Interactivity and live-streaming commerce purchase intention: Social presence as a mediator

Main Article Content

Lei Zhang
Xiaoli Liu
Cite this article:  Zhang, L., & Liu, X. (2023). Interactivity and live-streaming commerce purchase intention: Social presence as a mediator. Social Behavior and Personality: An international journal, 51(2), e12104.


Abstract
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We investigated the relationship between interactivity and consumer purchase intention in the context of live-streaming commerce, with consideration of social presence as a mediator. Participants were 339 undergraduate students at six universities in China who had experience of live-streaming commerce. The results indicated that interactivity in live-streaming commerce had a direct and positive relationship with consumers’ purchase intention, with social presence acting as a mediator of this relationship. Our findings shed light on how interactivity in live-streaming commerce helps to enhance consumers’ purchase intention. Theoretical and practical implications are discussed.

Live-streaming commerce is a business model in which streamers present products to consumers on an Internet platform in a way designed to attract active participation (X. Liu et al., 2022). Live-streaming commerce not only enriches the content and scenes of the live-streaming industry, but also injects new vitality into the growth of users of this industry. In particular, the large-scale restrictions on people’s movements because of the COVID-19 pandemic further promoted the development of live-streaming commerce. In China, there were 464 million live-streaming commerce users in 2021 (China Internet Network Information Center, 2022). As a new hotspot, live-streaming commerce has received a lot of attention from academia (J. Chen & Liao, 2022).

The key feature of live-streaming commerce is its interactivity (Sun et al., 2021). Streamers interact with consumers as they display products, and consumers can interact with each other and consult with the streamer (Y. Li et al., 2021; B. Zhang et al., 2021). Compared to traditional e-commerce, the interaction in live-streaming commerce is visual, immediate, and targeted (Xue et al., 2020). The multichannel, real-time, dynamic, and two-way interactions between streamers and consumers increase consumers’ purchase intention (Ma et al., 2022). Therefore, it is crucial to explore how live-streaming commerce interactivity influences consumers’ purchase intention (B. Zhang et al., 2021). However, there have been few empirical studies on the mechanism of how live-streaming commerce interactivity relates to consumers’ purchase intention (Ma et al., 2022).

In live-streaming research, another important construct is social presence (Sun et al., 2021), which is the warm feeling that the medium brings to the user through the psychological perception that they are interacting with others in a virtual space and perceiving the presence of others (Hassanein & Head, 2007). In live-streaming marketing settings, interactivity can improve consumers’ sense of social presence (J. Chen & Liao, 2022) and reduce their concerns about the product, thus enhancing their purchase intention (Y. Li et al., 2021). Therefore, social presence can be used to explore how live-streaming commerce interactivity influences consumers’ purchase intention. However, as a new consumption context, there are few empirical studies exploring the mechanism of the effect of live-streaming commerce interactivity on consumers’ purchase intention based on social presence (Sun et al., 2021). To fill these gaps in the literature, we investigated the relationship between interactivity and consumer purchase intention in the context of live-streaming commerce, with social presence considered as a mediator.

Interactivity refers to a purchase environment in which consumers can directly express their needs and desires through the company’s marketing communications. H. Liu et al. (2016) confirmed that interpersonal interaction factors positively influence consumers’ purchase intention in social commerce settings. In live-streaming commerce, interactivity can change consumers’ perceptions and emotions, and enhance their familiarity with and understanding of the product and the streamer, which will increase their trust (B. Zhang et al., 2021) and, in turn, enhance their purchase intentions (X. Liu et al., 2021). As such, we proposed the following hypothesis:
Hypothesis 1: Interactivity in a live-streaming commerce setting will be positively related to consumers’ purchase intention.
 
Interactions online can reduce users’ sense of loneliness and perceived risk (Kim & Kim, 2020). In live-streaming commerce, the interaction of consumers with streamers and other consumers can gradually instill a sense of warmth and socialization, creating a strong atmosphere of social presence (Feng & Lu, 2020). In the two-way interaction scenario of live-streaming commerce, streamers can show their products from all directions and multiple angles, and can exchange product information with consumers, creating a face-to-face shopping scenario where seeing is believing, which allows consumers to experience a sense of actually being there and potentially gives them a sense of social presence (Ma et al., 2022; Sun et al., 2021).
 
