Energy efficiency and congestion effects analysis for the production system with comprehensive input-output indicators

Many studies have conducted the energy efficiency measurement through data envelopment analysis (DEA) for energy conservation and emission reduction. However, for the production system with undesirable inputs and outputs, little literature considers the congestion effect, which will lead to the waste of resources and the aggravation of pollutants emission. To fill in the literature gap, this paper proposes an environmental DEA model with undesirable inputs to measure energy efficiency considering the congestion effects. Furthermore, for the improvement of energy efficiency, we measure the congestion effects, which are divided into the desirable congestion and undesirable congestion according to the undesirable inputs and desirable inputs, respectively. Based on the DEA model proposed, we can not only identify the type of congestion effects but also calculate the specific congested amount. Moreover, we decompose the improvement spaces of inputs and undesirable outputs into technically inefficient components and congested components. Finally, we apply the methods proposed in this paper to the Chinese industrial sector. Interestingly, the empirical results show that congestion effects are serious and obvious. The congestion effects bring huge potential in energy conservation and emission reduction. For energy conservation, energy congestion accounts for 86.93% of the saving potential. For emission reduction, the congested components account for more than 79% of the reduction potential of each pollutant.

Automated summary

This paper presents a new method to measure energy efficiency considering congestion effects, which is crucial for energy conservation and emission reduction.