Decoding CSR report: How report readability and tone influence M&A target and acquirer likelihood

IF 7.4 2区经济学 Q1 BUSINESS, FINANCE

Finance Research Letters Pub Date : 2025-07-08 DOI:10.1016/j.frl.2025.107917

Yufei Li

引用次数: 0

Abstract

This study examines the influence of CSR textual attributes, particularly complexity and tone, on M&A outcomes for firms listed on the Shanghai and Shenzhen Stock Exchanges between 2010 and 2023. Using deep learning-based NLP techniques implemented via BERT to measure CSR textual factors and addressing sample selection bias through Heckman’s two-step models, the findings reveal that higher CSR complexity significantly reduces the likelihood of firms becoming M&A targets or acquirers. While CSR tone has a limited effect on M&A likelihood, positive net sentiment enhances investor reactions to M&A announcements, particularly for target firms. These results underscore the critical role of CSR disclosure quality in shaping strategic corporate decisions and market perceptions.

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解读企业社会责任报告：报告可读性和语气如何影响并购目标和收购可能性

本研究考察了2010年至2023年间在上海和深圳证券交易所上市的公司的企业社会责任文本属性，特别是复杂性和语气对并购结果的影响。利用BERT实现的基于深度学习的NLP技术测量CSR文本因素，并通过Heckman的两步模型解决样本选择偏差，研究结果表明，较高的CSR复杂性显著降低了企业成为并购目标或收购者的可能性。虽然企业社会责任基调对并购可能性的影响有限，但积极的净情绪增强了投资者对并购公告的反应，尤其是对目标公司。这些结果强调了企业社会责任披露质量在塑造企业战略决策和市场认知方面的关键作用。

本文章由计算机程序翻译，如有差异，请以英文原文为准。

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来源期刊

Finance Research Letters BUSINESS, FINANCE-

CiteScore

11.10

自引率

14.40%

发文量

863

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