IDEAS home Printed from https://ideas.repec.org/a/taf/marpmg/v43y2016i3p371-385.html
   My bibliography  Save this article

Evaluation of alternative scenarios of labour flexibility for dockworkers in maritime container terminals

Author

Listed:
  • Patrizia Serra
  • Paolo Fadda
  • Gianfranco Fancello

Abstract

In the competitive environment of Container Terminals (CTs), it is essential to reduce unproductive costs and to offer efficient services to shipping companies. One of the most important factors for CT efficiency is to plan workforce optimally. However, in some CTs, strict work regulations can avoid an optimal use of the available resources leading to longer operation times and to additional related costs. This study analyses labour regulations in Italian CTs and evaluates the effects of a greater labour flexibility at the operational level by hypothesising an increase of the labour flexibility allowed within the pool of internal dockworkers. The scenario representing the current work organisation in Italian CTs is compared to five new scenarios constructed by increasing the share of daily working flexibility and introducing a new type of labour flexibility, the so-called mini-flexibility. The use of a state-of-the-art Integer Linear Programming Model for the daily assignment of human resources in CTs allows to simulate the quantitative effects of each scenario in terms of operating costs and workers undermanning. Quantitative results support the idea that an increased labour flexibility in CT activities can actually lead to a significant reduction of the operating costs and to a greater efficiency of the CT.

Suggested Citation

  • Patrizia Serra & Paolo Fadda & Gianfranco Fancello, 2016. "Evaluation of alternative scenarios of labour flexibility for dockworkers in maritime container terminals," Maritime Policy & Management, Taylor & Francis Journals, vol. 43(3), pages 371-385, April.
  • Handle: RePEc:taf:marpmg:v:43:y:2016:i:3:p:371-385
    DOI: 10.1080/03088839.2015.1043752
    as

    Download full text from publisher

    File URL: http://hdl.handle.net/10.1080/03088839.2015.1043752
    Download Restriction: Access to full text is restricted to subscribers.

    File URL: https://libkey.io/10.1080/03088839.2015.1043752?utm_source=ideas
    LibKey link: if access is restricted and if your library uses this service, LibKey will redirect you to where you can use your library subscription to access this item
    ---><---

    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. Gianfranco Fancello & Claudia Pani & Marco Pisano & Patrizia Serra & Paola Zuddas & Paolo Fadda, 2011. "Prediction of arrival times and human resources allocation for container terminal," Maritime Economics & Logistics, Palgrave Macmillan;International Association of Maritime Economists (IAME), vol. 13(2), pages 142-173, June.
    2. Theo Notteboom & Jasmine Siu Lee Lam, 2014. "Dealing with uncertainty and volatility in shipping and ports," Maritime Policy & Management, Taylor & Francis Journals, vol. 41(7), pages 611-614, December.
    Full references (including those not matched with items on IDEAS)

    Citations

    Citations are extracted by the CitEc Project, subscribe to its RSS feed for this item.
    as


    Cited by:

    1. Chargui, Kaoutar & Zouadi, Tarik & El Fallahi, Abdellah & Reghioui, Mohamed & Aouam, Tarik, 2021. "Berth and quay crane allocation and scheduling with worker performance variability and yard truck deployment in container terminals," Transportation Research Part E: Logistics and Transportation Review, Elsevier, vol. 154(C).

