Highlights
Augmented reality marketing is not just limited to the promotion mix.•
AR marketing can extend and replace physical products.•
Consumers tend to be fairly open to the substitution of real products by AR.•
Marketers should discuss AR as a disruptive technology.
Abstract
There is a general consensus that augmented reality (AR), once it becomes a mainstream medium, can disrupt marketing and management in many ways. One frequently discussed – but mostly unanswered – question is whether AR will render existing physical products and services obsolete or not. Based on a holistic deliberation of AR Marketing and four studies with more than 2,000 respondents, this article investigates consumer acceptance of holographic AR substitutes for real products. The findings show fairly high acceptance rates for some product categories (e.g., Post-it notes, manuals, navigation technology) and low ones for others (e.g., pets, memorabilia). This study also identifies certain product and consumer characteristics (e.g., utilitarian benefits, not visible to others, digitalized products, familiarity with AR) as drivers of substitution. Finally, this paper presents multiple marketing implications, such as the disruptive potential of AR, the possibility of “copying and pasting” the real world including the threat of virtual counterfeits, the role of offline ad blockers, and four generic response strategies for companies.
1. Introduction
„In short, software is eating the world.“
Marc Andreessen, board member, Hewlett Packard
In 2011, Marc Andreessen, an IT entrepreneur, investor, software engineer and board member of multiple leading IT companies, published a now famous article in The Wall Street Journal in which he claimed that “software is eating the world”. In a nutshell, Andreessen (2011) described how many established firms are disrupted by software companies (e.g., Borders by amazon.com), become software enterprises, or convert to suppliers of software companies (e.g., music labels to Spotify). While his general observations and conclusions are still valid, one specific technology that has received a tremendous boost since 2011 deserves particular attention: augmented reality (AR).
AR – a medium that integrates virtual information in real-time into a user’s field of view – was introduced in the previous century (Peddie, 2017). After decades of multiple technological challenges (e.g., lack of fast mobile internet, limited mobile computing power or unprecise sensors), recent hardware and software innovations have increased AR’s potential as a mass-market technology. Apple’s ARKit 3, for example, enables high-quality AR on smartphones and smart glasses such as Microsoft’s HoloLens allow hands-free integration of virtual 3D information directly into the user’s field of vision (holograms). Predictions and expectations are astonishing and indicate a hybrid future consisting of physical and real products. For example, Michael E. Porter and James Heppelman recently conjectured that “[the] screens in consumers’ pockets will be replaced by AR interfaces that people put on — and keep on—without a second thought, just as they do sunglasses” (Porter & Heppelmann, 2017).
If AR becomes mainstream and the technology allows users to perceive realistic virtual AR content continuously, it is likely that this will have a tremendous impact on businesses, companies and societies as a whole (Dwivedi et al., 2020; Hinsch, Felix, & Rauschnabel, 2020). For instance, research has shown that people interact with AR products in a similar fashion to physical products of the same category (Carozzi et al., 2020), which could motivate people to alter the real world so that it matches one’s dream world (Rauschnabel, 2018). This “could certainly transform a dull shop, cheap hotel room or an office into an elaborate palace or make it look like a spaceship” (Pearson, 2019). Consumers may thus even be willing to substitute certain physical products for virtual holograms.
There is a general consensus in the business community that this scenario of ubiquitous AR and holographic substitutes could become reality. For example, Facebook’s CEO Mark Zuckerberg expects that “[a]s a matter of fact, when we get to this world, a lot of things that we think about as physical objects today, like a TV for displaying an image, will actually just be $1 apps in an AR app store. So it’s going to take a long time to make this work. But this is the vision, and this is what we’re trying to get to over the next 10 years”1 . In a similar context, Yitzi Weider, the founder of Authority magazine, predicts that “in the near future AR devices will render many […] products obsolete”2 . The telecommunications corporation Ericsson (2018) concludes that AR content could “in essence turn into free versions of the products or services themselves”. Moreover, “immersive workspaces” entered just recently as a new technology into the Gartner hype cycle, and Microsoft made their office software packages ready to be used in AR on a HoloLens device – a threat to anything that is now on our desktops. Finally, Magic Leap, Microsoft and other AR players consistently communicate many examples of virtual pets, posters, wall painting, games, decorations and other products that can be replaced by AR substitutes (see Fig. 1 for an example, how a screen could be substituted). In short, all of these developments indicate a future in which some (or many) physical objects may not be necessary anymore, or – in Andreessen’s words – a future in which AR may be eating (parts of) the real world, as exemplarily shown in Fig. 1.
Little is known, however, about how consumers will react to the idea of replacing physical products with AR. For example, are some product substitutes more accepted than others? If yes, what product characteristics explain this variation? Likewise, do different consumer segments react differently to the idea of substitution products? This study attempts to answer these questions. More specifically, it shows – based on a series of studies – how “ready” consumers are, what categories of products they would most likely substitute (first), and why. By doing so, this study makes several contributions to the literature. For example, it presents surprisingly high acceptance rates for multiple product categories across different samples, and these acceptance rates are driven by numerous consumer and product characteristics. Likewise, the identified characteristics of consumers and products can serve as an assessment tool for multiple industries to assess the opportunities and threats of holographic substitutes. Finally, the paper discusses four generic response strategies for companies, examines the threat of holographic counterfeits, and calls for a strategic approach to AR in the long run. Overall, the main purpose of this article is to stimulate and inspire further discussions about how disruptive AR can be.
2. A holistic view of augmented reality in marketing
2.1. Augmented reality: definition, current state and future
AR is a “medium in which digital information is overlaid on the physical world that is in both spatial and temporal registration with the physical world and that is interactive in time” (Craig, 2013, p.20). In contrast to virtual reality (VR), AR users are not isolated from the real world; they still see their physical environment, but the technology enhances it with virtual information (Han & tom Dieck, 2019; Meißner, Pfeiffer, Pfeiffer, & Oppewal, 2019; Dwivedi et al., 2020; Han et al., 2020; Peddie, 2017). AR applications are typically installed on stationary (e.g., AR mirrors in stores), mobile (e.g., smartphones) or wearable (e.g., AR glasses) devices (Rauschnabel, 2018). Recently, some manufacturers (e.g., Microsoft) have used the term “mixed reality” to emphasize the realistic integration of 3D elements into the user’s perception of the real world (i.e. the real and virtual worlds are mixed), and “assisted reality” for applications that typically focus only on contextual information (e.g., Google Glass; Crucius, 2018). Dwivedi et al. (2020) therefore argue that mixed reality (very realistic AR content) and assisted reality (plain and functional content) are endpoints of the AR continuum, based on technical terminology (and unlike Milgram et al., 1995). Finally, XR (“extended reality”, “expanded reality” – or “X” for “anything” about new realities) is a comprehensive term that includes “virtual reality, augmented reality, and new immersive technologies” (Accenture.com, 2018).
Many people may associate AR with the success of Pokémon Go in 2016. However, the first AR concepts were realized decades earlier (for a review of AR history, see Peddie (2017)). With advances in mobile technology, AR has gained additional momentum. New sensors, better displays, new ways to visualize 3D content, better see-through displays and faster mobile Internet are just a few reasons why AR has received an additional boost since the 2010s. Nowadays, almost any mobile device has the necessary technology to run AR. These devices are typically limited to handheld mobile devices. Recent developments (including in related areas, such as artificial intelligence; Dwivedi et al. (2019)) and announcements of top tech companies suggest that AR will experience a breakthrough in the market once it is integrated into wearable devices that users can operate “hands free” – in particular AR smartglasses (ARSGs) and contact lenses. Indeed, leading companies – including Microsoft, Apple, Google, and Sony – have announced or already launched AR wearables (Kalantari, 2017; Porter & Heppelmann, 2017; Rauschnabel, He, & Ro, 2018).
Many academic studies have highlighted that AR is associated with multiple positive outcomes for consumers and companies compared to other media. For example, AR can increase consumer flow experience (Javornik et al., 2019; Smink et al., 2020), provides both hedonic and utilitarian benefits (Rese, Baier, Geyer-Schulz, & Schreiber, 2017), has high levels of satisfaction (Poushneh & Vasquez-Parraga, 2017), provides inspiration (e.g., Hinsch et al., 2020; Rauschnabel, Felix, & Hinsch, 2019) and improves/facilitates decision making (Alimamy, Deans, & Gnoth, 2017; Dacko, 2017; Hilken et al., 2017; Jessen et al., 2020). Not surprisingly, these and other positive evaluations translate into a variety of positive outcomes such as branding (e.g., Rauschnabel et al., 2019; Scholz & Duffy, 2018), purchase intentions (Dacko, 2017), positive experiences (Han, Weber, Bastiaansen, Mitas, & Lub, 2019) and engagement (Olya, Jung, tom Dieck, & Ryu, 2020).
On a broader level, discussions among academics and managers often center around the question of how disruptive AR can be for disciplines, industries and societies as a whole. Some argue that AR devices will replace smartphones (Porter & Heppelmann, 2017), whereas others focus on how AR can radically create new ways of working, socializing, and living (Peddie, 2017; Zhang et al., 2018). In the academic literature, for example, Rauschnabel (2018) claims that AR can trigger a “desired enhancement of reality” (p. 6) in which consumers may alter and enhance their perception of the real world by integrating AR objects into their personal spaces. Likewise, Carozzi et al. (2019) show that consumers feel psychological ownership of AR content and conclude that holograms can serve as a “distinct class of products” (p. 80). Scholz and Duffy (2018) argue that AR can bring consumers‘ favorite brands into their intimate spaces and thus create strong consumer-brand relationships. In sum, AR provides many new opportunities for marketing (Chylinski et al., 2020; Dwivedi et al., 2020; Hilken et al., 2018; Javornik, 2014; Qin et al., 2020; Smink et al., 2020). Other studies discuss the radical innovations AR can provide in specific industries, such as tourism (Dieck & Han, 2019; Yung & Khoo-Lattimore, 2019), training (Yousafzai, Chang, Gani, & Noor, 2016), manufacturing (Porter & Heppelmann, 2017), advertising (Feng & Mueller, 2019; Ruyter et al., 2020; Tsai et al., 2020), or retailing (Hilken et al., 2018; Pantano, 2014).
2.2. Holistic augmented reality marketing
This research conceptualizes AR marketing as a strategic concept that uses AR – alone or in combination with other channels – to achieve organizational goals by providing, communicating and/or delivering value to stakeholders. More specifically, AR marketing decisions range from strategic (e.g., branding, responsibilities, skills, goals, or the use of data) to tactical (e.g., its specific applications in the marketing mix) levels. The term „value“ is not limited to the financial value (c.f., Cranmer, tom Dieck, & Fountoulaki, 2020). Depending on the use case, it can cover different types of values (e.g. functional, hedonic, symbolic, social, etc.). Stakeholders are not limited to (potential) customers; AR marketing can also address the public, employees, applicants, journalists and others. Therefore, AR marketing is a concept that can be applied by commercial companies, but also by other types of brands or organizations (e.g. companies, NGOs, NPOs, destinations, etc.). Finally, organizational goals can be both financial (e.g. increase in sales) and non-financial (e.g. inspire users, improve branding).
AR marketing has received increased attention in the academic and managerial literature. For example, after surveying managers, the Boston Consulting Group (2018) concluded that, “[m]oving forward, we expect the AR ecosystem will continue to develop quickly … [and] players such as ad agencies, app and software developers, and ad networks are staking out their own roles in the value chain. Marketers can expect to have access to a wide array of AR-marketing options in the future.” Academics have started to study many of these marketing options in more detail. For instance, research has assessed how consumers perceive virtual product testers (e.g. Rese et al., 2017; Scholz & Duffy, 2018). Other studies have looked at inspirational branding (Rauschnabel et al., 2019), journalistic storytelling (Pavlik & Bridges, 2013) or ways to improve print ads with AR elements (Yaoyuneyong, Foster, Johnson, & Johnson, 2016). Further articles discuss how organizations can benefit from contextual data – that is, data about a user and his/her environment (Dwivedi et al., 2020).
