Next Article in Journal
Environmental Risk Assessment in the Hindu Kush Himalayan Mountains of Northern Pakistan: Palas Valley, Kohistan
Next Article in Special Issue
Empowering High-Quality Development of the Chinese Sports Education Market in Light of the “Double Reduction” Policy: A Hybrid SWOT-AHP Analysis
Previous Article in Journal
A Socio-Ecological Approach to Conserve and Manage Riverscapes in Designated Areas: Cases of the Loire River Valley and Dordogne Basin, France
Previous Article in Special Issue
Financial Health and Self-Sustainability of a Small European Football League: The Realities of Top-Flight Croatian Football
 
 
Search for Articles:
Title / Keyword
Author / Affiliation / Email
Journal
Article Type
 
 
Advanced Search
 
Section
Special Issue
Volume
Issue
Number
Page
 
Journals
Sustainability
Volume 14
Issue 24
10.3390/su142416678
sustainability-logo
Submit to this Journal Review for this Journal Propose a Special Issue
► Article Menu

Article Menu

share Share announcement Help format_quote Cite question_answer Discuss in SciProfiles thumb_up
...
Endorse textsms
...
Comment
first_page
settings
Order Article Reprints
Font Type:
Arial Georgia Verdana
Font Size:
Aa Aa Aa
Line Spacing:
Column Width:
Background:
Article

Exploring Experiential Patterns Depending on Time Lapses in Virtual Reality Spectatorship (VRS): The Role of Interruption in Reducing Satiation

by
Jihyeon Oh
,
Dae Hee Kim
and
Daehwan Kim
*
Department of Marine Sports, Pukyong National University, Busan 48513, Republic of Korea
*
Author to whom correspondence should be addressed.
Sustainability 2022, 14(24), 16678; https://doi.org/10.3390/su142416678
Submission received: 27 November 2022 / Revised: 3 December 2022 / Accepted: 10 December 2022 / Published: 13 December 2022
(This article belongs to the Special Issue Sustainability of Sport Management in the Post-COVID19 Era)
Browse Figures
Versions Notes

Abstract

:
Virtual reality spectatorship (VRS) is receiving the limelight as a new form of sports media consumption in the sports industry, but prolonged exposure to the virtual reality (VR) environment is likely to reduce the benefits of VR due to satiation or adaptation. Therefore, the purpose of the present study was to examine the experiential differences in telepresence, flow experience, and satisfaction between a two-dimensional (2D) screen, VRS without interruptions, and VRS with interruptions. For this purpose, 150 participants were recruited and randomly assigned to one of the three conditions. They watched a 12-min-long soccer game and then answered the measurement items. A total of 149 participants were used for the data analyses, including confirmatory factor analysis (CFA), multivariate analysis of variance (MANOVA), and repeated measures of analysis of variance (ANOVA). The results revealed that VRS offers more enhanced telepresence, flow experience, and satisfaction than a 2D screen. Furthermore, flow experience was enhanced in VRS with interruptions compared to VRS without interruptions. Lastly, satisfaction was found to increase depending on time lapses in VRS with interruptions. The experiential patterns in VRS depending on interruptions and time lapses imply that inserting interruptions such as commercials could be not only beneficial for viewing experiences but also effective practice for increasing revenue from advertising.

1. Introduction

A wide range of industries is paying tremendous attention to Fourth Industrial Revolution technologies, including VR, augmented reality (AR), mixed reality (MR), artificial intelligence (AI), etc. In particular, VR technology is actively used in shopping, product design, education and training, entertainment, and manufacturing process simulation [1]. The global VR industry was valued at USD 11.64 billion in 2021, and it is expected to grow to USD 227.35 billion by 2029 [2]. With such rapid growth, practitioners in the sports industry actively adopt VR technologies and apply them to the development of VR sports, such as screen golf and screen baseball. Additionally, watching sports via VR is becoming a popular and sensational form of sports media consumption in the major sports leagues. For example, the National Basketball Association (NBA) recently launched a VR broadcasting service for its basketball contents, and SK Telecom, which is an AI and digital infrastructure service company in South Korea, commercialized VR steaming service for esports contents in 2019. Furthermore, the COVID-19 pandemic has dramatically accelerated the development of contactless services in the sports industry; stakeholders in the sports spectatorship area pay more attention to virtual environments in which spectators feel like they are watching sports competitions in person. As such, watching sports via VR is likely to be positioned as a major form of sports media consumption in the post-COVID-19 era.
Why is VR becoming more popular in sports media consumption? Sports consumers usually prefer attending a sporting event than watching it via media; the former gives much more experiential depth, which is difficult to deliver via traditional mass media [3]. However, sports fans are increasingly seeking optimal home-watching experiences that are on par with or better than live sports spectatorship [4]. In this regard, VR technologies offer experiential depth and provide users with a sense of being at the game (i.e., telepresence), thereby amplifying immersive experiences (i.e., flow experience) and ultimately satisfying users.
Although watching sports via VR is receiving the limelight as a new form of sports media consumption in the sports industry, it has several negative outcomes such as cybersickness or satiation [5,6,7]. In particular, such negative effects of watching sports via VR become prominent when users are exposed to the VR environment for a longer time [6,7]. This implies that prolonged exposure to watching sports in VR environments is likely to reduce the benefits of watching sports via VR due to cybersickness and satiation. Despite the potential threat for the sustainability of VR sports services, little is known about the experiential patterns in watching sports via VR. To fill the gap in the existing literature on sports media consumption, it is necessary to explore factors that reduce negative outcomes of watching sports via VR.
In this study, we basically assume that watching sports via VR offers more positive experiences such as telepresence, flow experience, and satisfaction than watching sports via traditional media (i.e., 2D screen), but that such positive experiences may be reduced as the watching experience is prolonged. We also assume that interruption (i.e., breaks) in watching sports via VR is likely to counteract such reduction of positive experiences because it does not only protect users from cybersickness, but it also slows down satiation [8,9]. Based on these assumptions, the purpose of the present study is to examine the differences in spectators’ telepresence, flow experience, and satisfaction between traditional sports media consumption, watching sports via VR, and watching sports via VR with interruptions. Exploring experiential patterns in VR sports services depending on time lapse and interruptions expands the literature on sport media consumption by offering theoretical explanations regarding negative outcomes of VRS and potential remedies for them. Additionally, the present study provides meaningful insight into developing advanced VR sport services based on immersive spectatorship environments and finding business opportunities for VR sport content developers to enhance their revenue.

