Experiencing virtual reality in retail: Extending the acceptance model for VR hardware towards VR experiences

Experiencing virtual reality in retail: Extending the acceptance model for VR hardware towards VR experiences | Research Square window.SnipcartSettings = { analytics: { enabled: false } }; (function() { var accessVector = localStorage.getItem('access_vector') || ''; window.dataLayer = window.dataLayer || []; if (accessVector) { window.dataLayer.push({ user: { profile: { profileInfo: { snid: accessVector } } } }); } })(); (function(w,d,s,l,i){w[l]=w[l]||[];w[l].push({'gtm.start':new Date().getTime(),event:'gtm.js'});var f=d.getElementsByTagName(s)[0],j=d.createElement(s),dl=l!='dataLayer'?'&l='+l:'';j.async=true;j.src='https://www.googletagmanager.com/gtm.js?id='+i+dl;f.parentNode.insertBefore(j,f);})(window,document,'script','dataLayer','GTM-K279D39R'); Browse Preprints In Review Journals COVID-19 Preprints AJE Video Bytes Research Tools Research Promotion AJE Professional Editing AJE Rubriq About Preprint Platform In Review Editorial Policies Our Team Advisory Board Help Center Sign In Submit a Preprint Cite Share Download PDF Research Article Experiencing virtual reality in retail: Extending the acceptance model for VR hardware towards VR experiences Eric Holdack, Katja Lurie-Stoyanov This is a preprint; it has not been peer reviewed by a journal. https://doi.org/ 10.21203/rs.3.rs-7101500/v1 This work is licensed under a CC BY 4.0 License Status: Posted Version 1 posted You are reading this latest preprint version Abstract VR glasses are an upcoming trend in retail. However, little is known about customer acceptance of VR experiences. The literature considers acceptance drivers for VR content and hardware separately, despite both elements affecting technology acceptance. This paper extends the existing VR hardware acceptance model by assessing VR content perception. In particular, the resulting VR experience acceptance model (VR-XAM) incorporates perceived informativeness and perceived playfulness into a structural equation model to predict attitude and usage intention towards VR glasses. The results show the outstanding role of utilitarian variables for VR glasses, suggesting that companies should first focus on informative and useful elements when implementing VR experiences into retail landscapes. Furthermore, the study stresses the importance of playfulness as the most important hedonic aspect of customer acceptance for VR in retail. Thus, the paper extends the understanding of technology acceptance and provides useful implications for the development of VR applications in retail. Virtual Reality (VR) VR glasses Technology Acceptance Model (TAM) Retail Informativeness Playfulness Figures Figure 1 Figure 2 Figure 3 Figure 4 Figure 5 1. Introduction Retailers increasingly attempt to integrate immersive technologies as sales and information channels to enhance customers’ in-store experiences. Due to the fast progress of application development, as well as the decreasing costs of such hardware, VR glasses have emerged as one of the most relevant interactive technologies. From the customer’s point of view, VR offers entertaining experiences and provides product information beyond the limits of in-store availability and traditional media [55, 79]. However, the high implementation and exploitation costs, as well as the uncertain long-term return of investment, limit the adoption of VR glasses by retailers [48]. To avoid such adoption risks, retailers and designers alike need to understand the drivers that influence customer acceptance of this immersive technology. The literature understands VR as a technology that suspends real-life surroundings and creates a realistic computer environment in which users can virtually examine and interact with objects. Users respond to the environment as if the medium itself does not exist. In essence, VR in retail is an experience, to which a VR wearable is the medium [4, 79]. Hence, VR experiences with wearable devices in retail consist of two elements: (1) the VR wearable hardware, which displays (2) the VR content [48]. Even though both elements are inseparable and simultaneously necessary for the establishment of VR environments, most studies focus only on one of the two. The authors argue that to predict future usage intentions of VR glasses in retail, it is necessary to analyze the acceptance of complete VR experiences. When asking people about their attitudes, beliefs, and intentions associated with wearable VR hardware, the acceptance and the intention to buy VR wearables primarily depends on a user’s anticipated ease of use, usefulness, enjoyment, and the price of the technology (Manis and Choi 2019). When using VR software on a 2D desktop computer screen in an online shopping scenario, perceived informativeness and perceived playfulness largely predict product evaluations. More specifically, playful interactions relate to perceived hedonic product benefits (enjoyment), whereas the informativeness of the software strongly relates to utilitarian perceptions (usefulness) and the willingness to buy the displayed products [35]. It is not clear how these findings combine and relate to the acceptance of VR applications as sales and information channels in retail when customers actually experience hardware and software simultaneously. Besides this, it is unclear how the effect of an application’s informativeness and playfulness on the acceptance of VR wearables compares in a retail context. To answer these questions, the authors enhance the virtual reality hardware acceptance model (VR-HAM), including perceived enjoyment and perceived usefulness, proposed by 48 [48] towards a VR experience acceptance model (VR-XAM). In particular, the authors gear the model towards the question of whether VR software deployed in a retailing context should provide customers with extensive product information or instead emphasize its playful elements. To this end, we aim to answer the following research questions: How do perceived informativeness and perceived playfulness influence attitude and behavioral intention to use VR wearables in a retail environment? To what degree does perceived playfulness affect attitudes and behavioral intentions towards VR wearables in comparison to perceived informativeness? The new model follows a call from Manis and Choi (2019) to enable research that shows “the true value of VR hardware while simultaneously considering the VR content available to customers” (Manis and Choi 2019, p.8). The study provides valuable insights for retailers and developers for the successful implementation of VR wearables in a retail context. Furthermore, the paper contributes to the general discussion surrounding the acceptance of immersive technologies in retail. The paper is structured as follows: The first section gives an overview of the current literature on VR in retailing. Subsequently, the authors will introduce the concept of the original TAM, in addition to VR-HAM, and further discuss the former’s prior extensions, which are relevant to this study. This will lead into the explanation of the suggested new acceptance model of the VR experience. In the following sections, the methodological approach and its results, as well as the discussion including the managerial implications, limitations, and suggestions for future research, are described. 2. Background and Conceptual Framework 2.1. VR VR is a computer-simulated 360° environment that builds solely on virtual content and does not include physical elements [ 57 , 60 , 79 ]. It allows humans to interact with virtual objects in real-time and to move around freely. The objects in VR are realistic and respond to human interactions [ 4 , 79 ]. Consequently, in VR environments customers can experience products, services, and brands in a similar manner to direct product experiences [ 34 , 48 ]. In addition they can zoom in, visualize details, and display product information [ 55 , 56 ]. Users do not have to operate the medium used to display the content of virtual environments concisely but do perceive it. One such medium are VR glasses, which contain small screens for each eye. Together, these screens create a visual picture over an ample space. This picture entirely suppresses the individual’s surrounding and, thus, completely immerses him [ 34 , 79 ]. They are “purposefully designed to take advantage of the human information processing system and to mimic how we interpret the world” [ 4 ]. Together, the computer simulated content and the medium used to display it create VR experiences. Hence, “a virtual reality experience is defined as an encounter, in which the user is effectively immersed in virtual reality content by means of virtual reality hardware” [ 48 ]. Therefore, to entirely retract and assess the VR experience, scholars need to distinguish between the evaluation of VR content and VR hardware. These definitions are essential to put the original VR-HAM and our suggested extensions into perspective. While the VR-HAM assesses the acceptance of VR hardware, we suggest an extension with elements that are related to VR content. 2.2. Technology acceptance model The market success of technologies is highly dependent on its users’ acceptance [ 67 ]. The technology acceptance model is a widely used approach in research that is empirically verified to assess and predict users’ future acceptance of technologies [ 38 , 48 ]. As such, it is found to be robust and succinct with a strong measurement property [ 32 ]. The original TAM builds on the Theory of Reasoned Action and suggests that a successful implementation of an innovation depends on the user’s attitude (AT) towards the technology and the consequent behavioral intention (BI) to use it henceforth [ 18 ]. AT implies the evaluation of a technology representing users’ likes or dislikes. Positive attitudes are rooted in the belief that using a specific technology offers additional value. BI describes the conscious disposition to perform or to engage in a particular action [ 48 , 55 , 68 ]. The original TAM suggests that both perceived usefulness (PU) and perceived ease of use (PEOU) influence users’ attitudes towards technologies, which in turn affect BI [ 19 ]. PU is the degree to which a person perceives the use of a technology as advantageous in fulfilling a specific task [ 19 ]. In the context of this study, usefulness reflects the utility value of VR in the purchasing process [ 12 , 48 , 53 , 56 ]. PEOU refers to the degree to which the usage of technologies is free of cognitive effort; in other words, it is the anticipated user-friendliness and intuitivism of a device [ 12 , 27 , 48 ]. Subsequent, these four variables comprise the initial TAM, whereby PU and PEOU influence AT, which, in turn, impacts BI [ 20 , 32 , 56 ] Subsequent to the original model, 21 [ 21 ] suggested perceived enjoyment (PE) as an additional antecedent to perceived usefulness. The construct reflects the hedonic value a technology has independent of its performance. Researchers adopted this variable as a major motivator to use an innovation [ 8 , 48 ]. Previous studies validated the TAM as a robust and concise acceptance model with effective instrumental measures and empirical soundness. As such, the framework has proven to be applicable for different contexts, including for the framework of this study [ 32 , 48 , 55 , 69 ]. However, the literature stresses that depending on the context the variables of the model alone might not be sufficient to predict and explain user acceptance. Therefore, researchers regularly add explanatory variables to the model to account for specific technologies and application environments (74; 75). After reviewing the literature, the authors included the variables perceived informativeness and perceived playfulness as well as variables proposed by Manis and Choi [ 48 ] in VR-HAM, which is further explained in detail. 2.3. VR-HAM 74 [ 74 ], as well as 75 [ 75 ], outline the need to examine potential variables influencing the believe variables perceived usefulness, perceived ease of use, and perceived enjoyment in the context of different technologies. Following this call for research, 48 [ 48 ] proposed a modified acceptance model for virtual reality hardware (VR-HAM). It aims to explain attitudes and behavioral intentions to buy and use VR hardware. The model considers users’ age, past use of VR, and curiosity as antecedents to perceived usefulness, perceived ease of use, perceived enjoyment, and behavioral intention. Past use refers to previous experiences a user has had with a specific technology [ 3 , 39 , 48 ], while curiosity is a state of high intrinsic desire to obtain new information, which motivates human behavior and activates information search [ 31 , 46 , 47 ]. Further, 48 [ 48 ] include the intention to buy and the price customers are willing to pay for VR glasses. However, in the research context of the present work, VR glasses are examined as integrated tools of retail environments and not as devices that customers buy for home use. Thus, we exclude the price willing to pay and the intention to buy VR glasses variables from our proposed model. In the following section, we theoretically deduce the effects of age, past use, and curiosity on the variables of the original TAM. 2.4. VR-XAM The present study intends to reflect VR experiences in a retail context. We assume situations in which customers rely on their perceptions of virtual product metaphors and virtual shopping environments when assessing product information. Wearable VR devices as the most promising hardware solution make these virtual elements perceptible and bridge the gap between human senses and virtual content. Previous research has reflected VR content and VR hardware separately. While the VR-HAM considers the perception of VR hardware, research on VR software for 2D desktop computer screens solely considers the perception for VR content [ 35 ]. When creating virtual shopping experiences, however, the elements of VR content and hardware give rise and presuppose each other. The customer perceives them both inseparable and simultaneously. When assessing customer acceptance of technology experiences as a sales and information channel in retail, both elements therefore need to be considered simultaneously. Manis and Choi (2019) state that “VR hardware, coupled with VR content, has the potential to create VR experiences that will revolutionize multiple industries and impact society as a whole” (Manis and Choi 2019, p.8) The study at hand, as a result, expands the VR-HAM by content-related constructs enabling researchers and practitioners to assess the acceptance of entire VR experiences in a retail context. VR content compared to other product experiences offers additional information and entertainment in these interactive components at the same time [ 11 , 26 , 79 ]. Our model therefore considers the constructs perceived informativeness and perceived playfulness [ 35 ]. Appendix A displays the differences between TAM, VR-HAM, and VR-XAM. Perceived informativeness is defined as the availability and richness of product information observed by customers [ 35 , 58 ]. Perceived playfulness describes the degree to which VR enables feelings of intrinsic pleasure and escapism [ 33 , 35 ]. Escapism in this context “reflect[s] a state of psychological immersion” [ 35 ], allowing users to forget their physical surroundings when entering virtual realities [ 33 , 49 ]. 2.5. Hypotheses Based on the described extension of the original Technology Acceptance Model for assessing the VR experience, we suggest the following conceptual framework: As described in the previous chapter, TAM follows the Theory of Reasoned Action (TRA) assuming that AT directly predicts BI. H1a: AT towards using VR glasses has positive effect on BI to use VR glasses. H1b: AT towards using VR glasses has positive effect on BI to purchase the product. Following the initial acceptance model and its extension by 21 [ 21 ], the variables PU, PEOU, and PE are beliefs about the technology, which determine the individual’s attitude towards the technology. As such, PU, PEOU, and PE are considered to significantly impact AT [ 18 , 48 ]. Further, several studies showed that functional attributes benefit the buying decision. Consequently, the authors expect PU to influence BI not just indirectly through AT but also directly [ 32 , 66 , 67 ]. In addition, PE fosters the intrinsic motivation of users, which in turn influences cognitive processes. As such, PE positively effects the perception of the technology’s usefulness (Holdack et al., 2020; Rese et al., 2017) From these findings, the authors deduce the following hypotheses for the present study: H2a: PU has positive effect on AT towards using VR glasses. H2b: PU has positive effect on BI to use VR glasses. H2c: PEOU has positive effect on AT towards using VR glasses. H2d: PE has positive effect on AT towards using VR glasses. H2e: PE has positive effect on PU. The relationship between PEOU and PU has been subject of research across different consumer contexts including VR hardware showing that PEOU has positive impact on PU [ 32 , 42 , 48 ]. Moreover, PEOU implicates that a technology requires a low level of cognitive efforts. As such, users believe that innovations with higher PEOU will help to reduce cognitive resources needed for the information searching process, while complex application will rather aggravate the search efforts. As such, straightforward technologies leave the impression of being more convenient and informative [ 32 , 55 ]. Hence, PEOU indirectly influences AT and BI through PU and PI [ 32 , 33 , 67 ]. Furthermore, several studies analyzed the relationship between PEOU and PE, suggesting that when a technology is easy to use and its usage requires less mental efforts it increases the enjoyment [ 21 , 32 , 56 ]. Additionally, research showed that PEOU is an antecedent of perceived playfulness, as technology that is easy to use is not just perceived as more enjoyable but also supports the flow experience. Hereby, flow is understood as “the state of playfulness” [ 14 , 17 , 51 ]. Hence, the authors expect PEOU to positively influence PP and propose the following hypotheses: H3a: PEOU has positive effect on PU. H3b: PEOU has positive effect on PI. H3c: PEOU has positive effect on PE. H3d: PEOU has positive effect on PP. While most studies accord that past use positively influences behavioral intentions [ 3 , 39 , 48 ], there is an ongoing debate on its influence on perceived usefulness with some results a positive impact, while other show non-significance. With regard to buying VR hardware, 48 [ 48 ] did not identify an effect on perceived usefulness. However, it is conceivable that prior experiences with VR might be advantageous when using it in the shopping context [ 22 ]. Thus, we assume a positive impact of past use on intention to use and perceived usefulness. H4a: Past use has positive effect on BI. H4b: Past use has positive effect on PU. In the context of technology acceptance, previous studies identified a divide between different age groups [ 13 , 52 ]. The access to digital media is occurring at an increasingly young age. It can be assumed that younger individuals are more proficient in adopting innovations and perceive them as easier to use. As a consequence, younger individuals are also able to make better use of the technology [ 48 , 50 , 77 ]. Thus, we expect a negative relationship between age and the perceived ease of use as well as perceived usefulness variables [ 48 , 56 ]. H5a: Age has negative effect on PEOU. H5b: Age has negative effect on PU. As previously described, curiosity is a strong intrinsic motivation, which activates certain behaviour. More specifically, interest curiosity refers to the positive feeling of obtaining knowledge and closing information gaps. Thereby, personal inquisitiveness also encourages individuals to learn how to operate technology. As a result, curious individuals learn faster, increase their cognitive and processing and, thus, perceive innovations as easier to use [ 40 , 45 , 47 , 48 ]Manis and Choi 2019). According to 47 [ 47 ], curiosity arises when a person becomes aware of having a knowledge gap that can be closed with available information [ 31 ]. In the context of the present study, VR is used to display exclusive content. Therefore, it is plausible to assume that a high degree of curiosity is also intertwined with the degree to which VR in retail is perceived as informative 1 . In summary, we theorize that more curious individuals perceive VR hardware as easier to use and VR content as being more informative H6a: Curiosity has positive effect on PEOU. H6b: Curiosity has positive effect on PI. Perceived informativeness Insufficient product information impedes the obtainment of a holistic product evaluation and leads to perceived risks, uncertainties and doubts [ 32 , 38 , 64 ]. VR glasses are a source for supplementary product information, which reduces risk and supports customers in achieving shopping goals [ 26 , 35 ]. As such, they may affect users’ attitude towards VR glasses in retail. Furthermore, previous studies reveal that customers perceive retail technologies that provide additional, credible, and useful product information as being more useful [ 32 , 43 , 64 , 67 ]. Thus, we assume a positive impact of perceived informativeness on attitude and perceived usefulness. H7: Perceived informativeness has positive effect on PU. Perceived playfulness VR has the unique ability to create high degrees of immersion by entirely covering visual and auditory perceptions. In previous studies, the level of anticipated and perceived playfulness, therefore, was one of the main antecedents of attitudes towards VR software [ 60 , 79 ]. Playful, interactive, and realistic VR content also creates pleasurable and entertaining shopping experiences, which customers perceive as being more informative [ 35 ]. Consequently, we expect perceived playfulness to positively influence attitude, perceived enjoyment and perceived informativeness [ 33 – 35 , 57 ] H8a: Perceived playfulness has positive effect on PI. H8b: Perceived playfulness has positive effect on PE. H8c: Perceived playfulness has positive effect on AT towards using. 3. Field Study 3.1 Data collection The authors collected the data needed to test customer acceptance with the VR-XAM from customers of one of the largest German retail chains. The retailer is known for its broad range of weekly changing products, of which only a specific assortment is available in its stationary stores, while a much broader range of products is offered online. The latter includes clothing, furniture, household items, and electronics. Hitherto, the only chance customers had to look at these products in store were using paper-based catalogues. The company considers VR as a technology that enables the cross-channel integration of online content into store experiences. Over a period of three weeks, it provided store visitors with to the opportunity to shop furniture and household goods with the help of VR. The fieldwork took place in Hamburg, covering the most important geo-demographic cluster for the retailer located in the city’s second largest mall. With a focus on German retail customers, we were able to analyze the acceptance of actual VR wearables in a technologically and economically advanced state, despite little-to-no market penetration and retail experiences in the field of VR glasses. 3.2 VR concept A photo-real 3D model of a studio apartment constituted the VR environment for the product presentation. Apartment metaphors used in physical stores combine the benefits of pictorial and real-world product presentations. Consequently, they rate high in immersion and user experience [72]. In order to create this high degree of immersion, the developers of the metaphor focused on simulating a modern home atmosphere, as suggested by 72 [72]. In the process of doing so, the authors conducted two pre-studies with 20 VR experts and doctoral students to test different apartment specifications and product displays. Between these pre-studies, the authors revised and refined the initial architectural design of the apartment model. Figure 2 provides an impression of the final virtual environment experienced by the customers. The second pre-study helped to review the product categories displayed in the apartment. The authors finally decided to display 3D models of 20 products that, at the time of the study, were available, constituted the most searched products in the retailer’s web shop and had different materials with different properties (wood and fabric). The virtual product models were comprehensive reproductions of the original products with complete functionality. For example, customers could heat water and brew a cup of coffee in the kitchen of the virtual apartment by using a heater and a coffee machine offered by the retailer. Each interactive item in the apartment had realistic physics, including gravity. All items for sale in the apartment offered detailed product information when selected. This included product names, short descriptions, prices, and partly selectable specifications like colors. Figure 3 shows the display of this information from a user’s perspective. 