It is important to note that AR can affect all four P’s of the marketing mix. Many people might associate AR particularly with the promotion mix, since AR can generate new forms of communication and advertising (Feng & Mueller, 2019; Ruyter et al., 2020; Tsai et al., 2020). When it comes to place, AR can offer new opportunities for distribution (e.g., AR shopping apps); for example, Amazon’s mobile app offers AR try-out-features for many products. A recent Deloitte report concludes that the “sweet spot for today’s augmented shopping capabilities generally lies with product sets that are highly standardized with high opportunity for customizing features” (Cook, Ohri, Kusumoto, Reynolds, & Schwertzel, 2020, p. 4) – such as furniture or cars – whereas other use cases are still in an experimentation or early phase. AR also raises issues about pricing. For example, companies need to determine how to price products in AR channels. Likewise, some firms – such as Lego – offer AR features for their products and need to determine how this should be priced. Finally, the product mix includes decisions about AR content that can generate revenue (e.g. the development of Pokémon Go from the point of view of Niantec), how it can improve existing products (e.g. AR features for Lego products, or AR manuals for complex products) or after service (e.g. remote assist though AR). This study argues that AR content can serve as a distinct category of products that companies can launch or at least must deal with, if launched by other firms.
3. Substitution research
3.1. Substitution as a strategic force
The five factor model by Porter (1979, 2008) is probably the most popular tool for analyzing the situation of a company and/or a specific industry. In short, Porter simplified microeconomic theories to derive five major competitive forces that affect the success of any company in any industry. These are (1) existing competitors, (2) the bargaining power of suppliers of primary materials, (3) the bargaining power of customers, (4) new competitors entering the market, and (5) the threat of the substitution of a firm’s offerings by new products, what are known as substitutes. There are many well-known examples of how new digital companies replaced existing business models with digital products. In a recent publication, Michael Porter predicted that AR interfaces will replace smartphones (Porter & Heppelmann, 2017), which may provide the technological necessity to substitute various other things.
3.2. Substitution in AR research
It is important to note that digital substitutes for analog products are not new. Many analog products, such as typewriters and cameras, have been replaced by some sort of digital technology (e.g. personal computers and digital cameras). Therefore, it is important to clarify the differences between digital products in general (i.e., non-AR) and AR substitutes. In this article, digital products refer to products with a specific IT hardware component, such as an e-book reader or a digital camera. AR substitutes are holographic (i.e. virtual) versions that imitate the functions and design of real products in AR. For example, the Microsoft Outlook Calendar on a desktop computer is a digital substitute of a real calendar. An AR substitute of a calendar could, for example, be a virtual calendar attached to a user’s kitchen wall which he or she can see through ARSGs.
So far, only few studies have touched on the substitution potential of AR, but none of them has investigated it specifically. Carozzi et al. (2019) showed that consumers may treat holographic products similarly to real products and concluded that companies should consider AR as a new product category. Rauschnabel (2018)introduced the concept of “Desired Enhancement of Reality”, which describes AR’s potential to alter the real world in an anticipated way. In other words, consumers can create their own dream world consisting of virtual fires, dragons, animals, art, and so forth through AR. Finally, Ernst et al. (2016) proposed and tested a HoloLens acceptance model that included perceived substitutability as an antecedent. The findings of this study showed that substitutability is associated with higher levels of utilitarian and hedonic benefits, which subsequently drive acceptance. Other publications mention more potential uses of substitution. For example, Carmigniani et al. (2011) argue that AR can serve as a substitute for missing human senses, such as augmenting one’s limited field of view with acoustic cues. Some articles also discuss the role of advertisements that are augmented or replaced in the real world (e.g. Azuma et al., 2001). Further articles present prototypes of AR ad blockers – in other words, AR apps that block brand logos in the real world (Cuthbertson, 2015). In short, these articles touch on the idea of substitution products and services briefly, yet they typically do not study substitution in detail. Thus, we still do not know if consumers can imagine replacing real products – and if so, what products and why.
While consumer research on AR substitutes is scarce, the industry is making progress towards realizing them. Announcements and publications of leading technology companies indicate that providing such substitutes – or at least the ecosystem to do so – may be part of their long-term strategy. For example, Mark Zuckerberg of Facebook expects that products such as Post-it notes, bulletin boards, computer monitors and screens may be threatened by low-priced AR substitutes. A similar conclusion comes from research by Ericsson (2018), a leading networking and telecommunications company that contributes to the necessary infrastructure for AR (e.g. fast mobile internet connections). Likewise, companies including Microsoft and Magic Leap are showing futuristic homes and offices where many products are replaced by holograms.
3.3. Substitution in related research
Since research on AR substitutes is scare, related research streams can contribute to a better understanding. This section therefore provides some findings from related areas.
One stream of research is tackling how technologies (or innovations in general) replace one another. These studies typically examine how one technology (e.g. video streaming) replaces an existing one (e.g. DVDs). Many of these studies aim at modelling the diffusion and substitution mathematically (Bretschneider & Mahajan, 1980; Singh, Anand, Kapur, & Aggrawal, 2012). Early research in innovation management was based on the assumption that products are introduced into a “vacuum” where no existing products are available (Norton & Bass, 1987; Peres, Muller, & Mahajan, 2010; Steffens & Kaya, 2009). Nowadays, scholars and managers have incorporated the notion that new products are introduced into markets where consumers usually have experience with an older generation of technologies. Thus, this “installed base” of prior technologies determines the diffusion (and substitution) of newer products. Scholars have argued that the introduction of innovations in replacement markets requires an understanding of both adoption (adopting a new product) and replacement, that is, replacing the existing product with a new one (Huh & Kim, 2008; Kaya, 2008; Steffens & Kaya, 2009). Therefore, it is important to note that some innovations are just “better” than previous generations (e.g. better smartphones or USB sticks with larger storage capacity), whereas others have additional functions (e.g. a smartphone has the same functions as a regular mobile phone, but it allows mobile internet access and is linked to an app ecosystem). This is what is known as “partial substitutability” (Steffens & Kaya, 2009). AR substitutes can have both. For example, a wall painting in AR may be less expensive (i.e. “better”), and it may also have additional features that physical counterparts typically do not have (e.g. interactive content).
Adner and Kapoor (2016a) studied the pace of substitution. According to their findings, the pace is determined by the speed at which the ecosystem of a new technology can overcome the challenges of emergence, relative to the speed at which the ecosystem of the old technology can exploit its potential for expansion. By splitting both dimensions into low and high, they identified four possible scenarios (Adner & Kapoor, 2016a, 2016b): creative destruction (fastest substitution; e.g. inkjet printers vs. dot matrix printers), robust resilience (slowest substitution; e.g. RFID chips vs. barcodes), robust coexistence (gradual substitution, e.g. flash memory vs. magnetic storage), and the illusion of resilience (stasis followed by rapid substitution, e.g. mp3 files vs. CDs). Holographic substitutes require a sophisticated ecosystem consisting of technological advances such as ubiquitous AR technologies (in particular ARSGs or AR contact lenses), applications and infrastructure (e.g. fast mobile internet). Additionally, using (i.e. wearing) these technologies continuously must be accepted by consumers and their peers. Therefore, the scenario may still be still somehow science fiction, but the quotations from the business community and the forecasts indicate that this will likely occur. The pace of substitution may thus depend not only on the availability and adoption of wearable AR technology but also on the product. However, many substitutable products (e.g. product manuals) may continue to exist under the “illusion of resilience”, where the old solution (i.e. paper manuals) will not change much until wearable AR technology has a substantial market share.
Two findings from prior research are relevant to the context of this study. First, it is important to note that most (if not all) potential AR substitutes require a sophisticated AR ecosystem consisting of hardware and software (i.e. well-developed AR content as substitutes). Second, consumers need to accept both the technology and the idea of giving up physical products. While the acceptance of AR hardware itself has been studied in multiple publications (e.g. Rauschnabel, Brem, & Ivens, 2015), there has been little research on consumer evaluations of the idea of substitution.
To provide a better understanding of consumers, some researchers have examined how individuals value physical vs. digital products (e.g. CDs vs. streaming, e-books vs. printed books) and found that, with established technologies, digital products cannot satisfy consumer expectations in the same way that physical products do. For example, Belk (2013) concluded that dematerialized virtual products may not play the same role in consumers’ lives as physical products, and Mittal (2006) found that owning and using a real product can support the construction of consumers’ identities. There is an emerging trend, however, that people are creating weaker (or fewer) relationships with products and brands. For example, the industry is realizing that brand loyalty rates are decreasing. This trend is making possible new business models in the sharing economy (e.g. car sharing), where people share or rent products instead of owning them (Bardhi & Eckhardt, 2012). More specifically, Bardhi, Eckhardt and Arnould (2012) found that consumers are creating more situational, instrumentally based relationships with many products. These are known as “liquid relationships”. They found three characteristics of liquid relationships with possessions, namely temporary situational value, use value, and immateriality. Liquid consumption and the sharing economy are thus instances of substitution, and AR substitutes will probably experience a similar process.
Although not discussed in this context, flexible and customizable AR content can allow users situational and instrumentally positioned “products” to foster these types of relationships. The dynamic and interactive nature of virtual content in particular may trigger anthropomorphic thinking and a pragmatic customization to situational problems a user has (e.g. a shopping list that highlights only the products one needs in one’s field of view) – and therefore may increase the acceptance of such products.
Research on digital hoarding and ownership has shown that consumers can indeed create relationships and bonds with digital objects (Sweeten, Sillence, & Neave, 2018; Watkins, Denegri-Knott, & Molesworth, 2016). This ownership value can vary between consumers. For example, Helm, Ligon, Stovall & van Riper (2018) examined e-books. As expected, respondents expressed a high “value in use”, and one could argue that digital books are not as symbolic as real books that guests can see in one’s home. However, they also reported consumers who explicitly do not want other people to see what they are consuming (i.e. hidden or even inconspicuous consumption). AR facilitates the secret consumption of content.
Additionally, research has shown that consumers nowadays perceive their technologies (e.g. smartphones and laptop computers) to be “systems of products” that are central to their lives rather than just individual hardware devices (Orth, Thurgood, & van den Hoven, 2019). This may be even stronger for AR, where these systems can spill over into many “physical” areas of life.
4. Research framework and study overview
Given the exploratory nature of this article, this aricle proposes an exploratory research question and six hypotheses. Together they will serve as a framework for the four empirical studies and their analyses (see Table 1).
Table 1. Study overview.
| Study | Objective | Research Design | RQs/Hs |
|---|---|---|---|
| 1 | Assess substitutability across broad product categories | N = 1,078, USA | RQ1; H1, H2, H3 |
| 2 | Assess substitutability across 55 specific product categories | N = 579, Germany | RQ1; H3, H4 |
| 3 | Replicate substitutability across 55 specific product categories and assess relationships to digital substitutes | N = 401, Germany | RQ1, H5 |
| 4 | Assess the relationship between product characteristics and substitutability | N = 55 pairs of product characteristics and substitutability | H6 |
As mentioned above, the idea of substitution products has been widely discussed in the business community and has been occasionally addressed in academic circles. Research on technology adoption and innovation diffusion repeatedly shows that the awareness and evaluation of an innovation by consumers is related to higher adoption rates (Rogers, 2003). Understanding the extent to which consumers are open to the idea of substituting real products is thus highly relevant for practitioners. Manufacturers of physical products can use these findings to assess the risks of substitution for their own offers. Other businesses (i.e. AR content creators can generate ideas for AR products based on these insights. For theory building, insights into consumers’ reactions to AR substitutes can serve as a starting point for theory development. RQ1 thus starts by exploring evaluations by consumers of a variety of products in terms of substitutability.
RQ1
To what extent do consumers accept AR substitutes for real products, and how does acceptance differ between different product categories?
4.1. Consumer characteristics
Results of RQ1 are limited to a descriptive overview of products and their substitutability scores. There may, however, be underlying factors that explain why some products receive higher scores than others. Therefore, the following set of hypotheses aims at providing insights into this variation.
As known from innovation, technology and media adoption research (e.g., Liébana-Cabanillas, Sánchez-Fernández, & Muñoz-Leiva, 2014; Patil, Tamilmani, Rana, & Raghavan, 2020) different consumers might react differently to the idea of substituting physical products through AR. In other words, individual consumer characteristics might pay an important role.
The first hypothesis deals with consumers’ chronological age. After reviewing research on the role of age, Botwinick (2013) concludes that younger consumers are more likely to make consumption decisions that are somehow risky and may require a change in everyday situations. In contrast, older consumers are generally more cautious. Buhler’s life span model (1968) describes early adulthood as a pursuit of creative expansion or the acquisition of new experiences, which could include AR – especially holographic substitutes. Finally, younger consumers are generally less accustomed to existing habits and views and therefore tend to be more open to new ideas, especially with regard to new technologies (Lustig, Konkel, & Jacoby, 2004). Consequently, older consumers typically have strong habits (e.g. how a typical product should look – for instance, a wall clock) that make it difficult for them to adapt to something new (e.g., a holographic wall clock). Therefore, H1 proposes that younger consumers are more likely to accept AR substitutes:
H1
Age is negatively related to the acceptance of AR substitutes.
