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nt. J. Internet Marketing and Advertising, Vol. 8, No. 4, 2014
Copyright © 2014 Inderscience Enterprises Ltd.
Conceptualising and modelling virtual product
experience for online retailers
Raed S. Algharabat
Department of Marketing,
School of Business,
The University of Jordan,
Amman 11942, Jordan
Abstract: This study aims to define and conceptualise three-dimensional (3D)
virtual product experience (VPE) for online retailers. Therefore, this research
designed a hypothetical retailer website, which presents a variety of 3D laptop
and ring sites that allow participants to control the content and form of the 3D
flashes. This research finds that the measurement of VPE should be based on a
multi-dimensional construct rather than a unidimensional one. In other words,
this research finds that defining and operationalising VPE should be based on
the authenticity, perceived diagnosticity, compatibility, flow and enjoyment
aspects of the 3D product. Results show positive relationships among VPE,
attitude to the product and purchase intention.
Keywords: 3D virtual experience; authenticity; diagnosticity; compatibility;
flow; enjoyment; attitude toward product; purchase intention.
Reference to this paper should be made as follows: Algharabat, R.S. (2014)
‘Conceptualising and modelling virtual product experience for online retailers’,
Int. J. Internet Marketing and Advertising, Vol. 8, No. 4, pp.300–319.
Biographical notes: Raed S. Algharabat received a PhD from Brunel
University, UK. He is an Associate Professor of Marketing at the Marketing
Department, University of Jordan, Amman, Jordan. His teaching and areas of
interest include: e-marketing (e-)retail and consumer behaviour, the vital, final
link of the marketing process for satisfying the end consumer, particularly, 3D
virtual models and their impact on consumer behaviour within the online
retailer context. He has published a few papers in reputed journals of
marketing. He received best paper awards for papers related to e-marketing.
Online customer experience considers one of the main elements of determining the scope
of e-marketing. According to Rafi et al. (2005), online customer experience often
enhances the way that users feel, think and do. The authors posit that designing a website
should be centred on three stages; functionality, intimacy and evangelism. Furthermore,
the authors state that websites which provide customers with the ability to customise and
personalise their product online, using three-dimensional (3D) product presentation, often
enhance customer experience.
online retailers 301
The significance of investigating virtual product experience (VPE) lies in its ability
to simulate the conventional in-store experience (Algharabat and Dennis, 2010a, 2012;
Kempf and Smith 1998). Furthermore, interacting with 3D product presentation, as a
main type of VPE, on online retailers’ websites enables potential customers to experience
products virtually (Algharabat and Shatnawi, 2014; Jiang and Benbasat, 2005), enhances
their feeling (Algharabat and Abu-ElSamen, 2013; Algharabat and Dennis, 2010a, 2010b,
2010c; Klein, 2003; Li et al., 2001, 2002, 2003), conveys relevant information (Jiang and
Benbasat, 2005) and boosts customers’ understanding and evaluation of the quality and
performance of products sold online (Algharabat and Zamil, 2013; Jiang and Benbasat,
However, we noticed that, in the area of 3D product presentation, previous research
has defined and conceptualised VPE based on two approaches. The first one focuses on
online product experience and uses terminologies such as authenticity, which reflects
users’ physical experience (Algharabat and Dennis, 2010a, 2010b), perceived
diagnosticity (PD), which represents consumers’ belief that VPE is helpful for evaluating
products’ quality and performance (Jiang and Benbasat, 2005), compatibility, which
reflects the consistency of VPE with consumers’ existing shopping habits, product
evaluation styles and past experiences (Jiang and Benbasat, 2005) and telepresence,
which stimulates customers’ ability to be transformed into another area (Klein, 2003; Suh
and Lee, 2005). Meanwhile, the second approach centres on the overall online experience
and utilises notions such as flow, which is related to time distortion (Hoffman and Novak,
1996) and enjoyment (Li et al., 2001).
Even though we respect previous attempts (Algharabat and Dennis, 2010a; Jiang
and Benbasat, 2005, 2007; Kim and Forsythe, 2007, 2008; Li et al., 2003; Suh and
Lee, 2005) to define and conceptualise VPE, based on a unidimensional aspect, yet
we think that previous research did not get the chance to have a comprehensive
definition of VPE. Therefore, previous research described VPE characteristics without
attempting to link them together. For example, Jiang and Benbasat (2005, 2007)
found that VPE technology composed of two factors; diagnosticity and compatibility.
However, the authors did not clearly state how these two types might impact online
customers’ experience. Li et al. (2001) have explored the impact of two-dimensional
(2D) versus three-dimensional (3D) representations on the creation of VPEs.