3.3 Customer interaction To navigate in the virtual apartment, customers had to use the “Point and Teleport” locomotion technique. In this technique, the users point the controller in their dominant hand to the location or object they wish to approach until a virtual ray appears. By pressing the trigger button on the controller, the user moves through the apartment. The system then automatically teleports the user to the selected location. This technique does not involve translational motion and, hence, reduces motion sickness. In addition, it allows users to navigate in the virtual environment without physically moving. Therefore, the VR system used requires minimal space and does not interfere with the retailer’s core business. It is, therefore, the most commonly used movement technique in commercial VR systems [7]. In addition to navigating around the virtual apartment, the controller helped users to interact with the displayed products, view product information, and choose between product specifications. It appeared as a virtual hand in the view field of the user. Product information appeared in a small pop-up window when customers pointed the virtual hand towards a specific product. By pressing a second trigger button, users were able to grab and interact with a product or the specific durability of a product. By pressing the button a second time, the virtual hand released the latter. By using this so-called Virtual Hand-technique to grab items, the authors opted for an isomorphic and, thus, maximally intuitive and familiar way of manipulating the virtual reality [6, 72]. To facilitate retrievability, items automatically reappeared at their original spawn point when dropped outside their initial location. Figure 4 provides an impression of the equipment that customers used during the field study. 3.4 Procedure To test the VR-XAM with the described apartment metaphor, the authors used a standard approach in usability testing [15, 24]. First, employees in the test branch attracted customers who were interested in the extended product portfolio to the availability of the VR service. In a second step, an instructor introduced interested customers to the experiment. After adjusting the VR wearable to the head shape of the users, he explained the functionality and usage of the VR system. To acquaint them with the technology, the instructor asked the customers to perform a set of small tasks, like moving around the apartment and picking up a specific item. The subsequent phase of the procedure allowed customers to explore the apartment and all displayed products without restrictions. At the end of the exploration, the retailer provided the participants with the chance to order products from the apartment metaphor or to transfer chosen products to the wish list of their online account. In order to reduce confounding effects that were not part of the research objective, the instructor followed a prescribed plan of procedure and a specific dress code for each participant. The average duration for the entire procedure per customer was about 30 minutes. 3.5 Measures We developed the questionnaire for the unstructured interview in German. The operationalization of the VR-XAM stems from the corresponding literature on TAM and VR-HAM. Besides, the authors discussed the items used with an expert group with a VR background. When possible, we adapted existing measures and adjusted them to the context of VR wearables. Three bilinguists conducted a double-blind translation-retranslation process. Additionally, the questionnaire was pretested with several Ph.D. students to ensure the clarity and comprehensiveness of the item scales. Altogether, the questionnaire consisted of three sections: The item scales of the VR-XAM, measured on a 5-point Likert scale ranging from 1 (meaning ‘strongly disagree’) to 5 (meaning ‘strongly agree’). Table 1 displays the item scales in detail. The demographics of the participants. A free input field to add comments on the experience with the VR technology. Table 1: Item scales used in the field study Items a Questions b References c Curiosity CU1 CU2 I like to shop around and look at displays. I often read advertisements just out of curiosity. 48 [48] Perceived informativeness PI1 PI2 PI3 PI4 VR provides information that helps me in my decision. After using VR, I have a better understanding of the product. VR supplies relevant product information. VR is a good source of product information. 1 [1]; 29 [29]; 67 [67]; 81 [81] Perceived ease of use PEOU1 PEOU2 PEOU3 PEOU4 Using VR glasses is easy for me. It is easy to get the VR glasses to do what I want them to do. Using VR glasses is clear and understandable. I find VR glasses flexible to interact with. 33 [33]; 48 [48]; 67 [67]; 69 [69]; Perceived playfulness PP1 PP2 PP3 PP4 Shopping via VR makes me feel like I am in another world. I get so involved when I shop via VR that I forget everything else. I enjoy shopping via VR for the sake of it, not just for the items I may have purchased. Shopping via VR makes me want to explore. 2 [2]; 33 [33]; 44 [44] Perceived usefulness PU1 PU2 PU3 Using VR glasses is useful in my shopping process. Using VR glasses improves my shopping process. The VR glasses enhance my effectiveness when shopping. 33 [33]; 48 [48]; 77 [77]; Perceived enjoyment PE1 PE2 PE3 PE4 The actual process of using VR glasses is pleasant. I have fun using VR glasses. Using VR glasses is exciting. Using VR glasses is enjoyable. 48 [48]; 67 [67], 73 [73] Attitude toward using AT1 AT2 AT3 AT4 AT5 Using VR glasses is a good idea. VR glasses make shopping more interesting. Shopping with VR glasses is fun. I like shopping with VR glasses. Other people should also use VR glasses for shopping. 65 [65]; 67 [67]; 69 [69]; 77 [77] Behavioral intention to use BI1 BI2 BI3 There is a high likelihood that I will use VR glasses in the foreseeable future. I intend to use VR glasses in the foreseeable future. Using VR glasses in the foreseeable future is important to me. 1 [1]; 48 [48]; 67 [67]; 78 [78]; 77 [77] Product purchase intention PUI1 PUI2 Notes: a All items were measured on a 5 point Likert scale anchored from 1 (strongly disagree) to 5 (strongly agree) b The final wording was discussed with an expert group with VR background c Includes only studies with independent and dependent variables similar to the ones examined in this paper 4. Results 4.1. Reliability and validity of measures The nine multi-item aspects described in Chap. 2.3 constituted the latent constructs of the structural model evaluation. Measurement validation consisted of testing for internal consistency, convergent validity, and discriminate validity. The fact that all items used in the model evaluation are of a self-reported nature produces the potential for common method variance [ 16 , 25 , 62 , 63 ]. In addition, therefore, the authors performed a posthoc factor analysis (Herman’s single-factor test). Concerning convergent validity, all estimated factor loadings were statistically significant, and all standardized loadings exceeded .5. Average variance extracted (AVE) scores above 5 and composite reliability scores above .7 further supported the impression of convergent validity, with the exception of curiosity (AVE: .489, CR: .652; Appendix B). Moreover, Cronbach’s alphas greater than .7 indicated internal consistency (Appendix B). The items of curiosity and product purchase intention, for which the assumptions of Cronbach’s alpha cannot be tested, were highly correlated (curiosity: r = .759, product purchase intention: r = .691), but mostly uncorrelated with all other variables [ 83 ]. As Appendix C illustrates, correlations between the constructs, which served as exogenous variables of our model, indicated potential multicollinearity. This was especially true for attitude towards using VR and its antecedent variables. However, removing one of the correlated variables did not substantially affect the results of the analysis. In a separate model with all constructs pointing at a latent variable with a single random indicator (values varying from 0 to 1), no VIF was equal to or greater than 3.3 (Appendix D). Although the values for attitude towards and perceived usefulness were close to 3.3, collinearity was not an apparent issue [ 9 , 59 ]. The high inter-factor correlations of attitude towards and its antecedent variables also raised the concern of whether respondents perceived the construct as a distinguishable aspect of technology acceptance (Appendix C). Besides, the factor correlation analysis questioned the discriminability of perceived playfulness from perceived enjoyment and perceived informativeness from perceived usefulness. Therefore, we compared the average heterotrait-heteromethod correlations to the average monotrait-heterotrait correlations between the constructs. Only the ratio between perceived usefulness and perceived informativeness and the ratio between perceived usefulness and attitude towards exceeded the threshold of .85 (Appendix E). However, the two exceeding comparisons remained under the .90 threshold (HTMT of .879 and .855) [ 30 ]. Comparing the AVE estimates with the squared correlation estimates between the constructs indicated discriminant validity for all constructs (see Appendix C). In conclusion, the measurement model fits the observed data well. The fit indices supported convergent and discriminant validity for the measurement model [ 28 , 80 ]. An unrotated principal component analysis indicated the presence of eight distinct factors with eigenvalues greater than 1.0 and one factor with an eigenvalue greater than 0.9 (Appendix F). The factors accounted for 75.653 percent of the variance. No single factor emerged from the analysis and none of the nine factors accounted for the majority of the variance. In conclusion, no general factor was apparent [ 16 , 25 , 62 ]. Moreover, the authors used the \(\:{{\chi\:}}^{2}/\text{d}\text{f}\) ratio, the comparative fit index (CFI), the Tucker-Lewis index (TLI), the standardized root mean square residual (SRMR), and the root mean square error of approximation (RMSEA) to test a single-factor model [ 70 ]. The related confirmatory factor analysis revealed that the single-factor model did not explain the data well ( \(\:{{\chi\:}}^{2}\) = 1576.906, \(\:{{\chi\:}}^{2}/\text{d}\text{f}\) = 3.186, CFI = 0.689, TLI = 0.668, SRMR = 0.092, RMSEA = 0.126). While these results do not wholly preclude the existence of common method variance, it does not appear to be a likely explanation for the results reported hereinafter [ 16 , 25 ]. 4.2. Structural model evaluation After assessing the validity and reliability of the measurement model, we conducted structure equation modeling (SEM) and tested the proposed paths by maximum likelihood estimation. We introduced the new variables of perceived playfulness and perceived informativeness, stepwise. First, we rebuilt the VR hardware acceptance model. We subsequently replaced the intention to purchase a VR wearable with the intention to buy the products displayed and stated this model as VR-HAM (Table 2 ). Then we added perceived informativeness and perceived playfulness. Table 2 displays the resulting model as Model 1. The table also shows the maximum likelihood statistics for model selection, including the Akaike information criterion (AIC), Bayesian information criterion (BIC), \(\:{{\chi\:}}^{2}/\text{d}\text{f}\) ratio, CFI, TLI, SRMR, RMSEA, and the coefficients of determination for the endogenous variables [ 70 ]. The maximum likelihood statistics revealed comparable indices for VR-HAM ( \(\:{{\chi\:}}^{2}\) =293.791, \(\:{{\chi\:}}^{2}/\text{d}\text{f}\) = 1.348, CFI = .924, TLI = .913, SRMR = .072, RMSEA = .069, AIC= 8661.110, BIC= 8886.001) and Model 1 ( \(\:{{\chi\:}}^{2}\) = 753.625, \(\:{{\chi\:}}^{2}/\text{d}\text{f}\) = 1.587, CFI = 0.896, TLI = 0.885, SRMR = 0.069, RMSEA = 0.073, AIC= 8533.507, BIC= 8842.393). However, when introducing perceived playfulness, we noticed that perceived enjoyment lost its contribution to explaining customer acceptance (Table 3 ). In accordance with the VR hardware acceptance model, without perceived playfulness, perceived enjoyment had a significant direct effect on the attitude towards using VR hardware (H2d, β = .361, p < .001). When introducing perceived playfulness, it successfully predicted perceived enjoyment (H8b, β = .433, p .05). Instead, perceived playfulness had a significant direct effect on attitude towards using VR (H8c, β = .387, p < .001). To achieve the best possible model for data fit, we thus considered two additional model modifications by eliminating one of the constructs. Model 2 incorporates perceived enjoyment, while the construct is replaced with perceived playfulness in Model 3 (Table 3 ). Table 2 Maximum likelihood statistics for model selection Evaluation criteria Model fit VR-HAM VR-XAM Model 1 Model 2 Model 3 \(\:{{\chi\:}}^{2}\) 293.791 753.625 576.764 571.696 \(\:{{\chi\:}}^{2}/\text{d}\text{f}\) 1.348 1.587 1.598 1.584 CFI .924 .896 .907 .909 TLI .913 .885 .896 .902 SRMR .072 .069 .072 .065 RMSEA .069 .073 .073 .073 AIC 8661.110 8533.507 7665.790 7563.356 BIC 8886.001 8842.393 7931.324 7828.890 \(\:{R}^{2}\) Perceived ease of use .246 .229 .227 .227 \(\:{R}^{2}\) Perceived usefulness .588 .844 .857 .843 \(\:{R}^{2}\) Perceived enjoyment .341 .541 .361 - \(\:{R}^{2}\) Perceived playfulness - .183 - .184 \(\:{R}^{2}\) Perceived informativeness - .659 .557 .659 \(\:{R}^{2}\) Attitude towards using VR .774 .845 .786 .837 \(\:{R}^{2}\) Intention to use .612 .626 .608 .638 \(\:{R}^{2}\) Product purchase intention .364 .353 .354 .355 Table 3 Summary from hypothesis testing No Relationship Regression weights VR-XAM Assessment Model 1 Model 2 Model 3 B(SE B) a β b B(SE B) a β b B(SE B) a β b H1a- Age ◊ Perceived ease of use − .347*** (.105) − .309 − .348***(.105) − .309 − .338***(.105) − .302 Supported H1b- Age ◊ Perceived usefulness − .031(.064) − .028 .046(.061) .041 .015(.064) .013 Not supported H1a+ H1b+ Attitude towards using ◊ Intention to use Attitude towards using ◊ Product purchase intention 1.269***(.241) .570***(.124) .952 .594 1.239***(.251) .577***(.123) .931 .596 1.305***(.239) .575***(.123) .978 .596 Supported Supported H2a+ H2b+ H2c+ H2d+ H2e+ Perceived usefulness ◊ Attitude towards using Perceived usefulness ◊ Intention to use Perceived ease of use ◊ Attitude towards using Perceived enjoyment ◊ Attitude towards using Perceived enjoyment ◊ Perceived usefulness .414***(.084) − .230(.172) − .001(.071) .137(.099) .076(.118) .545 − .227 − .001 .121 .051 601***(.094) − .211(.184) − .098(.084) .361***(.105) .099(.116) .790 − .208 − .132 .319 .067 .414***(.085) − .257(.170) .033(.067) - - .547 − .254 .044 - - Supported Not supported Not supported Supported Not supported H3a+ H3b+ H3c+ H3d+ Perceived ease of use ◊ Perceived usefulness Perceived ease of use ◊ Perceived informativeness Perceived ease of use ◊ Perceived enjoyment Perceived ease of use ◊ Perceived playfulness .210* (.092) .446***(.092) .245***(.067) . 324***(.081) .212 .435 .371 .428 .211*(.095) .615***(.099) .397***(.077) - 215 .595 .601 - .223*(.089) .446***(.093) - .320***(.081) .223 .433 - .429 Supported Supported Supported Supported H4a+ H4b+ Past use ◊ Intention to Use Past use ◊ Perceived usefulness .023*(.010) − .003(.008) .163 − .022 .022*(.010) − .003(.007) .162 − .025 .023*(.010) − .002(.008) .165 − .015 Supported Not supported H5a- H5b- Age ◊ Perceived ease of use Age ◊ Perceived usefulness − .347*** (.105) − .031(.064) − .309 − .028 − .348***(.105) .046(.061) − .309 .041 − .338***(.105) .015(.064) − .302 .013 Supported Not supported H6a+ Curiosity ◊ Perceived ease of use .532**(.178) .364 .525**(.178) .363 .535**(.178) .369 Supported H6b+ Curiosity ◊ Perceived informativeness .349*(.150) .233 .424**(.165) .284 .337*(.150) .226 Supported H7+ Perceived informativeness ◊ Perceived usefulness .709***(.096) .734 .701***(.094) .737 .728***(.094) .752 Supported H8a+ H8b+ H8c+ Perceived playfulness ◊ Perceived informativeness Perceived playfulness ◊ Perceived enjoyment Perceived playfulness ◊ Attitude towards using .547***(.124) .433***(.098) .387***(.096) .403 .496 .389 - - - - - - .563***(.127) - .456***(.090) .409 - .452 Supported Supported Supported Notes: a () Standard error in parenthesis; * p < 0.05; ** p < 0.01; ***p < 0.001 (N = 137) b Completely standardized path coefficients For Model 2 ( \(\:{{\chi\:}}^{2}\) = 576.764, \(\:{{\chi\:}}^{2}/\text{d}\text{f}\) = 1.598, CFI = 0.907, TLI = 0.896, SRMR = 0.072, RMSEA = 0.073) and Model 3 ( \(\:{{\chi\:}}^{2}\) = 571.696, \(\:{{\chi\:}}^{2}/\text{d}\text{f}\) = 1.584, CFI = 0.909, TLI = 0.902, SRMR = 0.065, RMSEA = 0.073), parsimonious, incremental, and absolute fit measures indicated reasonable model fit, according to the thresholds suggested in the literature [ 70 ]. However, all these indices were slightly in favor of Model 3. Nevertheless, we obtained minimum comparative fit indices for Model 3, which we therefore selected as our final model (AIC = 7563.356, BIC = 7828.890). Furthermore, the results show that Model 3 offers valuable insights in explaining the determinants accepting VR experiences in retail. Figure 3 shows the final model with path coefficients and significance levels. The model explained a substantial amount of variance for intention to use ( \(\:{R}^{2}=\:\) .638) and attitude towards using ( \(\:{R}^{2}=\:\) .837) VR wearables. It also helped to explain the intention to purchase the products experienced in the virtual apartment ( \(\:{R}^{2}=\:\) .355). The same applies to perceived usefulness ( \(\:{R}^{2}=\:\) .843), as well as perceived ease of use ( \(\:{R}^{2}=\:\) .227), perceived informativeness ( \(\:{R}^{2}=\:\) .659), and perceived playfulness ( \(\:{R}^{2}=\:\) .184). In the model, age did not influence perceived usefulness (H5b; β = − .015, p > .05). However, older respondents perceived the VR application as being more difficult to use (H5a; β = − .338, p < .001). In contrast, curiosity positively affected perceived ease of use (H6a, β = .535, p < .01); it also successfully predicted perceived informativeness (H6b, β = .337, p .05), past use directly affected the intention to use (H4a, β = .023, p < .05). As expected, customers who perceived the VR wearable as being easy to use also experienced it as more informative (H3b, β = .446, p < .001), playful (H3d, β = .320, p < .001), and useful (H3a, β = .223, p .05). Together with perceived ease of use, perceived informativeness had a strong direct effect on perceived usefulness (H7, β = .728, p < .001). In turn, perceived informativeness increased when participants experienced the VR experience as playful (H8a, β = .563, p < .001). Higher perceived playfulness also led to stronger attitudes towards using VR glasses in general (H8c, β = .456, p < .001). Comparing the standardized path coefficients revealed that perceived playfulness was the second strongest direct antecedent of attitude ( \(\:{\beta\:}_{std}\) = .452). In line with the original TAM, participants of the field study who viewed the technology as more useful had a stronger attitude towards VR experiences (H2a, β = .414, p < .001). A comparison of the standardized path coefficients showed that perceived usefulness was the strongest direct antecedent of attitude ( \(\:{\beta\:}_{std}\) = .547). However, perceived usefulness had no significant direct effect on intention to use (H2b, β = − .257, p > .05). Eventually, attitude towards using had a strong direct relationship with intention to use (H1a, β = 1.305, p < .001). Interestingly, the attitude towards using VR glasses in retail also positively affected the intention to purchase the displayed products (H1b, β = .575, p < .001). Table 2 summarizes the hypothesized relationship, the unstandardized and standardized coefficients, as well as the model assessment. 5. Discussion 5.1. Perceived usefulness, perceived enjoyment, and attitude The literature suggests that cross-channel technologies need to simultaneously provide hedonic and utilitarian value to improve attitudes and behavioral intentions [ 55 , 79 ]. Accordingly, study participants formed stronger attitudes and usage intentions if they perceived VR glasses as useful and enjoyable. Interestingly, in a retailing context, the attitude also predicts the willingness to purchase the products displayed. The possibility to test the functionality of products and more effectively perform decision tasks in a VR-enriched customer experience directly impacts the purchase decision. When comparing the path coefficients towards attitudes and behavioral intentions, perceived usefulness appears to be the most potent predictor compared to the remaining variables. This finding is in line with the original TAM [ 11 , 21 ]. However, the finding is remarkable because enjoyment appeared as the strongest predictor of attitudes and behavioral intentions in research for which customers reported beliefs and attitudes without actually using VR wearables [ 48 ]. One possible explanation for this finding could be that perceiving technology as useful gains importance for attitudes and behavioral intentions when experiencing the hardware combined with a specific application in a retailing environment. However, research also indicates the higher importance of perceived enjoyment when customers experience wearable AR technologies in retail stores [ 32 ]. This difference might stem from the fact that AR, in contrast to VR, adds virtual elements to the product information already provided by the store environment. When using VR applications, customers wholly depend on the information provided and by the virtual product displayed and, hence, the application's usefulness in evaluating products. 5.2. Perceived informativeness and perceived playfulness Consistent with the notion of a high dependence on virtual information in VR, the degree of perceived usefulness in our field study depended on whether customers perceived the application as being informative. This finding is in line with research suggesting the importance of perceived informativeness in predicting customers' purchase intentions when using VR software on a desktop computer in an online shopping scenario [ 35 ]. The study at hand expands this knowledge by demonstrating that the informativeness of the product display strongly impacts attitudes towards the technology as a whole, including the hardware thereof. Enjoyment may have a substantial impact on the acceptance of VR wearables. However, hedonic benefits alone would not necessarily lead customers to reuse VR wearables in retail and purchase products if the product display is not informative. As our Model 1 shows, the enjoyment of VR glasses builds on playful elements. Moreover, customers who perceive VR as playful also perceive higher degrees of informativeness. This finding is in line with the literature stating that VR goggles provide additional product details in a playful way beyond the limits of stationary retail environments [ 79 ]. Customers tend to experience products as visually attractive when presented in a playful manner [ 35 ]. Surprisingly, when comparing different models, perceived playfulness reflects the hedonic aspects of VR experiences in retail better than perceived enjoyment. One possible explanation could be the high utilization of attentional resources in virtual environments. The literature considers VR experiences as particularly immersive and attention-grabbing. With decreasing attentional resources, playful cues are easier to process [ 23 , 54 , 61 ]. In line with this notion, perceived playfulness had a strong direct impact on customers' attitudes towards VR. To conclude, acceptance models for wearable VR technologies in retail need to address functional and playful elements simultaneously. The informativeness that comes from life-sized 3D product displays and the possibility to move and rotate items makes the technology useful in retail stores. At the same time, customers form positive attitudes towards VR when experiencing highly playful virtual shopping environments. The joy and informativeness linked to the playful interaction with virtual elements in a physical environment may encourage customers to spend more time with a retailer and to purchase more items. 5.3. Perceived ease of use, age, curiosity, and past use Customers’ perceptions of informativeness and playfulness improve when customers perceive VR wearables as easy to use. This finding is in line with previous literature considering perceived ease of use to be the primary determinant of technology usage [ 11 , 21 ]. In our study, more curious and younger participants found the VR application easier to use. Consistent with this finding, in previous research curiosity and youth were predictive of learning and engagement, both being associated with perceived ease of use [ 10 , 48 ]. More curious individuals also perceived the 3D product display as more informative. This finding relates to an understanding of curiosity as a person’s willingness to seek novel information. Innovatively receiving novel product information is appreciated more by customers with a higher desire to seek information [ 10 , 37 ]. In contrast to this idea, several studies have identified information system user behavior to be self-repetitive [ 5 , 36 , 48 , 77 ]. In line with this notion, customers who already used VR wearables had stronger intentions to reuse the technology in the future. 6. Conclusion 6.1. Theoretical implications Even though practitioners and researchers alike expect the market for VR glasses to grow tremendously, the research on the acceptance drivers of these wearables in retail environments is scarce. The separate consideration of VR hardware and VR content in previous studies makes it difficult to assess the entire VR experience and to draw conclusions for retailers. Therefore, the study adapts and extends 48’s [ 48 ] VR-HAM by including VR content elements to evaluate the drivers, which influence the acceptance of entire VR experiences. In particular, the authors empirically tested a VR experience model geared towards the following aspects: (1) users’ perceptions of informativeness and playfulness and their impact on the perceptions of usefulness, ease of use, and enjoyment; and (2) the resulting impact on attitudes and behavioral intentions towards using VR glasses. The results of this paper indicate the robustness of VR-XAM, which offers valuable insights to explain the determinants influencing users’ attitudes towards and intention to use VR wearables. The model stresses the importance of customer attitudes towards specific technologies when considering them as a channel through which to market or sell products in a cross-channel environment. The content-related variables perceived playfulness and perceived informativeness appeared as important predictors for attitudes and behavioral intentions when researching VR experiences in retail. Particularly noteworthy is the outstanding role of the utilitarian variables when comparing VR to retail technologies that do not entirely rely on virtual content. Furthermore, the perceived playfulness variable seems to be the best representation for the hedonic value of VR experiences in retail. Indeed, most of the previous technology acceptance studies conceptualized perceived enjoyment as the direct hedonic antecedent of attitudes and behavioral intentions. 