Social presence is an important factor for using virtual shopping platforms. Wang et al. (2014) emphasized that increased social presence in business-to-customer websites can effectively promote consumers’ positive attitude toward these websites. Having a social presence in live-streaming commerce helps to close the psychological distance between merchant and consumer, thus promoting a closer relationship between the consumer and the company or platform and increasing consumer trust in and satisfaction with the product (Ye et al., 2020). W. Li et al. (2021) found that social presence in online reading communities plays a full mediating role between human-to-human interactivity and member satisfaction. As such, we speculate that consumer–streamer interaction and consumer–consumer interaction in live-streaming commerce settings will give consumers a sense of social presence that will, in turn, stimulate their willingness to purchase. Therefore, we proposed the following hypothesis:
Hypothesis 2: Interactivity in a live-streaming commerce setting will have an indirect positive relationship with consumers’ purchase intention via the mediator of social presence.
 
The conceptual framework of the study is shown in Figure 1.

Table/Figure

Figure 1. Conceptual Framework

Method

Participants and Procedure

Participants were undergraduate students at six universities in China who had experience with using live-streaming commerce. We chose an undergraduate sample because 23.7% of Chinese netizens were students in 2019 (China Internet Network Information Center, 2020). Our study was approved by the Ethics Committees of China Jiliang University and Zhejiang Gongshang University. With the help of university faculty members we distributed 360 paper surveys to students, told them about the purpose of the study, and gained their agreement in writing to participate. The participants made their responses according to their recall of a recent live-streaming commerce experience. We received 339 valid survey forms, for a response rate of 94.2%. There were 196 (57.8%) women and 143 (42.2%) men (Mage = 19.74 years, SD = 1.37, range = 18–23). As compensation, participants received a small gift worth USD 1.00–2.00.

Measures

All constructs were rated on a 5-point Likert scale rated from 1 = strongly disagree to 5 = strongly agree. We translated the English items into Chinese and then two bilingual researchers translated them back into English. After the review of two professors in the field of consumer psychology, the wording and meaning of some items in this version were revised to facilitate Chinese understanding.
 

Interactivity

Four items assessing interactivity were adopted from Wei et al. (2022). A sample item is “I was able to communicate with the streamer immediately while watching the live streaming.” The Cronbach’s alpha of these items was .80.
 

Social Presence

Five items assessing social presence were adopted from Busalim et al. (2021). A sample item is “The interaction with the streamer in live-streaming commerce was warm.” The Cronbach’s alpha of these items was .87.
 

Purchase Intention           

We adapted three items assessing purchase intention from A. Chen et al. (2017) so they fit the live-streaming setting: “I intended to purchase products or services from this live-streaming room,” “I predicted that I would purchase products or services from this live-streaming room,” and “If there was a product or service that I would like to purchase, I would firstly purchase from this live-streaming room.” The Cronbach’s alpha of these items was .77.

Results

Measurement Model

We validated the measures using Amos 21.0. According to Table 1, the proposed model had a good fit to the data. Moreover, composite reliability values were all above .70 and average variance extracted values were greater than .50. Therefore, the measures had good reliability and validity.

Table 1. Validity Analysis Results for Study Constructs

Table/Figure
Note. CR = composite reliability; AVE = average variance extracted; RMSEA = root mean square error of approximation; CFI = comparative fit index; IFI = incremental fit index.
** p < .01.

Hypothesis Testing

To verify the hypotheses we conducted structural equation modeling with 95% confidence intervals (CIs) using Amos 21.0. The results indicated that interactivity had a significant and positive relationship with consumers’ purchase intention for products shown in live-streaming commerce, β = .30, p < .01, 95% CI [0.16, 0.43]. Thus, Hypothesis 1 was supported.

Further, interactivity had a significant and positive relationship with social presence, β = .39, p < .01, 95% CI [0.26, 0.50], and social presence had a significant and positive relationship with purchase intention, β = .43, p < .01, 95% CI [0.31, 0.54]. We then performed a bootstrapping analysis with 5,000 replications to examine the mediating role of social presence and the results were as follows: indirect effect = .17, 95% CI [0.10, 0.24]. Therefore, Hypothesis 2 was supported.