2. Theoretical Background

2.1. VRS and User Experiences

What is VR? This new media technology is typically defined as technological hardware, for example, head-mounted displays (HMD). Kruger (1991) defined VR as “three-dimensional realities implemented with stereo viewing goggles and reality gloves” [10,11]. This was a typical definition, focusing on the technological aspects of VR rather than user experiences. Steuer (1992) argued that such a conceptualization of VR, based on its technological aspects, was not appropriate for software developers, policymakers, or media consumers because it did not provide any insight into the nature of VR or the underlying mechanisms of such a system [12]. Taking human experiences into consideration, telepresence theory provides a useful theoretical lens to understand user experiences in the context of VRS.
In general, VRS is defined as “a sport-watching behavior in a mediated spectating environment wherein virtual reality technologies provide a user with immersive experiences via amplified depth and breadth of sensory information, as well as an interactive user interface” [1]. One of the distinguishing features of VRS is its ability to provide media users with immersive experiences. Such immersive experience is enhanced through telepresence, which is escalated with media vividness and interactivity, and is a key determinant of consumer satisfaction [1]. Telepresence refers to “the extent to which one feels present in the mediated environment, rather than in the immediate physical environment” [12]. According to the telepresence theory [12,13,14,15], telepresence is a function of interactivity and vividness in diverse media usage contexts. For example, Kim and Ko (2019) reported that VRS provides more interactivity and vividness than the traditional sports watching service, thereby offering enhanced telepresence [1]. Furthermore, existing literature on media technologies and user experiences has suggested that telepresence is amplified with the levels of interactivity and vividness [14,16,17,18,19,20,21,22,23]. In general, VR technologies provide a greater level of interactivity and vividness than traditional media [12,24,25]. Accordingly, the present study hypothesized that VRS offers a greater level of telepresence than watching sports on a 2D screen (e.g., TV).
H1: 
Individuals will experience a greater level of telepresence in VRS than watching sports via 2D screen.
Meanwhile, one of the unique aspects of VRS is its offer of immersive experiences. Such immersive experiences are commonly conceptualized as flow experiences [26] in diverse contexts. Flow experience refers to the “state in which people are so involved in an activity and experience that nothing else seems to matter; the experience itself is so enjoyable that people will do it even at great cost for the sheer sake of doing it” [26]. Flow theory has been used to explore optimal experience in a wide range of sports areas including elite sports [27,28], recreational sports [29,30], and sports spectatorship [31,32]. These works commonly reported that flow experience is a crucial indicator of high-quality sports consumption. In general, it is assumed that the interplay between an individual’s personal characteristics (e.g., motivations, task involvement, and skills) and situational factors (e.g., task challenges, significance of tasks, and feedback) generates flow experience [33]. In the field of sports management, scholars exploring sports spectators’ flow experience have mainly relied on this assumption. However, sports media consumption is a unique context where spectators watch sports competitions through a medium, and its quality is simultaneously subject to that medium. Previous studies on media technologies and user experiences have actively adopted the flow theory to explain how media technologies amplify user experiences [34]. For example, Lee and Jeong (2012) showed that flow experience is a hedonic mediator on relationships among e-servicescape and user behaviors in the context of hospitality [35]. In the context of sports consumer behavior, Kim and Ko (2019) also suggested that flow experience is a pivotal mechanism in which VR technology enhances spectators’ viewing experiences [1]. Therefore, we hypothesized that VRS is likely to offer a greater level of flow experience than watching sports on a 2D screen.
H2: 
Individuals will experience a greater level of flow state in VRS than watching sports via 2D screen.
The ultimate goal of VRS is to satisfy its users via differentiated experiences. Existing literature on consumer satisfaction has mainly assumed that it is determined based on the disconfirmation between prior expectations of a product or service and its actual performance [36,37]. Such post purchase reaction (i.e., satisfaction) plays an important role in future consumption (e.g., repurchase) directly, but it also affects information search (i.e., formation of consideration sets) and the evaluation of alternatives. However, this perspective would be an inappropriate theoretical framework for some products/services that are based on fulfilling hedonic desires and symbolic meanings rather than satisfying utilitarian functions [38]. In general, sports spectator satisfaction is determined by both the cognitive and affective factors of sports events [39,40,41]. For example, Wakefield and Blodgett (1999) found that the quality of the facility (i.e., cognitive factor) and the excitement of the event (i.e., affective factor) directly determine customer satisfaction [42]. In the context of sports media consumption, media technology is likely to affect user satisfaction due to enhanced experiences, such as telepresence and flow experience [1]. Hence, the current study hypothesized that VRS offers a greater level of spectatorship satisfaction than watching sports on 2D screen.
H3: 
Individuals will experience a greater level of spectatorship satisfaction in VRS than watching sports via 2D screen.

2.2. Experiential Patterns in VRS

The existing literature on VR has mainly focused on positive experiences in VR environments and has assumed that VR environments uniformly enhance user experiences. However, there are skeptical views on such positive VR experiences due to cybersickness (i.e., motion sickness) and satiation [6,7]. First, cybersickness is defined as the negative effects and symptoms that users experience during or after immersion into VR environments [43,44]. The existing empirical evidence on VR experiences reported that 60%–95% of VR users experience cybersickness during exposure to a VR environment [7,45,46,47]. VRS offers an optimal environment in which users are blocked from outside sensory stimuli; thus, they can be easily immersed into the VR environment. However, it paradoxically results in fatigue, nausea, headache, etc., due to excessive sensory information and discrepancy in the visual, vestibular, and proprioceptive senses between reality and the virtual environment [7,48]. These negative experiences are likely to cause user dissatisfaction with VR environments and decreased use intentions.
Next, existing research suggests that individuals tend to adapt to a positive experience (e.g., watching sports via VR), making it less enjoyable over time [49]. This implies that sports media consumers could be satiated with watching sports via VR which, in turn, could lead to a less enjoyable viewing experience. Satiation is defined as the reduction of enjoyment resulting from prolonged or repeated exposure to a certain stimulus [50]. Satiation usually occurs due to hedonic adaptation and habituation [6,51]. Adaptation refers to lowered stimulus intensity and hedonic decline due to past exposure or experiences [52]. Similarly, habituation occurs from repeated exposure to a given stimulus and shows reduced attention levels and hedonic reduction for the stimulus.
The notion of satiation is a ubiquitous phenomenon in daily life. For example, individuals grow tired of repeatedly listening to a favorite song [53], eating the same food [54], and socializing with the same friends [55]. In line with this notion, prolonged exposure to VR sports services without any breaks may lead to a reduction of positive experiences in the services. However, the existing literature on satiation indicates that satiation is a transient phenomenon; it can be reduced by several ways. For instance, researchers reported that individuals promptly recover from satiation when time gaps are inserted between consuming the same stimuli or remembering different stimuli [55,56]. Furthermore, existing literature showed that disrupting continuous hedonic experiences, such as listening to music, getting a massage, and watching a television program, generates a more enjoyable overall experience [8,9]. This implies that inserting breaks into VR sports services may enhance sports media consumers’ experiences by slowing down satiation.
Specifically, previous research showed that disruptions to hedonic consumption, which have the effect of resetting the initial intensity of enjoyment, tend to slow satiation [9]. The underlying mechanism of the impact of disruptions on satiation in sports media consumption can be explained by three principles: dishabituation, spontaneous recovery [9,56], and categorization [57]. First, dishabituation suggests that the introduction of new stimuli influences sensitivity to the stimuli and results in decreased satiation. Second, spontaneous recovery implies that sensitivity to a stimulus gradually returns in the absence of the stimulus to which consumers are habituated and, in turn, the recovered sensitivity brings about decreased satiation. Third, the principle of categorization indicates that when consumers perceive more components to a consumption experience, they perceive greater variety, which leads to less satiation [57]. Inserting interruptions could activate these mechanisms. Accordingly, we predict that watching sports via VR with interruptions offers more positive experiences (i.e., telepresence, flow experience, and satisfaction) than watching sports via VR without interruptions and watching sports on 2D screen. Stated formally, we hypothesize that:
H4: 
Individuals will experience a greater level of telepresence in VRS with interruptions than VRS without interruptions.
H5: 
Individuals will experience a greater level of flow state in VRS with interruptions than VRS without interruptions.
H6: 
Individuals will experience a greater level of spectatorship satisfaction in VRS with interruptions than VRS without interruptions.
Meanwhile, inserting interruptions into watching sports via VR may lead to hedonic escalation. Hedonic escalation is the increased positive experiences of watching sports via VR as time lapses [58]. The source of hedonic escalation is sensitization [59]. Sensitization is defined as a process occurring when repeated exposures to a stimulus result in the amplification of a response [60]. Individuals tend to adapt easily to monotonous experiences, such as watching an apparently winning or losing game, but they may not adapt to nonmonotonous experiences; for example, individuals tend to adapt to a monotonous vacuum cleaner’s noise [8], but they tend to have trouble adapting to noises from a highway [61] because the highway generates a variety of noises. Thus, when individuals are exposed to stimuli that contain variation, they may be more likely to sensitize to the stimuli rather than adapt to them. In line with this notion, intensity of positive experiences may be amplified by sensitization resulting from prolonged exposure to nonmonotonous stimuli, including interruptions. Taken together, the following hypotheses are suggested:
H7: 
The level of telepresence will increase depending on time lapses in VRS with interruptions.
H8: 
The level of flow state will increase depending on time lapses in VRS with interruptions.
H9: 
The level of spectatorship satisfaction will increase depending on time lapses in VRS with interruptions.

