Abstract
Electronic sports (esports) have become one of the fastest-growing forms of new media. As a result, esports livestreaming media is a necessary medium for connecting viewers and esports livestreams. Drawing on the media richness theory, the purpose of the current study was to explore how livestreaming media attributes and viewers’ individual characteristics (esports involvement) influence the viewer’s experience (satisfaction and flow experience) and media loyalty. The results of a latent moderated structural equations (LMS) modeling analysis using a total of 568 viewers revealed that informativeness and convenience significantly influenced viewer satisfaction and flow experience, which in turn influenced media loyalty. Interestingly, interactivity was found to be a more important attribute for viewer satisfaction and flow experience among highly involved viewers while informativeness was an important attribute for less involved viewers. Furthermore, viewer satisfaction is pivotal in establishing media loyalty for less involved viewers, while flow experience is key for highly involved viewers. The findings of this research have theoretical implications for the literature on esports media and media consumption experiences and offer managers effective strategies for developing esports media loyalty.
Introduction
Electronic sports (esports), also known as organized video game competitions, are a fast-growing phenomenon among younger generations (Gawrysiak et al., 2020) and have emerged as a global entertainment sensation with far-reaching economic and cultural implications (Abbasi et al., 2020). Esports generated nearly $1.38 billion in revenue globally by the end of 2022 while the global esports audience grew 8.7% year-on-year to reach 532 million. It is expected that the total audience will surpass 640 million by 2025 (Newzoo, 2022). The rapid growth of esports is thought to have occurred due to livestreaming media (Lukowicz & Strzelecki, 2020). Currently, 66% of esports media consumers watch livestreaming media, making such media more popular than television viewership (43%) and attendance at esports events (16%; Goldman Sachs, 2018).
A large number of livestreaming media platforms have emerged (e.g., Twitch, Facebook, Twitter, and YouTube), and such an increase in livestreaming media results in “streaming wars” among different platforms in order to secure the greatest user base (Lobato & Lotz, 2021). This competition occurs because media users can either choose to livestream esports on their current platform of choice or switch to another platform with better conditions (Koo, 2018). In this respect, maintaining customer relationships and creating loyalty between a specific platform and its users is essential for success in the competitive livestreaming media market (Ryu et al., 2014). Thus, it is crucial to determine which specific attributes of livestreaming media can improve viewer experiences.
Unlike general livestreaming programs (e.g., online shopping and online education), esports is inherently a competitive sports phenomenon that represents a new frontier for study in the field of communication and sport (Abbasi et al., 2020). Scholars are aware of the importance of examining media characteristics that influence viewer experiences (e.g., flow experience and satisfaction) during livestreamed games. However, most prior media and communication psychology research has primarily focused on esports contents itself and experiences and perceptions of the viewer, such as streamers (Koo, 2018; Xu et al., 2022), esports content or community (Giertz et al., 2022; Sjöblom et al., 2017), esports recreational gameplay (Jang et al., 2020), and on viewer’s motivation (Yu et al., 2022). A clearer understanding of the medium that connects the viewer and esports, namely the attributes of esports livestreaming media becomes very important due to variations in research contexts, such as online shopping live streaming platforms (Kang et al., 2021; Sun et al., 2019) and tourism live streaming platforms (Lv et al., 2022).
In the sports context, involvement would describe the level that a consumer values or believes that sports are relevant and important in their lives (Kim & Ko, 2019). In contrast to extant research that primarily focused on socio-demographic variables such as age, gender, and income to segment consumers (e.g., Qian et al., 2022; Yu et al., 2018; Yu et al., 2022), the present study focused on the degree of the association between individuals and esports and examined the moderating effect of viewer involvement with a specific focus on two aspects of this moderation. First, we examined how various media attributes influence the consumer experience under the moderation of esports involvement. Second, we questioned what other factors influence consumers’ decision-making process. Although positive viewing experiences likely encourage a consumer to continue using livestreaming media, watching a livestream does not necessarily create loyalty to that specific livestream provider (Chang & Zhu, 2012; Pham et al., 2021). Does a viewer’s level of involvement (high or low) influence the degree to which a positive viewing experience will increase their loyalty? Research addressing this gap can delineate the boundary conditions of the relationship between a positive viewing experience (i.e., satisfaction and flow experience) and loyalty, expanding our understanding of media loyalty among esports livestreaming viewers. The research results will enhance explanatory and predictive power by providing a deeper theoretical understanding of the experiences of esports consumers and their thought processes (Düsenberg et al., 2016). Therefore, the results of a nuanced analysis of diverse consumers (i.e., high/low levels of involvement) will also help develop effective segmentation and positioning strategies in the context of esports livestreaming services.
In responding to the call for a more systematic investigation into such issues, the present study aims to explore when and how the attributes of esports livestreaming media influence media loyalty by drawing on the media richness theory (Daft et al., 1987) and elaboration likelihood model (ELM: Petty & Cacioppo, 1986). Specifically, the purpose of this study is to examine the effect of the attributes of livestreaming media (interactivity, informativeness, and convenience) on media loyalty via viewing experiences (i.e., flow experiences and viewer satisfaction) depending on the level of involvement in esports.
By exploring these dynamics within the context of communication, this research aims to contribute to the growing body of knowledge not only in the sport management literature but also in the sport communication literature. The findings of the present study are expected to provide theoretical insights into the psychological mechanism of how esports viewers develop media loyalty and to offer meaningful, practical implications to sport communication scholars and practitioners for developing optimal esports livestreaming environments depending on viewer characteristics.
Theoretical Background and Hypothesis Development
Esports as a professional sports genre has been recognized as a spectator sport. When attendance occurs in a virtual world, viewers and esports are indirectly connected through livestreaming media, which makes the interacting parties feel each other’s presence affectionately (i.e., social presence theory [SPT] in Short et al., 1976). Esports livestreaming media has become an effective marketing communication medium for maintaining existing media users and attracting potential users. Esports livestreaming media can not only enhance the viewer’s experience but also increase the viewer–media relationship through the viewer’s stickiness or loyalty.
The Media Richness Theory in Esports Livestreaming Media Consumption
The media richness theory is one of the most frequently used theories to explain how different media affect task performance (Suh, 1999). It is based on the concept of task–media fit (Daft et al., 1987), which refers to the degree to which the task characteristics of media users match the media-selection attributes (Koo et al., 2011). This theory starts with the essential properties of media and assumes that the differences in media’s ability to handle a task in different media channels will affect the user’s choice of and preference for media channels (Chen et al., 2020).