Furthermore the authors employed a qualitative study, using protocol analysis;
the authors defined five critical characteristics of virtual experiences resulting
from exposure to 3D product representations. However, the authors were not able
to establish any causal linkages with this methodology. Algharabat and Dennis
(2010a) define VPE based on the authenticity of the 3D product presentation. However,
the authors did not test the impact of diagnosticity, compatibility, flow and enjoyment as
elements of VPE. Novak et al. (2000) define VPE based on the notion of flow; however,
the authors’ study probed broad experiences of flow, rather than specific product
To that end, we noticed that previous research on this area has employed individual
constructs to measure VPE. Nevertheless, the main dimensions of VPE are still
questionable. For example, should researchers depend solely on notions such as PD,
authenticity, compatibility, telepresence, flow and enjoyment to measure VPE or should
they use a combination of them? The aim of this paper is to answer this question
empirically. Therefore, based on the prior classifications of VPE, this research defines
VPE ‘as a virtual online experience that users can have while navigating a 3D product
presentation, which aims to simulate direct product experiences (i.e., conventional
in-store experience) and often enhances diagnosticity, authenticity, compatibility, flow
and enjoyment’. This proposed definition has not been examined in the previous research
and we therefore expect that measuring VPE based on this issue will be the contribution
of this research.
2 Research model and hypotheses
2.1 Virtual product experience
As a result of the interaction between a product or an environment and an individual,
researchers (Li et al., 2001, 2002, 2003) classify product experiences into three types.
The first is physical (direct) experience, which permits consumers to interact directly
with the presented products. The second is an indirect product experience that often
allows consumers to interact with second-hand sources such as static visual pictures. The
third is VPE, which allows consumers to interact directly with 3D virtual models.
Furthermore, physical experience and VPE combine within virtual reality, such that the
latter enhances and enriches product experience because consumers use almost all of their
senses when interacting with 3D product presentation (Algharabat and Dennis, 2010a;
Klein, 2003; Li et al., 2001, 2002, 2003; Jiang and Benbasat 2005, 2007). A 3D product
presentation enables consumers to interact with products and creates a sense of being in a
simulated real world (Algharabat, 2014; Algharabat and Abu-ElSamen, 2013; Algharabat
and Zamil, 2013).
2.2 Dimensions of the VPE
This study believes that, for a VPE to represent a direct product experience, the virtual
experience should reflect genuine dimensions that will help users to imagine the
illustrated product properly. Previous research on VPE (Algharabat and Dennis, 2010a;
Jiang and Benbasat 2005, 2007; Kim and Forsythe, 2007, 2008; Li et al., 2003; Suh and
Lee, 2005) defines and conceptualises VPE based on one of the following constructs: PD,
authenticity, compatibility, flow and enjoyment. However, none of the above research
tries to combine PD, authenticity, compatibility, flow and enjoyment constructs to
produce a combined scale which can be used in the area of e-marketing. Therefore, we
suggest the following combined VPE scale, a second-order (Figure 1). The suggested
scale is expected to enhance readers’ understanding of this notion. Furthermore, we used
the combined scale to examine the relationships among VPE, attitude to the product and
purchase intention (PI) (Figure 2).
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Figure 1 Users’ VPE combined scale: a second order CFA
Figure 2 Conceptual framework
3D virtual product
2.3 Perceived diagnosticity
For a product to be simulated and experienced virtually, it should reflect the diagnosticity
of the offline experience. Based on the direct product experience, Kempf and Smith
(1998) have used the concept of PD to represent the extent to which consumers believe
that a particular experience is helpful for evaluating products’ quality and performance.
In the context of online retailers, Jiang and Benbasat (2005, p.117) adopted the notion of
PD (Kempf and Smith, 1998) and implemented it to measure VPE. The authors assert
that the concept of PD reflects the perceived ability of a web interface to convey to
customers relevant product information that helps them in understanding and evaluating
the quality and performance of products sold online. Jiang and Benbasat (2005) posit that
virtual control (consumers’ ability to manipulate web product images, to view products
from various angles and distances) and functional control (consumers’ ability to explore
and experience different features and functions of products) are the main determinants of
PD. Therefore, users can exert a high level of control while examining the product
virtually. Control levels often add an opportunity for users to customise information flow
(Taylor, 2009) and to obtain the relevant information (Liu and Shrum, 2002; Truong
et al., 2010). Jiang and Benbasat (2005) assert that PD is the main determinant for VPE.
Therefore, in order to have a VPE, users must believe that using 3D presentation will
help them to evaluate products’ quality and performance.