3. Methods

3.1. Design and Participants

For the purpose of the current study, we used a mixed experimental design. A between-subjects factor is the viewing type with three groups (2D vs. VR without interruptions vs. VR with interruptions), and a within-subjects factor is the interruptions with three levels (4 min vs. 8 min vs. 12 min). We performed a statistical power analysis using G*Power 3.1 software [62] to determine the number of participants required to detect statistical effects of the independent variables on dependent variables (effect size = 0.25, alpha level = 0.05, power = 0.90, number of measurements = 3, number of groups = 3). The results indicated that the design of the present study required a total of 126 participants. Therefore, the current study aimed to recruit 150 participants due to potential data attrition. After deleting a participant who wanted to stop participating in the experiment, a total of 149 were included in the final data analysis (49 in the 2D group, 50 in the VR without interruptions group, and 50 in the VR with interruptions group). The participants were undergraduate students at a major national university in South Korea. They were offered USD 10 of compensation to participate in this experiment. The average age of participants was 21.21 (SD = 2.54), and 89 participants (59.3%) were male (Table 1).

3.2. Stimulus

Three scholars in the field of sports management reviewed several sports event contents, and then they selected a soccer game between the all-star team of K League in South Korea and the Juventus Football Club, which was held in South Korea in 2019. This stimulus was selected due to its high similarity between the versions of 2D screen and VR. The full content was edited to the 12-min version, in which the game score was tied, to control the effect of game result on participants’ responses to measurement items. In the VR with/without groups, participants watched the target stimulus using an Oculus Quest 2 VR headset that provides 1832 × 1920 resolution and a 60–90 Hz refresh rate. In the 2D screen group, participants watched the target stimulus with a 2D computer screen, which was a 24” widescreen flat-panel LCD monitor with 1920 × 1080 resolution.

3.3. Measurement Model

The survey consists of items for measuring demographic information, telepresence, flow experience, spectatorship satisfaction, and several potential control variables including sport involvement and team identification. The dependent variables, including telepresence, flow experience, and spectatorship satisfaction, were measured using existing measurement items from relevant research, and the response scale was anchored by 1 = not at all and 7 = very much. First, the concept of telepresence was operationalized as the degree to which a sports viewer forgets the physical environment and feels present in the mediated environment where the target sports event is held, and we measured it with four items adopted and modified from the existing literature on [tele]presence [1,63,64]. Second, the concept of flow experience was a psychological state containing time distortion, absorption, and enjoyment during the watching of the target sports event, and it was measured with seven items adopted from the previous studies on flow experience in media contexts [65,66,67]. Lastly, spectatorship satisfaction was operationalized in terms of overall viewing experience and the target sports event, and it was measured with four items from the existing literature on sports media consumption [1,68].
A CFA was conducted using Mplus8 software to evaluate the measurement model based on maximum likelihood estimation. Specifically, we examined a three-factor measurement model, including telepresence, satisfaction, and the second-order factor of flow experience, including time distortion, absorption, and enjoyment. The results of CFA indicated that the measurement model secures an acceptable fit to the data: χ2(84) = 204.186, p < 0.05; root mean square error of approximation (RMSEA) = 0.098; comparative fit index (CFI) = 0.949; Tucker-Lewis index (TLI) = 0.937; and standardized root mean square residual (SRMR) = 0.051. The results of CFA also showed that all factor loadings of the measurement model were statistically significant (see Table 2). The average variance extracted (AVE) values ranged from 0.69 (telepresence) to 0.92 (time distortion). The composite reliability coefficients ranged from 0.84 (telepresence) to 0.96 (time distortion). These results are empirical evidence of convergent validity and reliability of each construct in the measurement model [69,70]. Furthermore, the AVE values were greater than the squared correlation coefficients between and constructs in the measurement model (see Table 3). These results represent the discriminant validity of the constructs in the measurement model. Taken together, we concluded that the measurement model secures construct validity and reliability; thus, we collapsed all measurement items on each of the theorized constructs to yield single variables.

3.4. Procedure

The experiment comprised three steps. In the first step, participants were randomly assigned to one of the three conditions, were briefly informed of the overall procedure, signed a consent form, and answered survey questions regarding demographic information. In the second phase, participants watched the target stimulus via either VR device or 2D screen for 12 min. In the third step, participants in the 2D screen and VR without interruptions groups answered questions regarding telepresence, flow experience, and spectatorship satisfaction after 12 min. However, participants in the VR with interruptions group answered the same questions three times after 4 min, 8 min, and 12 min. The average time for completing the experiment for each participant was 25–30 min.

