A bibliometric analysis and systematic review of shipboard Decision Support Systems for accident prevention
A2 Katsausartikkeli tieteellisessä aikakauslehdessä
Safety Science, Volume 128
AbstractMaritime transport faces new safety-related challenges resulting from constantly increasing traffic density, along with increasing dimensions of ships. Consequently, the number of new concepts related to Decision Support Systems (DSSs) supporting safe shipborne operations in the presence of reduced ship manning is rapidly growing, both in academia and industry. However, there is a lack of a systematic description of the state-of-the-art in this field. Moreover, there is no comprehensive overview of the level of technology readiness of proposed concepts. Therefore, this paper presents an analysis aiming at (1) increasing the understanding of the structure and contents of the academic field concerned with this topic; (2) determining and mapping scientific networks in this domain; (3) analyzing and visualizing Technology Readiness Level (TRL) of analyzed systems. Bibliometric methods are utilized to depict the domain of onboard DSSs for operations focused on safety ensurance and accident prevention. The scientific literature is reviewed in a systematic way using a comparative analysis of existing tools. The results indicate that there are relatively many developments in selected DSS categories, such as collision avoidance and ship routing. However, even in these categories some issues and gaps still remain, so further improvements are needed. The analysis indicates a relatively low level of technology readiness of tools and concepts presented in academic literature. This signifies a need to move beyond the conceptual stages toward demonstration and validation in realistic, operating environments.
Bibliometrics, Decision Support System (DSS), Maritime risk and safety, Maritime Transportation System (MTS), Systematic literature review
Gil , M , Wróbel , K , Montewka , J & Goerlandt , F 2020 , ' A bibliometric analysis and systematic review of shipboard Decision Support Systems for accident prevention ' , Safety Science , vol. 128 , 104717 . https://doi.org/10.1016/j.ssci.2020.104717