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Supply Chain Network Structure and Firm Returns

1. Jing Wu, The Chinese University of Hong Kong (CUHK) - CUHK Business School
2. John R. Birge, University of Chicago - Booth School of Business

2014

SSRN

Supply Chain, Lead-lag Effect, Network Centrality, Systematic Risk

The complexity and opacity of the network of interconnections among firms and their supply chains inhibits understanding of the impact of management decisions concerning the boundaries of the firm and the number and intensity of its relationships with suppliers and customers. Using recently available data on the relationships of public US firms, this paper investigates the effects of supply chain connections on firm performance as reflected in stock returns. The paper finds that supply chain structure is closely related to firm returns at two levels, a first-order effect from direct connections and a second-order impact from systemic exposures through the network. For the first order effect, using a cross-sectional data set of the supply chain network and monthly returns, we show that a firm’s return can be explained by its concurrent supplier returns, concurrent customer returns, own momentum, and supplier momentum, whereas customer momentum has little impact. A long-short equity strategy based on the supplier momentum yields monthly abnormal returns of 56 basis points. This result implies investors’ limited attention to supplier firms relative to customer firms and gradual diffusion of information downstream as opposed to upstream in the supply chain. For the second-order effect, we find a market anomaly by grouping firms according to their centrality in the supply chain. Specifically, manufacturing firms that are more central in the network earn lower returns, while logistics firms that are more central in the network earn higher returns. This result holds for both eigenvector centrality and in-degree centrality (number of suppliers). We argue that centrality and multiplicity of suppliers have different risk implications for firms operating in different industries. More central firms in manufacturing choose their suppliers to operationally hedge shocks transmitted from other firms and earn lower returns due to lower systematic risk. On the contrary, more central firms in logistics are shock aggregators, earning higher returns due to their exposure to greater systematic risk. Our results are robust after controlling for common asset pricing factors.

Wu, Jing, and John R. Birge. “Supply chain network structure and firm returns.” Available at SSRN 2385217 (2014).

1. https://papers.ssrn.com/sol3/papers.cfm?abstract_id=2385217
2. https://eyun.baidu.com/s/3c3uTtKG

1. 论文是关于什么的？[请提供该论文的简要摘要。]

论文研究了供应链结构与企业回报的关系，分两个方面：一阶效应和二阶效应。一阶效应中发现，供应商和客户的并发效应都对公司收益有显著影响，而在滞后效应中，公司收益只与供应商和自身的滞后效应相关，与客户滞后效应无关；在二阶效应中，本文研究了处于网络中心的制造企业与物流企业与公司回报的关系，发现制造企业集中度与公司股票回报呈负向关系，物流企业则相反。

2. 这篇论文的长处和短处是什么？[请以以下角度评述：（a）创新（研究问题、建模、方法等）；（b）相关性（研究问题、发现等）；（c）严谨性（适当的方法、分析的正确性等）]

研究问题、建模、方法等

本文研究了供应链与公司股票回报之间的关系，从供应商滞后效应、客户滞后效应、并发供应商回报、并发客户回报四个方面分析，采用混合OLS回归对面板数据进行研究。

研究问题、发现

本文研究发现公司回报与供应商的滞后效应存在显著性关系，而与客户滞后效应并无显著关系。在集中度上，处于中心的制造业与公司回报呈负向关系，而处于中心的物流企业与公司回报呈正向关系。

适当的方法、分析的正确性等

控制CAPM模型、FF三因子和Carhart四因子模型中相关因子进行对比分析，较为全面。

3.如果有的话，潜在改进的主要地方是什么？[如果这些关键要求和建议能够被适当处理，请重点关注能使文章发表的关键要求和建议。如果你看到不可逾越的障碍，请清楚地描述你的担忧。如果能为编辑和作者提供具体有建设性的意见最好不过了，并在可能的情况下，提出可行的建议。同样，应避免含糊不清和/或含糊不清的批评。]

供应商与客户之间可能存在交叉关系，两者的交乘项是否可以放入模型中。

4.如果有的话，潜在改进的微小地方是什么？[再次，请具体说明。]

无

5.有没有机会做一项新的研究？

论文对供应链的研究局限在网络的入度（供应商数量）与出度（客户数量）上，对供应商与客户未进行进一步区别，后续可以尝试在供应商与客户的重要性上对公司的影响进行相关研究。