Second, consumers’ gender might play a similar role like age, in a way that males are proposed to be more open to AR substitutes. This assumption is supported by the findings presented in Citrin, Stem, Spangenberg and Clark (2003) that indicate that women rely more on tactile cues when evaluation products than males. Since holograms do not offer tactile cues (yet), females might evaluate AR substitutes less positively. Likewise, there is a replicated finding that males react more positively to (digital) innovations than women (for a review and possible explanations, see Li, Glass, & Records, 2008). Thus, more formally:
H2
Gender has an effect on the acceptance of AR substitutes in a way that males show higher preferences for AR substitutes than females.
Next, AR substitutes are under the umbrella of AR. Consumers with more or less familiarity with AR in general may thus react differently to AR. One could argue that highly familiar consumers know more about the AR market and its future and thus may be more open to AR substitutes. Theoretically, prior AR experiences lead to a higher knowledge, in particular “tacit knowledge” about AR and its potential use cases – including substitutes. This is typically also associated with more positive evaluations of AR. For instance, Hinsch et al. (2020) report correlations between familarity with AR and various positive outcomes of AR, such as ease of use or hedonic benefits. Likewise, consumers with a higher familiarity of early stage technologies, including AR, typically score higher on openness to experience (Rauschnabel et al., 2015), a personality trait closely linked to innovativeness, curiosity, and a general proneness to adopt innovations (Costa & McCrae, 1992). Thus:
H3
AR familiarity is positively related to the acceptance of AR substitutes.
Consumers with a higher level of familiarity with AR may also have given more thought to how AR can affect their lives in general. In other words, these consumers may have their own personal AR vision. In contrast to familiarity, an AR vision is even more specific, since it includes specific personal ideas and use cases. The vision concept is also similar to the theory of inspiration (Thrash & Elliot, 2004), which, although not uniformly defined, can be described as an “appetite state”. It has been shown that inspiration in the AR context has a significant impact on changes in attitudes (Rauschnabel et al., 2019) and behaviors (Hinsch et al., 2020). However, a personal AR vision is even more specific than inspiration in general, as it represents concrete ideas about how AR – and especially holograms – can contribute to the lives of consumers. Consumers with a strong AR vision may therefore already have developed specific ideas and scenarios (rather than a general idea), are more aware of the possibilities and may therefore be more positive about the idea of AR substitutes. Thus:
H4
Consumers’ personal AR vision is positively related to the acceptance of AR substitutes.
Finally, H5 proposes that consumers with a “digital substitution history” are also more likely to substitute products though AR. As discussed, the term “digital substitute” describes digital, but non-AR, versions of products, such as ebook readers (instead of books) or music files (instead of CDs) (Sweeten et al., 2018; Watkins et al., 2016). Consumers that have gained experiences in “giving up” certain characteristics, maybe even benefits, of physical products (e.g., the touchiness or smell of a book or the visibility of one’s music collection) might therefore also be more prone to adopt AR substitutes. On the one hand, these consumers might have already “learned” that digital benefits can outperform certain drawbacks of physical products (e.g. weight, size or price). On the other hand, these consumers might have a general preference for any form of digital product. Thus:
H5
Consumers general preferences for digital products (non-AR) is positively related to the acceptance of AR substitutes.
4.2. Product characteristics
In addittion to consumer characteristics, typical characteristics of each product category may explain this variation, and H6 will specify this in more detail. For example, one could argue that consumers consider product categories to be more substitutable if they are already digital (e.g. TV screens), at least to a certain degree – such as TVs. In this case, consumers might develop clear ideas of how this could work more easily and associate it with fewer drawbacks or concerns. Likewise, consumers may be more open to substitute products that are typically expensive. There, consumers might expect the same, or a similar, value in use for a lower price. Following established acceptance research (e.g., Venkatesh et al., 2012). This price advantage should translate into higher acceptance rates of AR substitutes. Likewise, the literature on AR has shown that utilitarian, hedonic and symbolic benefits determine its use (e.g. Rauschnabebel, 2018), so that realistic representations of products with similar benefits might have it easier to achieve a high substitution acceptance. Furthermore, although consumers have varying levels of “need for touch” (Peck & Childers, 2003), consumers’ haptic motivations might differ between product categories3 . Finally, one could argue that because most AR substitutes lack specific features (e.g., tangibility or visibility to thers), AR substitutes are more accepted for products that are “nice to have”, compared to essential products. In short:
H6
Category-specific product characteristics relate to substitution acceptance.
5. Study 1: are consumers ready to accept AR substitutes?
5.1. Objective
The objective of the first study is to gain an initial understanding of how consumers react to the general idea of substituting products. This study focuses on product categories as a whole based on a sample of US respondents.
5.2. Methodology and research design
A professional market research firm recruited and surveyed 1,078 US consumers (age: m = 40.0; SD = 13.5 years; 51.4 % female) who reflect the US population in terms of age, gender and region via an online questionnaire. The survey began with an ice-breaker question about the technologies they use (e.g. tablet, smartphone, etc.). This was followed by a definition of AR and examples to ensure a common understanding of it. Respondents were then asked to rate their knowledge of AR. Next, they rated a list of eight categories in terms of their personal substitutability, ranging from 1 (not at all) to 7 (very likely): decorative products, functional products, electronic devices, personal memorabilia, pets, flowers, atmospheric objects, and toys. The measurement appendix lists all items.
5.3. Results
RQ1: As presented in more detail in Table 2 and in Figure 2, the results indicate the highest consumer acceptance for replacing electronic products (M = 3.87), followed by other functional products (M = 3.83) and toys (M = 3.63). Pets were rated the lowest (M = 3.13). It is important to note that standard deviation was between 2.06 and 2.14, which is fairly high for seven-point scales. This indicates the different perceptions of respondents about these substitutes.
Table 2. AR Substitution acceptance in the United States (Study 1).
| Complete Sample (n=1,078) | Familiarity with AR | ||||||||||
|---|---|---|---|---|---|---|---|---|---|---|---|
| High (n = 154) | Moderate (n = 264) | Low (n = 390) | No (n = 270) | ANOVA | |||||||
| M | SD | M | SD | M | SD | M | SD | M | SD | η2 | |
| Products that I use to decorate my house (e.g. pictures, posters) | 3.51 | 2.02 | 4.97 | 2.05 | 3.70 | 1.95 | 3.06 | 1.87 | 3.15 | 1.87 | .103 |
| Functional products with which I organize and manage my life (e.g. Post-it notes, shopping lists, calendars) | 3.83 | 1.99 | 5.36 | 1.71 | 4.04 | 1.94 | 3.44 | 1.88 | 3.31 | 1.87 | .118 |
| Electronic devices/hardware (e.g. televisions, radios, game consoles) | 3.87 | 2.01 | 5.23 | 1.78 | 4.08 | 1.94 | 3.52 | 1.94 | 3.41 | 1.91 | .094 |
| Personal memorabilia (e.g. souvenirs, pictures of people who are important to me) | 3.44 | 2.07 | 4.94 | 2.09 | 3.57 | 2.00 | 3.00 | 1.94 | 3.10 | 1.89 | .100 |
| Pets (such as a virtual dog or bird) | 3.13 | 2.14 | 4.59 | 2.28 | 3.45 | 2.08 | 2.55 | 1.96 | 2.81 | 1.90 | .105 |
| Flowers (such as palm trees or orchids) | 3.36 | 2.05 | 4.86 | 1.93 | 3.48 | 2.02 | 2.92 | 1.91 | 3.00 | 1.93 | .102 |
| Atmospheric objects (e.g. candles, atmospheric lamps, chimneys) | 3.52 | 2.07 | 5.01 | 1.90 | 3.67 | 2.08 | 3.13 | 1.95 | 3.07 | 1.92 | .100 |
| Toys (e.g. board games, soft toys) | 3.63 | 2.06 | 5.20 | 1.73 | 3.86 | 2.06 | 3.20 | 1.94 | 3.14 | 1.92 | .117 |
Note: ANOVA; all p < .001; eta squared effect size.
The first set of analyses compared substitution acceptance between different demographic groups. In line with H1, results show significant (all p < 0.001) negative correlations for age with all product categories. These coefficients ranged from r=-0.213 (personal memorabilia) to r=-0.272 (functional products), and thus, partially support H1. Males tend to respond more positively to the idea of substituting objects, but this effect was only significant for functional products (Mmale = 3.95; Mfemale = 3.71; p = 0.048), electronic devices (Mmale = 4.03; Mfemale = 3.72; p = 0.010), personal memorabilia (Mmale = 3.60; Mfemale = 3.29; p = 0.012), atmospheric objects (Mmale = 3.65; Mfemale = 3.38; p = 0.032), and toys (Mmale = 3.77; Mfemale = 3.50; p = 0.028). These results provide partial support for H2.
Additionally, one could hypothesize that AR substitutes may be more accepted by low-income consumers, since virtual products are typically less expensive than their physical counterparts. This would be in line with the development of H5 (see Section 4.1; results will be presented in Study 4). The results, however, indicate that this may not be true (all p > 0.11) at all. Pets were the only exception among the studied products. In this case, low-income consumers (n = 328; defined as less than $75,000 in household income per year) showed higher means (Mlow = 3.23; Mhigh = 2.95; p = 0.041).
The next analyses focus on the relationship between different levels of AR knowledge and substitution acceptance. ANOVAs using Scheffé post hoc tests provide empirical evidence for H4. Results show significantly higher levels between very high and high AR knowledge (on average 1.22 higher; all p < 0.001), whereas the differences between moderate, low and high AR familiarity were much smaller (on average 0.63; all p < 0.007). One interesting finding is that AR substitution is substantially above the scale mid-point of four among the highly familiar respondents. Results support H3 (Fig. 2).
5.4. Discussion of study 1
In conclusion, this study provides some initial and interesting insights. Consumers show a fairly high level of acceptance of AR substitutes, especially young male consumers with a high level of AR knowledge and experience. However, the acceptance varies between product categories, where some categories, such as functional products, have fairly high rates.
6. Study 2: Refinement of substitutable products
6.1. Objective
Study 1 identified a fairly high substitution intention based on a sample of US consumers among “broad” product categories rather than specific products. Study 2 complements Study 1 by investigating specific products and by assessing the substitution potential in a different market – Germany. Therefore, we conducted preliminary work4 to identify 55 products to be evaluated by respondents. Study 2 further aims at providing insights into the advantages and disadvantages of holographic substitutes.
6.2. Methodology and research design
With the help of a professional market research firm, we surveyed 579 German consumers (age: M = 43.9, SD = 12.3 years; 54.1 % female; 6.2 % students). The survey started with an explanation of AR technologies, followed by an introduction to the idea of substituting AR for real products. Next, the respondents rated their level of familiarity with AR, their personal AR vision (i.e. the extent to which consumers have already thought about the consequences of AR for their lives), and their anticipated AR substitution (i.e. the extent to which they believe that AR can make certain products obsolete for them in the future). The measurement appendix lists all items.
The main part of the questionnaire included a list of 55 products that respondents rated in terms of substitutability on a scale from one to seven (higher values indicate higher substitution). These items were analyzed individually (Table 4) as well as averaged to a general “average substitution score”. Finally, to learn more about the pros and cons of substitutes, we asked consumers to contrast the benefits and risks of real versus virtual products by asking them to rate a variety of statements (see Table 5).
6.3. Results
6.3.1. Correlational analyses
The discussion of the results starts with an inspection of the correlations between the core variables (Table 3). First, consumers’ general acceptance of substitution correlates highly (r = 0.699; p < 0.001) with their average substitution score across all products, which serves as a plausibility measure. Higher familiarity with AR is associated with a clearer vision of how AR can affect consumers’ lives (r = 0.603; p < 0.001). Additionally, familiarity is associated with higher values on all other substitution-related variables (e.g. general acceptance of substitution: r = 0.351; average substitution: r = 0.274; anticipated AR substitution: r = 0.348; all p < 0.001), which replicates the findings of Study 1 in a different country with a different measure of familiarity and thus provide additional support for H3. In line with H4, respondents with a clearer personal AR vision are significantly more open to the idea of substitution (e.g. general acceptance of substitution: r = 0.482; average substitution: r = 0.409; anticipated AR substitution: r = 0.505; all p < 0.001). The results for age and gender also support H1 and H2, namely that males and younger consumers tend to be more open to AR substitutes (Table 4).
