Introduction
With the steadily increasing prevalence of online business, firms face formidable challenges with regard to providing compelling customer experiences at the online organizational frontline. Customer satisfaction with—and trust in—privacy safeguards remains low, as do conversion rates (McDowell et al.
2016). Virtual shopping cart abandonment and product return rates continue to rise, partly because of the limited service scope of online retailers (Janakiraman et al.
2016). As online shopping is considered to be a service experience (e.g., Dabholkar and Bagozzi
2002), developing an innovative, distinctive service strategy to tackle these challenges is crucial for driving firm value (Dotzel et al.
2013). Such a strategy must acknowledge that many online customers find it hard to visualize how products fit into their personal environments or get a feel for a service experience (Cadirci and Kose
2016). To enhance customer affinity for online offerings and facilitate online decision making, many firms (e.g., IKEA, L’Oreal, De Beers, Westpac, UPS, American Apparel, Volvo, Marriott) have adopted a strategy of service augmentation, focusing not on the core product but on the interaction between customers and the organizational frontline (Grönroos
1990). To simulate aspects of service that normally are reserved for in-store shopping experiences, they leverage augmented reality (AR) applications (Brynjolfsson et al.
2013) that contextualize products by embedding virtual content into the customer’s physical environment, interactively and in real-time (Azuma et al.
2001).
According to Apple CEO Tim Cook, AR-based experiences allow for “a more productive conversation” (CNBC
2016). Apple refers to AR as a core technology and actively pursues an AR-related acquisition strategy. With AR, customers can dynamically engage with goods and services, for example by virtually placing an IKEA sofa in a real-time view of their living room, changing the Dulux color of their wallpaper, or trying on the latest style of sunglasses, clothing, or makeup in a virtual mirror. Thus AR helps customers see how products fit them personally or in their environments, while still maintaining the convenience of online purchasing. From a service augmentation perspective, AR is a “smart” technology (Marinova et al.
2017), set to enhance online service experiences through a more intuitive, context-sensitive interface that aligns with the ways customers naturally process information. Such an advanced frontline interface can improve service quality and offer customers more effective, enjoyable online shopping (Huang and Liao
2015).
A recent industry report forecasts that investments in AR-enabled service augmentation will exceed $2.5 billion in 2018 (ABI Research
2013). However, due to inflated expectations there are concerns about the business reality of these market projections (Gartner
2015). Customers expect AR to deliver experiential benefits while also reducing their decision-making uncertainty (Dacko
2016), but most extant research into AR is limited to a focus on generic technology acceptance models (e.g., Rese et al.
2016). Furthermore, compound annual growth rates for AR are estimated primarily using device types and industry segmentation, rather than specific online customer needs (e.g., visualization of offerings) and concerns (e.g., privacy). Therefore, these projections may not be a bellwether for sustained success; firms face a clear risk of building AR solutions that customers will not embrace. Service managers need a more in-depth understanding of which customers are likely to engage with this new technology, what makes for a compelling experience, and how AR can improve decision making. The paucity of knowledge on these matters also reveals the strong managerial need to understand how the deployment of AR can transform online shopping into a value-added service experience. By addressing three critical issues, this article contributes to emerging research on the methods available to enhance online service experiences.
First, we draw on situated cognition theorizing (Robbins and Aydede
2009) to show that customers’ information processing is embedded in their physical environment and embodied through physical simulations and actions. That is, situated cognition enables customers to learn more about the value of an offering when the associated service experience enables them to link abstract “facts” with a real-time context and physical interaction (e.g., trying on or trying out a product). We conceptualize AR-based service augmentation as a strategy to enhance the customer’s ability to interact with online offerings in two interrelated ways: (1) environmentally embedding the offering in a personally relevant context (e.g., projecting a visualization of sunglasses on the customer’s face or furniture items into their home) and (2) simulating physical control over the offering (e.g., being able to perform natural movements to adjust the sunglasses or furniture). The lack of these capabilities to personally experience an offering traditionally has made it difficult for customers to engage in effective, enjoyable online shopping (Childers et al.
2001). In line with contemporary services theorizing (e.g., Dabholkar and Bagozzi
2002), we view online shopping as a technology-based service experience and assess whether the AR-enabled interaction effect of simulated physical control and environmental embedding positively influences customers’ utilitarian and hedonic value perceptions of the online service experience.
