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Research Note

E-Commerce Influencers in China: Dual-Route Model on Likes, Shares, and Sales

, &
Pages 486-501 | Received 04 Feb 2021, Accepted 05 Oct 2021, Published online: 17 Nov 2021
 

Abstract

This study investigates behavioral routes deployed by e-commerce influencers in product promotion in China. By analyzing videos posted on Douyin (China’s version of TikTok), it posits that the stature of the influencer and the reception of the content are the drivers of audience likes, shares, and sales. Further, how influencers strategically title their videos (product focus, engagement) and how the audience responds through live comments (positive identification, negative identification) are posited to moderate the effects of these two routes. The findings support some of the postulates and uncover unexpected results that provide directions for future research and useful managerial insights. In addition, the deployment of social listening is shown to be a useful research tool, and the dual-route model presents an overarching framework for future studies.

Number of followers: This term refers to the quantity of people who subscribe to an influencer’s link or channel. We use this to capture an influencer’s stature.

Audience: This term refers to those who have watched the video and may or may not be a follower.

Audience live comments: As audience members watch a Douyin video, they can type in and post their thoughts and feelings as live comments. The live comments are machine-read by Douchacha to form free-flow categories, which in turn are content-analyzed by the research team to form constructs such as positive identification and negative identification.

Likes: Number of audience members who expressed liking a video.

Shares: Number of audience members who shared a video.

Sales: Each Douyin e-commerce video (our unit of analysis) has a focal influencer who promotes a single product in the video. As audience members view the video, they can place an order directly through the link provided in the video. Thus, the sales figure reflects the direct effect of the video. Some audience members may purchase the promoted product through other means (i.e., without clicking the link); these nondirect sales are not included in our analysis, as these sales cannot be traced directly to the video.

Additional information

Funding

The authors acknowledge the financial support provided by a General Research Fund (GRF) grant (17504017).

Notes on contributors

Kineta Hung

Kineta Hung (PhD, Schulich School of Business, York University) is a professor, Department of Communication Studies, School of Communication, Hong Kong Baptist University.

David K. Tse

David K. Tse (PhD, University of California, Berkeley) is a visiting professor, Department of Marketing, Hong Kong University of Science and Technology.

Terri H. Chan

Terri H. Chan (PhD, University of Hong Kong) is an assistant professor, Department of Communication Studies, School of Communication, Hong Kong Baptist University.

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