Demand analysis and forecast for piggyback transportation in China

被引:0
|
作者
Xiao, Fang [1 ,2 ]
Xie, Ruhe [3 ]
Zou, Huaisen [4 ]
Zou, Yifeng [3 ]
Zhang, Haiqi [4 ]
机构
[1] School of Economics and Management, Qiannan Normal University for Nationalities, Duyun,558000, China
[2] School of Business Administration, Guizhou University of Finance and Economics, Guiyang,550025, China
[3] School of Business, Guangzhou University, Guangzhou,510006, China
[4] Beijing TF High-Tech Co Ltd, Beijing,100043, China
关键词
Economics;
D O I
10.19713/j.cnki.43-1423/u.T20191124
中图分类号
学科分类号
摘要
For piggyback transportation is still in the stage of theoretical and practical exploration in China, so there is no historical transport volume data. The refore, according to the theory and practice of the piggyback transportation development in foreign countries and the investigation and analysis of the demand of piggyback transportation, the analysis of the flow direction, velocity, volume, distance, cargo and price of the components of transportation demand were made based on the theory of Transport Economics. And the piggyback transportation demand in China was forecasted by output coefficient, exponential smoothing method and proportion method with the idea of classified forecasting, which is about(1.54~1.93) million tons in 2020 and shows that piggyback transportation has a certain development prospect in the market of China. Simultaneously, the results of different lines and directions can be used to provide support for the network layout, innovation of operating model, transport organization plan design, pricing and benefit evaluation of piggyback transportation in China. © 2020, Central South University Press. All rights reserved.
引用
收藏
页码:2125 / 2132
相关论文
共 50 条
  • [41] Freight transportation demand elasticities: a geographic multimodal transportation network analysis
    Beuthe, M
    Jourquin, B
    Geerts, JF
    Ha, CKAN
    [J]. TRANSPORTATION RESEARCH PART E-LOGISTICS AND TRANSPORTATION REVIEW, 2001, 37 (04) : 253 - 266
  • [42] Imperfect Price-Reversibility of Passenger Transportation Demand in China
    Yang, Ying
    Chai, Jian
    Zhu, Qing
    Lu, Quanying
    [J]. 2014 SEVENTH INTERNATIONAL JOINT CONFERENCE ON COMPUTATIONAL SCIENCES AND OPTIMIZATION (CSO), 2014, : 131 - 134
  • [43] Characteristic analysis and forecast of electricity supply and demand in APEC
    Yong Sun
    Li Zhu
    Zhaofeng Xu
    Lingjuan Xiao
    Jianyun Zhang
    Jiqiang Zhang
    [J]. Global Energy Interconnection, 2019, 2 (05) : 414 - 423
  • [44] Energy demand and emissions from road transportation vehicles in China
    Yan, Xiaoyu
    Crookes, Roy J.
    [J]. PROGRESS IN ENERGY AND COMBUSTION SCIENCE, 2010, 36 (06) : 651 - 676
  • [45] Analysis and forecast on the demand and supply of Chinese insurance market
    Ju, XF
    Wang, L
    [J]. PROCEEDINGS OF '97 INTERNATIONAL CONFERENCE ON MANAGEMENT SCIENCE & ENGINEERING, 1997, : 568 - 575
  • [46] Holiday and Tourism Demand: Change Analysis and Trend Forecast
    Sun Ruihong
    Ye Xinliang
    Wu Mingyuan
    Jin Jiawen
    [J]. RECENT ADVANCE IN STATISTICS APPLICATION AND RELATED AREAS, VOLS I AND II, 2009, : 1780 - 1789
  • [47] Hotel Parking Demand Forecast and Sharing Strategy Analysis
    Cheng, Jiaxin
    Chen, Hong
    Hu, Xinxin
    Yang, Boyu
    [J]. CICTP 2021: ADVANCED TRANSPORTATION, ENHANCED CONNECTION, 2021, : 1950 - 1962
  • [48] Study on analysis and forecast model of housing demand in Guangzhou
    Tan, Jian-Hui
    [J]. PROCEEDINGS OF CRIOCM 2007 INTERNATIONAL RESEARCH SYMPOSIUM ON ADVANCEMENT OF CONSTRUCTION MANAGEMENT AND REAL ESTATE, VOLS 1 AND 2, 2007, : 301 - 313
  • [49] Electric vehicle development trends and electricity demand forecast in East China
    Yao, Yingbei
    Lu, Jianzhong
    Fu, Yesheng
    Xue, Jiliang
    Zhu, Beichan
    [J]. Dianli Xitong Baohu yu Kongzhi/Power System Protection and Control, 2021, 49 (04): : 141 - 145
  • [50] Peak oil models forecast China's oil supply demand
    Lianyong, Feng
    Junchen, Li
    Xiongqi, Pang
    Xu, Tang
    Lin, Zhao
    Qingfei, Zhao
    [J]. OIL & GAS JOURNAL, 2008, 106 (02) : 43 - 47