Balancing sustainability and innovation: The role of artificial intelligence in shaping mining practices for sustainable mining development

被引:3
|
作者
Liang, Guangqi [1 ,4 ]
Liang, Yi [2 ,3 ]
Niu, Dongxiao [1 ]
Shaheen, Musarat [5 ]
机构
[1] North China Elect Power Univ, Sch Econ & Management, Beijing 102206, Peoples R China
[2] Hebei GEO Univ, Sch Management, Shijiazhuang 050031, Peoples R China
[3] Hebei GEO Univ, Strategy & Management Base Mineral Resources Hebei, Shijiazhuang 050031, Peoples R China
[4] GIIT Investment Dev CO LTD, Nanning 530000, Peoples R China
[5] HEC Montreal, Dept Management Sci, Montreal, PQ, Canada
基金
国家教育部科学基金资助;
关键词
Mineral policy; ARDL; Artificial intelligence; Mining sustainability; NARDL; Mining development; CORPORATE SOCIAL-RESPONSIBILITY; CLIMATE-CHANGE; INDUSTRY;
D O I
10.1016/j.resourpol.2024.104793
中图分类号
X [环境科学、安全科学];
学科分类号
08 ; 0830 ;
摘要
Attaining sustainable development involves a mounting role in modern innovations especially in the mining industry. It is anticipated that the world's need for minerals will increase extensively. The research is of paramount significance as it scrutinizes how artificial intelligence can act as a central force in balancing sustainability and innovation within the mining industry for China over the period 1960 to 2022. In this regard, it paves the way for sustainable mining development and the resolution of pressing environmental and social issues. The finding of (ADF) Augmented Dickey-Fuller & Phillips Perron (PP) unit root tests advocate that variables follows order of integration 1 & (ARDL) bound test of Autoregressive Distributed Lag and Nonlinear Autoregressive Distributed Lag (NARDL) approve a long-term association between concerned variables. The ARDL and Fully Modified Ordinary Least Squares (FMOLS) results depict that the coefficient of artificial intelligence has a positive and substantial impact on mining sustainability in both the short-run (SR) and long-run (LR). Additionally, the outcomes of NARDL reveal that there lies an asymmetric LR relationship between artificial intelligence and mining sustainability. Additionally, the impact of economic growth, climate change, and political stability on mining sustainability has been examined. Based on the findings, it is proposed that incentives should be given to mining companies for investment and adoption of artificial intelligence-related activities and implement such policies that enhance transparency and accountability in the mining sector to attain sustainability, efficiency, and reduction in the social and environmental costs of various mining activities.
引用
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页数:12
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