供应链
盈利能力指数
财务
业务
职位(财务)
银行信贷
面板数据
贸易信贷
首都(建筑)
供应链管理
经济
信用记录
产业组织
零售银行业务
信用增级
实证研究
资本市场
信用卡利息
金融市场
融资渠道
市场份额
信贷紧缩
作者
Anqi Wu,Qi Wu,Sridhar Seshadri
出处
期刊:Management Science
[Institute for Operations Research and the Management Sciences]
日期:2025-10-28
标识
DOI:10.1287/mnsc.2024.08465
摘要
Bank credit access allows firms to borrow funds from banks and other financial institutions. Although theories have been developed on how bank financing affects firms’ operational decisions, empirical investigations in operations management (OM) literature remain limited. This study examines firms’ inventory management strategies in response to the enhanced credit lines from the adoption of interstate bank branching laws, which introduced staggered access to bank credit for operational firms. By merging multiple datasets with credit line information from 10-K SEC filings, we constructed a panel data set covering 1990–2005. Utilizing a difference-in-differences (DID) approach, we find that improved bank credit access leads to a 6% faster inventory turnover, rather than an increase in inventory investment. This outcome appears to stem from short-term increases in capacity investments leveraging their enhanced bank credit and increased use of trade credit, alongside long-term improvements in infrastructure and capital intensity. While these developments are more pronounced for small firms in concentrated markets, their advantage translates into increased competition, negatively impacting the market position and profitability of larger firms. Additionally, in a broader supply chain context, focal firms experience faster inventory turnover when their major customers access more bank credit. The effect is especially prominent for large suppliers in competitive markets, driven by increased sales volumes. This research enhances understanding of the extensive impact of bank credit on operational management and offers insights for policymakers about the diverse effects of bank regulations across different market players and sectors. This paper was accepted by J. George Shanthikumar, data science. Supplemental Material: The online appendix and data files are available at https://doi.org/10.1287/mnsc.2024.08465 .
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