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This study aims to investigate the factors that affect an audience's purchase decisions on a new type of social media, namely live video streaming platforms.

This study is based on data from an online survey providing 488 valid responses. These responses are used to test the research model by employing partial least squares (PLS) modeling.

Three antecedents (consumer competitive arousal, gift design aesthetics and broadcaster's image) influence the audience's purchase decisions (impulse buying and continuous buying intention). Chinese impression management (mianzi) acts as a moderator. Self-mianzi, mutual mianzi and other mianzi (i.e. three subtypes of mianzi) moderate the effects of consumer competitive arousal, gift design aesthetics and broadcaster's image on impulse buying.

The findings encourage practitioners developing marketing strategies for live video streaming platforms in the Chinese cultural context to consider peer influence, gift appearance, broadcaster's image and mianzi.

Drawing on the community gift-giving model and face-negotiation theory, this study provides an integrated research model to investigate a new type of social media (live video streaming). It offers insight into virtual gifting behaviors by confirming the effects of three antecedents on the audience's purchase decisions, with mianzi acting as a moderator.

The boom in live streaming has intensified competition among streamers for viewers' gifts, which makes it meaningful to study the factors that affect the viewers’ gifting behavior. Given the emotional attachment between streamers and viewers, the authors set out to elucidate a new driver on viewer gifting: expressions of the streamer. This research aims to explore the impact of streamer emotions on the viewer gifting behaviors, including free and paid gifting. The loyalty level of the viewers is also introduced as a moderating factor to investigate the heterogeneous effect of streamer emotions on gifting behavior.

The dataset the authors collected consists of two parts, including 1809.69 h of live streaming videos and 358,002 gift giving records. Combined with deep learning methods and regression analysis, the authors performed empirical tests on the 81,110 valid samples. Several robustness checks were also conducted to ensure the reliability of main results.

The empirical results show that streamer emotions do have effects on viewers' free and paid gifting behavior. The authors’ findings show that positive streamer expressions, such as happiness and surprise, have a positive influence on viewer gifting behavior. However, some negative expressions, like sadness, can also have a positive impact. Moreover, the authors discovered that higher viewer loyalty amplifies the positive effect of streamer emotions and reduces the negative effect.

This research contributes to the study about streamer emotions and viewers' consumption behavior, which extends the application of emotion as social information model (EASI model) in the live streaming setting. The authors carefully divide the gifting behavior into two types: free and paid, and study how these two types are affected by streamer emotions. Besides, these effects are analyzed within viewers of different loyalty levels. This study offers practical emotion management strategies for streamers and live streaming platforms to gain more economic profits.

This study aims to explore how specific cues with new manifestations (i.e. herding message and price discount information) and customer cognitive style influence attention allocation and purchase intention.

To empirically validate the research hypotheses, an eye-tracking experiment with a 2 × 2 × 2 mixed design was conducted on a sample of 44 participants recruited from a university in China. Repeated measures analysis of variance was employed for data analysis.

The results show that herding message and price discount information play different roles in viewers' attention and have an interactive effect on attention. Moreover, individual cognitive styles moderate the impact of herding message on attention allocation. Still, two cues positively affect customer purchase intention.

This study guides future research by applying cue utilization theory to investigate the effects of two cues in live streaming. Findings offer practical implications for how live streaming cues affect viewers' attention allocation and purchase intention.

This study aims to investigate how sports customers adopted over-the-top (OTT) services to consume sport content. Inspired by the technology acceptance model (TAM), the study aims to understand users' behavior when consuming sporting events and users' perceptions toward OTT services.

The participants of the study are Chinese sports consumers that use streaming services to watch live sport content. An online survey was distributed through HUPU Sports, a Chinese online communication community where sports fans can share opinions. To make sure all responses qualified to take part in the study, skip logic questions were added at the beginning of the questionnaire to ask participants to answer whether they used streaming services for watching sports. A total of 352 responses were received and there were 327 useable questionnaires.

The results revealed that viewing convenience, free of commercials and viewing quality were the main reasons impacting them to adopt OTT services. In terms of users' perceptions, paid users rated higher in perceived enjoyment, perceived value, perceived usefulness (PU) and ease of use than nonpaid users. OTT users' fandom and PU could predict the time the users spent on using these services, while the users' fandom and perceived value are positively related to the money users spent on these services. In addition, this study also found that users' fandom, perceived value, content quality, and ease of use are positively associated with users' intention to continue to use the service.

