Consumer store experience through virtual reality: its effect on emotional states and perceived store attractiveness

Abstract

Based on the stimuli-organism-response model, this study aims to examine whether consumers’ store experience through virtual reality (VR), compared to website experience, can attract them enough to perceive the online store as appealing. Two types of stimuli were developed for the experiments: consumers’ VR store experience (106 data) (i.e., having respondents experience 360-degree-based VR store videos recorded at a fashion retailer) and store website experience (107 data) (i.e., having respondents experience the same store’s website). The results revealed that relative to an ordinary store website, consumers’ VR store experience evoked positive emotions and increased perceived store attractiveness. This study also discovered that store familiarity does not moderate the relationship between the two store experience types and evoked emotions, implying that VR technology is effective regardless of consumers’ familiarity with a store. Text analytics were also utilized, providing additional insights about their VR store experiences. This study suggests an effective method for online retailers to emulate an attractive store environment and entice consumers through VR, regardless of the retailers’ fame. Specifically, it demonstrates the effectiveness of VR over website in enhancing store attractiveness, an under-studied area.

Full text

Consumer store experience throughvirtual
reality: its eect onemotional states
andperceived store attractiveness
Byoungho Jin1, Gwia Kim2*, Marguerite Moore3 and Lori Rothenberg4
Introduction
Retailers invest in creating an attractive store environment because it induces consum-
ers to visit and provides them with an enjoyable shopping experience (e.g., Baek etal.,
2018; Darden etal., 1983; Orth & Wirtz, 2014). Retailers, however, cannot fully portray
their store environment through their websites. One way to offer a unique store experi-
ence online is using virtual reality (VR). By replicating the real world (Herz & Rausch-
nabel, 2019; Steuer, 1992), VR enables consumers to experience the store atmosphere
without actually visiting the store. A growing number of retailers are testing VR online.
One example is eBay, which collaborated with Myer, an Australian department store,
and created a VR environment on eBay’s website to allow its consumers to explore the
Abstract
Based on the stimuli-organism-response model, this study aims to examine whether
consumers’ store experience through virtual reality (VR), compared to website experi-
ence, can attract them enough to perceive the online store as appealing. Two types
of stimuli were developed for the experiments: consumers’ VR store experience (106
data) (i.e., having respondents experience 360-degree-based VR store videos recorded
at a fashion retailer) and store website experience (107 data) (i.e., having respondents
experience the same store’s website). The results revealed that relative to an ordinary
store website, consumers’ VR store experience evoked positive emotions and increased
perceived store attractiveness. This study also discovered that store familiarity does
not moderate the relationship between the two store experience types and evoked
emotions, implying that VR technology is effective regardless of consumers’ familiarity
with a store. Text analytics were also utilized, providing additional insights about their
VR store experiences. This study suggests an effective method for online retailers to
emulate an attractive store environment and entice consumers through VR, regardless
of the retailers’ fame. Specifically, it demonstrates the effectiveness of VR over website
in enhancing store attractiveness, an under-studied area.
Keywords: Virtual reality, Store attractiveness, Emotions, Sentiment analysis, Semantic
network analysis
Open Access
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RESEARCH
Jinetal. Fash Text (2021) 8:19
https://doi.org/10.1186/s40691-021-00256-7
*Correspondence:
gkim7@ncsu.edu
2 Doctoral Candidate,
Department of Textile
and Apparel, Technology
and Management, North
Carolina State University,
Raleigh, USA
Full list of author information
is available at the end of the
article

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store environment virtually (Team, 2016). As with this case, VR can be an effective tool
in delivering store atmosphere and providing unique shopping experiences.
ere are several types of VR. Among them, a viable way for any retailer to utilize eas-
ily is the 360-degree-based VR videos because these videos require fewer skill sets and
financial budgets to operate than other VR types. To create 360-degree-based VR videos,
retailers can use 360-degree cameras that can be used to record in-store environments.
e cameras are inexpensive and easy to use. To play VR videos, consumers can use any
VR headsets, even mobile-based VR operators, such as Google Cardboard (Jang etal.,
2019). ese VR devices are also easy to use. By playing VR videos, consumers can expe-
rience the store virtually and overcome the physical limitation of geographical locations.
erefore, this study posits that this type of VR is practical for retailers.
With the emergence of VR and its use in practice, several academic studies have
emerged on the use of VR in retailing and marketing. Most of these studies have paid
attention to VR-led consumer responses, such as behavioral intention and customer sat-
isfaction (Domina etal., 2012; Gabisch, 2011; Lau & Lee, 2018; Pizzi etal., 2019), but do
not fully explain why the VR store environment results in positive behavioral intentions.
Another research gap is that previous VR studies have not considered the potential
impact of consumers’ level of familiarity with the store in question. Positive emotions,
such as excitement, arousal, and pleasure, may depend on consumers’ prior exposure to
the store. at is, consumers’ prior experience with the store may lessen the novelty of
experiencing the store a second or subsequent time through VR. To evaluate the effect
of VR store experience accurately, this study employs consumers’ store familiarity as
a moderator. e third research gap pertains to the way the VR store environment is
created in previous studies. Most of the earlier studies created a VR store environment
digitally with graphic tools (e.g., Pizzi etal., 2019; Van Herpen etal., 2016) or web plat-
form (e.g., Domina etal., 2012; Gabisch, 2011), rather than creating it in a real retail
store (Domina etal., 2012; Gabisch, 2011; Lau & Lee, 2018; Pizzi etal., 2019; Van Her-
pen etal., 2016). is approach may have a limitation in representing a physical store
and thus capturing customers’ positive emotions because the store environment is less
authentic. Also, this approach requires more budgets and skill sets for retailers to oper-
ate. Related to this, previous VR studies call for research in a more reality-oriented store
setting (Lau & Lee, 2018).
Addressing the research gaps, this study builds a conceptual framework based on the
stimuli-organism-response (SOR) model (Mehrabian & Russell, 1974) and schema the-
ory and tests it through experiments. e framework specifies whether VR can deliver
a physical store atmosphere better than a website to increase the consumers’ emotional
states, which in turn helps consumers perceive the store as attractive. e SOR model
explains that the stimuli (i.e., VR versus website store experience) affect organisms (i.e.,
emotional states), and the organism influences consumer responses (i.e., store attrac-
tiveness). Schema theory is employed to explain whether consumers’ elicited emotional
states (i.e., arousal and pleasure) vary with their familiarity with the store (Kent & Allen,
1994). In addition, this study aims to understand more about consumers’ VR store expe-
rience through text analytics.
is study contributes to the literature by observing how consumers’ emotional
states lead to perceive a boutique store attractiveness, which has been less studied in

