Abstract
Recently, automation is gaining an even more important role in the port and maritime industry. In particular, several technological innovations are changing both the freight and passenger transport sector. The introduction of these technologies in port terminals (smart ports) require involved stakeholders to adapt their asset and organisations in order to improve the economic competitiveness in global markets. The geographical context where new technologies are put in place can also influence their deployment and foreseen impacts. Hence, in order to take the proper decisions at a strategic level and maximize the positive effects in a selected scenario, a feasibility analysis is essential. In the present study, this challenge is addressed for the Adriatic region by proposing a procedure for evaluating and selecting the most promising innovations. Several relevant stakeholders from the selected area are inquired to assess the relevance and deployment difficulties for a set of new technologies dealing with automation in port areas. Then, the impacts on technical operation and labour market are assessed, thus, providing valuable information to support the regional organisations in facing the change and deploying procedures to be potentially replicated in other geographical areas.
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References
Christensen, C.M.: The Innovator’s Dilemma: When New Technologies Cause Great Firms to Fail. Management of Innovation and Change. Harvard Business School Press, Boston (1997)
Mazzarino, M., et al.: On the digitalisation processes in the adriatic region. In: Proceedings of the 3rd International Conference of Nautical and Maritime Culture – CNM 2019, Naples, Italy, pp. 180–190 (2019). https://doi.org/10.3233/PMST190019
Gupta, A.K., Arora, S.K.: Industrial Automation and Robotics. Laxmi Publications, New Delhi (2009)
Zrnić, N., Petković, Z., Bošnjak, S.: Automation of ship-to-shore container cranes: a review of state-of-the-art. FME Trans. 33(3), 111–121 (2005)
Kim, K.H., Günther, H.-O. (eds.): Container Terminals and Cargo Systems. Springer, Heidelberg (2007). https://doi.org/10.1007/978-3-540-49550-5
Wang, P., Mileski, J.P., Zeng, Q.: Alignments between strategic content and process structure: the case of container terminal service process automation. Marit. Econ. Logistics 21, 543–558 (2019)
Brinkmann, B.: Operations systems of container terminals: a compendious overview. In: Böse, J. (eds.) Handbook of Terminal Planning. Operations Research/Computer Science Interfaces Series, vol. 49, pp. 25–39. Springer, New York (2011). https://doi.org/10.1007/978-1-4419-8408-1_2
Baker, P., Halim, Z.: An exploration of warehouse automation implementations: cost, service and flexibility issues. Supply Chain Manag. Int. J. 12(2), 12–138 (2007)
Xu, L., Kamat, V.R., Menassa, C.: Automatic extraction of 1D barcodes from video scans for drone-assisted inventory management in warehousing applications. Int. J. Logistics Res. Appl. 21(3), 243–258 (2018)
United Nations Conference on Trade and Development: Review of Maritime Transport 2019. United Nations Publications, New York, USA (2019)
Jahn, C., Scheidweiler, T.: Port call optimization by estimating ships’ time of arrival. In: Freitag, M., Kotzab, H., Pannek, J. (eds.) LDIC 2018. LNL, pp. 172–177. Springer, Cham (2018). https://doi.org/10.1007/978-3-319-74225-0_23
Wojtusiak, J., Warden, T., Herzog, O.: The learnable evolution model in agent-based delivery optimization. Memetic Comput. 4, 165–181 (2012)
Loklindt, C., Moeller, M.P., Kinra, A.: How blockchain could be implemented for exchanging documentation in the shipping industry. In: Freitag, M., Kotzab, H., Pannek, J. (eds.) LDIC 2018. LNL, pp. 194–198. Springer, Cham (2018). https://doi.org/10.1007/978-3-319-74225-0_27
Muñuzuri, J., Onieva, L., Cortés, P., Guadix, J.: Using IoT data and applications to improve port-based intermodal supply chains. Comput. Ind. Eng. 139 (2020)
Bahnes, N., Kechar, B., Haffaf, H.: Co-operation between intelligent autonomous vehicles to enhance container terminal operations. J. Innovation Digit. Ecosys. 3(1), 22–29 (2016)
Flämig, H.: Autonomous vehicles and autonomous driving in freight transport. In: Maurer, M., Gerdes, J.C., Lenz, B., Winner, H. (eds.) Autonomous Driving. LNL, pp. 365–385. Springer, Heidelberg (2016). https://doi.org/10.1007/978-3-662-48847-8_18
Hogg, T., Ghosh, S.: Autonomous merchant vessels: examination of factors that impact the effective implementation of unmanned ships. Aust. J. Marit. Ocean Affairs 8(3), 206–222 (2016)
Fiedler, R., Bosse, C., Gehlken, D., Brümmerstedt, K., Burmeister, H.S.: Autonomous Vehicles’ Impact On Port Infrastructure Requirements. Fraunhofer Center for Maritime Logistics and Services CML, Hamburg (2019)
Ghaderi, H.: Autonomous technologies in short sea shipping: trends, feasibility and implications. Transp. Rev. 39(1), 152–173 (2019)
Gausdal, A.H., Czachorowski, K.V., Solesvik, M.Z.: Applying blockchain technology: evidence from Norwegian companies. Sustainability 10(6), 1985 (2018)
Autor, D.H.: Why are there still so many jobs? The history and future of workplace automation. J. Econ. Perspect. 29(3), 3–30 (2015)
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This work was entirely financed by “DigLogs - Digitalising Logistics Process” Interrog Italy-Croatia 2014–2020 project.
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Braidotti, L., Mazzarino, M., Cociancich, M., Bucci, V. (2020). On the Automation of Ports and Logistics Chains in the Adriatic Region. In: Gervasi, O., et al. Computational Science and Its Applications – ICCSA 2020. ICCSA 2020. Lecture Notes in Computer Science(), vol 12255. Springer, Cham. https://doi.org/10.1007/978-3-030-58820-5_8
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