4. Results

To test hypotheses 1 to 7, we conducted one-way MANOVA with viewing type (49 cases in 2D vs. 50 cases in VR without interruptions vs. 50 cases in VR with interruptions) as an independent variable and three dependent variables, including telepresence, flow experience, and spectatorship satisfaction using SPSS 27. The results showed a significant main effect of viewing type on the dependent variables, F(6, 286) = 7.573, p < 0.001, partial η2 = 0.137, Hotelling T = 0.318 (see Table 4). Therefore, we performed follow-up univariate ANOVA to examine the effect of viewing type on each of the dependent variables. The results revealed that viewing type has significant main effects on telepresence, F(2, 146) = 18.393, p < 0.001, partial η2 = 0.201; flow experience, F(2, 146) = 5.374, p < 0.01, partial η2 = 0.069; and spectatorship satisfaction, F(2, 146) = 5.489, p < 0.01, partial η2 = 0.070. Hence, we conducted post hoc tests based on Fisher’s LSD [71].
First, the results showed that there are significant differences in telepresence between a 2D screen (M = 3.23, SE = 0.19), VR without interruptions (M = 4.64, SE = 0.19), and VR with interruptions (M = 4.77, SE = 0.19). Therefore, hypothesis 1 is tenable. Second, the results revealed that there are significant differences in flow experience between 2D screen (M = 5.36, SE = 0.16), VR without interruptions (M = 5.46, SE = 0.16), and VR with interruptions (M = 6.10, SE = 0.16). Accordingly, hypothesis 2 is supported. Third, the results indicated that there are significant differences in spectatorship satisfaction between 2D screen (M = 5.48, SE = 0.14), VR without interruptions (M = 5.89, SE = 0.14), and VR with interruptions (M = 6.16, SE = 0.14). Thus, hypothesis 3 is supported.
Regarding the effect of interruptions on VRS (H4–H6), we compared VR without interruptions and VR with interruptions. Specifically, it was found that there is significant difference in flow experience between these groups (mean difference = −0.60, p < 0.05), but there is no significant difference in telepresence (mean difference = −0.13, p = 0.18) and spectatorship satisfaction (mean difference = −0.27, p = 0.18) between the groups (see Figure 1). Taken together, hypothesis 5 was supported while hypotheses 4 and 6 were rejected.
Lastly, we performed a repeated measure of ANOVA using cases in VR with interruptions to examine experiential patterns of VRS depending on time lapses (4 min vs. 8 min vs. 12 min). The result indicated that there is a marginally significant difference in spectatorship satisfaction between time lapses (see Table 5); however, there are no significant differences in telepresence and flow experience depending on time lapse even though the experiential patterns are consistent with the hypotheses (see Figure 2). All in all, hypotheses 7 and 8 were not tenable whereas hypothesis 9 was partially supported.

5. Discussion

5.1. Interpretations of Hypothesis Testing

Drawing on media theories regarding telepresence and flow experience, the present study demonstrated that VRS significantly enhances telepresence, flow experience, and spectatorship satisfaction compared to traditional sports media consumption (i.e., 2D screen). Specifically, the results revealed that VRS offers a higher level of telepresence, flow experience, and spectatorship satisfaction than 2D screen. These findings are consistent with the basic assumption of diverse theories and findings in the media literature; high-quality media technologies improve user experiences, including telepresence, flow experience, and user satisfaction [1,72,73,74,75]. Interestingly, there was no difference in flow experience between 2D screen and VRS without interruptions, but there was significant difference in flow experience between 2D screen and VRS with interruptions. In general, flow experience tends to be determined by three factors including media factor (e.g., media attributes), personal factor (e.g., sports involvement), and content factors (e.g., quality of the target game). In particular, a personal factor has a significant effect on flow experience in the context of sports media consumption [1,41,76]. In the present study, a plausible speculation is that participants were highly interested in sports (sports involvement: M = 6.40, SD = 0.78); thus, they were likely to experience flow state even in the 2D screen condition. As a result, experiential benefits (i.e., flow experience) from the media technology seemed to be prominent only in VR with interruptions, which amplify user experiences.
With respect to the role of interruptions in VRS, the current study demonstrated that the interruptions significantly enhance sports media consumers’ flow experience. This finding is interpreted as interruptions in VRS potentially playing a pivotal role of slowing down satiation or disrupting adaptation, thereby amplifying flow experience. According to the basic tenet of satiation and adaption, continuous exposure to a stimulus necessarily leads to hedonic decline [52]. One of the plausible remedies for such hedonic decline in VRS is inserting breaks or interruptions to disrupt hedonic adaption, which leads to more enjoyable experiences than ones without interruptions [8,9]. In line with this notion, we concluded that the interruptions in VRS may disrupt the adaptation to VRS, thereby amplifying flow experience. However, the present study failed to find significant differences in telepresence and satisfaction between VRS without interruptions and the one with interruptions. The absence of significant differences may result from the nature of these constructs. Specifically, telepresence reflects cognitive evaluations of media attributes, and satisfaction represents cognitive assessment of an overall experience based on disconfirmation between expectation and actual performance. Hedonic experience tends to be more sensitive to affective attributes than cognitive attributes of the experience [38,77]. For this reason, only flow experience, which contains both the cognitive and affective attributes, may react to interruptions whereas the telepresence and satisfaction may not in VRS.
Lastly, the current study revealed that spectatorship satisfaction tends to slightly increase as time flows; however, there were no significantly increasing patterns in telepresence and flow experience depending on time lapses. Only significant increase in spectatorship satisfaction may come from the nature of the target stimulus; the all-star team of K League made a goal after the first interruption session. Since the concept of spectatorship satisfaction measured satisfaction with the game and viewing experience, it is likely to be affected by the nature of the target stimulus. Additionally, simple break times (interruptions) may not be enough to escalate the quality of viewing experience in VRS. According to the literature on sensitization [8,60,61], when consumers perceive more components to a consumption experience, they perceive greater variety, which leads to experiential escalation. In other words, such interruptions during a sports game function as new stimuli (i.e., dishabituation), keep viewers from the game for a while, thus allowing enjoyment to recover (i.e., spontaneous recovery), or allow viewers to construe watching the game as an experience composed of multiple units rather than a single unit, thus escalating the experiential quality of VRS. However, simple breaks, which may not be perceived as multiple units by the participants, did not work in the present study. Therefore, there is no evidence regarding experiential escalation in VRS depending on time lapses.

5.2. Theoretical and Practical Implications

The findings of the present study make several meaningful theoretical contributions to the literature on sports media consumption and sports consumer behavior. First, the findings of the current study extend the existing literature on VRS by examining its diverse positive outcomes, including telepresence, flow experience, and spectatorship satisfaction in a longer stimulus (12 min). For example, a previous study examined the effect of VRS on consumption experiences, including telepresence, flow experience, and satisfaction in a five-minute stimulus [1,25]; thus, it was uncertain whether such positive outcomes could be maintained in a prolonged viewing episode. Additionally, numerous experts in the field of VR technologies have pointed out potential negative outcomes of long usages of VR [7,78,79]. The present study provides evidence regarding positive outcomes of VRS in a long viewing episode.
Second, the present study revealed that such positive outcomes can be enhanced by inserting interruptions into VRS to slow down satiation or disrupt adaptation. This implies that the quality of sports media consumption is not only enhanced by media technologies (traditional media vs. immersive media), but it is also affected by effective remedies (e.g., interruptions) even in the same media platform. The existing literature on VR has heavily relied on the concept of cybersickness to explain hedonic decline in the context of VR environments [7,46,47]; however, the present study introduces a useful theoretical lens to explore such hedonic decline in the context of VR environments. In other words, the theories of hedonic adaptation and satiation can explain why VR users’ positive experiences are attenuated. Third, the present study provides a future research agenda regarding hedonic escalation in VRS. Although we failed to find statistically significant increasing patterns of telepresence and flow experience depending on time lapses, such increasing patterns may become prominent when inserting more effective interruptions into VRS.
Lastly, the current study also offers several important practical implications to the field of sports media consumption and sports consumer behavior. The positive outcomes in longer viewing episodes imply the sustainability of VRS products and services; therefore, practitioners in the sports industry should actively adopt VRS to provide sports media consumers with high-quality experiences. Furthermore, the experiential patterns in VRS depending on interruptions and time lapses imply that inserting commercials, which is a common marketing strategy in televised sports events, is not only beneficial for viewing experiences but also effective practice for increasing revenue from advertising; thus, practitioners should develop effective and efficient strategies to arrange diverse commercials in VRS.

