Study on the Efficiency Estimation for Chinese Construction Industry through Three-Stage DEA Model

Dynamic Transition and Convergence Trend of the Innovation Efficiency among Companies Listed on the Growth Enterprise Market in the Yangtze River Economic Belt—Empirical Analysis Based on DEA—Malmquist Model

“…Therefore, the DEA method is increasingly widely applied and continuously expanding. Li et al (2010) [16] and other related studies constructed a resource allocation model based on the DEA method; Kádárová et al (2015) [17] integrated the DEA and balanced scorecard methods to establish a comprehensive performance and efficiency management system for industrial enterprises and their processes; Genwen et al (2017) [18] further conducted a comprehensive study on the three-stage DEA model; Na et al (2019) [19], Tachega et al (2021) [20], and other related studies used static DEA methods to calculate the innovation efficiency of China's environmental protection industry and the energy efficiency of African oil-producing economies, respectively; Wenjinget al (2015) [21] and Shijian et al ( 2018) [22] used the two-stage DEA method to compute innovation efficiency using interprovincial and industrial industry data, respectively; Pishgar-Komleh et al (2020) [23] and other related studies further calculated the efficiency of the poor output of Polish winter wheat using the life cycle assessment + DEA framework; Huangbao (2014) [24] adopted the DEA Malmquist method to evaluate the innovation efficiency of Chinese high-technology industries. Regarding research on the convergence trend of innovation efficiency, most scholars conducted comprehensive studies on their convergence trends of innovation efficiency using macro inter-provincial and industry data from the regional [25][26][27][28][29] and industrial [30][31][32][33] levels, which provided a solid theoretical foundation for this study.…”