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the literature. Comparing the 360-degree-based video driven VR store environment cre-
ated in an actual store, (rather than a digitally created store), with website experience
with the same store will extend the literature by discovering the effectiveness of VR over
websites in conveying the store atmosphere. Further, the comparison of VR with website
store experiences will suggest whether VR store experiences can overcome the limitation
of websites and lead consumers to perceive greater store attractiveness. e findings of
this study further suggest whether the volume of benefits driven by VR store experiences
vary with customers’ store familiarity level, by including it as a moderator.
is study is tested in a small independent fashion boutique that maintains both its
own brick-and-mortar store and website. An additional reason for the selection of a
small fashion store is that consumers’ familiarity with the store may vary greatly, com-
pared to a large retail store mostly known to many people.
Literature review
Theoretical framework
Stimuli‑organism‑response (SOR) model
is study is built on the stimulus-organism-response model (SOR) by Mehrabian and
Russell (1974). According to the SOR model, the environment that contains stimuli (S)
can influence people’s organisms (i.e., internal states) (O), which subsequently causes
people’s responses (R). Specifically, stimulus is referred to as the factor that influences an
individual’s internal states, which means an organism. Organism represents individual
emotional reactions to the environment (Mehrabian & Russell, 1974). When an indi-
vidual encounters a stimulus (S), he or she can form or change his or her internal states
(O). Here, response (R) is the individual’s reactions driven by the organism. Researchers
further identified three dimensions of affective responses (i.e., organism) triggered by
stimuli; pleasure, arousal, and dominance (i.e., PAD) (Mehrabian & Russell, 1974). Pleas-
ure and arousal are found to be two important variables that explain consumer behaviors
(Russell & Pratt, 1980); we hence focus on these two affective responses. Arousal is an
affective state “ranging from sleep to frantic excitement” (Mehrabian & Russell, 1974, p.
18). It describes a person feeling simulated or alert when exposed to a stimulus. Pleasure
is a person’s hedonic state—feeling happy and joyful when exposed to a stimulus (Meh-
rabian & Russell, 1974).
In retail and marketing research, the SOR model has been actively utilized to explain
the impact of the store environment on shopping behavior (Vieira, 2013). Elements of
the store environment, including color, temperature, spatial and temporal components,
are considered as stimuli in many previous studies (Vieira, 2013). e SOR literature
also provides research insight into atmospheric stimuli such as music and scent (Roschk
etal., 2017) and advertising stimuli (Min etal., 2019). Arousal and pleasure represent the
most commonly evoked emotions, also some studies focus on different primary emo-
tional responses such as dominance (Vieira, 2013), satisfaction (Roschk etal., 2017), and
attitudes (Min etal., 2019). In the retailing context, the responses evoked by emotional
states incorporated behavioral intentions (Roschk etal., 2017), buying intention (Min
etal., 2019), flow (Wang etal., 2007), and shopping motivation and value (Babin etal.,
1994; Wang etal., 2007).

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In earlier studies, stimuli meant external marketing mix variables or other environ-
mental inputs that can affect consumers (Bagozzi, 1986). As with previous studies
that considered store environments as stimuli (e.g., Donovan & Rossiter, 1982, 1994;
Huang & Liu, 2014; Watson etal., 2018), stimuli in this study consist of respond-
ents’ store experiences through either VR or website. The organism is ‘arousal’ and
‘pleasure’, following the previous studies (Mehrabian & Russell, 1974) and response
is ‘store attractiveness’ that can be evoked by the consumers’ emotional states.
Schema theory
While the SOR model builds the overall research framework, schema theory (Dahlén
et al., 2005; Kent & Allen, 1994) is applied to describe the moderation effect of
store familiarity in consumers’ emotional states on store experiences. The concept
of schema was first introduced by Bartlett (1932), and many researchers developed
and elaborated it (Kent & Allen, 1994; Piaget, 1953; Rumelhart, 1980). Schema is
an active framework created by past experiences and reactions in one’s procedural
memory that can help to understand a new experience with the expectations shaped
by the framework (Bartlett, 1932). Schema was then considered as a key concept of
cognitive science (Piaget, 1953; Rumelhart, 1980). According to Rumelhart (1980),
the schema theory explains how the brain organizes knowledge. All knowledge is
packed into units, which become schema, which is stored in memory to be a data
structure representing knowledge about all concepts. In other words, underlying
objects, situations, events, sequences of events, actions, and sequences of actions are
stored in memory, and these saved underlying experiences help to understand new
experiences. Thus, schema construe a network of associations that serve as a guide
for a person’s perception (Bem, 1981). Incoming stimuli are processed in an indi-
vidual’s perception based on the individual’s existing schema (Bem, 1981).
The schema theory has been used for exploring consumers’ product or brand
familiarity, as a consumer tends to form a set of expectations about a product cat-
egory through previous experiences, and these expectations develop the percep-
tions of product and brand attributes (Sujan & Bettman, 1989). Consumers utilize
schemas to recognize, understand, and judge a new product or a brand because they
can recall previous associations already stored in their memory (Heckler & Childers,
1992; Lange & Dahlén, 2003; Low & Lamb, 2000; Sujan & Bettman, 1989). Further,
when new information that is not consistent with the present brands and conflicts
with previous schemas is provided, consumers can choose to either assimilate or
accommodate, so that it can be incorporated into the current schema or accommo-
date the new information to modify the present schema, in order to understand the
new information (Sujan & Bettman, 1989). In the current research, the schema the-
ory explains why less familiar stores can achieve more benefits by using VR technol-
ogy than famous retailers. The level of store familiarity is included as a moderator
to observe whether the effectiveness of VR store experience in evoking consum-
ers’ emotional states can be strengthened if the store is unfamiliar and new to the
consumers.

