IDEAS home Printed from https://ideas.repec.org/a/gam/jsusta/v16y2024i11p4427-d1400404.html
   My bibliography  Save this article

An Assessment of Container Seaport Efficiency Determinants

Author

Listed:
  • Paulo Caldas

    (CIGEST, Business and Economic School, Instituto Superior de Gestão, Av. Mal. Craveiro Lopes 2A, 1700-284 Lisbon, Portugal
    CEG-IST, Centro de Estudos em Gestão, Instituto Superior Técnico, University of Lisbon, Av. Rovisco Pais 1, 1040-001 Lisbon, Portugal
    Centre for Local Government, University of New England, Armidale, NSW 2350, Australia)

  • Maria Isabel Pedro

    (CEG-IST, Centro de Estudos em Gestão, Instituto Superior Técnico, University of Lisbon, Av. Rovisco Pais 1, 1040-001 Lisbon, Portugal)

  • Rui Cunha Marques

    (RCM2+, Research Centre for Asset Management and Systems Engineering, Lusofona University, Campo Grande 376, 1749-024 Lisboa, Portugal)

Abstract

Maritime transport plays a pivotal role in the global economy, facilitating the majority of international trade and serving as a cornerstone for efficient and expansive logistics networks. The proliferation of economic globalisation has resulted in a significant upsurge in intercontinental transactions, thereby fostering the utilisation of ports and shipping enterprises as cost-effective and expeditious means of accessing a wide range of destinations in Europe, Asia, Africa, and North America. The objective of this study is to evaluate the significance of five exogenous variables, namely, GDP per capita, water depth, commodity-type diversification, management model, and European directional division, in relation to the performance of seaports. Measuring the impact of exogenous variables in seaport performance is crucial for understanding how external factors influence efficiency, enabling informed decision-making, and facilitating the development of targeted policies for sustainable and effective port operations. This assessment will be conducted using robust benchmarking analysis methods, specifically the nonparametric order-α model. Several findings suggest that there is a negative relationship between GDP per capita and the performance of seaports when GDP per capita reaches very high levels. However, seaports located in regions with lower GDP per capita tend to exhibit superior performance. The inefficiency of southern seaports is evident, whereas seaports located in Central/Eastern Europe exhibit superior performance, irrespective of their model orientation. These findings underscore the importance of considering economic context and regional factors in understanding seaport performance and highlight potential areas for improvement in southern seaports.

Suggested Citation

  • Paulo Caldas & Maria Isabel Pedro & Rui Cunha Marques, 2024. "An Assessment of Container Seaport Efficiency Determinants," Sustainability, MDPI, vol. 16(11), pages 1-39, May.
  • Handle: RePEc:gam:jsusta:v:16:y:2024:i:11:p:4427-:d:1400404
    as

    Download full text from publisher

    File URL: https://www.mdpi.com/2071-1050/16/11/4427/pdf
    Download Restriction: no

    File URL: https://www.mdpi.com/2071-1050/16/11/4427/
    Download Restriction: no
    ---><---