The capabilities of a medium depend on its degree of media richness, which consists of four criteria: availability of immediate feedback, multiple cues, language variety, and personal focus (Daft et al., 1987). In the context of a livestreaming service, the availability of immediate feedback refers to the extent to which a livestreaming service enables users to rapidly respond to received messages. Multiple cues refer to the ways in which a livestreaming service conveys messages in such diverse forms as physical presence, voice inflection, bodily gestures, words, numbers, and graphic symbols. Language variety suggests the range of meanings that can be communicated through symbols or alternatives in a livestreaming service. Finally, personal focus refers either to the conveyance of emotions and feelings or to the ability of livestreaming media to be tailored to the specific needs and perspectives of the receiver or to encompass a variety of personal feelings.
The richer the medium, the more components of media richness it incorporates (Hasim et al., 2020). Based on the aforementioned four criteria of media richness theory proposed by Daft et al. (1987) and applied to online livestreaming media, online livestreaming is considered a form of rich media because it provides real-time, face-to-face communication and immediate feedback in several meaningful ways. First, viewers can use bullet screens, rewards, and other methods to offer feedback according to the content provided by the broadcaster and multiple cues via the broadcaster’s body language and tone of voice. In this process, the viewers realize the interaction between themselves and the broadcaster through the current livestreaming media or interact with other viewers in real time through the chat window message (i.e., interactivity). Second, the sound effects of the game, its music, the provision of program information, text message exchanges in a chat window, and so on provide each viewer with live game content that meets his or her needs and interests (Chen et al., 2020). The online streaming media provide useful, timely, accurate, and relevant information for the viewers; enable users to save time and effort for information searches; and help users to easily obtain the livestreaming content information they want, which provides them with convenience (i.e., informativeness and convenience).
Although the media richness theory is applicable to many media situations (e.g., telephone, mail, web pages) to judge the level of media richness, its four criteria are not relevant enough for the current research context. Therefore, conceptualizing media attributes into more relevant attributes to the current study was necessary to determine the valid effects of media attributes on viewing experiences in the context of esports livestreaming services. Thus, in the current study, we conducted an extensive literature review and carefully selected media attributes such as interactivity, informativeness, and convenience that livestreaming media possess and that could serve as judgment criteria for media richness in the context of esports livestreaming services.
The Attributes of Esports Livestreaming Media and Viewer Satisfaction
In modern cognitive psychology, attributes are defined as the characteristics of something that are a concrete description of an abstract quality of an object (Mervis & Rosch, 1981). The research on attributes/factors has been consistently receiving significant attention from the academic community in the marketing and consumer psychology and behavior context (e.g., service quality factors, website quality attributes etc.). It provides a comprehensive understanding of market marketing and consumer behavior, making it a crucial factor in driving marketing strategies and influencing consumer decision-making (Ko & Pastore, 2005). In the sport literature, scholars have also paid attention to the attributes of online livestreaming services. For example, by focusing on broadcaster attributes, Kim and Kim (2022) found positive effects of broadcasters’ friendship and skill on the viewer’s flow experience, psychological well-being, and commitment and loyalty. Sjöblom et al. (2017) examined the relationship between the attributes of video game content/genre and viewer gratification in the context of live gaming and found that the attributes of the video game content had a stronger impact on viewer gratification than the video game genre.
Literature Review on Live Streaming (2018–2023).
Interactivity
On closer examination, these contextual factors can be broadly divided into human–human, human–message/content, and human–computer/system/machine interactions (Kim et al., 2012; Ko et al., 2005). Specific to the current study, livestreaming media works as a functional base to enable viewers to interact with the broadcaster and other viewers. Furthermore, it is worth noting that, during esports livestreams, the interaction between the viewer and other viewers is accomplished by means of messaging through, for example, text comments, emojis, and chat content in the embedded chat channel. In short, the current study employs the two-dimensional concept of interactivity defined as the degree to which the viewer engages in esports livestreams by actively interacting with the broadcaster (viewer–broadcaster) and with other viewers’ communications (viewer–viewer).
Li et al. (2015) stated that online livestreaming media are viewed as a social place where users can establish and develop social relationships as well as receive feedback from other participants, which enables the viewers to achieve a desirable viewing experience and improve their satisfaction with the game livestream. In this regard, social presence theory (SPT) (Short et al., 1976) provides a useful theoretical lens through which we can understand the role of interactivity in viewer satisfaction. According to SPT, media can make the individuals establish personal connections with others via media and feel each other’s presence affectionately. Viewers are motivated to choose media with a high level of social presence to create positive human interaction and to gratify their need for psychological connection with others. Moreover, from a psychological perspective, interactivity is viewed as a perceived warmth that promotes social intimacy (Rice & Case, 1983), increases a sense of belonging (Xiang & Chae, 2022), and thus generates positive response (e.g., satisfaction).
Informativeness
Informativeness refers to the degree to which using the livestreaming service provides viewers with useful, timely, and adequate information (Hsu & Lin, 2021). Scholars in social media advertising have emphasized that viewers consider an advertisement’s ability to provide such information to be the primary reason for accepting the advertisement itself (Lee & Hong, 2016). Similarly, in the context of livestreaming services, Hilvert-Bruce et al. (2018) suggested that information seeking is a major motive of livestream engagement; specifically, the motivation to explore information is an important factor for developing emotional connectedness (i.e., psychological attachment) to a specific platform. As such, informativeness is a major factor in determining viewer attitudes and attachment to livestreaming media. This importance is consistent with the premise of uses and gratifications (U&G) theory, which posits that media have the ability to deliver useful information as a gratification factor and user satisfaction (Hsu & Lin, 2021).
Convenience
Convenience refers to the user’s perception of the time and effort required to find and facilitate the use of media service technologies (Copeland, 1923). With the advancement of technologies, and when similar products and services exist, convenience will be a determining factor in user acceptance (Davis, 1989) since the core technology and services will already have been tested and standardized (Yang et al., 2014). Sports communication scholars suggested that viewer availability and access (convenience) is a crucial predictive factor for esports gameplay and spectatorship (Tang et al., 2022). In livestreaming service contexts, Qian et al., 2020b noted that convenience is a component of the Scale for Esports Spectator Demand (SESD) and that it significantly influences the consumption experience of esports spectators. Furthermore, livestreaming media convenience can be considered the viewer’s time and effort costs associated with viewing in a livestreaming environment. These consumer resources of time and effort are viewed as non-monetary costs that influence consumer attitudes and behaviors (Duarte et al., 2018). The current study defines convenience as the degree to which individuals find the livestreaming media convenient for the process of viewing livestreamed esports (Shin et al., 2021). Relevant factors include the level of convenience with respect to joining as a member, accessing livestreams, and searching for information. Additionally, Thuy (2011) claimed that a high-level convenience service positively affects perceived value and leads to an increase in customer satisfaction. Therefore, based on the theoretical and empirical support, we developed the following hypotheses (H1-3):
The interactivity of livestreaming media positively influences viewer satisfaction.