Table 3. Correlations (Study 2).
| 1 | 2 | 3 | 4 | 5 | 6 | ||
|---|---|---|---|---|---|---|---|
| 1 | Familiarity with AR | ||||||
| 2 | Personal AR vision | .603 | |||||
| 3 | General acceptance of substitution | .357 | .482 | ||||
| 4 | Average substitution (55 products) | .274 | .409 | .699 | |||
| 5 | Anticipated AR substitution | .348 | .505 | .602 | .519 | ||
| 6 | Gender (0=female, 1= male) | .104 | .129 | .074 | .073 | .105 | |
| 7 | Age | −.359 | −.224 | −.19 | −.072 | −.12 | .374 |
Table 4. Substitution acceptance for different products (Studies 2 and 3).
| Study 2 | Study 3 | ||||||
|---|---|---|---|---|---|---|---|
| No | Product | M | SD | M | SD | r(DS) | p |
| 1 | Repair/assembly instructions | 4.71 | 2.13 | 5.38 | 1.68 | .25 | .00 |
| 2 | Navigation devices | 4.53 | 2.18 | 5.57 | 1.66 | .36 | .00 |
| 3 | Shopping lists | 4.53 | 2.21 | 4.93 | 1.86 | .40 | .00 |
| 4 | Advertising (leaflets) | 4.46 | 2.17 | 5.07 | 1.97 | .17 | .00 |
| 5 | Weather stations (thermometers) | 4.38 | 2.16 | 5.06 | 1.83 | .22 | .00 |
| 6 | Configurators for vehicles | 4.21 | 2.14 | 5.26 | 1.79 | .26 | .00 |
| 7 | Wall calendars | 4.13 | 2.23 | 4.23 | 2.07 | .28 | .00 |
| 8 | Post-it notes/notepads | 4.13 | 2.19 | 4.67 | 2.02 | .26 | .00 |
| 9 | Newspapers/magazines | 4.09 | 2.17 | 4.49 | 1.90 | .32 | .00 |
| 10 | Signs | 3.96 | 2.18 | 3.93 | 2.22 | .12 | .01 |
| 11 | Game consoles | 3.82 | 2.27 | 4.62 | 2.02 | .16 | .00 |
| 12 | Pin boards | 3.81 | 2.19 | 4.13 | 2.09 | .31 | .00 |
| 13 | Cockpits in cars | 3.77 | 2.15 | 4.92 | 1.93 | .28 | .00 |
| 14 | TV sets | 3.74 | 2.22 | 4.39 | 1.96 | .21 | .00 |
| 15 | Board games, games | 3.73 | 2.13 | 3.87 | 2.07 | .29 | .00 |
| 16 | Wall clocks | 3.73 | 2.23 | 3.75 | 2.15 | .20 | .00 |
| 17 | Posters | 3.61 | 2.14 | 3.45 | 2.09 | .17 | .00 |
| 18 | Tablet PCs | 3.56 | 2.20 | 4.22 | 1.97 | .19 | .00 |
| 19 | Computers | 3.51 | 2.11 | 4.04 | 1.96 | .16 | .00 |
| 20 | Wristwatches | 3.42 | 2.17 | 3.74 | 2.11 | .19 | .00 |
| 21 | Photo albums | 3.37 | 2.23 | 3.26 | 2.02 | .31 | .00 |
| 22 | Large paintings | 3.32 | 2.13 | 2.83 | 1.91 | .19 | .00 |
| 23 | Smartphones | 3.32 | 2.13 | 4.21 | 2.01 | .21 | .00 |
| 24 | Digital cameras | 3.30 | 2.04 | 4.05 | 2.03 | .23 | .00 |
| 25 | Small pictures | 3.30 | 2.12 | 2.95 | 1.93 | .22 | .00 |
| 26 | Paintings | 3.28 | 2.14 | 2.89 | 1.99 | .21 | .00 |
| 27 | Aquaria | 3.22 | 2.17 | 3.16 | 2.03 | .23 | .00 |
| 28 | Floor clocks | 3.19 | 2.16 | 3.23 | 2.07 | .26 | .00 |
| 29 | Private pictures | 3.09 | 2.14 | 2.76 | 1.92 | .31 | .00 |
| 30 | Light switches | 3.06 | 2.14 | 3.16 | 2.16 | .23 | .00 |
| 31 | Stereo systems | 3.02 | 2.04 | 3.11 | 2.04 | .16 | .00 |
| 32 | Wall colors | 3.00 | 2.14 | 2.64 | 1.94 | .14 | .00 |
| 33 | Seasonal decorations (Christmas, Easter, etc.) | 3.00 | 2.04 | 2.80 | 1.90 | .22 | .00 |
| 34 | Decorative books | 3.00 | 2.17 | 2.59 | 1.97 | .08 | .11 |
| 35 | Window decorations | 2.94 | 2.07 | 2.71 | 1.88 | .14 | .01 |
| 36 | Wood-burning stoves | 2.89 | 2.10 | 2.56 | 1.90 | .09 | .06 |
| 37 | Wallpaper | 2.83 | 2.10 | 2.57 | 1.87 | .09 | .08 |
| 38 | Candles | 2.77 | 2.02 | 2.42 | 1.77 | .14 | .01 |
| 39 | Window flowers | 2.72 | 2.04 | 2.14 | 1.64 | .15 | .00 |
| 40 | Carpets for decoration | 2.70 | 1.99 | 2.41 | 1.75 | .11 | .03 |
| 41 | Decorative cushions (i.e. without a functional use) | 2.70 | 2.00 | 2.53 | 1.87 | .14 | .01 |
| 42 | Toy figures | 2.61 | 1.94 | 2.22 | 1.56 | .22 | .00 |
| 43 | Floor mats (decoration) | 2.60 | 1.98 | 2.33 | 1.78 | .10 | .05 |
| 44 | Placemats | 2.52 | 1.85 | 2.26 | 1.63 | .09 | .07 |
| 45 | Hanging lights | 2.51 | 1.87 | 2.02 | 1.46 | .06 | .27 |
| 46 | Table plants | 2.46 | 1.90 | 1.95 | 1.45 | .13 | .01 |
| 47 | Flowers | 2.45 | 1.91 | 1.87 | 1.38 | .18 | .00 |
| 48 | Curtains | 2.42 | 1.89 | 1.91 | 1.46 | .08 | .13 |
| 49 | Toy cars | 2.41 | 1.83 | 2.10 | 1.45 | .17 | .00 |
| 50 | Bedspreads | 2.41 | 1.87 | 2.03 | 1.58 | .10 | .05 |
| 51 | Tablecloths | 2.40 | 1.84 | 2.03 | 1.54 | .10 | .05 |
| 52 | Personal memorabilia | 2.28 | 1.81 | 1.68 | 1.36 | .26 | .00 |
| 53 | Soft toys | 2.22 | 1.81 | 1.49 | 1.04 | .19 | .00 |
| 54 | Jewelry | 2.20 | 1.69 | 1.73 | 1.35 | .18 | .00 |
| 55 | Pets (dogs, cats, etc.) | 1.83 | 1.63 | 1.52 | 1.26 | .17 | .00 |
| Average | 3.32 | 1.45 | 3.23 | 1.12 | .19 | .000 |
Note: Correlation (n = 55) between the means of Study 2 and Study 3: r = .96; SDs: r = .85; average correlation (r = .19) was calculated after a Fisher’s z transformation of all correlations.
6.3.2. Substitutability of specific products
RQ1: The next analyses address substitution acceptance for each of the 55 products. Table 4 lists the means and standard deviations for all products. Practical products, such as repair instructions, navigation devices and shopping lists are leading the list with ratings above the scale midpoint. Personal momorabilia, soft toys, jewelry, and pets received the lowest ratings.
6.3.3. Advantages of holographic substitutes vs. physical products
As discussed above, the survey included general advantages and disadvantages of holographic substitutes. Table 5 presents these statements and their descriptive statistics. A factor analysis revealed a clear two-factor solution where all advantages loaded on one factor (α = 0.922) and all disadvantages on the other (α = 0.888). A regression analysis in which the general acceptance of substitution served as a dependent variable showed that these factors both drive intention in the proposed direction (R squared = 54 %).
Table 5. Drivers of substitution (Study 2).
| Descriptive Statistics | Regression Analyses | |||||
|---|---|---|---|---|---|---|
| DV: General substitution intention | Combined level | Item level | ||||
| M | SD | Beta | p | Beta | p | |
| Advantages (Combined) | 3.818 | 1.502 | 0.703 | 0.000 | ||
| … cheaper than real products | 4.081 | 1.873 | 0.041 | 0.346 | ||
| … more flexible than real products | 4.513 | 1.847 | −0.006 | 0.902 | ||
| … more practical than real products | 3.446 | 1.817 | 0.221 | 0.000 | ||
| … more entertaining than real products | 3.442 | 1.850 | 0.235 | 0.000 | ||
| … more environmentally friendly than real products | 4.471 | 1.870 | 0.066 | 0.100 | ||
| … more functional than real products | 3.775 | 1.855 | 0.050 | 0.269 | ||
| … for me more private/secret than real products | 3.279 | 1.956 | 0.133 | 0.003 | ||
| … generally less risky than real products | 3.536 | 1.861 | 0.113 | 0.015 | ||
| Disadvantages (Combined) | 5.801 | 1.206 | −0.162 | 0.000 | ||
| … not touchable | 6.090 | 1.442 | 0.018 | 0.702 | ||
| … less personal than real products | 6.041 | 1.394 | 0.008 | 0.865 | ||
| … less prestigious than real products | 4.840 | 1.855 | −0.020 | 0.547 | ||
| … more dependent on technology than real products | 5.932 | 1.444 | 0.018 | 0.689 | ||
| … less authentic than real products | 5.705 | 1.524 | −0.177 | 0.000 | ||
| … only visible with technology | 6.196 | 1.322 | −0.004 | 0.927 | ||
| Model fit | ||||||
| R squared | .54 | .58 | ||||
| R squared (adjusted) | .54 | .57 | ||||
| VIF (max) | 1.01 | 3.24 |
Note standardized coefficients only; OLS regression analyses.
However, since the effects of these two broad constructs do not provide any specific insights, a second regression included all items separately as independent variables. These results show that greater perceived hedonic and utilitarian benefits as well as the possibility of “hiding” products from other people tend to drive their substitution acceptance. This contradicts the concept of conspicuous consumption, where people consume to enhance their prestige, and is in line with the benefits some respondents in Helm, Ligon, Stovall and van Riper (2018) reported about not showing others the books they read. However, consumers who rate AR substitutes as less authentic are less open to the idea of substitution.
Finally, it is important to note that the disadvantages receive higher agreement scores than the advantages (as indicated in the mean scores in Table 5). However, not all of them are relevant in explaining substitution, as the results of the regression analyses show.
6.4. Discussion of study 2
Study 2 makes two several important insights. First, in line with Study 1, the results indicate fairly high acceptance rates for several products, especially among AR experienced users. Second, looking at this more detailed list of products provides deeper descriptive insights (as discussed later) from another country.
7. Study 3: extended replication
7.1. Objective
Study 3 is an extended replication of Study 2 based on a separate sample in Germany. Moreover, it links the findings to the tendency of consumers to use digital products instead of physical ones.
7.2. Methodology and research design
The research design of Study 3 is similar to Study 2. The sample (n = 401) was collected using a convenience sampling approach, such as via social media platforms and email lists of a German university (sample: age: M = 30.5, SD = 12.3 years; 39.7 % female; 48.1 % students). The survey included the same list of products as in Study 2, and respondents rated the substitutability of each item again on a scale from one to seven. In addition, the survey included the preference of consumers for digital products over physical one (e.g. read a real book vs. read an e-book; higher values indicate “more digital” preferences; in short; digitalism scire (DS), see measurement appendix).
7.3. Results
7.3.1. Substitutability of products
RQ1: The results of Study 3 are contrasted in Table 5 with the results of Study 2. A correlation between the 55 substitution ratings of Studies 2 and 3 indicates an almost “perfect” correlation of 0.96, which indicates consistency between the two studies (see Table 4).
7.3.2. Individual difference variables
A series of correlations assessed the association between the general preferences of consumers for digital products and the AR substitutes. The correlation between the average substitution score of consumers across the 55 products and the digitalism score (DS) is 0.327 (p < 0.001), which signifies that consumers who prefer digital products in general are also more open to entirely virtual versions of products. These findings support H5. Table 4 also lists the correlations for each product (right column).
