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Why and who will adopt extended reality technology? Literature review, synthesis, and future research agenda


Abstract and Figures

The advent of extended reality is revamping the way people experience the physical and the virtual environments, from observation to immersion. XR is an umbrella term that encompasses both augmented reality and virtual reality. Microsoft HoloLens is one example of AR smart glass that superimposes digital information onto a user’s field of view, while Oculus Rift is a type of virtual reality headset that allows users to experience and interact with a 3D world that does not actually exist. Despite the promising outlook, this nascent technology has been shrouded by uncertain possibilities, making the adoption of XR technology much slower than expected. Moreover, the interdisciplinary applications of XR technology have led to scattered scholarly works and fragmentary insights to be translated into practice. Thus, there is a pressing need for a critical review and synthesis of prior XR research in order to strengthen this emerging field of IS. To accomplish this, the current study identifies and analyzes a total of 45 articles through an extensive literature search. As a result, this study identifies the major antecedents and factors significant to XR adoption classifies and map them onto the reference models. A review of relevant literature also uncovers those areas where research is lacking – and subsequently details future research directions with specific agenda to fill these gaps.
Content may be subject to copyright.
Wearable XR-technology: literature review,
conceptual framework and future research directions
Stephanie Hui-Wen Chuah
Institute of Innovation and Circular Economy,
Asia University,
Taichung, Taiwan
Please cite as: Chuah, S.H-W. (2019). Wearable XR-technology: literature
review, conceptual framework and future research directions. International
Journal of Technology Marketing, 13(3/4), 205-259
Wearable XR-technology: literature review,
conceptual framework and future research directions
Abstract: Extended reality (XR) has revamped the way people experience
the physical and the virtual environments, from observation to immersion.
XR is an umbrella term that encompasses both augmented reality (AR) and
virtual reality (VR), among others. Despite the promising outlook, this
nascent technology has been shrouded by uncertain possibilities, making
the adoption of XR technology much slower than expected. Moreover, the
interdisciplinary applications of XR technology have led to scattered
scholarly works and fragmentary insights to be translated into practice.
Thus, there is a pressing need for a critical review and synthesis of prior XR
research in order to strengthen this emerging field in IS. To accomplish this,
the current study identifies and analyses a total of 45 articles through an
extensive literature search. As a result, this study identifies the major
drivers, barriers, and boundary conditions to XR adoption, classifies and
map them into a holistic conceptual model.
Keywords: extended reality; XR; augmented reality; virtual reality;
wearable; literature review; future research; technology adoption.
Since we cannot change reality, let us change the eyes which see reality.
Nikos Kazantzakis
1 Introduction
Extended reality (hereafter referred to as XR)the next generation computing platform
has changed the way we work, learn, connect, and play by bridging the physical world to
a digital one (Rauschnabel et al., 2017). It also transforms how enterprises train workforce,
serve customers, design products, and manage their value chain (Chmielewski, 2017;
Porter and Heppelmann, 2017). XR is an umbrella term encapsulating augmented reality
(AR), virtual reality (VR), and mixed reality (MR). While AR integrates virtual and real
objects in a real-time display, VR allows users to control and navigate their movements in
a stimulated real or imagined world (Ro et al., 2018; Suh and Prophet, 2018). Both
technologies are often melded together (i.e., MR) to induce more immersive experience.
Whether watching 360° movies, playing games, walking through 3D models of the
buildings, travelling through the universe, or any other immersive experiences, XR devices
create the illusion to make people feel as if they are in an entirely new digital world
(O’Donnell, 2018). Such technologies have been praised for its ability to create virtual
tours in the stores and destinations, rehabilitate brain injury, and virtually inspect the
interior and exterior design of a car which no existing technology could do (Sheikh, 2016).
Given its enormous potential, XR technology has been increasingly applied and studied in
a plethora of fields, ranging from tourism (Jung et al., 2015), education (Kerawalla et al.,
2006), retailing (Yim et al., 2017), gaming (Rauschnabel et al., 2017) and healthcare
(Glegg et al., 2017) to manufacturing (Choi et al., 2015).
Recent forecasts by International Data Corporation (IDC) anticipate the global
shipments of AR/VR headsets to soar from 4.2 million units in 2018 to 53.1 million units
by 2022, achieving a compound annual growth rate (CAGR) of 88% (IDC, 2018a). By
2020, the sales of AR/VR devices are expected to generate a staggering $150 billion in
revenue (Gaudiosi, 2015). Given its rise, Google, Alibaba, Warner Bros, and other firms
have invested approximately $800 million of venture capital into an AR startup called
Magic Leap. Likewise, large brands like Coca Cola, McDonald’s and Disney have rolled
out AR/VR applications to create an enchanting experience for customers. Total spending
on AR/VR is estimated to increase by 92% to hit 17.8 billion in 2018 and to reach as high
as $215 billion by 2021 (IDC, 2018b). Seeing the rising hype in the marketplace, Jabil’s
recent survey documents that “AR/VR will become mainstream within five years” (Jabil,
2018) and Goldman Sachs (2016, p.4) concludes that “VR/AR has the potential to spawn
a multibillion-dollar industry, and possibly be as game changing as the advent of PC”.
Yet, despite the strong growth potential for XR, such technologies still struggle to gain
traction among consumers and enterprises (Herz and Rauschnabel, 2018). Market research
reports have indicated that cost, technical limitation and performance issues, bulky
hardware, among others, are the barriers that hold back XR from becoming mainstream
(Jabil, 2018; Perkins Coie, 2018). For XR technology to be successfully adopted, these
obstacles need to be overcome, and at the same time, further strengthen the benefits
(Adapa et al., 2018). While an increasing number of studies have investigated the factors
leading to XR market success, these studies so far seem fragmented and a thorough review
of existing works remains scarce, thus impeding the progress of this field. The exception
is a study by Suh and Prophet (2018) who have consolidated and mapped the factors
associated with XR use onto the stimulus-organism-response (S-O-R) framework. The
conceptual framework illustrates how technological (e.g., sensory and perceptual stimuli)
and content features of XR lead to positive (e.g., learning effectiveness) and negative
outcomes (e.g., cognitive overload) through the mediation of users’ cognitive (e.g.,
immersion) and affective (e.g., pleasure) responses. However, the list of factors is not
exhaustive and they focus mainly on the technology and media aspects of XR, thus
disregarding the fact that XR device is also a fashion accessory (Herz and Rauschnabel,
2018). Having identified these gaps, the present study systematically reviews the relevant
XR studies that have been conducted, summarises previous findings, discusses the relevant
theories, as well as classifies various factors that impact XR adoption. To facilitate the
analysis of the literature, this study develops reference models that explain why individuals
and firms adopt XR technology. A customer types matrix is also proposed to explain who
will buy XR devices from the lens of technology, fashion, and media. By analysing prior
XR research, this study is able to identify gaps in the extant literature and to outline a
research agenda for further study of this new phenomenon.
This study contributes in several ways to the body of knowledge on technology
acceptance. First, this study adopts a holistic approach and analyses user acceptance of
XR technology from multiple disciplines, theories, and perspectives. A synthesis of
existing studies can avoid repetition of similar works and unveil important gaps that could
otherwise be overlooked. Second, the two reference models of XR adoption proposed here
offer a guidance structure that allows future researchers to accumulate knowledge and to
interpret the existing research findings. Managerially, this study provides a comprehensive
pool of the drivers of XR adoption, which managers can use as a checklist to access the
performance of their XR devices or apps. Also, managers can use the customer types
(fashion-media-technology) matrix proposed in this study to determine the most effective
strategy to promote their XR devices to each customer segment.
2 XR: augmented reality vs. virtual reality
Recent years have witnessed rapid evolution of smart mobile technologies from ‘always
online’ to ‘always be there’. The breakthrough of smart devices was the smartphones (e.g.,
Apple’s iPhone) in 2007, followed by tablets (e.g., iPad), smartwatches (e.g., Pebble) in
2013, and smart glasses (e.g., Google Glass) in 2014. This diffusion is not caused by the
need of seamless multimedia data communication but also by the need for escape from
real-life. Nowadays, consumers are not just ‘always and everywhere’ connected to the
internet through their smartphones and tablets. The arrival of XR technology has allowed
users to experience a sense of presence in the virtual environments as though they were
real. By blurring the lines between the physical and digitally stimulated worlds, XR
technology creates a sense of immersion while enhancing the realism of virtual experience
(Soliman et al., 2017; Suh and Prophet, 2018).
Definition of XR
XR an umbrella term including AR and VR has revolutionised the way people
experience their environment (tom Dieck and Jung, 2018). Rauschnabel et al. (2018b)
argued that AR and VR are different approaches, whereas contradictory to the Milgram
et al.’s (1995) continuumAR can range from unrealistic and functional ‘assisted reality’
to realistic ‘MR’. As the mid-point of reality-virtuality continuum, AR can be defined as
“the digital overlay of information (or image) into users’ direct surrounding using devices
such as smartphones or wearable smart glasses” [tom Dieck et al., (2018b), p.45]. For
example, smartphone users can download civilization AR app from BBC to explore
various historical artefacts ‘out of the display’ and view them in 3D mode. Wearable smart
glasses, on the other hand, are wearable devices with installed AR apps.
As a type of ‘fashnology’ (a combination of fashion and technology), ARSGs are worn
like regular glasses and superimpose virtual information into the user’s perception of
physical world in real time through the embedded cameras, accelerometers, GPS, and
other sensors (Rauschnabel, 2018b; Rauschnabel et al., 2016). Compared to Google Glass,
one of the first commercially launched ARSGs, Microsoft HoloLens does not have one
prism to display information but rather realistically incorporates 3D hologram images into
a user’s field of vision. As such, AR enhances the user’s experience in the realworld rather
than substituting it.
In contrast to AR, VR blocks out the real world and electronically set-up the objects
(e.g., sound, videos, graphics, and texts) in the entire real life setting in other words, in
a fully artificial environment (Bonetti et al., 2018; Yim et al., 2017). VR’s capability to
simulate intricate, real-life situations provides new possibilities for users to
psychologically immerse themselves in the virtual, 3D world, and experience the feeling
of ‘being there’ (van Kerrebroeck et al., 2017; Tussyadiah et al., 2018b). Therefore, VR
has been touted as an immersive digital media that creates a three-dimensional, virtual
imaginary, and interactive media environment that a user conceives much as he/she was
in the real world (Herz and Rauschnabel, 2018). Similar to AR devices, VR devices are
mobile by nature, either portable (e.g., smartphones) or wearable (e.g., glasses, headsets,
and head-mounted displays). Compared to wearable devices, Google Cardboard which
places a smartphone into a cardboard viewer is to promote affordable VR experience.
