International Journal of Information Management 33 (2013) 199–208
Contents lists available at SciVerse ScienceDirect
International Journal of Information Management
journal homepage: www.elsevier.com/locate/ijinfomgt
What drives purchase intention in the context of online content services? The
moderating role of ethical self-efficacy for online piracy
Yi-Shun Wang a,∗ , Ching-Hsuan Yeh a , Yi-Wen Liao b
a
b
Department of Information Management, National Changhua University of Education, No. 2, Shi-Da Road, Changhua City 500, Taiwan
Department of Information Management, Chia Nan University of Pharmacy and Science, No. 60, Sec. 1, Erren Road, Rende District, Tainan City 71710, Taiwan
a r t i c l e
i n f o
Article history:
Available online 2 November 2012
Keywords:
Online content services
Perceived value
Value-based adoption model
Purchase intention
Ethical self-efficacy for online piracy
a b s t r a c t
With the proliferation of online content service industry, understanding the factors affecting consumer
intention to purchase online content services has become an important issue for academics and practitioners. While previous research has suggested that consumers’ perceived value and moral judgment
are two main factors influencing behavioral intention to purchase online content services, few studies have explored what drives perceived value and if customers’ ethical self-efficacy will moderate the
effect of perceived value on purchase intention. Thus, based on the value-based adoption model and
previous literature, this study explores the antecedents of perceived value and the moderating effect of
ethical self-efficacy for online piracy (ESEOP) on the relationship between perceived value and purchase
intention in the context of online content services. Data collected from 124 respondents in Taiwan are
tested against the research model using the partial least squares (PLS) approach. The results indicate
that perceived enjoyment, perceived usefulness, perceived fee, and ESEOP have a significant influence on
perceived value and that ESEOP can enhance the positive effect of perceived value on purchase intention.
The findings of this study provide several important theoretical and practical implications for consumer
online content purchase behaviors.
© 2012 Elsevier Ltd. All rights reserved.
1. Introduction
With the development of the Internet, online content service
industries have recently grown rapidly in the form of online game,
e-book, e-learning, e-music, Internet broadcasting, and video on
demand (VOD) (Joo & Sohn, 2008). However, when compared with
the rapid growth of the online content services markets, especially
online music services in the USA and Western Europe, no such success has emerged in Asia (Chu & Lu, 2007). Previous studies have
suggested that Asians are reluctant to pay for the download of
online contents, particularly in Great China Region (i.e., Mainland
China, and Hong Kong) (Chen, Shang, & Lin, 2008; Chu & Lu, 2007;
Joo & Sohn, 2008; Lu & Hsiao, 2010). Thus, in order for the online
content industry to succeed, it is essential to understand why consumers are willing to pay for online/digital content services or not.
That is, investigating the factors affecting consumer intention to
purchase online content services has been an important issue for
academics and practitioners.
Several previous studies have explored the factors affecting
online consumers’ behavior (e.g., Doong, Wang, & Foxall, 2011;
∗ Corresponding author. Tel.: +886 4 7232105x7331.
E-mail addresses: [email protected] (Y.-S. Wang), [email protected]
(C.-H. Yeh), [email protected] (Y.-W. Liao).
0268-4012/$ – see front matter © 2012 Elsevier Ltd. All rights reserved.
http://dx.doi.org/10.1016/j.ijinfomgt.2012.09.004
Hong & Cho, 2011; Kuo & Wu, 2012; Liu, Guo, & Lee, 2011; Song,
Baker, Lee, & Wetherbe, 2012; Udo, Bagchi, & Kirs, 2010). Some
studies have also suggested that customer-perceived value is a critical factor affecting behavioral intention to purchase or repurchase
online services in the context of electronic/mobile commerce (Chen
et al., 2008; Chu & Lu, 2007; Kim, Chan, & Gupta, 2007; Lin & Wang,
2006; Lu & Hsiao, 2010; Wang, 2008). Perceived value is frequently
conceptualized as involving a consumer’s assessment of the ratio
of perceived benefits to perceived costs (Monroe, 1990; Zeithaml,
1988). However, few studies have investigated the antecedents of
perceived value from the perspective of perceived benefits and
perceived costs in the context of online content services (e.g., Chen
et al., 2008; Chu & Lu, 2007; Lu & Hsiao, 2010). Thus, there is a need
for research to explore what factors drive consumers’ perceived
value of online content services in the cost–benefit framework.
In addition to perceived value, previous studies have also suggested that moral judgment or ethical self-efficacy is another
influential factor of digital material piracy (Chen et al., 2008; Gopal,
Sanders, Bhattacharjee, Agrawal, & Wager, 2004; Kuo & Hsu, 2001;
Moores & Chang, 2006). Many researchers have found that more
strongly held beliefs that piracy is wrong, unethical, or immoral
lead to a lower likelihood of intended piracy behavior (Miyazaki,
Rodriguez, & Langenderfer, 2009). While perceived value is a critical influential factor of consumer intention to purchase online
contents, considering that illegal online music and video file
200
Y.-S. Wang et al. / International Journal of Information Management 33 (2013) 199–208
download are still rampant in most of the Asian region, a question
remains; that is, are consumers willing to purchase high perceived
value online contents. Furthermore, although some researchers
found a direct relationship between moral judgment and ethical
behavior (Cronan & Al-Rafee, 2008; Pan & Sparks, 2012; Yoon,
2011a), Chen et al. (2008) found that the degree of morality has not
a significant influence on behavioral intention to download unauthorized music files, but that perceived value of downloading free
music files influences behavioral intention to download unauthorized music files more strongly for the low morality group than for
the high morality group. These results imply that consumers’ moral
beliefs or self-efficacy toward online piracy may play a moderating
role in the effect of perceived value on online content purchase
intentions. Thus, the relationship between perceived value, purchase intention, and piracy ethics still needs to be further addressed
in the context of online content services.
Therefore, the main purpose of this study is to (1) investigate the antecedents of perceived value from the cost–benefit
framework, and (2) explore the moderating effect of consumers’
ethical self-efficacy for online piracy on the relationship between
perceived value and purchase intention in the context of online
content services. This paper is structured as follows. First, this study
reviews the conceptualization and antecedents of perceived value
and discusses the concept of online piracy ethics. Second, based on
previous literature, a research model and a comprehensive set of
hypotheses are proposed. Next, the methods, measures, and results
of this study are then presented. Finally, the results are discussed
in terms of their implications for research and managerial activity.
2. Theoretical background
2.1. Conceptualization and antecedents of perceived value
As noted earlier, several previous studies have suggested that
perceived value is a crucial factor that influences user intention
to use/purchase online service in the context of electronic/mobile
commerce (e.g., Chen et al., 2008; Chu & Lu, 2007; Kim et al., 2007;
Lin & Wang, 2006; Lu & Hsiao, 2010; Wang, 2008). Perceived value
is frequently conceptualized as involving a consumer’s assessment of the ratio of perceived quality and perceived sacrifice
(Monroe, 1990; Zeithaml, 1988). Bolton and Drew (1991) suggested that perceived value is a richer measure of customers’ overall
evaluation of a service than perceived service quality. According to Zeithaml (1988), perceived sacrifice are influenced by both
perceived monetary price and perceived nonmonetary price. Similarly, Parasuraman and Grewal (2000) contend that perceived
value is a function of a ‘get’ component – i.e., the benefits a buyer
derives from a seller’s offering – and a ‘give’ component – i.e., the
buyer’s monetary and nonmonetary costs of acquiring the offering
(Zeithaml, 1988).
Traditionally, technology acceptance model (TAM) is one of the
most influential models in the research area of user acceptance of
information systems (IS) (Davis, 1989; Davis, Bagozzi, & Warshaw,
1989), which posits that user acceptance can be explained by
two beliefs: perceived usefulness and perceived ease of use. IS
researchers have investigated and replicated the TAM, and agreed
that it is valid in predicting an individual’s acceptance of various
corporate IT (Adams, Nelson, & Todd, 1992; Chin & Todd, 1995;
Segars & Grover, 1993). However, as Wang (2008) noted, in the
context of electronic/mobile commerce, many users may abandon or be reluctant to use a for-fee information service even if
it is useful for them. This phenomenon may decrease the power
of TAM in explaining and predicting user acceptance of for-fee
information and content services, which have become very popular in the context of electronic/mobile commerce, because TAM’s
perceived usefulness only taps the perceived benefit component,
but it omits the perceived monetary cost component in user acceptance of information services (Wang, 2008). Consequently, Wang
(2008) proposed a revised TAM (i.e., a value-based TAM), which
replaces perceived usefulness with perceived value, and suggested
that perceived value is more dominant than perceived usefulness
in explaining the behavioral intention to use for-fee information
and content services. This also implies that for-fee online content
services appear to be accepted less because of their perceived usefulness than because of their perceived value.
