Abstract
Today, ample AI developers exist in the port ecosystem who focus on technology development in a particular port and shipping industry domain. They believe that with the utilization of AI, there is a potential to boost the port and shipping industry through higher commercial speed and better quality of services. Therefore, AI would be an opportunity to enhance efficiency in diverse aspects of port stakeholders' operations. On the other hand, introducing AI to port stakeholders needs evaluation of whether AI technologies' benefits emerge and what cost elements stakeholders will incur while implementing AI technologies. This way, assessing these innovations is essential to align the port stakeholders and AI developers. However, there is no cohesive framework for assessing AI technologies' applications within the port and shipping industries. Thus, this research tends to fill this gap in the existing literature. To do so, this dissertation investigates how implementing AI innovations can influence port stakeholders' operational efficiency in the same logistics process. This investigation is performed from the perspective of specific case studies concerning the level of AI innovation (micro/company, macro/port, sustainable). The answer to this investigation is generated by providing the cost-effectiveness applications supplemented by multi-criteria methods based on the validated AI cost-benefit framework. Finally, this dissertation gives insight into whether implementing AI innovations brings benefits to port stakeholders.
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