Network Technology, Whole-Process Performance, and Variable-Specific Decomposition Analysis: Solutions for Energy-Economy-Environment Nexus

Abstract

The sustainability of the industrial sector is often evaluated in a one-stage process. On the other hand, industrial activities are characterized by complex and multistage natures, which creates challenges for industrial performance assessment. Properly measuring industrial sustainability and understanding the driving factors (e.g., energy use or labor) of whole-process industrial operation is important for sustainable industrial sector management. To address these difficulties, we propose two new frameworks: the network variable-specific bounded-adjusted measure and network variable-specific Luenberger productivity indicators decomposition. These both take into account the whole-process context and network nature of industrial production, and unpack and quantify the contributions of specific components of the industrial process affecting sustainability. In order to capture both the status and evolution of sustainability performance, two indices are constructed. These are then decomposed to investigate the contribution of particular components to overall sustainability. The proposed approach is applied to analyze the sustainability of the industrial sector in 30 of China's provincial administrative regions between 2006 and 2015. The static sustainability inefficiency indicator results indicate that in the production and treatment process, use of the most efficient existing technology would allow a further 48.0% and 23.6% of pollutant emissions to be reduced and treated, respectively. In the production process, the most efficient technology could produce a 10.7% improvement in energy conservation. The average annual dynamic environmental performance was 2.45% and 2.07% for the production and treatment processes, respectively. There is significant heterogeneity between regions and for different variables.