摘要
上海港是全球第一大港,连续十年集装箱吞吐量保持全球第一,其运输吞吐能力的升级换代是上海国际航运中心建设的重要目标。随着国内外经济环境的变化和不确定性的增加,上海港如何进一步适应国家战略需求和国际环境变化,对集装箱吞吐量进行科学预测,及时化解瓶颈和风险,是港口发展的重要战略目标。上海港要严格疫情防控,全面复工复产;推进重大项目建设,深化发展战略;做精企业管理,推动科技创新;借助自由贸易港,发展航运金融业;打造航运服务产业链,建设高端航运服务市场;加强党的领导,引领港口持续发展。
As the world's largest port,the upgrade of the throughput at Shanghai Port,which has remained the first in the world for ten consecutive years,is an important part of the construction of Shanghai international shipping center.However,with the change of domestic and international economic environment and the increase of uncertainty,it is an important strategy for Shanghai port to further adapt to national strategic demands and international environment changes,scientifically predict the container throughput,and timely resolve bottlenecks and risks.Based on the analysis of the development history and strategic positioning of Shanghai port,this paper establishes a grey prediction model of container throughput,makes a reasonable prediction of container throughput during the"14th five year plan"period,and puts forward such countermeasures and suggestions for the construction and development of Shanghai Port as strict epidemic prevention and control,comprehensive resumption of work and production,promotion of major projects and deepening of development strategy,improvement of enterprise management and promotion of scientific and technological innovation,development of a free trade port,development of shipping finance industry,building of shipping service industry chains and high-end shipping service markets,and strengthening the party's leadership in order to lead the sustainable development of Shanghai Port.
作者
桂德怀
张显璇
GUI Dehuai;ZHANG Xianxuan(Suzhou Institute of Industrial Technology,Suzhou,215104,China)
出处
《滁州职业技术学院学报》
2020年第3期33-36,40,共5页
Journal of Chuzhou Polytechnic
基金
苏州工业职业技术学院毕业设计(论文)重点资助课题“基于组合模型的上海港集装箱吞吐量预测分析”(NO.20)
中国物流学会物流教改教研课题计划“智能工厂物流人才培养模式改革与探索”(JZW2020083)
江苏高校“青蓝工程”资助优秀教学团队“智能工厂物流教学团队”项目(NO.60)。
关键词
上海港
集装箱吞吐量
灰色预测模型
Shanghai Port
container throughput
grey prediction model
