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In the present world of constant connectivity, the barrage system, as a system of real-time dynamic comments coupled with video content, has become a popular interactive system technology for video sharing platforms. This study investigates how barrage system fluctuation characteristics, namely, barrage fluctuation amplitude and frequency, impact user interaction.

The research model was estimated with a fixed-effects regression applied to a longitudinal panel dataset collected from one of the most popular video sharing platforms in China (Bilibili.com).

Barrage fluctuation frequency has positive effects on users' real-time (synchronous) barrage interaction and the traditional (asynchronous) comment interaction. Barrage fluctuation amplitude has a positive effect on users' real-time (synchronous) barrage interaction but a negative effect on traditional (asynchronous) comment interaction. In addition, the interaction effects of the barrage fluctuation frequency and the barrage fluctuation amplitude on user interaction show adverse effects.

The results revealed the impact of different barrage fluctuation characteristics on different forms of interaction and provide important theoretical contributions and managerial implications in terms of user interaction on video sharing platforms.

Although prior studies have studied the relationship between online consumers' attitudes and buying behaviour, the research focussing on online consumers' impulse buying behaviours and exploring the role of celebrity endorsement is limited. Drawing on the social presence and the social facilitation theory, this paper establishes a research model based on the stimuli–organism–response (S–O–R) model and the motivation theory. It explores how live streamers impact online consumers' impulse buying behaviours under specific social and cultural backgrounds, with celebrity endorsement as a moderating variable.

To test the research model, the online questionnaire method has been conducted in this study. This paper utilises Chinese online consumers as samples and promotes an online survey. Using the variance-based structural equation modelling and partial least squares path modelling (SEM-PLS), 433 valid questionnaires have been analysed on SmartPLS.

First, live streamers' attractive appearance positively correlates with online consumers' hedonic attitude and positively impacts their utilitarian attitude to live shopping. Second, live streamers' real-time interaction positively affects consumers' utilitarian attitudes because of their professional marketing and communication skills. Third, their hedonic and utilitarian attitudes positively influence online consumers' impulse buying behaviours. Finally, this paper presents that celebrity endorsement negatively moderates the relationship between online consumers' hedonic attitudes and impulse buying during live shopping.

This research combines the S–O–R model and the motivation theory and analyses related social influencing factors to study online consumers' impulse buying behaviours. Meanwhile, it explores the celebrity endorsement factor as a moderate role and identifies the different effects between live streamers and celebrities in live shopping, which is of great significance to the strategy of live shopping marketing and the literature on online consumers' behaviours.

Live streaming commerce, a new form of social commerce where firms integrate with broadcasters, community members and customers in live chat rooms for real-time interaction to help sell products, has become increasingly popular. However, factors that impact the success of live streaming commerce are not fully explored. The purpose of this study is to examine these factors by exploring the relationships among customer trust (i.e., trust in broadcasters, community members, and products) and customer engagement, and the mediating role of swift guanxi.

The authors surveyed 422 customers who have watched Taobao Live, one of the largest live streaming commerce sites in China, and used their questionnaires to test the research model employing partial least squares modeling.

The authors’ results indicate that trust in broadcasters has a positive effect on trust in products and community members, which positively influences trust in products. Additionally, swift guanxi has a fully mediating effect on the relationship between customers' trust in broadcasters and customer engagement.

First, from the theoretical perspective, this study comprehensively identifies three types of trust, explores the transfer relationships among trust in broadcasters, community members, and products based on Trust Transfer Theory. In addition, this study examines the mediating influence of swift guanxi on the relationship between customer trust and engagement. Second, from the managerial perspective, the study provides insights to help broadcasters and practitioners use live streaming to facilitate shopping.

In recent years, more and more e-retailers have adopted live streaming services to attract customers. Although the extant literature has mostly examined the motivations for live streaming usage, it remains unclear how to enhance customers’ purchase behaviour. Based on the social exchange theory, in the context of live streaming platforms (LSP), this study aims to investigate the impact of information quality and interaction quality on swift guanxi and customers’ purchase intention.