Using Google Cardboard or Google Daydream VR, users can swim with sharks in the
ocean or being transported to the stage of the Broadway hit, Hamilton. VR devices can
also give users ‘out-of-body experiences’ by allowing them to experience ‘death’ without
dying. This can help assuage the fear of death.
Fashnology and fashmedianology
As Adapa et at. (2018) pointed out, consumers based their adoption decision of wearable
technologies not only on technological functions, but also on design aesthetics In support,
Rauschnabel et al. (2016) found that the majority of the users (75%) regard ARSGs as
fashion and technology, and they termed these users as ‘fashnologists’. Compared to
ARSGs, VR headsets allow users to escape into different bodies and environments,
providing a much more immersive experience (Herz and Rauschnabel, 2018). Thus, we
term XR as a type of ‘fashmedianology’ – a unique blend of fashion accessory, immersive
media, and technology gadget. We argue that users who view XR solely as a technology
focus on the ‘usability’ aspect of the device in making their adoption decisions, whereas
those who view XR from a fashion perspective value the ‘wearability’ aspect. For users
who perceive XR as a media, the ‘sensibility’ aspect the device plays a crucial role in their
adoption decision. To facilitate a better understanding of this tripartite perspective, this
study develops a customer types matrix with media optimism along the horizontal axis and
technology optimism along the vertical axis. Figure 1 shows the four quadrants of the
customer types matrix with low or high media optimism linked to low or high technology
optimism. Each quadrant is further divided into low or high fashion consciousness.
The upper right quadrant represents individuals with high levels of technology and
media optimism. Such individuals can be described as pragmatic but unrealistic.
Individuals here are optimistic about futuristic technology and they believe that XR
technology can make their lives more efficient and enjoyable as well as improve their
social relationships. Therefore, they use XR technology for practical reasons. At the same
time, this group of individuals are also unrealistic in the sense that they want to detach
from reality and immerse themselves in the non-physical environment. In particular,
individuals who score high in fashion consciousness might want to achieve ‘use-wear-
sense integration’. They prefer wearing XR device that is visually appealing while not
losing its sophisticated features and a sense of realism.
Figure 1 Customer types (fashion-media-technology) matrix
The upper left area is the area that delineates pragmatic and realistic individuals who have
comparatively low levels of media optimism. Instead of achieving a sense of escapism in
the virtual world, individuals in this area prefer using XR technology for professional
development (e.g., corporate training). While the technology features remain important,
high fashion-conscious individuals might purchase aesthetically designed devices only for
the sake of achieving ‘use-wear balance’.
The lower right quadrant in the model is the area that depicts fantastic but
technological pessimist. Individuals in the area do not appreciate or even see the typical
benefits technology can bring. Rather, these individuals use XR technology to do
something they unable to do in real-life or beyond their imagination e.g., being present
and explored the fantasy land. It is also worth noting that individuals who score high in
fashion consciousness might choose well-designed devices only in order to achieve a
balance between a sense of aesthetic and realism or ‘wear-sense balance’.
The lower left area represents individuals who are neither technology nor media
optimism, and hence, we term them as technology and media pessimist. Nonetheless, some
‘fashionistas’ who score high in fashion conscious might still purchase the XR devices
because of their virtual appearance.
ARSG (individuals)
high functional benefits and social conformity of smart glasses
are more likely to adopt such wearables. The strength of these
effects is moderated by consumers’ levels of openness to
experience, extraversion and neuroticism
Rauschnabel and
Ro (2016)
To understand the drivers and barriers
of smart glasses from the view of
potential users
ARSG (individuals)
TAM N = 201
analyses/descriptive statistics
Functional benefits, ease of use, individual difference variables,
brand attitudes, and social norms are the key drivers of smart
glasses adoption, whereas self-presentation benefits and
potential privacy concerns are not
Hein and
To discuss the opportunities of smart
glasses for firms
ARSG (enterprise social networks,
Conceptual A conceptual model is proposed to illustrate theunderlying
mechanisms that drive smart glasses ESN adoption on a firm
level. On the individual employee level, the antecedents to
active and passive use are proposed
et al. (2016)
To understand consumer perceptions
toward smart glasses (as a type of
technology, a fashion accessory, or
ARSG (individuals)
To examine people’s expected
gratifications from ARSG usage in
different contexts
ARSG (individuals)
TAM Study 1 (N = 266)
Study 2(N=1,682)
U&GT N = 228
The perception of smart glasses as technology, fashion, or
fashnology is influenced by the characteristics of the product
and the consumers’ product familiarity
Utilitarian, hedonic, sensual, social, and symbolic needs drive
ARSG usage intention. Wearable comfort and socialising have
no significant effects for ARSG use in private, whereas life
efficiency has no significant effects for ARSG use in public
Ro et al. (2018) To provide relevant definitions and
discuss potential success factors of
ARGS adoption
To explain how ARGS can increase
firm value
ARSG (firms)
Conceptual Internal value creation factors (e.g., R&D, collaboration, and
process efficiency) are distinguished from external value
creation (e.g., new apps and customer interactions)
Notes: ANOVA = analysis of variance; ARIT = augmented-reality interactive technology; SEM = structural equation modeling; TAM = technology acceptance model;
TOE = technology-organisation-environment; TPB = theory of planned behavior; TRA = theory of reasoned action; TTF = task-technology fit;
U&GT = uses and gratification theory; UTAUT = unified theory of acceptance and use of technology.
Table 1
Prior research on wearable-XR adoption
Research objective and context
Main theory
Research methodology and design
Key findings
et al. (2015)
To investigate the role of personality in
predicting smart glasses adoption
Big five model
of human
Study 1 (N = 146)
Study 2 (N = 201)
Open and emotionally stable consumers tend to be more aware
of Google Glass. Consumers who perceive the potential for
implementation of at a museum
AR (firms)
Semi-structured interviews
Content analysis
added benefits to both visitors and staffs are identified
Hein et al. (2018) To understand how do consumers
evaluate the potential opportunities and
threats of smart glasses for society.
To understand how these potential
opportunities and threats related to
consumers’ desired andanticipated
success of smart glasses
ARSG (societies)
Exploratory N = 364
Computer-assisted personal
Consumers rate the societal risks higher than the societal
benefits. They also rate the anticipated success higher than
the desired success. Consumer perceptions of smart glasses
differed by gender, familiarity level, and their attitudes
toward the manufacturer brand.
For potential benefits, consumers’ beliefs in general
usefulness and safety improvements enabled by smart
glasses increase their expected success. On the other hand,
societal progress and perceived usefulness enhance
consumers’ desire for Google Glass’s success
Kalantari and
To understand how people to react to
ARSG (individuals)
TAM N = 116
Descriptive statistics/ multiple
regression analyses
Consumers’ adoption decision is driven by various expected
benefits, including usefulness, ease of use, and image. Hedonic
benefit has no significant effect on adoption intention. The
influence of the descriptive norms on the adoption intention
outperforms the influence of the injunctive norms
To conceptualise how ARSGs can
address fundamental human needs, and
which factors need to be incorporated
in understanding the psychological
mechanisms that explain consumers’
reactions to them
ARSG (individuals)
U&GT Conceptual Five categories of need (cognitive, tension-release, social
integrative, affective, and personalintegrative) are each
conceptually linked to a broader category of gratifications
(utilitarian, hedonic, social, sensual, and symbolic) consisting
of several specific factors. The strengths for the effects of
gratifications on consumer reactions to ARGSs might differ
based on the usage context, device, and consumer. Physical,
social, psychological, and financial are identified as potential
risk factors
Notes: ANOVA = analysis of variance; ARIT = augmented-reality interactive technology; SEM = structural equation modeling; TAM = technology acceptance model;
TOE = technology-organisation-environment; TPB = theory of planned behavior; TRA = theory of reasoned action; TTF = task-technology fit;
U&GT = uses and gratification theory; UTAUT = unified theory of acceptance and use of technology.
Table 1
Prior research on wearable-XR adoption (continued)
Research objective and context
Main theory Research methodology and design
Key findings
Cranmer et al.
To understand the internal
stakeholders’ perceptions towardthe
- N = 9
- UK
Respondents generally support the AR implementation. A
variety of ways in which AR can be implemented to provide
No. Study Research objective and context Main theory Research methodology and design Key findings
Akçayır et al.
To investigate whether there is a
significant difference between the lab
skills and attitudes of students who use
AR technology in their science labs
and those who do not
To elicit the students’ and instructors’
opinions about and suggestions for the
use of AR technology in science labs
AR (science laboratory)
- N = 38
Semi-structured interviews
The use of AR technology not only enhance the students’
laboratory skills but also improve their attitudes toward physics
Yilmaz (2016) To elicit teachers’ and children’s
opinions on educational magic toys
To determine children’s behavioural
patterns and their cognitive attainment,
and the relationship between them
while playing with EMT
AR (early childhood education)
TAM N = 63 (30 teachers and 33 children)
Turkey-mixed-method (survey,
observation, and interview)
Descriptive, content, and
correlational analyses
All teachers and children like EMT. When teachers perceive the
EMT as useful and ease to use, their attitudes will be positive.
Children prefer mostly pointing, responding, inspecting and
turning behaviors when playing with the EMT. They tend to
have low levels of cognitive attainment and there is a
relationship between their behaviors and cognitive attainment.
While appearance description is related to the behaviors of
pointing, responding and turning, extensive description is
related to the behaviors of commenting and questioning. When
the children are more active in EMT, they display more
cognitive attainment in terms of both descriptions
Jung et al. (2015) To examine the relationship between
the perceived quality (content, system,
and personalised service) of AR apps
and tourist satisfaction to predict their
recommendation intention
To explore how personal
innovativeness moderates the
relationship between perceived quality
and AR satisfaction
AR (theme park)
DeLone &
N = 241
South Korea
Content, system, and personalised service quality significantly
affect users’ satisfaction and their intention to recommend the
AR apps, with personal innovativeness moderates some of the
relationships. AR system quality matters when personal
innovativeness is high, whereas AR content quality matters
when personal innovativeness is low
Chung et al.
