Citation

Chen ST. J. Transp. Saf. Secur. 2020; 12(10): 1252-1294.

Copyright

(Copyright © 2020, Southeastern Transportation Center, and Beijing Jiaotong University, Publisher Informa - Taylor and Francis Group)

DOI

10.1080/19439962.2019.1583297

PMID

unavailable

Abstract

In considering effective countermeasures for preventing the same (or similar) type of accidents from happening again, an investigation and analysis to identify the common human and organisational factors (HOFs) among a group of accidents would be beneficial for decision making. The present study aims at proposing an approach that is capable of identifying the common HOFs between or among accidents, in line with the concept of reason's swiss cheese model, without losing the context details of individual accidents. This approach applies why-because analysis, Human Factors Analysis and Classification System (HFACS) for Maritime Accidents (HFACS-MA, a derivative of HFACS) and grey relational analysis (GRA) to constitute a systematic analysis procedure that is divided into three stages. The first two are to identify the causal HOFs involved in every accident and to figure out the causation among them, and then the categories of the identified HOFs are classified according to the HFACS-MA in turn. Having these analysis results, the GRA, and two associative analysis processes, constituting the third stage of the procedure, are applied to identify the common HOFs from those accidents concerned. An experimental case study, with five marine accidents, is utilised to demonstrate that the analysis results of the proposed approach can not only illustrate the common HOFs among these accidents, but also reveal a comprehensive insight into each analyzed accident. Some considerations, including the future work, associated with the proposed method are also discussed and concluded in this article.

Language: en

Keywords

Accidents analysis; grey relational analysis; HFACS; human factors; maritime safety; why-because analysis