7.4. Discussion of study 3
Study 3 makes two important contributions. First, although the data was collected differently, the patterns are almost identical. Second, the study shows that consumers who prefer digital goods in general tend to be more open to AR substitutes. This finding adds some nomological validity to the study. Furthermore, it may help marketers with targeting.
8. Study 4: Characteristics of substitutable products
8.1. Objective
So far, we have learned from the first three studies that a fairly large number of consumers show high acceptance rates for holographic substitutes but that there is also variation in this evaluation which is partly explained by demographic and psychographic variables. However, there are not just variations within each product but also between products. In other words, some products are more substitutable than others. Study 4 aims to explain these variations based on product characteristics, as hypothesized in H6.
8.2. Methodology and research design
This study uses the data from aggregated Study 2 (more specifically: the 55 mean scores presented in Table 4) and links them to specific characteristics of each of these products. To quantify these product characteristics, n = 245 respondents from a commercial market research panel in Germany completed a short online questionnaire. Participants were blind to the AR and study context. They randomly received ∼six out of 55 product categories and were asked to rate each one of them in general according to 10 different criteria on a scale from 1 (does not apply at all) to 7 (totally applies), as introduced in the hypotheses section. These criteria were (exact wording in parentheses):•
Utilitarian benefits ([product] “is useful in everyday life”)•
Hedonic benefits ([product] “is entertaining”)•
Symbolic benefits ([product] “is symbolic, i.e. it says something about the owner”)•
Decorative benefits ([product] “is decorative”)•
Visibility ([product] “is visible for guests”)•
Personal benefits ([product] “is something very personal”)•
Digitalism (“[product] has a digital component (i.e. is digital/shares with digital things)”)•
Expensive ([product] “is usually very expensive”)•
Tactile benefits (“I must (be able to) touch – at least occasionally”)•
Non-essentiality ([product] “is something I could do without if I had to”)
To analyze the data, the mean substitution scores from Study 2 were paired with the ratings from this study. Thus, n = 55 substitution-product characteristic sets served as the empirical base for this study. The correlations between the substitution scores and each criterion served as an indicator for characteristics that contributed to substitution acceptance.
8.3. Results
Due to the small sample size, bivariate correlations provided a pragmatic approach for inspecting the relationship between general characteristics of the product category and AR substitution acceptance.
The results (see Table 6) show positive and significant correlations for utilitarian benefits (r = 0.491) and the “digitalism” of product categories (r = 0.451). Furthermore, symbolic (r=−0.575) and decorative (r−0.626) benefits, as well as visibility (r=−0.610) and the degree to which products in a category represent “something” personal (r=−0.402) show a significant negative correlation. Expensiveness, tactile benefits, and non-essentiality show negative correlations which, however, do not reach significance (all p > 0.199). An inspection of the scatterplots did not indicate any biased results due to one or very few outliers. Thus, since product characteristics (but not all of them) show significant correlations with substitution, H6 receives partial support. Fig. 3 plosts some of these correlations.
Table 6. Product characteristics and substitution.
| Product Category | r | p |
|---|---|---|
| Utilitarian benefits | .419** | .001 |
| Hedonic benefits | .052 | .706 |
| Symbolic benefits | −.575** | .000 |
| Decorative benefits | −.626** | .000 |
| Visibility | −.610** | .000 |
| Personal benefits | −.402** | .002 |
| Digitalism | .451** | .001 |
| Expensive | −.143 | .298 |
| Tactile benefits | −.149 | .278 |
| Non-essentiality | −.176 | .199 |
N = 55 pairs of product ratings and substitution scores; r = correlations .
8.4. Discussion of study 4
Study 4 identified several product characteristics that relate to consumer acceptance of AR substitutes. The findings complement the regression findings of Study 2 (Table 5). In Study 2, consumers’ expressed acceptance of substitutes was strongly driven by increased utilitarian (compared to physical products) and weakly by hedonic benefits. Here, in this relatively small sample (n = 55), hedonic benefits did not reach significance.
9. General discussion
As mentioned above, forecasts consistently indicate that AR has the potential to develop into a mass medium in the coming years. Current research typically addresses narrow issues in AR, such as how people perceive AR technology or respond to specific AR content (Carozzi et al., 2019; Javornik et al., 2019; Rese et al., 2017). These findings are highly relevant in order to develop better communicative activities and better AR content. There is, however, little “visionary” research on how AR can affect societies and industries as a whole. This article applies a more “radical” and future-oriented approach to studying AR’s future as a disruptor of the real world. Instead of investigating AR as a “helper tool” for our physical world, this research treats AR content as a substitute for parts of our physical world. The main findings are as follows.
First, many products received substitution scores around or above the scale mid point. In some segments (e.g., consumers with AR experience, as discussed below) even substantially above. Given that AR is still quite new to most people (see Table 3), these numbers are faily high.
Second, the differences in substitutability across products are not random, but somehow systematic. Study 4 shows that products with high substitution scores are typically characterized as utilitarian, digitized, but less symbolic, visible or decorative. The results did not confirm the assumption that expensive, “must-touch products”, or non-essential products have higher or weaker substitution scores. Likewise, both highly and poorly substitutable products show similar patterns in terms of hedonic characteristics. However, the finding that expensive products do not receive higher substitution scores per se indicates that consumers do not treat AR substitutes as a “cheap copy” of real products but rather a new category of products (Carozzi et al., 2019). Consumers tend to perceive AR substitutes as something different, and this deserves more academic attention. Interestingly, the possibility to experience AR products somehow secretly (i.e. a user can hide content from other people), as indicated in study 2, tends to be a driver of substitution.
Third, consumers respond differently to the idea of AR substitutes. Male and young consumers, mostly independent of their financial situation, are more open to it, as indicated by the first two studies. Consumers with a personal AR vision – i.e. consumers who have ideas about how AR can affect their lives – accept AR substitutes significantly more. Finally, Study 3 shows that consumers who have a tendency to prefer digital substitutes (e.g. e-books instead of real books) are also more open to AR substitutes. An important finding across Studies 1 and 2 is that consumers with a higher familiarity with AR are more open to AR substitutes. This could mean that with an increase in familiarity (currently, as reported in study 1, only ∼14% have actual AR usage experience, but this number will likely increase once AR develops to a mass medium), consumers become aware of more possibilities and thus have more ideas about how AR can contribute to their lifes – with substitutes as one aspect of it.
Studying a novel, perhaps futuristic, view of AR and its impact on businesses and thus societies as a whole provides multiple contributions. The following sections will discuss the main implications for theory and managerial practice in more detail.
9.1. Theoretical implications
The introduction and specific focus on the substitution of physical products by AR yields results that advance prior work on AR in several ways. First, AR marketing theory in the past has treated AR often as a tool for communicating product benefits or for promoting sales (e.g., Feng & Mueller, 2019; Ruyter et al., 2020; Tsai et al., 2020). As a result, AR’s role has been viewed more as a “supporter” of the product mix which, for example, promotes sales, adds features (e.g. Lego), or provides remote services – often in B2B marketing (“AR-for-a-product-view”). Thus, one could summarize the marketing research on AR as being “tactical” rather than strategic or even visionary. Only a few studies have carefully questioned this view, such as Dwivedi et al. (2019), who discuss a broader view of AR marketing, including new sources of data. This research complements this mostly tactical view with a radically new view that AR content – i.e. holographic versions of products – might not just support existing products. It might even replace real products (“AR-as-a-product-view”). For a company, this can indicate a new type of product category (if a company is launching new products in AR) or a new competitor (if other, maybe even new players, launch such AR products). This disruptive potential could play a serious role in a firm’s product mix – with further implications for pricing (e.g. the value of AR substitutes), distribution (e.g. how to distribute them), and communication (e.g. how to advertise the benefits of holographic products). Therefore, this study updates the prevalent view of AR as a tactical tool by lifting it to a highly strategic level including the entire marketing mix, marketing strategy (in particular new competitors), and new opportunities that arise from holographic products (as discussed in the managerial implications section later). Thus, future theoretical advances should treat AR marketing as a highly strategic concept with a role beyond communication.
Second, AR marketing research has mostly been discussed from the perspective of the firm that is applying it (e.g., Rauschnabel et al., 2019; Scholz & Duffy, 2018). Studies have thus concluded that companies that apply certain AR marketing activities can benefit from a positive impact on their brands (Rauschnabel et al., 2019), higher prices (Heller, Chylinski, de Ruyter, Mahr, & Keeling, 2019), and customer satisfaction, among other managerially relevant variables. However, companies that do not incorporate AR into their marketing plans have not received much attention so far. In simple terms, one could say that these companies will not benefit from the advantages AR can provide. This study highlights the belief that this assumption may be dangerous in the future. Companies – regardless of whether they have an impressive AR app or not – can be affected by AR if other players create and market AR content that can replace their products.
Third, this leads us to the question of who the “manufacturers” of virtual products can be. On the one hand, traditional competitors can launch holographic versions of their products, or professional AR content creators can enter existing markets. This could be relatively easy for firms that have CAD data of their products. On the other hand, almost any consumer can serve as a “manufacturer” of AR content in the future, as is indicated by various consumer trends. For example, since the advent of social media, many consumers have not only been consuming content but also producing it (Kaplan & Haenlein, 2010), such as the almost professionally looking user-generated content (UGC) on YouTube or Instagram. Next, although AR is still in an early stage, numerous companies are offering development kits that promise the creation of AR content without coding – in other words, the ability for everyone to produce AR content. Finally, the literature on 3D printing proposed the “innovation as data” (IAD) view, which indicates that “consumers employ new digital tools such as audio and video editing software and 3D printing technology to directly turn data into innovative product offerings.” (Rindfleisch, O’Hern, & Sachdev, 2017, p. 681). The openness of consumers to the idea of substituting new products, combined with the general acceptance of creating UGC with easy-to-use tools, indicates a realistic scenario in which user-generated augmented reality content (UGARC) may present a new challenge for marketers. This study thus contributes to the IAD view by suggesting its extension to AR content. It also contributes to Porter’s Five Forces Model by discussing AR content developpers as new competitors in existing markets for physical products.
Fourth, the comprehensive assessment of the substitutability of products advances prior research on how consumers interact with real vs. virtual products (Carozzi et al., 2018). While the pioneering work on this inquiry has shown similarities in processing, boundary conditions remain unanswered. This study shows that different consumers can imagine the substitution of different product categories differently. For example, the studies indicate that consumers do not see holographic substitutes as a plan B for products they cannot afford. Instead, they could treat them as a new category of products with benefits (e.g. secret consumption; see Carozzi et al.,2018) that physical products may not always offer. For instance, although not explicitly examined here, the “hidden” consumption of AR content may be conceptually linked to inconspicuous consumption (e.g., Helm et al. (2018)in a different context).
9.2. Implications for managers and educators
This study reveals that consumers – especially some segments – tend to be fairly open to the idea of replacing real products with holographic versions. The central managerial implication of this article is thus that managers and educators must think more strategically about AR and must consider it a disruptor. The following sections will explain this in more detail.
9.2.1. New ways of thinking about AR: A disruptor, not a gimmick
Consumers may have difficulty articulating their future needs and may underestimate their need for innovative new products. They may even underestimate their future needs. For this reason, these results do not show that certain product categories will eventually be replaced. Preferences may change, most likely in favor of substitution. The results indicate that some consumers are fairly open to the idea of living in a world that is consistently enriched with virtual products that make physical products somehow obsolete. This could make the introduction of such virtual products easier than it would be if consumers consistently opposed them. One argument against substitutes is that virtual products are not tangible and thus do not create haptic experiences. Certain products have a core function that requires physical elements (e.g. a bottle). For other products, the haptic experience is a benefit (e.g., toys). Recent developments indicate that haptic experience can be reproduced in the future, either with gloves that have pneumatic actuators that imitate contact between a user and a hologram (Zhu et al., 2020) or with similar technology implanted under a user’s skin.
What does this mean for companies? First, building on findings from other research (e.g. that AR can generate new forms of data), the findings underline that AR has the potential to be highly disruptive in marketing. Second, if certain products are replaced, this could lead to economic turbulence. Some products may become obsolete, and companies will need to find ways to compensate. But there will also be an increasing demand for content creators. Third, it may be risky to rest on one’s laurels because current AR cannot yet mimic certain sensual experiences. We do not know what future technologies will bring. Therefore, the findings should encourage ALL managers not to think of AR as a toy or a gimmick for communication purposes only. It may become disruptive for entire industries.