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Types ofvirtual reality
As per previous studies, VR can be categorized into immersive VR and non-immersive
VR (Mills & Noyes, 1999; Park etal., 2018). is classification is based on how realisti-
cally the VR type can respond to VR users’ movements, and the virtual environment’s
scale (Mills & Noyes, 1999; Park etal., 2018). Immersive VR can operate more realistic
VR experiences because the virtual world completely surrounds the VR users (Mills &
Noyes, 1999; Park etal., 2018), while non-immersive VR allows VR users to experience
virtual spaces through a flat screen (i.e., a monitor) (Costello, 1997). erefore, immer-
sive VR requires high-performance software and equipment, such as head-mounted dis-
plays (HMDs) to surround users, but non-immersive VR does not need them (Costello,
1997). In immersive VR, HMDs can sense VR users’ movement and alter the views and
orientation of VR environments to address the movements (Meissner etal. 2017), so it
has a higher influence on VR users than non-immersive VR (Alshaer etal., 2017; Park
etal., 2018).
Another way VR in retailing and marketing is classified into two levels based on the
product involvement system (Cowan & Ketron, 2019). When VR users are allowed to
engage more in observing each individual product shown in the virtual world, it has a
high level of involvement. On the contrary, in low involvement VR type, VR users can-
not access each product presented in the virtual world.
is study uses 360-degree-based VR videos played through HMDs. VR users of this
type are fully surrounded by virtual environments using HMD, so it is categorized as
immersive VR. At the same time, VR users cannot select, touch, or manipulate each
product in this VR type, so it is classified as a low-involvement VR.
Use ofvirtual reality inpractice
Recently, VR has been noted for its use in marketing and retailing to offer richer con-
sumer experiences (CB Insights, 2018a; Cognizant Reports, 2016), among apparel and
fashion retailers. VR users can virtually explore and shop as they access stores using
headsets without physical visits (CB Insights, 2018b; Grieder etal., 2014). e tourism
industry is one of the fields actively using VR. For example, Marriott Hotels partnered
with Samsung to launch VRoom Service, which enables Marriott guests to request deliv-
ery of a VR headset to their room using the hotel’s mobile app, through which they can
virtually explore destinations. e pre-filmed VR videos of travel destinations are saved
in the VR headset so that guests can easily immerse themselves in the virtual tours.
Compared to the limited experience conveyed through static photos, the VR experience
can offer more realistic experiences to guests (Stephens, 2017).
More recently, Amazon opened its VR kiosks in 10 shopping malls to promote the
Prime Day shopping event (Horwitz, 2018). Customers wearing VR headsets walked
through virtually created rooms reflecting Amazon store sections, such as fashion, bath
and beauty, and toys. ese customers used VR controllers to handle any product in full
three-dimensional view.
Apparel and fashion retailers also use VR technology to enlarge consumers’ shopping
experience. TopShop and Rebecca Minkoff offered VR fashion show to their custom-
ers, affording the customers a 360-degree view of the products (Milnes, 2017). Rebecca
Minkoff further attempted to introduce this advanced technology to commerce, so that

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consumers can enter the VR world and shop as if they are in a real shopping setting
(Milnes, 2017). A shoe brand, TOMS brought VR to provide trips to retail customers
(Nafarrete, 2015). In its flagship store in Los Angeles, consumers could watch a four-
minute 360-degree film (i.e., VR video) that allowed them to virtually travel along with
TOMS in Peru. TOMS’s policy is to donate a matched pair of shoes to a child whenever
a pair of shoes are sold to a customer, and the VR video shows how their donation helps
Peru.
Online retailers have also accepted the technology. eBay, an online retailer, partnered
with Myer, an Australian fashion retailer, to launch a VR departmental store (Team,
2016). Australian consumers can get an immersive shopping experience of a Myer’s VR
store, as they browse and purchase Myer’s items online. Myer’s VR store, based on the
eBay platform, enables consumers to view items just as though they were in the physical
store. Similarly, Alibaba’s Taobao consumers are able to walk through the virtual online
mall with a 360-degree panoramic view (Zuo, 2016). Despite the active use of VR in
larger companies, smaller retailers have rarely adopted the technology yet.
As VR can offer immersive and interactive experiences, companies tend to apply the
technology to provide virtual tours and enhance the online shopping experience (Cam-
mareri, 2019; McDowell, 2020). Companies frequently partner with an independent VR
platform provider to implement these activities. For example, the Tommy Hilfiger brand,
partnered with Obsess, a VR platform enabler, to create a successful implementation of
virtual tours. Allison Mitchell, a handbag designer brand, also partnered with Obsess to
create a 360-degree virtual storefront (Mihalic, 2019). Furthermore, as VR requires min-
imal physical interaction, its use is expected to increase in retailing during the COVID-
19 pandemic (Rueter, 2020; Sandel, 2020).
Academic studies onVR inretailing andmarketing
Earlier studies on VR are summarized in Table1. As can be seen from the Table, VR-
related studies focused on shopping settings in various product categories: apparel (e.g.,
Domina etal., 2012), food (e.g., Pizzi etal., 2019) and IT (Gabisch, 2011). ese previ-
ous studies have conducted experiments mainly to observe how the VR experience can
be effective in retailing and marketing, mostly relying on digitally-created virtual stores
using graphics to mimic actual shopping places (Lau & Lee, 2018; Pizzi etal., 2019; Van
Herpen etal., 2016). For example, Van Herpen etal. (2016) built a store interior and
store display using 3D graphic design, to generate food products and layout of the prod-
ucts, mirroring an actual grocery store. Some researchers utilized virtually-created retail
store at Second Life, which is a platform that allows brands to create their own virtual
world using an avatar and 3D graphically-created places (Domina etal., 2012; Gabisch,
2011). For example, Gabisch (2011) asked respondents to visit brand stores (e.g., Adidas
and IBM) created virtually at Second Life.
Earlier studies listed in Table 1 confirmed that VR experience can drive purchase
intention (Lau & Lee, 2018; Park etal., 2018) and shopping intention (Domina etal.,
2012) in the virtual world. Especially, Domina etal. (2012) discovered that consumers’
heightened enjoyment through VR experience led to higher shopping intentions. Fur-
ther, Gabisch (2011) found that the virtual store experience resulted in real-world visit
intention and purchase behavior. In food shopping context, two studies investigated