6.2. Implications for industry From a practical perspective, this study is particularly relevant for retailers, hardware developers, and software developers. Companies have started to test different forms of VR shopping. Despite this, little is known about what makes customers accept VR experiences provided by wearable devices in stores. The results provide clear evidence for practitioners to refine and develop VR content and hardware for retailing applications. They are especially meaningful for companies selling large-scale luxury or designer goods like furniture. When buying these goods, customers have a high need to experience product characteristics prior to purchasing. At the same time, displaying these products physically occupies expensive store space and requires backup inventories. While the functionality of VR wearables is increasingly improving, companies should also focus on VR content to increase the usefulness of VR applications in retail. Customers perceive content that is particularly informative as useful. At the same time, our results indicate that companies should add playful content to form positive customer attitudes. However, the relatively stronger impact of usefulness suggests that firms can capitalize on utilitarian attributes first to achieve better customer acceptance while gradually integrating playful elements. In doing so, the hardware and software should be conceptualized in a way that is easy to use for customers. At the same time, it could be beneficial for companies to target specific customer groups when introducing VR applications in stores. VR is easier to use and more informative for younger customers with a high level of inherent curiosity. Companies could also focus on customers who have already used VR in the past when aiming at maximum customer acceptance during the implementation of such VR applications. 6.3. Limitations and future research The model developed in this paper is the first attempt to simultaneously consider the acceptance of VR content and hardware. The model enables future research to assess the acceptance of VR content across different devices and the acceptance for hardware for various VR content elements. Such studies can build on between-subject experimental design approaches. The same content would be used across different devices or the same device for different content modifications. The paper at hand outlines the significance of customer attitudes towards VR wearables in retail for the intention to reuse VR and the willingness to buy the products displayed. While the relationship between attitudes and the intention to reuse is well established in technology acceptance research, it is not clear how the impact on the willingness to purchase products varies across different retail technologies. We suggest that future research further examine this relationship. Contributing to the research debate concerning whether attitude measures are the conclusive predictors of behavioral intentions, the authors recommend testing additional predictors. In particular, social influence as a normative element in the technology acceptance model is expected to have a major impact on the behavioral intention of the users [ 66 , 76 ]. A vital concern that can be mentioned is the choice of product. It is conceivable that the particularly interactive product display used in the field study especially benefits products with a high need for interaction during the purchase decision process, for example furniture. This idea is in line with research indicating that customers have a higher opinion of more interactive technologies in purchase decisions that involve co-designing products [ 41 ]. Therefore, the authors recommend considering the product categories displayed via VR. Defining those product categories might be a future avenue for research. As an example, body fit might be a more critical concern than visual 3D information when buying fashion apparel [ 35 ]. Further, furniture purchases are mainly goal-oriented and thus customers search for performance and goal-oriented information during the shopping process [ 11 ]. Consequently, other product categories like cars might increase the relevance of the hedonic value, which requires further analysis. For other utility-oriented product categories like computer hardware and books, the hedonic valuation found in our study might not be applicable at all [ 35 ]. Concerning the importance of perceived usefulness for retail technologies, the question arises of whether the characteristics of VR have indeed provoked the shift towards utilitarian evaluations. We suggest that future research conduct a time series analysis to find out if this tendency endures over time. The role of hedonic and utilitarian evaluations might also differ across different technologies. A comparison of our findings to study results on AR glasses indicates a higher impotence usefulness. Future studies should further assess these differences using between-subject experimental designs. In such a study, researchers should present the same virtual product metaphor to customers with physical and virtual surroundings. In general, future research could test to what degree the VR-XAM is applicable in assessing customer acceptance for other interactive and immersive technologies. Besides these findings, this study analyzed past use, curiosity and age as exogenous variables. Considering that age did not have a significant influence on perceived usefulness, we propose future research examine these variables in moderating the effect of perceived playfulness, perceived informativeness, and perceived ease of use on perceived usefulness and attitude. Other models (e.g., UTAUT) have already indicated the moderating effect of these variables [ 77 ]. We also suggest including additional exogenous variables and moderators, such as gender, need for touch, and process fluency. Further research might also include the personalization, self-efficacy, perceived risk, immersion, and individual characteristics variables; these were sufficient in explaining customer attitudes and adoption intentions for other interactive technologies, such as augmented reality [ 65 , 71 , 82 ]. Examining VR glasses in a marketplace with very little penetration of VR wearables allows the literature to survey neutral, unbiased customers to the maximum possible extent. However, the low market penetration limits the data collection to the query of behavioral intention. Considering the growing integration of VR glasses in the retail landscape, future research should test whether the intention precedes the actual behavior. Finally, results from previous research indicated that positive attitudes towards technologies positively influence other important variables, such as customer experience, loyalty, and time spent in a store [ 60 ]. Declarations Decleration of interests The authors declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper. Human Ethics and Consent to Participate declarations Human Ethics and Consent to Participate declarations: not applicable. Funding Acknowledgements This research received no specific grant from any funding agency in the public, commercial, or not-for-profit sectors. Author Contribution E.H. was responsible for the data analysis. K.L. developed the theory and hypotheses.Both authors were responsible for the study design, collecting data, writing the main manuscript, preparing the figures and reviewing the manuscript. References Ahn, T., Ryu, S., and Han, I. 2004. The impact of the online and offline features on the user acceptance of Internet shopping malls. Electronic Commerce Research and Applications 3, 4, 405–420. Ahn, T., Ryu, S., and Han, I. 2007. The impact of Web quality and playfulness on user acceptance of online retailing. Information & Management 44, 3, 263–275. Bajaja, A. and Nidumolu, S. R. 1998. A feedback model to understand information system usage. Information & Management 33, 213–224. Berg, L. P. and Vance, J. M. 2017. Industry use of virtual reality in product design and manufacturing: a survey. Virtual Reality 21, 1, 1–17. Bhattacherjee, A. 2001. Understanding Information Systems Continuance: An Expectation-Confirmation Model. MIS Quarterly 25, 3, 351–370. Bowman, D. A., Kruijff, E., LaViola, J. J., and Poupyrev, I. 2004. 3D User Interfaces: Theory and Practice . Addison Wesley Longman Publishing Co, Redwood City. Bozgeyikli, E., Raij, A., Katkoori, S., and Dubey, R. 2016. Point & Teleport Locomotion Technique for Virtual Reality. CHI PLAY '16: Proceedings of the 2016 Annual Symposium on Computer-Human Interaction in Play , 205–216. Bruner, G. C. and Kumar, A. 2005. Explaining consumer acceptance of handheld Internet devices. Journal of Business Research 58, 5, 553–558. Cenfetelli, R. T. and Basselier, G. 2009. Interpretation of Formative Measurement in Information System Research. MIS Quarterly 33, 4, 689–707. Chien, S.-E., Chu, L., Lee, H.-H., Yang, C.-C., Lin, F.-H., Yang, P.-L., Wang, T.-M., and Yeh, S.-L. 2019. Age Difference in Perceived Ease of Use, Curiosity, and Implicit Negative Attitude toward Robots. J. Hum.-Robot Interact. 8, 2, 1–19. Childers, T. L., Carr, C. L., Peck, J., and Carson, S. 2001. Hedonic and utilitarian motivations for online retail shopping behavior. Journal of Retailing 77, 4, 511–535. Choi, Y. K. and Totten, J. W. 2012. Self-construal's role in mobile TV acceptance: Extension of TAM across cultures. Journal of Business Research 65, 11, 1525–1533. Choudrie, J., Pheeraphuttranghkoon, S., and Davari, S. 2020. The Digital Divide and Older Adult Population Adoption, Use and Diffusion of Mobile Phones: a Quantitative Study. Inf Syst Front 22, 3, 673–695. Chung, J. and Tan, F. B. 2004. Antecedents of perceived playfulness: an exploratory study on user acceptance of general information-searching websites. Information & Management 41, 7, 869–881. Cockton, G., Woolrych, A., and Lavery, D. 2008. Inspections-based Evaluations. In The Human-Computer Interaction Handbook: Fundamentals, Evolving Technologies and Emerging Applications , A. Sears and J. A. Jacko, Eds. Taylor and Francis Group, New York. Craighead, C. W., Ketchen, D. J., Dunn, K. S., and Hult, G. T. M. 2011. Addressing Common Method Variance: Guidelines for Survey Research on Information Technology, Operations, and Supply Chain Management. IEEE Trans. Eng. Manage. 58, 3, 578–588. Csikszentmihalyi, M. 1975. Beyond boredom and anxiety . Jossey-Bass, San Francisco. Davis, F. D. 1986. A Technology Acceptance Model for Empirically Testing New End-User Information Systems. Theory and Results. Doctoral Thesis. Massachusetts Institute of Technology . Davis, F. D. 1989. Perceived Usefulness, Perceived Ease of Use, and User Acceptance of Information Technology. MIS Quarterly 13, 3, 319–340. Davis, F. D. 1989. Perceived Usefulness, Perceived Ease of Use, and User Acceptance of Information Technology. MIS Quarterly 13, 3, 319. Davis, F. D., Bagozzi, R. P., and Warshaw, P. R. 1992. Extrinsic and Intrinsic Motivation to Use Computers in the Workplace1. Journal of Applied Social Psychology 22, 14, 1111–1132. Dishaw, M. T. and Strong, D. M. 1999. Extending the technology acceptance model with task-technology fit constructs. Information & Management 36, 9–21. Dolan, R. J. 2002. Emotion, Cognition, and Behavior. Science 298, 5596, 1191–1194. Dumas, J. S. and Fox, J. E. 2008. Usability Testing: Current Practice and Future Directions. In The Human-Computer Interaction Handbook: Fundamentals, Evolving Technologies and Emerging Applications , A. Sears and J. A. Jacko, Eds. Taylor and Francis Group, New York. Fuller, C. M., Simmering, M. J., Atinc, G., Atinc, Y., and Babin, B. J. 2016. Common methods variance detection in business research. Journal of Business Research 69, 8, 3192–3198. Guttentag, D. A. 2010. Virtual reality: Applications and implications for tourism. Tourism Management 31, 5, 637–651. Ha, S. and Stoel, L. 2009. Consumer e-shopping acceptance: Antecedents in a technology acceptance model. Journal of Business Research 62, 5, 565–571. Hair, J. F., Risher, J. J., Sarstedt, M., and Ringle, C. M. 2019. When to use and how to report the results of PLS-SEM. European Business Review 31, 1, 2–24. Hausman, A. V. and Siekpe, J. S. 2009. The effect of web interface features on consumer online purchase intentions. Journal of Business Research 62, 1, 5–13. Henseler, J., Ringle, C. M., and Sarstedt, M. 2015. A new criterion for assessing discriminant validity in variance-based structural equation modeling. Journal of the Academy of Marketing Science 43, 1, 115–135. Hill, K. M., Fombelle, P. W., and Sirianni, N. J. 2016. Shopping under the influence of curiosity: How retailers use mystery to drive purchase motivation. Journal of Business Research 69, 3, 1028–1034. Holdack, E., Lurie-Stoyanov, K., and Fromme, H. F. 2020. The role of perceived enjoyment and perceived informativeness in assessing the acceptance of AR wearables. Journal of Retailing and Consumer Services , 102259. Huang, T.-L. and Liao, S. 2015. A model of acceptance of augmented-reality interactive technology: the moderating role of cognitive innovativeness. Electron Commer Res 15, 2, 269–295. Jung, T. and tom Dieck, M. C., Eds. 2018. Augmented Reality and Virtual Reality . Springer International Publishing, Cham. Kang, H. J., Shin, J., and Ponto, K. 2020. How 3D Virtual Reality Stores Can Shape Consumer Purchase Decisions: The Roles of Informativeness and Playfulness. Journal of Interactive Marketing 49, 3, 70–85. Karahanna, E., Straub, D. W., and Chervany, N. L. 1999. Information Technology Adoption Across Time: A Cross-Sectional Comparison of Pre-Adoption and Post-Adoption Beliefs. MIS Quarterly 23, 2, 183–213. Kashdan, T. B., Rose, P., and Fincham, F. D. 2004. Curiosity and exploration: Facilitating positive subjectiveexperiences and personal growth opportunities. Journal of Personality Assessment 82, 3, 291–305. Kim, J. and Forsythe, S. 2008. Adoption of Virtual Try-on technology for online apparel shopping. Journal of Interactive Marketing 22, 2, 45–59. Kim, S. S. and Malhotra, N. K. 2005. A Longitudinal Model of Continued IS Use: An Integrative View of Four Mechanisms Underlying Postadoption Phenomena. Management Science 51, 5, 741–755. Koo, D.-M. and Ju, S.-H. 2010. The interactional effects of atmospherics and perceptual curiosity on emotions and online shopping intention. Computers in Human Behavior 26, 3, 377–388. Lee, H.-H., Fiore, A. M., and Kim, J. 2006. The role of the technology acceptance model inexplaining effects of image interactivity technology on consumer responses. InternationalJournal of Retail and Distribution Management 34, 8, 621–644. Lee, Y.-K., Park, J.-H., Chung, N., and Blakeney, A. 2012. A unified perspective on the factors influencing usage intention toward mobile financial services. Journal of Business Research 65, 11, 1590–1599. Li, T. and Meshkova, Z. 2013. Examining the impact of rich media on consumer willingness to pay in online stores. Electronic Commerce Research and Applications 12, 6, 449–461. Liao, C., To, P.-L., Liu, C.-C., Kuo, P.-Y., and Chuang, S.-H. 2011. Factors influencing the intended use of web portals. Online Information Review 35, 2, 237–254. Litman, J. A. 2008. Interest and deprivation factors of epistemic curiosity. Personality and Individual Differences 44, 7, 1585–1595. Litman, J. A. and Spielberger, C. D. 2003. Measuring epistemic curiosity and its diversive and specific components. Journal of Personality Assessment 80, 1, 75–86. Loewenstein, G. 1994. The psychology of curiosity: A review and reinterpretation. Psychological Bulletin 116, 1, 75–98. Manis, K. T. and Choi, D. 2019. The virtual reality hardware acceptance model (VR-HAM): Extending and individuating the technology acceptance model (TAM) for virtual reality hardware. Journal of Business Research 100, 503–513. Mathwick, C. and Rigdon, E. 2004. Play, Flow, and the Online Search. Journal of Consumer Research 31, 2, 324–332. Melenhorst, A.-S., Rogers, W. A., and Caylor, E. C. 2001. The Use of Communication Technologies by Older Adults: Exploring the Benefits from the User's Perspective. PROCEEDINGS of the HUMAN FACTORS AND ERGONOMICS SOCIETY 45th ANNUAL MEETING- , 221–225. Moon, J.-W. and Kim, Y.-G. 2001. Extending the TAM for a World-Wide-Web context. Information & Management 38, 217–230. Morris, M. G. and Venkatesh, V. 2000. Age Differences in Technology Adoption Decisions: Implications for a Changing Work Force. Personnel Psychology 53, 375–403. Muk, A. and Chung, C. 2015. Applying the technology acceptance model in a two-country study of SMS advertising. Journal of Business Research 68, 1, 1–6. Mullins, J. K. and Sabherwal, R. 2018. Beyond Enjoyment: A Cognitive-Emotional Perspective of Gamification. Proceedings of the 51st Hawaii International Conference on System Sciences , 1237–1246. Pantano, E. and Di Pietro, L. 2012. Understanding Consumer’s Acceptance of Technology-Based Innovations in Retailing. Journal of Technology Management & Innovation 7, 4. Pantano, E. and Servidio, R. 2012. Modeling innovative points of sales through virtual and immersive technologies. Journal of Retailing and Consumer Services 19, 3, 279–286. Park, M., Im, H., and Kim, D. Y. 2018. Feasibility and user experience of virtual reality fashion stores. Fash Text 5, 1, 1. Pavlou, P. A., Liang, H., and Xue, Y. 2007. Understanding and Mitigating Uncertainty in Online Exchange Relationships. MIS Quarterly 31, 1, 105–136. Petter, S., Straub, D. W., and Rai, A. 2007. Specifying Formative Constructs in Information System Research. MIS Quarterly 31, 4, 623–655. Peukert, C., Pfeiffer, J., Meißner, M., Pfeiffer, T., and Weinhardt, C. 2019. Shopping in Virtual Reality Stores: The Influence of Immersion on System Adoption. Journal of Management Information Systems 36, 3, 755–788. Phelps, E. A. 2006. Emotion and Cognition: Insights from Studies of the Human Amygdala 57, 1. Podsakoff, P. M., MacKenzie, S. B., Lee, J.-Y., and Podsakoff, N. P. 2003. Common method Biases in behavioral research: a critical review of the literature and recommended remedies. Journal of Applied Psychology 88, 5, 879–903. Podsakoff, P. M. and Organ, D. W. 1986. Self-reports in organizational research: Problems and prospects. Journal of Management 12, 2, 531–544. Poushneh, A. 2018. Augmented reality in retail: A trade-off between user's control of access to personal information and augmentation quality. Journal of Retailing and Consumer Services 41, 169–176. Rauschnabel, P. A., He, J., and Ro, Y. K. 2018. Antecedents to the adoption of augmented reality smart glasses: A closer look at privacy risks. Journal of Business Research 92, 374–384. Rauschnabel, P. A. and Ro, Y. K. 2016. Augmented reality smart glasses: an investigation of technology acceptance drivers. International Journal of Technology Marketing 11, 2. Rese, A., Baier, D., Geyer-Schulz, A., and Schreiber, S. 2017. How augmented reality apps are accepted by consumers: A comparative analysis using scales and opinions. Technological Forecasting and Social Change 124, 306–319. Sager, J. K. and Menon, A. 1994. The Role of Behavioral Intentions in Turnover of Salespeople. Journal of Business Research 29, 179–188. Schierz, P. G., Schilke, O., and Wirtz, B. W. 2010. Understanding consumer acceptance of mobile payment services: An empirical analysis. Electronic Commerce Research and Applications 9, 3, 209–216. Schreiber, J., Amaury, N., Stage, F. K., Barlow, E. A., and King, J. 2006. Reporting Structural Equation Modeling and Confirmatory Factor Analysis Results: A Review. The Journal of Educational Research 99, 6, 323–337. Smink, A. R., van Reijmersdal, E. A., van Noort, G., and Neijens, P. C. 2020. Shopping in augmented reality: The effects of spatial presence, personalization and intrusiveness on app and brand responses. Journal of Business Research 118, 474–485. Speicher, M., Hell, P., Daiber, F., Simeone, A., and Krüger, A. 2018. A virtual reality shopping experience using the apartment metaphor. Proceedings of the International Conference on Advanced Visual Interfaces (AVI-2018) , 1–9. Sun, H. and Zhang, P. 2008. An exploration of affect factors and their role in user technology acceptance: Mediation and causality. J. Am. Soc. Inf. Sci. 59, 8, 1252–1263. Venkatesh, V. 2000. Determinants of Perceived Ease of Use: Integrating Control, Intrinsic Motivation, and Emotion into the Technology Acceptance Model. Information Systems Research 11, 4, 342–365. Venkatesh, V. and Brown, S. A. 2001. A Longitudinal Investigation of Personal Computers in Homes: Adoption Determinants and Emerging Challenges. MIS Quarterly 25, 1, 71–102. Venkatesh, V. and Davis, F. D. 2000. A Theoretical Extension of the Technology Acceptance Model: Four Longitudinal Field Studies. Management Science 46, 2, 186–204. Venkatesh, V., Morris, M. G., Davis, G. B., and Davis, F. D. 2003. User Acceptance of Information Technology: Toward a Unified View. MIS Quarterly 27, 3, 425–478. Venkatesh, V., Speier, C., and Morris, M. G. 2002. User Acceptance Enablers in Individual Decision Making About Technology: Toward an Integrated Model. Decision Sciences 33, 2, 297–316. Violante, M. G., Vezzetti, E., and Piazzolla, P. 2019. How to design a virtual reality experience that impacts the consumer engagement: the case of the virtual supermarket. Int J Interact Des Manuf 13, 1, 243–262. Voorhees, C. M., Brady, M. K., Calantone, R., and Ramirez, E. 2016. Discriminant validity testing in marketing: an analysis, causes for concern, and proposed remedies. J. of the Acad. Mark. Sci. 44, 1, 119–134. Yaoyuneyong, G. S., Pollitte, W. A., Foster, J. K., and Flynn, L. R. 2018. Virtual dressing room media, buying intention and mediation. Jnl of Res in Interact Mrkting 12, 1, 125–144. Yim, M. Y.-C. and Park, S.