    References listed on IDEAS

    as
    1. Simar, Léopold & Vanhems, Anne, 2012. "Probabilistic characterization of directional distances and their robust versions," Journal of Econometrics, Elsevier, vol. 166(2), pages 342-354.
    2. Trujillo, L. & Tovar, B., 2007. "The European port industry: an analysis of its economic efficiency," Working Papers 07/05, Department of Economics, City University London.
    3. Ferreira, Diogo Cunha & Marques, Rui Cunha & Pedro, Maria Isabel, 2016. "Comparing efficiency of holding business model and individual management model of airports," Journal of Air Transport Management, Elsevier, vol. 57(C), pages 168-183.
    4. Aragon, Y. & Daouia, A. & Thomas-Agnan, C., 2005. "Nonparametric Frontier Estimation: A Conditional Quantile-Based Approach," Econometric Theory, Cambridge University Press, vol. 21(2), pages 358-389, April.
    5. Leopold Simar & Valentin Zelenyuk, 2006. "On Testing Equality of Distributions of Technical Efficiency Scores," Econometric Reviews, Taylor & Francis Journals, vol. 25(4), pages 497-522.
    6. Talley, Wayne K. & Ng, ManWo & Marsillac, Erika, 2014. "Port service chains and port performance evaluation," Transportation Research Part E: Logistics and Transportation Review, Elsevier, vol. 69(C), pages 236-247.
    7. Ferreira, D.C. & Marques, R.C. & Nunes, A.M., 2018. "Economies of scope in the health sector: The case of Portuguese hospitals," European Journal of Operational Research, Elsevier, vol. 266(2), pages 716-735.
    8. Carlos Pestana Barros, 2006. "A Benchmark Analysis of Italian Seaports Using Data Envelopment Analysis," Maritime Economics & Logistics, Palgrave Macmillan;International Association of Maritime Economists (IAME), vol. 8(4), pages 347-365, December.
    9. Tongzon, Jose, 2001. "Efficiency measurement of selected Australian and other international ports using data envelopment analysis," Transportation Research Part A: Policy and Practice, Elsevier, vol. 35(2), pages 107-122, February.
    10. Daraio, Cinzia & Simar, Léopold, 2014. "Directional distances and their robust versions: Computational and testing issues," European Journal of Operational Research, Elsevier, vol. 237(1), pages 358-369.
    11. Wanke, Peter F., 2013. "Physical infrastructure and flight consolidation efficiency drivers in Brazilian airports: A two-stage network-DEA approach," Journal of Air Transport Management, Elsevier, vol. 31(C), pages 1-5.
    12. Antonio Giuffrida & Hugh Gravelle, 2001. "Measuring performance in primary care: econometric analysis and DEA," Applied Economics, Taylor & Francis Journals, vol. 33(2), pages 163-175.
    13. Badin, Luiza & Daraio, Cinzia & Simar, Léopold, 2010. "Optimal bandwidth selection for conditional efficiency measures: A data-driven approach," European Journal of Operational Research, Elsevier, vol. 201(2), pages 633-640, March.
    14. Lam, Jasmine Siu Lee & Gu, Yimiao, 2016. "A market-oriented approach for intermodal network optimisation meeting cost, time and environmental requirements," International Journal of Production Economics, Elsevier, vol. 171(P2), pages 266-274.
    15. K. X. Li & Jin Cheng, 2007. "The determinants of maritime policy," Maritime Policy & Management, Taylor & Francis Journals, vol. 34(6), pages 521-533, December.
    16. Cinzia Daraio & Léopold Simar, 2005. "Introducing Environmental Variables in Nonparametric Frontier Models: a Probabilistic Approach," Journal of Productivity Analysis, Springer, vol. 24(1), pages 93-121, September.
    17. Pablo Coto-Millan & Jose Banos-Pino & Ana Rodriguez-Alvarez, 2000. "Economic efficiency in Spanish ports: some empirical evidence," Maritime Policy & Management, Taylor & Francis Journals, vol. 27(2), pages 169-174, April.
    18. Wanke, Peter F., 2013. "Physical infrastructure and shipment consolidation efficiency drivers in Brazilian ports: A two-stage network-DEA approach," Transport Policy, Elsevier, vol. 29(C), pages 145-153.
    19. Chang, Víctor & Tovar, Beatriz, 2014. "Drivers explaining the inefficiency of Peruvian and Chilean ports terminals," Transportation Research Part E: Logistics and Transportation Review, Elsevier, vol. 67(C), pages 190-203.
    20. Cullinane, Kevin & Wang, Teng-Fei & Song, Dong-Wook & Ji, Ping, 2006. "The technical efficiency of container ports: Comparing data envelopment analysis and stochastic frontier analysis," Transportation Research Part A: Policy and Practice, Elsevier, vol. 40(4), pages 354-374, May.
    21. Cazals, Catherine & Florens, Jean-Pierre & Simar, Leopold, 2002. "Nonparametric frontier estimation: a robust approach," Journal of Econometrics, Elsevier, vol. 106(1), pages 1-25, January.
    22. Lourdes Trujillo & Beatriz Tovar, 2007. "The European Port Industry: An Analysis of its Economic Efficiency," Maritime Economics & Logistics, Palgrave Macmillan;International Association of Maritime Economists (IAME), vol. 9(2), pages 148-171, June.
    23. Teng-Fei Wang & Kevin Cullinane, 2006. "The Efficiency of European Container Terminals and Implications for Supply Chain Management," Maritime Economics & Logistics, Palgrave Macmillan;International Association of Maritime Economists (IAME), vol. 8(1), pages 82-99, March.
    24. R. G. Chambers & Y. Chung & R. Färe, 1998. "Profit, Directional Distance Functions, and Nerlovian Efficiency," Journal of Optimization Theory and Applications, Springer, vol. 98(2), pages 351-364, August.
