Learning by helping: Evidence from Chinese brokerages' community CSR

• 成果类型: Article
• 署名作者: Li, Jingyuan; Kim, Yong H.; Uribe, Jose
• 署名单位: The Chinese University of Hong Kong, Shenzhen; Texas A&M University System; Texas A&M University College Station; Mays Business School; Indiana University System; IU Kelley School of Business; Indiana University Bloomington
• 刊物名称: STRATEGIC MANAGEMENT JOURNAL
• ISSN/ISSBN: 0143-2095
• DOI: 10.1002/smj.3719
• 发表日期: 2025
• 页码: 2166-2198
• 关键词: CSR; FORECAST ACCURACY; learning; local knowledge; poverty alleviation

摘要

Research SummaryWe propose that firms engaging in community corporate social responsibility (CSR) can acquire valuable local knowledge that improves their core operations. We test our proposition leveraging a unique context-the Securities Association of China's pairing assistance scheme under the country's targeted poverty alleviation program. Under this scheme, financial brokerage houses conducted community CSR in quasi-randomly matched impoverished regions. We find support for the local knowledge learning effect of CSR by showing how community CSR participation enabled brokerages to more accurately forecast the earnings of companies in those regions. We complement our quantitative analyses with qualitative data from in-depth interviews, surveys of brokerage employees, and archival documents. The evidence indicates that forecast accuracy improved when CSR engagements enhanced learning about local companies' capabilities and business environment.Managerial SummaryMany firms engage in community CSR, leveraging their expertise to address issues beyond the capacity of governments and public organizations. Firms can benefit from these CSR efforts, often experiencing performance improvements driven by enhanced corporate reputation and stronger stakeholder relationships. Our research highlights an additional, understudied benefit: CSR can serve as a channel for local knowledge acquisition, whereby firms learn by helping. In a unique context where financial brokerage houses participated in community CSR through quasi-randomized regional matching, we find that community CSR enabled brokerages to more accurately forecast the earnings of companies in those regions. This improvement occurred because brokerages, through community CSR, gained a deeper understanding of local companies' capabilities and business environment.