This study conducted an online survey to conduct two rounds of data collection and analyses the data using SPSS and SmartPLS softwares.

The results show that information quality (believability, usefulness and vividness) and interaction quality (responsiveness, real-time interaction and empathy) are positively related to swift guanxi, which may influence customers’ online purchase intention on LSP.

Prior service quality studies tend to focus on traditional physical stores and e-commerce websites context. This study offers the description of key dimensions of service quality on emerging LSP context. The study also confirms the importance of swift guanxi in an online marketplace.

Social live-streaming services are an emerging form of social media that is gaining in popularity among researchers and practitioners. By facilitating real-time interactions between video content creators (i.e. streamers) and viewers, live-streaming platforms provide an environment for novel engagement behaviors and monetization structures. This research aims to examine communication foci and styles as levers of streaming success. In doing so, the authors analyze their impact on viewers' engagement with the stream.

This research draws on a unique dataset collected via a multi-wave questionnaire comprising viewers' perceptions of a specific streamer's communications and their actual behavior toward them. The authors analyze the proposed impact of communication foci on viewing and donating behavior while considering the moderating role of communication style using seemingly unrelated regressions.

The results show that communication foci represent a double-edged sword: community-focused communication drives viewership while reducing donations made to the streamer. By contrast, content-focused communication curbs viewing but drives donating.

Of specific interest for practitioners, the study demonstrates how streaming content providers (e.g. influencers) should adjust their communications to drive engagement in the context of synchronous social media such as social live-streaming services. Beyond that, this research identifies unique characteristics of engagement that can help managers to improve their digital service offerings.

Social live-streaming services provide an environment that offers unique opportunities for self-development and co-creation among social media users. By allowing for real-time interactions, these emerging social media services build on ephemeral content to provide altered experiences for users.

The authors highlight the need to distinguish between engagement behaviors in asynchronous and synchronous social media. The proposed conceptualization sheds new light on success factors of social media in general and social live-streaming services specifically. To maximize user engagement, content creators in synchronous social media must consider their communications' focus (content or community) and style (utilitarian or hedonic).

An enterprise social network (ESN) is part of the landscape of information reform by enterprises, using Web 2.0. In terms of the marketing targets of typical Web 2.0 techniques, enterprise knowledge sharing in Web 2.0 can be classified into different types (individual interaction type, group interaction type, social interaction type, real‐time interaction type and delay interaction type). The purpose of this paper is to summarize the features and modes of different enterprises' knowledge sharing and study enterprise knowledge sharing quantitatively from an ESN perspective by selecting real‐time interaction type as the case.

Because of the area of research, the authors supplemented social network analysis (SNA) with a mathematical modeling method and additional in‐depth interviews.

The Web 2.0 era provides the opportunity to quantify knowledge sharing. Also, SNA can quantitatively and visually diagnose the knowledge sharing status of the enterprise and guide the enterprise's knowledge‐sharing process.

Only a case study regarding real‐time interaction type is presented; other types of interaction are not studied empirically.

SNA, combined with a mathematical modeling method and additional in‐depth interviews with team leaders or key managers in organizations, can diagnose quantitatively, visually and comprehensively the knowledge‐sharing status of the enterprise.

This paper systematically summarizes the features and modes of Web 2.0 enterprise knowledge sharing, and the multiple‐method research design represents a sound approach to targeting enterprise knowledge sharing.

This paper aims to propose and implement an integrated augmented-reality (AR)-aided assembly environment to incorporate the interaction between real and virtual components, so that users can obtain a more immersive experience of the assembly simulation in real time and achieve better assembly design.

A component contact handling strategy is proposed to model all the possible movements of virtual components when they interact with real components. A novel assembly information management approach is proposed to access and modify the information instances dynamically corresponding to user manipulation. To support the interaction between real and virtual components, a hybrid marker-less tracking method is implemented.

A prototype system has been developed, and a case study of an automobile alternator assembly is presented. A set of tests is implemented to validate the feasibility, efficiency, accuracy and intuitiveness of the system.