-Y. 2019. "I am not satisfied with my body, so I like augmented reality (AR)" Consumer responses to AR-based product presentations. Journal of Business Research 100, 581–589. Yong, A. G. and Pearce, S. 2013. A Beginner’s Guide to Factor Analysis: Focusing on Exploratory Factor Analysis. Tutorials in Quantitative Methods for Psychology 9, 2, 79–94. Footnotes The definition and logic of the perceived informativeness variable is further stressed in Chap. 2.4. Additional Declarations No competing interests reported. Supplementary Files AppendixA.docx Cite Share Download PDF Status: Posted Version 1 posted You are reading this latest preprint version Research Square lets you share your work early, gain feedback from the community, and start making changes to your manuscript prior to peer review in a journal. As a division of Research Square Company, we’re committed to making research communication faster, fairer, and more useful. We do this by developing innovative software and high quality services for the global research community. Our growing team is made up of researchers and industry professionals working together to solve the most critical problems facing scientific publishing. Also discoverable on Platform About Our Team In Review Editorial Policies Advisory Board Help Center Resources Author Services Accessibility API Access RSS feed Manage Cookie Preferences © Research Square 2026 | ISSN 2693-5015 (online) Privacy Policy Terms of Service Do Not Sell My Personal Information {"props":{"pageProps":{"initialData":{"identity":"rs-7101500","acceptedTermsAndConditions":true,"allowDirectSubmit":true,"archivedVersions":[],"articleType":"Research Article","associatedPublications":[],"authors":[{"id":489765684,"identity":"71949cd5-312a-440f-a628-25132a3492c8","order_by":0,"name":"Eric Holdack","email":"","orcid":"","institution":"","correspondingAuthor":false,"prefix":"","firstName":"Eric","middleName":"","lastName":"Holdack","suffix":""},{"id":489765686,"identity":"36abb2b8-5593-48eb-81b7-39462557d4f3","order_by":1,"name":"Katja Lurie-Stoyanov","email":"data:image/png;base64,iVBORw0KGgoAAAANSUhEUgAAAZAAAAAyAQMAAABI0h/eAAAABlBMVEX///8AAABVwtN+AAAACXBIWXMAAA7EAAAOxAGVKw4bAAAA4klEQVRIie2RvQrCMBRGvxLoFO16S9VnSAmIgw9jKTgrLoJLJ118gAq+h44FQZdCV8FBpeDkJoiDg6k/q+komAOBDPdwLlzAYPhBSD0BtAAGK7ci9Um0CisUKhQmrYjKKe8YbK+U4k6ypHcDBYsJW4/6S0J1E31XPB7CnyplvrK7u1lKcFNNpoEQgislZry5q4wJYtvRKE4O//5UnOvgqewPmsUohHxXbPaqfDfgxrmQNUEyZrb0lMLdVLMYZcHJPw/b9dhZHS+VcbtR3SSajDqHKI75gWvnFexQZspgMBj+mAfriDfyVoZLGgAAAABJRU5ErkJggg==","orcid":"","institution":"","correspondingAuthor":true,"prefix":"","firstName":"Katja","middleName":"","lastName":"Lurie-Stoyanov","suffix":""}],"badges":[],"createdAt":"2025-07-11 12:08:17","currentVersionCode":1,"declarations":"","doi":"10.21203/rs.3.rs-7101500/v1","doiUrl":"https://doi.org/10.21203/rs.3.rs-7101500/v1","draftVersion":[],"editorialEvents":[],"editorialNote":"","failedWorkflow":false,"files":[{"id":87503119,"identity":"33f102ae-8a06-41c4-b960-f5826a0b92df","added_by":"auto","created_at":"2025-07-24 14:18:03","extension":"png","order_by":1,"title":"Figure 1","display":"","copyAsset":false,"role":"figure","size":103306,"visible":true,"origin":"","legend":"\u003cp\u003eConceptual framework\u003c/p\u003e","description":"","filename":"1.png","url":"https://assets-eu.researchsquare.com/files/rs-7101500/v1/2668e02e3ddbb794490b3c90.png"},{"id":87503122,"identity":"91b87b4f-1a74-4609-bf89-762b44c80b98","added_by":"auto","created_at":"2025-07-24 14:18:03","extension":"png","order_by":2,"title":"Figure 2","display":"","copyAsset":false,"role":"figure","size":944312,"visible":true,"origin":"","legend":"\u003cp\u003eView of the virtual apartment from a participant’s perspective\u003c/p\u003e","description":"","filename":"2.png","url":"https://assets-eu.researchsquare.com/files/rs-7101500/v1/79ef4617bac163a9f2bb67df.png"},{"id":87503125,"identity":"28d82d14-db35-4f9c-935b-6953df492f32","added_by":"auto","created_at":"2025-07-24 14:18:04","extension":"png","order_by":3,"title":"Figure 3","display":"","copyAsset":false,"role":"figure","size":870981,"visible":true,"origin":"","legend":"\u003cp\u003eDisplay of product information when pointing at specific products\u003c/p\u003e","description":"","filename":"3.png","url":"https://assets-eu.researchsquare.com/files/rs-7101500/v1/51f14ee56ed519df59098f31.png"},{"id":87504314,"identity":"aa87f238-7e51-4b61-ab96-424f56e5aaf9","added_by":"auto","created_at":"2025-07-24 14:26:03","extension":"png","order_by":4,"title":"Figure 4","display":"","copyAsset":false,"role":"figure","size":1259656,"visible":true,"origin":"","legend":"\u003cp\u003eEquipment used for customer interaction\u003c/p\u003e","description":"","filename":"4.png","url":"https://assets-eu.researchsquare.com/files/rs-7101500/v1/a355604eb777fd6b1fe4320c.png"},{"id":87503126,"identity":"a806748d-5e0a-41b1-aa80-c9264f5d2883","added_by":"auto","created_at":"2025-07-24 14:18:04","extension":"png","order_by":5,"title":"Figure 5","display":"","copyAsset":false,"role":"figure","size":154413,"visible":true,"origin":"","legend":"\u003cp\u003eFinal structural model with path coefficients and significance levels\u003c/p\u003e","description":"","filename":"5.png","url":"https://assets-eu.researchsquare.com/files/rs-7101500/v1/093f2ec7b9383410e4dc052f.png"},{"id":104404978,"identity":"c4ecf780-d232-4bed-8841-43b2bec59860","added_by":"auto","created_at":"2026-03-11 12:21:29","extension":"pdf","order_by":0,"title":"","display":"","copyAsset":false,"role":"manuscript-pdf","size":5918137,"visible":true,"origin":"","legend":"","description":"","filename":"manuscript.pdf","url":"https://assets-eu.researchsquare.com/files/rs-7101500/v1/cdf99267-1aa5-452f-bd25-f73c467b40c7.pdf"},{"id":87503118,"identity":"029ea049-140c-4aeb-8764-bd24b5234465","added_by":"auto","created_at":"2025-07-24 14:18:03","extension":"docx","order_by":1,"title":"","display":"","copyAsset":false,"role":"supplement","size":29298,"visible":true,"origin":"","legend":"","description":"","filename":"AppendixA.docx","url":"https://assets-eu.researchsquare.com/files/rs-7101500/v1/738f9d65d35b2bc64f679aa0.docx"}],"financialInterests":"No competing interests reported.","formattedTitle":"Experiencing virtual reality in retail: Extending the acceptance model for VR hardware towards VR experiences ","fulltext":[{"header":"1. Introduction","content":"\u003cp\u003eRetailers increasingly attempt to integrate immersive technologies as sales and information channels to enhance customers\u0026rsquo; in-store experiences. Due to the fast progress of application development, as well as the decreasing costs of such hardware, VR glasses have emerged as one of the most relevant interactive technologies. From the customer\u0026rsquo;s point of view, VR offers entertaining experiences and provides product information beyond the limits of in-store availability and traditional media [55, 79]. However, the high implementation and exploitation costs, as well as the uncertain long-term return of investment, limit the adoption of VR glasses by retailers [48]. To avoid such adoption risks, retailers and designers alike need to understand the drivers that influence customer acceptance of this immersive technology.\u003c/p\u003e\n\u003cp\u003eThe literature understands VR as a technology that suspends real-life surroundings and creates a realistic computer environment in which users can virtually examine and interact with objects. Users respond to the environment as if the medium itself does not exist. In essence, VR in retail is an experience, to which a VR wearable is the medium [4, 79]. Hence, VR experiences with wearable devices in retail consist of two elements: (1) the VR wearable hardware, which displays (2) the VR content [48]. Even though both elements are inseparable and simultaneously necessary for the establishment of VR environments, most studies focus only on one of the two. The authors argue that to predict future usage intentions of VR glasses in retail, it is necessary to analyze the acceptance of complete VR experiences.\u003c/p\u003e\n\u003cp\u003eWhen asking people about their attitudes, beliefs, and intentions associated with wearable VR hardware, the acceptance and the intention to buy VR wearables primarily depends on a user\u0026rsquo;s anticipated ease of use, usefulness, enjoyment, and the price of the technology (Manis and Choi 2019). When using VR software on a 2D desktop computer screen in an online shopping scenario, perceived informativeness and perceived playfulness largely predict product evaluations. More specifically, playful interactions relate to perceived hedonic product benefits (enjoyment), whereas the informativeness of the software strongly relates to utilitarian perceptions (usefulness) and the willingness to buy the displayed products [35].\u003c/p\u003e\n\u003cp\u003eIt is not clear how these findings combine and relate to the acceptance of VR applications as sales and information channels in retail when customers actually experience hardware and software simultaneously. Besides this, it is unclear how the effect of an application\u0026rsquo;s informativeness and playfulness on the acceptance of VR wearables compares in a retail context.\u003c/p\u003e\n\u003cp\u003eTo answer these questions, the authors enhance the virtual reality hardware acceptance model (VR-HAM), including perceived enjoyment and perceived usefulness, proposed by 48 [48] towards a VR experience acceptance model (VR-XAM).\u003c/p\u003e\n\u003cp\u003eIn particular, the authors gear the model towards the question of whether VR software deployed in a retailing context should provide customers with extensive product information or instead emphasize its playful elements. To this end, we aim to answer the following research questions:\u003c/p\u003e\n\u003col class=\"decimal_type\"\u003e\n \u003cli\u003eHow do perceived informativeness and perceived playfulness influence attitude and behavioral intention to use VR wearables in a retail environment?\u003c/li\u003e\n \u003cli\u003eTo what degree does perceived playfulness affect attitudes and behavioral intentions towards VR wearables in comparison to perceived informativeness?\u003c/li\u003e\n\u003c/ol\u003e\n\u003cp\u003eThe new model follows a call from Manis and Choi (2019) to enable research that shows \u0026ldquo;the true value of VR hardware while simultaneously considering the VR content available to customers\u0026rdquo; (Manis and Choi 2019, p.8). The study provides valuable insights for retailers and developers for the successful implementation of VR wearables in a retail context. Furthermore, the paper contributes to the general discussion surrounding the acceptance of immersive technologies in retail.\u0026nbsp;\u003c/p\u003e\n\u003cp\u003eThe paper is structured as follows: The first section gives an overview of the current literature on VR in retailing. Subsequently, the authors will introduce the concept of the original TAM, in addition to VR-HAM, and further discuss the former\u0026rsquo;s prior extensions, which are relevant to this study. This will lead into the explanation of the suggested new acceptance model of the VR experience. In the following sections, the methodological approach and its results, as well as the discussion including the managerial implications, limitations, and suggestions for future research, are described.\u003c/p\u003e"},{"header":"2. Background and Conceptual Framework","content":"\u003cdiv id=\"Sec2\" class=\"Section2\"\u003e\n \u003ch2\u003e2.1. VR\u003c/h2\u003e\n \u003cp\u003eVR is a computer-simulated 360\u0026deg; environment that builds solely on virtual content and does not include physical elements [\u003cspan class=\"CitationRef\"\u003e57\u003c/span\u003e, \u003cspan class=\"CitationRef\"\u003e60\u003c/span\u003e, \u003cspan class=\"CitationRef\"\u003e79\u003c/span\u003e]. It allows humans to interact with virtual objects in real-time and to move around freely. The objects in VR are realistic and respond to human interactions [\u003cspan class=\"CitationRef\"\u003e4\u003c/span\u003e, \u003cspan class=\"CitationRef\"\u003e79\u003c/span\u003e]. Consequently, in VR environments customers can experience products, services, and brands in a similar manner to direct product experiences [\u003cspan class=\"CitationRef\"\u003e34\u003c/span\u003e, \u003cspan class=\"CitationRef\"\u003e48\u003c/span\u003e]. In addition they can zoom in, visualize details, and display product information [\u003cspan class=\"CitationRef\"\u003e55\u003c/span\u003e, \u003cspan class=\"CitationRef\"\u003e56\u003c/span\u003e].\u003c/p\u003e\n \u003cp\u003eUsers do not have to operate the medium used to display the content of virtual environments concisely but do perceive it. One such medium are VR glasses, which contain small screens for each eye. Together, these screens create a visual picture over an ample space. This picture entirely suppresses the individual\u0026rsquo;s surrounding and, thus, completely immerses him [\u003cspan class=\"CitationRef\"\u003e34\u003c/span\u003e, \u003cspan class=\"CitationRef\"\u003e79\u003c/span\u003e]. They are \u0026ldquo;purposefully designed to take advantage of the human information processing system and to mimic how we interpret the world\u0026rdquo; [\u003cspan class=\"CitationRef\"\u003e4\u003c/span\u003e].\u003c/p\u003e\n \u003cp\u003eTogether, the computer simulated content and the medium used to display it create VR experiences. Hence, \u0026ldquo;a virtual reality experience is defined as an encounter, in which the user is effectively immersed in virtual reality content by means of virtual reality hardware\u0026rdquo; [\u003cspan class=\"CitationRef\"\u003e48\u003c/span\u003e]. Therefore, to entirely retract and assess the VR experience, scholars need to distinguish between the evaluation of VR content and VR hardware. These definitions are essential to put the original VR-HAM and our suggested extensions into perspective. While the VR-HAM assesses the acceptance of VR hardware, we suggest an extension with elements that are related to VR content.\u003c/p\u003e\n\u003c/div\u003e\n\u003cdiv id=\"Sec3\" class=\"Section2\"\u003e\n \u003ch2\u003e2.2. Technology acceptance model\u003c/h2\u003e\n \u003cp\u003eThe market success of technologies is highly dependent on its users\u0026rsquo; acceptance [\u003cspan class=\"CitationRef\"\u003e67\u003c/span\u003e]. The technology acceptance model is a widely used approach in research that is empirically verified to assess and predict users\u0026rsquo; future acceptance of technologies [\u003cspan class=\"CitationRef\"\u003e38\u003c/span\u003e, \u003cspan class=\"CitationRef\"\u003e48\u003c/span\u003e]. As such, it is found to be robust and succinct with a strong measurement property [\u003cspan class=\"CitationRef\"\u003e32\u003c/span\u003e].\u003c/p\u003e\n \u003cp\u003eThe original TAM builds on the Theory of Reasoned Action and suggests that a successful implementation of an innovation depends on the user\u0026rsquo;s attitude (AT) towards the technology and the consequent behavioral intention (BI) to use it henceforth [\u003cspan class=\"CitationRef\"\u003e18\u003c/span\u003e]. AT implies the evaluation of a technology representing users\u0026rsquo; likes or dislikes. Positive attitudes are rooted in the belief that using a specific technology offers additional value. BI describes the conscious disposition to perform or to engage in a particular action [\u003cspan class=\"CitationRef\"\u003e48\u003c/span\u003e, \u003cspan class=\"CitationRef\"\u003e55\u003c/span\u003e, \u003cspan class=\"CitationRef\"\u003e68\u003c/span\u003e].\u003c/p\u003e\n \u003cp\u003eThe original TAM suggests that both perceived usefulness (PU) and perceived ease of use (PEOU) influence users\u0026rsquo; attitudes towards technologies, which in turn affect BI [\u003cspan class=\"CitationRef\"\u003e19\u003c/span\u003e]. PU is the degree to which a person perceives the use of a technology as advantageous in fulfilling a specific task [\u003cspan class=\"CitationRef\"\u003e19\u003c/span\u003e]. In the context of this study, usefulness reflects the utility value of VR in the purchasing process [\u003cspan class=\"CitationRef\"\u003e12\u003c/span\u003e, \u003cspan class=\"CitationRef\"\u003e48\u003c/span\u003e, \u003cspan class=\"CitationRef\"\u003e53\u003c/span\u003e, \u003cspan class=\"CitationRef\"\u003e56\u003c/span\u003e]. PEOU refers to the degree to which the usage of technologies is free of cognitive effort; in other words, it is the anticipated user-friendliness and intuitivism of a device [\u003cspan class=\"CitationRef\"\u003e12\u003c/span\u003e, \u003cspan class=\"CitationRef\"\u003e27\u003c/span\u003e, \u003cspan class=\"CitationRef\"\u003e48\u003c/span\u003e]. Subsequent, these four variables comprise the initial TAM, whereby PU and PEOU influence AT, which, in turn, impacts BI [\u003cspan class=\"CitationRef\"\u003e20\u003c/span\u003e, \u003cspan class=\"CitationRef\"\u003e32\u003c/span\u003e, \u003cspan class=\"CitationRef\"\u003e56\u003c/span\u003e]\u003c/p\u003e\n \u003cp\u003eSubsequent to the original model, 21 [\u003cspan class=\"CitationRef\"\u003e21\u003c/span\u003e] suggested perceived enjoyment (PE) as an additional antecedent to perceived usefulness. The construct reflects the hedonic value a technology has independent of its performance. Researchers adopted this variable as a major motivator to use an innovation [\u003cspan class=\"CitationRef\"\u003e8\u003c/span\u003e, \u003cspan class=\"CitationRef\"\u003e48\u003c/span\u003e].\u003c/p\u003e\n \u003cp\u003ePrevious studies validated the TAM as a robust and concise acceptance model with effective instrumental measures and empirical soundness. As such, the framework has proven to be applicable for different contexts, including for the framework of this study [\u003cspan class=\"CitationRef\"\u003e32\u003c/span\u003e, \u003cspan class=\"CitationRef\"\u003e48\u003c/span\u003e, \u003cspan class=\"CitationRef\"\u003e55\u003c/span\u003e, \u003cspan class=\"CitationRef\"\u003e69\u003c/span\u003e]. However, the literature stresses that depending on the context the variables of the model alone might not be sufficient to predict and explain user acceptance. Therefore, researchers regularly add explanatory variables to the model to account for specific technologies and application environments (74; 75). After reviewing the literature, the authors included the variables perceived informativeness and perceived playfulness as well as variables proposed by Manis and Choi [\u003cspan class=\"CitationRef\"\u003e48\u003c/span\u003e] in VR-HAM, which is further explained in detail.\u003c/p\u003e\n\u003c/div\u003e\n\u003cdiv id=\"Sec4\" class=\"Section2\"\u003e\n \u003ch2\u003e2.3. VR-HAM\u003c/h2\u003e\n \u003cp\u003e74 [\u003cspan class=\"CitationRef\"\u003e74\u003c/span\u003e], as well as 75 [\u003cspan class=\"CitationRef\"\u003e75\u003c/span\u003e], outline the need to examine potential variables influencing the believe variables perceived usefulness, perceived ease of use, and perceived enjoyment in the context of different technologies. Following this call for research, 48 [\u003cspan class=\"CitationRef\"\u003e48\u003c/span\u003e] proposed a modified acceptance model for virtual reality hardware (VR-HAM). It aims to explain attitudes and behavioral intentions to buy and use VR hardware. The model considers users\u0026rsquo; age, past use of VR, and curiosity as antecedents to perceived usefulness, perceived ease of use, perceived enjoyment, and behavioral intention. Past use refers to previous experiences a user has had with a specific technology [\u003cspan class=\"CitationRef\"\u003e3\u003c/span\u003e, \u003cspan class=\"CitationRef\"\u003e39\u003c/span\u003e, \u003cspan class=\"CitationRef\"\u003e48\u003c/span\u003e], while curiosity is a state of high intrinsic desire to obtain new information, which motivates human behavior and activates information search [\u003cspan class=\"CitationRef\"\u003e31\u003c/span\u003e, \u003cspan class=\"CitationRef\"\u003e46\u003c/span\u003e, \u003cspan class=\"CitationRef\"\u003e47\u003c/span\u003e].\u003c/p\u003e\n \u003cp\u003eFurther, 48 [\u003cspan class=\"CitationRef\"\u003e48\u003c/span\u003e] include the intention to buy and the price customers are willing to pay for VR glasses. However, in the research context of the present work, VR glasses are examined as integrated tools of retail environments and not as devices that customers buy for home use. Thus, we exclude the price willing to pay and the intention to buy VR glasses variables from our proposed model. In the following section, we theoretically deduce the effects of age, past use, and curiosity on the variables of the original TAM.\u003c/p\u003e\n\u003c/div\u003e\n\u003cdiv id=\"Sec5\" class=\"Section2\"\u003e\n \u003ch2\u003e2.4. VR-XAM\u003c/h2\u003e\n \u003cp\u003eThe present study intends to reflect VR experiences in a retail context. We assume situations in which customers rely on their perceptions of virtual product metaphors and virtual shopping environments when assessing product information. Wearable VR devices as the most promising hardware solution make these virtual elements perceptible and bridge the gap between human senses and virtual content. Previous research has reflected VR content and VR hardware separately. While the VR-HAM considers the perception of VR hardware, research on VR software for 2D desktop computer screens solely considers the perception for VR content [\u003cspan class=\"CitationRef\"\u003e35\u003c/span\u003e]. When creating virtual shopping experiences, however, the elements of VR content and hardware give rise and presuppose each other. The customer perceives them both inseparable and simultaneously. When assessing customer acceptance of technology experiences as a sales and information channel in retail, both elements therefore need to be considered simultaneously. Manis and Choi (2019) state that \u0026ldquo;VR hardware, coupled with VR content, has the potential to create VR experiences that will revolutionize multiple industries and impact society as a whole\u0026rdquo; (Manis and Choi 2019, p.8)\u003c/p\u003e\n \u003cp\u003eThe study at hand, as a result, expands the VR-HAM by content-related constructs enabling researchers and practitioners to assess the acceptance of entire VR experiences in a retail context. VR content compared to other product experiences offers additional information and entertainment in these interactive components at the same time [\u003cspan class=\"CitationRef\"\u003e11\u003c/span\u003e, \u003cspan class=\"CitationRef\"\u003e26\u003c/span\u003e, \u003cspan class=\"CitationRef\"\u003e79\u003c/span\u003e]. Our model therefore considers the constructs perceived informativeness and perceived playfulness [\u003cspan class=\"CitationRef\"\u003e35\u003c/span\u003e]. Appendix A displays the differences between TAM, VR-HAM, and VR-XAM.\u003c/p\u003e\n \u003cp\u003ePerceived informativeness is defined as the availability and richness of product information observed by customers [\u003cspan class=\"CitationRef\"\u003e35\u003c/span\u003e, \u003cspan class=\"CitationRef\"\u003e58\u003c/span\u003e]. Perceived playfulness describes the degree to which VR enables feelings of intrinsic pleasure and escapism [\u003cspan class=\"CitationRef\"\u003e33\u003c/span\u003e, \u003cspan class=\"CitationRef\"\u003e35\u003c/span\u003e]. Escapism in this context \u0026ldquo;reflect[s] a state of psychological immersion\u0026rdquo; [\u003cspan class=\"CitationRef\"\u003e35\u003c/span\u003e], allowing users to forget their physical surroundings when entering virtual realities [\u003cspan class=\"CitationRef\"\u003e33\u003c/span\u003e, \u003cspan class=\"CitationRef\"\u003e49\u003c/span\u003e].\u003c/p\u003e\n\u003c/div\u003e\n\u003cdiv id=\"Sec6\" class=\"Section2\"\u003e\n \u003ch2\u003e2.5. Hypotheses\u003c/h2\u003e\n \u003cp\u003eBased on the described extension of the original Technology Acceptance Model for assessing the VR experience, we suggest the following conceptual framework:\u003c/p\u003e\n \u003cp\u003eAs described in the previous chapter, TAM follows the Theory of Reasoned Action (TRA) assuming that AT directly predicts BI.\u003c/p\u003e\n \u003cp\u003e\u003cstrong\u003eH1a: AT towards using VR glasses has positive effect on BI to use VR glasses.\u003c/strong\u003e\u003c/p\u003e\n \u003cp\u003e\u003cstrong\u003eH1b: AT towards using VR glasses has positive effect on BI to purchase the product.\u003c/strong\u003e\u003c/p\u003e\n \u003cp\u003eFollowing the initial acceptance model and its extension by 21 [\u003cspan class=\"CitationRef\"\u003e21\u003c/span\u003e], the variables PU, PEOU, and PE are beliefs about the technology, which determine the individual\u0026rsquo;s attitude towards the technology. As such, PU, PEOU, and PE are considered to significantly impact AT [\u003cspan class=\"CitationRef\"\u003e18\u003c/span\u003e, \u003cspan class=\"CitationRef\"\u003e48\u003c/span\u003e]. Further, several studies showed that functional attributes benefit the buying decision. Consequently, the authors expect PU to influence BI not just indirectly through AT but also directly [\u003cspan class=\"CitationRef\"\u003e32\u003c/span\u003e, \u003cspan class=\"CitationRef\"\u003e66\u003c/span\u003e, \u003cspan class=\"CitationRef\"\u003e67\u003c/span\u003e]. In addition, PE fosters the intrinsic motivation of users, which in turn influences cognitive processes. As such, PE positively effects the perception of the technology\u0026rsquo;s usefulness (Holdack et al., 2020; Rese et al., 2017)\u003c/p\u003e\n \u003cp\u003eFrom these findings, the authors deduce the following hypotheses for the present study:\u003c/p\u003e\n \u003cp\u003e\u003cstrong\u003eH2a: PU has positive effect on AT towards using VR glasses.\u003c/strong\u003e\u003c/p\u003e\n \u003cp\u003e\u003cstrong\u003eH2b: PU has positive effect on BI to use VR glasses.\u003c/strong\u003e\u003c/p\u003e\n \u003cp\u003e\u003cstrong\u003eH2c: PEOU has positive effect on AT towards using VR glasses.\u003c/strong\u003e\u003c/p\u003e\n \u003cp\u003e\u003cstrong\u003eH2d: PE has positive effect on AT towards using VR glasses.\u003c/strong\u003e\u003c/p\u003e\n \u003cp\u003e\u003cstrong\u003eH2e: PE has positive effect on PU.\u003c/strong\u003e\u003c/p\u003e\n \u003cp\u003eThe relationship between PEOU and PU has been subject of research across different consumer contexts including VR hardware showing that PEOU has positive impact on PU [\u003cspan class=\"CitationRef\"\u003e32\u003c/span\u003e, \u003cspan class=\"CitationRef\"\u003e42\u003c/span\u003e, \u003cspan class=\"CitationRef\"\u003e48\u003c/span\u003e].\u003c/p\u003e\n \u003cp\u003eMoreover, PEOU implicates that a technology requires a low level of cognitive efforts. As such, users believe that innovations with higher PEOU will help to reduce cognitive resources needed for the information searching process, while complex application will rather aggravate the search efforts. As such, straightforward technologies leave the impression of being more convenient and informative [\u003cspan class=\"CitationRef\"\u003e32\u003c/span\u003e, \u003cspan class=\"CitationRef\"\u003e55\u003c/span\u003e]. Hence, PEOU indirectly influences AT and BI through PU and PI [\u003cspan class=\"CitationRef\"\u003e32\u003c/span\u003e, \u003cspan class=\"CitationRef\"\u003e33\u003c/span\u003e, \u003cspan class=\"CitationRef\"\u003e67\u003c/span\u003e]. Furthermore, several studies analyzed the relationship between PEOU and PE, suggesting that when a technology is easy to use and its usage requires less mental efforts it increases the enjoyment [\u003cspan class=\"CitationRef\"\u003e21\u003c/span\u003e, \u003cspan class=\"CitationRef\"\u003e32\u003c/span\u003e, \u003cspan class=\"CitationRef\"\u003e56\u003c/span\u003e]. Additionally, research showed that PEOU is an antecedent of perceived playfulness, as technology that is easy to use is not just perceived as more enjoyable but also supports the flow experience. Hereby, flow is understood as \u0026ldquo;the state of playfulness\u0026rdquo; [\u003cspan class=\"CitationRef\"\u003e14\u003c/span\u003e, \u003cspan class=\"CitationRef\"\u003e17\u003c/span\u003e, \u003cspan class=\"CitationRef\"\u003e51\u003c/span\u003e]. Hence, the authors expect PEOU to positively influence PP and propose the following hypotheses:\u003c/p\u003e\n \u003cp\u003e\u003cstrong\u003eH3a: PEOU has positive effect on PU.\u003c/strong\u003e\u003c/p\u003e\n \u003cp\u003e\u003cstrong\u003eH3b: PEOU has positive effect on PI.\u003c/strong\u003e\u003c/p\u003e\n \u003cp\u003e\u003cstrong\u003eH3c: PEOU has positive effect on PE.\u003c/strong\u003e\u003c/p\u003e\n \u003cp\u003e\u003cstrong\u003eH3d: PEOU has positive effect on PP.\u003c/strong\u003e\u003c/p\u003e\n \u003cp\u003eWhile most studies accord that past use positively influences behavioral intentions [\u003cspan class=\"CitationRef\"\u003e3\u003c/span\u003e, \u003cspan class=\"CitationRef\"\u003e39\u003c/span\u003e, \u003cspan class=\"CitationRef\"\u003e48\u003c/span\u003e], there is an ongoing debate on its influence on perceived usefulness with some results a positive impact, while other show non-significance. With regard to buying VR hardware, 48 [\u003cspan class=\"CitationRef\"\u003e48\u003c/span\u003e] did not identify an effect on perceived usefulness. However, it is conceivable that prior experiences with VR might be advantageous when using it in the shopping context [\u003cspan class=\"CitationRef\"\u003e22\u003c/span\u003e]. Thus, we assume a positive impact of past use on intention to use and perceived usefulness.