Description
This paper proposes a model for the formation of online purchase intention based on perceived value,
trust and the antecedents of perceived security and privacy, using the model proposed by Ray, Ow, and
Kim (2011) extended to cover third-party assurance seals and related constructs, and examines the influence
on trust of consumers' perceived information quality, privacy, and security. A total of 451 individuals
participated in an experiment. The partial least squares technique was applied to data collected
via a questionnaire to test the proposed model. The results indicate that online purchase intention depends
on perceived value and trust. The main predictors of perceived trust are perceived information
quality and perceived security. Consumers' perceived security depends on vendor reputation, website
investment, third-party assurance seals, understanding of third-party seals, privacy and security policies,
familiarity with the website, Internet privacy concerns, and disposition towards third-party certification.
In?uence of trust and perceived value on the intention to purchase
travel online: Integrating the effects of assurance on trust antecedents
Enrique Bons
on Ponte
a, 1
, Elena Carvajal-Trujillo
b, *
, Tom
as Escobar-Rodríguez
a, 2
a
Department of Accounting and Information Systems, University of Huelva, Plaza de la Merced, 21002 Huelva, Spain
b
Department of Business Administration and Marketing, University of Huelva, Plaza de la Merced, 21002 Huelva, Spain
h i g h l i g h t s
We analyze the effects of assurance on trust antecedents in travel website.
Trust depends on perceived information quality and perceived security.
Security is mainly affected by reputation, investment, third-party assurance seals.
Online purchase intention is in?uenced by perceived value and trust.
a r t i c l e i n f o
Article history:
Received 2 April 2014
Accepted 8 October 2014
Available online 30 October 2014
Keywords:
E-commerce
Trust
Assurance
Privacy concerns
Security
Online purchase intention
a b s t r a c t
This paper proposes a model for the formation of online purchase intention based on perceived value,
trust and the antecedents of perceived security and privacy, using the model proposed by Ray, Ow, and
Kim (2011) extended to cover third-party assurance seals and related constructs, and examines the in-
?uence on trust of consumers' perceived information quality, privacy, and security. A total of 451 in-
dividuals participated in an experiment. The partial least squares technique was applied to data collected
via a questionnaire to test the proposed model. The results indicate that online purchase intention de-
pends on perceived value and trust. The main predictors of perceived trust are perceived information
quality and perceived security. Consumers' perceived security depends on vendor reputation, website
investment, third-party assurance seals, understanding of third-party seals, privacy and security policies,
familiarity with the website, Internet privacy concerns, and disposition towards third-party certi?cation.
© 2014 Elsevier Ltd. All rights reserved.
1. Introduction
The Internet and information communication technology are
leading to great developments in the tourism industry (Buhalis &
Law, 2008). The Internet is ideal for the tourism industry because
of the characteristics of tourism products (McCole, 2002): 1) they
are intangible, 2) their production and consumption cannot be
separated, 3) they are perishable, and 4) they are seasonal. More-
over, the Internet is used in the tourismindustry when users search
for information and enter into online transactions (Kim, Chung, &
Lee, 2011). Internet technology allows suppliers of travel products
to sell their products anywhere and at any time (Bernstein & Awe,
1999; Connolly, Olsen, & Moore, 1998; Law & Wong, 2003; Llach,
Mariomon, Alonso-Almeida, & Bernardo, 2013). Online trans-
actions represent a new stage in the tourism industry, which is
working to develop better commercial practices (Kim et al., 2011).
Some of the attributes associated with e-commerce that have
brought about a modi?cation of commercial transactions are con-
venience, economic cost, and product diversity (Yoon, 2002).
Although the number of Internet users has substantially
increased, many users do not make purchases online. They are
reluctant to provide personal information and/or transactional in-
formation for electronic payments online because they do not trust
e-commerce (Kim et al., 2011; Kim, Ferrin, & Rao, 2008). A study of
e-commerce showed that more than 87% of users were concerned
about security and privacy protection in online shopping (Ray, Ow,
&Kim, 2011). In addition, the lack of perceived privacy and security
protection is a major reason why many consumers choose not to
shop online; trust therefore plays a relevant role in online trans-
actions (Kim et al., 2011; Wu & Chang, 2005). In this general
context, previous studies have analyzed trust in e-commerce
* Corresponding author.
E-mail addresses: [email protected] (E. Bons on Ponte), [email protected].
es (E. Carvajal-Trujillo), [email protected] (T. Escobar-Rodríguez).
1
Tel./fax: þ34 959217892x7850.
2
Tel./fax: þ34 959217895x7850.
Contents lists available at ScienceDirect
Tourism Management
j ournal homepage: www. el sevi er. com/ l ocat e/ t ourmanhttp://dx.doi.org/10.1016/j.tourman.2014.10.009
0261-5177/© 2014 Elsevier Ltd. All rights reserved.
Tourism Management 47 (2015) 286e302
together with other factors (Cyr, 2008, 2013; Cyr, Kindra, & Dash,
2008; Harris & Goode, 2004; Jin, Park, & Kim, 2007; Kim et al.,
2008; Kim, Xu, & Gupta, 2012; McKnight & Chervany, 2001; Wu,
Hu, & Wu, 2010). Previous research in e-commerce has examined
the antecedents of perceived privacy and/or perceived security (Li,
2014; Lowry et al., 2011; Ray et al., 2011). Ray et al. (2011), besides
studying these antecedents, analyzed the in?uence of perceived
privacy and security on consumers' perceived trust in online
transactions.
In the tourism context, trust has also been proved to be one of
the most relevant variables that makes e-business successful in the
travel industry (Kim et al., 2011), the accommodation industry
(speci?cally hotels and resorts) (Fam, Foscht, & Collins, 2004), and
the air travel industry, both in general (Kim, Kim, &Shin, 2009) and
for low-cost carriers (LCCs) and in particular (Escobar-Rodríguez &
Carvajal-Trujillo, 2014). Kim et al. (2011) tried to examine the fac-
tors in?uencing trust (navigation functionality, perceived security,
and transaction cost) and the effect of trust and satisfaction on
loyalty in online shopping for travel products in South Korea.
Escobar-Rodríguez and Carvajal-Trujillo (2014) examined the fac-
tors in?uencing the intention to use LCC e-commerce websites to
purchase tickets in Spain, analyzing, among other variables, the
in?uence of perceived privacy, perceived security, and information
quality on consumer trust in the website. Kim et al. (2009) studied
the determinants of e-commerce on airline e-commerce websites,
on the basis of the technology acceptance model (TAM), and trust
and subjective norms in South Korea.
Few studies in the ?eld of tourism and e-commerce analyze the
antecedents of perceived privacy and/or perceived security.
Although studies have examined consumers' perceived value and
purchase intentions (Llach et al., 2013), and their trust and purchase
intentions (Kim et al., 2011), none have examined the effect of
perceived trust on perceived value in the ?eld of e-commerce and
tourism. Furthermore, Kim et al. (2011) noted that there is little
research regarding online consumers' perceived trust in travel
products. In this study, we analyze the antecedents of perceived
security and privacy, extending the model proposed by Ray et al.
(2011) by adding a new factor, consumers' perception of third-
party assurance seals, and two constructs related to this, the
disposition towards third-party certi?cation and the understanding
of third-party seals. In addition, using the model proposed by Kim
et al. (2012), we examine the in?uence of trust on perceived value,
and the in?uence of these two factors on purchase intention.
We have extended the model to include third-party assurance
seals and the related constructs following the recommendations of
€
Ozpolat, Gao, Jank, and Viswanathan (2013); these authors stated
that there are very few studies examining the role of third-party
mechanisms in helping to increase trust in e-commerce, unlike
the position for the third-party certi?cation mechanisms that exist
in of?ine settings. Among the fewstudies that address the issue, Xu,
Teo, Tan, and Agarwal (2010) in the general context, and Lee and
Cranage (2011) in the context of tourism and e-commerce,
concluded that the use of privacy seals, such as TRUSTe, increases
reliability in relation to privacy protection and information
disclosure. Lee and Cranage (2011) analyzed howprivacy assurance
and personalization affect both consumers' perceptions of value
and their privacy concerns, in the context of travel websites. They
found that privacy assurance statements and the use of security
symbols increase perceived privacy protection and perceived trust.
In this study, we used the model proposed by Ray et al. (2011)
for three reasons. First, it presents a current integrated frame-
work to study the in?uence of signals such as third-party assurance
seals on travel websites and the in?uence of different consumer
predispositions on perceived security and privacy protection in
online transactions. Second, Ray et al. (2011) suggest further
research to determine whether the personal predispositions
included, but not found to be signi?cant, in their model, could in-
?uence perceived security and privacy if they are analyzed together
with other predispositions. Third, Ray et al. indicate the need to
research whether signals from websites in?uence online services
other than the general retail websites that they analyze.
With this in mind, this study aims: 1) to examine the in?uence
of perceived trust and perceived value on the intention to use e-
commerce websites when shopping for travel products; 2) to
analyze the in?uence of privacy and security signals and the per-
sonal predispositions of consumers on perceived privacy and
perceived security; and 3) to assess the effect of information
quality, perceived security, and perceived privacy on consumer
trust in a website.
The remainder of the paper is structured as follows. In the next
section, we provide a literature review and propose our working
hypotheses. Following that, we describe the research methodology.
The results are then presented, and ?nally we provide our con-
clusions and the implications for future research.
2. Literature review
2.1. Perceived trust, perceived privacy, perceived security,
information quality, and the relationships between them
Trust in websites plays an important role in e-commerce,
because consumers are unlikely to shop online if they do not trust
the seller's website on which they are shopping (Gefen, 2002;
Jarvenpaa, Tractinsky, Saarinen, & Vitale, 1999; Kim et al., 2008,
2011). Studies have analyzed the factors that can in?uence con-
sumers' perceived trust, and these help tourism product managers
to design their websites in such a way that consumers perceive the
transactions to be reliable. In this research, we examine, in relation
to travel websites, the antecedents of trust that, according to Kim
et al. (2008), are related to consumers' perceptions, such as secu-
rity protection, privacy protection, and the quality of the informa-
tion given on the website. We analyze these factors for travel
websites because only a few previous studies have examined the
antecedents of trust (Escobar-Rodríguez & Carvajal-Trujillo, 2014;
Kim et al., 2008, 2011). Escobar-Rodríguez and Carvajal-Trujillo
(2014) con?rm that previous studies have indicated that these
antecedents are very relevant for e-commerce (Au Yeung & Law,
2003; Flavian & Cuinaliu, 2006; Kim et al., 2011; Wong & Law,
2005). In e-commerce, it is dif?cult to gauge whether online
sellers will meet their commitment to protect the privacy of con-
sumers' personal information (McKnight, Choudhury, & Kacmar,
2002) and/or the security of online transactions (Kim et al.,
2008). Additionally, the content of sellers' websites can affect
consumers' perceived trust (Vila & Kuster, 2011). Hence, it is rele-
vant for online sellers to establish trusted transaction processes so
that consumers place trust in them and consequently form an on-
line purchase intention (Grabosky, 2001).
