管理评论

管理评论 ›› 2021, Vol. 33 ›› Issue (2): 289-297.

• 物流与供应链管理 • 上一篇    下一篇

基于复杂网络的上海出口集装箱运价指数波动传导特征研究

汤霞1,2,3, 匡海波1, 郭媛媛1   

  1. 1. 大连海事大学综合交通运输协同创新中心, 大连 116026;
    2. 大连海事大学交通运输工程学院, 大连 116026;
    3. 珠海城市职业技术学院经济管理学院, 珠海 519000
  • 收稿日期:2020-03-30 出版日期:2021-02-28 发布日期:2021-03-08
  • 通讯作者: 匡海波(通讯作者),大连海事大学综合交通运输协同创新中心教授,博士生导师,博士
  • 作者简介:汤霞,大连海事大学综合交通运输协同创新中心、交通运输工程学院博士研究生,珠海城市职业技术学院经济管理学院讲师;郭媛媛,大连海事大学综合交通运输协同创新中心讲师,博士。
  • 基金资助:
    国家自然科学基金重点项目（71831002）；国家自然科学基金项目（71672016）；科技部重点专项项目（2019YFB1600400）；教育部长江学者和创新团队发展计划（IRT_17R13）；广东省教育厅科研课题（2017GkQNCX070）。

Transmission Characteristics of Fluctuation among Shanghai(Export) Containerized Freight Indices Based on Complex Network Theory

Tang Xia1,2,3, Kuang Haibo1, Guo Yuanyuan1   

  1. 1. Collaborative Innovation Center for Transport Studies, Dalian Maritime University, Dalian 116026;
    2. Transportation Engineering College, Dalian Maritime University, Dalian 116026;
    3. School of Economics and Management, Zhuhai City Polytechnic, Zhuhai 519000
  • Received:2020-03-30 Online:2021-02-28 Published:2021-03-08

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摘要： 引入复杂网络理论和格兰杰因果关系检验方法，构建了上海出口集装箱运价指数（SCFI）13条航线运价波动格兰杰因果关系网络，从系统整体这一新的视角研究了SCFI航线子市场地位与作用、波动传导特征。研究发现：SCFI航线运价波动传导平均距离短、传导速度快；不同航线运价波动传导的影响范围与被影响范围、媒介能力、聚集效应均不同；13条航线运价波动传导网络可分为四个成员数、成员间联系紧密程度、媒介能力均不同的社团，波动传导的主要路径为社团2、社团1经社团3至社团4。基于以上结论，提出政府港航管理部门加强集装箱航运市场波动风险精细化监管及航运企业精准化经营决策的相关建议。

关键词: 水路运输, 波动传导, 集装箱航运, 运价指数, 复杂网络

Abstract: In this paper, we introduce the complex network theory and Granger causality approach to build the Granger causality network of Shanghai (Export) Containerized Freight Index (SCFI) from 13 routes. We explore the sub market of SCFI's market position, function and transmission characteristic from a systematic prospective. Our findings are as follows. The fluctuation's average transmission distance is short and therefore the speed is fast among SCFI freight routes. Different route has different fluctuation which is differed by impact range, intermediation capacity and cohesion. The fluctuation network of all 13 freight routes can be divided into 4 different clusters which include different quantities, degree of connection and intermediation capacity. The main routes: cluster 2 and 1 transmit the fluctuation to cluster 3 and then cluster 4. The above findings suggest the port and shipping administration together with the shipping enterprises need to closely monitor the shipping market fluctuation and take advantage of this factor as an important part of making precise management decisions.

Key words: waterway transportation, fluctuation transmission, container shipping, freight index, complex network theory