Research on Environmental Accounting Information Disclosure of Listed Companies in Gansu Province: Based on Multiple Linear Regression Model

Yuyiqi Shen, Qianyun Hou

2022

Abstract

In this paper, the environmental accounting information disclosure status of A-share list companies on Shanghai Stock Exchange and Shenzhen Stock Exchange in Gansu Province from 2017 to 2019 was analyzed. Then a multiple linear regression model for empirical research was established. The study results show that the enterprise size, operating capacity, social responsibility report preparation and media attention have notable influence on the environmental information disclosure of listed companies. Therefore, to facilitate environmental information disclosure of listed companies, it is essential to expand their size, optimize their operating capacity, prepare social responsibility reports, and enhance social supervision.

Paper Citation

in Harvard Style

Shen Y. and Hou Q. (2022). Research on Environmental Accounting Information Disclosure of Listed Companies in Gansu Province: Based on Multiple Linear Regression Model. In Proceedings of the 4th International Conference on Economic Management and Model Engineering - Volume 1: ICEMME; ISBN 978-989-758-636-1, SciTePress, pages 355-360. DOI: 10.5220/0012033000003620

in Bibtex Style

@conference{icemme22,
author={Yuyiqi Shen and Qianyun Hou},
title={Research on Environmental Accounting Information Disclosure of Listed Companies in Gansu Province: Based on Multiple Linear Regression Model},
booktitle={Proceedings of the 4th International Conference on Economic Management and Model Engineering - Volume 1: ICEMME},
year={2022},
pages={355-360},
publisher={SciTePress},
organization={INSTICC},
doi={10.5220/0012033000003620},
isbn={978-989-758-636-1},
}

in EndNote Style

TY - CONF

JO - Proceedings of the 4th International Conference on Economic Management and Model Engineering - Volume 1: ICEMME
TI - Research on Environmental Accounting Information Disclosure of Listed Companies in Gansu Province: Based on Multiple Linear Regression Model
SN - 978-989-758-636-1
AU - Shen Y.
AU - Hou Q.
PY - 2022
SP - 355
EP - 360
DO - 10.5220/0012033000003620
PB - SciTePress