The de?nition of trust is complicated because it is an abstract
and complex factor. The literature gives various de?nitions of trust
(Corbitt, Thanasankit, & Yi, 2003; Gefen, Karahanna, & Straub,
2003). In the ?eld of e-commerce, according to Pavlou (2003),
trust is the belief that renders consumers vulnerable to the good
faith of online sellers after learning of their characteristics. Gefen
(2000) conceives of trust in a very similar way, as a general belief
in an online seller that results in a behavioral intention. Another
de?nition of trust in this context is provided by Kim et al. (2008);
they de?ne trust as the subjective belief that the online seller will
ful?ll its transactional obligations, as those obligations are under-
stood by the consumer. In this paper, we use this last de?nition.
E. Bons on Ponte et al. / Tourism Management 47 (2015) 286e302 287
The information quality antecedent can be conceived as the
consumers' general perception about the completeness and accu-
racyof the website informationconcerning boththe services offered
and the procedure for carrying out an online purchase transaction
(Kimet al., 2008). Then, depending on the quality of information on
the website, a consumer may perceive that the site is or is not
suitable for making the required online purchase correctly (Kim
et al., 2008). In other words, when various websites contain infor-
mation about similar products, the factor that induces consumers to
opt for one particular website over the rest to make the required
purchase is the quality of the information that the site is perceived
to provide (Raganathan & Ganapathy, 2002). Thus, the greater
consumers' perception that the website of an online seller contains
high-quality information, the more likely they are to think that the
website of the online seller is trustworthy (Kim et al., 2008).
Regarding the perceived security antecedent, this can be de?ned
as the perception of consumers that the online seller has included
the antecedents of security, such as veri?cation, authentication,
encryption, protection, and non-repudiation (Kim et al., 2008).
Chellappa and Pavlou (2002) noted that if consumers perceive that
the website of the online seller offers security factors such as a
security policy, a safe shopping guarantee, and other protection
mechanisms, they will deduce that the online seller guarantees the
security of an online purchase. Thus, the greater consumers'
perception that the website of an online seller guarantees security
during online transactions, the more likely they are to perceive that
the website of the online seller is trustworthy (Kim et al., 2008).
The perceived privacy protection antecedent can be conceptu-
alized as the probability that the online seller will ensure that the
con?dential information about the consumer acquired during the
online transaction is protected against unauthorized disclosure or
use (Kim et al., 2008). During an online transaction, the online
seller requests and collects a large amount of personal information
about the consumer, such as his or her name, home address, phone
number, email address, bank account and credit card details; the
consumer may suspect that the online seller will give or sell this
information to other entities, companies and persons (Kim et al.,
2008). Faced with the possibility of this occurring, the consumer
may decide against purchasing online e the consumer has lacks
con?dence that the online seller will properly protect his or her
privacy.
In the ?eld of e-commerce, Kim et al. (2008) con?rmed the
relationship between information quality, perceived security, and
perceived privacy protection and trust. In the context of tourismand
e-commerce, Escobar-Rodríguez and Carvajal-Trujillo (2014)
examined the effect of information quality, perceived security and
perceived privacy protection on trust. Thus, for travel websites that
sell travel products, information quality, perceived security, and
perceived privacy protectionwill almost certainly affect consumers'
trust.
Based on the previous evidence, we formulate the following
hypotheses for travel websites:
H01. Consumers' perception of the quality of website information
has a positive effect on trust.
H02. Consumers' perception of website security protection has a
positive effect on trust.
H03. Consumers' perception of website protection of privacy has a
positive in?uence on trust.
2.2. Antecedents of perceived privacy and perceived security
Although Ray et al. (2011) examined the factors in?uencing
perceived privacy and perceived security, these factors have not
been analyzed in the ?eld of tourism. We decided to explore the
antecedents of perceived privacy and perceived security in the
?eld of tourism for travel products, because of the great in?uence
of these factors on trust in the sales websites (Kim et al., 2009).
Accordingly, we extend the model proposed by Ray et al. (2011) by
incorporating third-party assurance seals and a couple of related
constructs. Ray et al. (2011), as suggested by Gefen et al. (2003)
and Kim and Benbasat (2003), differentiated the antecedents of
privacy and security in response to the ?ve sources that confer
trust: 1) a consumer's personality; 2) knowledge based on a con-
sumer's prior experiences; 3) institutional assurances from the
online seller; 4) calculative assurances from the online seller; and
5) cognitive assurances from third parties. These ?ve sources are
grouped into two broad components: ?rst, the consumers' indi-
vidual predispositions regarding privacy and security signals; and
second, privacy and security signals according to signaling theory
(Table 1).
The ?rst component, consumers' personal predispositions, re-
fers to the factors that might predispose users to perceive privacy
and security measures on the website of the online seller. Those
factors are relevant because online sellers use a variety of tools to
adhere to privacy and security standards, some of which are quite
technical and are not always perceptible to consumers, such as
encrypted transmissions, ?rewalls, and intrusion detection systems
(Bhimani, 1996; Cavusoglu, Raghunathan, & Cavusoglu, 2009;
Furnell & Karweni, 1999; Ray et al., 2011). Other tools, for
example privacy and security policies, third-party certi?cates, and
the emailing of the proof of purchase are implemented during the
interaction with a user (Ray et al., 2011). Within the ?rst compo-
nent, we added to the two variables considered by Ray et al. (2011)
(Internet privacy and security concerns and familiarity with the
travel website), two others (disposition towards third-party certi-
?cation and understanding of third-party assurance seals). The
Internet privacy concerns and disposition towards third-party
certi?cation factors represent consumers' personality-based trust
sources, because they refer to a consumer's predisposition to trust
others and believe in their good intentions (Gefen et al., 2003; Ray
et al., 2011). On the other hand, familiarity with the website and
understanding of third-party assurance seals are consumers'
knowledge-based trust sources (Table 1), the former because a
consumer's familiarity with a seller's website reduces uncertainty
(Gefen et al., 2003; Kim et al., 2008), and the latter because a
consumer's understanding of the seals displayed on a seller's
website increases his or her trust. Internet privacy concerns refer to
the propensity to be generally concerned about threats to personal
information submitted over the Internet and/or the safety of pay-
ments in online transactions (Dinev &Hart, 2006; Malhotra, Kim, &
Agarwal, 2004; Ray et al., 2011; Sheehan & Hoy, 2000; Smith,
Milberg, & Burke, 1996). According to Ray et al. (2011), familiarity
Table 1
Antecedents of consumers' perceived privacy and security.
Factors Source of trust Origin
Predispositions Internet privacy concern Personality NA
Familiarity with the website Knowledge NA
Disposition to third-party
certi?cation
Personality NA
Understanding of third-party
assurance seals
Knowledge NA
Security
signals
Privacy and security policies Institution First-party
Website investment Calculative First-party
Vendor reputation Cognitive Second-party
Third-party assurance seals Institution Third-party
NA ¼ not available.
E. Bons on Ponte et al. / Tourism Management 47 (2015) 286e302 288
with the website includes the predisposition of consumers to trust
online sellers based on their prior knowledge of those sellers.
The second component proposed by Ray et al. (2011), security/
privacy signals, is based on signaling theory. This theory states that
companies can perform actions and provide cues that give infor-
mation about quality to customers, whether or not these signals are
credible to and interpretable by the customers (Duncan &Moriarty,
1998; Rao, Qu, & Ruekert, 1999; Ray et al., 2011). Within this
component, they include the factors used by online sellers to in-
crease trust by providing institutional, calculative, and cognitive
assurances (Gefen et al., 2003; Ray et al., 2011) (Table 1). These
signals cannot directly in?uence the perceptions of consumers,
because the quality of security and privacy is dif?cult for consumers
to appreciate (Ray et al., 2011). As noted by Wang, Beatty, and Foxx
(2004), online sellers utilize different strategies to signal their
trustworthiness and to ease consumers' concerns over e-commerce
(Wu et al., 2010). Thus, consumers should rely on indirect cues, or
signals, to assess the level of quality (Ray et al., 2011; Zeithaml,
1988). Ray et al. (2011) included three signals from online sellers
that could affect perceived privacy and security: privacy and se-
curity policies, perceived website investment, and the reputation of
the online seller. In our model, we add a fourth signal, third-party
assurance seals. Privacy and security policies are statements pro-
vided by online sellers that supply information and claim that
privacy and security are assured (Kim & Benbasat, 2003; Lowry
et al., 2011; Ray et al., 2011). Schlosser, White, and Lloyd (2006)
refer to the website investment made by the online seller in
terms of the effort, time, and money spent on developing it. This
investment signals the importance of security and privacy protec-
tion for the online seller, because the physical appearance of
products has always been a signal of quality (Dawar &Parker, 1994;
Ray et al., 2011). Privacy and security policies and website in-
vestments are ?rst-hand quality information sources about the
seller's website, provided directly by the online seller (
€
Ozpolat
et al., 2013). Regarding the reputation of the online seller, Ray
et al. (2011) considered that second-party information on sellers
is a signal of quality, indicating privacy and security protection to
consumers (Duncan & Moriarty, 1998; Gefen et al., 2003). The
reputation of the online seller provides quality information about
the seller's website, and is based on the experience of previous
shoppers, that is, a second-party information source (
€
Ozpolat et al.,
2013).
In accordance with the constructs and relationships of the
model proposed by Ray et al. (2011), as well as the previous evi-
dence, we suggest, in the context of tourism and e-commerce for
travel websites, the following hypotheses regarding consumers'
perceived privacy and security:
H04. Internet privacy concern negatively in?uences consumers'
perception of website security protection.
H05. Internet privacy concern negatively in?uences consumers'
perception of website privacy protection.
H06. Familiarity with the seller's website positively in?uences
consumers' perception of website security protection.
H07. Familiarity with the seller's website positively in?uences
consumers' perception of website privacy protection.
H08. Privacy and security policies positively in?uence consumers'
perception of website security protection.
H09. Privacy and security policies positively in?uence consumers'
perception of website privacy protection.
H10. Perceived website investment positively in?uences con-
sumers' perception of website security protection.
H11. Perceived website investment positively in?uences con-
sumers' perception of website privacy protection.
H12. The online seller's reputation positively in?uences con-
sumers' perception of website security protection.
H13. The online seller's reputation positively in?uences con-
sumers' perception of website privacy protection.
2.2.1. Third-party assurance seals
Third-party assurance seals (e.g., TRUSTe, VeriSign, BBBOnline)
provide assurance to consumers that a website follows particular
operating practices, that payments are secure, and/or that the
privacy policy indicates what the seller can and cannot do with
personal data collected online (Kim et al., 2008; Kim, Sivasailam, &
Rao, 2004; Shapiro, 1987). According to
€
Ozpolat et al. (2013),
companies that provide assurance seals examine the website's se-
curity, privacy, and service quality and, if these meet a number of
quality standards, the seller is allowed to display the assurance seal.
