Next Article in Journal
Synergistic Mechanism of the High-Quality Development of the Urban Digital Economy from Blockchain Adoption Perspective—A Configuration Approach
Previous Article in Journal
The Effect of Digital Orientation and Digital Capability on Digital Transformation of SMEs during the COVID-19 Pandemic
 
 
Font Type:
Arial Georgia Verdana
Font Size:
Aa Aa Aa
Line Spacing:
Column Width:
Background:
Article

Virtual Reality Experience of Mega Sports Events: A Technology Acceptance Study

Sustainable Marketing, Faculty of Economics and Management, University of Kassel, 34125 Kassel, Germany
*
Author to whom correspondence should be addressed.
J. Theor. Appl. Electron. Commer. Res. 2022, 17(2), 686-703; https://0-doi-org.brum.beds.ac.uk/10.3390/jtaer17020036
Submission received: 11 April 2022 / Revised: 12 May 2022 / Accepted: 22 May 2022 / Published: 24 May 2022

Abstract

:
Digitalization has advanced to become an opportunity to spectate sports during the pandemic and its restrictions for traveling to competitions. The purpose of this study is to investigate the antecedents of using virtual reality technology for spectating mega sports events. Based on a literature review, the authors created a model of behavioral intention, built on the unified theory of acceptance and use of technology and technology acceptance model to examine the curiosity and self-construal of spectators. An online survey obtained empirical evidence from 339 sports enthusiasts. The research model was fitted using the partial least squares algorithm. The results show that all the antecedents significantly affected the intention to use a VR device to spectate mega sports events, which explains a significant variance. Surprisingly, influences arising from social norm predominated over those arising from curiosity and the hedonic exploration of VR (enjoyment, and experience). The social norm strongly influences a VR device’s perceived usefulness, implying that people believe using VR will enhance their position in society and that they will thus perceive the technology as being more beneficial. The novelty of this study arises from quantifying the importance of curiosity’s relationship to VR acceptance and pinpointing the relevance of self-construal for VR acceptance.

1. Introduction

Digitization has started to gain ground in modern sports, especially the digitization of spectator experiences [1,2] and the purposeful design of experiential spaces and websites [3,4] offers new opportunities in sports marketing [5]. Virtual reality (VR) is one of the technologies shifting the role of digitalization “from being a driver of marginal efficiency to an enabler of fundamental innovation and disruption” [6] (p. 83).
The reality–virtuality continuum [7] has been the starting point for researchers to classify realities in four classes [8]: real environment, augmented reality, augmented virtuality and virtual environment. The real environment encompassing the reality itself, including direct or indirect (via displays) views of a scene, represents the one extreme of the continuum. The virtual environment represents the other extreme. Here the environment is entirely computer generated, and the objects actually do not exist. In between is the technology-mediated-mixed reality with a wide variety of augmented reality, such as additional information on the mobile phone or augmented virtuality such as the videogame Pokémon Go [9]. Flavián et al. [8] extended the taxonomy by incorporating pure mixed reality, where users are placed in the real world with totally integrated digital content to their surroundings. Pure mixed reality allows users to interact with digital and real-world content, and these elements can also interact with each other.
The market for VR technology is growing with its rapid development [10,11]. With the emergence of affordable, consumer-ready VR headsets for gaming and entertainment, VR offers new entertainment applications. The technology provides opportunities for spectators to use VR devices to feel as though they are physically attending an event while enjoying it at home or to experience competition from the perspective of athletes. Researchers highlight the impact of VR experience on affective responses and attitude toward a winter sport—luge [1]. In doing so, they establish a new form of sports experience. The opportunity to use various technologies to follow mega sports events emerged during the 2018 Olympic Games in Pyeongchang. So far, little research has focused on experiences enhanced by VR devices in the context of sporting events [1,6,12].
VR environments stimulate users, who are immersed to the extent that they feel “being there” [13]. There is a narrow understanding of virtual environments as settings for brand-enabled relationships [14]. However, VR and also augmented reality applications and potential can be substantially different. The theory of technological mediation [15] aims to explain human–technology mediation processes. Here, embodiment is a state in which technological devices mediate users’ experiences. Devices become intertwined with users and allow them to perceive, interpret and interact with their immediate environment [16]. Technologies range from no or minimum embodiment to fully integrated devices [17]. With the embodiment–presence–interactivity cube (EPI Cube; [8]), this taxonomy is developed further, enabling understanding of technological embodiment as the degree of contact between the device and the human senses. Stationary external devices (e.g., desktop computers) represent the lowest level of technological embodiment, as they are detached from the body. Portable devices such as smartphones are in the medium-low part of the continuum, and wearables such as VR headsets have a medium-high position, as they are more physically integrated with the users’ bodies. When the technology and the human body are abundantly integrated (e.g., smart contact lenses), forming the same entity, the maximum level of the technological embodiment is achieved [16].
In the last few years, the creation of content and industry applications has become critical. Services share attributes, such as intangibility, heterogeneity, and inseparability of production and consumption [18]. Additionally, 360-degree videos have the potential to even resemble real-life experiences [19] and have become more and more popular among customers [20]. Compared to desktop computers and mobile phones, virtual reality devices evoke more positive emotional reactions and higher levels of psychological and behavioral engagement [17]. These results derived in the context of hospitality management [18,20] might be transferable to spectating mega sports events because both industries have comparable characteristics of being service based and experiential in nature, with the impossibility to experience in advance [8].
VR’s applications and their potentials have been studied in various non-sports contexts, such as tourism and hospitality [18,21,22,23], theme parks [21], aeronautics [24], shopping [25,26], learning [27], gaming [28,29], and clinical settings [30]. Given the potential importance of these technologies, researchers and practitioners need to better understand how consumers respond to experiences in order to effectively address current trends and develop valuable proposals [18]. In this line, previous research lacks insights into why people intend to use VR in specific situations [9]. Notably, research has stressed the relevance of investigating curiosity concerning VR acceptance [31] and highlighted the influence of self-construal when studying the acceptance of new technology [32]. The current study provides valuable insights into consumers’ adoption of VR for spectating mega sports events. Specifically, we draw from the unified theory of acceptance and use of technology (UTAUT) to build a broad intention model that captures the cognitive-, social-, and personality-related influences that affect the use of VR. Evaluating evidence provided by 339 respondents, we aimed to answer the research question of whether spectator’s curiosity or the fulfilment of an expectation mainly drives the adoption of VR technology to spectate mega sports events.
To address this question, we complement technology acceptance model 3 (TAM3) and the unified theory of acceptance and use of technology 2 (UTAUT2) by considering curiosity and the components of construal level theory. Construal level theory provides insights that explain the relationship between an individual’s abstract or concrete thinking and psychological distance [33,34].
This study contributes to the scholarly discussion by highlighting the relevance of social- and personality-related drivers. From a manager’s point of view, the findings are relevant because the conception of a marketing campaign differs depending on whether the social norm or joy and fun elements are more important in explaining the spectators’ intention to use.
The research is reported as follows: first, the theoretical framing is described along with the deviation between the research hypotheses and the model; next, the methodology and the data analysis are provided; lastly, the contributions are outlined.

2. Related Research and Conceptual Model

2.1. VR and Its Application for Media Consumption in Mega Sports Events

Contemporary VR usually involves head-mounted displays that allow users to immerse themselves in a virtual world by blocking out the real world [35]. The VR user can interact with a simulated environment [36].
Following [37], VR research focuses on two distinct areas: (i) the technology itself and (ii) the user’s viewpoint. The latter focus examines the user experience of VR and, therefore, the primary determinants of expectations, the experience itself, and the post hoc evaluation of being immersed in the artificial environment [1,31,38].
Concerns about the affordability of VR have been resolved, as people and industries willing to buy VR devices use the technology at an affordable cost [35,39]. Hartl and Berger [37] stress that the emergence of VR glasses transformed VR into a more advanced technology, which started to be cost effective and involve human senses [40], making it suitable for the mass market. VR is used in sports to give spectators the experience of a great view [12].
VR has significant relevance as a medium that enables athletes to improve their performance while training [41,42,43], allowing them to analyze what they do while exercising and consider possible improvements [44]. Little research, however, has considered the spectators’ perspective of using VR in the context of mega sports events [45] beyond the examples of the National Basketball Association and the National Football League [12]. In conclusion, VR offers more intense experiences than just watching TV.