9.2.2. Holographic counterfeits: copy and paste for the real world
The next generation of smart mobile devices will include depth sensors. Scanning real products and integrating them into AR may therefore become an easy way to copy real products into an AR world. The findings (particularly of Study 4) show that this may not be limited to expensive products. For example, wall clocks, calendars, posters and signs are among the more acceptable substitutes. Consumers could easily “scan” physical products and replicate them as a hologram – and they might accept these virtual versions. Platforms, such as thingiverse.com (which offers 3D models for almost anything for printing on 3D printers), might become a “Napster for holograms”, where people share and download (illegal?) AR models of branded products. Following the concept of “brand remixing” from the literature on 3D printing (e.g., Rindfleisch & O’Hern, 2015), consumers could also alter branded products in AR.
How should manufacturers of physical products deal with this? As long as AR is limited to optical and acoustic augmentation, focusing on other senses (e.g. haptic benefits, taste and smell) may be a promising strategy. However, many tech players are aiming at mimicking other senses, too. Another approach could be to promote individualized products that provide less value for consumers other than the buyer. Likewise, increasing decorative values could lead to a lower risk of being scanned and copied – for example, by better designs or customized elements of products. Study 2 also suggests that the increased authenticity of physical products could make them less substitutable. However, the concept of authenticity is twofold. First, there is indexical authenticity that “distinguishes ‘the real thing’ from its copies” (Grayson & Martinec, 2004, p. 298), i.e. a Black Forest wall clock that was also actually manufactured in the Black Forest and its associated manufacturing tradition. Second, there is iconic authenticity, which represents how a user feels and imagines where a product actually comes from (e.g. by visualizing a wall clock like a prototypical Black Forest clock). Iconic authenticity could be relatively easy to copy and transfer to holograms, whereas indexical authenticity could remain a USP for many physical products for a longer time.
9.2.3. Basic response strategies: get inspired, don’t ignore
Finally, there are basic response strategies to help companies deal with these findings. These strategies range – in theory – from very passive (ignore) to very aggressive (adopt) responses. These two extremes may not be the best initial approach for a company.
Ignore: The most passive approach is to disregard potential threats and to continue doing what you are currently doing. This is a risky approach in general, since many industries have been quite confident that a disrupter could not threaten their business (e.g. hotels versus Airbnb). For this reason, companies should have a strong justification for this approach, should monitor the market, and should continually review this decision. This approach could work for certain commodity or utility products that require physical elements such as concrete, mechanical machines, screws or corn. But even for these companies, AR can play a role in maintenance or sales and therefore digital twins could be relevant as an enterprise technology (but not as a substitute).
Extend: With this approach, the value of existing products is enhanced by an AR layer. This strategy can combine the benefits of real products (e.g. authenticity) with additional features that can increase authenticity even further. Consider, for example, a wooden Black Forest wall clock with AR features. This additional layer can provide an “x-ray view” into the clock to reveal the mechanism. Additional layers could also change the design of the clock, such as by adding dynamic and moving paintings. Lego is currently applying this strategy to many of its products, for example virtual torches on castles or interactive figures in AR that provide additional features to consumers. Some newspapers have introduced AR elements that provide interactive 3D content to selected articles, and some machines in manufacturing departments contain AR manuals.
Complement: With this strategy, companies extend their existing product portfolio by adding AR products. These could be the same or similar products in AR as well as new products that are exclusively offered in AR. These AR versions could also serve as a prototype and, if successful, could be developed into physical versions at a later date. The success of these holographic versions might be a good predictor of future market success. Customizable AR products can also serve as a source of inspiration. If marketers can track and analyze how consumers alter and use their AR products, they may develop ideas about how to improve their (core) physical products in the future. For example, if Lego created numerous versions of new figures and learned (by monitoring usage/downloads and by tracking visual contextual data, as discussed in Dwivedi et al. (2019)), they might be able to predict the success of physical versions of certain products.
Adopt: Finally, the most extreme response strategy would be to change a business model entirely to AR versions of products. This may, at least nowadays, be the riskiest option. However, this strategy is less risky if market indicators are pointing towards a disruption in a market. For example, if a producer of pin boards realizes that the market for physical pin boards is shrinking and that other players in the market have a strategic advantage (e.g. a better cost structure or higher market share), then using one’s knowledge about pin boards to incrementally virtualize a product portfolio might not be a bad idea at all. Indeed, many companies that have focused on traditional products (e.g. Kodak with film cameras) have been disrupted (or at least strongly negatively affected) because they did not adapt to new developments in time.
9.2.4. Substituting can also mean eliminating: Real-world ad blockers in Marketing
Whenever a virtual substitute is integrated into a consumer’s view of the real world, a certain part of the real world is blocked out. We can therefore expect a variety of apps that systematically block out specific real-world content and overlay it with virtual content. In times of information overload, consumers can thus create their own, personalized realities that include the things they want and exclude the things they do not want. One of the things many people do not like in real life is beying exposed to advertising messages. When it comes to the Internet, many consumers install ad blockers to experience an ad-free web experience (this is an enormous challenge for marketers). The same could be done in the real world. Ad blockers could overlay the real world with neutral content or advertisements of favorite brands. Algorithms could identify disliked or irrelevant brands and automatically block out physical advertisements in the real world. Many websites do not load when users have ad blockers. We can probably expect similar approaches if AR ad blockers are used in the real world.
9.2.5. Educators: incorporate AR into your curricula
Finally, this research also calls for the incorporation of AR into curricula as a disruptive technology and for an assessment of substitutability in particular. So far, some contemporary digital marketing textbooks (e.g. Hanlon (2019)) have tackled selected popular AR examples such as Pokémon Go or the IKEA Place App. That is a great starting point! However, students should be made aware that AR is more than just about gaming or product trials. Managers have stated that a lack of knowledge about the implementation, management and evaluation of AR is a major barrier to its adoption in marketing (Bona, Kon, Koslow, Ratajczak, & Robinson, 2018). Academics should therefore take these calls seriously and teach students that AR marketing is (or can be) highly strategic and potentially disruptive. The findings of this study can serve as a starting point for practical exercises in which students develop their own AR substitutes, identify other substitutable industries (e.g. based on the findings of Study 4), or discuss how specific firms should react to AR substitutes. In a nutshell, modern curricula should dedicate entire courses to AR.
9.3. Limitations and future research
As with all (survey) research, this study has some limitations. In the last century, people may have found it frightening to think of substituting digital files for books or reading newspapers on a screen. Nowadays, we can see that such behavior is common across many consumer segments. For this reason, asking consumers about their opinions or intentions in an unknown future may not realistically predict whether physical products – and if yes, which ones – will someday be substituted. The familiarity of people with AR, the behavior of other people, the marketing strategies of companies, as well as the availability and advancements of AR technology itself (e.g. devices, geo-locations of content, etc.) and its ecosystem can (or will) affect the success of AR substitutes and thus change (and probably increase) the reported substitutability scores. Therefore, it is important to note that the results reported here are not market forecasts. The substitution ratings in Studies 1 through 3 represent only a snapshot of how consumers evaluate AR substitutes nowadays, and these scores may have been influenced by the way (e.g. through photographs or wording) AR was explained in the questionnaire and the cultural contexts of the studies (Jung, Lee, Chung, & tom Dieck, 2018).
Future research should examine how AR substitutes are processed in real life. Consumers could perform certain tasks and researchers could assess their outcomes with real versus AR products (e.g. the enjoyment of watching a movie on a real screen versus virtual AR screen) in a laboratory setting. More research is also needed to build on the exploratory findings of this paper and to advance theories about the processing of AR substitutes. Do the factors that drive the evaluation of physical vs. holographic products differ? Do people pay more (or less) attention to tangible features when processing physical (vsersus holographic) products? What should AR substitutes look like – should they be as similar as possible to the physical products they imitate or completely different?
10. General conclusion
Will augmented reality be eating the real word? Will we be living in a hybrid world that contains fewer physical, and more virtual objects in our perception of reality? This article does not provide a clear yes or no answer to these and similar questions. However, the results across the studies indicate that consumers tend to be open to such new developments. And according to the announcements of leading IT companies, technologies that can offer realistic substitutes are right around the corner. The first digital revolution digitized information (Rindfleisch, 2019). AR, as part of the second digital revolution, can virtualize a variety of physical goods. Academics and managers should therefore treat AR not just as another communication gimmick but instead as a potential disruptor.
Author statement
This is a sole-authored paper. Persons who have significantly supported the author are listed in the acknowledgements. The idea for this project was born during an MBA course at MCI.
Acknowledgements
I would like to thank the editor and reviewers for their invaluable and constructive feedback, as well as Jonas Heller, Reto Felix, Danny Han, and Katrin E. Schein for comments on previous versions of this paper. I would also like to thank D. Glatzel (in particular for Studies 2 and 3) and M. Rusch for research assistance and support.
Appendix 1 Measurement background
Study 1:
Familiarity with AR (adopted from Herz & Rauschnabel, 2018): Are you familiar with augmented reality (AR)? Please select the best answer.•
Yes, I consider myself pretty knowledgeable and I have actual experience using AR. [high]•
Yes, I consider myself pretty knowledgeable but I do not have any actual experience so far. [moderate]•
I have only heard about it but don’t really know what it is. [low]•
No, I don’t know what AR is. [no]
No matter how much you like AR and how experienced you are, we want to know if you can think of different products that could be – at least partially – replaced by augmented reality holograms in the future. Instead of owning, using or interacting with a „real“ product, you would do so with a virtual product. A device (e.g. a smartphone, a tablet, or special AR glasses) would integrate these holograms into your perception of the real world. How likely is it that you would replace – at least partially – the following products with AR?•
Products that I use to decorate my house (e.g. pictures, posters)•
Functional products with which I organize and manage my life (e.g. Post-it notes, shopping lists, calendars)•
Electronic devices/hardware (e.g. televisions, radios, game consoles)•
Personal memorabilia (e.g. souvenirs, pictures of people who are important to me)•
Pets (such as a virtual dog or bird)•
Flowers (such as palm trees or orchids)•
Atmospheric objects (e.g. candles, atmospheric lamps, chimneys)•
Toys (e.g. board games, soft toys)•
Other (please specify)
(1 = not at all, 2, 3, 4 = maybe, 5, 6, 7 = very likely; ad hoc scale)
Study 2:
We would like to know whether you could imagine replacing these products – at least partially – in the future with a virtual product that you could see through augmented reality glasses. Scale: 1 = not at all; 2; 3; 4 = maybe; 5; 6; 7 = yes, in any case plus don’t know/don’t use or own (only in Study 2); coded as a missing value
Therefore, we asked, “Generally speaking, what advantages and disadvantages do you see in replacing real products with virtual elements – at least in part? In comparison to real products, virtual, holographic AR products are…” [Items: See Table 6]
AR Vision (followed by a brief explanation of AR substitutes; ad hoc scale; r = .78; alpha = .87; ad hoc scale)•
I’ve given it some thought.•
I have a concrete idea of what a future like this could look like.
AR substitution intention (DV in the regression analyses; ad hoc scale; alpha = .919; ad hoc scale)•
I would replace real products with holograms / AR content•
I would replace real products with holograms / AR content•
I would enhance real products with holograms / AR content
Familiarity with AR (alpha = .949; adapted from Bracken & Skalski, 2006; Shehryar & Hunt, 2005)•
I know a lot about augmented reality.•
I am familiar with augmented reality.•
I already have experience with augmented reality.