5.3. Limitations and Future Research Agendas

Despite the theoretical and practical implications of the present study, several limitations should be discussed to offer insight for future research agendas. First, we used a 12-min-long stimulus to prevent potential side effects from longer viewing experiences. However, a unit of diverse sports events usually ranged from 12 min (a quarter of NBA basketball) to 45 min (each half of a soccer game). Accordingly, future research needs to explore VRS experiences in longer episodes to verify its feasibility in the sports media industry. Second, the present study failed to find hedonic escalation (i.e., sensitization) depending on time lapses and interruptions. As discussed above, simple breaks may not activate such a psychological mechanism; thus, future research may need to insert diverse interruptions, such as commercials or tasks. Lastly, the present study utilized a student sample through the purposive sampling method; in particular, we found that they were highly interested in sports; hence, this study should be replicated with diverse participants to secure external validity. Furthermore, the current study utilized a soccer game as a stimulus; thus, major sports contents such as basketball, baseball, and mixed martial arts would be compelling research contexts for future research.

6. Conclusions

VRS is considered a new form of sport media consumption, but there are several areas in which the quality of user experiences could be improved. Based on this issue, the present study aimed to explore experiential patterns in VRS depending on interruptions and time lapses to provide insight into finding optimal VRS conditions. We found that VRS offers enhanced user experiences compared to traditional sport media, but such benefit tends to be diluted due to prolonged exposure to VRS environment. We also found that the adverse effects of prolonged exposure to VRS could be solved via interruptions. In conclusion, VRS can be a viable form of sport media consumption, but smart strategies such as interruptive commercials for disrupting adaptation and satiation should be considered.

Author Contributions

Conceptualization, J.O. and D.K.; methodology, D.K. and D.H.K.; validation, formal analysis, D.K.; data curation, D.K.; writing—original draft preparation, J.O.; writing—review and editing, D.K. and D.H.K.; visualization, D.H.K.; supervision, D.K.; project administration, D.K.; funding acquisition, D.K. All authors have read and agreed to the published version of the manuscript.

Funding

This work was supported by the Ministry of Education of the Republic of Korea and the National Research Foundation of Korea (NRF-2021S1A5A8069352).

Institutional Review Board Statement

The study was approved by the Institutional Review Board of Pukyong National University (1041386-202110-HR-55-02).

Informed Consent Statement

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

Data Availability Statement

Not applicable.

Conflicts of Interest

The authors declare no conflict of interest.