The prototype system allows the users to manipulate and assemble the designed virtual components to the real components, so that the users can check for possible design errors and modify the original design in the context of their final use and in the real-world scale.

This paper proposes an integrated AR simulation and planning platform based on hybrid-tracking and ontology-based assembly information management. Component contact handling strategy based on collision detection and assembly feature surfaces mating reasoning is proposed to solve component degree of freedom.

Live streaming commerce enhances shopping experience and reduces uncertainty. However, with increasingly fierce competitions, it has become a challenging task for live streaming commerce platforms to retain existing customers. The purpose of this study to explore factors affecting customers’ stickiness intention toward live streaming commerce platforms.

A research model was developed by modifying e-commerce system success model (ES success model) based on the context of live streaming commerce and meanwhile integrating serendipity and flow into the model. Using the data collected from 380 customers who have live streaming shopping experience, the established model was empirically assessed by partial least squares based structural equation model.

The results show that vividness, real-time interaction and diagnosticity are antecedents of perceived value and customer satisfaction toward a live streaming commerce platform which in turn influence customers’ stickiness intention. Besides, as new factors introducing into the ES success model, serendipity and flow are two important motivators of satisfaction and stickiness.

This study establishes a well-organized framework to understand the mechanism regarding why customers stick with a live streaming commerce platform. It provides a socio-technical approach to analyze how the stickiness intention can be influenced.

Marketing researchers currently lack a systematic and empirical understanding of digital social viewing strategies. Drawing on social impact theory, this study aims to investigate if and how firm-initiated digital social viewing strategies (livestreaming vs pre-recorded) influence consumer viewing experiences and consequential behavioral intentions.

A scenario-based experiment was conducted with 462 participants. The study involved social viewing strategies in a new product launch context. Data were analyzed using structural equation modeling.

This study demonstrates that social influence cues (social presence and synchronicity) inherent in a livestreaming strategy induce a more authentic consumer viewing experience than a pre-recorded strategy, which in turn increases consumers’ searching and subscribing intention. However, a company’s social viewing strategy does not moderate the effect of search and subscribe intention on purchase intention.

This study extends the application of social impact theory by showing that social presence and synchronicity impact authentic consumer viewing experiences, which influence consumers’ searching, subscribing and purchasing intention.

This study validates the importance of using social viewing as a viable digital marketing strategy for practitioners. The paper provides marketers ways to increase consumer purchase intention via livestreaming marketing content, particularly for new products.

This study extends the traditional research on social viewing into the realm of digital social viewing. It is among the first to delineate the advantages of both livestreaming and pre-recorded social viewing approaches.

With a team interaction analysis model, the authors sought to identify a varying range of individual and collective intellectual behaviors in a series of communicative intents particularly expressed with multimodal interaction methods. In this paper, the authors aim to present a new construct (i.e. collective intelligence ratio (CIR)) which refers to a numeric indicator representing the degree of intelligence of a team in which each team member demonstrates an individual intelligence ratio (IR) specific to a team goal.

The authors analyzed multimodal team interaction data linked to communicative intents with a Poisson‐hierarchical generalized linear model (HGLM).

The study found evidence of a distinctive IR for each team member in selecting a communicative method for a certain task, ultimately leading to varying degrees of team CIR.

The authors limited the type and nature of human intelligence observed with a very short list of categories. Also, the data were evaluated by only one subject matter expert, leading to reliability issues. Therefore, generalization should be limited to situations in which teams, with pre‐specified team goals and tasks, are collaborating in multimodal interaction environments.

This study presents potential ways to directly or indirectly optimize team performance by identifying and incorporating IRs and CIRs in team composition strategies.

In the literature of team cognition and performance, the authors offer a new insight on team schema by suggesting a new task‐expertise‐person (TEP) unit integrating information on who uses what communicative methods to best tackle on what cognitive task (i.e. optimum cognition with least cognitive burden). Individual and collective intelligence ratios should be considered as new extensions to conventional transactive memory systems in multimodal team interaction scenarios.