Study 3:
Preference for digital products (ad hoc scale)
We would like to know in advance which products you prefer. [7 P semantic differential; higher values indicate more “digital” product preferences]
Read a real book – Read an e-book / Listen to a CD – Stream music / Read a printed document – Read a PDF on a tablet / laptop / View a private photo album – View private digital photos / Play a board game – Play online / mobile game / Read a real newspaper – Read an e-newspaper / Read a real magazine – Read an e-magazine / Watch a DVD / BlueRay – Stream a movie / Send a vacation postcard – Send a vacation email / Use a hiking map – Use a hiking app / Write a shopping list – Use a shopping list app
References
Adner and Kapoor, 2016aR. Adner, R. KapoorInnovation ecosystems and the pace of substitution: Re-examining technology S-curvesStrategic Management Journal, 37 (4) (2016), pp. 625-648CrossRefView Record in ScopusGoogle ScholarAdner and Kapoor, 2016bR. Adner, R. KapoorRight tech, wrong timeHarvard Business Review, 94 (11) (2016), pp. 60-67View Record in ScopusGoogle ScholarAlimamy et al., 2017S. Alimamy, K. Deans, J. GnothAn empirical investigation of augmented reality to reduce customer perceived riskProceedings of the Academyof Marketing Science and Marketing Transformation: Marketing Practice in an EverChanging World AMSWMC 2017 Developments in Marketing Science (2017), pp. 127-135View Record in ScopusGoogle ScholarAndreessen, 2011M. AndreessenWhy software is eating the worldWall Street Journal, 20 (C2) (2011)Retrieved from https://www.wsj.com/articles/SB10001424053111903480904576512250915629460(09/09/2020)Google ScholarAzuma et al., 2001R. Azuma, Y. Baillot, R. Behringer, S. Feiner, S.S. Julier, B. MacIntyreRecent advances in augmented realityIEEE Computer Graphics and Applications, 21 (6) (2001), pp. 34-47CrossRefView Record in ScopusGoogle ScholarBardhi and Eckhardt, 2012F. Bardhi, G.M. EckhardtAccess-based consumption: The case of car sharing: Table 1The Journal of Consumer Research, 39 (4) (2012), pp. 881-898 Download PDFCrossRefView Record in ScopusGoogle ScholarBardhi et al., 2012F. Bardhi, G.M. Eckhardt, E.J. ArnouldLiquid relationship to possessionsThe Journal of Consumer Research, 39 (3) (2012), pp. 510-529 Download PDFCrossRefView Record in ScopusGoogle ScholarBona et al., 2018C. Bona, M. Kon, L. Koslow, D. Ratajczak, M. RobinsonAugmented reality: Is the camera the next big thing in advertising?The Boston Consulting Group (2018)retrieved from: https://www.bcg.com/de-de/publications/2018/augmented-reality-is-camera-next-big-thing-advertising [09/08/2020]Google ScholarBotwinick, 2013J. BotwinickAging and behavior: A comprehensive integration of research findingsSpringer, New York (2013)Google ScholarBracken and Skalski, 2006C.C. Bracken, P. SkalskiPresence and video games: The impact of image quality and skill levelAugustProceedings of the 9th Annual International Workshop on Presence, Cleveland State University, Cleveland, OH (2006), pp. 28-29View Record in ScopusGoogle ScholarBretschneider and Mahajan, 1980S.I. Bretschneider, V. MahajanAdaptive technological substitution modelsTechnological Forecasting and Social Change, 18 (2) (1980), pp. 129-139ArticleDownload PDFView Record in ScopusGoogle ScholarBuhler, 1968C. BuhlerThe general structure of the human life cycleC. Buhler, F. Mossarik (Eds.), The course of human life: A study of goalsin the humanistic perspective, Springer, New York (1968), pp. 12-26Google ScholarCarmigniani et al., 2011J. Carmigniani, B. Furht, M. Anisetti, P. Ceravolo, E. Damiani, M.IvkovicAugmented reality technologies, systems and applicationsMultimedia Tools and Applications, 51 (1) (2011), pp. 341-377CrossRefView Record in ScopusGoogle ScholarChylinski et al., 2020M. Chylinski, J. Heller, T. Hilken, D.I. Keeling, D. Mahr, K. de. RuyterAugmented reality marketing: A technology-enabled approach to situated customerAustralasian Marketing Journal, 28 (4) (2020), pp. 374-384ArticleDownload PDFCrossRefView Record in ScopusGoogle ScholarCitrin et al., 2003A.V. Citrin, D.E. Stem Jr., E.R. Spangenberg, M.J. ClarkConsumer need for tactile input: An internet retailing challengeJournal of Business Research, 56 (11) (2003), pp. 915-922ArticleDownload PDFView Record in ScopusGoogle ScholarCook et al., 2020A.V. Cook, L. Ohri, L. Kusumoto, C. Reynolds, E. SchwertzelAugmented shopping: The quiet revolution. Uncovering value for retailers and customers through 3D technologyRetrieved from https://www2.deloitte.com/content/dam/insights/us/articles/6367_Augmented-shopping/DI_Augmented-shopping.pdf [09/09/2020](2020)Google ScholarCosta and McCrae, 1992P.T. Costa, R.R. McCraeNormal personality assessment in clinical practice: The NEO personality inventoryPsychological Assessment, 4 (1) (1992), p. 5CrossRefView Record in ScopusGoogle ScholarCranmer et al., 2020E.E. Cranmer, M.C. tom Dieck, P. FountoulakiExploring the value of augmented reality for tourismTourism Management Perspectives, 35 (7) (2020), 10.1016/j.tmp.2020.100672in pressGoogle ScholarCuthbertson, 2015A. CuthbertsonBrand killer: Augmented reality goggles create real-world adblock: January 232015Internatinal business times (2015)Retrieved from https://www.ibtimes.co.uk/brand-killer-augmented-reality-goggles-create-real-world-adblock-1484844 [08/10/2020]Google ScholarDacko, 2017S.G. DackoEnabling smart retail settings via mobile augmented reality shopping appsTechnological Forecasting and Social Change, 124 (2017), pp. 243-256ArticleDownload PDFView Record in ScopusGoogle ScholarDieck and Han, 2019M.C. Dieck, D.‑I. HanTourism and augmented reality: Trends, implications, and future directionsD.J. Timothy (Ed.), Handbooks on globalisation. Handbook of globalisation and tourism, Edward Elgar Publishing, Cheltenham, UK (2019), pp. 235-246CrossRefGoogle ScholarDwivedi et al., 2019Y.K. Dwivedi, L. Hughes, E. Ismagilova, G. Aarts, C. Coombs, T. Crick, …, M.D. WilliamsArtificial Intelligence (AI): Multidisciplinary perspectives on emerging challenges, opportunities, and agenda for research, practice and policyInternational Journal of Information Management (2019), 10.1016/j.ijinfomgt.2019.08.002in pressGoogle ScholarDwivedi et al., 2020Y.K. Dwivedi, E. Ismagilova, D.L. Hughes, J. Carlson, R. Filieri, J. Jacobson, …, Y. WangSetting the future of digital and social media marketing research: Perspectives and research propositionsInternational Journal of Information Management (2020), 10.1016/j.ijinfomgt.2020.102168in pressGoogle ScholarEricsson, 2018Ericsson10 hot consumer trends 2018Retrieved from https://www.ericsson.com/49e88d/assets/local/reports-papers/consumerlab/reports/2018/10hct_report2018_rgb.pdf [07/09/2020](2018)Google ScholarFeng and Mueller, 2019Y. Feng, B. MuellerThe state of augmented reality advertising around the globe: A multi-cultural content analysisJournal of Promotion Management, 25 (4) (2019), pp. 453-475CrossRefView Record in ScopusGoogle ScholarGrayson and Martinec, 2004K. Grayson, R. MartinecConsumer perceptions of iconicity and indexicality and their influence on assessments of authentic market offeringsThe Journal of Consumer Research, 31 (2) (2004), pp. 296-312View Record in ScopusGoogle ScholarHan and tom Dieck, 2019D.‑I. D. Han, M.C. tom DieckCalling for user-centric VR design research in hospitality and tourismHospitality & Society, 9 (2) (2019), pp. 237-246CrossRefView Record in ScopusGoogle ScholarHan et al., 2020D.I.D. Han, J. Weber, M. Bastiaansen, O. Mitas, X. LubBlowing your mind: A conceptual framework of augmented reality and virtual reality enhanced cultural visitor experiences using EEG experience measuresInternational Journal of Technology Marketing, 14 (1) (2020), pp. 47-68CrossRefView Record in ScopusGoogle ScholarHan et al., 2019D.‑I. D. Han, J. Weber, M. Bastiaansen, O. Mitas, X. LubVirtual and augmented reality technologies to enhance the visitor experience in cultural tourismM.C. tom Dieck, T. Jung (Eds.), Progress in IS. Augmented reality and virtual reality: The power of AR and VR for business, Springer International Publishing, Cham (2019), pp. 113-128CrossRefView Record in ScopusGoogle ScholarHanlon, 2019A. HanlonDigital marketing: Strategic planning & integrationSAGE, Los Angeles, London, New Delhi, Singapore, Washington DC, Melbourne (2019)Google ScholarHeller et al., 2019J. Heller, M. Chylinski, K. de Ruyter, D. Mahr, D.I. KeelingLet me imagine that for you: Transforming the retail frontline through augmenting customer mental imagery abilityJournal of Retailing, 95 (2) (2019), pp. 94-114ArticleDownload PDFView Record in ScopusGoogle ScholarHelm et al., 2018S.V. Helm, V. Ligon, T. Stovall, S. van RiperConsumer interpretations of digital ownership in the book marketElectronic Markets, 28 (2) (2018), pp. 177-189CrossRefView Record in ScopusGoogle ScholarHilken et al., 2017T. Hilken, K. de Ruyter, M. Chylinski, D. Mahr, Keeling, DIAugmenting the eye of the beholder: exploring the strategic potential of augmented reality to enhance online service experiencesJournal of the Academy of Marketing Science, 45 (6) (2017), pp. 884-905 Download PDFCrossRefView Record in ScopusGoogle ScholarHilken et al., 2018T. Hilken, J. Heller, M. Chylinski, D.I. Keeling, D. Mahr, K. RuyterMaking omnichannel an augmented reality: the current and future state of the artJournal of Research in Interactive Marketing, 12 (4) (2018), pp. 509-523 Download PDFCrossRefView Record in ScopusGoogle ScholarHinsch et al., 2020C. Hinsch, R. Felix, P.A. RauschnabelNostalgia beats the wow-effect: Inspiration, awe and meaningful associations in augmented reality marketingJournal of Retailing and Consumer Services, 53 (2020), 10.1016/j.jretconser.2019.101987in pressGoogle ScholarHuh and Kim, 2008Y.E. Huh, S.‑H. KimDo early adopters upgrade early? Role of post-adoption behavior in the purchase of next-generation productsJournal of Business Research, 61 (1) (2008), pp. 40-46ArticleDownload PDFView Record in ScopusGoogle ScholarJavornik, 2014A. JavornikClassifications of augmented reality uses in marketingH. Duh (Ed.), Ieee International Symposium on Mixed and Augmented Reality – Media, Art, Social Science, Humanities and Design (ISMAR-MASH’D, Poster), 2014: 10–12 Sept. 2014, Munich, Germany (2014), pp. 67-68CrossRefView Record in ScopusGoogle ScholarJavornik et al., 2019A. Javornik, E. Kostopoulou, Y. Rogers, A. Fatah gen Schieck, P.Koutsolampros, A. Maria Moutinho, S. JulierAn experimental study on the role of augmented reality content type in an outdoor site explorationBehaviour & Information Technology, 38 (1) (2019), pp. 9-27CrossRefView Record in ScopusGoogle ScholarJessen et al., 2020A. Jessen, T. Hilken, M. Chylinski, D. Mahr, J. Heller, D.I. Keeling, K. de RuyterThe playground effect: How augmented reality drives creative customer engagementJournal of Business Research, 116 (2020), pp. 85-98ArticleDownload PDFView Record in ScopusGoogle ScholarJung et al., 2018T.H. Jung, H. Lee, N. Chung, M.C. tom DieckCross-cultural differences in adopting mobile augmented reality at cultural heritage tourism sitesInternational Journal of Contemporary Hospitality Management, 30 (3) (2018), pp. 1621-1645CrossRefView Record in ScopusGoogle ScholarKalantari, 2017M. KalantariConsumers’ adoption of wearable technologies: Literature review, synthesis, and future research agendaInternational Journal of Technology Marketing, 12 (3) (2017), p. 274View Record in ScopusGoogle ScholarKaya, 2008M. KayaEssays on diffusion and repeat sales of consumer durables: A study of the consumer electronics market (Doctoral dissertation, Christian-Albrechts Universität Kiel)(2008)Google ScholarLi et al., 2008S. Li, R. Glass, H. RecordsThe influence of gender on new technology adoption and use–mobile commerceJournal of Internet Commerce, 7 (2) (2008), pp. 270-289CrossRefView Record in ScopusGoogle ScholarLiébana-Cabanillas et al., 2014F. Liébana-Cabanillas, J. Sánchez-Fernández, F. Muñoz-LeivaThe moderating effect of experience in the adoption of mobile payment tools