Qiu Zeguo, Han Hao, Chen Yunhao, Wang Tianyu
School of Computer and Information Engineering, Harbin University of Commerce, Harbin, China.
Heilongjiang Key Laboratory of E-Commerce and Information Processing, Harbin, China.
PLoS One. 2025 Sep 2;20(9):e0326252. doi: 10.1371/journal.pone.0326252. eCollection 2025.
The breakthroughs in communication technologies, such as 5G, have significantly accelerated the popularity of high-traffic consumption entertainment activities, including short video live streaming and real-time broadcasting, making them one of the most prevalent social interaction methods today. It is the high activity level of such online engagements that has given rise to diversified online marketing business models, opening up new channels and opportunities for interactions between brands and consumers. This study focuses on the emerging "influencer marketing" strategy rooted in content marketing, employing double-layer network game theory to construct a dual-layer relationship network between "brands" and "influencers" and establish a game-theoretic mechanism between them. During the construction of the influencer network, a novel concept-tunable clustering of influencers' followers-is specifically introduced, followed by an analysis of how micro-level decision-making factors (from brands and influencers) and network structures influence the evolutionary mechanisms of macro-level cooperative emergence. This study focuses on the emerging "influencer marketing" strategy rooted in content marketing, employing double-layer network game theory to construct a dual-layer relationship network between "brands" and "influencers", establishing a game-theoretic mechanism between them and analyzing how micro-level decision-making factors (from brands and influencers) influence the evolutionary mechanisms of macro-level cooperative emergence. Specifically, during the construction of the influencer network, the network structural metric-tunable clustering-is integrated with the practical scenario of uneven follower distribution among influencers, thereby investigating the impact of influencer network clustering intensity on the system's evolutionary dynamics. The research findings reveal that:(1) Influencer marketing represents a win-win cooperative model. (2) Brands' decision-making outcomes are significantly affected by profit margins, additional costs, and commission rates. (3) Creative incentives and tunable clustering predominantly shape influencers' decision-making behaviors. (4) Product lifecycles and platform extraction rate impact decisions of both parties, with brands exhibiting higher sensitivity to environmental changes. Followers' trust levels in influencers have minimal influence on either party's decisions. Finally, applying reasonable values derived from parameter experiments to the influencer marketing model in the cosmetics industry demonstrates that this approach effectively enhances mutual benefits and stabilizes the overall business environment.
5G等通信技术的突破显著加速了高流量消费娱乐活动的普及，包括短视频直播和实时广播，使其成为当今最普遍的社交互动方式之一。正是这种在线参与的高活跃度催生了多样化的在线营销商业模式，为品牌与消费者之间的互动开辟了新渠道和机遇。本研究聚焦于源于内容营销的新兴“网红营销”策略，运用双层网络博弈理论构建“品牌”与“网红”之间的双层关系网络，并建立二者之间的博弈机制。在构建网红网络的过程中，特别引入了一个新颖的概念——网红粉丝的可调聚类，随后分析微观层面的决策因素（来自品牌和网红）以及网络结构如何影响宏观层面合作涌现的演化机制。本研究聚焦于源于内容营销的新兴“网红营销”策略，运用双层网络博弈理论构建“品牌”与“网红”之间的双层关系网络，建立二者之间的博弈机制，并分析微观层面的决策因素（来自品牌和网红）如何影响宏观层面合作涌现的演化机制。具体而言，在构建网红网络时，将网络结构指标可调聚类与网红粉丝分布不均的实际场景相结合，从而研究网红网络聚类强度对系统演化动态的影响。研究结果表明：（1）网红营销是一种双赢的合作模式。（2）品牌的决策结果受利润率、额外成本和佣金率的显著影响。（3）创意激励和可调聚类主要塑造网红的决策行为。（4）产品生命周期和平台抽取率影响双方的决策，品牌对环境变化表现出更高的敏感性。粉丝对网红的信任水平对双方的决策影响极小。最后，将参数实验得出的合理值应用于化妆品行业的网红营销模型，结果表明该方法有效提升了互利水平并稳定了整体商业环境。
