of personal consequences of digital piracy should be
effective in deterring future piracy intention. Such strategies could include using the
social context of consumers rather than communication by institutions, governments
or firms for communicating risks rather than benefits of piracy. For instance, in online
forum discussions, the perception of technical risks could be attenuated instead of
overemphasizing the benefits of piracy. Marketers’ role in this context could be to turn
attention to consumers’ benefits of legally obtaining products rather than using pirated
alternatives in their communication and product policy. Social media and discussion
forums could be used to understand the influence of the social environment on
consumers’ perception of risk and benefit, which helps in framing marketing messages.
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12. In the general public, the image of piracy as heroic acts needs to be transferred into
a perception of piracy as less acceptable behavior (e.g. by stressing the loss for
independent artists rather than stressing losses for big corporations). Our findings
reveal that perceived benefits have the strongest impact on both rationalization and
piracy intent. If illegal downloading provides fewer benefits than legal downloading,
then perceptions of risks might prevail, consequently reducing rationalization and
future piracy intent. For instance, these could include beliefs that legal options are
equally inexpensive and meet consumers’ needs at a convenient time, or that illegal
sources are difficult to find and do not offer a full range of options.
Rationalization can be seen as a cognitive mechanism which prevails if internal
standards and norms are less strongly reviewed by individuals. In other words, to
overcome the obligation to behave according to (learned) norms and standards,
individuals use commonly accepted arguments that are, for instance, brought forward
in informal communication among peers and are used in the mass media as well
(“piracy is a peccadillo”). Rationalization seems to be an effective way of achieving
distance to internal standards and could help in establishing a certain state of balance
between internal norms and standards and one’s behavior even if or because the
behavior violates existing norms. As long as rationalization arguments are personally
and socially accepted, individuals will use them for norm-violating behavior. A way to
reduce their effectiveness is to make arguments more difficult to accept, i.e. providing
counterarguments to rationalization arguments, or more difficult to build new ones.
For public policy makers, the results of this study can facilitate an understanding that
how individuals review their past behavior impacts their future intent. This could
mean that the review process (rationalization) could be controlled by educational and
consumer protection-related efforts. In other words, challenging the publicly accepted
arguments of piracy as peccadillo through projects in which key actors present
multiple views and consequences of piracy could be a way to counter the issue.
Based on the knowledge of how consumers use rationalization/neutralization
techniques to justify digital piracy, marketing communications and persuasion
activities can be designed to counter the arguments that consumers use. Nonetheless,
designing these activities requires some caution, as it is also possible that – instead of
adapting their behavior by reducing and/or eliminating piracy behaviors – consumers
might invent new neutralizing beliefs (Minor, 1981).
In summary, this study provides three target constructs, i.e. benefits, risk, and
rationalization, on which to focus in the development of preventive-based appeals of
persuasion (e.g. intentions, attitudes). From an academic perspective, our findings reveal
the importance of perceived benefit as antecedent for rationalization strategies and
subsequently its impact on future piracy intent. It shows also that perceived technical
risk is less influential on cognitive processes, but has a negative influence on future
piracy intent.Thisextendspreviousresearchon predictorsforpiracyintentandbehavior
in that perceived gains rather than losses drive rationalization of past piracy behavior.
The findings and contributions of this study are constrained by certain limitations of
our empirical effort, in turn suggesting potentially fruitful avenues for future research.
First, our measure of perceived adverse consequences was limited to technical aspect
of risk. Examining a wider scope of risk dimensions, such as prosecution risk or other
types of psychological risks (Chiou et al., 2005; Liao et al., 2010) may offer a more
comprehensive insight into this concept. Second, the cross-sectional design of the study
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13. creates some limitations. Although rarely applied in the piracy research (Williams et al.,
2010), a longitudinal methodology could provide a stronger inference, particularly with
respect to the sequencing of rationalization. What is more, experimental designs could
help determining the causality of rationalization and perceived benefit and risk. This
topic has been recognized as an under-researched area needing further investigation
(Harris and Dumas, 2009). Third, while precautions have been taken in the sampling and
data collection process across five countries to ensure reliable data, the use of constructs
of potentially sensitive nature (i.e. aberrant behavior) in self-reported surveys may
have been impacted by socially desirable responding (Steenkamp et al., 2010). This
limitation is more likely present in a non-student population. Students and other
younger consumers, who have grown up with easy access to free content on the internet,
have a more liberal view of sharing content and may fail to recognize piracy as a
transgression of social norms (Sinha and Mandel, 2008).
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About the authors
Irena Vida is a Professor of Marketing at Faculty of Economics at the University of Ljubljana.
Her research focus is on application of consumer behaviour theories and models in cross-cultural
settings and on strategic issues in international marketing. She published articles in various
journals such as Journal of Business Research, European Journal of Marketing, Journal of
International Marketing, International Marketing Review and International Business Review.
Irena Vida is the corresponding author and can be contacted at: irena.vida@ef.uni-lj.si
Mateja Kos Koklič is an Assistant Professor of Marketing at the Faculty of Economics,
University of Ljubljana in Slovenia. Her research focuses on topics such as consumer behaviour
and consumer decision making, especially with respect to counterfeiting and piracy, as well as
perceived risk in different purchasing situations. She has published her findings in journals, such
as International Journal of Consumer Studies and Managing Global Transitions.
Monika Kukar-Kinney is Associate Professor of Marketing in the Robins School of Business,
University of Richmond, Richmond, Virginia and a Visiting Professor at the University of
Ljubljana, Faculty of Economics, Slovenia. Her research focuses on compulsive buying,
behavioral pricing, retailing and electronic commerce. Her work has appeared in journals such as
the Journal of the Academy of Marketing Science, Journal of Consumer Research, Journal of
Retailing, and Journal of Business Research, among others.
Elfriede Penz is Associate Professor at the Institute for International Marketing Management
at the Wirtschaftsuniversität Wien in Austria. Her research includes consumer behaviour, both
in online and offline contexts, the interplay between consumers and organisations (power)
as well as methodological issues in international marketing and management. She has published
in refereed international journals: Psychology & Marketing, Journal of Economic Psychology,
Management International Review and International Marketing Review.
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