Choosing optimal bunkering ports for liner shipping companies: A hybrid Fuzzy-Delphi–TOPSIS approach Ying Wang a , Gi-Tae Yeo a,n , Adolf K.Y. Ng b a Graduate School of Logistics, Incheon National University, Incheon, Republic of Korea b Department of Supply Chain Management, I.H. Asper School of Business, University of Manitoba, Winnipeg, MB, Canada R3T 2N2 article info Available online 16 May 2014 Keywords: Bunkering port Key performance factor (KPF) Liner shipping company Fuzzy-Delphi–TOPSIS abstract With sustained high bunker prices, new methods for choosing optimal bunkering ports to save on total operating costs have appeared in research involving liner shipping companies. Generally speaking, the bunkering port selection problem is solved by utilizing ship planning software. However, this can only work optimally when ship arrivals can be forecasted rather accurately, and its primary limitation is that it ignores unforeseen circumstances in actual operations. There are as yet no fixed rules for bunkering port selection. To address this, the paper develops a benchmarking framework that evaluates bunkering ports’ performances with in regular liner routes in order to choose optimal ones. Bunkering port selection is typically a multi-criteria group decision problem, and in many practical situations, decision makers cannot form proper judgments using incomplete and uncertain information in an environment with exact and crisp values; thus, fuzzy numbers are proposed in this paper. A hybrid Fuzzy-Delphi– TOPSIS based methodology that divides the benchmarking into three stages is employed to support the entire framework. Additionally, a sensitivity analysis is performed. The proposed framework can enable decision makers to better understand the complex relationships of the relevant key performance factors and assist managers in comprehending the present strengths and weaknesses of their strategies. & 2014 Elsevier Ltd. All rights reserved. 1. Introduction Bunker fuel is used by most of the international seagoing ships. Given that 90 percent of world trade is carried out by sea (IMO, 2009) and the shipping industry must work within the ever-evolving international sea transportation requirements, the world bunker demand is increasing. Bunker prices have risen considerably in recent years, and fuel costs form more than half of a liner shipping company's total running costs (Yao et al., 2012). In addition, environmental policies are another difficulty for the operation of liner shipping companies. With increasing bunker prices, many liner shipping companies have sought to save fuel by making some operational adjustments, including: (1) re-deployment of ships, (2) consolidation of services, (3) speed adjustment, (4) reduction of resistance, and (5) bunkering port selection (Mazraati, 2011). Among these methods, optimizing bunkering port selection is crucial (Besbes and Savin, 2009) to save on total running costs. Generally speaking, vessels visit a port for various purposes, such as taking bunkers, going to shipyards for repair, stevedoring cargoes at terminals, or a combination of the above (Huang et al., 2011). In the case of tramp routes, bunkering service is required only when there is insufficient fuel or when the bunker prices are attractive; in such instances, bunkering port selections are simple. However, with regard to regular liner routes, bunkering port selection processes are rather complicated, mainly because liner shipping companies prefer a combination purpose of obtaining bunkering services at the ports and berthing for stevedoring cargoes; hence, there are more factors under consideration (Hu, 2005). Hence, it is important to study liner routes so that liner shipping companies can maintain their shipping schedules at each port and reduce their operating costs. Understanding such, the paper aims to develop a benchmarking frame work for choosing optimal bunkering ports for liner shipping companies along a regular liner route by evaluating the bunkering ports’ performances. Therefore, key performance factors (KPFs) of bunkering ports are identified; further, via a case study analysis, the strengths and weaknesses of these alternative bunkering ports can be understood, and the developed benchmarking rule can be determined to be applicable or not. Additionally, a sensitivity Contents lists available at ScienceDirect journal homepage: www.elsevier.com/locate/tranpol Transport Policy http://dx.doi.org/10.1016/j.tranpol.2014.04.009 0967-070X/& 2014 Elsevier Ltd. All rights reserved. n Corresponding author. Tel.: þ82 1023590720; fax: þ82 328350703. E-mail address: ktyeo@incheon.ac.kr (G.-T. Yeo). Transport Policy 35 (2014) 358–365