Evaluation and spatiotemporal analysis of low-carbon efficiency of the “ship-port” system
Weipan Zhang, Weijie Chen, Xianhua Wu, Jihong Chen, Zhaomin Zhang
Abstract
Evaluating the port low-carbon efficiency is essential for promoting decarbonization and mitigating climate change. This paper firstly constructs a two-stage ‘ship-port’ system, and then based on data from sources such as ship automatic identification system (AIS) data, the ‘bottom-up’ and ‘top-down’ methods are employed to measure and analyze carbon dioxide (CO2) emissions at both the ship and port stages. Subsequently, a multi-period network data envelopment analysis (DEA) model is introduced, which addresses the limitation of traditional models that evaluate efficiency independently across different periods, thereby facilitating comparability of efficiency over time. The proposed model is applied to evaluate the dynamic low-carbon efficiency of both the overall and internal stages of the ‘ship-port’ system, and to identify the key links contributing to system inefficiency. Then the paper analyzes the temporal trends and spatial distribution characteristics of efficiency. The research conclusion finds that the system efficiency shows a slow and fluctuating upward trend over time, and the differences within regions constitute the primary cause of overall differences of port low-carbon efficiency. Finally, the targeted improvement strategies are proposed. The findings offer valuable insights for emission reduction policy of the government and enterprises, and contribute to the theoretical framework of network DEA.