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Ma, L. Live Streaming and Consumer Purchase Intentions. Encyclopedia. Available online: https://encyclopedia.pub/entry/18932 (accessed on 08 July 2024).
Ma L. Live Streaming and Consumer Purchase Intentions. Encyclopedia. Available at: https://encyclopedia.pub/entry/18932. Accessed July 08, 2024.
Ma, Linye. "Live Streaming and Consumer Purchase Intentions" Encyclopedia, https://encyclopedia.pub/entry/18932 (accessed July 08, 2024).
Ma, L. (2022, January 28). Live Streaming and Consumer Purchase Intentions. In Encyclopedia. https://encyclopedia.pub/entry/18932
Ma, Linye. "Live Streaming and Consumer Purchase Intentions." Encyclopedia. Web. 28 January, 2022.
Live Streaming and Consumer Purchase Intentions
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This entry is adapted from the peer-reviewed paper 10.3390/su14021045

As a new business model, live-streaming commerce has great commercial value. Interactivity, visualization, entertainment, and professionalization play considerable roles in consumer behavioral responses and that their psychological mechanisms are different. Male respondents are more satisfied with interactivity than females. E-commerce platforms are more interactive, visible and professional than social media platforms, and the trust mechanism of social media platforms is immature.

live-streaming commerce interactivity visualization entertainment professionalization

1. Live-Streaming Commerce

With the rapid development of mobile communication technology, live-streaming commerce has emerged in recent years as a new business model, consisting of “live streaming + social + e-commerce”. Traditional e-commerce has been enabled by Web 1.0 technology, which allows for one-to-one interaction, while social commerce has been enabled by Web 2.0 technology, which allows for many-to-many interaction, and live-streaming commerce enabled by Web 3.0 technology, which allows for real-time multidimensional interaction [1]. Interactivity is significantly improved in live-streaming commerce [2][3]. In addition, visualization [4][5], entertainment [4][6], and professionalization [7] have been greatly improved. Some screenshots of a live streaming studio are shown in Figure 1. The streamer shows various details of his or her products to consumers by means of strategic explanations, such as try-ons. When watching live streaming, consumers can interact with the streamer, draw prizes, and grab cash vouchers.
Sustainability 14 01045 g001 550
Figure 1. Screenshots of live streaming: (a) The streamers are trying on the product. (b)The streamer is showing details of the product.

2. Stimulus–Organism–Response Framework

Under the SOR framework, an external environmental stimulus (S) impacts the internal state of a consumer (O) and subsequently influences his or her behavioral responses (R) while shopping online [2][3]. Xue applied the SOR framework to conceptualize interactivity as a stimulus, perceived usefulness, psychological distance, and perceived risk as internal states, and social commerce engagement as a response in social commerce [2]. Kang employed the SOR framework to explore the dynamic effect of interactivity on customer engagement behaviors through tie strength in live-streaming commerce platforms [3]. Therefore, the SOR framework offers a structured method for testing the impact of live peculiarities as external environmental stimuli on customer behavioral responses. In this study, social presence, psychological distance, and trust were selected to assess the internal states of consumers, and engagement and purchase intentions were selected to assess their responses. By structuring a causal relationship among stimuli, organisms, and responses, a systematic framework was provided to trace the impact of live peculiarities on purchase intentions.

2.1. Live Peculiarities as Environmental Stimuli (S)

Media richness theory regards rich information as being more capable of reducing equivocality than lean information [8]. Currently, live-streaming commerce, which provides real-time communication, text messages, voice, and video, possesses high media richness [9]. Compared with social commerce, live-streaming commerce is more interactive [2][3][10], visual [4][5], entertaining [4][6] and professional [7]. Therefore, this study adopted four live peculiarities, namely, interactivity, visualization, entertainment, and professionalization, as external stimuli.

2.2. Cognitive and Affective Factors as Inner States of the Organism (O)

The SOR framework demonstrates that the effect of environmental stimuli on customer behavioral responses is mediated through virtual experiences [2]. Trust is widely used as an internal state to impact purchase intentions in e-commerce [1][11]. Compared with traditional e-commerce, frequent interactions shorten the social distance between customers and sellers [2][3]. Social presence has been used to quantify the cognitive state of consumers in live-streaming commerce [12]. Therefore, we utilized social presence, psychological distance and trust to measure the cognitive and affective states of consumers in live-streaming commerce.