Similarly, as Kim et al. (2007) contend, in an organizational context, the cost of mandatory adoption and usage is borne by the
organization; in contrast, in an online service context, the cost of
voluntary adoption and usage is borne by the individuals. Thus, the
adopters of online services play the dual roles of IT user and service
consumer, and they would concern about the cost and benefit of
using the online services when deciding whether or not to adopt the
services. Using the theory of consumer choice and decision making from the field of economics and marketing research, Kim et al.
(2007) proposed a value-based adoption model (VAM) to explain
customers’ mobile Internet service adoption from the value maximization perspective. Their empirical findings also indicate that
perceived value of mobile Internet service is a principal determinant of adoption intention, and that two cost beliefs (i.e., perceived
fee and technicality) and two benefit beliefs (i.e., usefulness and
enjoyment) affect adoption intention through the mediation of
perceived value. Meanwhile, Chu and Lu (2007) also empirically
investigated the factors influencing online music purchase intention based on the value–intention framework. Similarly, they found
that perceived value of online music has a positive influence on purchaser intention to buy online music and that two beneficial factors
(i.e., perceived usefulness and perceived playfulness) and one sacrificing factor (i.e., perceived price) are determinants of perceived
value. Thus, VAM’s benefit-sacrifice framework proposed by previous researchers (Chu & Lu, 2007; Kim et al., 2007; Wang, 2008) can
be used to explain and predict consumer behaviors of purchasing
online content services.
While several typologies of value are proposed (e.g., Holbrook,
1999; Sheth, Newman, & Gross, 1991), they are comprehensive in
explaining the benefits customers get from consumption but they
fail to take into account the costs associated with consumption (Kim
et al., 2007). Thus, this study adopts Zeithaml’s (1988) definition
of perceived value which is the most widely accepted by previous consumer behavior research. According to Zeithaml (1988),
perceived value of online content services in this study is defined as
a consumer’s overall perception of online content service based on
the considerations of its benefits and sacrifices needed to acquire
and/or use it. Thus, perceived value in the VAM is equivalent to
the framework of cost–benefit analysis. Further, the VAM could not
only capture the utilitarian and hedonic benefit components (i.e.,
perceived usefulness and perceived enjoyment), but it also could
take into account the monetary and nonmonetary sacrifice components (i.e., perceived fee and perceived technicality). Thus, this
study uses the VAM to develop a comprehensive model for explaining and predicting consumer intention to purchase online content
services by integrating the concepts of perceived value and online
piracy ethics. The following section elaborates the conceptualization of online piracy ethics and its potential role in moderating the
effect of perceived value on online content purchase intention.
2.2. Online piracy ethics
To achieve a profitable online content service, both perceived
value and consumers’ piracy behavior should be seriously contemplated since the former contributes to consumers’ purchase
intention and the latter results in firms’ earnings downturn. Based
Y.-S. Wang et al. / International Journal of Information Management 33 (2013) 199–208
on the work of Prasad and Mahajan (2003), piracy refers to the
duplication, purchase, and distribution of unauthorized products
including functional software and digital entertainment contents.
A multitude of studies have claimed that piracy is a pervasive phenomenon in Internet society on account of the ease of access, low
reproduction cost, and the dearth of vigilance and empathy resulting from the human-to-machine interface (Peitz & Waelbroeck,
2006; Shanahan & Hyman, 2010). Compared with other online misconducts such as defamation or virus dissemination, piracy is a
typical form which strongly relates to consumption (Huang, 2005;
Kuo & Hsu, 2001).
The negative effect of piracy on consumption is intuitively recognized, and has been empirically verified and observed in practice
(Sandulli, 2007). The rampant of piracy will lead to a tremendous
decrease in product sales, and erode the rewards of producers
and their corresponding affiliations (Hennig-Thurau, Henning, &
Sattler, 2007). Although piracy is likely to contribute to faster product diffusion, greater brand/artist familiarity, more opportunity for
product trial, and the habitualization of consumer’s usage, which
may in turn foster the product sales, this ‘potential’ benefit is uncertain and lacks of empirical evidence (Coyle, Gould, Gupta, & Gupta,
2009). For example, in the music industry, the digitalization of
music really impacts consumers’ music consumption behavior and
invokes the prevalence of music piracy (Peitz & Waelbroeck, 2006;
Warr & Goode, 2011). It is believed that piracy is detrimental to the
development of online content industry from a long term perspective. Thus, there is a need for research to better understand the role
that piracy ethics plays in consumers’ purchasing of online content.
Researchers have paid much effort to identify the factors
influencing consumers’ digital material piracy and to draw effective deterrent strategies (Chen et al., 2008; Gopal et al., 2004;
Huang, 2005; Levin, Dato-On, & Rhee, 2004; Moores & Chang,
2006; Plowman & Goode, 2009). Of these influential factors,
ethics/morality has been widely explored and suggested to be negatively related to behavioral intention to pirate (e.g., Chen et al.,
2008; Coyle et al., 2009). Marshall (1999) defines ethics as guidelines to influence human social behaviors in a manner intended to
protect and fulfill the rights of individuals in a society. Previous
research has suggested that stronger ethical concerns regarding
piracy are associated with less pirating behaviors (Coyle et al., 2009;
Cronan & Al-Rafee, 2008; Levin et al., 2004; Pan & Sparks, 2012;
Yoon, 2011b). Unlike mandatory legal system, ethics is the unwritten consensus which is shared by the same group, and steers its
members’ acts to conform to the expectation of the group (Green,
1994).
Previous research has explored the ethical decision making
models, which parsimoniously illustrate consumers’ cognitive
activities to deal with ethical dilemma (e.g., Goolsby & Hunt, 1992;
Hunt & Vitell, 1986; Rest, 1986; Tan, 2002; Yoon, 2011a). While
encountering a situation/issue which is likely to raise an ethical
concern, individuals will attempt to identify whether it is ethicsinvolved; once an individual recognizes an event/action to be
ethically involved, his/her behavioral intention will be guided and
not violate the common moral requirements (Pan & Sparks, 2012).
In this vein, ethical judgment or moral obligation has frequently
been proposed as a critical predictor of individual ethical intention
or behavior (Cronan & Al-Rafee, 2008; Jung, 2009; Moores & Chang,
2006; Pan & Sparks, 2012; Thong & Yap, 1998; Yoon, 2011a, 2011b).
However, a review of prior studies shows controversial conclusions about the effect of ethical judgment concerning online
piracy on online content purchase behavior. For example, Coyle
et al. (2009) found that consumers who consider music piracy to
be unethical and illegal will be less likely to engage in music piracy.
However, Chen et al. (2008) found that the degree of morality has
an insignificant effect on unauthorized music download intention,
but that perceived value of downloading free music files influences
201
behavioral intention to download illegal music files more strongly
for the low morality group than for the high morality group, implying that moral judgment or belief may play a moderating effect on
the relationship between perceived value of using online content
and behavioral intention to purchase online content. Considering
that ethical judgment or concern has been suggested as a critical
factor affecting behavioral intention to pirate digital material (software, music, etc.) (Cronan & Al-Rafee, 2008; Jung, 2009; Levin et al.,
2004) and that mix results regarding the effect of ethical judgment
on ethical behavior have been found in previous research on digital
content usage behavior, this study continues to investigate the role
that individual ethical judgment concerning online piracy plays in
the VAM.
