A tripartite evolutionary game for strategic decision-making in live-streaming e-commerce

IF 3.1 3区计算机科学 Q2 COMPUTER SCIENCE, INTERDISCIPLINARY APPLICATIONS

Journal of Computational Science Pub Date : 2025-04-09 DOI:10.1016/j.jocs.2025.102585

Georgia Fargetta, Laura R.M. Scrimali

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引用次数: 0

Abstract

The rapid growth of live-streaming has transformed traditional e-commerce into an interactive and immersive experience, giving birth to live-streaming e-commerce. This paper investigates the strategic interactions between brands, social media influencers, and consumers under this mechanism. Using evolutionary game theory, we model decision-making dynamics across these three parties and analyze how their strategies develop over time. Our framework incorporates contractual penalties between brands and influencers, rewards for influencers, product returns, and subscription fees to capture realistic market behaviors. We derive replicator dynamics equations for each participant group and identify stable equilibrium strategies for the entire system. The application of replicator dynamics offers valuable perspectives on temporary states and strategies that achieve long-term equilibrium. We also present numerical simulations to validate the effectiveness of our model. In addition, we show how parameters, such as penalties and rewards, influence strategy selection and allow the system to achieve stability successfully. This research provides actionable recommendations for optimizing partnerships in live-streaming e-commerce supply chains.

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直播电子商务中战略决策的三方进化博弈

视频直播的快速发展，将传统的电子商务转变为一种互动、沉浸式的体验，催生了视频直播电子商务。本文研究了在这一机制下，品牌、社交媒体影响者和消费者之间的战略互动。利用进化博弈论，我们模拟了这三方的决策动态，并分析了他们的策略是如何随着时间的推移而发展的。我们的框架包括品牌和网红之间的合同处罚、对网红的奖励、产品退货和订阅费，以捕捉现实的市场行为。我们推导了每个参与者群体的复制因子动力学方程，并确定了整个系统的稳定平衡策略。复制因子动力学的应用为实现长期平衡的临时状态和策略提供了有价值的视角。通过数值模拟验证了模型的有效性。此外，我们还展示了惩罚和奖励等参数如何影响策略选择，并使系统成功实现稳定性。本研究为优化网络直播电子商务供应链中的合作伙伴关系提供了可行的建议。

本文章由计算机程序翻译，如有差异，请以英文原文为准。

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来源期刊

Journal of Computational Science COMPUTER SCIENCE, INTERDISCIPLINARY APPLICATIONS-COMPUTER SCIENCE, THEORY & METHODS

CiteScore

5.50

自引率

3.00%

发文量

227

审稿时长

41 days

期刊介绍： Computational Science is a rapidly growing multi- and interdisciplinary field that uses advanced computing and data analysis to understand and solve complex problems. It has reached a level of predictive capability that now firmly complements the traditional pillars of experimentation and theory. The recent advances in experimental techniques such as detectors, on-line sensor networks and high-resolution imaging techniques, have opened up new windows into physical and biological processes at many levels of detail. The resulting data explosion allows for detailed data driven modeling and simulation. This new discipline in science combines computational thinking, modern computational methods, devices and collateral technologies to address problems far beyond the scope of traditional numerical methods. Computational science typically unifies three distinct elements: • Modeling, Algorithms and Simulations (e.g. numerical and non-numerical, discrete and continuous); • Software developed to solve science (e.g., biological, physical, and social), engineering, medicine, and humanities problems; • Computer and information science that develops and optimizes the advanced system hardware, software, networking, and data management components (e.g. problem solving environments).