2.3. Engagement and Purchase Intentions as Behavioral Responses (R)

Engagement has been widely used in social commerce to conceptualize consumer behavioral responses [13][14][15]. In live-streaming commerce, some scholars employ engagement to describe consumer behavioral responses [5,8,9], while others employ purchase intentions [6,10,17]. In this study, both engagement and purchase intentions were employed to describe consumer behavioral responses. To explore how to choose these two dependent variables, engagement and purchase intentions, we assumed that engagement positively affects purchase intentions.

References

  1. Mou, J.; Benyoucef, M. Consumer behavior in social commerce: Results from a meta-analysis. Technol. Forecast. Soc. Change 2021, 167, 120734.
  2. Xue, J.; Liang, X.; Xie, T.; Wang, H. See now, act now: How to interact with customers to enhance social commerce engagement? Inf. Manag. 2020, 57, 103324.
  3. Kang, K.; Lu, J.; Guo, L.; Li, W. The dynamic effect of interactivity on customer engagement behavior through tie strength: Evidence from live streaming commerce platforms. Int. J. Inf. Manag. 2021, 56, 102251.
  4. Wongkitrungrueng, A.; Assarut, N. The role of live streaming in building consumer trust and engagement with social commerce sellers. J. Bus. Res. 2020, 117, 543–556.
  5. Su, Q.L.; Zhou, F.; Wu, Y.J. Using virtual gifts on live streaming platforms as a sustainable strategy to stimulate consumers’ green purchase intention. Sustainability 2020, 12, 3783.
  6. Wei, H.; Gao, J.; Wang, F. The impact of information interaction on user engagement behavior in live streaming commerce. Inf. Sci. 2021, 39, 148–156.
  7. Liu, F.; Meng, L.; Chen, Y.; Duan, K. The impact of network celebrities’ information source charecteristics on purchase intention. Chin. J. Manag. 2020, 17, 94–104.
  8. Tseng, F.C.; Cheng, T.C.E.; Li, K.; Teng, C.I. How does media richness contribute to customer loyalty to mobile instant messaging? Internet Res. 2017, 27, 520–537.
  9. Chen, Y.H.; Chen, M.C.; Keng, C.J. Measuring online live streaming of perceived servicescape Scale development and validation on behavior outcome. Internet Res. 2020, 30, 737–762.
  10. Li, Y.; Li, X.L.; Cai, J.L. How attachment affects user stickiness on live streaming platforms: A socio-technical approach perspective. J. Retail. Consum. Serv. 2021, 60, 102478.
  11. Sarkar, S.; Chauhan, S.; Khare, A. A meta-analysis of antecedents and consequences of trust in mobile commerce. Int. J. Inf. Manag. 2020, 50, 286–301.
  12. Ma, Y.Y. To shop or not: Understanding Chinese consumers’ live-stream shopping intentions from the perspectives of uses and gratifications, perceived network size, perceptions of digital celebrities, and shopping orientations. Telemat. Inform. 2021, 59, 101562.
  13. Pancer, E.; Chandler, V.; Poole, M.; Noseworthy, T.J. How readability shapes social media engagement. J. Consum. Psychol. 2019, 29, 262–270.
  14. Busalim, A.H.; Hussin, A.R.C.; Iahad, N.A. Factors influencing customer engagement in social commerce websites: A systematic literature review. J. Theor. Appl. Electron. Commer. Res. 2019, 14, 1–14.
  15. Molinillo, S.; Anaya-Sánchez, R.; Liebana-Cabanillas, F. Analyzing the effect of social support and community factors on customer engagement and its impact on loyalty behaviors toward social commerce websites. Comput. Hum. Behav. 2020, 108, 105980.
  16. Sun, Y.; Shao, X.; Li, X.; Guo, Y.; Nie, K. How live streaming influences purchase intentions in social commerce: An IT affordance perspective. Electron. Commer. Res. Appl. 2019, 37, 100886.
  17. Zhang, M.; Sun, L.; Qin, F.; Wang, G.A. E-service quality on live streaming platforms: Swift guanxi perspective. J. Serv. Mark. 2021, 35, 312–324.
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Linye Ma
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