| Title | Measuring industrial operational efficiency and factor analysis: A dynamic series-parallel recycling DEA model |
|---|---|
| ID_Doc | 18764 |
| Authors | Zhang, LA; Du, XY; Chiu, YH; Pang, QH; Wang, X; Yu, QW |
| Title | Measuring industrial operational efficiency and factor analysis: A dynamic series-parallel recycling DEA model |
| Year | 2022 |
| Published | |
| Abstract | Countries are now struggling to improve their recycling efficiency of an industrial operational system to achieve the Sustainable Development Goals, yet scant studies have viewed the series-parallel recycling structure of the system based on data envelopment analysis (DEA). This research divides the system into industrial production and industrial waste treatment (IWT) processes connected serially, while the IWT process is further separated into treatment sub-units for wastewater, waste gas, and solid wastes connected in parallel. We propose a dynamic series-parallel recycling DEA model within a directional distance function to measure efficiency and discuss the efficiency relationship among the system, processes, and sub-units. By using the spatial Durbin model, we explore factors that mainly influence the efficiency for the 30 provinces during 2011-2019. The results show the following. (1) The medium performance of the industrial operational system with an average overall recycling efficiency of 0.69 is mainly caused by the poor perfor-mance of the IWT process with a score of 0.61. (2) The highest performance is observed in the wastewater treatment sub-unit, followed by waste gas treatment and solid waste treatment sub-units. (3) Market-based environmental regu-lations significantly promote local IWT efficiency, while command-and-control environmental regulations have no sig-nificant effect on local IWT efficiency. But they all have significant spatial spillovers. The voluntary environmental regulations have no significant impact. |
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