2.2. Technology Acceptance of VR for Spectating Mega Sports Events

The TAM is the framing most suited to this study [46], as it evaluates the acceptance of a specific technology (in this case, VR) and can be adapted to various fields and situations [47,48]. The TAM3 was adopted for our research design to study the acceptance of VR regarding perceived usefulness, the subjective norm, image, perceived ease of use, perceived enjoyment, usage attitude, intention to use, and experience [49,50,51]. Components of other theories have enriched the TAM model to strengthen its explanatory power.
Previous research has successfully integrated the literature on curiosity with TAM [31,52,53,54]. Curiosity is defined as the degree to which individuals are willing to increase their knowledge about the innovation to understand as many things as possible. Furthermore, the price value derived from UTAUT2 is interesting in the context of the consumption of mega sports events, as it reflects a technology user’s trade-off between the benefit of a given technology and the monetary cost of using it [44]. It provides evidence of whether spectating mega sports events through VR is a potentially profitable market.
In mega sports events, emotions and enjoyment usually play a central role in consumption [55,56,57]. Therefore, it is crucial to apply construal level theory in the context of the acceptance of VR for consuming mega sports events. Previous research [32,58,59] has already combined construal level theory with TAM to understand the role of emotions and enjoyment when using a specific technology.
Construal level theory provides insights into the relationship between the individual’s abstract or concrete thinking and the psychological distance between the object and the individual [33,60]. This distance can be of four distinct dimensions [58,59]: spatial (here or there), temporal (near or distant future), social (in-group or alone, self or other), and hypothetical (certainty or uncertainty). The closer an arbitrary object or incidence is, the more the individual’s thinking about it will be concrete and the greater the fun of spectating the event. However, this boost of fun and excitement will be the opposite resulting in frustration if technical challenges thwart the spectator. Choi and Totten [32] have already provided evidence of the relevance of (expected) self-construal to technology acceptance. Building upon Kuhnen’s work [45], they argue that self-construal positively influences the use of mobile TV technologies.

3. Research Hypotheses

This study contributes to the recent stream of adoption studies developed in the context of other technologies that are currently in the process of implementation, such as artificial intelligence [61,62,63], e-wallets [64] or online streaming services [65]. In the context of VR acceptance in the context of sports, the initial TAM hypotheses have been verified in various studies [6,27,30,37,66,67,68].

3.1. Subjective Norm

Subjective norm has been defined as “a person’s perception that most people who are important to him think he should or should not perform the behavior in question” [69] (p. 90). Previous research [51] highlighted that the subjective norm positively influences the individual’s image, in this case the spectator’s image. This influence comes from relevant members of the user’s social group, who impact the user and his or her decision to use the technology, which elevates the user’s position within the group [70,71,72]. Therefore, the following hypothesis is proposed:
Hypothesis 1a (H1a).
The subjective norm positively affects the spectator’s image.
In the same study, Venkatesh and Davis [51] support the idea that the social norm positively influences the perceived usefulness of innovative technology. Indeed, following the earlier work [73,74,75,76,77] suggests that identification affects the subjective norm concerning the user’s perception of the usefulness of the technology, already well-established in previous research [50,78,79,80]. Therefore, a second hypothesis regarding the subjective norm is proposed:
Hypothesis 1b (H1b).
The subjective norm has positive effects on perceived usefulness.
Enlarging the TAM [51] points out the influence of the subjective norm on image and perceived usefulness but also suggests that the subjective norm affects the intention to use. Previous research [62,81,82] indicated subjective norms to root in interpersonal sources and external sources of information. In line with previous research [61] on technology-based innovations, this demonstrates how the opinion of society affects the individuals’ behavior. Therefore, the following hypothesis is proposed:
Hypothesis 1c (H1c).
The subjective norm has positive effects on intention to use.

3.2. Image

The reasoning applied to the impact of the subjective norm on the image also applies to the spectators’ image itself, which positively affects the perceived usefulness of a technology. Indeed, the status, and therefore the image, of individuals within a group enhances their opinions on a topic within the same group [51]; if a high-status person in the group perceives VR as valuable, that person’s image will positively affect the perceived usefulness of VR within the group. This gives rise to the second research hypothesis:
Hypothesis 2 (H2).
Image positively affects perceived usefulness.

3.3. Output Quality

The output quality is defined as “over and above considerations of what tasks a system is capable of performing and the degree to which those tasks match their job goals (job relevance), people will take into consideration how well the system performs those tasks” [51] (p. 191).
TAM measures the output quality [83,84], stressing that output quality positively influences users’ propensity to adopt certain technologies. Therefore, this hypothesis of the model aims to study whether, contrasting to the original TAM, the output quality directly affects the usage attitude instead of the perceived usefulness.
Hypothesis 3 (H3).
Output quality positively affects usage attitude.

3.4. Perceived Enjoyment

Lee [29] presents evidence of perceived enjoyment’s effects on perceived ease of use. Moreover, other studies [48,80,85] underline the fact that enjoyment plays a crucial role in analyzing the acceptance of VR; indeed, entertainment devices that are diverting for users have been proven to have positive effects on the perceived ease of use of the technology. Consequently, the fourth hypothesis is proposed:
Hypothesis 4 (H4).
Perceived enjoyment of a VR device positively affects perceived ease of use.

3.5. Perceived Ease of Use

Perceived ease of use is not only affected by other constructs, but also influences other variables. Consequently, Sagnier [24] underlines the positive effects that the perceived ease of use has on the perceived usefulness of VR, basing that hypothesis on the study of Davis [49] and confirming it using the computations of King and He [86]. Moreover, the same work [24] presents evidence of such an influence [79,87,88,89]. To strengthen the underpinning of this relationship, Venkatesh and Davis [51] add a further explanation: the more accessible a technology is and the more effortless it is to use, the more valuable it will be perceived to be (taking all the other variables as constant). This inspires the following hypothesis:
Hypothesis 5a (H5a).
The perceived ease of use of a VR device positively affects perceived usefulness.
Further investigating the influence that a technology’s perceived ease of use has on other constructs of the model, [90] affirms that innovative technology is likely to be accepted if it is perceived as easy to use, which creates a positive attitude in the consumer. The same hypothesis was formulated by previous researchers [32,62,65]. Therefore, the following hypothesis is proposed:
Hypothesis 5b (H5b).
The perceived ease of use of a VR device positively affects usage attitude.

3.6. Perceived Usefulness

Wallace and Sheetz [74] apply similar reasoning to perceived usefulness as was mentioned in regard to perceived ease of use: an innovative technology that is perceived as useful creates a positive attitude among consumers. Based on previous studies [62,64] findings, perceived usefulness positively and significantly influences consumer’s attitude.
A valuable technology is more suitable for use, which inspires a positive attitude toward the technology itself. The sixth research hypothesis is based on this evidence:
Hypothesis 6 (H6).
The perceived usefulness of a VR device positively affects usage attitude.

3.7. Usage Attitude

The development of the following hypothesis begins with previous research [62], investigating usage attitudes toward a technology. An earlier study of VR acceptance [29] clearly found that user attitude toward the use of a technology positively influences the intention to use it. Adapting the well-established TAM relationships, the following hypothesis is proposed:
Hypothesis 7 (H7).
Usage attitude toward a VR device positively affects intention to use.

3.8. Experience

Venkatesh and Bala [50] discovered a link between the one-time use of a technology and its perceived enjoyment: users who have already experienced the use of the technology perceive it as more entertaining than those who have never tried it. This inspires the following hypothesis:
Hypothesis 8a (H8a).
Experience has positive effects on perceived enjoyment.
Moreover, [50] underlines the relevance of experience in relation to perceived ease of use; people who use a technology more strongly perceive it to be more straightforward to use than those who are trying the technology for the first time. Accordingly, the following hypothesis is proposed:
Hypothesis 8b (H8b).
Experience positively affects perceived ease of use.

3.9. Price Value

Price value is a relevant variable affecting usage attitude. In the second version of UTAUT, this construct positively affects the usage attitude toward the technology investigated in the model [54]. Therefore, the ninth hypothesis is as follows:
Hypothesis 9 (H9).
Price value positively affects usage attitude.

3.10. Curiosity

Curiosity affects perceived ease of use [31]. The current research aims to understand whether curiosity affects the usage attitude in addition to perceived ease of use. Thus, the following hypothesis is proposed:
Hypothesis 10a (H10a).
Curiosity positively affects usage attitude.
Research underlines that people who seem to be more curious by nature are more motivated to try new technology [31], inspiring the following hypothesis:
Hypothesis 10b (H10b).
Curiosity positively affects intention to use.