The informativeness of livestreaming media positively influences viewer satisfaction.
The convenience of livestreaming media positively influences viewer satisfaction.
Flow Experience in Viewer Experience
Csikszentmihalyi (1975) defined flow as “the holistic sensations that people feel when they act with total involvement” (p. 36). Flow experience can also be described as an optimal mental state in which an individual can devote all of his or her attention to a limited stimulus field without interruptions so as to allow the participant to filter out other unrelated perceptions, such as daily troubles. The flow concept has been verified as a variable in the evaluation of consumer or viewer experience in relation to, for example, website quality (Hsu et al., 2012), online shopping (Hsu et al., 2017), virtual reality (Kim & Ko, 2019), and online gaming (Hsu & Lin, 2021). Additionally, Arnould and Price (1993) suggested that in experiential consumption such as sport spectatorship, the flow experience can be regarded as the core representative of the quality of consumption experience. In particular, Kim and Ko (2019) indicated that the flow experience, as a psychological peak experience, is the common pursuit of viewers of sport media.
Thus, in the current research, we argue that the flow experience can represent a diagnostic cue for viewers of sport media to evaluate their livestreaming service experience. We conceptualized the flow experience in livestreaming services as a psychological state, namely the psychological feelings that viewers experience during esports livestreaming, including cognitive absorption, time distortion, and enjoyment. Kim and Kim (2020) suggested three reasons that the fundamental notion of the flow experience can be applied to esports livestreaming media services. First, esports livestreaming services rest on a form of sport media consumption, which is viewed as an autotelic experience that brings viewers pleasure and enjoyment. According to flow theory, this autotelic experience is regarded as a core driver of an individual’s flow experience. Second, esports usually feature a competitive activity or event. Viewers concentrate intensely on the esports game, which leads to cognitive absorption, something that the existing literature views as a key indicator of a flow experience (Kim & Ko, 2019; Lee et al., 2017). Third, not only the pleasure, amusement, or interest but also the extensive attention that esports generate can make viewers tend to underestimate the duration of time when watching livestreams (Kim & Ko, 2019). Such time distortion can be considered an indicator of the flow experience; therefore, we argue that watching livestreamed esports via the media will generate a flow experience.
Moreover, Kim and Ko (2019) found that media attributes significantly influence the flow experience of media users. Livestreaming participants (e.g., viewers and live broadcasters) communicate and interact with each other through the functions of the livestreaming system (e.g., interacting with others and giving gifts). In this context, the viewers perceive pleasure and enjoyment and even lose awareness of time (Hsu & Lin, 2021). Similarly, Skadberg and Kimmel (2004) verified that interactivity makes a website more engaging and enjoyable and gives users a greater sense of freedom and control. Jeon et al. (2018) also showed that the interactivity a website visitor perceived positively influenced his or her flow experience.
Regarding informativeness, Jeon et al. (2018) also claimed that website users’ attention is likely to be piqued when they are aroused by external stimulation, such as detailed information (e.g., text, pictures, visual design), and that, in this case, users tend to perceive time’s passing quickly. According to Kim and Han (2014), consumers did not feel annoyed by the information and were likely to experience enjoyment and pleasure and even become immersed in understanding the details of the information they needed Thus, following the discussion in this section, these factors contribute to the formation of the flow experience.
Although media contents and user characteristics have been recognized as the predeterminants of the flow experience as a mental or spiritual state (Kim & Ko, 2019), the flow experience may be sensitive to the media environment. Chen and Lin (2018) explained that because concentration is a delicate state of mind, it is not easy to maintain; therefore, the user’s flow state can be easily broken by the media environment (Kim & Kim, 2022). In the context of media livestreaming, media disturbances (e.g., a complex user interface, inconvenient procedures, low synchrony) may undermine a user’s sense of control over his or her behaviors. Conversely, if the media environment is properly maintained, viewers are more likely to concentrate and achieve a flow experience. Thus, convenience is an essential attribute for creating an optimal online media environment (Jiang et al., 2013). Likewise, Zhang et al. (2014) emphasized that the use of a smartphone requires little effort and is free of time or space limitations (i.e., convenient), which means that users will be more likely to become focused and enjoy their activity (i.e., achieve a flow experience). Thus, we hypothesized the following (H4-6):
Interactivity positively influences the flow experience.
Informativeness positively influences the flow experience.
Perceived convenience positively influences the flow experience.
The Role of Esports Involvement in Viewer Experience
Involvement is defined as the degree of interest in a specific subject as an individual characteristic or the degree of centrality that the subject occupies in an individual’s ego structure (Zaichkowsky, 1994). Since consumers’ consumption patterns vary according to their individual characteristics, the consumer group should be viewed as heterogeneous rather than homogeneous. Involvement, as a construct linked to the degree of association between an individual and an object, has been recognized as an important factor in judging the consumer’s individual preferences; thus, it is a central concern in media-use research (Sun, 2008). From the segmentation perspective, both lowly involved and highly involved consumers are important because low-involvement consumers can be considered important potential customers (Park et al., 2007). Furthermore, the concept of involvement is generally considered a cognitive characteristic and enduring in nature (O’Cass, 2000), and it has been argued that characteristics of the environment and temporary changes in the consumers’ situation do not directly affect their levels of involvement (Rodríguez-Molina et al., 2015). Accordingly, the level of esports involvement can serve as a moderator that modulates the effect of the attributes of esports livestreaming media on viewer experiences because the consumers’ information-processing, judgement, and decision-making tend to depend on their level of involvement (see elaboration likelihood model [ELM] in Petty & Cacioppo, 1986).
According to ELM, individuals follow a peripheral or a central route depending on their motivation for processing the given information and their ability to evaluate that information, which ultimately affects the formation of individual attitudes and behavior. Specifically, if the level of an individual’s involvement is high, information is processed by the central route and evaluated based on information directly related to the target. On the contrary, when the involvement level is low, individuals follow the peripheral route and are generally led by the information indirectly related to the target (Petty & Cacioppo, 1986).
