A Novel Ratio-Based Parallel DEA Approach for Evaluating the Energy and Environmental Performance of Chinese Transportation Sectors

Abstract

As a high-energy-consumption and high-CO₂-emission industry in China, the transportation sector has been under increasing pressure to improve its performance. This paper develops a novel parallel DEA approach to measure Chinese transportation sector’s energy and environmental performance (EEP) over all possible weights, which is to avoid the risk of using the extreme or the most favorable weights in performance evaluation. In our method, the transportation sector is consisted of two parallel subsystems (passenger transportation and freight transportation) with shared inputs and undesirable shared outputs. All possible weights are considered in the EEP evaluation, then the EEP of a transportation sector is represented by a ranking interval. Finally, the proposed approach is applied to the transportation sectors in 30 Chinese provinces. Results show that the best and the worst ranking of most provinces vary greatly. Besides, the EEP of most provinces is hard to dominate others strictly, but the general tendency is the EEP of eastern provinces better than western provinces. Furthermore, the EEP difference of some adjacent provinces with similar features is distinct. These findings are not all the same as previous studies, which verifies the necessity of considering all possible weights in performance evaluation. Therefore, our method provides a new point of view in performance evaluation and can give more robust results for decision makers.

Keywords

Data envelopment analysis / energy and environmental performance / transportation sector / parallel system / ranking interval

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