A two-stage DEA evaluation of Chinese mining industry technological innovation efficiency and eco-efficiency

Improving technological innovation efficiency and eco-efficiency is the key to achieving a high-quality, sustainable mining industry in China. In order to explore the internal process of technological innovation to promote economic and environmental benefits and to clarify the optimization path to improve the overall efficiency of the mining industry. A two-stage DEA model is used to construct indicators to measure Chinese 30 provinces mining technological innovation efficiency (MTIE), mining eco-efficiency (MEE), and mining comprehensive efficiency (MCE). Because of the lag in innovation, the study period was divided into nine periods from 2008 to 2018 into three-year time slices, and the dynamic evolution of time and space was analyzed. It was found that: (i) MCE and MTIE maintained the same changing trends, with the MCE being generally higher in areas with higher levels of mining economic development; (ii) the MTIE and MEE in the western area were higher than in the other regions, of which Qinghai was the only province that had efficiencies of more than 1 in both stages; (iii) most provinces belonged to type II regions with high MEE-low MTIE or type III regions with low MEE-low MTIE. The scientific achievements output in the first stage was generally insufficient, and the inputs and outputs in the second stage were redundant. There are three paths to optimize efficiency: unilateral optimization, gradual optimization, and jumping optimization. Finally, based on the above findings, policy recommendations are given from three aspects; reducing excess capacity, increasing investment, and building a platform, all of which can provide optimized plans and references for realizing the high-quality development of the Chinese mining industry. • A two-stage DEA model for measuring Chinese MTIE, MEE, and MCE from 2008 to 2018. • The MTIE and MEE in the western area were higher than in the other regions. • Most provinces belonged to type II or type III. • Three optimization paths are proposed to improve MCE.