In sport media consumption, viewers’ satisfaction and flow experiences tend to vary depending on their involvement with the specific services (Kim & Ko, 2019). In the current study, building on Zaichkowsky’s (1994) definition of involvement, we operationalized esports involvement as the degree of interest in esports and importance and relevance of esports in an individual’s life. In the sport media context, Kim and Ko (2019) determined that users who are highly involved in sports tend to evaluate their sports media experience more in terms of central cues such as the quality of the sports game. On the contrary, users who are less involved tend to focus on peripheral cues such as the vividness of the media and telepresence.
According to the ELM, previous studies typically classified the attributes of livestreaming into central cues, which are directly related to the quality of the livestream itself, and peripheral cues, which are indirectly associated with the livestream in the research model (Yoo et al., 2017; Zeng et al., 2022). Most prior studies have followed this principle. However, to capture the specific characteristics of esports livestreaming media more accurately than many previous studies, the current study conceptualizes the attributes of media based on media richness theory, specifically focusing on interactivity, informativeness, and convenience as key factors. Given that the primary focus of the current study is on the influence of attributes of livestreaming esports media on viewer experience and loyalty, rather than solely on the attributes of esports livestreaming itself, the ELM suggests that factors indirectly related to the media are considered peripheral cues, such as the visual design of the media’s webpage, the reputation and word of mouth surrounding the media, and the media’s streaming quality. The factors or attributes directly associated with the media can serve as central cues, such as the three media attributes conceptualized in this study.
In fact, through extensive literature review, we noticed that while scholars agree on the importance of interactivity, there remains significant divergence regarding whether interactivity should be considered a central cue (Wang et al., 2018) or a peripheral cue (Yoo et al., 2017). Moreover, in the majority of the livestreaming literature, interactivity has been demonstrated to be an essential component of online livestreaming, positively influencing consumer stickiness (Ma, 2023) and consumer behavior (Zeng et al., 2022). Additionally, the study of Ahmadi and Hudrasyah (2022) on online consumer purchase intention in livestreaming commerce found that interactivity is considered a determining factor of argument quality as a central cue. In the current study, the essence of the concept of interactivity lies in the interactions and communications of viewers–viewers and viewers–broadcasters regarding the content and information presented in esports livestreams. Moreover, individuals without the relevant knowledge or expertise (i.e., less involved) simply cannot assess the quality of the information (Zhai et al., 2022) and are more inclined to rely on factors such as the reputation of the livestreaming media and its visual design as criteria for evaluating their viewing experience. Therefore, we believe that in the realm of esports livestreaming, viewers are more likely to perceive the interactivity of the media as a central cue. Within the context of esports livestreaming services, interaction via media is considered to be the main motivation for watching esports livestreams (Sjöblom & Hamari, 2017). Viewers who place great emphasis on the livestream viewing experience (high involvement) are more motivated to devote the cognitive effort required to evaluate the true merits of a livestream.
Therefore, highly involved viewers tend to spend more time interacting with others (Islam et al., 2021) and convey a higher experiential value (Shankar, 2021) of the interactivity of esports livestreaming, such that the viewing experience is enjoyable and satisfying. Indeed, compared to viewers with low involvement, highly involved viewers tend to feel excited by their interactive behavior and enjoy being immersed in their livestreaming experience (Islam et al., 2021). Thus, we hypothesized the following (H7–8):
The level of esports involvement will positively moderate the relationship between interactivity and viewer satisfaction.
The level of esports involvement will positively moderate the relationship between interactivity and flow experience.
Regarding informativeness, consumers’ cognitive effort in evaluating the cues presented in the media environment is different between those with high and low levels of involvement. Park et al. (2007) showed that highly involved customers have exact knowledge of the information they want and prefer to search for relevant information more intensively by themselves. Typically, highly involved customers are more likely to engage in thoughtful analysis in order to reduce feelings of risk (related to inaccurate, delayed, or incomplete information), and they dedicate more time to using online platforms and thoroughly evaluating the information provided (Dholakia, 1997). As a result, highly involved viewers may rely more heavily on the information provided by the platform during the esports livestreaming experience. In contrast, less-involved customers may lack esports-related knowledge and the ability or motivation to search for information, and they are not as willing to exert substantial cognitive processing and dissonance resolution efforts. Compared to viewers with high involvement, viewers with low involvement are more easily influenced by peripheral information cues (e.g., media reputation, word-of-mouth information, and public relations activities). Therefore, we hypothesized the following (H9–10):
The level of esports involvement will positively moderate the relationship between informativeness and viewer satisfaction.
The level of esports involvement will positively moderate the relationship between informativeness and flow experience.
Lastly, regarding convenience, scholars found that association between the convenience of a website and the positive attitudes and purchase intentions generated by the website will vary depending on the customer’s involvement in online shopping (Islam et al., 2021). According to Islam et al. (2021), when highly involved customers feel that e-shopping is more convenient and effortless, they tend to get excited and immersed in their shopping experiences. In other words, highly involved customers tend to give more value to convenient features of e-shopping websites, such as user-friendly interfaces and convenient search engines. In line with this notion, we speculated that highly involved viewers are more likely to be satisfied with the target media and reach a flow state more easily via the convenience of the media compared with lowly involved viewers. Thus, we hypothesized the following (H11–12):
The level of esports involvement will positively moderate the relationship between convenience and viewer satisfaction.
The level of esports involvement will positively moderate the relationship between convenience and flow experience.
Viewer Experience and Media Loyalty
In general, loyalty is defined as the customer’s repurchase and favorable word of mouth for a product or service (Oliver, 1999). Based on this definition, the current study conceptualized media loyalty as the viewer’s intention to use the same livestreaming media repeatedly and have the intention to pass on favorable recommendations to others. Loyal viewers tend to purchase long-term memberships or subscriptions and make donations or tips, which are main sources of revenue for a livestreaming media platform (Pham et al., 2021). Previous studies have revealed that customer satisfaction has been considered the main factor for building loyalty (Ryu et al., 2014). In the context of online game livestreaming services, viewer loyalty results from the viewer’s satisfaction with the media (Ho & Huang, 2009).
