Peak-Shifting or Same-Screen? The Manufacturer’s Selection of Live-Streaming Modes and the Influencer Streamer’s Contract Strategy

Liu Yang et al.

Asia-Pacific Journal of Operational Research2026https://doi.org/10.1142/s0217595926400014article
AJG 1
Weight
0.50

What the paper says

In the live streaming (LS) environment, there are currently two types of streamers: human influencer streamers and virtual streamers. The time and energy of influencer streamers are limited, making it difficult to meet the audiences’ continuous demand for LS. Therefore, many manufacturers, while collaborating with influencer streamers, have also introduced virtual streamers. The manufacturers have two options: have influencer streamers and virtual streamers appear on the same screen ([Formula: see text]-mode), or to arrange them to live-stream in different time slots (peak-shifting LS, [Formula: see text]-mode). For an influencer streamer, he can choose between different contracts: revenue-sharing contract (RS-contract) and hybrid contract ([Formula: see text]-contract). In this paper, we investigate the manufacturer’s choice of LS modes, considering the influencer streamer’s contract strategies. Our research indicates that the manufacturer’s choice of LS modes depends on the technical cost of virtual live-streaming (VLS). Additionally, under the same technical cost, an increase in the platform commission rate will prompt the manufacturer to choose the [Formula: see text]-mode, while the growth in the influencer streamer’s traffic will encourage it to choose the [Formula: see text]-mode. The influencer streamer’s choice of contracts is influenced by the manufacturer’s LS strategy. The influencer streamer can perform better under either contract, depending on specific conditions.

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https://doi.org/https://doi.org/10.1142/s0217595926400014

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@article{liu2026,
  title        = {{Peak-Shifting or Same-Screen? The Manufacturer’s Selection of Live-Streaming Modes and the Influencer Streamer’s Contract Strategy}},
  author       = {Liu Yang et al.},
  journal      = {Asia-Pacific Journal of Operational Research},
  year         = {2026},
  doi          = {https://doi.org/https://doi.org/10.1142/s0217595926400014},
}

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Evidence weight

0.50

Balanced mode · F 0.40 / M 0.15 / V 0.05 / R 0.40

F · citation impact0.50 × 0.4 = 0.20
M · momentum0.50 × 0.15 = 0.07
V · venue signal0.50 × 0.05 = 0.03
R · text relevance †0.50 × 0.4 = 0.20

† Text relevance is estimated at 0.50 on the detail page — for your query’s actual relevance score, open this paper from a search result.