The study is one of the first attempts to explore how sports audiences adopted OTT services to consume sport content and explore the audiences' perceptions toward OTT usage. Previous studies have already investigated how users adopted music streaming services (Fernandes and Guerra, 2019) and other online streaming services (Shin and Park, 2021), but little attention has been given to sports streaming services specifically. Therefore, the findings of the study fill the gap in the extant knowledge of sport consumers' behavior and provide more insights to their online behaviors. Moreover, the authors also contribute to the growing digital media literature by advancing our understanding perceptional differences between paid users and unpaid users. The streaming services literature has primarily focused on general users (Fernandes and Guerra, 2019), but the services neglect to understand the differences in between paid and unpaid users.

This study aimed to understand better what makes esports fans engage with streamers' live-streaming of esports gameplay. This study used the Theory of Planned Behavior (TPB) and additionally adopted streamer identification and esports game identification as moderating variables.

Data were collected from streamers' esports content streaming viewers over 18 years of age using an online survey in Amazon M-Turk (N = 307). Based on past esports live-streaming weekly watching hours, which range from 1 to 45 h, the participants were divided into lower (n = 152) and higher (n = 155) frequency groups. PLS-SEM and bootstrapping techniques were used to test the moderated mediation relationships among the constructs.

This study found a negative moderating effect of past watching experience on the relationship between attitudes and behavioral intention, and it positively moderated the path between perceived behavioral control and behavioral intention. Also, it was found statistically significant direct impacts of streamer identification (STI) and esports game identification (EGI) on attitude and subjective norms. While the indirect impact of STI on behavioral intention through attitude was statistically significant, there were no significant indirect impacts of EGI on attitude and behavioral intention through subjective norms.

Theoretically, this study extends the TPB model by exploring the two identifications (i.e. streamers and esports games) as antecedents of the focal TPB factors (i.e. attitudes, subjective norms and perceived behavioral control) and the moderating effect of prior experience based on high/low weekly watching frequencies. Practically, content creators of esports live-streaming and live-streaming platform managers can use the study’s findings to develop strategies to nurture their current and future viewership.

E-commerce live streaming is a new influencer advertising method that allows influencers to interact directly with consumers on e-commerce platforms. Although evidence suggests that influencer live-streaming advertisements (ads) on social media can increase consumers’ buying impulses, little research examined how this similar but new advertising method on e-commerce platforms may influence consumers’ urge to buy impulsively. This study explores the role of influencer credibility, celebrity effect, perceived entertainment, trust and perceived usefulness on consumers’ attitudes toward influencer ads and their urge to buy impulsively.

A questionnaire containing seven constructs was developed and distributed to participants using a convenient sample and snowball sampling approach. The constructs were measured based on validated measurement items from the literature and adjusted according to this study’s focus. A total of 236 valid responses were obtained from the survey and used for data analysis. A partial least squares structural equation modeling approach was employed for parameter estimation and model testing.

The empirical results show that all constructs influenced consumers’ urge to buy impulsively via attitude toward influencer ads. The proposed research model explains 61.7% of the variance in attitude toward influencer ads and 19.4% of the urge to buy impulsively.

This is an early study investigating the relationship between influencer advertising and impulse buying. The results provide valuable insights into improving the design of influencer ads and marketing strategies.

1. I-eIB model tests the mechanism of influencer ads on consumers’ buying impulse.

2. Consumers’ attitude towards influencer ads affects their urge to buy impulsively.

3. Influencer credibility affects consumer attitude via celebrity effect as a mediator.

4. Trust affects consumer attitude via perceived usefulness as a mediator.

5. Entertaining ads help develop favorable consumer attitude.

I-eIB model tests the mechanism of influencer ads on consumers’ buying impulse.

Consumers’ attitude towards influencer ads affects their urge to buy impulsively.

Influencer credibility affects consumer attitude via celebrity effect as a mediator.

Trust affects consumer attitude via perceived usefulness as a mediator.

Entertaining ads help develop favorable consumer attitude.

Video game streaming (VGS) is emerging as an extremely popular, highly interactive, inordinately subscribed and very dynamic form of digital media. Incorporated environmental elements, gratifications and user pre-existing attitudes in VGS, this paper presents the development of an extended model of uses and gratification theory (EUGT) for predicting users' behavior in novel technological context.