References

  1. 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]
  2. Fortune Business Insights. Market Research Report; Fortune Business Insights: Pune, India, 2022. [Google Scholar]
  3. Ludvigsen, M.; Veerasawmy, R. Designing Technology for Active Spectator Experiences at Sporting Events. In Proceedings of the 22nd Conference of the Computer-Human Interaction Special Interest Group of Australia on Computer-Human Interaction, Brisbane, Australia, 22–26 November 2010; ACM: New York, NY, USA, 2010; pp. 96–103. [Google Scholar]
  4. King, B. What Makes Fans Crazy about Sports? Available online: http://www.sportsbusinessdaily.com/Journal/Issues/%0A2010/04/20100419/SBJ-In-Depth/What-Makes-Fans-Crazy-%0AAbout-Sports.aspx (accessed on 10 January 2018).
  5. Guttentag, D.A. Virtual Reality: Applications and Implications for Tourism. Tour. Manag. 2010, 31, 637–651. [Google Scholar] [CrossRef]
  6. Pala, E.; Kapitan, S.; van Esch, P. Simulated Satiation through Reality-enhancing Technology. Psychol. Mark. 2022, 39, 483–494. [Google Scholar] [CrossRef]
  7. Caserman, P.; Garcia-Agundez, A.; Gámez Zerban, A.; Göbel, S. Cybersickness in Current-Generation Virtual Reality Head-Mounted Displays: Systematic Review and Outlook. Virtual Real. 2021, 25, 1153–1170. [Google Scholar] [CrossRef]
  8. Nelson, L.D.; Meyvis, T. Interrupted Consumption: Disrupting Adaptation to Hedonic Experiences. J. Mark. Res. 2008, 45, 654–664. [Google Scholar] [CrossRef]
  9. Nelson, L.D.; Meyvis, T.; Galak, J. Enhancing the Television-Viewing Experience through Commercial Interruptions. J. Consum. Res. 2009, 36, 160–172. [Google Scholar] [CrossRef] [Green Version]
  10. Kruger, M. Artificial Reality; Addison-Wesley: Reading, MA, USA, 1991. [Google Scholar]
  11. Rebbani, Z.; Azougagh, D.; Bahatti, L.; Bouattane, O. Definitions and Applications of Augmented/Virtual Reality: A Survey. Int. J. 2021, 9, 279–285. [Google Scholar]
  12. Steuer, J. Defining Virtual Reality: Dimensions Determining Telepresence. J. Commun. 1992, 42, 73–93. [Google Scholar] [CrossRef]
  13. Laurel, B. Computers as Theatre Addison-Wesley; Addison-Wesley: Reading, MA, USA, 1991. [Google Scholar]
  14. Lombard, M.; Ditton, T. At the Heart of It All: The Concept of Presence. J. Comput.-Mediat. Commun. 1997, 3, JCMC321. [Google Scholar] [CrossRef]
  15. Naimark, M. Realness and Interactivity. In The Art of Human-Computer Interface Design; Addison-Wesley: Reading, MA, USA, 1990; pp. 455–459. [Google Scholar]
  16. Bartneck, C.; Hu, J. Presence in a Distributed Media Environment. In Proceedings of the User Experience Design for Pervasive Computing, Pervasive; Terrenghi, L., Lindt, I., Butz, A., Kuniavsky, M., Eds.; Ludwig-Maximilians-Universitat: Munich, Germany, 2005. [Google Scholar]
  17. Cauberghe, V.; Geuens, M.; de Pelsmacker, P. Context Effects of TV Programme-Induced Interactivity and Telepresence on Advertising Responses. Int. J. Advert. 2011, 30, 641–663. [Google Scholar] [CrossRef] [Green Version]
  18. Coyle, J.R.; Thorson, E. The Effects of Progressive Levels of Interactivity and Vividness in Web Marketing Sites. J. Advert. 2001, 30, 65–77. [Google Scholar] [CrossRef]
  19. Fortin, D.R.; Dholakia, R.R. Interactivity and Vividness Effects on Social Presence and Involvement with a Web-Based Advertisement. J. Bus. Res. 2005, 58, 387–396. [Google Scholar] [CrossRef]
  20. Khalifa, M.; Shen, N. System Design Effects on Social Presence and Telepresence in Virtual Communities. In Proceedings of the International Conference on Information Systems, Washington, DC, USA, 12–15 December 2004; pp. 547–558. [Google Scholar]
  21. Lessiter, J.; Freeman, J.; Keogh, E.; Davidoff, J. A Cross-Media Presence Questionnaire: The ITC-Sense of Presence Inventory. Presence Teleoperators Virtual Environ. 2001, 10, 282–297. [Google Scholar] [CrossRef] [Green Version]
  22. Skadberg, Y.X.; Kimmel, J.R. Visitors’ Flow Experience While Browsing a Web Site: Its Measurement, Contributing Factors and Consequences. Comput. Human Behav. 2004, 20, 403–422. [Google Scholar] [CrossRef]
  23. Kim, J.-H.; Kim, M.; Park, M.; Yoo, J. How Interactivity and Vividness Influence Consumer Virtual Reality Shopping Experience: The Mediating Role of Telepresence. J. Res. Interact. Mark. 2021, 15, 502–525. [Google Scholar] [CrossRef]
  24. Hyun, M.Y.; Lee, S.; Hu, C. Mobile-Mediated Virtual Experience in Tourism: Concept, Typology and Applications. J. Vacat. Mark. 2009, 15, 149–164. [Google Scholar] [CrossRef]
  25. Kim, D. The Effects of Telepresence and Social Needs Fulfillment on Spectatorship Satisfaction in Virtual Reality Spectatorship (VRS). Korean J. Phys. Educ. 2019, 58, 159–171. [Google Scholar] [CrossRef]
  26. Csikszentmihalyi, M. Flow: The Psychology of Optimal Experience; HarperCollins: New York, NY, USA, 1991. [Google Scholar]
  27. Jackson, S.A.; Marsh, H.W. Development and Validation of a Scale to Measure Optimal Experience: The Flow State Scale. J. Sport Exerc. Psychol. 1996, 18, 17–35. [Google Scholar] [CrossRef]
  28. Swann, C.; Keegan, R.; Piggott, D.; Crust, L.; Smith, M.F. Exploring Flow Occurrence in Elite Golf. Athl. Insight 2012, 4, 171–186. [Google Scholar]
  29. Stein, G.L.; Kimiecik, J.C.; Daniels, J.; Jackson, S.A. Psychological Antecedents of Flow in Recreational Sport. Personal. Soc. Psychol. Bull. 1995, 21, 125–135. [Google Scholar] [CrossRef]
  30. Cheng, T.-M.; Hung, S.-H.; Chen, M.-T. The Influence of Leisure Involvement on Flow Experience during Hiking Activity: Using Psychological Commitment as a Mediate Variable. Asia Pac. J. Tour. Res. 2016, 21, 1–19. [Google Scholar] [CrossRef]
  31. Lee, H.-W.; Gipson, C.; Barnhill, C. Experience of Spectator Flow and Perceived Stadium Atmosphere: Moderating Role of Team Identification. Sport Mark. Q. 2017, 26, 87–98. [Google Scholar]
  32. Madrigal, R. Measuring the Multidimensional Nature of Sporting Event Performance Consumption. J. Leis. Res. 2006, 38, 267–292. [Google Scholar] [CrossRef]
  33. Kimiecik, J.C.; Stein, G.L. Examining Flow Experiences in Sport Contexts: Conceptual Issues and Methodological Concerns. J. Appl. Sport Psychol. 1992, 4, 144–160. [Google Scholar] [CrossRef]
  34. Kim, M.J.; Hall, C.M. A Hedonic Motivation Model in Virtual Reality Tourism: Comparing Visitors and Non-Visitors. Int. J. Inf. Manag. 2019, 46, 236–249. [Google Scholar] [CrossRef]
  35. Lee, S.A.; Jeong, M. Effects of E-servicescape on Consumers’ Flow Experiences. J. Hosp. Tour. Technol. 2012, 3, 47–59. [Google Scholar] [CrossRef]
  36. Oliver, R.L. A Cognitive Model of the Antecedents and Consequences of Satisfaction Decisions. J. Mark. Res. 1980, 17, 460–469. [Google Scholar] [CrossRef]