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whether VR store experience is perceived similar to a real, physical store experience
through a comparison (Pizzi etal., 2019; Van Herpen etal., 2016) and confirmed that VR
store experience could offer customer satisfaction (Pizzi etal., 2019).
While these studies offer a preliminary understanding of the role of VR in shopping
contexts, a couple of areas are worthy of research attention. First, earlier VR studies were
mostly limited to customers’ behavioral intentions (e.g., purchase intention), rather than
the customers’ perceptions of the store atmosphere. VR capabilities that replicate the
real world could effectively help consumers experience the store atmosphere, which fur-
ther facilitates positive evaluations toward the store, such as perceived store attractive-
ness. Perceived store attractiveness is defined as the consumers’ perception of the extent
to which a store is appealing to generate positive evaluation (Baek etal., 2018; Orth &
Wirtz, 2014). Consumers’ perceived store attractiveness is an important factor in retail-
ing, as it can lead to store patronage intentions (e.g., Darden etal., 1983), re-patronage
intention (e.g., Orth & Wirtz, 2014), and approach-avoidance behavior (e.g., Baek etal.,
2018; Orth & Wirtz, 2014). Despite the potential use of VR in creating a store atmos-
phere and subsequent positive evaluation towards the store, earlier literature has paid
little attention to this aspect.
Second, experiencing a store through VR is still a novelty to the majority of consumers
(Pizzi etal., 2019). erefore, just as other technology can provide shoppers with posi-
tive emotions (e.g., pleasure) by evoking sensory and affective experience (e.g., Dennis
etal., 2014), so can VR produce positive heightened emotions (Park & Im, 2016; Park
etal., 2018). Related to this reasoning, consumers’ familiarity with the store may reduce
the novelty of the VR store environment, thus impacting the magnitude of consumers’
emotions. Nonetheless, earlier studies listed in Table1 disregarded the influence of con-
sumers’ store familiarity level.
Table 1 Experimental studies on the virtual reality experience in shopping context
Developed by authors based on literature review
Study Context Stimuli Focus
Gabisch (2011) Apparel, Food, IT 3D online virtual world (Sec-
ond Life) experience Real world purchase intention,
real world purchase behavior
Domina et al. (2012) Apparel and fashion 3D online virtual world (Sec-
ond Life) experience Shopping intention within the
3D online virtual world
van Herpen et al. (2016) Food products Comparison among physical-
store vs. virtually created
VR-based store vs. pictorially
represented store shopping
experience
Similarity between real-life and
VR shopping behavior
Lau and Lee (2018) Apparel Virtually created shopping mall
experience Purchase intention, interac-
tive and hedonic shopping
experience
Park et al. (2018) Apparel VR model store visits using
HMD Purchase intention
Pizzi et al. (2019) Food products Comparison between physical-
store vs. virtually created
VR-based store shopping
experience
Store satisfaction
Jang et al. (2019) Footwear VR store using mobile-based
HMDs Experiential shopping value,
Approach intention
Baek et al. (2020) Apparel 360-degree VR photos Brand equity, visit intentions

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ird, most VR studies in shopping settings used digitally-created VR graphic stores
(Domina etal., 2012; Gabisch, 2011; Lau & Lee, 2018; Pizzi etal., 2019; Van Herpen
etal., 2016). e use of VR-view videos showing actual places is limited to the tourism
field (Deng etal., 2019; Griffin etal., 2017). In apparel retailing, Baek etal. (2020) con-
ducted a study of virtual tours using 360-degree photos of a physical store. However,
though they used VR with an actual store, they did not incorporate video stimuli, which
can provide more realistic experiences than static photos. To reduce the gap between
actual store experience and virtual store experience, this study posits that it is helpful to
use VR video stimuli that record and capture the actual store, rather than a graphically-
created one.
Considering all the aforesaid, this study investigates whether consumers’ perceived
store attractiveness can be increased by VR-heightened emotions (i.e., arousal and pleas-
ure). Specifically, by comparing consumers’ store experiences through VR that features
the physical store interior of a real fashion boutique vs. website of the store, this study
examines the role of VR-view store experience in conveying actual store environments
to please and arouse consumers, which in turn helps consumers feel the store more
attractive. is study further tests whether consumers’ store familiarity level carries
some weight relating to VR store experience, which was not considered in earlier lit-
erature. In order to better understand consumers’ opinion on VR store experience, this
study includes text analytics answered an open-ended question.
Research framework andhypotheses development
Based on the SOR model by Mehrabian and Russell (1974), this study posits that con-
sumers’ store experience (S) (i.e., VR vs. website) triggers an emotional state (O) (i.e.,
arousal and pleasure), and subsequent response to the store (R) (i.e., perceived store
attractiveness). Further, the relationship between store experiences and emotional states
is expected to be moderated by store familiarity, applying the schema theory. Figure1
shows the research framework and hypotheses.
Donovan and Rossiter (1982) and Mehrabian and Russell (1974) proposed that the
amount of information in the environment (i.e., information rate) decides the level of
consumers’ affective reactions and a newer environment elicits greater emotional states.
e information rate is referred to as its degree of novelty and complexity. Novelty
includes new and unexpected environmental settings, and complexity means “the num-
ber of elements or features” (Donovan & Rossiter, 1982, p. 40).
is study expects that VR store experience offers higher novelty and complexity to
consumers and that such experience will provide more detailed information than web-
sites. Specifically, by wearing VR headsets, consumers can have a 360-degree view of
the store and virtually experience the store atmosphere, while websites cannot convey
the environment of the physical store adequately. In the virtual world, consumers can
encounter more “number of elements or features” that replicate the real world. Indeed,
the VR shopping experience can overcome the shortcomings of traditional online shop-
ping, such as a lack of realistic view and feeling the presence with a virtual affluence (Van
Herpen etal., 2016). Consumers too may not expect that they will directly feel the store
atmosphere through virtual media, so the VR experience will be a new and unexpected
experience for them.

