Evolution of spatial–temporal characteristics and financial development as an influencing factor of green ecology

Peng, Benhong; Zhang, Xingchao; Elahi, Ehsan; Wan, Anxia

doi:10.1007/s10668-021-01469-y

Cited by 24 publications

(21 citation statements)

References 41 publications

(36 reference statements)

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“…Economic growth is usually measured with the traditional GDP which is defined as an increase in per head level of the production of goods and services (Ahmed et al, 2021); during this production process, different resources such as mineral, water, and other such resources are extracted from the environment which deteriorate the environmental quality (EQ) (Ncube et al, 2021). Consequently, deterioration in EQ negatively impacts production systems (Elahi et al, 2017;Elahi et al, 2019c;Zheng et al, 2020;Peng et al, 2022). This deterioration in EQ is a major warning to an economy's sustainable development (Khan et al, 2021), as it falls out with serious economic consequences like poverty, inequality, food-shortage, etc.…”

Section: Introductionmentioning

confidence: 99%

Financial Development, Trade Openness, and Foreign Direct Investment: A Battle Between the Measures of Environmental Sustainability

Huo

Ullah

Zulfiqar

et al. 2022

Front. Environ. Sci.

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Deterioration in the environmental quality is a major threat to the sustainable development of an economy as it results in serious economic problems and the researchers are conscious about the environment sustainability. They have identified several factors including financial development, inflow of foreign aid, and openness of trade to promote environmental sustainability. Unfortunately, their findings remain inconclusive as they have imperfectly measured environmental sustainability. This study, thus, aims to contribute to the ongoing debate of environmental sustainability by testing the role of financial development, trade openness, and foreign direct investment (FDI) in promoting environmental sustainability by using adjusted net savings as a measure of environmental sustainability. To do this, the study collects data from 1996 to 2019. The study uses financial development, trade openness, and FDI as predictors and environmental sustainability as an outcome variable. The study applies Auto Regressive Distributive Lag (ARDL) methodology to analyze the impact. The findings show positive contributions of financial development, trade openness, and foreign direct investment in promoting environment sustainability. We suggest encouraging trade through lower-taxation programs and increasing competition in the financial markets through privatization and domestic and international liberalization to stimulate environmental sustainability. We also recommend imposing high taxes and penalties on such activities that damage the quality of the environment.

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Section: Introductionmentioning

confidence: 99%

Financial Development, Trade Openness, and Foreign Direct Investment: A Battle Between the Measures of Environmental Sustainability

Huo

Ullah

Zulfiqar

et al. 2022

Front. Environ. Sci.

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“…The projection pursuit model is a multi-dimensional data processing method that projects high-dimensional data to one-dimensional space and retains the most data information by finding the optimal projection direction [ 57 ]. Compared with traditional evaluation methods, such as the analytic hierarchy process and the Delphi method, the projection pursuit model has the advantage of avoiding artificial subjective factors and processing nonlinear distributed data [ 58 , 59 , 60 ]. Here, projection pursuit model based on a genetic algorithm is used to evaluate the RECC and SCDI.…”

Section: Methodsmentioning

confidence: 99%

Resources and Environment Carrying Capacity, Social Development and Their Decoupling Relationship: A Case Study of Hubei Province, China

Wei

Wang

et al. 2021

IJERPH

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With the rapid urbanization in recent decades, resource shortage and environmental damage have hindered the process of urban sustainable development (SD). As a yardstick of sustainable development, the evaluation of resources and environment carrying capacity (RECC) and its decoupling relationship with social comprehensive development index (SCDI) are of great significance. In this paper, RECC and SCDI are taken as research objects to establish resource and environment system evaluation index system and social comprehensive development level evaluation index system, respectively. Then, the RECC and SCDI of 17 cities in Hubei province during 2009–2018 are calculated by the projection pursuit model based on genetic algorithm, and their spatial-temporal variance characteristics are analyzed. On this basis, the RECC-SCDI Tapio decoupling model is constructed to explore the decoupling relationship between RECC and SCDI. The result shows that: (1) The RECC of Hubei shows a V-shaped development trend during 2009–2018. The SCDI of Hubei rose steadily during 2009–2018. (2) RECC in western and eastern Hubei Province is higher than that in central Hubei Province. SCDI in eastern and central Hubei Province is higher than that in the west. (3) 11 of the 17 cities in Hubei Province have got rid of excessive dependence on resources environment for social development. The study could contribute to scientific and effective policies be formulated by government to promote urban sustainable development.

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“…The regression coefficient of AI is still positive and significant, which is consistent with the benchmark regression results, indicating that the research hypothesis H1 still holds. Considering that few variables can be selected to replace the level of corporate governance and the level of artificial intelligence application, to further test the robustness, this paper chooses to replace the research sample data range and perform regression analysis on the variable of artificial intelligence application level with a lag of one period (Peng et al, 2021b;Wang et al, 2021;Zhao et al, 2021;Zhong et al, 2021).…”

Section: Robustness Checkmentioning

confidence: 99%

Can Application of Artificial Intelligence in Enterprises Promote the Corporate Governance?

Cui

Razzaq

2022

Front. Environ. Sci.

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The impact of artificial intelligence (AI) on the economy and industry has gradually extended from the macroeconomic to the microeconomic level. Artificial intelligence technology has brought great innovation and impact to the company’s operation and management and has a strong role in promoting the level of corporate governance. Based on an in-depth analysis of the theoretical mechanism of artificial intelligence affecting corporate governance, and based on the balanced panel data of Chinese A-share listed companies from 2011 to 2020, this paper empirically analyzes the mechanism and intermediary effect of artificial intelligence affecting corporate governance. The study found that AI applications can significantly improve corporate governance levels, and a higher level of artificial intelligence application can produce a higher level of corporate governance. From the perspective of the impact path, artificial intelligence technology can significantly improve the degree of information symmetry required for corporate governance, thereby providing favorable technical conditions and decision support for improving the level of corporate governance. Artificial intelligence technology has a positive and effective impact on corporate governance through the information symmetry effect.

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Evolution of spatial–temporal characteristics and financial development as an influencing factor of green ecology

Cited by 24 publications

References 41 publications

Financial Development, Trade Openness, and Foreign Direct Investment: A Battle Between the Measures of Environmental Sustainability

Financial Development, Trade Openness, and Foreign Direct Investment: A Battle Between the Measures of Environmental Sustainability

Resources and Environment Carrying Capacity, Social Development and Their Decoupling Relationship: A Case Study of Hubei Province, China

Can Application of Artificial Intelligence in Enterprises Promote the Corporate Governance?

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