港口供需匹配指标体系构建研究

科研管理 ›› 2015, Vol. 36 ›› Issue (12): 92-102.

港口供需匹配指标体系构建研究

赵广田¹, 汪克夷¹, 余方平²

1. 大连理工大学管理与经济学部, 辽宁大连 116024;
2. 大连海事大学交通运输管理学院, 辽宁大连 116026

收稿日期:2015-02-04 修回日期:2015-09-20 出版日期:2015-12-25 发布日期:2015-12-22
通讯作者: 赵广田
作者简介:赵广田(1971-),男(汉),辽宁锦州市人,大连理工大学管理与经济学部博士研究生,研究方向:港口风险管理。
汪克夷(1944-),男(汉),江苏苏州市人,大连理工大学管理与经济学部教授,博士生导师,研究方向:企业管理、战略管理。
余方平(1981-),男(汉),湖南攸县人,研究方向:港口风险管理。
基金资助:
国家自然科学基金:低碳港口生成机理及评价模式研究(71273037)。

A research on construction of the port supply and demand matching index system

Zhao Guangtian¹, Wang Keyi¹, Yu Fangping²

1. Faculty of Management and Economics, Dalian University of Technology, Dalian 116024, Liaoning, China;
2. School of Transportation Management, Dalian Maritime University, Dalian 116026, Liaoning, China

Received:2015-02-04 Revised:2015-09-20 Online:2015-12-25 Published:2015-12-22

摘要/Abstract

摘要： 港口供需匹配及其评价指标体系直接关乎着港口运营效率的高低,是港口管理部门和港口运营部门关注的重要内容。本研究对港口供需匹配指标体系构建进行了研究,主要创新点包括:一是提出了港口供给和需求匹配的影响因素,海选出了港口供给和需求匹配相关指标体系。二是利用相关-主成分分析得到了优化精简港口供需匹配指标体系。在采集上海港2000-2013年年度数据,利用相关分析剔除了相关系数高于0.8的指标,一次优化指标体系中供给和需求指标数量分别仅保留了44%和33.3%;利用主成分分析对初筛的评价指标体系进行二次优化筛选,结果表明优化筛选后的供给和需求指标用25%和24%的评价指标都能够反映90%以上的一次优化指标信息。

关键词: 港口, 供需匹配, 指标体系, 相关分析, 主成分分析

Abstract: The port supply and demand matching and the evaluation index system is directly related to the efficiency of port operation level, and it is the core problem which draws the attention of the port management and operation departments. This paper studies the construction of port supply and demand matching index system. The key innovations include:firstly, the port supply and demand matching factors is proposed, and the port supply and demand matching index system is selected; secondly, the port supply and demand matching index system has been optimized with the correlation -principal component analysis method. By collecting the annual data of Shanghai port 2000-2013 and using correlation analysis, the index with correlation coefficient greater than 0.8 is removed, and the number of supply index and demand index were retained by 44% and 33.3% respectively in the first optimization. Using the principal component analysis method, a second optimization was made to the first-optimized indices, showing that the supply and demand indices after screening were 25% and 24% respectively, and they were able to reflect more than 90% of the first-optimized index information.

Key words: port, supply and demand matching, index system, correlation analysis, principal component analysis

中图分类号:

U-9
N945.16

赵广田, 汪克夷, 余方平. 港口供需匹配指标体系构建研究[J]. 科研管理, 2015, 36(12): 92-102.

Zhao Guangtian, Wang Keyi, Yu Fangping. A research on construction of the port supply and demand matching index system[J]. Science Research Management, 2015, 36(12): 92-102.

