为应对日益增多的国际物流风险,基于超网络理论及方法构建了海关物流监控超网络(CLMSN),创建了两个考虑了超网络节点静态维度和动态维度特性的风险判定指标,提出了一种高风险节点评判算法。通过算例验证了该算法能够识别判定CLMSN中的高风险节点。采用此算法判定高风险节点并优先实施重点监控能够控制风险发生及传播的可能性,从而对目前海关物流监控风险管理进行有效优化。
In order to cope with the increasing international logistics risk, optimizing Customs Logistics Monitoring system risk management is necessary. This article use super-network theory and method to build Customs Logistics Monitoring Super-network(CLMSN) and put forward an evaluation algorithm considering static and dynamic characteristic of nodes. Numerical analyses of examples show that the method is correct and effective in identifying high risk nodes. Using the algorithm in this paper to determine the high risk nodes and giving priority to the implementation of key monitoring can control the occurrence and spread of risk, and will effectively improve the Customs Logistics risk management.
[1] 段景辉.海关风险管理分析与评价方法[J].上海海关学院学报,2012,3:35-43.
Duan Jinghui. Analysis and evaluation method on customs risk management[J].Journal of Shanghai Customs College,2012,3:35-43.
[2] 张彦.海关监管职能的优化研究——以风险管理为视角[D].上海:上海交通大学,2009.
Zhang Yan. Study on optimization of the customs supervises——the visual angle of the risk management[D].Shanghai:Shanghai Jiao Tong University,2009.
[3] 韩婷婷.海关物流监控风险管理[D].大连:大连海事大学,2008.
Han Tingting. Risk management on customs logistics supervision[D].Dalian : Dalian Maritime University,2008.
[4] Anna Nagurney. Optimal supply chain network design and redesign at minimal total cost and with demand satisfaction[J].International Journal of Production Economics,2010,128(1): 200-208.
[5] Anna Nagurney. Supernetworks: the science of complexity[J].上海理工大学学报,2011, 3: 205-228.
[6] Smith B G. Socially distributing public relations:twitter,haiti,and interactivity in social media[J].Public Relations Review,2010,36( 4): 329-335.
[7] Westerman D,Spence P R,Heide B. A social network as information: the effect of system generated reports of connectedness on credibility on Twitter[J].Computers in Human Behavior,2012,28(1):199-206.
[8] 王志平,王众托. 超网络理论及其应用[M].北京:科学出版社,2008.
[9] 王众托,王志平. 超网络初探[J].管理学报,2008, 5(1):1-8.
Wang Zhongtuo, Wang Zhiping. Elementary study of supernet works[J].Chinese Journal of Management.2008,5(1): 1-8.
[10] 王众托.关于超网络的一点思考[J].上海理工大学学报,2011, 3: 229-237.
Wang Zhongtuo. Reflection on supernetwork[J].Journal of University of Shanghai for Science and Technology,2011, 3: 229-237.
[11] 刘军.社会网络分析导论[M].北京: 社会科学文献出版社,2004.
[12] 刘军.整体网分析: UCINET 软件实用指南[M].2版. 上海:格致出版社,2014.
[13] 胡枫,赵海兴,何佳倍,等.基于超图结构的科研合作网络演化模型[J].物理学报,2013,19:1-8.
Hu Feng,Zhao Haixing,He Jiabei,et al.An evolving model for hypergraph-structure-based scientific collaboration networks[J].Acta Physica Sinica,2013,19:1-8.
[14] 漆玉虎,郭进利,王志省.超网络度参数研究[J].科技与管理,2013,01:34-38.
Qi Yuhu, Guo Jinli, Wang Zhixing. Research on the degree of hypernetwork[J].Science-Technology and Management,2013,01:34-38.
[15] 朱莉,曹杰.灾害风险下应急资源调配的超网络优化研究[J].中国管理科学,2012,12:141-147.
Zhu Li, Cao Jie. Supernetwork optimization of emergency resource allocation under disaster risk[J].Chinese Journal of Management Science,2012,12:141-147.
[16] 马军.供应链超网络均衡模型研究[D].大连:大连理工大学,2013.
Ma Jun. Research on supply chain supernetwork equilibrium models[D].Dalian:Dalian University of Technology,2013.
[17] 黄建华,党延忠.快递超网络模型及基于效率的优化方法[J].北京理工大学学报,2011, 6: 68-72.
Huang Jianhua, Dang Yanzhong. Express super-network model and efficiency-based optimization method[J].Journal of Beijing Institution of Technology(Social Sciences Edition)2011, 6: 68-72.
[18] 于丽英,胡朝辉.超网络视角下的高校公共危机预警管理研究[J].中国安全学报,2014, 7: 146-151.
Yu Liying,Hu Chaohui. Research on public crisis early-warning management in universities from a supernetwork perspective[J].China Safety Science Journal, 2014, 7: 146-151.
[19] 马宁,刘怡君.基于超网络的舆论领袖识别应用研究[J].中国科学院院刊,2012, 5: 586-594.
Ma Ning, Liu Yijun. Recognition of online opinion leaders based on supernetwork analysis[J].Bulletin of Chinese Academy of Sciences, 2012, 5: 586-594.