3.11. Self-Construal

The final hypothesis derived from construal level theory in this study focuses on the importance of self-construal. This considers the self as a dynamic creation in which an individual’s self-views, emotions, and motivations form a consistent structure of preferences, convictions, and goals [34,91,92]. Clearly, using VR technology can support the individual by reducing the distance to athletes in mega sport events, allowing the user to become immersed in the event rather than merely being an external spectator [76]. Therefore, the last hypothesis is as follows:
Hypothesis 11 (H11).
Self-construal positively affects intention to use.
Based on the previous research discussed above, we developed the research model in Figure 1 to examine VR acceptance in the consumption of mega sports events.

4. Materials, Methods, and Data

Data Gathering

To obtain empirical evidence, an online survey was developed in English. After pretesting, it was translated to and backtranslated from Italian. The survey was spread in Italian and English via social media in a purposive sampling procedure. The target population, interested in spectating sports events (on-site or digital), is unknown, but we assume that individuals who are practicing sports activities by themselves have a higher interest to spectate sports events. In general, younger people are more likely to practice sport activities than older ones. Moreover, young people might score higher in curiosity with respect to digital innovation. Young consumers become familiar with innovative devices easily [63], as they have grown up in a world of digitization in various domains including sports (e.g., goal line technology or video referee in soccer). To meet the sampling advice of [93], the target respondents qualified by being sports enthusiasts who were active members of clubs or teams, by having a particular interest in the Olympic disciplines, or by having previously virtually attended the Olympic Games. The prior experience of participants was validated by means of self-reports. Consolidating the criteria applied ensured that the respondents were sampled from the target population. The questionnaire was distributed online through sports clubs, university sports centers, and sporting events. Respondents were not incentivized, but participated due to their intrinsic motivation and curiosity for new sport spectating experience. All questions of the survey were measured through a 7-point Likert scale. The online questionnaire also includes a video that provides an example for VR, a video produced during the 2018 Winter Olympic Games. To ensure a common understanding, participants were given an explanation of VR as well as an exemplary video. The respondents could not progress in answering the questionnaire without watching the video.
The sample includes 348 responses. Following [94], nine replies were deleted due to incomplete and inconsistent responses.
As shown in Table 1, a target group of young sports enthusiasts was recruited. The sample embraces a substantial variety of disciplines, so we expected it to provide us with valid, reliable information to answer the research question of whether curiosity or the fulfilment of an expectation is the main driver for adopting VR technology to spectate mega sports events.

5. Results

The results described in this section were obtained by applying the consistent partial least squares (PLS) procedure [95,96] in SmartPLS version 3.3.3 [97]. PLS fitting is well established and very prominent in technology acceptance analysis [98,99].

5.1. Reliability and Validity Assessment

Table 2 presents the outer loadings, Cronbach’s alpha, Rho_A, CR, and AVE. The measurement specifications of all the constructs met the common quality standards. Hair [83] points out that outer loadings should not be higher than 0.950 to avoid redundancy, which could compromise the items’ validity. As shown in Table 2, none of the values exceeds that limit. We conducted the Harman–Test for assessing the common method variance. The result of 0.318 of common variance is far below the threshold of 0.5.
The overall model fit confirms the above conceptual reasoning with an SRMR of 0.043. Hu and Bentler [104] affirm that a good SRMR value should be lower than 0.080. The chi-square/degrees of freedom ratio is 3.49, far below the threshold of 5.00, providing evidence to substantially explain the models’ response patterns. Discriminant validity is established by the Fornell–Larcker criterion and the heterotrait–monotrait ratio (HTMT) in Table 3.

5.2. Inner Model and Hypotheses Evaluation

The variance explained by the R2 of the model’s endogenous constructs exceeds the 0.5 threshold. The Q2 values are all strongly predictive as is the f2 value shown in Table 4 Furthermore, we tested the characteristics of gender, age, education, and income for structural differences with the multi-group analysis [105]. The results do not indicate meaningful differences among distinct groups. The results in Table 4 clarify that VR is likely to be adopted by the spectator when relevant peers have (or are assumed to have) a favorable opinion of the technology so that adopting VR elevates the spectator’s position within the peer group. Obviously, status maintenance substantially impacts perceived usefulness (hypotheses H1a, H1b, and H2). These results support the previous studies’ findings [51,80], revealing the relationships between subjective norm, image, perceived usefulness, and intention to use.
Our results highlight the equally strong influence of perceived enjoyment (H4) and experience (H8b) on perceived ease of use. This result supports that of previous research [29,31,50] affirms this ease-of-use relationship for other technologies. In line with [106], our study highlights the importance of experience. When spectators have previous experience of using VR, they perceive watching sports with such a device as more entertaining (H8a). Therefore, regarding technologies in general [107,108] and specifically in the context of VR [31,80], perceived ease of use positively influences the perceived usefulness for spectating mega sports events (H5a). In general, it can be stated that the intention to use VR technology increases with knowledge about the devices. Expanded knowledge reduces.
Perceived usefulness (H6) and perceived ease of use (H5b) positively influence usage attitude. These findings are in line with previous research [108] in a general technological context and, specifically, in the context of VR [31,80]. This study’s finding of a positive effect of usage attitude on intention to use supports what was previously found for technologies in general [32,108] and specifically for VR [80,106]. Price value (H9) and curiosity (H10a) positively influence usage attitude, but technical output quality (H3) plays a more substantial role in explaining usage attitude than the social, personality, economic, and skill-related constructs mentioned earlier.
Attitude toward using the technology positively influences the intention to use a VR device to watch the next Olympics (H7) to the same extent that curiosity (H10b) influences this intention to use. The results indicate that spectators are twice as likely to use VR when they perceive that VR is viewed favorably in their group and that using it will improve their position in the group (H1c) and when spectators perceive that the technology is close to them, not something far from their lives (H11).

6. Conclusions and Discussion

6.1. Scholarly Contributions

Digital spectating of sport events has been propelled by the COVID-19 pandemic due to real world restrictions. Previous research in other domains of digitalization [17] indicated that the technology by itself could be a value proposition. Therefore, this study challenges the drivers of spectators’ intention to use VR technologies for leveraging their experiences of mega sport events and quantifies the relevance of barriers.
This study clearly answers the research question of whether curiosity or the fulfilment of an expectation is the main driver for adopting VR technology to spectate mega sports events. Consolidating the results, we conclude that spectators’ curiosity is a relevant and substantial diver of the usage intention, but subjective norm and self-construal turned out to have a stronger impact. Curiosity, perceived enjoyment together with experience explain substantial parts of the variance in intention to use. The users’ intention to use increases when spectators take advantage of VR technology. The self is a dynamic cultural creation, with individuals’ self-views, emotions, and motivations taking shape and forming within a framework provided by cultural values, ideals, structures, and practices [91]. As conceptualized, the level of construal as a mental representation is invoked by distance rather than representing a distance [73], and VR is thought to bridge the athlete–spectator distance.
Spectators tend to adopt VR technologies because of extrinsic motivations: they meet their presumed social norms and use the technology for self-construal to impress others. This result aligns with previous research emphasizing the relevance of social norms for the adaption of disruptive technologies [62]. An important contribution is the relevance of the self-construal that has been rarely considered in previous technology adaption studies. Mapping of the results to the EPI Cube taxonomy [8] indicates the importance of self-construal for the adoption of immersive technologies. This study contributes the first empirical result in the medium–high spectrum of the taxonomy and aligns well with the scarce empirical research obtained in the medium–low spectrum [32].
Intrinsically motivated antecedents of using VR technologies turned out to have a substantial and statistically significant impact. However, the curiosity of spectators and the usage attitude are inferior compared to the extrinsic motivators. Putting this finding in the context of previous research [65,109], it becomes obvious that positive emotions, such as enjoyment or emotional gratification, are antecedents for explaining the intention to use in the context of digital services (either streaming or, as here, the usage of VR technology to spectate mega sports events).
The surprising dominance of the extrinsic motivators calls for further research in a later point in the technology cycle when the VR immersion is adopted by broader segments and, therefore, is less significant for self-construal purposes. Particularly of interest will be a possible change in the relevance of the subjective norm as a driver of the intention to use VR for spectating mega sports events when relevant peers have (or are assumed to have) a favorable opinion of the technology so that using it elevates the spectator’s position within the peer group.
Recent research prompts maintaining a sound fit between theory and the real-world setting when going from theory to phenomenon [110]. This study contributes to closing two gaps in the research: first by discovering the importance of curiosity’s relationship to the acceptance of VR [31] and second by finding the importance of self-construal in relation to the acceptance of new technology [32].