2.4 3D authenticity
Algharabat and Dennis (2010a) noticed that none of the previous definitions of VPE that
use 3D virtual models realistically reflects products’ virtual experience. The authors
argue that a 3D virtual experience should be an authentic representation of the physical
experience. Furthermore, the authors introduce a new notion that relates to the simulation
of VPE, namely, the authenticity of the 3D product presentation. The authors argue that
previous definitions that focus on mind transportation (i.e., telepresence and presence) are
not particularly well suited to defining VPE because they reflect lack of reality.
Therefore, Algharabat and Dennis (2010a, 2010b) define and conceptualise VPE based
on the authenticity of 3D product presentation. The authors argue that 3D authenticity is
the basis for measuring VPE, which often aids customers’ affective and cognitive
responses toward the presented products. Algharabat and Dennis (2010a, p.101) define
the authenticity of the 3D product as ‘a psychological state in which virtual objects
presented in 3D in a computer-mediated environment are perceived as actual objects’.
Furthermore, the authors identify users’ ability to control the content and form of the 3D
flash (interactivity) and their ability to see the products with their chosen colours
(vividness) as the main antecedents of 3D authenticity. In the same context, Algharabat
and Abu-ElSamen (2013, p.264) define 3D VPE as a ‘psychological state in which virtual
objects presented in 3D are perceived by consumers as actual objects, which convey to
customers relevant product information that helps them in understanding and evaluating
the quality and performance of products sold online’. The authors assert that authenticity
of the 3D product is the main determinant for VPE. Therefore, in order to have a VPE,
users must believe that using 3D presentation will help them to perceive the presented
products as actual objects that they can find and with which they can interact.
Jiang and Benbasat (2007, p.457) relied on previous studies (Moore and Benbasat, 1991;
Jarvenpaa and Todd, 1996–1997) and defined compatibility as ‘the extent to which
consumers believe their online shopping experience is consistent with their existing
shopping habits, product evaluation styles and past experiences in physical shopping
environments’. Advanced technologies, such as 3D product presentations, often provide
online retailers 305
customers with VPE, which is compatible with their physical product experience
(Peterson et al., 1997). The importance of compatibility clearly appears on the surface
whenever online product experiences are insufficient to enable consumers to evaluate
product quality. In the same context, Peterson et al. (1997) suggested that more advanced
technologies, such as 3D product presentation, are needed to provide customers with
product experiences that are similar to or compatible with their physical product
experiences. Prior research (Jiang and Benbasat, 2005, 2007) has revealed that 3D
presentations can portray products more concretely and convey more information cues
than pallid presentation formats, because 3D technology involves non-verbal language
and multiple sensory channels (Lim et al., 2000). Therefore, the more compatible a 3D
presentation with users’ past experience, the richer the product information exposed to
consumers (Jiang and Benbasat, 2007). Jiang and Benbasat (2007) assert that
compatibility of the 3D product presentation is the main determinant for VPE. Therefore,
in order to have a VPE, users must believe in the authentic nature of the 3D product and,
hence, that using 3D presentation will help them to experience the presented products in a
similar way to their physical product experiences.
Previous research (Csikszentmihalyi, 1990; Lin et al., 2008; Novak et al., 2000; Pace,
2004) has focused on the notion of flow experience. For example, Csikszentmihalyi
(1990) defines flow as a state of consciousness that is sometimes experienced by people
who are deeply involved in an enjoyable activity [as cited in Lin et al., (2008), p.42].
Further, Csikszentmihalyi (1990) posits that the notion of flow often creates a state of
involvement in a certain activity where people will focus only on such activity and
nothing else seems to matter. Novak et al. (2000) studied online consumer experience
through a large-scale survey asking individuals to retrospectively evaluate their
experiences on the web in order to investigate the antecedents and consequences of flow.
Thus, the authors identified both virtual control and telepresence as the main antecedents
to consumers’ flow, which the authors consider to be the basis for online customer
experience. Pace (2004) presented a grounded theory of the flow experiences of web
users engaged in information-seeking activities. The author asserted the following
characteristics of flow:
1 curiosity and interest
2 losing a sense of time and external surroundings.