The proposed model was empirically tested in VGS context due to its popularity, interactivity and relevance. Data collected from 308 VGS users and structural equation modeling (SEM) was employed to assess the hypotheses. Multi-model comparison technique was used to assess the explanatory power of EUGT.

The findings confirmed three significant types elements in determining VGS viewers' engagement, including gratifications (e.g. involvement), environmental cues (e.g. medium appeal) and user predispositions (e.g. pre-existing attitudes). The results revealed that emerging technologies provide potential opportunities for new motives and gratifications, and highlighted the significant of pre-existing attitudes as a mediator in the gratification-uses link.

This study is one of its kind in tackling the criticism on UGT of considering media users too rational or active. The study achieved this objective by considering environmental impacts on user behavior which is largely ignored in recent UGT studies. Also, by incorporating users pre-existing attitudes into UGT framework, this study conceptualized and empirically verified the higher explanatory power of EUGT through a novel multi-modal approach in VGS. Compared to other rival models, EUGS provides a more robust explanation of users' behavior. The findings contribute to the literature of UGT, VGS and users' engagement.

The purpose of this paper is to perform a comparative analysis of the delay associated in running two real-time machine learning-based applications, namely, a video quality assessment (VQA) and a phishing detection application by using the edge, fog and cloud computing paradigms.

The VQA algorithm was developed using Android Studio and run on a mobile phone for the edge paradigm. For the fog paradigm, it was hosted on a Java server and for the cloud paradigm on the IBM and Firebase clouds. The phishing detection algorithm was embedded into a browser extension for the edge paradigm. For the fog paradigm, it was hosted on a Node.js server and for the cloud paradigm on Firebase.

For the VQA algorithm, the edge paradigm had the highest response time while the cloud paradigm had the lowest, as the algorithm was computationally intensive. For the phishing detection algorithm, the edge paradigm had the lowest response time, and the cloud paradigm had the highest, as the algorithm had a low computational complexity. Since the determining factor for the response time was the latency, the edge paradigm provided the smallest delay as all processing were local.

The main limitation of this work is that the experiments were performed on a small scale due to time and budget constraints.

A detailed analysis with real applications has been provided to show how the complexity of an application can determine the best computing paradigm on which it can be deployed.

This study explores how perceived interactivity effects in Livecommerce influences consumers' shopping intentions in live stream commerce. The authors specifically examine the mediating roles of immersion and hedonic/utilitarian gratification, as well as the moderating role of product involvement in identifying the boundary conditions.

A scenario-based online survey was conducted among American consumers via Prolific.co, an online crowdsourcing platform. The final sample included 187 respondents (male, 63.1 per cent; Caucasian, 61.5 per cent).

The results indicate that perceived interactivity significantly influenced consumers' shopping intentions. Consumers' sense of immersion and hedonic/utilitarian gratification were identified as serial mediators between perceived interactivity and consumers' shopping intentions. It was also found that individuals' product involvement moderated the serial effects of perceived interactivity on consumers' shopping intentions in live stream commerce.

This study provides empirical evidence that perceived interactivity plays an important role in creating an effectively immersive media experience in live stream commerce, which further contributes to higher shopping intentions via perceived utilitarian and hedonic gratifications. It was also found that varying levels of product involvement can have differing effects. Managerial implications are provided.

The rapid development of live-streaming commerce has increased companies’ marketing effectiveness. While previous studies have explored the effects of its technical features on consumers, the effects of marketing-related factors remain unknown. This study aims to investigate the effects of the marketing elements of live-streaming commerce on consumers’ purchase intentions.

The research model is derived from the Yale model and the benefit–risk framework. To test the study hypotheses, data were collected through a questionnaire survey of 392 live-streaming shoppers and analyzed using SmartPLS.

The empirical results indicate that broadcaster competence and online crowding increase consumers’ perception of price attractiveness while reducing their perceived uncertainty. Information diagnosticity also reduces consumers’ perceived uncertainty. Furthermore, purchase intention is positively and negatively affected by perceived price attractiveness and perceived uncertainty, respectively. Finally, product scarcity moderates the relationships between broadcaster competence, online crowding, information diagnosticity, perceived price attractiveness and perceived uncertainty.

The study identifies the different marketing elements in live-streaming commerce and their effects on consumers’ value evaluations and purchase intentions. The findings provide comprehensive insights into the antecedents of live-streaming shopping and offer new perceptions and recommendations for practitioners.