IDEAS home Printed from https://ideas.repec.org/a/lrk/eeaart/36_3_6.html
   My bibliography  Save this article

Clasificación de los puertos españoles atendiendo a su tipología de tráfico e infraestructuras/Classification of Spanish Ports According to Their Type of Traffic and Infrastructures

Author

Listed:
  • CORTÉS RODRÍGUEZ, CONCEPCIÓN

    (Universidad de Huelva, Facultad de Ciencias Empresariales y Turismo, Campus de la Merced, Plaza de la Merced, 11, 21002 Huelva, España.)

  • CORDÓN LAGARES, ENCARNACIÓN

    (Universidad de Huelva, Facultad de Ciencias Empresariales, Campus de la Merced, Plaza de la Merced, 21071 Huelva, España)

  • ANA GONZÁLEZ GALÁN

    (Universidad de Huelva, Facultad de Ciencias Empresariales y Turismo, Campus de la Merced, Plaza de la Merced, 11, 21002 Huelva, España.)

  • GARCÍA DEL HOYO, JUAN JOSÉ

    (DUniversidad de Huelva, Facultad de Ciencias Empresariales y Turismo, Campus de la Merced, Plaza de la Merced, 11, 21002 Huelva, España.)

Abstract

El principal objetivo de este trabajo es la clasificación de los puertos españoles de interés general utilizando diversos indicadores que caracterizan la actividad portuaria referente al transporte de mercancías y pasajeros e indicadores de infraestructuras y servicios portuarios. La información ha sido obtenida principalmente a partir de las estadísticas de Puertos del Estado y de las memorias anuales de las Autoridades Portuarias. Mediante el uso de diferentes técnicas del análisis multivariante, se analiza un conjunto de variables cuantitativas y cualitativas. El Análisis Factorial de Componentes Principales ha permitido reducir el número de variables en cuatro factores, y con el Análisis de Conglomerados se obtuvo la clasificación de los puertos. Como conclusiones relevantes del análisis, cabe resaltar la existencia de tres grupos de puertos de titularidad estatal claramente diferenciados en función de su nivel de especialización en el tráfico portuario e infraestructuras, y otro conjunto de puertos que destacan por el tráfico de pasajeros de cruceros. ABSTRACT The main purpose of this paper is the classification of the Spanish ports of general interest using a set of indicators related to port activity such transport of goods and passengers, infrastructures, and port services. The information has been mainly obtained from the State Port statistics and the annual reports of Port Authorities. We analyse a set of quantitative and qualitative variables through different multivariate analysis techniques. Principal Components Analysis allowed us to reduce the number of variables in four factors, and the classification of the ports has been carried out through Cluster Analysis. The main finding of this paper reveal the existence of clearly different three groups of the state ports depending on their level of specialization in port traffic port and infrastructures, and other ports group that stand out for their cruise passenger traffic.

Suggested Citation

  • Cortés Rodríguez, Concepción & Cordón Lagares, Encarnación & Ana González Galán & García Del Hoyo, Juan José, 2018. "Clasificación de los puertos españoles atendiendo a su tipología de tráfico e infraestructuras/Classification of Spanish Ports According to Their Type of Traffic and Infrastructures," Estudios de Economia Aplicada, Estudios de Economia Aplicada, vol. 36, pages 765-788, Septiembr.
  • Handle: RePEc:lrk:eeaart:36_3_6
    as

    Download full text from publisher

    File URL: http://www.revista-eea.net
    Download Restriction: Access to full text is restricted to subscribers.
    ---><---

    As the access to this document is restricted, you may want to search for a different version of it.

