Research on the influence of chain shareholders on auditor behavior-An empirical study based on Logistic and Ols regression analysis
- DOI
- 10.2991/978-94-6463-304-7_17How to use a DOI?
- Keywords
- chain shareholders; audit behavior; audit expenses; audit opinions; real earnings management; regression analysis; Stata16
- Abstract
Based on the real situation of China's capital market, this paper takes non-financial listed companies in Shanghai and Shenzhen from 2007 to 2021 as samples to explore the impact of chain shareholders from the perspective of auditor behavior. Using Stata16 software for data processing, Logistic and Ols regression results show that chain shareholders achieve portfolio value maximization through the "collusion effect", which would intensify the manipulation of real earnings management of enterprises, Risk premium would lead auditors to demand higher fees, andthey are motivated to issue non-standard audit opinion reports in order to maintain their own reputation and reduce potential litigation risk. This study has not only enriched the research literature in the field of audit behavior influencing factors and economic consequences of chain shareholders, but also provided a new perspective for auditors to pay attention to the potential audit risks of chain shareholders in the process of implementing audit procedures.
- Copyright
- © 2023 The Author(s)
- Open Access
- Open Access This chapter is licensed under the terms of the Creative Commons Attribution-NonCommercial 4.0 International License (http://creativecommons.org/licenses/by-nc/4.0/), which permits any noncommercial use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons license and indicate if changes were made.
Cite this article
TY - CONF AU - Xiuying He AU - Xinxin Li PY - 2023 DA - 2023/12/04 TI - Research on the influence of chain shareholders on auditor behavior-An empirical study based on Logistic and Ols regression analysis BT - Proceedings of the 3rd International Conference on Digital Economy and Computer Application (DECA 2023) PB - Atlantis Press SP - 146 EP - 152 SN - 2589-4900 UR - https://doi.org/10.2991/978-94-6463-304-7_17 DO - 10.2991/978-94-6463-304-7_17 ID - He2023 ER -