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Taken together, this study posits that because VR offers a higher information rate
and new experience than a website, consumers’ VR experience will cause them greater
arousal and pleasure than a website experience. ereby, H1 is developed as follows.
H1: VR store experience leads consumers to greater (a) arousal and (b) pleasure
than website experience.
Based on the Schema theory, researchers have found that consumers usually form
more elaborate and sophisticated schema towards familiar brands, compared to unfa-
miliar brands (Heckler & Childers, 1992; Kent & Allen, 1994; Low & Lamb, 2000).
is is because they possess more associations for a familiar brand (Low & Lamb,
2000), and the knowledge of a brand can be easily retrieved from a familiar brand,
rather than a less familiar brand (Heckler & Childers, 1992). Higher brand familiar-
ity could be formed from a stronger schema consisting of many previous experiences
related to the brand (Kent & Allen, 1994) so that this strongly formed schema of a
familiar brand is difficult to change with a single additional encounter.
On the contrary, consumers’ weaker schema towards less familiar brands can be
easily influenced by a single new encounter, such as a new experience (Dahlén etal.,
2005; Klein etal., 2016). Consumers form a less sophisticated and less established
schema about unfamiliar brands, vis-a-vis the well-known brands (Dahlén etal., 2005;
Kent & Allen, 1994). erefore, a weak schema towards a less famous store can be
influenced by a new experience (i.e., VR) easily, compared to the famous stores.
Accordingly, this study posits that consumers may possess altered impressions of
the store image and feel higher enjoyment when they virtually experience relatively
less-known stores, compared to familiar stores. Following this, when consumers are
less familiar with the store, a single store experience can have a greater influence on
their responses to the store. Similarly, consumers with weaker store familiarity may
feel VR experience to be more novel to them than those with higher store familiarity;
thus, the former feels a more heightened emotional state.
H2: Store familiarity moderates H1 such that lower store familiarity leads to
Store experience
(VR vs. Website)
Arousal
Pleasure
Perceived
store aracveness
Store familiarity
(highvs. low)
SmulusOrganism Responses
H1a (+)
H1b (+)
H3a (+)
H3b (+)
H2a (-)
H2b (-)
Fig. 1 Conceptual framework.
*In measuring store experiences, VR store experience is coded as 2, website store experience is coded as 1.
*Store familiarity: moderator

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greater (a) arousal and (b) pleasure.
Store-evoked arousal and pleasure are known to increase positive consumer responses
to the store (Ha & Lennon, 2010). Arousal and pleasure evoked in the store or Web envi-
ronments are positively related to consumers’ desire to explore or shop (Eroglu etal.,
2003), satisfaction (Eroglu etal., 2003; Ha & Lennon, 2010), behavioral intention (Ha &
Lennon, 2010), and retail choice and retail preferences (Dawson etal., 1990). Arousal
and pleasure stimulated by the online store atmosphere, created by background color
and music, increase consumers’ behavioral intention and approach (Wu etal., 2008).
Pleasure stimulated by shopping experience and technology has a positive effect on con-
sumers’ responses (Das & Varshneya, 2017; Dennis etal., 2014).
Among the consumers’ responses, the study proposes that the arousal and pleasure
(Os) enhance consumers’ perceived store attractiveness (R). Perceived store attractive-
ness is the extent to which a store is appealing to consumers, enough to generate positive
store evaluation (Baek etal., 2018; Orth & Wirtz, 2014). Store environments can have an
influence on perceived store attractiveness (Baek etal., 2018) and even through emotion,
such as pleasure (Orth & Wirtz, 2014). Accordingly, this study expects that once con-
sumers feel arousal and pleasure through experiencing the store atmosphere through VR
or a website, they will be more likely to feel the store is attractive.
H3: Heightened (a) arousal and (b) pleasure lead consumers to higher perceived
store attractiveness.
Methods
Overview
A study was designed to discover whether VR store video experiences can evoke con-
sumers’ emotional states, compared to the effectiveness of store website experiences,
which in turn increase perceived store attractiveness. For a comparison between VR
store videos and store website on emotional states, a one-factor between-subjects exper-
iment was designed. Two hundred and thirteen usable observations (106 from VR and
107 from website) out of 237 items of data were collected from students of a Southeast-
ern University using a convenience sampling. e student sample was selected based
on their great interest in or heavy use of technology (e.g., Lee et al. 2006). Data were
collected from May to September 2019. Demographic information is summarized in
Table2.
Stimuli andprocedures
is study tested the VR store experience against the website store experience by con-
ducting experiments using stimuli rather than through measurement by scales. To com-
pare VR and website store experiences relating to a real fashion boutique, two types of
stimuli were employed. e VR experience was measured by having consumers experi-
ence the VR store video stimuli developed by the authors from a local fashion boutique.
e website experience was gauged by having the respondents browse and explore the
same boutique’s website, which conveyed the store’s atmosphere through images of the
store and social media links as well as products.