2.3. Ethical self-efficacy for online piracy
Individual difference variables, such as locus of control (internal
vs. external) and the Big Five personality traits have been examined to see if individuals with different traits will present distinct
reactions to ethical issues (Karim, Zamzuri, & Nor, 2009; Pan &
Sparks, 2012). Self-efficacy is also an important individual difference variable which has received increasing attention in the recent
research of software piracy ethics (Kuo & Hsu, 2001). Bandura
(1986) defined self-efficacy beliefs as “people’s judgments of their
capabilities to organize and execute courses of action required to
attain designated types of performances” (p. 391). According to the
social cognitive theory (SCT), individuals with high self-efficacy –
that is, those who believe they can perform well – are more likely
to view difficult tasks as something to be mastered rather than
something to be avoided. Self-efficacy has also been widely used
to predict behavioral intentions in the Internet context (e.g., Hong,
Thong, Wong, & Tam, 2001; Luarn & Lin, 2005; Wang, Lin, & Luarn,
2006). However, SCT and self-efficacy have rarely been applied to
investigate information ethics decisions (Kuo & Hsu, 2001). Thus,
based on the SCT, Kuo and Hsu (2001) developed a 3-dimension,
12-item measure of ethical computer self-efficacy (ECSE) construct
concerning software piracy and suggested that this construct can
be used to investigate people’s ethical conduct related to computer use. Consistent with the computer self-efficacy measures
(Compeau & Higgins, 1995), the ECSE measures considered three
relevant dimensions of self-efficacy judgments: magnitude (i.e.,
task difficulty), strength, and generalizability. Self-efficacy can be
seen as perceived behavioral control (PBC) in the theory of planned
behavior (TPB) (Kok, deVries, Muddle, & Strecher, 1991; Kuo & Hsu,
2001), which can serve as a determinant of behavioral intention
and can be affected by demographics, personality traits, beliefs
concerning objects, attitude toward objects, task characteristics,
and situational variables (Ajzen, 1989). Kuo and Hsu (2001) also
argued that “the stronger the perceived self-regulatory efficacy, the
more perseverant people are in their self-controlling efforts and
the greater is their success in resisting social pressures to behave
in ways that violate their standards” (p. 301). Therefore, based on
the aforementioned literature and the ECSE construct presented by
Kuo and Hsu (2001), this study attempts to investigate the main and
interaction effects of ethical self-efficacy and perceived value on
online content purchase intentions by adding the construct of ethical self-efficacy for online piracy (ESEOP), defined as an individual’s
propensity of ethical usage of online content, into the VAM.
3. Research model and hypotheses
This study attempts to better understand why consumers are
willing to purchase online content. To this end, this study uses the
VAM mentioned earlier to investigate consumers’ online content
consumption behavior in the e-commerce context. However, the
202
Y.-S. Wang et al. / International Journal of Information Management 33 (2013) 199–208
Benefit
Perceived
Usefulness
Ethical Self-efficacy for
Online Piracy
Perceived
Enjoyment
Sacrifice
Perceived
Value
Purchase
Intention
Technicality
Perceived Fee
Fig. 1. Research model.
value–intention relationship in the VAM may not always sustain
and may have exceptions. It is still frequently observed in practice
that some consumers pirate music even though the value of online
music services is recognized. Therefore, this study incorporates the
construct of ESEOP into the VAM to concurrently examine the main
effect and interaction effect of perceived value and ESEOP on behavioral intention to purchase online content services. The research
model used to guide this study is shown in Fig. 1, which suggests
that perceived usefulness, perceived enjoyment, technicality, and
perceived fee all have a relationship with perceived value, and
that ESEOP has a moderating effect on the relationship between
perceived value and purchase intention. Based on previous literature, this section conceptualizes the constructs and derives the
hypotheses for the research model.
3.1. Perceived benefits
In the contemporary consumer-oriented business environment,
delivering benefits to consumers is a necessity to trigger their
buying. Researchers in the marketing field have devoted much
effort to develop a better understanding of the concept of consumer benefits. Previous research has suggested that the shopping
experience provides consumers with a combination of utilitarian
and hedonic benefits (e.g., Babin & Darden, 1995; Babin, Darden,
& Griffin, 1994; Carpenter & Moore, 2009; Chandon, Wansink, &
Laurent, 2000; Holbrook, 1994; Jones, Reynolds, & Arnold, 2006;
Klein & Ford, 2003). Thus, it is generally agreed to classify customers’ perceived benefits into two fundamental types: utilitarian
and hedonic (Childers, Carr, Peck, & Carson, 2001; Diep & Sweeney,
2008; To, Liao, & Lin, 2007). Utilitarian benefit is task-related, cognitive, and extrinsic. Consumers can derive utilitarian benefits from
the performance of the product/service which achieves the task
requirement. On the contrary, hedonic benefit such as appreciation
and entertainment is emotionally and intrinsically evaluated, and is
derived from the process of the product/service usage. These two
kinds of benefits are applicable not only at the brick-and-mortar
shopping context but also at the Internet shopping context (Kim,
2002; Rintamäki, Kanto, Kuusela, & Spence, 2006).
In line with the utilitarian–hedonic benefit framework, Kim
et al. (2007) suggested that perceived usefulness is an extrinsic
and cognitive factor while perceived enjoyment is an intrinsic and affective factor. Similarly, Chu and Lu (2007) also used
perceived usefulness and perceived playfulness to represent functional benefit and recreational benefit in the value–intention
framework. In this study, perceived usefulness is akin to the marketing concept of product/service quality (Kim et al., 2007), which
is the consumer’s evaluation of the online content service performance and can be defined as the extent to which a consumer
believes that using an online content service would fulfill his/her
certain purpose (Chu & Lu, 2007; Davis, 1989). Perceived enjoyment
is the perceived fun or pleasure sourcing from the online content
service experience, which is defined as the extent to which the
activity of using an online content service is perceived to be enjoyable in its own right, apart from any performance consequences
that may be anticipated (Davis, Bagozzi, & Warshaw, 1992).
An online content service which highly accomplishes consumers’ task and arouses consumers’ feeling of delight will earn a
better consumer value appraisal. Taking online music service as an
example, consumers can search and purchase a pop song or a classical music, aged or latest through an online music service at any time
from any place rather than visiting physical music stores. Additionally, the customization strategies of online music service providers
offer customers with the flexibility to buy a single music, a personalized album, or to subscribe the services. In this vein, online music
services are helpful for consumers to achieve their purposes, and
thus perceive usefulness is derived. Meanwhile, consumers may
also perceive fun and excitement while searching, purchasing and
using the desired online music services, and thus perceived enjoyment is derived. Previous studies have suggested that perceived
usefulness and perceived enjoyment are instrumental in explaining user adoption of hedonic information systems (e.g., van der
Heijden, 2004). Further, both of them have also been found to positively influence perceived value in the context of mobile Internet
(Kim et al., 2007). Thus, the following hypotheses are proposed:
H1. Perceived usefulness is positively related to perceived value in
the context of online content service.
H2. Perceived enjoyment is positively related to perceived value in
the context of online content service.
3.2. Perceived sacrifice
In addition to perceived benefit, consumer’s perceived sacrifice is another antecedent of perceived value. In general, prior
Y.-S. Wang et al. / International Journal of Information Management 33 (2013) 199–208
studies classified consumer’s perceived sacrifice into two types:
nonmonetary and monetary sacrifice (Zeithaml, 1988). Zeithaml
(1988) defined nonmonetary sacrifice as temporal, physical, and
psychological cost. Consumers who spend more time and effort on
a product/service tend to have a higher perceived nonmonetary
sacrifice and then diminish their value perception toward the product/service. Kim et al. (2007) used technicality, defined as users’
perceptions of ease of use, to represent the nonmonetary sacrifice.
Similarly, Chu and Lu (2007) employed perceived ease of use to represent the nonmonetary sacrifice. However, technicality/perceived
ease of use defined by Kim et al. (2007) and Chu and Lu (2007) is conceptually opposite to the concept of nonmonetary “sacrifice”. Thus,
to be consistent with the benefit–sacrifice framework and serve as
a sacrifice-related construct in the VAM, technicality in this study
is redefined as the extent to which a customer believes that using
an online content service would suffer from physical, mental and
learning effort (Davis, 1989; Kim et al., 2007), which is conceptually
similar to perceived non ease of use. As such, greater technicality of an online content service will increase consumers’ temporal,
physical, and psychological loss, and thus negatively contribute
to perceived value. Previous research also found that technicality/perceived ease of use has a significant influence on perceived
value (Kim et al., 2007).