\u003c/p\u003e\n \u003cp\u003e\u003cstrong\u003eH4a: Past use has positive effect on BI.\u003c/strong\u003e\u003c/p\u003e\n \u003cp\u003e\u003cstrong\u003eH4b: Past use has positive effect on PU.\u003c/strong\u003e\u003c/p\u003e\n \u003cp\u003eIn the context of technology acceptance, previous studies identified a divide between different age groups [\u003cspan class=\"CitationRef\"\u003e13\u003c/span\u003e, \u003cspan class=\"CitationRef\"\u003e52\u003c/span\u003e]. The access to digital media is occurring at an increasingly young age. It can be assumed that younger individuals are more proficient in adopting innovations and perceive them as easier to use. As a consequence, younger individuals are also able to make better use of the technology [\u003cspan class=\"CitationRef\"\u003e48\u003c/span\u003e, \u003cspan class=\"CitationRef\"\u003e50\u003c/span\u003e, \u003cspan class=\"CitationRef\"\u003e77\u003c/span\u003e]. Thus, we expect a negative relationship between age and the perceived ease of use as well as perceived usefulness variables [\u003cspan class=\"CitationRef\"\u003e48\u003c/span\u003e, \u003cspan class=\"CitationRef\"\u003e56\u003c/span\u003e].\u003c/p\u003e\n \u003cp\u003e\u003cstrong\u003eH5a: Age has negative effect on PEOU.\u003c/strong\u003e\u003c/p\u003e\n \u003cp\u003e\u003cstrong\u003eH5b: Age has negative effect on PU.\u003c/strong\u003e\u003c/p\u003e\n \u003cp\u003eAs previously described, curiosity is a strong intrinsic motivation, which activates certain behaviour. More specifically, interest curiosity refers to the positive feeling of obtaining knowledge and closing information gaps. Thereby, personal inquisitiveness also encourages individuals to learn how to operate technology. As a result, curious individuals learn faster, increase their cognitive and processing and, thus, perceive innovations as easier to use [\u003cspan class=\"CitationRef\"\u003e40\u003c/span\u003e, \u003cspan class=\"CitationRef\"\u003e45\u003c/span\u003e, \u003cspan class=\"CitationRef\"\u003e47\u003c/span\u003e, \u003cspan class=\"CitationRef\"\u003e48\u003c/span\u003e]Manis and Choi 2019).\u003c/p\u003e\n \u003cp\u003eAccording to 47 [\u003cspan class=\"CitationRef\"\u003e47\u003c/span\u003e], curiosity arises when a person becomes aware of having a knowledge gap that can be closed with available information [\u003cspan class=\"CitationRef\"\u003e31\u003c/span\u003e]. In the context of the present study, VR is used to display exclusive content. Therefore, it is plausible to assume that a high degree of curiosity is also intertwined with the degree to which VR in retail is perceived as informative\u003csup\u003e1\u003c/sup\u003e.\u003ca class=\"FNLink\" href=\"#Fn1\" id=\"#FNLinkFn1\"\u003e\u003c/a\u003e In summary, we theorize that more curious individuals perceive VR hardware as easier to use and VR content as being more informative\u003c/p\u003e\n \u003cp\u003e\u003cstrong\u003eH6a: Curiosity has positive effect on PEOU.\u003c/strong\u003e\u003c/p\u003e\n \u003cp\u003e\u003cstrong\u003eH6b: Curiosity has positive effect on PI.\u003c/strong\u003e\u003c/p\u003e\n \u003cp\u003ePerceived informativeness\u003c/p\u003e\n \u003cp\u003eInsufficient product information impedes the obtainment of a holistic product evaluation and leads to perceived risks, uncertainties and doubts [\u003cspan class=\"CitationRef\"\u003e32\u003c/span\u003e, \u003cspan class=\"CitationRef\"\u003e38\u003c/span\u003e, \u003cspan class=\"CitationRef\"\u003e64\u003c/span\u003e]. VR glasses are a source for supplementary product information, which reduces risk and supports customers in achieving shopping goals [\u003cspan class=\"CitationRef\"\u003e26\u003c/span\u003e, \u003cspan class=\"CitationRef\"\u003e35\u003c/span\u003e]. As such, they may affect users\u0026rsquo; attitude towards VR glasses in retail. Furthermore, previous studies reveal that customers perceive retail technologies that provide additional, credible, and useful product information as being more useful [\u003cspan class=\"CitationRef\"\u003e32\u003c/span\u003e, \u003cspan class=\"CitationRef\"\u003e43\u003c/span\u003e, \u003cspan class=\"CitationRef\"\u003e64\u003c/span\u003e, \u003cspan class=\"CitationRef\"\u003e67\u003c/span\u003e]. Thus, we assume a positive impact of perceived informativeness on attitude and perceived usefulness.\u003c/p\u003e\n \u003cp\u003e\u003cstrong\u003eH7: Perceived informativeness has positive effect on PU.\u003c/strong\u003e\u003c/p\u003e\n \u003cp\u003e\u003cem\u003ePerceived playfulness\u003c/em\u003e\u003c/p\u003e\n \u003cp\u003eVR has the unique ability to create high degrees of immersion by entirely covering visual and auditory perceptions. In previous studies, the level of anticipated and perceived playfulness, therefore, was one of the main antecedents of attitudes towards VR software [\u003cspan class=\"CitationRef\"\u003e60\u003c/span\u003e, \u003cspan class=\"CitationRef\"\u003e79\u003c/span\u003e].\u003c/p\u003e\n \u003cp\u003ePlayful, interactive, and realistic VR content also creates pleasurable and entertaining shopping experiences, which customers perceive as being more informative [\u003cspan class=\"CitationRef\"\u003e35\u003c/span\u003e]. Consequently, we expect perceived playfulness to positively influence attitude, perceived enjoyment and perceived informativeness [\u003cspan class=\"CitationRef\"\u003e33\u003c/span\u003e\u0026ndash;\u003cspan class=\"CitationRef\"\u003e35\u003c/span\u003e, \u003cspan class=\"CitationRef\"\u003e57\u003c/span\u003e]\u003c/p\u003e\n \u003cp\u003e\u003cstrong\u003eH8a: Perceived playfulness has positive effect on PI.\u003c/strong\u003e\u003c/p\u003e\n \u003cp\u003e\u003cstrong\u003eH8b: Perceived playfulness has positive effect on PE.\u003c/strong\u003e\u003c/p\u003e\n \u003cp\u003e\u003cstrong\u003eH8c: Perceived playfulness has positive effect on AT towards using.\u003c/strong\u003e\u003c/p\u003e\n\u003c/div\u003e"},{"header":"3. Field Study","content":"\u003cp\u003e\u003cem\u003e3.1 Data collection\u003c/em\u003e\u003c/p\u003e\n\u003cp\u003eThe authors collected the data needed to test customer acceptance with the VR-XAM from customers of one of the largest German retail chains. The retailer is known for its broad range of weekly changing products, of which only a specific assortment is available in its stationary stores, while a much broader range of products is offered online. The latter includes clothing, furniture, household items, and electronics. Hitherto, the only chance customers had to look at these products in store were using paper-based catalogues. The company considers VR as a technology that enables the cross-channel integration of online content into store experiences. Over a period of three weeks, it provided store visitors with to the opportunity to shop furniture and household goods with the help of VR.\u003c/p\u003e\n\u003cp\u003eThe fieldwork took place in Hamburg, covering the most important geo-demographic cluster for the retailer located in the city\u0026rsquo;s second largest mall. With a focus on German retail customers, we were able to analyze the acceptance of actual VR wearables in a technologically and economically advanced state, despite little-to-no market penetration and retail experiences in the field of VR glasses.\u003c/p\u003e\n\u003cp\u003e\u003cem\u003e3.2 VR concept\u003c/em\u003e\u003c/p\u003e\n\u003cp\u003eA photo-real 3D model of a studio apartment constituted the VR environment for the product presentation. Apartment metaphors used in physical stores combine the benefits of pictorial and real-world product presentations. Consequently, they rate high in immersion and user experience [72]. In order to create this high degree of immersion, the developers of the metaphor focused on simulating a modern home atmosphere, as suggested by 72 [72]. In the process of doing so, the authors conducted two pre-studies with 20 VR experts and doctoral students to test different apartment specifications and product displays. Between these pre-studies, the authors revised and refined the initial architectural design of the apartment model. Figure 2 provides an impression of the final virtual environment experienced by the customers.\u003c/p\u003e\n\u003cp\u003eThe second pre-study helped to review the product categories displayed in the apartment. The authors finally decided to display 3D models of 20 products that, at the time of the study, were available, constituted the most searched products in the retailer\u0026rsquo;s web shop and had different materials with different properties (wood and fabric).\u003c/p\u003e\n\u003cp\u003eThe virtual product models were comprehensive reproductions of the original products with complete functionality. For example, customers could heat water and brew a cup of coffee in the kitchen of the virtual apartment by using a heater and a coffee machine offered by the retailer. Each interactive item in the apartment had realistic physics, including gravity.\u003c/p\u003e\n\u003cp\u003eAll items for sale in the apartment offered detailed product information when selected. This included product names, short descriptions, prices, and partly selectable specifications like colors. Figure 3 shows the display of this information from a user\u0026rsquo;s perspective.\u003c/p\u003e\n\u003cp\u003e\u003cem\u003e3.3 Customer interaction\u003c/em\u003e\u003c/p\u003e\n\u003cp\u003eTo navigate in the virtual apartment, customers had to use the \u0026ldquo;Point and Teleport\u0026rdquo; locomotion technique. In this technique, the users point the controller in their dominant hand to the location or object they wish to approach until a virtual ray appears. By pressing the trigger button on the controller, the user moves through the apartment. The system then automatically teleports the user to the selected location. This technique does not involve translational motion and, hence, reduces motion sickness. In addition, it allows users to navigate in the virtual environment without physically moving. Therefore, the VR system used requires minimal space and does not interfere with the retailer\u0026rsquo;s core business. It is, therefore, the most commonly used movement technique in commercial VR systems [7].\u003c/p\u003e\n\u003cp\u003eIn addition to navigating around the virtual apartment, the controller helped users to interact with the displayed products, view product information, and choose between product specifications. It appeared as a virtual hand in the view field of the user. Product information appeared in a small pop-up window when customers pointed the virtual hand towards a specific product. By pressing a second trigger button, users were able to grab and interact with a product or the specific durability of a product. By pressing the button a second time, the virtual hand released the latter. By using this so-called Virtual Hand-technique to grab items, the authors opted for an isomorphic and, thus, maximally intuitive and familiar way of manipulating the virtual reality [6, 72]. To facilitate retrievability, items automatically reappeared at their original spawn point when dropped outside their initial location. Figure 4 provides an impression of the equipment that customers used during the field study.\u003c/p\u003e\n\u003cp\u003e\u003cem\u003e3.4 Procedure\u003c/em\u003e\u003c/p\u003e\n\u003cp\u003eTo test the VR-XAM with the described apartment metaphor, the authors used a standard approach in usability testing [15, 24]. First, employees in the test branch attracted customers who were interested in the extended product portfolio to the availability of the VR service. In a second step, an instructor introduced interested customers to the experiment. After adjusting the VR wearable to the head shape of the users, he explained the functionality and usage of the VR system. To acquaint them with the technology, the instructor asked the customers to perform a set of small tasks, like moving around the apartment and picking up a specific item.\u003c/p\u003e\n\u003cp\u003eThe subsequent phase of the procedure allowed customers to explore the apartment and all displayed products without restrictions. At the end of the exploration, the retailer provided the participants with the chance to order products from the apartment metaphor or to transfer chosen products to the wish list of their online account. In order to reduce confounding effects that were not part of the research objective, the instructor followed a prescribed plan of procedure and a specific dress code for each participant. The average duration for the entire procedure per customer was about 30 minutes.\u003c/p\u003e\n\u003cp\u003e\u0026nbsp;3.5\u0026nbsp;\u003cem\u003eMeasures\u003c/em\u003e\u003c/p\u003e\n\u003cp\u003eWe developed the questionnaire for the unstructured interview in German. The operationalization of the VR-XAM stems from the corresponding literature on TAM and VR-HAM. Besides, the authors discussed the items used with an expert group with a VR background. When possible, we adapted existing measures and adjusted them to the context of VR wearables. Three bilinguists conducted a double-blind translation-retranslation process. Additionally, the questionnaire was pretested with several Ph.D. students to ensure the clarity and comprehensiveness of the item scales. Altogether, the questionnaire consisted of three sections:\u003c/p\u003e\n\u003col\u003e\n \u003cli\u003eThe item scales of the VR-XAM, measured on a 5-point Likert scale ranging from 1 (meaning \u0026lsquo;strongly disagree\u0026rsquo;) to 5 (meaning \u0026lsquo;strongly agree\u0026rsquo;). Table 1 displays the item scales in detail.\u003c/li\u003e\n \u003cli\u003eThe demographics of the participants.\u003c/li\u003e\n \u003cli\u003eA free input field to add comments on the experience with the VR technology.\u003cbr\u003e\u0026nbsp;\u003c/li\u003e\n\u003c/ol\u003e\n\u003ch5\u003eTable 1: \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; Item scales used in the field study\u003c/h5\u003e\n\u003ctable border=\"1\" cellspacing=\"0\" cellpadding=\"0\" width=\"120%\" class=\"fr-table-selection-hover\"\u003e\n \u003ctbody\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 170px;\"\u003e\n \u003cp\u003eItems\u003csup\u003ea\u003c/sup\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 55.1505%;\"\u003e\n \u003cp\u003eQuestions\u003csup\u003eb\u003c/sup\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 16.6298%;\"\u003e\n \u003cp\u003eReferences\u003csup\u003ec\u003c/sup\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 170px;\"\u003e\n \u003cp\u003e\u003cem\u003eCuriosity\u003c/em\u003e\u003c/p\u003e\n \u003cp\u003eCU1\u003c/p\u003e\n \u003cp\u003eCU2\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 55.1505%;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003cp\u003eI like to shop around and look at displays.\u003c/p\u003e\n \u003cp\u003eI often read advertisements just out of curiosity.\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 16.6298%;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003cp\u003e48 [48]\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 170px;\"\u003e\n \u003cp\u003ePerceived informativeness\u003c/p\u003e\n \u003cp\u003ePI1\u003c/p\u003e\n \u003cp\u003e\u0026nbsp;PI2\u003c/p\u003e\n \u003cp\u003e\u0026nbsp;PI3\u003c/p\u003e\n \u003cp\u003ePI4\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 55.1505%;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003cp\u003eVR provides information that helps me in my decision.\u003c/p\u003e\n \u003cp\u003eAfter using VR, I have a better understanding of the product.\u003c/p\u003e\n \u003cp\u003eVR supplies relevant product information.\u003c/p\u003e\n \u003cp\u003eVR is a good source of product information.\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 16.6298%;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003cp\u003e1 [1]; 29 [29]; 67 [67]; 81 [81]\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 170px;\"\u003e\n \u003cp\u003e\u003cem\u003ePerceived ease of use\u003c/em\u003e\u003c/p\u003e\n \u003cp\u003e\u003cem\u003ePEOU1\u003c/em\u003e\u003c/p\u003e\n \u003cp\u003e\u003cem\u003ePEOU2\u003c/em\u003e\u003c/p\u003e\n \u003cp\u003e\u003cem\u003ePEOU3\u003c/em\u003e\u003c/p\u003e\n \u003cp\u003e\u003cem\u003ePEOU4\u003c/em\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 55.1505%;\"\u003e\n \u003cp\u003e\u003cem\u003e\u0026nbsp;\u003c/em\u003e\u003c/p\u003e\n \u003cp\u003eUsing VR glasses is easy for me.\u003c/p\u003e\n \u003cp\u003eIt is easy to get the VR glasses to do what I want them to do.\u003c/p\u003e\n \u003cp\u003eUsing VR glasses is clear and understandable.\u003c/p\u003e\n \u003cp\u003eI find VR glasses flexible to interact with.\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 16.6298%;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003cp\u003e33 [33]; 48 [48]; 67 [67]; 69 [69];\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 170px;\"\u003e\n \u003cp\u003e\u003cem\u003ePerceived playfulness\u003c/em\u003e\u003c/p\u003e\n \u003cp\u003ePP1\u003c/p\u003e\n \u003cp\u003e\u0026nbsp;PP2\u003c/p\u003e\n \u003cp\u003e\u0026nbsp;PP3\u003c/p\u003e\n \u003cp\u003e\u0026nbsp;PP4\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 55.1505%;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003cp\u003eShopping via VR makes me feel like I am in another world.\u003c/p\u003e\n \u003cp\u003eI get so involved when I shop via VR that I forget everything else.\u003c/p\u003e\n \u003cp\u003eI enjoy shopping via VR for the sake of it, not just for the items I may have purchased.\u003c/p\u003e\n \u003cp\u003eShopping via VR makes me want to explore.\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 16.6298%;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003cp\u003e2 [2];\u003c/p\u003e\n \u003cp\u003e33 [33]; 44 [44]\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 170px;\"\u003e\n \u003cp\u003e\u003cem\u003ePerceived usefulness\u003c/em\u003e\u003c/p\u003e\n \u003cp\u003ePU1\u003c/p\u003e\n \u003cp\u003ePU2\u003c/p\u003e\n \u003cp\u003ePU3\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 55.1505%;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003cp\u003eUsing VR glasses is useful in my shopping process.\u003c/p\u003e\n \u003cp\u003eUsing VR glasses improves my shopping process.\u003c/p\u003e\n \u003cp\u003eThe VR glasses enhance my effectiveness when shopping.\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 16.6298%;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003cp\u003e33 [33]; 48 [48]; 77 [77];\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 170px;\"\u003e\n \u003cp\u003e\u003cem\u003ePerceived enjoyment\u003c/em\u003e\u003c/p\u003e\n \u003cp\u003ePE1\u003c/p\u003e\n \u003cp\u003ePE2\u003c/p\u003e\n \u003cp\u003ePE3\u003c/p\u003e\n \u003cp\u003ePE4\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 55.1505%;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003cp\u003eThe actual process of using VR glasses is pleasant.\u003c/p\u003e\n \u003cp\u003eI have fun using VR glasses.\u003c/p\u003e\n \u003cp\u003eUsing VR glasses is exciting.\u003c/p\u003e\n \u003cp\u003eUsing VR glasses is enjoyable.\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 16.6298%;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003cp\u003e48 [48]; 67 [67], 73 [73]\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 170px;\"\u003e\n \u003cp\u003e\u003cem\u003eAttitude toward using\u003c/em\u003e\u003c/p\u003e\n \u003cp\u003eAT1\u003c/p\u003e\n \u003cp\u003eAT2\u003c/p\u003e\n \u003cp\u003eAT3\u003c/p\u003e\n \u003cp\u003eAT4\u003c/p\u003e\n \u003cp\u003eAT5\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 55.1505%;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003cp\u003eUsing VR glasses is a good idea.\u003c/p\u003e\n \u003cp\u003eVR glasses make shopping more interesting.\u003c/p\u003e\n \u003cp\u003eShopping with VR glasses is fun.\u003c/p\u003e\n \u003cp\u003eI like shopping with VR glasses.\u003c/p\u003e\n \u003cp\u003eOther people should also use VR glasses for shopping.\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 16.6298%;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003cp\u003e65 [65]; 67 [67]; 69 [69]; 77 [77]\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 170px;\"\u003e\n \u003cp\u003e\u003cem\u003eBehavioral intention to use\u003c/em\u003e\u003c/p\u003e\n \u003cp\u003eBI1\u003c/p\u003e\n \u003cp\u003e\u0026nbsp;BI2\u003c/p\u003e\n \u003cp\u003eBI3\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 55.1505%;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003cp\u003eThere is a high likelihood that I will use VR glasses in the foreseeable future.\u003c/p\u003e\n \u003cp\u003eI intend to use VR glasses in the foreseeable future.\u003c/p\u003e\n \u003cp\u003eUsing VR glasses in the foreseeable future is important to me.\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 16.6298%;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003cp\u003e1 [1]; 48 [48]; 67 [67]; 78 [78]; 77 [77]\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 170px;\"\u003e\n \u003cp\u003e\u003cem\u003eProduct purchase intention\u003c/em\u003e\u003c/p\u003e\n \u003cp\u003ePUI1\u003c/p\u003e\n \u003cp\u003ePUI2\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 55.1505%;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 16.6298%;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003c/tbody\u003e\n\u003c/table\u003e\n\u003cp\u003eNotes:\u003csup\u003e\u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp;a\u0026nbsp;\u003c/sup\u003eAll items were measured on a 5 point Likert scale anchored from 1 (strongly disagree) to 5 (strongly agree)\u003c/p\u003e\n\u003cp\u003e\u003csup\u003eb\u0026nbsp;\u003c/sup\u003eThe final wording was discussed with an expert group with VR background\u003c/p\u003e\n\u003cp\u003e\u003csup\u003ec\u0026nbsp;\u003c/sup\u003eIncludes only studies with independent and dependent variables similar to the ones examined in this paper\u003c/p\u003e"},{"header":"4. Results","content":"\u003cdiv id=\"Sec14\" class=\"Section2\"\u003e\n \u003ch2\u003e4.1. Reliability and validity of measures\u003c/h2\u003e\n \u003cp\u003eThe nine multi-item aspects described in Chap.\u0026nbsp;2.3 constituted the latent constructs of the structural model evaluation. Measurement validation consisted of testing for internal consistency, convergent validity, and discriminate validity. The fact that all items used in the model evaluation are of a self-reported nature produces the potential for common method variance [\u003cspan class=\"CitationRef\"\u003e16\u003c/span\u003e, \u003cspan class=\"CitationRef\"\u003e25\u003c/span\u003e, \u003cspan class=\"CitationRef\"\u003e62\u003c/span\u003e, \u003cspan class=\"CitationRef\"\u003e63\u003c/span\u003e]. In addition, therefore, the authors performed a \u003cem\u003eposthoc\u003c/em\u003e factor analysis (Herman\u0026rsquo;s single-factor test).\u003c/p\u003e\n \u003cp\u003eConcerning convergent validity, all estimated factor loadings were statistically significant, and all standardized loadings exceeded .5. Average variance extracted (AVE) scores above 5 and composite reliability scores above .7 further supported the impression of convergent validity, with the exception of curiosity (AVE: .489, CR: .652; Appendix B). Moreover, Cronbach\u0026rsquo;s alphas greater than .7 indicated internal consistency (Appendix B). The items of curiosity and product purchase intention, for which the assumptions of Cronbach\u0026rsquo;s alpha cannot be tested, were highly correlated (curiosity: r\u0026thinsp;=\u0026thinsp;.759, product purchase intention: r\u0026thinsp;=\u0026thinsp;.691), but mostly uncorrelated with all other variables [\u003cspan class=\"CitationRef\"\u003e83\u003c/span\u003e].\u003c/p\u003e\n \u003cp\u003eAs Appendix C illustrates, correlations between the constructs, which served as exogenous variables of our model, indicated potential multicollinearity. This was especially true for attitude towards using VR and its antecedent variables. However, removing one of the correlated variables did not substantially affect the results of the analysis. In a separate model with all constructs pointing at a latent variable with a single random indicator (values varying from 0 to 1), no VIF was equal to or greater than 3.3 (Appendix D). Although the values for attitude towards and perceived usefulness were close to 3.3, collinearity was not an apparent issue [\u003cspan class=\"CitationRef\"\u003e9\u003c/span\u003e, \u003cspan class=\"CitationRef\"\u003e59\u003c/span\u003e].\u003c/p\u003e\n \u003cp\u003eThe high inter-factor correlations of attitude towards and its antecedent variables also raised the concern of whether respondents perceived the construct as a distinguishable aspect of technology acceptance (Appendix C). Besides, the factor correlation analysis questioned the discriminability of perceived playfulness from perceived enjoyment and perceived informativeness from perceived usefulness. Therefore, we compared the average heterotrait-heteromethod correlations to the average monotrait-heterotrait correlations between the constructs. Only the ratio between perceived usefulness and perceived informativeness and the ratio between perceived usefulness and attitude towards exceeded the threshold of .85 (Appendix E). However, the two exceeding comparisons remained under the .90 threshold (HTMT of .879 and .855) [\u003cspan class=\"CitationRef\"\u003e30\u003c/span\u003e]. Comparing the AVE estimates with the squared correlation estimates between the constructs indicated discriminant validity for all constructs (see Appendix C). In conclusion, the measurement model fits the observed data well. The fit indices supported convergent and discriminant validity for the measurement model [\u003cspan class=\"CitationRef\"\u003e28\u003c/span\u003e, \u003cspan class=\"CitationRef\"\u003e80\u003c/span\u003e].