    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. Xueni Gou & Jasmine Siu Lee Lam, 2019. "Risk analysis of marine cargoes and major port disruptions," Maritime Economics & Logistics, Palgrave Macmillan;International Association of Maritime Economists (IAME), vol. 21(4), pages 497-523, December.
    2. Raeesi, Ramin & Sahebjamnia, Navid & Mansouri, S. Afshin, 2023. "The synergistic effect of operational research and big data analytics in greening container terminal operations: A review and future directions," European Journal of Operational Research, Elsevier, vol. 310(3), pages 943-973.
    3. Antoine Kauffmann, 2018. "Ostrom's common goods governance model : which adapation to inland waterway transport ? [Le modèle d'Ostrom de gouvernance des biens communs : quelle transposabilité au transport fluvial ?]," Post-Print hal-02429522, HAL.
    4. Sungil Kim & Heeyoung Kim & Yongro Park, 2017. "Early detection of vessel delays using combined historical and real-time information," Journal of the Operational Research Society, Palgrave Macmillan;The OR Society, vol. 68(2), pages 182-191, February.
    5. Yun Peng & Xiangda Li & Wenyuan Wang & Ke Liu & Xiao Bing & Xiangqun Song, 2018. "A Method for Determining the Required Power Capacity of an On-Shore Power System Considering Uncertainties of Arriving Ships," Sustainability, MDPI, vol. 10(12), pages 1-17, November.
    6. Itoh, Ryo & Zhang, Anming, 2023. "Shipping alliances under an unexpected shock: Effects on market volatility and social welfare," Transportation Research Part A: Policy and Practice, Elsevier, vol. 178(C).
    7. Filom, Siyavash & Amiri, Amir M. & Razavi, Saiedeh, 2022. "Applications of machine learning methods in port operations – A systematic literature review," Transportation Research Part E: Logistics and Transportation Review, Elsevier, vol. 161(C).
    8. Iris, Çağatay & Lam, Jasmine Siu Lee, 2019. "Recoverable robustness in weekly berth and quay crane planning," Transportation Research Part B: Methodological, Elsevier, vol. 122(C), pages 365-389.
    9. Massimo Di Francesco & Gianfranco Fancello & Patrizia Serra & Paola Zuddas, 2015. "Optimal management of human resources in transhipment container ports," Maritime Policy & Management, Taylor & Francis Journals, vol. 42(2), pages 127-144, February.
    10. Scheidweiler, Tina & Jahn, Carlos, 2019. "Business analytics on AIS data: Potentials, limitations and perspectives," Chapters from the Proceedings of the Hamburg International Conference of Logistics (HICL), in: Jahn, Carlos & Kersten, Wolfgang & Ringle, Christian M. (ed.), Digital Transformation in Maritime and City Logistics: Smart Solutions for Logistics. Proceedings of the Hamburg International Conference of Logistics, volume 28, pages 342-368, Hamburg University of Technology (TUHH), Institute of Business Logistics and General Management.
    11. Notteboom, Theo E. & Parola, Francesco & Satta, Giovanni, 2019. "The relationship between transhipment incidence and throughput volatility in North European and Mediterranean container ports," Journal of Transport Geography, Elsevier, vol. 74(C), pages 371-381.
    12. Sara El Mekkaoui & Loubna Benabbou & Abdelaziz Berrado, 2023. "Deep learning models for vessel’s ETA prediction: bulk ports perspective," Flexible Services and Manufacturing Journal, Springer, vol. 35(1), pages 5-28, March.
    13. Albert Veenstra & Rogier Harmelink, 2021. "On the quality of ship arrival predictions," Maritime Economics & Logistics, Palgrave Macmillan;International Association of Maritime Economists (IAME), vol. 23(4), pages 655-673, December.
    14. Lorenz Kolley & Nicolas Rückert & Marvin Kastner & Carlos Jahn & Kathrin Fischer, 2023. "Robust berth scheduling using machine learning for vessel arrival time prediction," Flexible Services and Manufacturing Journal, Springer, vol. 35(1), pages 29-69, March.
    15. Theo Notteboom & Thanos Pallis & Jean-Paul Rodrigue, 2021. "Disruptions and resilience in global container shipping and ports: the COVID-19 pandemic versus the 2008–2009 financial crisis," Maritime Economics & Logistics, Palgrave Macmillan;International Association of Maritime Economists (IAME), vol. 23(2), pages 179-210, June.

    More about this item

    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:taf:marpmg:v:43:y:2016:i:3:p:371-385. 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: Chris Longhurst (email available below). General contact details of provider: http://www.tandfonline.com/TMPM20 .

    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.