On the other hand, monetary sacrifice refers to a consumer’s
financial payment for the online content service. Since customers
do not always remember actual product/service prices, previous
research usually used the customers’ perception of price or fee to
measure customers’ monetary sacrifice (Jacobby & Olson, 1977;
Monroe, 1973). Kim et al. (2007) used perceived fee to represent
monetary sacrifice in the mobile Internet context while Chu and
Lu (2007) employed a similar perceived fee construct to represent
monetary sacrifice in the online music setting. According to Kim
et al. (2007), perceived fee in this study is defined as the extent to
which a customer believes that using an online content service is
expensive. It has been suggested that perceived fee/perceived price
has a direct influence on perceived value (Chang & Wildt, 1994;
Dodds & Monroe, 1985; Kim et al., 2007; Zeithaml, 1988). Previous
studies also found that perceived fee/perceived price is negatively
related to perceived value (Chang & Wildt, 1994; Chu & Lu, 2007;
Kim et al., 2007). Based on the aforementioned reasoning, this study
tests the following hypotheses:
H3. Technicality is negatively related to perceived value in the context
of online content service.
H4. Perceived fee is negatively related to perceived value in the context of online content service.
203
H5. Perceived value is positively related to purchase intention in the
context of online content service.
3.4. ESEOP
As stated earlier, ESEOP refers to an individual’s propensity of
ethical usage of online content. Previous research has suggested
that stronger ethical concerns regarding piracy are related to less
pirating behaviors (Coyle et al., 2009; Cronan & Al-Rafee, 2008;
Levin et al., 2004; Pan & Sparks, 2012; Yoon, 2011b), implying that
ESEOP may have a positive influence on purchase intention in the
context of online content services. Once a consumer with high ethical self-efficacy is in the face of an ethics-related consumption
situation, he or she will have the intention to show disciplined conducts to fulfill moral norms, regardless of the moral intensity of that
situation is high or low. Prior studies have also found a significant
relationship between moral judgment and ethical behavior (e.g.,
Coyle et al., 2009; Cronan & Al-Rafee, 2008; Jung, 2009; Moores &
Chang, 2006; Pan & Sparks, 2012; Yoon, 2011a, 2011b). Thus, it is
inferred that customers who have high ESEOP are more likely to
purchase online content services than those who have low ESEOP.
This study proposes the following hypotheses:
H6. ESEOP is positively related to purchase intention in the context
of online content service.
While prior studies have found the positive relationship
between perceived value and purchase intention, this relationship may not always be sustainable for all consumers. As noted
earlier, Chen et al. (2008) found that perceived value of downloading free music files influences behavioral intention to download
illegal music files more strongly for the low morality group than
for the high morality group, implying that an individual’s ethical self-efficacy concerning online piracy may play a moderating
effect on the relationship between perceived value and purchase
intention in the context of online content services. It is thus
inferred that customers who have high ESEOP are more likely
have strong perceptions regarding the effect of perceived value on
purchase intention than those who have low ESEOP. Specifically,
perceived value influences purchase intention more strongly for
customers with high ESEOP than for those with low ESEOP. Based
on the aforementioned reasoning, this study proposes the following
hypothesis:
H7. When ESEOP is higher, the positive relationship between
perceived value and purchase intention is stronger in the context of
online content service.
4. Methods
3.3. Perceived value
4.1. Measures
Based on the exchange theory in marketing studies, it is believed
that consumer’s perceived value is the prerequisite of purchase
intention. As noted earlier, perceived value refers herein to a
customer’s overall assessment of the benefits and sacrifices of
acquiring and/or using an online content service. Consumers are
assumed as economically rational and will pursuit their maximum
utility. After a comprehensive trade-off evaluation of the benefits
and costs, a consumer may conclude whether a product/service
is valuable and take it as the basis for his/her following behavioral decision (Zeithaml, 1988). It has been proposed that perceived
value has a positive effect on consumer intention to buy (Dodds,
Monroe, & Grewal, 1991; Lu & Hsiao, 2010; Sweeney, Soutar, &
Johnson, 1997; Zeithaml, 1988). Several previous studies have also
provided empirical evidence for the positive influence of perceived
value on purchase intention (Chu & Lu, 2007; Kim et al., 2007; Lu &
Hsiao, 2010). Thus, the hypothesis is presented.
Selected measurement items must represent the concept about
which generalizations are to be made to ensure the content
validity of the measurement (Bohmstedt, 1970). Therefore, to
ensure content validity, measurement items in this study were
mainly adapted from prior studies. Besides, to simplify the
validation of our research model, the measures of this study
focuses on the online music services. The measures for perceived
value were adapted from Kim et al. (2007) and Sirdeshmukh,
Singh, and Sabol (2002). The scale for perceived usefulness
was modified from Kim et al. (2007) and Chu and Lu (2007),
while the scale for perceived enjoyment was adapted from Kim
et al. (2007) and Agarwal and Karahanna (2000). The items for
measuring technicality were modified from Kim et al. (2007) and
Davis (1989). Also, the items used to measure perceived fee were
adapted from Kim et al. (2007) and Voss, Parasuraman, and Grewal
204
Y.-S. Wang et al. / International Journal of Information Management 33 (2013) 199–208
(1998). Twelve items for measuring ESEOP were adapted from
the scale of ethical self-efficacy for software piracy developed by
Kuo and Hsu (2001). Finally, the scale for purchase intention was
adapted from Kim et al. (2007) and Davis et al. (1989). Likert scales
(ranging from 1 to 7), with anchors ranging from “strongly disagree” to “strongly agree” were used for all construct items, with
the exception of those items for measuring ESEOP whose anchors
ranged from “not at all confident” to “totally confident.” The survey
items were pre-tested by a small number of e-commerce experts
and were modified to fit the context of online music services
studied. The survey items are listed in Appendix A. In addition, a
declaration of anonymity and aggregation analysis is emphasized in
the introduction of the questionnaire to increase the response rate
and to mitigate the bias effect of social desirability while respondents answer their ethical judgment (Coyle et al., 2009; Gupta,
Gould, & Pola, 2004; Shanahan & Hyman, 2010).
4.2. Data collection
Data used to test the research model was gathered from an
online convenience sample in Taiwan. The online survey questionnaire of this study was established on a survey portal in Taiwan,
where the interested online users can connect the portal. Willing
respondents were asked to participate in the survey. Respondents
then self-administered the questionnaire and were asked to circle
the response that best described their level of agreement with the
statements. A sample of 124 valid responses was obtained from
a variety of respondents with different demographic background.
In terms of the respondents, 41.13% were male and 58.87% were
female. Approximately, 33.26% of the respondents were aged 20–29
and 89.52% of the respondents had over six years of computer experience. Also, 96.7% of the respondents had attained a degree at the
collegiate level or above. Almost all of the respondents (94.94%) had
online music use experiences.
4.3. Data analysis
The empirical data was analyzed using the partial least squares
(PLS) approach, which was employed because it does not require
the data to have a multivariate normal distribution and is less
demanding in terms of sample size. SmartPLS software was used
for the data analysis of this study, which contained two steps. In
the first step, all measurement models were examined for their
psychometric properties, while the second step focused on testing
the research model and hypotheses. The PLS provides a convenient
approach for the simultaneous analysis of measurement model,
structural model, and interaction effects.
5. Results
5.1. Measurement model
Assessment of the measurement model involved evaluations
of reliability, convergent validity, and discriminant validity of
the construct measures. Reliability was examined using composite reliability. As shown in Table 1, reliability exceeded 0.8 for
each construct. Convergent validity of the construct measures was
examined using factor loading and average variance extracted
(AVE).
As shown in Table 1, each item’s factor loading is larger than 0.5
and has a significant t-value, confirming the convergent validity
of the construct measures. Additionally, the AVE for each construct
exceeded the recommended level of 0.50 (see Table 1), which meant
that more than one-half of the variances observed in the items
were accounted for by their hypothesized constructs. To assure
discriminant validity, the square root of AVE for each construct
Table 1
Reliability, AVE and factor loading.