  37. Wirtz, J.; Bateson, J.E.G. Consumer Satisfaction with Services: Integrating the Environment Perspective in Services Marketing into the Traditional Disconfirmation Paradigm. J. Bus. Res. 1999, 44, 55–66. [Google Scholar] [CrossRef]
  38. Holbrook, M.B.; Hirschman, E.C. The Experiential Aspects of Consumption: Consumer Fantasies, Feelings, and Fun. J. Consum. Res. 1982, 9, 132–140. [Google Scholar] [CrossRef] [Green Version]
  39. van Leeuwen, L.; Quick, S.; Daniel, K. The Sport Spectator Satisfaction Model: A Conceptual Framework for Understanding the Satisfaction of Spectators. Sport Manag. Rev. 2002, 5, 99–128. [Google Scholar] [CrossRef]
  40. Madrigal, R. Cognitive and Affective Determinants of Fan Satisfaction with Sporting Event Attendance. J. Leis. Res. 1995, 27, 205–227. [Google Scholar] [CrossRef]
  41. Kim, D.; Kim, A.; Kim, J.; Ko, Y.J. Symbiotic Relationship Between Sport Media Consumption and Spectatorship: The Role of Flow Experience and Hedonic Need Fulfillment. J. Glob. Sport Manag. 2020, 7, 112–134. [Google Scholar] [CrossRef]
  42. Wakefield, K.L.; Blodgett, J.G. Customer Response to Intangible and Tangible Service Factors. Psychol. Mark. 1999, 16, 51–68. [Google Scholar] [CrossRef]
  43. Kim, J.; Chung, C.Y.L.; Nakamura, S.; Palmisano, S.; Khuu, S.K. The Oculus Rift: A Cost-Effective Tool for Studying Visual-Vestibular Interactions in Self-Motion Perception. Front. Psychol. 2015, 6, 248. [Google Scholar] [CrossRef] [Green Version]
  44. Merhi, O.; Faugloire, E.; Flanagan, M.; Stoffregen, T.A. Motion Sickness, Console Video Games, and Head-Mounted Displays. Hum. Factors 2007, 49, 920–934. [Google Scholar] [CrossRef]
  45. Stanney, K.M.; Hale, K.S.; Nahmens, I.; Kennedy, R.S. What to Expect from Immersive Virtual Environment Exposure: Influences of Gender, Body Mass Index, and Past Experience. Hum. Factors 2003, 45, 504–520. [Google Scholar] [CrossRef]
  46. Arns, L.L.; Cerney, M.M. The Relationship between Age and Incidence of Cybersickness among Immersive Environment Users. In Proceedings of the IEEE Proceedings, VR 2005, Virtual Reality, Bonn, Germany, 12–16 March 2005; IEEE: Piscataway, NJ, USA, 2005; pp. 267–268. [Google Scholar]
  47. Roberts, W.K.; Gallimore, J.J. A Physiological Model of Cybersickness during Virtual Environment Interaction. In Proceedings of the Human Factors and Ergonomics Society Annual Meeting, Orlando, FL, USA, 26–30 September 2005; SAGE Publications: Los Angeles, CA, USA, 2005; Volume 49, pp. 2230–2234. [Google Scholar]
  48. Guo, X.; Wan, D.; Liu, D.; Mousas, C.; Chen, Y. HAVIT: A VR-Based Platform to Support Human-Autonomous Vehicle Interaction Study. In Proceedings of the International Conference on Human-Computer Interaction, London, UK, 21–24 July 2022; Springer: Berlin/Heidelberg, Germany, 2022; pp. 371–390. [Google Scholar]
  49. Frederick, S.; Loewenstein, G. 16 Hedonic Adaptation. In Well-Being: The foundations of Hedonic Psychology; Kahneman, D., Diener, E., Schwarz, N., Eds.; Russell Sage: New York, NY, USA, 1999; pp. 302–329. [Google Scholar]
  50. Loewenstein, G.; Angner, E. Predicting and Indulging Changing Preferences. In Time and Decision: Economic and Psychological Perspectives on Intertemporal Choice; Russell Sage: New York, NY, USA, 2003; pp. 351–391. [Google Scholar]
  51. Antón, C.; Camarero, C.; Garrido, M.-J. A Journey through the Museum: Visit Factors That Prevent or Further Visitor Satiation. Ann. Tour. Res. 2018, 73, 48–61. [Google Scholar] [CrossRef]
  52. Galak, J.; Redden, J.P. The Properties and Antecedents of Hedonic Decline. Annu. Rev. Psychol. 2018, 69, 1–25. [Google Scholar] [CrossRef]
  53. Ratner, R.K.; Kahn, B.E.; Kahneman, D. Choosing Less-Preferred Experiences for the Sake of Variety. J. Consum. Res. 1999, 26, 1–15. [Google Scholar] [CrossRef]
  54. Rolls, B.J.; van Duijvenvoorde, P.M.; Rolls, E.T. Pleasantness Changes and Food Intake in a Varied Four-Course Meal. Appetite 1984, 5, 337–348. [Google Scholar] [CrossRef]
  55. Galak, J.; Redden, J.P.; Kruger, J. Variety Amnesia: Recalling Past Variety Can Accelerate Recovery from Satiation. J. Consum. Res. 2009, 36, 575–584. [Google Scholar] [CrossRef]
  56. Thompson, R.F.; Spencer, W.A. Habituation: A Model Phenomenon for the Study of Neuronal Substrates of Behavior. Psychol. Rev. 1966, 73, 16. [Google Scholar] [CrossRef] [PubMed] [Green Version]
  57. Redden, J.P. Reducing Satiation: The Role of Categorization Level. J. Consum. Res. 2008, 34, 624–634. [Google Scholar] [CrossRef]
  58. Epstein, L.H.; Robinson, J.L.; Temple, J.L.; Roemmich, J.N.; Marusewski, A.; Nadbrzuch, R. Sensitization and Habituation of Motivated Behavior in Overweight and Non-Overweight Children. Learn. Motiv. 2008, 39, 243–255. [Google Scholar] [CrossRef] [Green Version]
  59. Crolic, C.; Janiszewski, C. Hedonic Escalation: When Food Just Tastes Better and Better. J. Consum. Res. 2016, 43, 388–406. [Google Scholar] [CrossRef] [Green Version]
  60. Shettleworth, S.J. Cognition, Evolution, and Behavior; Oxford University Press: Oxford, UK, 2009; ISBN 0199886385. [Google Scholar]
  61. Weinstein, N.D. Community Noise Problems: Evidence against Adaptation. J. Environ. Psychol. 1982, 2, 87–97. [Google Scholar] [CrossRef]
  62. Faul, F.; Erdfelder, E.; Buchner, A.; Lang, A.-G. Statistical Power Analyses Using G* Power 3.1: Tests for Correlation and Regression Analyses. Behav. Res. Methods 2009, 41, 1149–1160. [Google Scholar] [CrossRef] [Green Version]
  63. Novak, T.P.; Hoffman, D.L.; Yung, Y.-F. Measuring the Customer Experience in Online Environments: A Structural Modeling Approach. Mark. Sci. 2000, 19, 22–42. [Google Scholar] [CrossRef] [Green Version]
  64. Kim, T.; Biocca, F. Telepresence via Television: Two Dimensions of Telepresence May Have Different Connections to Memory and Persuasion. J. Comput.-Mediat. Commun. 1997, 3, JCMC325. [Google Scholar] [CrossRef]
  65. Koufaris, M. Applying the Technology Acceptance Model and Flow Theory to Online Consumer Behavior. Inf. Syst. Res. 2002, 13, 205–223. [Google Scholar] [CrossRef] [Green Version]
  66. Shin, N. Online Learner’s ‘Flow’Experience: An Empirical Study. Br. J. Educ. Technol. 2006, 37, 705–720. [Google Scholar] [CrossRef]
  67. Ghani, J.A.; Supnick, R.; Rooney, P. The Experience of Flow in Computer-Mediated and in Face-to-Face Groups. Proc. ICIS 1991, 91, 229–237. [Google Scholar]
  68. Yoshida, M.; James, J.D. Customer Satisfaction with Game and Service Experiences: Antecedents and Consequences. J. Sport Manag. 2010, 24, 338–361. [Google Scholar] [CrossRef]
