Evaluating Shipping Efficiency in Chinese Port Cities: Four-Stage Bootstrap DEA Model

Abstract

This study examines shipping efficiency and its influencing factors in 19 Chinese port cities using a four-stage bootstrap DEA approach. Infrastructure, asset investment, and labor are selected as its inputs; cargo throughput and cargo turnover are selected as the outputs. First, in the three-stage DEA model, the SFA regression method is used to eliminate the impact of external environmental factors and random factors on shipping efficiency. Furthermore, the Bootstrap DEA method is applied to correct deviation to solve the problem of the traditional DEA method being sensitive to the number of variables of a chosen sample. Finally, the real shipping efficiency of the port cities is measured. The empirical results show that the shipping efficiency of each port city is affected by the factors of foreign trade, population size, economic development, consumption level, and government support. Additionally, the average efficiency values of port cities in the eastern region is higher than the general average at each stage; on the contrary, the average efficiency values in the central and western regions are lower than the general average. Finally, the study provides policy implications for the future improvement of shipping efficiency.