6.2. Practical Contributions

The implementation of this innovative technology enhances the whole experience of spectating mega sports events, allowing a more realistic and involving view of sports for the audience. This study indicates that it is essential for marketers to ensure that sport spectators can perceive value for using the VR technology according to their self-construal. Self-construal and social value turned out to be more important than intrinsic motivators were. Concretely, marketers could facilitate extrinsic assets by implementing engagement campaigns by uploading screenshots, videos or other materials in social media. Using VR technology provides a unique spectatorship experience; allowing the audience to attend mega sports events as members of the public or as athletes competing in the Olympic Games are practical means for adding value. VR devices heighten spectators’ experiences by showing extra material, such as the athletes’ training, their warm-up, and the Olympic Village experience, feeling like an athlete and presenting a “behind the scenes” view of the event to the public. Allowing the audience to live the mega sports event from the inside could attract more people and increase awareness of the efforts of both the athletes and the organization.
Studying the acceptance of VR helps managers to develop a communication strategy [84,85]. Recent research prompts scholars to connect to real-world examples and trends [110]. This is met by this study, as VR spectatorship is becoming increasingly relevant [12], so companies associated with the sports world, media, and entertainment need to follow this trend. This study suggests the bases for understanding the characteristics of spectators who follow this trend; the findings can be exploited in a company’s existing practices or can be a starting point for market analysis that understands the most relevant aspects for VR users or potential users.
Furthermore, promotional campaigns related to the sports market or mega sports events benefit from these findings: focusing on entertainment and fun through VR will increase the attraction of sport enthusiasts. From the sponsors’ perspective, it is an additional opportunity to display and highlight their brand, as the spectators have additional perspectives compared to on-site experience or watching on traditional displays. When companies understand the importance of specific VR characteristics, they can adapt their communication strategies and products accordingly. For instance, Nike focusing substantially on customers’ experience can benefit from the findings of this study: their branding can take advantage of VR, knowing that it is perceived positively by its consumers, to communicate its messages and to attract new people facilitated by borrowed attention. A spot that can be seen only through VR will provide a more realistic feeling of what being an athlete means. Installing VR inside the company’s stores provides a unique shopping experience. Among other factors, this study concretely shows the impact of the output quality on user attitude toward the use of VR; consequently, improving the image, video, and sound of VR will inspire an optimistic consumer attitude and a greater willingness to pay for and use VR.

6.3. Social Implications

Companies and organizational institutions are not the only parties benefitting from the use of VR in mega sports events. In fact, this research provides implications also for individuals: spectators, athletes, trainers and amateurs are some of them.
The mega sports event acquires a new value thanks to the implementation of VR: the event becomes a real-life experience in which the person can be immersed, living the competition from the athlete’s perspective, and gaining insights that could not be found otherwise. Moreover, the COVID-19 pandemic has affected the spectatorship of the mega sports event, limiting the audience to attend and enjoy the different sports events—resulting in a loss in the interest toward the mega sports event itself and generally, toward the different disciplines, which have a limited attraction power due to this lack of audience. Therefore, implementing VR in the Olympic Games following the findings presented in this study may prevent the decrease in the attractiveness of the event and of the different sports presented there since the audience could be able to attend the various competitions simply from home using a VR device.
Going further, using a VR device is less expensive than travelling to the events and spectating them on site. This contributes to a democratization of mega-sports events, providing a special experience to fans with a lower budget. Selling virtual tickets is a new opportunity to generate additional profits without investing in the physical stadium building. This might be equalizing the difference between affluent and emerging societies in organizing mega sports events.

6.4. Limitations and Future Research

In light of our research design and findings, we wish to discuss some limitations and how future research may address them. One limitation of our study arises from the question of whether the results are valid for other entertainment applications. So far, it is unclear whether the results are transferable, so further research is merited to examine how to exploit the intrinsic curiosity, joyfulness, and playfulness of users’ motivations. Furthermore, positive emotions, engagement, relationships, meaning, and accomplishment [56] should be evaluated with respect to their change due to the adoption of VR technologies in the spectating process. Perceived social norms are a relatively weak basis for advancing VR technology in the leisure sector, as they are relatively unstable and change over time.
As our findings highlight, variance for the intention to use is in substantial part explained by constructs (curiosity, experience, and perceived enjoyment), which can be related to hedonism. This relation could be validated and extended by future research. Considering the motivations of the target group by itself, potential limitations arise from the predominance of young respondents, mainly from Italy. This is due to the fact that the questionnaire was spread on social media, starting from an Italian account. However, group testing by countries did not result in significant differences.
Future research could consider three perspectives for implementing VR. On the one hand, users could feel like spectators in the stadium and participate as fans. On the other hand, they could participate from an athlete’s perspective. Here, it is crucial to consider the viewpoints of the athletes as well. From a marketing perspective, both the content and positioning of advertising would differ according to the spectators’ perspective. In the future, advertisers are more likely to customize advertisements to the spectator’s profile.
Third, considering the importance of social interactions in the course of spectating sports events [55,111], a technical advancement of the VR technology enabled by the projection of avatars to the virtual space enriches the experience. This way, friends could also meet virtually to experience the sporting event.
Furthermore, media multitasking and multiscreening with its impact on willingness to use VR devices could be considered in future research.
In fact, virtual reality experiences frequently are limited to the senses of sight and hearing. Notably, recent research [112] addresses the inclusion of pleasant smells congruent with the experience, which turns out to have a positive effect on users’ perceptions.

Author Contributions

All authors contributed equally. All authors have read and agreed to the published version of the manuscript.

Funding

This research received no external funding.

Institutional Review Board Statement

Ethical review and approval were waived for this study, but the regulations of the University of Kassel, the regulations of the federal state of Hessia, the German data protection regulations and the declaration of Helsinki were met.

Informed Consent Statement

Informed consent was obtained from all subjects involved in the study.

Data Availability Statement

Available upon request.

Conflicts of Interest

There are no conflict of interest.