Second, we examine the influence of this interaction by conceptualizing and empirically assessing the mediating role of spatial presence. When a customer senses spatial presence, the online service experience becomes “real.” He or she neglects the technology-mediated nature of the experience (ISPR
2000; Lombard and Snyder-Duch
2001). The strength of this feeling is jointly determined by the possibilities for action that a technology offers and how well these possibilities are integrated into the person’s immediate environment (Carassa et al.
2005; Schubert
2009). The concept of spatial presence thus captures customers’ convictions that they are experiencing an authentic, situated experience, in which virtual content is located in their physical reality and available for interaction (Wirth et al.
2007). In other words, the online service experience is enhanced and decision comfort increases when customers forget about the role of AR and believe they are really trying on and interacting with an “actual” pair of sunglasses, a new makeup look, or clothing from next season’s fashion line. Spatial presence sheds light on the process through which AR-based service augmentation translates into favorable customer evaluations of the online service experience, in terms of both perceived value and decision comfort.
Third, we propose two important customer-related boundary conditions for deploying AR as a service augmentation strategy: (1) style of information processing and (2) privacy concerns. Previous research shows that the effectiveness of visual product representations depends on individual preferences for visual versus verbal processing (Wyer et al.
2008). Jiang et al. (
2007) demonstrate for example that adding a visual representation to a verbal description of an offering has little impact on the offering’s evaluation for visualizers, because they rely predominantly on their own mental imagery. We anticipate that the spatial presence offered by AR may have a stronger impact on the value perceptions of those who are inclined to rely on semantic processing (i.e., verbalizers), such that AR-enabled visualizations might complement their verbal processing style. Because AR technologies also record personal data (e.g., facial recognition), customer concerns about privacy are another pertinent issue (Dacko
2016). Perceptions of risk and vulnerability are associated with data privacy (Martin et al.
2017) and could interfere with the comforting effect of spatial presence for customer decision making. Noting the significant differences in the degree to which customers expect transparency and disclosure of how their data is collected and used, we assess whether customers’ concerns about their awareness of a firm’s privacy practices attenuate the impact of spatial presence on decision comfort.
Conceptual framework
Various academic disciplines address AR, including information systems (e.g., Milgram and Kishino
1994), education (Dunleavy et al.
2009), and psychology (Riva et al.
2016). Within the marketing domain, substantial research has focused on customer acceptance modeling, though a growing research stream also recognizes the potential of AR to enhance customer service experiences in a multichannel environment. In Table
1 we summarize selected relevant literature, revealing common research themes and gaps. In particular, recent research emphasizes that AR is able to deliver a compelling user experience (e.g., Poushneh and Vasquez-Parraga
2017), and AR is also expected to benefit customer decision making (Dacko
2016). Many studies share an appreciation for AR’s ability to embed virtual content into reality and enable interactions with the content. However, despite initial research efforts (Javornik
2016b), a substantive conceptualization and empirical investigation of these AR features is lacking. Furthermore, there is limited insight into AR-specific process variables or relevant boundary conditions.
Table 1
Selected augmented reality (AR) literature per strategic services marketing theme
Theme: Gaining customer acceptance of new service technologies |
Hopp and Gangadharbatla ( 2016) | AR advertising for an automobile brand; quasi experimental study | Novelty effects, self-efficacy beliefs | Novelty | Attitude toward AR | Technological self-efficacy beliefs | Attitude toward brand | Novelty is negatively related to attitude toward AR. High technological self-efficacy individuals also transfer these negative evaluations to the brand. |
| AR for online clothing retail; online experiment | Technology acceptance model (TAM), experiential value | Presence | Ease of use, usefulness, aesthetics, service excellence, playfulness | Cognitive innovativeness | Sustainable relationship behavior intentions | Presence predicts technology acceptance and experiential value variables. The effects on behavioral intentions vary across levels of individual cognitive innovativeness. |
| Consumer responses to AR media characteristics; lab experiments | Media characteristics | Interactivity, augmentation | Flow | - | Affective, cognitive, behavioral responses | Flow mediates the positive effect of augmentation on consumers’ affective, cognitive and behavioral responses. |
| Consumer acceptance of AR applications; lab experiments | Technology acceptance model (TAM) | Informativeness, enjoyment, ease of use | Usefulness, attitude towards using | - | Intention to use | The TAM model predicts acceptance of AR applications. |