\u003c/p\u003e\n \u003cp\u003eAn unrotated principal component analysis indicated the presence of eight distinct factors with eigenvalues greater than 1.0 and one factor with an eigenvalue greater than 0.9 (Appendix F). The factors accounted for 75.653 percent of the variance. No single factor emerged from the analysis and none of the nine factors accounted for the majority of the variance. In conclusion, no general factor was apparent [\u003cspan class=\"CitationRef\"\u003e16\u003c/span\u003e, \u003cspan class=\"CitationRef\"\u003e25\u003c/span\u003e, \u003cspan class=\"CitationRef\"\u003e62\u003c/span\u003e]. Moreover, the authors used the \u003cspan class=\"InlineEquation\"\u003e\u003cspan class=\"mathinline\"\u003e\\(\\:{{\\chi\\:}}^{2}/\\text{d}\\text{f}\\)\u003c/span\u003e\u003c/span\u003e ratio, the comparative fit index (CFI), the Tucker-Lewis index (TLI), the standardized root mean square residual (SRMR), and the root mean square error of approximation (RMSEA) to test a single-factor model [\u003cspan class=\"CitationRef\"\u003e70\u003c/span\u003e]. The related confirmatory factor analysis revealed that the single-factor model did not explain the data well (\u003cspan class=\"InlineEquation\"\u003e\u003cspan class=\"mathinline\"\u003e\\(\\:{{\\chi\\:}}^{2}\\)\u003c/span\u003e\u003c/span\u003e = 1576.906, \u003cspan class=\"InlineEquation\"\u003e\u003cspan class=\"mathinline\"\u003e\\(\\:{{\\chi\\:}}^{2}/\\text{d}\\text{f}\\)\u003c/span\u003e\u003c/span\u003e = 3.186, CFI = 0.689, TLI = 0.668, SRMR = 0.092, RMSEA = 0.126). While these results do not wholly preclude the existence of common method variance, it does not appear to be a likely explanation for the results reported hereinafter [\u003cspan class=\"CitationRef\"\u003e16\u003c/span\u003e, \u003cspan class=\"CitationRef\"\u003e25\u003c/span\u003e].\u003c/p\u003e\n\u003c/div\u003e\n\u003cdiv id=\"Sec15\" class=\"Section2\"\u003e\n \u003ch2\u003e4.2. Structural model evaluation\u003c/h2\u003e\n \u003cp\u003eAfter assessing the validity and reliability of the measurement model, we conducted structure equation modeling (SEM) and tested the proposed paths by maximum likelihood estimation. We introduced the new variables of perceived playfulness and perceived informativeness, stepwise. First, we rebuilt the VR hardware acceptance model. We subsequently replaced the intention to purchase a VR wearable with the intention to buy the products displayed and stated this model as VR-HAM (Table\u0026nbsp;\u003cspan class=\"InternalRef\"\u003e2\u003c/span\u003e). Then we added perceived informativeness and perceived playfulness. Table\u0026nbsp;\u003cspan class=\"InternalRef\"\u003e2\u003c/span\u003e displays the resulting model as Model 1. The table also shows the maximum likelihood statistics for model selection, including the Akaike information criterion (AIC), Bayesian information criterion (BIC), \u003cspan class=\"InlineEquation\"\u003e\u003cspan class=\"mathinline\"\u003e\\(\\:{{\\chi\\:}}^{2}/\\text{d}\\text{f}\\)\u003c/span\u003e\u003c/span\u003e ratio, CFI, TLI, SRMR, RMSEA, and the coefficients of determination for the endogenous variables [\u003cspan class=\"CitationRef\"\u003e70\u003c/span\u003e]. The maximum likelihood statistics revealed comparable indices for VR-HAM (\u003cspan class=\"InlineEquation\"\u003e\u003cspan class=\"mathinline\"\u003e\\(\\:{{\\chi\\:}}^{2}\\)\u003c/span\u003e\u003c/span\u003e =293.791, \u003cspan class=\"InlineEquation\"\u003e\u003cspan class=\"mathinline\"\u003e\\(\\:{{\\chi\\:}}^{2}/\\text{d}\\text{f}\\)\u003c/span\u003e\u003c/span\u003e = 1.348, CFI = .924, TLI = .913, SRMR = .072, RMSEA = .069, AIC= 8661.110, BIC= 8886.001) and Model 1 (\u003cspan class=\"InlineEquation\"\u003e\u003cspan class=\"mathinline\"\u003e\\(\\:{{\\chi\\:}}^{2}\\)\u003c/span\u003e\u003c/span\u003e = 753.625, \u003cspan class=\"InlineEquation\"\u003e\u003cspan class=\"mathinline\"\u003e\\(\\:{{\\chi\\:}}^{2}/\\text{d}\\text{f}\\)\u003c/span\u003e\u003c/span\u003e = 1.587, CFI = 0.896, TLI = 0.885, SRMR = 0.069, RMSEA = 0.073, AIC= 8533.507, BIC= 8842.393).\u003c/p\u003e\n \u003cp\u003eHowever, when introducing perceived playfulness, we noticed that perceived enjoyment lost its contribution to explaining customer acceptance (Table \u003cspan class=\"InternalRef\"\u003e3\u003c/span\u003e). In accordance with the VR hardware acceptance model, without perceived playfulness, perceived enjoyment had a significant direct effect on the attitude towards using VR hardware (H2d, \u0026beta;\u0026thinsp;=\u0026thinsp;.361, p\u0026thinsp;\u0026lt;\u0026thinsp;.001). When introducing perceived playfulness, it successfully predicted perceived enjoyment (H8b, \u0026beta;\u0026thinsp;=\u0026thinsp;.433, p\u0026thinsp;\u0026lt;\u0026thinsp;.001). However, perceived enjoyment no longer predicted the attitude towards using VR (H8b, \u0026beta;\u0026thinsp;=\u0026thinsp;.137, p\u0026thinsp;\u0026gt;\u0026thinsp;.05). Instead, perceived playfulness had a significant direct effect on attitude towards using VR (H8c, \u0026beta;\u0026thinsp;=\u0026thinsp;.387, p\u0026thinsp;\u0026lt;\u0026thinsp;.001). To achieve the best possible model for data fit, we thus considered two additional model modifications by eliminating one of the constructs. Model 2 incorporates perceived enjoyment, while the construct is replaced with perceived playfulness in Model 3 (Table \u003cspan class=\"InternalRef\"\u003e3\u003c/span\u003e).\u003c/p\u003e\n \u003cp\u003e\u003c/p\u003e\n \u003ctable id=\"Tab2\" border=\"1\"\u003e\n \u003ccaption language=\"En\"\u003e\n \u003cdiv class=\"CaptionNumber\"\u003eTable 2\u003c/div\u003e\n \u003cdiv class=\"CaptionContent\"\u003e\n \u003cp\u003eMaximum likelihood statistics for model selection\u003c/p\u003e\n \u003c/div\u003e\n \u003c/caption\u003e\n \u003cthead\u003e\n \u003ctr\u003e\n \u003cth align=\"left\" rowspan=\"2\"\u003e\n \u003cp\u003eEvaluation criteria\u003c/p\u003e\n \u003c/th\u003e\n \u003cth align=\"left\" colspan=\"4\"\u003e\n \u003cp\u003eModel fit\u003c/p\u003e\n \u003c/th\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003cth align=\"left\"\u003e\n \u003cp\u003e\u003cbr\u003e\u003c/p\u003e\n \u003c/th\u003e\n \u003cth align=\"left\" colspan=\"3\"\u003e\n \u003cp\u003e\u003cbr\u003e\u003c/p\u003e\n \u003c/th\u003e\n \u003c/tr\u003e\n \u003c/thead\u003e\n \u003ctbody\u003e\n \u003ctr\u003e\n \u003ctd\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd\u003eVR-HAM\u003cbr\u003e\u003c/td\u003e\n \u003ctd style=\"width: 36.0687%;\" colspan=\"3\"\u003e\u003cbr\u003eVR-XAM\u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd\u003eModel 1\u003cbr\u003e\u003c/td\u003e\n \u003ctd\u003eModel 2\u003cbr\u003e\u003c/td\u003e\n \u003ctd\u003eModel 3\u003cbr\u003e\u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e\u003cspan class=\"InlineEquation\"\u003e\u003cspan class=\"mathinline\"\u003e\\(\\:{{\\chi\\:}}^{2}\\)\u003c/span\u003e\u003c/span\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e293.791\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e753.625\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e576.764\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e571.696\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e\u003cspan class=\"InlineEquation\"\u003e\u003cspan class=\"mathinline\"\u003e\\(\\:{{\\chi\\:}}^{2}/\\text{d}\\text{f}\\)\u003c/span\u003e\u003c/span\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e1.348\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e1.587\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e1.598\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e1.584\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eCFI\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e.924\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e.896\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e.907\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e.909\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eTLI\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e.913\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e.885\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e.896\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e.902\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eSRMR\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e.072\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e.069\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e.072\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e.065\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eRMSEA\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e.069\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e.073\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e.073\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e.073\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eAIC\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e8661.110\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e8533.507\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e7665.790\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e7563.356\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eBIC\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e8886.001\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e8842.393\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e7931.324\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e7828.890\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e\u003cspan class=\"InlineEquation\"\u003e\u003cspan class=\"mathinline\"\u003e\\(\\:{R}^{2}\\)\u003c/span\u003e\u003c/span\u003e Perceived ease of use\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e.246\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e.229\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e.227\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e.227\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e\u003cspan class=\"InlineEquation\"\u003e\u003cspan class=\"mathinline\"\u003e\\(\\:{R}^{2}\\)\u003c/span\u003e\u003c/span\u003e Perceived usefulness\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e.588\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e.844\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e.857\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e.843\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e\u003cspan class=\"InlineEquation\"\u003e\u003cspan class=\"mathinline\"\u003e\\(\\:{R}^{2}\\)\u003c/span\u003e\u003c/span\u003e Perceived enjoyment\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e.341\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e.541\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e.361\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e-\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e\u003cspan class=\"InlineEquation\"\u003e\u003cspan class=\"mathinline\"\u003e\\(\\:{R}^{2}\\)\u003c/span\u003e\u003c/span\u003e Perceived playfulness\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e-\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e.183\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e-\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e.184\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e\u003cspan class=\"InlineEquation\"\u003e\u003cspan class=\"mathinline\"\u003e\\(\\:{R}^{2}\\)\u003c/span\u003e\u003c/span\u003e Perceived informativeness\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e-\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e.659\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e.557\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e.659\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e\u003cspan class=\"InlineEquation\"\u003e\u003cspan class=\"mathinline\"\u003e\\(\\:{R}^{2}\\)\u003c/span\u003e\u003c/span\u003e Attitude towards using VR\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e.774\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e.845\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e.786\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e.837\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e\u003cspan class=\"InlineEquation\"\u003e\u003cspan class=\"mathinline\"\u003e\\(\\:{R}^{2}\\)\u003c/span\u003e\u003c/span\u003e Intention to use\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e.612\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e.626\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e.608\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e.638\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e\u003cspan class=\"InlineEquation\"\u003e\u003cspan class=\"mathinline\"\u003e\\(\\:{R}^{2}\\)\u003c/span\u003e\u003c/span\u003e Product purchase intention\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e.364\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e.353\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e.354\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e.355\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003c/tbody\u003e\n \u003c/table\u003e\n \u003cp\u003e\u003c/p\u003e\n \u003cp\u003e\u003cbr\u003e\u003c/p\u003e\n \u003ctable id=\"Tab3\" border=\"1\"\u003e\n \u003ccaption language=\"En\"\u003e\n \u003cdiv class=\"CaptionNumber\"\u003eTable 3\u003c/div\u003e\n \u003cdiv class=\"CaptionContent\"\u003e\n \u003cp\u003eSummary from hypothesis testing\u003c/p\u003e\n \u003c/div\u003e\n \u003c/caption\u003e\n \u003cthead\u003e\n \u003ctr\u003e\n \u003cth align=\"left\" rowspan=\"3\"\u003e\n \u003cp\u003eNo\u003c/p\u003e\n \u003c/th\u003e\n \u003cth align=\"left\" rowspan=\"3\"\u003e\n \u003cp\u003eRelationship\u003c/p\u003e\n \u003c/th\u003e\n \u003cth align=\"left\" colspan=\"6\"\u003e\n \u003cp\u003eRegression weights VR-XAM\u003c/p\u003e\n \u003c/th\u003e\n \u003cth align=\"left\" rowspan=\"3\"\u003e\n \u003cp\u003eAssessment\u003c/p\u003e\n \u003c/th\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003cth align=\"left\" colspan=\"2\"\u003e\n \u003cp\u003eModel 1\u003c/p\u003e\n \u003c/th\u003e\n \u003cth align=\"left\" colspan=\"2\"\u003e\n \u003cp\u003eModel 2\u003c/p\u003e\n \u003c/th\u003e\n \u003cth align=\"left\" colspan=\"2\"\u003e\n \u003cp\u003eModel 3\u003c/p\u003e\n \u003c/th\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003cth align=\"left\"\u003e\n \u003cp\u003eB(SE B) \u003csup\u003ea\u003c/sup\u003e\u003c/p\u003e\n \u003c/th\u003e\n \u003cth align=\"left\"\u003e\n \u003cp\u003e\u0026beta; \u003csup\u003eb\u003c/sup\u003e\u003c/p\u003e\n \u003c/th\u003e\n \u003cth align=\"left\"\u003e\n \u003cp\u003eB(SE B) \u003csup\u003ea\u003c/sup\u003e\u003c/p\u003e\n \u003c/th\u003e\n \u003cth align=\"left\"\u003e\n \u003cp\u003e\u0026beta; \u003csup\u003eb\u003c/sup\u003e\u003c/p\u003e\n \u003c/th\u003e\n \u003cth align=\"left\"\u003e\n \u003cp\u003eB(SE B) \u003csup\u003ea\u003c/sup\u003e\u003c/p\u003e\n \u003c/th\u003e\n \u003cth align=\"left\"\u003e\n \u003cp\u003e\u0026beta; \u003csup\u003eb\u003c/sup\u003e\u003c/p\u003e\n \u003c/th\u003e\n \u003c/tr\u003e\n \u003c/thead\u003e\n \u003ctbody\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eH1a-\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eAge \u0026loz; Perceived ease of use\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e\u0026minus;\u0026thinsp;.347*** (.105)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e\u0026minus;\u0026thinsp;.309\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e\u0026minus;\u0026thinsp;.348***(.105)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e\u0026minus;\u0026thinsp;.309\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e\u0026minus;\u0026thinsp;.338***(.105)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e\u0026minus;\u0026thinsp;.302\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eSupported\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eH1b-\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eAge \u0026loz; Perceived usefulness\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e\u0026minus;\u0026thinsp;.031(.064)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e\u0026minus;\u0026thinsp;.028\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e.046(.061)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e.041\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e.015(.064)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e.013\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eNot supported\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eH1a+\u003c/p\u003e\n \u003cp\u003eH1b+\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eAttitude towards using \u0026loz; Intention to use\u003c/p\u003e\n \u003cp\u003eAttitude towards using \u0026loz; Product purchase intention\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e1.269***(.241)\u003c/p\u003e\n \u003cp\u003e.570***(.124)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e.952\u003c/p\u003e\n \u003cp\u003e.594\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e1.239***(.251)\u003c/p\u003e\n \u003cp\u003e.577***(.123)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e.931\u003c/p\u003e\n \u003cp\u003e.596\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e1.305***(.239)\u003c/p\u003e\n \u003cp\u003e.575***(.123)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e.978\u003c/p\u003e\n \u003cp\u003e.596\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eSupported\u003c/p\u003e\n \u003cp\u003eSupported\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eH2a+\u003c/p\u003e\n \u003cp\u003eH2b+\u003c/p\u003e\n \u003cp\u003eH2c+\u003c/p\u003e\n \u003cp\u003eH2d+\u003c/p\u003e\n \u003cp\u003eH2e+\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003ePerceived usefulness \u0026loz; Attitude towards using\u003c/p\u003e\n \u003cp\u003ePerceived usefulness \u0026loz; Intention to use\u003c/p\u003e\n \u003cp\u003ePerceived ease of use \u0026loz; Attitude towards using\u003c/p\u003e\n \u003cp\u003ePerceived enjoyment \u0026loz; Attitude towards using\u003c/p\u003e\n \u003cp\u003ePerceived enjoyment \u0026loz; Perceived usefulness\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e.414***(.084)\u003c/p\u003e\n \u003cp\u003e\u0026minus;\u0026thinsp;.230(.172)\u003c/p\u003e\n \u003cp\u003e\u0026minus;\u0026thinsp;.001(.071)\u003c/p\u003e\n \u003cp\u003e.137(.099)\u003c/p\u003e\n \u003cp\u003e.076(.118)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e.545\u003c/p\u003e\n \u003cp\u003e\u0026minus;\u0026thinsp;.227\u003c/p\u003e\n \u003cp\u003e\u0026minus;\u0026thinsp;.001\u003c/p\u003e\n \u003cp\u003e.121\u003c/p\u003e\n \u003cp\u003e.051\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e601***(.094)\u003c/p\u003e\n \u003cp\u003e\u0026minus;\u0026thinsp;.211(.184)\u003c/p\u003e\n \u003cp\u003e\u0026minus;\u0026thinsp;.098(.084)\u003c/p\u003e\n \u003cp\u003e.361***(.105)\u003c/p\u003e\n \u003cp\u003e.099(.116)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e.790\u003c/p\u003e\n \u003cp\u003e\u0026minus;\u0026thinsp;.208\u003c/p\u003e\n \u003cp\u003e\u0026minus;\u0026thinsp;.132\u003c/p\u003e\n \u003cp\u003e.319\u003c/p\u003e\n \u003cp\u003e.067\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e.414***(.085)\u003c/p\u003e\n \u003cp\u003e\u0026minus;\u0026thinsp;.257(.170)\u003c/p\u003e\n \u003cp\u003e.033(.067)\u003c/p\u003e\n \u003cp\u003e-\u003c/p\u003e\n \u003cp\u003e-\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e.547\u003c/p\u003e\n \u003cp\u003e\u0026minus;\u0026thinsp;.254\u003c/p\u003e\n \u003cp\u003e.044\u003c/p\u003e\n \u003cp\u003e-\u003c/p\u003e\n \u003cp\u003e-\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eSupported\u003c/p\u003e\n \u003cp\u003eNot supported\u003c/p\u003e\n \u003cp\u003eNot supported\u003c/p\u003e\n \u003cp\u003eSupported\u003c/p\u003e\n \u003cp\u003eNot supported\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eH3a+\u003c/p\u003e\n \u003cp\u003eH3b+\u003c/p\u003e\n \u003cp\u003eH3c+\u003c/p\u003e\n \u003cp\u003eH3d+\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003ePerceived ease of use \u0026loz; Perceived usefulness\u003c/p\u003e\n \u003cp\u003ePerceived ease of use \u0026loz; Perceived informativeness\u003c/p\u003e\n \u003cp\u003ePerceived ease of use \u0026loz; Perceived enjoyment\u003c/p\u003e\n \u003cp\u003ePerceived ease of use \u0026loz; Perceived playfulness\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e.210* (.092)\u003c/p\u003e\n \u003cp\u003e.446***(.092)\u003c/p\u003e\n \u003cp\u003e.245***(.067)\u003c/p\u003e\n \u003cp\u003e. 324***(.081)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e.212\u003c/p\u003e\n \u003cp\u003e.435\u003c/p\u003e\n \u003cp\u003e.371\u003c/p\u003e\n \u003cp\u003e.428\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e.211*(.095)\u003c/p\u003e\n \u003cp\u003e.615***(.099)\u003c/p\u003e\n \u003cp\u003e.397***(.077)\u003c/p\u003e\n \u003cp\u003e-\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e215\u003c/p\u003e\n \u003cp\u003e.595\u003c/p\u003e\n \u003cp\u003e.601\u003c/p\u003e\n \u003cp\u003e-\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e.223*(.089)\u003c/p\u003e\n \u003cp\u003e.446***(.093)\u003c/p\u003e\n \u003cp\u003e-\u003c/p\u003e\n \u003cp\u003e.320***(.081)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e.223\u003c/p\u003e\n \u003cp\u003e.433\u003c/p\u003e\n \u003cp\u003e-\u003c/p\u003e\n \u003cp\u003e.429\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eSupported\u003c/p\u003e\n \u003cp\u003eSupported\u003c/p\u003e\n \u003cp\u003eSupported\u003c/p\u003e\n \u003cp\u003eSupported\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eH4a+\u003c/p\u003e\n \u003cp\u003eH4b+\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003ePast use \u0026loz; Intention to Use\u003c/p\u003e\n \u003cp\u003ePast use \u0026loz; Perceived usefulness\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e.023*(.010)\u003c/p\u003e\n \u003cp\u003e\u0026minus;\u0026thinsp;.003(.008)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e.163\u003c/p\u003e\n \u003cp\u003e\u0026minus;\u0026thinsp;.022\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e.022*(.010)\u003c/p\u003e\n \u003cp\u003e\u0026minus;\u0026thinsp;.003(.007)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e.162\u003c/p\u003e\n \u003cp\u003e\u0026minus;\u0026thinsp;.025\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e.023*(.010)\u003c/p\u003e\n \u003cp\u003e\u0026minus;\u0026thinsp;.002(.008)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e.165\u003c/p\u003e\n \u003cp\u003e\u0026minus;\u0026thinsp;.015\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eSupported\u003c/p\u003e\n \u003cp\u003eNot supported\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eH5a-\u003c/p\u003e\n \u003cp\u003eH5b-\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eAge \u0026loz; Perceived ease of use\u003c/p\u003e\n \u003cp\u003eAge \u0026loz; Perceived usefulness\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e\u0026minus;\u0026thinsp;.347*** (.105)\u003c/p\u003e\n \u003cp\u003e\u0026minus;\u0026thinsp;.031(.064)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e\u0026minus;\u0026thinsp;.309\u003c/p\u003e\n \u003cp\u003e\u0026minus;\u0026thinsp;.028\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e\u0026minus;\u0026thinsp;.348***(.105)\u003c/p\u003e\n \u003cp\u003e.046(.061)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e\u0026minus;\u0026thinsp;.309\u003c/p\u003e\n \u003cp\u003e.041\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e\u0026minus;\u0026thinsp;.338***(.105)\u003c/p\u003e\n \u003cp\u003e.015(.064)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e\u0026minus;\u0026thinsp;.302\u003c/p\u003e\n \u003cp\u003e.013\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eSupported\u003c/p\u003e\n \u003cp\u003eNot supported\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eH6a+\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eCuriosity \u0026loz; Perceived ease of use\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e.532**(.178)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e.364\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e.525**(.178)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e.363\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e.535**(.178)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e.369\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eSupported\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eH6b+\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eCuriosity \u0026loz; Perceived informativeness\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e.349*(.150)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e.233\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e.424**(.165)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e.284\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e.337*(.150)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e.226\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eSupported\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eH7+\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003ePerceived informativeness \u0026loz; Perceived usefulness\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e.709***(.096)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e.734\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e.701***(.094)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e.737\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e.728***(.094)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e.752\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eSupported\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eH8a+\u003c/p\u003e\n \u003cp\u003eH8b+\u003c/p\u003e\n \u003cp\u003eH8c+\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003ePerceived playfulness \u0026loz; Perceived informativeness\u003c/p\u003e\n \u003cp\u003ePerceived playfulness \u0026loz; Perceived enjoyment\u003c/p\u003e\n \u003cp\u003ePerceived playfulness \u0026loz; Attitude towards using\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e.547***(.124)\u003c/p\u003e\n \u003cp\u003e.433***(.098)\u003c/p\u003e\n \u003cp\u003e.387***(.096)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e.403\u003c/p\u003e\n \u003cp\u003e.496\u003c/p\u003e\n \u003cp\u003e.389\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e-\u003c/p\u003e\n \u003cp\u003e-\u003c/p\u003e\n \u003cp\u003e-\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e-\u003c/p\u003e\n \u003cp\u003e-\u003c/p\u003e\n \u003cp\u003e-\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e.563***(.127)\u003c/p\u003e\n \u003cp\u003e-\u003c/p\u003e\n \u003cp\u003e.456***(.090)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e.409\u003c/p\u003e\n \u003cp\u003e-\u003c/p\u003e\n \u003cp\u003e.452\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eSupported\u003c/p\u003e\n \u003cp\u003eSupported\u003c/p\u003e\n \u003cp\u003eSupported\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003c/tbody\u003e\n \u003ctfoot\u003e\n \u003ctr\u003e\n \u003ctd colspan=\"9\"\u003eNotes: \u003csup\u003ea\u003c/sup\u003e () Standard error in parenthesis; * p\u0026thinsp;\u0026lt;\u0026thinsp;0.05; ** p\u0026thinsp;\u0026lt;\u0026thinsp;0.01; ***p\u0026thinsp;\u0026lt;\u0026thinsp;0.001 (N\u0026thinsp;=\u0026thinsp;137)\u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd colspan=\"9\"\u003e\u003csup\u003eb\u003c/sup\u003e Completely standardized path coefficients\u003c/td\u003e\n \u003c/tr\u003e\n \u003c/tfoot\u003e\n \u003c/table\u003e\n \u003cp\u003eFor Model 2 (\u003cspan class=\"InlineEquation\"\u003e\u003cspan class=\"mathinline\"\u003e\\(\\:{{\\chi\\:}}^{2}\\)\u003c/span\u003e\u003c/span\u003e = 576.764, \u003cspan class=\"InlineEquation\"\u003e\u003cspan class=\"mathinline\"\u003e\\(\\:{{\\chi\\:}}^{2}/\\text{d}\\text{f}\\)\u003c/span\u003e\u003c/span\u003e = 1.598, CFI = 0.907, TLI = 0.896, SRMR = 0.072, RMSEA = 0.073) and Model 3 (\u003cspan class=\"InlineEquation\"\u003e\u003cspan class=\"mathinline\"\u003e\\(\\:{{\\chi\\:}}^{2}\\)\u003c/span\u003e\u003c/span\u003e = 571.696, \u003cspan class=\"InlineEquation\"\u003e\u003cspan class=\"mathinline\"\u003e\\(\\:{{\\chi\\:}}^{2}/\\text{d}\\text{f}\\)\u003c/span\u003e\u003c/span\u003e = 1.584, CFI = 0.909, TLI = 0.902, SRMR = 0.065, RMSEA = 0.073), parsimonious, incremental, and absolute fit measures indicated reasonable model fit, according to the thresholds suggested in the literature [\u003cspan class=\"CitationRef\"\u003e70\u003c/span\u003e]. However, all these indices were slightly in favor of Model 3. Nevertheless, we obtained minimum comparative fit indices for Model 3, which we therefore selected as our final model (AIC = 7563.356, BIC = 7828.890). Furthermore, the results show that Model 3 offers valuable insights in explaining the determinants accepting VR experiences in retail. Figure \u003cspan class=\"InternalRef\"\u003e3\u003c/span\u003e shows the final model with path coefficients and significance levels.