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Recently, Jang and Byon (2020) found that esports recreational gameplay consumption is causally linked to esports online media consumption. In the context of esports, live-streaming content (by individual creators) is a new type of media consumption, which should be distinguished from esports event broadcast. Extending Jang and Byon’s finding, the purpose of this study is to examine the mediating effect of esports content live streaming in the relationship between esports recreational gameplay and esports event broadcast because it allows the games to be more accessible to viewers due to two-way communication. In order to test for stability of the mediating effect of esports live content streaming, we examined the hypothesized model across the three genres (i.e. imagination [n = 224], physical enactment [n = 195], sport simulation [n = 179]).

Data (N = 598) were collected via an online survey from individuals who had experienced esports recreational gameplay. A total of 15 items with five dimensions (i.e. esports recreational gameplay, esports content live streaming, esports event broadcast, streamer identification, and pro-player identification) were adapted from existing studies. The two identification constructs and gender were used as control variables.

The model fit of the measurement model was found to be acceptable via CFA. The results of SEM indicated that the intention of esports content live streaming consumption played a full mediation role in the relationship between esports recreational gameplay behavior and the intention of esports event broadcast consumption. Additionally, we found the mediating effect of esports content live streaming across the three genres.

This study contributes to literature related to the esports consumer behavior by conceptualizing esports content live streaming and found that esports content live streaming represents a mechanism that underlies the relationship between esports recreational gameplay intention and esports event broadcast consumption.

The purpose of this paper is to investigate why do people spectate eSports on the internet. The authors define eSports (electronic sports) as “a form of sports where the primary aspects of the sport are facilitated by electronic systems; the input of players and teams as well as the output of the eSports system are mediated by human-computer interfaces.” In more practical terms, eSports refer to competitive video gaming (broadcasted on the internet).

The study employs the motivations scale for sports consumption which is one of the most widely applied measurement instruments for sports consumption in general. The questionnaire was designed and pre-tested before distributing to target respondents (n=888). The reliability and validity of the instrument both met the commonly accepted guidelines. The model was assessed first by examining its measurement model and then the structural model.

The results indicate that escapism, acquiring knowledge about the games being played, novelty and eSports athlete aggressiveness were found to positively predict eSport spectating frequency.

During recent years, eSports (electronic sports) and video game streaming have become rapidly growing forms of new media in the internet driven by the growing provenance of (online) games and online broadcasting technologies. Today, hundreds of millions of people spectate eSports. The present investigation presents a large study on gratification-related determinants of why people spectate eSports on the internet. Moreover, the study proposes a definition for eSports and further discusses how eSports can be seen as a form of sports.

Grounded in the Unified Theory of Acceptance and Use of Technology 2 (UTAUT2) (Venkatesh et al., 2012), the purpose of this paper is to examine the antecedents and consequence associated with esports gameplay by proposing the Esports Consumption (ESC) model, including six determinants of esports gameplay intention (hedonic motivation, habit, price value, perceived effort expectancy, social influence and flow) and behavioral consequence (media consumption intention of esports events) that were linked to esports gameplay.

The proposed model was tested using the data (n=348) that were collected from esports consumers at two points in time. Per the technology adoption theories (i.e. TAM, UTAUT2), the authors incorporated a temporal separation when measuring the relationship between playing intention and playing behavior. For the purpose of data analysis, CFA and SEM were used to examine the hypothesized model.

As a result, four determinants (i.e. hedonic motivation, price value, effort expectancy and flow) were identified as the critical factors influencing esports consumers’ esports gameplay intention. Furthermore, the bootstrap method procedure verified that a sequential relationship among esports gameplay intention, esports gameplay and media consumption of esports events.

Theoretically, it has developed a research model that explains various triggers resulting from esports gameplay intention, which is causally linked to esports gameplay and media consumption behavior. Practically, the primary implication has to do with providing information regarding esports consumers’ playing behavior with esports game publishers, which organize esports events and leagues.

Esports is rapidly growing in popularity and viewership. The study's purpose was threefold: (1) to provide a systematic review and synthesis of esports spectatorship research. (2) to provide a reference for the psychology of consumer behavior in esports live streaming and esports event attendance. (3) to deliver a clear picture of the factors that impact consumer behavior in esports online and on-site consumption.

