Please use this identifier to cite or link to this item: https://scholarbank.nus.edu.sg/handle/10635/134444
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dc.titleA MODELLING STUDY OF GLOBAL MARITIME FREIGHT DEMAND FORECASTING
dc.contributor.authorSOU WENG SUT
dc.date.accessioned2016-12-31T18:01:39Z
dc.date.available2016-12-31T18:01:39Z
dc.date.issued2016-08-12
dc.identifier.citationSOU WENG SUT (2016-08-12). A MODELLING STUDY OF GLOBAL MARITIME FREIGHT DEMAND FORECASTING. ScholarBank@NUS Repository.
dc.identifier.urihttp://scholarbank.nus.edu.sg/handle/10635/134444
dc.description.abstractThere is a huge increase in maritime trade volume in recent decades, and in particular, most of these traded commodities are transported by seaborne containers. Forecasting of maritime container demand in the context of international trade has always been of importance to government and policy makers so that countries and regions can plan ahead (in terms of infrastructure development or policies) to remain competitive. Numerous efforts have been made in the literature to forecast container demand but most of these studies have either adopted an economic approach or the transportation perspective. Few have actually considered the forecasting of maritime container demand from an integrative economic trade-transportation modelling perspective. This study therefore presents the development of a quantitative demand forecasting approach that is capable of predicting future seaborne container demand in the global context. The integrated forecasting framework follows the conventional four step approach (i.e. generation, distribution, modal split and assignment) with combining efforts from economic approach and transportation perspective.
dc.language.isoen
dc.subjectFreight Transportation, Maritime Freight Forecasting, International Trade, Freight Demand, Container Forecast
dc.typeThesis
dc.contributor.departmentCIVIL & ENVIRONMENTAL ENGINEERING
dc.contributor.supervisorONG GHIM PING, RAYMOND
dc.description.degreePh.D
dc.description.degreeconferredDOCTOR OF PHILOSOPHY
dc.identifier.isiutNOT_IN_WOS
Appears in Collections:Ph.D Theses (Open)

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