The macroeconomic impact of COVID-19 on occupations
In: Portuguese economic journal, Volume 23, Issue 3, p. 439-458
ISSN: 1617-9838
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In: Portuguese economic journal, Volume 23, Issue 3, p. 439-458
ISSN: 1617-9838
In: Sage open, Volume 14, Issue 3
ISSN: 2158-2440
Green innovation has become one of the most effective ways to deal with ecological problems such as environmental pollution, global warming and resource depletion. A comprehensive and accurate understanding of regional differences and influencing factors of green innovation level is of great significance further to promote green innovation and to realize the harmonious coexistence between man and nature. This paper analyzes the regional differences of green innovation level in China from 2011 to 2020 by using GDI, Moran's I, Getis-Ord Gi*, and other indices at provincial, urban agglomeration and prefecture-level city scales, and identifies with geographical detectors, the leading factors influencing the spatial differentiation of green innovation level as well as their interactions. The results show that from 2011 to 2020, the overall level of green innovation in China gradually improves and the regional differences gradually decrease, and that the smaller the scale, the greater the regional differences. Green innovation level increases with the increase of urban agglomeration level and the expansion of city scale. There are differences in the spatial structure features of green innovation level at different scales, the degree of spatial agglomeration decreases as the scale reduces. At provincial and prefecture-level city scale, areas of higher green innovation level are mainly located at the east side of Hu Line, while at the urban agglomeration scale, they are mainly national urban agglomerations such as Yangtze River Delta and Pearl River Delta, and regional urban agglomerations such as Ha Chang and Shandong Peninsula Urban Agglomeration. The leading factors influencing the spatial differentiation of green innovation level and their interactions vary with the different scales. At provincial and prefecture-level city scales, the core factors are venture capital level, quality of faculty and education level. On the scale of urban agglomeration, the core factors are venture capital level and economic level. JEL Classification: M10, O32, R12.
In: Corporate social responsibility and environmental management, Volume 31, Issue 1, p. 274-291
ISSN: 1535-3966
AbstractAlthough previous studies have explored the effect of corporate environmental performance on the content of environmental disclosure, little research has investigated its impact on the textual characteristics of environmental disclosure, particularly readability. This study constructs three measures of corporate environmental disclosure (CED) readability and examines the effect of corporate environmental performance on it. Using panel data from Chinese listed firms in heavy pollution industries during the period from 2008 to 2019, we find a robust positive association between corporate environmental performance and CED readability. Furthermore, we find that this association is stronger in firms with worse earning performance, stricter regional environmental regulation, or more media attention. Our analyses also reveal a positive association between CED readability and stock price crash risk. Overall, our study contributes to the research on corporate environmental performance and environmental disclosure readability and has important implications for optimizing the regulations of environmental disclosure. Our study contributes to the literature on corporate environmental performance and environmental disclosure and also provides important theoretical and practical implications for improving corporate environmental disclosure regulation.
In: China economic review, Volume 54, p. 350-366
ISSN: 1043-951X
In: Ecotoxicology and environmental safety: EES ; official journal of the International Society of Ecotoxicology and Environmental safety, Volume 255, p. 114776
ISSN: 1090-2414
In: HELIYON-D-24-31422
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