Luxury brands’ live streaming sales: the roles of streamer identity and level strategy
Bibliographic record
Abstract
Today, live streaming selling has grown and pioneered sales opportunities for luxury brands. Through a lens of influencer marketing and source credibility theory, this study investigates the role of streamer identity (i.e. internet celebrities and e-shop sellers) and streamer level (macro vs. micro) on luxury brands’ live streaming sales. Using fixed-effect models, the data from 7,164 live streaming campaigns between 1 August 2020 and 31 December 2020 are analyzed covering 17 international luxury brands on Taobao Live. The results suggest the use of a greater number of internet celebrities and e-shop sellers yields greater live streaming sales. Internet celebrities’ live streaming sales are positively associated with e-shop sellers’ live streaming sales. We further find that the streamer level moderates the effects of internet celebrity count and e-shop seller count on live streaming sales. These findings offer novel managerial implications for luxury brands’ streamer selection strategies.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.005 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.002 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.005 | 0.000 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".