Construct/item
Composite
reliability
AVE
Purchase intention
PI1
PI2
PI3
Perceived value
PV1
PV2
PV3
PV4
Perceived usefulness
PU1
PU2
PU3
PU4
PU5
PU6
Perceived enjoyment
PE1
PE2
PE3
PE4
Perceived fee
PF1
PF2
PF3
Technicality
TE1
TE2
TE3
TE4
ESEOP
ES1
ES2
ES3
ES4
ES5
ES6
ES7
ES8
ES9
ES10
ES11
ES12
0.98
0.94
0.89
Factor
loading
t-Value
0.96
0.97
0.97
137.15
225.32
163.21
0.65
0.87
0.90
0.63
14.26
66.80
84.83
36.79
0.85
0.92
0.82
0.86
0.88
0.85
46.46
104.89
21.27
34.41
62.03
42.38
0.94
0.96
0.95
0.87
122.19
213.21
188.42
25.93
0.85
0.98
0.95
28.11
339.50
89.97
0.93
0.93
0.92
0.73
103.70
96.89
107.85
14.87
0.87
0.88
0.88
0.82
0.85
0.86
0.69
0.75
0.70
0.76
0.49
0.70
67.25
71.16
59.95
26.15
38.03
53.28
16.27
25.05
16.74
16.34
10.05
16.52
0.67
0.95
0.75
0.96
0.87
0.95
0.86
0.78
0.93
0.95
0.61
should be greater than the correlations between that construct
and all other constructs (Fornell & Larcker, 1981). This study compared the correlations between constructs with the square root
of AVE of the individual constructs. This analysis indicated that
the correlations between constructs were lower than the square
root of AVE of the individual constructs, confirming discriminant
validity (see Table 2). Thus, the measurement model demonstrated adequate reliability, convergent validity, and discriminant
validity.
Table 2
Square root of AVE and correlation.
Construct
PE
ES
PF
PU
PV
PI
TE
PE
ES
PF
PU
PV
PI
TE
0.93
−0.17
−0.21
0.81
0.72
0.16
0.50
0.78
0.20
−0.19
−0.10
0.32
−0.19
0.93
−0.25
−0.34
0.02
−0.10
0.87
0.69
0.06
0.57
0.82
0.27
0.38
0.97
0.10
0.88
PU, perceived usefulness; PE, perceived enjoyment; TE, technicality; PF, perceived
fee; PV, perceived value; ES, ethical self-efficacy for online piracy; PI, purchase intention.
Diagonal elements are the square roots of AVE; off-diagonal elements are the correlations.
Y.-S. Wang et al. / International Journal of Information Management 33 (2013) 199–208
205
Table 3
Statistical results of the structural model.
Dependent variable
Independent variable
Path coefficient
t-Value
R-square
Perceived value
Perceived usefulness
Perceived enjoyment
Technicality
Perceived fee
Perceived value
ESEOP
Perceived value × ESEOP
0.295
0.461
−0.036
−0.169
0.327
0.342
0.270
4.776*
6.265*
0.985
5.716*
7.863*
9.172*
10.431*
57.7%
Purchase intention
*
27.2%
p < 0.05.
5.2. Structural model
6. Discussion
This study proceeded to test the path significances using a
bootstrapping resampling technique. Statistical results of the structural model, including path coefficients, t-values, and R-square
are shown in Table 3. As expected, both perceived usefulness and
perceived enjoyment had a significant positive effect on perceived
value (ˇ = 0.295 and ˇ = 0.461, respectively). Thus, H1 and H2 were
supported. Perceived fee was found to have a significant negative influence on perceived value (ˇ = −0.169); therefore, H4 was
supported. However, technicality was unexpectedly found to have
an insignificant effect on perceived value (ˇ = −0.036). Thus, H3
was not supported. Additionally, both perceived value and ESEOP
were observed to positively affect purchase intention (ˇ = 0.327 and
ˇ = 0.342, respectively), supporting H5 and H6.
As to the moderating effect, ESEOP was found to have a moderating effect on the relationship between perceived value and
purchase intention, with higher ESEOP leading to higher positive
relationship of perceived value to purchase intention (ˇ = 0.270).
Therefore, H7 was supported. Fig. 2 shows how ESEOP moderates
the relationship between perceived value and purchase intention.
Altogether, the proposed model accounted for 57.7 percent of the
variance in perceived value and 27.2 percent of the variance in purchase intention, with perceived enjoyment having the strongest
effect on perceived value and ESEOP exerting the strongest total
effect on purchase intention among the explanatory variables.
Additionally, Cohen’s (1988) effect size f2 was used to examine
the substantive effect of adding ESEOP to the VAM model. The R2 for
the full model is 27.2% while that for the VAM model is 7.6%, leading
to an f2 value of 0.267. Cohen (1988) suggested 0.02, 0.15, and 0.35
as operational definitions of small, medium, and large effect sizes
respectively. Thus, ESEOP provided a substantial (i.e., larger than
medium) effect on purchase intention.
Considering the importance of consumers’ willingness to pay
for the success of online content industries, this study, based on the
VAM and previous literature, explores the antecedents of perceived
value and the moderating effect of ESEOP on the relationship
between perceived value and purchase intention. This study also
helps build a theoretical framework for the research of consumer
purchase behavior in the field of online content services. The results
indicate that perceived enjoyment, perceived usefulness, perceived
fee have a significant influence on perceived value, which, in turn,
significantly influences purchase intention. The results also show
that ESEOP moderates the positive effect of perceived value on purchase intention. The following paragraphs sequentially discuss the
theoretical and practical implication of our findings for consumer
online content purchase behaviors.
As expected, both perceived enjoyment and perceived usefulness were found to be significant determinants of perceived value.
This finding is consistent with previous studies which found that
utilitarian and hedonic benefits resulting from using online services
are critical in determining consumers’ perception of value (e.g., Chu
& Lu, 2007; Kim et al., 2007). However, different from previous
research regarding the TAM (e.g., van der Heijden, 2004) which
suggests that both perceived usefulness and perceived enjoyment
affect adoption intention directly, the results of this study indicate
that both perceived usefulness and perceived enjoyment influence
purchase intention indirectly through the mediation of perceived
value. Importantly, perceived enjoyment was observed to exert
a strongest effect on perceived value among the antecedents of
perceived value. The finding implies that acquiring and using online
music services is in nature a leisure-oriented activity and that
online content marketers should include more enjoyable and entertaining elements into their services to increase the value perceived
by consumers. Whereas, our findings emphasize that consumers’
value perceptions are motivated not only by hedonic benefits but
also by the utilitarian benefits of using online content services.
Thus, the development of new functionality and the enhancement of information quality, content quality, system quality, and
service quality still should not be neglected in promoting customers’ perceived value in the online content service settings.
Consistent with the finding of Chu and Lu (2007), technicality
(similar to perceived ease of use) was found to have an insignificant
impact on perceived value. This implies that consumers’ computer
self-efficacy has been largely increased in the Internet age, causing the insignificant effect of technicality. In line with the works of
Kim et al. (2007) and Chu and Lu (2007), our finding suggests that
perceived fee (similar to perceived price) has a significant negative on perceived value, which means that consumers who have
high perceived fee will have a lower level of value perception than
those who have low perceived fee. Thus, reasonable pricing strategies are crucial in enhancing customers’ value perceptions of using
online content services. Online content service providers could take
advantage of online consumer surveys to discover the acceptable
price range by online consumers before marketing a new online
Fig. 2. The moderating effect of ethical self-efficacy on the relationship between
perceived value and purchase intention.
206
Y.-S. Wang et al. / International Journal of Information Management 33 (2013) 199–208
content service. Additionally, adopting personalized pricing strategies for customized online content services and allowing online
contents to be downloaded into different electronic devices without repeated payment is also a feasible way to enhance customers’
value perceptions.
