Estimation method of port handling efficiency value based on ship big data

Abstract

The handling efficiency of container port is one of the key indicators that reflects the port's competitiveness and attracts shipping companies to call. To accurately estimate the port's handling efficiency value, this paper proposes a method with Greatmaps (GMap) visualization technology to calculate the port's handling efficiency value based on the data of the Automatic Identification System (AIS). Empirically, this method was applied to estimate the monthly handling efficiency values of Shanghai Port, Singapore Port, Shenzhen Port and Ningbo-Zhoushan Port, the average monthly handling efficiency values of the four ports in the first half of 2017 were respectively 2.85, 1.87, 2.17 and 2.10. Based on the obtained values in the first half of the year, the study managed to estimate the monthly throughput for the above four ports in the second half of the year, with the average estimation error being respectively 2.77%, 2.06%, 2.93% and 2.46%. The results show that the method can generate the ports' handling efficiency value with good accuracy and can be used to infer and monitor the port's throughput in real time. Further, results calculated by the method could provide a theoretical reference for the port to improve the performance and help the shipping company to choose the port strategy, and ultimately improve the port's digital management level. 集装箱港口的装卸效率是衡量港口竞争力和吸引船公司前来挂靠的关键指标之一。为准确估计港口的装卸效率值,基于船舶自动识别系统（AIS）数据,利用Greatmaps（GMap）可视化技术,提出一种计算港口装卸效率值的方法。利用该方法估算上海港、新加坡港、深圳港和宁波-舟山港的月度装卸效率值,4个港口2017年上半年的装卸效率月度均值分别为2.85、1.87、2.17和2.10。基于上半年估计的装卸效率值,对4个港口下半年的月度吞吐量进行估计,估算误差均值分别为2.77%、2.06%、2.93%和2.46%。结果表明,该方法能够较为准确地反映港口的装卸效率,可应用于推断和实时监控港口的吞吐量,为港口提高绩效和船公司选择港口策略提供理论参考,提升港口数字化管理水平。