in virtual social networks: The m-payment acceptance model in virtual social networks (MPAM-VSN)International Journal of Information Management, 34 (2) (2014), pp. 151-166ArticleDownload PDFView Record in ScopusGoogle ScholarLustig et al., 2004C. Lustig, A. Konkel, L.L. JacobyWhich route to recovery? Controlled retrieval and accessibility bias in retroactive interferencePsychological Science, 15 (11) (2004), pp. 729-735View Record in ScopusGoogle ScholarMeißner et al., 2019M. Meißner, J. Pfeiffer, T. Pfeiffer, H. OppewalCombining virtual reality and mobile eye tracking to provide a naturalistic experimental environment for shopper researchJournal of Business Research, 100 (7) (2019), pp. 445-458ArticleDownload PDFView Record in ScopusGoogle ScholarNorton and Bass, 1987J.A. Norton, F.M. BassA diffusion theory model of adoption and substitution for successive generations of high-technology productsManagement Science, 33 (9) (1987), pp. 1069-1086CrossRefView Record in ScopusGoogle ScholarOlya et al., 2020H. Olya, T.H. Jung, M.C. Tom Dieck, K. RyuEngaging visitors of science festivals using augmented reality: Asymmetrical modellingInternational Journal of Contemporary Hospitality Management, 32 (2) (2020), pp. 769-796CrossRefView Record in ScopusGoogle ScholarOrth et al., 2019D. Orth, C. Thurgood, E. van den HovenDesigning meaningful products in the digital ageACM Transactions on Computer-Human Interaction, 26 (5) (2019), pp. 1-28CrossRefGoogle ScholarPantano, 2014E. PantanoInnovation drivers in retail industryInternational Journal of Information Management, 34 (3) (2014), pp. 344-350ArticleDownload PDFView Record in ScopusGoogle ScholarPatil et al., 2020P. Patil, K. Tamilmani, N.P. Rana, V. RaghavanUnderstanding consumer adoption of mobile payment in India: Extending meta-UTAUT model with personal innovativeness, anxiety, trust, and grievance redressalInternational Journal of Information Management (2020), 10.1016/j.ijinfomgt.2020.102144in pressGoogle ScholarPavlik and Bridges, 2013J.V. Pavlik, F. BridgesThe emergence of augmented reality (AR) as a storytelling medium in journalismJournalism & Communication Monographs, 15 (1) (2013), pp. 4-59CrossRefView Record in ScopusGoogle ScholarPearson, 2019I.D. PearsonAugmented reality will objectify womenRetrieved from https://timeguide.wordpress.com/2019/03/16/augmented-reality-will-objectify-women-2/ [08/09/2020](2019)Google ScholarPeddie, 2017J. PeddieAugmented reality: Where we will all liveSpringer, Cham (2017)Google ScholarPeres et al., 2010R. Peres, E. Muller, V. MahajanInnovation diffusion and new product growth models: A critical review and research directionsInternational Journal of Research in Marketing, 27 (2) (2010), pp. 91-106ArticleDownload PDFView Record in ScopusGoogle ScholarPorter, 1979M.E. PorterHow competitive forces shape strategyHarvard Business Review, 57 (2) (1979), pp. 137-145View Record in ScopusGoogle ScholarPorter, 2008M.E. PorterThe five competitive forces that shape strategyHarvard Business Review, 86 (1) (2008), pp. 25-40View Record in ScopusGoogle ScholarPorter and Heppelmann, 2017M.E. Porter, J.E. HeppelmannWhy every organization needs an augmented reality strategyRetrieved from hbr.org/2017/11/a-managers-guide-to-augmented-reality [06/05/2020](2017)Google ScholarPoushneh and Vasquez-Parraga, 2017A. Poushneh, A.Z. Vasquez-ParragaDiscernible impact of augmented reality on retail customer’s experience, satisfaction and willingness to buyJournal of Retailing and Consumer Services, 34 (1) (2017), pp. 229-234ArticleDownload PDFView Record in ScopusGoogle ScholarQin et al., 2020H. Qin, D.A. Peak, V. PrybutokA virtual market in your pocket: How does mobile augmented reality (MAR) influence consumer decision making?Journal of Retailing and Consumer Services, 58 (2020), p. 102337Google ScholarRauschnabel, 2018P.A. RauschnabelVirtually enhancing the real world with holograms: An exploration of expected gratifications of using augmented reality smart glassesPsychology & Marketing, 35 (8) (2018), pp. 557-572CrossRefView Record in ScopusGoogle ScholarRauschnabel et al., 2015P.A. Rauschnabel, A. Brem, B.S. IvensWho will buy smart glasses? Empirical results of two pre-market-entry studies on the role of personality in individual awareness and intended adoption of google glass wearablesComputers in Human Behavior, 49 (2015), pp. 635-647ArticleDownload PDFView Record in ScopusGoogle ScholarRauschnabel et al., 2019P.A. Rauschnabel, R. Felix, C. HinschAugmented reality marketing: How mobile AR-apps can improve brands through inspirationJournal of Retailing and Consumer Services, 49 (7) (2019), pp. 43-53ArticleDownload PDFView Record in ScopusGoogle ScholarRauschnabel et al., 2018P.A. Rauschnabel, J. He, Y.K. RoAntecedents to the adoption of augmented reality smart glasses: A closer look at privacy risksJournal of Business Research, 92 (11) (2018), pp. 374-384ArticleDownload PDFView Record in ScopusGoogle ScholarRese et al., 2017A. Rese, D. Baier, A. Geyer-Schulz, S. SchreiberHow augmented reality apps are accepted by consumers: A comparative analysis using scales and opinionsTechnological Forecasting and Social Change, 124 (11) (2017), pp. 306-319ArticleDownload PDFView Record in ScopusGoogle ScholarRindfleisch, 2019A. RindfleischThe second digital revolutionMarketing Letters, 31 (3) (2019), pp. 1-5View Record in ScopusGoogle ScholarRindfleisch and O’Hern, 2015A. Rindfleisch, M. O’HernBrand remixing: 3D printing the Nokia caseReview of Marketing Research, 12 (1) (2015), pp. 53-81View Record in ScopusGoogle ScholarRindfleisch et al., 2017A. Rindfleisch, M. O’Hern, V. SachdevThe digital revolution, 3D printing, and innovation as dataThe Journal of Product Innovation Management, 34 (5) (2017), pp. 681-690CrossRefView Record in ScopusGoogle ScholarRogers, 2003E.M. RogersDiffusion of innovations (Fifth edition). Social scienceFree Press, New York, London, Toronto, Sydney (2003)Google ScholarRuyter et al., 2020K. Ruyter, J. Heller, T. Hilken, M. Chylinski, D.I. Keeling, D. MahrSeeing with the customer’s eye: Exploring the challenges and opportunities of AR advertisingJournal of Advertising, 49 (2) (2020), pp. 109-124Google ScholarSmink et al., 2020A.R. Smink, E.A. van Reijmersdal, G. van Noort, P.C. NeijensShopping in augmented reality: The effects of spatial presence, personalization and intrusiveness on app and brand responsesJournal of Business Research, 118 (2020), pp. 474-485ArticleDownload PDFView Record in ScopusGoogle ScholarScholz and Duffy, 2018J. Scholz, K. DuffyWe are at home: How augmented reality reshapes mobile marketing and consumer-brand relationshipsJournal of Retailing and Consumer Services, 44 (9) (2018), pp. 11-23ArticleDownload PDFView Record in ScopusGoogle ScholarShehryar and Hunt, 2005O. Shehryar, D.M. HuntBuyer behavior and procedural fairness in pricing: Exploring the moderating role of product familiarityJournal of Product and Brand Management, 14 (4) (2005), pp. 271-276CrossRefView Record in ScopusGoogle ScholarSingh et al., 2012O. Singh, A. Anand, P.K. Kapur, D. AggrawalConsumer behaviour-based innovation diffusion modelling using stochastic differential equation incorporating change in adoption rateInternational Journal of Technology Marketing, 7 (4) (2012), pp. 346-360CrossRefView Record in ScopusGoogle ScholarSteffens and Kaya, 2009P. Steffens, M. KayaDrivers of technology substitution: Successive generations of high tech productsGSE International Entrepreneurship Research Exchange (2009)Google ScholarSweeten et al., 2018G. Sweeten, E. Sillence, N. NeaveDigital hoarding behaviours: Underlying motivations and potential negative consequencesComputers in Human Behavior, 85 (8) (2018), pp. 54-60ArticleDownload PDFView Record in ScopusGoogle ScholarThrash and Elliot, 2004T.M. Thrash, A.J. ElliotInspiration: Core characteristics, component processes, antecedents, and functionJournal of Personality and Social Psychology, 87 (6) (2004), p. 957CrossRefView Record in ScopusGoogle ScholarTsai et al., 2020Tsai, W.‑H. S., Tian, S. C., Chuan, C.‑H., & Li, C. (2020). https://doi.org/10.1080/15252019.2020.1738292.Google ScholarWatkins et al., 2016R.D. Watkins, J. Denegri-Knott, M. MolesworthThe relationship between ownership and possession: Observations from the context of digital virtual goodsJournal of Marketing Management, 32 (1–2) (2016), pp. 44-70View Record in ScopusGoogle ScholarYaoyuneyong et al., 2016G. Yaoyuneyong, J. Foster, E. Johnson, D. JohnsonAugmented reality marketing: Consumer preferences and attitudes toward hypermedia print adsJournal of Interactive Advertising, 16 (1) (2016), pp. 16-30View Record in ScopusGoogle ScholarYousafzai et al., 2016A. Yousafzai, V. Chang, A. Gani, R.M. NoorMultimedia augmented m-learning: Issues, trends and open challengesInternational Journal of Information Management, 36 (5) (2016), pp. 784-792ArticleDownload PDFView Record in ScopusGoogle ScholarYung and Khoo-Lattimore, 2019R. Yung, C. Khoo-LattimoreNew realities: A systematic literature review on virtual reality and augmented reality in tourism researchCurrent Issues in Tourism, 22 (17) (2019), pp. 2056-2081CrossRefView Record in ScopusGoogle ScholarZhang et al., 2018W. Zhang, B. Han, P. Hui, V. Gopalakrishnan, E. Zavesky, F. QianCarsM. Kim, A. Balasubramanian (Eds.), Hotmobile’18: Proceedings of the 19th International Workshop on Mobile Computing Systems & Applications: February 12-13, 2018, Tempe, AZ, USA, ACM Association for Computing Machinery, New York, NY, USA (2018), pp. 25-30CrossRefView Record in ScopusGoogle ScholarZhu et al., 2020M. Zhu, Z. Sun, Z. Zhang, Q. Shi, T. He, H. Liu, C. LeeHaptic-feedback smart glove as a creative human-machine interface (HMI) for virtual/augmented reality applicationsScience Advances, 6 (19) (2020), 10.1126/sciadv.aaz8693Google Scholar1
This quote was taken from https://www.theverge.com/2016/4/12/11415366/mark-zuckerberg-facebook-f8-virtual-augmented-reality-glasses2
This quote was taken from https://medium.com/thrive-global/39-ways-ar-can-change-the-world-in-the-next-five-years-a7736f8bfaa53
The data of study 4 supports this and shows, for instance, that the haptic motivations are particularly high for pets or smartphones, and low for posters or wall colors.4
To identify consumer products to be used in further studies, research assistants started by inspecting promotional videos from AR companies for substitutes that were advertised. For example, the Microsoft HoloLens trailer shows holographic substitutes for TVs, pets, toys, etc. In the next phase, we explored multiple inventory lists provided by moving and insurance companies. Based on plausibility discussions, we excluded products that were definitely not substitutable (e.g. silverware, beverages). In addition, we created an online survey consisting of mostly open-ended questions. We emailed this list to students who took part in at least one Master’s level university course on XR. This ensured a generally high level of experience in XR among the thirteen students who replied. A check question (“How would you rate your experience/knowledge of augmented reality?”; 1 = very low to 7 = very high) confirmed this (M=5.10). We asked students “What products can you think of that could be replaced by virtual products? Please give as many examples as possible” and searched for additional products that were not identified in our previous efforts. Next, we presented the list to four AR experts (#1: Research fellow in immersive tech; five years of XR experience; #2: Partner/CMO in an XR company, four years of XR experience; #3: Professor of computer science and consulting in AR; 11 years of XR experience; #4: Designer; 10 years of XR experience) and asked for additional feedback, further suggestions or deletions. We eliminate redundant or non-personal products. This lead to some minor changes. The final list comprised 55 different products.© 2021 The Author. Published by Elsevier Ltd.
Quelle:
https://www.sciencedirect.com/science/article/pii/S026840122031478X
