Recent research on live-streaming commerce
| Authors | Theoretical foundation | Data source | Independent variables | Dependent variables | Main findings |
|---|---|---|---|---|---|
| Main Research Stream 1: Consumer engagement | |||||
| Kang et al. (2021) | SOR | Field data | Interactivity | Consumer engagement | Interactivity has a nonlinear (inverted U-shaped) relationship with consumer engagement |
| Guo et al. (2021) | Trust transfer theory | Survey data | Trust | Consume engagement | Trust in broadcasters positively affects trust in products and community members, which positively influences trust in products |
| Hu and Chaudhry (2020) | SOR | Survey data | Relational bonds | Consumer engagement | Social and structural bonds positively affect consumer engagement, directly and indirectly, via affective commitment. Meanwhile, financial bonds only indirectly affect consumer engagement via affective commitment |
| Wongkitrungrueng et al. (2020) | Theories of relationship marketing | Qualitative research | Live-streaming strategy | Consumer engagement | These authors identified four sales approaches and 12 strategies adopted in acquiring and retaining consumers |
| Wongkitrungrueng and Assarut (2020) | Value theory | Survey data | Perceived value | Consumer engagement | Symbolic value, directly and indirectly, affects consumer engagement via trust in sellers. Utilitarian and hedonic values affect customer engagement indirectly and sequentially through customer trust in products and trust in sellers |
| Xue et al. (2020) | SOR | Survey data | Interactions | Consumer engagement | Live interactions (i.e. personalization, responsiveness, entertainment, mutuality, and perceived control) positively affect perceived usefulness and negatively affect perceived risks and psychological distance, promoting social commerce engagement |
| Chen and Lin (2018) | Flow theory | Survey data | Flow, entertainment, and social interaction | Usage intentions | Flow, entertainment, and social interaction are the main factors that affect consumers' usage intentions for live-streaming services |
| Main Research Stream 2: Consumption behavior | |||||
| Addo et al. (2021) | / | Field data | Customer engagement price | Purchase intentions | Consumer engagement (likes, chats, visits, and exposure time in social commerce) positively influences followership and purchase intentions in live-streaming commerce. While price is a significant moderator, its effect becomes insignificant once consumers become followers |
| Lin et al. (2021) | / | Field data | Broadcasters' emotion | Gift-giving | Happier broadcasters make audiences happier and trigger more gift-giving from audiences |
| Hou et al. (2020) | Uses and gratification theory | Survey data | Interactivity, social status display, humor appeal, and sex appeal | Consumption intentions | Sex and humor appeal, social status displays, and interactivity influence viewers' consumption intentions in live-streaming commerce, and their effects vary across different live streaming types |
| Zhou et al. (2019) | Social interaction theory | Field data | Viewers' social interaction | Gift-giving | Other broadcast viewers' presence and social competition positively affect viewers' gift-giving behavior in live-streaming commerce |
| Zhang et al. (2019) | Construal level theory | Survey and field data | Psychological distance | Purchase intentions | Live video streaming strategies improve consumers' online purchase intentions by reducing psychological distance and perceived uncertainty in live-streaming commerce |
| Yu et al. (2018) | / | Field data | Engagement socialization motives | Gift-giving | Viewer engagement is positively associated with their gift-giving decisions. Their socialization motive highly correlates with their gift-giving behavior. The relationship between viewers and broadcasters affects the number of gifts from viewers |
| Authors | Theoretical foundation | Data source | Independent variables | Dependent variables | Main findings |
|---|---|---|---|---|---|
| SOR | Field data | Interactivity | Consumer engagement | Interactivity has a nonlinear (inverted U-shaped) relationship with consumer engagement | |
| Trust transfer theory | Survey data | Trust | Consume engagement | Trust in broadcasters positively affects trust in products and community members, which positively influences trust in products | |
| SOR | Survey data | Relational bonds | Consumer engagement | Social and structural bonds positively affect consumer engagement, directly and indirectly, via affective commitment. Meanwhile, financial bonds only indirectly affect consumer engagement via affective commitment | |
| Theories of relationship marketing | Qualitative research | Live-streaming strategy | Consumer engagement | These authors identified four sales approaches and 12 strategies adopted in acquiring and retaining consumers | |
| Value theory | Survey data | Perceived value | Consumer engagement | Symbolic value, directly and indirectly, affects consumer engagement via trust in sellers. Utilitarian and hedonic values affect customer engagement indirectly and sequentially through customer trust in products and trust in sellers | |
| SOR | Survey data | Interactions | Consumer engagement | Live interactions (i.e. personalization, responsiveness, entertainment, mutuality, and perceived control) positively affect perceived usefulness and negatively affect perceived risks and psychological distance, promoting social commerce engagement | |
| Flow theory | Survey data | Flow, entertainment, and social interaction | Usage intentions | Flow, entertainment, and social interaction are the main factors that affect consumers' usage intentions for live-streaming services | |
| / | Field data | Customer engagement price | Purchase intentions | Consumer engagement (likes, chats, visits, and exposure time in social commerce) positively influences followership and purchase intentions in live-streaming commerce. While price is a significant moderator, its effect becomes insignificant once consumers become followers | |
| / | Field data | Broadcasters' emotion | Gift-giving | Happier broadcasters make audiences happier and trigger more gift-giving from audiences | |
| Uses and gratification theory | Survey data | Interactivity, social status display, humor appeal, and sex appeal | Consumption intentions | Sex and humor appeal, social status displays, and interactivity influence viewers' consumption intentions in live-streaming commerce, and their effects vary across different live streaming types | |
| Social interaction theory | Field data | Viewers' social interaction | Gift-giving | Other broadcast viewers' presence and social competition positively affect viewers' gift-giving behavior in live-streaming commerce | |
| Construal level theory | Survey and field data | Psychological distance | Purchase intentions | Live video streaming strategies improve consumers' online purchase intentions by reducing psychological distance and perceived uncertainty in live-streaming commerce | |
| / | Field data | Engagement socialization motives | Gift-giving | Viewer engagement is positively associated with their gift-giving decisions. Their socialization motive highly correlates with their gift-giving behavior. The relationship between viewers and broadcasters affects the number of gifts from viewers | |
Note(s): SOR represents the stimulus organism response theory;/means no specific theory applied in studies
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