File Download
There are no files associated with this item.
Links for fulltext
(May Require Subscription)
- Publisher Website: 10.1016/j.elerap.2023.101266
- Scopus: eid_2-s2.0-85158067667
- WOS: WOS:001001012900001
- Find via

Supplementary
- Citations:
- Appears in Collections:
Article: Understanding the role of live streamers in live-streaming e-commerce
| Title | Understanding the role of live streamers in live-streaming e-commerce |
|---|---|
| Authors | |
| Keywords | Clustering Determinants Fan growth Gross merchandise value Live-streaming e-commerce |
| Issue Date | 29-Apr-2023 |
| Publisher | Elsevier |
| Citation | Electronic Commerce Research and Applications, 2023, v. 59 How to Cite? |
| Abstract | The rise of live-streaming e-commerce has attracted the wide participation of online influencers, brands, and retailers. Live streamers offer a fresh shopping experience to consumers through broadcasting product demonstrations and communicating with them. This study characterizes the streamers’ behavior and explores the key drivers of live-streaming e-commerce success as measured by gross merchandise value (GMV) and fan growth. We employ both machine learning and econometric methods to analyze a unique dataset of 55,096 shows by the top 1,000 live streamers on Alibaba’s live streaming platform. We identify three distinct clusters. The most important differentiating features include a live streamer’s platform affiliation and product category. Selling more products and spending more time on each product in a live-streaming show are two factors driving both GMV and fan growth. We also discover that a large fan base does not always help, as the positive effect of fan base only exists conditionally. |
| Persistent Identifier | http://hdl.handle.net/10722/330977 |
| ISSN | 2023 Impact Factor: 5.9 2023 SCImago Journal Rankings: 1.338 |
| ISI Accession Number ID |
| DC Field | Value | Language |
|---|---|---|
| dc.contributor.author | Chen, Hailiang | - |
| dc.contributor.author | Dou, Yifan | - |
| dc.contributor.author | Xiao, Yongbo | - |
| dc.date.accessioned | 2023-09-21T06:51:43Z | - |
| dc.date.available | 2023-09-21T06:51:43Z | - |
| dc.date.issued | 2023-04-29 | - |
| dc.identifier.citation | Electronic Commerce Research and Applications, 2023, v. 59 | - |
| dc.identifier.issn | 1567-4223 | - |
| dc.identifier.uri | http://hdl.handle.net/10722/330977 | - |
| dc.description.abstract | <p>The rise of live-streaming e-commerce has attracted the wide participation of online influencers, brands, and retailers. Live streamers offer a fresh shopping experience to consumers through broadcasting product demonstrations and communicating with them. This study characterizes the streamers’ behavior and explores the key drivers of live-streaming e-commerce success as measured by gross merchandise value (GMV) and fan growth. We employ both <a href="https://www.sciencedirect.com/topics/computer-science/machine-learning" title="Learn more about machine learning from ScienceDirect's AI-generated Topic Pages">machine learning</a> and econometric methods to analyze a unique dataset of 55,096 shows by the top 1,000 live streamers on Alibaba’s live streaming platform. We identify three distinct clusters. The most important differentiating features include a live streamer’s platform affiliation and product category. Selling more products and spending more time on each product in a live-streaming show are two factors driving both GMV and fan growth. We also discover that a large fan base does not always help, as the positive effect of fan base only exists conditionally.<br></p> | - |
| dc.language | eng | - |
| dc.publisher | Elsevier | - |
| dc.relation.ispartof | Electronic Commerce Research and Applications | - |
| dc.subject | Clustering | - |
| dc.subject | Determinants | - |
| dc.subject | Fan growth | - |
| dc.subject | Gross merchandise value | - |
| dc.subject | Live-streaming e-commerce | - |
| dc.title | Understanding the role of live streamers in live-streaming e-commerce | - |
| dc.type | Article | - |
| dc.identifier.doi | 10.1016/j.elerap.2023.101266 | - |
| dc.identifier.scopus | eid_2-s2.0-85158067667 | - |
| dc.identifier.volume | 59 | - |
| dc.identifier.eissn | 1873-7846 | - |
| dc.identifier.isi | WOS:001001012900001 | - |
| dc.identifier.issnl | 1567-4223 | - |
