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An application of Fuzzy Quality Function Deployment to bunkering services

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Języki publikacji
EN
Abstrakty
EN
Bunkering is very important for the maritime industry because of the need for continuity of trade, its relation to the energy industry and its great economic value. Today, the volume of the world’s bunkering market is around 350 million tons annually. Although there are about 400 major bunkering ports in the world, most of the demand is concentrated in a few strategic ports: when comparing strategic regions of the world, Istanbul has a very small share. With this in mind, this paper aims to demonstrate the current situation of Istanbul and to improve service quality using Fuzzy Quality Function Deployment. Our results show that the criteria which customers look for, in order of importance, are: supply waiting time; bunker quality; usage and availability of barges; duration of bunkering operation; and bunker price and price competitiveness. The steps to be taken to improve service quality are determined as: increase storage facilities and capacities; create a structure that can provide 24/7 bunker supply; and increase importance of bunkering in port infrastructure and management in Turkey, to improve service quality and increase their fuel sales volume.
Rocznik
Strony
19--27
Opis fizyczny
Bibliogr. 24 poz., rys., tab.
Twórcy
autor
  • Dokuz Eylül University, Maritime Faculty Department of Maritime Transportation Engineering 35160 Buca-Izmir, Turkey
autor
  • Dokuz Eylül University, Maritime Faculty Department of Maritime Transportation Engineering 35160 Buca-Izmir, Turkey
Bibliografia
  • 1. Acosta, M., Coronado, D. & Cerban, M.D.M. (2011) Bunkering competition and competitiveness at the ports of the Gibraltar Strait. Journal of Transport Geography 19, 4, pp. 911–916. doi: 10.1016/j.jtrangeo.2010.11.008.
  • 2. Akao, Y. (1990) Quality Function Deployment Integrating Customer Requirement into Product Design. Cambridge: Productivity Press.
  • 3. Akbaba, A. (2005) The quality function deployment (QFD) approach in customer focused service production: an application study for hospitality industry. Anatolia: Turizm Araştırma Dergisi 1, 1, pp. 59–81 (in Turkish).
  • 4. Akman, G. & Özcan, B. (2011) A fuzzy quality function deployment (QFD) approach to determine customer needs for driving mirror. İstanbul Ticaret Üniversitesi Fen Bilimleri Dergisi 10, 19, pp. 1–21.
  • 5. Boutsikas, A. (2003) The bunkering industry and its effect on shipping tanker operations. MSc Thesis, Massachusetts Institute of Technology, Cambridge.
  • 6. Çelikyilmaz, A. & Türkşen, I.B. (2009) Modeling Uncertainty with Fuzzy Logic with Recent Theory and Applications. Berlin: Springer.
  • 7. Chan, L.K. & Wu, M.L. (2002) Quality Function Deployment: A literature review. European Journal of Operational Research 143, 3, pp. 463–497. doi: 10.1016/S0377- 2217(02)00178-9.
  • 8. Chang, Y.C. & Chen, C.C. (2006) Knowledge-based simulation of bunkering services in the Port of Kaohsiung. Civil Engineering and Environmental Systems 23, 1, pp. 21–34. doi: 10.1080/10286600600585625.
  • 9. Cohen, L. (1995) Quality Function Deployment: How to Make QFD Work for You. Massachusetts: Addison-Wesley Longman, Inc.
  • 10. Draffin, N. (2008) Introduction to Bunkering. Oxford: Petrospot.
  • 11. Draffin, N. (2010) Introduction to Bunker Operations. Oxford: Petrospot.
  • 12. Draffin, N. (2011) Commercial Practise in Bunkering. Oxford: Petrospot.
  • 13. DTO (2015) Gemi ikmal hizmetleri. [Online] Available from: http://www.denizticaretodasi.org.tr/Shared%20Documents/Deniz%20Ticareti%20Dergisi/eksayi_subat_15.pdf. [Accessed: February 12, 2017].
  • 14. Dupre, A. (2010) An Introduction to Bunker Credit Risk. Oxford: Petrospot.
  • 15. Ficalora, J.P. & Cohen, L. (2009) Quality Function Deployment and Six Sigma: A QFD Handbook. Indiana: Prentice Hall.
  • 16. Jang, J.S.R., Sun, T.C. & Mizutani, E. (1997) Neuro-fuzzy and Soft Computing: A Computational Approach to Learning and Machine Intelligence. New Jersey: Prentice-Hall, Inc.
  • 17. Lam, J.S.L., Chen, D., Cheng, F. & Wong, K. (2011) Assessment of the competitiveness of ports as bunkering hubs: Empirical studies on Singapore and Shanghai. Transportation Journal 50, 2, pp. 176–203. doi: 10.5325/transportationj.50.2.0176.
  • 18. MPA (2017) Singapore’s 2016 maritime performance. [Online] Available from: http://www.mpa.gov.sg/web/portal/ home/media-centre/news-releases/detail/05460688-fe49- 42e7-9740-4ce88b157b46. [Accessed: 18th June 2017]
  • 19. OPEC (2015) World Oil Outlook 2015. [Online] Available from: http://www.opec.org/opec_web/static_files_project/ media/downloads/publications/WOO%202015.pdf. [Accessed: April 06, 2017]
  • 20. Port of Rotterdam (2017) Fewer bunkers in Rotterdam in 2016. [Online] Available from: https://www.portofrotterdam.com/en/news-and-press-releases/fewer-bunkers-in-rotterdam-in-2016. [Accessed: June 17, 2017]
  • 21. Van Leekwijck, W. & Kerre, E.E. (1999) Defuzzification: criteria and classification. Fuzzy sets and systems 108, 2, pp. 159–178.
  • 22. Vilhelmsen, C., Lusby, R.M. & Larsen, J. (2013) Routing and scheduling in tramp shipping-integrating bunker optimization: Technical report. Copenhagen: Department of Management Engineering, Technical University of Denmark.
  • 23. Wang, Y., Yeo, G.T. & Ng, A.K. (2014) Choosing optimal bunkering ports for liner shipping companies: A hybrid Fuzzy-Delphi–TOPSIS approach. Transport Policy 35, pp. 358–365. doi: 10.1016/j.tranpol.2014.04.009.
  • 24. Yao, Z., Ng, S.H. & Lee, L.H. (2012) A Study on bunker fuel management for the shipping liner services. Computers & Operations Research 39, 5, pp. 1160–1172. doi: 10.1016/j.cor.2011.07.012.
Uwagi
PL
Opracowanie rekordu w ramach umowy 509/P-DUN/2018 ze środków MNiSW przeznaczonych na działalność upowszechniającą naukę (2018).
Typ dokumentu
Bibliografia
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bwmeta1.element.baztech-39c3dcb5-c326-4290-ad4f-084586b8e3cc
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