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Abstract: The airline service quality is an important issue in the international air travel transportation industry. Although a number of studies focus on the subject of airline service quality evaluation in the past, most of these studies applied the SERVQUAL method to evaluate the airline service quality. But only few have attempted to evaluate the airline service quality using the weighted SERVQUAL method. Furthermore, human judgments are often vague and it is not easy for passengers to express the weights of evaluation criteria and the satisfaction of airline service quality using an exact numerical value. It is more realistic to use linguistic terms to describe the expectation value, perception value and important weight of evaluation criteria. Due to this type of existing fuzziness in the airline service quality evaluation, fuzzy set theory is an appropriate method for dealing with uncertainty. The subjective evaluation data can be more adequately expressed in linguistic variables. Thus this article attempts to fill this gap in the current literature by establishing a fuzzy weighted SERVQUAL model for evaluating the airline service quality. A case study of Taiwanese airline is conduced to demonstrate the effectiveness of the fuzzy weighted SERVQUAL model. Finally, some interesting conclusions and useful suggestions are given to airlines to improve the service quality. [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]

Abstract: Hub location selection problems have become one of the most popular and important issues not only in the truck transportation and the air transportation, but also in the marine transportation. The main focus of this paper is on container transshipment hub locations in southeastern Asia. Transshipment is the fastest growing segment of the containerport market, resulting in significant scope to develop new transshipment terminal capacity to cater for future expected traffic flows. A shipping carrier not only calculates transport distances and operation costs, but also evaluates some qualitative conditions for existing hub locations and then selects an optimal container transshipment hub location in the region. In this paper, a fuzzy multiple criteria decision-making (FMCDM) model is proposed for evaluating and selecting the container transshipment hub port. Finally, the utilization of the proposed FMCDM model is demonstrated with a case study of hub locations in southeastern Asia. The results show that the FMCDM model proposed in this paper can be used to explain the evaluation and decision-making procedures of hub location selection well. In addition, the preferences are calculated for existing hub locations and these are then compared with a new proposed container transshipment hub location in the region, in this instance the Port of Shanghai. Furthermore, a sensitivity analysis is performed. [Copyright &y& Elsevier]

Abstract: “Transshipment” is a very popular and important issue in the present international trade container transportation market. In order to reduce the international trade container transportation operation cost, it is very important for shipping companies to choose the best transshipment container port. The aim of this paper is to present a new Fuzzy Multiple Criteria Decision Making Method (FMCDM) for solving the transshipment container port selection problem under fuzzy environment. In this paper we present first the canonical representation of multiplication operation on three fuzzy numbers, and then this canonical representation is applied to the selection of transshipment container port. Based on the canonical representation, the decision maker of shipping company can determine quickly the ranking order of all candidate transshipment container ports and select easily the best one. [Copyright &y& Elsevier]