Hoffman and Novak (1996, p.57) define flow as ‘the state occurring during network
navigation which is:
1 characterised by a seamless sequence of responses facilitated by machine
2 intrinsically enjoyable
3 accompanied by a loss of self-consciousness
Furthermore, Novak et al. (2000) have found that flow is a key component for compelling
an online shopping experience. Flow experience has been widely used in online
environments. Previous studies posit the significant role that flow experience plays in
determining users’ online behaviour in many areas such as online banking (Lee et al.,
2007), online games (Lee and Tsai, 2010) and mobile instant messaging (Zhou and Lu,
Previous scholarly literature (e.g., Novak et al., 2000) posits that flow experience is
characterised by focused attention, complete involvement and an intrinsically enjoyable
experience. However, focused attention and complete involvement results in time
distortion. Previous research (Ghani and Deshpande, 1994; Hoffman and Novak, 1996;
Novak et al., 2000) focused on two dimensions to measure flow experience; enjoyment
and time distortion. However, Lin et al. (2008) and Pace (2004) noted that flow should
not be considered as the general concept of enjoyment. The authors state that flow could
be regarded as an extreme form of enjoyment and it is a more restricted concept than
enjoyment. The authors posit that enjoyment experience is broader than flow because
customers can have enjoyable experiences without being in flow. Therefore, In order to
have a VPE, users must believe that using a 3D presentation will generate a state flow.
Shih (1998) posits that enjoyment, play and fun are the main consequences of using 3D
product presentation. Li et al. (2003) suggest that 3D product presentation can strongly
impact users’ affective evaluation, which refers to users’ feelings of pleasure and fun.
Kim and Forsythe (2007) find that 3D product presentation provides participants with
hedonic benefits. Kim and Forsythe’s (2008) empirical result reveals that users’ ability to
rotate a product using the technology of 3D often enhances their hedonic values. In the
same context, Lee et al. (2006) find significant indirect effects of the 3D product
presentation on attitude and behavioural intention toward online retailers mediated by the
direct effects of TAM’s perceived usefulness, perceived ease of use and perceived
enjoyment. In the same context, Algharabat and Abu-ElSamen (2013) investigate the
effects of 3D product presentation on online diamond ring customers. The authors find
that 3D product presentation has a significant impact on enjoyment. Therefore, In order
to have a VPE, users must believe that using a 3D presentation will generate enjoyment.
2.8 VPE, attitude toward the product and PI
Attitudes toward products refer to consumers’ overall evaluations of products [Jiang and
Benbasat (2005), p.460]. If consumers believe that a 3D product presentation is authentic
and diagnostic to their offline experience (the direct experience), consumers’ beliefs
about the online products’ attributes will be stronger (Kempf and Smith, 1998) and they
will have more confidence in their own evaluations of product attributes (Smith and
Swinyard, 1983; Smith, 1993). As a result, consumers will perceive product information
thoroughly and favourably. For example, Algharabat and Abu-ElSamen’s (2013) results
reveal that 3D product presentation has a positive influence on attitude toward the
presented products. Li et al. (2003) posit that users’ ability to interact with 3D through
rotating, customising and zooming in or out on the product has a positive influence on
online retailers 307
brand attitudes and PI. Suh and Lee (2005) reported that a 3D product presentation has a
strong relationship with product knowledge, product attitude and PIs. Fiore and Jin’s
(2003) study reveals that using a highly interactive 3D product presentation has a positive
influence on customers’ attitude. Hopkins et al. (2004) state the importance of the new
technology in influencing attitude toward the advert, the brand and PI. Li et al.’s (2001,
2002) studies highlight the ability of 3D product presentation to enhance brand attitudes
and purchasing intention. Therefore,
H1 VPE has a positive impact on attitude toward the product.
H2 VPE has a positive impact on PI.
3.1 Stimuli and interface design
A hypothetical retailer’s website was custom-designed for this study to test the proposed
hypotheses. We designed two websites (laptops and rings) that allow participants to
control the content and form of the 3D. Furthermore, we employed a between-subjects
design in which our participants can see one experiment. For each website, participants
can zoom in or out on the rings or laptops, rotate them and see different parts of them
when clicking on them. The 3D sites permit the participants to change the colour of the
rings/laptops and see them in their chosen colour. Moreover, the 3D sites allow
participants to obtain information about the rings/laptops’ attributes (i.e., weight, size,
visual clarity, price, warranty, special effect features, etc.). Each site offers a wide variety
of rings or laptops, similar to those that many women and men currently buy and use.
The 3D stimuli were designed to help consumers imagine the rings or the laptops in
appropriate and relevant ways, thus enhancing their virtual experiences (Algharabat and
Abu-ElSamen, 2013; Algharabat and Dennis, 2010a). The website we created for this
study was not previously known to users, nor did users have any knowledge (i.e., we did
not include any brand name for the presented product) of the fictitious brands on it. Thus,
we eliminated any impact of previous experiences or attitudes (Algharabat and Dennis,
2010a; Fiore et al., 2005). Please see Appendix for screen shot of the 3D rings and
3.2 Justifications for using the stimuli
We select laptops and rings products because;
1 They represent product categories whose salient features can be adequately evaluated
with 3D interfaces using both experience attributes (i.e., weight, size, visual clarity,
etc.) and search attributes (i.e., price, warranty, special effect features, etc.).
