title: A grounded theory model for analysis of marine accidents.
abstract: The purpose of this paper was to design a conceptual model for analysis of marine accidents. The model is grounded on large amounts of empirical data, i.e. the Swedish Maritime Administration database, which was thoroughly studied. This database contains marine accidents organized by ship and variable. The majority of variables are non-metric and some have never been analyzed because of the large number of values. Summary statistics were employed in the data analysis. In order to develop a conceptual model, the database variables were clustered into eleven main categories or constructs, which were organized according to their properties and connected with the path diagram of relationships. For demonstration purposes, one non-metric and five metric variables were selected, namely fatality, ship's properties (i.e. age, gross register tonnage, and length), number of people on board, and marine accidents. These were analyzed using the structural equation modeling (SEM) approach. The combined prediction power of the 'ship's properties' and 'number of people on board' independent variables accounted for 65% of the variance of the fatality. The model development was largely based on the data contained in the Swedish database. However, as this database shares a number of variables in common with other databases in the region and the world, the model presented in this paper could be applied to other datasets. The model has both theoretical and practical values. Recommendations for improvements in the database are also suggested.
authors.affiliation: Lund University, Lund Faculty of Engineering, Industrial Management and Logistics, Ole Romer vag 1 Lund, Sweden. arben.mullai@glocalnet.net
authors.forename: Arben
authors.initials: A
authors.lastname: Mullai
authors.forename: Ulf
authors.initials: U
authors.lastname: Paulsson
mesh_terms: D000059:Accidents / Q000706:statistics & numerical data*; D008962:Models, Theoretical; D012306:Risk; D018570:Risk Assessment / Q000379:methods* / Q000706:statistics & numerical data; D012767:Ships / Q000706:statistics & numerical data*; D013548:Sweden