Purpose: The purpose of this paper is to devise a efficient method for the importance analysis on Port Throughput Influence Factors. Design/methodology/approach: Neighborhood rough sets is applied to solve the problem of selection factors. First the throughput index system is established. Then, we build the attribute reduction model using the updated numerical attribute to reduction algorithm based on neighborhood rough sets. We optimized the algorithm in order to achieve high efficiency performance. Finally, the article do empirical validation using Guangzhou Port throughput and influencing factors’ historical data of year 2000 to 2013. Findings: Through the model and algorithm, port enterprises can identify the importance of port throughput factors. It can provide support for their decisions. Research limitations: The empirical data are historical data of year 2000 to 2013. The amount of data is small. Practical implications: The results provide support for port business investment, decisions and risk control, and also provide assistance for port enterprises’ or other researchers’ throughput forecasting. Originality/value: In this paper, we establish a throughput index system, and optimize the algorithm for efficiency performance.

Peer Reviewed