2 Rings and laptops represent product categories which previous research (Algharabat
and Abu-ElSamen, 2013; Algharabat and Zamil, 2013; Algharabat and Dennis,
2010a, 2010b; Li et al., 2001) tested. For example, Li et al. (2001) stated that using
3D laptops and rings often impact online attitude and behaviour. Algharabat and
Abu-ElSamen (2013) state that 3D rings often impact online attitude, trust and
enjoyment. Furthermore, according to Li et al. (2001), choosing a 3D ring not only
gives participants the impression of owning them, but also it puts more personality
3 Rings and laptops represent product categories which are popular and interesting to
our sample. Therefore, consumers’ examination of 3D products, such as rings and
laptops often enhance their virtual experience (Algharabat and Abu-ElSamen, 2013;
Algharabat and Zamil, 2013; Algharabat and Dennis, 2010a, 2010b; Li et al., 2001,
2002, 2003). Therefore, the sites provide a suitable context for the present sample.
3.3 Sample and procedures
A convenience non-student sample has been employed to conduct this research. We used
a sample of 400 for the data collection. The sample consists of 200 subjects for each
stimulus. The sample was gender-balanced, consisting of 50% women and 50% men and
98% of the sample were aged between 23 and 45. Approximately 98% reported having
had prior online shopping experience (we excluded the remaining 2% from the analysis).
We conducted a non-response bias test (Armstrong and Overton, 1977) to confirm the
generalisation of our results, comparing the late responses with the early responses. The
results show no significant difference between respondents (p > 0.05 regarding
authenticity, PD, compatibility, flow, enjoyment, VPE, attitude toward the product and
PI). As a result, a non-response bias was not considered to be a serious limitation in this
We conducted the study in Jordan, Middle East and used an English language
questionnaire that was translated into Arabic and then translated back into English to test
for equivalency. The questionnaire was pre-tested with a small Jordanian non-student
sample (employees from a governmental university in Jordan) before field
implementation. In determining the proper time for each site, we followed Zajonc’s
(2001) study in determining the limit exposure for each experiment up to five minutes.
Prior to the collection of our data, participants were given a series of practice trials to
familiarise themselves with websites. After this, we informed the participants that this
study aims to measure their experience via different online retailers. In order to engage
participants in the study, we asked users to browse one of two websites (one for laptops
and one for rings) and then answer the attached questionnaire.
To enable potential users to experience products virtually, we manipulated VPE using
two levels, i.e., low, vs. high. We classify high VPE by having a high level of
diagnosticity, authenticity, compatibility, flow and enjoyment. While low level of VPE
has low level of diagnosticity, authenticity, compatibility, flow and enjoyment.
Therefore, we designed two 3D sites, one always participants to zoom in or out on the
rings and or laptops, rotate them and see different parts of them in different colours (high
level of diagnosticity, authenticity, compatibility, flow and enjoyment) and get
information about the product such as the size of the product and its prices (high level of
diagnosticity and compatibility). For the low level of VPE, we designed 3D sites which
have a product which rotates alone, users neither can zoom in or out on the rings and or
laptops, nor can they rotate them or see them in different colours (low level of
online retailers 309
diagnosticity, authenticity, flow and enjoyment). Furthermore, the designed websites did
not allow users to get information about the presented product (low level of
We ran a pre-test to develop the study materials. Respondents (n = 50), a convenience
non-student sample from a governmental university in Jordan, were asked to rate several
VPE based on their diagnosticity, authenticity, compatibility, flow and enjoyment of
rings (seven-point scales) and laptops (seven-point scales), using different samples of
Manipulation checks were used to decide whether the participants had noticed the
differences between the various conditions of each construct (i.e., high vs. low). After
each level, participants were shown the following statements: the 3D website is: ‘helpful
for me to evaluate the product’, ‘helpful in familiarising me with the product’, ‘helpful
for me to understand the performance of the product’, ‘helpful for me to understand the
quality of the product’, ‘I feel like I am dealing with a salesman who is responding to my
orders’, I feel like I am holding a real laptop and rotating’, ‘I feel time passes quickly
while using the 3D site’, ‘I felt curious while using 3D site’, ‘I never thought of other
things while using 3D site’, while using 3D site, I was entirely absorbed’, ‘evaluating the
product on this website is compatible with how I evaluate products in physical stores’,
‘evaluating the product on this website fits well with the way I like to evaluate products
in physical stores’, ‘familiarising myself with the product on this website is similar to my
product evaluation style in physical stores’, ‘I find my experience with this website
interesting’, ‘I find my experience with this website enjoyable’.