In line with the finding of previous research (e.g., Chu & Lu, 2007;
Wang, 2008), this study further confirms that perceived value has
a significant positive influence on purchase intention in the context of online content services. This implies that consumers who
have high perceived value of using online content services are more
likely to purchase the online content services than those who have
low perceived value. Thus, in order to attract more customers to buy
online content services and remain sustainable competitive advantage, online content service providers, based on our findings, should
enhance customers’ value perceptions by improving the utilitarian
and hedonic benefits of their online content services and adopting
a reasonable pricing strategy for their online offerings. When the
price is too high, customers may not only refrain from purchasing, but also become suspicious of the quality (Patterson & Spreng,
1997).
Importantly, our findings indicate that ESEOP not only has a significant positive influence on purchase intention, but it also has a
positive moderating effect on the relationship between perceived
value and purchase intention. Consumers who have high confidence in ethical usage of online contents tend to have a higher
behavioral intention to purchase online content services than those
who have low confidence in the same moral event. This result somewhat coincides with the studies of Coyle et al. (2009), Yoon (2011b),
Moores and Chang (2006), and Cronan and Al-Rafee (2008) who
found the effect of ethical factors on individual digital piracy. However, the main effect of ESEOP on purchase intention found by this
study is inconsistent with the work of Chen et al. (2008) who found
that the degree of morality has not a significant influence on behavioral intention to download unauthorized music files. Nevertheless,
the interaction effect of ESEOP and perceived value on purchase
intention is somewhat consistent with the exploratory finding by
Chen et al. (2008) who found that perceived value of downloading
free music files influences behavioral intention to download unauthorized music files more strongly for the low morality group than
for the high morality group. Similarly, our finding suggests that
perceived value of using online content services affects purchase
intention more strongly for the consumers with high ESEOP than
for those with low ESEOP. As Shanahan and Hyman (2010) note,
many misconducts result from unknowing something immoral or
illegal. Thus, a comprehensive moral education on digital content
piracy is required to facilitate the growth and development of
the online content service markets, especially in the Asian areas.
For example, teaching students that downloading an unauthorized music file online is an equity-infringing conduct like stealing
a CD in a physical shop would gradually change students’ ethical self-efficacy for online piracy, which, in the long run, will
reduce online piracy and guide consumers into right consumption
mode.
7. Limitations
While this study was conducted with methodological rigor,
there are some limitations to address in the future. First, the findings discussed and their implications were obtained from one single
study that examined a particular online content service (i.e., online
music service) and targeted a specific user group in Taiwan. If future
researcher wishes to make glittering generalities, they should first
randomize their sample to include other nationalities and geographical areas beside Taiwan. Therefore, continued research is
needed to generalize the findings of this study and extend the
discussion to include additional online content services (e.g., video
on demand) or cultural groups.
Second, this study does not incorporate all potential determinants and moderators into the value–intention framework, leading
to a relatively low explained variance in purchase intention. Hence,
there may be a need to search for additional determinants and moderators that can improve predictions regarding purchase intention
in the online content service environment. For example, personality traits are potential moderators of the relationship between
perceived value and purchase intention (Lu & Hsiao, 2010). Future
research could examine how personality traits or other potential
moderators interact with perceived value to affect purchase intention.
Finally, this study employs a snapshot research approach. Additional research efforts are needed to evaluate the validity of the
proposed model and our findings. Longitudinal evidence might
enhance the current understanding of the relationships among
perceived usefulness, perceived enjoyment, perceived fee, technicality, ESEOP, and purchase intention.
8. Conclusions
This study contributes to a more thorough understanding of
the antecedents of perceived value and the moderator of the relationship between perceived value and purchase intention. The
contributions of this study to research on consumer online content purchase behaviors are threefold. First, different from previous
research on the value–intention framework, the current study
not only explores the antecedents of perceived value, but it also
investigates the moderator of the relationship between perceived
value and purchase intention. As such, this study represents a new
direction for online consumer purchase behavior research. Second,
this study supports that perceived enjoyment, perceived usefulness, and perceived fee significantly influence purchase intention
through the mediation of perceived value, confirming the nomological structure of the VAM (Kim et al., 2007; Wang, 2008), which
is quite different from that of the TAM (Davis, 1989; Davis et al.,
1989; van der Heijden, 2004). Third, this study provides empirical
evidence to support that ethical self-efficacy for online piracy not
only has a positive effect on purchase intention, but also enhances
the positive influence of perceived value on purchase intention.
This is a new finding of this study since the main and interaction effects of perceived value and ethical self-efficacy on purchase
intention have rarely been explored in previous online purchase
behavior research. Future studies are still required to address
the determinants and moderators in the value-based adoption
model.
Acknowledgement
This research was substantially supported by the National
Science Council (NSC) of Taiwan under grant number NSC 98-2410H-018-019-MY2.
Appendix A. Measuring items used in this study
Perceived usefulness
PU1
Using online music services enables me to acquire the music
files that I need more quickly.
Using online music services enhances my music appreciation.
PU2
PU3
Using online music services makes it easier to get the music
information.
Y.-S. Wang et al. / International Journal of Information Management 33 (2013) 199–208
PU4
PU5
PU6
Using online music services improves my music appreciation.
Online music services provide a variety of music.
Overall, I find online music services are useful.
Perceived enjoyment
PE1
I have fun interacting with online music services.
PE2
Using online music services provides me with a lot of
enjoyment.
I enjoy using online music services.
PE3
Using online music services is interesting to me.
PE4
Technicality
TE1
TE2
TE3
TE4
Perceived fee
PF1
PF2
PF3
It is not easy to use online music services.
Online music services can be connected instantly (reversed).
Online music services take a long time to respond.
It is not easy to get online music services to do what I want it
to do.
The fee that I have to pay for the use of online music services is
too high.
The fee that I have to pay for the use of online music services is
not reasonable.
I am not pleased with the fee that I have to pay for the use of
online music services.
Perceived value
PV1
Compared to the fee I need to pay, the use of online music
services offers value for money.
Compared to the effort I need to put in, the use of online music
PV2
services is beneficial to me.
Compared to the time I need to spend, the use of online music
PV3
services is worthwhile to me.
Overall, the use of online music services delivers me good
PV4
value.
Ethical self-efficacy for online piracy
ES1
When you badly need a music file but feel it is too expensive,
how confident are you to refuse to have an illegal copy of that
music.
When you badly need a music file but do not have time to
ES2
purchase a copy, how confident are you to refuse to have an
illegal copy of that music.
When you badly need a music file and have the opportunity to
ES3
obtain an illegal copy without anybody else’s knowing, how
confident are you not to take advantage of it.
ES4
When you badly need a music file and have seen other
colleagues use an illegal copy, how confident are you not to
take advantage of it.
ES5
When you badly need an illegal copy of a music file to benefit
your life, how confident are you not to take advantage of it.
ES6
If a colleague has a music file that you like very much, how
confident are you not to ask for an illegal copy of it.
If a good friend badly needs a music file, how confident are you
ES7
not to make an illegal copy for him or her.
If a good friend badly needs a music file and is asking for your
ES8
help to obtain an illegal copy, how confident are you to refuse
to accept that request.
ES9
If a good friend badly needs a music file that you own and is
asking you for a copy, how confident are you to refuse to grant
the request.
If you see colleagues using an illegal copy of a music file, how
ES10
confident are you to try to dissuade them from using it.
If you see a colleague selling an illegal copy of a music file for
ES11
profit, how confident are you to try to talk him or her to give it
up.
ES12
If you see a colleague attempting to make an illegal copy of a
music file, how confident are you to try to talk him or her out
of it.
Purchase intention
I plan to pay for online music services in the future.
PI1
I intend to purchase online music services in the future.
PI2
PI3
I predict I would buy online music services in the future.
References
Adams, D. A., Nelson, R. R., & Todd, P. A. (1992). Perceived usefulness, ease of use, and
usage of information technology: A replication. MIS Quarterly, 16(2), 227–247.
Agarwal, R., & Karahanna, E. (2000). Time flies when you’re having fun: Cognitive absorption and beliefs about Information Technology Usage. MIS Quarterly,
24(4), 665–694.
207
Ajzen, I. (1989). Attitude structure and behavior. In A. R. Pratkanis, S. J. Breckler, &
A. G. Greenwald (Eds.), Attitude structure and function (pp. 241–274). Hillsdale,
NJ: Lawrence Erlbaum Associates.
Babin, B. J., & Darden, W. R. (1995). Consumer self-regulation in a retail environment.