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To create the VR store experience, the researchers developed a 360-degree-based VR
video at a small local boutique with IRB approval. 360-degree-based VR videos were
selected as methods as they are an easy way for any retailer to adopt. e videos were
recorded in the store after the business hours, using Richo eta V 360 camera. e
recorded videos were edited using iMovie on Mac, into approximately eight one-min-
ute-long videos showing eight sections: entrance, women’s wear, men’s wear, jewelry and
accessories sections, and so on. Background music that simulates a store-like atmos-
phere was also created by the researchers. For the website version, the official store web-
site was used with the owner’s approval.
VR participants were asked to visit VR facilities in the university library for around
20–25min. ey first received a short orientation relating to research agreement and
safety. ereafter, they watched the VR store videos with VR headsets that were played
through the software, Steam. e mono layout and 360-degree format on Steam were
selected to play the VR videos because these settings were the most suitable option. ey
watched eight one-minute videos showing different parts of the store (e.g., entrance,
women’s, men’s and accessories sections) by clicking each section. e participants
looked, walked, and moved around the store environments shown in the VR videos.
While exploring the videos, background music was played to construct an atmosphere
similar to the store. After finishing all eight videos, they completed an electronic Qual-
trics questionnaire in the same facility, which took 10–15min.
For the website experience, the participants were asked to explore the official web-
site of the store and then completed the Qualtrics questionnaire. e survey first asked
whether they actually visited the website. If they answered that they did not, participants
were asked to stop the survey. On completion, they were also provided an opportunity
for a drawing selection as compensation.
Measurements
e survey questions were developed based on earlier studies. Arousal (e.g., not
aroused—aroused) and pleasure (e.g., annoyed—pleased) were measured by a 7-point
Likert scale of four semantic items each, adopted from Donavan and Rossiter (1982).
Store attractiveness (e.g., unattractive—attractive) was measured by a 7-point Lik-
ert scale of three semantic scales adopted and modified from Baek etal., 2018; Orth &
Wirtz 2014. Respondents narrated how much they felt each item during the store expe-
riences when answering arousal, pleasure, and store attractiveness. Respondents indi-
cated the degree to which they agreed with the statement, using a 7-point Likert scale
Table 2 Descriptive analysis of demographic information (n = 213)
Variable Category N % Variable Category N %
Age Mean = 20.94 SD = 2.60
Min. = 18 Max. = 34
N = 213
Ethnicity Caucasian 143 67.14
Black or African American 12 5.63
American Indian or Alaska Native 0 0.00
Asian 47 22.07
Gender Female 166 77.93 Native Hawaiian or Pacific Islander 0 0.00
Male 47 22.07 Other 11 5.16

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(1 = “strongly disagree” to 7 = “strongly agree”). Store familiarity, the moderator, was
measured by one item modified from Netemeyer etal. (2004) (i.e., e e XYZ is a
store of apparel and fashion products I am familiar with). e respondents answered
with either “Yes” or “No.”
e measurements are summarized in Table3. Additionally, in order to evaluate VR
respondents’ opinions about the VR experience, the participants responded to an open-
end question: “How was this VR experience?”.
Results
e data analyses were conducted using JMP 14.2. Exploratory factor analysis (EFA) on
maximum likelihood with varimax rotation confirmed that all items were acceptable
with factor loadings over 0.5 (Hair etal., 2010). Cronbach’s alpha for all variables was
over 0.7, presenting a satisfactory level (Hair etal., 2010). Table3 shows the results of
EFA and reliability tests.
Hypothesis testing
e study considered that previous VR experience can be an important factor impacting
VR users’ arousal and pleasure. at is, whether the VR store experience is the consum-
ers’ first use of VR or not was regarded as an influential determinant. us, this study
tested whether VR- experienced users, who already had an experience using VR (coded
as 1), and first-time users, who had never used VR (coded as 2), were differently aroused
and pleased by the VR store experience in this experiment. e regression results con-
firmed that there are no differences in arousal (
β
=−0.24, p = 0.32) and pleasure (
β
=0.17, p = 0.44) caused by previous VR experience. Hence, the study did not control the
effect of previous VR experience for further hypothesis testing.
Table 3 Exploratory factor analysis and reliability
Scale items Factor loading Eigen value Variance
explained (%) Cronbach’s alpha
Arousal
2.20 55.06 0.82
Not aroused—aroused 0.65
Sleepy—wide awake 0.79
Calm—excited 0.78
Sluggish—Frenzied 0.73
Pleasure
3.13 78.20 0.93
Depressed—contented 0.86
Unhappy—happy 0.90
Unsatisfied—satisfied 0.88
Annoyed—pleased 0.90
Store attractiveness
2.33 77.74 0.91
Unattractive—attractive 0.80
Bad—good 0.90
Unfavorable—favorable 0.94

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Hypotheses were tested using regression analyses by coding the website as 1 and VR
as 2. e results are summarized in Table4 and show that the VR store experience elic-
ited greater arousal (
β
=0.72, p < 0.001) and pleasure (
β
=0.51, p < 0.001) than the website;
thus, H1a and H1b were supported. H2 investigated the moderating effect of store famil-
iarity between store experience and arousal (H2a) and pleasure (H2b). e moderating
regression models (H2a and H2b) displayed in Table4 were not significantly changed
from the original regression models (H1a and H1b). us, it was concluded that there
was no evidence of a moderating effect due to store familiarity, rejecting H2a (F = 1.47,
β
=−0.12p = 0.23) and H2b (F = 0.78,
β
=−0.09, p = 0.38). Finally, consumers with greater
arousal (
β
=0.49, p < 0.001) and pleasure (
β
=0.71, p < 0.001) were more likely to perceive
the store as attractive, providing support for H3a and H3b.
Sentiment analysis andtext analytics ofparticipants’ opinions aboutVR store experience
e sentiment analysis and text analytics were conducted using the Tidytext package in
the R studio software. First, the sentiment analysis was used to score the valence of opin-
ions (i.e., positive or negative) using Bing Liu’s lexicon (Liu, 2012). e results revealed
82.30% positive and 17.70% negative words. Figure2 shows the most common responses
revealed by sentiment analysis. e left chart shows the negative word sets, while the
right one presents positive words. Among the positive words, “cool” (n = 32), “fun”
(n = 10), and “enjoyed” (n = 9) were ranked as the top three, followed by realistic, pretty,
enjoyable. “Blurry,” “dizzy,”, and “hard” were mentioned three times each by participants,
and ranked as the most commonly used negative words. Other negative words related to
the physical discomfort were “sore,” “sick,” “headaches,” and “fall.”
is study further conducted a semantic network analysis to understand how the men-
tioned words were related to each other. First, the top ten most frequently used words
were selected: “store,” experience,” “cool,” “VR,” “feel,” “fun,” “enjoyed,” “time,” “music,” and
Table 4 Hypotheses testing results
* p < .05, **p < .01, ***p < .001
DV IV β SE t VIF
H1a Arousal Store experience .72 0.16 24.62*** 1.00
R2 = .09, F-value = 21.30, p-value = .000
H1b Pleasure Store experience .51 0.15 3.37*** 1.00
R2 = .05, F-value = 11.33, p-value = .000
H2a Arousal (moderator) Store experience .72 0.16 4.58*** 1.00
Store familiarity .19 0.05 0.27 1.01
Store experience*Store familiarity − .09 0.10 − 1.21 1.00
R2 = .01, F-value = 7.59, p-value = .000, F change = 1.47, Sig. F change = .23
H2b Pleasure (moderator) Store experience .50 .15 3.27** 1.01
Store familiarity .06 .05 1.20 1.01
Store experience*Store familiarity − .09 .10 − .88 1.00
R2 = .06, F-value = 4.50, p-value = .01, F change = .78, Sig. F change = .38
H3a Store attractiveness Arousal .49 .05 9.47*** 1.00
R2 = .30, F-value = 89.73, p-value = .000
H3b Store attractiveness Pleasure .71 .04 16.57*** 1.00
R2 = .57, F-value = 274.51, p-value = .000