Additionally, there is considerable evidence in the literature that the flow experience has a significant impact on the user’s loyalty (Pham et al., 2021). For example, in a mobile Social Networking Services (SNS) environment, Zhou et al. (2010) confirmed that flow significantly enhanced the experiencer’s loyalty. Meanwhile, the flow experience allows individuals to feel gratified and influences the users’ well-being (Kim & Kim, 2022), reaffirming their intention to reuse along with an increase in their flow experience. Therefore, we hypothesized the following (H13–14):
Viewer satisfaction positively influences media loyalty.
Flow experience positively influences media loyalty.
As noted above, positive customer experiences significantly influence online gamer loyalty (Ryu et al., 2014). However, Mittal and Kamakura (2001) noted that customers with similar satisfaction levels exhibit varying degrees of repurchase behavior. For example, older consumers tend to display higher brand loyalty for offline physical products than their younger counterparts. This is attributed to their accumulation of brand-specific knowledge and experience (Ratchford, 2001). Conversely, younger individuals are more likely to seek and compare information actively, potentially leading to brand switching (Ratchford, 2001). However, this might be different in the online game environment. Pham et al. (2021) affirmed that when individuals accumulate experience in online gaming or frequently experience gaming stimuli, they may exhibit lower emotional responses or engagement. This could be because, according to the desensitization theory (Brockmyer, 2015; Bushman & Anderson, 2009), repeated or prolonged exposure to a particular stimulus can reduce emotional response or sensitivity. Highly involved viewers often consider esports viewing a crucial aspect of their lives, dedicating much time and effort to it, thus accumulating extensive viewing experience (Islam et al., 2021). However, according to the desensitization theory, highly involved individuals’ prolonged exposure to games may increase familiarity with the viewing experience, resulting in reduced sensitivity to esports content. On the other hand, for viewers with low involvement, who have less experience and exposure, esports can provide novel experiences and ignite excitement, satisfying such viewers and boosting their loyalty. Hence, we hypothesize as follows (H15–16):
Esports involvement negatively moderates the relationship between viewer satisfaction and media loyalty, such that the relationship is weaker for those with high involvement.
Esports involvement negatively moderates the relationship between flow experience and media loyalty, such that the relationship is weaker for those with high involvement.
Furthermore, as previously mentioned, we posit that viewer experiences during esports livestreaming (i.e., viewer satisfaction and flow experience), amplified by media attributes (i.e., interactivity, informativeness, and convenience), can serve as diagnostic clues for evaluating media loyalty (Ho & Huang, 2009; Pham et al., 2021). In a similar vein, when esports media provides interactive features, high-quality relevant information, and convenient viewing to engage viewers, it enhances their satisfaction with the overall viewing experience; this, in turn, leads to increasing viewer loyalty to the particular media. Therefore, we hypothesized the following (H17–22):
Esports livestreaming viewers’ satisfaction mediates the relationship between interactivity, informativeness, convenience, and media loyalty.
Esports livestreaming viewers’ flow experience mediates the relationship between interactivity, informativeness, convenience, and media loyalty.
To test our hypotheses, we identified three personal factors and controlled their effects: income, the frequency of media use, and the duration of media use. These variables are highly correlated with viewers’ media loyalty. The participant’s frequency and duration of media use was measured as a control variable because previous researchers have shown that the frequency and duration of usage can potentially affect a viewer’s media loyalty (Wang et al., 2021). A research model that summarizes the hypothesized relationships can be found in Figure 1. Hypothesized research model.
Methods
Participants and Procedure
In the current study, the target population was users of livestreaming media in South Korea who frequently watched esports via livestreaming media. To obtain quality data, the study samples were randomly drawn using Embrain (https://embrain.com/), a highly rated online survey firm. To ensure a representative sample, Embrain, which currently has seven million research panels, utilized a multistage random sampling technique based on geographic region and demographic characteristics to select survey participants. Furthermore, Embrain used rigorous selection procedures in which panel registration numbers were used to verify the identity of respondents, and then each respondent was double-checked via his or her legal name and membership identification. The survey system identified and eliminated respondents who completed too quickly or in recurring patterns to qualify for incentives. By participating in our survey, the participants were offered an incentive of 6,000 Korean won, a little more than $US4. Additionally, to ensure that the appropriate samples were collected, the survey was set up with two pieces of screening information: (a) “Have you ever experienced internet livestreaming?” (Participants had to say “yes” to answer the next questions; otherwise, they were forcibly moved to the end of the survey.); and (b) “Have you recently watched esports via livestreaming media? (Participants who answered “none” were removed from this data purification process.). Consequently, of 600 total online questionnaires obtained, we excluded 32 cases that either included dishonest answers or were treated as insufficient responses, leaving 568 useful cases for analysis. The participants consisted of 301 males (53%) whose average age was 28.67 years (SD = 5.79). A majority of the participants (n = 440 77.4%) had a bachelor’s degree, and 55 participants (9.7%) had a graduate-level education.
Instrument
Seven constructs were assessed using existing scales on 7-point Likert-type scales, ranging from 1 = “not at all” to 7 = “very much.” Specifically, we modified and adopted existing scales to measure three attributes of esports livestreaming media, including interactivity (four items; Chen & Lin, 2018; Hu et al., 2017), informativeness (five items; Huang et al., 2017; Hsu et al., 2020), and convenience (four items; Hwang & Lim, 2015; Jiang et al., 2013). Viewing satisfaction was measured using three items adopted from Ho and Huang (2009). Based on the extensive literature review, we conceptualized viewers’ flow experience as a psychological state characterized by cognitive absorption, time distortion, and enjoyment. These three aspects were measured with eight items adopted from Kim and Ko’s (2019) sport media consumption. Media loyalty was measured with three items from Ho and Huang (2009). Lastly, we measured esports involvement using three items adopted from the previous studies (Kim & Ko, 2019).
Measurement Coefficients, Reliability, and Convergent Validity.
Data Analysis
Before testing the hypotheses, we performed a confirmatory factor analysis (CFA) to establish validity of the measurement model using Mplus 8. To test our research hypotheses, we conducted a latent moderated structural equations (LMS) modelling using a two-step evaluation method (Klein & Moosbrugger, 2000). Based on this approach, the current study estimated the model (hereafter referred to as Model 0) without latent interaction terms, and the evaluation was performed based on the existing fit index (i.e., χ2/df ratio, CFI, TLI, RMSEA, and SRMR) in the first step. Once the model fit indices ensured that Model 0 fit the data well, the second model (hereafter referred to as Model 1) with interaction terms was estimated. To evaluate the model fit of Model 1, the log-likelihood difference test was performed by using a formula (D = −2[log-likelihood value of Model 0 − log-likelihood value of Model 1]) with the difference of degree of freedom between the two models (△df). When the log-likelihood difference test was statistically significant, we were able to use and interpret the path coefficients of Model 1. Based on the path coefficients of the interaction terms in Model 1, we were able to determine the moderating role(s) that a certain variable(s) played in a hypothesized structural model.
