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Strategic Analysis of the Automation of Container Port Terminals through BOT (Business Observation Tool)

Author

Listed:
  • Alberto Camarero Orive

    (Department of Transport Engineering, Urban and Regional Planning; Universidad Politécnica de Madrid, 28040 Madrid, Spain)

  • José Ignacio Parra Santiago

    (Department of Transport Engineering, Urban and Regional Planning; Universidad Politécnica de Madrid, 28040 Madrid, Spain)

  • María Magdalena Esteban-Infantes Corral

    (Department of Transport Engineering, Urban and Regional Planning; Universidad Politécnica de Madrid, 28040 Madrid, Spain)

  • Nicoletta González-Cancelas

    (Department of Transport Engineering, Urban and Regional Planning; Universidad Politécnica de Madrid, 28040 Madrid, Spain)

Abstract

The port system is immersed in a process of digital transformation towards the concept of Ports 4.0, under the new regulatory and connectivity requirements that are expected of them. As a result of the changes that the industrial revolution 4.0 is imposing, based on new information technologies and the change of energy model, the electrification of modes of transport from alternative energies and the total digitalization of the processes is occurring. This conversion to digital, intelligent, and green ports requires the implementation of the new technologies offered by the market. The inclusion of these enabling tools has allowed the development of automated terminals under a functional approach. This article aims to offer the responsible entities a new methodology (BOT) that allows them to successfully undertake the automation of terminals, taking into account the reality of the conditions of the environment in which they are developed. By quantifying the factors that facilitate or impede implementation, it will be possible to determine the strategy to be followed and the necessary measures to be adopted in the project; constituting, therefore, a novel management and planning tool.

Suggested Citation

  • Alberto Camarero Orive & José Ignacio Parra Santiago & María Magdalena Esteban-Infantes Corral & Nicoletta González-Cancelas, 2020. "Strategic Analysis of the Automation of Container Port Terminals through BOT (Business Observation Tool)," Logistics, MDPI, vol. 4(1), pages 1-14, February.
    • Handle: RePEc:gam:jlogis:v:4:y:2020:i:1:p:3-:d:316141
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    References listed on IDEAS

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    Cited by:

    1. Rachid Oucheikh & Tuwe Löfström & Ernst Ahlberg & Lars Carlsson, 2021. "Rolling Cargo Management Using a Deep Reinforcement Learning Approach," Logistics, MDPI, vol. 5(1), pages 1-18, February.
    2. Bokyung Kim & Geunsub Kim & Moohong Kang, 2022. "Study on Comparing the Performance of Fully Automated Container Terminals during the COVID-19 Pandemic," Sustainability, MDPI, vol. 14(15), pages 1-13, August.
    3. Wang, Nanxi & Wu, Min & Yuen, Kum Fai, 2023. "Assessment of port resilience using Bayesian network: A study of strategies to enhance readiness and response capacities," Reliability Engineering and System Safety, Elsevier, vol. 237(C).
    4. Li, Kevin X. & Li, Mengchi & Zhu, Yuhan & Yuen, Kum Fai & Tong, Hao & Zhou, Haoqing, 2023. "Smart port: A bibliometric review and future research directions," Transportation Research Part E: Logistics and Transportation Review, Elsevier, vol. 174(C).
    5. Geraldine Knatz & Theo Notteboom & Athanasios A. Pallis, 2022. "Container terminal automation: revealing distinctive terminal characteristics and operating parameters," Maritime Economics & Logistics, Palgrave Macmillan;International Association of Maritime Economists (IAME), vol. 24(3), pages 537-565, September.
    6. Alberto Rodrigo González & Nicoletta González-Cancelas & Beatriz Molina Serrano & Alberto Camarero Orive, 2020. "Preparation of a Smart Port Indicator and Calculation of a Ranking for the Spanish Port System," Logistics, MDPI, vol. 4(2), pages 1-22, May.
    7. Domenico Gattuso & Domenica Savia Pellicanò, 2023. "HUs Fleet Management in an Automated Container Port: Assessment by a Simulation Approach," Sustainability, MDPI, vol. 15(14), pages 1-19, July.

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