• DocumentCode
    2922255
  • Title

    A Decision Support Framework for Port Efficiency Discovery Based on Intelligent Data Integration

  • Author

    Meng, Yan-Ping ; Yang, Bin ; Huang, You-Fang ; Yang, Yong-Sheng ; Hu, Zhi-Hua

  • Author_Institution
    Logistics Res. Center, Shanghai Maritime Univ., Shanghai, China
  • Volume
    4
  • fYear
    2009
  • fDate
    26-27 Dec. 2009
  • Firstpage
    58
  • Lastpage
    61
  • Abstract
    Trading port efficiency is an important determinant of the competitiveness of the goods and a key factor to improve the investment climate of the countries. Managing the efficiency and coordinating distributed entities in a supply chain is a challenging task. This paper provide proposed s decision support framework for port efficiency discovery based on intelligent data integration, and provided some intelligent approaches to measure and analysis the trading port efficiency from supply chain aspect. The solution can take adequate use of the massive operational data accumulated in the distributed information system scattered in different sectors, and give useful information to support decision-making. A Case study has been developed to give an illustration of employing the proposed decision support framework in one of the trading port in China. The results obtained indicate that the prototype system is capable of get some useful insights into port efficiency.
  • Keywords
    decision support systems; supply chains; decision support framework; distributed information system; intelligent data integration; port efficiency discovery; supply chain; supply chain aspect; trading port efficiency; Costs; Data mining; Friction; Information management; Innovation management; Investments; Logistics; Production facilities; Supply chain management; Supply chains;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Information Management, Innovation Management and Industrial Engineering, 2009 International Conference on
  • Conference_Location
    Xi´an
  • Print_ISBN
    978-0-7695-3876-1
  • Type

    conf

  • DOI
    10.1109/ICIII.2009.476
  • Filename
    5369707