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

As a high-energy-consumption and high-CO_2-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.

作为中国的高能耗和高二氧化碳排放行业，交通运输部门面临着越来越大的提升其绩效的压力。本文提出了一种新的平行数据包络分析（DEA）方法，用于在所有可能的权重下衡量中国交通运输部门的能源与环境绩效（EEP），以避免在绩效评估中使用极端或最有利权重的风险。在我们的方法中，交通运输部门由两个具有共享投入和不良共享产出的平行子系统（客运和货运）组成。在能源与环境绩效评估中考虑了所有可能的权重，然后交通运输部门的能源与环境绩效由一个排名区间来表示。最后，将所提出的方法应用于中国30个省份的交通运输部门。结果表明，大多数省份的最佳排名和最差排名差异很大。此外，大多数省份的能源与环境绩效很难严格优于其他省份，但总体趋势是东部省份的能源与环境绩效优于西部省份。此外，一些具有相似特征的相邻省份的能源与环境绩效差异明显。这些发现与以往的研究并不完全相同，这验证了在绩效评估中考虑所有可能权重的必要性。因此，我们的方法为绩效评估提供了一个新的视角，并能为决策者提供更稳健的结果。