To conceptualise crucial factors of AR
in terms of personal, stimulus, and
situational factors
AR (heritage site)
N = 145
South Korea
Personal (technology readiness), stimulus (visual appeal), and
situational factors (facilitating conditions) prompt visitors use
AR and visit a heritage site through the belief andattitude
toward AR
Notes: ANOVA = analysis of variance; ARIT = augmented-reality interactive technology; SEM = structural equation modeling; TAM = technology acceptance model;
TOE = technology-organisation-environment; TPB = theory of planned behavior; TRA = theory of reasoned action; TTF = task-technology fit;
U&GT = uses and gratification theory; UTAUT = unified theory of acceptance and use of technology.
Table 1
Prior research on wearable-XR adoption (continued)
applicable to the urban heritage
tourism context
AR (urban heritage tourism)
Thematic analysis
quality, system quality, costs of use, recommendations,
personal innovativeness and risk as well as facilitating
tom Dieck et
al. (2018b)
To investigate how visitor experience
using AR affect visitors’ satisfaction,
memory, and eventually their
engagement with science experience
AR (science festival)
Pine and
N = 220
Esthetics is a strong predictor of escapism, education, and
entertainment, suggesting that experience economy in the AR
science festival context does not consist of four independent
dimensions. These three realms of experience economy
influence visitors’ satisfaction and memories and, ultimately,
their engagement with science experiences
tom Dieckand
Jung (2017)
To explore stakeholders’ perceived
value regarding the implementation of
AR to enhance the museum experience
AR (cultural heritage tourism)
- N = 24
Focus groups/interviews
AR has economic, experiential, social, epistemic, cultural and
historical, and educational value from both internal and external
stakeholders’ perspectives
Paulo et al.
et al. (2018a)
To understand the factors that
influence users to adopt mobile AR in
Mobile AR (tourism)
To provide a theoretical reflection on
the phenomenon of embodiment
relation in technological mediation and
then assess the embodiment of
wearable AR technology in a tourism
AR (art gallery)
N = 335
N = 211
The proposed model explains 72 per cent of the variance in
behavioural intention to use mobile AR in tourism and 45 per
cent of the variance in use behavior
Technology embodiment is a multidimensional construct
consisting of ownership, location and agency, thus supporting
the notion of technology withdrawal. Technology embodiment,
in turn, enhances visitors’ enjoyment and overall experiences
interacting with exhibits in the art gallery
Olsson et al.
To understand potential users’
expectations and requirements of
mobile AR services
AR (shopping centers)
- N = 28
16 semi-structured interviews
Physical affinity program
User expectations of mobile AR is multifaceted and affected by
various elements of the service, (e.g., functionalities and
software features, information content, interaction,and
presentation). A set of design requirements (e.g., privacy and
control, reactivity, relevance, and reliability, easy and flexible
access, and distinct affordances) is identified
Notes: ANOVA = analysis of variance; ARIT = augmented-reality interactive technology; SEM = structural equation modeling; TAM = technology acceptance model;
TOE = technology-organisation-environment; TPB = theory of planned behavior; TRA = theory of reasoned action; TTF = task-technology fit;
U&GT = uses and gratification theory; UTAUT = unified theory of acceptance and use of technology.
Table 1
Prior research on wearable-XR adoption (continued)
Research objective and context
Main theory
Research methodologyand design
Key findings
tom Dieckand
Jung (2018)
To qualitatively investigate and
propose an AR acceptance model
Five focusgroups
N = 44
Seven external dimensions that influence young British tourists’
acceptance of mobile AR apps were identified: information
et al. (2015)
learning with young children inthe
AR (education)
To present a mobile AR travelguide,
namely Corfu AR, which supports
personalised recommendations
AR (tourism)
Video-recorded lessons of AR-
trained teachers
Video footage of traditional teaching
Audio-recorded interviewswith
N = 105
successfully adopting AR into classroom practice: flexible
content, guided exploration, and attention to the needs of
instituitional and curricular requirements
The functional properties of CorfuAR evoke feelings of
pleasure and arousal, which, in turn, influence the behavioral
intention of using it. There are no differences between users of
the personalised version and ones using the non-personalised
et al. (2018a)
tom Dieck et al.
To investigate which factors drive
ARSG adoption and whether people
care about their ownvs.otherpeople’s
ARSG (individuals)
To explore factors that drivetourists’
VR adoption and their behavioral
intentions toward the national park
VR (national park)
U&GT Study 1: quantitative (onlinesurvey)
N = 285
Study 2:qualitative (unstructured
N = 21
- N = 35
Exploratory, semi-structured
Thematic analysis
Expected utilitarian, hedonic, and symbolic benefits drive
consumers’ reactions to ARSGs. ARSGs threaten other
people’s, but not one’s own, privacy can strongly influence
users’ decision making.
Factors that influence tourists’ VR adoption can be divided into
four main groups: usability (perceived ease of use, comfort,
personalisation, perceived control), hedonic benefits
(enjoyment, experienced, realism), personal benefits (perceived
usefulness), and emotional benefits (place attachment)
Nunes and Filho
To analyse consumer behavior in
relation to Google Glass
ARSGs (individuals)
N = 8 discussions
Three categories (socially satisfied, socially constrained, and
early adopters) and two categories (enthusiasts and visionaries)
of consumers are found
Notes: ANOVA = analysis of variance; ARIT = augmented-reality interactive technology; SEM = structural equation modeling; TAM = technology acceptance model;
TOE = technology-organisation-environment; TPB = theory of planned behavior; TRA = theory of reasoned action; TTF = task-technology fit;
U&GT = uses and gratification theory; UTAUT = unified theory of acceptance and use of technology.
Table 1
Prior research on wearable-XR adoption (continued)
Research objective and context
Main theory
Research methodology and design
Key findings
et al. (2006)
To identify the potential of AR
technology to support teachingand
N = 133
Children using AR were less engaged than those using
traditional resources. Four design requirements necessary for
No. Study Research objective and context Main theory Research methodology and design Key findings
He et al. (2018) To examine the impact of information
type (dynamic verbal vs. dynamic
visual cues) and augmenting immersive
scenes (high vs. low virtual presence)
on visitors’ museum experience and
their subsequent purchase intentions
AR (museum)
Yim et al. (2017) To evaluate the effectiveness of AR as
an e-commerce tool using two products
sunglasses and watches
AR (online retailing)
- N = 225
Experiment and survey
Study 1: Online experiment
N = 258
Study 2: online survey
N = 801
SEM, sentiment analysis, and text
Compared with dynamic visual cues, dynamic verbal cues lead
to heightened willingness to pay more, such effectsare more
salient under the condition of high virtual presence. Such
effects can be explained by the psychological mechanism of
mental imagery
AR-based product presentations are superior to traditional web-
based product presentation in the effect on media novelty,
immersion, enjoyment, usefulness, attitude toward medium, and
purchase intention. The impact of interactivity/vividness on
usefulness and enjoyment is mediated by immersion
Huang and Liao
To investigate which factors may elicit
positive sustainable relationship
behaviour among consumers with
different levels of cognitive
ARIT (online clothing retailers)
typology of
N = 220
Presence has a positive effect on consumers’ perceived
usefulness, aesthetics, service excellence, and playfulness, and
ultimately their sustainable behavior. Consumers with high
cognitive innovativeness place more emphasis on usefulness,
aesthetics, and service excellence. In contrast, those with low
cognitive innovativeness focus on playfulness and ease of use
Baek et al. (2018) To examine the influence of AR
viewing on consumers’ purchase
intentions by considering the mediating
role of self-brand connection and the
moderating role of narcissim
AR virtual mirrors
Study 1 (N = 174)
Study 2 (N = 209)
Experiment and survey
Consumers tend to form higher self-brand connections and
purchase intention when viewing themselves trying a product
via a virtual mirror, rather than when viewing professional
models wearing the product. Narcissistic people show
pronounced positive self-viewing effects, but non-narcissistic
people show attenuated effects
Pantano et al.
To investigate the influence of AR
technology on the usage decision
within e-commerce among consumers
in two different cultural settings
AR (online retailing)
TAM N = 318
Experiment and survey
Italy vs. Germany
Cross-market similarities and dissimilarities were identified in
relation to consumers’ motivation to employ AR systems for
supporting their online purchase decision across two countries
Notes: ANOVA = analysis of variance; ARIT = augmented-reality interactive technology; SEM = structural equation modeling; TAM = technology acceptance model;
TOE = technology-organisation-environment; TPB = theory of planned behavior; TRA = theory of reasoned action; TTF = task-technology fit;
U&GT = uses and gratification theory; UTAUT = unified theory of acceptance and use of technology.
Table 1
Prior research on wearable-XR adoption (continued)
customer value perceptions through the
mediating role of spatial presence and
the boundary the condition for
consumer traits
AR (online service)
Study 2 (N = 173)
Study 3 (N = 321)
Study 4 (N = 100)
Regression and Process
utilitarian and hedonic value perceptions. The effect of spatial
presence on utilitarian value is greater for customers who are
disposed to verbal and its effect on decision comfort is
attenuated by customers privacy concerns
Jetter et al. (2018) To investigate the key performance
indicators (KPIs) for AR in automotive
AR (automotive)
TAM N = 9
Semi-structured expert interviews
Content analysis
Significant enhancements of all KPIs (reduction in time and
errors, spatial representation, cognitive workload) are observed
and novice users are identified as a potential target group
Shin (2018) To test a VR experience model that
integrates presence, flow, empathy, and
VR (storytelling)
Theory of
N = 200
Experiment andsurvey
South Korea
High immersive devices affect the users’ perceived presence
and and make them feel flow. The users own traits determine
their levels of empathy and embodiment and arouse
Herz and
To develop a comprehensive
framework to study consumer reactions
to wearable VR glasses
VR glasses (individuals)
A combination
of media,
fashion, and
N = 661
A set of potential benefits and risks associated with VR glasses
are identified. VR-adoption intention is highest when
consumers experience a strong sense of virtual embodiment and
virtual presence. Health and privacy risks diminish adoption
rates, whereas psychological and physical risks donot
Wei et al. (2019) To explore how VR technologycan
help enhance theme park visitors’
experience and behaviors
VR (theme park)
Process theory N = 396
Regression, sensitivity test,and
Users’ sense of presence is predominantly driven by their
feeling of control, followed by participation, effectiveness,
curiosity, vividness, temporary association, and enjoyment.
Consumers’ familiarity with VR and personal innovativeness
moderate some of these effects
Notes: ANOVA = analysis of variance; ARIT = augmented-reality interactive technology; SEM = structural equation modeling; TAM = technology acceptance model;
TOE = technology-organisation-environment; TPB = theory of planned behavior; TRA = theory of reasoned action; TTF = task-technology fit;
U&GT = uses and gratification theory; UTAUT = unified theory of acceptance and use of technology.
