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Research on electric sports (eSports) has experienced significant growth in recent years as a consequence of increasing connectivity, institutionalization, and technological advances. However, the interdisciplinary nature of the eSports as a field and the burgeoning growth in eSports articles have rendered it necessary to conduct a systematic review of extant literature to take stock of the knowledge accumulated. To this end, we aim to undertake a comprehensive review of extant literature that takes stock of published research to derive opportunities for future research in the realm of eSports. In so doing, we contribute to the advancement of the field by mapping out the knowledge trajectory of eSports research and elucidating areas that have remained underexplored thus far.

To conduct systematic review of the eSports literature, we employed a framework that included six essential steps: protocol, search, appraisal, synthesis, analysis, and report. This comprehensive approach enables us to meticulously investigate the existing body of literature on eSports and identify key trends and topics addressed within the field. By conducting the multidisciplinary systematic literature review, we thoroughly assess the current state of eSports literature and subsequently outline potential research avenues that can contribute to eSports fields.

This study draws on a six-phase framework – member preparation, team formation, character selection, team coordination, team performance, and team reflection – to illustrate the roles played by different levels of analysis unit (i.e. characters, players, and teams) and three distinct yet interconnected stages (i.e. inputs, process, and outputs) within eSports games as well as the research opportunities it brings.

We conducted a rigorous systematic review of the eSports literature by using quantitative citation analysis and qualitative content analysis. Furthermore, we adopted team dynamic view of eSports to identify potential research avenues for future research that contribute to advancing our understanding of the eSports tournaments.

Contemporary focus on infections and deaths in the event of pandemics may distract health institutions and medical practitioners from the psychosocial consequences of the outbreak in individuals. In light of the devastation, persistency and scarcity of pandemics, it is imperative to delve into individuals' psychological state and self-preservation instincts when confronted with the environmental danger arising from pandemic conditions and the environmental restrictions being imposed.

Guided by the self-preservation theory, the authors advance a research model to elucidate the moderated mediation effect of secondary traumatic stress on an individual's reactions when faced with environmental danger and restriction. The authors also consider the moderating influence of environmental restriction and media use diversity. The authors subsequently validated the research model via a survey with 2,016 respondents in China. The authors employed PLS-SEM to analyze the data and assess the hypothesized paths.

Analytical results revealed that secondary traumatic stress fully mediated the impact of environmental danger on external reliance but suppresses the mediating effects on internal reliance. The authors further confirmed that environmental restriction moderated the relationship between environmental danger and reliance. Furthermore, the authors attest to the moderating influence of media use diversity on the relationship between secondary traumatic stress and external reliance.

This study not only extends the theoretical lens of self-preservation to public health emergencies but also yields practical guidelines for coping with pandemics. Insights from this study can be harnessed to aid populations worldwide in coping and recovering from pandemics.

Peer-to-Peer Accommodation Service (P2PAS) has emerged as a novel paradigm that enables consumers to book temporary accommodation through P2PAS platforms (online transaction), and then reside in hosts' rooms (offline consumption). Due to potential variance in performance and conflict of interest between hosts and platforms, consumers may differ in their trust perceptions of the two parties, which in turn affects consumers' continuous usage of P2PAS. To this end, the authors endeavor to unravel the effect of consumers' trust incongruence on continuance intention, and to further elucidate the moderating influence of transaction and consumption risks on this relationship. This paper aims to discuss the aforementioned objectives.

This study collected data through an online survey of 408 P2PAS consumers. Polynomial modeling and response surface analysis were conducted to validate the hypothesized relationships.

Response surface analysis reveals that trust incongruence did not significantly affect consumers' continuance intention. However, continuance intention would be greater when TP was higher than TH compared with when TH was higher than TP. Furthermore, the analytical results suggest that trust incongruence exerts greater negative effect on continuance intention when transaction and consumption risks were high.

First, the study marks a paradigm shift in conceptualizing the incongruence between TP and TH as a determinant of consumers' continuance intention toward P2PAS. Second, the authors derive a typology of risks that is contextualized to P2PAS. Finally, the authors establish transaction and consumption risks as boundary conditions influencing the effects of trust incongruence on consumers' continuance intention toward P2PAS.

Artificial intelligence (AI) has gained significant momentum in recent years. Among AI-infused systems, one prominent application is context-aware systems. Although the fusion of AI and context awareness has given birth to personalized and timely AI-powered context-aware systems, several challenges still remain. Given the “black box” nature of AI, the authors propose that human–AI collaboration is essential for AI-powered context-aware services to eliminate uncertainty and evolve. To this end, this study aims to advance a research agenda for facilitators and outcomes of human–AI collaboration in AI-powered context-aware services.

Synthesizing the extant literature on AI and context awareness, the authors advance a theoretical framework that not only differentiates among the three phases of AI-powered context-aware services (i.e. context acquisition, context interpretation and context application) but also outlines plausible research directions for each stage.

The authors delve into the role of human–AI collaboration and derive future research questions from two directions, namely, the effects of AI-powered context-aware services design on human–AI collaboration and the impact of human–AI collaboration.

This study contributes to the extant literature by identifying knowledge gaps in human–AI collaboration for AI-powered context-aware services and putting forth research directions accordingly. In turn, their proposed framework yields actionable guidance for AI-powered context-aware service designers and practitioners.