McKnight and Chervany (2001) argue that third-party seals are
sources of trust based on institutional assurances (Table 1) and, as
suggested by Jiang, Jones, and Javie (2008) and Kimery and McCord
(2002a), they might increase consumers' perceived security and
privacy.
A number of studies have analyzed the in?uence of third-party
assurance seals on trust, but there is a lack of consensus on this
(
€
Ozpolat et al., 2013). While some studies found a positive in?uence
(Grazioli & Jarvenpaa, 2000; Jiang et al., 2008; Rifon, LaRose, &
Choi, 2005; Yang, Hung, Sung, & Farn, 2006), others did not (Hui,
Teo, & Lee, 2007; Kim et al., 2008; Kimery & McCord, 2002a;
McKnight, Kacmar, & Choudhury, 2004; Metzger, 2006;
Pennington, Wilcox, & Grover, 2003; Yousafzai, Pallister, & Foxall,
2005). On the other hand, very little is known about the effect of
assurance seals on consumers' perceived security and/or privacy,
except for the results of the studies of Kim and Kim (2011), who
found a positive in?uence, and Lowry et al. (2011), who found that
seals fail to increase consumers' perceived privacy. Furthermore, in
the context of tourism and e-commerce, no study has analyzed
either the impact of seals on trust or their impact on consumers'
perceived security and privacy, so our study is the ?rst to address
those issues.
If consumers perceive, by means of signals such as third-party
assurance seals, that the online seller provides security and pri-
vacy protection in online transactions, their perception of uncer-
tainty and online shopping risks should tend to be reduced (Kim &
Benbasat, 2003; Wu et al., 2010). In fact, seals should contribute to
increasing consumers' privacy protection (Hoffman, Novak, &
Peralta, 1999) and/or security protection (Udo, 2001). Thus, for
online shopping for travel products, if third-party assurance seals
are cues for security and privacy protection on the travel websites
of online sellers, it can be hypothesized that displaying these
assurance seals will positively in?uence consumers' perception of
website privacy and security protection. Thus, this study suggests
the following research hypotheses in the context of tourism and e-
commerce for travel products:
H14. The presence of a third-party assurance seal positively in-
?uences consumers' perception of website privacy protection.
H15. The presence of a third-party assurance seal positively in-
?uences consumers' perception of website security protection.
2.2.2. Disposition towards third-party certi?cates
With this construct, we refer to the disposition to trust third-
party certi?cation such as seals. The disposition to trust is de?ned
as a consumer personality trait that shows the degree to which
E. Bons on Ponte et al. / Tourism Management 47 (2015) 286e302 289
consumers are predisposed to perceive others as trustworthy (Jiang
et al., 2008; Kim et al., 2008). This predisposition of consumers is
based on the result of ongoing lifelong experiences with and
knowledge of a certain trusted party (Kim et al., 2008; McKnight,
Cummings, & Chervany, 1998). Therefore, if a consumer has a
high inclination to trust others in general, this disposition is likely
to have a positive in?uence on her or his trust in a particular seller,
and if she or he has a low inclination to trust others in general, she
or he is likely to develop a lower level of trust in a particular seller
(Kim et al., 2008; McKnight et al., 1998). The in?uence of the
disposition to trust on trust has been studied in the general liter-
ature (Kim et al., 2008; Kimery & McCord, 2002a; Mayer, Davis, &
Schoorman, 1995; Wu et al., 2010). Jiang et al. (2008) proposed
that the disposition to trust third-party certi?cation has an in?u-
ence on the perception of the identifying logos for third-party
certi?cation, and that this factor has an in?uence on online
seller trust. The disposition to trust third-party certi?cation is
de?ned as the tendency to depend on third parties for trustworthy
information during online transactions. If consumers have a high
tendency to trust third-party certi?cation, such as security and
privacy protection assurances, this disposition is likely to have a
positive effect on her or his perception of the privacy and security of
the online seller. As noted by Wu et al. (2010), consumers with a
higher disposition to trust are more credulous (Gefen, 2000), and
they are more likely to trust online sellers displaying third-party
assurance seals, increasing their perception of website security
and privacy protection (Wu et al., 2010). Thus, for travel e-com-
merce websites for the purchase of travel products, consumers'
disposition to trust third-party certi?cation will almost certainly
in?uence their trust in those websites. In this study, it is hypothe-
sized that security and privacy protection will be related to the
disposition towards third-party certi?cation in tourism e-com-
merce products, as follows:
H16. Consumers' disposition towards third-party certi?cation
positively affects their perception of website security protection.
H17. Consumers' disposition towards third-party certi?cation
positively affects their perception of website privacy protection.
2.2.3. Understanding of third-party assurance seals
Lowry et al. (2011) suggested that an understanding of third-
party assurance seals indicates that the consumer knows that his/
her data are protected. Online sellers display third-party assurance
seals on their websites to increase consumers' perception of web-
site security and privacy protection; however, if the consumers do
not understand the seals, it is useless to display them. In fact,
McKnight et al. (2004) and Moores (2005) highlighted the fact that
third-party assurance seals fail because consumers do not under-
stand their forms or function; hence, it is necessary to study con-
sumers' understanding of the seals. This factor was analyzed by
Lowry et al. (2011), who also considered that the use of a third-
party privacy assurance seal will not be effective if consumers do
not understand it. In the context of tourism and e-commerce, it is
also relevant that consumers understand the seals if they are to be
useful. Given the relevance of the consumers' understanding of the
seals for shopping for travel products, we propose the following
research hypotheses:
H18. Consumers' understanding of third-party assurance seals
positively in?uences their perception of website security
protection.
H19. Consumers' understanding of third-party assurance seals
positively in?uences their perception of website privacy protection.
2.3. Perceived value, perceived trust, purchase intention, and the
relationships between them
On the basis of prospect theory (Kahneman & Tversky, 1979;
Wang & Wang, 2010), we assume in this research that an overall
judgment of value in?uences the online purchase intention. In the
e-commerce context, perceived value can be de?ned as the con-
sumer's assessment of bene?ts against costs when shopping with
an online seller (Zeithaml, 1988). Consequently, the perceived
value of a transaction with an online seller is the net bene?t (Kim
et al., 2012; Seddon, 1997). Obviously, consumers wish to shop for
products with those vendors who offer maximumvalue (Kim et al.,
2012; Wang & Wang, 2010; Zeithaml, 1988). In fact, the literature
has shown that the perceived value of a product in?uences the
purchase intention (Chang & Wildt, 1994; Dodds, Monroe, &
Grewal, 1991). In the e-commerce context, studies have
con?rmed the relationship between perceived value and purchase
intention (Chang & Wang, 2011; Fuentes-Blasco, Gil-Saura,
Berenguer-Contrí, & Moliner-Velazquez, 2010; Kim et al., 2012;
Wu, Chen, Chen, & Cheng, 2014). In the tourism e-commerce ?eld,
Llach et al. (2013) examined the in?uence of perceived value on
intention in the purchasing of airline tickets, concluding that the
effect is signi?cant and positive. Thus, this study proposes
the following hypothesis regarding online shopping for travel
products:
H20. Perceived value on a website positively in?uences the online
purchase intention.
According to Kim et al. (2012), if consumers have trust in an
online seller, they expend less effort on searching for information
about the online seller and on executing the online transaction.
Perceived trust can decrease the transaction's non-monetary cost;
this cost incorporates variables such as the time and effort
required to choose an online seller (Chiles & McMackin, 1996) and
the perceived risk of online shopping (Jarvenpaa, Tractinsky, &
Vitale, 2000; Kim et al., 2012). As perceived trust reduces the
non-monetary cost, it raises the perceived value when shopping
online on a seller's website (Kim et al., 2012). Only Kim et al.
(2012), in the e-commerce context, have examined the in?uence
of perceived trust on perceived value, and they con?rmed this
in?uence. There is no study examining this relationship in the ?eld
of tourism and e-commerce. For our research, for shopping online
for travel products, consumers' perceived trust in travel websites
will reduce the non-monetary cost and this will raise the
perceived value of the online shopping. In our study, we hypoth-
esize that perceived trust has an in?uence on perceived value as
follows:
H21. Trust in an online seller positively affects the perceived value
for customers.
In the e-commerce ?eld, several previous studies have
con?rmed the relationship between trust and the intention to
purchase online (Chiu, Huang, & Hui, 2010; Gefen et al., 2003;
Grazioli & Jarvenpaa, 2000; Jarvenpaa et al., 2000; Kim et al.,
2008, 2012). In the ?eld of tourism and e-commerce, this rela-
tionship has also been analyzed, and the conclusion has been
reached that the in?uence is signi?cant and positive (Bign e, Sanz,
Ruiz, & Ald as, 2010; Escobar-Rodríguez & Carvajal-Trujillo, 2014;
Kamarulzaman, 2007; Kim et al., 2009, 2011; Sanz-Blas, Ruiz-Maf e,
& P erez P erez, 2014; Wen, 2009, 2010). Thus, for online shopping
for travel products, we hypothesize:
H22. Trust positively affects the online purchase intention.
Fig. 1 graphically represents the different research hypotheses.
E. Bons on Ponte et al. / Tourism Management 47 (2015) 286e302 290
3. Methodology
3.1. Measurements
A set of measurement items was adapted to the speci?c context
of this research, and a total of 55 items was obtained. In Table 2, we
present the complete list of items, which were measured by means
of multi-item scales, for the constructs taken into account in this
research. The responses of the survey participants to each of the
items were measured on a seven-point Likert scale, ranging from 1
(¼ “strongly disagree”) to 7 (¼ “strongly agree”). This is the usual
way of measuring variables that are not directly quanti?able or
observed (Churchill & Iacobucci, 2002).
The items in the questionnaire were validated on the basis of the
opinions of a focus group of e-commerce and e-tourism academics
and professionals, who were asked whether the items were
appropriate for the purpose of evaluating e-commerce and trust.
The focus group's opinions led us to modify some items to make the
meanings clearer. A pre-test was carried out on 40 individuals of
different ages and genders, selected by quota and convenience
sampling, who had purchased travel products on a website in the
past year. This ensured that those individuals who had not pur-
chased travel products in the past year were dropped from the pre-
test. Using the feedback from this pre-test, modi?cations were
made to the wording of some items to increase the clarity further,
but these were only minor. A ?nal questionnaire was created and
administered to 30 individuals of different genders and ages,
selected by quota and convenience sampling, who had purchased
travel products on a website in the past year. The clarity of the
questionnaire was thus con?rmed, and no more changes were
made to it.
The questionnaire was originally drafted in English, but it was
intended for use in Spanish for consumers from Spain who had
experience of purchasing tourism products on websites. Therefore,
the English questionnaire was translated into Spanish by a
professional native English translator and by researchers, working
independently. After a careful analysis of the differences between
these independently translated questionnaires, a de?nitive version
of the Spanish questionnaire was agreed. This ?nal version was
then translated back into English by another native English pro-
fessional translator to ensure consistency between the English and
the Spanish version of the questionnaire (Brislin, 1970). Table 2
shows the items for this study and the supporting literature for
each construct.
