Antecedents and consequence associated with esports gameplay

Abstract

Purpose 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. Design/methodology/approach 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. Findings 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. Originality/value 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.

Social Atmospherics, Affective Response, and Behavioral Intention Associated With Esports Events

“…The survey items related to the social atmospherics of esports events, affective responses, and behavioral intention were adapted from Wakefield and Sloan (1995) (i.e., social density), Brocato et al (2012) (i.e., suitable behavior and similarity), Uhrich and Benkenstein (2012) (i.e., affective response), and Jang and Byon (2020) (i.e., behavioral intention). Based on the review of the literature, we adapted cosplay (three items) and cheering behavior (four items).…”

“…Social identity theory has focused on the dimension of similarity because individuals want to be members of or included in social groups, and “the intergroup categorization leads to favoring the in-group and discriminating against the out-group ” ( Tajfel, 1981 , p. 386). Since most esports fans have experienced esports gameplay ( Jang and Byon, 2020 ) and because esports events attendance might signify that attendees are enthusiastic esports fans, it may be reasonable to suggest that esports event spectators are identified as gamers. Furthermore, Brocato et al (2012) found that similarity significantly influenced consumers’ responses.…”

“…More specifically, scholars have prompted and largely facilitated in-depth discussions regarding the definition of esports and the qualification of esports as sport and sport management scholarship ( Cunningham et al, 2018 ; Hallmann and Giel, 2018 ). Researchers have also empirically examined esports consumer behavior in different contexts such as esports gameplay ( Seo, 2016 ; Jang and Byon, 2020 ), online esports media consumption ( Sjöblom and Hamari, 2017 ; Qian et al, 2019 ), and esports event attendance ( Pizzo et al, 2018 ).…”

Proposing a TAM-SDT-Based Model to Examine the User Acceptance of Massively Multiplayer Online Games

“…The flow experience is divided into three constructs [ 19 ]: (1) focused attention, (2) control, and (3) curiosity. Online games can take great concentration by immersing the user in a virtual world [ 56 ]. In this respect, the flow experience in online games could measure the user attention during the game which would be related to the difficulty to play it [ 18 ].…”

“…It is usually assumed that these tasks are difficult and demand the whole user concentration [ 18 ]. In this manner, flow experience is related to continuance intention [ 4 , 15 , 19 , 56 ]. Supported on this, the following hypothesis has been proposed:…”