References

  1. Uhm, J.P.; Lee, H.W.; Han, J.W. Creating sense of presence in a virtual reality experience: Impact on neurophysiological arousal and attitude towards a winter sport. Sport Manag. Rev. 2020, 23, 588–600. [Google Scholar] [CrossRef]
  2. Xu, Z.; Gonzalez-Serrano, M.H.; Porreca, R.; Jones, P. Innovative sports-embedded gambling promotion: A study of spectators’ enjoyment and gambling intention during XFL games. J. Bus. Res. 2021, 131, 206–216. [Google Scholar] [CrossRef]
  3. Daries, N.; Cristobal-Fransi, E.; Ferrer-Rosell, B. Implementation of Website Marketing Strategies in Sports Tourism: Analysis of the Online Presence and E-Commerce of Golf Courses. J. Theor. Appl. Electron. Commer. Res. 2021, 16, 542–561. [Google Scholar] [CrossRef]
  4. Gillooly, L.; Crowther, P.; Medway, D. Experiential sponsorship activation at a sports mega-event: The case of Cisco at London 2012. Sports Bus. Manag. 2017, 7, 404–425. [Google Scholar] [CrossRef] [Green Version]
  5. Alonso-Dos-Santos, M.; Moreno, F.C.; Ríos, F.M.; Alguacil, M. Online Sport Event Consumers: Attitude, E-Quality and E-Satisfaction. J. Theor. Appl. Electron. Commer. Res. 2017, 12, 54–70. [Google Scholar] [CrossRef] [Green Version]
  6. Kunz, R.E.; Santomier, J.P. Sport content and virtual reality technology acceptance. Sports Bus. Manag. 2020, 10, 88–103. [Google Scholar] [CrossRef]
  7. Milgram, P.; Kishino, F. A taxonomy of mixed reality visual displays. IEICE TRANS. Inf. Syst. 1994, 77, 1321–1329. [Google Scholar]
  8. Flavián, C.; Ibáñez-Sánchez, S.; Orús, C. The impact of virtual, augmented and mixed reality technologies on the customer experience. J. Bus. Res. 2019, 100, 547–560. [Google Scholar] [CrossRef]
  9. Rauschnabel, P.A. Virtually enhancing the real world with holograms: An exploration of expected gratifications of using augmented reality smart glasses. Psych. Mark. 2018, 35, 557–572. [Google Scholar] [CrossRef]
  10. Lo, W.H.; Cheng, K.L.B. Does virtual reality attract visitors? The mediating effect of presence on consumer response in virtual reality tourism advertising. Inf. Technol. Tour. 2020, 22, 537–562. [Google Scholar] [CrossRef]
  11. Lui, T.W. Augmented reality and virtual reality: Changing realities in a dynamic world. Inf. Technol. Tour. 2021, 23, 637–639. [Google Scholar] [CrossRef]
  12. Kim, D.; Ko, Y.J. The impact of virtual reality (VR) technology on sport spectators’ flow experience and satisfaction. Comput. Hum. Behav. 2019, 93, 346–356. [Google Scholar] [CrossRef]
  13. Bowman, D.A.; McMahan, R.P. Virtual reality: How much immersion is enough? Computer 2007, 40, 36–43. [Google Scholar] [CrossRef]
  14. Veloutsou, C.; Mafe, C.R. Brands as relationship builders in the virtual world: A bibliometric analysis. Electron. Commer. Res. Appl. 2020, 39, 100901. [Google Scholar] [CrossRef]
  15. Ihde, D. Technology and the Lifeworld: From Garden to Earth; Indiana University Press: Bloomington, IN, USA, 1990. [Google Scholar]
  16. Tussyadiah, I.P.; Jung, T.H.; tom Dieck, M.C. Embodiment of wearable augmented reality technology in tourism experiences. J. Tr. Res. 2017, 57, 597–611. [Google Scholar] [CrossRef] [Green Version]
  17. Flavián, C.; Ibáñez-Sánchez, S.; Orús, C. Impacts of technological embodiment through virtual reality on potential guests’ emotions and engagement. J. Hosp. Mark. Manag. 2021, 30, 1–20. [Google Scholar] [CrossRef]
  18. Orús, C.; Ibáñez-Sánchez, S.; Flavián, C. Enhancing the customer experience with virtual and augmented reality: The impact of content and device type. I. J. Hosp. Mark. Manag. 2021, 98, 103019. [Google Scholar] [CrossRef]
  19. Wagler, A.; Hanus, M.D. Comparing virtual reality tourism to real-life experience: Effects of presence and engagement on attitude and enjoyment. Commun. Res. Rep. 2018, 35, 456–464. [Google Scholar] [CrossRef]
  20. Martínez-Navarro, J.; Bign’e, E.; Guixeres, J.; Alcãniz, M.; Torrecilla, C. The influence of virtual reality in e-commerce. J. Bus. Res. 2019, 100, 475–482. [Google Scholar] [CrossRef]
  21. Wei, W. Research progress on virtual reality (VR) and augmented reality (AR) in tourism and hospitality: A critical review of publications from 2000 to 2018. J. Hos. Tour. Techn. 2019, 10, 539–570. [Google Scholar] [CrossRef]
  22. Tussyadiah, I.P.; Wang, D.; Jung, T.H.; tom Dieck, M.C. Virtual reality, presence and attitude change: Empirical evidence from tourism. Tour. Manag. 2018, 66, 140–154. [Google Scholar] [CrossRef]
  23. Pencarelli, T. The digital revolution in the travel and tourism industry. Inf. Technol. Tour. 2020, 22, 455–476. [Google Scholar] [CrossRef]
  24. Sagnier, C.; Loup-Escande, E.; Lourdeaux, D.; Thouvenin, I.; Valléry, G. User acceptance of virtual reality: An extended technology acceptance model. Int. J. Hum. Comput. Stud. 2020, 36, 993–1007. [Google Scholar] [CrossRef]
  25. Peukert, C.; Pfeiffer, J.; Meißner, M.; Pfeiffer, T.; Weinhardt, C. Shopping in virtual reality stores: The influence of immersion on system adoption. J. Inf. Syst. 2019, 36, 755–788. [Google Scholar] [CrossRef]
  26. Pfeiffer, J.; Pfeiffer, T.; Meißner, M.; Weiß, E. Eye-tracking-based classification of information search behavior using machine learning: Evidence from experiments in physical shops and virtual reality shopping environments. Inf. Syst. Res. 2020, 31, 675–691. [Google Scholar] [CrossRef]
  27. Huang, H.M.; Liaw, S.S. An analysis of learners’ intentions toward virtual reality learning based on constructivist and technology acceptance approaches. Int. Rev. Res. Open. Dis. Learn. 2018, 19, 1–25. [Google Scholar] [CrossRef] [Green Version]
  28. Bender, S.M.; Sung, B. Fright, attention, and joy while killing zombies in virtual reality: A psychophysiological analysis of VR user experience. Psych. Mark. 2021, 38, 937–947. [Google Scholar] [CrossRef]
  29. Lee, J.; Kim, J.; Choi, J.Y. The adoption of virtual reality devices: The technology acceptance model integrating enjoyment, social interaction, and strength of the social ties. Tel. Inf. 2019, 39, 37–48. [Google Scholar] [CrossRef]
  30. Bertrand, M.; Bouchard, S. Applying the technology acceptance model to VR with people who are favourable to its use. Journ. Cyb. Ther. Reh. 2008, 1, 200–210. [Google Scholar]
  31. Manis, K.T.; Choi, D. The virtual reality hardware acceptance model (VR-HAM): Extending and individuating the technology acceptance model (TAM) for virtual reality hardware. J. Bus. Res. 2019, 100, 503–513. [Google Scholar] [CrossRef]
  32. Choi, Y.K.; Totten, J.W. Self-construal’s role in mobile TV acceptance: Extension of TAM across cultures. J. Bus. Res. 2012, 65, 1525–1533. [Google Scholar] [CrossRef]
  33. Trope, Y.; Liberman, N. Construal-level theory of psychological distance. Psych. Rev. 2010, 117, 440–463. [Google Scholar] [CrossRef] [Green Version]
  34. Qi, J.Y.; Qu, Q.X.; Zhou, Y.P. How does customer self-construal moderate CRM value creation chain? Elec. Com. Res. App. 2014, 13, 295–304. [Google Scholar] [CrossRef]
  35. Wohlgenannt, I.; Simons, A.; Stieglitz, S. Virtual reality. Bus. Inf. Syst. Eng. 2020, 62, 455–461. [Google Scholar] [CrossRef]
  36. Jun, S.H.; Kim, J.H. 5G will popularize virtual and augmented reality: KT’s trials for world’s first 5G Olympics in PyeongChang. In Proceedings of the International Conference on Electronic Commerce, Pangyo, Korea, 17–18 August 2017; pp. 1–8. [Google Scholar] [CrossRef] [Green Version]
  37. Hartl, E.; Berger, B. Escaping reality: Examining the role of presence and escapism in user adoption of virtual reality glasses. In Proceedings of the 25th European Conference on Information Systems, Guimarães, Portugal, 5–11 June 2017; pp. 2413–2428. [Google Scholar]
