IDEAS home Printed from https://ideas.repec.org/p/arx/papers/2509.23424.html
   My bibliography  Save this paper

What influenced the lack of diversity in CSR after the company's losses: evidence from topic modeling

Author

Listed:
  • Ruiying Liu
  • Yuchi Li
  • Zhanli Li

Abstract

The diversity of corporate social responsibility (CSR) disclosure is a crucial dimension of corporate transparency, reflecting the breadth and resilience of a firm's social responsibility. Using CSR reports of Chinese A-share firms from 2006 to 2023, this paper applies Latent Dirichlet Allocation (LDA) to extract topics and quantifies disclosure diversity using the Gini-Simpson index and Shannon entropy. Regression results show that corporate losses significantly compress CSR topic diversity, consistent with the slack resources hypothesis. Both external and internal governance mechanisms mitigate this effect: higher media attention, stronger executive compensation incentives, and greater supervisory board shareholding attenuate the loss-diversity penalty. Results are robust to instrumental variables estimation, propensity score matching, and placebo tests. Heterogeneity analyses indicate weaker effects in firms with third-party assurance, those disclosing work safety content, large firms, and those in less competitive industries. Our study highlights the structural impact of financial distress on non-financial disclosure and provides practical implications for optimizing CSR communication, refining evaluation frameworks for rating agencies, and designing diversified disclosure standards.

Suggested Citation

  • Ruiying Liu & Yuchi Li & Zhanli Li, 2025. "What influenced the lack of diversity in CSR after the company's losses: evidence from topic modeling," Papers 2509.23424, arXiv.org.
  • Handle: RePEc:arx:papers:2509.23424
    as

    Download full text from publisher

    File URL: http://arxiv.org/pdf/2509.23424
    File Function: Latest version
    Download Restriction: no
    ---><---

    More about this item

    Statistics

    Access and download statistics

    Corrections

    All material on this site has been provided by the respective publishers and authors. You can help correct errors and omissions. When requesting a correction, please mention this item's handle: RePEc:arx:papers:2509.23424. See general information about how to correct material in RePEc.

    If you have authored this item and are not yet registered with RePEc, we encourage you to do it here. This allows to link your profile to this item. It also allows you to accept potential citations to this item that we are uncertain about.

    We have no bibliographic references for this item. You can help adding them by using this form .

    If you know of missing items citing this one, you can help us creating those links by adding the relevant references in the same way as above, for each refering item. If you are a registered author of this item, you may also want to check the "citations" tab in your RePEc Author Service profile, as there may be some citations waiting for confirmation.

    For technical questions regarding this item, or to correct its authors, title, abstract, bibliographic or download information, contact: arXiv administrators (email available below). General contact details of provider: http://arxiv.org/ .

    Please note that corrections may take a couple of weeks to filter through the various RePEc services.

    IDEAS is a RePEc service. RePEc uses bibliographic data supplied by the respective publishers.