用简单学习机制模拟供应链如何自发形成。
The Formation of Production Networks: How Supply Chains Arise from Simple Learning with Minimal Information
- 企业通过强化学习动态决策价格、产量和采购
- 无需完美知识也能自适应需求、供应等冲击
- 适合研究供应链演化与韧性，尤其对复杂系统建模者
我们构建了一个模型，企业决定其可区分产品的售价、生产量以及从其他企业采购的投入品类型和数量。生产网络在没有均衡假设或对生产技术完全认知的前提下，通过一种简单的强化学习机制内生形成。具有异质技术的企业在不确定性中通过学习最大化利润，能够应对需求波动、供应商/客户关闭、生产率变化及技术调整等冲击，从而有效重塑生产网络。为验证该模型潜力，我们分析了需求和生产率冲击对上下游的影响。
原文摘要 · Abstract (English)
We develop a model where firms determine the price at which they sell their differentiable goods, the volume that they produce, and the inputs (types and amounts) that they purchase from other firms. A steady-state production network emerges endogenously without resorting to assumptions such as equilibrium or perfect knowledge about production technologies. Through a simple version of reinforcement learning, firms with heterogeneous technologies cope with uncertainty and maximize profits. Due to this learning process, firms can adapt to shocks such as demand shifts, suppliers/clients closure, productivity changes, and production technology modifications; effectively reshaping the production network. To demonstrate the potential of this model, we analyze the upstream and downstream impact of demand and productivity shocks.
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