| User acceptance of AR applications; online ratings/reviews, lab experiments | Technology acceptance model (TAM) | Informativeness, enjoyment, ease of use | Usefulness, attitude towards using | - | Intention to use | The TAM model predicts acceptance of AR applications. Online reviews can be used to model TAM constructs. |
Spreer and Kallweit ( 2014) | AR for book retailing; field study | Technology acceptance model (TAM) | Usefulness, enjoyment, ease of use | - | - | Assessment of information offer, information completeness, intention to reuse | Users assess AR-enabled information more positively and more complete. AR reuse intentions are driven by perceived usefulness and enjoyment. |
Yaoyuneyong et al. ( 2016) | AR hypermedia print ads, online and lab experiment | Relationship and experiential marketing, interactive advertising | - | - | - | Attitude toward the ad, informativeness, entertainment, irritation, ad value, time-effort, novelty, ad effectiveness | AR print ads are rated more positively in terms of preference, informativeness, novelty, and effectiveness compared to QR and traditional print ads. |
Theme: Enhancing customer service experiences in a multichannel environment |
| AR virtual fitting rooms for on- and offline retail, online experiments | Intrinsic and extrinsic motivation | - | Perpetual-specific curiosity, patronage intention | - | Purchase intention | AR use increases online and offline purchase intentions through perceptual specific curiosity and patronage intentions. |
| Mobile AR applications for smart retail; survey | Experiential value | - | - | - | Experiential shopping benefits, behavioral intentions, perceived drawbacks | AR is expected to provide more efficient and entertaining shopping experiences, more complete information, and more decision certainty, resulting in positive behavioral intentions. Privacy concerns are considered as a drawback of AR use. |
| Mobile AR services for shopping centers; semi-structured interviews | User experience, central user requirements | - | - | - | - | AR services are expected to provide efficiency, empowerment, and increased awareness and knowledge. Emotionally, AR services are expected to offer stimulating and pleasant experiences. |
| AR in physical retail; field study | Store atmospherics | - | Store atmosphere, perceived value, positive emotion | - | Satisfaction, patronage intention | AR positively affects store atmospherics, perceived value, and positive emotions. Perceived value and positive emotions mediate the effect of store atmospherics on satisfaction, which also promotes repatronage intention. |
Poushneh and Vasquez-Parraga ( 2017) | Impact of AR on retail customer experiences; lab experiment | User experience | Interactivity | User experience | Trade-off between price and value, user’s information privacy control | Willingness to buy, satisfaction | AR positively influences the user experience. This promotes user satisfaction and willingness to buy. |
This study | Strategic potential of AR for online service experiences; lab experiments and survey | Situated cognition theory | Simulated physical control, environmental embedding | Spatial presence | Style of-processing, awareness of privacy practices | Utilitarian and hedonic value perceptions, decision comfort, WOM and purchase intentions | The AR-enabled interaction of simulated physical control and environmental embedding positively affects customer value perceptions of the online service experience. Spatial presence functions as a mediator and also predicts decision comfort. Customer value perceptions and decision comfort translate into positive behavioral intentions. Customers’ style-of-processing and privacy concerns are relevant boundary conditions. |
Addressing these research gaps is important to differentiate the AR value creation process from that of other interactive technologies. We draw on emerging theories of situated cognition to explain how AR-based service augmentation aligns customer online interactions with natural information processing to influence decision making. A situated cognition perspective implies that information processing occurs within (i.e., is embedded in) and actively exploits (i.e., embodies) a person’s environment, rather than taking place as an abstract activity in the mind (Robbins and Aydede
2009; Semin and Smith
2013).
First, with regard to embedding, research has shown that customers not only mentally picture themselves trying out an offering (e.g., Escalas
2004) but also use their immediate environment to facilitate such visualization. For example, customers often lay out the parts of self-assembly furniture in the correct spatial proportions (Wilson
2002). As such, we propose that AR facilitates situated information processing by providing customers with a service to embed a product in a personally relevant context (e.g., fitting a virtual image of sunglasses or makeup on the customer’s face, projecting a sofa into their living room). We conceptualize this aspect of AR as
environmental embedding, defined as the visual integration of virtual content into a person’s real-world environment
. Services researchers have emphasized that enabling customers to mentally grasp the qualities and benefits of an offering (e.g., through enhanced visualization) reduces perceived risk (Laroche et al.
2004). Mentally picturing how furniture from an online shop fits with the existing decor or how sunglasses look when worn may be too complex for customers. Environmental embedding relieves customers of this mental burden and provides enhanced information about how an offering relates to the context in which customers use it.