参考文献

[1] Wayne K. T.. An economic theory of the port[J].Research in Transportation Economics, 2006(16):43-65. [2] Winkelmans W.. Port:Competitiveness[M]. University of Antwerpen, 2002. [3] 肖钟熙.要重视港口通过能力计算方法的研究[J].港口经济, 2012(10):5-7.Xiao Zhongxi. Pay attention to study on port through capacity calculation method[J]. Port Economy, 2012(10):5-7. [4] 杜麒栋,孟文君.港口产能过剩之探讨及解决之道[J].中国港口, 2010(1):13-15.Du Qidong, Meng Wenjun. Excess capacity of the port and the solution[Jl. China Port, 2010(1):13-15. \李芬.我国集装箱港口产能过剩问题研究[D].中国海洋大学, 2011年.Li Fen. Study on the overcapacity of the container ports in China[D]. Ocean University of China, 2011. [6] 施欣.港口产业供需函数及福利效率分析[J].系统工程, 2000,18(5):35-39.Shi Xin.The study on the demand and supply of the port and its welfare[J]. 2000, 18(5):35-39. [7] Fung, M. K.. Forecasting Hong Kong'scontainer throughput:An error-correction model[J]. Journal of Forecasting, 2002(21):69-80. [8] 张萍,严以新,许长新.港口吞吐量的内在影响因素提取[J].中国港湾建设, 2006(6):70-72.Zhang Ping, Yan Yixin, Xu Changxin. Distilling inner influencing factors on port throughput[J]. China Harbor Engineering, 2006(6):70-72. [9] 王丹,杨赞.港口吞吐量影响因素分析[J].水运工程, 2007(1):45-48.Wang Dan, Yang Zan.Analysis of influential factors of port throughput[J]. Port & Waterway Engineering, 2007(1):45-48. [10] 张丽君,刘佳骏.中国沿海港口吞吐量内在影响因素研究[J].中国水运, 2008, 8(10):54-56.Zhang Lijun, Liu Jiajun. Research on the internal influence factors of China coastal port throughput[J]. China Water Transport, 2008, 8(10):54-56. [11] 匡海波.中国沿海港口吞吐量预测模型研究[J].科研管理, 2009, 30(3):187-192.Kuang Haibo.Research on the prediction model of Chinese coastal port throughput[J]. Science Research Management, 2009, 30(3):187-192. [12] 栾维新,马新华.我国集装箱港口吞吐能力供需平衡研究[J].经济地理, 2011,31(11):1774-1780, 1792.Luan Weixin, Ma Xinhua. The Study on supply-demand balance for throughput capacity of the container ports in China[J]. Economic Geography, 2011, 31(11):1774-1780, 1792. [13] 刘枚莲,朱美华,黄键.港口吞吐量预测影响因素筛选方法研究[J].水运工程, 2011(3):76-80.Liu Meilian, Zhu Meihua, Huang Jian. Screening of influential indices for port throughput forecasting[J]. Port & Waterway Engineering, 2011(3):76-80. [14] 张萍,张守国.江苏沿海港口吞吐量影响因素及预测分析[J].水运工程, 2011(10):63-65.Zhang Ping, Zhang Shouguo. Influential factors and forecast of coastal port throughput in Jiangsu province[J]. Port & Waterway Engineering, 2011(10):63-65. [15] 匡海波,李伟,张欣.我国沿海集装箱港口的供需缺口研究[J].系统工程理论与实践, 2012, 32(1):83-90.Kuang Haibo, Li Wei, Zhang Xin. Reseach on China's coastal container port supply-demand gap[J]. Systems Engineering-Theory & Practice, 2012, 32(1):83-90. [16] Fan L., Wilson W. W., Dahl B.. Risk analysis in port competition for containerized imports[J]. European Journal of Operational Research, 2015, 245(3):743-753. [17] Cai T.T., Shen X.T.. High dimensional data analysis(Frontiers of statistics)[M]. Singapore:World Scientific Publishing Company,2010. [18] Richard A. J., Dean W.W.. Applied multivariate statistical analysis (6th Edition)[M]. USA:New Jersey, Prentice Hall, 2007. [19] Yap W. Y., Lam J. S. L..80 million-twenty-foot-equivalent-unit container port? Sustainability issues in port and coastal development[J]. Ocean & Coastal Management,2013,71:13-25.

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