The results confirmed that participants noticed the different levels of VPE. They
perceived that the 3D ring website with high level of diagnosticity, authenticity,
compatibility, flow and enjoyment as being significantly providing VPE more than the
3D website with low level of diagnosticity, authenticity, compatibility, flow and
enjoyment (M high VPE = 6.35, M low VPE = 1.54; F 1, 49 = 116.4, p < .001).
We followed the same procedures for laptops and our results confirm that participants
noticed the different levels of VPE. They perceived that the 3D laptop website with high
level of diagnosticity, authenticity, compatibility, flow and enjoyment as being
significantly providing VPE more than the 3D website with low level of diagnosticity,
authenticity, compatibility, flow and enjoyment (M high VPE = 5.75, M low VPE = 1.55;
F 1, 49 = 145.3, p < .001).
3.5 Construct operationalisation
The participants were informed that this study pertained to consumer evaluations of
laptops and rings retailers’ websites. The questionnaire contained seven-point Likert-type
scales, anchored by 1 = ‘strongly disagree’ and 7 = ‘strongly agree’. The items and the
supporting literature for the measurement scales are shown in Table 1.
To measure the authenticity construct (AUT), we adopted a three-item scale based on
Algharabat and Dennis’ (2010a) scale. To measure PD and compatibility (COM), we
adopted a three-item scale for each based on Jiang and Benbasat (2005). We used a
modified version of Lee and Tsai’s (2010) three-item scale to measure flow (FLW). We
used Koufaris’ (2002) scale to measure enjoyment (ENJ). For attitude toward the product
(AT), we used the scale of van der Heijden et al. (2003), Grazioli and Jarvenpaa (2000)
and Coyle and Thorson (2001). Finally, for PI, we employed Fiore et al.’s (2005a) scale.
Table 1 Research construct operationalisation
3D perceived diagnosticity (PD1–PD3)
PD1 The 3D presentation is helpful for me to evaluate the product. Jiang and
and Kempf and
PD2 The 3D presentation is helpful in familiarising me with the
PD3 The 3D presentation is helpful for me to understand the
performance of the product.
3D authenticity (AUT1–AUT3) Algharabat and
AUT1 The 3D presentation is helpful for me to understand the quality
of the product.
AUT2 The 3D lets me feel like I am dealing with a salesman who is
responding to my orders.
AUT3 The 3D lets me feel like I am holding a real laptop and
3D flow (FLW1–FLW4) Lee and Tsai
FLW1 I feel time passes quickly while using the 3D site.
FLW2 I felt curious while using 3D site.
FLW3 I never thought of other things while using 3D site.
FLW4 While using 3D site, I was entirely absorbed.
3D compatibility (COM1–COM4) Jiang and
COM1 Evaluating the product on this website is compatible with how
I evaluate products in physical stores.
COM2 Evaluating the product on this website fits well with the way I
like to evaluate products in physical stores.
COM3 Familiarising myself with the product on this website is
similar to my product evaluation style in physical stores.
Shopping enjoyment (ENJ1–ENJ4) Koufaris (2002)
ENJ1 I find my experience with this website interesting.
ENJ2 I find my experience with this website enjoyable.
Purchase Intention (PI1–PI3) Fiore et al.
PI1 After seeing the website, it is likely that I would buy a product
from this online store
PI2 I would be willing to purchase a product through this online
PI3 I would be willing to tell a friend about this online store
Attitude toward the product (AT1–AT3) van der Heijden
et al. (2003),
AT1 I would have positive feelings towards buying a product from
AT2 The thought of buying a product from this website is appealing
AT3 It would be a good idea to buy a product from this website
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4 Analysis and results
We examined all the scale items to reflect the hypothesised direction. We used a
combination of SPSS 17 and AMOS 17. Further, we examined the univariate skewness
and kurtosis of the variables and found them to be within acceptable levels.
4.1 Measurement models
The analysis started with an examination of the structure and dimensionality of the study
constructs using exploratory factor analysis (EFA) and reliability analysis. After
examining the pattern matrix of the EFA, all items had loadings greater than 0.4 and
communalities greater than 0.5. We found no crossed loadings in other factors.
