电商物流中的异质双边竞标机制设计与效率优化

Design and Efficiency Optimization of Heterogeneous Bilateral Bidding Mechanism in E-Commerce Logistics

摘要: 电子商务驱动的物流需求呈现碎片化、高频次与强时效性特征，传统货运模式因信息孤岛与局部寻优难以满足动态资源配置需求。针对货运市场因信息不对称、交易成本高及局部寻优导致的资源配置效率低下问题，本文提出一种基于货运网络节点的异质双边竞标交易机制。首先，通过解构货运市场，将异质货运标的按运距区间分层并实现同质化计量，基于大数据与智能算法的标准化交易单元设计：基于货物积载因数与运距区间划分，设计运量同质化计价模型，统一货运需求与供给的计量维度，降低交易复杂度。其次，改进McAfee双边拍卖机制，提出多单位异质标的匹配规则，通过供需双方密封竞标实现价格生成与自动匹配，并严格证明该机制满足激励相容、个体理性及预算平衡约束。仿真结果表明，在活跃市场中，交易者可通过真实报价获取绝大部分交易剩余(效率损失 ≤ 0.02)，且交易成功率随报价方差降低显著提升(最高达98%)，验证了机制在电商物流高波动场景下的鲁棒性。本文机制通过突破传统标价与议价模式的信息壁垒与效率瓶颈，为数字化物流平台规模化处理异质交易、优化资源配置提供了理论与技术支撑。

Abstract: E-commerce-driven logistics demand is characterized by fragmentation, high frequency and strong timeliness, and the traditional freight transport model is difficult to meet the dynamic resource allocation needs due to information silos and local optimization. In view of the inefficiency of resource allocation due to information asymmetry, high transaction cost and local optimization in the freight market, this paper proposes a heterogeneous bilateral bidding and trading mechanism based on freight network nodes. First, by deconstructing the freight market, the heterogeneous freight targets are stratified according to the distance interval and realize homogeneous measurement, based on the design of standardized trading units of big data and intelligent algorithms: based on the division of cargo accumulation factor and distance interval, the design of homogeneous pricing model of the freight volume, the unified freight demand and supply of measurement dimensions, and reduce the complexity of the transaction. Secondly, we improve McAfee bilateral auction mechanism, propose multi-unit heterogeneous bid matching rules, realize price generation and automatic matching through sealed bidding between supply and demand sides, and rigorously prove that the mechanism satisfies incentive compatibility, individual rationality and budget balance constraints. The simulation results show that in the active market, traders can obtain the majority of the transaction surplus through real quotes (efficiency loss ≤ 0.02), and the success rate of the transaction is significantly improved with the reduction of the quotes’ variance (up to 98%), which verifies the robustness of the mechanism in the high volatility scenario of e-commerce logistics. By breaking through the information barriers and efficiency bottlenecks of traditional bidding and bargaining models, the mechanism in this paper provides theoretical and technical support for digital logistics platforms to deal with heterogeneous transactions at scale and optimize resource allocation.