The primary objective of this study is to create an advanced management system that seamlessly integrates ChatGPT, an intelligent chatbot, with a cutting-edge two-stage auctions model. This integration aims to optimize the recycling process of electric vehicle batteries, ensuring utmost efficiency. To gauge the effect of incorporating ChatGPT on participants' values, we introduce technology coefficient parameters, providing a deeper understanding of its impact. In the initial phase of the auction, a sophisticated platform or an impartial third-party appraisal firm is employed. Their task is to collect vital attribute information from potential sellers regarding the waste batteries. Subsequently, this information is carefully matched with interested buyers. To determine the appropriate number of buyers both before and after the auction, we introduce two innovative matching mechanisms. We propose the implementation of a pioneering one-sided affine VCG (Vickrey-Clarke-Groves) auction, which portrays the affine externality of buyers to other buyers, along with a weighted generalized second-price auction. Additionally, we introduce a ground-breaking mechanism known as weighted multi-unit trade reduction. This inventive process allows successful bidders from the first stage to actively participate in the subsequent auction. Within this paper, we develop auction allocation rules based on the interplay between winning sellers' supply and winning buyers' demand. The outcomes of our numerical studies demonstrate the efficacy of the two-stage auction method in addressing buyers' concerns regarding battery performance. Furthermore, we have found that the utilization of ChatGPT technology proves advantageous for both participants and the platform; if buyers have a positive affine externality on other buyers, then the platform's revenue will be reduced, while social welfare will increase. In the realm of incentive compatibility, individual rationality, and budget balancing, our proposed mechanism stands unwaveringly strong, having undergone rigorous scrutiny and demonstrating commendable performance in numerous numerical experiments. Lastly, we offer practical management insights for stakeholders in the battery recycling market. These invaluable insights are derived from our hands-on experience, providing a fresh perspective for industry managers.

中文翻译：

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ChatGPT 支持电动汽车电池回收的两阶段拍卖

本研究的主要目标是创建一个先进的管理系统，将智能聊天机器人 ChatGPT 与尖端的两阶段拍卖模型无缝集成。这种整合旨在优化电动汽车电池的回收过程，确保最高效率。为了衡量纳入 ChatGPT 对参与者价值观的影响，我们引入了技术系数参数，以更深入地了解其影响。在拍卖的初始阶段，会采用成熟的平台或公正的第三方评估公司。他们的任务是从潜在卖家那里收集有关废电池的重要属性信息。随后，这些信息会与感兴趣的买家进行仔细匹配。为了确定拍卖前后的适当买家数量，我们引入了两种创新的匹配机制。我们建议实施一种开创性的单边仿射 VCG（Vickrey-Clarke-Groves）拍卖，它描绘了买家对其他买家的仿射外部性，以及加权广义第二价格拍卖。此外，我们引入了一种突破性的机制，称为加权多单位贸易减少。这一创造性的过程使得第一阶段的中标者能够积极参与随后的拍卖。在本文中，我们根据获胜卖家的供应和获胜买家的需求之间的相互作用制定了拍卖分配规则。我们的数值研究结果证明了两阶段拍卖方法在解决买家对电池性能的担忧方面的有效性。此外，我们发现ChatGPT技术的利用对于参与者和平台来说都是有利的；如果买家对其他买家有正的仿射外部性，那么平台的收入就会减少，而社会福利就会增加。在激励相容性、个体理性和预算平衡领域，我们提出的机制坚定不移，经过了严格的审查，并在大量数值实验中表现出了值得称赞的表现。最后，我们为电池回收市场的利益相关者提供实用的管理见解。这些宝贵的见解源自我们的实践经验，为行业管理者提供了全新的视角。