Results
Measurement Model Validation
Summary Results of Measurement Model Validation.
Note. The diagonal shows AVE values of each construct. Correlations are under the diagonal, and squared correlations are above the diagonal. INT = interactivity; INF = informativeness; CON = convenience; INV = esports involvement; VS = viewer satisfaction; FLOW = flow experience; ML = media loyalty.
Common Method Bias
We examined potential common method bias by estimating a measurement model in which all measurement items were loaded with a single latent construct (Podsakoff et al., 2003). Otherwise, erroneous perceptions about the adequacy of a scale’s reliability and convergent validity might have arisen (Williams et al., 2010). If common method bias poses a threat, a single latent factor model should yield a better fit than the multifactor model (Podsakoff et al., 2003). The CFA results of the model for a single latent variable indicated that the single-factor measurement model did not fit the data, suggesting that common method bias was less likely to exist (χ2/df = 3478.445/324 = 10.736, CFI = .638, TLI = .608, and RMSEA = .131).
Hypothesis Testing
To test the hypotheses established in this study, a LMS analysis was performed. Based on the two-step evaluation method suggested by Klein and Moosbrugger (2000), this study estimated the structural model (Model 0), excluding the latent interaction factors (interactivity × esports involvement, informativeness × esports involvement, convenience × esports involvement, satisfaction × esports involvement, flow experience × esports involvement) in the first step. The results indicated an acceptable model fit between the specified model and data: χ2 (382) = 2.756, CFI = .942, TLI = .934, RMSEA = .056, and SRMR = .071. Therefore, we proceeded to the second step, where we estimated the structural model (Model 1) including the latent interaction factors (interactivity × esports involvement, informativeness × esports involvement, convenience × esports involvement, satisfaction × esports involvement, flow experience × esports involvement), and performed the log-likelihood ratio test of Models 0 and 1 (see log-likelihood ratio test in Klein & Moosbrugger, 2000; Maslowsky et al., 2015). As a result, Model 1 with the latent interaction terms was found to statistically outperform Model 0 (D = 2[|−18333.073|–| −18323.094|] = 19.958, △df = 8). Accordingly, we interpreted the path coefficients from Model 1 to test the hypotheses.
The results revealed that the path coefficient from interactivity to viewer satisfaction was not statistically significant (β = .025, p = .498, f2 = .021 1 ). Therefore, H1 was untenable. The path coefficients from informativeness (β = .311, p < .001, f2 = .081) and convenience (β = .260, p < .001, f2 = .130) to viewer satisfaction were statistically significant. Hence, H2 and H3 were supported. However, interactivity did not significantly impact flow experience (β = −.007, p = .875, f2 = .021); therefore, H4 was untenable. The path coefficients from informativeness (β = .213, p < .01, f2 = .034) and convenience (β = .114, p < .01, f2 = .043) to flow experience were statistically significant; hence, H5 and H6 were supported.
In terms of the moderating roles of esports involvement (H7–H12), the results indicated that the path coefficients from the latent interaction terms between esports involvement and interactivity to viewer satisfaction (β = .145, p < .001) and flow experience (β = .108, p < .01) were significant, thus supporting H7 and H8. Regarding H9 and H10, esports involvement was found to negatively moderate the effect of informativeness on viewer satisfaction (β = −.148, p < .05) whereas it had no moderating effect on the relationship between informativeness and flow experience (β = −.076, p = .208). Therefore, H9 was supported, but H10 was untenable. With regard to H11 and H12, esports involvement did not moderate either the relationship between convenience and viewer satisfaction (β = −.055, p = .218) or the relationship between convenience and flow experience (β = −.032, p = .553). Thus, H11 and H12 were untenable. Furthermore, the path coefficients from viewer satisfaction (β = .352, p < .001, f2 = .068) and flow experience (β = .230, p < .001, f2 = .144) to media loyalty were statistically significant. Taken together, H13 and H14 were thus supported.
In terms of the moderating roles of esports involvement (H15–H16), esports involvement was found to negatively moderate the effect of viewer satisfaction (β = −.111, p < .05) and positively moderate the effect of flow experience (β = .101, p < .05) on media loyalty. Therefore, H15 was supported, but H16 was untenable.
Regarding the explanatory power of our research model, our theoretical model explicates a percent of 53.1 variances in viewer satisfaction, a percent of 51.1 variations in flow experience, and a percent of 43.6 variations in media loyalty, demonstrating adequate explanatory power.
Standardized Indirect and Total Indirect Effects.
Results of Hypothesis Testing. Note. INT = interactivity; INF = informativeness; CON = convenience; INV = esports involvement; VS = viewer satisfaction; FLOW = flow experience; ML = media loyalty.
Discussion
Drawing on the media richness theory, flow theory, and ELM principles, the current study investigated the influences of media attributes on viewer experience and the formation mechanism of media loyalty in the context of esports livestreaming services. Although sport communication scholars and practitioners have realized that the properties of the media itself play an important role in developing media loyalty (Koo, 2018; Ryu et al., 2014), understanding the theoretical relationships is still nascent in the esports livestreaming context. The current research explored psychological mechanisms of developing media loyalty, particularly focusing on specific media attributes and consumer involvement. The current study offers several meaningful theoretical and managerial implications.
Theoretical Implications
The intricate interplay of media attributes and their impact on viewer experience resonates with Sundar et al.’s (2019) MAIN model. Sundar asserts that each medium possesses specific affordances—distinct functionalities, properties, or capabilities. These attributes collectively shape the media environment, transforming it from a mere conduit of information into an interactive space with unique characteristics. The MAIN model categorizes media affordances into modality, agency, interactivity, and navigability, which are pivotal in shaping user perceptions. The model elucidates how media attributes influence individuals’ attitudes and behavioral intentions toward products or services. However, the impact of such attributes in the context of esports has not been explored. The present research unveils the psychological mechanisms underlying viewers’ experiences, thus extending our theoretical understanding of the role of media attributes in establishing media loyalty.