Figure 3 Second-order factor analysis of VPE dimensions
Notes: χ2 = 164.499, df = 85, χ2/df = 1.935, CFI = .967, GFI = .950, TLI = .959,
IFI = .967, RMSEA = .048
*p < 0.05, **p <0.01; *** p <0.001
We evaluated measurement properties by running AMOS 17.0. We treated the focal
construct of VPE as a second-order construct, while its five dimensions (AUT, PD, FLW,
COM and ENJ) are first-order factors measured through their respective indicators. The
second-order CFA model fit was deemed to be acceptable on the basis of a battery of fit
indices (χ2 = 164.499, df = 85; and χ2/df = 1.935), comparative fit index (CFI) = .967,
goodness-of-fit index (GFI) = .950, Tucker-Lewis index (TLI) = .959, incremental fit
index (IFI) = .967 and root mean square error of approximation (RMSEA) = .048
(Figure 3 and Table 2). The set of fit indices reported is consistent with Hu and Bentler’s
(1999) recommendations. The path coefficients between the indicators and their
respective first-order factors were significant at
= .05 level. In addition, all the path
coefficients between the second-order construct (VPE) and its five dimensions (AUT,
PD, FLW, COM and ENJ) were significant at the
= .05 level (Figure 3 and Table 2).
The analysis supports the operationalisation of overall VPE as a second-order factor
consisting of the five factors. Furthermore, Table 3 illustrates the average variance
extracted (AVE) for VPE dimensions.
Table 2 Results of the CFA: using a second-order conceptualisation of VPE
Indicator Direction Construct
loading SE t-value P
PD1 ← PD .90
PD2 ← PD .86 . 083 13.777 ***
PD3 ← PD .85 .077 12.784 ***
AUT1 ← AUT .87
AUT2 ← AUT .90 .068 14.440 ***
AUT3 ← AUT .94 .063 15.054 ***
FLW1 ← FLW .85
FLW2 ← FLW .89 .111 14.274 ***
FLW3 ← FLW .88 .089 15.411 ***
COM1 ← COM .96
COM2 ← COM .92 .07 15.411 ***
COM3 ← COM .87 .10 11.416 *
ENJ1 ← ENJ .90
ENJ2 ← ENJ .94 .12 15.84 ***
PDa ← VPEb .90 .053 14.319 ***
AUTa ← VPEb .85 .055 14.921 ***
FLWa ← VPEb .92 .034 16.78 ***
COMa ← VPEb .87 .053 15.055 ***
ENJa ← VPEb .99 .055 18.945 ***
Notes: aSecond-order indicators,
The respective indicators of PD, AUT, CE, FLW, ENJ and COM are numbered
serially (e.g., PD1, PD2,…, COM3)
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Table 3 Convergent and discriminant validity of VPE
PD AT FLW COM ENJ
FLW .25 .26
COM .23 .34 .15 .92
ENJ 24 .27 .22 .19 .91
Notes: The numbers in diagonal line are the AVE by each construct,
The numbers above the diagonal show the squared correlation coefficients
between the constructs
Before estimating the path coefficients of the hypothesised structural model, we
proceeded to fit a CFA on all three latent factors: VPE, AT and PI. Composite reliability
is an indicator of the shared variance among the set of observed variables used as
indicators of a latent construct (Fornell and Larcker, 1981; Kandemir et al., 2006). As
Table 4 shows, construct reliabilities for all three latent constructs ranged from VPE (.96)
to AT (.91) and PI (.90), all of which are acceptable (Hair et al., 1998). In addition, the
coefficient alpha values were well above the threshold value of .7 that Nunnally (1978)
recommends. The standardised factor loadings ranged from .84 to greater than .90 and
were statistically significant at the
= .95 level (Table 5). This provided the necessary
evidence that all the constructs exhibited convergent validity.
Table 4 Measurement model: a scale properties of the three latent factors
Construct Construct reliability Coefficient alpha AVE
VPE .96 .96 0.83
At .91 .90 0.77
PI .90 .90 0.69
Table 5 Results of the CFA within the three latent factors
Indicator Direction Construct Estimate Standardised
estimate SE t-value P
PD ← VPE .494 .90 .053 19.319 ***
AUT ← VPE .489 .85 .055 16.921 ***
FLW ← VPE .301 .92 .034 18.78 ***
COM ← VPE .206 .87 .053 17.055 ***
ENJ ← VPE .602 .99 .055 18.945 ***
PI1 ← PI .915 .812 .052 17.531 ***
PI2 ← PI .961 .88 .050 19.122 ***
PI3 ← PI .884 .84 .048 16.486 ***
AT1 ← AT 1.00 .85 .045 15.456 ***
AT2 ← AT 1.09 .90 .048 19.22 ***
AT3 ← AT .502 .88 .052 18.854 ***
We tested discriminant validity depending on the AVE values, which should be within
the cut-off point of 50%. The discriminant validity is established, first, by the absence of
significant cross-loadings that are not represented by the measurement model (i.e.,
congeneric measures). Second, we compared the shared variance among the constructs
with AVE from each construct (Anderson and Gerbing, 1988; Voss et al., 2003). The
square roots of the AVE by each construct exceed the correlation between them
(Table 6), demonstrating discriminant validity.
