Quality of environmental information disclosure and enterprise characteristics: Based on heavily polluted industries of A-share in the Shanghai Stock Exchange

Abstract

Purpose

Based on several important environmental protection and information disclosure policies that have been issued in China, the purpose of this paper is to test the relationship between characteristics and the environmental information disclosure quality of sample companies.

Design/methodology/approach

The OLS regression analysis is selected for this research which takes China’s heavy pollution companies listed on the Shanghai Stock Exchange from 2015 to 2016 as samples.

Findings

The quality of these environmental information disclosures needs to be strengthened, and while the quality of the disclosures among the companies examined improved significantly in 2016 compared with 2015, there are still high variations in quality from industry to industry. In addition, the scale of company is most closely correlated to the quality of environmental information disclosure and the economic situation of the enterprises is the next. Other factors affecting the disclosure quality include in order the degree of local economic development the scale of the state-owned shares and the independent directors. Listed years and equity restriction show a positive correlation but not significant in statistics.

Originality/value

The research will assist administrative organizations to allocate governance sources effectively, plan governance investment as a whole, and improve the overall level of the disclosure of environmental information while strengthening the governance efficiency and effectiveness, according to the correlation and degree between the company characteristics and environmental information disclosure quality.

Citation

Wang, J. and Zhang, B. (2019), "Quality of environmental information disclosure and enterprise characteristics: Based on heavily polluted industries of A-share in the Shanghai Stock Exchange", Management of Environmental Quality, Vol. 30 No. 5, pp. 963-979. https://doi.org/10.1108/MEQ-11-2018-0194