Proceedings of the 2022 International Conference on Bigdata Blockchain and Economy Management (ICBBEM 2022)

An Empirical Experiment of Factors Influencing the Quality of Carbon Accounting Disclosure in the Context of Big Data

Empirical Evidence from 21 A-Share Listed Companies in China

Authors
Xiaowen Gan1, *
1School of Economics and Management, Harbin Institute of Technology, Harbin, China
*Corresponding author. Email: gxw2646726061@163.com
Corresponding Author
Xiaowen Gan
Available Online 20 December 2022.
DOI
10.2991/978-94-6463-030-5_101How to use a DOI?
Keywords
Carbon accounting disclosure; chemical industry; econometrics; empirical analysis
Abstract

In the context of global carbon neutrality, the development of information technology has strengthened the accuracy and efficiency of accounting information disclosure, and carbon accounting information disclosure has become an important initiative for global enterprises in the development of the digital economy. Major enterprises actively display carbon accounting information disclosure in their accounting information systems to the public and other stakeholders, which can more effectively reflect the social responsibility undertaken by enterprises. This paper selects the financial data of 21 chemical companies listed on Chinese A-shares from 2017 to 2020 as the research sample, constructs a multiple regression analysis model in econometrics, and conducts an empirical study on the factors influencing the quality of carbon accounting information disclosure in the chemical industry, which is a highly polluting industry, and finds that: (1) the profitability of chemical companies, the concentration of company equity and the quality of carbon information disclosure are positively correlated. (2) The degree of indebtedness was negatively correlated with the level of carbon information disclosure. (3) There was no exact correlation between development capacity and the quality of carbon information disclosure. On this basis, the industry is called upon to disclose carbon accounting information more effectively and fulfil its social responsibility. For that, major chemical companies should strengthen the development and transformation of enterprise information technology and enhance the accuracy of carbon accounting information disclosure in the context of information technology.

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.

Download article (PDF)

Volume Title
Proceedings of the 2022 International Conference on Bigdata Blockchain and Economy Management (ICBBEM 2022)
Series
Atlantis Highlights in Intelligent Systems
Publication Date
20 December 2022
ISBN
10.2991/978-94-6463-030-5_101
ISSN
2589-4919
DOI
10.2991/978-94-6463-030-5_101How to use a DOI?
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  - Xiaowen Gan
PY  - 2022
DA  - 2022/12/20
TI  - An Empirical Experiment of Factors Influencing the Quality of Carbon Accounting Disclosure in the Context of Big Data
BT  - Proceedings of the 2022 International Conference on Bigdata Blockchain and Economy Management (ICBBEM 2022)
PB  - Atlantis Press
SP  - 1027
EP  - 1037
SN  - 2589-4919
UR  - https://doi.org/10.2991/978-94-6463-030-5_101
DO  - 10.2991/978-94-6463-030-5_101
ID  - Gan2022
ER  -