Discussion


In this paper our focus was on the influence of interactivity on consumers’ purchase intention in live-streaming commerce via the mediator of social presence. The results show that interactivity in live-streaming commerce has a positive relationship with consumers’ purchase intention, and that social presence mediates this relationship. Streamers showcase products, share experiences, and interact with consumers through message boards and pop-ups to understand consumers’ demands and doubts, and provide them with more information about the products (M. Zhang et al., 2021), which reduces consumers’ concerns about the product and helps to increase their willingness to purchase. These continued, in-depth interactions can also increase consumers’ sense of social presence (J. Chen & Liao, 2022), thus enhancing their purchase intention (Y. Li et al., 2021).

Theoretical and Practical Implications

This study has two main theoretical contributions: First, we examined how live-streaming commerce interactivity relates to consumers’ purchase intention. There have been few empirical studies on the mechanism of this relationship (Ma et al., 2022); thus, our findings provide a fresh perspective for quantitative studies in the research area of live-streaming commerce. Second, we examined the mediating effect of social presence in the relationship between interactivity in live-streaming commerce and consumers’ purchase intention, which contributes to the existing research (Lu & Chen, 2021). Few empirical studies have explored the mechanism of live-streaming commerce interactivity on consumers’ purchase intention based on social presence (Sun et al., 2021). Our findings reveal that interactivity is indeed associated with social presence, which further contributes to consumers’ purchase intention. Thus, our research provides a new mechanism for explaining the formation of consumer intention.

From a practical perspective, we have provided an analysis of how interactivity in live-streaming commerce facilitates consumers’ purchase intention partially through the enhancement of social presence. Therefore, it is crucial for streamers to improve interactivity to facilitate consumers’ purchase intention and perceived social presence. For example, the streamer can welcome new consumers, enliven the atmosphere of the live-streaming room, and respond to consumers’ questions as soon as possible. Second, the streamer should understand the needs of consumers and dynamically adjust the live-streaming content to suit, improve the sense of participation of consumers, and provide a platform for consumer-to-consumer communication. All these features are essential to maximizing the appeal of live-streaming commerce to the consumer; therefore, the streamer should be constantly striving to improve on and add to the way these features of the shopping service are delivered. These practices and strategies can deepen the interactions of consumers and streamers and of consumers with other consumers, thus enhancing the perception of social presence and, ultimately, enhancing their willingness to purchase.

Limitations and Directions for Future Research

This study has limitations. First, live-streaming commerce has many other features, such as entertainment and professionalization, so future studies could introduce these into the research model to explore the psychology and behavior of consumers in the context of live-streaming commerce. Second, as the research data were obtained from a sample composed only of students, this may affect the generalizability of our research results. Future studies could be conducted to sample other populations. Finally, interactivity in live-streaming commerce relates to consumers’ cognitive responses, but whether there are other mediating and moderating constructs in the influence mechanism needs further study.

References

Busalim, A. H., Ghabban, F., & Hussin, A. R. C. (2021). Customer engagement behaviour on social commerce platforms: An empirical study. Technology in Society, 64, Article 101437.
 
Chen, A., Lu, Y., & Wang, B. (2017). Customers’ purchase decision-making process in social commerce: A social learning perspective. International Journal of Information Management, 37(6), 627–638.
 
Chen, J., & Liao, J. (2022). Antecedents of viewers’ live streaming watching: A perspective of social presence theory. Frontiers in Psychology, 13, Article 839629.
 
China Internet Network Information Center. (2020). The 46th statistical report on Internet development in China [In Chinese].
 
China Internet Network Information Center. (2022). The 49th statistical report on Internet development in China [In Chinese].
 
Feng, J., & Lu, M. (2020). An empirical study of impulse buying intention during live marketing in the mobile Internet era [In Chinese]. Soft Science, 34(12), 128–133 + 144.
 
