Optimal contracts with moral hazard and adverse selection in a live streaming commerce market
Why this work is in the frame
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Bibliographic record
Abstract
Live streaming commerce, as a new online selling channel, is increasingly gaining popularity and creating a vast market worth. Many brand suppliers are entrusting streamers to recommend their products via this channel. However, the cooperation between brand suppliers and streamers may not always achieve a win-win situation due to moral hazard and adverse selection problems, which has largely been ignored in previous studies. To address this gap, we develop two game models based on the Principal-agent theory to design incentive contracts under the streamer's influence and recommendation effort information asymmetry and investigate the price discount decisions in a live streaming commerce supply chain . The findings revealed that the equilibrium contracts depend on the prior beliefs that the brand suppliers hold on the streamers' influence. The information rent held by the high-influence streamers is unavoidable because of the information gap between the brand suppliers and streamers. Under double information asymmetry , brand suppliers maintain the unit commission and price discount for high-influence streamers unchanged while decreasing the unit commission and increasing the price discount for low-influence streamers. An important implication for brand suppliers is that they can obtain more benefits by cooperating with high-influence streamers who require low-price discounts.
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Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 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 it