The study systematically reviews motivational aspects of online and on-site spectatorship using the Preferred Reporting Items for Systematic Review and Meta-Analysis Protocols (PRISMA). SCOPUS and Google Scholar were selected as social science databases. Twenty-five papers met the inclusion criteria: (1) published between 2000 and 2022, (2) empirical investigation, (3) focus on online and/or on-site esports spectatorship/events. Five papers implemented randomization to assess common method bias.

Twenty-five papers qualified for subsequent analysis. The papers were mostly quantitative. They included a theoretical framework and investigated online esports spectatorship. Significant antecedents for motivation to watch esports online and/or on-site were fanship, tension release, entertainment, escaping everyday life and unique features like chat and direct communication. No consensus was found concerning similarities or differences between online and on-site esports spectatorship and traditional sports spectatorship.

This research contributed to a new theoretical, methodological and practical agenda. A more comparative approach analyzing contextual, structural and demographic cues could lead to a holistic picture of esports spectator motivation.

Electronic Sports (eSports) is an emerging sector of the sports and entertainment industry experiencing an accelerated increase in consumer and sponsor demand. This paper aims to study selected cases of eSports service ecosystems, to identify similarities and differences and to understand the different roles, relationships and multiple interactions of actors involved in value co-creation processes.

This empirical paper follows the service-dominant logic to highlight value creation. Based on the sport value framework, an organizing logic for the actors in sports-related ecosystems to exchange service and co-create value, the authors apply the conceptualization of an eSports service ecosystem framework in which actors create value through their interactions. A case study approach was applied to qualitatively describe two cases of value co-creation by multiple actors during three eSports events. Case study 1a is the 2019 League of Legends World Championship Finals in Paris. Case study 1b is the 2020 League of Legends World Championship Finals in Shanghai. Case study 2 is the BLAST Premier Counter-Strike: Global Offensive Global Final 2020, which was entirely virtual.

The outcome is an empirically investigated conceptual framework of multiple actors co-creating value within a service ecosystem in eSports. The insights of the cases explain how actors interact with each other and co-create value during events in eSports ecosystems. The cases illustrate interactions in the context of eSports where the actors are connected within ecosystems. This enables further development of a value co-creation concept and a better understanding of value co-creation in eSports.

This study contributes to research by explicating a theoretically grounded framework for eSports service ecosystems based on empirical evidence. This research extends the scope of value co-creation beyond the firm–customer dyad to a service ecosystem in eSports, demonstrating the dynamic interactions of multiple actors.

While each genre and gender has been revealed as significant moderators for esports gameplay intention, exploring the interaction effects between genre and gender could broaden our understanding of the drivers’ relative effects on esports gameplay intention. Thus, the purpose of this study is to examine the interaction effects of gender and genre in the relationship between esports gameplay intention and its drivers (i.e. hedonic motivation, habit, price value, effort expectancy, social influence and flow).

The hypothesized model was examined using data from a sample (N = 1,194). For the purposes of data analysis, confirmatory factor analysis and structural equation modeling were used to examine the hypothesized model. Then, a series of structural invariance tests were conducted to compare the interrelationship between the six determinants and esports gameplay for the six-group model.

The results of the six-group model comparison indicated that the interaction between gender and genre moderates the relationship between drivers and esports gameplay intention. In particular, the following moderation effects were observed: (1) “social influence-esports gameplay intention” between “male-physical enactment” and “female-physical enactment”; (2) “habit-esports gameplay intention” and (3) “effort expectancy-esports gameplay intention” between “female-imagination” and “female-physical enactment”; (4) “hedonic motivation-esports gameplay intention” and (5) “effort expectancy-esports gameplay intention” between “female-physical enactment” and “female-sport simulation.”

The findings of this current study contributed to clarifying the genre and gender effects in esports gameplay intention and thus the extension of the Esports Consumption (ESC) model (Jang et al., 2020a) and the technology adoption literature. Since the ESC model grounded the Unified Theory of Acceptance and Use of Technology 2 (UTAUT2), the improvement of the ESC model extended UTAUT2. In consumer behavior research in the esports context, this current study contributed to the extension of UTAUT2 on the new moderating mechanisms by adding the interaction between gender and esports game genre.

The tremendous market growth of mobile platforms for esports underscores the need to understand players' psychological states and consumption behavior. Based on flow theory, this study examines players' psychological states (flow and clutch experiences) and consumption behavior based on the interaction effects of playing frequency, playing duration and players' levels on the PC (LOL – League of Legends) and mobile (LOLWR – League of Legends: Wild Rift) versions of the same esports title.