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“realistic”. en, this study checked what two words were commonly reported together.
is study identified several pairs of representative topic words: “experience; store,” “feel;
store,” “cool; store,” “experience; cool,” actual; store,” and “enjoyed; experience.” ere
were also negative words: “bit; dizzy.” Fig.3 presents how the words are related. ere
are 23 nodes and 28 relationships.
To observe this more broadly, we further used Gephi 0.9.2. to draw a wider range of
relationships based on representative words. Figure4 shows the relationships among
the entire word sets mentioned by the respondents after deleting words that were men-
tioned only once. In the figure, the nodes that are commonly mentioned are written in
larger font sizes. e stronger (or weaker) relationships between any two words are pre-
sented as thicker (or thinner) lines.
Fig. 2 Sentiment analysis results: Commonly mentioned negative vs. positive words
Fig. 3 Semantic network analysis result using R: The relationship of two words reported commonly together

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Conclusion anddiscussion
Retailers attract consumers through a unique shopping experience. One unique shop-
ping experience consumers can enjoy online is through virtual reality (VR), as it can
convey a store atmosphere without a physical visit. With this in mind, this study pro-
posed a research framework based on the stimuli-organism-response model and the
schema theory, tested with data collected in the U.S.
e results of this study indicated that the 360-degree VR store video can arouse
(H1a) and please (H1b) consumers more than traditional websites can, supporting the
literature. e finding of the study is in line with earlier research in the tourism field
that found the effectiveness of VR, compared to 2D videos and static photos (Deng
etal., 2019; Griffin etal., 2017). By overcoming the shortcoming of the website, VR
amplifies consumers’ arousal and pleasure states. Furthermore, the findings are con-
sistent with previous VR research in retailing, which confirmed that feelings present
through VR positively influences pleasure and arousal (Park etal., 2018).
ere was no support for a moderation effect of store familiarity between store
experience (i.e., VR vs. website) and consumers’ emotional states (H2). e results
conflicted with the literature on schema theory, because lower familiarity should be
easier to change the perception towards a store than higher familiarity (Kent & Allen,
1994), presenting higher emotional states. e findings indicate that regardless of
Fig. 4 Semantic network analysis result using Gephi

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consumers’ store familiarity, VR is more effective in eliciting positive feelings com-
pared to websites. is implies that the helpfulness of VR in evoking arousal and
pleasure is not mitigated either in well-known or less-known companies. One possi-
ble explanation for this result is that consumers may have a weaker schema regarding
VR than websites. Because the VR store experience remains novel to the consumers
(Pizzi etal., 2019), it may elicit a greater change in their responses than the website.
erefore, the weaker schema related to VR may have a stronger impact on consum-
ers’ responses than the weaker schema related to store familiarity itself. Accordingly,
the findings offered the new empirical suggestion that store-related schema may have
a weak explanation in the VR context.
Further, consumers’ heightened arousal and pleasure states were found to lead them
to perceive a store as more attractive (H3). e outcome is in accordance with the pre-
vious literature that store-evoked arousal and pleasure augment positive consumer
responses to the retailers (Eroglu etal., 2003; Ha & Lennon, 2010). Earlier studies also
found that heightened arousal and pleasure through online store atmosphere and tech-
nology-related shopping experience elicited positive responses from consumers (Das &
Varshneya, 2017; Dennis etal., 2014; Wu etal., 2008). is study further confirmed that
store-elicited arousal and pleasure led consumers to find the store more attractive.
According to the findings of the sentiment analysis, consumers felt more positive emo-
tion than negative toward the 360-degree-based VR-video experiences. e VR store
experience was connected to positive words, such as “cool,” “feel,” “actual,”, and “enjoyed.”
Furthermore, semantic network analyses discovered how the commonly mentioned
words are related to each other. Several pairs, such as “experience; store,” “feel; store,”
and “actual; store” were identified. ese imply that consumers were able to experience
and feel the store through VR videos. However, negative words were also identified by
text analytics. ese were related to VR quality, such as “blurry,” and user-related, such
as “dizzy,” “sore,” “sick,” and “headaches.” Previous studies have discussed several nega-
tive emotions and side effects resulting from VR experiences, called VR sickness (Chang
etal., 2020; Kim etal., 2018). e major symptoms of VR sickness include fatigue, nau-
sea, headache, blurred vision, and dizziness. e study results denote that VR videos still
have room for improvement to offer a better experience, supporting previous literature.
is study contributes to the literature in at least two respects. Academically, first, this
study tested the VR store experience developed in an actual retail store. Previous studies
pointed out the need for virtual environments other than 3D types (Gabisch, 2011) and
of a virtual shop to portray a real-life retail store (Lau & Lee, 2018). While the replication
of the actual place was used in tourism fields (e.g., Deng etal., 2019; Griffin etal., 2017),
and a study in retail incorporated only static VR photos (Baek etal., 2020), this study
extended the use of VR videos to the actual store context that was untested in previous
literature.
Second, by using the store-recorded VR videos that can sufficiently deliver store
atmosphere and environments, this study was able to link the VR store experience to
consumers’ heightened emotional states and perception towards a store. While it is well
accepted in the literature that VR store experience can lead to consumers’ behavioral
intentions (Domina etal., 2012; Gabisch, 2011; Lau & Lee, 2018), the present study fur-
ther focused on the perception towards a store atmosphere by emotions. e results