    25. Tongzon, Jose & Heng, Wu, 2005. "Port privatization, efficiency and competitiveness: Some empirical evidence from container ports (terminals)," Transportation Research Part A: Policy and Practice, Elsevier, vol. 39(5), pages 405-424, June.
    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. Ferreira, Diogo Cunha & Marques, Rui Cunha & Pedro, Maria Isabel, 2018. "Explanatory variables driving the technical efficiency of European seaports: An order-α approach dealing with imperfect knowledge," Transportation Research Part E: Logistics and Transportation Review, Elsevier, vol. 119(C), pages 41-62.
    2. Cinzia Daraio & Léopold Simar & Paul W. Wilson, 2020. "Fast and efficient computation of directional distance estimators," Annals of Operations Research, Springer, vol. 288(2), pages 805-835, May.
    3. Odeck, James & Schøyen, Halvor, 2020. "Productivity and convergence in Norwegian container seaports: An SFA-based Malmquist productivity index approach," Transportation Research Part A: Policy and Practice, Elsevier, vol. 137(C), pages 222-239.
    4. Figueiredo De Oliveira, Gabriel & Cariou, Pierre, 2015. "The impact of competition on container port (in)efficiency," Transportation Research Part A: Policy and Practice, Elsevier, vol. 78(C), pages 124-133.
    5. Odeck, James & Bråthen, Svein, 2012. "A meta-analysis of DEA and SFA studies of the technical efficiency of seaports: A comparison of fixed and random-effects regression models," Transportation Research Part A: Policy and Practice, Elsevier, vol. 46(10), pages 1574-1585.
    6. Léopold Simar & Paul W. Wilson, 2015. "Statistical Approaches for Non-parametric Frontier Models: A Guided Tour," International Statistical Review, International Statistical Institute, vol. 83(1), pages 77-110, April.
    7. Amir Moradi-Motlagh & Ali Emrouznejad, 2022. "The origins and development of statistical approaches in non-parametric frontier models: a survey of the first two decades of scholarly literature (1998–2020)," Annals of Operations Research, Springer, vol. 318(1), pages 713-741, November.
    8. Hong-Oanh Nguyen & Hong-Van Nguyen & Young-Tae Chang & Anthony T. H. Chin & Jose Tongzon, 2016. "Measuring port efficiency using bootstrapped DEA: the case of Vietnamese ports," Maritime Policy & Management, Taylor & Francis Journals, vol. 43(5), pages 644-659, July.
    9. Tovar, Beatriz & Wall, Alan, 2015. "Can ports increase traffic while reducing inputs? Technical efficiency of Spanish Port Authorities using a directional distance function approach," Transportation Research Part A: Policy and Practice, Elsevier, vol. 71(C), pages 128-140.
    10. 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.
    11. Shilin Ye & Xinhua Qi & Yecheng Xu, 2020. "Analyzing the relative efficiency of China’s Yangtze River port system," Maritime Economics & Logistics, Palgrave Macmillan;International Association of Maritime Economists (IAME), vol. 22(4), pages 640-660, December.
    12. Güner, Samet, 2015. "Investigating infrastructure, superstructure, operating and financial efficiency in the management of Turkish seaports using data envelopment analysis," Transport Policy, Elsevier, vol. 40(C), pages 36-48.
    13. Rabeb KAMMOUN & Souhir ABBES, 2020. "The technical efficiency of Tunisian ports: Comparing data envelopment analysis and stochastic frontier analysis scores," Romanian Journal of Economics, Institute of National Economy, vol. 51(2(60)), pages 83-102, December.
    14. Tzeremes, Nickolaos G., 2015. "Efficiency dynamics in Indian banking: A conditional directional distance approach," European Journal of Operational Research, Elsevier, vol. 240(3), pages 807-818.
    15. George E. Halkos & Shunsuke Managi, 2017. "Measuring the Effect of Economic Growth on Countries’ Environmental Efficiency: A Conditional Directional Distance Function Approach," Environmental & Resource Economics, Springer;European Association of Environmental and Resource Economists, vol. 68(3), pages 753-775, November.
    16. Kevork, Ilias S. & Pange, Jenny & Tzeremes, Panayiotis & Tzeremes, Nickolaos G., 2017. "Estimating Malmquist productivity indexes using probabilistic directional distances: An application to the European banking sector," European Journal of Operational Research, Elsevier, vol. 261(3), pages 1125-1140.
    17. Fall, François Seck & Tchakoute Tchuigoua, Hubert & Vanhems, Anne & Simar, Léopold, 2022. "Investigating the unobserved heterogeneity effect on microfinance social efficiency," LIDAM Discussion Papers ISBA 2022010, Université catholique de Louvain, Institute of Statistics, Biostatistics and Actuarial Sciences (ISBA).
    18. 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).
    19. Renata Machado de Andrade & Suhyung Lee & Paul Tae-Woo Lee & Oh Kyoung Kwon & Hye Min Chung, 2019. "Port Efficiency Incorporating Service Measurement Variables by the BiO-MCDEA: Brazilian Case," Sustainability, MDPI, vol. 11(16), pages 1-18, August.
    20. Simar, Léopold & Vanhems, Anne, 2012. "Probabilistic characterization of directional distances and their robust versions," Journal of Econometrics, Elsevier, vol. 166(2), pages 342-354.

    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:gam:jsusta:v:16:y:2024:i:11:p:4427-:d:1400404. See general information about how to correct material in RePEc.

    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: MDPI Indexing Manager (email available below). General contact details of provider: https://www.mdpi.com .

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

    IDEAS is a RePEc service. RePEc uses bibliographic data supplied by the respective publishers.