Single vs multiple collaborations in influencer-driven information dissemination: an evolutionary game model approach DOI

Junjie Lv,

Chaoyue Gong,

Ziyi Wang

et al.

Asia Pacific Journal of Marketing and Logistics, Journal Year: 2025, Volume and Issue: unknown

Published: April 8, 2025

Purpose This paper aims to counteract the time-related decay of information dissemination in social commerce by proposing an evolutionary game model based on complex networks, analyzing how companies with limited budgets strategically select or re-select macro- and meso-influencers maximize effectiveness. Design/methodology/approach The integrates utility environment updating mechanisms simulate individual forwarding decisions, utilizing a purchase intention function influenced environmental personal factors, as well number previous purchasers. A pre-experiment was conducted determine optimal time interval, followed numerical simulations comparing single-stage versus two-stage influencer engagement strategies. Findings Results demonstrate that low brand popularity should prioritize investments macro-influencers at initial stage, particularly risk-averse markets. Those medium-to-high benefit more from strategy, where investment ranges 0.5 0.8, while subsequent remains below 0.5. approach is especially effective markets higher proportion risk-seeking consumers. Research limitations/implications study constrained simulation parameters lacks validation real-world data, which may affect generalizability findings. Future research explore empirical strengthen these insights. Originality/value introduces novel optimizing collaborations strategies, providing valuable insights for adapting communication stage.

Language: Английский

Single vs multiple collaborations in influencer-driven information dissemination: an evolutionary game model approach DOI

Junjie Lv,

Chaoyue Gong,

Ziyi Wang

et al.

Asia Pacific Journal of Marketing and Logistics, Journal Year: 2025, Volume and Issue: unknown

Published: April 8, 2025

Purpose This paper aims to counteract the time-related decay of information dissemination in social commerce by proposing an evolutionary game model based on complex networks, analyzing how companies with limited budgets strategically select or re-select macro- and meso-influencers maximize effectiveness. Design/methodology/approach The integrates utility environment updating mechanisms simulate individual forwarding decisions, utilizing a purchase intention function influenced environmental personal factors, as well number previous purchasers. A pre-experiment was conducted determine optimal time interval, followed numerical simulations comparing single-stage versus two-stage influencer engagement strategies. Findings Results demonstrate that low brand popularity should prioritize investments macro-influencers at initial stage, particularly risk-averse markets. Those medium-to-high benefit more from strategy, where investment ranges 0.5 0.8, while subsequent remains below 0.5. approach is especially effective markets higher proportion risk-seeking consumers. Research limitations/implications study constrained simulation parameters lacks validation real-world data, which may affect generalizability findings. Future research explore empirical strengthen these insights. Originality/value introduces novel optimizing collaborations strategies, providing valuable insights for adapting communication stage.

Language: Английский

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