Hassanein, K., & Head, M. (2007). Manipulating perceived social presence through the web interface and its impact on attitude towards online shopping. International Journal of Human-Computer Studies, 65(8), 689–708.
 
Kim, H. S., & Kim, M. (2020). Viewing sports online together? Psychological consequences on social live streaming service usage. Sport Management Review, 23(5), 869–882.
 
Li, W., Mao, Y., & Zhou, L. (2021). The impact of interactivity on user satisfaction in digital social reading: Social presence as a mediator. International Journal of Human–Computer Interaction, 37(17), 1636–1647.
 
Li, Y., Li, X., & Cai, J. (2021). How attachment affects user stickiness on live streaming platforms: A socio-technical approach perspective. Journal of Retailing and Consumer Services, 60, Article 102478.
 
Liu, H., Chu, H., Huang, Q., & Chen, X. (2016). Enhancing the flow experience of consumers in China through interpersonal interaction in social commerce. Computers in Human Behavior, 58, 306–314.
 
Liu, X., Xiang, G., & Zhang, L. (2021). Social support and social commerce purchase intention: The mediating role of social trust. Social Behavior and Personality: An international journal, 49(7), Article 10381.
 
Liu, X., Zhang, L., & Chen, Q. (2022). The effects of tourism e-commerce live streaming features on consumer purchase intention: The mediating roles of flow experience and trust. Frontiers in Psychology, 13, Article 995129.
 
Lu, B., & Chen, Z. (2021). Live streaming commerce and consumers’ purchase intention: An uncertainty reduction perspective. Information & Management, 58(7), Article 103509.
 
Ma, L., Gao, S., & Zhang, X. (2022). How to use live streaming to improve consumer purchase intentions: Evidence from China. Sustainability, 14(2), Article 1045.
 
Sun, W., Gao, W., & Geng, R. (2021). The impact of the interactivity of Internet celebrity anchors on consumers’ purchase intention. Frontiers in Psychology, 12, Article 757059.
 
Wang, Q., Yang, Y., Wang, Q., & Ma, Q. (2014). The effect of human image in B2C website design: An eye-tracking study. Enterprise Information Systems, 8(5), 582–605.
 
Wei, J., Li, M., & Liu, B. (2022). Research on the influence of anchor characteristics on consumers’ impulse purchase intention in e-commerce live streaming [In Chinese]. China Business and Market, 36(4), 32–42.
 
Xue, J., Liang, X., Xie, T., & Wang, H. (2020). See now, act now: How to interact with customers to enhance social commerce engagement? Information & Management, 57(6), Article 103324.
 
Ye, S., Lei, S. I., Shen, H., & Xiao, H. (2020). Social presence, telepresence and customers’ intention to purchase online peer-to-peer accommodation: A mediating model. Journal of Hospitality and Tourism Management, 42, 119–129.
 
Zhang, B., Zhang, Q., & Zhao, C. (2021). The influence of webcast characteristics on consumers’ purchase intention under e-commerce live broadcasting mode—The mediating role of consumer perception [In Chinese]. China Business and Market, 35(6), 52–61.
 
Zhang, M., Sun, L., Qin, F., & Wang, G. A. (2021). E-service quality on live streaming platforms: Swift guanxi perspective. Journal of Services Marketing, 35(3), 312–324.

Busalim, A. H., Ghabban, F., & Hussin, A. R. C. (2021). Customer engagement behaviour on social commerce platforms: An empirical study. Technology in Society, 64, Article 101437.
 
Chen, A., Lu, Y., & Wang, B. (2017). Customers’ purchase decision-making process in social commerce: A social learning perspective. International Journal of Information Management, 37(6), 627–638.
 
Chen, J., & Liao, J. (2022). Antecedents of viewers’ live streaming watching: A perspective of social presence theory. Frontiers in Psychology, 13, Article 839629.
 
China Internet Network Information Center. (2020). The 46th statistical report on Internet development in China [In Chinese].
 
China Internet Network Information Center. (2022). The 49th statistical report on Internet development in China [In Chinese].
 
Feng, J., & Lu, M. (2020). An empirical study of impulse buying intention during live marketing in the mobile Internet era [In Chinese]. Soft Science, 34(12), 128–133 + 144.
 