Data were collected from 930 valid responses and analyzed with confirmatory factor analysis and multiple regression (PROCESS macro, Model 3).

There are two main findings. First, across PC and mobile participants, casual gamers (low playing frequency and duration) have firm purchase intention when they have a clutch experience, but flow experience hinders their purchasing intention. Second, hardcore gamers' (high playing frequency and duration) psychological states are clearly distinguished according to technological platforms. Flow experience is the most effective for their purchase intention in the PC platform, but both flow and clutch states are important in the mobile platform. Flow experience is essential overall for hardcore gamers to intend their in-game item purchasing.

This study has two primary originality/values. First, this study explores flow and clutch together to measure psychological states and the impact on the purchase intention of in-game items. Second, the interacting effects of playing frequency, duration, and skill level with technical platforms (i.e. PC and mobile) for esports gaming.

This study aimed to understand better what makes esports fans engage with streamers' live-streaming of esports gameplay. This study used the Theory of Planned Behavior (TPB) and additionally adopted streamer identification and esports game identification as moderating variables.

Data were collected from streamers' esports content streaming viewers over 18 years of age using an online survey in Amazon M-Turk (N = 307). Based on past esports live-streaming weekly watching hours, which range from 1 to 45 h, the participants were divided into lower (n = 152) and higher (n = 155) frequency groups. PLS-SEM and bootstrapping techniques were used to test the moderated mediation relationships among the constructs.

This study found a negative moderating effect of past watching experience on the relationship between attitudes and behavioral intention, and it positively moderated the path between perceived behavioral control and behavioral intention. Also, it was found statistically significant direct impacts of streamer identification (STI) and esports game identification (EGI) on attitude and subjective norms. While the indirect impact of STI on behavioral intention through attitude was statistically significant, there were no significant indirect impacts of EGI on attitude and behavioral intention through subjective norms.

Theoretically, this study extends the TPB model by exploring the two identifications (i.e. streamers and esports games) as antecedents of the focal TPB factors (i.e. attitudes, subjective norms and perceived behavioral control) and the moderating effect of prior experience based on high/low weekly watching frequencies. Practically, content creators of esports live-streaming and live-streaming platform managers can use the study’s findings to develop strategies to nurture their current and future viewership.

The purpose of this study is to present a conceptual model where consumer electronic sports (eSports) engagement (CeSE) acts a predictor for gamers’ online engagement in eSports-related products/firm either through direct contribution (purchase intention) or indirect contribution (co-production, community engagement, word-of-mouth and recruitment).

Data from 262 eSports consumers aged 18–24 years were collected and analyzed through WarpPLS 8.0.

The findings of this study confirm that CeSE significantly influences all dimensions of the consumption behaviors (purchase intention, co-production, community engagement, word-of-mouth and recruitment).

This study provides empirical support for a conceptual framework developed through the social exchange theory and engagement theory. Besides, hierarchical component model approach is applied to estimate the composite model of CeSE.

This paper aims to shed novel light to further the ongoing debate about the relationship between traditional sports and eSports by gathering empirical evidence on the role that eSports play on the consumption of traditional sports (i.e. live matches at the Stadium, TV matches spectating, merchandise or sponsor purchase), in the peculiar context of soccer.

An extensive literature review on both sports and eSports consumption has informed the creation of a novel dataset through the design and administration of a structured questionnaire to Italian citizens 18+. Questions were about eSports and soccer consumption, information-seeking behaviour and psychometric factors. All constructs have been measured against validated scales. A total of 279 high-quality responses have been analysed through a prediction model based on regression trees in the Machine Learning domain.

Results show that soccer consumption is predicted by the degree of vicarious achievement (positive effect), the degree of playing sport-related eSports (positive effect) and the degree of playing non-sport-related eSports (negative effect). Vertical analyses have been on sub-dimensions of soccer consumption (attending live matches at the Stadium, spectating TV matches, buying merchandise or sponsors’ products).

To the best of our knowledge, this study is the first to offer empirical evidence to bridge two main limitations: the lack of studies about the eSports-soccer consumptions relationship and the reduction of soccer consumption as just Stadium attendance. Our results have both theoretical and practical implications.