Search

The attractiveness of ports is usually a pre-requisite and necessary condition for ports to achieve competitiveness, as well as the springboard to explore the competitive advantages of ports. To determine whether a port is competitive, it is necessary to explore whether it boasts certain factors that make the port attractive to users. The main purpose of this article is to apply the Analytic Hierarchy Process (AHP) method and the Decision Making Trial and Evaluation Laboratory (DEMATEL) technique to evaluate key determinants of attractiveness and their cause/effect relationships for container ports in Taiwan. The empirical results showed that: (1) Top six determinates of attractiveness for container ports are 'ample cargo sources,' 'favorable port charges,' 'dense ship network and routes,' 'low transshipment costs,' 'efficient wharf operations,' and 'adequate wharfs and back-line land,' respectively. (2) Among the above six determinants of attractiveness, 'ample cargo sources' is the cause determinant. Three determinants of port attractiveness, 'favorable port charges,' 'dense ship network and routes,' 'low transshipment costs,' which are the effect determinants. They are affected by the determinants of attractiveness of 'ample cargo sources'. In addition, this study discusses the above findings and expects to provide the study results to Taiwan's port authorities for reference. [ABSTRACT FROM AUTHOR]

Customer value is an important factor to evaluate the competitive strength for an international express service provider. It is also a key criterion to choose an express service. Hence, the main purpose of this paper was to develop a fuzzy multiple criteria decision-making (MCDM) model to assess the customer value for three express service providers in Taiwan based on the shippers’ perspective. Firstly we employed some concepts of fuzzy set theory to develop a fuzzy MCDM model. Subsequently, a hierarchical structure was constructed with four criteria, twenty sub-criteria and three alternatives (i.e. U PS , FedEx and DHL ). Then, this paper conducts an empirical study by means of a survey from the viewpoints of shippers in Taiwan. Finally, the results of this study showed that: (1) the ‘time’ aspect is the most important criterion affecting the customer service based on the viewpoints of exporters and importers in Taiwan; (2) the top six key factors affecting customer value for express service providers are ‘land time between house and airport at both ends,’ ‘administrative processing time,’ ‘pick-up and haul time in warehouse,’ ‘level of accuracy,’ ‘level of safety,’ and ‘rapid turnover,’ respectively; (3) FedEx offers the best customer value in Taiwan based on the proposed fuzzy MCDM model. Furthermore, some discussions are provided for express service companies. The main contribution of this paper is to provide a practical survey for business application on customer value of express service providers. [ABSTRACT FROM AUTHOR]

Abstract: The container transportation demand split is one of the most important decision issues for government transportation departments and port organizations. In previous studies, many researchers assumed that the shipping carrier would aim to minimize the total operation cost by selecting an appropriate port as the most favorable one to call, and the shipper would aim to minimize the inland freight cost by selecting the nearest port as the most favorable one to import and export international trade containers. Thus, a number of mathematical programming models have been developed. But in practice, the shipping carrier not only aims to minimize the total operation cost but also takes into account other criteria such as the volume of containers and port facility conditions when choosing an appropriate port as the most favorable one to call. The shipper not only aims to minimize the inland freight cost but also takes into account the frequency of ship callings when choosing an appropriate port as the most favorable one to import and export international trade containers. Thus, the purpose of this paper is to formulate a combined fuzzy multiple criteria decision making and optimization programming model for solving the container transportation demand split problem. There are two stages in this combined model: in stage one, we first compute the container transportation demand split rate by using fuzzy multiple criteria decision making (MCDM) method; whereas in stage two, an optimization mathematical programming network model is proposed for determining the inland origin destination (O-D) of import/export containers. The utilization of the proposed model is demonstrated with a case of Taiwanese ports. The results show that the proposed combined fuzzy MCDM and optimization programming model can be used to explain the container transportation demand split practice. [ABSTRACT FROM AUTHOR]

Abstract: Containerization transportation has been growing fast in the past few decades. International trades have been growing fast since the globalization of world economies intensified in the early 1990s. However, these international trades are typically imbalanced in terms of the numbers of import and export containers. As a result, the relocation of empty containers has become one of the important problems faced by liner shipping companies. In this paper, we consider the empty container allocation problem where we need to determine the optimal volume of empty containers at a port and to reposition empty containers between ports to meet exporters’ demand over time. We formulate this empty container allocation problem as a two-stage model: in stage one, we propose a fuzzy backorder quantity inventory decision making model for determining the optimal quantity of empty container at a port; whereas in stage two, an optimization mathematical programming network model is proposed for determining the optimal number of empty containers to be allocated between ports. The parameters such as the cost of loading container, cost of unloading container, leasing cost of empty container, cost of storing container, supplies, demands and ship capacities for empty containers are considered in this model. By taking advantages of the fuzzy decision making and the network structure, we show how a mixed fuzzy decision making and optimization programming model can be applied to solve the empty container allocation problem. The utilization of the proposed model is demonstrated with a case of trans-Pacific liner route in the real world. Six major container ports on the trans-Pacific route are considered in the case study, including the Port of Kaohsiung, the Port of Hong Kong, the Port of Keelung, the Port of Kobe, the Port of Yokohama and the Port of Los Angles. The results show that the proposed mixed fuzzy decision making and optimization programming model can be used to solve the empty container allocation problem well. [Copyright &y& Elsevier]