Table 1
Prior research on wearable-XR adoption (continued)
Research objective and context
Main theory
Research methodology and design
Key findings
Hilken et al.
To assess whether the AR-enabled
service augmentation enhances
Experiment and survey
Study 1 (N = 156)
Spatial presence mediates the interaction effect of simulated
physical control and environmental embedding on customers’
Yim and Park
Tussyadiah et al.
and invest money in in-app purchases
AR gaming
To examine the role of consumers’
perceived body image in their reactions
to AR-based vs. Web-based product
AR (e-commerce)
To investigate the sense of presence
during a virtual walkthrough of a
tourism destination and how presence
influences post-VR attitude change
toward the destination
VR (tourism)
- N = 406
- N = 926
Hong Kong andUK
importance of these drivers differs depending on the form of
user behavior
Consumers who perceive their body image as unfavorable
evaluate AR more favorably than traditional Web-based
product presentations. For those who perceive their body image
as favourable record no differences in their responses to the two
presentations. Body image moderates the impacts of
interactivity and media irritation on the AR adoption intention
The sense of presence during a VR experience is associated
with higher enjoyment, preference and liking, ultimately
prompting tourists to visit the destination
Shin and Biocca
Chung et al.
To explicate the user experience to
determine what is likely to experience
news stories in VR and how immersion
improves viewing experiences in
AR/VR (journalism)
To identify whether satisfaction with
AR influences the attitude toward and
intention to visit tourism sites
To empirically identify the impact of
expectation-confirmation on positive
beliefs and aesthetic experience, which
are predictors of AR satisfaction
AR (heritage sites)
Experiment (N = 50)
Survey (N = 250)
N = 145
South Korea
The users’ cognitive processes of experiencing quality, value,
and satisfaction determine how they empathise with and
embody VR stories. Users decide future intentions based on
their confirmed satisfaction
Perceived advantage and aesthetics influence tourists’
behavioural intentions toward the heritage destination indirectly
via AR satisfaction and attitude toward the destination through
Tabacchi et al.
To explain the influence of personality
traits on Pokémon Go early adoption
AR gaming
- N = 561
The profile of early Pokémon Go players are more introverted,
close persons with high agreeability and consciousness.
Extraversion and stability are positively correlated with the
connection part of the game, while agreeableness is a negative
predictor thereof. Openness is correlated to the level of
Notes: ANOVA = analysis of variance; ARIT = augmented-reality interactive technology; SEM = structural equation modeling; TAM = technology acceptance model;
TOE = technology-organisation-environment; TPB = theory of planned behavior; TRA = theory of reasoned action; TTF = task-technology fit;
U&GT = uses and gratification theory; UTAUT = unified theory of acceptance and use of technology.
Table 1
Prior research on wearable-XR adoption (continued)
Research objective and context
Main theory
Research methodology and design
Key findings
et al. (2017)
To examine the factors that drive
gamers’ intention to play AR games
N = 642
Hedonic, emotional, and social benefits drive consumer
reactions, while physical risks hinder consumer reactions. The
Glegg et al.
Research objective and context
To evaluate the impact of knowledge
translation on factors influencing VR
adoption and to identify support needs
of therapists AR (heal thc are)
Main theory Research methodology and design
TPB N = 37
Descriptive, content analys is and
McNemar’s test
Key findings
Increases in perceived ease of use and self-efficacy, but not
behavioural intention to use VR, are found following
knowledge translation, along with decreases in the frequency of
perceived barriers. Post-test changes in the frequency and
nature of perceived facilitators and barriers are evident, with
increased emphasis on peer influence, organisational-level
supports and client factors.
Stockinger (2016) To in vestigate th e current state and
future path of AR from an expert
perspective AR (individuals)
N = 12
Open Dephi
Friedman test and
Wilcoxon Signed
Rank test
AR is yet to be accepted by general consumers. This is due to a
lack of consumer understanding, knowledge, and awareness of
AR as well as low benefit and usefulness perceptions toward
such technology
Huang and Liu To examine the extent to which
(2014) presence, media richness, and narrative
experiences yield the highest
experiential value.
ARIT (online clothing retailers)
et al. (2018)
sense of presence, brand recall and
purchase intention, as well as their
VR (e-commerce)
conation model
N = 344
Compared to features such as presence and media richness,
using the narrative perspective to design ARIT creates
experiential value for online consumers
N = 178
Experiment and survey
A dual route of influence of VR on consumers’ purchase
intention in virtual stores was identified: one though emotions
and sense of presence and the other through the affect evoked
by the virtual environment and brand recall
Notes: ANOVA = analysis of variance; ARIT = augmented-reality interactive technology; SEM = structural equati on mod eling ; TAM = technology acceptance model;
TOE = technology-organisation-enviro nmen t; TPB = theory of planned behavior; TRA = theory of reasoned action; TTF = task-technology fit;
U&GT = uses and gratification theory; UTAUT = unified theory of acceptance and use of technology.
Table 1
Prior research on wearable-XR adoption (continued)
3 Literature search
This study follows a systematic procedure of retrieving data from reliable source. For the
search, keywords such as ‘AR’, ‘ARSGs’ and ‘VR’ were used in searching and retrieving
the literature from ISI Web of Science and Scopus databases, as well as Google Scholar.
The search covers the studies published between 2006 to 2019. The initial search results
retrieve conference papers, book chapters, literature review papers, and journal articles.
However, literature review papers were discarded. After a careful screening and selection
process, a total of 45 studies were found to be relevant to this study. Table 1 summarises
these studies. As this table shows, this research stream started with the seminal work by
Rauschnabel et al. (2015) on Google Glass, followed by multiple additional studies from
different disciplines.
As Table 1 shows, diverse theoretical and methodological approaches have been used
in prior research. Among them, technology acceptance model (TAM) (n = 11) is the most
popular framework used to understand users’ acceptance of XR technology. With regard
to research methods, 28 studies employed a quantitative approach (e.g., surveys and
experiments), eight studies employed a qualitative approach (e.g., interviews, focus
groups, and netnography), and six studies employed a mixed-method approach combining
both qualitative and quantitative designs. In addition, most prior empirical studies
collected the data from potential users of AR/VR devices/apps or non-users who exposed
to experimental stimuli.
4 Relevant theories and prior research
Prior research has incorporated theories from various domains such as computer science,
management information system, and consumer psychology in the quest to understand
emergent technologies While the established theories; for instance, TAM (Davis, 1989),
provide initial insights into why people use computers and other information technology
(IT) (King and He, 2006; Schepers and Wetzels, 2007), rapid technological innovation
disrupts the existing IT products and acceptance theories. Therefore, an overarching
framework which combines multiple theories or extends with novel constructs is needed.
For example, ARSGs or VR headsets are arguably one of the most groundbreaking
inventions in recent years; they are more conspicuous, realistic, and immersive than do
other mobile or stationary devices (Rauschnabel et al., 2018a). Due to its distinctive
characteristics, established technology acceptance theories might be inadequate in
explaining users’ reactions to XR technology and thus research findings from fashion and
media literatures might be beneficial. In the next paragraphs, the applied theories and their
relevance to the adoption of XR technology are brieflyreviewed.
Technology acceptance model
Technology acceptance model (TAM) is one the most influential and vastly applied
frameworks to explicate the individuals’ acceptance and use of new technologies since its
inception by Davis in 1986 (King and He, 2006). Originated from the theory of reasoned
action (TRA) (Ajzen and Fishbein, 1980) a well-grounded theory in the behavioural
psychology domain, TAM is initially designed to explain users’ adoption behaviour of
computer and information systems in the workplace (Davis, 1989). TAM postulates that
an individual’s adoption decision is influenced by the degree to which his/her believes that
using a particular system would enhance his/her job performance (i.e., perceived
usefulness) and be effortless (i.e., perceived ease of use). In a related context, ease of use
which reflects the simplicity and user-friendliness of AR apps is driven by the quality of
system (e.g., high levels of accuracy and multi-language support). On the other hand,
perceived usefulness which represents the performance outcome of AR is determined by
the quality of information in terms of relevance and attractiveness (tom Dieck and Jung,
While TAM’s superiority lies in its parsimony, it has been criticised for being too
generic; in other words, neglecting the contingent and contextual factors that are crucial
for decision-making across different technologies (Bagozzi, 2007). Another inherent
limitation of TAM lies in the quantitative-based technique which provides superficial
insights into the users’ perceptions (Baron et al., 2006). Therefore, tom Dieck and Jung
(2018) suggested the need for TAM modification and called for qualitative investigations
to uncover XR technology-specific external variables. Several scholars have applied the
revised TAM-models on XR technology. For example, Rauschnabel (2018a) argued that
scholars should identify relevant utilitarian factors specific to the context or the specific
technology rather than focusing on a broad usefulness measure. Jung et al. (2018) studied
the adoption of mobile at cultural heritage tourism sites using a modified TAM. They have
included perceived aesthetics, perceived enjoyment, and social influence as additional
factors. In addition, Chung et al. (2015) have extended the original TAM with personal
(technology readiness), stimulus (visual appeal), and situational factors (facilitating
conditions) to better understand the visitor’s behavioural intentions toward AR apps.
Unified theory of acceptance and use of technology
As an extension to TAM, the unified theory of acceptance and use of technology (UTAUT)
model was proposed by Venkatesh et al. (2003) to explain technology acceptance among
the employees. The development of UTAUT is based on a synthesis of eight notable
theories: the TRA, TAM, the motivational model (MM), the theory of planned behaviour
(TPB), the model of PC utilisation model (MPCU), the innovation diffusion theory (IDT),
the social cognitive theory (SCT), and the combined TAM and TPB (C-TAM-TPB).
UTAUT posits that performance expectancy, effort expectancy, and social influence drive
behavioural intention, which along with facilitating conditions, determine technology use.
Conceptually, performance expectancy is tantamount to perceived usefulness (TAM),
extrinsic motivation (MM), relative advantage (IDT), job-fit (MPCU), and outcome
expectation (SCT). Effort expectancy is tantamount to perceived ease of use (TAM/IDT)
and complexity (MPCU). Moreover, UTAUT hypothesises that the effects of these four
core constructs on behavioural outcomes are moderated by individual differences (gender,
age, and experience) and situational factors (voluntariness to use). Later, Venkatesh et al.