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added to the literature with regard to the role of customers’ VR store experience provok-
ing emotions, applying the SOR model. Also, the exploration of an actual store through
VR discovered that eliciting positive feelings led to heightened perceptions of store
attractiveness, which has received little attention in the existing literature, compared to
other responses. is discovery is unique, in that consumers feel the same store to be
more attractive when experiencing the store through VR than websites. is study fur-
ther added to the SOR literature in retail and marketing by incorporating a less tested
variable—perceived store attractiveness—and by extending the model to compare the
VR and website experiences.
ird, this study added to the literature by performing text analytics. Previous stud-
ies have mostly conducted experimental studies to reveal the effectiveness of VR and
explain theoretically explained hypotheses. is study adds to this understanding by
directly asking and exploring VR users’ opinions. In particular, the emotions evoked by
consumers beyond arousal and pleasure were examined, illustrated by words such as
“cool,” fun,” “enjoyed,” “blurry,” “scared”, and so forth as shown in Fig.2. ese seman-
tic words provide the future direction of VR research observing various emotions other
than arousal and pleasure driven by VR and leads to subsequent consumer responses.
On a practical side, first, with the discovery of the higher effectiveness of VR, com-
pared to websites, this study suggests that retailers can utilize VR to create the per-
ception of an attractive store environment, thereby bringing more consumers into the
store (e.g., Baek etal., 2018; Darden etal., 1983; Orth & Wirtz, 2014). is presents an
approach for online retailers to overcome physical limitations to offer store environ-
ments and atmosphere. Especially because the store attractiveness is led by heightened
emotional states, arousal and pleasure, the VR store experience is suggested to be cre-
ated in such a way as to enhance consumers’ and arousal and pleasure. In other words,
retailers need to evoke consumers’ positive emotions through the shopping experience,
to help consumers perceive the store attractive.
Second, this study found that the effectiveness of VR is consistent, regardless of con-
sumers’ familiarity with the store. erefore, any store, regardless of renown, can benefit
from adopting VR technology.
ird, this research suggested a way to convey the store atmosphere to consumers
without having them physically visiting the store, viz., recording VR store videos and
uploading them to the website. e VR store experience used in this study consisted
of 360-degree-based VR videos that recorded a physical store. Unlike the suggestion
from earlier studies to create virtual stores graphically, this study recommends a simple
method for any retailer. Retailers can record and post 360° store videos using 360° cam-
era on their website or other video portals (Griffin etal., 2017; Lawton & Stapley, 2020),
in addition to 2D store images. If the retailers upload VR video materials on their web-
site, consumers can watch the videos with VR headsets from any location. Because sim-
ple 360° VR videos can encourage customers to perceive the store as attractive, and both
the camera and VR headsets are inexpensive and widely available already, this method
can be cost-effective for retailers, including small businesses.
ird, text analytics that analyzed an open-ended question about VR store experience
offered more understanding to retailers. Based on the results of semantic network analy-
ses, retailers are recommended to create more realistic but less dizzy VR environments

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and to decrease any possibility to cause discomfort. Some discomforts, conveyed
through words such as “sore,” “blurry,” and “dizzy”, would need to be solved by the manu-
facturers of VR equipment. us, this study generates managerial implications and rec-
ommends that the VR manufacturers as well as retailers consider these discomforts.
Limitations andfuture research
Despite the useful implications of this research, there are some limitations. First, the VR
technology used in this study is the 360-degree-based VR video. is method is inexpen-
sive for retailers but does not allow consumers to control the environment sufficiently.
To create a more interactive atmosphere, other modes of VR usage can be included in
further studies. Second, this study was conducted in a small boutique setting, where
store familiarity was measured. For future studies, two stores varying by popularity can
be used for experiments, such as comparing a large company (e.g., well-known glob-
ally) with a small company (e.g., its fame limited to a local area). ird, this study tested
whether the VR store experience can help consumers find the store attractive. Further
research is needed to explore whether this prediction of behavioral intentions through
store attractiveness is consistent in the VR shopping context. For example, the relation-
ship between store attractiveness displayed through VR and store visit intention can be
tested. Fourth, we could not ensure that the same products were displayed in the VR
videos and the website. e focus of the study was to compare the overall store experi-
ence delivered through the VR videos and website atmosphere rather than to examine
the perceptions of individual items. us, future research may compare how the same
items are perceived differently across these two stimuli.
Acknowledgements
Not applicable.
Authors’ contributions
BJ initially offered research idea and built research framework. BJ and GK were major contributors in writing the
manuscript. BJ and GK collected and analyzed data. MM and LR reviewed and revised the research framework and the
manuscript. All authors read and approved the final manuscript.
Funding
Not applicable.
Availability of data and materials
Not applicable.
Declaration
Competing interests
The authors declare that they have no competing interests.
Author details
1 Albert Myers Distinguished Professor, Department of Textile and Apparel, Technology and Management, North Carolina
State University, Raleigh, USA. 2 Doctoral Candidate, Department of Textile and Apparel, Technology and Management,
North Carolina State University, Raleigh, USA. 3 Professor, Department of Textile and Apparel, Technology and Manage-
ment, North Carolina State University, Raleigh, USA. 4 Associate Professor, Depar tment of Textile and Apparel, Technology
and Management, North Carolina State University, Raleigh, USA.
Received: 30 October 2020 Accepted: 14 March 2021
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