Journal of Retailing, 71(1), 47–70.
Babin, B. J., Darden, W. R., & Griffin, M. (1994). Work and/or fun: Measuring hedonic
and utilitarian shopping value. Journal of Consumer Research, 20(4), 644–656.
Bandura, A. (1986). Social foundations of thought and action: A social cognitive theory.
Englewood Cliffs, NJ: Prentice Hall.
Bohmstedt, G. W. (1970). Reliability and validity assessment in attitude measurement. In G. F. Summers (Ed.), Attitude measurement (pp. 80–99). Chicago:
Rand-McNally.
Bolton, R. N., & Drew, J. H. (1991). A multistage model of customers’ assessment of
service quality and value. Journal of Consumer Research, 17, 375–384.
Carpenter, J. M., & Moore, M. (2009). Utilitarian and hedonic shopping value in the
US discount sector. Journal of Retailing and Consumer Services, 16(1), 68–74.
Chandon, P., Wansink, B., & Laurent, G. (2000). A benefit congruency framework of
sales promotion and effectiveness. Journal of Marketing, 64(4), 65–81.
Chang, T. Z., & Wildt, A. R. (1994). Price, product information, and purchase intention: An empirical study. Journal of the Academy of Marketing Science, 22(1),
16–27.
Chen, Y.-C, Shang, R.-A., & Lin, A.-K. (2008). The intention to download music files in
a P2P environment: Consumption value, fashion, and ethical decision perspectives. Electronic Commerce Research and Applications, 7(4), 411–422.
Childers, T. L., Carr, C. L., Peck, J., & Carson, S. (2001). Hedonic and utilitarian
motivations for online retail shopping behavior. Journal of Retailing, 77(4),
511–535.
Chin, W. C., & Todd, P. A. (1995). On the use, usefulness and ease of use of structural equation modeling in MIS research: A note of caution. MIS Quarterly, 19(2),
237–246.
Chu, C.-W., & Lu, H.-P. (2007). Factors influencing online music purchase intention
in Taiwan: An empirical study based on the value–intention framework. Internet
Research, 17(2), 139–155.
Cohen, J. (1988). Statistical power analysis for the behavioral science (2nd ed.).
Lawrence Erlbaum, NJ: Hillsdale.
Compeau, D. R., & Higgins, C. A. (1995). Computer self-efficacy: Development of a
measure and initial test. MIS Quarterly, 19(2), 189–211.
Coyle, J. R., Gould, S. J., Gupta, P., & Gupta, R. (2009). To buy or to pirate: The
matrix of music consumers’ acquisition-mode decision-making. Journal of Business Research, 62(10), 1031–1037.
Cronan, T. P., & Al-Rafee, S. (2008). Factors that influence the intention to pirate
software and media. Journal of Business Ethics, 78(4), 527–545.
Davis, F. D. (1989). Perceived usefulness, perceived ease of use, and user acceptance
of information technology. MIS Quarterly, 13(3), 318–339.
Davis, F. D., Bagozzi, R. P., & Warshaw, P. R. (1989). User acceptance of computer
technology: A comparison of two theoretical models. Management Science, 35(8),
982–1003.
Davis, F. D., Bagozzi, R. P., & Warshaw, P. R. (1992). Extrinsic and intrinsic motivation
to use computers in the workplace. Journal of Applied Social Psychology, 22(14),
1111–1132.
Diep, V. C. S., & Sweeney, J. C. (2008). Shopping trip value: Do stores and products
matter? Journal of Retailing and Consumer Services, 15(5), 399–409.
Dodds, W. B., & Monroe, K. B. (1985). The effect of brand and price information on subjective product evaluations. Advances in Consumer Research, 12(1),
85–90.
Dodds, W. B., Monroe, K. B., & Grewal, D. (1991). Effects of price, brand, and store
information on buyers’ product evaluations. Journal of Marketing Research, 28(3),
307–319.
Doong, H.-S., Wang, H.-C., & Foxall, G. R. (2011). An investigation of consumers’
webstore shopping: A view of click-and-mortar company. International Journal
of Information Management, 31(3), 210–216.
Fornell, C., & Larcker, D. F. (1981). Evaluating structural equation models with unobservable variables and measurement error. Journal of Marketing Research, 18(1),
39–50.
Goolsby, J. R., & Hunt, S. D. (1992). Cognitive moral development and marketing.
Journal of Marketing, 56(1), 55–68.
Gopal, R. D., Sanders, G. L., Bhattacharjee, S., Agrawal, M., & Wager, S. C. (2004). A
behavior model of digital music piracy. Journal of Organizational Computing and
Electronic Commerce, 14(2), 89–105.
Green, R. M. (1994). The ethical manager: A new method for business ethics. Upper
Saddle River, NJ: Prentice Hall.
Gupta, P. B., Gould, S. J., & Pola, B. (2004). To pirate or not to pirate: A comparative study of the ethical versus other influences on the consumer’s software
acquisition-mode decision. Journal of Business Ethics, 55(3), 255–274.
Hennig-Thurau, T., Henning, V., & Sattler, H. (2007). Consumer file sharing of motion
pictures. Journal of Marketing, 71(4), 1–18.
Holbrook, M. B. (1994). The nature of customer value: An axiology of service in
the consumption experience. In R. T. Rust, & R. L. Oliver (Eds.), Service quality: New directions in theory and practice (pp. 21–71). Thousand Oaks, CA: Sage
Publications.
Holbrook, M. B. (1999). Introduction to consumer value. In M. B. Holbrook (Ed.),
Consumer value: A framework for analysis and research (pp. 1–28). New York:
Routledge.
Hong, I. B., & Cho, H. (2011). The impact of consumer trust on attitudinal loyalty and
purchase intention in B2C e-marketplaces: Intermediary trust vs. seller trust.
International Journal of Information Management, 31(5), 469–479.
208
Y.-S. Wang et al. / International Journal of Information Management 33 (2013) 199–208
Hong, W., Thong, J. Y. L., Wong, W. M., & Tam, K. Y. (2001). Determinants of user
acceptance of digital libraries: An empirical examination of individual differences and system characteristics. Journal of Management Information Systems,
18(3), 97–124.
Huang, C.-Y. (2005). File sharing as a form of music consumption. International Journal of Electronic Commerce, 9(4), 37–55.
Hunt, S. D., & Vitell, S. J. (1986). A general theory of marketing ethics. Journal of
Macromarketing, 6(1), 5–16.
Jacobby, J., & Olson, J. C. (1977). Consumer response to price: An attitudinal information processing perspective. In Y. Wind, & M. Greenberg (Eds.), Moving ahead
with attitude research. Chicago: American Marketing Association.
Jones, M. A., Reynolds, K. E., & Arnold, M. J. (2006). Hedonic and utilitarian shopping
value: Investigating differential effects on retail outcomes. Journal of Business
Research, 59(9), 974–981.
Joo, Y. G., & Sohn, S. Y. (2008). Structural equation model for effective CRM of digital
content industry. Expert Systems with Applications, 34(1), 63–71.
Jung, I. (2009). Ethical judgments and behaviors: Applying a multidimensional ethics
scale to measuring ICT ethics of college students. Computers & Education, 53(3),
940–949.
Karim, N. S. A., Zamzuri, N. H. A., & Nor, Y. M. (2009). Exploring the relationship
between Internet ethics in university students and the big five model of personality. Computers & Education, 53(1), 86–93.
Kim, H.-W., Chan, H. C., & Gupta, S. (2007). Value-based adoption of Mobile Internet:
An empirical investigation. Decision Support Systems, 43(1), 111–126.
Kim, Y.-K. (2002). Consumer value: An application to mall and Internet shopping.
International Journal of Retail and Distribution Management, 30(12), 595–602.
Klein, L. R., & Ford, G. T. (2003). Consumer search for information in the digital age:
An empirical study of prepurchase search for automobiles. Journal of Interactive
Marketing, 17(3), 29–49.
Kok, G., deVries, H., Muddle, A. N., & Strecher, V. J. (1991). Planned health education
and the role of self-efficacy: Dutch research. Health Education Research, 6(2),
231–238.