(2012) extended the UTAUT model to the consumer context by incorporating three new
constructs: hedonic motivation, price value, and habit. The proposed UTAUT2 model has
been found to outperform the UTAUT in explaining the variance of behavioural outcome
variables. Kourouthanassis et al. (2015) have integrated UTAUT with S-O-R in the context
of mobile AR travel guides. They
have specified performance expectancy and effort expectancy as stimuli that evoke
tourists’ emotional states and, in turn, their behaviours of using the apps. Likewise, Paulo
et al. (2018) have studied the behavioural intentions of mobile AR from the lens of
UTAUT2 and task technology fit (TTF) and showed their applicability in the tourism
Uses and gratification theory
Rooted in communication science, uses and gratification theory (U&GT) was initially
applied to understand how and why people use particular media has gained traction in the
IS field (e.g., Ku et al., 2013; Smock et al., 2011). In essence, U&GT is a theoretical
motivational paradigm (Katz, 1959), assuming that audiences are goal-directed and they
are actively choosing the media to satisfy their psychological and social needs (Rubin,
2002). Although individuals’ needs may vary, Rauschnabel (2018a) identified five broad
categories of gratifications for ARSG use: utilitarian (life efficiency; usefulness); hedonic
(enjoyment; entertainment); social (socialising; maintaining existing relationships);
sensual (enhancement of reality; wearable comfort); and symbolic (self-expressiveness;
status). In a subsequent study, Rauschnabel (2018b) related ARSG gratifications tousage
context (private vs. public). They found that the existence of other people matters not only
to the socialising and self-expression goal achievements, but also to make ARSGs more
comfortable to wear. However, it is important to note that, practically speaking, U&GT
and TAM/UTAUT models are not very different. For example, what U&GT research calls
‘utilitarian benefit’ represents ‘perceived usefulness’ in TAM and ‘performance
expectancies’ in UTAUT research.
Media richness theory
Media richness theory, proposed by Daft et al. (1987), assumes that communication media
varies in their ‘richness’ the ability to reproduce and disseminate information to users
for communication and comprehension purposes. The richness of media is organised in a
hierarchy consisting of four criteria:
the availability of instant feedback
the ability to transmit multiple cues (e.g., social presence, body language, and voice
the use of natural language
the personal focus.
According to Newberry (2001), people perceive richer media (e.g., XR technology)
containing more modalities, sensory stimulations, and social cues and less rich media (e.g.,
print newspaper) as having less cues in delivering messages. One of the most common
features of rich media is 3D view. Li et al. (2002) demonstrated that 3D advertising
increases the level of vividness and audiences’ feelings of presence in a scene depicted by
the media, thereby driving more favourable brand attitude and purchase intention. Huang
and Liu (2014) found that the media richness presented by augmented-reality interactive
technology (ARIT) enhances customers’ perceptions aesthetics and service excellence
toward online retailers.
Social presence theory
Social presence theory, developed by Short et al. (1976), suggests that communication
media differs in their amount of social presencewhich is determined by social cues such
as sociable, warm, and personal. In other words, social presence, “the extent to which other
beings (living or synthetic) also exist in the virtual environment” [Schuemie et al., (2001),
p.184]. Jung et al. (2016b) applied AR and VR in the context of museum and found that
the social presence enabled by XR technology enhances visitors’ experience (educational,
aesthetic, entertainment, and escape) and, ultimately their revisit intention.
Technology-organisation-environment framework
Technology-organisation-environment (TOE) framework (Tornatzky and Fleischer, 1990)
provides a useful analytical framework that can be used to studying the adoption of
technological innovation at the firm level. It identifies three facets of a firm’s context that
influence the innovation process:
technological context describes both the existing technologies in use and emerging
technologies applicable to the firm
organisational context refers to the characteristics of an organisation, including the
scope and size of a firm, degree of centralisation, formalisation, the complexity of its
managerial structure, the quality of its human resource and the availability of internal
environmental context is the platform in which an organisation conducts the business
its industry, business partners, competitors, and dealings with government (Wang
et al., 2010; Zhu et al., 2006).
Hein and Rauschnabel (2016) extended the applicability of TOE framework to the
adoption of ARSGs in the context of enterprise social networks (ESNs). They featured
‘environment and external pressure’ (i.e., competitive pressure and industry pressure) as
external factors, whereas ‘expected cost-benefits ratio’ and ‘corporate climate’ (i.e.,
innovation-friendliness and knowledge sharing) as internal forces driving ARSG adoption.
5 Reference models for the adoption of XR technology
This study analyses and organises the factors impacting the adoption of XR technology
into a set of themes according to their similarity. Figure 2 is a multi-level, categorisation
framework since it includes both individual and firm-level factors, with six main
categories in each. Figure 3 shows the relationships among the antecedents of the
determinants of XR technology. The details of classification and research findings are
summarised in Tables 23.
Figure 2 Reference model summarising the factors related to user reactions to wearable-XR
Ease of use/ Effort expectancy (4)+ve
Immersion (1) +ve
Presence (1) +ve
Response time (1) +ve
Information quality (1) +ve,
System quality (1) ©
Cognitive workload (1) #
Spatial representation (1) #
Reduction of time and errors (1) +ve
Costs of use (1) ©
(Expectation) confirmation (1) +ve
Task technology fit (1) +ve
Aesthetic experience (1) +ve
Visual appeal (1) +ve
Technology readiness (1) +ve
Recommendation (1) ©
Personal innovativeness (1) ©
Risk (1) ©
Facilitating conditions (1) ©
Utilitarian benefit
(e.g., functionalbenefit,
perceived usefulness,
and performance
Boundary conditions
Usage context
(public vs. private)
Device (e.g.,
perception as fashion
gadget and/or technology)
Consumer (e.g., big
five personality, empathy,
immersion tendency,
and self-expressiveness)
Cultural traits
- Immersion (1) +ve
Presence (3) *
Media richness (1) #
Interactivity 1(#)
Embodiment (1) +ve
Narrative (1) +ve
Esthetics (1) +v e
Ease of use/ Effort expectancy (3) *
Hedonic benefit
(e.g., enjoyment,
entertainment, and
perceived playfulness)
User reactions toward
wearable -XR tec hnology
(2) +ve
Aesthetic quality/experience(2) +ve
Expectation confirmation (1) +ve
Presence (2) +ve
-Narrative (1) +ve
Media richness (1) +ve
Control variables
Ease of us e
Brand attitude
Device types
Sensual benefit
Virtual presence
1 (*)
Confirmation (1) +ve
Virtual embodiment
(e.g., symbolicbenefit,
benefit, and
Fashion-speci fic
Figure 3 Relationships among antecedents of the determinants of wearable-XR technology
Antecedents Determinants Reactions
Functional quality
-Effectiveness (1) +ve
-Vividness (1) +ve
Experiential quality
Temporal dissociation (1)+ve
Heightened enjoyment (1) +ve
Emotions (1) +ve
Control (1) +ve
Curiosity (1) +ve
Participation (1) +ve
Discomfort (1) #
Table 2
Summary of the factors affecting user reactions to wearable-XR technology
Variables Studies including this
Individual-level variables
Summary of findings
Perceived benefits
Utilitarian benefits 4, 18, 23, 34 A significant positive effect was found
in all studies
Functional benefit 1, 2 Both studies found a significant
positive effect
9, 14,24, 27, 28, 30,
A significant positive effect was found
in all studies
Relative advantage 40 A significant positive effect was found
Life efficiency 5 A mixed result was found
Hedonic benefit 9, 16, 24, 34 A significant positive effect was found
in all studies
Enjoyment 5, 24, 27, 30, 36, 38,
Six studies found a significant positive
effect, while the other one did not
Entertainment 16 A significant positive effect was found
Perceived playfulness 28 A significant positive effect was found
Pleasure and arousal 22 A significant positive effect was found
Flow 33, 36 One found a significant positive effect,
while the other one found a mixed
Social benefit 4 A significant positive effect was found
Socialising 5, 36 Both studies found a significant
positive effect
Impression management
Symbolic benefit
A significant positive effect was found
Self-presentation benefit
No significant effect was found
A significant positive effect was found
(Design) aesthetics
28, 40
Both studies found a significant
positive effect
A significant positive effect was found
9, 36
Both studies found a significant
positive effect
Wearable comfort
5, 24, 34
A significant positive effect was found
in all studies
Note: *Cross-reference with Table 1.
Table 2 Summary of the factors affecting user reactions to wearable-XR technology
Studies including this
Summary of findings
Individual-level variables
Sensual benefit 10 One proposed this relationship
Immersion 10 One proposed this relationship
Desired enhancement of
5, 24 Both studies found a significant
positive effect
Virtual presence 34, 35, 38, 45 Three studies found a significant
positive effect, while the other one did
Virtual embodiment 33, 34, 39 Two studies found a significant
positive/negative effect, while the
other one found a mixed result
Perceived risks
Technology risk
A significant negative effect was
Health risk
A significant negative effect was
Physical risk
34, 36
One found a significant negative
effect, while the one did not
Psychological risk
No significant effect was found
Loss of autonomy
No significant effect was found
Privacy risk
Personal privacy 9, 23, 34, 36 One found significant negative effect,
while the other three did not
Perceived risk to other
people’s privacy 23 A significant negative effect was
Privacy brand image 2 No significant effect was found
Individual differences
Consumer personality traits
Openness to
experience/technology or
personal innovativeness
1, 2, 22, 41 A significant positive effect was found
in all studies
Extraversion 1, 41 Both studies found a significant
positive effect
Neuroticism 1, 41 Both studies found a significant
negative effect
Agreeableness 41 A significant positive effect was found
Consciousness 41 A significant positive effect was found
Note: *Cross-reference with Table 1.
Table 2
Summary of the factors affecting user reactions to wearable-XR technology
Firm-level variables
Expected cost-benefit ratio
Perceived benefits
Costs of technology
One proposed this relationship
One proposed this relationship
Technology readiness
Internal infrastructure
3 One proposed this relationship
readiness conceptually
Internal infrastructure
3 One proposed this relationship
integration conceptually
Innovation readiness
One proposed this relationship
Variables Studies including this
Individual-level variables
Summary of findings
Individual differences
Consumer demographics
1, 2, 23, 34
One found a significant negative
effect, while the other three did not
1, 2, 23, 34
One found a significant positive effect,
while the other three did not
Experience and habit
1, 23, 36
One found significant positive effect,
while the other two did not
No significant effect was found
16, 24
Both studies found a significant
positive effect
Manufacturer-related variables
Brand attitude
1, 2
Both studies found a significant
positive effect
Price value
No significant effect was found
Psychological variables
Social norm/influence
2, 36
Both studies found a significant
positive effect
Social conformity
A significant positive effect was found
Descriptive norms
A significant positive effect was found
Injunctive norm
No significant effect was found
Situational variables
Facilitating conditions
A significant positive effect was found
Note: *Cross-reference with Table 1.