\u003c/p\u003e\n \u003cp\u003eThe model explained a substantial amount of variance for intention to use (\u003cspan class=\"InlineEquation\"\u003e\u003cspan class=\"mathinline\"\u003e\\(\\:{R}^{2}=\\:\\)\u003c/span\u003e\u003c/span\u003e.638) and attitude towards using (\u003cspan class=\"InlineEquation\"\u003e\u003cspan class=\"mathinline\"\u003e\\(\\:{R}^{2}=\\:\\)\u003c/span\u003e\u003c/span\u003e.837) VR wearables. It also helped to explain the intention to purchase the products experienced in the virtual apartment (\u003cspan class=\"InlineEquation\"\u003e\u003cspan class=\"mathinline\"\u003e\\(\\:{R}^{2}=\\:\\)\u003c/span\u003e\u003c/span\u003e.355). The same applies to perceived usefulness (\u003cspan class=\"InlineEquation\"\u003e\u003cspan class=\"mathinline\"\u003e\\(\\:{R}^{2}=\\:\\)\u003c/span\u003e\u003c/span\u003e.843), as well as perceived ease of use (\u003cspan class=\"InlineEquation\"\u003e\u003cspan class=\"mathinline\"\u003e\\(\\:{R}^{2}=\\:\\)\u003c/span\u003e\u003c/span\u003e.227), perceived informativeness (\u003cspan class=\"InlineEquation\"\u003e\u003cspan class=\"mathinline\"\u003e\\(\\:{R}^{2}=\\:\\)\u003c/span\u003e\u003c/span\u003e.659), and perceived playfulness (\u003cspan class=\"InlineEquation\"\u003e\u003cspan class=\"mathinline\"\u003e\\(\\:{R}^{2}=\\:\\)\u003c/span\u003e\u003c/span\u003e.184).\u003c/p\u003e\n \u003cp\u003eIn the model, age did not influence perceived usefulness (H5b; \u0026beta; = \u0026minus;\u0026thinsp;.015, p\u0026thinsp;\u0026gt;\u0026thinsp;.05). However, older respondents perceived the VR application as being more difficult to use (H5a; \u0026beta; = \u0026minus;\u0026thinsp;.338, p\u0026thinsp;\u0026lt;\u0026thinsp;.001). In contrast, curiosity positively affected perceived ease of use (H6a, \u0026beta;\u0026thinsp;=\u0026thinsp;.535, p\u0026thinsp;\u0026lt;\u0026thinsp;.01); it also successfully predicted perceived informativeness (H6b, \u0026beta;\u0026thinsp;=\u0026thinsp;.337, p\u0026thinsp;\u0026lt;\u0026thinsp;.05). Although it left no significant effect on perceived usefulness (H4b; \u0026beta; = \u0026minus;\u0026thinsp;.002, p\u0026thinsp;\u0026gt;\u0026thinsp;.05), past use directly affected the intention to use (H4a, \u0026beta;\u0026thinsp;=\u0026thinsp;.023, p\u0026thinsp;\u0026lt;\u0026thinsp;.05).\u003c/p\u003e\n \u003cp\u003eAs expected, customers who perceived the VR wearable as being easy to use also experienced it as more informative (H3b, \u0026beta;\u0026thinsp;=\u0026thinsp;.446, p\u0026thinsp;\u0026lt;\u0026thinsp;.001), playful (H3d, \u0026beta;\u0026thinsp;=\u0026thinsp;.320, p\u0026thinsp;\u0026lt;\u0026thinsp;.001), and useful (H3a, \u0026beta;\u0026thinsp;=\u0026thinsp;.223, p\u0026thinsp;\u0026lt;\u0026thinsp;.05). Surprisingly, perceived ease of use did not have a direct effect on attitude towards using the wearable (H2c, \u0026beta; = \u0026minus;\u0026thinsp;.033, p\u0026thinsp;\u0026gt;\u0026thinsp;.05). Together with perceived ease of use, perceived informativeness had a strong direct effect on perceived usefulness (H7, \u0026beta;\u0026thinsp;=\u0026thinsp;.728, p\u0026thinsp;\u0026lt;\u0026thinsp;.001). In turn, perceived informativeness increased when participants experienced the VR experience as playful (H8a, \u0026beta;\u0026thinsp;=\u0026thinsp;.563, p\u0026thinsp;\u0026lt;\u0026thinsp;.001). Higher perceived playfulness also led to stronger attitudes towards using VR glasses in general (H8c, \u0026beta;\u0026thinsp;=\u0026thinsp;.456, p\u0026thinsp;\u0026lt;\u0026thinsp;.001). Comparing the standardized path coefficients revealed that perceived playfulness was the second strongest direct antecedent of attitude (\u003cspan class=\"InlineEquation\"\u003e\u003cspan class=\"mathinline\"\u003e\\(\\:{\\beta\\:}_{std}\\)\u003c/span\u003e\u003c/span\u003e = .452).\u003c/p\u003e\n \u003cp\u003eIn line with the original TAM, participants of the field study who viewed the technology as more useful had a stronger attitude towards VR experiences (H2a, \u0026beta;\u0026thinsp;=\u0026thinsp;.414, p\u0026thinsp;\u0026lt;\u0026thinsp;.001). A comparison of the standardized path coefficients showed that perceived usefulness was the strongest direct antecedent of attitude (\u003cspan class=\"InlineEquation\"\u003e\u003cspan class=\"mathinline\"\u003e\\(\\:{\\beta\\:}_{std}\\)\u003c/span\u003e\u003c/span\u003e = .547). However, perceived usefulness had no significant direct effect on intention to use (H2b, \u0026beta; = \u0026minus;\u0026thinsp;.257, p\u0026thinsp;\u0026gt;\u0026thinsp;.05). Eventually, attitude towards using had a strong direct relationship with intention to use (H1a, \u0026beta;\u0026thinsp;=\u0026thinsp;1.305, p\u0026thinsp;\u0026lt;\u0026thinsp;.001). Interestingly, the attitude towards using VR glasses in retail also positively affected the intention to purchase the displayed products (H1b, \u0026beta;\u0026thinsp;=\u0026thinsp;.575, p\u0026thinsp;\u0026lt;\u0026thinsp;.001). Table\u0026nbsp;\u003cspan class=\"InternalRef\"\u003e2\u003c/span\u003e summarizes the hypothesized relationship, the unstandardized and standardized coefficients, as well as the model assessment.\u003c/p\u003e\n\u003c/div\u003e"},{"header":"5. Discussion","content":"\u003cdiv id=\"Sec17\" class=\"Section2\"\u003e\u003ch2\u003e5.1. Perceived usefulness, perceived enjoyment, and attitude\u003c/h2\u003e\u003cp\u003eThe literature suggests that cross-channel technologies need to simultaneously provide hedonic and utilitarian value to improve attitudes and behavioral intentions [\u003cspan citationid=\"CR55\" class=\"CitationRef\"\u003e55\u003c/span\u003e, \u003cspan citationid=\"CR79\" class=\"CitationRef\"\u003e79\u003c/span\u003e]. Accordingly, study participants formed stronger attitudes and usage intentions if they perceived VR glasses as useful and enjoyable. Interestingly, in a retailing context, the attitude also predicts the willingness to purchase the products displayed. The possibility to test the functionality of products and more effectively perform decision tasks in a VR-enriched customer experience directly impacts the purchase decision.\u003c/p\u003e\u003cp\u003eWhen comparing the path coefficients towards attitudes and behavioral intentions, perceived usefulness appears to be the most potent predictor compared to the remaining variables. This finding is in line with the original TAM [\u003cspan citationid=\"CR11\" class=\"CitationRef\"\u003e11\u003c/span\u003e, \u003cspan citationid=\"CR21\" class=\"CitationRef\"\u003e21\u003c/span\u003e]. However, the finding is remarkable because enjoyment appeared as the strongest predictor of attitudes and behavioral intentions in research for which customers reported beliefs and attitudes without actually using VR wearables [\u003cspan citationid=\"CR48\" class=\"CitationRef\"\u003e48\u003c/span\u003e]. One possible explanation for this finding could be that perceiving technology as useful gains importance for attitudes and behavioral intentions when experiencing the hardware combined with a specific application in a retailing environment. However, research also indicates the higher importance of perceived enjoyment when customers experience wearable AR technologies in retail stores [\u003cspan citationid=\"CR32\" class=\"CitationRef\"\u003e32\u003c/span\u003e]. This difference might stem from the fact that AR, in contrast to VR, adds virtual elements to the product information already provided by the store environment. When using VR applications, customers wholly depend on the information provided and by the virtual product displayed and, hence, the application's usefulness in evaluating products.\u003c/p\u003e\u003c/div\u003e\u003cdiv id=\"Sec18\" class=\"Section2\"\u003e\u003ch2\u003e5.2. Perceived informativeness and perceived playfulness\u003c/h2\u003e\u003cp\u003eConsistent with the notion of a high dependence on virtual information in VR, the degree of perceived usefulness in our field study depended on whether customers perceived the application as being informative. This finding is in line with research suggesting the importance of perceived informativeness in predicting customers' purchase intentions when using VR software on a desktop computer in an online shopping scenario [\u003cspan citationid=\"CR35\" class=\"CitationRef\"\u003e35\u003c/span\u003e]. The study at hand expands this knowledge by demonstrating that the informativeness of the product display strongly impacts attitudes towards the technology as a whole, including the hardware thereof. Enjoyment may have a substantial impact on the acceptance of VR wearables. However, hedonic benefits alone would not necessarily lead customers to reuse VR wearables in retail and purchase products if the product display is not informative.\u003c/p\u003e\u003cp\u003eAs our Model 1 shows, the enjoyment of VR glasses builds on playful elements. Moreover, customers who perceive VR as playful also perceive higher degrees of informativeness. This finding is in line with the literature stating that VR goggles provide additional product details in a playful way beyond the limits of stationary retail environments [\u003cspan citationid=\"CR79\" class=\"CitationRef\"\u003e79\u003c/span\u003e]. Customers tend to experience products as visually attractive when presented in a playful manner [\u003cspan citationid=\"CR35\" class=\"CitationRef\"\u003e35\u003c/span\u003e]. Surprisingly, when comparing different models, perceived playfulness reflects the hedonic aspects of VR experiences in retail better than perceived enjoyment. One possible explanation could be the high utilization of attentional resources in virtual environments. The literature considers VR experiences as particularly immersive and attention-grabbing. With decreasing attentional resources, playful cues are easier to process [\u003cspan citationid=\"CR23\" class=\"CitationRef\"\u003e23\u003c/span\u003e, \u003cspan citationid=\"CR54\" class=\"CitationRef\"\u003e54\u003c/span\u003e, \u003cspan citationid=\"CR61\" class=\"CitationRef\"\u003e61\u003c/span\u003e]. In line with this notion, perceived playfulness had a strong direct impact on customers' attitudes towards VR.\u003c/p\u003e\u003cp\u003eTo conclude, acceptance models for wearable VR technologies in retail need to address functional and playful elements simultaneously. The informativeness that comes from life-sized 3D product displays and the possibility to move and rotate items makes the technology useful in retail stores. At the same time, customers form positive attitudes towards VR when experiencing highly playful virtual shopping environments. The joy and informativeness linked to the playful interaction with virtual elements in a physical environment may encourage customers to spend more time with a retailer and to purchase more items.\u003c/p\u003e\u003c/div\u003e\u003cdiv id=\"Sec19\" class=\"Section2\"\u003e\u003ch2\u003e5.3. Perceived ease of use, age, curiosity, and past use\u003c/h2\u003e\u003cp\u003eCustomers\u0026rsquo; perceptions of informativeness and playfulness improve when customers perceive VR wearables as easy to use. This finding is in line with previous literature considering perceived ease of use to be the primary determinant of technology usage [\u003cspan citationid=\"CR11\" class=\"CitationRef\"\u003e11\u003c/span\u003e, \u003cspan citationid=\"CR21\" class=\"CitationRef\"\u003e21\u003c/span\u003e]. In our study, more curious and younger participants found the VR application easier to use. Consistent with this finding, in previous research curiosity and youth were predictive of learning and engagement, both being associated with perceived ease of use [\u003cspan citationid=\"CR10\" class=\"CitationRef\"\u003e10\u003c/span\u003e, \u003cspan citationid=\"CR48\" class=\"CitationRef\"\u003e48\u003c/span\u003e]. More curious individuals also perceived the 3D product display as more informative. This finding relates to an understanding of curiosity as a person\u0026rsquo;s willingness to seek novel information. Innovatively receiving novel product information is appreciated more by customers with a higher desire to seek information [\u003cspan citationid=\"CR10\" class=\"CitationRef\"\u003e10\u003c/span\u003e, \u003cspan citationid=\"CR37\" class=\"CitationRef\"\u003e37\u003c/span\u003e]. In contrast to this idea, several studies have identified information system user behavior to be self-repetitive [\u003cspan citationid=\"CR5\" class=\"CitationRef\"\u003e5\u003c/span\u003e, \u003cspan citationid=\"CR36\" class=\"CitationRef\"\u003e36\u003c/span\u003e, \u003cspan citationid=\"CR48\" class=\"CitationRef\"\u003e48\u003c/span\u003e, \u003cspan citationid=\"CR77\" class=\"CitationRef\"\u003e77\u003c/span\u003e]. In line with this notion, customers who already used VR wearables had stronger intentions to reuse the technology in the future.\u003c/p\u003e\u003c/div\u003e"},{"header":"6. Conclusion","content":"\u003cdiv id=\"Sec21\" class=\"Section2\"\u003e\u003ch2\u003e6.1. Theoretical implications\u003c/h2\u003e\u003cp\u003eEven though practitioners and researchers alike expect the market for VR glasses to grow tremendously, the research on the acceptance drivers of these wearables in retail environments is scarce. The separate consideration of VR hardware and VR content in previous studies makes it difficult to assess the entire VR experience and to draw conclusions for retailers. Therefore, the study adapts and extends 48\u0026rsquo;s [\u003cspan citationid=\"CR48\" class=\"CitationRef\"\u003e48\u003c/span\u003e] VR-HAM by including VR content elements to evaluate the drivers, which influence the acceptance of entire VR experiences.\u003c/p\u003e\u003cp\u003eIn particular, the authors empirically tested a VR experience model geared towards the following aspects: (1) users\u0026rsquo; perceptions of informativeness and playfulness and their impact on the perceptions of usefulness, ease of use, and enjoyment; and (2) the resulting impact on attitudes and behavioral intentions towards using VR glasses.\u003c/p\u003e\u003cp\u003eThe results of this paper indicate the robustness of VR-XAM, which offers valuable insights to explain the determinants influencing users\u0026rsquo; attitudes towards and intention to use VR wearables. The model stresses the importance of customer attitudes towards specific technologies when considering them as a channel through which to market or sell products in a cross-channel environment. The content-related variables perceived playfulness and perceived informativeness appeared as important predictors for attitudes and behavioral intentions when researching VR experiences in retail. Particularly noteworthy is the outstanding role of the utilitarian variables when comparing VR to retail technologies that do not entirely rely on virtual content. Furthermore, the perceived playfulness variable seems to be the best representation for the hedonic value of VR experiences in retail. Indeed, most of the previous technology acceptance studies conceptualized perceived enjoyment as the direct hedonic antecedent of attitudes and behavioral intentions.\u003c/p\u003e\u003c/div\u003e\u003cdiv id=\"Sec22\" class=\"Section2\"\u003e\u003ch2\u003e6.2. Implications for industry\u003c/h2\u003e\u003cp\u003eFrom a practical perspective, this study is particularly relevant for retailers, hardware developers, and software developers. Companies have started to test different forms of VR shopping. Despite this, little is known about what makes customers accept VR experiences provided by wearable devices in stores. The results provide clear evidence for practitioners to refine and develop VR content and hardware for retailing applications. They are especially meaningful for companies selling large-scale luxury or designer goods like furniture. When buying these goods, customers have a high need to experience product characteristics prior to purchasing. At the same time, displaying these products physically occupies expensive store space and requires backup inventories.\u003c/p\u003e\u003cp\u003eWhile the functionality of VR wearables is increasingly improving, companies should also focus on VR content to increase the usefulness of VR applications in retail. Customers perceive content that is particularly informative as useful. At the same time, our results indicate that companies should add playful content to form positive customer attitudes. However, the relatively stronger impact of usefulness suggests that firms can capitalize on utilitarian attributes first to achieve better customer acceptance while gradually integrating playful elements.\u003c/p\u003e\u003cp\u003eIn doing so, the hardware and software should be conceptualized in a way that is easy to use for customers. At the same time, it could be beneficial for companies to target specific customer groups when introducing VR applications in stores. VR is easier to use and more informative for younger customers with a high level of inherent curiosity. Companies could also focus on customers who have already used VR in the past when aiming at maximum customer acceptance during the implementation of such VR applications.\u003c/p\u003e\u003c/div\u003e\u003cdiv id=\"Sec23\" class=\"Section2\"\u003e\u003ch2\u003e6.3. Limitations and future research\u003c/h2\u003e\u003cp\u003eThe model developed in this paper is the first attempt to simultaneously consider the acceptance of VR content and hardware. The model enables future research to assess the acceptance of VR content across different devices and the acceptance for hardware for various VR content elements. Such studies can build on between-subject experimental design approaches. The same content would be used across different devices or the same device for different content modifications.\u003c/p\u003e\u003cp\u003eThe paper at hand outlines the significance of customer attitudes towards VR wearables in retail for the intention to reuse VR and the willingness to buy the products displayed. While the relationship between attitudes and the intention to reuse is well established in technology acceptance research, it is not clear how the impact on the willingness to purchase products varies across different retail technologies. We suggest that future research further examine this relationship. Contributing to the research debate concerning whether attitude measures are the conclusive predictors of behavioral intentions, the authors recommend testing additional predictors. In particular, social influence as a normative element in the technology acceptance model is expected to have a major impact on the behavioral intention of the users [\u003cspan citationid=\"CR66\" class=\"CitationRef\"\u003e66\u003c/span\u003e, \u003cspan citationid=\"CR76\" class=\"CitationRef\"\u003e76\u003c/span\u003e].\u003c/p\u003e\u003cp\u003eA vital concern that can be mentioned is the choice of product. It is conceivable that the particularly interactive product display used in the field study especially benefits products with a high need for interaction during the purchase decision process, for example furniture. This idea is in line with research indicating that customers have a higher opinion of more interactive technologies in purchase decisions that involve co-designing products [\u003cspan citationid=\"CR41\" class=\"CitationRef\"\u003e41\u003c/span\u003e]. Therefore, the authors recommend considering the product categories displayed via VR. Defining those product categories might be a future avenue for research. As an example, body fit might be a more critical concern than visual 3D information when buying fashion apparel [\u003cspan citationid=\"CR35\" class=\"CitationRef\"\u003e35\u003c/span\u003e].\u003c/p\u003e\u003cp\u003eFurther, furniture purchases are mainly goal-oriented and thus customers search for performance and goal-oriented information during the shopping process [\u003cspan citationid=\"CR11\" class=\"CitationRef\"\u003e11\u003c/span\u003e]. Consequently, other product categories like cars might increase the relevance of the hedonic value, which requires further analysis. For other utility-oriented product categories like computer hardware and books, the hedonic valuation found in our study might not be applicable at all [\u003cspan citationid=\"CR35\" class=\"CitationRef\"\u003e35\u003c/span\u003e].\u003c/p\u003e\u003cp\u003eConcerning the importance of perceived usefulness for retail technologies, the question arises of whether the characteristics of VR have indeed provoked the shift towards utilitarian evaluations. We suggest that future research conduct a time series analysis to find out if this tendency endures over time.\u003c/p\u003e\u003cp\u003eThe role of hedonic and utilitarian evaluations might also differ across different technologies. A comparison of our findings to study results on AR glasses indicates a higher impotence usefulness. Future studies should further assess these differences using between-subject experimental designs. In such a study, researchers should present the same virtual product metaphor to customers with physical and virtual surroundings. In general, future research could test to what degree the VR-XAM is applicable in assessing customer acceptance for other interactive and immersive technologies.\u003c/p\u003e\u003cp\u003eBesides these findings, this study analyzed past use, curiosity and age as exogenous variables. Considering that age did not have a significant influence on perceived usefulness, we propose future research examine these variables in moderating the effect of perceived playfulness, perceived informativeness, and perceived ease of use on perceived usefulness and attitude. Other models (e.g., UTAUT) have already indicated the moderating effect of these variables [\u003cspan citationid=\"CR77\" class=\"CitationRef\"\u003e77\u003c/span\u003e]. We also suggest including additional exogenous variables and moderators, such as gender, need for touch, and process fluency. Further research might also include the personalization, self-efficacy, perceived risk, immersion, and individual characteristics variables; these were sufficient in explaining customer attitudes and adoption intentions for other interactive technologies, such as augmented reality [\u003cspan citationid=\"CR65\" class=\"CitationRef\"\u003e65\u003c/span\u003e, \u003cspan citationid=\"CR71\" class=\"CitationRef\"\u003e71\u003c/span\u003e, \u003cspan citationid=\"CR82\" class=\"CitationRef\"\u003e82\u003c/span\u003e].