Kuo, F.-Y., & Hsu, M.-H. (2001). Development and validation of ethical computer
self-efficacy measure: The case of softlifting. Journal of Business Ethics, 32(4),
299–315.
Kuo, Y.-F., & Wu, C.-M. (2012). Satisfaction and post-purchase intentions with service
recovery of online shopping websites: Perspectives on perceived justice and
emotions. International Journal of Information Management, 32(2), 127–138.
Levin, A. M., Dato-On, M. C., & Rhee, K. (2004). Money for nothing and hits for free: The
ethics of downloading music from peer-to-peer web sites. Journal of Marketing
Theory and Practice, 12(1), 48–60.
Lin, H.-H., & Wang, Y.-S. (2006). An examination of the determinants of customer loyalty in mobile commerce contexts. Information & Management, 43(3), 271–282.
Liu, C.-T., Guo, Y. M., & Lee, C.-H. (2011). The effects of relationship quality and
switching barriers on customer loyalty. International Journal of Information Management, 31(1), 71–79.
Lu, H.-P., & Hsiao, K.-L. (2010). The influence of extro/introversion on the intention
to pay for social networking sites. Information & Management, 47(3), 150–157.
Luarn, P., & Lin, H. H. (2005). Toward an understanding of the behavioral intention
to use mobile banking. Computers in Human Behavior, 21(6), 873–891.
Marshall, K. P. (1999). Has technology introduced new ethical problems? Journal of
Business Ethics, 19(1), 81–90.
Miyazaki, A. D., Rodriguez, A. A., & Langenderfer, J. (2009). Price, scarcity, and consumer willingness to purchase pirated media products. Journal of Public Policy &
Marketing, 28(1), 71–84.
Monroe, K. B. (1973). Buyers’ subjective perceptions of price. Journal of Marketing
Research, 10(1), 70–80.
Monroe, K. B. (1990). Pricing: Making profitable decision (2nd ed.). New York, NY:
McGraw-Hill Book Company.
Moores, T. T., & Chang, J. C.-J. (2006). Ethical decision making in software piracy:
Initial development and test of a four-component model. MIS Quarterly, 30(1),
167–180.
Pan, Y., & Sparks, J. R. (2012). Predictors, consequence, and measurement of ethical
judgments: Review and meta-analysis. Journal of Business Research, 65(1), 84–91.
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(1), 168–174.
Patterson, P. G., & Spreng, R. A. (1997). Modeling the relationship between perceived
value, satisfaction and repurchase intentions in a business-business, services
context: An empirical examination. International Journal of Service Industry Management, 8(5), 414–434.
Peitz, M., & Waelbroeck, P. (2006). Piracy of digital products: A critical review of the
theoretical literature. Information Economics and Policy, 18(4), 449–476.
Plowman, S., & Goode, S. (2009). Factors affecting the intention to download music:
Quality perceptions and downloading intensity. Journal of Computer Information
Systems, 49(4), 84–97.
Prasad, A., & Mahajan, V. (2003). How many pirates should a software firm tolerate?
An analysis of piracy protection on the diffusion of software. International Journal
of Research in Marketing, 20(4), 337–353.
Rest, J. (1986). Moral development: Advances in research and theory. New York:
Praeger.
Rintamäki, T., Kanto, A., Kuusela, H., & Spence, M. T. (2006). Decomposing the value of
department store shopping into utilitarian, hedonic and social dimensions: Evidence from Finland. International Journal of Retail and Distribution Management,
34(1), 6–24.
Sandulli, F. D. (2007). CD music purchase behaviour of P2P users. Technovation,
27(6–7), 325–334.
Segars, A. H., & Grover, V. (1993). Re-examining perceived ease of use and usefulness:
A confirmatory factor analysis. MIS Quarterly, 17(4), 517–525.
Shanahan, K. J., & Hyman, M. R. (2010). Motivators and enablers of SCOURing: A
study of online piracy in the US and UK. Journal of Business Research, 63(9–10),
1095–1102.
Sheth, J. N., Newman, B. I., & Gross, B. L. (1991). Why we buy what we buy: A theory
of consumption values. Journal of Business Research, 22(2), 159–170.
Sirdeshmukh, D., Singh, J., & Sabol, B. (2002). Consumer trust, value, and loyalty in
relational exchanges. Journal of Marketing, 66(1), 15–37.
Song, J., Baker, J., Lee, S., & Wetherbe, J. C. (2012). Examining online consumers’
behavior: A service-oriented view. International Journal of Information Management, 32(3), 221–231.
Sweeney, J. C., Soutar, G. N., & Johnson, L. W. (1997). Retail service quality and
perceived value. Journal of Retailing and Consumer Services, 4(1), 39–48.
Tan, B. (2002). Understanding consumer ethical decision making with respect to
purchase of pirated software. Journal of Consumer Marketing, 19(2), 96–111.
Thong, J. Y. L., & Yap, C. S. (1998). Testing an ethical decision-making theory: The
case of softlifting. Journal of Management Information Systems, 15(1), 213–237.
To, P.-L., Liao, C., & Lin, T.-H. (2007). Shopping motivations on Internet: A study based
on utilitarian and hedonic value. Technovation, 27(12), 774–787.
Udo, G. J., Bagchi, K. K., & Kirs, P. J. (2010). An assessment of customers’ e-service
quality perception, satisfaction and Intention. International Journal of Information
Management, 30(6), 481–492.
van der Heijden, H. (2004). User acceptance of hedonic information systems. MIS
Quarterly, 28(4), 695–704.
Voss, G. B., Parasuraman, A., & Grewal, D. (1998). The roles of price, performance,
and expectations in determining satisfaction in service exchanges. Journal of
Marketing, 62(4), 46–61.
Wang, Y.-S. (2008). Assessing e-commerce systems success: A respecification and
validation of the DeLone and McLean model of IS success. Information Systems
Journal, 18(5), 529–557.
Wang, Y.-S., Lin, H.-H., & Luarn, P. (2006). Predicting consumer intention to use
mobile service. Information Systems Journal, 16(2), 157–179.
Warr, R., & Goode, M. M. H. (2011). Is the music industry stuck between rock and
a hard place? The role of the Internet and three possible scenarios. Journal of
Retailing and Consumer Services, 18(2), 126–131.
Yoon, C. (2011a). Ethical decision-making in the Internet context: Development and
test of an initial model based on moral philosophy. Computers in Human Behavior,
27(6), 2401–2409.
Yoon, C. (2011b). Theory of planned behavior and ethics theory in digital piracy: An
integrated model. Journal of Business Ethics, 100(3), 405–417.
Zeithaml, V. A. (1988). Consumer perceptions of price, quality, and value: A meansend model and synthesis of evidence. Journal of Marketing, 52(3), 2–22.
Yi-Shun Wang is Distinguished Professor in the Department of Information Management at National Changhua University of Education, Taiwan. He received his Ph.D.
in MIS from National Chengchi University, Taiwan. His current research interests
include IT/IS adoption strategies, IS success models, customer relationship management, and e-learning. He has published in journals such as Information Systems
Journal, International Journal of Information Management, Information & Management,
Government Information Quarterly, Journal of Information Science, Journal of Global
Information Management, Computers & Education, British Journal of Educational Technology, Cyber Psychology & Behavior, Computers in Human Behavior, Service Industries
Journal, Managing Service Quality, among others. He has served as a Project Reexamination Committee Member for both research areas of Information Management
and Applied Science Education in the National Science Council of Taiwan.
Ching-Hsuan Yeh is a post-doctoral fellow in the Department of Information Management at National Changhua University of Education, Taiwan. He received his
Ph.D. in International Business from National Chi Nan University, Taiwan. His current
research interests include consumer behavior, e-commerce, and Internet marketing. He has published papers in journals such as International Journal of Information
Management, Journal of Business Research, and Food Quality and Preference.
Yi-Wen Liao is an assistant professor in the Department of Information Management, Taiwan at Chia Nan University of Pharmacy and Science, Taiwan. She received
her Ph.D. in MIS from National Sun Yat-sen University, Taiwan. Her current research
interests include electronic commerce, online shopping behavior, and e-learning.
Her work has been published in academic journals such as International Journal of
Information Management, Government Information Quarterly, British Journal of Educational Technology, and Computers in Human Behavior.