First, the informativeness and convenience media attributes significantly influence viewer satisfaction in livestreaming service. Of the two attributes, according to Parasuraman et al. (1988), standardized slope coefficients can verify the relative importance of variable components and suggested that higher coefficients had higher importance. Although the result indicates that the path coefficients are similar on viewer satisfaction, the effect of informativeness on satisfaction was greater than convenience. This implies that enhancing the ability of esports livestreaming media to provide information, such as timely game results, adequate game schedules, and useful anchor information, directly influenced the level of satisfaction associated with the livestreaming media. Meanwhile, convenience was another salient driver of esports viewer satisfaction and continued use. This result is consistent with the findings of Duarte et al.’'s study (2018), which showed that online user satisfaction is engendered by online convenience, which, in turn, enhances behavioral responses including electronic word of mouth (eWOM). Interestingly, we found that the informativeness attribute had a more pronounced effect on flow experience than convenience did. Past research (Bao & Yang, 2022; Jeon et al., 2018) showed that informativeness is a crucial feature for inducing the flow experience because information with relevant, complete, and timely content will generate the experiences of concentration and enjoyment, which triggers the perception of the flow experience more easily and improves the willingness of the viewers to involve themselves in esports livestreaming viewing via the media.
Surprisingly, in contrast to existing studies (Su et al., 2016) and our prediction, interactivity did not play a significant role in viewer satisfaction and flow experience. However, this does not mean that interactivity assumes a lesser role in influencing viewer experiences (Qian et al., 2020b). This result can be explained by desensitization theory (Brockmyer, 2015; Bushman & Anderson, 2009), which suggests that repetitive stimulation or exposure (i.e., frequent, similar, and repetitive interaction experiences) should reduce the individual’s psychological responses (i.e., satisfaction and flow experience). As Brockmyer (2015) noted, repeating a similar task for a certain period of time reduces the perceived novelty, and task novelty is a critical factor in the individual’s experience (Yang et al., 2020). Therefore, one of the reasons for this result may be the monotonous form of interaction in esports livestreaming media and the lack of updates. Additionally, the measure used in the current study focused on two interaction aspects: viewer–viewer and viewer–broadcaster. However, due to the substantial number of viewers in esports livestreams, it may be difficult for broadcasters to immediately respond to or interact with each viewer through chat messages, which leads to untimely responses and ineffective communication. This might also be another alternative explanation of the result.
Second, esports involvement was found to moderate the effect of each attribute on user experiences in different directions. That is, viewers evaluated their experiences by weighing different informational cues depending on their perceived importance of esports. These findings correspond to the principle of ELM (Petty & Cacioppo, 1986). Particularly, the path coefficient from the latent interaction term between interactivity and esports involvement to viewer satisfaction became statistically significant; that is, the effect of interactivity on viewer satisfaction and flow experience escalated as the level of esports involvement increased. This may be because viewers who attributed greater importance to esports preferred the interaction and may have felt more pleasure and enjoyment than did low-involvement viewers. However, contrary to the hypothesis, the effect of informativeness on viewer satisfaction escalated as the level of esports involvement decreased, and there were no significant moderation effects on the association between informativeness and flow experience. This result conflicts with classic information processing models (e.g., ELM), but is considered novel and important. As noted earlier, the ELM suggests that highly involved consumers tend to central cues, whereas less involved people are influenced by peripheral cues. However, some researchers have posited that individuals undergo entirely distinct decision-making processes in specific situations (e.g., affective choice mode [ACM], Mittal, 1988). Mittal (1988) suggested that in hedonic consumption, individuals' decision-making processes are driven by their emotional state rather than rational thinking, even if they have high product involvement. Moreover, emotional message appeal has a greater impact than factual information in facilitating this psychological mode because it aligns more closely with the core value of hedonic consumption (Mittal, 1988). For example, Asada and Ko (2016) extended the ACM in the sport viewership context and noted that individuals with abundant event memories rely on their memories and external information to construct images of their future viewership, they are not influenced by the content of WOM messages; whereas people with fewer memories need to seek further information from external sources. In line with this principle, a possible explanation for our current finding is that, as a hedonic experience, the information processing of viewers who highly involved in esports livestreaming was mainly affected by their emotional state and may rely more on their own previous knowledge and judgment (i.e., viewers’ memory), considering the platform-provided information as complementary rather than as the sole basis for their experience evaluations. However, due to the lack of memories (e.g., previous experience) or motivation, less-involved viewers may pay more attention to factual information, i.e., informativeness-related factors (e.g., information quality, information richness, and topical relevance) in order to saves resources—including time, effort, and processing costs—and enhance their entertainment enjoyment, thereby increasing viewer satisfaction (Shin et al., 2016). In conclusion, this study’s integration of the ELM and ACM theories in the context of esports live streaming contributes to the sports communication and management literature, offering valuable insights into information processing. In addition, the insignificant moderation effects of involvement indicate that, regardless of the level of esports involvement, convenience is viewed as a fundamental attribute of media and an important antecedent of satisfaction and flow experience, which supports previous findings (Hwang & Lim, 2015; Kim & Kim, 2022).
Third, the study results verified that viewer satisfaction and flow experience exerted a positive effect on media loyalty, which was consistent with most of the literature (Koo, 2018; Su et al., 2016). When esports viewers felt psychological fulfillment or achieved an optimal mental state, their loyalty toward that media increased. Furthermore, the effect of flow experiences on loyalty was found to be greater than that of viewer satisfaction. This finding can be interpreted to mean that viewers evaluate esports media while relying more on the feeling of the optimal flow state during their viewing experiences. This interpretation corresponds to the sport media consumer literature suggesting that a sense of experience of complete concentration and full enjoyment plays a more significant role in predicting loyalty in the context of hedonic consumption than does pure psychological fulfillment (Liao & Teng, 2017).