  38. Shin, D. Empathy and embodied experience in virtual environment: To what extent can virtual reality stimulate empathy and embodied experience? Comput. Hum. Behav. 2018, 78, 64–73. [Google Scholar] [CrossRef]
  39. Zhang, M.; Zhang, Z.; Chang, Y.; Aziz, E.S.; Esche, S.; Chassapis, C. Recent developments in game-based virtual reality educational laboratories using the Microsoft Kinect. Int. J. Emer. Tech. Learn. 2018, 13, 138–159. [Google Scholar] [CrossRef] [Green Version]
  40. Hilfert, T.; König, M. Low-cost virtual reality environment for engineering and construction. Vis. Eng. 2016, 4, 2. [Google Scholar] [CrossRef] [Green Version]
  41. Ahir, K.; Govani, K.; Gajera, R.; Shah, M. Application on virtual reality for enhanced education learning, military training and sports. Aug. Hum. Res. 2020, 5, 7. [Google Scholar] [CrossRef]
  42. Jackson, T., II. Immersive Virtual Reality in Sports: Coaching and Training. In Implementing Augmented Reality into Immersive Virtual Learning Environments; Russel, D., Ed.; IGI Global: Hershey, PA, USA, 2021; pp. 135–150. [Google Scholar] [CrossRef]
  43. Neumann, D.L.; Moffitt, R.L.; Thomas, P.R.; Loveday, K.; Watling, D.P.; Lombard, C.L.; Tremeer, M.A. A systematic review of the application of interactive virtual reality to sport. J. Virtual Real. 2018, 22, 183–198. [Google Scholar] [CrossRef] [Green Version]
  44. Bideau, B.; Kulpa, R.; Vignais, N.; Brault, S.; Multon, F.; Craig, C. Using virtual reality to analyze sports performance. IEEE Comput. Graph. Appl. 2009, 30, 14–21. [Google Scholar] [CrossRef]
  45. Kuhnen, U.; Hannover, B.; Schubert, B. The semantic-procedural interface model of the self: The role of self-knowledge for context-dependent versus context-independent modes of thinking. J. Pers. Soc. Psychol. 2001, 80, 397–409. [Google Scholar] [CrossRef] [PubMed]
  46. Rondan-Cataluña, F.J.; Arenas-Gaitán, J.; Ramírez-Correa, P.E. A comparison of the different versions of popular technology acceptance models. Kybernetes 2015, 4, 788–805. [Google Scholar] [CrossRef]
  47. Tao, M.; Nawaz, M.Z.; Nawaz, S.; Butt, A.H.; Ahmad, H. Users’ acceptance of innovative mobile hotel booking trends: UK vs. PRC. Inf. Tech. Tour. 2018, 20, 9–36. [Google Scholar] [CrossRef]
  48. Zhang, J.; Mao, E. Cash, credit, or phone? An empirical study on the adoption of mobile payments in the United States. Psychol. Mark. 2020, 37, 87–98. [Google Scholar] [CrossRef]
  49. Davis, F.D. Perceived usefulness, perceived ease of use, and user acceptance of information technology. MIS Q. 1989, 13, 319–340. [Google Scholar] [CrossRef] [Green Version]
  50. Venkatesh, V.; Bala, H. Technology acceptance model 3 and a research agenda on interventions. Dec. Sci. 2008, 39, 273–315. [Google Scholar] [CrossRef] [Green Version]
  51. Venkatesh, V.; Davis, F.D. A theoretical extension of the technology acceptance model: Four longitudinal field studies. Manag. Sci. 2000, 46, 186–204. [Google Scholar] [CrossRef] [Green Version]
  52. Hsu, C.L.; Lu, H.P. Why do people play online games? An extended TAM with social influences and flow experience. Inf. Manag. 2004, 41, 853–868. [Google Scholar] [CrossRef]
  53. Moon, J.W.; Kim, Y.G. Extending the TAM for a World-Wide-Web context. Inf. Manag. 2001, 38, 217–230. [Google Scholar] [CrossRef]
  54. Venkatesh, V.; Thong, J.Y.; Xu, X. Consumer acceptance and use of information technology: Extending the unified theory of acceptance and use of technology. Manag. Inf. Syst. Q. 2012, 36, 157–178. [Google Scholar] [CrossRef] [Green Version]
  55. Jang, W.; Wu, L.; Wen, J. Understanding the effects of different types of meaningful sports consumption on sports consumers’ emotions, motivations, and behavioral intentions. Sport Manag. Rev. 2021, 24, 46–68. [Google Scholar] [CrossRef]
  56. Doyle, J.P.; Filo, K.; Lock, D.; Funk, D.C.; McDonald, H. Exploring PERMA in spectator sport: Applying positive psychology to examine the individual-level benefits of sport consumption. Sport Manag. Rev. 2016, 19, 506–519. [Google Scholar] [CrossRef] [Green Version]
  57. Teal, R.; Roberts, M.; Harrigan, P.; Clarkson, J.; Rosenberg, M. Leveraging spectator emotion: A review and conceptual framework for marketing health behaviors in elite sports. Sport Manag. Rev. 2020, 23, 183–199. [Google Scholar] [CrossRef]
  58. Li, G.X.; Liu, J.X. Construal level theory: Theoretical framework and affect process in consumer behaviors. In Proceedings of the International Conference on Management Science & Engineering 21th Annual Conference Proceedings, Helsinki, Finland, 17–19 August 2014; Lan, H., Yang, Y.H., Eds.; IEEE: Piscataway, NJ, USA, 2014; pp. 475–483. [Google Scholar] [CrossRef]
  59. Lo, C.J.; Tsarenko, Y.; Tojib, D. Does consumer-firm affiliation matter? The impact of social distance on consumers’ moral judgments. Psychol. Mark. 2019, 36, 1215–1225. [Google Scholar] [CrossRef]
  60. Zhang, Z.; Wang, X.; Wu, R. Is the devil in the details? Construal-level effects on perceived usefulness of online reviews for experience services. Electron. Commer. Res. Appl. 2021, 46, 101033. [Google Scholar] [CrossRef]
  61. Belanche, D.; Casaló, L.V.; Flavián, C. Artificial Intelligence in FinTech: Understanding robo-advisors adoption among customers. Ind. Manag. Data Syst. 2019, 119, 1411–1430. [Google Scholar] [CrossRef]
  62. Belanche, D.; Casaló, L.V.; Flavián, F. Customer’s acceptance of humanoid robots in services: The moderating role of risk aversion. In Marketing and Smart Technologies; Rocha, A., Reis, J.L., Peter, M.K., Cayolla, R., Loureiro, S., Bogdanović, Z., Eds.; Springer: Singapore, 2020; pp. 449–458. [Google Scholar]
  63. Flavián, C.; Pérez-Rueda, A.; Belanche, D.; Casaló, L.V. Intention to use analytical artificial intelligence (AI) in services–the effect of technology readiness and awareness. J. Serv. Manag. 2022, 33, 293–320. [Google Scholar] [CrossRef]
  64. Ariffin, S.K.; Abd Rahman, M.F.R.; Muhammad, A.M.; Zhang, Q. Understanding the consumer’s intention to use the e-wallet services. Span. J. Mark.-ESIC 2021, 25, 446–461. [Google Scholar] [CrossRef]
  65. Camilleri, M.A.; Falzon, L. Understanding motivations to use online streaming services: Integrating the technology acceptance model (TAM) and the uses and gratifications theory (UGT). Span. J. Mark.–ESIC 2021, 25, 217–238. [Google Scholar] [CrossRef]
  66. Rynarzewska, A.I. Virtual reality: A new channel in sport consumption. J. Res. Interact. Mark. 2018, 12, 472–488. [Google Scholar] [CrossRef]
  67. Mütterlein, J.; Hess, T. Immersion, presence, interactivity: Towards a joint understanding of factors influencing virtual reality acceptance and use. In A Tradition of Innovation, Proceedings of the 23rd Americas Conference on Information Systems, Association for Information Systems, Boston, MA, USA, 10–12 August 2017; Association for Information Systems (AIS): Atlanta, GA, USA, 2017; pp. 1–10. [Google Scholar]
  68. Mlekus, L.; Bentler, D.; Paruzel, A.; Kato-Beiderwieden, A.L.; Maier, G.W. How to raise technology acceptance: User experience characteristics as technology-inherent determinants. Gruppe. Interaktion. Organ. 2020, 51, 273–283. [Google Scholar] [CrossRef]
  69. Schepers, J.; Wetzels, M. A meta-analysis of the technology acceptance model: Investigating subjective norm and moderation effects. Inf. Manag. 2007, 44, 90–103. [Google Scholar] [CrossRef]
  70. Blau, P.M. Exchange and Power in Social Life; Wiley: New York, NY, USA, 1964. [Google Scholar]
  71. Kiesler, C.A.; Kiesler, S.B. Conformity; Addison Wesley Publishing Company: Reading, MA, USA, 1969. [Google Scholar]
  72. Pfeffer, J. Organizations and Organization Theory; Pitman: Boston, MA, USA, 1982. [Google Scholar]
