Please use this identifier to cite or link to this item: https://doi.org/10.3141/2168-07
Title: Utility-Based Estimation of probabilistic port hinterland for networks of intermodal Freight Transportation
Authors: Meng, Q. 
Wang, X.
Issue Date: 12-Jan-2010
Source: Meng, Q., Wang, X. (2010-01-12). Utility-Based Estimation of probabilistic port hinterland for networks of intermodal Freight Transportation. Transportation Research Record (2168) : 53-62. ScholarBank@NUS Repository. https://doi.org/10.3141/2168-07
Abstract: The inland area served by a particular port is known as the port hinterland. The probability-within a certain range [α1, α2], where parameters α1, α2 ε [0, 1]-that shippers will use that port to transport containers to a given destination is referred to as the port's probabilistic hinterland.The probabilistic port hinterland is a key performance index that refle ts the attractiveness and competitiveness of a port, which is determined by a shipper's decision of whether to choose a route passing through the port. The random utility of an intermodal route is defined as a summation of Transportation cost and transport time multiplied by the value of time (VOT) perceived by shippers. The random transshipment time per container incurred at a transfer terminal on an intermodal route is then derived by modeling the transshipment process as an M[X]/G/1 queue due to containers arriving in batches. According to the utility maximization principle for shippers faced with intermodal route choice, a mathematical expression of the utility-based probabilistic port hinterland is presented. An algorithm based on Monte Carlo simulation is proposed for finding the probabilistic port hinterland. A case study is performed to estimate the probabilistic hinterland of the port of Shanghai, China, and to analyze the impact of the handling capacity at the Shanghai port and VOT on the port hinterland.
Source Title: Transportation Research Record
URI: http://scholarbank.nus.edu.sg/handle/10635/84699
ISSN: 03611981
DOI: 10.3141/2168-07
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