Table 2 Summary of the factors affecting user reactions to wearable-XR technology
Studies including this
Summary of findings
Environment and external
Note: *Cross-reference with Table 1.
The integer beside the variables is the total number of studies that include these
antecedents/determinants in the investigation. The symbols beside the parentheses have
the following meaning:
+ve positive relationship is found in all studies
–ve negative relationship is found in all studies
# there is no significant relationships found in all studies
* the findings are mixed among the studies
© the relationship is proposed conceptually with no empirical findings.
The contributions of these reference models are twofold. First, they provide researchers
with an overview of previous research findings, disclose areas where a copious amount of
studies already exists, and pinpoint those areas where research is needed. Second, the
reference models can facilitate the identification of inconsistent findings, which requires
more empirical studies to reconcile them.
Firm-level variables
Competitive pressure
One proposed this relationship
Industry pressure
One proposed this relationship
Competitive climate
One proposed this relationship
Knowledge sharing
One proposed this relationship
anisational readiness
Top management support
One proposed this relationship
Employee support
One proposed this relationship
Technology safety
One proposed this relationship
Informational safety
One proposed this relationship
Table 3 Summary of the relationships among antecedents of the determinants of wearable-XR
Independent variables Studies including this variable*
Utilitarian benefit
Ease of use/effort expectancy 14(+ve), 18(+ve), 28(+ve), 32(+ve)
Immersion 27(+ve)
Presence 28(+ve)
Response time 30(+ve)
Information quality 30(+ve)
System quality 15©
Cognitive workload 32(#)
Spatial representation 32(#)
Reduction of time and errors 32(+ve)
Costs of use 15©
(Expectation) confirmation 40(+ve)
Task technology fit 18(+ve)
Aesthetic experience 40(+ve)
Visual appeal 14(+ve)
Technology readiness 14(+ve)
Recommendation 15©
Personal innovativeness 15©
Risk 15©
Facilitating conditions 15©
Hedonic benefit
Immersion 27(+ve)
Presence 28(+ve), 38(+ve), 44(#)
Media richness 44(#)
Interactivity 30(#)
Embodiment 19(+ve)
Narrative 44(+ve)
Aesthetics 16(+ve)
Ease of use/effort expectancy 18(#), 22(+ve), 30(*)
Usefulness/performance expectancy 22(+ve), 30(+ve)
Aesthetic quality/experience 30(+ve), 40(+ve)
Expectation confirmation 40(+ve)
Note: *Cross-reference with Table 1.
Table 3 Summary of the relationships among antecedents of the determinants of wearable-XR
technology (continued)
Independent variables Studies including this variable*
Impression management
Presence 28(+ve), 44(+ve)
Narrative 44(+ve)
Media richness 44(+ve)
Sensual benefit
Virtual presence
Functional quality
Experiential quality
Temporal dissociation
Heightened enjoyment
Virtual embodiment
Note: *Cross-reference with Table 1.
Six main categories of factors that drive individuals to adopt XR technology were
identified. These categories are:
perceived benefits of XR technology
perceived risks of XR technology
individual differences
manufacturer-related variables
psychological variables
situational variables.
Perceived benefits of XR technology
Utilitarian benefit
Utilitarian benefit reflects the degree to which people believe that the use of new
technologies can optimise the task-related outcomes, e.g., by improving the life/work
efficiency, simplifying complex tasks, and expediting task completion (Dehghani, 2018).
In the matters of XR technology, task-oriented outcomes include searching for
information, organising functions, using navigation, to name a few; and such outcomes
might vary across usage contexts (personal vs. organisation) (Rauschnabel et al., 2018b).
In the technology acceptance literature and consumption value theory, ‘perceived
usefulness’, ‘relative advantage’, ‘performance expectancy’, and ‘functional value’ are
common examples of utilitarian benefit (Davis, 1989; Rogers, 2010; Sheth et al., 1991;
Venkatesh et al., 2012).
Rauschnabel and Ro (2016) conducted a study in a pre-market entry stage and found
that expected functional benefits are a dominant motivator or a salient intrinsic motivator
driving an individual to adopt ARSGs. Herz and Rauschnabel (2018) observed that people
have favourable attitudes toward VR if they perceive the technology is beneficial in
helping accomplish certain tasks easier, faster, or better. Interestingly, Rauschnabel
(2018b) showed that life efficiency is the main reason as to why people use ARSGs in
private (e.g., information gathering) but not in public (e.g., navigation systems) contexts.
Akçayır et al. (2016) demonstrated that the use of AR in science laboratories enhances the
learning capabilities of students. While the impact of utilitarian benefits on the adoption
of XR technology has been well established in the literature, empiricalevidence also shows
that the strengths of these effects are moderated by consumers’ personality traits (e.g.,
openness and neuroticism) (Rauschnabel et al., 2015) and device perceptions (technology,
fashion, or both) (Rauschnabel et al., 2016). Specifically, consumers who perceive high
functional benefits are more likely to adopt the ARSGs if they score high on openness to
experience, low on neuroticism, and see smart glasses as technology.
Hedonic benefit
Hedonic benefit represents an intrinsic motivational factor and can be defined as the extent
to an individual perceive performing an activity (e.g., leisure and playing) as fun and
pleasurable for its own sake (Davis et al., 1992). Such rewards are conceptually linked to
the construct of ‘enjoyment’ in the technology acceptance domain (Venkatesh et al.,
2012). To fulfil tension-related needs, people tend to choose highly entertaining
technologies and media (Katz et al., 1974; McGuire, 1974; Rubin, 2009; Sundar and
Limperors, 2013). Particularly in the online games context, people often play adventure
games to escape unpleasant situations, release stress, and break the tedium of daily life,
making them a strong determinant of gamers’ continuance intention (e.g., Li et al., 2015;
Merhi, 2016). Similarly, Zsila et al. (2018) found that people play AR games (e.g.,
Pokémon Go) to reduce boredom and Yang and Liu (2017) showed that ga mers expectto
have fun and distract themselves from daily routines. In playing Pokémon Go, people can
do activities they are unable to do in reality, such as catching virtual creatures hidden in
real-world locations. Besides, walking down to the real streets and seeing Pokémon
through the lens of phone camera is a fun experience. While Ghazali et al. (2018)
identified enjoyment as a key hedonic motivation to continue playing Pokémon Go,
Rauschnabel et al. (2017) confirmed that players who experience the flow are willing to
spend money in in-app purchases (e.g., buy Pokéballs).
From a psychological stance, hedonic consumption is associated with multisensory,
fantasy, and emotive aspects of one’s experience with products or services (Hirschman
and Holbrook, 1982). In a related context, tourism scholars (e.g., Jung et al., 2016b;
Tussyadiah et al., 2018a) revealed that visitors’ overall experience could be enhanced by
escapist, entertainment, and enjoyable experience of using XR technology. Likewise, tom
Dieck et al. (2018b) pointed out that three spheres of the experience economy (escapism,
education, and entertainment) significantly influence visitors’ satisfaction and memories
of the AR science festivals, which in turn influence their engagement with science
experience. In a professional setting, Hein and Rauschnabel (2016) proposed that
employees who enjoy learning ARSGs in ESNs will actively contribute to the networks
e.g., by posting own content on ESNs.
Social benefit
A widely replicated findings in the U&GT research is that people tend to choose certain
technologies and media to improve their social relationships (Ruggiero, 2000). Similar to
social networks, XR technology provides a means to meeting new people in addition to
staying in touch people they already know (Rauschnabel, 2018a; Ro et al., 2018). This
may offer significant hope for those who find it difficult to build a connection due to their
introverted personality. For example, Flirtar, the world’s first AR dating app using
geolocation, is essentially designed to help users identify nearby daters and encourage
them to meet in person. Another possible way to expand interpersonal networks is by
engaging individuals with shared enthusiasms in similar activities (e.g., catching Pokémon
in the hotspots) or discussions about topics related to XR technology in the online
communities (e.g., Microsoft Hololens group on Facebook). Recent evidence suggests that
social benefit significantly affects both the intended and continued use of various AR-
related technologies, including glasses (e.g., Rauschnabel, 2018b) and games (e.g.,
Ghazali et al., 2018). At a brand level, AR provides enormous opportunities for interacting
with customers in a more meaningful way (Javornik, 2016). A prominent example of AR
customer-brand interaction campaign is Kate Spade’s AR-guided tour of Paris, where
consumers can explore Paris with the influencers as virtual guides and share their ‘Joy
Walks’ on social media via the hashtag #KateSpadeJoy.
Impression management
In today’s appearance- and status-oriented society, fashion components, including
cosmetics, hairstyles, clothes, and trinkets, play an important role in managing and
portraying one’s impression (Browne and Kaldenberg, 1997; Chuah et al., 2016; O’Cass,
2004). In particular, people prefer carrying fashion accessories that are visible to others
(e.g., luxury handbags) because such possessions signify their wealth and differences from
others. Thus, people exploiting the visible aspect of luxury fashion brands to achieve their
self-presentation goals and consequently enhance their status in their social systems
(Hwang and Kandampully, 2012). As Belk (1978, p.39) succinctly put in, “In
virtually all cultures, visible products and services are bases for inferences about the status,
personality, and disposition of the owner or consumer of these goods”.
Visibility reflects the extent to which a technology is apparent in the sense of sight of
observable to others (Moore and Benbasat, 1996). Comparable to regular spectacles,
ARSGs are more eye-catching and self-defining, and hence are generally linked to positive
images, such as ‘cool’, ‘trendy’, ‘unique’, and ‘innovative’ (Rauschnabel, 2018a).
Therefore, individuals who are tech-literate and fashion-affine might wear ARSGs in
public as a means of communicating these traits to others (Rauschnabel and Ro, 2016).
Not surprisingly, research on wearables and luxury branding echoes the idea that
consumers who buy conspicuous products are driven by the reasons other than utilitarian;
they buy conspicuous products to impress others or to gain symbolic rewards, such as
being acknowledged by others and elevating their self-image within a society (Bian and
Forsythe, 2012; Kalantari and Rauschnabel, 2018; Rauschnabel, 2018b). For example,
Krey et al. (2019) found that consumers respond more favourably to smartwatches if they
believe that the visibility of the smartwatch itself can help them present themselves in a
desirable manner.
