Big data and artificial intelligence in the maritime industry: a bibliometric review and future research directions

ABSTRACT

This study provides a bibliometric review of 279 studies on the applications of big data and artificial intelligence (AI) in the maritime industry, published in 214 academic outlets, authored by 842 scholars. We extracted bibliographical data from the Web of Science database and analysed it using the Bibliometrix tool in R software. Based on citation analysis metrics, we revealed the most influential articles, journals, authors and institutions. Using the bibliographic coupling methodology, we identified four underlying research clusters: (1) digital transformation in maritime industry, (2) applications of big data from AIS, (3) energy efficiency and (4) predictive analytics. We analysed these clusters in detail and extracted future research questions. Besides, we present research collaboration networks on the institution and author level.     

‘Tool port’ to ‘landlord port’: a game theory approach to analyse gains from governance model transformation

This study investigates potential port users’ surplus and terminal operators’ profits due to transforming port governance from the ‘tool port’ model to the ‘landlord port’ model. Although the landlord port model is one of the most adopted and successful port governance models, many ports still operate under other models. Chittagong Port, the largest port in Bangladesh, currently operates under the tool port model, while the country’s second-largest port, Mongla Port, operates under the service port model. Chittagong Port is currently facing many challenges, including capacity expansion and renovation of port facilities. Therefore, we form four hypothetical situations for port governance model transformation, assuming that Chittagong Port will transform to the landlord port model but that Mongla Port will run under the existing governance model. Estimating a Bertrand game model, we present a cost-benefit analysis for port users and terminal operators (or port authorities) in hypothetical game situations. The results reveal that privatising one of the container terminals under a landlord setting is the most profitable scenario for Chittagong Port Authority, but privatising all terminals of Chittagong Port yields the highest users’ surplus. However, privatising two of the terminals while they cooperate yields the lowest users’ surplus.