    References listed on IDEAS

    as
    1. Henry Kaiser, 1958. "The varimax criterion for analytic rotation in factor analysis," Psychometrika, Springer;The Psychometric Society, vol. 23(3), pages 187-200, September.
    2. María Manuela González & Lourdes Trujillo, 2009. "Efficiency Measurement in the Port Industry: A Survey of the Empirical Evidence," Journal of Transport Economics and Policy, University of Bath, vol. 43(2), pages 157-192, May.
    3. Castillo-Manzano, José I. & Fageda, Xavier & Gonzalez-Laxe, Fernando, 2014. "An analysis of the determinants of cruise traffic: An empirical application to the Spanish port system," Transportation Research Part E: Logistics and Transportation Review, Elsevier, vol. 66(C), pages 115-125.
    Full references (including those not matched with items on IDEAS)

    Most related items

    These are the items that most often cite the same works as this one and are cited by the same works as this one.
    1. Bonhomme, Stphane & Robin, Jean-Marc, 2009. "Consistent noisy independent component analysis," Journal of Econometrics, Elsevier, vol. 149(1), pages 12-25, April.
    2. Fernando Castelló-Sirvent & Pablo Pinazo-Dallenbach, 2021. "Corruption Shock in Mexico: fsQCA Analysis of Entrepreneurial Intention in University Students," Mathematics, MDPI, vol. 9(14), pages 1-31, July.
    3. Matkovskyy, Roman, 2013. "To the Problem of Financial Safety Estimation: the Index of Financial Safety of Turkey," MPRA Paper 47673, University Library of Munich, Germany.
    4. Jha, Raghbendra & Murthy, K. V. Bhanu, 2003. "An inverse global environmental Kuznets curve," Journal of Comparative Economics, Elsevier, vol. 31(2), pages 352-368, June.
    5. Rodríguez-Fuentes, Carlos Javier & Hernández-López, Montserrat, 1997. "Análisis de diferencias estructurales interregionales determinantes en el impacto de la política monetaria," Estudios de Economia Aplicada, Estudios de Economia Aplicada, vol. 7, pages 141-157, Junio.
    6. Ivaldi, Enrico, 2013. "Proposal of a country risk index based on a factorial analysis - Una proposta di indice di rischio paese basato sull’analisi fattoriale: una applicazione ai paesi del sud del Mediterraneo e ai paesi d," Economia Internazionale / International Economics, Camera di Commercio Industria Artigianato Agricoltura di Genova, vol. 66(2), pages 231-249.
    7. Vesselina Dimitrova & Georgi Marinov & Lino Manosperta, 2019. "Developing Low-Carbon Tourism In Puglia: Case Study Of I. Archeo.S Project," Economic Archive, D. A. Tsenov Academy of Economics, Svishtov, Bulgaria, issue 2 Year 20, pages 16-32.
    8. Quintano, Claudio & Mazzocchi, Paolo & Rocca, Antonella, 2021. "Evaluation of the eco-efficiency of territorial districts with seaport economic activities," Utilities Policy, Elsevier, vol. 71(C).
    9. Noor Nahar Begum & Sarabia Rahman, 2016. "An Analytical Study on Investors¡¯ Preference towards Mutual Fund Investment: A Study in Dhaka City, Bangladesh," International Journal of Economics and Finance, Canadian Center of Science and Education, vol. 8(10), pages 184-191, October.
    10. Coppola, A. & Ianuario, S. & Chinnici, G. & Di Vita, G. & Pappalardo, G. & D'Amico, D., 2018. "Endogenous and Exogenous Determinants of Agricultural Productivity: What Is the Most Relevant for the Competitiveness of the Italian Agricultural Systems?," AGRIS on-line Papers in Economics and Informatics, Czech University of Life Sciences Prague, Faculty of Economics and Management, vol. 10(2).
    11. De Nicola, Arianna & Gitto, Simone & Mancuso, Paolo, 2013. "Airport quality and productivity changes: A Malmquist index decomposition assessment," Transportation Research Part E: Logistics and Transportation Review, Elsevier, vol. 58(C), pages 67-75.
    12. Henk Kiers, 1994. "Simplimax: Oblique rotation to an optimal target with simple structure," Psychometrika, Springer;The Psychometric Society, vol. 59(4), pages 567-579, December.
    13. Thomas Despois & Catherine Doz, 2022. "Identifying and interpreting the factors in factor models via sparsity : Different approaches," Working Papers halshs-03626503, HAL.
    14. Edyta Puskarczyk, 2020. "Application of Multivariate Statistical Methods and Artificial Neural Network for Facies Analysis from Well Logs Data: an Example of Miocene Deposits," Energies, MDPI, vol. 13(7), pages 1-18, March.
    15. Iversen, Sara V. & Naomi, van der Velden & Convery, Ian & Mansfield, Lois & Holt, Claire D.S., 2022. "Why understanding stakeholder perspectives and emotions is important in upland woodland creation – A case study from Cumbria, UK," Land Use Policy, Elsevier, vol. 114(C).
    16. Angela Stefania Bergantino & Enrico Musso, 2011. "A Multi-step Approach to Model the Relative Efficiency of European Ports: The Role of Regulation and Other Non-discretionary Factors," Chapters, in: Kevin Cullinane (ed.), International Handbook of Maritime Economics, chapter 18, Edward Elgar Publishing.
    17. Xia Vivian Zhou & Kimberly L. Jensen & James A. Larson & Burton C. English, 2021. "Farmer Interest in and Willingness to Grow Pennycress as an Energy Feedstock," Energies, MDPI, vol. 14(8), pages 1-16, April.
    18. Matkovskyy, Roman & Bouraoui, Taoufik & Hammami, Helmi, 2016. "Analysing the financial strength of Tunisia: An approach to estimate an index of financial safety," Research in International Business and Finance, Elsevier, vol. 38(C), pages 485-493.
    19. Chuanbo Shen & Solomon Asante-Okyere & Yao Yevenyo Ziggah & Liang Wang & Xiangfeng Zhu, 2019. "Group Method of Data Handling (GMDH) Lithology Identification Based on Wavelet Analysis and Dimensionality Reduction as Well Log Data Pre-Processing Techniques," Energies, MDPI, vol. 12(8), pages 1-16, April.
    20. Pablo Coto-Millán & Pedro Casares-Hontañón & Rubén Sainz González & Ingrid Mateo Mantecón & Manuel Agüeros & Alfonso Badiola & Juan Castanedo & Miguel Ángel Pesquera, 2016. "Regulation, competition, crisis and technical efficiency of companies operating in Spanish ports (2002–2011)," Maritime Economics & Logistics, Palgrave Macmillan;International Association of Maritime Economists (IAME), vol. 18(3), pages 282-294, September.

