Abstract
Scholars hold differing views on the topic of mineral resource efficiency. This paper explores the application of big data to enhance mineral resource efficiency within the context of 500 Chinese companies listed on the Shanghai Stock Exchange between 2010 and 2019. The research methodology employs panel data, consisting of 5000 observations, and employs the Autoregressive Distributed Lag approach for estimation. The study reveals that the incorporation of big data has a positive, enduring impact on the mineral resource efficiency of the selected Chinese firms. Specifically, a 1% increase in big data utilization corresponds to a 0.43% enhancement in mineral resource efficiency. Furthermore, stock prices, environmental investments, and transparency indices play pivotal roles in advancing the objective of improving mineral resource consumption efficiency among these Chinese enterprises. On the contrary, the tax burden has an adverse influence on their resource consumption efficiency. To promote mineral resource efficiency through big data technology, practical policies are recommended. These include fostering sustainable ICT education, developing IT-driven resource management solutions, and supporting the advancement of environmentally-friendly technologies within the mining industry.
Talk to us
Join us for a 30 min session where you can share your feedback and ask us any queries you have