Exploring the effect of digital CSR communication on firm performance: A deep learning approach

被引:7
作者
Han, Shuihua [1 ]
Liu, Zhenyuan [1 ]
Deng, Ziyue [1 ]
Gupta, Shivam [2 ]
Mikalef, Patrick [3 ,4 ]
机构
[1] Xiamen Univ, Sch Management, Dept Management Sci, Xiamen, Peoples R China
[2] NEOMA Business Sch, Dept Informat Syst Supply Chain Management & Decis, Reims, France
[3] Norwegian Univ Sci & Technol, Fac Informat Technol & Elect Engn, Dept Comp Sci, Trondheim, Norway
[4] SINTEF Digital, Dept Technol Management, Trondheim, Norway
关键词
Deep learning; Natural language processing; Digital CSR communication; Stakeholder engagement; Firm performance; Agenda -setting theory; CORPORATE SOCIAL-RESPONSIBILITY; MEDIA; IMPACT; ONLINE; NETWORKS; CHINA;
D O I
10.1016/j.dss.2023.114047
中图分类号
TP18 [人工智能理论];
学科分类号
081104 ; 0812 ; 0835 ; 1405 ;
摘要
This study proposes a novel research framework to examine the effect of digital CSR communications on financial performance while incorporating deep learning techniques to identify firms' CSR communications on social media. Particularly, this research aims to quantify firms' efforts in digital CSR communications by employing cutting-edge deep learning-based natural language processing (NLP) models to detect CSR-related tweets on social media. Utilizing a unique dataset of 65 Chinese public companies in the manufacturing sector between 2015 and 2019, we detected 64,769 long-form tweets posted on WeChat to acquire both digital CSR communications and stakeholder engagement data. Combining financial and secondary data of sample firms, this research reveals the positive but time-lagged influence of digital CSR communications on firms' financial performance, primarily through the lens of agenda-setting theory. We also find that stakeholder engagement plays an essential bridging role in the relationship above, while CSR ratings surprisingly hamper such a positive effect.
引用
收藏
页数:13
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