3.2. Sample and data collection
This study used quota and convenience sampling. The conve-
nience sampling method was utilized because the population size
is unknown for this study (San Martín & Herrero, 2012). The quota
sampling method was employed to match the target population
structure in both age and gender (Kimet al., 2009, 2011; San Martín
& Herrero, 2012). To calculate the number of participants that
would be suf?cient in each age and gender category, population
data were obtained from the 15th Internet users survey (AIMC,
2013), a study carried out by the Asociaci on para la Investigaci on
de Medios de Comunicaci on (Table 3). Afterwards, to combine the
diverse quotas, convenience sampling was carried out (San Martín
& Herrero, 2012). Males and females are represented as follows:
67.8% and 32.2%, respectively. The age groups constitute the
following: 5.8% aged under 20 years; 13.7% aged 20e24; 31.7% aged
25e34; 36.4% aged 35e44; 8.9% aged 45e54; 3.1% aged 55e64; and
0.4% aged 64 and over. Table 4 shows the data on the gender and
age of the participants. There were more males (67.8%) than fe-
males (32.2%). The largest proportion of the respondents (36.4%)
were aged between 35 and 44, followed by those aged between 25
and 34 (31.7%).
The participants were recruited by email among the community
of our university. We emailed an invitation to participate in our
research to current students, alumni, faculty members, and staff,
Fig. 1. Proposed model.
E. Bons on Ponte et al. / Tourism Management 47 (2015) 286e302 291
Table 2
Construct measurement.
Construct Item Supporting literature
Third-party assurance seal AS1. The third-party assurance seals on this website make me feel more comfortable. Cyr (2013)
Kim et al. (2008) AS2. The third-party assurance seals on this website make me feel more secure in terms of privacy.
AS3. Third-party assurance seals on this website make me feel safer in terms of the transaction.
AS4. The third party assurance seals on this website make me feel this website is secure.
Purchase intention BI1. The probability that I would consider to purchase a tourism product from this website is high. Kim et al. (2012)
BI2. If I were to purchase a tourism product, I would consider purchasing it from this website.
BI3. The likelihood of my purchasing a tourism product from this website is high.
BI4. My willingness to purchase a tourism product from this website is high.
Disposition to third-party
certi?cation
DC1. I speci?cally look for third-party certi?cation symbols. Jiang et al. (2008)
DC2. I generally have faith in third-party certi?cation.
DC3. I generally trust third parties.
Familiarity with the
website
FA1. I am familiar with this tourism product shopping website. Chiu, Hsu, Lai, and
Chang (2012) FA2. I am familiar with the processes of purchasing products from this tourism product shopping website.
FA3. I am familiar with searching for products at this tourism product shopping website.
Information quality IQ1. The tourism product website provides accurate information about the tourism product that
I want to purchase.
Kuan et al. (2008)
IQ2. The tourism product website provides suf?cient information when I try to make a transaction.
IQ3. The tourism product website provides enough depth of information about its products.
IQ4. The information provided by tourism product website is helpful to me in purchasing tourism products.
IQ5. The information in the tourism product website is clear for me to make a purchase.
IQ6. The tourism product website provides up-to-date information.
Internet privacy concerns PC1. Compared with other subjects on my mind, online privacy/security is very important. Ray et al. (2011)
PC2. I am concerned about threats to online privacy/security today.
PC3. The greater my interest to obtain a certain service or product from the Internet, the more
I tend to suppress my privacy/security concerns.
Perceived value PV1. Considering the money I pay to purchase tourism products on this website, online shopping
here is a good deal.
Kim et al. (2012)
PV2. Considering the effort I make in shopping on this website, online shopping here is worthwhile.
PV3. Considering the risk involved in shopping on this website, online shopping here is of value.
PV4. Overall, online shopping on this website delivers me good value.
Vendor reputation REP1. This company is well known. Ray et al. (2011)
REP2. This company has a good reputation.
REP3. This company has a good reputation in its market.
Trust PT1. This tourism product website has integrity. Kim et al. (2011)
PT2. This tourism product website is reliable.
PT3. This tourism product website is trustworthy.
Perceived privacy
a
PP1. I am concerned that tourism product website collects too much personal information from me. Kim et al. (2008)
PP2. I am concerned that the tourism product website will use my personal information for other
purposes
without my authorization.
PP3. I am concerned the tourism product website will share my personal information with other entities
without my authorization.
PP4. I am concerned that unauthorized persons (i.e. hackers) have access to my personal information.
PP5. I am concerned about the privacy of my personal information during a transaction.
PP6. I am concerned that the tourism product website will sell my personal information to others without
my permission.
Perceived security PS1. The tourism product website implements security measures to protect users. Kim et al. (2008)
PS2. The tourism product website usually ensures that transactional information is protected from
accidentally being altered or destroyed during a transmission on the Internet.
PS3. I feel secure about the electronic payment system of the tourism product website.
PS4. I am willing to use my credit card on this website to make a purchase.
PS5. I feel safe in making transactions on this website.
Privacy and security policy SS1. The availability of a privacy or a security statement was easily seen on the tourism product website. Ray et al. (2011)
SS2. This tourism product website has a policy on privacy or security.
SS3. I am aware of the details of this tourism product website's privacy or security policy.
Understanding of seals US1. Website assurance seals are designed to increase the privacy/security a customer has for a website. Lowry et al. (2011)
US2. Websites must state how they collect and share data in order to be awarded a website assurance seal.
US3. Third-party organizations assess the business practices of a website before awarding a seal.
US4. You can click on the seal to verify that the website is entitled to display the seal.
US5. A website must display a data privacy and security statement in order to get a seal
Website investment WI1. A lot of time seems to have been invested in developing this website. Ray et al. (2011)
WI2. A lot of effort seems to have been invested in developing this website.
WI3. A lot of money seems to have been invested in developing this website.
a
Reverse scaled.
E. Bons on Ponte et al. / Tourism Management 47 (2015) 286e302 292
and they were also asked to forward the invitation to their friends
and colleagues. An appointment for the computer lab was given to
the participants who answered our email. Additionally, we invited
people randomly selected outside the university to participate.
Those who agreed to participate were given a pen drive with the
university seal. Ahuja, Gupta, and Raman (2003) found that prior to
a purchase individuals tend to visit one to three websites. Conse-
quently, we replicated the work of Kim et al. (2008) by instructing
respondents to select just two or three travel websites from which
to make a purchase decision. The travel websites used were web-
sites through which travelers can purchase travel products such as
hotel bookings, airline tickets, and transportation reservations. As
in the study conducted by Kim et al. (2011), we excluded cruises.
Following the method of Kim et al. (2008), the participants were
instructed, in the computer room, to go through the online pur-
chasing process up to the clicking of the purchase button (this step
was excluded). After sur?ng the websites, they were randomly
assigned to one of two questionnaires: one questionnaire asked
questions about the website from which the participant was less
inclined to make a purchase; and the other questionnaire asked the
same questions but about the website from which the user was
more inclined to make a purchase. Accordingly, we could ensure
that the purchase intention construct had adequate variance,
because we had data to predict both purchases and non-purchases.
Following Hu, Wu, Wu, and Zhang (2010), we checked that all the
participants followed the instructions given in the computer room
with respect to viewing the websites and clicking each button up to
the purchase button. We excluded questionnaires ?lled out in less
than eight minutes because, following Ray et al. (2011), we felt that
the length of the questionnaire meant that this was not possible.
The data was collected fromNovember 2013 to January 2014 in a
computer room under the supervision of two members of the
research team and one graduate student. Fromthe 489 participants
who were recruited, a total of 451 usable questionnaires were ob-
tained. The characteristics of the participants are very similar to
those of the population (Table 3).
4. Data analysis and results
A regression analysis of latent variables is used in this study,
based on the partial least squares (PLS) optimization technique, to
build a model that represents the relationships between the four-
teen proposed constructs measured by many items. The PLS is a
multivariate technique to test structural models (Wold, 1985). It
estimates the model parameters that minimize the residual vari-
ance of the dependent variables of the whole model (Hsu, Chen, &
Hsieh, 2006), it does not require any parametric conditions (Chin,
1998), it is recommended for small samples (Hulland, 1999), and
it is particularly used for complex models, exploratory studies and
prediction (Henseler, Ringle, & Sinkovics, 2009). It is the preferred
algorithm when the study aim is prediction and theory develop-
ment (Ayeh, Au, & Law, 2013; Hair, Ringle, & Sarstedt, 2011). This
paper tries to explore the role of third-party assurance seals and
their related constructs as antecedents of trust, and the role of trust
and perceived value in predicting the intention to purchase travel
online. This is the reason we chose the PLS technique.
The data analysis took place through a two-stage methodology,
as suggested by Gerbing and Anderson (1988), in which the ?rst
stage was to develop and evaluate the measurement model and the
stage second was to develop the full structural equation model.
4.1. Measurement model evaluation
The ?rst step involved establishing the convergent and
discriminate validity of the constructs, and the individual reliability
for each item.
According to Falk and Miller (1992), the convergent validity of
each construct is acceptable for a loading higher than 0.505. The
individual reliability for each item is given by loadings or correla-
tions between the item and the construct. Table 5 indicates the
loadings for each item and the t-values that are signi?cant. They all
comply with the required conditions.
To measure the internal coherence of the indicators in relation
to the constructs, the reliability was calculated, and to verify the
reliability of the indicators, DilloneGoldstein’s rho, also referred to
as the composite reliability coef?cient (Werts, Linn, & J€ oreskog,
1974), and the Cronbach alpha coef?cient (Cronbach, 1970), were
utilized; these range from 0 (no similarities) to 1 (maximum sim-
ilarities). Both parameters are taken into account, as the ?rst con-
cerns the respective indicators while the second assumes the
contribution made by each indicator to be similar. Table 6 repre-
sents the values of each coef?cient. The composite reliabilities are
above the minimum acceptable limit of 0.70 (Gefen, Straub, &
Boudreau, 2000; Nunnally, 1978). The Cronbach alpha coef?cient
levels are also shown in Table 6. They are all above 0.70, which is
recommended for con?rmatory research (Churchill, 1979).
Convergent validity indicates the common variance between
the indicators and their construct. To evaluate this validity, as
suggested by Fornell and Larcker's (1981), each construct's average
variance extracted (AVE) was calculated; the acceptable threshold
should be higher than 0.50. Table 6 represents the AVE scores
achieved for each of the fourteen constructs employed, which in all
cases surpass the minimum desirable value.
In order to con?rm the discriminant validity among the con-
structs, the square root of the AVE must be superior to the
Table 3
Quota sampling method in terms of gender and age.