Table 6 Internal consistency and discriminant validity of constructs
Research constructs Correlations
1 2 3
1. VPE .911
2. AT .25 .877
3. PI .09 .06 .83
Notes: The figures under the diagonal are the Pearson (R) correlations between the
Diagonal elements are square roots of AVE
4.2 The structural model
The structural model used to test the hypotheses consisted of all three factors tested in the
measurement model (Figure 3). The model fit measures indicated acceptable agreement
with the covariance in the data (χ2 = 514.433, d.f. = 202; χ2/d.f. = 2.547; CFI = .92; GFI
= .91; AGFI = .91; TLI = .92; IFI = .94; and RMSEA = .062). The results of the
hypothesis testing support all postulated paths for H1–H2. We found that VPE was
positively associated with AT (
= .34, p < .001) and PI (
= .42, p < .001).
This study aims to investigate the main dimensions of VPE. Previous research
conceptualises and defines VPE based on a unidimensional construct. However, from our
results, we believe that VPE is a multi-dimensional construct. Also, compared to previous
studies that focused only on particular dimension(s) of the VPE (Algharabat and Dennis,
2010a; Fiore et al., 2005; Jiang and Benbasat, 2005; Li et al., 2001; Suh and Lee, 2005),
this research revised all studies conducted in the area and built a second-order,
multi-dimensional construct to measure VPE.
It is thought preferable for any measurement of VPE to reflect the authenticity,
diagnosticity, compatibility and flow of the online 3D-presented product and/or overall
experience. This will enhance customers’ ability to evaluate the quality of the product
and their ability to learn more about the product and/or the website. To that end,
enjoyment is considered an important element in measuring VPE, since this construct
focuses more on the entertainment part of the VPE. The results of the various tests
demonstrate that the combined VPE scale possesses strong psychometric properties,
suggesting that authenticity, diagnosticity, compatibility, flow and enjoyment constitute
five independent yet correlated dimensions of the construct. Furthermore, the combined
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VPE scale provides a first step in the direction of understanding virtual experience in
Our results confirm that the combined VPE measurement allows users to evaluate
product performance prior to purchase. By so doing, a virtual experience could be
perceived as being equivalent to a direct experience. This result is in accordance with
previous research (e.g., Li et al., 2001, 2002, 2003; Klein, 2003) that states the
importance of virtual experience in incorporating elements of both indirect and direct
experiences and exceeding the limits of each.
Measuring VPE should be based on different aspects of the technology. For example,
1 the technology should reflect the authentic part of the illustrated product
2 the technology should help users to have the belief that what they are seeing online is
what they will find offline (diagnosticity)
3 the technology should enhance consumers’ belief that their online shopping
experiences are consistent with their existing styles, habits and experiences in
physical shopping environments (compatibility)
4 VPE should not always lead to cognitive results; rather, many users might navigate
online retail sites for the sake of enjoyment.
The results of this research supported the hypotheses that VPE contributes significantly to
consumers’ attitudes to products and PIs. These findings are consistent with previous
research, confirming that favourable attitude and PIs are among the main outcomes of a
6 Managerial implications
Online retailers need to find ways of attracting and retaining customers (Khakimdjanova
and Park, 2005; Mummalaneni, 2005). A website with an authentic diagnostic 3D
product is an important stimulus that usually helps online retailers to be successful and it
often helps them to enhance the e-shopping environment (Khakimdjanova and Park,
2005; Park et al., 2008). Non-store retailers should pay more attention while designing
3D product presentation. In particular, the design should be focused on the VPE
dimensions. This will enhance the users’ virtual experience. Website developers,
marketers and managers should improve user perceptions of the authenticity and
diagnosticity of the 3D product presentation. Further, adding an innovative 3D flash with
more experiential and instrumental values often enhances consumer’s flow and
enjoyment, which may result in a positive attitude to the products and/or making a
purchase from the online retailer.
7 Limitations and future research
We admit that there are several limitations to this study. For example, we designed the
hypothetical retailer to be implemented on the rings and laptops industries. However, we
believe that rings and laptops are products that consumers need to research and they
reflect many users’ emotions and thinking.
We recommend that researchers investigate the impact of VPE on trust, in particular
the impact of VPE on graphical characteristics such as 3D. We argue that, since
customers are not in a position to touch and feel the 3D presented product online, the 3D
must be designed to induce feelings of trust by providing detailed and clear information,
which in turn will influence the decisions to buy.
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Appendix (see online version for colours)