Second, embodiment implies that customers’ information processing is tightly coupled with their experience of bodily simulations, states, and actions (Barsalou
2008; Niedenthal
2007). Accordingly, the importance of perceived control in service experiences is well acknowledged (Zhu et al.
2007); research has shown that particularly physical interaction with an offering evokes affective reactions in form of pleasure and improves the customer’s ability to evaluate the offering (Grohmann et al.
2007). We thus propose that AR enables an embodied online service experience by allowing customers to control a virtual product using the same physical movements they would use for an actual product (Rosa and Malter
2003). We conceptualize this ability of AR to simulate physical control over an offering (e.g., moving, rotating) as embodiment, labeled
simulated physical control.
In sum, we discern the simultaneous provision (i.e., conjunction) of environmental embedding and simulated physical control as the unique property of AR-based service augmentation. AR thus provides highly situated experiences that likely outperform current online service experiences with 360-degree product rotations or photo-based try-on, as these only partially fulfill customers’ needs for embodiment and embedding.
Following Grönroos (
1990), in our conceptualization, AR-based service augmentation seeks to enhance not only the product offering but also the interaction between customers and the online organizational frontline. For customers, this means that AR may provide a context-sensitive interface with enriched information (Yaoyuneyong et al.
2016) and a different form of interaction compared with current technologies (Javornik
2016b). Traditional (in-store) shopping allows for personal examination of offerings (Childers et al.
2001), and AR-based service augmentation brings this service aspect to the online environment. Specifically, customers can virtually view a product at home, use it in another environment, or even try it on virtually (Kim and Forsythe
2008). Such “smart” frontline interactions allow customers to engage in more productive inquiry and action, resulting in enhanced service experiences and decision making (Marinova et al.
2017).
As part of an innovative service strategy, AR-based service augmentation offers firms the means to achieve favorable customer behavioral outcomes (e.g., purchase behavior, word-of-mouth) and enhance their bottom lines (Dacko
2016). It is a readily adoptable technology that works on existing (customer-owned) devices (McKone et al.
2016), and AR-enhanced online service experiences may help deliver on services marketing imperatives (Berry
2016): competing on value, meeting or exceeding customer expectations, saving customers time and effort (including enhancing decision making ability), and being generous. For customers, AR’s enrichment and enhancement of online interactions offers a close alignment with their natural information processing, so it can provide a sense of comfort in online decision making. For example, customers perceive AR-enhanced advertisements as more informative and effective than their print counterparts (Yaoyuneyong et al.
2016). The potential of AR-based service augmentation to offer hedonic value, such as entertainment and shopping enjoyment, also should lead to higher customer satisfaction (Childers et al.
2001). Finally, AR-based service augmentation addresses customers’ “pain points” (e.g., travel, time constraints) while still offering personalized experiences (e.g., virtual applications that learn and apply customers’ preferences; McKone et al.
2016). Because AR-based service augmentation may lead to more enjoyable, effective online shopping and more comfortable decision making, it should increase perceived service quality and conversion rates, while reducing the likelihood of product returns. Considering the strategic potential of AR-based service augmentation, we develop testable hypotheses of its impact on marketing-relevant outcome variables.
Hypotheses development
What is unique about the situated cognition perspective on AR-based service augmentation is the interdependence of environmental embedding and simulated physical control. Effective environmental embedding depends on embodied actions to alter the immediate environment in a strategic manner (Robbins and Aydede
2009). The value of environmentally embedding a pair of sunglasses on a customer’s face depends on the ability to perform and register physical movements in such a way that the customer can view the glasses from different angles and develop a feel for the offering. Images of models wearing the sunglasses or a photo-based try-on cannot provide such an embodied online service experience. In turn, possibilities for embodied action arise from a dynamic relation between a person and his or her environment (Clancey
2009; Gibson
1979). Therefore, embodied action becomes meaningful for customers only if it is embedded in their immediate physical environment. Without such embedding in the relevant context, simulated physical control is less effective (i.e., online service experiences with 360-degree product rotation only partially fulfill customers’ cognitive needs). In contrast, AR provides a service experience that enables customers to exert physical control over offerings in their immediate environment, resulting in a more natural way of processing information about the offering.
It is broadly acknowledged that customers evaluate service experiences in terms of both
utilitarian and
hedonic value (Bauer et al.
2006; Babin et al.