  73. Kelman, H.C. Compliance, identification, and internalization three processes of attitude change. Int. J. Confl. Manag. 1958, 2, 51–60. [Google Scholar] [CrossRef]
  74. Warshaw, P.R. A new model for predicting behavioral intentions: An alternative to Fishbein. J. Mark. Res. 1980, 17, 153–172. [Google Scholar] [CrossRef]
  75. Salancik, G.R.; Pfeffer, J. A social information processing approach to job attitudes and task design. Adm. Sci. Q. 1978, 23, 224–253. [Google Scholar] [CrossRef] [PubMed]
  76. Fulk, J.; Steinfield, C.W.; Schmitz, J.; Power, J.G. A social information processing model of media use in organizations. Commun. Res. 1987, 14, 529–552. [Google Scholar] [CrossRef]
  77. Rice, R.E.; Aydin, C. Attitudes toward new organizational technology: Network proximity as a mechanism for social information processing. Adm. Sci. Q. 1991, 36, 219–244. [Google Scholar] [CrossRef]
  78. Lu, J.; Yao, J.E.; Yu, C.S. Personal innovativeness, social influences and adoption of wireless Internet services via mobile technology. J. Strateg. Inf. Syst. 2005, 14, 245–268. [Google Scholar] [CrossRef]
  79. Fetscherin, M.; Lattemann, C. User acceptance of virtual worlds. J. Electron. Commer. Res. 2008, 9, 231–242. [Google Scholar]
  80. Chen, C.Y.; Shih, B.Y.; Yu, S.H. Disaster prevention and reduction for exploring teachers’ technology acceptance using a virtual reality system and partial least squares techniques. Nat. Hazards 2012, 62, 1217–1231. [Google Scholar] [CrossRef]
  81. Bhattacherjee, A. Acceptance of e-commerce services: The case of electronic brokerages. IEEE Trans. Syst. Man Cybern. Syst. 2000, 30, 411–420. [Google Scholar] [CrossRef] [Green Version]
  82. Alalwan, A.A.; Yogesh, K.D.; Nripendra, P.R. Factors influencing adoption of mobile banking by Jordanian bank customers: Extending UTAUT2 with trust. Int. J. Inf. Manag. 2017, 37, 99–110. [Google Scholar] [CrossRef]
  83. Sanchez-Franco, M.J. WebCT–The quasimoderating effect of perceived affective quality on an extending Technology Acceptance Model. Comput. Educ. J. 2010, 54, 37–46. [Google Scholar] [CrossRef]
  84. Huang, Y.C.; Backman, S.J.; Backman, K.F.; Moore, D. Exploring user acceptance of 3D virtual worlds in travel and tourism marketing. Tour. Manag. 2013, 36, 490–501. [Google Scholar] [CrossRef]
  85. Yang, H.; Yu, J.; Zo, H.; Choi, M. User acceptance of wearable devices: An extended perspective of perceived value. Telemat. Inform. 2016, 33, 256–269. [Google Scholar] [CrossRef]
  86. King, W.R.; He, J. A meta-analysis of the technology acceptance model. Inf. Manag. 2006, 43, 740–755. [Google Scholar] [CrossRef]
  87. Chow, M.; Herold, D.K.; Choo, T.M.; Chan, K. Extending the technology acceptance model to explore the intention to use Second Life for enhancing healthcare education. Comput. Educ. J. 2012, 59, 1136–1144. [Google Scholar] [CrossRef]
  88. Kim, J.; Forsythe, S. Adoption of virtual try-on technology for online apparel shopping. J. Interact. Mark. 2008, 22, 45–59. [Google Scholar] [CrossRef]
  89. Tokel, S.T.; İsler, V. Acceptance of virtual worlds as learning space. Innov. Educ. Teach. Int. 2015, 52, 254–264. [Google Scholar] [CrossRef]
  90. Wallace, L.G.; Sheetz, S.D. The adoption of software measures: A technology acceptance model (TAM) perspective. Inf. Manag. 2014, 51, 249–259. [Google Scholar] [CrossRef]
  91. Cross, S.E.; Madson, L. Models of the self: Self-construals and gender. Psychol. Bull. 1997, 122, 5–37. [Google Scholar] [CrossRef] [PubMed]
  92. Ho, C.K.; Ke, W.; Liu, H. E-learning system implementation: Implications from the construal level theory. In Proceedings of the Pacific Asia Conference on Information Systems (PACIS), Jeju Island, Korea, 18–22 June 2013; p. 243. Available online: https://aisel.aisnet.org/pacis2013/243 (accessed on 23 May 2022).
  93. Horn, R.; Wagner, R. Advancing reputation measurement: Evolving toward improved quantitative assessments. Mark. Intell. Plan. 2019, 38, 181–194. [Google Scholar] [CrossRef]
  94. Grimm, M.S.; Wagner, R. The Impact of Missing Values on PLS, ML and FIML Model Fit. Arch. Data Sci. 2020, 6, 1–17. [Google Scholar] [CrossRef]
  95. Dijkstra, T.K.; Henseler, J. Consistent and asymptotically normal PLS estimators for linear structural equations. Comput. Stat. Data Anal. 2015, 81, 10–23. [Google Scholar] [CrossRef] [Green Version]
  96. Dijkstra, T.K.; Schermelleh-Engel, K. Consistent partial least squares for nonlinear structural equation models. Psychometrika 2014, 79, 585–604. [Google Scholar] [CrossRef]
  97. Hair, J.F.; Ringle, C.M.; Sarstedt, M. PLS-SEM: Indeed a silver bullet. J. Mark. Theory Pract. 2011, 19, 139–152. [Google Scholar] [CrossRef]
  98. Hair, J.F.; Ringle, C.M.; Sarstedt, M. The use of partial least squares (PLS) to address marketing management topics. J. Mark. Theory Pract. 2011, 19, 135–138. Available online: https://ssrn.com/abstract=2228902 (accessed on 23 May 2022). [CrossRef]
  99. Hair, J.F.; Risher, J.J.; Sarstedt, M.; Ringle, C.M. When to use and how to report the results of PLS-SEM. Eur. Bus. Rev. 2019, 31, 2–24. [Google Scholar] [CrossRef]
  100. Liberman, N.; Trope, Y.; Stephan, E. Psychological distance. In Social Psychology: Handbook of Basic Principles; Kruglanski, A.W., Higgins, E.T., Eds.; The Guilford Press: New York, NY, USA, 2007; pp. 353–381. [Google Scholar]
  101. Baumgartner, H.; Steenkamp, J.B.E. Exploratory consumer buying behavior: Conceptualization and measurement. Int. J. Res. Mark. 1996, 13, 121–137. [Google Scholar] [CrossRef]
  102. Thamizhvanan, A.; Xavier, M.J. Determinants of customers’ online purchase intention: An empirical study in India. J. Indian Bus. Res. 2013, 5, 17–32. [Google Scholar] [CrossRef]
  103. Yeo, V.C.S.; Goh, S.K.; Rezaei, S. Consumer experiences, attitude and behavioral intention toward online food delivery (OFD) services. J. Retail. Consum. Serv. 2017, 35, 150–162. [Google Scholar] [CrossRef]
  104. Hu, L.T.; Bentler, P.M. Fit indices in covariance structure modeling: Sensitivity to underparameterized model misspecification. Psychol. Methods 1998, 3, 424–453. [Google Scholar] [CrossRef]
  105. Sarstedt, M.; Henseler, J.; Ringle, C.M. Multigroup analysis in partial least squares (PLS) path modeling: Alternative methods and empirical results. Res. Methodol. Strategy Manag. 2011, 22, 195–218. [Google Scholar] [CrossRef]
  106. Kosa, M.; Uysal, A.; Eren, P.E. Acceptance of Virtual Reality Games: A Multi-Theory Approach. Int. J. Gaming. Comput. Mediat. Simul. 2020, 12, 43–70. [Google Scholar] [CrossRef]
  107. Szajna, B. Empirical evaluation of the revised technology acceptance model. Manag. Sci. 1996, 42, 85–92. [Google Scholar] [CrossRef]
  108. Wixom, B.H.; Todd, P.A. A theoretical integration of user satisfaction and technology acceptance. Inf. Syst. Res. 2005, 16, 85–102. [Google Scholar] [CrossRef]
  109. Zulauf, K.; Wagner, R. Online shopping therapy: If you want to be happy, shop around. J. Int. Consum. Mark. 2021. advance online publication. [Google Scholar] [CrossRef]
  110. Van Heerde, H.J.; Moorman, C.; Moreau, C.P.; Palmatier, R.W. Reality Check: Infusing Ecological Value into Academic Marketing Research. J. Mark. 2021, 85, 1–13. [Google Scholar] [CrossRef]
  111. Kim, H.S.; Kim, M. Viewing sports online together? Psychological consequences on social live streaming service usage. Sport Manag. Rev. 2020, 23, 869–882. [Google Scholar] [CrossRef]
  112. Flavián, C.; Ibáñez-Sánchez, S.; Orús, C. The influence of scent on virtual reality experiences: The role of aroma-content congruence. J. Bus. Res. 2021, 123, 289–301. [Google Scholar] [CrossRef]
Figure 1. Research model.
Figure 1. Research model.