Hassanein, K., & Head, M. (2007). Manipulating perceived social presence through the web interface and its impact on attitude towards online shopping. International Journal of Human-Computer Studies, 65(8), 689–708.
 
Kim, H. S., & Kim, M. (2020). Viewing sports online together? Psychological consequences on social live streaming service usage. Sport Management Review, 23(5), 869–882.
 
Li, W., Mao, Y., & Zhou, L. (2021). The impact of interactivity on user satisfaction in digital social reading: Social presence as a mediator. International Journal of Human–Computer Interaction, 37(17), 1636–1647.
 
Li, Y., Li, X., & Cai, J. (2021). How attachment affects user stickiness on live streaming platforms: A socio-technical approach perspective. Journal of Retailing and Consumer Services, 60, Article 102478.
 
Liu, H., Chu, H., Huang, Q., & Chen, X. (2016). Enhancing the flow experience of consumers in China through interpersonal interaction in social commerce. Computers in Human Behavior, 58, 306–314.
 
Liu, X., Xiang, G., & Zhang, L. (2021). Social support and social commerce purchase intention: The mediating role of social trust. Social Behavior and Personality: An international journal, 49(7), Article 10381.
 
Liu, X., Zhang, L., & Chen, Q. (2022). The effects of tourism e-commerce live streaming features on consumer purchase intention: The mediating roles of flow experience and trust. Frontiers in Psychology, 13, Article 995129.
 
Lu, B., & Chen, Z. (2021). Live streaming commerce and consumers’ purchase intention: An uncertainty reduction perspective. Information & Management, 58(7), Article 103509.
 
Ma, L., Gao, S., & Zhang, X. (2022). How to use live streaming to improve consumer purchase intentions: Evidence from China. Sustainability, 14(2), Article 1045.
 
Sun, W., Gao, W., & Geng, R. (2021). The impact of the interactivity of Internet celebrity anchors on consumers’ purchase intention. Frontiers in Psychology, 12, Article 757059.
 
Wang, Q., Yang, Y., Wang, Q., & Ma, Q. (2014). The effect of human image in B2C website design: An eye-tracking study. Enterprise Information Systems, 8(5), 582–605.
 
Wei, J., Li, M., & Liu, B. (2022). Research on the influence of anchor characteristics on consumers’ impulse purchase intention in e-commerce live streaming [In Chinese]. China Business and Market, 36(4), 32–42.
 
Xue, J., Liang, X., Xie, T., & Wang, H. (2020). See now, act now: How to interact with customers to enhance social commerce engagement? Information & Management, 57(6), Article 103324.
 
Ye, S., Lei, S. I., Shen, H., & Xiao, H. (2020). Social presence, telepresence and customers’ intention to purchase online peer-to-peer accommodation: A mediating model. Journal of Hospitality and Tourism Management, 42, 119–129.
 
Zhang, B., Zhang, Q., & Zhao, C. (2021). The influence of webcast characteristics on consumers’ purchase intention under e-commerce live broadcasting mode—The mediating role of consumer perception [In Chinese]. China Business and Market, 35(6), 52–61.
 
Zhang, M., Sun, L., Qin, F., & Wang, G. A. (2021). E-service quality on live streaming platforms: Swift guanxi perspective. Journal of Services Marketing, 35(3), 312–324.

Table/Figure

Figure 1. Conceptual Framework


Table 1. Validity Analysis Results for Study Constructs

Table/Figure
Note. CR = composite reliability; AVE = average variance extracted; RMSEA = root mean square error of approximation; CFI = comparative fit index; IFI = incremental fit index.
** p < .01.

This work was supported by the Soft Science Research Program of Zhejiang Province (2021C35045), the Scientific Research Project of Zhejiang Education Department (Y202248666), the Research Project on Higher Education of Zhejiang Gongshang University (Xgy22015), and the Key Project of Discipline Construction and Management of Zhejiang Gongshang University.

Xiaoli Liu, School of Humanities and Communication, Zhejiang Gongshang University, No. 18 Xuezheng Street, Xiasha, Hangzhou 310018, People’s Republic of China. Email: [email protected]

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