Sampling (n ¼ 451)
Population
a
(%) Sample (%)
Gender Male 74.1 67.8
Female 25.7 32.2
No answer 0.2 0
Total 100 100
Age in years
This paper proposes a model for the formation of online purchase intention based on perceived value,
trust and the antecedents of perceived security and privacy, using the model proposed by Ray, Ow, and
Kim (2011) extended to cover third-party assurance seals and related constructs, and examines the influence
on trust of consumers' perceived information quality, privacy, and security. A total of 451 individuals
participated in an experiment. The partial least squares technique was applied to data collected
via a questionnaire to test the proposed model. The results indicate that online purchase intention depends
on perceived value and trust. The main predictors of perceived trust are perceived information
quality and perceived security. Consumers' perceived security depends on vendor reputation, website
investment, third-party assurance seals, understanding of third-party seals, privacy and security policies,
familiarity with the website, Internet privacy concerns, and disposition towards third-party certification.
In?uence of trust and perceived value on the intention to purchase
travel online: Integrating the effects of assurance on trust antecedents
Enrique Bons
on Ponte
a, 1
, Elena Carvajal-Trujillo
b, *
, Tom
as Escobar-Rodríguez
a, 2
a
Department of Accounting and Information Systems, University of Huelva, Plaza de la Merced, 21002 Huelva, Spain
b
Department of Business Administration and Marketing, University of Huelva, Plaza de la Merced, 21002 Huelva, Spain
h i g h l i g h t s
We analyze the effects of assurance on trust antecedents in travel website.
Trust depends on perceived information quality and perceived security.
Security is mainly affected by reputation, investment, third-party assurance seals.
Online purchase intention is in?uenced by perceived value and trust.
a r t i c l e i n f o
Article history:
Received 2 April 2014
Accepted 8 October 2014
Available online 30 October 2014
Keywords:
E-commerce
Trust
Assurance
Privacy concerns
Security
Online purchase intention
a b s t r a c t
This paper proposes a model for the formation of online purchase intention based on perceived value,
trust and the antecedents of perceived security and privacy, using the model proposed by Ray, Ow, and
Kim (2011) extended to cover third-party assurance seals and related constructs, and examines the in-
?uence on trust of consumers' perceived information quality, privacy, and security. A total of 451 in-
dividuals participated in an experiment. The partial least squares technique was applied to data collected
via a questionnaire to test the proposed model. The results indicate that online purchase intention de-
pends on perceived value and trust. The main predictors of perceived trust are perceived information
quality and perceived security. Consumers' perceived security depends on vendor reputation, website
investment, third-party assurance seals, understanding of third-party seals, privacy and security policies,
familiarity with the website, Internet privacy concerns, and disposition towards third-party certi?cation.
© 2014 Elsevier Ltd. All rights reserved.
1. Introduction
The Internet and information communication technology are
leading to great developments in the tourism industry (Buhalis &
Law, 2008). The Internet is ideal for the tourism industry because
of the characteristics of tourism products (McCole, 2002): 1) they
are intangible, 2) their production and consumption cannot be
separated, 3) they are perishable, and 4) they are seasonal. More-
over, the Internet is used in the tourismindustry when users search
for information and enter into online transactions (Kim, Chung, &
Lee, 2011). Internet technology allows suppliers of travel products
to sell their products anywhere and at any time (Bernstein & Awe,
1999; Connolly, Olsen, & Moore, 1998; Law & Wong, 2003; Llach,
Mariomon, Alonso-Almeida, & Bernardo, 2013). Online trans-
actions represent a new stage in the tourism industry, which is
working to develop better commercial practices (Kim et al., 2011).
Some of the attributes associated with e-commerce that have
brought about a modi?cation of commercial transactions are con-
venience, economic cost, and product diversity (Yoon, 2002).
Although the number of Internet users has substantially
increased, many users do not make purchases online. They are
reluctant to provide personal information and/or transactional in-
formation for electronic payments online because they do not trust
e-commerce (Kim et al., 2011; Kim, Ferrin, & Rao, 2008). A study of
e-commerce showed that more than 87% of users were concerned
about security and privacy protection in online shopping (Ray, Ow,
&Kim, 2011). In addition, the lack of perceived privacy and security
protection is a major reason why many consumers choose not to
shop online; trust therefore plays a relevant role in online trans-
actions (Kim et al., 2011; Wu & Chang, 2005). In this general
context, previous studies have analyzed trust in e-commerce
* Corresponding author.
E-mail addresses: [email protected] (E. Bons on Ponte), [email protected].
es (E. Carvajal-Trujillo), [email protected] (T. Escobar-Rodríguez).
1
Tel./fax: þ34 959217892x7850.
2
Tel./fax: þ34 959217895x7850.
Contents lists available at ScienceDirect
Tourism Management
j ournal homepage: www. el sevi er. com/ l ocat e/ t ourmanhttp://dx.doi.org/10.1016/j.tourman.2014.10.009
0261-5177/© 2014 Elsevier Ltd. All rights reserved.
Tourism Management 47 (2015) 286e302
together with other factors (Cyr, 2008, 2013; Cyr, Kindra, & Dash,
2008; Harris & Goode, 2004; Jin, Park, & Kim, 2007; Kim et al.,
2008; Kim, Xu, & Gupta, 2012; McKnight & Chervany, 2001; Wu,
Hu, & Wu, 2010). Previous research in e-commerce has examined
the antecedents of perceived privacy and/or perceived security (Li,
2014; Lowry et al., 2011; Ray et al., 2011). Ray et al. (2011), besides
studying these antecedents, analyzed the in?uence of perceived
privacy and security on consumers' perceived trust in online
transactions.
In the tourism context, trust has also been proved to be one of
the most relevant variables that makes e-business successful in the
travel industry (Kim et al., 2011), the accommodation industry
(speci?cally hotels and resorts) (Fam, Foscht, & Collins, 2004), and
the air travel industry, both in general (Kim, Kim, &Shin, 2009) and
for low-cost carriers (LCCs) and in particular (Escobar-Rodríguez &
Carvajal-Trujillo, 2014). Kim et al. (2011) tried to examine the fac-
tors in?uencing trust (navigation functionality, perceived security,
and transaction cost) and the effect of trust and satisfaction on
loyalty in online shopping for travel products in South Korea.
Escobar-Rodríguez and Carvajal-Trujillo (2014) examined the fac-
tors in?uencing the intention to use LCC e-commerce websites to
purchase tickets in Spain, analyzing, among other variables, the
in?uence of perceived privacy, perceived security, and information
quality on consumer trust in the website. Kim et al. (2009) studied
the determinants of e-commerce on airline e-commerce websites,
on the basis of the technology acceptance model (TAM), and trust
and subjective norms in South Korea.
Few studies in the ?eld of tourism and e-commerce analyze the
antecedents of perceived privacy and/or perceived security.
Although studies have examined consumers' perceived value and
purchase intentions (Llach et al., 2013), and their trust and purchase
intentions (Kim et al., 2011), none have examined the effect of
perceived trust on perceived value in the ?eld of e-commerce and
tourism. Furthermore, Kim et al. (2011) noted that there is little
research regarding online consumers' perceived trust in travel
products. In this study, we analyze the antecedents of perceived
security and privacy, extending the model proposed by Ray et al.
(2011) by adding a new factor, consumers' perception of third-
party assurance seals, and two constructs related to this, the
disposition towards third-party certi?cation and the understanding
of third-party seals. In addition, using the model proposed by Kim
et al. (2012), we examine the in?uence of trust on perceived value,
and the in?uence of these two factors on purchase intention.
We have extended the model to include third-party assurance
seals and the related constructs following the recommendations of
€
Ozpolat, Gao, Jank, and Viswanathan (2013); these authors stated
that there are very few studies examining the role of third-party
mechanisms in helping to increase trust in e-commerce, unlike
the position for the third-party certi?cation mechanisms that exist
in of?ine settings. Among the fewstudies that address the issue, Xu,
Teo, Tan, and Agarwal (2010) in the general context, and Lee and
Cranage (2011) in the context of tourism and e-commerce,
concluded that the use of privacy seals, such as TRUSTe, increases
reliability in relation to privacy protection and information
disclosure. Lee and Cranage (2011) analyzed howprivacy assurance
and personalization affect both consumers' perceptions of value
and their privacy concerns, in the context of travel websites. They
found that privacy assurance statements and the use of security
symbols increase perceived privacy protection and perceived trust.
In this study, we used the model proposed by Ray et al. (2011)
for three reasons. First, it presents a current integrated frame-
work to study the in?uence of signals such as third-party assurance
seals on travel websites and the in?uence of different consumer
predispositions on perceived security and privacy protection in
online transactions. Second, Ray et al. (2011) suggest further
research to determine whether the personal predispositions
included, but not found to be signi?cant, in their model, could in-
?uence perceived security and privacy if they are analyzed together
with other predispositions. Third, Ray et al. indicate the need to
research whether signals from websites in?uence online services
other than the general retail websites that they analyze.
With this in mind, this study aims: 1) to examine the in?uence
of perceived trust and perceived value on the intention to use e-
commerce websites when shopping for travel products; 2) to
analyze the in?uence of privacy and security signals and the per-
sonal predispositions of consumers on perceived privacy and
perceived security; and 3) to assess the effect of information
quality, perceived security, and perceived privacy on consumer
trust in a website.
The remainder of the paper is structured as follows. In the next
section, we provide a literature review and propose our working
hypotheses. Following that, we describe the research methodology.
The results are then presented, and ?nally we provide our con-
clusions and the implications for future research.
2. Literature review
2.1. Perceived trust, perceived privacy, perceived security,
information quality, and the relationships between them
Trust in websites plays an important role in e-commerce,
because consumers are unlikely to shop online if they do not trust
the seller's website on which they are shopping (Gefen, 2002;
Jarvenpaa, Tractinsky, Saarinen, & Vitale, 1999; Kim et al., 2008,
2011). Studies have analyzed the factors that can in?uence con-
sumers' perceived trust, and these help tourism product managers
to design their websites in such a way that consumers perceive the
transactions to be reliable. In this research, we examine, in relation
to travel websites, the antecedents of trust that, according to Kim
et al. (2008), are related to consumers' perceptions, such as secu-
rity protection, privacy protection, and the quality of the informa-
tion given on the website. We analyze these factors for travel
websites because only a few previous studies have examined the
antecedents of trust (Escobar-Rodríguez & Carvajal-Trujillo, 2014;
Kim et al., 2008, 2011). Escobar-Rodríguez and Carvajal-Trujillo
(2014) con?rm that previous studies have indicated that these
antecedents are very relevant for e-commerce (Au Yeung & Law,
2003; Flavian & Cuinaliu, 2006; Kim et al., 2011; Wong & Law,
2005). In e-commerce, it is dif?cult to gauge whether online
sellers will meet their commitment to protect the privacy of con-
sumers' personal information (McKnight, Choudhury, & Kacmar,
2002) and/or the security of online transactions (Kim et al.,
2008). Additionally, the content of sellers' websites can affect
consumers' perceived trust (Vila & Kuster, 2011). Hence, it is rele-
vant for online sellers to establish trusted transaction processes so
that consumers place trust in them and consequently form an on-
line purchase intention (Grabosky, 2001).