Fourth, while prior researchers have explored the significance of positive consumption experiences as key predictors of loyalty, further research is needed to inform both the academic community and industry professionals about the intricate process of media loyalty formation, especially as it pertains to future media consumption studies on those who do not form media loyalty. Our research advances the study of media loyalty in the context of esports and proposes boundary conditions for the formation of media loyalty, which makes a significant theoretical contribution to the field of sports communication management literature. Specifically, we found that positive viewing experiences may not always lead to strong media loyalty under certain circumstances. Notably, viewer satisfaction and flow experience, two crucial constructs of the positive viewing experience, exhibit markedly different impacts on media loyalty under the moderating effect of esports involvement. Viewers with less involvement emphasize viewer satisfaction in esports livestreaming more, deeming it a crucial factor in enhancing loyalty. Conversely, for those with high involvement, flow experience exerts a more substantial influence on media loyalty. A reasonable explanation for this finding is that, in comparison to individuals with less involvement, highly involved viewers have extensive experience with esports livestreaming (Zaichkowsky, 1994). According to the desensitization theory (Brockmyer, 2015; Bushman & Anderson, 2009), positive responses will decrease in viewers repetitively exposed to stimuli over an extended period (i.e., experienced individuals). Therefore, viewers with lower involvement are more likely to derive enjoyment and satisfaction from the livestreaming experience, leading to the formation of loyalty. Conversely, to avoid becoming bored with a familiar viewing experience, highly involved viewers tend to seek immersive experiences to derive enjoyment, thereby maintaining their loyalty to the media and being more likely to recommend it to others. Flow experience provides a profound sense of pleasure that surpasses mere satisfaction (Chen et al., 2000).
From the results of verifying the relationship between media attributes and media loyalty, this study found that viewer satisfaction and flow experience partially mediated this relationship (excluding interactivity). Prior studies suggest that informativeness (Hanaysha & Momani, 2021) and convenience (Ozturk et al., 2016) act as decisive factors influencing customers’ loyalty. They assumed that informativeness and convenience directly determine intention or future behaviors. In this regard, the empirical evidence of the mediating role of viewer satisfaction and flow experience provides crucial theoretical insight, as it explains the mechanism through which esports livestreaming media influences viewers’ future behavior based on the viewing experience.
In sum, the current study makes an important theoretical contribution to the esports media literature. First, based on the media richness theory (Daft et al., 1987) and the concepts of media richness, we proposed interactivity, informativeness, and convenience as the principal attributes of esports livestreaming media in our research model and validated the model by exploring the moderating role of involvement. The differential impact of the three dimensions on customer satisfaction and flow experience extend theoretical knowledge on media consumers and their psychological process of building loyalty.
Managerial Implications
The results of the current study suggest that improving informativeness and convenience of esports livestreaming media is crucial to increase viewer satisfaction and flow experience and ultimately impact viewers’ media loyalty. To improve the informativeness attribute of media, managers need to continually update relevant information in a timely, accurate, and comprehensive manner. Additionally, media producers should develop some auxiliary functions. For example, to cultivate informativeness gratification, broadcasters can use effective methods (e.g., illustrations and animation) for making information more readable and comprehensible. Such elements are particularly important for low-involvement viewers.
Second, it is important for managers to provide a user-friendly media design to help minimize viewers’ time and effort while maximizing entertainment value. For example, AfreecaTV, YouTube, and Twitch allow for convenient syncing across multiple devices and easy access to viewers’ favorite content. AfreecaTV also recommends to viewers latest content based on their habits or previously viewed broadcasters.
Third, understanding the moderating effect of viewers’ involvement is meaningful because it helps managers of esports livestreaming media glean new insights into upgrading the media and the formulation of effective segmentation strategies. Specifically, providing interesting and interactive features (e.g., communication communities, topic groups, gift features, and funny emoticons) to highly involved esports viewers to create a rich viewing experience could be an effective strategy for enhancing their esports livestreaming media loyalty. In contrast, to attract the low-involvement group, managers may focus on informativeness (e.g., timely updates of game schedules and results and useful anchor information).
Furthermore, based on the research findings regarding the moderating effect of esports involvement on the relationship between positive viewing experiences (i.e., satisfaction and flow experience) and media loyalty among esports viewers, this study has uncovered a rarely observed outcome: in the process of media loyalty formation, less involved viewers are more concerned about whether their media usage satisfies them, while those with high involvement seek immersive experiences. Based on these findings, we offered several constructive recommendations for livestreaming media platforms. Media developers need to develop innovative media features and regularly update supplementary functionalities. Examples include offering a diverse range of entertaining gift features (Liu et al., 2022) and gamification mechanics (Qian et al., 2022). Moreover, livestreaming media could collaborate deeply with game developers to jointly introduce distinctive game features and experiences. Optimizing user interfaces and interactive functionalities ensures that the experienced user base remains deeply engaged throughout the livestreaming process, thus reinforcing loyalty among players with extensive gaming experience. Additionally, to maximize viewers’ flow experience, managers need to minimize distractions (e.g., excessive ads, inappropriate ad placement, and irrelevant comments) during esports livestreams to enhance their media loyalty.
Limitations and Future Research Directions
Several limitations need to be addressed for creating future research opportunities. First, we collected the main data from the target population in South Korea who had experience with livestreaming esports media based on a cross-sectional design. Therefore, care should be taken when generalizing the results from this study to other media or platforms (e.g., online shopping and learning platforms). In addition, future research could explore how distinct cultures may affect the research model by setting cultural backgrounds as a boundary condition.
Second, this study did not uncover any significant effects of interactivity on viewer satisfaction and flow experience. However, it has been well established in the literature that interactivity is one of the key attributes of livestreaming platforms (Qian et al., 2020b; Su et al., 2016). Instead of focusing on overall interactivity as an attribute of esports livestreaming media, future research may consider incorporating more detailed subcategories of interactivity, such as the viewer–message level (e.g., viewer–danmaku, viewer–chat window) and the viewer–broadcaster level (e.g., connectivity and responsiveness), as well as the viewer–media level (e.g., smoothness and vividness). Future studies should also consider incorporating the viewer’s psychological experiential factors—such as loneliness, sense of belonging, and happiness—alongside general experiential factors to gain a better understanding of how interactivity influences the viewing experience from a psychological perspective.
Third, in addition to the moderating effect of esports involvement, scholars could use the intensity and frequency of viewing esports livestreams or viewing goals and motivations as boundary conditions to deeply understand the effect of the media attributes on viewing experiences and media loyalty.
Conclusion
Despite the (de)limitations of the current study, the research outcome makes several theoretical contributions to the media and consumer-behavior literature. For one, the findings extend the application of the media richness model and ELM in the context of esports livestreaming media. By doing so, we can improve our understanding of the underlying mechanism for how media attributes maximize media loyalty and provide valuable insights for esports livestreaming media developers and managers harnessing esports livestreaming media as a viable means of improving the viewers’ experiences and enhancing their loyalty.
Footnotes
Declaration of Conflicting Interests
The author(s) declared no potential conflicts of interest with respect to the research, authorship, and/or publication of this article.
Funding
The author(s) received no financial support for the research, authorship, and/or publication of this article.
