Revolutionising Transportation Energy Efficiency

Improving #transportation #energy #efficiency is a critical aspect of ensuring sustainable economic growth in developing countries while minimizing carbon emissions. One effective way to assess transportation efficiency is to measure its energy consumption and productivity, such as passenger-kilometers and tone-kilometers. However, it is challenging to evaluate indirect measures of transportation efficiency, which makes it necessary to find an adequate margin that can help trade-off to improve decision-making units' weak efficiency.

Data Envelopment Analysis (#DEA) is a method used to calculate such margins. Several studies have proposed various DEA-based approaches to evaluate trade-offs for efficient managerial operations. For instance, Cooper et al. used marginal rates to determine valid trade-off margins and improve DMUs' efficiencies, while Khoshandam et al. proposed a new trade-off calculation method for non-discretionary factors. Although trade-offs have been extensively used in industrial operations to achieve efficiencies, it is not well-established in transportation energy literature.

This article contributes to the existing literature in two ways. First, it uses effective marginal values to perform quantitative trade-offs and fill the gap in transportation energy efficiency. Second, it applies quantitative trade-offs to domestic road transportation of weakly efficient DMUs to bring them to the optimal efficient boundary point. The study uses data from a previous study that evaluated the transportation energy efficiency of 19 “Belt and Road” (#BRI) stakeholder countries.

The study's results show that apparent efficient countries are weakly efficient due to the slack values in an undesirable output, carbon dioxide (#CO2). Then, the marginal trade-off method between desired and undesired outputs is applied, considering the ideal marginal range to improve DMUs' efficiencies. The selected output variables and analysis help identify different trade-off scenarios in the presence of desirable and undesirable outputs.

Transportation plays a significant role in the economic freedom of developing countries, but it also accompanies carbon emissions, considered an indirect cost. Quantitative trade-off methods can help find an effective balance between efficiency-related variables, and the operational plans and gains determine the selection of the trade-off method.

In conclusion, this article proposes a practical solution to address the weak efficiency of DMUs in the transportation sector by applying quantitative trade-offs using DEA. The study's limitations and future research recommendations are also discussed.