In addition to perceived visibility, the aesthetic aspect of an ARSG is vital for
impression management and visual communication (Chattaraman and Rudd, 2006;
Rauschnabel, 2018a). Design aesthetics satisfy human desire for beauty and consumers
evaluate the design aesthetics of a wearable in terms of the balance, emotional appeal, or
visual appeal as manifested in its colour, style, shape, and screen layout (Hsiao, 2018;
Hwang et al., 2016). These aesthetic criteria, in turn, determines wearable acceptance and
market success (e.g., Dehghani et al., 2018; Hsiao, 2018; Jeong et al., 2017; Yang et al.,
2016). For example, Apple Watch which has similar features like other smartwatches
achieved much success because of its aesthetic design. Apple Watch has lots of physical
customisation option, curated into different collections featuring different materials and
different colours and styles of straps (Hayes, 2014). Especially in the mature stage of
diffusion, rolling out smartwatches with diverse designs are needed to meet consumers’
demands for aesthetic (Jung et al, 2016a). With respect to ARSGs, Jeong et al. (2017)
argued that consumers prefer wearing them without losing their fashion sense. It is highly
likely that a consumer will adopt an ARSG if it matches with his/her regular clothing style
(Rauschnabel et al., 2018a). For example, Kopin’s SOLOS AR sports glasses maybe
favoured by a person with a sporty clothing style. Within a tourism sector, AR is
increasingly used for the enhancement of the tourist aesthetic experience (Di Serio et al.,
2013). A well-designed AR app not only aid in the delivery of clear and accurate
information, but also in the arousal of positive emotions such as fun and pleasure. In
support, Chung et al. (2015) and Jung et al. (2018) demonstrated that visually appealing
AR apps (e.g., in harmony with the tourism destinations and showing the design details),
in contrast with visually unappealing ones, can positively impact users’ impressions of the
AR apps in terms of ease of use, usefulness, and enjoyment.
Wearable comfort
Wearable comfort is described as a mental state of physical well-being expressive of
satisfaction with the design of a wearable such as weight, bulk, fit, temperature, and
pressure (Rauschnabel, 2018b; Sontag, 1985). Being anxious about the physical harm
caused by a device is a significant impediment to acceptance (Buenaflor and Kim, 2013).
For example, wearing fitness trackers may cause skin rash and that the radiation emitted
may cause cancer and other health problems. The same might hold for ARSGs.
Oftentimes, ARSGS are perceived as clunky, and people would not be receptive of such
technologies if they experience eye strain, dizziness, and headaches after wearing them
(tom Dieck et al., 2016). Therefore, it is not surprising that research on wearable and
related technologies concludes that wearable comfort is a deciding factor for use (e.g.,
Hwang et al., 2016; Coorevits and Coenen, 2016; Kalantari, 2017; Rauschnabel, 2018b).
Sensual benefit
Sensual benefit is related to sensual pleasures that users experience from the stimulation
of various human senses – e.g., senses of touch, sight, and hearing (Rauschnabel, 2018a).
As wearable technology is a form of ‘fashmedinology’, it should fulfil the sense of touch,
at the same time, the accompanying apps should be capable of eliciting visual and acoustic
senses (Rauschnabel, 2018a, 2018b). Similar technologies like haptic wearables use force
on the skin to deliver real-time tactile feedbacks. By bringing the feeling of realness into
perspective, haptic wearables help enhance our sense of sight, taste, hearing, touch, and
smell regardless of distance and disability. Notable examples include Apple
Smartwatch’s ‘taptic engine’ that produces haptic feedbacks to alert users whenever
notifications come in. Other wearable technologies like VR have allowed users to touch
and taste the virtual objects of which will add to the sense of experienced realism (Hoffman
et al., 1998).
Engaging with immersive media such as VR has been described as giving rise to
experiences of deep absorption, involvement, and engrossment enabled by virtual stimuli
(Palmer, 1995). In a technology-mediated VR environment, achieving an immersive
experience is an important goal (Shin and Biocca, 2018). To feel immersed, consumers
must be able to interact freely with vividly and realistically produced virtual objects from
diverse dimensional perspectives (Yim et al., 2017). The vividness and interactivity of VR
technology increase the real sense of being present in the computer-stimulated
environment, namely telepresence, by touching users’ senses of visual, aural, olfactory,
tactile, and proprioceptive (Pierce and Aguinis, 1997). However, there is a lack of
consensus surrounding the conceptualisation of immersion. While some studies view
immersion as a unidimensional construct (e.g., Shin and Biocca, 2018; Yim et al., 2017),
others view it to be multi-dimensional. For example, Georgiou and Kyza (2017) elucidated
the concept of immersion based on a hierarchical structure comprises:
engagement, which refers to users’ interest, time investment, and perceptions about
the VR’s usability
engrossment, which refers to users’ emotional attachment and their focus of attention
total immersion, which refers to a sense of presence and flow experienced in the use
of VR technology.
Zhang et al. (2017) classified immersion into four themes:
spatial immersion is induced by the spatial compositions of the virtual scene, such as
swift zoom-in and zoom-out or the whirling sensation of on-the-fly sky-diving shots
emotional immersion occurs when the user is emotionally aroused and absorbed by
the narrative content of the story
cognitive (strategic) immersion is related to the mental challenge encountered when
choosing the best-of-breed solution
sensory-motoric (tactical) immersion results from the repetition of rhythm-based
actions and sensory feedback (e.g., background music and visual demonstration of
Desired enhancement of reality/experienced realism
VR has the ability to enhance users’ perceptions of their world by helping them visualise
imaginary objects realistically; thus, corresponding to the sense of sight. Apart from
immersing themselves into a dream world, consumers can now compare their real-world
view or their ideal-world view and vice versa (Rauschnabel, 2018b). For example, through
IKEA Place app, consumers can preview how the furniture would look and fit in their
homes before actually buying it. Another newly released AR app is TaDa Time, a social
messenger app that mimics users’ real life movements and expressions. TaDa Time app
allows users to create and personalise their own 3D avatars with video recording feature
in the real world to interact with their friends’ avatars in the virtual world. In other words,
users’ imagination is seamlessly merged with the reality to create 3D avatars. Empirically,
Rauschnabel (2018b) showed the relevance of users’ desire for reality enhancement in
driving their ARSG usage in private sphere. In addition, desired enhancement of reality
could allow consumers to create their own worlds with their favourite brands, and by doing
so, improve customer engagement (e.g., Alvarez-Milán et al., 2018).
Virtual presence
VR is computer-mediated technology that allows for the manipulation of real environment
in which the users can interact with and feel a sense of presence (Diemer et al., 2015;
Serrano et al., 2016). The illusion of ‘being there’ is a psychological state that occurs when
a user feeling lost or immersed in the virtual world, which enables him/her to temporarily
‘escape’ from the real world (Schubert et al., 2001; Slater and Steed, 2000). Prior studies
have identified involvement, immersion, and realness as the fundamental psychological
states required for experiencing presence (Schuemie et al., 2001; Witmer and Singer,
1998). Schuemie et al. (2001) regarded presence as transportation, that is the sensation
being conveyed to the virtual world. The transportation metaphor of presence has been
operationalised with two measures: arrival and departure. The former describes a feeling
of being attached to the virtual environment, whereas the latter describes a feeling of
detachment from the physical environment (Kim and Biocca, 1997).
After reviewing the early works in the field, Herz and Rauschnabel (2018) redefined
virtual presence as “the subjective sense of being in a particular virtual environment even
when one is physically situated in another” (p.230). For example, when wearing VR
headsets at homes, one could fly through the Artic or feel that he/she is in a fantasy land.
Whether or not the immersive experience would translate into positive emotions would
depend on the level of presence (Riva et al., 2007). Empirical evidence from numerous
domains, including education, retailing, tourism, healthcare, and so forth, demonstrated
that VR experience generates positive attitudinal and behavioural outcomes, such as
consumer learning of products (Suh and Lee, 2005), brand recognition and persuasion
(Kim and Biocca, 1997), destination preference (Tussyadiah et al., 2018a), and mall
loyalty (van Kerrebroeck et al., 2017). These reactions are proposed as the results of
presence (Schuemie et al., 2001).
Virtual embodiment
Experiencing the self in the virtual world can occur when VR creates perceptual illusion
that external objects are part of users’ bodies (Botvinick and Cohen, 1998), they are out
of their bodies (Ehrsson, 2007), or they are embodied with a virtual body different from
their own (Banakou et al., 2016). This virtual embodiment describes the phenomenon
whereby a person’s body is replaced by a life-sized artificial one (i.e., avatar) that he/she
can feel a strong sense of belonging (Banakou et al., 2016). For example, when using VR
headsets, one feels that he/she is a different person/character, such as a Neanderthal man,
a knight, or Michael Jackson (Herz and Rauschnabel, 2018). In their study of embodiment
in social interactions in VR, Bailenson et al. (2008) introduced the concept of transformed
social interaction (TSI) which suggests that virtual representation of the self can
distinguish from a physical ones by self-representation, sensory abilities, and situational
contexts. For example, to address the issue of racial bias, previous studies have conducted
experiments where participants were visually owned different coloured rubber hands (light
vs. dark-skinned) and bodies (white vs. black) (Banakou et al., 2016; Maister et al., 2013).
The findings of these studies suggest that implicit bias decreased more for white
participants with dark-skinned rubber hands and black virtual bodies. Being able to
experience a digital self-representation not only alter the participants’ attitudes toward
other races, but also motivate them to use VR (Yee et al., 2009). This motivation has
become even more prominent after interacting with virtual presence (Herz and
Rauschnabel, 2018).