    More about this item

    Keywords

    Análisis multivariante; Puertos; Tráfico; Infraestructuras ; Multivariate analysis; Ports; Traffic; Infrastructures.;
    All these keywords.

    JEL classification:

    • C38 - Mathematical and Quantitative Methods - - Multiple or Simultaneous Equation Models; Multiple Variables - - - Classification Methdos; Cluster Analysis; Principal Components; Factor Analysis
    • L91 - Industrial Organization - - Industry Studies: Transportation and Utilities - - - Transportation: General

    Statistics

    Access and download statistics

    Corrections

    All material on this site has been provided by the respective publishers and authors. You can help correct errors and omissions. When requesting a correction, please mention this item's handle: RePEc:lrk:eeaart:36_3_6. See general information about how to correct material in RePEc.

    For technical questions regarding this item, or to correct its authors, title, abstract, bibliographic or download information, contact: . General contact details of provider: https://edirc.repec.org/data/fcvldes.html .

    If you have authored this item and are not yet registered with RePEc, we encourage you to do it here. This allows to link your profile to this item. It also allows you to accept potential citations to this item that we are uncertain about.

    If CitEc recognized a bibliographic reference but did not link an item in RePEc to it, you can help with this form .

    If you know of missing items citing this one, you can help us creating those links by adding the relevant references in the same way as above, for each refering item. If you are a registered author of this item, you may also want to check the "citations" tab in your RePEc Author Service profile, as there may be some citations waiting for confirmation.

    For technical questions regarding this item, or to correct its authors, title, abstract, bibliographic or download information, contact: Miguel Angel Sanchez Granero (email available below). General contact details of provider: https://edirc.repec.org/data/fcvldes.html .

    Please note that corrections may take a couple of weeks to filter through the various RePEc services.

    IDEAS is a RePEc service hosted by the Research Division of the Federal Reserve Bank of St. Louis . RePEc uses bibliographic data supplied by the respective publishers.