2005), where the former captures the performance-related effectiveness and the latter the experiential enjoyment provided in a service experience. For example, Childers et al. (
2001) demonstrate that customers assess both the usefulness and enjoyment of an online grocery shopping service. Recent studies suggest that the use of AR in a retail context enhances customer perceptions of both these value dimensions in the holistic shopping experience (e.g., Poncin and Mimoun
2014). The ability of AR to let customers virtually try on (i.e., environmentally embed) online offerings provides enhanced information (Poushneh and Vasquez-Parraga
2017) and a visually appealing experience (Huang and Liao
2015); it relieves customers of the mental burden of imagining how, for example, a pair of sunglasses would look when worn. The accompanying form of (simulated physical) control offered by AR differs from traditional web-based user control (Javornik
2016b); it allows customers to physically evaluate and playfully interact with a virtual offering, even though the offering is not physically present (Rosa and Malter
2003). In sum, AR should promote an effective, enjoyable online service experience because the interaction of environmental embedding and simulated physical control aligns with customers’ naturally embedded and embodied way of processing information. Whilst there may be individual effects of enabling an embodied or embedded online service experience, our theory-based prediction is that it is through their joint effect that AR makes online service experiences more effective and enjoyable for the customer. We therefore postulate:
The AR-enabled interaction of simulated physical control and environmental embedding provides customers with the means to engage in a situated online service experience. The authenticity of this service experience—that is, how well AR simulates trying on a pair of sunglasses in a physical store—is reflected in customers’ feelings of spatial presence.
Spatial presence describes a distinct psychological state in which a person neglects the role of technology in an experience (ISPR
2000; Lombard and Snyder-Duch
2001); he or she consequently feels physically situated in a different location and perceives possibilities for action (Wirth et al.
2007). Spatial presence is conceptually distinct from constructs such as involvement (Schubert et al.
2001; Wirth et al.
2007) and transportation (Lombard and Snyder-Duch
2001). A feeling of presence can be achieved in augmented environments; its level is contingent on the person’s control over at least one sense and the ability to alter the environment (Riva et al.
2016). Accordingly, the situated view of presence holds that for a person the sense of “being there” requires the ability for them to “do there” (Schultze
2010; see also Sanchez-Vives and Slater
2005), and AR-based service augmentation offers this ability. The interaction of simulated physical control and environmental embedding provides opportunities for action and the meaningful integration of these actions into the environment, which in turn elicits a strong sensation of spatial presence for a person (Schubert
2009; Schultze
2010).
However, an AR setting demands modification to our understanding of spatial presence (Schubert
2009). Rather than feeling present in wholly artificial environments (e.g., virtual shopping mall), customers should sense that virtual products are present and can be interacted with in their real world. In that respect, AR spatial presence is consistent with conceptualizations of object presence (Stevens et al.
2002) or “it is here” presence (Lombard and Ditton
1997). Using spatial presence as the metric of success for AR-based service augmentation thus requires replacing a person’s feeling of “self-location” with a feeling of “object-location” in the physical reality. Spatial presence is a consciously experienced cognitive feeling that varies in intensity and has informative value and positive valence; the opposite state (not feeling present) is manifested as a negative state of disorientation (Schubert
2009). As such, spatial presence intensifies media effects (Wirth et al.
2007) and can explain the effect of AR-based service augmentation on customer value perceptions of the online service experience. Customers become convinced of the authenticity of the situated service experience and feel that they are actually trying on, for example, a pair of sunglasses as in a physical service encounter. In support of this hypothesizing, Klein (
2003) demonstrates positive effects of a sense of presence on the strength of customers’ beliefs about product attributes and attitudes toward products. Moreover, Fiore et al. (
2005) find a significant effect on customer perceptions of instrumental and experiential value. Therefore:
Although the success of AR-based service augmentation likely relates to the aspects that align with a customer’s natural, situated information processing and the resulting feeling of spatial presence, it is unlikely that all customers realize these benefits equally. Previous research investigates the influence of divergent personal traits, such as trait absorption, emotional involvement (Wirth et al.
2012), and mental imagery ability (Weibel et al.
2011), on the emergence of spatial presence. But a paucity of knowledge describes individual differences in the value derived from spatial presence. Insight into which customers find AR-based service augmentation valuable is important for service managers. Because the predominant modality of AR is visual, customers’ responses to AR-based service augmentation are likely influenced by idiosyncrasies in how they process visual information. After all, most AR platforms overlay virtual content in a customer’s visual field through a computer screen, such as seeing a virtual pair of sunglasses on one’s own face.
