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A fuzzy AHP classification of container terminals

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Maritime Economics & Logistics Aims and scope

Abstract

This article proposes a methodology for the classification of container terminals aiming to identify groups of terminals with similar management characteristics. Based on physical and terminal operations data and the subjective judgment of experts in port management, we show that it is possible to identify the main factors affecting the management of container terminals and produce a classification of these facilities, allowing determination of their strengths, weaknesses, and place within their port system and in relation to their competitors. The methodology is based on the fuzzy analytic hierarchy process (F-AHP). As a case study to validate the procedure, the Spanish port system is selected, and the results are compared with other classification methods not including subjectivity criteria, namely cluster analysis. By assigning more weight to expert judgments, results differ and become more trustworthy, since expert knowledge can go beyond simple variables such as TEUs moved or number of available cranes.

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References

  • Bichou, K., and R. Gray. 2005. A critical review of conventional terminology for classifying seaports. Transportation Research Part A Policy and Practice 39: 75–92.

    Article  Google Scholar 

  • Cabral, A.M.R., and F. Sousa Ramos. 2014. Cluster analysis of the competitiveness of container ports in Brazil. Transportation Research Part A Policy and Practice 69: 423–431.

    Article  Google Scholar 

  • Chang, D.-Y. 1996. Applications of the extent analysis method on Fuzzy AHP. European Journal of Operational Research 95: 649–655.

    Article  Google Scholar 

  • Chou, C.-C., and K.-W. Yu. 2013. Application of a new hybrid Fuzzy AHP Model to the location choice. Mathematical Problems in Engineering. https://doi.org/10.1155/2013/592138.

    Article  Google Scholar 

  • Cullinane, K., T.-F. Wang, D.-W. Song, and P. Ji. 2006. The technical efficiency of container ports: Comparing data envelopment analysis and stochastic frontier analysis. Transportation Research Part A Policy and Practice 40: 354–374.

    Article  Google Scholar 

  • Da Cruz, M.R.P., J.J. Ferreira, and S.G. Azevedo. 2013. Key factors of seaport competitiveness based on the stakeholder perspective: An analytic hierarchy process (AHP) model. Maritime Economics & Logistics 15: 416–443.

    Article  Google Scholar 

  • De Koster, M.B.M., B.M. Balk, and W.T.I. Van Nus. 2009. On using DEA for benchmarking container terminals. International Journal of Operations & Production Management 29: 1140–1155.

    Article  Google Scholar 

  • Demirel, T., N.Ç. Demirel, and C. Kahraman. 2008. Fuzzy analytic hierarchy process and its application. In Fuzzy multi-criteria decision making, ed. C. Kahraman, 53–83. Boston: Springer.

    Chapter  Google Scholar 

  • Di Francesco, M., A. Manca, S. Zanda, and P. Zuddas. 2016. Planning and optimising manpower management in a transshipment container terminal. European Journal of Industrial Engineering 10: 777–793.

    Article  Google Scholar 

  • Dong, Q., and T.L. Saaty. 2014. An analytic hierarchy process model of group consensus. Journal of Systems Science and Systems Engineering 23: 362–374.

    Article  Google Scholar 

  • Ducruet, C., S. Cuyala, and A. El Hosni. 2018. Maritime networks as systems of cities: The long-term interdependencies between global shipping flows and urban development (1890–2010). Journal of Transport Geography 66: 340–355.

    Article  Google Scholar 

  • Estrada Llaquet, J. L., 2007. Mejora de la competitividad de un puerto por medio de un nuevo modelo de gestión de la estrategia aplicando el cuadro de mando integral. Doctoral thesis.

  • Gianfranco, F., P. Claudia, S. Patrizia, and F. Paolo. 2014. Port cooperation policies in the Mediterranean Basin: An experimental approach using cluster analysis. Transportation Research Procedia 3: 700–709.

    Article  Google Scholar 

  • Goepel, K.D. 2013. Implementing the analytic hierarchy process as a standard method for multi-criteria decision making in corporate enterprises—A new AHP excel template with multiple inputs. Conference Paper. https://doi.org/10.13033/isahp.y2013.047.

    Article  Google Scholar 

  • Guy, E., and B. Urli. 2006. Port selection and multicriteria analysis: An application to the Montreal–New York alternative. Maritime Economics & Logistics 8: 169–186.