\u003c/p\u003e\u003cp\u003eExamining VR glasses in a marketplace with very little penetration of VR wearables allows the literature to survey neutral, unbiased customers to the maximum possible extent. However, the low market penetration limits the data collection to the query of behavioral intention. Considering the growing integration of VR glasses in the retail landscape, future research should test whether the intention precedes the actual behavior. Finally, results from previous research indicated that positive attitudes towards technologies positively influence other important variables, such as customer experience, loyalty, and time spent in a store [\u003cspan citationid=\"CR60\" class=\"CitationRef\"\u003e60\u003c/span\u003e].\u003c/p\u003e\u003c/div\u003e"},{"header":"Declarations","content":"\u003ch2\u003eDecleration of interests\u003c/h2\u003e\n\u003cp\u003eThe authors declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper.\u003c/p\u003e\n\u003ch2\u003eHuman Ethics and Consent to Participate declarations\u003c/h2\u003e\n\u003cp\u003eHuman Ethics and Consent to Participate declarations: not applicable.\u003c/p\u003e\n\u003ch2\u003eFunding Acknowledgements\u003c/h2\u003e\n\u003cp\u003eThis research received no specific grant from any funding agency in the public, commercial, or not-for-profit sectors.\u003c/p\u003e\n\u003ch2\u003eAuthor Contribution\u003c/h2\u003e\n\u003cp\u003eE.H. was responsible for the data analysis. K.L. developed the theory and hypotheses.Both authors were responsible for the study design, collecting data, writing the main manuscript, preparing the figures and reviewing the manuscript.\u003c/p\u003e"},{"header":"References","content":"\u003col\u003e\n\u003cli\u003eAhn, T., Ryu, S., and Han, I. 2004. The impact of the online and offline features on the user acceptance of Internet shopping malls. \u003cem\u003eElectronic Commerce Research and Applications\u003c/em\u003e 3, 4, 405\u0026ndash;420.\u003c/li\u003e\n\u003cli\u003eAhn, T., Ryu, S., and Han, I. 2007. The impact of Web quality and playfulness on user acceptance of online retailing. \u003cem\u003eInformation \u0026amp; Management\u003c/em\u003e 44, 3, 263\u0026ndash;275.\u003c/li\u003e\n\u003cli\u003eBajaja, A. and Nidumolu, S. R. 1998. A feedback model to understand information system usage. \u003cem\u003eInformation \u0026amp; Management\u003c/em\u003e 33, 213\u0026ndash;224.\u003c/li\u003e\n\u003cli\u003eBerg, L. P. and Vance, J. M. 2017. Industry use of virtual reality in product design and manufacturing: a survey. \u003cem\u003eVirtual Reality\u003c/em\u003e 21, 1, 1\u0026ndash;17.\u003c/li\u003e\n\u003cli\u003eBhattacherjee, A. 2001. Understanding Information Systems Continuance: An Expectation-Confirmation Model. \u003cem\u003eMIS Quarterly\u003c/em\u003e 25, 3, 351\u0026ndash;370.\u003c/li\u003e\n\u003cli\u003eBowman, D. A., Kruijff, E., LaViola, J. J., and Poupyrev, I. 2004. \u003cem\u003e3D User Interfaces: Theory and Practice\u003c/em\u003e. Addison Wesley Longman Publishing Co, Redwood City.\u003c/li\u003e\n\u003cli\u003eBozgeyikli, E., Raij, A., Katkoori, S., and Dubey, R. 2016. Point \u0026amp; Teleport Locomotion Technique for Virtual Reality. \u003cem\u003eCHI PLAY \u0026apos;16: Proceedings of the 2016 Annual Symposium on Computer-Human Interaction in Play\u003c/em\u003e, 205\u0026ndash;216.\u003c/li\u003e\n\u003cli\u003eBruner, G. C. and Kumar, A. 2005. Explaining consumer acceptance of handheld Internet devices. \u003cem\u003eJournal of Business Research\u003c/em\u003e 58, 5, 553\u0026ndash;558.\u003c/li\u003e\n\u003cli\u003eCenfetelli, R. T. and Basselier, G. 2009. Interpretation of Formative Measurement in Information System Research. \u003cem\u003eMIS Quarterly\u003c/em\u003e 33, 4, 689\u0026ndash;707.\u003c/li\u003e\n\u003cli\u003eChien, S.-E., Chu, L., Lee, H.-H., Yang, C.-C., Lin, F.-H., Yang, P.-L., Wang, T.-M., and Yeh, S.-L. 2019. Age Difference in Perceived Ease of Use, Curiosity, and Implicit Negative Attitude toward Robots. \u003cem\u003eJ. Hum.-Robot Interact.\u003c/em\u003e 8, 2, 1\u0026ndash;19.\u003c/li\u003e\n\u003cli\u003eChilders, T. L., Carr, C. L., Peck, J., and Carson, S. 2001. Hedonic and utilitarian motivations for online retail shopping behavior. \u003cem\u003eJournal of Retailing\u003c/em\u003e 77, 4, 511\u0026ndash;535.\u003c/li\u003e\n\u003cli\u003eChoi, Y. K. and Totten, J. W. 2012. Self-construal\u0026apos;s role in mobile TV acceptance: Extension of TAM across cultures. \u003cem\u003eJournal of Business Research\u003c/em\u003e 65, 11, 1525\u0026ndash;1533.\u003c/li\u003e\n\u003cli\u003eChoudrie, J., Pheeraphuttranghkoon, S., and Davari, S. 2020. The Digital Divide and Older Adult Population Adoption, Use and Diffusion of Mobile Phones: a Quantitative Study. \u003cem\u003eInf Syst Front\u003c/em\u003e 22, 3, 673\u0026ndash;695.\u003c/li\u003e\n\u003cli\u003eChung, J. and Tan, F. B. 2004. Antecedents of perceived playfulness: an exploratory study on user acceptance of general information-searching websites. \u003cem\u003eInformation \u0026amp; Management\u003c/em\u003e 41, 7, 869\u0026ndash;881.\u003c/li\u003e\n\u003cli\u003eCockton, G., Woolrych, A., and Lavery, D. 2008. Inspections-based Evaluations. In \u003cem\u003eThe Human-Computer Interaction Handbook: Fundamentals, Evolving Technologies and Emerging Applications\u003c/em\u003e, A. Sears and J. A. Jacko, Eds. Taylor and Francis Group, New York.\u003c/li\u003e\n\u003cli\u003eCraighead, C. W., Ketchen, D. J., Dunn, K. S., and Hult, G. T. M. 2011. Addressing Common Method Variance: Guidelines for Survey Research on Information Technology, Operations, and Supply Chain Management. \u003cem\u003eIEEE Trans. Eng. Manage.\u003c/em\u003e 58, 3, 578\u0026ndash;588.\u003c/li\u003e\n\u003cli\u003eCsikszentmihalyi, M. 1975. \u003cem\u003eBeyond boredom and anxiety\u003c/em\u003e. Jossey-Bass, San Francisco.\u003c/li\u003e\n\u003cli\u003eDavis, F. D. 1986. A Technology Acceptance Model for Empirically Testing New End-User Information Systems. Theory and Results. Doctoral Thesis. \u003cem\u003eMassachusetts Institute of Technology\u003c/em\u003e.\u003c/li\u003e\n\u003cli\u003eDavis, F. D. 1989. Perceived Usefulness, Perceived Ease of Use, and User Acceptance of Information Technology. \u003cem\u003eMIS Quarterly\u003c/em\u003e 13, 3, 319\u0026ndash;340.\u003c/li\u003e\n\u003cli\u003eDavis, F. D. 1989. Perceived Usefulness, Perceived Ease of Use, and User Acceptance of Information Technology. \u003cem\u003eMIS Quarterly\u003c/em\u003e 13, 3, 319.\u003c/li\u003e\n\u003cli\u003eDavis, F. D., Bagozzi, R. P., and Warshaw, P. R. 1992. Extrinsic and Intrinsic Motivation to Use Computers in the Workplace1. \u003cem\u003eJournal of Applied Social Psychology\u003c/em\u003e 22, 14, 1111\u0026ndash;1132.\u003c/li\u003e\n\u003cli\u003eDishaw, M. T. and Strong, D. M. 1999. Extending the technology acceptance model with task-technology fit constructs. \u003cem\u003eInformation \u0026amp; Management\u003c/em\u003e 36, 9\u0026ndash;21.\u003c/li\u003e\n\u003cli\u003eDolan, R. J. 2002. Emotion, Cognition, and Behavior. \u003cem\u003eScience\u003c/em\u003e 298, 5596, 1191\u0026ndash;1194.\u003c/li\u003e\n\u003cli\u003eDumas, J. S. and Fox, J. E. 2008. Usability Testing: Current Practice and Future Directions. In \u003cem\u003eThe Human-Computer Interaction Handbook: Fundamentals, Evolving Technologies and Emerging Applications\u003c/em\u003e, A. Sears and J. A. Jacko, Eds. Taylor and Francis Group, New York.\u003c/li\u003e\n\u003cli\u003eFuller, C. M., Simmering, M. J., Atinc, G., Atinc, Y., and Babin, B. J. 2016. Common methods variance detection in business research. \u003cem\u003eJournal of Business Research\u003c/em\u003e 69, 8, 3192\u0026ndash;3198.\u003c/li\u003e\n\u003cli\u003eGuttentag, D. A. 2010. Virtual reality: Applications and implications for tourism. \u003cem\u003eTourism Management\u003c/em\u003e 31, 5, 637\u0026ndash;651.\u003c/li\u003e\n\u003cli\u003eHa, S. and Stoel, L. 2009. Consumer e-shopping acceptance: Antecedents in a technology acceptance model. \u003cem\u003eJournal of Business Research\u003c/em\u003e 62, 5, 565\u0026ndash;571.\u003c/li\u003e\n\u003cli\u003eHair, J. F., Risher, J. J., Sarstedt, M., and Ringle, C. M. 2019. When to use and how to report the results of PLS-SEM. \u003cem\u003eEuropean Business Review\u003c/em\u003e 31, 1, 2\u0026ndash;24.\u003c/li\u003e\n\u003cli\u003eHausman, A. V. and Siekpe, J. S. 2009. The effect of web interface features on consumer online purchase intentions. \u003cem\u003eJournal of Business Research\u003c/em\u003e 62, 1, 5\u0026ndash;13.\u003c/li\u003e\n\u003cli\u003eHenseler, J., Ringle, C. M., and Sarstedt, M. 2015. A new criterion for assessing discriminant validity in variance-based structural equation modeling. \u003cem\u003eJournal of the Academy of Marketing Science\u003c/em\u003e 43, 1, 115\u0026ndash;135.\u003c/li\u003e\n\u003cli\u003eHill, K. M., Fombelle, P. W., and Sirianni, N. J. 2016. Shopping under the influence of curiosity: How retailers use mystery to drive purchase motivation. \u003cem\u003eJournal of Business Research\u003c/em\u003e 69, 3, 1028\u0026ndash;1034.\u003c/li\u003e\n\u003cli\u003eHoldack, E., Lurie-Stoyanov, K., and Fromme, H. F. 2020. The role of perceived enjoyment and perceived informativeness in assessing the acceptance of AR wearables. \u003cem\u003eJournal of Retailing and Consumer Services\u003c/em\u003e, 102259.\u003c/li\u003e\n\u003cli\u003eHuang, T.-L. and Liao, S. 2015. A model of acceptance of augmented-reality interactive technology: the moderating role of cognitive innovativeness. \u003cem\u003eElectron Commer Res\u003c/em\u003e 15, 2, 269\u0026ndash;295.\u003c/li\u003e\n\u003cli\u003eJung, T. and tom Dieck, M. C., Eds. 2018. \u003cem\u003eAugmented Reality and Virtual Reality\u003c/em\u003e. Springer International Publishing, Cham.\u003c/li\u003e\n\u003cli\u003eKang, H. J., Shin, J., and Ponto, K. 2020. How 3D Virtual Reality Stores Can Shape Consumer Purchase Decisions: The Roles of Informativeness and Playfulness. \u003cem\u003eJournal of Interactive Marketing\u003c/em\u003e 49, 3, 70\u0026ndash;85.\u003c/li\u003e\n\u003cli\u003eKarahanna, E., Straub, D. W., and Chervany, N. L. 1999. Information Technology Adoption Across Time: A Cross-Sectional Comparison of Pre-Adoption and Post-Adoption Beliefs. \u003cem\u003eMIS Quarterly\u003c/em\u003e 23, 2, 183\u0026ndash;213.\u003c/li\u003e\n\u003cli\u003eKashdan, T. B., Rose, P., and Fincham, F. D. 2004. Curiosity and exploration: Facilitating positive subjectiveexperiences and personal growth opportunities. \u003cem\u003eJournal of Personality Assessment\u003c/em\u003e 82, 3, 291\u0026ndash;305.\u003c/li\u003e\n\u003cli\u003eKim, J. and Forsythe, S. 2008. Adoption of Virtual Try-on technology for online apparel shopping. \u003cem\u003eJournal of Interactive Marketing\u003c/em\u003e 22, 2, 45\u0026ndash;59.\u003c/li\u003e\n\u003cli\u003eKim, S. S. and Malhotra, N. K. 2005. A Longitudinal Model of Continued IS Use: An Integrative View of Four Mechanisms Underlying Postadoption Phenomena. \u003cem\u003eManagement Science\u003c/em\u003e 51, 5, 741\u0026ndash;755.\u003c/li\u003e\n\u003cli\u003eKoo, D.-M. and Ju, S.-H. 2010. The interactional effects of atmospherics and perceptual curiosity on emotions and online shopping intention. \u003cem\u003eComputers in Human Behavior\u003c/em\u003e 26, 3, 377\u0026ndash;388.\u003c/li\u003e\n\u003cli\u003eLee, H.-H., Fiore, A. M., and Kim, J. 2006. The role of the technology acceptance model inexplaining effects of image interactivity technology on consumer responses. \u003cem\u003eInternationalJournal of Retail and Distribution Management\u003c/em\u003e 34, 8, 621\u0026ndash;644.\u003c/li\u003e\n\u003cli\u003eLee, Y.-K., Park, J.-H., Chung, N., and Blakeney, A. 2012. A unified perspective on the factors influencing usage intention toward mobile financial services. \u003cem\u003eJournal of Business Research\u003c/em\u003e 65, 11, 1590\u0026ndash;1599.\u003c/li\u003e\n\u003cli\u003eLi, T. and Meshkova, Z. 2013. Examining the impact of rich media on consumer willingness to pay in online stores. \u003cem\u003eElectronic Commerce Research and Applications\u003c/em\u003e 12, 6, 449\u0026ndash;461.\u003c/li\u003e\n\u003cli\u003eLiao, C., To, P.-L., Liu, C.-C., Kuo, P.-Y., and Chuang, S.-H. 2011. Factors influencing the intended use of web portals. \u003cem\u003eOnline Information Review\u003c/em\u003e 35, 2, 237\u0026ndash;254.\u003c/li\u003e\n\u003cli\u003eLitman, J. A. 2008. Interest and deprivation factors of epistemic curiosity. \u003cem\u003ePersonality and Individual Differences\u003c/em\u003e 44, 7, 1585\u0026ndash;1595.\u003c/li\u003e\n\u003cli\u003eLitman, J. A. and Spielberger, C. D. 2003. Measuring epistemic curiosity and its diversive and specific components. \u003cem\u003eJournal of Personality Assessment\u003c/em\u003e 80, 1, 75\u0026ndash;86.\u003c/li\u003e\n\u003cli\u003eLoewenstein, G. 1994. The psychology of curiosity: A review and reinterpretation. \u003cem\u003ePsychological Bulletin\u003c/em\u003e 116, 1, 75\u0026ndash;98.\u003c/li\u003e\n\u003cli\u003eManis, K. T. and Choi, D. 2019. The virtual reality hardware acceptance model (VR-HAM): Extending and individuating the technology acceptance model (TAM) for virtual reality hardware. \u003cem\u003eJournal of Business Research\u003c/em\u003e 100, 503\u0026ndash;513.\u003c/li\u003e\n\u003cli\u003eMathwick, C. and Rigdon, E. 2004. Play, Flow, and the Online Search. \u003cem\u003eJournal of Consumer Research\u003c/em\u003e 31, 2, 324\u0026ndash;332.\u003c/li\u003e\n\u003cli\u003eMelenhorst, A.-S., Rogers, W. A., and Caylor, E. C. 2001. The Use of Communication Technologies by Older Adults: Exploring the Benefits from the User\u0026apos;s Perspective. \u003cem\u003ePROCEEDINGS of the HUMAN FACTORS AND ERGONOMICS SOCIETY 45th ANNUAL MEETING-\u003c/em\u003e, 221\u0026ndash;225.\u003c/li\u003e\n\u003cli\u003eMoon, J.-W. and Kim, Y.-G. 2001. Extending the TAM for a World-Wide-Web context. \u003cem\u003eInformation \u0026amp; Management\u003c/em\u003e 38, 217\u0026ndash;230.\u003c/li\u003e\n\u003cli\u003eMorris, M. G. and Venkatesh, V. 2000. Age Differences in Technology Adoption Decisions: Implications for a Changing Work Force. \u003cem\u003ePersonnel Psychology\u003c/em\u003e 53, 375\u0026ndash;403.\u003c/li\u003e\n\u003cli\u003eMuk, A. and Chung, C. 2015. Applying the technology acceptance model in a two-country study of SMS advertising. \u003cem\u003eJournal of Business Research\u003c/em\u003e 68, 1, 1\u0026ndash;6.\u003c/li\u003e\n\u003cli\u003eMullins, J. K. and Sabherwal, R. 2018. Beyond Enjoyment: A Cognitive-Emotional Perspective of Gamification. \u003cem\u003eProceedings of the 51st Hawaii International Conference on System Sciences\u003c/em\u003e, 1237\u0026ndash;1246.\u003c/li\u003e\n\u003cli\u003ePantano, E. and Di Pietro, L. 2012. Understanding Consumer\u0026rsquo;s Acceptance of Technology-Based Innovations in Retailing. \u003cem\u003eJournal of Technology Management \u0026amp; Innovation\u003c/em\u003e 7, 4.\u003c/li\u003e\n\u003cli\u003ePantano, E. and Servidio, R. 2012. Modeling innovative points of sales through virtual and immersive technologies. \u003cem\u003eJournal of Retailing and Consumer Services\u003c/em\u003e 19, 3, 279\u0026ndash;286.\u003c/li\u003e\n\u003cli\u003ePark, M., Im, H., and Kim, D. Y. 2018. Feasibility and user experience of virtual reality fashion stores. \u003cem\u003eFash Text\u003c/em\u003e 5, 1, 1.\u003c/li\u003e\n\u003cli\u003ePavlou, P. A., Liang, H., and Xue, Y. 2007. Understanding and Mitigating Uncertainty in Online Exchange Relationships. \u003cem\u003eMIS Quarterly\u003c/em\u003e 31, 1, 105\u0026ndash;136.\u003c/li\u003e\n\u003cli\u003ePetter, S., Straub, D. W., and Rai, A. 2007. Specifying Formative Constructs in Information System Research. \u003cem\u003eMIS Quarterly\u003c/em\u003e 31, 4, 623\u0026ndash;655.\u003c/li\u003e\n\u003cli\u003ePeukert, C., Pfeiffer, J., Mei\u0026szlig;ner, M., Pfeiffer, T., and Weinhardt, C. 2019. Shopping in Virtual Reality Stores: The Influence of Immersion on System Adoption. \u003cem\u003eJournal of Management Information Systems\u003c/em\u003e 36, 3, 755\u0026ndash;788.\u003c/li\u003e\n\u003cli\u003ePhelps, E. A. 2006. Emotion and Cognition: Insights from Studies of the Human Amygdala 57, 1.\u003c/li\u003e\n\u003cli\u003ePodsakoff, P. M., MacKenzie, S. B., Lee, J.-Y., and Podsakoff, N. P. 2003. Common method Biases in behavioral research: a critical review of the literature and recommended remedies. \u003cem\u003eJournal of Applied Psychology\u003c/em\u003e 88, 5, 879\u0026ndash;903.\u003c/li\u003e\n\u003cli\u003ePodsakoff, P. M. and Organ, D. W. 1986. Self-reports in organizational research: Problems and prospects. \u003cem\u003eJournal of Management\u003c/em\u003e 12, 2, 531\u0026ndash;544.\u003c/li\u003e\n\u003cli\u003ePoushneh, A. 2018. Augmented reality in retail: A trade-off between user\u0026apos;s control of access to personal information and augmentation quality. \u003cem\u003eJournal of Retailing and Consumer Services\u003c/em\u003e 41, 169\u0026ndash;176.\u003c/li\u003e\n\u003cli\u003eRauschnabel, P. A., He, J., and Ro, Y. K. 2018. Antecedents to the adoption of augmented reality smart glasses: A closer look at privacy risks. \u003cem\u003eJournal of Business Research\u003c/em\u003e 92, 374\u0026ndash;384.\u003c/li\u003e\n\u003cli\u003eRauschnabel, P. A. and Ro, Y. K. 2016. Augmented reality smart glasses: an investigation of technology acceptance drivers. \u003cem\u003eInternational Journal of Technology Marketing\u003c/em\u003e 11, 2.\u003c/li\u003e\n\u003cli\u003eRese, A., Baier, D., Geyer-Schulz, A., and Schreiber, S. 2017. How augmented reality apps are accepted by consumers: A comparative analysis using scales and opinions. \u003cem\u003eTechnological Forecasting and Social Change\u003c/em\u003e 124, 306\u0026ndash;319.\u003c/li\u003e\n\u003cli\u003eSager, J. K. and Menon, A. 1994. The Role of Behavioral Intentions in Turnover of Salespeople. \u003cem\u003eJournal of Business Research\u003c/em\u003e 29, 179\u0026ndash;188.\u003c/li\u003e\n\u003cli\u003eSchierz, P. G., Schilke, O., and Wirtz, B. W. 2010. Understanding consumer acceptance of mobile payment services: An empirical analysis. \u003cem\u003eElectronic Commerce Research and Applications\u003c/em\u003e 9, 3, 209\u0026ndash;216.\u003c/li\u003e\n\u003cli\u003eSchreiber, J., Amaury, N., Stage, F. K., Barlow, E. A., and King, J. 2006. Reporting Structural Equation Modeling and Confirmatory Factor Analysis Results: A Review. \u003cem\u003eThe Journal of Educational Research\u003c/em\u003e 99, 6, 323\u0026ndash;337.\u003c/li\u003e\n\u003cli\u003eSmink, A. R., van Reijmersdal, E. A., van Noort, G., and Neijens, P. C. 2020. Shopping in augmented reality: The effects of spatial presence, personalization and intrusiveness on app and brand responses. \u003cem\u003eJournal of Business Research\u003c/em\u003e 118, 474\u0026ndash;485.\u003c/li\u003e\n\u003cli\u003eSpeicher, M., Hell, P., Daiber, F., Simeone, A., and Kr\u0026uuml;ger, A. 2018. A virtual reality shopping experience using the apartment metaphor. \u003cem\u003eProceedings of the International Conference on Advanced Visual Interfaces (AVI-2018)\u003c/em\u003e, 1\u0026ndash;9.\u003c/li\u003e\n\u003cli\u003eSun, H. and Zhang, P. 2008. An exploration of affect factors and their role in user technology acceptance: Mediation and causality. \u003cem\u003eJ. Am. Soc. Inf. Sci.\u003c/em\u003e 59, 8, 1252\u0026ndash;1263.\u003c/li\u003e\n\u003cli\u003eVenkatesh, V. 2000. Determinants of Perceived Ease of Use: Integrating Control, Intrinsic Motivation, and Emotion into the Technology Acceptance Model. \u003cem\u003eInformation Systems Research\u003c/em\u003e 11, 4, 342\u0026ndash;365.\u003c/li\u003e\n\u003cli\u003eVenkatesh, V. and Brown, S. A. 2001. A Longitudinal Investigation of Personal Computers in Homes: Adoption Determinants and Emerging Challenges. \u003cem\u003eMIS Quarterly\u003c/em\u003e 25, 1, 71\u0026ndash;102.\u003c/li\u003e\n\u003cli\u003eVenkatesh, V. and Davis, F. D. 2000. A Theoretical Extension of the Technology Acceptance Model: Four Longitudinal Field Studies. \u003cem\u003eManagement Science\u003c/em\u003e 46, 2, 186\u0026ndash;204.\u003c/li\u003e\n\u003cli\u003eVenkatesh, V., Morris, M. G., Davis, G. B., and Davis, F. D. 2003. User Acceptance of Information Technology: Toward a Unified View. \u003cem\u003eMIS Quarterly\u003c/em\u003e 27, 3, 425\u0026ndash;478.\u003c/li\u003e\n\u003cli\u003eVenkatesh, V., Speier, C., and Morris, M. G. 2002. User Acceptance Enablers in Individual Decision Making About Technology: Toward an Integrated Model. \u003cem\u003eDecision Sciences\u003c/em\u003e 33, 2, 297\u0026ndash;316.\u003c/li\u003e\n\u003cli\u003eViolante, M. G., Vezzetti, E., and Piazzolla, P. 2019. How to design a virtual reality experience that impacts the consumer engagement: the case of the virtual supermarket. \u003cem\u003eInt J Interact Des Manuf\u003c/em\u003e 13, 1, 243\u0026ndash;262.\u003c/li\u003e\n\u003cli\u003eVoorhees, C. M., Brady, M. K., Calantone, R., and Ramirez, E. 2016. Discriminant validity testing in marketing: an analysis, causes for concern, and proposed remedies. \u003cem\u003eJ. of the Acad. Mark. Sci.\u003c/em\u003e 44, 1, 119\u0026ndash;134.\u003c/li\u003e\n\u003cli\u003eYaoyuneyong, G. S., Pollitte, W. A., Foster, J. K., and Flynn, L. R. 2018. Virtual dressing room media, buying intention and mediation. \u003cem\u003eJnl of Res in Interact Mrkting\u003c/em\u003e 12, 1, 125\u0026ndash;144.\u003c/li\u003e\n\u003cli\u003eYim, M. Y.-C. and Park, S.-Y. 2019. \u0026quot;I am not satisfied with my body, so I like augmented reality (AR)\u0026quot; Consumer responses to AR-based product presentations. \u003cem\u003eJournal of Business Research\u003c/em\u003e 100, 581\u0026ndash;589.\u003c/li\u003e\n\u003cli\u003eYong, A. G. and Pearce, S. 2013. A Beginner\u0026rsquo;s Guide to Factor Analysis: Focusing on Exploratory Factor Analysis. \u003cem\u003eTutorials in Quantitative Methods for Psychology\u003c/em\u003e 9, 2, 79\u0026ndash;94.\u003c/li\u003e\n\u003c/ol\u003e"},{"header":"Footnotes","content":"\u003col\u003e\u003cli\u003e\u003cspan\u003e The definition and logic of the perceived informativeness variable is further stressed in Chap.\u0026nbsp;2.4.\u003c/span\u003e\u003c/li\u003e\u003c/ol\u003e"}],"fulltextSource":"","fullText":"","funders":[],"hasAdminPriorityOnWorkflow":false,"hasManuscriptDocX":true,"hasOptedInToPreprint":true,"hasPassedJournalQc":"","hasAnyPriority":false,"hideJournal":true,"highlight":"","institution":"","isAcceptedByJournal":false,"isAuthorSuppliedPdf":false,"isDeskRejected":"","isHiddenFromSearch":false,"isInQc":false,"isInWorkflow":false,"isPdf":false,"isPdfUpToDate":true,"isWithdrawnOrRetracted":false,"journal":{"display":true,"email":"[email protected]","identity":"researchsquare","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":true,"externalIdentity":"","sideBox":"","snPcode":"","submissionUrl":"/submission","title":"Research Square","twitterHandle":"researchsquare","acdcEnabled":true,"dfaEnabled":false,"editorialSystem":"","reportingPortfolio":"","inReviewEnabled":false,"inReviewRevisionsEnabled":true},"keywords":"Virtual Reality (VR), VR glasses, Technology Acceptance Model (TAM), Retail, Informativeness, Playfulness","lastPublishedDoi":"10.21203/rs.3.rs-7101500/v1","lastPublishedDoiUrl":"https://doi.org/10.21203/rs.3.rs-7101500/v1","license":{"name":"CC BY 4.0","url":"https://creativecommons.org/licenses/by/4.0/"},"manuscriptAbstract":"\u003cp\u003eVR glasses are an upcoming trend in retail. However, little is known about customer acceptance of VR experiences. The literature considers acceptance drivers for VR content and hardware separately, despite both elements affecting technology acceptance. This paper extends the existing VR hardware acceptance model by assessing VR content perception. In particular, the resulting VR experience acceptance model (VR-XAM) incorporates perceived informativeness and perceived playfulness into a structural equation model to predict attitude and usage intention towards VR glasses. The results show the outstanding role of utilitarian variables for VR glasses, suggesting that companies should first focus on informative and useful elements when implementing VR experiences into retail landscapes. Furthermore, the study stresses the importance of playfulness as the most important hedonic aspect of customer acceptance for VR in retail. Thus, the paper extends the understanding of technology acceptance and provides useful implications for the development of VR applications in retail.\u003c/p\u003e","manuscriptTitle":"Experiencing virtual reality in retail: Extending the acceptance model for VR hardware towards VR experiences","msid":"","msnumber":"","nonDraftVersions":[{"code":1,"date":"2025-07-24 14:17:59","doi":"10.21203/rs.3.rs-7101500/v1","editorialEvents":[{"type":"communityComments","content":0}],"status":"published","journal":{"display":true,"email":"[email protected]","identity":"researchsquare","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":true,"externalIdentity":"","sideBox":"","snPcode":"","submissionUrl":"/submission","title":"Research Square","twitterHandle":"researchsquare","acdcEnabled":true,"dfaEnabled":false,"editorialSystem":"","reportingPortfolio":"","inReviewEnabled":false,"inReviewRevisionsEnabled":true}}],"origin":"","ownerIdentity":"3e34b656-6f26-43f4-8ca3-1c192a115f8c","owner":[],"postedDate":"July 24th, 2025","published":true,"recentEditorialEvents":[],"rejectedJournal":[],"revision":"","amendment":"","status":"posted","subjectAreas":[],"tags":[],"updatedAt":"2026-03-09T07:42:29+00:00","versionOfRecord":[],"versionCreatedAt":"2025-07-24 14:17:59","video":"","vorDoi":"","vorDoiUrl":"","workflowStages":[]},"version":"v1","identity":"rs-7101500","journalConfig":"researchsquare"},"__N_SSP":true},"page":"/article/[identity]/[[...version]]","query":{"redirect":"/article/rs-7101500","identity":"rs-7101500","version":["v1"]},"buildId":"8U1c8b4HqxoKbykW_rLl7","isFallback":false,"isExperimentalCompile":false,"dynamicIds":[84888],"gssp":true,"scriptLoader":[]}