Under the background of the globalization of international trade, the cooperation between the state and the country is closer in order to enhance China''s influence in international trade and the Chinese central government in 2013 put forward a strategic concept of building One Belt One Road. The development of the One Belt One Road can not be separated from the circulation of goods and materials, the level of logistics efficiency directly determines the operating cost of logistics, which also indirectly affects the competitiveness of China''s foreign export goods internationally.
This research focuses on the efficiency as the main line, firstly, comparing the efficiency of the provinces and cities in the same period of time by the BCC model in the DEA study, decomposing the comprehensive efficiency into pure technical efficiency and scale efficiency. Then the MALMQUIST model is used to compare the efficiency of the same decision making units in different years, and the efficiency of the decision making units is analyzed dynamically, analyzing the efficiency of decision making units dynamically, and decomposed the total factor productivity index into technical progress index, pure technical efficiency change index and scale efficiency
change index., the specific factors that affect the efficiency and the efficiency of the evaluation results are linked, using TOBIT model to analyze the factors: the level of economic development, Infrastructure, location factors, employees and investment which have a great influence on logistics efficiency of provinces and cities along One Belt One Road.
Main findings are: (1) in the starting provinces and cities along the One Belt One Road, only Shanghai and Fujian’s logistics efficiency is optimal, the logistics efficiency of other provinces and cities still have great room for improvement. (2) The influence on the One Belt One Road logistics efficiency from high to low ranking as follows: location factors, employees, investment, the level of economic development and infrastructure.