Examination and Analysis Theory of Acceptance and Use of Technology (UTAUT2) In Esports

Introduction
In recent years, electronic sports (Esports) have emerged as a prominent dimension of leisure, recreation, and competition, particularly among younger generations. The rapid growth and widespread popularity of Esports globally have transformed them from casual gaming activities into organized, professionalized, and monetized events with international audiences. This dynamic shift has captured the attention of researchers, marketers, educators, and sports administrators alike, calling for a deeper understanding of the factors driving user engagement and behavioral intention in this emerging domain.
As Esports continue to blur the boundaries between traditional sports and digital entertainment, the field of sport management must adapt to these technological and cultural changes. Recognizing this trend, the present study aims to investigate the determinants that influence individuals' behavioral intention to engage in Esports, specifically focusing on university students as a critical demographic group. University students are both technologically savvy and culturally immersed in digital interactions, making them ideal representatives for studying patterns in Esports adoption and usage.
To achieve this, the study employs the Unified Theory of Acceptance and Use of Technology2 (UTAUT2) model, an extension of the original UTAUT framework developed by Venkatesh et al. (2012), which integrates key psychological and behavioral constructs to predict technology adoption. This model is particularly well-suited for examining consumer contexts, including leisure-based digital platforms such as Esports. ObjectivesThis research seeks to:
Methodology
This study is applied in nature and follows a descriptive-survey approach for data collection. The research instrument was an electronic questionnaire consisting of 19 five-point Likert-scale items, ranging from "very important" to "very unimportant."To measure the constructs of hedonic motivation, habit, price value, effort expectancy, and social influence, items were adapted from the questionnaire developed by Venkatesh et al. (2012). For assessing behavioral intention to engage in Esports, the instrument developed by Jang and Byon (2020) was used.
To ensure the content validity of the questionnaire, it was reviewed by a panel of eight academic experts. A two-step approach was adopted to evaluate content validity, while construct validity was assessed through structural equation modeling (SEM) and confirmatory factor analysis (CFA).In addition, the reliability of the instrument was confirmed using Cronbach’s alpha coefficients, which were as follows:

To assess actual Esports behavior, participants were also asked to indicate the number of times they play Esports per week. The statistical population of the study consisted of all students from public universities in Tehran. A convenience sampling method was employed due to the accessibility of the population. Since the PLS method is relatively robust to sample size limitations, the required sample size was determined based on the guidelines of Barclay et al. (1995). Nonetheless, to enhance the generalizability of the findings and reduce statistical error, 200 questionnaires were randomly distributed among students who voluntarily agreed to participate in the study. Ultimately, 195 valid and analyzable responses were collected. For data analysis, PLS software was used to assess the reliability and validity of the measurement model and to test the structural model hypotheses.
 
Findings
The structural model assessment revealed several statistically significant relationships among the UTAUT2 constructs and the behavioral intention to engage in Esports. Key findings include:
Effort Expectancy (EE → BI): t = 347/2, indicating that students are more likely to engage in Esports when the games are perceived as easy to learn and interact with.
Social Influence (SI → BI): t = 593/2, suggesting that peer influence and social trends significantly impact Esports participation.
Price Value (PV → BI): t = 558/2, highlighting the perceived trade-off between cost (monetary or time-based) and benefits of Esports engagement.
Hedonic Motivation (HM → BI): t = 143/3, showing that the pleasure and enjoyment derived from gaming play a strong role in motivating users.
Habit (HT → BI): t = 753/2, emphasizing the influence of repeated behavior and routine on sustained Esports participation.
   Interestingly, performance expectancy and facilitating conditions were found to be non-significant predictors in this specific sample, which may reflect the non-utilitarian, recreational nature of Esports compared to task-oriented technologies.
Discussion and Conclusion
The findings of this study offer several theoretical and practical insights. From a theoretical standpoint, the validation of UTAUT2 in the context of Esports provides empirical support for the model's adaptability in non-traditional, leisure-oriented technological domains. The results reinforce the importance of hedonic motivation and habit, which are often underemphasized in utilitarian technology adoption studies.
The non-significance of performance expectancy implies that users may not prioritize functional outcomes (e.g., improving skills, winning tournaments) as the main driver for engagement. Instead, social dynamics and personal enjoyment are more dominant motivators. This aligns with the broader literature on consumer entertainment behavior, where affective experiences frequently outweigh instrumental objectives. From a managerial perspective, the findings suggest that Esports developers, marketers, and organizers should:
Emphasize ease of use and user-friendly interfaces in game design.
Leverage social platforms and influencers to create hype and communal engagement.
Offer free-to-play options or value-added pricing strategies to improve perceived value.
Integrate habit-forming mechanisms, such as daily rewards and tournaments, to enhance user retention.
Promote the fun and immersive aspects of the experience to appeal to intrinsic motivations.
This research represents a pioneering effort to apply the UTAUT2 framework to the study of Esports participation among university students in Tehran. By highlighting the significant impact of effort expectancy, social influence, price value, hedonic otivation, and habit on behavioral intention, the study provides a nuanced understanding of sports engagement dynamics in an emerging digital culture.In summary:
The study confirms the relevance of UTAUT2 in explaining technology-mediated sports behaviors. Behavioral intention toward Esports is more strongly influenced by affective and social constructs than by traditional utility-focused variables. Practical
applications include developing tailored marketing strategies, game features, and engagement initiatives that align with user motivations.

Limitations and Future Research
Although the findings are insightful, the study is not without limitations:
 The sample is restricted to students in Tehran, which may limit generalizability.
 The cross-sectional design precludes causal inferences.
Gender differences and genre preferences were not deeply explored.
Future research could expand the geographic scope, adopt longitudinal designs, or incorporate qualitative methods to capture richer insights into gaming cultures. Additionally, researchers may explore how cultural values or psychographic profiles moderate the UTAUT² relationships in the Esports domain.