AI-LLM Empowering Supply Chain Resilience: An Analysis Based on a Manufacturer-Supplier-Consumer Tripartite Evolutionary Game Model

This dataset comprises the numerical simulation results and associated code from the study entitled "AI-LLM Empowering Supply Chain Resilience: An Analysis Based on a Tripartite Evolutionary Game Model of Manufacturer-Supplier-Consumer." The study examines how artificial intelligence and large language models (AI-LLM) enhance supply chain resilience by influencing the strategic interactions among manufacturers, suppliers, and consumers. The core methodology employs a tripartite evolutionary game model, which simulates the dynamic strategic behaviors of the three stakeholders under various parameter configurations that reflect the impact of AI-LLM technology. Data used in this research are collected from prominent Chinese online platforms—including Toutiao, Sohu, and news forums—providing empirical support for parameter calibration in the model. Furthermore, the simulation codes for generating figures and solving equilibrium points were primarily implemented manually in MATLAB, encompassing time series data that depict the evolution of strategy adoption probabilities, along with the corresponding computational scripts necessary to reproduce the model outcomes. The dataset is systematically organized and comprehensive, thereby offering valuable reference material and practical insights for researchers working in the field of game theory.

本数据集包含题为《AI-大语言模型赋能供应链韧性：基于制造商-供应商-消费者三方演化博弈模型的分析》的研究中的数值模拟结果与配套代码。该研究探讨了人工智能与大语言模型（AI-LLM）如何通过影响制造商、供应商与消费者之间的战略互动，提升供应链韧性。本研究的核心方法论采用三方演化博弈模型，该模型可模拟三类利益相关者在反映AI-LLM技术影响的各类参数配置下的动态战略行为。本研究使用的数据取自今日头条（Toutiao）、搜狐（Sohu）等国内主流在线平台及新闻论坛，为模型的参数校准提供了实证支撑。此外，用于生成图表与求解均衡点的模拟代码主要通过MATLAB手动实现，涵盖了刻画策略采纳概率演化过程的时序数据，以及复现模型结果所需的配套计算脚本。本数据集组织系统且内容全面，可为博弈论领域的研究人员提供极具价值的参考资料与实践洞见。