    Article  Google Scholar 

  • Hinkka, V., J. Eckhardt, A. Permala, and H. Mantsinen. 2016. Changing training needs of port workers due to future trends. Transportation Research Procedia 14: 4085–4094.

    Article  Google Scholar 

  • Hothorn, T., and B.S. Everitt. 2014. A handbook of statistical analyses using R. Boca Raton: Chapman and Hall/CRC.

    Book  Google Scholar 

  • Jackson, M.C. 2007. Systems approaches to management. Boston: Springer.

    Google Scholar 

  • Kubler, S., et al. 2016. A state-of the-art survey & testbed of fuzzy AHP (FAHP) applications. Expert Systems with Applications 65: 398–422.

    Article  Google Scholar 

  • Kwong, C.-K., and H. Bai. 2003. Determining the importance weights for the customer requirements in QFD using a fuzzy AHP with an extent analysis approach. IIE Transactions 35: 619–626.

    Article  Google Scholar 

  • Lampe, H.W., and D. Hilgers. 2015. Trajectories of efficiency measurement: A bibliometric analysis of DEA and SFA. European Journal of Operational Research 240: 1–21.

    Article  Google Scholar 

  • Levinson, M. 2016. The box: How the shipping container made the world smaller and the world economy bigger-with a new chapter by the author. Princeton: Princeton University Press.

    Book  Google Scholar 

  • Lirn, T.-C., H.A. Thanopoulou, and A.K.C. Beresford. 2003. Transhipment port selection and decision-making behaviour: analysing the Taiwanese case. International Journal of Logistics: Research and Applications 6: 229–244.

    Article  Google Scholar 

  • Lirn, T.C., H.A. Thanopoulou, M.J. Beynon, and A.K.C. Beresford. 2004. An application of AHP on transhipment port selection: A global perspective. Maritime Economics & Logistics 6: 70–91.

    Article  Google Scholar 

  • Lloyds List. 2018. Lloyd’s List. https://lloydslist.maritimeintelligence.informa.com/one-hundred-container-ports-2018. Accessed 18 January 2019.

  • Lu, B., and Wang, S. 2017. DEA conceptual exposition and literature review. In Container Port Production and Management, 7–17. Singapore: Springer.

  • Mardani, A., et al. 2016. Multiple criteria decision-making techniques in transportation systems: A systematic review of the state of the art literature. Transport 31: 359–385.

    Article  Google Scholar 

  • Marios, K. 2006. Strategic management, global cultural perspectives for profit and non-profit organizations. Burlington, MA: Elsevier Butterworth-Heinemann.

    Google Scholar 

  • Martín-Soberón, A.M., A. Monfort, R. Sapiña, N. Monterde, and D. Calduch. 2014. Automation in port container terminals. Procedia-Social and Behavioral Sciences 160: 195–204.

    Article  Google Scholar 

  • Milligan, G.W., and M.C. Cooper. 1988. A study of standardization of variables in cluster analysis. Journal of Classification 5: 181–204.

    Article  Google Scholar 

  • Monfort, A., et al. 2001. Terminales marı́timas de contenedores: el desarrollo de la automatización. Valencia: Fundación Instituto Portuario de Estudios y Cooperación de la Comunidad Valenciana.

    Google Scholar 

  • Orive, A.C., et al. 2016. Metodologı́a para la clasificación de los puertos mediante indicadores de explotación utilizando análisis de conglomerados. INGE CUC 12: 41–49.

    Article  Google Scholar 

  • Palacio, A., Adenso-Dı́az, B., and Lozano, S. 2015. A decision-making model to design a sustainable container depot logistic network: The case of the port of Valencia. Transport 1–12.

  • Pallis, A.A., T.K. Vitsounis, and P.W. De Langen. 2010. Port economics, policy and management: Review of an emerging research field. Transport Reviews 30: 115–161.

    Article  Google Scholar 

  • Puertos del Estado. 2017. Corporate web site. http://www.puertos.es/es-es/estadisticas/Paginas/estadistica_mensual.aspx. Accessed 3 January 2019.

  • Puertos del Estado. 2018. Observatorio Permanente de los Servicios Portuarios. http://observatorio.puertos.es/. Accessed 9 January 2019.

  • Rios, L.R., and A.C.G. Maçada. 2006. Analysing the relative efficiency of container terminals of Mercosur using DEA. Maritime Economics & Logistics 8: 331–346.

    Article  Google Scholar 

  • Rodrigue, J.-P., and T. Notteboom. 2009. The terminalization of supply chains: Reassessing the role of terminals in port/hinterland logistical relationships. Maritime Policy & Management 36: 165–183.