  69. Fornell, C.; Larcker, D.F. Evaluating Structural Equation Models with Unobservable Variables and Measurement Error. J. Mark. Res. 1981, 18, 39–50. [Google Scholar] [CrossRef]
  70. Hair, J.F.; Black, W.C.; Babin, B.J.; Anderson, R.E.; Tatham, R.L. Multivariate Data Analysis, 6th ed.; Pearson Prentice Hall: Uppersaddle River, NJ, USA, 2006. [Google Scholar]
  71. Williams, L.J.; Abdi, H. Fisher’s Least Significant Difference (LSD) Test. Encycl. Res. Des. 2010, 218, 840–853. [Google Scholar]
  72. Hecht, D.; Reiner, M. Field Dependency and the Sense of Object-Presence in Haptic Virtual Environments. CyberPsycholo. Behav. 2006, 10, 243–251. [Google Scholar] [CrossRef] [Green Version]
  73. Lok, B.C. Toward the Merging of Real and Virtual Spaces. Commun. ACM 2004, 47, 48–53. [Google Scholar] [CrossRef]
  74. Nah, F.F.-H.; Eschenbrenner, B.; DeWester, D. Enhancing Brand Equity through Flow and Telepresence: A Comparison of 2D and 3D Virtual Worlds. MIS Q. 2011, 35, 731–747. [Google Scholar] [CrossRef]
  75. Riva, G.; Mantovani, F.; Capideville, C.S.; Preziosa, A.; Morganti, F.; Villani, D.; Gaggioli, A.; Botella, C.; Alcañiz, M. Affective Interactions Using Virtual Reality: The Link between Presence and Emotions. CyberPsycholo. Behav. 2007, 10, 45–56. [Google Scholar] [CrossRef]
  76. Finneran, C.M.; Zhang, P. A Person–Artefact–Task (PAT) Model of Flow Antecedents in Computer-Mediated Environments. Int. J. Hum. Comput. Stud. 2003, 59, 475–496. [Google Scholar] [CrossRef]
  77. Hirschman, E.C.; Holbrook, M.B. Hedonic Consumption: Emerging Concepts, Methods and Propositions. J. Mark. 1982, 46, 92–101. [Google Scholar] [CrossRef] [Green Version]
  78. Max, F. How Long Should You Use a VR Headset [Safe Playtime]. Available online: https://10scopes.com/how-long-should-you-use-a-vr-headset/ (accessed on 20 November 2022).
  79. Yoon, H.J.; Moon, H.S.; Sung, M.S.; Park, S.W.; Heo, H. Effects of Prolonged Use of Virtual Reality Smartphone-Based Head-Mounted Display on Visual Parameters: A Randomised Controlled Trial. Sci. Rep. 2021, 11, 15382. [Google Scholar] [CrossRef] [PubMed]
Sustainability 14 16678 g001 550
Figure 1. The results of the post-hoc test between viewing types. Note. w/o I = without interruptions; w/ I = with interruptions. * p < 0.05, ** p < 0.01, *** p < 0.001.
Figure 1. The results of the post-hoc test between viewing types. Note. w/o I = without interruptions; w/ I = with interruptions. * p < 0.05, ** p < 0.01, *** p < 0.001.
Sustainability 14 16678 g001
Sustainability 14 16678 g002 550
Figure 2. The results of the post-hoc test within VR with interruptions group. * p < 0.10.
Figure 2. The results of the post-hoc test within VR with interruptions group. * p < 0.10.
Sustainability 14 16678 g002
Table
Table 1. Participants’ Demographic Information.
Table 1. Participants’ Demographic Information.
VariableCategoryFrequencyPercentage
Age18–206644.2
21–235537.0
24–262214.8
27–2964.0
GenderMale8959.3
Female6040.7
Amount of Sport Viewing per WeekBelow 1 h6140.9
1 h–2 h4026.8
2 h–3 h2114.1
Over 3 h2718.1
Total149100
Table
Table 2. Summary results for confirmatory factor analysis (CFA).
Table 2. Summary results for confirmatory factor analysis (CFA).
Factors and ItemsλC.R.AVE
Telepresence 0.8390.689
When the game ended, I felt like I came back to the real world0.912
The world in the screen (VR) seemed to me somewhere I visited rather than something I saw0.900
When I watched the game, I felt I was in the arena0.731
When I watched the game, I forgot about my physical location.0.761
Flow Experience 0.9150.783
(Absorption) When I watched the game, I was totally focused on it0.911
(Absorption) When I watched the game, I was absorbed intensely0.978
(Absorption) When I watched the game, I was deeply engrossed in the game0.916
(Time Distortion) When I watched the game, it felt like time flew0.976
(Time Distortion) When I watched the game, time seemed to go by very quickly0.943
(Enjoyment) Watching the game was enjoyable0.917
(Enjoyment) Watching the game was fun0.927
Spectatorship Satisfaction 0.9230.751
I was satisfied with the game0.883
I was pleased with the game0.851
I was satisfied with my viewing experience0.912
I was pleased with my viewing experience0.816
Note. C.R.= composite reliability, AVE = Average variance extracted.
Table
Table 3. Inter-construct correlations.
Table 3. Inter-construct correlations.
123MeanSD
1 Tele0.689 4.321.53
2 Flow0.481 ***0.783 5.391.21
3 Sat0.519 ***0.883 ***0.7515.841.06
Note. Tele = telepresence; Flow = flow experience; SAT = spectatorship satisfaction; Bold = AVE value. *** p < 0.001.
Table
Table 4. Results of MANOVA.
Table 4. Results of MANOVA.
2DVR w/o IVR w/ IF StatisticPost Hoc
Mean (SD)Mean (SD)Mean (SD)
Tele3.23 (1.30)4.64 (1.39)4.77 (1.46)18.393 ***2D < VR w/o I
2D < VR w/ I
Flow5.36 (1.16)5.46 (1.25)6.10 (1.03)5.374 **2D < VR w/ I
VR w/o I < VR w/ I
Sat5.48 (0.96)5.88 (1.08)6.16 (0.98)5.489 ***2D < VR w/o I
2D < VR w/ I
Note. Tele = telepresence; Flow = flow experience; Sat = spectatorship satisfaction; 2D = 2D-screen; w/o I = without interruptions; w/ I = with interruptions. ** p < 0.01, *** p < 0.001.
Table
Table 5. Results of MANOVA.
Table 5. Results of MANOVA.
4 min8 min12 minF StatisticPost Hoc
Mean (SD)Mean (SD)Mean (SD)
Tele4.58 (1.28)4.72 (1.30)4.77 (1.46)2.57NS
Flow5.95 (1.16)6.03 (0.96)6.10 (1.03)0.70NS
Sat5.95 (1.03)6.12 (0.97)6.20 (0.98)3.20 *4 min < 8 min
4 min < 12 min
Note. Tele = telepresence; Flow = flow experience; Sat = spectatorship satisfaction; NS = not significant. * p < 0.10.
Publisher’s Note: MDPI stays neutral with regard to jurisdictional claims in published maps and institutional affiliations.

Share and Cite

MDPI and ACS Style

Oh, J.; Kim, D.H.; Kim, D. Exploring Experiential Patterns Depending on Time Lapses in Virtual Reality Spectatorship (VRS): The Role of Interruption in Reducing Satiation. Sustainability 2022, 14, 16678. https://doi.org/10.3390/su142416678

AMA Style

Oh J, Kim DH, Kim D. Exploring Experiential Patterns Depending on Time Lapses in Virtual Reality Spectatorship (VRS): The Role of Interruption in Reducing Satiation. Sustainability. 2022; 14(24):16678. https://doi.org/10.3390/su142416678

Chicago/Turabian Style

Oh, Jihyeon, Dae Hee Kim, and Daehwan Kim. 2022. "Exploring Experiential Patterns Depending on Time Lapses in Virtual Reality Spectatorship (VRS): The Role of Interruption in Reducing Satiation" Sustainability 14, no. 24: 16678. https://doi.org/10.3390/su142416678

Note that from the first issue of 2016, this journal uses article numbers instead of page numbers. See further details here.

Article Metrics

Back to TopTop