The de?nition of trust is complicated because it is an abstract
and complex factor. The literature gives various de?nitions of trust
(Corbitt, Thanasankit, & Yi, 2003; Gefen, Karahanna, & Straub,
2003). In the ?eld of e-commerce, according to Pavlou (2003),
trust is the belief that renders consumers vulnerable to the good
faith of online sellers after learning of their characteristics. Gefen
(2000) conceives of trust in a very similar way, as a general belief
in an online seller that results in a behavioral intention. Another
de?nition of trust in this context is provided by Kim et al. (2008);
they de?ne trust as the subjective belief that the online seller will
ful?ll its transactional obligations, as those obligations are under-
stood by the consumer. In this paper, we use this last de?nition.
E. Bons on Ponte et al. / Tourism Management 47 (2015) 286e302 287
The information quality antecedent can be conceived as the
consumers' general perception about the completeness and accu-
racyof the website informationconcerning boththe services offered
and the procedure for carrying out an online purchase transaction
(Kimet al., 2008). Then, depending on the quality of information on
the website, a consumer may perceive that the site is or is not
suitable for making the required online purchase correctly (Kim
et al., 2008). In other words, when various websites contain infor-
mation about similar products, the factor that induces consumers to
opt for one particular website over the rest to make the required
purchase is the quality of the information that the site is perceived
to provide (Raganathan & Ganapathy, 2002). Thus, the greater
consumers' perception that the website of an online seller contains
high-quality information, the more likely they are to think that the
website of the online seller is trustworthy (Kim et al., 2008).
Regarding the perceived security antecedent, this can be de?ned
as the perception of consumers that the online seller has included
the antecedents of security, such as veri?cation, authentication,
encryption, protection, and non-repudiation (Kim et al., 2008).
Chellappa and Pavlou (2002) noted that if consumers perceive that
the website of the online seller offers security factors such as a
security policy, a safe shopping guarantee, and other protection
mechanisms, they will deduce that the online seller guarantees the
security of an online purchase. Thus, the greater consumers'
perception that the website of an online seller guarantees security
during online transactions, the more likely they are to perceive that
the website of the online seller is trustworthy (Kim et al., 2008).
The perceived privacy protection antecedent can be conceptu-
alized as the probability that the online seller will ensure that the
con?dential information about the consumer acquired during the
online transaction is protected against unauthorized disclosure or
use (Kim et al., 2008). During an online transaction, the online
seller requests and collects a large amount of personal information
about the consumer, such as his or her name, home address, phone
number, email address, bank account and credit card details; the
consumer may suspect that the online seller will give or sell this
information to other entities, companies and persons (Kim et al.,
2008). Faced with the possibility of this occurring, the consumer
may decide against purchasing online e the consumer has lacks
con?dence that the online seller will properly protect his or her
privacy.
In the ?eld of e-commerce, Kim et al. (2008) con?rmed the
relationship between information quality, perceived security, and
perceived privacy protection and trust. In the context of tourismand
e-commerce, Escobar-Rodríguez and Carvajal-Trujillo (2014)
examined the effect of information quality, perceived security and
perceived privacy protection on trust. Thus, for travel websites that
sell travel products, information quality, perceived security, and
perceived privacy protectionwill almost certainly affect consumers'
trust.
Based on the previous evidence, we formulate the following
hypotheses for travel websites:
H01. Consumers' perception of the quality of website information
has a positive effect on trust.
H02. Consumers' perception of website security protection has a
positive effect on trust.
H03. Consumers' perception of website protection of privacy has a
positive in?uence on trust.
2.2. Antecedents of perceived privacy and perceived security
Although Ray et al. (2011) examined the factors in?uencing
perceived privacy and perceived security, these factors have not
been analyzed in the ?eld of tourism. We decided to explore the
antecedents of perceived privacy and perceived security in the
?eld of tourism for travel products, because of the great in?uence
of these factors on trust in the sales websites (Kim et al., 2009).
Accordingly, we extend the model proposed by Ray et al. (2011) by
incorporating third-party assurance seals and a couple of related
constructs. Ray et al. (2011), as suggested by Gefen et al. (2003)
and Kim and Benbasat (2003), differentiated the antecedents of
privacy and security in response to the ?ve sources that confer
trust: 1) a consumer's personality; 2) knowledge based on a con-
sumer's prior experiences; 3) institutional assurances from the
online seller; 4) calculative assurances from the online seller; and
5) cognitive assurances from third parties. These ?ve sources are
grouped into two broad components: ?rst, the consumers' indi-
vidual predispositions regarding privacy and security signals; and
second, privacy and security signals according to signaling theory
(Table 1).
The ?rst component, consumers' personal predispositions, re-
fers to the factors that might predispose users to perceive privacy
and security measures on the website of the online seller. Those
factors are relevant because online sellers use a variety of tools to
adhere to privacy and security standards, some of which are quite
technical and are not always perceptible to consumers, such as
encrypted transmissions, ?rewalls, and intrusion detection systems
(Bhimani, 1996; Cavusoglu, Raghunathan, & Cavusoglu, 2009;
Furnell & Karweni, 1999; Ray et al., 2011). Other tools, for
example privacy and security policies, third-party certi?cates, and
the emailing of the proof of purchase are implemented during the
interaction with a user (Ray et al., 2011). Within the ?rst compo-
nent, we added to the two variables considered by Ray et al. (2011)
(Internet privacy and security concerns and familiarity with the
travel website), two others (disposition towards third-party certi-
?cation and understanding of third-party assurance seals). The
Internet privacy concerns and disposition towards third-party
certi?cation factors represent consumers' personality-based trust
sources, because they refer to a consumer's predisposition to trust
others and believe in their good intentions (Gefen et al., 2003; Ray
et al., 2011). On the other hand, familiarity with the website and
understanding of third-party assurance seals are consumers'
knowledge-based trust sources (Table 1), the former because a
consumer's familiarity with a seller's website reduces uncertainty
(Gefen et al., 2003; Kim et al., 2008), and the latter because a
consumer's understanding of the seals displayed on a seller's
website increases his or her trust. Internet privacy concerns refer to
the propensity to be generally concerned about threats to personal
information submitted over the Internet and/or the safety of pay-
ments in online transactions (Dinev &Hart, 2006; Malhotra, Kim, &
Agarwal, 2004; Ray et al., 2011; Sheehan & Hoy, 2000; Smith,
Milberg, & Burke, 1996). According to Ray et al. (2011), familiarity
Table 1
Antecedents of consumers' perceived privacy and security.
Factors Source of trust Origin
Predispositions Internet privacy concern Personality NA
Familiarity with the website Knowledge NA
Disposition to third-party
certi?cation
Personality NA
Understanding of third-party
assurance seals
Knowledge NA
Security
signals
Privacy and security policies Institution First-party
Website investment Calculative First-party
Vendor reputation Cognitive Second-party
Third-party assurance seals Institution Third-party
NA ¼ not available.
E. Bons on Ponte et al. / Tourism Management 47 (2015) 286e302 288
with the website includes the predisposition of consumers to trust
online sellers based on their prior knowledge of those sellers.
The second component proposed by Ray et al. (2011), security/
privacy signals, is based on signaling theory. This theory states that
companies can perform actions and provide cues that give infor-
mation about quality to customers, whether or not these signals are
credible to and interpretable by the customers (Duncan &Moriarty,
1998; Rao, Qu, & Ruekert, 1999; Ray et al., 2011). Within this
component, they include the factors used by online sellers to in-
crease trust by providing institutional, calculative, and cognitive
assurances (Gefen et al., 2003; Ray et al., 2011) (Table 1). These
signals cannot directly in?uence the perceptions of consumers,
because the quality of security and privacy is dif?cult for consumers
to appreciate (Ray et al., 2011). As noted by Wang, Beatty, and Foxx
(2004), online sellers utilize different strategies to signal their
trustworthiness and to ease consumers' concerns over e-commerce
(Wu et al., 2010). Thus, consumers should rely on indirect cues, or
signals, to assess the level of quality (Ray et al., 2011; Zeithaml,
1988). Ray et al. (2011) included three signals from online sellers
that could affect perceived privacy and security: privacy and se-
curity policies, perceived website investment, and the reputation of
the online seller. In our model, we add a fourth signal, third-party
assurance seals. Privacy and security policies are statements pro-
vided by online sellers that supply information and claim that
privacy and security are assured (Kim & Benbasat, 2003; Lowry
et al., 2011; Ray et al., 2011). Schlosser, White, and Lloyd (2006)
refer to the website investment made by the online seller in
terms of the effort, time, and money spent on developing it. This
investment signals the importance of security and privacy protec-
tion for the online seller, because the physical appearance of
products has always been a signal of quality (Dawar &Parker, 1994;
Ray et al., 2011). Privacy and security policies and website in-
vestments are ?rst-hand quality information sources about the
seller's website, provided directly by the online seller (
€
Ozpolat
et al., 2013). Regarding the reputation of the online seller, Ray
et al. (2011) considered that second-party information on sellers
is a signal of quality, indicating privacy and security protection to
consumers (Duncan & Moriarty, 1998; Gefen et al., 2003). The
reputation of the online seller provides quality information about
the seller's website, and is based on the experience of previous
shoppers, that is, a second-party information source (
€
Ozpolat et al.,
2013).
In accordance with the constructs and relationships of the
model proposed by Ray et al. (2011), as well as the previous evi-
dence, we suggest, in the context of tourism and e-commerce for
travel websites, the following hypotheses regarding consumers'
perceived privacy and security:
H04. Internet privacy concern negatively in?uences consumers'
perception of website security protection.
H05. Internet privacy concern negatively in?uences consumers'
perception of website privacy protection.
H06. Familiarity with the seller's website positively in?uences
consumers' perception of website security protection.
H07. Familiarity with the seller's website positively in?uences
consumers' perception of website privacy protection.
H08. Privacy and security policies positively in?uence consumers'
perception of website security protection.
H09. Privacy and security policies positively in?uence consumers'
perception of website privacy protection.
H10. Perceived website investment positively in?uences con-
sumers' perception of website security protection.
H11. Perceived website investment positively in?uences con-
sumers' perception of website privacy protection.
H12. The online seller's reputation positively in?uences con-
sumers' perception of website security protection.
H13. The online seller's reputation positively in?uences con-
sumers' perception of website privacy protection.
2.2.1. Third-party assurance seals
Third-party assurance seals (e.g., TRUSTe, VeriSign, BBBOnline)
provide assurance to consumers that a website follows particular
operating practices, that payments are secure, and/or that the
privacy policy indicates what the seller can and cannot do with
personal data collected online (Kim et al., 2008; Kim, Sivasailam, &
Rao, 2004; Shapiro, 1987). According to
€
Ozpolat et al. (2013),
companies that provide assurance seals examine the website's se-
curity, privacy, and service quality and, if these meet a number of
quality standards, the seller is allowed to display the assurance seal.
