Monitoring the market has crucial roles for executing the shipping investment decisions in maritime transportation industry. The high level of managerial effort requires bringing market tendencies with the up-to-date data over dynamic parameters. This paper extends the Quality Function Deployment (QFD) principles towards shipping investment process via the originally proposed Ship of Quality (SoQ) framework. Furthermore, the Fuzzy Analytic Hierarchy Process (FAHP) and Fuzzy Axiomatic Design (FAD) algorithms are integrated into the SoQ frame in order to involve quantitative outcomes into the shipping investment decisions. The SoQ is performed over a set of periodical data and recent trends of the principal crude oil tanker markets such as Very Large Crude Oil Carriers (VLCCs), Suezmaxes, and Aframaxes in order to ensure the illustrative results. As an effective investment tool, the proposed SoQ model is expected to provide invaluable decision aid for the relevant shipping executives.
Monitoring and predicting dynamic parameters of the maritime transportation industry such as freight rates, ship sale and purchase prices, new building trends, bunker prices, and scrapping rates (Tsolakis, Cridland, & Haralambides, 2003) have enforced the executives in shipping business. Integration of innovative technologies (Lee et al., 2006), effective communication (Jenssen & Randoy, 2006), and improving managerial skills (Celik and Er, 2006a, Hork, 2004 and Panayides, 2006) are the key aspects to ensure customer satisfaction in the market. Especially, the investment decision and timing (Alizadeh & Nomikos, 2007) are the potential issues to manage the market competitiveness in maritime transportation industry. The investment decisions in shipping require assessing the high level of up-to-date information towards the technical and commercial variables of maritime transportation market. At this point, diversity of the different market options (i.e. bulk carrier market, crude oil market, container market, gas & chemical markets) increases the complexity of the shipping investment problem. Moreover, additional assessments need to be performed over critical issues such as return on investment (Cullinane, 1995), catastrophic risks (Celik & Er, 2006b), and oil crises (Bergin & Glick, 2007) to ensure the feasibility of the shipping enterprises. However, the customer satisfaction levels in the market can systematically be linked to the route of new investment decisions. This idea reduces the additional efforts in shipping investment decisions and it provides the reflection of the overall market trends for the relevant decision-makers. In maritime transportation industry, the charterers are recognized as the potential customers of the ship management companies who operate the merchant fleets on behalf of the ship owners. In this way, the ship owners and the relevant managers as potential decision-makers can shift the route of shipping investments with respect to the recent tendencies of charterers and daily statistics over the market indicators.
This paper focuses on structuring a decision aid mechanism on the basis of Quality Function Deployment (QFD) model under fuzzy environment in order to route investment decisions with respect to the customer satisfaction level of shipping charterers in crude oil tanker markets. It aims at measuring charterers’ tendencies to route the investment decisions of global ship owners. The research methodology ensures embedding the recent statistical data of different markets (i.e. Very Large Crude Oil Carriers (VLCCs), Suezmaxes, and Aframaxes) into the QFD-based decision-aid mechanism. On the other hand, the Fuzzy Analytic Hierarchy Process (FAHP) algorithm derives the relative importance of performance characteristics of each market while the Fuzzy Axiomatic Design (FAD) ensures the selection of the suitable market alternative.
The remaining parts of this paper are organized as follows: in Section 2, the theoretical background of the research methodology which also includes a literature review on the QFD applications through measuring customer satisfaction is described . In Section 3, the extension of the Fuzzy QFD model to shipping investment decisions is illustrated towards crude oil tanker markets via using the recent statistical data. Concluding remarks and proposals for further research are expressed within the last section of this paper.
The high level of managerial efforts has required for executing the shipping investment decisions in global crude oil tanker market due to the dynamic structure of maritime transportation industry. Therefore, the proposed SoQ framework overcomes the various difficulties during the initial decision process. As an effective investment decision tool, the SoQ provides the findings towards four significant points: (1) priorities of PCs of market, (2) charterers’ perceptions oriented investment decision (CPID), (3) industrial-data-oriented investment decision (DID), and (4) final investment decision. The system has a self-control option for the initial results based on periodical statistics of market dynamics for coupling with the direct measurement results over customer satisfaction levels in the different market alternatives. Therefore, the SoQ ensures the reliable and satisfactory results for the relevant shipping executives. As one of the further aspects, the SoQ can be modified in order to integrate into the existing sale and purchase procedures of shipping firms. In this study, the illustrative application of the proposed model was performed on crude oil tanker shipping markets. However, the scope of the model can be extended to the container, bulk carrier, gas, and chemical markets to redesign the SoQ framework in a wide perspective.
