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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.

PurposeThe purpose of this paper is to develop the scale of destination image (SDI) to assess destination image affecting the consumption associated with tourism.Design/methodology/approachThe scale was developed through four steps: review of literature, formulation of a preliminary scale, confirmatory factor analysis (CFA), and examination of predictive validity by a structural equation modeling (SEM) analysis. The preliminary scale consisted of 32 items. Employing a systematic sampling method, a total of 199 research participants responded to a mail survey.FindingsIn the CFA with maximum likelihood estimation, four factors with 18 pertinent items are retained. This four‐factor model displays good fit to the data, preliminary construct validity, and high reliability. The SEM analysis reveals that the SDI is found to be positively predictive of tourism behavioral intentions.Originality/valueThis paper develops an original multi‐dimensional 18‐item scale measuring destination image from the perspective of tourists, which can provide academicians and practitioners with a reliable and valid analytical tool to assess destination image.

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2016-12-24T18:10:15