Jtaer 17 00036 g001
Table 1. Sample description.
Table 1. Sample description.
VariableCases (%)VariableCases (%)
GenderMale148 (43.66%)EducationSecondary school119 (35.1%)
Female188 (55.46%) College degree57 (16.82%)
I prefer not to answer3 (0.88%) Bachelor’s degree111 (32.74%)
Do you do any sports?Yes219 (64.6%) Master’s degree44 (12.98%)
No120 (35.4%) Doctorate degree8 (2.36%)
What sport Age18–30229 (67.55%)
do you do? 31–4030 (8.85%)
(multiple 41–5037 (10.92%)
responses)Tennis20 (6.23%) 51–6034 (10.03%)
Swimming23 (7.16%) 61–706 (1.77%)
Volleyball12 (3.74%) 71–803 (0.88%)
Basketball13 (4.05%)CountryItaly221 (65.19%)
Gymnastics36 (11.21%) France68 (20.06%)
Fencing32 (9.97%) Poland13 (3.84%)
Jogging56 (17.45%) Germany5 (1.47%)
Athletics7 (2.18%) Spain4 (1.18%)
Football25 (7.79%) United Kingdom4 (1.18%)
Other97 (30.22%) Other24 (7.08%)
Table 2. Measurement model validity.
Table 2. Measurement model validity.
Outer LoadingCronbach’s AlphaRho_ACRAVE
Self-construal [88,100] 0.8380.8410.8390.723
When you are using a VR device …
Do you think about how useful it is to support you in watching sports?0.880
Do you think about how easy it is to use it to watch sports?0.819
Curiosity [101] 0.7390.7870.7560.614
I like to shop around and look at displays.0.657
I often read advertisements just out of curiosity.0.892
Experience [102,103] 0.8510.8520.8510.741
I feel comfortable using a VR device.0.844
I feel competent using a VR device.0.878
Image [50,51] 0.7770.7790.7780.637
Among my friends, people who use VR devices attract more attention.0.824
Having a VR device is a status symbol among my friends.0.771
Intention to use [50] 0.9230.9240.9240.801
There is a high likelihood that I will use a VR device during the next Olympic Games.0.879
I will use a VR device during the next Olympic Games.0.902
Using a VR device during the next Olympic Games is important to me.0.905
Output quality [50,51] 0.8060.8160.8090.681
I have no problem with the quality of VR’s video/image output.0.878
I rate the video/image I get from VR as excellent.0.769
Perceived ease of use [49] 0.8390.8400.8390.635
I believe it would be easy to get a VR device to do what I want it to do.0.791
I would find a VR device flexible to interact with.0.827
It would be easy for me to become skillful at using a VR device.0.772
Perceived enjoyment [49] 0.8960.8960.8960.811
I believe I would find using a VR device enjoyable.0.893
Using a VR device would be enjoyable.0.908
Perceived usefulness [49] 0.8370.8390.8380.722
I believe using a VR device would help me to be more effective.0.825
Using a VR device would improve my life.0.873
Price value [54] 0.9000.9040.9010.821
The current average price of a VR device is €100:
A VR device is a good value for the money.0.869
At the current average price, a VR device provides a good value.0.941
Subjective norm [32] 0.8120.8290.8200.606
I feel envy toward people who own a VR device.0.676
People important to me think I should use a VR device.0.855
People I look up to expect me to use a VR device.0.793
Usage attitude [49] 0.9660.9660.9660.852
My impression of using a VR device is: bad–good.0.918
My impression of using a VR device is: negative–positive.0.925
My impression of using a VR device is: unsatisfactory–satisfactory.0.937
My impression of using a VR device is: unfavorable–favorable.0.913
My impression of using a VR device is: unpleasant–pleasant.0.923
Table 3. Fornell–Larcker criterion and HTMT.
Table 3. Fornell–Larcker criterion and HTMT.
SCCEXIMIUOQPEOUPEPUPVSNUA
SC0.8500.1790.2730.3210.5170.1800.1730.1450.3540.1670.2400.247
C0.1830.7830.1740.2150.3510.0280.1110.2180.1860.1840.1740.213
EX0.2710.1680.8610.2220.2910.2600.6780.4880.3470.2430.3130.386
IM0.3190.2130.2230.7980.4820.3110.3240.3280.6560.1810.7560.311
IU0.5160.3520.2900.4820.8950.1860.2840.2340.5940.2380.5390.313
OQ0.177−0.0040.2610.3090.1830.8250.2880.2630.2300.4310.1560.641
PEOU0.1720.1040.6770.3280.2850.2900.7970.6570.5860.2990.3910.440
PE0.1450.2040.4880.3310.2330.2630.6580.9010.5070.3930.3100.599
PU0.3530.1850.3460.6570.5910.2270.5880.5070.8490.2460.6670.417
PV0.1660.1710.2440.1850.2370.4280.3010.3930.2450.9060.1820.487
SN0.2390.1750.3070.7470.5390.1490.3800.2960.6580.1760.7780.203
UA0.2470.2020.3850.3120.3120.6390.4410.5990.4160.4860.1950.923
Note: The diagonal elements (in bold) are the square root of the AVE. Values below the diagonal indicate the Fornell–Larcker criterion ratio. Values above the diagonal elements are the HTMT.
Table 4. Q2, R2, path coefficient, T-statistics, p-values, f2, VIF.
Table 4. Q2, R2, path coefficient, T-statistics, p-values, f2, VIF.
ImageStone–Geisser Q2 = 0.292R2 = 0.558R2 adjusted = 0.556
CoefficientPath CoefficientT-Statisticsp-Valuesf2VIFHypothesis
Subjective Norm0.74714.603<0.001***1.2601.000H1a (strongly supported)
Intention to useStone–Geisser Q2 = 0.350R2 = 0.502R2 adjusted = 0.496
CoefficientPath CoefficientT-Statisticsp-Valuesf2VIFHypothesis
Curiosity0.1954.163<0.001***0.0711.078H10b (strongly supported)
Self-Construal0.3597.132<0.001***0.2311.125H11 (strongly supported)
Subjective Norm0.3987.178<0.001***0.2901.098H1c (strongly supported)
Usage Attitude0.1072.2540.025*0.0211.112H7 (weakly supported)
Perceived ease of useStone–Geisser Q2 = 0.341R2 = 0.599R2 adjusted = 0.597
CoefficientPath CoefficientT-Statisticsp-Valuesf2VIFHypothesis
Experience0.4687.531<0.001***0.4161.312H8b (strongly supported)
Perceived Enjoyment0.4297.113<0.001***0.3511.312H4 (strongly supported)
Perceived enjoymentStone–Geisser Q2 = 0.161R2 = 0.238R2 adjusted = 0.235
CoefficientPath CoefficientT-Statisticsp-Valuesf2VIFHypothesis
Experience0.4889.766<0.001***0.3121.000H8a (strongly supported)
Perceived usefulnessStone–Geisser Q2 = 0.390R2 = 0.616R2 adjusted = 0.613
CoefficientPath CoefficientT-Statisticsp-Valuesf2VIFHypothesis
Image0.3362.9360.003**0.1292.272H2 (supported)
Perceived Ease of Use0.3786.362<0.001***0.3171.174H5a (strongly supported)
Subjective Norm0.2642.3390.020*0.0772.369H1b (weakly supported)
Usage attitudeStone–Geisser Q2 = 0.414R2 = 0.551R2 adjusted = 0.544
CoefficientPath CoefficientT-Statisticsp-Valuesf2VIFHypothesis
Curiosity0.1312.3790.018*0.0361.067H10a (weakly supported)
Output Quality0.4898.090<0.001***0.4141.285H3 strongly supported)
Perceived Ease of Use0.1422.0960.037*0.0281.622H5b (weakly supported)
Perceived Usefulness0.1552.4150.016*0.0341.578H6 (weakly supported)
Price Value0.1742.8270.005**0.0511.320H9 (supported)
Note: *** p < 0.001 strongly supported; ** p < 0.01 supported; * p < 0.05 weakly supported; p > 0.05 not supported burdens and skepticism toward using VR devices, and, notably, such spectators are more likely to believe that they need the technology.
Publisher’s Note: MDPI stays neutral with regard to jurisdictional claims in published maps and institutional affiliations.

Share and Cite

MDPI and ACS Style

Capasa, L.; Zulauf, K.; Wagner, R. Virtual Reality Experience of Mega Sports Events: A Technology Acceptance Study. J. Theor. Appl. Electron. Commer. Res. 2022, 17, 686-703. https://0-doi-org.brum.beds.ac.uk/10.3390/jtaer17020036

AMA Style

Capasa L, Zulauf K, Wagner R. Virtual Reality Experience of Mega Sports Events: A Technology Acceptance Study. Journal of Theoretical and Applied Electronic Commerce Research. 2022; 17(2):686-703. https://0-doi-org.brum.beds.ac.uk/10.3390/jtaer17020036

Chicago/Turabian Style

Capasa, Ludovica, Katrin Zulauf, and Ralf Wagner. 2022. "Virtual Reality Experience of Mega Sports Events: A Technology Acceptance Study" Journal of Theoretical and Applied Electronic Commerce Research 17, no. 2: 686-703. https://0-doi-org.brum.beds.ac.uk/10.3390/jtaer17020036

Article Metrics

Back to TopTop