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Container terminal automation: revealing distinctive terminal characteristics and operating parameters
Knatz, G.; Notteboom, T.; Pallis, A.A. (2022). Container terminal automation: revealing distinctive terminal characteristics and operating parameters. Maritime Economics & Logistics 24(3): 537-565. https://dx.doi.org/10.1057/s41278-022-00240-y
In: Maritime Economics & Logistics. Palgrave Macmillan: Basingstoke. ISSN 1479-2931; e-ISSN 1479-294X, more
Peer reviewed article  

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Author keywords
    Ports; Container terminals; Terminal automation; Port ownership; Automation investment; Return on investment (ROI)

Authors  Top 
  • Knatz, G.
  • Notteboom, T., more
  • Pallis, A.A.

Abstract
    This study focuses on the automation of terminal equipment used to handle containers. A dataset was compiled, which includes 63 fully and semi-automated container terminals in operation around the world, their organizational features, technical dimensions, and the maritime and urban markets they serve. The data analysis focuses on where, when, under which conditions, and to what extent container terminals were automated, and who is responsible for implementing terminal automation. Only 3% of the world’s container terminals were found to be either fully or semi-automated. A survey-based analysis of global terminal operators identifies how they implement their automation and the time necessary for terminal operators to start realizing a return on their investment. The results systematically map global automated terminal characteristics. Acknowledging that not all container terminals are candidates for automation of terminal equipment, this paper contributes to extant literature by presenting a systematic review of all global automated terminals in order to substantiate or refute any perceptions that might exist on their characteristics, for example, in terms of minimum cargo volumes needed for automation. The findings can provide some guidance to market actors considering investments in automation and public and private port authority decision makers that might also commit resources to automation.

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