    Article  Google Scholar 

  • Rousseeuw, P.J., and L. Kaufman. 1990. Finding groups in data. Series in Probability & Mathematical Statistics 34 (1): 111–112.

    Google Scholar 

  • Saaty, R.W. 1987. The analytic hierarchy process—What it is and how it is used. Mathematical Modelling 9: 161–176.

    Article  Google Scholar 

  • Sauri, S., and E. Martin. 2011. Space allocating strategies for improving import yard performance at marine terminals. Transportation Research Part E Logistics and Transportation Review 47: 1038–1057.

    Article  Google Scholar 

  • Sharma, M.J., and S.J. Yu. 2009. Performance based stratification and clustering for benchmarking of container terminals. Expert Systems with Applications 36: 5016–5022.

    Article  Google Scholar 

  • Song, D.-W., S. Cheon, and C. Pire. 2015. Does size matter for port coopetition strategy? Concept, motivation and implication. International Journal of Logistics Research and Applications 18: 207–227.

    Article  Google Scholar 

  • Song, D.-W., and K.-T. Yeo. 2004. A competitive analysis of Chinese container ports using the analytic hierarchy process. Maritime Economics & Logistics 6: 34–52.

    Article  Google Scholar 

  • Thompson, A., M. Peteraf, J. Gamble, and A. Strickland. 2018. Crafting & Executing Strategy 21/e: The Quest for Competitive Advantage: Concepts and Cases. McGraw-Hill Education.

    Google Scholar 

  • Torres, A.I.Z., and O.H.P. Rendón. 2013. El transporte internacional como factor de competitividad en el comercio exterior. Journal of Economics Finance and Administrative Science 18: 108–118.

    Article  Google Scholar 

  • Tovar, B., and H. Rodrı́guez-Déniz. 2015. Classifying ports for efficiency benchmarking: A review and a frontier-based clustering approach. Transport Reviews 35: 378–400.

    Article  Google Scholar 

  • Ugboma, C., O. Ugboma, and I.C. Ogwude. 2006. An analytic hierarchy process (AHP) approach to port selection decisions—Empirical evidence from Nigerian ports. Maritime Economics & Logistics 8: 251–266.

    Article  Google Scholar 

  • UNCTAD. 2018. Review of maritime transport 2018. Geneva: UNCTAD.

  • Ung, S.T., et al. 2006. Human error assessment and management in port operations using fuzzy AHP. Marine Technology Society Journal 40: 73–86.

    Article  Google Scholar 

  • Vaidya, O.S., and S. Kumar. 2006. Analytic hierarchy process: An overview of applications. European Journal of Operational Research 169: 1–29.

    Article  Google Scholar 

  • Van Laarhoven, P.J.M., and W. Pedrycz. 1983. A fuzzy extension of Saaty’s priority theory. Fuzzy Sets and Systems 11: 229–241.

    Article  Google Scholar 

  • Vieira, G.B.B., F.J. Kliemann Neto, and F.G. Amaral. 2014. Governance, governance models and port performance: A systematic review. Transport Reviews 34: 645–662.

    Article  Google Scholar 

  • Wilks, D.S. 2011. Cluster analysis. International Geophysics 100: 603–616.

    Article  Google Scholar 

  • Wu, Z., and J. Xu. 2012. A consistency and consensus based decision support model for group decision making with multiplicative preference relations. Decision Support Systems 52: 757–767.

    Article  Google Scholar 

  • Wu, J., H. Yan, and J. Liu. 2010. DEA models for identifying sensitive performance measures in container port evaluation. Maritime Economics & Logistics 12: 215–236.

    Article  Google Scholar 

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Acknowledgements

This research was carried out with partial financial support from the Spanish Ministry of Science and the European Regional Development Fund (ERDF) grant DPI2017-85343-P. The authors would like to thank Prof. Montes Peón and all personnel at the Spanish port authorities and different container terminals who contributed to the verification of terminal data and served as experts in the survey. We are especially grateful to MEL reviewers, whose comments were very useful in improving the manuscript and are greatly appreciated.

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Correspondence to B. Adenso-Díaz.

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Adenso-Díaz, B., Álvarez, N.G. & Alba, J.A.L. A fuzzy AHP classification of container terminals. Marit Econ Logist 22, 218–238 (2020). https://doi.org/10.1057/s41278-019-00144-4

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