McKnight and Chervany (2001) argue that third-party seals are
sources of trust based on institutional assurances (Table 1) and, as
suggested by Jiang, Jones, and Javie (2008) and Kimery and McCord
(2002a), they might increase consumers' perceived security and
privacy.
A number of studies have analyzed the in?uence of third-party
assurance seals on trust, but there is a lack of consensus on this
(
€
Ozpolat et al., 2013). While some studies found a positive in?uence
(Grazioli & Jarvenpaa, 2000; Jiang et al., 2008; Rifon, LaRose, &
Choi, 2005; Yang, Hung, Sung, & Farn, 2006), others did not (Hui,
Teo, & Lee, 2007; Kim et al., 2008; Kimery & McCord, 2002a;
McKnight, Kacmar, & Choudhury, 2004; Metzger, 2006;
Pennington, Wilcox, & Grover, 2003; Yousafzai, Pallister, & Foxall,
2005). On the other hand, very little is known about the effect of
assurance seals on consumers' perceived security and/or privacy,
except for the results of the studies of Kim and Kim (2011), who
found a positive in?uence, and Lowry et al. (2011), who found that
seals fail to increase consumers' perceived privacy. Furthermore, in
the context of tourism and e-commerce, no study has analyzed
either the impact of seals on trust or their impact on consumers'
perceived security and privacy, so our study is the ?rst to address
those issues.
If consumers perceive, by means of signals such as third-party
assurance seals, that the online seller provides security and pri-
vacy protection in online transactions, their perception of uncer-
tainty and online shopping risks should tend to be reduced (Kim &
Benbasat, 2003; Wu et al., 2010). In fact, seals should contribute to
increasing consumers' privacy protection (Hoffman, Novak, &
Peralta, 1999) and/or security protection (Udo, 2001). Thus, for
online shopping for travel products, if third-party assurance seals
are cues for security and privacy protection on the travel websites
of online sellers, it can be hypothesized that displaying these
assurance seals will positively in?uence consumers' perception of
website privacy and security protection. Thus, this study suggests
the following research hypotheses in the context of tourism and e-
commerce for travel products:
H14. The presence of a third-party assurance seal positively in-
?uences consumers' perception of website privacy protection.
H15. The presence of a third-party assurance seal positively in-
?uences consumers' perception of website security protection.
2.2.2. Disposition towards third-party certi?cates
With this construct, we refer to the disposition to trust third-
party certi?cation such as seals. The disposition to trust is de?ned
as a consumer personality trait that shows the degree to which
E. Bons on Ponte et al. / Tourism Management 47 (2015) 286e302 289
consumers are predisposed to perceive others as trustworthy (Jiang
et al., 2008; Kim et al., 2008). This predisposition of consumers is
based on the result of ongoing lifelong experiences with and
knowledge of a certain trusted party (Kim et al., 2008; McKnight,
Cummings, & Chervany, 1998). Therefore, if a consumer has a
high inclination to trust others in general, this disposition is likely
to have a positive in?uence on her or his trust in a particular seller,
and if she or he has a low inclination to trust others in general, she
or he is likely to develop a lower level of trust in a particular seller
(Kim et al., 2008; McKnight et al., 1998). The in?uence of the
disposition to trust on trust has been studied in the general liter-
ature (Kim et al., 2008; Kimery & McCord, 2002a; Mayer, Davis, &
Schoorman, 1995; Wu et al., 2010). Jiang et al. (2008) proposed
that the disposition to trust third-party certi?cation has an in?u-
ence on the perception of the identifying logos for third-party
certi?cation, and that this factor has an in?uence on online
seller trust. The disposition to trust third-party certi?cation is
de?ned as the tendency to depend on third parties for trustworthy
information during online transactions. If consumers have a high
tendency to trust third-party certi?cation, such as security and
privacy protection assurances, this disposition is likely to have a
positive effect on her or his perception of the privacy and security of
the online seller. As noted by Wu et al. (2010), consumers with a
higher disposition to trust are more credulous (Gefen, 2000), and
they are more likely to trust online sellers displaying third-party
assurance seals, increasing their perception of website security
and privacy protection (Wu et al., 2010). Thus, for travel e-com-
merce websites for the purchase of travel products, consumers'
disposition to trust third-party certi?cation will almost certainly
in?uence their trust in those websites. In this study, it is hypothe-
sized that security and privacy protection will be related to the
disposition towards third-party certi?cation in tourism e-com-
merce products, as follows:
H16. Consumers' disposition towards third-party certi?cation
positively affects their perception of website security protection.
H17. Consumers' disposition towards third-party certi?cation
positively affects their perception of website privacy protection.
2.2.3. Understanding of third-party assurance seals
Lowry et al. (2011) suggested that an understanding of third-
party assurance seals indicates that the consumer knows that his/
her data are protected. Online sellers display third-party assurance
seals on their websites to increase consumers' perception of web-
site security and privacy protection; however, if the consumers do
not understand the seals, it is useless to display them. In fact,
McKnight et al. (2004) and Moores (2005) highlighted the fact that
third-party assurance seals fail because consumers do not under-
stand their forms or function; hence, it is necessary to study con-
sumers' understanding of the seals. This factor was analyzed by
Lowry et al. (2011), who also considered that the use of a third-
party privacy assurance seal will not be effective if consumers do
not understand it. In the context of tourism and e-commerce, it is
also relevant that consumers understand the seals if they are to be
useful. Given the relevance of the consumers' understanding of the
seals for shopping for travel products, we propose the following
research hypotheses:
H18. Consumers' understanding of third-party assurance seals
positively in?uences their perception of website security
protection.
H19. Consumers' understanding of third-party assurance seals
positively in?uences their perception of website privacy protection.
2.3. Perceived value, perceived trust, purchase intention, and the
relationships between them
On the basis of prospect theory (Kahneman & Tversky, 1979;
Wang & Wang, 2010), we assume in this research that an overall
judgment of value in?uences the online purchase intention. In the
e-commerce context, perceived value can be de?ned as the con-
sumer's assessment of bene?ts against costs when shopping with
an online seller (Zeithaml, 1988). Consequently, the perceived
value of a transaction with an online seller is the net bene?t (Kim
et al., 2012; Seddon, 1997). Obviously, consumers wish to shop for
products with those vendors who offer maximumvalue (Kim et al.,
2012; Wang & Wang, 2010; Zeithaml, 1988). In fact, the literature
has shown that the perceived value of a product in?uences the
purchase intention (Chang & Wildt, 1994; Dodds, Monroe, &
Grewal, 1991). In the e-commerce context, studies have
con?rmed the relationship between perceived value and purchase
intention (Chang & Wang, 2011; Fuentes-Blasco, Gil-Saura,
Berenguer-Contrí, & Moliner-Velazquez, 2010; Kim et al., 2012;
Wu, Chen, Chen, & Cheng, 2014). In the tourism e-commerce ?eld,
Llach et al. (2013) examined the in?uence of perceived value on
intention in the purchasing of airline tickets, concluding that the
effect is signi?cant and positive. Thus, this study proposes
the following hypothesis regarding online shopping for travel
products:
H20. Perceived value on a website positively in?uences the online
purchase intention.
According to Kim et al. (2012), if consumers have trust in an
online seller, they expend less effort on searching for information
about the online seller and on executing the online transaction.
Perceived trust can decrease the transaction's non-monetary cost;
this cost incorporates variables such as the time and effort
required to choose an online seller (Chiles & McMackin, 1996) and
the perceived risk of online shopping (Jarvenpaa, Tractinsky, &
Vitale, 2000; Kim et al., 2012). As perceived trust reduces the
non-monetary cost, it raises the perceived value when shopping
online on a seller's website (Kim et al., 2012). Only Kim et al.
(2012), in the e-commerce context, have examined the in?uence
of perceived trust on perceived value, and they con?rmed this
in?uence. There is no study examining this relationship in the ?eld
of tourism and e-commerce. For our research, for shopping online
for travel products, consumers' perceived trust in travel websites
will reduce the non-monetary cost and this will raise the
perceived value of the online shopping. In our study, we hypoth-
esize that perceived trust has an in?uence on perceived value as
follows:
H21. Trust in an online seller positively affects the perceived value
for customers.
In the e-commerce ?eld, several previous studies have
con?rmed the relationship between trust and the intention to
purchase online (Chiu, Huang, & Hui, 2010; Gefen et al., 2003;
Grazioli & Jarvenpaa, 2000; Jarvenpaa et al., 2000; Kim et al.,
2008, 2012). In the ?eld of tourism and e-commerce, this rela-
tionship has also been analyzed, and the conclusion has been
reached that the in?uence is signi?cant and positive (Bign e, Sanz,
Ruiz, & Ald as, 2010; Escobar-Rodríguez & Carvajal-Trujillo, 2014;
Kamarulzaman, 2007; Kim et al., 2009, 2011; Sanz-Blas, Ruiz-Maf e,
& P erez P erez, 2014; Wen, 2009, 2010). Thus, for online shopping
for travel products, we hypothesize:
H22. Trust positively affects the online purchase intention.
Fig. 1 graphically represents the different research hypotheses.
E. Bons on Ponte et al. / Tourism Management 47 (2015) 286e302 290
3. Methodology
3.1. Measurements
A set of measurement items was adapted to the speci?c context
of this research, and a total of 55 items was obtained. In Table 2, we
present the complete list of items, which were measured by means
of multi-item scales, for the constructs taken into account in this
research. The responses of the survey participants to each of the
items were measured on a seven-point Likert scale, ranging from 1
(¼ “strongly disagree”) to 7 (¼ “strongly agree”). This is the usual
way of measuring variables that are not directly quanti?able or
observed (Churchill & Iacobucci, 2002).
The items in the questionnaire were validated on the basis of the
opinions of a focus group of e-commerce and e-tourism academics
and professionals, who were asked whether the items were
appropriate for the purpose of evaluating e-commerce and trust.
The focus group's opinions led us to modify some items to make the
meanings clearer. A pre-test was carried out on 40 individuals of
different ages and genders, selected by quota and convenience
sampling, who had purchased travel products on a website in the
past year. This ensured that those individuals who had not pur-
chased travel products in the past year were dropped from the pre-
test. Using the feedback from this pre-test, modi?cations were
made to the wording of some items to increase the clarity further,
but these were only minor. A ?nal questionnaire was created and
administered to 30 individuals of different genders and ages,
selected by quota and convenience sampling, who had purchased
travel products on a website in the past year. The clarity of the
questionnaire was thus con?rmed, and no more changes were
made to it.
The questionnaire was originally drafted in English, but it was
intended for use in Spanish for consumers from Spain who had
experience of purchasing tourism products on websites. Therefore,
the English questionnaire was translated into Spanish by a
professional native English translator and by researchers, working
independently. After a careful analysis of the differences between
these independently translated questionnaires, a de?nitive version
of the Spanish questionnaire was agreed. This ?nal version was
then translated back into English by another native English pro-
fessional translator to ensure consistency between the English and
the Spanish version of the questionnaire (Brislin, 1970). Table 2
shows the items for this study and the supporting literature for
each construct.