Irrespective of domain-specific processing abilities, Childers et al. (
1985) show that customers differ in their preference for a visual versus verbal
style-of-processing. Visualizers prefer to process information through the construction of visual images, whereas verbalizers prefer semantic processing without forming images. Drawing on evidence that object evaluations are negatively influenced by the associated processing difficulty (Winkielman et al.
2003), Wyer et al. (
2008) contend that the effectiveness of product visualization depends on a customer’s dispositional style-of-processing. Adding pictures to verbal descriptions of familiar products thus has less effect on product evaluations for visualizers than for verbalizers (Jiang et al.
2007), because they already mentally form visual images of described products, so the pictures convey little additional information. In contrast, verbalizers derive additional information from pictures. Thus, in online service experiences, customers who are verbalizers likely use the enhanced visualization experienced during spatial presence (i.e., feeling that products are situated in reality and available for interaction). Accordingly, we posit that verbalizers derive more utilitarian value from improved possibilities for engaging in better product evaluation—and thus experience more effective online shopping—but they also experience greater hedonic value due to reduced processing difficulty. Formally:
Extant research has shown that customers expect not only experiential benefits from AR use for online shopping but also reduced decision uncertainty (Dacko
2016). In support of this view, many service delivery models emphasize the importance of achieving consumer comfort in service interactions (Spake et al.
2003). The concept of
decision comfort, defined as the degree to which customers feel at ease or contented with a specific decision, has been introduced as an important element of a customer’s decision experience (Parker et al.
2016). Decision comfort constitutes a soft-positive affective response that can account for variations in customers’ overall evaluations of a decision experience, beyond generic affect and decision confidence. The latter reflects the level of certainty about making the best choice (based on a cognitive assessment of the pros and cons of a decision), but decision comfort is an affect-based sense of ease related to the process of making the choice. Parker et al. (
2016) thus argue that a customer’s decision comfort is driven by affect-laden cues. AR-based service augmentation is deployed to enhance the customer decision process through spatial presence, which is an affect-based cue. Spatial presence thus should be conducive to an experience that promotes ecological validity for the customer, marked by positive affect. Schubert (
2009) argues that as a result, customers’ perceptions of assurance grow, because customers regard the attributes of virtual objects as if they were real. This sense of a first-hand experience with online offerings, approximating a real-world service experience, allows customers to feel at ease with a decision. Therefore:
Customer concerns about marketers collecting and using personal information continue to be a pertinent issue (Martin et al.
2017), particularly in relation to AR technologies (Dacko
2016). The failure of Google Glass (an early entrant into the AR market) may have been due to concerns about its privacy implications (Downes
2013). Because AR technologies record personal data by employing facial recognition or spatial tracking functionalities, perceptions of risk and vulnerability are considerable and could have negative ramifications for the application of AR in online service experiences. Customers’ general information privacy concerns relate to their subjective perception of the fairness of the way their personal information is treated; though opinions about what is fair differ among customers. We contend that a specific dimension of privacy concerns related to customers’ concerns about their
awareness of privacy practices used by firms is pertinent to the use of AR. These concerns about awareness are based on a sense of interactional and informational justice, related to transparency and disclosure of how a firm collects and uses personal information (Malhotra et al.
2004). Since AR technology makes use of novel information collection methods, customers are likely to be concerned about transparency (Downes
2013) and being adequately informed about the associated privacy practices— that is, how their images in a virtual mirror or pictures of their homes are collected, processed, and used.
Previous research, however, has shown that considerable differences exist in the extent to which customers are concerned about their awareness of privacy practices. On the one hand, many customers do not make the effort to read privacy policies or find privacy statements too difficult to understand fully (Tsai et al.
2011). On the other hand, for some customers it is important to be highly cognizant of firm privacy practices. Although we expect an inverse relationship between customers’ concerns about their awareness of privacy practices and decision comfort, our focus is on testing these privacy concerns as a boundary condition for the impact of spatial presence on decision comfort. We posit that the more customers are concerned with being fully aware of the privacy practices associated with using, for example, an AR virtual mirror, the more likely these concerns are to interfere with their immersion in the mediated experience (Draper et al.
1998). Associated perceptions of risk and vulnerability may cast doubt on the nature of the authentic, situated experience offered by AR and attenuate the comforting effects of spatial presence for customer decision making. Therefore: