Choosing the Optimal Bunkering Ports by liner shipping companies:
A Hybrid Fuzzy-Delphi-TOPSIS Approach
Ying Wang
Graduate School of Logistics,
Incheon National University, Korea
2013.06.04
The rising bunker prices
Bunker prices between December, 2008 and July, 2010
The rising bunker prices lead to fuel costs forming more than half of a liner shipping company’s
total running costs.
Operating difficulties facing by liner shipping companies (lower profits, higher cost)
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Maritime environmental policy
- Environmental concerns:
Strict emission standards apply to some ports
- Sulphur emission control:
shift from heavy fuel to bunkers with low sulphur content
- Establishment of ECAs (Emission Control Areas):
Baltic Sea area, North Sea area, North American area
Liner shipping companies should minimize fuel emissions by some strategies.
Increasing total running costs.
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What should liner shipping companies do?
through some operational adjustments including:
(1)
redeployment of ships
(2)
consolidating services
(3)
speed adjustment
(4)
reducing resistance
(5)
bunkering ports selection
This paper is in the view of bunkering ports selection to help liner shipping companies
saving total running costs and minimizing fuel emissions.
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Shipping route selection
Vessels visit a port for various purposes, such as taking bunkers, going to shipyards for
repair, stevedoring cargoes at a terminal or a combination of the above.
Tramp shipping
bunkering service is only required when the fuel is not
enough or the bunker prices are attractive
Liner shipping
the bunkering port selection processes are complicated due
to liner shipping companies prefer a combination purpose to
both getting bunkering services at the ports and berthing for
stevedoring cargoes, there should have more influence factors
under considering
It is important to undertake studies on liner routes for the shipping companies to both
keep the shipping schedule at each port and reduce expense costs.
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The purpose of the study
Limitations of previous studies:
- the bunkering port selection problem is solved by ship planning software, which can
only work optimally when the ship arrivals can be forecasted rather accurately, but
ignoring some unforeseen circumstances in actual operations.
- no fixed rules for the bunkering port selection among several alternatives yet.
The aim of this study:
- this paper develops a benchmarking framework that evaluates the bunkering ports’
performance under the regular liner route to choose the optimal bunkering ports.
The methodology of this study:
- owing to bunkering port selection is typically a multi-criteria group decision problem,
and in many practical situations, decision makers cannot easily express their judgments
under incomplete and uncertain information environment with exact and crisp values, and
thus fuzzy numbers are proposed in this paper.
- a hybrid Fuzzy-Delphi-TOPSIS based methodology which divides the whole bench
marking into three stages is employed to support the entire framework.
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The benchmarking framework
Literature review
Level 1:
Expert questionnaires (1)
Open-ended questions,
Brainstorming
Select of appraisal key performance factor(KPF)s
Delphi Method
identification, synthesize and prioritization of
the KPFs which may affect the bunkering port
selection for liner shipping companies
Level 2: Expert questionnaires (2)
Level 3: Perform the questionnaire reliability test
Expert questionnaires (2)
Fuzzy Delphi Method
set up the fuzzy matrix and computes the
weights of each KPF
Real data from alternatives
Fuzzy TOPSIS
assessment of possible alternative
bunkering ports for saving operation costs
and time
Level 7: Calculate negative and positive ideal solutions and separation measures
Level 8: Rank the preference bunkering ports for the shipping line company
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Methodology: Fuzzy-Delphi-TOPSIS
- Delphi Method was widely applied to select performance factors in many fields. It is
strength is that it can effectively create a consensus about an issue through knowledge of
experts and collect, modify judgments using a series of data collection, analysis
techniques and brainstorming.
- Fuzzy-Delphi-TOPSIS is a methodology combined by Fuzzy Delphi and fuzzy TOPSIS
method using for optimal decision making strategies.
◈ Fuzzy Delphi method can improve uncertainty on decision space and combine
advantages of statistical methods.
advantages: (1) to decrease the times of questionnaire survey,
(2) to avoid distorting the individual expert opinion,
(3) to clearly express the semantic structure of predicted items,
(4) to consider the fuzzy nature during the interview process.
◈ Fuzzy TOPSIS, one of the MCDM techniques, is widely used to quantify the
performance measures of the alternatives by many researches. This method can embody
the fuzzy nature of the comparison or evaluation process and strengthen the
comprehensiveness and rationality of the decision making process.
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A case study
A case study under the regional route in East Asia is performed to check whether the
developed benchmarking rule is appropriate or not.
A representative regular shipping route: China-Korea-Japan shipping route is chosen as
the evaluation object.
According to the port time and the container volumes in the ports of call, four alternative
bunkering ports (Xingang, Dalian, Busan and Niigata) are selected for future evaluation.
A representative China-Korea-Japan regular shipping route
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Selection of appraisal KPFs
21 KPFs that affect the performance of bunkering ports were collected via previous
researches and expert interviews.
Under the Delphi method by questionnaire (7 scale) distributed to the top 20 liner
shipping companies, 15 KPFs which have the geometric value more than 4 are selected as
bunkering ports performance evaluation criteria shown in Table 2.
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Fuzzy ratings under each KPF
The selected 15 KPFs contain subjective and objective factors.
◈ The subjective KPFs: the fuzzy ratings under each subjective KPF can be given by the
decision makers according to the linguistic variables.
◈ The objective KPFs: evaluated by the crisp quantity value.
To ensure compatibility with the linguistic numbers of the KPFs, crisp quantities for the
KPFs should be transformed into fuzzy numbers.
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Assessment of alternatives
In the actual operation, the liner shipping companies normally get bunkering services at
the port of Busan. And if the port of Busan is unavailable for vessel bunkering, sometimes
bunker services are obtained from the ports Xingang or Niigata.
Such results illustrate that the developed benchmarking rule is appropriate and helpful to
liner shipping companies to make optimal decisions on the choice of bunkering ports.
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Discussion
the strengths and weaknesses of the target bunkering ports and strategic recommendations:
the port of Busan: superior to other ports except for the KPF supply waiting time and
efficiency of bunker supply.
The port of Busan should improve the efficiency of port operation under the limited port
capacity to enhance the bunker supply efficiency and shorten the waiting time.
The port of Xingang: take advantage of the KPF volume of containers and long port time but
also face the problem of long supply waiting time and port bunker suppliers.
The port operators should improve the efficiency of the port operation, but at the same time
to lead some powerful bunker suppliers locating in the port is also necessary due to their
partnership with liner shipping companies will attractive more liner shipping companies
getting bunker service at this port.
The port of Dalian: bunker capacity advantage and a set number of bunker suppliers but lack
of volume of containers and port time.
The port of Niigata: high bunker quality and few supply waiting time but limited bunker
capacity and container volume.
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Sensitivity analysis
- find out the changes in the final alternative selection with variation taken from expert
opinions
- judge the variation effects on the final selection of alternative
Implications:
the port of Niigata: expand the capacity of bunker fuel
the port of Dalian: relax the strict regulations about port bunkering supply
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Conclusion
By using a hybrid Fuzzy-Delphi-TOPSIS methodology, this paper has developed a
benchmarking framework for liner shipping companies operating regular liner routes so
as to evaluate the performance of bunkering ports.
◈ important factors in selecting bunkering port:
bunker price, bunker quality, safety of bunkering, and port tariffs
◈ the competitive bunkering port ranking:
Busan, Xingang, Niigata and Dalian.
In addition, the sensitivity analysis reveals that port Niigata can enhance the
competitiveness by increasing the capacity of bunker fuel (KPF 3) and port Dalian should
relax the strict regulations about port bunkering supply (KPF 9).
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Conclusion
There are some implications in this paper:
as liner shipping companies:
(1) the proposed framework can facilitate them to better understand the complex
relationships of the relevant KPFs,
(2) more clearly understand the condition and changes of alternative bunkering ports,
(3) check whether the bunkering services they received from the most efficient bunker
ports and make prompt adjustments to meet their development strategies
as bunkering port managers:
(1) assist them to comprehend the present strengths and weaknesses of the port, and
(2) help them to make future strategies to enhance the competitiveness of the port.
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Thank you !
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