3.2. Sample and data collection
This study used quota and convenience sampling. The conve-
nience sampling method was utilized because the population size
is unknown for this study (San Martín & Herrero, 2012). The quota
sampling method was employed to match the target population
structure in both age and gender (Kimet al., 2009, 2011; San Martín
& Herrero, 2012). To calculate the number of participants that
would be suf?cient in each age and gender category, population
data were obtained from the 15th Internet users survey (AIMC,
2013), a study carried out by the Asociaci on para la Investigaci on
de Medios de Comunicaci on (Table 3). Afterwards, to combine the
diverse quotas, convenience sampling was carried out (San Martín
& Herrero, 2012). Males and females are represented as follows:
67.8% and 32.2%, respectively. The age groups constitute the
following: 5.8% aged under 20 years; 13.7% aged 20e24; 31.7% aged
25e34; 36.4% aged 35e44; 8.9% aged 45e54; 3.1% aged 55e64; and
0.4% aged 64 and over. Table 4 shows the data on the gender and
age of the participants. There were more males (67.8%) than fe-
males (32.2%). The largest proportion of the respondents (36.4%)
were aged between 35 and 44, followed by those aged between 25
and 34 (31.7%).
The participants were recruited by email among the community
of our university. We emailed an invitation to participate in our
research to current students, alumni, faculty members, and staff,
Fig. 1. Proposed model.
E. Bons on Ponte et al. / Tourism Management 47 (2015) 286e302 291
Table 2
Construct measurement.
Construct Item Supporting literature
Third-party assurance seal AS1. The third-party assurance seals on this website make me feel more comfortable. Cyr (2013)
Kim et al. (2008) AS2. The third-party assurance seals on this website make me feel more secure in terms of privacy.
AS3. Third-party assurance seals on this website make me feel safer in terms of the transaction.
AS4. The third party assurance seals on this website make me feel this website is secure.
Purchase intention BI1. The probability that I would consider to purchase a tourism product from this website is high. Kim et al. (2012)
BI2. If I were to purchase a tourism product, I would consider purchasing it from this website.
BI3. The likelihood of my purchasing a tourism product from this website is high.
BI4. My willingness to purchase a tourism product from this website is high.
Disposition to third-party
certi?cation
DC1. I speci?cally look for third-party certi?cation symbols. Jiang et al. (2008)
DC2. I generally have faith in third-party certi?cation.
DC3. I generally trust third parties.
Familiarity with the
website
FA1. I am familiar with this tourism product shopping website. Chiu, Hsu, Lai, and
Chang (2012) FA2. I am familiar with the processes of purchasing products from this tourism product shopping website.
FA3. I am familiar with searching for products at this tourism product shopping website.
Information quality IQ1. The tourism product website provides accurate information about the tourism product that
I want to purchase.
Kuan et al. (2008)
IQ2. The tourism product website provides suf?cient information when I try to make a transaction.
IQ3. The tourism product website provides enough depth of information about its products.
IQ4. The information provided by tourism product website is helpful to me in purchasing tourism products.
IQ5. The information in the tourism product website is clear for me to make a purchase.
IQ6. The tourism product website provides up-to-date information.
Internet privacy concerns PC1. Compared with other subjects on my mind, online privacy/security is very important. Ray et al. (2011)
PC2. I am concerned about threats to online privacy/security today.
PC3. The greater my interest to obtain a certain service or product from the Internet, the more
I tend to suppress my privacy/security concerns.
Perceived value PV1. Considering the money I pay to purchase tourism products on this website, online shopping
here is a good deal.
Kim et al. (2012)
PV2. Considering the effort I make in shopping on this website, online shopping here is worthwhile.
PV3. Considering the risk involved in shopping on this website, online shopping here is of value.
PV4. Overall, online shopping on this website delivers me good value.
Vendor reputation REP1. This company is well known. Ray et al. (2011)
REP2. This company has a good reputation.
REP3. This company has a good reputation in its market.
Trust PT1. This tourism product website has integrity. Kim et al. (2011)
PT2. This tourism product website is reliable.
PT3. This tourism product website is trustworthy.
Perceived privacy
a
PP1. I am concerned that tourism product website collects too much personal information from me. Kim et al. (2008)
PP2. I am concerned that the tourism product website will use my personal information for other
purposes
without my authorization.
PP3. I am concerned the tourism product website will share my personal information with other entities
without my authorization.
PP4. I am concerned that unauthorized persons (i.e. hackers) have access to my personal information.
PP5. I am concerned about the privacy of my personal information during a transaction.
PP6. I am concerned that the tourism product website will sell my personal information to others without
my permission.
Perceived security PS1. The tourism product website implements security measures to protect users. Kim et al. (2008)
PS2. The tourism product website usually ensures that transactional information is protected from
accidentally being altered or destroyed during a transmission on the Internet.
PS3. I feel secure about the electronic payment system of the tourism product website.
PS4. I am willing to use my credit card on this website to make a purchase.
PS5. I feel safe in making transactions on this website.
Privacy and security policy SS1. The availability of a privacy or a security statement was easily seen on the tourism product website. Ray et al. (2011)
SS2. This tourism product website has a policy on privacy or security.
SS3. I am aware of the details of this tourism product website's privacy or security policy.
Understanding of seals US1. Website assurance seals are designed to increase the privacy/security a customer has for a website. Lowry et al. (2011)
US2. Websites must state how they collect and share data in order to be awarded a website assurance seal.
US3. Third-party organizations assess the business practices of a website before awarding a seal.
US4. You can click on the seal to verify that the website is entitled to display the seal.
US5. A website must display a data privacy and security statement in order to get a seal
Website investment WI1. A lot of time seems to have been invested in developing this website. Ray et al. (2011)
WI2. A lot of effort seems to have been invested in developing this website.
WI3. A lot of money seems to have been invested in developing this website.
a
Reverse scaled.
E. Bons on Ponte et al. / Tourism Management 47 (2015) 286e302 292
and they were also asked to forward the invitation to their friends
and colleagues. An appointment for the computer lab was given to
the participants who answered our email. Additionally, we invited
people randomly selected outside the university to participate.
Those who agreed to participate were given a pen drive with the
university seal. Ahuja, Gupta, and Raman (2003) found that prior to
a purchase individuals tend to visit one to three websites. Conse-
quently, we replicated the work of Kim et al. (2008) by instructing
respondents to select just two or three travel websites from which
to make a purchase decision. The travel websites used were web-
sites through which travelers can purchase travel products such as
hotel bookings, airline tickets, and transportation reservations. As
in the study conducted by Kim et al. (2011), we excluded cruises.
Following the method of Kim et al. (2008), the participants were
instructed, in the computer room, to go through the online pur-
chasing process up to the clicking of the purchase button (this step
was excluded). After sur?ng the websites, they were randomly
assigned to one of two questionnaires: one questionnaire asked
questions about the website from which the participant was less
inclined to make a purchase; and the other questionnaire asked the
same questions but about the website from which the user was
more inclined to make a purchase. Accordingly, we could ensure
that the purchase intention construct had adequate variance,
because we had data to predict both purchases and non-purchases.
Following Hu, Wu, Wu, and Zhang (2010), we checked that all the
participants followed the instructions given in the computer room
with respect to viewing the websites and clicking each button up to
the purchase button. We excluded questionnaires ?lled out in less
than eight minutes because, following Ray et al. (2011), we felt that
the length of the questionnaire meant that this was not possible.
The data was collected fromNovember 2013 to January 2014 in a
computer room under the supervision of two members of the
research team and one graduate student. Fromthe 489 participants
who were recruited, a total of 451 usable questionnaires were ob-
tained. The characteristics of the participants are very similar to
those of the population (Table 3).
4. Data analysis and results
A regression analysis of latent variables is used in this study,
based on the partial least squares (PLS) optimization technique, to
build a model that represents the relationships between the four-
teen proposed constructs measured by many items. The PLS is a
multivariate technique to test structural models (Wold, 1985). It
estimates the model parameters that minimize the residual vari-
ance of the dependent variables of the whole model (Hsu, Chen, &
Hsieh, 2006), it does not require any parametric conditions (Chin,
1998), it is recommended for small samples (Hulland, 1999), and
it is particularly used for complex models, exploratory studies and
prediction (Henseler, Ringle, & Sinkovics, 2009). It is the preferred
algorithm when the study aim is prediction and theory develop-
ment (Ayeh, Au, & Law, 2013; Hair, Ringle, & Sarstedt, 2011). This
paper tries to explore the role of third-party assurance seals and
their related constructs as antecedents of trust, and the role of trust
and perceived value in predicting the intention to purchase travel
online. This is the reason we chose the PLS technique.
The data analysis took place through a two-stage methodology,
as suggested by Gerbing and Anderson (1988), in which the ?rst
stage was to develop and evaluate the measurement model and the
stage second was to develop the full structural equation model.
4.1. Measurement model evaluation
The ?rst step involved establishing the convergent and
discriminate validity of the constructs, and the individual reliability
for each item.
According to Falk and Miller (1992), the convergent validity of
each construct is acceptable for a loading higher than 0.505. The
individual reliability for each item is given by loadings or correla-
tions between the item and the construct. Table 5 indicates the
loadings for each item and the t-values that are signi?cant. They all
comply with the required conditions.
To measure the internal coherence of the indicators in relation
to the constructs, the reliability was calculated, and to verify the
reliability of the indicators, DilloneGoldstein’s rho, also referred to
as the composite reliability coef?cient (Werts, Linn, & J€ oreskog,
1974), and the Cronbach alpha coef?cient (Cronbach, 1970), were
utilized; these range from 0 (no similarities) to 1 (maximum sim-
ilarities). Both parameters are taken into account, as the ?rst con-
cerns the respective indicators while the second assumes the
contribution made by each indicator to be similar. Table 6 repre-
sents the values of each coef?cient. The composite reliabilities are
above the minimum acceptable limit of 0.70 (Gefen, Straub, &
Boudreau, 2000; Nunnally, 1978). The Cronbach alpha coef?cient
levels are also shown in Table 6. They are all above 0.70, which is
recommended for con?rmatory research (Churchill, 1979).
Convergent validity indicates the common variance between
the indicators and their construct. To evaluate this validity, as
suggested by Fornell and Larcker's (1981), each construct's average
variance extracted (AVE) was calculated; the acceptable threshold
should be higher than 0.50. Table 6 represents the AVE scores
achieved for each of the fourteen constructs employed, which in all
cases surpass the minimum desirable value.
In order to con?rm the discriminant validity among the con-
structs, the square root of the AVE must be superior to the
Table 3
Quota sampling method in terms of gender and age.
Sampling (n ¼ 451)
Population
a
(%) Sample (%)
Gender Male 74.1 67.8
Female 25.7 32.2
No answer 0.2 0
Total 100 100
Age in years