Perceived risks of XR technology
Technology risk
Technology risk is frequently thought of as felt anxious and uncertainty regarding possible
adverse consequences of using a technology (Featherman and Pavlou, 2003). Kalantari
and Rauschnabel (2018) typified the risks associated with XR technology as having three
facets: psychological, uncertainty, and physical. Psychological risk is defined as the
possibility of the poorly performing product to disturb the consumer’s peace of mind and
the potential loss of self-esteem from the disappointment over the unaccomplished buying
goal (Featherman and Pavlou, 2003; Mitchell, 1992). For example, while VR is used by
therapists to treat post-traumatic stress disorder among the victims of war or terrorism,
misusing this technology could harm one’s psychological well-being (Herz and
Rauschnabel, 2018; Rizzo et al., 2015). Risk arising from the
uncertainties in purchase decision includes financial risk, time loss risk, and performance
risk. Consumers might feel that purchasing a technology that could possibly fall short of
their expectations is not worth the time and money they have invested in (e.g., maintenance
costs, evaluation costs, and learning costs) (Featherman and Pavlou, 2003; Kalantari and
Rauschnabel, 2018). Physical risk refers to the personal injury caused by the technology
(Kalantari and Rauschnabel, 2018). Being immersed in VR makes people ignore the reality
around them, which increases the possibility of hitting furniture or walking into wall (Herz
and Rauschnabel, 2018). High degree of perceived technology risk dilutes the potential
usefulness and ease of use of a technology, thereby discouraging the adoption of XR
technology (Kalantari and Rauschnabel, 2018; tom Dieck and Jung, 2018). However, Herz
and Rauschnabel (2018) found that consumers care very little about the physical and
psychological risks associated with the use of VR glasses. Rather, perceived health hazards
(e.g., eye strain, fatigue, dizziness, and motion stickness) appear to be a salient risk factor
that decreases the favourability of consumers’ evaluations of VR glasses.
Privacy risk
The growing ubiquity, pervasion, and personalisation of IT and media has posed serious
threats to individual privacy (Junglas et al., 2008; Malhotra et al., 2004). Privacy risk refers
to a person’s intrinsic fear about the potential loss of control over their personal
information e.g., personal information is being used without knowledge and consent
due to the use of a given technology (Featherman and Pavlou, 2003). AR/VR systems are
often criticised for collecting far more personal information than conventional systems.
For example, VR headsets with live microphones can record our private conversation;
tracking systems/HMD with always-on cameras can record videos of our private spaces;
and eye-tracking technology can track our eye movements (Fineman and Lewis, 2018).
While used properly, the collected biometric data can enhance customer experience
through personalisation; however, while misused, its abuse can lead to the intrusion of
personal privacy (Culnan, 2000). For example, hackers can compromise an application
and falsify information and vital signs on a patient’s AR display or glasses so as to mislead
the doctor (Dickson, 2018). The concern about privacy threats may thwart the cultivation
of the technology’s trust. Lack of trust is accompanied by the feelings of vulnerable and
uncertain, which constitute the psychological barriers of risk inhibiting adoption (Barney
and Hansen, 1994; Connolly and Bannister, 2007; Lewis and Weigert, 1985). However,
with the exception of Herz and Rauschnabel (2018), most studies did not find that privacy
and data security risks have a negative impact on consumers’ attitude toward using XR
technology (see e.g., Kalantari and Rauschnabel, 2018; Rauschnabel et al., 2017, 2018a).
As Rauschnabel et al. (2018a) observed, most people are generally care more about other
people’s privacy than their own because ARSGs can automatically screen and process a
user’s surrounding, and hence social desirable matters.
Individual differences
Consumer personality traits
A consensus prevails among personality psychologists that the human personality can best
represented by the big five framework that contains five trait factors: openness to
experience, conscientiousness, extraversion, agreeableness, and neuroticism (Devaraj et
al., 2008). The five personality traits are bipolar and perform well in predicting various
media and technology use (e.g., Correa et al., 2010; Guadagno et al., 2008; Kim et al.,
2017; Rauschnabel et al, 2015).
Openness to experience is a personality trait that describes the imagination and
originality of a person (Moore and McElroy, 2012). People who score high on this trait
were found to be more curious, open-minded, creative, and willingness to explore new
ideas than low scorers (Costa and McCrae, 1992; Digman and Takemoto-Chock, 1981).
Rauschnabel et al. (2015) showed that open individuals generally have a greater
knowledge and awareness of Google Glass because of their higher levels of curiosity.
Furthermore, open individuals value the functional benefit of Google Glass more than their
narrow-minded counterparts, and it influences their adoption decision. tom Dieck and Jung
(2018) discovered through focus group interviews that personal innovativeness
a similar construct significantly increases perceived usefulness and perceive ease of
use of AR apps. Likewise, Jung et al. (2015) compared the differences in quality attributes
between high- and low-innovativeness groups visiting a theme park. They found that high-
innovativeness group recognises AR’s system and service quality better than low-
innovativeness group because they dare to take risks, enjoy using and spreading new
technologies. Therefore, high innovators were found to have more favourable attitudes
toward ARSG adoption (Rauschnabel and Ro, 2016).
Conscientiousness refers the extent to which an individual is organised, self-
disciplined, persist in their goal-oriented behaviours (Costa and McCrae, 1992). This
intrinsic motivation drives individuals to achieve their goal e.g., improve job
performance (Moore and McElroy, 2012). Tabacchi et al. (2017) found that highly
conscientious people spend less time on training and collecting their Pokémon, probably
because they want to stay focused on their goals and avoid distraction.
Extraversion is “a trait characterized by a keen interest in other people and external
events, and venturing forth with confidence into the unknown” [Ewen, (1998), p.289].
Individuals who are high in extraversion are sociable, optimistic, fun-loving, affectionate,
and assertive, whereas those who are low in extraversion are introverts: quiet, reserved,
and retiring (Costa and McCrae, 1992; Guadagno et al., 2008; Kim et al., 2017). Generally,
extraverts exhibit a strong desire for self-presentation and are interested in forming new
interpersonal relationships. Consequently, extraverts are more inclined to adopt ARSGs
as its ‘fashmedianology’ nature provides them a way to present themselves to others and
to assimilate with their peers (Rauschnabel et al., 2015).
Agreeableness represents an individual’s sympathy, courtesy, flexibility, kindness,
trustiness, and forgiveness. Individuals high in agreeableness have been known to be more
cooperative and are less inclined to reject invitations from their friends (Wehrli, 2008).
Probably this explains why agreeable individuals tend to accept Pokémon Go in the early
stage. However, they are less likely to capture and collect the Pokémon in the later stage,
presumably because playing such games might engage them with
disrespectful behaviour e.g., catching Pokémon at the Holocaust Memorial Museum,
which is in conflict with their courteous nature (Tabacchi et al., 2017).
Neuroticism, also referred to as emotional stability, measures one’s predisposition or
vulnerability to confront negative emotions such as anxiety, anger, or depression (Kim et
al., 2017). High neuroticism is reflected in nervous, insecurity, and self-pitying; low levels
are evident in calmness, security, and self-satisfied (Guadagno et al., 2008). Hence,
neurotic individuals tend to be particularly averse of ARSGs when they believe that such
technologies will control their lives due to its functionality. Furthermore, neurotics are
also less interested in adopting ARSGs when they assume its usage is common among
their peers (Rauschnabel et al., 2015).
Consumer demographics
Age and gender are the most commonly studied demographic variables in the XR
adoption. However, the findings on these demographic variables are somewhat mixed. For
examples, Herz and Rauschnabel (2018) included age and gender as control variables in
their model. They found that gender but not age has a significant effect on purchase
intention. However, neither age nor gender was found to be significantly related to
adoption intention in the studies by Rauschnabel et al. (2015), Rauschnabel et al. (2018a),
and Rauschnabel and Ro (2016).
Experience and habit
Experience reflects an individual’s familiarity with and knowledge about XR technology.
Rauschnabel et al. (2016) discovered that consumers’ existing knowledge about or
familiarity with ARSGs influences the categorisation process. When consumers look at a
pair of ARSGs, their design and technical features are likely to trigger strong associations
with this core concept and thereby infer a particular categorical representation (e.g.,
fashion vs. technology). Habit describes a person’s nature tendency to behave in a
particular way because of learning (Limayem et al., 2007). Paulo et al. (2018) found that
habit is a strong predictor of continued use of mobile AR in tourism.
Manufacturer-related variables
Brand attitude
People often susceptible to the potential risks and uncertainties associated with new
technologies. To a certain extent, such vulnerability could be counteracted by people
attitude toward a brand, which is consumers’ overall evaluation of a brandwhether good
or bad (Mitchell and Olseon, 1981). Rauschnabel and Ro (2016) contended that consumers
who evaluate a brand positively will extend the likeability to other product categories that
the same company offers. For example, enthusiastic Apple fans that possess an intense
emotional attachment to Apple might camp for days on end in order to be first in line for
the latest Apple products, such as iPhone, iPad, and Apple Watch. These ‘irrational loyal’
customers would ‘love Apple no matter what’ even if all of its devices are at risk of
being hacked (Titcomb, 2018). Prior XR research has confirmed empirically that brand
attitude is closely tied to consumers’ intention to adopt ARSGs (see e.g., Rauschnabel et
al., 2015; Rauschnabel and Ro, 2016).
Price value is a key construct in the UTAUT2 model. By definition, price value
represents the consumers’ perceptions of the worth of the product or service results from
their cognitive trade-off between the monetary benefits and costs of using it (Dodds et al.,
1991; Kalantari, 2017). The price value is positive when the technology’s benefits has
surpassed the associated costs (Venkatesh et al., 2012). Price value has long been
recognised as a key factor determining consumers’ adoption of diverse technology-based
products or service, which include wearable technologies (Hsiao, 2018; Jung et al., 2016a;
Kim and Shin, 2015). However, price value was shown to be insignificant to the adoption
of mobile AR travel guide (e.g., Kourouthanassis et al., 2015).
Social norms/influence
Human need for companionship and association with others is mirrored in their
compliance with social norms that is, unwritten rule about how to behave (Cialdini and
Goldstein, 2004; Rauschnabel and Ro, 2016). Conceptually, social norm is similar to
social influence in the UTAUT, which reflects the degree to which a person’s decision on
certain behavioural performance is being stressed out by significant others (e.g., friends
and family) (White et al., 2009). According to Chan et al. (2018), people are under pressure
to follow other people for the purpose of maintaining positive expectations with them.
Social norm can be injunctive or descriptive in nature (Schultz et al., 2007). Injunctive
norms reflect perceptions of whether a behaviour will be approved or rejected by a given
group in other words, what others think one ought to do. In contrast, descriptive norms
are concerned with social conformity, referring to the observation of whether other group
members perform the behaviour. To put it simply, it highlights what others are doing
(Hardeman et al., 2017; White et al., 2009). Social norm is particularly matter in situations
where a technology is used visibly around other people (Hein and Rauschnabel, 2016). In
the case of ARSGs, Rauschnabel and Ro (2016) reported that the adoption intention of
German consumers is strongly influenced by injunctive norm i.e., expectations of
important referents. More recently, Kalantari and Rauschnabel (2018) compared two types
of norms and found that the US consumers would not simply purchase ARSGs just